Plotting helpers for TiledDataset (#408)

* Add broken plot method for TiledDataset

* Need projection in plots

* Just plot the first image of each tile

* Clear x and y labels except on the middle edge tiles

Assumes a grid of 3x3 tiles, not sure if this will always be true

* Make plot function plot at a user-supplied index

* Also pass plot kwargs through to ds.plot

* More robust axis labelling

* Swap tile titles for suptitle with timestamp

* Optionally share colour scaling

Just takes the clim values from each tile and uses the highest and lowest

* Add figure test for `TiledDataset.plot()`

* Update dkist/dataset/tiled_dataset.py

Co-authored-by: Stuart Mumford <[email protected]>

* Add filter to tar file extraction

This is to avoid a deprecation warning when it's not specified
explicitly, but is just using the default anyway.

* Use sample data for TiledDataset plot test and update hashes

* Add changelog

* Try downloading data before tests instead of during

* Make sure we're not running figure tests outside the figure test env

* Move sample data import into figure test

* Yeah still need this

* Explicit is better than implicit

* Maybe this will help

* Rebin tileddataset for plot test to reduce memory usage

* Try more memory again and smaller plots

* Looks like we don't actually need this after all?

* Update dkist/dataset/tests/test_tiled_dataset.py

Co-authored-by: Stuart Mumford <[email protected]>

* Update dkist/dataset/tests/test_tiled_dataset.py

Co-authored-by: Stuart Mumford <[email protected]>

* Resinstate codecov upload in figure test

* Update scale arg name to zscale

* Update figure hashes

* Add codecov_upload script for circle CI

Not sure how this wasn't already here

* Update TiledDataset plot title

---------

Co-authored-by: Stuart Mumford <[email protected]>

.circleci/codecov_upload.sh

@@ -0,0 +1,9 @@
+#!/bin/bash -e
+curl https://keybase.io/codecovsecurity/pgp_keys.asc | gpg --no-default-keyring --keyring trustedkeys.gpg --import
+curl -Os https://uploader.codecov.io/latest/linux/codecov
+curl -Os https://uploader.codecov.io/latest/linux/codecov.SHA256SUM
+curl -Os https://uploader.codecov.io/latest/linux/codecov.SHA256SUM.sig
+gpgv codecov.SHA256SUM.sig codecov.SHA256SUM
+shasum -a 256 -c codecov.SHA256SUM
+chmod +x codecov
+./codecov "$@"

.circleci/config.yml

@@ -43,9 +43,9 @@ jobs:
       - run: *apt-install
       - run: pip install --user -U tox tox-pypi-filter
       - run: tox -v
-      # - run:
-      #     name: Running codecov
-      #     command: bash -e .circleci/codecov_upload.sh -f ".tmp/${TOXENV}/coverage.xml"
+      - run:
+          name: Running codecov
+          command: bash -e .circleci/codecov_upload.sh -f ".tmp/${TOXENV}/coverage.xml"
       - store_artifacts:
           path: .tmp/<< parameters.jobname >>/figure_test_images
 

changelog/408.feature.rst

@@ -0,0 +1 @@
+Add `TiledDataset.plot()` quicklook method.

dkist/data/_sample.py

@@ -57,7 +57,7 @@ def _download_and_extract_sample_data(names, overwrite, path):
     for i, tarpath in enumerate(results):
         output_path = path / file_folder[Path(tarpath).name]
         with tarfile.open(tarpath, "r:*") as tar:
-            tar.extractall(path=output_path, filter="data")
+            tar.extractall(path=output_path, filter=tarfile.fully_trusted_filter)
         results[i] = output_path
 
     return results

dkist/dataset/tests/test_tiled_dataset.py

@@ -1,9 +1,11 @@
 import copy
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pytest
 
-from dkist import Dataset, TiledDataset
+from dkist import Dataset, TiledDataset, load_dataset
+from dkist.tests.helpers import figure_test
 
 
 def test_tiled_dataset(simple_tiled_dataset, dataset):
@@ -59,3 +61,17 @@ def test_tiled_dataset_from_components(dataset):
         assert ds.files == fm
         assert ds.meta["inventory"] is inventory
         assert ds.meta["headers"] is headers
+
+
+@figure_test
+@pytest.mark.parametrize("share_zscale", [True, False], ids=["share_zscale", "indpendent_zscale"])
+def test_tileddataset_plot(share_zscale):
+    from dkist.data.sample import VBI_AJQWW
+    ds = load_dataset(VBI_AJQWW)
+    newtiles = []
+    for tile in ds.flat:
+        newtiles.append(tile.rebin((1, 8, 8), operation=np.sum))
+    ds = TiledDataset(np.array(newtiles).reshape(ds.shape), inventory=ds.inventory)
+    fig = plt.figure(figsize=(600, 800))
+    ds.plot(0, share_zscale=share_zscale)
+    return plt.gcf()

dkist/dataset/tiled_dataset.py

@@ -7,6 +7,7 @@
 """
 from collections.abc import Collection
 
+import matplotlib.pyplot as plt
 import numpy as np
 
 from astropy.table import vstack
@@ -124,5 +125,30 @@ def shape(self):
         """
         return self._data.shape
 
-    # TODO: def plot()
+    def plot(self, slice_index: int, share_zscale=False, **kwargs):
+        vmin, vmax = np.inf, 0
+        fig = plt.figure()
+        for i, tile in enumerate(self.flat):
+            ax = fig.add_subplot(self.shape[0], self.shape[1], i+1, projection=tile[0].wcs)
+            tile[slice_index].plot(axes=ax, **kwargs)
+            if i == 0:
+                xlabel = ax.coords[0].get_axislabel() or ax.coords[0]._get_default_axislabel()
+                ylabel = ax.coords[1].get_axislabel() or ax.coords[1]._get_default_axislabel()
+                for coord in ax.coords:
+                    if "b" in coord.axislabels.get_visible_axes():
+                        fig.supxlabel(xlabel, y=0.05)
+                    if "l" in coord.axislabels.get_visible_axes():
+                        fig.supylabel(ylabel, x=0.05)
+            axmin, axmax = ax.get_images()[0].get_clim()
+            vmin = axmin if axmin < vmin else vmin
+            vmax = axmax if axmax > vmax else vmax
+            ax.set_ylabel(" ")
+            ax.set_xlabel(" ")
+        if share_zscale:
+            for ax in fig.get_axes():
+                ax.get_images()[0].set_clim(vmin, vmax)
+        timestamp = self[0, 0].axis_world_coords("time")[-1].iso[slice_index]
+        fig.suptitle(f"{self.inventory['instrumentName']} Dataset ({self.inventory['datasetId']}) at time {timestamp} (slice={slice_index})", y=0.95)
+        return fig
+
     # TODO: def regrid()

dkist/tests/figure_hashes_mpl_391_ft_261_astropy_611_animators_111_ndcube_222.json

@@ -5,5 +5,7 @@
   "dkist.dataset.tests.test_plotting.test_2d_plot[aslice0]": "b31423d5ec45941849564f4ec7e276f2c52a0fa5038ce0b3c8d4af1b7f848a1d",
   "dkist.dataset.tests.test_plotting.test_2d_plot[aslice1]": "cbb84fbae51d8238803f8f0d6820c575f024fe54b1656f1b181dc4ec645e9ff9",
   "dkist.dataset.tests.test_plotting.test_2d_plot[aslice2]": "132c5615832daff457dacb4cb770498f1fbb4460a5b90b5d4d01d224c70eeb28",
-  "dkist.dataset.tests.test_plotting.test_2d_plot2": "409b5a10ad8ccf005331261505e63ce8febdc38eb8b5a34f8863e567e3cccb9c"
+  "dkist.dataset.tests.test_plotting.test_2d_plot2": "409b5a10ad8ccf005331261505e63ce8febdc38eb8b5a34f8863e567e3cccb9c",
+  "dkist.dataset.tests.test_tiled_dataset.test_tileddataset_plot[share_zscale]": "08d480bf75e3461a3eb09b0fb78ac9a7e88ac6d80194f15a58ef531c7fc2bb53",
+  "dkist.dataset.tests.test_tiled_dataset.test_tileddataset_plot[indpendent_zscale]": "4d767a558ab1e0bd1bfeac5b8311a236e0ddcee484ae2b49cf32ffa8f0a4a93a"
 }

pytest.ini

@@ -31,6 +31,7 @@ addopts =
     --doctest-rst
     -p no:unraisableexception
     -p no:threadexception
+    -m "not mpl_image_compare"
 mpl-results-path = figure_test_images
 mpl-deterministic = true
 filterwarnings =

tox.ini

@@ -58,6 +58,7 @@ extras =
 commands_pre =
     oldestdeps: minimum_dependencies dkist --filename requirements-min.txt
     oldestdeps: pip install -r requirements-min.txt cryptography<42 jsonschema==4.0.1
+    figure: python -c "from dkist.data.sample import download_all_sample_data; download_all_sample_data()"
     pip freeze --all --no-input
 commands =
     figure: /bin/sh -c "mkdir -p ./figure_test_images; python -c 'import matplotlib as mpl; print(mpl.ft2font.__file__, mpl.ft2font.__freetype_version__, mpl.ft2font.__freetype_build_type__)' > ./figure_test_images/figure_version_info.txt"