Docs: some rewordings

tritemio · Nov 17, 2017 · d5f3e7c · d5f3e7c
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diff --git a/docs/notebooks/Simple FCS example.ipynb b/docs/notebooks/Simple FCS example.ipynb
@@ -110,7 +110,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Then load the timestamps in two arrays `t` and `u`:"
+    "Then we load the timestamps in two arrays `t` and `u`:"
    ]
   },
   {
@@ -147,7 +147,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Timestamps need to be monotonic:"
+    "Timestamps need to be monotonic, let's check:"
    ]
   },
   {
@@ -168,7 +168,7 @@
     "\n",
     "To avoid afterpulsing, we can compute the cross-correlation function (CCF) between D and A channels.\n",
     "\n",
-    "We first create the lag bins array with the [make_loglags()](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.make_loglags) function:"
+    "We first create the array of time-lag bins using [make_loglags()](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.make_loglags):"
    ]
   },
   {
@@ -179,7 +179,8 @@
    "source": [
     "# compute lags in sec. then convert to timestamp units\n",
     "bins_per_dec = 20\n",
-    "bins = pyc.make_loglags(-6, 1, bins_per_dec)[bins_per_dec // 2:] / unit"
+    "bins = pyc.make_loglags(-6, 1, bins_per_dec)[bins_per_dec // 2:] / unit\n",
+    "print('Number of time-lag bins:', bins.size)"
    ]
   },
   {
@@ -246,7 +247,7 @@
     "\n",
     "Here, for the sake of the example, we will just fit the simple 2D model.\n",
     "\n",
-    "Let's start defining the model functions and the array of time-lags:"
+    "Let's start defining the model functions and the array of time-lags `tau`:"
    ]
   },
   {
@@ -276,7 +277,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we build a \"fitting model\" with [lmfit](https://lmfit.github.io/lmfit-py/) \n",
+    "Now, we build a \"fitting model\" with [lmfit](https://lmfit.github.io/lmfit-py/) \n",
     "and use it to fit the CCF curve `Gn`:"
    ]
   },
@@ -361,7 +362,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "version": "3.6.2"
   },
   "toc": {
    "colors": {

diff --git a/docs/theory.rst b/docs/theory.rst
@@ -73,14 +73,14 @@ For FCS we normally want the normalized CCF, that is:
            \frac{(T-\Delta\tau_k)}{\Delta\tau_k}
     :label: Gk
 
-Eq. :eq:`Ck` and :eq:`Gk` are implemented by :func:`pcorrelate`,
-where the argument `normalize` allows choosing between the normalized
-and unnormalized version.
+Both eq. :eq:`Ck` and :eq:`Gk` are implemented by :func:`pcorrelate`.
+You can choose between the normalized and unnormalized version with the
+input argument `normalize`.
 
 .. note::
-    Due to a typo, in *Laurence 2006*, the expression for *G(k)* (they call it
-    :math:`C_{AB}(\tau)`) does not include the :math:`\Delta\tau_k`
-    in the denominator.
+    Due to a typo, in *Laurence 2006*, the expression for *G(k)*
+    (which they call :math:`C_{AB}(\tau)`) is missing the term
+    :math:`\Delta\tau_k` in the denominator.
 
 References
 ----------