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--git a/docs/.doctrees/autoapi/dasf/utils/index.doctree b/docs/.doctrees/autoapi/dasf/utils/index.doctree index bfccadd..cd29f6c 100644 Binary files a/docs/.doctrees/autoapi/dasf/utils/index.doctree and b/docs/.doctrees/autoapi/dasf/utils/index.doctree differ diff --git a/docs/.doctrees/autoapi/dasf/utils/labels/index.doctree b/docs/.doctrees/autoapi/dasf/utils/labels/index.doctree index 0e74987..13cfdf6 100644 Binary files a/docs/.doctrees/autoapi/dasf/utils/labels/index.doctree and b/docs/.doctrees/autoapi/dasf/utils/labels/index.doctree differ diff --git a/docs/.doctrees/environment.pickle b/docs/.doctrees/environment.pickle index d02ebc4..34b9f2c 100644 Binary files a/docs/.doctrees/environment.pickle and b/docs/.doctrees/environment.pickle differ diff --git a/docs/_modules/dasf/datasets/base.html b/docs/_modules/dasf/datasets/base.html index d1fccdc..c7b034c 100644 --- a/docs/_modules/dasf/datasets/base.html +++ b/docs/_modules/dasf/datasets/base.html @@ -80,7 +80,6 @@

Source code for dasf.datasets.base

 #!/usr/bin/env python3
-
 """ Base module for most of the DASF Datasets. """
 
 import json
@@ -104,14 +103,14 @@ 

Source code for dasf.datasets.base

     # This is just to enable Xarray Cupy capabilities
     import cupy_xarray as cx  # noqa
     import dask_cudf as dcudf
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 try:
-    import numcodecs
+    import numcodecs  # noqa
     from kvikio.nvcomp_codec import NvCompBatchCodec
     from kvikio.zarr import GDSStore
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from pathlib import Path
@@ -131,7 +130,8 @@ 

Source code for dasf.datasets.base

 
[docs] class Dataset(TargeteredTransform): - """Class representing a generic dataset based on a TargeteredTransform + """ + Class representing a generic dataset based on a TargeteredTransform object. Parameters @@ -154,7 +154,10 @@

Source code for dasf.datasets.base

                  root: str = None,
                  *args,
                  **kwargs):
-        """ Constructor of the object Dataset. """
+        """
+        Constructor of the object Dataset.
+
+        """
         super().__init__(*args, **kwargs)
 
         # Dataset internals
@@ -170,7 +173,8 @@ 

Source code for dasf.datasets.base

         self.download()
 
     def __set_dataset_cache_dir(self):
-        """Generate cached directory in $HOME to store dataset(s).
+        """
+        Generate cached directory in $HOME to store dataset(s).
 
         """
         self._cache_dir = os.path.abspath(str(Path.home()) + "/.cache/dasf/datasets/")
@@ -182,7 +186,8 @@ 

Source code for dasf.datasets.base

 
[docs] def download(self): - """Skeleton of the download method. + """ + Skeleton of the download method. """ if self._download: @@ -192,7 +197,8 @@

Source code for dasf.datasets.base

 
[docs] def __len__(self) -> int: - """Return internal data length. + """ + Return internal data length. """ if self._data is None: @@ -204,7 +210,8 @@

Source code for dasf.datasets.base

 
[docs] def __getitem__(self, idx): - """Generic __getitem__() function based on internal data. + """ + Generic __getitem__() function based on internal data. Parameters ---------- @@ -223,7 +230,8 @@

Source code for dasf.datasets.base

 
[docs] class DatasetArray(Dataset): - """Class representing an dataset wich is defined as an array of a defined + """ + Class representing an dataset wich is defined as an array of a defined shape. Parameters @@ -243,7 +251,9 @@

Source code for dasf.datasets.base

                  download: bool = False,
                  root: str = None,
                  chunks="auto"):
-        """ Constructor of the object DatasetArray. """
+        """
+        Constructor of the object DatasetArray.
+        """
         Dataset.__init__(self, name, download, root)
 
         self._chunks = chunks
@@ -259,8 +269,9 @@ 

Source code for dasf.datasets.base

 
[docs] def __operator_check__(self, other): - """Check what type of the data we are handling - + """ + Check what type of the data we are handling + Examples: DatasetArray with array-like; or DatasetArray with DatasetArray @@ -284,8 +295,8 @@

Source code for dasf.datasets.base

 
[docs] def __repr__(self): - """Return a class representation based on internal array. - + """ + Return a class representation based on internal array. """ return repr(self._data)
@@ -293,7 +304,8 @@

Source code for dasf.datasets.base

 
[docs] def __array__(self, dtype=None): - """Array interface is required to support most of the array functions. + """ + Array interface is required to support most of the array functions. Parameters ---------- @@ -312,7 +324,34 @@

Source code for dasf.datasets.base

 
[docs] def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): - + """ + Any class, array subclass or not, can define this method or set + it to None in order to override the behavior of Arrays ufuncs. + + Parameters + ---------- + ufunc : Callable + The ufunc object that was called. + + method : Str + A string indicating which Ufunc method was called (one of + "__call__", "reduce", "reduceat", "accumulate", "outer", "inner"). + + inputs : Any + A tuple of the input arguments to the ufunc. + + kwargs : Any + A dictionary containing the optional input arguments of the ufunc. + If given, any out arguments, both positional and keyword, are + passed as a tuple in kwargs. See the discussion in Universal + functions (ufunc) for details. + + Returns + ------- + array : array-like + The return either the result of the operation. + + """ assert self._data is not None, "Data is not loaded yet." if method == '__call__': scalars = [] @@ -332,7 +371,8 @@

Source code for dasf.datasets.base

 
 
     def __check_op_input(self, in_data):
-        """Return the proper type of data for operation
+        """
+        Return the proper type of data for operation
 
           >>> Result = DatasetArray + Numpy; or
           >>> Result = DatasetArray + DatasetArray
@@ -357,7 +397,8 @@ 

Source code for dasf.datasets.base

 
[docs] def __add__(self, other): - """Internal function of adding two array datasets. + """ + Internal function of adding two array datasets. Parameters ---------- @@ -366,7 +407,7 @@

Source code for dasf.datasets.base

 
         Returns
         -------
-        DatasetArry
+        DatasetArray
             A sum with two arrays.
 
         """
@@ -378,7 +419,8 @@ 

Source code for dasf.datasets.base

 
[docs] def __sub__(self, other): - """Internal function of subtracting two array datasets. + """ + Internal function of subtracting two array datasets. Parameters ---------- @@ -399,7 +441,8 @@

Source code for dasf.datasets.base

 
[docs] def __mul__(self, other): - """Internal function of multiplication two array datasets. + """ + Internal function of multiplication two array datasets. Parameters ---------- @@ -420,7 +463,8 @@

Source code for dasf.datasets.base

 
[docs] def __div__(self, other): - """Internal function of division two array datasets. + """ + Internal function of division two array datasets. Parameters ---------- @@ -439,7 +483,8 @@

Source code for dasf.datasets.base

 
 
     def __copy_attrs_from_data(self):
-        """Extends metadata to new transformed object (after operations).
+        """
+        Extends metadata to new transformed object (after operations).
 
         """
         self._metadata["type"] = type(self._data)
@@ -451,7 +496,8 @@ 

Source code for dasf.datasets.base

                     self.__dict__[attr] = getattr(self._data, attr)
 
     def __npy_header(self):
-        """Read an array header from a filelike object.
+        """
+        Read an array header from a filelike object.
 
         """
         with open(self._root_file, 'rb') as fobj:
@@ -463,7 +509,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _lazy_load(self, xp, **kwargs): - """Lazy load the dataset using an CPU dask container. + """ + Lazy load the dataset using an CPU dask container. Parameters ---------- @@ -482,7 +529,8 @@

Source code for dasf.datasets.base

 
         local_data = dask.delayed(xp.load)(self._root_file, **kwargs)
 
-        local_data = da.from_delayed(local_data, shape=npy_shape, dtype=xp.float32, meta=xp.array(()))
+        local_data = da.from_delayed(local_data, shape=npy_shape,
+                                     dtype=xp.float32, meta=xp.array(()))
         if isinstance(self._chunks, tuple):
             local_data = local_data.rechunk(self._chunks)
 
@@ -492,7 +540,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _load(self, xp, **kwargs): - """Load data using CPU container. + """ + Load data using CPU container. Parameters ---------- @@ -509,7 +558,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_meta(self) -> dict: - """Load metadata to inspect. + """ + Load metadata to inspect. Returns ------- @@ -517,18 +567,19 @@

Source code for dasf.datasets.base

             A dictionary with metadata information.
 
         """
-        assert self._root_file is not None, ("There is no temporary file to "
-                                             "inspect")
-        assert os.path.isfile(self._root_file), ("The root variable should "
-                                                 "be a NPY file")
+        assert self._data is not None or self._root_file is not None, \
+               ("There is no temporary file to inspect")
+        assert self._data is not None or os.path.isfile(self._root_file), \
+               ("The root variable should be a NPY file")
 
-        return self.inspect_metadata()
+ return self.metadata()
[docs] def _lazy_load_gpu(self): - """Load data with GPU container + DASK. (It does not load immediattly) + """ + Load data with GPU container + DASK. (It does not load immediattly) """ self._metadata = self._load_meta() @@ -539,7 +590,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_cpu(self): - """Load data with CPU container + DASK. (It does not load immediattly) + """ + Load data with CPU container + DASK. (It does not load immediattly) """ self._metadata = self._load_meta() @@ -550,7 +602,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_gpu(self): - """Load data with GPU container (e.g. cupy). + """ + Load data with GPU container (e.g. cupy). """ self._metadata = self._load_meta() @@ -561,7 +614,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_cpu(self): - """Load data with CPU container (e.g. numpy). + """ + Load data with CPU container (e.g. numpy). """ self._metadata = self._load_meta() @@ -572,7 +626,8 @@

Source code for dasf.datasets.base

 
[docs] def from_array(self, array): - """Load data from an existing array. + """ + Load data from an existing array. Parameters ---------- @@ -587,7 +642,8 @@

Source code for dasf.datasets.base

 [docs]
     @task_handler
     def load(self):
-        """Placeholder for load function.
+        """
+        Placeholder for load function.
 
         """
         ...
@@ -595,7 +651,8 @@

Source code for dasf.datasets.base

 
     @property
     def shape(self) -> tuple:
-        """Returns the shape of an array.
+        """
+        Returns the shape of an array.
 
         Returns
         -------
@@ -603,15 +660,16 @@ 

Source code for dasf.datasets.base

             A tuple with the shape.
 
         """
-        if self._data:
+        if self._data is not None:
             return self._data.shape
 
         return self.__npy_header()[0]
 
-
-[docs] - def inspect_metadata(self) -> dict: - """Return a dictionary with all metadata information from data. +
+[docs] + def metadata(self) -> dict: + """ + Return a dictionary with all metadata information from data. Returns ------- @@ -619,10 +677,14 @@

Source code for dasf.datasets.base

             A dictionary with metadata information.
 
         """
-        array_file_size = human_readable_size(
-            os.path.getsize(self._root_file),
-            decimal=2
-        )
+        if self._root_file is not None:
+            size = os.path.getsize(self._root_file)
+        elif self._data is not None:
+            size = self._data.size
+        else:
+            size = 0
+
+        array_file_size = human_readable_size(size, decimal=2)
 
         npy_shape = self.shape
 
@@ -639,7 +701,8 @@ 

Source code for dasf.datasets.base

 
[docs] class DatasetZarr(Dataset): - """Class representing an dataset wich is defined as a Zarr array of a + """ + Class representing an dataset wich is defined as a Zarr array of a defined shape. Parameters @@ -677,7 +740,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load(self, xp, **kwargs): - """Lazy load the dataset using an CPU dask container. + """ + Lazy load the dataset using an CPU dask container. Parameters ---------- @@ -693,8 +757,8 @@

Source code for dasf.datasets.base

 
         """
         if (self._backend == "kvikio" and is_kvikio_supported() and
-            (is_gds_supported() or is_kvikio_compat_mode())
-            and is_nvcomp_codec_supported()):
+           (is_gds_supported() or is_kvikio_compat_mode()) and
+           is_nvcomp_codec_supported()):
             store = GDSStore(self._root_file)
             meta = json.loads(store[".zarray"])
             meta["compressor"] = NvCompBatchCodec("lz4").get_config()
@@ -709,7 +773,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _load(self, xp, **kwargs): - """Load data using CPU container. + """ + Load data using CPU container. Parameters ---------- @@ -793,7 +858,7 @@

Source code for dasf.datasets.base

         """
         assert self._root_file is not None, "There is no temporary file to inspect"
 
-        return self.inspect_metadata()
+ return self.metadata()
def __read_zarray(self, key): @@ -813,7 +878,8 @@

Source code for dasf.datasets.base

 
     @property
     def shape(self) -> tuple:
-        """Returns the shape of an array.
+        """
+        Returns the shape of an array.
 
         Returns
         -------
@@ -831,7 +897,8 @@ 

Source code for dasf.datasets.base

 
     @property
     def chunksize(self):
-        """Returns the chunksize of an array.
+        """
+        Returns the chunksize of an array.
 
         Returns
         -------
@@ -847,10 +914,11 @@ 

Source code for dasf.datasets.base

 
         return self._data.chunksize
 
-
-[docs] - def inspect_metadata(self) -> dict: - """Return a dictionary with all metadata information from data. +
+[docs] + def metadata(self) -> dict: + """ + Return a dictionary with all metadata information from data. Returns ------- @@ -885,14 +953,16 @@

Source code for dasf.datasets.base

 
[docs] def __repr__(self): - """Return a class representation based on internal array. + """ + Return a class representation based on internal array. """ return repr(self._data)
def __check_op_input(self, in_data): - """Return the proper type of data for operation + """ + Return the proper type of data for operation >>> Result = DatasetZarr + Numpy; or >>> Result = DatasetZarr + DatasetZarr @@ -917,7 +987,8 @@

Source code for dasf.datasets.base

 
[docs] def __add__(self, other): - """Internal function of adding two array datasets. + """ + Internal function of adding two array datasets. Parameters ---------- @@ -938,7 +1009,8 @@

Source code for dasf.datasets.base

 
[docs] def __sub__(self, other): - """Internal function of subtracting two array datasets. + """ + Internal function of subtracting two array datasets. Parameters ---------- @@ -959,7 +1031,8 @@

Source code for dasf.datasets.base

 
[docs] def __mul__(self, other): - """Internal function of multiplication two array datasets. + """ + Internal function of multiplication two array datasets. Parameters ---------- @@ -980,7 +1053,8 @@

Source code for dasf.datasets.base

 
[docs] def __div__(self, other): - """Internal function of division two array datasets. + """ + Internal function of division two array datasets. Parameters ---------- @@ -999,7 +1073,8 @@

Source code for dasf.datasets.base

 
 
     def __copy_attrs_from_data(self):
-        """Extends metadata to new transformed object (after operations).
+        """
+        Extends metadata to new transformed object (after operations).
 
         """
         self._metadata["type"] = type(self._data)
@@ -1015,7 +1090,8 @@ 

Source code for dasf.datasets.base

 
[docs] class DatasetHDF5(Dataset): - """Class representing an dataset wich is defined as a HDF5 dataset of a + """ + Class representing an dataset wich is defined as a HDF5 dataset of a defined shape. Parameters @@ -1038,7 +1114,10 @@

Source code for dasf.datasets.base

                  root: str = None,
                  chunks="auto",
                  dataset_path: str = None):
-        """ Constructor of the object DatasetHDF5. """
+        """
+        Constructor of the object DatasetHDF5.
+
+        """
         Dataset.__init__(self, name, download, root)
 
         self._chunks = chunks
@@ -1059,7 +1138,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _lazy_load(self, xp, **kwargs): - """Lazy load the dataset using an CPU dask container. + """ + Lazy load the dataset using an CPU dask container. Parameters ---------- @@ -1082,7 +1162,8 @@

Source code for dasf.datasets.base

 
[docs] def _load(self, xp=None, **kwargs): - """Load data using CPU container. + """ + Load data using CPU container. Parameters ---------- @@ -1099,7 +1180,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_cpu(self): - """Load data with CPU container + DASK. (It does not load immediattly) + """ + Load data with CPU container + DASK. (It does not load immediattly) """ self._metadata = self._load_meta() @@ -1110,7 +1192,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_gpu(self): - """Load data with GPU container + DASK. (It does not load immediattly) + """ + Load data with GPU container + DASK. (It does not load immediattly) """ self._metadata = self._load_meta() @@ -1121,7 +1204,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_cpu(self): - """Load data with CPU container (e.g. numpy). + """ + Load data with CPU container (e.g. numpy). """ self._metadata = self._load_meta() @@ -1132,7 +1216,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_gpu(self): - """Load data with GPU container (e.g. cupy). + """ + Load data with GPU container (e.g. cupy). """ self._metadata = self._load_meta() @@ -1144,7 +1229,8 @@

Source code for dasf.datasets.base

 [docs]
     @task_handler
     def load(self):
-        """Placeholder for load function.
+        """
+        Placeholder for load function.
 
         """
         ...
@@ -1153,7 +1239,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_meta(self) -> dict: - """Load metadata to inspect. + """ + Load metadata to inspect. Returns ------- @@ -1164,13 +1251,14 @@

Source code for dasf.datasets.base

         assert self._root_file is not None, "There is no temporary file to inspect"
         assert self._dataset_path is not None, "There is no path to fetch data"
 
-        return self.inspect_metadata()
+ return self.metadata()
-
-[docs] - def inspect_metadata(self) -> dict: - """Return a dictionary with all metadata information from data. +
+[docs] + def metadata(self) -> dict: + """ + Return a dictionary with all metadata information from data. Returns ------- @@ -1198,7 +1286,8 @@

Source code for dasf.datasets.base

 
[docs] class DatasetXarray(Dataset): - """Class representing an dataset wich is defined as a Xarray dataset of a + """ + Class representing an dataset wich is defined as a Xarray dataset of a defined shape. Parameters @@ -1221,7 +1310,10 @@

Source code for dasf.datasets.base

                  root: str = None,
                  chunks=None,
                  data_var=None):
-        """ Constructor of the object DatasetXarray. """
+        """
+        Constructor of the object DatasetXarray.
+
+        """
         Dataset.__init__(self, name, download, root)
 
         self._chunks = chunks
@@ -1242,7 +1334,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _lazy_load_cpu(self): - """Load data with CPU container + DASK. (It does not load immediattly) + """ + Load data with CPU container + DASK. (It does not load immediattly) """ assert self._chunks is not None, "Lazy operations require chunks" @@ -1259,7 +1352,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_gpu(self): - """Load data with GPU container + DASK. (It does not load immediattly) + """ + Load data with GPU container + DASK. (It does not load immediattly) """ assert self._chunks is not None, "Lazy operations require chunks" @@ -1276,7 +1370,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_cpu(self): - """Load data with CPU container (e.g. numpy). + """ + Load data with CPU container (e.g. numpy). """ if self._data_var: @@ -1290,7 +1385,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_gpu(self): - """Load data with GPU container (e.g. cupy). + """ + Load data with GPU container (e.g. cupy). """ if self._data_var: @@ -1305,7 +1401,8 @@

Source code for dasf.datasets.base

 [docs]
     @task_handler
     def load(self):
-        """Placeholder for load function.
+        """
+        Placeholder for load function.
 
         """
         ...
@@ -1314,7 +1411,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_meta(self) -> dict: - """Load metadata to inspect. + """ + Load metadata to inspect. Returns ------- @@ -1324,13 +1422,14 @@

Source code for dasf.datasets.base

         """
         assert self._root_file is not None, "There is no temporary file to inspect"
 
-        return self.inspect_metadata()
+ return self.metadata()
-
-[docs] - def inspect_metadata(self) -> dict: - """Return a dictionary with all metadata information from data. +
+[docs] + def metadata(self) -> dict: + """ + Return a dictionary with all metadata information from data. Returns ------- @@ -1354,7 +1453,8 @@

Source code for dasf.datasets.base

 
[docs] def __len__(self) -> int: - """Return internal data length. + """ + Return internal data length. """ if self._data is None: @@ -1369,7 +1469,8 @@

Source code for dasf.datasets.base

 
[docs] def __getitem__(self, idx): - """A __getitem__() function based on internal Xarray data. + """ + A __getitem__() function based on internal Xarray data. Parameters ---------- @@ -1392,7 +1493,8 @@

Source code for dasf.datasets.base

 
[docs] class DatasetLabeled(Dataset): - """A class representing a labeled dataset. Each item is a 2-element tuple, + """ + A class representing a labeled dataset. Each item is a 2-element tuple, where the first element is a array of data and the second element is the respective label. The items can be accessed from `dataset[x]`. @@ -1418,7 +1520,10 @@

Source code for dasf.datasets.base

                  download: bool = False,
                  root: str = None,
                  chunks="auto"):
-        """ Constructor of the object DatasetLabeled. """
+        """
+        Constructor of the object DatasetLabeled.
+
+        """
         Dataset.__init__(self, name, download, root)
 
         self._chunks = chunks
@@ -1426,7 +1531,8 @@ 

Source code for dasf.datasets.base

 
[docs] def download(self): - """Download the dataset. + """ + Download the dataset. """ if hasattr(self, "_train") and hasattr(self._train, "download"): @@ -1436,10 +1542,11 @@

Source code for dasf.datasets.base

             self._val.download()
-
-[docs] - def inspect_metadata(self) -> dict: - """Return a dictionary with all metadata information from data +
+[docs] + def metadata(self) -> dict: + """ + Return a dictionary with all metadata information from data (train and labels). Returns @@ -1448,8 +1555,8 @@

Source code for dasf.datasets.base

             A dictionary with metadata information.
 
         """
-        metadata_train = self._train.inspect_metadata()
-        metadata_val = self._val.inspect_metadata()
+        metadata_train = self._train.metadata()
+        metadata_val = self._val.metadata()
 
         assert (
             metadata_train["shape"] == metadata_val["shape"]
@@ -1465,7 +1572,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _lazy_load(self, xp, **kwargs) -> tuple: - """Lazy load the dataset using an CPU dask container. + """ + Lazy load the dataset using an CPU dask container. Parameters ---------- @@ -1489,7 +1597,8 @@

Source code for dasf.datasets.base

 
[docs] def _load(self, xp, **kwargs) -> tuple: - """Load data using CPU container. + """ + Load data using CPU container. Parameters ---------- @@ -1513,7 +1622,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_meta(self) -> dict: - """Load metadata to inspect. + """ + Load metadata to inspect. Returns ------- @@ -1534,13 +1644,14 @@

Source code for dasf.datasets.base

             "The root variable should be a file"
         )
 
-        return self.inspect_metadata()
+ return self.metadata()
[docs] def _lazy_load_gpu(self): - """Load data with GPU container + DASK. (It does not load immediattly) + """ + Load data with GPU container + DASK. (It does not load immediattly) """ self._metadata = self._load_meta() @@ -1550,7 +1661,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_cpu(self): - """Load data with CPU container + DASK. (It does not load immediattly) + """ + Load data with CPU container + DASK. (It does not load immediattly) """ self._metadata = self._load_meta() @@ -1560,7 +1672,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_gpu(self): - """Load data with GPU container (e.g. cupy). + """ + Load data with GPU container (e.g. cupy). """ self._metadata = self._load_meta() @@ -1570,7 +1683,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_cpu(self): - """Load data with CPU container (e.g. numpy). + """ + Load data with CPU container (e.g. numpy). """ self._metadata = self._load_meta() @@ -1581,7 +1695,8 @@

Source code for dasf.datasets.base

 [docs]
     @task_handler
     def load(self):
-        """Placeholder for load function.
+        """
+        Placeholder for load function.
 
         """
         ...
@@ -1590,7 +1705,8 @@

Source code for dasf.datasets.base

 
[docs] def __getitem__(self, idx): - """A __getitem__() function for data and labeled data together. + """ + A __getitem__() function for data and labeled data together. Parameters ---------- @@ -1609,7 +1725,8 @@

Source code for dasf.datasets.base

 
[docs] class DatasetDataFrame(Dataset): - """Class representing an dataset wich is defined as a dataframe. + """ + Class representing an dataset wich is defined as a dataframe. Parameters ---------- @@ -1628,7 +1745,10 @@

Source code for dasf.datasets.base

                  download: bool = True,
                  root: str = None,
                  chunks="auto"):
-        """ Constructor of the object DatasetDataFrame. """
+        """
+        Constructor of the object DatasetDataFrame.
+
+        """
         Dataset.__init__(self, name, download, root)
 
         self._chunks = chunks
@@ -1644,7 +1764,8 @@ 

Source code for dasf.datasets.base

 
[docs] def _load_meta(self) -> dict: - """Load metadata to inspect. + """ + Load metadata to inspect. Returns ------- @@ -1656,13 +1777,14 @@

Source code for dasf.datasets.base

             "There is no temporary file to inspect"
         )
 
-        return self.inspect_metadata()
+ return self.metadata()
-
-[docs] - def inspect_metadata(self) -> dict: - """Return a dictionary with all metadata information from data. +
+[docs] + def metadata(self) -> dict: + """ + Return a dictionary with all metadata information from data. Returns ------- @@ -1687,7 +1809,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_gpu(self): - """Load data with GPU container + DASK. (It does not load immediattly) + """ + Load data with GPU container + DASK. (It does not load immediattly) """ self._data = dcudf.read_csv(self._root_file) @@ -1698,7 +1821,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_cpu(self): - """Load data with CPU container + DASK. (It does not load immediattly) + """ + Load data with CPU container + DASK. (It does not load immediattly) """ self._data = ddf.read_csv(self._root_file) @@ -1709,7 +1833,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_gpu(self): - """Load data with GPU container (e.g. CuDF). + """ + Load data with GPU container (e.g. CuDF). """ self._data = cudf.read_csv(self._root_file) @@ -1720,7 +1845,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_cpu(self): - """Load data with CPU container (e.g. pandas). + """ + Load data with CPU container (e.g. pandas). """ self._data = pd.read_csv(self._root_file) @@ -1732,7 +1858,8 @@

Source code for dasf.datasets.base

 [docs]
     @task_handler
     def load(self):
-        """Placeholder for load function.
+        """
+        Placeholder for load function.
 
         """
         ...
@@ -1740,7 +1867,8 @@

Source code for dasf.datasets.base

 
     @property
     def shape(self) -> tuple:
-        """Returns the shape of an array.
+        """
+        Returns the shape of an array.
 
         Returns
         -------
@@ -1756,7 +1884,8 @@ 

Source code for dasf.datasets.base

 
[docs] def __len__(self) -> int: - """Return internal data length. + """ + Return internal data length. """ if self._data is None: raise Exception("Data is not loaded yet") @@ -1767,7 +1896,8 @@

Source code for dasf.datasets.base

 
[docs] def __getitem__(self, idx): - """A __getitem__() function based on internal dataframe. + """ + A __getitem__() function based on internal dataframe. Parameters ---------- @@ -1786,7 +1916,8 @@

Source code for dasf.datasets.base

 
[docs] class DatasetParquet(DatasetDataFrame): - """Class representing an dataset wich is defined as a Parquet. + """ + Class representing an dataset wich is defined as a Parquet. Parameters ---------- @@ -1805,13 +1936,17 @@

Source code for dasf.datasets.base

                  download: bool = True,
                  root: str = None,
                  chunks="auto"):
-        """ Constructor of the object DatasetParquet. """
+        """
+        Constructor of the object DatasetParquet.
+
+        """
         DatasetDataFrame.__init__(self, name, download, root, chunks)
 
 
[docs] def _lazy_load_gpu(self): - """Load data with GPU container + DASK. (It does not load immediattly) + """ + Load data with GPU container + DASK. (It does not load immediattly) """ self._data = dcudf.read_parquet(self._root_file) @@ -1822,7 +1957,8 @@

Source code for dasf.datasets.base

 
[docs] def _lazy_load_cpu(self): - """Load data with CPU container + DASK. (It does not load immediattly) + """ + Load data with CPU container + DASK. (It does not load immediattly) """ self._data = ddf.read_parquet(self._root_file) @@ -1833,7 +1969,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_gpu(self): - """Load data with GPU container (e.g. CuDF). + """ + Load data with GPU container (e.g. CuDF). """ self._data = cudf.read_parquet(self._root_file) @@ -1844,7 +1981,8 @@

Source code for dasf.datasets.base

 
[docs] def _load_cpu(self): - """Load data with CPU container (e.g. pandas). + """ + Load data with CPU container (e.g. pandas). """ self._data = pd.read_parquet(self._root_file) diff --git a/docs/_modules/dasf/datasets/datasets.html b/docs/_modules/dasf/datasets/datasets.html index bdc4693..bc10c02 100644 --- a/docs/_modules/dasf/datasets/datasets.html +++ b/docs/_modules/dasf/datasets/datasets.html @@ -90,7 +90,7 @@

Source code for dasf.datasets.datasets

     import cupy as cp
     from cuml.dask.datasets import make_blobs as make_blobs_MGPU
     from cuml.datasets import make_blobs as make_blobs_GPU
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from dask_ml.datasets import make_classification as make_classification_MCPU
@@ -99,7 +99,7 @@ 

Source code for dasf.datasets.datasets

 try:
     from cuml.dask.datasets import make_classification as make_classification_MGPU
     from cuml.datasets import make_classification as make_classification_GPU
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from dask_ml.datasets import make_regression as make_regression_MCPU
@@ -108,7 +108,7 @@ 

Source code for dasf.datasets.datasets

 try:
     from cuml.dask.datasets import make_regression as make_regression_MGPU
     from cuml.datasets import make_regression as make_regression_GPU
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from dasf.utils.funcs import is_dask_gpu_supported, is_dask_supported, is_gpu_supported
diff --git a/docs/_modules/dasf/feature_extraction/histogram.html b/docs/_modules/dasf/feature_extraction/histogram.html
index 6efcd56..0d91eb3 100644
--- a/docs/_modules/dasf/feature_extraction/histogram.html
+++ b/docs/_modules/dasf/feature_extraction/histogram.html
@@ -79,15 +79,15 @@
            

Source code for dasf.feature_extraction.histogram

-""" Histogram module. """
-#!/usr/bin/env python3
+#!/usr/bin/env python3
+""" Histogram module. """
 
 import dask.array as da
 import numpy as np
 
 try:
     import cupy as cp
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from dasf.transforms.base import TargeteredTransform, Transform
@@ -143,7 +143,9 @@ 

Source code for dasf.feature_extraction.histogram

self._weights = weights self._density = density - def __lazy_transform_generic(self, X): +
+[docs] + def _lazy_transform_generic(self, X): """ Compute the histogram of a dataset using Dask. @@ -161,6 +163,9 @@

Source code for dasf.feature_extraction.histogram

bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. """ + if self._range is None: + raise ValueError("Argument `range` cannot be None for Dask based methods.") + return da.histogram( X, bins=self._bins, @@ -168,9 +173,12 @@

Source code for dasf.feature_extraction.histogram

normed=self._normed, weights=self._weights, density=self._density, - ) + )
+ - def __transform_generic(self, X, xp): +
+[docs] + def _transform_generic(self, X, xp): """ Compute the histogram of a dataset using local libraries. @@ -188,14 +196,19 @@

Source code for dasf.feature_extraction.histogram

bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. """ + kwargs = {} + if xp == np: + kwargs['normed'] = self._normed + return xp.histogram( X, bins=self._bins, range=self._range, - normed=self._normed, weights=self._weights, density=self._density, - ) + **kwargs, + )
+
[docs] @@ -217,7 +230,7 @@

Source code for dasf.feature_extraction.histogram

bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. """ - return self.__lazy_transform_generic(X)
+ return self._lazy_transform_generic(X)
@@ -240,7 +253,7 @@

Source code for dasf.feature_extraction.histogram

bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. """ - return self.__lazy_transform_generic(X)
+ return self._lazy_transform_generic(X)
@@ -263,7 +276,7 @@

Source code for dasf.feature_extraction.histogram

bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. """ - return self.__transform_generic(X, np)
+ return self._transform_generic(X, np)
@@ -286,7 +299,7 @@

Source code for dasf.feature_extraction.histogram

bin_edges : array of dtype float Return the bin edges ``(length(hist)+1)``. """ - return self.__transform_generic(X, cp)
+ return self._transform_generic(X, cp)
diff --git a/docs/_modules/dasf/ml/cluster/agglomerative.html b/docs/_modules/dasf/ml/cluster/agglomerative.html index 71b250d..56b1605 100644 --- a/docs/_modules/dasf/ml/cluster/agglomerative.html +++ b/docs/_modules/dasf/ml/cluster/agglomerative.html @@ -114,12 +114,11 @@

Source code for dasf.ml.cluster.agglomerative

The number of clusters to find. It must be ``None`` if ``distance_threshold`` is not ``None``. - affinity : str or callable, default='euclidean' - Metric used to compute the linkage. Can be "euclidean", "l1", "l2", - "manhattan", "cosine", or "precomputed". - If linkage is "ward", only "euclidean" is accepted. - If "precomputed", a distance matrix (instead of a similarity matrix) - is needed as input for the fit method. + metric : str or callable, default=”euclidean” + Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, + “manhattan”, “cosine”, or “precomputed”. If linkage is “ward”, only + “euclidean” is accepted. If “precomputed”, a distance matrix is needed + as input for the fit method. memory : str or object with the joblib.Memory interface, default=None Used to cache the output of the computation of the tree. @@ -203,7 +202,7 @@

Source code for dasf.ml.cluster.agglomerative

def __init__( self, n_clusters=2, - affinity="euclidean", + metric="euclidean", connectivity=None, linkage="single", memory=None, @@ -216,10 +215,11 @@

Source code for dasf.ml.cluster.agglomerative

output_type=None, **kwargs ): + """ Constructor of the class AgglomerativeClustering. """ super().__init__(**kwargs) self.n_clusters = n_clusters - self.affinity = affinity + self.metric = metric self.connectivity = connectivity self.linkage = linkage self.memory = memory @@ -233,7 +233,7 @@

Source code for dasf.ml.cluster.agglomerative

self.__agg_cluster_cpu = AgglomerativeClustering_CPU( n_clusters=n_clusters, - affinity=affinity, + metric=metric, memory=memory, connectivity=connectivity, compute_full_tree=compute_full_tree, @@ -248,7 +248,7 @@

Source code for dasf.ml.cluster.agglomerative

self.__agg_cluster_gpu = AgglomerativeClustering_GPU( n_clusters=n_clusters, - affinity=affinity, + affinity=metric, linkage=linkage, handle=handle, verbose=verbose, diff --git a/docs/_modules/dasf/ml/cluster/dbscan.html b/docs/_modules/dasf/ml/cluster/dbscan.html index ffe579e..910633e 100644 --- a/docs/_modules/dasf/ml/cluster/dbscan.html +++ b/docs/_modules/dasf/ml/cluster/dbscan.html @@ -214,6 +214,7 @@

Source code for dasf.ml.cluster.dbscan

         verbose=False,
         **kwargs
     ):
+        """ Constructor of the class DBSCAN. """
         super().__init__(**kwargs)
 
         self.eps = eps
diff --git a/docs/_modules/dasf/ml/cluster/hdbscan.html b/docs/_modules/dasf/ml/cluster/hdbscan.html
index 192c5e4..9aeb58b 100644
--- a/docs/_modules/dasf/ml/cluster/hdbscan.html
+++ b/docs/_modules/dasf/ml/cluster/hdbscan.html
@@ -285,6 +285,7 @@ 

Source code for dasf.ml.cluster.hdbscan

         verbose=0,
         **kwargs
     ):
+        """ Constructor of the class HDBSCAN. """
         super().__init__(**kwargs)
 
         self.alpha = alpha
diff --git a/docs/_modules/dasf/ml/cluster/kmeans.html b/docs/_modules/dasf/ml/cluster/kmeans.html
index ef69f83..6b63e09 100644
--- a/docs/_modules/dasf/ml/cluster/kmeans.html
+++ b/docs/_modules/dasf/ml/cluster/kmeans.html
@@ -182,15 +182,12 @@ 

Source code for dasf.ml.cluster.kmeans

     init_max_iter : int, default=None
         Number of iterations for init step.
 
-    algorithm : {"auto", "full", "elkan"}, default="full"
-        K-means algorithm to use. The classical EM-style algorithm is "full".
-        The "elkan" variation is more efficient on data with well-defined
-        clusters, by using the triangle inequality. However it's more memory
-        intensive due to the allocation of an extra array of shape
-        (n_samples, n_clusters).
-
-        For now "auto" (kept for backward compatibiliy) chooses "elkan" but it
-        might change in the future for a better heuristic.
+    algorithm : {“lloyd”, “elkan”}, default=”lloyd”
+        K-means algorithm to use. The classical EM-style algorithm is "lloyd".
+        The "elkan" variation can be more efficient on some datasets with
+        well-defined clusters, by using the triangle inequality. However
+        it’s more memory intensive due to the allocation of an extra array of
+        shape (n_samples, n_clusters).
 
         .. versionchanged:: 0.18
             Added Elkan algorithm
@@ -272,7 +269,7 @@ 

Source code for dasf.ml.cluster.kmeans

         verbose=0,
         random_state=None,
         copy_x=True,
-        algorithm='full',
+        algorithm='lloyd',
         oversampling_factor=2.0,
         n_jobs=1,
         init_max_iter=None,
@@ -281,6 +278,7 @@ 

Source code for dasf.ml.cluster.kmeans

         output_type=None,
         **kwargs
     ):
+        """ Constructor of the class KMeans. """
         super().__init__(**kwargs)
 
         self.n_clusters = n_clusters
@@ -679,7 +677,7 @@ 

Source code for dasf.ml.cluster.kmeans

         labels : ndarray of shape (n_samples,)
             Index of the cluster each sample belongs to.
         """
-        return self.__kmeans_cpu.predict(X, sample_weight)
+ return self.__kmeans_cpu.predict(X)
diff --git a/docs/_modules/dasf/ml/cluster/som.html b/docs/_modules/dasf/ml/cluster/som.html index 9a705e9..07a736e 100644 --- a/docs/_modules/dasf/ml/cluster/som.html +++ b/docs/_modules/dasf/ml/cluster/som.html @@ -200,6 +200,7 @@

Source code for dasf.ml.cluster.som

         compact_support=False,
         **kwargs
     ):
+        """ Constructor of the class SOM. """
         super().__init__(**kwargs)
 
         self.x = x
diff --git a/docs/_modules/dasf/ml/cluster/spectral.html b/docs/_modules/dasf/ml/cluster/spectral.html
index dc0fd72..a45a0a0 100644
--- a/docs/_modules/dasf/ml/cluster/spectral.html
+++ b/docs/_modules/dasf/ml/cluster/spectral.html
@@ -285,6 +285,7 @@ 

Source code for dasf.ml.cluster.spectral

         verbose=False,
         **kwargs
     ):
+        """ Constructor of the class SpectralClustering. """
         super().__init__(**kwargs)
 
         self.n_clusters = n_clusters
diff --git a/docs/_modules/dasf/ml/decomposition/pca.html b/docs/_modules/dasf/ml/decomposition/pca.html
index d227dcc..38fdc1c 100644
--- a/docs/_modules/dasf/ml/decomposition/pca.html
+++ b/docs/_modules/dasf/ml/decomposition/pca.html
@@ -374,6 +374,7 @@ 

Source code for dasf.ml.decomposition.pca

         *args,
         **kwargs,
     ):
+        """ Constructor of the class PCA. """
         TargeteredTransform.__init__(self, *args, **kwargs)
 
         self.__pca_cpu = PCA_CPU(
diff --git a/docs/_modules/dasf/pipeline/executors/base.html b/docs/_modules/dasf/pipeline/executors/base.html
index 04e1f33..48f902d 100644
--- a/docs/_modules/dasf/pipeline/executors/base.html
+++ b/docs/_modules/dasf/pipeline/executors/base.html
@@ -4,7 +4,7 @@
   
   
   dasf.pipeline.executors.base — DASF 1.0b5 documentation
-      
+      
       
       
 
@@ -105,8 +105,8 @@ 

Source code for dasf.pipeline.executors.base

dataset = list(kwargs.values())
 
         if len(dataset) != 1:
-            raise Exception(f"This function requires one dataset only. "
-                            "We found {len(dataset)}.")
+            raise Exception("This function requires one dataset only. "
+                            f"We found {len(dataset)}.")
 
         return dataset.pop()
diff --git a/docs/_modules/dasf/pipeline/executors/dask.html b/docs/_modules/dasf/pipeline/executors/dask.html index b8ed4c9..fd04ba9 100644 --- a/docs/_modules/dasf/pipeline/executors/dask.html +++ b/docs/_modules/dasf/pipeline/executors/dask.html @@ -4,7 +4,7 @@ dasf.pipeline.executors.dask — DASF 1.0b5 documentation - + @@ -80,6 +80,7 @@

Source code for dasf.pipeline.executors.dask

 #!/usr/bin/env python3
+""" Dask executor module. """
 
 import os
 from typing import Union
@@ -87,7 +88,7 @@ 

Source code for dasf.pipeline.executors.dask

try:
     import cupy as cp
     import rmm
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from pathlib import Path
@@ -182,7 +183,8 @@ 

Source code for dasf.pipeline.executors.dask

LocalCUDACluster(**cluster_kwargs), **client_kwargs
                 )
             else:
-                os.environ["CUDA_VISIBLE_DEVICES"] = "" # This avoids initializing workers on GPU:0 when available
+                # This avoids initializing workers on GPU:0 when available
+                os.environ["CUDA_VISIBLE_DEVICES"] = ""
                 self.client = Client(LocalCluster(**cluster_kwargs),
                                      **client_kwargs)
 
diff --git a/docs/_modules/dasf/pipeline/executors/ray.html b/docs/_modules/dasf/pipeline/executors/ray.html
index cc32f69..bbb2327 100644
--- a/docs/_modules/dasf/pipeline/executors/ray.html
+++ b/docs/_modules/dasf/pipeline/executors/ray.html
@@ -88,7 +88,7 @@ 

Source code for dasf.pipeline.executors.ray

     from ray.util.dask import disable_dask_on_ray, enable_dask_on_ray
 
     USE_RAY = True
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     USE_RAY = False
 
 from dasf.pipeline.executors.base import Executor
@@ -98,7 +98,8 @@ 

Source code for dasf.pipeline.executors.ray

 
[docs] class RayPipelineExecutor(Executor): - """A pipeline executor based on ray data flow. + """ + A pipeline executor based on ray data flow. Parameters ---------- diff --git a/docs/_modules/dasf/pipeline/executors/wrapper.html b/docs/_modules/dasf/pipeline/executors/wrapper.html index 9486730..d7eab71 100644 --- a/docs/_modules/dasf/pipeline/executors/wrapper.html +++ b/docs/_modules/dasf/pipeline/executors/wrapper.html @@ -81,26 +81,14 @@

Source code for dasf.pipeline.executors.wrapper

 #!/usr/bin/env python3
 
-import numpy as np
-
 try:
     import cupy as cp
     import rmm
-except ImportError: # pragma: no cover
-    pass
-
-try:
-    from jax import jit
-except ImportError: # pragma: no cover
+except ImportError:  # pragma: no cover
     pass
 
 from dasf.pipeline.types import TaskExecutorType
-from dasf.utils.funcs import (
-    get_backend_supported,
-    get_gpu_count,
-    is_gpu_supported,
-    is_jax_supported,
-)
+from dasf.utils.funcs import get_backend_supported, get_gpu_count, is_gpu_supported
 
 
 
diff --git a/docs/_modules/dasf/pipeline/pipeline.html b/docs/_modules/dasf/pipeline/pipeline.html index df9dc08..d6fd691 100644 --- a/docs/_modules/dasf/pipeline/pipeline.html +++ b/docs/_modules/dasf/pipeline/pipeline.html @@ -4,7 +4,7 @@ dasf.pipeline.pipeline — DASF 1.0b5 documentation - + @@ -314,7 +314,7 @@

Source code for dasf.pipeline.pipeline

 
         if not hasattr(self._executor, "execute"):
             raise Exception(
-                f"Executor {self._executor.__name__} has not a execute() "
+                f"Executor {self._executor.__class__.__name__} has not a execute() "
                 "method."
             )
 
@@ -359,6 +359,8 @@ 

Source code for dasf.pipeline.pipeline

                 self.execute_callbacks("on_task_error", func=func,
                                        params=params, name=name, exception=e)
                 failed = True
+                failed_at = name
+
                 err = str(e)
                 self._logger.exception(f"Task '{name}': Failed with:\n{err}")
 
@@ -368,7 +370,7 @@ 

Source code for dasf.pipeline.pipeline

                 self._logger.error(f"Task '{name}': Finished task run")
 
         if failed:
-            self._logger.info(f"Pipeline failed at '{name}'")
+            self._logger.info(f"Pipeline failed at '{failed_at}'")
         else:
             self._logger.info("Pipeline run successfully")
 
diff --git a/docs/_modules/dasf/transforms/base.html b/docs/_modules/dasf/transforms/base.html
index 0368690..f72fd35 100644
--- a/docs/_modules/dasf/transforms/base.html
+++ b/docs/_modules/dasf/transforms/base.html
@@ -79,8 +79,9 @@
            

Source code for dasf.transforms.base

-""" Definition of the generic operators of the pipeline. """
-#!/usr/bin/python3
+#!/usr/bin/python3
+
+""" Definition of the generic operators of the pipeline. """
 
 import inspect
 from uuid import uuid4
@@ -91,8 +92,11 @@ 

Source code for dasf.transforms.base

 try:
     import cupy as cp
     import dask_cudf as dcudf
+    from rmm._cuda.gpu import CUDARuntimeError
 except ImportError: # pragma: no cover
     pass
+except CUDARuntimeError:
+    pass
 
 from dasf.utils.decorators import task_handler
 from dasf.utils.funcs import block_chunk_reduce
@@ -581,6 +585,7 @@ 

Source code for dasf.transforms.base

     """
 
     def __init__(self, run_local=None, run_gpu=None):
+        """ Constructor of the class TargeteredTransform. """
         super().__init__()
 
         self._run_local = run_local
diff --git a/docs/_modules/dasf/transforms/memory.html b/docs/_modules/dasf/transforms/memory.html
index 2f9da75..66eec10 100644
--- a/docs/_modules/dasf/transforms/memory.html
+++ b/docs/_modules/dasf/transforms/memory.html
@@ -4,7 +4,7 @@
   
   
   dasf.transforms.memory — DASF 1.0b5 documentation
-      
+      
       
       
 
@@ -81,6 +81,8 @@
   

Source code for dasf.transforms.memory

 #!/usr/bin/env python3
 
+""" Memory Management module. """
+
 from dasf.transforms.base import Transform
 from dasf.utils.types import is_dask_array, is_dask_dataframe
 
diff --git a/docs/_modules/dasf/transforms/operations.html b/docs/_modules/dasf/transforms/operations.html
index 95deaa7..aff34aa 100644
--- a/docs/_modules/dasf/transforms/operations.html
+++ b/docs/_modules/dasf/transforms/operations.html
@@ -81,6 +81,8 @@
   

Source code for dasf.transforms.operations

 #!/usr/bin/env python3
 
+""" Basic transform operations module. """
+
 import dask.array as da
 import numpy as np
 from scipy import stats
diff --git a/docs/_modules/dasf/transforms/transforms.html b/docs/_modules/dasf/transforms/transforms.html
index 251c973..2e2046d 100644
--- a/docs/_modules/dasf/transforms/transforms.html
+++ b/docs/_modules/dasf/transforms/transforms.html
@@ -81,6 +81,8 @@
   

Source code for dasf.transforms.transforms

 #!/usr/bin/env python3
 
+""" All the essential data transforms module. """
+
 import math
 
 import dask
@@ -103,11 +105,28 @@ 

Source code for dasf.transforms.transforms

 
[docs] class ExtractData(Transform): - """Extract Data from Dataset Object + """ + Extract data from Dataset object + """
[docs] def transform(self, X): + """ + Extract data from datasets that contains internal data. + + Parameters + ---------- + X : Dataset-like + A dataset object that could be anything that contains an internal + structure representing the raw data. + + Returns + ------- + data : Any + Any representation of the internal Dataset data. + + """ if hasattr(X, "_data") and X._data is not None: return X._data raise ValueError("Data could not be extracted. Dataset needs to be previously loaded.")
@@ -118,9 +137,28 @@

Source code for dasf.transforms.transforms

 
[docs] class Normalize(Transform): + """ + Normalize data object + + """
[docs] def transform(self, X): + """ + Normalize the input data based on mean() and std(). + + Parameters + ---------- + X : Any + Any data that could be normalized based on mean and standard + deviation. + + Returns + ------- + data : Any + Normalized data + + """ return (X - X.mean()) / (X.std(ddof=0))
diff --git a/docs/_modules/dasf/utils/funcs.html b/docs/_modules/dasf/utils/funcs.html index 3093679..fd932e4 100644 --- a/docs/_modules/dasf/utils/funcs.html +++ b/docs/_modules/dasf/utils/funcs.html @@ -4,7 +4,7 @@ dasf.utils.funcs — DASF 1.0b5 documentation - + @@ -373,6 +373,12 @@

Source code for dasf.utils.funcs

         if progressbar:
             progressbar.set_error(True)
 
+    # XXX: workaround to fix thread starvation while gdown does not support
+    # external pbar's. See [1].
+    # [1] https://github.com/wkentaro/gdown/pull/241
+    if progressbar is not None:
+        progressbar.set_current(100, 100)
+
     return output
diff --git a/docs/_modules/index.html b/docs/_modules/index.html index 64cdb62..527e9bd 100644 --- a/docs/_modules/index.html +++ b/docs/_modules/index.html @@ -84,11 +84,19 @@

All modules for which code is available

  • dasf.datasets.download
  • dasf.debug.debug
  • dasf.feature_extraction.histogram
  • -
  • dasf.feature_extraction.transform
  • +
  • dasf.feature_extraction.transforms
  • dasf.ml.cluster.agglomerative
  • dasf.ml.cluster.classifier
  • dasf.ml.cluster.dbscan
  • +
  • dasf.ml.cluster.hdbscan
  • +
  • dasf.ml.cluster.kmeans
  • +
  • dasf.ml.cluster.som
  • +
  • dasf.ml.cluster.spectral
  • dasf.ml.decomposition.pca
  • +
  • dasf.ml.dl.clusters.dask
  • +
  • dasf.ml.dl.lightning_fit
  • +
  • dasf.ml.dl.models.devconvnet
  • +
  • dasf.ml.dl.pytorch_lightning
  • dasf.ml.inference.loader.base
  • dasf.ml.inference.loader.torch
  • dasf.ml.mixture.classifier
  • diff --git a/docs/_sources/autoapi/dasf/datasets/base/index.rst.txt b/docs/_sources/autoapi/dasf/datasets/base/index.rst.txt index 1d71f15..3fede50 100644 --- a/docs/_sources/autoapi/dasf/datasets/base/index.rst.txt +++ b/docs/_sources/autoapi/dasf/datasets/base/index.rst.txt @@ -32,7 +32,7 @@ Module Contents Bases: :py:obj:`dasf.transforms.base.TargeteredTransform` - Class representing a generic dataset based on a TargeteredTransform + Class representing a generic dataset based on a TargeteredTransform object. Parameters @@ -49,14 +49,36 @@ Module Contents Additional keyworkded arguments. - Constructor of the object Dataset. + Constructor of the object Dataset. + + + + .. py:attribute:: _name + + + .. py:attribute:: _download + + + .. py:attribute:: _root + + + .. py:attribute:: _metadata + + + .. py:attribute:: _data + :value: None + + + + .. py:attribute:: _chunks + :value: None + .. py:method:: __set_dataset_cache_dir() Generate cached directory in $HOME to store dataset(s). - @@ -64,7 +86,6 @@ Module Contents Skeleton of the download method. - @@ -72,7 +93,6 @@ Module Contents Return internal data length. - @@ -93,7 +113,7 @@ Module Contents Bases: :py:obj:`Dataset` - Class representing an dataset wich is defined as an array of a defined + Class representing an dataset wich is defined as an array of a defined shape. Parameters @@ -108,7 +128,13 @@ Module Contents Number of blocks of the array (the default is "auto"). - Constructor of the object DatasetArray. + Constructor of the object DatasetArray. + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file .. py:method:: __operator_check__(other) @@ -135,8 +161,6 @@ Module Contents Return a class representation based on internal array. - - .. py:method:: __array__(dtype=None) @@ -157,6 +181,34 @@ Module Contents .. py:method:: __array_ufunc__(ufunc, method, *inputs, **kwargs) + Any class, array subclass or not, can define this method or set + it to None in order to override the behavior of Arrays ufuncs. + + Parameters + ---------- + ufunc : Callable + The ufunc object that was called. + + method : Str + A string indicating which Ufunc method was called (one of + "__call__", "reduce", "reduceat", "accumulate", "outer", "inner"). + + inputs : Any + A tuple of the input arguments to the ufunc. + + kwargs : Any + A dictionary containing the optional input arguments of the ufunc. + If given, any out arguments, both positional and keyword, are + passed as a tuple in kwargs. See the discussion in Universal + functions (ufunc) for details. + + Returns + ------- + array : array-like + The return either the result of the operation. + + + .. py:method:: __check_op_input(in_data) @@ -189,7 +241,7 @@ Module Contents Returns ------- - DatasetArry + DatasetArray A sum with two arrays. @@ -250,7 +302,6 @@ Module Contents Extends metadata to new transformed object (after operations). - @@ -258,7 +309,6 @@ Module Contents Read an array header from a filelike object. - @@ -311,7 +361,6 @@ Module Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -319,7 +368,6 @@ Module Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -327,7 +375,6 @@ Module Contents Load data with GPU container (e.g. cupy). - @@ -335,7 +382,6 @@ Module Contents Load data with CPU container (e.g. numpy). - @@ -354,7 +400,6 @@ Module Contents Placeholder for load function. - @@ -371,7 +416,7 @@ Module Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -406,6 +451,15 @@ Module Contents Constructor of the object DatasetZarr. + .. py:attribute:: _backend + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file + + .. py:method:: _lazy_load(xp, **kwargs) Lazy load the dataset using an CPU dask container. @@ -523,7 +577,7 @@ Module Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -539,7 +593,6 @@ Module Contents Return a class representation based on internal array. - @@ -635,7 +688,6 @@ Module Contents Extends metadata to new transformed object (after operations). - @@ -661,7 +713,17 @@ Module Contents Relative path of the internal HDF5 dataset (the default is None). - Constructor of the object DatasetHDF5. + Constructor of the object DatasetHDF5. + + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file + + + .. py:attribute:: _dataset_path .. py:method:: _lazy_load(xp, **kwargs) @@ -701,7 +763,6 @@ Module Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -709,7 +770,6 @@ Module Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -717,7 +777,6 @@ Module Contents Load data with CPU container (e.g. numpy). - @@ -725,7 +784,6 @@ Module Contents Load data with GPU container (e.g. cupy). - @@ -733,7 +791,6 @@ Module Contents Placeholder for load function. - @@ -749,7 +806,7 @@ Module Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -783,14 +840,23 @@ Module Contents Key (or index) of the internal Xarray dataset (the default is None). - Constructor of the object DatasetXarray. + Constructor of the object DatasetXarray. + + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file + + + .. py:attribute:: _data_var .. py:method:: _lazy_load_cpu() Load data with CPU container + DASK. (It does not load immediattly) - @@ -798,7 +864,6 @@ Module Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -806,7 +871,6 @@ Module Contents Load data with CPU container (e.g. numpy). - @@ -814,7 +878,6 @@ Module Contents Load data with GPU container (e.g. cupy). - @@ -822,7 +885,6 @@ Module Contents Placeholder for load function. - @@ -838,7 +900,7 @@ Module Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -854,7 +916,6 @@ Module Contents Return internal data length. - @@ -896,18 +957,21 @@ Module Contents Description of attribute `__chunks`. - Constructor of the object DatasetLabeled. + Constructor of the object DatasetLabeled. + + + + .. py:attribute:: _chunks .. py:method:: download() Download the dataset. - - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data (train and labels). @@ -974,7 +1038,6 @@ Module Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -982,7 +1045,6 @@ Module Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -990,7 +1052,6 @@ Module Contents Load data with GPU container (e.g. cupy). - @@ -998,7 +1059,6 @@ Module Contents Load data with CPU container (e.g. numpy). - @@ -1006,7 +1066,6 @@ Module Contents Placeholder for load function. - @@ -1041,7 +1100,14 @@ Module Contents Number of blocks of the array (the default is "auto"). - Constructor of the object DatasetDataFrame. + Constructor of the object DatasetDataFrame. + + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file .. py:method:: _load_meta() @@ -1056,7 +1122,7 @@ Module Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -1072,7 +1138,6 @@ Module Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -1080,7 +1145,6 @@ Module Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -1088,7 +1152,6 @@ Module Contents Load data with GPU container (e.g. CuDF). - @@ -1096,7 +1159,6 @@ Module Contents Load data with CPU container (e.g. pandas). - @@ -1104,7 +1166,6 @@ Module Contents Placeholder for load function. - @@ -1124,7 +1185,6 @@ Module Contents .. py:method:: __len__() Return internal data length. - @@ -1145,7 +1205,7 @@ Module Contents Bases: :py:obj:`DatasetDataFrame` - Class representing an dataset wich is defined as a Parquet. + Class representing an dataset wich is defined as a Parquet. Parameters ---------- @@ -1159,14 +1219,14 @@ Module Contents Number of blocks of the array (the default is "auto"). - Constructor of the object DatasetParquet. + Constructor of the object DatasetParquet. + .. py:method:: _lazy_load_gpu() Load data with GPU container + DASK. (It does not load immediattly) - @@ -1174,7 +1234,6 @@ Module Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -1182,7 +1241,6 @@ Module Contents Load data with GPU container (e.g. CuDF). - @@ -1190,7 +1248,6 @@ Module Contents Load data with CPU container (e.g. pandas). - diff --git a/docs/_sources/autoapi/dasf/datasets/download/index.rst.txt b/docs/_sources/autoapi/dasf/datasets/download/index.rst.txt index cb7ee5e..4b662ae 100644 --- a/docs/_sources/autoapi/dasf/datasets/download/index.rst.txt +++ b/docs/_sources/autoapi/dasf/datasets/download/index.rst.txt @@ -43,6 +43,12 @@ Module Contents Constructor of the object DownloadWget. + .. py:attribute:: __url + + + .. py:attribute:: __filename + + .. py:method:: download() Download the dataset. @@ -71,6 +77,12 @@ Module Contents Constructor of the object DownloadGDrive. + .. py:attribute:: __google_file_id + + + .. py:attribute:: __filename + + .. py:method:: download() Download the dataset. diff --git a/docs/_sources/autoapi/dasf/datasets/index.rst.txt b/docs/_sources/autoapi/dasf/datasets/index.rst.txt index 770f327..c908fbb 100644 --- a/docs/_sources/autoapi/dasf/datasets/index.rst.txt +++ b/docs/_sources/autoapi/dasf/datasets/index.rst.txt @@ -45,7 +45,7 @@ Package Contents Bases: :py:obj:`dasf.transforms.base.TargeteredTransform` - Class representing a generic dataset based on a TargeteredTransform + Class representing a generic dataset based on a TargeteredTransform object. Parameters @@ -62,14 +62,36 @@ Package Contents Additional keyworkded arguments. - Constructor of the object Dataset. + Constructor of the object Dataset. + + + + .. py:attribute:: _name + + + .. py:attribute:: _download + + + .. py:attribute:: _root + + + .. py:attribute:: _metadata + + + .. py:attribute:: _data + :value: None + + + + .. py:attribute:: _chunks + :value: None + .. py:method:: __set_dataset_cache_dir() Generate cached directory in $HOME to store dataset(s). - @@ -77,7 +99,6 @@ Package Contents Skeleton of the download method. - @@ -85,7 +106,6 @@ Package Contents Return internal data length. - @@ -106,7 +126,7 @@ Package Contents Bases: :py:obj:`Dataset` - Class representing an dataset wich is defined as an array of a defined + Class representing an dataset wich is defined as an array of a defined shape. Parameters @@ -121,7 +141,13 @@ Package Contents Number of blocks of the array (the default is "auto"). - Constructor of the object DatasetArray. + Constructor of the object DatasetArray. + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file .. py:method:: __operator_check__(other) @@ -148,8 +174,6 @@ Package Contents Return a class representation based on internal array. - - .. py:method:: __array__(dtype=None) @@ -170,6 +194,34 @@ Package Contents .. py:method:: __array_ufunc__(ufunc, method, *inputs, **kwargs) + Any class, array subclass or not, can define this method or set + it to None in order to override the behavior of Arrays ufuncs. + + Parameters + ---------- + ufunc : Callable + The ufunc object that was called. + + method : Str + A string indicating which Ufunc method was called (one of + "__call__", "reduce", "reduceat", "accumulate", "outer", "inner"). + + inputs : Any + A tuple of the input arguments to the ufunc. + + kwargs : Any + A dictionary containing the optional input arguments of the ufunc. + If given, any out arguments, both positional and keyword, are + passed as a tuple in kwargs. See the discussion in Universal + functions (ufunc) for details. + + Returns + ------- + array : array-like + The return either the result of the operation. + + + .. py:method:: __check_op_input(in_data) @@ -202,7 +254,7 @@ Package Contents Returns ------- - DatasetArry + DatasetArray A sum with two arrays. @@ -263,7 +315,6 @@ Package Contents Extends metadata to new transformed object (after operations). - @@ -271,7 +322,6 @@ Package Contents Read an array header from a filelike object. - @@ -324,7 +374,6 @@ Package Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -332,7 +381,6 @@ Package Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -340,7 +388,6 @@ Package Contents Load data with GPU container (e.g. cupy). - @@ -348,7 +395,6 @@ Package Contents Load data with CPU container (e.g. numpy). - @@ -367,7 +413,6 @@ Package Contents Placeholder for load function. - @@ -384,7 +429,7 @@ Package Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -419,6 +464,15 @@ Package Contents Constructor of the object DatasetZarr. + .. py:attribute:: _backend + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file + + .. py:method:: _lazy_load(xp, **kwargs) Lazy load the dataset using an CPU dask container. @@ -536,7 +590,7 @@ Package Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -552,7 +606,6 @@ Package Contents Return a class representation based on internal array. - @@ -648,7 +701,6 @@ Package Contents Extends metadata to new transformed object (after operations). - @@ -674,7 +726,17 @@ Package Contents Relative path of the internal HDF5 dataset (the default is None). - Constructor of the object DatasetHDF5. + Constructor of the object DatasetHDF5. + + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file + + + .. py:attribute:: _dataset_path .. py:method:: _lazy_load(xp, **kwargs) @@ -714,7 +776,6 @@ Package Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -722,7 +783,6 @@ Package Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -730,7 +790,6 @@ Package Contents Load data with CPU container (e.g. numpy). - @@ -738,7 +797,6 @@ Package Contents Load data with GPU container (e.g. cupy). - @@ -746,7 +804,6 @@ Package Contents Placeholder for load function. - @@ -762,7 +819,7 @@ Package Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -796,14 +853,23 @@ Package Contents Key (or index) of the internal Xarray dataset (the default is None). - Constructor of the object DatasetXarray. + Constructor of the object DatasetXarray. + + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file + + + .. py:attribute:: _data_var .. py:method:: _lazy_load_cpu() Load data with CPU container + DASK. (It does not load immediattly) - @@ -811,7 +877,6 @@ Package Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -819,7 +884,6 @@ Package Contents Load data with CPU container (e.g. numpy). - @@ -827,7 +891,6 @@ Package Contents Load data with GPU container (e.g. cupy). - @@ -835,7 +898,6 @@ Package Contents Placeholder for load function. - @@ -851,7 +913,7 @@ Package Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -867,7 +929,6 @@ Package Contents Return internal data length. - @@ -909,18 +970,21 @@ Package Contents Description of attribute `__chunks`. - Constructor of the object DatasetLabeled. + Constructor of the object DatasetLabeled. + + + + .. py:attribute:: _chunks .. py:method:: download() Download the dataset. - - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data (train and labels). @@ -987,7 +1051,6 @@ Package Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -995,7 +1058,6 @@ Package Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -1003,7 +1065,6 @@ Package Contents Load data with GPU container (e.g. cupy). - @@ -1011,7 +1072,6 @@ Package Contents Load data with CPU container (e.g. numpy). - @@ -1019,7 +1079,6 @@ Package Contents Placeholder for load function. - @@ -1054,7 +1113,14 @@ Package Contents Number of blocks of the array (the default is "auto"). - Constructor of the object DatasetDataFrame. + Constructor of the object DatasetDataFrame. + + + + .. py:attribute:: _chunks + + + .. py:attribute:: _root_file .. py:method:: _load_meta() @@ -1069,7 +1135,7 @@ Package Contents - .. py:method:: inspect_metadata() + .. py:method:: metadata() Return a dictionary with all metadata information from data. @@ -1085,7 +1151,6 @@ Package Contents Load data with GPU container + DASK. (It does not load immediattly) - @@ -1093,7 +1158,6 @@ Package Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -1101,7 +1165,6 @@ Package Contents Load data with GPU container (e.g. CuDF). - @@ -1109,7 +1172,6 @@ Package Contents Load data with CPU container (e.g. pandas). - @@ -1117,7 +1179,6 @@ Package Contents Placeholder for load function. - @@ -1137,7 +1198,6 @@ Package Contents .. py:method:: __len__() Return internal data length. - @@ -1158,7 +1218,7 @@ Package Contents Bases: :py:obj:`DatasetDataFrame` - Class representing an dataset wich is defined as a Parquet. + Class representing an dataset wich is defined as a Parquet. Parameters ---------- @@ -1172,14 +1232,14 @@ Package Contents Number of blocks of the array (the default is "auto"). - Constructor of the object DatasetParquet. + Constructor of the object DatasetParquet. + .. py:method:: _lazy_load_gpu() Load data with GPU container + DASK. (It does not load immediattly) - @@ -1187,7 +1247,6 @@ Package Contents Load data with CPU container + DASK. (It does not load immediattly) - @@ -1195,7 +1254,6 @@ Package Contents Load data with GPU container (e.g. CuDF). - @@ -1203,7 +1261,6 @@ Package Contents Load data with CPU container (e.g. pandas). - diff --git a/docs/_sources/autoapi/dasf/debug/debug/index.rst.txt b/docs/_sources/autoapi/dasf/debug/debug/index.rst.txt index b302390..3b4bc7a 100644 --- a/docs/_sources/autoapi/dasf/debug/debug/index.rst.txt +++ b/docs/_sources/autoapi/dasf/debug/debug/index.rst.txt @@ -66,6 +66,9 @@ Module Contents Generic constructor of the VisualizeDaskData object. + .. py:attribute:: filename + + .. py:method:: display(X) Display Dask task graph using visualize method. diff --git a/docs/_sources/autoapi/dasf/debug/index.rst.txt b/docs/_sources/autoapi/dasf/debug/index.rst.txt index 867a753..963ab57 100644 --- a/docs/_sources/autoapi/dasf/debug/index.rst.txt +++ b/docs/_sources/autoapi/dasf/debug/index.rst.txt @@ -3,6 +3,11 @@ dasf.debug .. py:module:: dasf.debug +.. autoapi-nested-parse:: + + Init module for debugging DASF. + + Submodules ---------- @@ -70,6 +75,9 @@ Package Contents Generic constructor of the VisualizeDaskData object. + .. py:attribute:: filename + + .. py:method:: display(X) Display Dask task graph using visualize method. diff --git a/docs/_sources/autoapi/dasf/feature_extraction/histogram/index.rst.txt b/docs/_sources/autoapi/dasf/feature_extraction/histogram/index.rst.txt index a1d45f0..a303827 100644 --- a/docs/_sources/autoapi/dasf/feature_extraction/histogram/index.rst.txt +++ b/docs/_sources/autoapi/dasf/feature_extraction/histogram/index.rst.txt @@ -58,7 +58,22 @@ Module Contents Generic constructor of the class Histogram. - .. py:method:: __lazy_transform_generic(X) + .. py:attribute:: _bins + + + .. py:attribute:: _range + + + .. py:attribute:: _normed + + + .. py:attribute:: _weights + + + .. py:attribute:: _density + + + .. py:method:: _lazy_transform_generic(X) Compute the histogram of a dataset using Dask. @@ -78,7 +93,7 @@ Module Contents - .. py:method:: __transform_generic(X, xp) + .. py:method:: _transform_generic(X, xp) Compute the histogram of a dataset using local libraries. diff --git a/docs/_sources/autoapi/dasf/feature_extraction/index.rst.txt b/docs/_sources/autoapi/dasf/feature_extraction/index.rst.txt index 7048995..284dbb8 100644 --- a/docs/_sources/autoapi/dasf/feature_extraction/index.rst.txt +++ b/docs/_sources/autoapi/dasf/feature_extraction/index.rst.txt @@ -11,7 +11,7 @@ Submodules :maxdepth: 1 /autoapi/dasf/feature_extraction/histogram/index - /autoapi/dasf/feature_extraction/transform/index + /autoapi/dasf/feature_extraction/transforms/index Classes @@ -22,7 +22,6 @@ Classes dasf.feature_extraction.Histogram dasf.feature_extraction.ConcatenateToArray dasf.feature_extraction.GetSubDataframe - dasf.feature_extraction.GetSubeCubeArray dasf.feature_extraction.SampleDataframe @@ -67,7 +66,22 @@ Package Contents Generic constructor of the class Histogram. - .. py:method:: __lazy_transform_generic(X) + .. py:attribute:: _bins + + + .. py:attribute:: _range + + + .. py:attribute:: _normed + + + .. py:attribute:: _weights + + + .. py:attribute:: _density + + + .. py:method:: _lazy_transform_generic(X) Compute the histogram of a dataset using Dask. @@ -87,7 +101,7 @@ Package Contents - .. py:method:: __transform_generic(X, xp) + .. py:method:: _transform_generic(X, xp) Compute the histogram of a dataset using local libraries. @@ -203,6 +217,9 @@ Package Contents + .. py:attribute:: flatten + + .. py:method:: __transform_generic(xp, **kwargs) @@ -229,18 +246,7 @@ Package Contents - .. py:method:: transform(X) - - -.. py:class:: GetSubeCubeArray(percent) - - Get a subcube with x% of samples from the original one. - - Parameters - ---------- - percent : float - Percentage of the samples to get from the cube. - + .. py:attribute:: __percent .. py:method:: transform(X) @@ -248,6 +254,9 @@ Package Contents .. py:class:: SampleDataframe(percent) + Bases: :py:obj:`dasf.transforms.base.Transform` + + Return a subset with random samples of the original dataset. Parameters @@ -257,7 +266,10 @@ Package Contents - .. py:method:: run(X) + .. py:attribute:: __percent + + + .. py:method:: transform(X) Returns a subset with random samples from the dataset `X`. diff --git a/docs/_sources/autoapi/dasf/index.rst.txt b/docs/_sources/autoapi/dasf/index.rst.txt index 3e621f3..7cab251 100644 --- a/docs/_sources/autoapi/dasf/index.rst.txt +++ b/docs/_sources/autoapi/dasf/index.rst.txt @@ -3,6 +3,11 @@ dasf .. py:module:: dasf +.. autoapi-nested-parse:: + + Init all modules for DASF. + + Subpackages ----------- diff --git a/docs/_sources/autoapi/dasf/ml/cluster/agglomerative/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/agglomerative/index.rst.txt index f4b04d2..1bae152 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/agglomerative/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/agglomerative/index.rst.txt @@ -20,7 +20,7 @@ Classes Module Contents --------------- -.. py:class:: AgglomerativeClustering(n_clusters=2, affinity='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs) +.. py:class:: AgglomerativeClustering(n_clusters=2, metric='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs) Bases: :py:obj:`dasf.ml.cluster.classifier.ClusterClassifier` @@ -38,12 +38,11 @@ Module Contents The number of clusters to find. It must be ``None`` if ``distance_threshold`` is not ``None``. - affinity : str or callable, default='euclidean' - Metric used to compute the linkage. Can be "euclidean", "l1", "l2", - "manhattan", "cosine", or "precomputed". - If linkage is "ward", only "euclidean" is accepted. - If "precomputed", a distance matrix (instead of a similarity matrix) - is needed as input for the fit method. + metric : str or callable, default=”euclidean” + Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, + “manhattan”, “cosine”, or “precomputed”. If linkage is “ward”, only + “euclidean” is accepted. If “precomputed”, a distance matrix is needed + as input for the fit method. memory : str or object with the joblib.Memory interface, default=None Used to cache the output of the computation of the tree. @@ -124,7 +123,46 @@ Module Contents - https://docs.rapids.ai/api/cuml/stable/api.html#agglomerative-clustering - A generic constructor method. + Constructor of the class AgglomerativeClustering. + + + .. py:attribute:: n_clusters + + + .. py:attribute:: metric + + + .. py:attribute:: connectivity + + + .. py:attribute:: linkage + + + .. py:attribute:: memory + + + .. py:attribute:: compute_full_tree + + + .. py:attribute:: distance_threshold + + + .. py:attribute:: compute_distances + + + .. py:attribute:: handle + + + .. py:attribute:: verbose + + + .. py:attribute:: n_neighbors + + + .. py:attribute:: output_type + + + .. py:attribute:: __agg_cluster_cpu .. py:method:: _fit_cpu(X, y=None, convert_dtype=True) diff --git a/docs/_sources/autoapi/dasf/ml/cluster/dbscan/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/dbscan/index.rst.txt index df775c8..f3f84a1 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/dbscan/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/dbscan/index.rst.txt @@ -129,7 +129,34 @@ Module Contents ACM Transactions on Database Systems (TODS), 42(3), 19. - A generic constructor method. + Constructor of the class DBSCAN. + + + .. py:attribute:: eps + + + .. py:attribute:: leaf_size + + + .. py:attribute:: metric + + + .. py:attribute:: min_samples + + + .. py:attribute:: p + + + .. py:attribute:: output_type + + + .. py:attribute:: calc_core_sample_indices + + + .. py:attribute:: verbose + + + .. py:attribute:: __dbscan_cpu .. py:method:: _lazy_fit_gpu(X, y=None, out_dtype='int32') diff --git a/docs/_sources/autoapi/dasf/ml/cluster/hdbscan/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/hdbscan/index.rst.txt index e47d52c..92c7ebe 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/hdbscan/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/hdbscan/index.rst.txt @@ -191,7 +191,61 @@ Module Contents Density-based Cluster Selection. arxiv preprint 1911.02282. - A generic constructor method. + Constructor of the class HDBSCAN. + + + .. py:attribute:: alpha + + + .. py:attribute:: gen_min_span_tree + + + .. py:attribute:: leaf_size + + + .. py:attribute:: metric + + + .. py:attribute:: min_cluster_size + + + .. py:attribute:: min_samples + + + .. py:attribute:: p + + + .. py:attribute:: algorithm + + + .. py:attribute:: approx_min_span_tree + + + .. py:attribute:: core_dist_n_jobs + + + .. py:attribute:: cluster_selection_method + + + .. py:attribute:: allow_single_cluster + + + .. py:attribute:: prediction_data + + + .. py:attribute:: match_reference_implementation + + + .. py:attribute:: connectivity + + + .. py:attribute:: output_type + + + .. py:attribute:: verbose + + + .. py:attribute:: __hdbscan_cpu .. py:method:: _fit_cpu(X, y=None) diff --git a/docs/_sources/autoapi/dasf/ml/cluster/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/index.rst.txt index 3d3ee4d..a621eb7 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/index.rst.txt @@ -40,7 +40,7 @@ Classes Package Contents ---------------- -.. py:class:: AgglomerativeClustering(n_clusters=2, affinity='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs) +.. py:class:: AgglomerativeClustering(n_clusters=2, metric='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs) Bases: :py:obj:`dasf.ml.cluster.classifier.ClusterClassifier` @@ -58,12 +58,11 @@ Package Contents The number of clusters to find. It must be ``None`` if ``distance_threshold`` is not ``None``. - affinity : str or callable, default='euclidean' - Metric used to compute the linkage. Can be "euclidean", "l1", "l2", - "manhattan", "cosine", or "precomputed". - If linkage is "ward", only "euclidean" is accepted. - If "precomputed", a distance matrix (instead of a similarity matrix) - is needed as input for the fit method. + metric : str or callable, default=”euclidean” + Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, + “manhattan”, “cosine”, or “precomputed”. If linkage is “ward”, only + “euclidean” is accepted. If “precomputed”, a distance matrix is needed + as input for the fit method. memory : str or object with the joblib.Memory interface, default=None Used to cache the output of the computation of the tree. @@ -144,7 +143,46 @@ Package Contents - https://docs.rapids.ai/api/cuml/stable/api.html#agglomerative-clustering - A generic constructor method. + Constructor of the class AgglomerativeClustering. + + + .. py:attribute:: n_clusters + + + .. py:attribute:: metric + + + .. py:attribute:: connectivity + + + .. py:attribute:: linkage + + + .. py:attribute:: memory + + + .. py:attribute:: compute_full_tree + + + .. py:attribute:: distance_threshold + + + .. py:attribute:: compute_distances + + + .. py:attribute:: handle + + + .. py:attribute:: verbose + + + .. py:attribute:: n_neighbors + + + .. py:attribute:: output_type + + + .. py:attribute:: __agg_cluster_cpu .. py:method:: _fit_cpu(X, y=None, convert_dtype=True) @@ -338,7 +376,34 @@ Package Contents ACM Transactions on Database Systems (TODS), 42(3), 19. - A generic constructor method. + Constructor of the class DBSCAN. + + + .. py:attribute:: eps + + + .. py:attribute:: leaf_size + + + .. py:attribute:: metric + + + .. py:attribute:: min_samples + + + .. py:attribute:: p + + + .. py:attribute:: output_type + + + .. py:attribute:: calc_core_sample_indices + + + .. py:attribute:: verbose + + + .. py:attribute:: __dbscan_cpu .. py:method:: _lazy_fit_gpu(X, y=None, out_dtype='int32') @@ -680,7 +745,61 @@ Package Contents Density-based Cluster Selection. arxiv preprint 1911.02282. - A generic constructor method. + Constructor of the class HDBSCAN. + + + .. py:attribute:: alpha + + + .. py:attribute:: gen_min_span_tree + + + .. py:attribute:: leaf_size + + + .. py:attribute:: metric + + + .. py:attribute:: min_cluster_size + + + .. py:attribute:: min_samples + + + .. py:attribute:: p + + + .. py:attribute:: algorithm + + + .. py:attribute:: approx_min_span_tree + + + .. py:attribute:: core_dist_n_jobs + + + .. py:attribute:: cluster_selection_method + + + .. py:attribute:: allow_single_cluster + + + .. py:attribute:: prediction_data + + + .. py:attribute:: match_reference_implementation + + + .. py:attribute:: connectivity + + + .. py:attribute:: output_type + + + .. py:attribute:: verbose + + + .. py:attribute:: __hdbscan_cpu .. py:method:: _fit_cpu(X, y=None) @@ -753,7 +872,7 @@ Package Contents -.. py:class:: KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='full', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs) +.. py:class:: KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='lloyd', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs) Bases: :py:obj:`dasf.ml.cluster.classifier.ClusterClassifier` @@ -839,15 +958,12 @@ Package Contents init_max_iter : int, default=None Number of iterations for init step. - algorithm : {"auto", "full", "elkan"}, default="full" - K-means algorithm to use. The classical EM-style algorithm is "full". - The "elkan" variation is more efficient on data with well-defined - clusters, by using the triangle inequality. However it's more memory - intensive due to the allocation of an extra array of shape - (n_samples, n_clusters). - - For now "auto" (kept for backward compatibiliy) chooses "elkan" but it - might change in the future for a better heuristic. + algorithm : {“lloyd”, “elkan”}, default=”lloyd” + K-means algorithm to use. The classical EM-style algorithm is "lloyd". + The "elkan" variation can be more efficient on some datasets with + well-defined clusters, by using the triangle inequality. However + it’s more memory intensive due to the allocation of an extra array of + shape (n_samples, n_clusters). .. versionchanged:: 0.18 Added Elkan algorithm @@ -919,7 +1035,58 @@ Package Contents - https://docs.rapids.ai/api/cuml/stable/api.html#cuml.dask.cluster.KMeans - A generic constructor method. + Constructor of the class KMeans. + + + .. py:attribute:: n_clusters + + + .. py:attribute:: random_state + + + .. py:attribute:: max_iter + + + .. py:attribute:: init + + + .. py:attribute:: n_init + + + .. py:attribute:: tol + + + .. py:attribute:: verbose + + + .. py:attribute:: copy_x + + + .. py:attribute:: algorithm + + + .. py:attribute:: oversampling_factor + + + .. py:attribute:: n_jobs + + + .. py:attribute:: init_max_iter + + + .. py:attribute:: max_samples_per_batch + + + .. py:attribute:: precompute_distances + + + .. py:attribute:: output_type + + + .. py:attribute:: __kmeans_cpu + + + .. py:attribute:: __kmeans_mcpu .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None) @@ -1429,7 +1596,61 @@ Package Contents SOM(x=3, y=2, input_len=2, num_epochs=100) - A generic constructor method. + Constructor of the class SOM. + + + .. py:attribute:: x + + + .. py:attribute:: y + + + .. py:attribute:: input_len + + + .. py:attribute:: num_epochs + + + .. py:attribute:: sigma + + + .. py:attribute:: sigmaN + + + .. py:attribute:: learning_rate + + + .. py:attribute:: learning_rateN + + + .. py:attribute:: decay_function + + + .. py:attribute:: neighborhood_function + + + .. py:attribute:: std_coeff + + + .. py:attribute:: topology + + + .. py:attribute:: activation_distance + + + .. py:attribute:: random_seed + + + .. py:attribute:: n_parallel + + + .. py:attribute:: compact_support + + + .. py:attribute:: __som_cpu + + + .. py:attribute:: __som_mcpu .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None) @@ -1927,7 +2148,64 @@ Package Contents https://www1.icsi.berkeley.edu/~stellayu/publication/doc/2003kwayICCV.pdf - A generic constructor method. + Constructor of the class SpectralClustering. + + + .. py:attribute:: n_clusters + + + .. py:attribute:: eigen_solver + + + .. py:attribute:: random_state + + + .. py:attribute:: n_init + + + .. py:attribute:: gamma + + + .. py:attribute:: affinity + + + .. py:attribute:: n_neighbors + + + .. py:attribute:: eigen_tol + + + .. py:attribute:: assign_labels + + + .. py:attribute:: degree + + + .. py:attribute:: coef0 + + + .. py:attribute:: kernel_params + + + .. py:attribute:: n_jobs + + + .. py:attribute:: n_components + + + .. py:attribute:: persist_embedding + + + .. py:attribute:: kmeans_params + + + .. py:attribute:: verbose + + + .. py:attribute:: __sc_cpu + + + .. py:attribute:: __sc_mcpu .. py:method:: _fit_cpu(X, y=None, sample_weight=None) diff --git a/docs/_sources/autoapi/dasf/ml/cluster/kmeans/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/kmeans/index.rst.txt index 3de34d2..6beea3b 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/kmeans/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/kmeans/index.rst.txt @@ -20,7 +20,7 @@ Classes Module Contents --------------- -.. py:class:: KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='full', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs) +.. py:class:: KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='lloyd', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs) Bases: :py:obj:`dasf.ml.cluster.classifier.ClusterClassifier` @@ -106,15 +106,12 @@ Module Contents init_max_iter : int, default=None Number of iterations for init step. - algorithm : {"auto", "full", "elkan"}, default="full" - K-means algorithm to use. The classical EM-style algorithm is "full". - The "elkan" variation is more efficient on data with well-defined - clusters, by using the triangle inequality. However it's more memory - intensive due to the allocation of an extra array of shape - (n_samples, n_clusters). - - For now "auto" (kept for backward compatibiliy) chooses "elkan" but it - might change in the future for a better heuristic. + algorithm : {“lloyd”, “elkan”}, default=”lloyd” + K-means algorithm to use. The classical EM-style algorithm is "lloyd". + The "elkan" variation can be more efficient on some datasets with + well-defined clusters, by using the triangle inequality. However + it’s more memory intensive due to the allocation of an extra array of + shape (n_samples, n_clusters). .. versionchanged:: 0.18 Added Elkan algorithm @@ -186,7 +183,58 @@ Module Contents - https://docs.rapids.ai/api/cuml/stable/api.html#cuml.dask.cluster.KMeans - A generic constructor method. + Constructor of the class KMeans. + + + .. py:attribute:: n_clusters + + + .. py:attribute:: random_state + + + .. py:attribute:: max_iter + + + .. py:attribute:: init + + + .. py:attribute:: n_init + + + .. py:attribute:: tol + + + .. py:attribute:: verbose + + + .. py:attribute:: copy_x + + + .. py:attribute:: algorithm + + + .. py:attribute:: oversampling_factor + + + .. py:attribute:: n_jobs + + + .. py:attribute:: init_max_iter + + + .. py:attribute:: max_samples_per_batch + + + .. py:attribute:: precompute_distances + + + .. py:attribute:: output_type + + + .. py:attribute:: __kmeans_cpu + + + .. py:attribute:: __kmeans_mcpu .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None) diff --git a/docs/_sources/autoapi/dasf/ml/cluster/som/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/som/index.rst.txt index 50f191e..2da659a 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/som/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/som/index.rst.txt @@ -105,7 +105,61 @@ Module Contents SOM(x=3, y=2, input_len=2, num_epochs=100) - A generic constructor method. + Constructor of the class SOM. + + + .. py:attribute:: x + + + .. py:attribute:: y + + + .. py:attribute:: input_len + + + .. py:attribute:: num_epochs + + + .. py:attribute:: sigma + + + .. py:attribute:: sigmaN + + + .. py:attribute:: learning_rate + + + .. py:attribute:: learning_rateN + + + .. py:attribute:: decay_function + + + .. py:attribute:: neighborhood_function + + + .. py:attribute:: std_coeff + + + .. py:attribute:: topology + + + .. py:attribute:: activation_distance + + + .. py:attribute:: random_seed + + + .. py:attribute:: n_parallel + + + .. py:attribute:: compact_support + + + .. py:attribute:: __som_cpu + + + .. py:attribute:: __som_mcpu .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None) diff --git a/docs/_sources/autoapi/dasf/ml/cluster/spectral/index.rst.txt b/docs/_sources/autoapi/dasf/ml/cluster/spectral/index.rst.txt index dda6ba2..7ae6a71 100644 --- a/docs/_sources/autoapi/dasf/ml/cluster/spectral/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/cluster/spectral/index.rst.txt @@ -196,7 +196,64 @@ Module Contents https://www1.icsi.berkeley.edu/~stellayu/publication/doc/2003kwayICCV.pdf - A generic constructor method. + Constructor of the class SpectralClustering. + + + .. py:attribute:: n_clusters + + + .. py:attribute:: eigen_solver + + + .. py:attribute:: random_state + + + .. py:attribute:: n_init + + + .. py:attribute:: gamma + + + .. py:attribute:: affinity + + + .. py:attribute:: n_neighbors + + + .. py:attribute:: eigen_tol + + + .. py:attribute:: assign_labels + + + .. py:attribute:: degree + + + .. py:attribute:: coef0 + + + .. py:attribute:: kernel_params + + + .. py:attribute:: n_jobs + + + .. py:attribute:: n_components + + + .. py:attribute:: persist_embedding + + + .. py:attribute:: kmeans_params + + + .. py:attribute:: verbose + + + .. py:attribute:: __sc_cpu + + + .. py:attribute:: __sc_mcpu .. py:method:: _fit_cpu(X, y=None, sample_weight=None) diff --git a/docs/_sources/autoapi/dasf/ml/decomposition/index.rst.txt b/docs/_sources/autoapi/dasf/ml/decomposition/index.rst.txt index a77ade2..26d63ac 100644 --- a/docs/_sources/autoapi/dasf/ml/decomposition/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/decomposition/index.rst.txt @@ -295,6 +295,14 @@ Package Contents >>> print(pca.singular_values_) [6.30061...] + Constructor of the class PCA. + + + .. py:attribute:: __pca_cpu + + + .. py:attribute:: __pca_mcpu + .. py:method:: _lazy_fit_cpu(X, y=None, sample_weights=None) diff --git a/docs/_sources/autoapi/dasf/ml/decomposition/pca/index.rst.txt b/docs/_sources/autoapi/dasf/ml/decomposition/pca/index.rst.txt index cf32f73..b2af7a9 100644 --- a/docs/_sources/autoapi/dasf/ml/decomposition/pca/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/decomposition/pca/index.rst.txt @@ -286,6 +286,14 @@ Module Contents >>> print(pca.singular_values_) [6.30061...] + Constructor of the class PCA. + + + .. py:attribute:: __pca_cpu + + + .. py:attribute:: __pca_mcpu + .. py:method:: _lazy_fit_cpu(X, y=None, sample_weights=None) diff --git a/docs/_sources/autoapi/dasf/ml/dl/clusters/dask/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/clusters/dask/index.rst.txt index 7126da8..0dfb491 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/clusters/dask/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/clusters/dask/index.rst.txt @@ -35,6 +35,11 @@ Module Contents Constructor of the object DaskClusterEnvironment using dict metadata. + .. py:attribute:: _master_port + :value: 23456 + + + .. py:method:: detect() Detect if important data are present into metadata dictionary. diff --git a/docs/_sources/autoapi/dasf/ml/dl/clusters/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/clusters/index.rst.txt index 87ffb34..4976e03 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/clusters/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/clusters/index.rst.txt @@ -39,6 +39,11 @@ Package Contents Constructor of the object DaskClusterEnvironment using dict metadata. + .. py:attribute:: _master_port + :value: 23456 + + + .. py:method:: detect() Detect if important data are present into metadata dictionary. diff --git a/docs/_sources/autoapi/dasf/ml/dl/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/index.rst.txt index acc78b3..bb4a437 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/index.rst.txt @@ -3,6 +3,11 @@ dasf.ml.dl .. py:module:: dasf.ml.dl +.. autoapi-nested-parse:: + + Init module for Deep Learning algorithms. + + Subpackages ----------- @@ -67,6 +72,39 @@ Package Contents The dimension to unsqueeze the input data, by default None. + .. py:attribute:: model + + + .. py:attribute:: accelerator + + + .. py:attribute:: batch_size + + + .. py:attribute:: max_epochs + + + .. py:attribute:: limit_train_batches + + + .. py:attribute:: limit_val_batches + + + .. py:attribute:: devices + + + .. py:attribute:: num_nodes + + + .. py:attribute:: shuffle + + + .. py:attribute:: strategy + + + .. py:attribute:: unsqueeze_dim + + .. py:method:: fit(train_data, val_data = None) Perform the training of the model using torch Lightning. @@ -103,6 +141,43 @@ Package Contents Class representing a Fit operation of the pipeline. + .. py:attribute:: _model + + + .. py:attribute:: _accel + :value: None + + + + .. py:attribute:: _strategy + :value: None + + + + .. py:attribute:: _max_iter + + + .. py:attribute:: _devices + :value: 0 + + + + .. py:attribute:: _ngpus + :value: 0 + + + + .. py:attribute:: _batch_size + + + .. py:attribute:: __trainer + :value: False + + + + .. py:attribute:: __handler + + .. py:method:: _lazy_fit_generic(X, y, accel, ngpus) diff --git a/docs/_sources/autoapi/dasf/ml/dl/lightning_fit/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/lightning_fit/index.rst.txt index 8963ad0..23dd126 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/lightning_fit/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/lightning_fit/index.rst.txt @@ -34,6 +34,12 @@ Module Contents The dimension to be unsqueezed in the output, by default None + .. py:attribute:: dataset + + + .. py:attribute:: unsqueeze_dim + + .. py:method:: __len__() @@ -84,6 +90,39 @@ Module Contents The dimension to unsqueeze the input data, by default None. + .. py:attribute:: model + + + .. py:attribute:: accelerator + + + .. py:attribute:: batch_size + + + .. py:attribute:: max_epochs + + + .. py:attribute:: limit_train_batches + + + .. py:attribute:: limit_val_batches + + + .. py:attribute:: devices + + + .. py:attribute:: num_nodes + + + .. py:attribute:: shuffle + + + .. py:attribute:: strategy + + + .. py:attribute:: unsqueeze_dim + + .. py:method:: fit(train_data, val_data = None) Perform the training of the model using torch Lightning. diff --git a/docs/_sources/autoapi/dasf/ml/dl/models/devconvnet/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/models/devconvnet/index.rst.txt index 05211d2..8523fe5 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/models/devconvnet/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/models/devconvnet/index.rst.txt @@ -58,29 +58,22 @@ Module Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. - .. py:method:: set_idx(idx) - + .. py:attribute:: idx + :value: 0 - .. py:method:: update(preds, target) - Override this method to update the state variables of your metric class. + .. py:method:: set_idx(idx) - .. py:method:: __str__() + .. py:method:: update(preds, target) - Return str(self). + .. py:method:: __str__() .. py:method:: compute() - Override this method to compute the final metric value. - - This method will automatically synchronize state variables when running in distributed backend. - - - .. py:class:: NNModule(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None) @@ -121,6 +114,18 @@ Module Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: learned_billinear + + + .. py:attribute:: n_classes + + + .. py:attribute:: clip + + + .. py:attribute:: class_names + + .. py:method:: cross_entropy_loss(input, target, weight=None, ignore_index=255) Use 255 to fill empty values when padding or doing any augmentation operations @@ -484,6 +489,66 @@ Module Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. @@ -545,6 +610,66 @@ Module Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. @@ -606,6 +731,66 @@ Module Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. @@ -667,6 +852,66 @@ Module Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. diff --git a/docs/_sources/autoapi/dasf/ml/dl/models/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/models/index.rst.txt index c8cfc12..1945003 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/models/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/models/index.rst.txt @@ -66,6 +66,66 @@ Package Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. @@ -127,6 +187,66 @@ Package Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. @@ -188,6 +308,66 @@ Package Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. @@ -249,6 +429,66 @@ Package Contents Initializes internal Module state, shared by both nn.Module and ScriptModule. + .. py:attribute:: unpool + + + .. py:attribute:: conv_block1 + + + .. py:attribute:: conv_block2 + + + .. py:attribute:: conv_block3 + + + .. py:attribute:: conv_block4 + + + .. py:attribute:: conv_block5 + + + .. py:attribute:: conv_block6 + + + .. py:attribute:: conv_block7 + + + .. py:attribute:: deconv_block8 + + + .. py:attribute:: unpool_block9 + + + .. py:attribute:: deconv_block10 + + + .. py:attribute:: unpool_block11 + + + .. py:attribute:: deconv_block12 + + + .. py:attribute:: unpool_block13 + + + .. py:attribute:: deconv_block14 + + + .. py:attribute:: unpool_block15 + + + .. py:attribute:: deconv_block16 + + + .. py:attribute:: unpool_block17 + + + .. py:attribute:: deconv_block18 + + + .. py:attribute:: seg_score19 + + .. py:method:: forward(x) Same as :meth:`torch.nn.Module.forward()`. diff --git a/docs/_sources/autoapi/dasf/ml/dl/pytorch_lightning/index.rst.txt b/docs/_sources/autoapi/dasf/ml/dl/pytorch_lightning/index.rst.txt index ec10fd8..5bfe0f1 100644 --- a/docs/_sources/autoapi/dasf/ml/dl/pytorch_lightning/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/dl/pytorch_lightning/index.rst.txt @@ -66,6 +66,18 @@ Module Contents Default value is False. + .. py:attribute:: _train + + + .. py:attribute:: _val + + + .. py:attribute:: _test + + + .. py:attribute:: _batch_size + + .. py:method:: prepare_data() Use this to download and prepare data. Downloading and saving data with multiple processes (distributed @@ -340,6 +352,43 @@ Module Contents Class representing a Fit operation of the pipeline. + .. py:attribute:: _model + + + .. py:attribute:: _accel + :value: None + + + + .. py:attribute:: _strategy + :value: None + + + + .. py:attribute:: _max_iter + + + .. py:attribute:: _devices + :value: 0 + + + + .. py:attribute:: _ngpus + :value: 0 + + + + .. py:attribute:: _batch_size + + + .. py:attribute:: __trainer + :value: False + + + + .. py:attribute:: __handler + + .. py:method:: _lazy_fit_generic(X, y, accel, ngpus) diff --git a/docs/_sources/autoapi/dasf/ml/inference/loader/base/index.rst.txt b/docs/_sources/autoapi/dasf/ml/inference/loader/base/index.rst.txt index 13ae3d8..24488c9 100644 --- a/docs/_sources/autoapi/dasf/ml/inference/loader/base/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/inference/loader/base/index.rst.txt @@ -20,6 +20,9 @@ Module Contents BaseLoader for DL models. When running in a Dask Cluster instantiates a model per worker that will be reused on every subsequent prediction task. + .. py:attribute:: model_instances + + .. py:method:: inference(model, data) :abstractmethod: @@ -72,14 +75,6 @@ Module Contents - .. py:method:: inference(model, data) - :abstractmethod: - - - Inference method, receives model and input data - - - .. py:method:: postprocessing(data) Postprocessing stage which is called after inference diff --git a/docs/_sources/autoapi/dasf/ml/inference/loader/torch/index.rst.txt b/docs/_sources/autoapi/dasf/ml/inference/loader/torch/index.rst.txt index 2398435..466c1c5 100644 --- a/docs/_sources/autoapi/dasf/ml/inference/loader/torch/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/inference/loader/torch/index.rst.txt @@ -28,6 +28,18 @@ Module Contents device: device to place model ("cpu" or "gpu") + .. py:attribute:: model_class_or_file + + + .. py:attribute:: dtype + + + .. py:attribute:: checkpoint + + + .. py:attribute:: device + + .. py:method:: load_model(**kwargs) Load Model method is specific for each framework/model. @@ -36,7 +48,4 @@ Module Contents .. py:method:: inference(model, data) - Inference method, receives model and input data - - diff --git a/docs/_sources/autoapi/dasf/ml/mixture/gmm/index.rst.txt b/docs/_sources/autoapi/dasf/ml/mixture/gmm/index.rst.txt index a40573e..dd58055 100644 --- a/docs/_sources/autoapi/dasf/ml/mixture/gmm/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/mixture/gmm/index.rst.txt @@ -206,6 +206,9 @@ Module Contents array([1, 0]) + .. py:attribute:: __gmm_cpu + + .. py:method:: _fit_cpu(X, y=None) Estimate Gaussian Mixture model parameters with the EM algorithm using diff --git a/docs/_sources/autoapi/dasf/ml/model_selection/split/index.rst.txt b/docs/_sources/autoapi/dasf/ml/model_selection/split/index.rst.txt index 1245385..ea3ab69 100644 --- a/docs/_sources/autoapi/dasf/ml/model_selection/split/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/model_selection/split/index.rst.txt @@ -33,6 +33,29 @@ Module Contents Define if the operator will use GPU(s) or not. + Constructor of the class TargeteredTransform. + + + .. py:attribute:: output + + + .. py:attribute:: test_size + + + .. py:attribute:: train_size + + + .. py:attribute:: random_state + + + .. py:attribute:: shuffle + + + .. py:attribute:: blockwise + + + .. py:attribute:: convert_mixed_types + .. py:method:: _lazy_transform_cpu(X) diff --git a/docs/_sources/autoapi/dasf/ml/neighbors/index.rst.txt b/docs/_sources/autoapi/dasf/ml/neighbors/index.rst.txt index ca6af31..77e1f11 100644 --- a/docs/_sources/autoapi/dasf/ml/neighbors/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/neighbors/index.rst.txt @@ -140,6 +140,9 @@ Package Contents Constructor of the class NearestNeighbors. + .. py:attribute:: __nn_cpu + + .. py:method:: _fit_cpu(X, y=None, **kwargs) Fit the nearest neighbors estimator from the training dataset using diff --git a/docs/_sources/autoapi/dasf/ml/neighbors/neighbors/index.rst.txt b/docs/_sources/autoapi/dasf/ml/neighbors/neighbors/index.rst.txt index b1f1319..c3de1ee 100644 --- a/docs/_sources/autoapi/dasf/ml/neighbors/neighbors/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/neighbors/neighbors/index.rst.txt @@ -131,6 +131,9 @@ Module Contents Constructor of the class NearestNeighbors. + .. py:attribute:: __nn_cpu + + .. py:method:: _fit_cpu(X, y=None, **kwargs) Fit the nearest neighbors estimator from the training dataset using diff --git a/docs/_sources/autoapi/dasf/ml/preprocessing/index.rst.txt b/docs/_sources/autoapi/dasf/ml/preprocessing/index.rst.txt index c7cb57c..7eda4dc 100644 --- a/docs/_sources/autoapi/dasf/ml/preprocessing/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/preprocessing/index.rst.txt @@ -135,6 +135,12 @@ Package Contents Constructor of the class StandardScaler. + .. py:attribute:: __std_scaler_cpu + + + .. py:attribute:: __std_scaler_dask + + .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None) Compute the mean and std to be used for later scaling using Dask with diff --git a/docs/_sources/autoapi/dasf/ml/preprocessing/standardscaler/index.rst.txt b/docs/_sources/autoapi/dasf/ml/preprocessing/standardscaler/index.rst.txt index 26f9280..b1dfe68 100644 --- a/docs/_sources/autoapi/dasf/ml/preprocessing/standardscaler/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/preprocessing/standardscaler/index.rst.txt @@ -126,6 +126,12 @@ Module Contents Constructor of the class StandardScaler. + .. py:attribute:: __std_scaler_cpu + + + .. py:attribute:: __std_scaler_dask + + .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None) Compute the mean and std to be used for later scaling using Dask with diff --git a/docs/_sources/autoapi/dasf/ml/svm/index.rst.txt b/docs/_sources/autoapi/dasf/ml/svm/index.rst.txt index 925b49b..32c22f4 100644 --- a/docs/_sources/autoapi/dasf/ml/svm/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/svm/index.rst.txt @@ -211,6 +211,9 @@ Package Contents Array dimensions of training vector ``X``. + .. py:attribute:: __svc_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Respective immediate fit mocked function for local CPU(s). @@ -372,6 +375,9 @@ Package Contents Constructor of the class SVR. + .. py:attribute:: __svr_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Respective immediate fit mocked function for local CPU(s). @@ -538,6 +544,9 @@ Package Contents Constructor of the class LinearSVC. + .. py:attribute:: __linear_svc_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Fit the model according to the given training data using CPU only. @@ -707,6 +716,9 @@ Package Contents Constructor of the class LinearSVR. + .. py:attribute:: __linear_svr_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Respective immediate fit mocked function for local CPU(s). diff --git a/docs/_sources/autoapi/dasf/ml/svm/svm/index.rst.txt b/docs/_sources/autoapi/dasf/ml/svm/svm/index.rst.txt index a73d9d2..572eb3c 100644 --- a/docs/_sources/autoapi/dasf/ml/svm/svm/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/svm/svm/index.rst.txt @@ -202,6 +202,9 @@ Module Contents Array dimensions of training vector ``X``. + .. py:attribute:: __svc_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Respective immediate fit mocked function for local CPU(s). @@ -363,6 +366,9 @@ Module Contents Constructor of the class SVR. + .. py:attribute:: __svr_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Respective immediate fit mocked function for local CPU(s). @@ -529,6 +535,9 @@ Module Contents Constructor of the class LinearSVC. + .. py:attribute:: __linear_svc_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Fit the model according to the given training data using CPU only. @@ -698,6 +707,9 @@ Module Contents Constructor of the class LinearSVR. + .. py:attribute:: __linear_svr_cpu + + .. py:method:: _fit_cpu(X, y, sample_weight=None) Respective immediate fit mocked function for local CPU(s). diff --git a/docs/_sources/autoapi/dasf/ml/xgboost/index.rst.txt b/docs/_sources/autoapi/dasf/ml/xgboost/index.rst.txt index 0e7a0a2..6e70183 100644 --- a/docs/_sources/autoapi/dasf/ml/xgboost/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/xgboost/index.rst.txt @@ -37,6 +37,12 @@ Package Contents Class representing a Fit operation of the pipeline. + .. py:attribute:: __xgb_cpu + + + .. py:attribute:: __xgb_mcpu + + .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None, *args, **kwargs) Respective lazy fit mocked function for CPUs. diff --git a/docs/_sources/autoapi/dasf/ml/xgboost/xgboost/index.rst.txt b/docs/_sources/autoapi/dasf/ml/xgboost/xgboost/index.rst.txt index 16ec7d7..e0ef220 100644 --- a/docs/_sources/autoapi/dasf/ml/xgboost/xgboost/index.rst.txt +++ b/docs/_sources/autoapi/dasf/ml/xgboost/xgboost/index.rst.txt @@ -23,6 +23,12 @@ Module Contents Class representing a Fit operation of the pipeline. + .. py:attribute:: __xgb_cpu + + + .. py:attribute:: __xgb_mcpu + + .. py:method:: _lazy_fit_cpu(X, y=None, sample_weight=None, *args, **kwargs) Respective lazy fit mocked function for CPUs. diff --git a/docs/_sources/autoapi/dasf/pipeline/executors/dask/index.rst.txt b/docs/_sources/autoapi/dasf/pipeline/executors/dask/index.rst.txt index 6b7d8f1..40b706a 100644 --- a/docs/_sources/autoapi/dasf/pipeline/executors/dask/index.rst.txt +++ b/docs/_sources/autoapi/dasf/pipeline/executors/dask/index.rst.txt @@ -3,6 +3,11 @@ dasf.pipeline.executors.dask .. py:module:: dasf.pipeline.executors.dask +.. autoapi-nested-parse:: + + Dask executor module. + + Classes ------- @@ -47,6 +52,15 @@ Module Contents client_kwargs -- extra Client parameters. + .. py:attribute:: address + + + .. py:attribute:: port + + + .. py:attribute:: local + + .. py:property:: ngpus :type: int @@ -102,6 +116,9 @@ Module Contents client_kwargs -- extra Client parameters. + .. py:attribute:: _tasks_map + + .. py:method:: pre_run(pipeline) @@ -131,3 +148,6 @@ Module Contents Bases: :py:obj:`dasf.pipeline.executors.base.Executor` + .. py:attribute:: client + + diff --git a/docs/_sources/autoapi/dasf/pipeline/executors/index.rst.txt b/docs/_sources/autoapi/dasf/pipeline/executors/index.rst.txt index 373128f..e124529 100644 --- a/docs/_sources/autoapi/dasf/pipeline/executors/index.rst.txt +++ b/docs/_sources/autoapi/dasf/pipeline/executors/index.rst.txt @@ -74,6 +74,9 @@ Package Contents Bases: :py:obj:`dasf.pipeline.executors.base.Executor` + .. py:attribute:: client + + .. py:class:: DaskPipelineExecutor(address=None, port=8786, local=False, use_gpu=False, profiler=None, protocol=None, gpu_allocator='cupy', cluster_kwargs=None, client_kwargs=None) Bases: :py:obj:`dasf.pipeline.executors.base.Executor` @@ -94,6 +97,15 @@ Package Contents client_kwargs -- extra Client parameters. + .. py:attribute:: address + + + .. py:attribute:: port + + + .. py:attribute:: local + + .. py:property:: ngpus :type: int @@ -149,6 +161,9 @@ Package Contents client_kwargs -- extra Client parameters. + .. py:attribute:: _tasks_map + + .. py:method:: pre_run(pipeline) @@ -175,6 +190,9 @@ Package Contents .. py:class:: LocalExecutor(use_gpu=None, backend='numpy', gpu_allocator='cupy') + .. py:attribute:: backend + + .. py:property:: ngpus :type: int diff --git a/docs/_sources/autoapi/dasf/pipeline/executors/ray/index.rst.txt b/docs/_sources/autoapi/dasf/pipeline/executors/ray/index.rst.txt index 493175e..0d3c499 100644 --- a/docs/_sources/autoapi/dasf/pipeline/executors/ray/index.rst.txt +++ b/docs/_sources/autoapi/dasf/pipeline/executors/ray/index.rst.txt @@ -54,6 +54,12 @@ Module Contents Constructor of the object RayPipelineExecutor. + .. py:attribute:: address + + + .. py:attribute:: port + + .. py:property:: ngpus Return the number of GPUs in total. diff --git a/docs/_sources/autoapi/dasf/pipeline/executors/wrapper/index.rst.txt b/docs/_sources/autoapi/dasf/pipeline/executors/wrapper/index.rst.txt index 44ec935..86cf02d 100644 --- a/docs/_sources/autoapi/dasf/pipeline/executors/wrapper/index.rst.txt +++ b/docs/_sources/autoapi/dasf/pipeline/executors/wrapper/index.rst.txt @@ -17,6 +17,9 @@ Module Contents .. py:class:: LocalExecutor(use_gpu=None, backend='numpy', gpu_allocator='cupy') + .. py:attribute:: backend + + .. py:property:: ngpus :type: int diff --git a/docs/_sources/autoapi/dasf/pipeline/index.rst.txt b/docs/_sources/autoapi/dasf/pipeline/index.rst.txt index 06b7c4b..9ffe313 100644 --- a/docs/_sources/autoapi/dasf/pipeline/index.rst.txt +++ b/docs/_sources/autoapi/dasf/pipeline/index.rst.txt @@ -3,6 +3,11 @@ dasf.pipeline .. py:module:: dasf.pipeline +.. autoapi-nested-parse:: + + Init module for DASF Pipeline and its features. + + Subpackages ----------- @@ -37,6 +42,30 @@ Package Contents .. py:class:: Pipeline(name, executor=None, verbose=False, callbacks = None) + .. py:attribute:: _name + + + .. py:attribute:: _executor + + + .. py:attribute:: _verbose + + + .. py:attribute:: _dag + + + .. py:attribute:: _dag_table + + + .. py:attribute:: _dag_g + + + .. py:attribute:: _logger + + + .. py:attribute:: _callbacks + + .. py:method:: register_plugin(plugin) diff --git a/docs/_sources/autoapi/dasf/pipeline/pipeline/index.rst.txt b/docs/_sources/autoapi/dasf/pipeline/pipeline/index.rst.txt index c85fb82..a7aa34a 100644 --- a/docs/_sources/autoapi/dasf/pipeline/pipeline/index.rst.txt +++ b/docs/_sources/autoapi/dasf/pipeline/pipeline/index.rst.txt @@ -35,6 +35,30 @@ Module Contents .. py:class:: Pipeline(name, executor=None, verbose=False, callbacks = None) + .. py:attribute:: _name + + + .. py:attribute:: _executor + + + .. py:attribute:: _verbose + + + .. py:attribute:: _dag + + + .. py:attribute:: _dag_table + + + .. py:attribute:: _dag_g + + + .. py:attribute:: _logger + + + .. py:attribute:: _callbacks + + .. py:method:: register_plugin(plugin) diff --git a/docs/_sources/autoapi/dasf/profile/analysis/index.rst.txt b/docs/_sources/autoapi/dasf/profile/analysis/index.rst.txt index 7b32b3f..b713d6d 100644 --- a/docs/_sources/autoapi/dasf/profile/analysis/index.rst.txt +++ b/docs/_sources/autoapi/dasf/profile/analysis/index.rst.txt @@ -34,6 +34,9 @@ Module Contents .. py:class:: TraceAnalyser(database, process_trace_before = True) + .. py:attribute:: _database + + .. py:method:: create_annotated_task_graph() diff --git a/docs/_sources/autoapi/dasf/profile/index.rst.txt b/docs/_sources/autoapi/dasf/profile/index.rst.txt index d588659..1a6a360 100644 --- a/docs/_sources/autoapi/dasf/profile/index.rst.txt +++ b/docs/_sources/autoapi/dasf/profile/index.rst.txt @@ -38,6 +38,9 @@ Package Contents .. py:class:: TraceAnalyser(database, process_trace_before = True) + .. py:attribute:: _database + + .. py:method:: create_annotated_task_graph() @@ -52,20 +55,17 @@ Package Contents .. py:class:: MultiEventDatabase(databases) - .. py:method:: __iter__() + .. py:attribute:: _databases - .. py:method:: __str__() + .. py:method:: __iter__() - Return str(self). + .. py:method:: __str__() .. py:method:: __repr__() - Return repr(self). - - .. py:function:: register_default_profiler(pipeline, name = None, enable_nvtx = False, add_time_suffix = True) diff --git a/docs/_sources/autoapi/dasf/profile/plugins/index.rst.txt b/docs/_sources/autoapi/dasf/profile/plugins/index.rst.txt index 2b08d0b..5b9aaaf 100644 --- a/docs/_sources/autoapi/dasf/profile/plugins/index.rst.txt +++ b/docs/_sources/autoapi/dasf/profile/plugins/index.rst.txt @@ -58,6 +58,9 @@ Module Contents >>> client.register_worker_plugin(plugin) # doctest: +SKIP + .. py:attribute:: name + + .. py:method:: setup(worker) Run when the plugin is attached to a worker. This happens when the plugin is registered @@ -94,6 +97,24 @@ Module Contents .. py:class:: ResourceMonitor(time=100, autostart = True, name = 'ResourceMonitor', **monitor_kwargs) + .. py:attribute:: time + + + .. py:attribute:: name + + + .. py:attribute:: hostname + + + .. py:attribute:: database + + + .. py:attribute:: monitor + + + .. py:attribute:: callback + + .. py:method:: __del__() @@ -147,6 +168,17 @@ Module Contents >>> client.register_worker_plugin(plugin) # doctest: +SKIP + .. py:attribute:: name + + + .. py:attribute:: gpu_num + :value: None + + + + .. py:attribute:: marks + + .. py:method:: setup(worker) Run when the plugin is attached to a worker. This happens when the plugin is registered diff --git a/docs/_sources/autoapi/dasf/profile/profiler/index.rst.txt b/docs/_sources/autoapi/dasf/profile/profiler/index.rst.txt index 352455f..0e164da 100644 --- a/docs/_sources/autoapi/dasf/profile/profiler/index.rst.txt +++ b/docs/_sources/autoapi/dasf/profile/profiler/index.rst.txt @@ -308,6 +308,27 @@ Module Contents inheritance. + .. py:attribute:: database_file + + + .. py:attribute:: commit_threshold + + + .. py:attribute:: commit_on_close + + + .. py:attribute:: queue + + + .. py:attribute:: lock_timeout + + + .. py:attribute:: byte_size + + + .. py:attribute:: flush + + .. py:method:: record(event) @@ -322,15 +343,9 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:class:: EventProfiler(database_file = None, database_creation_kwargs = None, database = None) @@ -345,6 +360,11 @@ Module Contents .. py:attribute:: default_database_kwargs + .. py:attribute:: output_file + :value: None + + + .. py:method:: _record(event) @@ -365,15 +385,9 @@ Module Contents .. py:method:: __str__() - Return str(self). - - .. py:method:: __repr__() - Return repr(self). - - .. py:method:: commit() diff --git a/docs/_sources/autoapi/dasf/profile/utils/index.rst.txt b/docs/_sources/autoapi/dasf/profile/utils/index.rst.txt index fef363f..22711f8 100644 --- a/docs/_sources/autoapi/dasf/profile/utils/index.rst.txt +++ b/docs/_sources/autoapi/dasf/profile/utils/index.rst.txt @@ -25,20 +25,17 @@ Module Contents .. py:class:: MultiEventDatabase(databases) - .. py:method:: __iter__() + .. py:attribute:: _databases - .. py:method:: __str__() + .. py:method:: __iter__() - Return str(self). + .. py:method:: __str__() .. py:method:: __repr__() - Return repr(self). - - .. py:function:: register_default_profiler(pipeline, name = None, enable_nvtx = False, add_time_suffix = True) diff --git a/docs/_sources/autoapi/dasf/transforms/base/index.rst.txt b/docs/_sources/autoapi/dasf/transforms/base/index.rst.txt index 0abfb00..ea8cb8c 100644 --- a/docs/_sources/autoapi/dasf/transforms/base/index.rst.txt +++ b/docs/_sources/autoapi/dasf/transforms/base/index.rst.txt @@ -421,6 +421,14 @@ Module Contents Define if the operator will use GPU(s) or not. + Constructor of the class TargeteredTransform. + + + .. py:attribute:: _run_local + + + .. py:attribute:: _run_gpu + .. py:class:: MappedTransform(function, depth=None, boundary=None, trim=True, output_chunk=None, drop_axis=None, new_axis=None) @@ -460,6 +468,27 @@ Module Contents + .. py:attribute:: function + + + .. py:attribute:: depth + + + .. py:attribute:: boundary + + + .. py:attribute:: trim + + + .. py:attribute:: output_chunk + + + .. py:attribute:: drop_axis + + + .. py:attribute:: new_axis + + .. py:method:: __lazy_transform_generic(X, xp, **kwargs) @@ -517,6 +546,18 @@ Module Contents + .. py:attribute:: output_size + + + .. py:attribute:: func_aggregate + + + .. py:attribute:: func_chunk + + + .. py:attribute:: func_combine + + .. py:method:: _operation_aggregate_cpu(block, axis=None, keepdims=False) diff --git a/docs/_sources/autoapi/dasf/transforms/index.rst.txt b/docs/_sources/autoapi/dasf/transforms/index.rst.txt index 7cfe129..b4d56e9 100644 --- a/docs/_sources/autoapi/dasf/transforms/index.rst.txt +++ b/docs/_sources/autoapi/dasf/transforms/index.rst.txt @@ -3,6 +3,11 @@ dasf.transforms .. py:module:: dasf.transforms +.. autoapi-nested-parse:: + + Init module for all transformation structures. + + Submodules ---------- @@ -83,6 +88,27 @@ Package Contents + .. py:attribute:: function + + + .. py:attribute:: depth + + + .. py:attribute:: boundary + + + .. py:attribute:: trim + + + .. py:attribute:: output_chunk + + + .. py:attribute:: drop_axis + + + .. py:attribute:: new_axis + + .. py:method:: __lazy_transform_generic(X, xp, **kwargs) @@ -140,6 +166,18 @@ Package Contents + .. py:attribute:: output_size + + + .. py:attribute:: func_aggregate + + + .. py:attribute:: func_chunk + + + .. py:attribute:: func_combine + + .. py:method:: _operation_aggregate_cpu(block, axis=None, keepdims=False) @@ -206,6 +244,14 @@ Package Contents Define if the operator will use GPU(s) or not. + Constructor of the class TargeteredTransform. + + + .. py:attribute:: _run_local + + + .. py:attribute:: _run_gpu + .. py:class:: Fit @@ -555,6 +601,9 @@ Package Contents + .. py:attribute:: shape + + .. py:method:: fit(X, y=None) Generic fit funtion according executor. @@ -569,6 +618,9 @@ Package Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: x + + .. py:method:: transform(X) Generic transform funtion according executor. @@ -583,6 +635,15 @@ Package Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: x + + + .. py:attribute:: y + + + .. py:attribute:: z + + .. py:method:: transform(X) Generic transform funtion according executor. @@ -638,6 +699,20 @@ Package Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: dataset_path + + + .. py:attribute:: chunks + + + .. py:attribute:: save + :value: True + + + + .. py:attribute:: filename + + .. py:method:: _convert_filename(url) :staticmethod: @@ -687,6 +762,17 @@ Package Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: chunks + + + .. py:attribute:: save + :value: True + + + + .. py:attribute:: filename + + .. py:method:: _convert_filename(url) :staticmethod: @@ -733,13 +819,25 @@ Package Contents Bases: :py:obj:`dasf.transforms.base.Transform` - Extract Data from Dataset Object - + Extract data from Dataset object + .. py:method:: transform(X) - Generic transform funtion according executor. + Extract data from datasets that contains internal data. + + Parameters + ---------- + X : Dataset-like + A dataset object that could be anything that contains an internal + structure representing the raw data. + + Returns + ------- + data : Any + Any representation of the internal Dataset data. + @@ -748,12 +846,25 @@ Package Contents Bases: :py:obj:`dasf.transforms.base.Transform` - Class representing a Transform operation of the pipeline. + Normalize data object + .. py:method:: transform(X) - Generic transform funtion according executor. + Normalize the input data based on mean() and std(). + + Parameters + ---------- + X : Any + Any data that could be normalized based on mean and standard + deviation. + + Returns + ------- + data : Any + Normalized data + @@ -765,6 +876,15 @@ Package Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: chunks + + + .. py:attribute:: save + + + .. py:attribute:: filename + + .. py:method:: _convert_filename(url) :staticmethod: diff --git a/docs/_sources/autoapi/dasf/transforms/memory/index.rst.txt b/docs/_sources/autoapi/dasf/transforms/memory/index.rst.txt index d9f4688..0c5fc26 100644 --- a/docs/_sources/autoapi/dasf/transforms/memory/index.rst.txt +++ b/docs/_sources/autoapi/dasf/transforms/memory/index.rst.txt @@ -3,6 +3,11 @@ dasf.transforms.memory .. py:module:: dasf.transforms.memory +.. autoapi-nested-parse:: + + Memory Management module. + + Classes ------- diff --git a/docs/_sources/autoapi/dasf/transforms/operations/index.rst.txt b/docs/_sources/autoapi/dasf/transforms/operations/index.rst.txt index cff8f9a..a49ea26 100644 --- a/docs/_sources/autoapi/dasf/transforms/operations/index.rst.txt +++ b/docs/_sources/autoapi/dasf/transforms/operations/index.rst.txt @@ -3,6 +3,11 @@ dasf.transforms.operations .. py:module:: dasf.transforms.operations +.. autoapi-nested-parse:: + + Basic transform operations module. + + Classes ------- @@ -35,6 +40,9 @@ Module Contents + .. py:attribute:: shape + + .. py:method:: fit(X, y=None) Generic fit funtion according executor. @@ -49,6 +57,9 @@ Module Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: x + + .. py:method:: transform(X) Generic transform funtion according executor. @@ -63,6 +74,15 @@ Module Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: x + + + .. py:attribute:: y + + + .. py:attribute:: z + + .. py:method:: transform(X) Generic transform funtion according executor. @@ -77,6 +97,9 @@ Module Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: p + + .. py:method:: _internal_chunk_array_positive(block, axis=None, keepdims=False, xp=np) @@ -127,6 +150,24 @@ Module Contents offsets: list of offsets for overlapping patches extraction + .. py:attribute:: _function + + + .. py:attribute:: _weight_function + + + .. py:attribute:: _input_size + + + .. py:attribute:: _offsets + + + .. py:attribute:: overlap + + + .. py:attribute:: _overlap_config + + .. py:method:: _apply_patches(patch_set) Applies function to each patch in a patch set @@ -236,6 +277,12 @@ Module Contents num_classes: number of classes possible + .. py:attribute:: _voting + + + .. py:attribute:: _num_classes + + .. py:method:: _combine_patches(results, offsets, indexes) How results are combined is dependent on what is being combined. diff --git a/docs/_sources/autoapi/dasf/transforms/transforms/index.rst.txt b/docs/_sources/autoapi/dasf/transforms/transforms/index.rst.txt index 7609c80..afaed7e 100644 --- a/docs/_sources/autoapi/dasf/transforms/transforms/index.rst.txt +++ b/docs/_sources/autoapi/dasf/transforms/transforms/index.rst.txt @@ -3,6 +3,11 @@ dasf.transforms.transforms .. py:module:: dasf.transforms.transforms +.. autoapi-nested-parse:: + + All the essential data transforms module. + + Classes ------- @@ -25,13 +30,25 @@ Module Contents Bases: :py:obj:`dasf.transforms.base.Transform` - Extract Data from Dataset Object - + Extract data from Dataset object + .. py:method:: transform(X) - Generic transform funtion according executor. + Extract data from datasets that contains internal data. + + Parameters + ---------- + X : Dataset-like + A dataset object that could be anything that contains an internal + structure representing the raw data. + + Returns + ------- + data : Any + Any representation of the internal Dataset data. + @@ -40,12 +57,25 @@ Module Contents Bases: :py:obj:`dasf.transforms.base.Transform` - Class representing a Transform operation of the pipeline. + Normalize data object + .. py:method:: transform(X) - Generic transform funtion according executor. + Normalize the input data based on mean() and std(). + + Parameters + ---------- + X : Any + Any data that could be normalized based on mean and standard + deviation. + + Returns + ------- + data : Any + Normalized data + @@ -57,6 +87,17 @@ Module Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: chunks + + + .. py:attribute:: save + :value: True + + + + .. py:attribute:: filename + + .. py:method:: _convert_filename(url) :staticmethod: @@ -106,6 +147,20 @@ Module Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: dataset_path + + + .. py:attribute:: chunks + + + .. py:attribute:: save + :value: True + + + + .. py:attribute:: filename + + .. py:method:: _convert_filename(url) :staticmethod: @@ -155,6 +210,15 @@ Module Contents Class representing a Transform operation of the pipeline. + .. py:attribute:: chunks + + + .. py:attribute:: save + + + .. py:attribute:: filename + + .. py:method:: _convert_filename(url) :staticmethod: diff --git a/docs/_sources/autoapi/dasf/utils/benchmark/index.rst.txt b/docs/_sources/autoapi/dasf/utils/benchmark/index.rst.txt index bf5a245..2dfb8a2 100644 --- a/docs/_sources/autoapi/dasf/utils/benchmark/index.rst.txt +++ b/docs/_sources/autoapi/dasf/utils/benchmark/index.rst.txt @@ -35,6 +35,9 @@ Module Contents .. py:class:: TimeBenchmark(backend='cprofile') + .. py:attribute:: __backend + + .. py:method:: __enter__() @@ -46,6 +49,21 @@ Module Contents .. py:class:: MemoryBenchmark(backend='memray', debug=False, output_file=None, *args, **kwargs) + .. py:attribute:: __backend + + + .. py:attribute:: __debug + + + .. py:attribute:: __output_file + + + .. py:attribute:: __args + + + .. py:attribute:: __kwargs + + .. py:method:: __enter__() diff --git a/docs/_sources/autoapi/dasf/utils/funcs/index.rst.txt b/docs/_sources/autoapi/dasf/utils/funcs/index.rst.txt index e24df3c..70ee91c 100644 --- a/docs/_sources/autoapi/dasf/utils/funcs/index.rst.txt +++ b/docs/_sources/autoapi/dasf/utils/funcs/index.rst.txt @@ -119,6 +119,35 @@ Module Contents .. py:attribute:: MIN_TOTAL + .. py:attribute:: bar + :value: None + + + + .. py:attribute:: percentage + :value: None + + + + .. py:attribute:: data + :value: None + + + + .. py:attribute:: __lock + + + .. py:attribute:: __current + + + .. py:attribute:: __total + + + .. py:attribute:: __error + :value: False + + + .. py:method:: show() Return the HTML representation of the ProgressBar. diff --git a/docs/_sources/autoapi/dasf/utils/index.rst.txt b/docs/_sources/autoapi/dasf/utils/index.rst.txt index 11e89a5..4041f5d 100644 --- a/docs/_sources/autoapi/dasf/utils/index.rst.txt +++ b/docs/_sources/autoapi/dasf/utils/index.rst.txt @@ -3,6 +3,11 @@ dasf.utils .. py:module:: dasf.utils +.. autoapi-nested-parse:: + + Init module for any utils in DASF. + + Submodules ---------- diff --git a/docs/_sources/autoapi/dasf/utils/labels/index.rst.txt b/docs/_sources/autoapi/dasf/utils/labels/index.rst.txt index 65fde69..764b9f9 100644 --- a/docs/_sources/autoapi/dasf/utils/labels/index.rst.txt +++ b/docs/_sources/autoapi/dasf/utils/labels/index.rst.txt @@ -47,6 +47,27 @@ Module Contents Bases: :py:obj:`object` + .. py:attribute:: __label + + + .. py:attribute:: __color + + + .. py:attribute:: __start + + + .. py:attribute:: __stop + + + .. py:attribute:: __hash_attrs + + + .. py:attribute:: __func_attrs + + + .. py:attribute:: __data_attrs + + .. py:method:: start(start) diff --git a/docs/autoapi/dasf/datasets/base/index.html b/docs/autoapi/dasf/datasets/base/index.html index df6d8c0..653fd42 100644 --- a/docs/autoapi/dasf/datasets/base/index.html +++ b/docs/autoapi/dasf/datasets/base/index.html @@ -140,8 +140,10 @@

    Module Contents class dasf.datasets.base.Dataset(name, download=False, root=None, *args, **kwargs)[source]

    Bases: dasf.transforms.base.TargeteredTransform

    -

    Class representing a generic dataset based on a TargeteredTransform -object.

    +
    +

    Class representing a generic dataset based on a TargeteredTransform

    +
    +

    object.

    Parameters

    @@ -157,6 +159,36 @@

    Parameters +
    +_name
    +

    + +
    +
    +_download
    +
    + +
    +
    +_root
    +
    + +
    +
    +_metadata
    +
    + +
    +
    +_data = None
    +
    + +
    +
    +_chunks = None
    +
    +
    __set_dataset_cache_dir()
    @@ -209,8 +241,10 @@

    Parameters
    class dasf.datasets.base.DatasetArray(name, download=False, root=None, chunks='auto')[source]

    Bases: Dataset

    -

    Class representing an dataset wich is defined as an array of a defined -shape.

    +
    +

    Class representing an dataset wich is defined as an array of a defined

    +
    +

    shape.

    Parameters

    @@ -224,6 +258,16 @@

    Parameters

    Constructor of the object DatasetArray.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    +
    __operator_check__(other)[source]
    @@ -278,7 +322,33 @@

    Returns
    __array_ufunc__(ufunc, method, *inputs, **kwargs)[source]
    -

    +

    Any class, array subclass or not, can define this method or set +it to None in order to override the behavior of Arrays ufuncs.

    +
    +

    Parameters

    +
    +
    ufuncCallable

    The ufunc object that was called.

    +
    +
    methodStr

    A string indicating which Ufunc method was called (one of +“__call__”, “reduce”, “reduceat”, “accumulate”, “outer”, “inner”).

    +
    +
    inputsAny

    A tuple of the input arguments to the ufunc.

    +
    +
    kwargsAny

    A dictionary containing the optional input arguments of the ufunc. +If given, any out arguments, both positional and keyword, are +passed as a tuple in kwargs. See the discussion in Universal +functions (ufunc) for details.

    +
    +
    +
    +
    +

    Returns

    +
    +
    arrayarray-like

    The return either the result of the operation.

    +
    +
    +
    +
    @@ -288,15 +358,15 @@

    Returns>>> Result = DatasetArray + DatasetArray

    -
    -

    Parameters

    +
    +

    Parameters

    in_dataAny

    Input data to be analyzed.

    -
    -

    Returns

    +
    +

    Returns

    dataAny

    A data representing the internal array or the class itself.

    @@ -308,17 +378,17 @@

    Returns __add__(other)[source]

    Internal function of adding two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    -
    DatasetArry

    A sum with two arrays.

    +
    DatasetArray

    A sum with two arrays.

    @@ -328,15 +398,15 @@

    Returns __sub__(other)[source]

    Internal function of subtracting two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A subtraction of two arrays.

    @@ -348,15 +418,15 @@

    Returns __mul__(other)[source]

    Internal function of multiplication two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A multiplication of two arrays.

    @@ -368,15 +438,15 @@

    Returns __div__(other)[source]

    Internal function of division two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A division of two arrays.

    @@ -400,17 +470,17 @@

    Returns _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The data (or a Future load object, for _lazy operations).

    @@ -422,12 +492,12 @@

    Returns _load(xp, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function)

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    @@ -437,8 +507,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -479,8 +549,8 @@

    Returns from_array(array)[source]

    Load data from an existing array.

    -
    -

    Parameters

    +
    +

    Parameters

    arrayarray-like

    Input data to be initialized.

    @@ -498,8 +568,8 @@

    Parameters
    property shape: tuple

    Returns the shape of an array.

    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the shape.

    @@ -513,11 +583,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -548,8 +618,8 @@

    Returns

    Bases: Dataset

    Class representing an dataset wich is defined as a Zarr array of a defined shape.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -561,21 +631,36 @@

    Parameters

    Constructor of the object DatasetZarr.

    +
    +
    +_backend
    +
    + +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    +
    _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The data (or a Future load object, for _lazy operations).

    @@ -587,12 +672,12 @@

    Returns _load(xp, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function)

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    @@ -632,8 +717,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -656,8 +741,8 @@

    Returns property shape: tuple

    Returns the shape of an array.

    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the shape.

    @@ -675,8 +760,8 @@

    Returnsproperty chunksize
    Returns the chunksize of an array.
    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the chunksize.

    @@ -685,11 +770,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -716,15 +801,15 @@

    Returns>>> Result = DatasetZarr + DatasetZarr

    -
    -

    Parameters

    +
    +

    Parameters

    in_dataAny

    Input data to be analyzed.

    -
    -

    Returns

    +
    +

    Returns

    dataAny

    A data representing the internal array or the class itself.

    @@ -736,15 +821,15 @@

    Returns __add__(other)[source]

    Internal function of adding two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A sum with two arrays.

    @@ -756,15 +841,15 @@

    Returns __sub__(other)[source]

    Internal function of subtracting two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A subtraction of two arrays.

    @@ -776,15 +861,15 @@

    Returns __mul__(other)[source]

    Internal function of multiplication two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A multiplication of two arrays.

    @@ -796,15 +881,15 @@

    Returns __div__(other)[source]

    Internal function of division two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A division of two arrays.

    @@ -837,8 +922,8 @@

    Returns

    Bases: Dataset

    Class representing an dataset wich is defined as a HDF5 dataset of a defined shape.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -852,21 +937,36 @@

    Parameters

    Constructor of the object DatasetHDF5.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    + +
    +
    +_dataset_path
    +
    +
    _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The data (or a Future load object, for _lazy operations).

    @@ -878,12 +978,12 @@

    Returns _load(xp=None, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function) (placeholder).

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    @@ -923,8 +1023,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -938,11 +1038,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -974,8 +1074,8 @@

    Returns

    Bases: Dataset

    Class representing an dataset wich is defined as a Xarray dataset of a defined shape.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -989,6 +1089,21 @@

    Parameters

    Constructor of the object DatasetXarray.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    + +
    +
    +_data_var
    +
    +
    _lazy_load_cpu()[source]
    @@ -1023,8 +1138,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1038,11 +1153,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1070,8 +1185,8 @@

    Returns __getitem__(idx)[source]

    A __getitem__() function based on internal Xarray data.

    -
    -

    Parameters

    +
    +

    Parameters

    idxAny

    Key of the fetched data. It can be an integer or a tuple.

    @@ -1098,8 +1213,8 @@

    Parameters

    A class representing a labeled dataset. Each item is a 2-element tuple, where the first element is a array of data and the second element is the respective label. The items can be accessed from dataset[x].

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -1118,6 +1233,11 @@

    Attributes +
    +_chunks
    +

    +
    download()[source]
    @@ -1125,12 +1245,12 @@

    Attributes -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data (train and labels).

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1147,17 +1267,17 @@

    Returns _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Tuple

    A Future object that will return a tuple: (data, label).

    @@ -1174,17 +1294,17 @@

    Returns _load(xp, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function)

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    -
    -

    Returns

    +
    +

    Returns

    Tuple

    A 2-element tuple: (data, label)

    @@ -1201,8 +1321,8 @@

    Returns _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1249,8 +1369,8 @@

    Returns __getitem__(idx)[source]

    A __getitem__() function for data and labeled data together.

    -
    -

    Parameters

    +
    +

    Parameters

    idxAny

    Key of the fetched data. It can be an integer or a tuple.

    @@ -1275,8 +1395,8 @@

    Parameters class dasf.datasets.base.DatasetDataFrame(name, download=True, root=None, chunks='auto')[source]

    Bases: Dataset

    Class representing an dataset wich is defined as a dataframe.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -1288,12 +1408,22 @@

    Parameters

    Constructor of the object DatasetDataFrame.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    +
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1307,11 +1437,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1358,8 +1488,8 @@

    Returns property shape: tuple

    Returns the shape of an array.

    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the shape.

    @@ -1387,8 +1517,8 @@

    Returns __getitem__(idx)[source]

    A __getitem__() function based on internal dataframe.

    -
    -

    Parameters

    +
    +

    Parameters

    idxAny

    Key of the fetched data. It can be an integer or a tuple.

    @@ -1412,9 +1542,11 @@

    Parameters
    class dasf.datasets.base.DatasetParquet(name, download=True, root=None, chunks='auto')[source]

    Bases: DatasetDataFrame

    -

    Class representing an dataset wich is defined as a Parquet.

    -
    -

    Parameters

    +
    +

    Class representing an dataset wich is defined as a Parquet.

    +
    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    diff --git a/docs/autoapi/dasf/datasets/download/index.html b/docs/autoapi/dasf/datasets/download/index.html index 3aac3f0..4dfb9b8 100644 --- a/docs/autoapi/dasf/datasets/download/index.html +++ b/docs/autoapi/dasf/datasets/download/index.html @@ -136,6 +136,16 @@

    Parameters +
    +__url
    +

    + +
    +
    +__filename
    +
    +
    download()[source]
    @@ -173,6 +183,16 @@

    Parameters

    Constructor of the object DownloadGDrive.

    +
    +
    +__google_file_id
    +
    + +
    +
    +__filename
    +
    +
    download()[source]
    diff --git a/docs/autoapi/dasf/datasets/index.html b/docs/autoapi/dasf/datasets/index.html index f03022a..1e8d15e 100644 --- a/docs/autoapi/dasf/datasets/index.html +++ b/docs/autoapi/dasf/datasets/index.html @@ -155,8 +155,10 @@

    Package Contents class dasf.datasets.Dataset(name, download=False, root=None, *args, **kwargs)[source]

    Bases: dasf.transforms.base.TargeteredTransform

    -

    Class representing a generic dataset based on a TargeteredTransform -object.

    +
    +

    Class representing a generic dataset based on a TargeteredTransform

    +
    +

    object.

    Parameters

    @@ -172,6 +174,36 @@

    Parameters +
    +_name
    +

    + +
    +
    +_download
    +
    + +
    +
    +_root
    +
    + +
    +
    +_metadata
    +
    + +
    +
    +_data = None
    +
    + +
    +
    +_chunks = None
    +
    +
    __set_dataset_cache_dir()
    @@ -224,8 +256,10 @@

    Parameters
    class dasf.datasets.DatasetArray(name, download=False, root=None, chunks='auto')[source]

    Bases: Dataset

    -

    Class representing an dataset wich is defined as an array of a defined -shape.

    +
    +

    Class representing an dataset wich is defined as an array of a defined

    +
    +

    shape.

    Parameters

    @@ -239,6 +273,16 @@

    Parameters

    Constructor of the object DatasetArray.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    +
    __operator_check__(other)[source]
    @@ -293,7 +337,33 @@

    Returns
    __array_ufunc__(ufunc, method, *inputs, **kwargs)[source]
    -

    +

    Any class, array subclass or not, can define this method or set +it to None in order to override the behavior of Arrays ufuncs.

    +
    +

    Parameters

    +
    +
    ufuncCallable

    The ufunc object that was called.

    +
    +
    methodStr

    A string indicating which Ufunc method was called (one of +“__call__”, “reduce”, “reduceat”, “accumulate”, “outer”, “inner”).

    +
    +
    inputsAny

    A tuple of the input arguments to the ufunc.

    +
    +
    kwargsAny

    A dictionary containing the optional input arguments of the ufunc. +If given, any out arguments, both positional and keyword, are +passed as a tuple in kwargs. See the discussion in Universal +functions (ufunc) for details.

    +
    +
    +
    +
    +

    Returns

    +
    +
    arrayarray-like

    The return either the result of the operation.

    +
    +
    +
    +

    @@ -303,15 +373,15 @@

    Returns>>> Result = DatasetArray + DatasetArray

    -
    -

    Parameters

    +
    +

    Parameters

    in_dataAny

    Input data to be analyzed.

    -
    -

    Returns

    +
    +

    Returns

    dataAny

    A data representing the internal array or the class itself.

    @@ -323,17 +393,17 @@

    Returns __add__(other)[source]

    Internal function of adding two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    -
    DatasetArry

    A sum with two arrays.

    +
    DatasetArray

    A sum with two arrays.

    @@ -343,15 +413,15 @@

    Returns __sub__(other)[source]

    Internal function of subtracting two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A subtraction of two arrays.

    @@ -363,15 +433,15 @@

    Returns __mul__(other)[source]

    Internal function of multiplication two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A multiplication of two arrays.

    @@ -383,15 +453,15 @@

    Returns __div__(other)[source]

    Internal function of division two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A division of two arrays.

    @@ -415,17 +485,17 @@

    Returns _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The data (or a Future load object, for _lazy operations).

    @@ -437,12 +507,12 @@

    Returns _load(xp, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function)

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    @@ -452,8 +522,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -494,8 +564,8 @@

    Returns from_array(array)[source]

    Load data from an existing array.

    -
    -

    Parameters

    +
    +

    Parameters

    arrayarray-like

    Input data to be initialized.

    @@ -513,8 +583,8 @@

    Parameters
    property shape: tuple

    Returns the shape of an array.

    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the shape.

    @@ -528,11 +598,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -563,8 +633,8 @@

    Returns

    Bases: Dataset

    Class representing an dataset wich is defined as a Zarr array of a defined shape.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -576,21 +646,36 @@

    Parameters

    Constructor of the object DatasetZarr.

    +
    +
    +_backend
    +
    + +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    +
    _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The data (or a Future load object, for _lazy operations).

    @@ -602,12 +687,12 @@

    Returns _load(xp, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function)

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    @@ -647,8 +732,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -671,8 +756,8 @@

    Returns property shape: tuple

    Returns the shape of an array.

    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the shape.

    @@ -690,8 +775,8 @@

    Returnsproperty chunksize
    Returns the chunksize of an array.
    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the chunksize.

    @@ -700,11 +785,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -731,15 +816,15 @@

    Returns>>> Result = DatasetZarr + DatasetZarr

    -
    -

    Parameters

    +
    +

    Parameters

    in_dataAny

    Input data to be analyzed.

    -
    -

    Returns

    +
    +

    Returns

    dataAny

    A data representing the internal array or the class itself.

    @@ -751,15 +836,15 @@

    Returns __add__(other)[source]

    Internal function of adding two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A sum with two arrays.

    @@ -771,15 +856,15 @@

    Returns __sub__(other)[source]

    Internal function of subtracting two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A subtraction of two arrays.

    @@ -791,15 +876,15 @@

    Returns __mul__(other)[source]

    Internal function of multiplication two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A multiplication of two arrays.

    @@ -811,15 +896,15 @@

    Returns __div__(other)[source]

    Internal function of division two array datasets.

    -
    -

    Parameters

    +
    +

    Parameters

    otherAny

    A data representing an array or a DatasetArray.

    -
    -

    Returns

    +
    +

    Returns

    DatasetArry

    A division of two arrays.

    @@ -852,8 +937,8 @@

    Returns

    Bases: Dataset

    Class representing an dataset wich is defined as a HDF5 dataset of a defined shape.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -867,21 +952,36 @@

    Parameters

    Constructor of the object DatasetHDF5.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    + +
    +
    +_dataset_path
    +
    +
    _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The data (or a Future load object, for _lazy operations).

    @@ -893,12 +993,12 @@

    Returns _load(xp=None, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function) (placeholder).

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    @@ -938,8 +1038,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -953,11 +1053,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -989,8 +1089,8 @@

    Returns

    Bases: Dataset

    Class representing an dataset wich is defined as a Xarray dataset of a defined shape.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -1004,6 +1104,21 @@

    Parameters

    Constructor of the object DatasetXarray.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    + +
    +
    +_data_var
    +
    +
    _lazy_load_cpu()[source]
    @@ -1038,8 +1153,8 @@

    Parameters
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1053,11 +1168,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1085,8 +1200,8 @@

    Returns __getitem__(idx)[source]

    A __getitem__() function based on internal Xarray data.

    -
    -

    Parameters

    +
    +

    Parameters

    idxAny

    Key of the fetched data. It can be an integer or a tuple.

    @@ -1113,8 +1228,8 @@

    Parameters

    A class representing a labeled dataset. Each item is a 2-element tuple, where the first element is a array of data and the second element is the respective label. The items can be accessed from dataset[x].

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -1133,6 +1248,11 @@

    Attributes +
    +_chunks
    +

    +
    download()[source]
    @@ -1140,12 +1260,12 @@

    Attributes -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data (train and labels).

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1162,17 +1282,17 @@

    Returns _lazy_load(xp, **kwargs)[source]

    Lazy load the dataset using an CPU dask container.

    -
    -

    Parameters

    +
    +

    Parameters

    xptype

    Library used to load the file. It must follow numpy library.

    -
    **kwargstype

    Additional keyworkded arguments to the load.

    +
    **kwargstype

    Additional keyworkded arguments to the load.

    -
    -

    Returns

    +
    +

    Returns

    Tuple

    A Future object that will return a tuple: (data, label).

    @@ -1189,17 +1309,17 @@

    Returns _load(xp, **kwargs)[source]

    Load data using CPU container.

    -
    -

    Parameters

    +
    +

    Parameters

    xpModule

    A module that load data (implement load function)

    -
    **kwargstype

    Additional kwargs to xp.load function.

    +
    **kwargstype

    Additional kwargs to xp.load function.

    -
    -

    Returns

    +
    +

    Returns

    Tuple

    A 2-element tuple: (data, label)

    @@ -1216,8 +1336,8 @@

    Returns _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1264,8 +1384,8 @@

    Returns __getitem__(idx)[source]

    A __getitem__() function for data and labeled data together.

    -
    -

    Parameters

    +
    +

    Parameters

    idxAny

    Key of the fetched data. It can be an integer or a tuple.

    @@ -1290,8 +1410,8 @@

    Parameters class dasf.datasets.DatasetDataFrame(name, download=True, root=None, chunks='auto')[source]

    Bases: Dataset

    Class representing an dataset wich is defined as a dataframe.

    -
    -

    Parameters

    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -1303,12 +1423,22 @@

    Parameters

    Constructor of the object DatasetDataFrame.

    +
    +
    +_chunks
    +
    + +
    +
    +_root_file
    +
    +
    _load_meta()[source]

    Load metadata to inspect.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1322,11 +1452,11 @@

    Returns

    -
    -inspect_metadata()[source]
    +
    +metadata()[source]

    Return a dictionary with all metadata information from data.

    -
    -

    Returns

    +
    +

    Returns

    dict

    A dictionary with metadata information.

    @@ -1373,8 +1503,8 @@

    Returns property shape: tuple

    Returns the shape of an array.

    -
    -

    Returns

    +
    +

    Returns

    tuple

    A tuple with the shape.

    @@ -1402,8 +1532,8 @@

    Returns __getitem__(idx)[source]

    A __getitem__() function based on internal dataframe.

    -
    -

    Parameters

    +
    +

    Parameters

    idxAny

    Key of the fetched data. It can be an integer or a tuple.

    @@ -1427,9 +1557,11 @@

    Parameters
    class dasf.datasets.DatasetParquet(name, download=True, root=None, chunks='auto')[source]

    Bases: DatasetDataFrame

    -

    Class representing an dataset wich is defined as a Parquet.

    -
    -

    Parameters

    +
    +

    Class representing an dataset wich is defined as a Parquet.

    +
    +
    +

    Parameters

    namestr

    Symbolic name of the dataset.

    @@ -1484,8 +1616,8 @@

    Parameters

    For an example of usage, see sphx_glr_auto_examples_datasets_plot_random_dataset.py.

    Read more in the User Guide.

    -
    -

    Parameters

    +
    +

    Parameters

    n_samplesint or array-like, default=100

    If int, it is the total number of points equally divided among clusters. @@ -1520,8 +1652,8 @@

    Parameters

    -
    -

    Returns

    +
    +

    Returns

    Xndarray of shape (n_samples, n_features)

    The generated samples.

    @@ -1600,8 +1732,8 @@

    Examples

    For an example of usage, see sphx_glr_auto_examples_datasets_plot_random_dataset.py.

    Read more in the User Guide.

    -
    -

    Parameters

    +
    +

    Parameters

    n_samplesint, default=100

    The number of samples.

    @@ -1662,8 +1794,8 @@

    Parameters

    -
    -

    Returns

    +
    +

    Returns

    Xndarray of shape (n_samples, n_features)

    The generated samples.

    @@ -1671,8 +1803,8 @@

    Returns

    -
    -

    See Also

    +
    +

    See Also

    make_blobs : Simplified variant. make_multilabel_classification : Unrelated generator for multilabel tasks.

    @@ -1684,15 +1816,15 @@

    Notes

    References

    -
    -

    Examples

    +
    +

    Examples

    >>> from sklearn.datasets import make_classification
     >>> X, y = make_classification(random_state=42)
     >>> X.shape
    diff --git a/docs/autoapi/dasf/debug/debug/index.html b/docs/autoapi/dasf/debug/debug/index.html
    index c58a133..94d6d61 100644
    --- a/docs/autoapi/dasf/debug/debug/index.html
    +++ b/docs/autoapi/dasf/debug/debug/index.html
    @@ -167,6 +167,11 @@ 

    Parameters

    Generic constructor of the VisualizeDaskData object.

    +
    +
    +filename
    +
    +
    display(X)[source]
    diff --git a/docs/autoapi/dasf/debug/index.html b/docs/autoapi/dasf/debug/index.html index 55131c3..9efe8a0 100644 --- a/docs/autoapi/dasf/debug/index.html +++ b/docs/autoapi/dasf/debug/index.html @@ -101,6 +101,7 @@

    dasf.debug

    +

    Init module for debugging DASF.

    Submodules

    @@ -173,6 +174,11 @@

    Parameters

    Generic constructor of the VisualizeDaskData object.

    +
    +
    +filename
    +
    +
    display(X)[source]
    diff --git a/docs/autoapi/dasf/feature_extraction/histogram/index.html b/docs/autoapi/dasf/feature_extraction/histogram/index.html index a03616e..e61daa3 100644 --- a/docs/autoapi/dasf/feature_extraction/histogram/index.html +++ b/docs/autoapi/dasf/feature_extraction/histogram/index.html @@ -23,7 +23,7 @@ - + @@ -149,9 +149,34 @@

    Attributes +
    +_bins
    +

    + +
    +
    +_range
    +
    + +
    +
    +_normed
    +
    + +
    +
    +_weights
    +
    + +
    +
    +_density
    +
    +
    -
    -__lazy_transform_generic(X)
    +
    +_lazy_transform_generic(X)[source]

    Compute the histogram of a dataset using Dask.

    Parameters

    @@ -174,8 +199,8 @@

    Returns

    -
    -__transform_generic(X, xp)
    +
    +_transform_generic(X, xp)[source]

    Compute the histogram of a dataset using local libraries.

    Parameters

    @@ -313,7 +338,7 @@

    Returns

    @@ -123,10 +123,7 @@

    Classes

    GetSubDataframe

    Get the first x% samples from the dataset.

    -

    GetSubeCubeArray

    -

    Get a subcube with x% of samples from the original one.

    - -

    SampleDataframe

    +

    SampleDataframe

    Return a subset with random samples of the original dataset.

    @@ -168,9 +165,34 @@

    Attributes +
    +_bins
    +
    + +
    +
    +_range
    +
    + +
    +
    +_normed
    +
    + +
    +
    +_weights
    +
    + +
    +
    +_density
    +
    +
    -
    -__lazy_transform_generic(X)
    +
    +_lazy_transform_generic(X)[source]

    Compute the histogram of a dataset using Dask.

    Parameters

    @@ -193,8 +215,8 @@

    Returns

    -
    -__transform_generic(X, xp)
    +
    +_transform_generic(X, xp)[source]

    Compute the histogram of a dataset using local libraries.

    Parameters

    @@ -326,7 +348,7 @@

    Returns
    -class dasf.feature_extraction.ConcatenateToArray(flatten=False)[source]
    +class dasf.feature_extraction.ConcatenateToArray(flatten=False)[source]

    Bases: dasf.transforms.base.Transform

    Concatenate data from different Arrays into a single array.

    @@ -337,6 +359,11 @@

    Parameters concatenated (the default is False).

    +
    +
    +flatten
    +
    +
    __transform_generic(xp, **kwargs)
    @@ -344,13 +371,13 @@

    Parameters
    -_transform_cpu(**kwargs)[source]
    +_transform_cpu(**kwargs)[source]

    Respective immediate transform mocked function for local CPU(s).

    -_transform_gpu(**kwargs)[source]
    +_transform_gpu(**kwargs)[source]

    Respective immediate transform mocked function for local GPU(s).

    @@ -364,7 +391,7 @@

    Parameters
    -class dasf.feature_extraction.GetSubDataframe(percent)[source]
    +class dasf.feature_extraction.GetSubDataframe(percent)[source]

    Get the first x% samples from the dataset.

    Parameters

    @@ -372,9 +399,14 @@

    Parameters
    percentfloat

    Percentage of the samples to get from the dataframe.

    +
    +
    +__percent
    +
    +
    -transform(X)[source]
    +transform(X)[source]
    @@ -386,51 +418,34 @@

    Parameters

    -
    -class dasf.feature_extraction.GetSubeCubeArray(percent)[source]
    -

    Get a subcube with x% of samples from the original one.

    +
    +class dasf.feature_extraction.SampleDataframe(percent)[source]
    +

    Bases: dasf.transforms.base.Transform

    +

    Return a subset with random samples of the original dataset.

    Parameters

    -
    percentfloat

    Percentage of the samples to get from the cube.

    +
    percentfloat

    Percentage of the samples to get from the dataset.

    -
    -
    -transform(X)[source]
    +
    +
    +__percent
    -
    -
    -
    Parameters:
    -

    percent (float)

    -
    -
    -
    - -
    -
    -class dasf.feature_extraction.SampleDataframe(percent)[source]
    -

    Return a subset with random samples of the original dataset.

    -
    -

    Parameters

    -
    -
    percentfloat

    Percentage of the samples to get from the dataset.

    -
    -
    -
    -run(X)[source]
    +
    +transform(X)[source]

    Returns a subset with random samples from the dataset X.

    -
    -

    Parameters

    +
    +

    Parameters

    XAny

    The dataset.

    -
    -

    Returns

    +
    +

    Returns

    Any

    The sampled subset.

    diff --git a/docs/autoapi/dasf/index.html b/docs/autoapi/dasf/index.html index 5624a37..13f2068 100644 --- a/docs/autoapi/dasf/index.html +++ b/docs/autoapi/dasf/index.html @@ -100,6 +100,7 @@

    dasf

    +

    Init all modules for DASF.

    Subpackages

    diff --git a/docs/autoapi/dasf/ml/cluster/agglomerative/index.html b/docs/autoapi/dasf/ml/cluster/agglomerative/index.html index 8f40213..54e5807 100644 --- a/docs/autoapi/dasf/ml/cluster/agglomerative/index.html +++ b/docs/autoapi/dasf/ml/cluster/agglomerative/index.html @@ -118,7 +118,7 @@

    Classes

    Module Contents

    -class dasf.ml.cluster.agglomerative.AgglomerativeClustering(n_clusters=2, affinity='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs)
    +class dasf.ml.cluster.agglomerative.AgglomerativeClustering(n_clusters=2, metric='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Agglomerative Clustering

    Recursively merges the pair of clusters that minimally increases @@ -130,11 +130,10 @@

    Parametersint or None, default=2

    The number of clusters to find. It must be None if distance_threshold is not None.

    -
    affinitystr or callable, default=’euclidean’

    Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, -“manhattan”, “cosine”, or “precomputed”. -If linkage is “ward”, only “euclidean” is accepted. -If “precomputed”, a distance matrix (instead of a similarity matrix) -is needed as input for the fit method.

    +
    metricstr or callable, default=”euclidean”

    Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, +“manhattan”, “cosine”, or “precomputed”. If linkage is “ward”, only +“euclidean” is accepted. If “precomputed”, a distance matrix is needed +as input for the fit method.

    memorystr or object with the joblib.Memory interface, default=None

    Used to cache the output of the computation of the tree. By default, no caching is done. If a string is given, it is the @@ -211,7 +210,72 @@

    Examples

    For further informations see: - https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html - https://docs.rapids.ai/api/cuml/stable/api.html#agglomerative-clustering

    -

    A generic constructor method.

    +

    Constructor of the class AgglomerativeClustering.

    +
    +
    +n_clusters
    +
    + +
    +
    +metric
    +
    + +
    +
    +connectivity
    +
    + +
    +
    +linkage
    +
    + +
    +
    +memory
    +
    + +
    +
    +compute_full_tree
    +
    + +
    +
    +distance_threshold
    +
    + +
    +
    +compute_distances
    +
    + +
    +
    +handle
    +
    + +
    +
    +verbose
    +
    + +
    +
    +n_neighbors
    +
    + +
    +
    +output_type
    +
    + +
    +
    +__agg_cluster_cpu
    +
    +
    _fit_cpu(X, y=None, convert_dtype=True)[source]
    diff --git a/docs/autoapi/dasf/ml/cluster/dbscan/index.html b/docs/autoapi/dasf/ml/cluster/dbscan/index.html index 5987379..0d641c3 100644 --- a/docs/autoapi/dasf/ml/cluster/dbscan/index.html +++ b/docs/autoapi/dasf/ml/cluster/dbscan/index.html @@ -214,7 +214,52 @@

    References +
    +eps
    +

    + +
    +
    +leaf_size
    +
    + +
    +
    +metric
    +
    + +
    +
    +min_samples
    +
    + +
    +
    +p
    +
    + +
    +
    +output_type
    +
    + +
    +
    +calc_core_sample_indices
    +
    + +
    +
    +verbose
    +
    + +
    +
    +__dbscan_cpu
    +
    +
    _lazy_fit_gpu(X, y=None, out_dtype='int32')[source]
    diff --git a/docs/autoapi/dasf/ml/cluster/hdbscan/index.html b/docs/autoapi/dasf/ml/cluster/hdbscan/index.html index 283c418..5447055 100644 --- a/docs/autoapi/dasf/ml/cluster/hdbscan/index.html +++ b/docs/autoapi/dasf/ml/cluster/hdbscan/index.html @@ -118,7 +118,7 @@

    Classes

    Module Contents

    -class dasf.ml.cluster.hdbscan.HDBSCAN(alpha=1.0, gen_min_span_tree=False, leaf_size=40, metric='euclidean', min_cluster_size=5, min_samples=None, p=None, algorithm='auto', approx_min_span_tree=True, core_dist_n_jobs=4, cluster_selection_method='eom', allow_single_cluster=False, prediction_data=False, match_reference_implementation=False, connectivity='knn', output_type=None, verbose=0, **kwargs)
    +class dasf.ml.cluster.hdbscan.HDBSCAN(alpha=1.0, gen_min_span_tree=False, leaf_size=40, metric='euclidean', min_cluster_size=5, min_samples=None, p=None, algorithm='auto', approx_min_span_tree=True, core_dist_n_jobs=4, cluster_selection_method='eom', allow_single_cluster=False, prediction_data=False, match_reference_implementation=False, connectivity='knn', output_type=None, verbose=0, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Perform HDBSCAN clustering from vector array or distance matrix.

    HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications @@ -295,10 +295,100 @@

    References +
    +alpha
    +

    + +
    +
    +gen_min_span_tree
    +
    + +
    +
    +leaf_size
    +
    + +
    +
    +metric
    +
    + +
    +
    +min_cluster_size
    +
    + +
    +
    +min_samples
    +
    + +
    +
    +p
    +
    + +
    +
    +algorithm
    +
    + +
    +
    +approx_min_span_tree
    +
    + +
    +
    +core_dist_n_jobs
    +
    + +
    +
    +cluster_selection_method
    +
    + +
    +
    +allow_single_cluster
    +
    + +
    +
    +prediction_data
    +
    + +
    +
    +match_reference_implementation
    +
    + +
    +
    +connectivity
    +
    + +
    +
    +output_type
    +
    + +
    +
    +verbose
    +
    + +
    +
    +__hdbscan_cpu
    +
    +
    -_fit_cpu(X, y=None)
    +_fit_cpu(X, y=None)[source]

    Perform HDBSCAN clustering from features or distance matrix using CPU only.

    Parameters

    @@ -319,7 +409,7 @@

    Returns
    -_fit_gpu(X, y=None, convert_dtype=True)
    +_fit_gpu(X, y=None, convert_dtype=True)[source]

    Perform HDBSCAN clustering from features or distance matrix using GPU only (from CuML).

    @@ -341,7 +431,7 @@

    Returns
    -_fit_predict_cpu(X, y=None)
    +_fit_predict_cpu(X, y=None)[source]

    Performs clustering on X and returns cluster labels using only CPU.

    Parameters

    @@ -362,7 +452,7 @@

    Returns
    -_fit_predict_gpu(X, y=None)
    +_fit_predict_gpu(X, y=None)[source]

    Performs clustering on X and returns cluster labels using only GPU (from CuML).

    diff --git a/docs/autoapi/dasf/ml/cluster/index.html b/docs/autoapi/dasf/ml/cluster/index.html index 17df9f0..c0ffa4e 100644 --- a/docs/autoapi/dasf/ml/cluster/index.html +++ b/docs/autoapi/dasf/ml/cluster/index.html @@ -146,7 +146,7 @@

    Classes

    Package Contents

    -class dasf.ml.cluster.AgglomerativeClustering(n_clusters=2, affinity='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs)
    +class dasf.ml.cluster.AgglomerativeClustering(n_clusters=2, metric='euclidean', connectivity=None, linkage='single', memory=None, compute_full_tree='auto', distance_threshold=None, compute_distances=False, handle=None, verbose=False, n_neighbors=10, output_type=None, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Agglomerative Clustering

    Recursively merges the pair of clusters that minimally increases @@ -158,11 +158,10 @@

    Parametersint or None, default=2

    The number of clusters to find. It must be None if distance_threshold is not None.

    -
    affinitystr or callable, default=’euclidean’

    Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, -“manhattan”, “cosine”, or “precomputed”. -If linkage is “ward”, only “euclidean” is accepted. -If “precomputed”, a distance matrix (instead of a similarity matrix) -is needed as input for the fit method.

    +
    metricstr or callable, default=”euclidean”

    Metric used to compute the linkage. Can be “euclidean”, “l1”, “l2”, +“manhattan”, “cosine”, or “precomputed”. If linkage is “ward”, only +“euclidean” is accepted. If “precomputed”, a distance matrix is needed +as input for the fit method.

    memorystr or object with the joblib.Memory interface, default=None

    Used to cache the output of the computation of the tree. By default, no caching is done. If a string is given, it is the @@ -239,10 +238,75 @@

    Examples

    For further informations see: - https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html - https://docs.rapids.ai/api/cuml/stable/api.html#agglomerative-clustering

    -

    A generic constructor method.

    +

    Constructor of the class AgglomerativeClustering.

    +
    +
    +n_clusters
    +
    + +
    +
    +metric
    +
    + +
    +
    +connectivity
    +
    + +
    +
    +linkage
    +
    + +
    +
    +memory
    +
    + +
    +
    +compute_full_tree
    +
    + +
    +
    +distance_threshold
    +
    + +
    +
    +compute_distances
    +
    + +
    +
    +handle
    +
    + +
    +
    +verbose
    +
    + +
    +
    +n_neighbors
    +
    + +
    +
    +output_type
    +
    + +
    +
    +__agg_cluster_cpu
    +
    +
    -_fit_cpu(X, y=None, convert_dtype=True)
    +_fit_cpu(X, y=None, convert_dtype=True)[source]

    Fit without validation using CPU only.

    Parameters

    @@ -263,7 +327,7 @@

    Returns
    -_fit_gpu(X, y=None, convert_dtype=True)
    +_fit_gpu(X, y=None, convert_dtype=True)[source]

    Fit without validation using GPU only.

    Parameters

    @@ -284,7 +348,7 @@

    Returns
    -_fit_predict_cpu(X, y=None)
    +_fit_predict_cpu(X, y=None)[source]

    Fit and return the result of each sample’s clustering assignment using CPU only.

    In addition to fitting, this method also return the result of the @@ -310,7 +374,7 @@

    Returns
    -_fit_predict_gpu(X, y=None)
    +_fit_predict_gpu(X, y=None)[source]

    Fit and return the result of each sample’s clustering assignment using GPU only.

    In addition to fitting, this method also return the result of the @@ -339,7 +403,7 @@

    Returns
    -class dasf.ml.cluster.DBSCAN(eps=0.5, leaf_size=40, metric='euclidean', min_samples=5, p=None, output_type=None, calc_core_sample_indices=True, verbose=False, **kwargs)
    +class dasf.ml.cluster.DBSCAN(eps=0.5, leaf_size=40, metric='euclidean', min_samples=5, p=None, output_type=None, calc_core_sample_indices=True, verbose=False, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Perform DBSCAN clustering from vector array or distance matrix.

    DBSCAN - Density-Based Spatial Clustering of Applications with Noise. @@ -435,10 +499,55 @@

    References +
    +eps
    +

    + +
    +
    +leaf_size
    +
    + +
    +
    +metric
    +
    + +
    +
    +min_samples
    +
    + +
    +
    +p
    +
    + +
    +
    +output_type
    +
    + +
    +
    +calc_core_sample_indices
    +
    + +
    +
    +verbose
    +
    + +
    +
    +__dbscan_cpu
    +
    +
    -_lazy_fit_gpu(X, y=None, out_dtype='int32')
    +_lazy_fit_gpu(X, y=None, out_dtype='int32')[source]

    Perform DBSCAN clustering from features, or distance matrix using Dask with GPUs only (from CuML).

    @@ -468,7 +577,7 @@

    Returns
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Perform DBSCAN clustering from features, or distance matrix using CPU only.

    @@ -498,7 +607,7 @@

    Returns
    -_fit_gpu(X, y=None, out_dtype='int32')
    +_fit_gpu(X, y=None, out_dtype='int32')[source]

    Perform DBSCAN clustering from features, or distance matrix using GPU only (from CuML).

    @@ -528,7 +637,7 @@

    Returns
    -_lazy_fit_predict_gpu(X, y=None, out_dtype='int32')
    +_lazy_fit_predict_gpu(X, y=None, out_dtype='int32')[source]

    Compute clusters from a data or distance matrix and predict labels using Dask and GPUs (from CuML).

    @@ -558,7 +667,7 @@

    Returns
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Compute clusters from a data or distance matrix and predict labels using CPU only.

    @@ -588,7 +697,7 @@

    Returns
    -_fit_predict_gpu(X, y=None, out_dtype='int32')
    +_fit_predict_gpu(X, y=None, out_dtype='int32')[source]

    Compute clusters from a data or distance matrix and predict labels using GPU only (from CuML).

    @@ -621,7 +730,7 @@

    Returns
    -class dasf.ml.cluster.HDBSCAN(alpha=1.0, gen_min_span_tree=False, leaf_size=40, metric='euclidean', min_cluster_size=5, min_samples=None, p=None, algorithm='auto', approx_min_span_tree=True, core_dist_n_jobs=4, cluster_selection_method='eom', allow_single_cluster=False, prediction_data=False, match_reference_implementation=False, connectivity='knn', output_type=None, verbose=0, **kwargs)
    +class dasf.ml.cluster.HDBSCAN(alpha=1.0, gen_min_span_tree=False, leaf_size=40, metric='euclidean', min_cluster_size=5, min_samples=None, p=None, algorithm='auto', approx_min_span_tree=True, core_dist_n_jobs=4, cluster_selection_method='eom', allow_single_cluster=False, prediction_data=False, match_reference_implementation=False, connectivity='knn', output_type=None, verbose=0, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Perform HDBSCAN clustering from vector array or distance matrix.

    HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications @@ -798,10 +907,100 @@

    References Density-based Cluster Selection. arxiv preprint 1911.02282.

    -

    A generic constructor method.

    +

    Constructor of the class HDBSCAN.

    +
    +
    +alpha
    +
    + +
    +
    +gen_min_span_tree
    +
    + +
    +
    +leaf_size
    +
    + +
    +
    +metric
    +
    + +
    +
    +min_cluster_size
    +
    + +
    +
    +min_samples
    +
    + +
    +
    +p
    +
    + +
    +
    +algorithm
    +
    + +
    +
    +approx_min_span_tree
    +
    + +
    +
    +core_dist_n_jobs
    +
    + +
    +
    +cluster_selection_method
    +
    + +
    +
    +allow_single_cluster
    +
    + +
    +
    +prediction_data
    +
    + +
    +
    +match_reference_implementation
    +
    + +
    +
    +connectivity
    +
    + +
    +
    +output_type
    +
    + +
    +
    +verbose
    +
    + +
    +
    +__hdbscan_cpu
    +
    +
    -_fit_cpu(X, y=None)
    +_fit_cpu(X, y=None)[source]

    Perform HDBSCAN clustering from features or distance matrix using CPU only.

    Parameters

    @@ -822,7 +1021,7 @@

    Returns
    -_fit_gpu(X, y=None, convert_dtype=True)
    +_fit_gpu(X, y=None, convert_dtype=True)[source]

    Perform HDBSCAN clustering from features or distance matrix using GPU only (from CuML).

    @@ -844,7 +1043,7 @@

    Returns
    -_fit_predict_cpu(X, y=None)
    +_fit_predict_cpu(X, y=None)[source]

    Performs clustering on X and returns cluster labels using only CPU.

    Parameters

    @@ -865,7 +1064,7 @@

    Returns
    -_fit_predict_gpu(X, y=None)
    +_fit_predict_gpu(X, y=None)[source]

    Performs clustering on X and returns cluster labels using only GPU (from CuML).

    @@ -890,7 +1089,7 @@

    Returns
    -class dasf.ml.cluster.KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='full', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs)
    +class dasf.ml.cluster.KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='lloyd', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    K-Means clustering.

    Read more in the User Guide.

    @@ -955,13 +1154,11 @@

    Parameters

    init_max_iterint, default=None

    Number of iterations for init step.

    -
    algorithm{“auto”, “full”, “elkan”}, default=”full”

    K-means algorithm to use. The classical EM-style algorithm is “full”. -The “elkan” variation is more efficient on data with well-defined -clusters, by using the triangle inequality. However it’s more memory -intensive due to the allocation of an extra array of shape -(n_samples, n_clusters).

    -

    For now “auto” (kept for backward compatibiliy) chooses “elkan” but it -might change in the future for a better heuristic.

    +
    algorithm{“lloyd”, “elkan”}, default=”lloyd”

    K-means algorithm to use. The classical EM-style algorithm is “lloyd”. +The “elkan” variation can be more efficient on some datasets with +well-defined clusters, by using the triangle inequality. However +it’s more memory intensive due to the allocation of an extra array of +shape (n_samples, n_clusters).

    Changed in version 0.18: Added Elkan algorithm

    @@ -1028,10 +1225,95 @@

    Examples< - https://ml.dask.org/modules/generated/dask_ml.cluster.KMeans.html - https://docs.rapids.ai/api/cuml/stable/api.html#k-means-clustering - https://docs.rapids.ai/api/cuml/stable/api.html#cuml.dask.cluster.KMeans

    -

    A generic constructor method.

    +

    Constructor of the class KMeans.

    +
    +
    +n_clusters
    +
    + +
    +
    +random_state
    +
    + +
    +
    +max_iter
    +
    + +
    +
    +init
    +
    + +
    +
    +n_init
    +
    + +
    +
    +tol
    +
    + +
    +
    +verbose
    +
    + +
    +
    +copy_x
    +
    + +
    +
    +algorithm
    +
    + +
    +
    +oversampling_factor
    +
    + +
    +
    +n_jobs
    +
    + +
    +
    +init_max_iter
    +
    + +
    +
    +max_samples_per_batch
    +
    + +
    +
    +precompute_distances
    +
    + +
    +
    +output_type
    +
    + +
    +
    +__kmeans_cpu
    +
    + +
    +
    +__kmeans_mcpu
    +
    +
    -_lazy_fit_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_cpu(X, y=None, sample_weight=None)[source]

    Compute Dask k-means clustering.

    Parameters

    @@ -1059,7 +1341,7 @@

    Returns
    -_lazy_fit_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_gpu(X, y=None, sample_weight=None)[source]

    Compute Dask CuML k-means clustering.

    Parameters

    @@ -1088,7 +1370,7 @@

    Returns
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Compute Scikit Learn k-means clustering.

    Parameters

    @@ -1117,7 +1399,7 @@

    Returns
    -_fit_gpu(X, y=None, sample_weight=None)
    +_fit_gpu(X, y=None, sample_weight=None)[source]

    Compute CuML k-means clustering.

    Parameters

    @@ -1146,7 +1428,7 @@

    Returns
    -_lazy_fit_predict_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using Dask ML.

    Convenience method; equivalent to calling fit(X) followed by @@ -1173,7 +1455,7 @@

    Returns
    -_lazy_fit_predict_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using Dask CuML.

    Convenience method; equivalent to calling fit(X) followed by @@ -1201,7 +1483,7 @@

    Returns
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using Scikit Learn.

    Convenience method; equivalent to calling fit(X) followed by @@ -1228,7 +1510,7 @@

    Returns
    -_fit_predict_gpu(X, y=None, sample_weight=None)
    +_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using CuML.

    Convenience method; equivalent to calling fit(X) followed by @@ -1256,7 +1538,7 @@

    Returns
    -_lazy_predict_cpu(X, sample_weight=None)
    +_lazy_predict_cpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using Dask ML.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -1281,7 +1563,7 @@

    Returns
    -_lazy_predict_gpu(X, sample_weight=None)
    +_lazy_predict_gpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using Dask CuML.

    In the vector quantization literature, cluster_centers_ is called @@ -1308,7 +1590,7 @@

    Returns
    -_predict_cpu(X, sample_weight=None)
    +_predict_cpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using Scikit Learn.

    In the vector quantization literature, cluster_centers_ is called @@ -1335,7 +1617,7 @@

    Returns
    -_predict_gpu(X, sample_weight=None)
    +_predict_gpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using CuML.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -1361,7 +1643,7 @@

    Returns
    -_lazy_predict2_cpu(X, sample_weight=None)
    +_lazy_predict2_cpu(X, sample_weight=None)[source]

    A block predict using Scikit Learn variant but for Dask.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -1387,7 +1669,7 @@

    Returns
    -_lazy_predict2_gpu(X, sample_weight=None)
    +_lazy_predict2_gpu(X, sample_weight=None)[source]

    A block predict using CuML variant but for Dask.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -1413,7 +1695,7 @@

    Returns
    -_predict2_cpu(X, sample_weight=None, compat=True)
    +_predict2_cpu(X, sample_weight=None, compat=True)[source]

    A block predict using Scikit Learn variant as a placeholder.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -1443,7 +1725,7 @@

    Returns
    -_predict2_gpu(X, sample_weight=None, compat=True)
    +_predict2_gpu(X, sample_weight=None, compat=True)[source]

    A block predict using CuML variant as a placeholder.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -1473,7 +1755,7 @@

    Returns
    -predict2(sample_weight=None)
    +predict2(sample_weight=None)[source]

    Generic predict2 funtion according executor (for some ML methods only).

    @@ -1482,7 +1764,7 @@

    Returns
    -class dasf.ml.cluster.SOM(x, y, input_len, num_epochs=100, sigma=0, sigmaN=1, learning_rate=0.5, learning_rateN=0.01, decay_function='exponential', neighborhood_function='gaussian', std_coeff=0.5, topology='rectangular', activation_distance='euclidean', random_seed=None, n_parallel=0, compact_support=False, **kwargs)
    +class dasf.ml.cluster.SOM(x, y, input_len, num_epochs=100, sigma=0, sigmaN=1, learning_rate=0.5, learning_rateN=0.01, decay_function='exponential', neighborhood_function='gaussian', std_coeff=0.5, topology='rectangular', activation_distance='euclidean', random_seed=None, n_parallel=0, compact_support=False, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Initializes a Self Organizing Maps.

    A rule of thumb to set the size of the grid for a dimensionality @@ -1548,10 +1830,100 @@

    Examples< SOM(x=3, y=2, input_len=2, num_epochs=100)

    -

    A generic constructor method.

    +

    Constructor of the class SOM.

    +
    +
    +x
    +
    + +
    +
    +y
    +
    + +
    +
    +input_len
    +
    + +
    +
    +num_epochs
    +
    + +
    +
    +sigma
    +
    + +
    +
    +sigmaN
    +
    + +
    +
    +learning_rate
    +
    + +
    +
    +learning_rateN
    +
    + +
    +
    +decay_function
    +
    + +
    +
    +neighborhood_function
    +
    + +
    +
    +std_coeff
    +
    + +
    +
    +topology
    +
    + +
    +
    +activation_distance
    +
    + +
    +
    +random_seed
    +
    + +
    +
    +n_parallel
    +
    + +
    +
    +compact_support
    +
    + +
    +
    +__som_cpu
    +
    + +
    +
    +__som_mcpu
    +
    +
    -_lazy_fit_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using Dask with CPUs only.

    Parameters

    @@ -1573,7 +1945,7 @@

    Returns
    -_lazy_fit_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using Dask with GPUs only.

    Parameters

    @@ -1595,7 +1967,7 @@

    Returns
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using CPU only.

    Parameters

    @@ -1617,7 +1989,7 @@

    Returns
    -_fit_gpu(X, y=None, sample_weight=None)
    +_fit_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using GPU only.

    Parameters

    @@ -1639,7 +2011,7 @@

    Returns
    -_lazy_fit_predict_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using Dask with CPUs only.

    @@ -1665,7 +2037,7 @@

    Returns
    -_lazy_fit_predict_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using Dask with GPUs only.

    @@ -1691,7 +2063,7 @@

    Returns
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using CPU only.

    Parameters

    @@ -1716,7 +2088,7 @@

    Returns
    -_fit_predict_gpu(X, y=None, sample_weight=None)
    +_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using GPU only.

    Parameters

    @@ -1741,7 +2113,7 @@

    Returns
    -_lazy_predict_cpu(X, sample_weight=None)
    +_lazy_predict_cpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using Dask with CPUs only.

    Parameters

    @@ -1763,7 +2135,7 @@

    Returns
    -_lazy_predict_gpu(X, sample_weight=None)
    +_lazy_predict_gpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using Dask with GPUs only.

    Parameters

    @@ -1785,7 +2157,7 @@

    Returns
    -_predict_cpu(X, sample_weight=None)
    +_predict_cpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using CPU only.

    Parameters

    @@ -1807,7 +2179,7 @@

    Returns
    -_predict_gpu(X, sample_weight=None)
    +_predict_gpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using GPU only.

    Parameters

    @@ -1829,7 +2201,7 @@

    Returns<
    -_lazy_quantization_error_cpu(X)
    +_lazy_quantization_error_cpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using Dask with CPUs only.

    @@ -1848,7 +2220,7 @@

    Returns<
    -_lazy_quantization_error_gpu(X)
    +_lazy_quantization_error_gpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using Dask with GPUs only.

    @@ -1867,7 +2239,7 @@

    Returns<
    -_quantization_error_cpu(X)
    +_quantization_error_cpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using CPU only.

    @@ -1885,7 +2257,7 @@

    Returns<
    -_quantization_error_gpu(X)
    +_quantization_error_gpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using GPU only.

    @@ -1903,7 +2275,7 @@

    Returns<
    -quantization_error(X)
    +quantization_error(X)[source]

    Generic quantization_error funtion according executor (for SOM method only).

    @@ -1913,7 +2285,7 @@

    Returns<
    -class dasf.ml.cluster.SpectralClustering(n_clusters=8, eigen_solver=None, random_state=None, n_init=10, gamma=1.0, affinity='rbf', n_neighbors=10, eigen_tol=0.0, assign_labels='kmeans', degree=3, coef0=1, kernel_params=None, n_jobs=None, n_components=None, persist_embedding=False, kmeans_params=None, verbose=False, **kwargs)
    +class dasf.ml.cluster.SpectralClustering(n_clusters=8, eigen_solver=None, random_state=None, n_init=10, gamma=1.0, affinity='rbf', n_neighbors=10, eigen_tol=0.0, assign_labels='kmeans', degree=3, coef0=1, kernel_params=None, n_jobs=None, n_components=None, persist_embedding=False, kmeans_params=None, verbose=False, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Apply clustering to a projection of the normalized Laplacian.

    In practice Spectral Clustering is very useful when the structure of @@ -2066,10 +2438,105 @@

    References Stella X. Yu, Jianbo Shi https://www1.icsi.berkeley.edu/~stellayu/publication/doc/2003kwayICCV.pdf

    -

    A generic constructor method.

    +

    Constructor of the class SpectralClustering.

    +
    +
    +n_clusters
    +
    + +
    +
    +eigen_solver
    +
    + +
    +
    +random_state
    +
    + +
    +
    +n_init
    +
    + +
    +
    +gamma
    +
    + +
    +
    +affinity
    +
    + +
    +
    +n_neighbors
    +
    + +
    +
    +eigen_tol
    +
    + +
    +
    +assign_labels
    +
    + +
    +
    +degree
    +
    + +
    +
    +coef0
    +
    + +
    +
    +kernel_params
    +
    + +
    +
    +n_jobs
    +
    + +
    +
    +n_components
    +
    + +
    +
    +persist_embedding
    +
    + +
    +
    +kmeans_params
    +
    + +
    +
    +verbose
    +
    + +
    +
    +__sc_cpu
    +
    + +
    +
    +__sc_mcpu
    +
    +
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Perform spectral clustering from features, or affinity matrix using CPU only.

    @@ -2097,7 +2564,7 @@

    Returns<
    -_lazy_fit_predict_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Perform spectral clustering on X and return cluster labels using Dask with CPU only.

    @@ -2125,7 +2592,7 @@

    Returns<
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Perform spectral clustering on X and return cluster labels using CPU only.

    diff --git a/docs/autoapi/dasf/ml/cluster/kmeans/index.html b/docs/autoapi/dasf/ml/cluster/kmeans/index.html index 8be27be..b3cbfb6 100644 --- a/docs/autoapi/dasf/ml/cluster/kmeans/index.html +++ b/docs/autoapi/dasf/ml/cluster/kmeans/index.html @@ -118,7 +118,7 @@

    Classes

    Module Contents

    -class dasf.ml.cluster.kmeans.KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='full', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs)
    +class dasf.ml.cluster.kmeans.KMeans(n_clusters=8, init=None, n_init=None, max_iter=300, tol=0.0001, verbose=0, random_state=None, copy_x=True, algorithm='lloyd', oversampling_factor=2.0, n_jobs=1, init_max_iter=None, max_samples_per_batch=32768, precompute_distances='auto', output_type=None, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    K-Means clustering.

    Read more in the User Guide.

    @@ -183,13 +183,11 @@

    Parametersint, default=None

    Number of iterations for init step.

    -
    algorithm{“auto”, “full”, “elkan”}, default=”full”

    K-means algorithm to use. The classical EM-style algorithm is “full”. -The “elkan” variation is more efficient on data with well-defined -clusters, by using the triangle inequality. However it’s more memory -intensive due to the allocation of an extra array of shape -(n_samples, n_clusters).

    -

    For now “auto” (kept for backward compatibiliy) chooses “elkan” but it -might change in the future for a better heuristic.

    +
    algorithm{“lloyd”, “elkan”}, default=”lloyd”

    K-means algorithm to use. The classical EM-style algorithm is “lloyd”. +The “elkan” variation can be more efficient on some datasets with +well-defined clusters, by using the triangle inequality. However +it’s more memory intensive due to the allocation of an extra array of +shape (n_samples, n_clusters).

    Changed in version 0.18: Added Elkan algorithm

    @@ -256,10 +254,95 @@

    Examples - https://ml.dask.org/modules/generated/dask_ml.cluster.KMeans.html - https://docs.rapids.ai/api/cuml/stable/api.html#k-means-clustering - https://docs.rapids.ai/api/cuml/stable/api.html#cuml.dask.cluster.KMeans

    -

    A generic constructor method.

    +

    Constructor of the class KMeans.

    +
    +
    +n_clusters
    +
    + +
    +
    +random_state
    +
    + +
    +
    +max_iter
    +
    + +
    +
    +init
    +
    + +
    +
    +n_init
    +
    + +
    +
    +tol
    +
    + +
    +
    +verbose
    +
    + +
    +
    +copy_x
    +
    + +
    +
    +algorithm
    +
    + +
    +
    +oversampling_factor
    +
    + +
    +
    +n_jobs
    +
    + +
    +
    +init_max_iter
    +
    + +
    +
    +max_samples_per_batch
    +
    + +
    +
    +precompute_distances
    +
    + +
    +
    +output_type
    +
    + +
    +
    +__kmeans_cpu
    +
    + +
    +
    +__kmeans_mcpu
    +
    +
    -_lazy_fit_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_cpu(X, y=None, sample_weight=None)[source]

    Compute Dask k-means clustering.

    Parameters

    @@ -287,7 +370,7 @@

    Returns
    -_lazy_fit_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_gpu(X, y=None, sample_weight=None)[source]

    Compute Dask CuML k-means clustering.

    Parameters

    @@ -316,7 +399,7 @@

    Returns
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Compute Scikit Learn k-means clustering.

    Parameters

    @@ -345,7 +428,7 @@

    Returns
    -_fit_gpu(X, y=None, sample_weight=None)
    +_fit_gpu(X, y=None, sample_weight=None)[source]

    Compute CuML k-means clustering.

    Parameters

    @@ -374,7 +457,7 @@

    Returns
    -_lazy_fit_predict_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using Dask ML.

    Convenience method; equivalent to calling fit(X) followed by @@ -401,7 +484,7 @@

    Returns
    -_lazy_fit_predict_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using Dask CuML.

    Convenience method; equivalent to calling fit(X) followed by @@ -429,7 +512,7 @@

    Returns
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using Scikit Learn.

    Convenience method; equivalent to calling fit(X) followed by @@ -456,7 +539,7 @@

    Returns
    -_fit_predict_gpu(X, y=None, sample_weight=None)
    +_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Compute cluster centers and predict cluster index for each sample using CuML.

    Convenience method; equivalent to calling fit(X) followed by @@ -484,7 +567,7 @@

    Returns
    -_lazy_predict_cpu(X, sample_weight=None)
    +_lazy_predict_cpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using Dask ML.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -509,7 +592,7 @@

    Returns
    -_lazy_predict_gpu(X, sample_weight=None)
    +_lazy_predict_gpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using Dask CuML.

    In the vector quantization literature, cluster_centers_ is called @@ -536,7 +619,7 @@

    Returns
    -_predict_cpu(X, sample_weight=None)
    +_predict_cpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using Scikit Learn.

    In the vector quantization literature, cluster_centers_ is called @@ -563,7 +646,7 @@

    Returns
    -_predict_gpu(X, sample_weight=None)
    +_predict_gpu(X, sample_weight=None)[source]

    Predict the closest cluster each sample in X belongs to using CuML.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -589,7 +672,7 @@

    Returns
    -_lazy_predict2_cpu(X, sample_weight=None)
    +_lazy_predict2_cpu(X, sample_weight=None)[source]

    A block predict using Scikit Learn variant but for Dask.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -615,7 +698,7 @@

    Returns
    -_lazy_predict2_gpu(X, sample_weight=None)
    +_lazy_predict2_gpu(X, sample_weight=None)[source]

    A block predict using CuML variant but for Dask.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -641,7 +724,7 @@

    Returns
    -_predict2_cpu(X, sample_weight=None, compat=True)
    +_predict2_cpu(X, sample_weight=None, compat=True)[source]

    A block predict using Scikit Learn variant as a placeholder.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -671,7 +754,7 @@

    Returns
    -_predict2_gpu(X, sample_weight=None, compat=True)
    +_predict2_gpu(X, sample_weight=None, compat=True)[source]

    A block predict using CuML variant as a placeholder.

    In the vector quantization literature, cluster_centers_ is called the code book and each value returned by predict is the index of @@ -701,7 +784,7 @@

    Returns
    -predict2(sample_weight=None)
    +predict2(sample_weight=None)[source]

    Generic predict2 funtion according executor (for some ML methods only).

    diff --git a/docs/autoapi/dasf/ml/cluster/som/index.html b/docs/autoapi/dasf/ml/cluster/som/index.html index caf9aee..7b4c7e8 100644 --- a/docs/autoapi/dasf/ml/cluster/som/index.html +++ b/docs/autoapi/dasf/ml/cluster/som/index.html @@ -118,7 +118,7 @@

    Classes

    Module Contents

    -class dasf.ml.cluster.som.SOM(x, y, input_len, num_epochs=100, sigma=0, sigmaN=1, learning_rate=0.5, learning_rateN=0.01, decay_function='exponential', neighborhood_function='gaussian', std_coeff=0.5, topology='rectangular', activation_distance='euclidean', random_seed=None, n_parallel=0, compact_support=False, **kwargs)
    +class dasf.ml.cluster.som.SOM(x, y, input_len, num_epochs=100, sigma=0, sigmaN=1, learning_rate=0.5, learning_rateN=0.01, decay_function='exponential', neighborhood_function='gaussian', std_coeff=0.5, topology='rectangular', activation_distance='euclidean', random_seed=None, n_parallel=0, compact_support=False, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Initializes a Self Organizing Maps.

    A rule of thumb to set the size of the grid for a dimensionality @@ -184,10 +184,100 @@

    Examples SOM(x=3, y=2, input_len=2, num_epochs=100)

    -

    A generic constructor method.

    +

    Constructor of the class SOM.

    +
    +
    +x
    +
    + +
    +
    +y
    +
    + +
    +
    +input_len
    +
    + +
    +
    +num_epochs
    +
    + +
    +
    +sigma
    +
    + +
    +
    +sigmaN
    +
    + +
    +
    +learning_rate
    +
    + +
    +
    +learning_rateN
    +
    + +
    +
    +decay_function
    +
    + +
    +
    +neighborhood_function
    +
    + +
    +
    +std_coeff
    +
    + +
    +
    +topology
    +
    + +
    +
    +activation_distance
    +
    + +
    +
    +random_seed
    +
    + +
    +
    +n_parallel
    +
    + +
    +
    +compact_support
    +
    + +
    +
    +__som_cpu
    +
    + +
    +
    +__som_mcpu
    +
    +
    -_lazy_fit_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using Dask with CPUs only.

    Parameters

    @@ -209,7 +299,7 @@

    Returns
    -_lazy_fit_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using Dask with GPUs only.

    Parameters

    @@ -231,7 +321,7 @@

    Returns
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using CPU only.

    Parameters

    @@ -253,7 +343,7 @@

    Returns
    -_fit_gpu(X, y=None, sample_weight=None)
    +_fit_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM method using GPU only.

    Parameters

    @@ -275,7 +365,7 @@

    Returns
    -_lazy_fit_predict_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using Dask with CPUs only.

    @@ -301,7 +391,7 @@

    Returns
    -_lazy_fit_predict_gpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using Dask with GPUs only.

    @@ -327,7 +417,7 @@

    Returns
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using CPU only.

    Parameters

    @@ -352,7 +442,7 @@

    Returns
    -_fit_predict_gpu(X, y=None, sample_weight=None)
    +_fit_predict_gpu(X, y=None, sample_weight=None)[source]

    Fit SOM and select the winner neurons for the input using GPU only.

    Parameters

    @@ -377,7 +467,7 @@

    Returns
    -_lazy_predict_cpu(X, sample_weight=None)
    +_lazy_predict_cpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using Dask with CPUs only.

    Parameters

    @@ -399,7 +489,7 @@

    Returns
    -_lazy_predict_gpu(X, sample_weight=None)
    +_lazy_predict_gpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using Dask with GPUs only.

    Parameters

    @@ -421,7 +511,7 @@

    Returns
    -_predict_cpu(X, sample_weight=None)
    +_predict_cpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using CPU only.

    Parameters

    @@ -443,7 +533,7 @@

    Returns
    -_predict_gpu(X, sample_weight=None)
    +_predict_gpu(X, sample_weight=None)[source]

    Predict the input using a fitted SOM using GPU only.

    Parameters

    @@ -465,7 +555,7 @@

    Returns
    -_lazy_quantization_error_cpu(X)
    +_lazy_quantization_error_cpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using Dask with CPUs only.

    @@ -484,7 +574,7 @@

    Returns
    -_lazy_quantization_error_gpu(X)
    +_lazy_quantization_error_gpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using Dask with GPUs only.

    @@ -503,7 +593,7 @@

    Returns
    -_quantization_error_cpu(X)
    +_quantization_error_cpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using CPU only.

    @@ -521,7 +611,7 @@

    Returns
    -_quantization_error_gpu(X)
    +_quantization_error_gpu(X)[source]

    Returns the quantization error computed as the average distance between each input sample and its best matching unit using GPU only.

    @@ -539,7 +629,7 @@

    Returns
    -quantization_error(X)
    +quantization_error(X)[source]

    Generic quantization_error funtion according executor (for SOM method only).

    diff --git a/docs/autoapi/dasf/ml/cluster/spectral/index.html b/docs/autoapi/dasf/ml/cluster/spectral/index.html index 0ba8c31..8af29cd 100644 --- a/docs/autoapi/dasf/ml/cluster/spectral/index.html +++ b/docs/autoapi/dasf/ml/cluster/spectral/index.html @@ -118,7 +118,7 @@

    Classes

    Module Contents

    -class dasf.ml.cluster.spectral.SpectralClustering(n_clusters=8, eigen_solver=None, random_state=None, n_init=10, gamma=1.0, affinity='rbf', n_neighbors=10, eigen_tol=0.0, assign_labels='kmeans', degree=3, coef0=1, kernel_params=None, n_jobs=None, n_components=None, persist_embedding=False, kmeans_params=None, verbose=False, **kwargs)
    +class dasf.ml.cluster.spectral.SpectralClustering(n_clusters=8, eigen_solver=None, random_state=None, n_init=10, gamma=1.0, affinity='rbf', n_neighbors=10, eigen_tol=0.0, assign_labels='kmeans', degree=3, coef0=1, kernel_params=None, n_jobs=None, n_components=None, persist_embedding=False, kmeans_params=None, verbose=False, **kwargs)[source]

    Bases: dasf.ml.cluster.classifier.ClusterClassifier

    Apply clustering to a projection of the normalized Laplacian.

    In practice Spectral Clustering is very useful when the structure of @@ -271,10 +271,105 @@

    Referenceshttps://www1.icsi.berkeley.edu/~stellayu/publication/doc/2003kwayICCV.pdf

    -

    A generic constructor method.

    +

    Constructor of the class SpectralClustering.

    +
    +
    +n_clusters
    +
    + +
    +
    +eigen_solver
    +
    + +
    +
    +random_state
    +
    + +
    +
    +n_init
    +
    + +
    +
    +gamma
    +
    + +
    +
    +affinity
    +
    + +
    +
    +n_neighbors
    +
    + +
    +
    +eigen_tol
    +
    + +
    +
    +assign_labels
    +
    + +
    +
    +degree
    +
    + +
    +
    +coef0
    +
    + +
    +
    +kernel_params
    +
    + +
    +
    +n_jobs
    +
    + +
    +
    +n_components
    +
    + +
    +
    +persist_embedding
    +
    + +
    +
    +kmeans_params
    +
    + +
    +
    +verbose
    +
    + +
    +
    +__sc_cpu
    +
    + +
    +
    +__sc_mcpu
    +
    +
    -_fit_cpu(X, y=None, sample_weight=None)
    +_fit_cpu(X, y=None, sample_weight=None)[source]

    Perform spectral clustering from features, or affinity matrix using CPU only.

    @@ -302,7 +397,7 @@

    Returns
    -_lazy_fit_predict_cpu(X, y=None, sample_weight=None)
    +_lazy_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Perform spectral clustering on X and return cluster labels using Dask with CPU only.

    @@ -330,7 +425,7 @@

    Returns
    -_fit_predict_cpu(X, y=None, sample_weight=None)
    +_fit_predict_cpu(X, y=None, sample_weight=None)[source]

    Perform spectral clustering on X and return cluster labels using CPU only.

    diff --git a/docs/autoapi/dasf/ml/decomposition/index.html b/docs/autoapi/dasf/ml/decomposition/index.html index fe32348..29258ce 100644 --- a/docs/autoapi/dasf/ml/decomposition/index.html +++ b/docs/autoapi/dasf/ml/decomposition/index.html @@ -372,6 +372,17 @@

    Examples [6.30061...]

    +

    Constructor of the class PCA.

    +
    +
    +__pca_cpu
    +
    + +
    +
    +__pca_mcpu
    +
    +
    _lazy_fit_cpu(X, y=None, sample_weights=None)[source]
    diff --git a/docs/autoapi/dasf/ml/decomposition/pca/index.html b/docs/autoapi/dasf/ml/decomposition/pca/index.html index 26215b3..b03f135 100644 --- a/docs/autoapi/dasf/ml/decomposition/pca/index.html +++ b/docs/autoapi/dasf/ml/decomposition/pca/index.html @@ -365,6 +365,17 @@

    Examples [6.30061...]

    +

    Constructor of the class PCA.

    +
    +
    +__pca_cpu
    +
    + +
    +
    +__pca_mcpu
    +
    +
    _lazy_fit_cpu(X, y=None, sample_weights=None)[source]
    diff --git a/docs/autoapi/dasf/ml/dl/clusters/dask/index.html b/docs/autoapi/dasf/ml/dl/clusters/dask/index.html index 224f4c6..9c68dbd 100644 --- a/docs/autoapi/dasf/ml/dl/clusters/dask/index.html +++ b/docs/autoapi/dasf/ml/dl/clusters/dask/index.html @@ -119,7 +119,7 @@

    Classes

    Module Contents

    -class dasf.ml.dl.clusters.dask.DaskClusterEnvironment(metadata=None)
    +class dasf.ml.dl.clusters.dask.DaskClusterEnvironment(metadata=None)[source]

    Bases: pytorch_lightning.plugins.environments.ClusterEnvironment

    Create a Dask Cluster environment for workers

    @@ -129,9 +129,14 @@

    Parameters +
    +_master_port = 23456
    +

    +
    -detect()
    +detect()[source]

    Detect if important data are present into metadata dictionary.

    Returns

    @@ -180,7 +185,7 @@

    Returns
    -creates_children()
    +creates_children()[source]

    Fork children when generate a cluster.

    Return type:
    @@ -191,7 +196,7 @@

    Returns
    -world_size()
    +world_size()[source]

    Return worker world size.

    Return type:
    @@ -202,7 +207,7 @@

    Returns
    -global_rank()
    +global_rank()[source]

    Return worker global rank.

    Return type:
    @@ -213,7 +218,7 @@

    Returns
    -local_rank()
    +local_rank()[source]

    Return worker local rank.

    Return type:
    @@ -224,7 +229,7 @@

    Returns
    -node_rank()
    +node_rank()[source]

    Return worker node rank (which is similar to global rank).

    Return type:
    @@ -235,7 +240,7 @@

    Returns
    -set_world_size(size)
    +set_world_size(size)[source]

    Set the index of the world size.

    Parameters

    @@ -256,7 +261,7 @@

    Parameters
    -set_global_rank(rank)
    +set_global_rank(rank)[source]

    Set the index of the global rank.

    Parameters

    diff --git a/docs/autoapi/dasf/ml/dl/clusters/index.html b/docs/autoapi/dasf/ml/dl/clusters/index.html index 1f06f1c..5b2b675 100644 --- a/docs/autoapi/dasf/ml/dl/clusters/index.html +++ b/docs/autoapi/dasf/ml/dl/clusters/index.html @@ -125,7 +125,7 @@

    Classes

    Package Contents

    -class dasf.ml.dl.clusters.DaskClusterEnvironment(metadata=None)
    +class dasf.ml.dl.clusters.DaskClusterEnvironment(metadata=None)[source]

    Bases: pytorch_lightning.plugins.environments.ClusterEnvironment

    Create a Dask Cluster environment for workers

    @@ -135,9 +135,14 @@

    Parameters +
    +_master_port = 23456
    +

    +
    -detect()
    +detect()[source]

    Detect if important data are present into metadata dictionary.

    Returns

    @@ -186,7 +191,7 @@

    Returns
    -creates_children()
    +creates_children()[source]

    Fork children when generate a cluster.

    Return type:
    @@ -197,7 +202,7 @@

    Returns
    -world_size()
    +world_size()[source]

    Return worker world size.

    Return type:
    @@ -208,7 +213,7 @@

    Returns
    -global_rank()
    +global_rank()[source]

    Return worker global rank.

    Return type:
    @@ -219,7 +224,7 @@

    Returns
    -local_rank()
    +local_rank()[source]

    Return worker local rank.

    Return type:
    @@ -230,7 +235,7 @@

    Returns
    -node_rank()
    +node_rank()[source]

    Return worker node rank (which is similar to global rank).

    Return type:
    @@ -241,7 +246,7 @@

    Returns
    -set_world_size(size)
    +set_world_size(size)[source]

    Set the index of the world size.

    Parameters

    @@ -262,7 +267,7 @@

    Parameters
    -set_global_rank(rank)
    +set_global_rank(rank)[source]

    Set the index of the global rank.

    Parameters

    diff --git a/docs/autoapi/dasf/ml/dl/index.html b/docs/autoapi/dasf/ml/dl/index.html index 8bce695..160bce6 100644 --- a/docs/autoapi/dasf/ml/dl/index.html +++ b/docs/autoapi/dasf/ml/dl/index.html @@ -102,6 +102,7 @@

    dasf.ml.dl

    +

    Init module for Deep Learning algorithms.

    Subpackages

    @@ -137,7 +138,7 @@

    Classes

    Package Contents

    -class dasf.ml.dl.LightningTrainer(model, use_gpu=False, batch_size=1, max_epochs=1, limit_train_batches=None, limit_val_batches=None, devices='auto', num_nodes=1, shuffle=True, strategy='ddp', unsqueeze_dim=None)
    +class dasf.ml.dl.LightningTrainer(model, use_gpu=False, batch_size=1, max_epochs=1, limit_train_batches=None, limit_val_batches=None, devices='auto', num_nodes=1, shuffle=True, strategy='ddp', unsqueeze_dim=None)[source]

    Initialize the LightningFit class.

    Parameters

    @@ -165,9 +166,64 @@

    Parametersint, optional

    The dimension to unsqueeze the input data, by default None.

    +
    +
    +model
    +
    + +
    +
    +accelerator
    +
    + +
    +
    +batch_size
    +
    + +
    +
    +max_epochs
    +
    + +
    +
    +limit_train_batches
    +
    + +
    +
    +limit_val_batches
    +
    + +
    +
    +devices
    +
    + +
    +
    +num_nodes
    +
    + +
    +
    +shuffle
    +
    + +
    +
    +strategy
    +
    + +
    +
    +unsqueeze_dim
    +
    +
    -fit(train_data, val_data=None)
    +fit(train_data, val_data=None)[source]

    Perform the training of the model using torch Lightning.

    Parameters

    @@ -190,34 +246,33 @@

    Parameters
    -_fit(train_data, val_data=None)
    +_fit(train_data, val_data=None)[source]
    -_lazy_fit_cpu(train_data, val_data=None)
    +_lazy_fit_cpu(train_data, val_data=None)[source]
    -_lazy_fit_gpu(train_data, val_data=None)
    +_lazy_fit_gpu(train_data, val_data=None)[source]
    -_fit_cpu(train_data, val_data=None)
    +_fit_cpu(train_data, val_data=None)[source]
    -_fit_gpu(train_data, val_data=None)
    +_fit_gpu(train_data, val_data=None)[source]

    Parameters:
      -
    • model (lightning.LightningModule)

    • use_gpu (bool)

    • batch_size (int)

    • max_epochs (int)

    • @@ -235,23 +290,68 @@

      Parameters
      -class dasf.ml.dl.NeuralNetClassifier(model, max_iter=100, batch_size=32)
      +class dasf.ml.dl.NeuralNetClassifier(model, max_iter=100, batch_size=32)[source]

      Bases: dasf.transforms.base.Fit

      Class representing a Fit operation of the pipeline.

      +
      +
      +_model
      +
      + +
      +
      +_accel = None
      +
      + +
      +
      +_strategy = None
      +
      + +
      +
      +_max_iter
      +
      + +
      +
      +_devices = 0
      +
      + +
      +
      +_ngpus = 0
      +
      + +
      +
      +_batch_size
      +
      + +
      +
      +__trainer = False
      +
      + +
      +
      +__handler
      +
      +
      -_lazy_fit_generic(X, y, accel, ngpus)
      +_lazy_fit_generic(X, y, accel, ngpus)[source]
      -_lazy_fit_gpu(X, y=None)
      +_lazy_fit_gpu(X, y=None)[source]

      Respective lazy fit mocked function for GPUs.

      -_lazy_fit_cpu(X, y=None)
      +_lazy_fit_cpu(X, y=None)[source]

      Respective lazy fit mocked function for CPUs.

      @@ -262,13 +362,13 @@

      Parameters
      -_fit_gpu(X, y=None)
      +_fit_gpu(X, y=None)[source]

      Respective immediate fit mocked function for local GPU(s).

      -_fit_cpu(X, y=None)
      +_fit_cpu(X, y=None)[source]

      Respective immediate fit mocked function for local CPU(s).

      diff --git a/docs/autoapi/dasf/ml/dl/lightning_fit/index.html b/docs/autoapi/dasf/ml/dl/lightning_fit/index.html index a018315..2611e6b 100644 --- a/docs/autoapi/dasf/ml/dl/lightning_fit/index.html +++ b/docs/autoapi/dasf/ml/dl/lightning_fit/index.html @@ -120,7 +120,7 @@

      Classes

      Module Contents

      -class dasf.ml.dl.lightning_fit.LazyDatasetComputer(dataset, unsqueeze_dim=None)
      +class dasf.ml.dl.lightning_fit.LazyDatasetComputer(dataset, unsqueeze_dim=None)[source]

      This class encapsulates a map-style dataset that returns a Dask or GPU array. The __getitem__ method will compute the dask array before returning it. Thus, we can wrap this class into a DataLoader to make it compatible @@ -135,14 +135,24 @@

      Parametersint, optional

      The dimension to be unsqueezed in the output, by default None

      +
      +
      +dataset
      +
      + +
      +
      +unsqueeze_dim
      +
      +
      -__len__()
      +__len__()[source]
      -__getitem__(index)
      +__getitem__(index)[source]

      Compute the dask array and return it.

      Parameters

      @@ -181,7 +191,7 @@

      Returns
      -class dasf.ml.dl.lightning_fit.LightningTrainer(model, use_gpu=False, batch_size=1, max_epochs=1, limit_train_batches=None, limit_val_batches=None, devices='auto', num_nodes=1, shuffle=True, strategy='ddp', unsqueeze_dim=None)
      +class dasf.ml.dl.lightning_fit.LightningTrainer(model, use_gpu=False, batch_size=1, max_epochs=1, limit_train_batches=None, limit_val_batches=None, devices='auto', num_nodes=1, shuffle=True, strategy='ddp', unsqueeze_dim=None)[source]

      Initialize the LightningFit class.

      Parameters

      @@ -209,9 +219,64 @@

      Parameters
      unsqueeze_dimint, optional

      The dimension to unsqueeze the input data, by default None.

      +
      +
      +model
      +
      + +
      +
      +accelerator
      +
      + +
      +
      +batch_size
      +
      + +
      +
      +max_epochs
      +
      + +
      +
      +limit_train_batches
      +
      + +
      +
      +limit_val_batches
      +
      + +
      +
      +devices
      +
      + +
      +
      +num_nodes
      +
      + +
      +
      +shuffle
      +
      + +
      +
      +strategy
      +
      + +
      +
      +unsqueeze_dim
      +
      +
      -fit(train_data, val_data=None)
      +fit(train_data, val_data=None)[source]

      Perform the training of the model using torch Lightning.

      Parameters

      @@ -234,34 +299,33 @@

      Parameters
      -_fit(train_data, val_data=None)
      +_fit(train_data, val_data=None)[source]
      -_lazy_fit_cpu(train_data, val_data=None)
      +_lazy_fit_cpu(train_data, val_data=None)[source]
      -_lazy_fit_gpu(train_data, val_data=None)
      +_lazy_fit_gpu(train_data, val_data=None)[source]
      -_fit_cpu(train_data, val_data=None)
      +_fit_cpu(train_data, val_data=None)[source]
      -_fit_gpu(train_data, val_data=None)
      +_fit_gpu(train_data, val_data=None)[source]

      Parameters:
        -
      • model (lightning.LightningModule)

      • use_gpu (bool)

      • batch_size (int)

      • max_epochs (int)

      • diff --git a/docs/autoapi/dasf/ml/dl/models/devconvnet/index.html b/docs/autoapi/dasf/ml/dl/models/devconvnet/index.html index e5a10be..7110bfc 100644 --- a/docs/autoapi/dasf/ml/dl/models/devconvnet/index.html +++ b/docs/autoapi/dasf/ml/dl/models/devconvnet/index.html @@ -133,7 +133,7 @@

        Classes

        Module Contents

        -class dasf.ml.dl.models.devconvnet.MyAccuracy(dist_sync_on_step=False)
        +class dasf.ml.dl.models.devconvnet.MyAccuracy(dist_sync_on_step=False)[source]

        Bases: torchmetrics.Metric

        Base class for all metrics present in the Metrics API.

        This class is inherited by all metrics and implements the following functionality: @@ -164,16 +164,20 @@

        Module Contents +
        +idx = 0
        +

        +
        -set_idx(idx)
        +set_idx(idx)[source]
        -update(preds, target)
        -

        Override this method to update the state variables of your metric class.

        -
        +update(preds, target)[source] +
        Parameters:
        • preds (torch.Tensor)

        • @@ -185,22 +189,19 @@

          Module Contents
          -__str__()
          -

          Return str(self).

          -

        +__str__()[source] +
        -compute()
        -

        Override this method to compute the final metric value.

        -

        This method will automatically synchronize state variables when running in distributed backend.

        -
        +compute()[source] +

      -class dasf.ml.dl.models.devconvnet.NNModule(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.devconvnet.NNModule(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: pytorch_lightning.LightningModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -234,16 +235,36 @@

      Module Contents +
      +learned_billinear
      +

      + +
      +
      +n_classes
      +
      + +
      +
      +clip
      +
      + +
      +
      +class_names
      +
      +
      -cross_entropy_loss(input, target, weight=None, ignore_index=255)
      +cross_entropy_loss(input, target, weight=None, ignore_index=255)[source]

      Use 255 to fill empty values when padding or doing any augmentation operations like rotation.

      -configure_optimizers()
      +configure_optimizers()[source]

      Choose what optimizers and learning-rate schedulers to use in your optimization. Normally you’d need one. But in the case of GANs or similar you might have multiple.

      @@ -381,7 +402,7 @@

      Module Contents
      -training_step(batch, batch_idx)
      +training_step(batch, batch_idx)[source]

      Here you compute and return the training loss and some additional metrics for e.g. the progress bar or logger.

      @@ -449,7 +470,7 @@

      Module Contents
      -test_step(test_batch, batch_idx)
      +test_step(test_batch, batch_idx)[source]

      Operates on a single batch of data from the test set. In this step you’d normally generate examples or calculate anything of interest such as accuracy.

      @@ -533,7 +554,7 @@

      Module Contents
      -class dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -567,9 +588,109 @@

      Module Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -582,12 +703,12 @@

      Module Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      @@ -595,7 +716,7 @@

      Module Contents
      -class dasf.ml.dl.models.devconvnet.TorchPatchDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.devconvnet.TorchPatchDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -629,9 +750,109 @@

      Module Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -644,12 +865,12 @@

      Module Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      @@ -657,7 +878,7 @@

      Module Contents
      -class dasf.ml.dl.models.devconvnet.TorchSectionDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=False)
      +class dasf.ml.dl.models.devconvnet.TorchSectionDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=False)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -691,9 +912,109 @@

      Module Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -706,12 +1027,12 @@

      Module Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      @@ -719,7 +1040,7 @@

      Module Contents
      -class dasf.ml.dl.models.devconvnet.TorchSectionDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.devconvnet.TorchSectionDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -753,9 +1074,109 @@

      Module Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -768,12 +1189,12 @@

      Module Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      diff --git a/docs/autoapi/dasf/ml/dl/models/index.html b/docs/autoapi/dasf/ml/dl/models/index.html index 05a1e84..9854f54 100644 --- a/docs/autoapi/dasf/ml/dl/models/index.html +++ b/docs/autoapi/dasf/ml/dl/models/index.html @@ -134,7 +134,7 @@

      Classes

      Package Contents

      -class dasf.ml.dl.models.TorchPatchDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.TorchPatchDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -168,9 +168,109 @@

      Package Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -183,12 +283,12 @@

      Package Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      @@ -196,7 +296,7 @@

      Package Contents
      -class dasf.ml.dl.models.TorchPatchDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.TorchPatchDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -230,9 +330,109 @@

      Package Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -245,12 +445,12 @@

      Package Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      @@ -258,7 +458,7 @@

      Package Contents
      -class dasf.ml.dl.models.TorchSectionDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=False)
      +class dasf.ml.dl.models.TorchSectionDeConvNet(n_classes=4, learned_billinear=False, clip=0.1, class_weights=False)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -292,9 +492,109 @@

      Package Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -307,12 +607,12 @@

      Package Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      @@ -320,7 +620,7 @@

      Package Contents
      -class dasf.ml.dl.models.TorchSectionDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)
      +class dasf.ml.dl.models.TorchSectionDeConvNetSkip(n_classes=4, learned_billinear=False, clip=0.1, class_weights=None)[source]

      Bases: NNModule

      Base class for all neural network modules.

      Your models should also subclass this class.

      @@ -354,9 +654,109 @@

      Package Contents +
      +unpool
      +

      + +
      +
      +conv_block1
      +
      + +
      +
      +conv_block2
      +
      + +
      +
      +conv_block3
      +
      + +
      +
      +conv_block4
      +
      + +
      +
      +conv_block5
      +
      + +
      +
      +conv_block6
      +
      + +
      +
      +conv_block7
      +
      + +
      +
      +deconv_block8
      +
      + +
      +
      +unpool_block9
      +
      + +
      +
      +deconv_block10
      +
      + +
      +
      +unpool_block11
      +
      + +
      +
      +deconv_block12
      +
      + +
      +
      +unpool_block13
      +
      + +
      +
      +deconv_block14
      +
      + +
      +
      +unpool_block15
      +
      + +
      +
      +deconv_block16
      +
      + +
      +
      +unpool_block17
      +
      + +
      +
      +deconv_block18
      +
      + +
      +
      +seg_score19
      +
      +
      -forward(x)
      +forward(x)[source]

      Same as torch.nn.Module.forward().

      Args:

      *args: Whatever you decide to pass into the forward method. @@ -369,12 +769,12 @@

      Package Contents
      -init_vgg16_params(vgg16, copy_fc8=True)
      +init_vgg16_params(vgg16, copy_fc8=True)[source]

      -load()
      +load()[source]

      This is just a no-op load method.

      diff --git a/docs/autoapi/dasf/ml/dl/pytorch_lightning/index.html b/docs/autoapi/dasf/ml/dl/pytorch_lightning/index.html index 49eb7ca..7d20998 100644 --- a/docs/autoapi/dasf/ml/dl/pytorch_lightning/index.html +++ b/docs/autoapi/dasf/ml/dl/pytorch_lightning/index.html @@ -133,7 +133,7 @@

      Functions

      -class dasf.ml.dl.pytorch_lightning.TorchDataLoader(train, val=None, test=None, batch_size=64)
      +class dasf.ml.dl.pytorch_lightning.TorchDataLoader(train, val=None, test=None, batch_size=64)[source]

      Bases: pytorch_lightning.LightningDataModule

      A DataModule standardizes the training, val, test splits, data preparation and transforms. The main advantage is consistent data splits, data preparation and transforms across models.

      @@ -172,9 +172,29 @@

      Module Contents +
      +_train
      +

      + +
      +
      +_val
      +
      + +
      +
      +_test
      +
      + +
      +
      +_batch_size
      +
      +
      -prepare_data()
      +prepare_data()[source]

      Use this to download and prepare data. Downloading and saving data with multiple processes (distributed settings) will result in corrupted data. Lightning ensures this method is called only within a single process, so you can safely add your downloading logic within.

      @@ -231,7 +251,7 @@

      Module Contents
      -setup(stage=None)
      +setup(stage=None)[source]

      Called at the beginning of fit (train + validate), validate, test, or predict. This is a good hook when you need to build models dynamically or adjust something about them. This hook is called on every process when using DDP.

      @@ -260,7 +280,7 @@

      Module Contents
      -train_dataloader()
      +train_dataloader()[source]

      Implement one or more PyTorch DataLoaders for training.

      Return:

      A collection of torch.utils.data.DataLoader specifying training samples. @@ -337,7 +357,7 @@

      Module Contents
      -val_dataloader()
      +val_dataloader()[source]

      Implement one or multiple PyTorch DataLoaders for validation.

      The dataloader you return will not be reloaded unless you set :paramref:`~pytorch_lightning.trainer.Trainer.reload_dataloaders_every_n_epochs` to @@ -387,7 +407,7 @@

      Module Contents
      -test_dataloader()
      +test_dataloader()[source]

      Implement one or multiple PyTorch DataLoaders for testing.

      For data processing use the following pattern:

      @@ -446,33 +466,78 @@

      Module Contents
      -dasf.ml.dl.pytorch_lightning.run_dask_clustered(func, client=None, **kwargs)
      +dasf.ml.dl.pytorch_lightning.run_dask_clustered(func, client=None, **kwargs)[source]

      -dasf.ml.dl.pytorch_lightning.fit(model, X, y, max_iter, accel, strategy, devices, ngpus, batch_size=32, plugins=None, meta=None)
      +dasf.ml.dl.pytorch_lightning.fit(model, X, y, max_iter, accel, strategy, devices, ngpus, batch_size=32, plugins=None, meta=None)[source]
      -class dasf.ml.dl.pytorch_lightning.NeuralNetClassifier(model, max_iter=100, batch_size=32)
      +class dasf.ml.dl.pytorch_lightning.NeuralNetClassifier(model, max_iter=100, batch_size=32)[source]

      Bases: dasf.transforms.base.Fit

      Class representing a Fit operation of the pipeline.

      +
      +
      +_model
      +
      + +
      +
      +_accel = None
      +
      + +
      +
      +_strategy = None
      +
      + +
      +
      +_max_iter
      +
      + +
      +
      +_devices = 0
      +
      + +
      +
      +_ngpus = 0
      +
      + +
      +
      +_batch_size
      +
      + +
      +
      +__trainer = False
      +
      + +
      +
      +__handler
      +
      +
      -_lazy_fit_generic(X, y, accel, ngpus)
      +_lazy_fit_generic(X, y, accel, ngpus)[source]
      -_lazy_fit_gpu(X, y=None)
      +_lazy_fit_gpu(X, y=None)[source]

      Respective lazy fit mocked function for GPUs.

      -_lazy_fit_cpu(X, y=None)
      +_lazy_fit_cpu(X, y=None)[source]

      Respective lazy fit mocked function for CPUs.

      @@ -483,13 +548,13 @@

      Module Contents
      -_fit_gpu(X, y=None)
      +_fit_gpu(X, y=None)[source]

      Respective immediate fit mocked function for local GPU(s).

      -_fit_cpu(X, y=None)
      +_fit_cpu(X, y=None)[source]

      Respective immediate fit mocked function for local CPU(s).

      diff --git a/docs/autoapi/dasf/ml/index.html b/docs/autoapi/dasf/ml/index.html index 927890c..0b8cd4e 100644 --- a/docs/autoapi/dasf/ml/index.html +++ b/docs/autoapi/dasf/ml/index.html @@ -24,7 +24,7 @@ - + @@ -124,7 +124,7 @@

      Subpackages - +

    diff --git a/docs/autoapi/dasf/ml/inference/loader/base/index.html b/docs/autoapi/dasf/ml/inference/loader/base/index.html index 122c40e..9193583 100644 --- a/docs/autoapi/dasf/ml/inference/loader/base/index.html +++ b/docs/autoapi/dasf/ml/inference/loader/base/index.html @@ -120,6 +120,11 @@

    Module Contents class dasf.ml.inference.loader.base.BaseLoader[source]

    BaseLoader for DL models. When running in a Dask Cluster instantiates a model per worker that will be reused on every subsequent prediction task.

    +
    +
    +model_instances
    +
    +
    abstract inference(model, data)[source]
    @@ -184,12 +189,6 @@

    Module Contents -
    -abstract inference(model, data)[source]
    -

    Inference method, receives model and input data

    -

    -
    postprocessing(data)[source]
    diff --git a/docs/autoapi/dasf/ml/inference/loader/torch/index.html b/docs/autoapi/dasf/ml/inference/loader/torch/index.html index 4a18dbd..d8e481a 100644 --- a/docs/autoapi/dasf/ml/inference/loader/torch/index.html +++ b/docs/autoapi/dasf/ml/inference/loader/torch/index.html @@ -125,6 +125,26 @@

    Module Contents +
    +model_class_or_file
    +

    + +
    +
    +dtype
    +
    + +
    +
    +checkpoint
    +
    + +
    +
    +device
    +
    +
    load_model(**kwargs)[source]
    @@ -134,8 +154,7 @@

    Module Contents
    inference(model, data)[source]
    -

    Inference method, receives model and input data

    -

    +

    diff --git a/docs/autoapi/dasf/ml/mixture/gmm/index.html b/docs/autoapi/dasf/ml/mixture/gmm/index.html index 9484c98..4a455a1 100644 --- a/docs/autoapi/dasf/ml/mixture/gmm/index.html +++ b/docs/autoapi/dasf/ml/mixture/gmm/index.html @@ -269,6 +269,11 @@

    Examples array([1, 0])

    +
    +
    +__gmm_cpu
    +
    +
    _fit_cpu(X, y=None)[source]
    diff --git a/docs/autoapi/dasf/ml/model_selection/split/index.html b/docs/autoapi/dasf/ml/model_selection/split/index.html index 3261507..074364e 100644 --- a/docs/autoapi/dasf/ml/model_selection/split/index.html +++ b/docs/autoapi/dasf/ml/model_selection/split/index.html @@ -130,6 +130,42 @@

    Parametersbool

    Define if the operator will use GPU(s) or not.

    +

    Constructor of the class TargeteredTransform.

    +
    +
    +output
    +
    + +
    +
    +test_size
    +
    + +
    +
    +train_size
    +
    + +
    +
    +random_state
    +
    + +
    +
    +shuffle
    +
    + +
    +
    +blockwise
    +
    + +
    +
    +convert_mixed_types
    +
    +
    _lazy_transform_cpu(X)[source]
    diff --git a/docs/autoapi/dasf/ml/neighbors/index.html b/docs/autoapi/dasf/ml/neighbors/index.html index 1d5654b..07d5d6d 100644 --- a/docs/autoapi/dasf/ml/neighbors/index.html +++ b/docs/autoapi/dasf/ml/neighbors/index.html @@ -226,6 +226,11 @@

    Notesalgorithm and leaf_size.

    https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    Constructor of the class NearestNeighbors.

    +
    +
    +__nn_cpu
    +
    +
    _fit_cpu(X, y=None, **kwargs)[source]
    diff --git a/docs/autoapi/dasf/ml/neighbors/neighbors/index.html b/docs/autoapi/dasf/ml/neighbors/neighbors/index.html index 7ea2ba1..472d454 100644 --- a/docs/autoapi/dasf/ml/neighbors/neighbors/index.html +++ b/docs/autoapi/dasf/ml/neighbors/neighbors/index.html @@ -219,6 +219,11 @@

    Notesalgorithm and leaf_size.

    https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    Constructor of the class NearestNeighbors.

    +
    +
    +__nn_cpu
    +
    +
    _fit_cpu(X, y=None, **kwargs)[source]
    diff --git a/docs/autoapi/dasf/ml/preprocessing/index.html b/docs/autoapi/dasf/ml/preprocessing/index.html index fcc8b59..81ee8e7 100644 --- a/docs/autoapi/dasf/ml/preprocessing/index.html +++ b/docs/autoapi/dasf/ml/preprocessing/index.html @@ -215,6 +215,16 @@

    Attributes +
    +__std_scaler_cpu
    +

    + +
    +
    +__std_scaler_dask
    +
    +
    _lazy_fit_cpu(X, y=None, sample_weight=None)[source]
    diff --git a/docs/autoapi/dasf/ml/preprocessing/standardscaler/index.html b/docs/autoapi/dasf/ml/preprocessing/standardscaler/index.html index 8797737..7465e1d 100644 --- a/docs/autoapi/dasf/ml/preprocessing/standardscaler/index.html +++ b/docs/autoapi/dasf/ml/preprocessing/standardscaler/index.html @@ -208,6 +208,16 @@

    Attributes +
    +__std_scaler_cpu
    +

    + +
    +
    +__std_scaler_dask
    +
    +
    _lazy_fit_cpu(X, y=None, sample_weight=None)[source]
    diff --git a/docs/autoapi/dasf/ml/svm/index.html b/docs/autoapi/dasf/ml/svm/index.html index ecc2204..1b7a44f 100644 --- a/docs/autoapi/dasf/ml/svm/index.html +++ b/docs/autoapi/dasf/ml/svm/index.html @@ -283,6 +283,11 @@

    Attributesshape_fit_tuple of int of shape (n_dimensions_of_X,)

    Array dimensions of training vector X.

    +
    +
    +__svc_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    @@ -426,6 +431,11 @@

    Attributes

    Constructor of the class SVR.

    +
    +
    +__svr_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    @@ -573,6 +583,11 @@

    Attributes

    Constructor of the class LinearSVC.

    +
    +
    +__linear_svc_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    @@ -730,6 +745,11 @@

    Attributes

    Constructor of the class LinearSVR.

    +
    +
    +__linear_svr_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    diff --git a/docs/autoapi/dasf/ml/svm/svm/index.html b/docs/autoapi/dasf/ml/svm/svm/index.html index ea5f1fc..b102990 100644 --- a/docs/autoapi/dasf/ml/svm/svm/index.html +++ b/docs/autoapi/dasf/ml/svm/svm/index.html @@ -276,6 +276,11 @@

    Attributesshape_fit_tuple of int of shape (n_dimensions_of_X,)

    Array dimensions of training vector X.

    +
    +
    +__svc_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    @@ -419,6 +424,11 @@

    Attributes

    Constructor of the class SVR.

    +
    +
    +__svr_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    @@ -566,6 +576,11 @@

    Attributes

    Constructor of the class LinearSVC.

    +
    +
    +__linear_svc_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    @@ -723,6 +738,11 @@

    Attributes

    Constructor of the class LinearSVR.

    +
    +
    +__linear_svr_cpu
    +
    +
    _fit_cpu(X, y, sample_weight=None)[source]
    diff --git a/docs/autoapi/dasf/ml/xgboost/index.html b/docs/autoapi/dasf/ml/xgboost/index.html index 53a8ead..340f024 100644 --- a/docs/autoapi/dasf/ml/xgboost/index.html +++ b/docs/autoapi/dasf/ml/xgboost/index.html @@ -128,6 +128,16 @@

    Package Contentsclass dasf.ml.xgboost.XGBRegressor(max_depth=None, max_leaves=None, max_bin=None, grow_policy=None, learning_rate=None, n_estimators=100, verbosity=None, objective=None, booster=None, tree_method=None, n_jobs=None, gamma=None, min_child_weight=None, max_delta_step=None, subsample=None, sampling_method=None, colsample_bytree=None, colsample_bylevel=None, colsample_bynode=None, reg_alpha=None, reg_lambda=None, scale_pos_weight=None, base_score=None, random_state=None, num_parallel_tree=None, monotone_constraints=None, interaction_constraints=None, importance_type=None, gpu_id=None, validate_parameters=None, predictor=None, enable_categorical=False, max_cat_to_onehot=None, eval_metric=None, early_stopping_rounds=None, callbacks=None, **kwargs)[source]

    Bases: dasf.transforms.Fit, dasf.transforms.FitPredict, dasf.transforms.Predict

    Class representing a Fit operation of the pipeline.

    +
    +
    +__xgb_cpu
    +
    + +
    +
    +__xgb_mcpu
    +
    +
    _lazy_fit_cpu(X, y=None, sample_weight=None, *args, **kwargs)[source]
    diff --git a/docs/autoapi/dasf/ml/xgboost/xgboost/index.html b/docs/autoapi/dasf/ml/xgboost/xgboost/index.html index 1810606..5f2e867 100644 --- a/docs/autoapi/dasf/ml/xgboost/xgboost/index.html +++ b/docs/autoapi/dasf/ml/xgboost/xgboost/index.html @@ -120,6 +120,16 @@

    Module Contentsclass dasf.ml.xgboost.xgboost.XGBRegressor(max_depth=None, max_leaves=None, max_bin=None, grow_policy=None, learning_rate=None, n_estimators=100, verbosity=None, objective=None, booster=None, tree_method=None, n_jobs=None, gamma=None, min_child_weight=None, max_delta_step=None, subsample=None, sampling_method=None, colsample_bytree=None, colsample_bylevel=None, colsample_bynode=None, reg_alpha=None, reg_lambda=None, scale_pos_weight=None, base_score=None, random_state=None, num_parallel_tree=None, monotone_constraints=None, interaction_constraints=None, importance_type=None, gpu_id=None, validate_parameters=None, predictor=None, enable_categorical=False, max_cat_to_onehot=None, eval_metric=None, early_stopping_rounds=None, callbacks=None, **kwargs)[source]

    Bases: dasf.transforms.Fit, dasf.transforms.FitPredict, dasf.transforms.Predict

    Class representing a Fit operation of the pipeline.

    +
    +
    +__xgb_cpu
    +
    + +
    +
    +__xgb_mcpu
    +
    +
    _lazy_fit_cpu(X, y=None, sample_weight=None, *args, **kwargs)[source]
    diff --git a/docs/autoapi/dasf/pipeline/executors/dask/index.html b/docs/autoapi/dasf/pipeline/executors/dask/index.html index e9664a9..e5314f0 100644 --- a/docs/autoapi/dasf/pipeline/executors/dask/index.html +++ b/docs/autoapi/dasf/pipeline/executors/dask/index.html @@ -103,6 +103,7 @@

    dasf.pipeline.executors.dask

    +

    Dask executor module.

    Classes

    @@ -154,6 +155,21 @@

    Module Contents +
    +address
    +
    + +
    +
    +port
    +
    + +
    +
    +local
    +
    +
    property ngpus: int
    @@ -243,6 +259,11 @@

    Module Contents +
    +_tasks_map
    +

    +
    pre_run(pipeline)[source]
    @@ -289,6 +310,11 @@

    Module Contents class dasf.pipeline.executors.dask.DaskPBSPipelineExecutor(**kwargs)[source]

    Bases: dasf.pipeline.executors.base.Executor

    +
    +
    +client
    +
    +

    diff --git a/docs/autoapi/dasf/pipeline/executors/index.html b/docs/autoapi/dasf/pipeline/executors/index.html index 7fcf0d1..9404495 100644 --- a/docs/autoapi/dasf/pipeline/executors/index.html +++ b/docs/autoapi/dasf/pipeline/executors/index.html @@ -211,6 +211,11 @@

    Package Contents class dasf.pipeline.executors.DaskPBSPipelineExecutor(**kwargs)[source]

    Bases: dasf.pipeline.executors.base.Executor

    +
    +
    +client
    +
    +
    @@ -231,6 +236,21 @@

    Package Contents +
    +address
    +

    + +
    +
    +port
    +
    + +
    +
    +local
    +
    +
    property ngpus: int
    @@ -320,6 +340,11 @@

    Package Contents +
    +_tasks_map
    +

    +
    pre_run(pipeline)[source]
    @@ -365,7 +390,12 @@

    Package Contents
    class dasf.pipeline.executors.LocalExecutor(use_gpu=None, backend='numpy', gpu_allocator='cupy')[source]
    -
    +
    +
    +backend
    +
    + +
    property ngpus: int
    diff --git a/docs/autoapi/dasf/pipeline/executors/ray/index.html b/docs/autoapi/dasf/pipeline/executors/ray/index.html index c0d4886..ed0df72 100644 --- a/docs/autoapi/dasf/pipeline/executors/ray/index.html +++ b/docs/autoapi/dasf/pipeline/executors/ray/index.html @@ -150,6 +150,16 @@

    Parameters +
    +address
    +

    + +
    +
    +port
    +
    +
    property ngpus
    diff --git a/docs/autoapi/dasf/pipeline/executors/wrapper/index.html b/docs/autoapi/dasf/pipeline/executors/wrapper/index.html index 3c0a3ac..40d12ab 100644 --- a/docs/autoapi/dasf/pipeline/executors/wrapper/index.html +++ b/docs/autoapi/dasf/pipeline/executors/wrapper/index.html @@ -118,7 +118,12 @@

    Module Contents
    class dasf.pipeline.executors.wrapper.LocalExecutor(use_gpu=None, backend='numpy', gpu_allocator='cupy')[source]
    -
    +
    +
    +backend
    +
    + +
    property ngpus: int
    diff --git a/docs/autoapi/dasf/pipeline/index.html b/docs/autoapi/dasf/pipeline/index.html index bfa073f..267eb07 100644 --- a/docs/autoapi/dasf/pipeline/index.html +++ b/docs/autoapi/dasf/pipeline/index.html @@ -101,6 +101,7 @@

    dasf.pipeline

    +

    Init module for DASF Pipeline and its features.

    Subpackages

    @@ -141,6 +142,46 @@

    Package Contents

    callbacks (List[PipelinePlugin])

    +
    +
    +_name
    +
    + +
    +
    +_executor
    +
    + +
    +
    +_verbose
    +
    + +
    +
    +_dag
    +
    + +
    +
    +_dag_table
    +
    + +
    +
    +_dag_g
    +
    + +
    +
    +_logger
    +
    + +
    +
    +_callbacks
    +
    +
    register_plugin(plugin)[source]
    diff --git a/docs/autoapi/dasf/pipeline/pipeline/index.html b/docs/autoapi/dasf/pipeline/pipeline/index.html index a6d50ba..b68df28 100644 --- a/docs/autoapi/dasf/pipeline/pipeline/index.html +++ b/docs/autoapi/dasf/pipeline/pipeline/index.html @@ -155,6 +155,46 @@

    Module Contents

    callbacks (List[PipelinePlugin])

    +
    +
    +_name
    +
    + +
    +
    +_executor
    +
    + +
    +
    +_verbose
    +
    + +
    +
    +_dag
    +
    + +
    +
    +_dag_table
    +
    + +
    +
    +_dag_g
    +
    + +
    +
    +_logger
    +
    + +
    +
    +_callbacks
    +
    +
    register_plugin(plugin)[source]
    diff --git a/docs/autoapi/dasf/profile/analysis/index.html b/docs/autoapi/dasf/profile/analysis/index.html index 73c8068..96a8d92 100644 --- a/docs/autoapi/dasf/profile/analysis/index.html +++ b/docs/autoapi/dasf/profile/analysis/index.html @@ -148,6 +148,11 @@

    Module Contents +
    +_database
    +

    +
    create_annotated_task_graph()[source]
    diff --git a/docs/autoapi/dasf/profile/index.html b/docs/autoapi/dasf/profile/index.html index 7d8e9ae..c0cf2c3 100644 --- a/docs/autoapi/dasf/profile/index.html +++ b/docs/autoapi/dasf/profile/index.html @@ -148,6 +148,11 @@

    Package Contents +
    +_database
    +

    +
    create_annotated_task_graph()[source]
    @@ -183,6 +188,11 @@

    Package Contents

    databases (List[dasf.profile.profiler.EventDatabase])

    +
    +
    +_databases
    +
    +
    __iter__()[source]
    @@ -191,8 +201,7 @@

    Package Contents
    __str__()[source]
    -

    Return str(self).

    -
    +
    Return type:

    str

    @@ -202,8 +211,7 @@

    Package Contents
    __repr__()[source]
    -

    Return repr(self).

    -
    +
    Return type:

    str

    diff --git a/docs/autoapi/dasf/profile/plugins/index.html b/docs/autoapi/dasf/profile/plugins/index.html index 5622584..a3981e0 100644 --- a/docs/autoapi/dasf/profile/plugins/index.html +++ b/docs/autoapi/dasf/profile/plugins/index.html @@ -157,6 +157,11 @@

    Examples >>> client.register_worker_plugin(plugin) +
    +
    +name
    +
    +
    setup(worker)[source]
    @@ -212,6 +217,36 @@

    Parameters +
    +time
    +

    + +
    +
    +name
    +
    + +
    +
    +hostname
    +
    + +
    +
    +database
    +
    + +
    +
    +monitor
    +
    + +
    +
    +callback
    +
    +
    __del__()[source]
    @@ -271,6 +306,21 @@

    Examples>>> client.register_worker_plugin(plugin) +
    +
    +name
    +
    + +
    +
    +gpu_num = None
    +
    + +
    +
    +marks
    +
    +
    setup(worker)[source]
    diff --git a/docs/autoapi/dasf/profile/profiler/index.html b/docs/autoapi/dasf/profile/profiler/index.html index 48779e0..45e5540 100644 --- a/docs/autoapi/dasf/profile/profiler/index.html +++ b/docs/autoapi/dasf/profile/profiler/index.html @@ -493,6 +493,41 @@

    Module Contents +
    +database_file
    +

    + +
    +
    +commit_threshold
    +
    + +
    +
    +commit_on_close
    +
    + +
    +
    +queue
    +
    + +
    +
    +lock_timeout
    +
    + +
    +
    +byte_size
    +
    + +
    +
    +flush
    +
    +
    record(event)[source]
    @@ -526,8 +561,7 @@

    Module Contents
    __str__()[source]
    -

    Return str(self).

    -
    +
    Return type:

    str

    @@ -537,8 +571,7 @@

    Module Contents
    __repr__()[source]
    -

    Return repr(self).

    -
    +
    Return type:

    str

    @@ -574,6 +607,11 @@

    Module Contentsdefault_database_kwargs

    +
    +
    +output_file = None
    +
    +
    _record(event)[source]
    @@ -650,14 +688,12 @@

    Module Contents
    __str__()[source]
    -

    Return str(self).

    -

    +
    __repr__()[source]
    -

    Return repr(self).

    -
    +
    Return type:

    str

    diff --git a/docs/autoapi/dasf/profile/utils/index.html b/docs/autoapi/dasf/profile/utils/index.html index ac9f4c7..b0adcd2 100644 --- a/docs/autoapi/dasf/profile/utils/index.html +++ b/docs/autoapi/dasf/profile/utils/index.html @@ -132,6 +132,11 @@

    Module Contents

    databases (List[dasf.profile.profiler.EventDatabase])

    +
    +
    +_databases
    +
    +
    __iter__()[source]
    @@ -140,8 +145,7 @@

    Module Contents
    __str__()[source]
    -

    Return str(self).

    -
    +
    Return type:

    str

    @@ -151,8 +155,7 @@

    Module Contents
    __repr__()[source]
    -

    Return repr(self).

    -
    +
    Return type:

    str

    diff --git a/docs/autoapi/dasf/transforms/base/index.html b/docs/autoapi/dasf/transforms/base/index.html index 36385f5..fc5a23a 100644 --- a/docs/autoapi/dasf/transforms/base/index.html +++ b/docs/autoapi/dasf/transforms/base/index.html @@ -461,6 +461,17 @@

    Parametersbool

    Define if the operator will use GPU(s) or not.

    +

    Constructor of the class TargeteredTransform.

    +
    +
    +_run_local
    +
    + +
    +
    +_run_gpu
    +
    +
    @@ -498,6 +509,41 @@

    Parameters (the default is None).

    +
    +
    +function
    +
    + +
    +
    +depth
    +
    + +
    +
    +boundary
    +
    + +
    +
    +trim
    +
    + +
    +
    +output_chunk
    +
    + +
    +
    +drop_axis
    +
    + +
    +
    +new_axis
    +
    +
    __lazy_transform_generic(X, xp, **kwargs)
    @@ -556,6 +602,26 @@

    Parameters default is None).

    +
    +
    +output_size
    +
    + +
    +
    +func_aggregate
    +
    + +
    +
    +func_chunk
    +
    + +
    +
    +func_combine
    +
    +
    _operation_aggregate_cpu(block, axis=None, keepdims=False)[source]
    diff --git a/docs/autoapi/dasf/transforms/index.html b/docs/autoapi/dasf/transforms/index.html index be94532..c373661 100644 --- a/docs/autoapi/dasf/transforms/index.html +++ b/docs/autoapi/dasf/transforms/index.html @@ -101,6 +101,7 @@

    dasf.transforms

    +

    Init module for all transformation structures.

    Submodules

    @@ -165,10 +166,10 @@

    Classes

    - + - + @@ -212,6 +213,41 @@

    Parameters +
    +function
    +
    + +
    +
    +depth
    +
    + +
    +
    +boundary
    +
    + +
    +
    +trim
    +
    + +
    +
    +output_chunk
    +
    + +
    +
    +drop_axis
    +
    + +
    +
    +new_axis
    +
    +
    __lazy_transform_generic(X, xp, **kwargs)
    @@ -270,6 +306,26 @@

    Parameters default is None).

    +
    +
    +output_size
    +
    + +
    +
    +func_aggregate
    +
    + +
    +
    +func_chunk
    +
    + +
    +
    +func_combine
    +
    +
    _operation_aggregate_cpu(block, axis=None, keepdims=False)[source]
    @@ -348,6 +404,17 @@

    Parameters
    run_gpubool

    Define if the operator will use GPU(s) or not.

    +

    Constructor of the class TargeteredTransform.

    +
    +
    +_run_local
    +
    + +
    +
    +_run_gpu
    +
    + @@ -645,6 +712,11 @@

    Parameters
    iline_indexint

    The index of the inline to get.

    +
    +
    +shape
    +
    +
    fit(X, y=None)[source]
    @@ -664,6 +736,11 @@

    Parametersclass dasf.transforms.SliceArray(output_size)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +x
    +
    +
    transform(X)[source]
    @@ -677,6 +754,21 @@

    Parametersclass dasf.transforms.SliceArrayByPercent(x=100.0, y=100.0, z=100.0)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +x
    +
    + +
    +
    +y
    +
    + +
    +
    +z
    +
    +
    transform(X)[source]
    @@ -736,6 +828,26 @@

    Parametersclass dasf.transforms.ArrayToHDF5(dataset_path, chunks=None, save=True, filename=None)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +dataset_path
    +
    + +
    +
    +chunks
    +
    + +
    +
    +save = True
    +
    + +
    +
    +filename
    +
    +
    static _convert_filename(url)[source]
    @@ -792,6 +904,21 @@

    Parametersclass dasf.transforms.ArrayToZarr(chunks=None, save=True, filename=None)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +chunks
    +
    + +
    +
    +save = True
    +
    + +
    +
    +filename
    +
    +
    static _convert_filename(url)[source]
    @@ -847,11 +974,26 @@

    Parameters
    class dasf.transforms.ExtractData[source]

    Bases: dasf.transforms.base.Transform

    -

    Extract Data from Dataset Object

    +

    Extract data from Dataset object

    transform(X)[source]
    -

    Generic transform funtion according executor.

    +

    Extract data from datasets that contains internal data.

    +
    +

    Parameters

    +
    +
    XDataset-like

    A dataset object that could be anything that contains an internal +structure representing the raw data.

    +
    +
    +
    +
    +

    Returns

    +
    +
    dataAny

    Any representation of the internal Dataset data.

    +
    +
    +

    @@ -860,11 +1002,26 @@

    Parameters
    class dasf.transforms.Normalize[source]

    Bases: dasf.transforms.base.Transform

    -

    Class representing a Transform operation of the pipeline.

    +

    Normalize data object

    transform(X)[source]
    -

    Generic transform funtion according executor.

    +

    Normalize the input data based on mean() and std().

    +
    +

    Parameters

    +
    +
    XAny

    Any data that could be normalized based on mean and standard +deviation.

    +
    +
    +
    +
    +

    Returns

    +
    +
    dataAny

    Normalized data

    +
    +
    +

    @@ -874,6 +1031,21 @@

    Parametersclass dasf.transforms.ZarrToArray(chunks=None, save=True, filename=None)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +chunks
    +
    + +
    +
    +save
    +
    + +
    +
    +filename
    +
    +
    static _convert_filename(url)[source]
    diff --git a/docs/autoapi/dasf/transforms/memory/index.html b/docs/autoapi/dasf/transforms/memory/index.html index cbbbada..66c6a89 100644 --- a/docs/autoapi/dasf/transforms/memory/index.html +++ b/docs/autoapi/dasf/transforms/memory/index.html @@ -102,6 +102,7 @@

    dasf.transforms.memory

    +

    Memory Management module.

    Classes

    Class representing a Transform operation of the pipeline.

    ExtractData

    Extract Data from Dataset Object

    Extract data from Dataset object

    Normalize

    Class representing a Transform operation of the pipeline.

    Normalize data object

    ZarrToArray

    Class representing a Transform operation of the pipeline.

    diff --git a/docs/autoapi/dasf/transforms/operations/index.html b/docs/autoapi/dasf/transforms/operations/index.html index cdd8750..e6f0eb5 100644 --- a/docs/autoapi/dasf/transforms/operations/index.html +++ b/docs/autoapi/dasf/transforms/operations/index.html @@ -102,6 +102,7 @@

    dasf.transforms.operations

    +

    Basic transform operations module.

    Classes

    @@ -143,6 +144,11 @@

    Parametersint

    The index of the inline to get.

    +
    +
    +shape
    +
    +
    fit(X, y=None)[source]
    @@ -162,6 +168,11 @@

    Parametersclass dasf.transforms.operations.SliceArray(output_size)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +x
    +
    +
    transform(X)[source]
    @@ -175,6 +186,21 @@

    Parametersclass dasf.transforms.operations.SliceArrayByPercent(x=100.0, y=100.0, z=100.0)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +x
    +
    + +
    +
    +y
    +
    + +
    +
    +z
    +
    +
    transform(X)[source]
    @@ -188,6 +214,11 @@

    Parametersclass dasf.transforms.operations.SliceArrayByPercentile(percentile)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +p
    +
    +
    _internal_chunk_array_positive(block, axis=None, keepdims=False, xp=np)[source]
    @@ -244,6 +275,36 @@

    Parameters +
    +_function
    +

    + +
    +
    +_weight_function
    +
    + +
    +
    +_input_size
    +
    + +
    +
    +_offsets
    +
    + +
    +
    +overlap
    +
    + +
    +
    +_overlap_config
    +
    +
    _apply_patches(patch_set)[source]
    @@ -350,6 +411,16 @@

    Parameters +
    +_voting
    +

    + +
    +
    +_num_classes
    +
    +
    _combine_patches(results, offsets, indexes)[source]
    diff --git a/docs/autoapi/dasf/transforms/transforms/index.html b/docs/autoapi/dasf/transforms/transforms/index.html index 14fd61b..55f5f78 100644 --- a/docs/autoapi/dasf/transforms/transforms/index.html +++ b/docs/autoapi/dasf/transforms/transforms/index.html @@ -102,15 +102,16 @@

    dasf.transforms.transforms

    +

    All the essential data transforms module.

    Classes

    - + - + @@ -133,11 +134,26 @@

    Module Contents class dasf.transforms.transforms.ExtractData[source]

    Bases: dasf.transforms.base.Transform

    -

    Extract Data from Dataset Object

    +

    Extract data from Dataset object

    transform(X)[source]
    -

    Generic transform funtion according executor.

    +

    Extract data from datasets that contains internal data.

    +
    +

    Parameters

    +
    +
    XDataset-like

    A dataset object that could be anything that contains an internal +structure representing the raw data.

    +
    +
    +
    +
    +

    Returns

    +
    +
    dataAny

    Any representation of the internal Dataset data.

    +
    +
    +
    @@ -146,11 +162,26 @@

    Module Contents class dasf.transforms.transforms.Normalize[source]

    Bases: dasf.transforms.base.Transform

    -

    Class representing a Transform operation of the pipeline.

    +

    Normalize data object

    transform(X)[source]
    -

    Generic transform funtion according executor.

    +

    Normalize the input data based on mean() and std().

    +
    +

    Parameters

    +
    +
    XAny

    Any data that could be normalized based on mean and standard +deviation.

    +
    +
    +
    +
    +

    Returns

    +
    +
    dataAny

    Normalized data

    +
    +
    +
    @@ -160,6 +191,21 @@

    Module Contentsclass dasf.transforms.transforms.ArrayToZarr(chunks=None, save=True, filename=None)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +chunks
    +
    + +
    +
    +save = True
    +
    + +
    +
    +filename
    +
    +
    static _convert_filename(url)[source]
    @@ -216,6 +262,26 @@

    Module Contentsclass dasf.transforms.transforms.ArrayToHDF5(dataset_path, chunks=None, save=True, filename=None)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +dataset_path
    +
    + +
    +
    +chunks
    +
    + +
    +
    +save = True
    +
    + +
    +
    +filename
    +
    +
    static _convert_filename(url)[source]
    @@ -272,6 +338,21 @@

    Module Contentsclass dasf.transforms.transforms.ZarrToArray(chunks=None, save=True, filename=None)[source]

    Bases: dasf.transforms.base.Transform

    Class representing a Transform operation of the pipeline.

    +
    +
    +chunks
    +
    + +
    +
    +save
    +
    + +
    +
    +filename
    +
    +
    static _convert_filename(url)[source]
    diff --git a/docs/autoapi/dasf/utils/benchmark/index.html b/docs/autoapi/dasf/utils/benchmark/index.html index 95bf993..5e90384 100644 --- a/docs/autoapi/dasf/utils/benchmark/index.html +++ b/docs/autoapi/dasf/utils/benchmark/index.html @@ -143,7 +143,12 @@

    Module Contents
    class dasf.utils.benchmark.TimeBenchmark(backend='cprofile')[source]
    -
    +
    +
    +__backend
    +
    + +
    __enter__()[source]
    @@ -163,7 +168,32 @@

    Module Contents
    class dasf.utils.benchmark.MemoryBenchmark(backend='memray', debug=False, output_file=None, *args, **kwargs)[source]
    -
    +
    +
    +__backend
    +
    + +
    +
    +__debug
    +
    + +
    +
    +__output_file
    +
    + +
    +
    +__args
    +
    + +
    +
    +__kwargs
    +
    + +
    __enter__()[source]
    diff --git a/docs/autoapi/dasf/utils/funcs/index.html b/docs/autoapi/dasf/utils/funcs/index.html index 4f6250e..ea52b33 100644 --- a/docs/autoapi/dasf/utils/funcs/index.html +++ b/docs/autoapi/dasf/utils/funcs/index.html @@ -317,6 +317,41 @@

    Module ContentsMIN_TOTAL

    +
    +
    +bar = None
    +
    + +
    +
    +percentage = None
    +
    + +
    +
    +data = None
    +
    + +
    +
    +__lock
    +
    + +
    +
    +__current
    +
    + +
    +
    +__total
    +
    + +
    +
    +__error = False
    +
    +
    show()[source]
    diff --git a/docs/autoapi/dasf/utils/index.html b/docs/autoapi/dasf/utils/index.html index 6f50d24..1f55c7c 100644 --- a/docs/autoapi/dasf/utils/index.html +++ b/docs/autoapi/dasf/utils/index.html @@ -101,6 +101,7 @@

    dasf.utils

    +

    Init module for any utils in DASF.

    Submodules

    diff --git a/docs/autoapi/dasf/utils/labels/index.html b/docs/autoapi/dasf/utils/labels/index.html index c552b26..809d91e 100644 --- a/docs/autoapi/dasf/utils/labels/index.html +++ b/docs/autoapi/dasf/utils/labels/index.html @@ -167,6 +167,41 @@

    Module Contents class dasf.utils.labels.DaskLabel(start, stop, label=None, color=None)[source]

    Bases: object

    +
    +
    +__label
    +
    + +
    +
    +__color
    +
    + +
    +
    +__start
    +
    + +
    +
    +__stop
    +
    + +
    +
    +__hash_attrs
    +
    + +
    +
    +__func_attrs
    +
    + +
    +
    +__data_attrs
    +
    +
    start(start)[source]
    diff --git a/docs/genindex.html b/docs/genindex.html index 896f7a6..262f127 100644 --- a/docs/genindex.html +++ b/docs/genindex.html @@ -106,6 +106,7 @@

    Index

    | V | W | X + | Y | Z

    @@ -133,6 +134,14 @@

    _

  • __add_item() (dasf.utils.labels.DaskLabel method) +
  • +
  • __agg_cluster_cpu (dasf.ml.cluster.agglomerative.AgglomerativeClustering attribute) + +
  • +
  • __args (dasf.utils.benchmark.MemoryBenchmark attribute)
  • __array__() (dasf.datasets.base.DatasetArray method) @@ -144,6 +153,12 @@

    _

  • +
  • __backend (dasf.utils.benchmark.MemoryBenchmark attribute) + +
  • __call__() (dasf.datasets.datasets.make_blobs method) @@ -168,6 +183,8 @@

    _

  • (dasf.datasets.DatasetZarr method)
  • +
  • __color (dasf.utils.labels.DaskLabel attribute) +
  • __copy_attrs_from_data() (dasf.datasets.base.DatasetArray method)
  • +
  • __current (dasf.utils.funcs.NotebookProgressBar attribute) +
  • +
  • __data_attrs (dasf.utils.labels.DaskLabel attribute) +
  • +
  • __dbscan_cpu (dasf.ml.cluster.DBSCAN attribute) + +
  • +
  • __debug (dasf.utils.benchmark.MemoryBenchmark attribute) +
  • __del__() (dasf.pipeline.executors.ray.RayPipelineExecutor method)
  • +
  • __error (dasf.utils.funcs.NotebookProgressBar attribute) +
  • __execute() (dasf.pipeline.Pipeline method)
  • +
  • __filename (dasf.datasets.download.DownloadGDrive attribute) + +
  • __fit_generic() (dasf.ml.dl.NeuralNetClassifier method) @@ -230,6 +267,8 @@

    _

  • (dasf.ml.dl.pytorch_lightning.NeuralNetClassifier method)
  • +
  • __func_attrs (dasf.utils.labels.DaskLabel attribute) +
  • __generate_hashtable() (dasf.utils.labels.DaskLabel method)
  • __getitem__() (dasf.datasets.base.Dataset method) @@ -250,6 +289,24 @@

    _

  • (dasf.datasets.DatasetXarray method)
  • (dasf.ml.dl.lightning_fit.LazyDatasetComputer method) +
  • + +
  • __gmm_cpu (dasf.ml.mixture.gmm.GaussianMixture attribute) +
  • +
  • __google_file_id (dasf.datasets.download.DownloadGDrive attribute) +
  • +
  • __handler (dasf.ml.dl.NeuralNetClassifier attribute) + +
  • +
  • __hash_attrs (dasf.utils.labels.DaskLabel attribute) +
  • +
  • __hdbscan_cpu (dasf.ml.cluster.HDBSCAN attribute) + +
  • __inspect_element() (dasf.pipeline.Pipeline method) @@ -264,13 +321,25 @@

    _

  • (dasf.profile.utils.MultiEventDatabase method)
  • -
  • __lazy_transform_generic() (dasf.feature_extraction.Histogram method) +
  • __kmeans_cpu (dasf.ml.cluster.KMeans attribute) + +
  • +
  • __kmeans_mcpu (dasf.ml.cluster.KMeans attribute)
  • +
  • __kwargs (dasf.utils.benchmark.MemoryBenchmark attribute)
  • -
  • (dasf.transforms.base.MappedTransform method) +
  • __label (dasf.utils.labels.DaskLabel attribute)
  • +
  • __lazy_transform_generic() (dasf.transforms.base.MappedTransform method) + +
  • +
  • __linear_svc_cpu (dasf.ml.svm.LinearSVC attribute) + +
  • +
  • __linear_svr_cpu (dasf.ml.svm.LinearSVR attribute) + +
  • +
  • __lock (dasf.utils.funcs.NotebookProgressBar attribute) +
  • __mul__() (dasf.datasets.base.DatasetArray method)
      @@ -310,6 +393,12 @@

      _

  • __name() (dasf.utils.labels.DaskLabel method)
  • +
  • __nn_cpu (dasf.ml.neighbors.NearestNeighbors attribute) + +
  • __npy_header() (dasf.datasets.base.DatasetArray method)
  • +
  • __sc_cpu (dasf.ml.cluster.spectral.SpectralClustering attribute) + +
  • +
  • __sc_mcpu (dasf.ml.cluster.spectral.SpectralClustering attribute) + +
  • __set_dataset_cache_dir() (dasf.datasets.base.Dataset method) @@ -358,6 +485,34 @@

    _

  • (dasf.datasets.Dataset method)
  • +
  • __som_cpu (dasf.ml.cluster.SOM attribute) + +
  • +
  • __som_mcpu (dasf.ml.cluster.SOM attribute) + +
  • +
  • __start (dasf.utils.labels.DaskLabel attribute) +
  • +
  • __std_scaler_cpu (dasf.ml.preprocessing.StandardScaler attribute) + +
  • +
  • __std_scaler_dask (dasf.ml.preprocessing.StandardScaler attribute) + +
  • +
  • __stop (dasf.utils.labels.DaskLabel attribute) +
  • __str__() (dasf.ml.dl.models.devconvnet.MyAccuracy method)
  • +
  • __svc_cpu (dasf.ml.svm.SVC attribute) + +
  • +
  • __svr_cpu (dasf.ml.svm.svm.SVR attribute) + +
  • +
  • __total (dasf.utils.funcs.NotebookProgressBar attribute) +
  • +
  • __trainer (dasf.ml.dl.NeuralNetClassifier attribute) + +
  • __transform_generic() (dasf.feature_extraction.ConcatenateToArray method)
  • +
  • __url (dasf.datasets.download.DownloadWget attribute) +
  • +
  • __xgb_cpu (dasf.ml.xgboost.xgboost.XGBRegressor attribute) + +
  • +
  • __xgb_mcpu (dasf.ml.xgboost.xgboost.XGBRegressor attribute) + +
  • +
  • _accel (dasf.ml.dl.NeuralNetClassifier attribute) + +
  • _adjust_patches() (dasf.transforms.operations.ApplyPatchesBase method)
  • _apply_patches() (dasf.transforms.operations.ApplyPatchesBase method)
  • +
  • _backend (dasf.datasets.base.DatasetZarr attribute) + +
  • +
  • _batch_size (dasf.ml.dl.NeuralNetClassifier attribute) + +
  • +
  • _bins (dasf.feature_extraction.Histogram attribute) + +
  • _build_dataframe() (dasf.transforms.ArraysToDataFrame method)
  • +
  • _callbacks (dasf.pipeline.Pipeline attribute) + +
  • +
  • _chunks (dasf.datasets.base.Dataset attribute) + +
  • _combine_patches() (dasf.transforms.operations.ApplyPatchesBase method) @@ -420,6 +667,78 @@

    _

  • (dasf.transforms.transforms.ZarrToArray static method)
  • (dasf.transforms.ZarrToArray static method) +
  • + +
  • _dag (dasf.pipeline.Pipeline attribute) + +
  • +
  • _dag_g (dasf.pipeline.Pipeline attribute) + +
  • +
  • _dag_table (dasf.pipeline.Pipeline attribute) + +
  • +
  • _data (dasf.datasets.base.Dataset attribute) + +
  • +
  • _data_var (dasf.datasets.base.DatasetXarray attribute) + +
  • +
  • _database (dasf.profile.analysis.TraceAnalyser attribute) + +
  • +
  • _databases (dasf.profile.MultiEventDatabase attribute) + +
  • +
  • _dataset_path (dasf.datasets.base.DatasetHDF5 attribute) + +
  • +
  • _density (dasf.feature_extraction.Histogram attribute) + +
  • +
  • _devices (dasf.ml.dl.NeuralNetClassifier attribute) + +
  • +
  • _download (dasf.datasets.base.Dataset attribute) + +
  • +
  • _executor (dasf.pipeline.Pipeline attribute) + +
  • _extract_patches() (dasf.transforms.operations.ApplyPatchesBase method) @@ -654,6 +973,8 @@

    _

  • (dasf.transforms.FitTransform method)
  • +
  • _function (dasf.transforms.operations.ApplyPatchesBase attribute) +
  • _get_covariance_cpu() (dasf.ml.decomposition.PCA method)
      @@ -689,6 +1010,8 @@

      _

  • _hard_voting() (dasf.transforms.operations.ApplyPatchesVoting method) +
  • +
  • _input_size (dasf.transforms.operations.ApplyPatchesBase attribute)
  • _internal_aggregate_array_negative() (dasf.transforms.operations.SliceArrayByPercentile method)
  • @@ -806,6 +1129,8 @@

    _

  • (dasf.transforms.FitPredict method)
  • + +

    - @@ -1640,24 +2109,80 @@

    _

    A

    ExtractData

    Extract Data from Dataset Object

    Extract data from Dataset object

    Normalize

    Class representing a Transform operation of the pipeline.

    Normalize data object

    ArrayToZarr

    Class representing a Transform operation of the pipeline.

    +
  • _overlap_config (dasf.transforms.operations.ApplyPatchesBase attribute) +
  • _partial_fit_cpu() (dasf.ml.preprocessing.StandardScaler method)
  • + -
    • Array (in module dasf.utils.types)
    • ArrayCPU (in module dasf.utils.types) @@ -1692,6 +2215,12 @@

      A

    • +
    • assign_labels (dasf.ml.cluster.spectral.SpectralClustering attribute) + +
    • ASYNC_BEGIN (dasf.profile.profiler.EventPhases attribute) @@ -1706,11 +2235,35 @@

      A

      B

      @@ -1718,12 +2271,46 @@

      B

      C

      - + - +
    • - dasf.feature_extraction.transform + dasf.feature_extraction.transforms
    • @@ -2141,8 +2912,6 @@

      D

    • module
    • -
      • dasf.pipeline.executors.wrapper @@ -2262,6 +3031,8 @@

        D

      • module
      +
      +
    • data (dasf.utils.funcs.NotebookProgressBar attribute) +
    • +
    • database (dasf.profile.plugins.ResourceMonitor attribute) +
    • +
    • database_file (dasf.profile.profiler.FileDatabase attribute) +
    • DataCPU (in module dasf.utils.types)
    • DataDask (in module dasf.utils.types) @@ -2327,6 +3104,14 @@

      D

    • +
    • dataset (dasf.ml.dl.lightning_fit.LazyDatasetComputer attribute) +
    • +
    • dataset_path (dasf.transforms.ArrayToHDF5 attribute) + +
    • DatasetArray (class in dasf.datasets) @@ -2383,14 +3168,148 @@

      D

    • (class in dasf.debug.debug)
    • -
    • default_database (dasf.profile.profiler.EventProfiler attribute) +
    • decay_function (dasf.ml.cluster.SOM attribute) + +
    • +
    • deconv_block10 (dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet attribute) + +
    • +
    • deconv_block12 (dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet attribute) + +
    • +
    • deconv_block14 (dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet attribute) + +
    • +
    • deconv_block16 (dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet attribute) + +
    • +
    • deconv_block18 (dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet attribute) + +
    • +
    • deconv_block8 (dasf.ml.dl.models.devconvnet.TorchPatchDeConvNet attribute) + +
    • +
    • default_database (dasf.profile.profiler.EventProfiler attribute)
    • default_database_kwargs (dasf.profile.profiler.EventProfiler attribute)
    • +
    • degree (dasf.ml.cluster.spectral.SpectralClustering attribute) + +
    • +
    • depth (dasf.transforms.base.MappedTransform attribute) + +
    • detect() (dasf.ml.dl.clusters.dask.DaskClusterEnvironment method)
    • +
    • device (dasf.ml.inference.loader.torch.TorchLoader attribute) +
    • +
    • devices (dasf.ml.dl.lightning_fit.LightningTrainer attribute) + +
    • display() (dasf.debug.Debug method) @@ -2401,6 +3320,12 @@

      D

    • (dasf.debug.debug.VisualizeDaskData method)
    • (dasf.debug.VisualizeDaskData method) +
    • + +
    • distance_threshold (dasf.ml.cluster.agglomerative.AgglomerativeClustering attribute) + +
    • download() (dasf.datasets.base.Dataset method) @@ -2424,6 +3349,14 @@

      D

    • DownloadGDrive (class in dasf.datasets.download)
    • DownloadWget (class in dasf.datasets.download) +
    • +
    • drop_axis (dasf.transforms.base.MappedTransform attribute) + +
    • +
    • dtype (dasf.ml.inference.loader.torch.TorchLoader attribute)
    • duration (dasf.profile.profiler.CompleteEvent attribute)
    • @@ -2441,6 +3374,24 @@

      D

      E

      - + @@ -2617,8 +3618,20 @@

      G

    • g_hash_attrs (in module dasf.utils.labels)
    • +
    • gamma (dasf.ml.cluster.spectral.SpectralClustering attribute) + +
    • GaussianMixture (class in dasf.ml.mixture.gmm)
    • +
    • gen_min_span_tree (dasf.ml.cluster.HDBSCAN attribute) + +
    • get_attributes() (in module dasf.utils.labels)
    • get_backend() (dasf.pipeline.executors.LocalExecutor method) @@ -2657,12 +3670,12 @@

      G

    • (dasf.pipeline.executors.Executor method)
    • + + -
      -
    • GetSubDataframe (class in dasf.feature_extraction) - -
    • -
    • GetSubeCubeArray (class in dasf.feature_extraction) +
    • GetSubDataframe (class in dasf.feature_extraction)
    • GLOBAL (dasf.profile.profiler.InstantEventScope attribute) @@ -2721,6 +3730,8 @@

      G

    • (dasf.ml.dl.clusters.DaskClusterEnvironment method)
    • +
    • gpu_num (dasf.profile.plugins.GPUAnnotationPlugin attribute) +
    • GPU_SUPPORTED (in module dasf.utils.funcs)
    • GPUAnnotationPlugin (class in dasf.profile.plugins) @@ -2731,6 +3742,12 @@

      G

      H

      @@ -2767,7 +3786,9 @@

      H

      I

        +
      • monitor (dasf.profile.plugins.ResourceMonitor attribute) +
      • multi_cpu (dasf.pipeline.types.TaskExecutorType attribute)
      • multi_gpu (dasf.pipeline.types.TaskExecutorType attribute) @@ -3256,9 +4431,73 @@

        M

        N

        + - @@ -3334,8 +4597,6 @@

        O

      • (dasf.pipeline.PipelinePlugin method)
      • - - +
        -
      • NotebookProgressBar (class in dasf.utils.funcs)
      • +
      • num_epochs (dasf.ml.cluster.SOM attribute) + +
      • +
      • num_nodes (dasf.ml.dl.lightning_fit.LightningTrainer attribute) + +
      • NV_COMP_BATCH_CODEC_SUPPORTED (in module dasf.utils.funcs)
      • P

        +
        +
      • precompute_distances (dasf.ml.cluster.KMeans attribute) + +
      • Predict (class in dasf.transforms) @@ -3474,6 +4813,12 @@

        P

      • +
      • prediction_data (dasf.ml.cluster.HDBSCAN attribute) + +
      • prepare_data() (dasf.ml.dl.pytorch_lightning.TorchDataLoader method) @@ -3505,11 +4850,33 @@

        Q

      • R

        + -
        + +
      • time (dasf.profile.plugins.ResourceMonitor attribute) +
      • TimeBenchmark (class in dasf.utils.benchmark)
      • timestamp (dasf.profile.profiler.CompleteEvent attribute) @@ -3786,6 +5221,18 @@

        T

      • (dasf.profile.profiler.DurationEndEvent attribute)
      • (dasf.profile.profiler.InstantEvent attribute) +
      • + +
      • tol (dasf.ml.cluster.KMeans attribute) + +
      • +
      • topology (dasf.ml.cluster.SOM attribute) + +
      • TorchDataLoader (class in dasf.ml.dl.pytorch_lightning) @@ -3827,6 +5274,8 @@

        T

      • traces_file_prefix (dasf.profile.profiler.EventProfiler attribute)
      • train_dataloader() (dasf.ml.dl.pytorch_lightning.TorchDataLoader method) +
      • +
      • train_size (dasf.ml.model_selection.split.train_test_split attribute)
      • train_test_split (class in dasf.ml.model_selection.split)
      • @@ -3837,11 +5286,13 @@

        T

      • transform() (dasf.feature_extraction.GetSubDataframe method)
          -
        • (dasf.feature_extraction.GetSubeCubeArray method) +
        • (dasf.feature_extraction.SampleDataframe method)
        • -
        • (dasf.feature_extraction.transform.GetSubDataframe method) +
        • (dasf.feature_extraction.transforms.GetSubCubeArray method)
        • -
        • (dasf.feature_extraction.transform.GetSubeCubeArray method) +
        • (dasf.feature_extraction.transforms.GetSubDataframe method) +
        • +
        • (dasf.feature_extraction.transforms.SampleDataframe method)
        • (dasf.transforms.base.MappedTransform method)
        • @@ -3880,6 +5331,12 @@

          T

          +
        • trim (dasf.transforms.base.MappedTransform attribute) + +
        • trim_chunk_location() (in module dasf.utils.funcs) @@ -3890,14 +5347,130 @@

          T

          U

            +
          • visualize() (dasf.pipeline.Pipeline method) + +
          • VisualizeDaskData (class in dasf.debug)
              @@ -3954,10 +5549,24 @@

              W

              X

              +

              Y

              + + +
              +

              Z

              + diff --git a/docs/searchindex.js b/docs/searchindex.js index 690bf2b..f237f9d 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"Analysing the profile data": [[79, "Analysing-the-profile-data"]], "Attributes": [[1, "attributes"], [4, "attributes"], [7, "attributes"], [8, "attributes"], [19, "attributes"], [20, "attributes"], [34, "attributes"], [37, "attributes"], [38, "attributes"], [39, "attributes"], [40, "attributes"], [41, "attributes"], [41, "id4"], [41, "id6"], [41, "id11"], [42, "attributes"], [42, "id4"], [42, "id6"], [42, "id11"], [48, "attributes"], [53, "attributes"], [56, "attributes"], [63, "attributes"], [65, "attributes"], [67, "attributes"], [69, "attributes"]], "Basic Usage": [[80, "Basic-Usage"]], "Classes": [[1, "classes"], [2, "classes"], [3, "classes"], [4, "classes"], [5, "classes"], [6, "classes"], [7, "classes"], [8, "classes"], [9, "classes"], [11, "classes"], [12, "classes"], [13, 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API": [[73, "dasf-as-a-simple-api"]], "DASF is an Accelerated and Scalable Framework": [[70, "dasf-is-an-accelerated-and-scalable-framework"]], "Development version": [[71, "development-version"]], "Enabling profiling": [[79, "Enabling-profiling"]], "Examples": [[2, "examples"], [2, "id5"], [2, "id8"], [4, "examples"], [4, "id91"], [11, "examples"], [13, "examples"], [14, "examples"], [15, "examples"], [15, "id9"], [15, "id25"], [15, "id42"], [15, "id76"], [15, "id110"], [16, "examples"], [17, "examples"], [18, "examples"], [19, "examples"], [20, "examples"], [34, "examples"], [55, "examples"], [55, "id1"]], "Function Bottleneck Report": [[79, "Function-Bottleneck-Report"]], "Functions": [[27, "functions"], [46, "functions"], [53, "functions"], [54, "functions"], [57, "functions"], [64, "functions"], [65, "functions"], [67, "functions"], [68, "functions"], [69, "functions"]], "Implemented Machine Learning Algorithms": [[72, "implemented-machine-learning-algorithms"]], "Indices and tables": [[70, "indices-and-tables"]], "Installation Guide": [[71, null]], "Model Inference": [[80, "Model-Inference"]], "Module Contents": [[1, "module-contents"], [2, "module-contents"], [3, "module-contents"], [5, "module-contents"], [7, "module-contents"], [9, "module-contents"], [11, "module-contents"], [12, "module-contents"], [13, "module-contents"], [14, "module-contents"], [16, "module-contents"], [17, "module-contents"], [18, "module-contents"], [20, "module-contents"], [21, "module-contents"], [24, "module-contents"], [25, "module-contents"], [27, "module-contents"], [30, "module-contents"], [32, "module-contents"], [33, "module-contents"], [34, "module-contents"], [36, "module-contents"], [38, "module-contents"], [40, "module-contents"], [42, "module-contents"], [44, "module-contents"], [45, "module-contents"], [46, "module-contents"], [48, "module-contents"], [49, "module-contents"], [51, "module-contents"], [52, "module-contents"], [53, "module-contents"], [55, 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"Principles", "Tutorials", "Tutorial 1 - A Quick Demo", "Tutorial 2 - How to extend DASF Datasets", "Tutorial 3 - How Create Your Own Trasform", "Tutorial 4 - How Create an Agnostic Pipeline", "Tutorial 5 - Using profiler", "Tutorial 6 - How Use the ApplyPatches Operator", "Tutorial 7 - Trainig a PyTorch Lightning model", "Tutorial 8 - HDBSCAN Differences between CPU and GPU versions"], "titleterms": {"1": 75, "2": 76, "3": 77, "4": 78, "5": 79, "6": 80, "7": 81, "8": 82, "A": 75, "acceler": 70, "agglom": 11, "agnost": 78, "algorithm": 72, "also": [2, 4, 13, 15, 16, 19, 20, 34, 37, 38], "an": [70, 78], "analys": 79, "analysi": 53, "api": [0, 73], "applypatch": 80, "attribut": [1, 4, 7, 8, 19, 20, 34, 37, 38, 39, 40, 41, 42, 48, 53, 56, 63, 65, 67, 69], "balanc": 79, "base": [1, 30, 45, 58], "basic": 80, "benchmark": 63, "between": 82, "bootleneck": 79, "bottleneck": 79, "class": [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 32, 33, 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              • ZarrToArray (class in dasf.transforms) diff --git a/docs/objects.inv b/docs/objects.inv index c1c474c..8a65cbe 100644 Binary files a/docs/objects.inv and b/docs/objects.inv differ diff --git a/docs/py-modindex.html b/docs/py-modindex.html index a483cc3..f41d798 100644 --- a/docs/py-modindex.html +++ b/docs/py-modindex.html @@ -140,7 +140,7 @@

                Python Module Index

                  - dasf.feature_extraction.transform + dasf.feature_extraction.transforms