DOC: Add custom :button_text: for all examples

See jupyterlite/jupyterlite-sphinx#157

doc/source/ref/cwt.rst

@@ -90,6 +90,7 @@ A variety of continuous wavelets have been implemented. A list of the available
 wavelet names compatible with ``cwt`` can be obtained by:
 
 .. try_examples::
+  :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelist = pywt.wavelist(kind='continuous')
@@ -207,6 +208,7 @@ sampled at 100 Hz, a center frequency of 1.0 corresponds to ~100 Hz at
 particular wavelet, one would analyze a signal using ``scales >= 2``.
 
 .. try_examples::
+  :button_text: Try it in your browser!
 
     >>> import numpy as np
     >>> import pywt
@@ -237,6 +239,7 @@ frequency fs. This function is useful for specifying the transform as a function
 of frequency directly.
 
 .. try_examples::
+  :button_text: Try it in your browser!
 
     >>> import numpy as np
     >>> import pywt

doc/source/ref/signal-extension-modes.rst

@@ -90,6 +90,7 @@ computations can be performed with the `periodization`_ mode:
 **Example:**
 
 .. try_examples::
+  :button_text: Try it in your browser!
 
     >>> import pywt
     >>> print(pywt.Modes.modes)
@@ -105,6 +106,7 @@ Notice that you can use any of the following ways of passing wavelet and mode
 parameters:
 
 .. try_examples::
+  :button_text: Try it in your browser!
 
   >>> import pywt
   >>> (a, d) = pywt.dwt([1,2,3,4,5,6], 'db2', 'smooth')

doc/source/ref/wavelets.rst

@@ -49,6 +49,7 @@ Custom discrete wavelets are also supported through the
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.Wavelet('db1')
@@ -129,6 +130,7 @@ Custom discrete wavelets are also supported through the
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> def format_array(arr):
     ...     return "[%s]" % ", ".join(["%.14f" % x for x in arr])
@@ -172,6 +174,7 @@ Approximating wavelet and scaling functions - ``Wavelet.wavefun()``
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.Wavelet('db2')
@@ -187,6 +190,7 @@ Approximating wavelet and scaling functions - ``Wavelet.wavefun()``
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.Wavelet('bior3.5')
@@ -240,6 +244,7 @@ from plain Python lists of filter coefficients and a *filter bank-like* object.
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt, math
     >>> c = math.sqrt(2)/2
@@ -274,6 +279,7 @@ from plain Python lists of filter coefficients and a *filter bank-like* object.
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.ContinuousWavelet('gaus1')
@@ -329,6 +335,7 @@ from plain Python lists of filter coefficients and a *filter bank-like* object.
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.ContinuousWavelet('gaus1')
@@ -359,6 +366,7 @@ Approximating wavelet functions - ``ContinuousWavelet.wavefun()``
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.ContinuousWavelet('gaus1')
@@ -376,6 +384,7 @@ Approximating wavelet functions - ``ContinuousWavelet.wavefun()``
   **Example:**
 
   .. try_examples::
+    :button_text: Try it in your browser!
 
     >>> import pywt
     >>> wavelet = pywt.DiscreteContinuousWavelet('db1')