matplotlib · timhoffm · Apr 5, 2021 · Mar 14, 2021 · Mar 16, 2021 · Mar 16, 2021
diff --git a/doc/_templates/layout.html b/doc/_templates/layout.html
@@ -57,6 +57,7 @@
             <li><a href="{{ pathto('users/installing') }}">Installation</a></li>
             <li><a href="{{ pathto('contents') }}">Documentation</a></li>
             <li><a href="{{ pathto('api/index') }}">API</a></li>
+            <li><a href="{{ pathto('plot_types/index') }}">Plot Types</a></li>
             <li><a href="{{ pathto('gallery/index') }}">Examples</a></li>
             <li><a href="{{ pathto('tutorials/index') }}">Tutorials</a></li>
             <li><a href="{{ pathto('devel/index') }}">Contributing</a></li>

diff --git a/doc/conf.py b/doc/conf.py
@@ -151,9 +151,9 @@ def _check_dependencies():
 
 # Sphinx gallery configuration
 sphinx_gallery_conf = {
-    'examples_dirs': ['../examples', '../tutorials'],
+    'examples_dirs': ['../examples', '../tutorials', '../plot_types'],
     'filename_pattern': '^((?!sgskip).)*$',
-    'gallery_dirs': ['gallery', 'tutorials'],
+    'gallery_dirs': ['gallery', 'tutorials', 'plot_types'],
     'doc_module': ('matplotlib', 'mpl_toolkits'),
     'reference_url': {
         'matplotlib': None,

diff --git a/lib/matplotlib/mpl-data/stylelib/mpl_plot_gallery.mplstyle b/lib/matplotlib/mpl-data/stylelib/mpl_plot_gallery.mplstyle
@@ -0,0 +1,19 @@
+# from the Matplotlib cheatsheet as used in our gallery:
+
+axes.grid: True
+axes.axisbelow: True
+
+figure.figsize: 2, 2
+# make it so the axes labels don't show up.  Obviously 
+# not good style for any quantitative analysis:
+figure.subplot.left: 0.01
+figure.subplot.right: 0.99
+figure.subplot.bottom: 0.01
+figure.subplot.top: 0.99
+
+xtick.major.size: 0.0
+ytick.major.size: 0.0
+
+# colors:
+image.cmap    : Blues
+# axes.prop_cycle: cycler('color', ['FF7F0E', '1F77B4', '2CA02C'])
diff --git a/plot_types/A_basic/README.rst b/plot_types/A_basic/README.rst
@@ -0,0 +1,6 @@
+.. _basic_plots:
+
+Basic
+-----
+
+Basic plot types, usually x versus y.  
diff --git a/plot_types/A_basic/a_plot.py b/plot_types/A_basic/a_plot.py
@@ -0,0 +1,25 @@
+"""
+======================
+plot([X], Y, [fmt]...)
+======================
+"""
-"""
-======================
-plot([X], Y, [fmt]...)
-======================
-"""
+"""
+======
+plot()
+======
+"""
+.. code-block:: none
+
+   plot([X], Y, [fmt]...)
+
+Plot y versus x as lines and/or markers.
+
+Documentation: `matplotlib.axes.Axes.plot()` / `matplotlib.pyplot.plot()`
-"""
-======================
-plot([X], Y, [fmt]...)
-======================
-"""
+"""
+======
+plot()
+======
+"""
+.. code-block:: none
+
+   plot([X], Y, [fmt]...)
+
+Plot y versus x as lines and/or markers.
+
+Documentation: `matplotlib.axes.Axes.plot()` / `matplotlib.pyplot.plot()`
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+X = np.linspace(0, 10, 100)
+Y = 4 + 2 * np.sin(2 * X)
+
+# plot
+fig, ax = plt.subplots()
+
+ax.plot(X, Y, linewidth=2.0)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+plt.show()
diff --git a/plot_types/A_basic/b_scatter.py b/plot_types/A_basic/b_scatter.py
@@ -0,0 +1,27 @@
+"""
+==================
+scatter(X, Y, ...)
+==================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make the data
+np.random.seed(3)
+X = 4 + np.random.normal(0, 2, 24)
+Y = 4 + np.random.normal(0, 2, len(X))
+# size and color:
+S = np.random.uniform(15, 80, len(X))
+
+# plot
+fig, ax = plt.subplots()
+
+ax.scatter(X, Y, s=S, c=-S, cmap=plt.get_cmap('Blues'), vmin=-100, vmax=0)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+plt.show()
diff --git a/plot_types/A_basic/c_bar.py b/plot_types/A_basic/c_bar.py
@@ -0,0 +1,24 @@
+"""
+======================
+bar[h](x, height, ...)
+======================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+plt.style.use('mpl_plot_gallery')
+
+# make data:
+np.random.seed(3)
+X = 0.5 + np.arange(8)
+Y = np.random.uniform(2, 7, len(X))
+
+# plot
+fig, ax = plt.subplots()
+
+ax.bar(X, Y, width=1, edgecolor="white", linewidth=0.7)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+plt.show()
diff --git a/plot_types/A_basic/d_stem.py b/plot_types/A_basic/d_stem.py
@@ -0,0 +1,25 @@
+"""
+=================
+stem([x], y, ...)
+=================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+np.random.seed(3)
+X = 0.5 + np.arange(8)
+Y = np.random.uniform(2, 7, len(X))
+
+# plot
+fig, ax = plt.subplots()
+
+ax.stem(X, Y, bottom=0, linefmt="-", markerfmt="d")
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+plt.show()
diff --git a/plot_types/A_basic/e_step.py b/plot_types/A_basic/e_step.py
@@ -0,0 +1,25 @@
+"""
+=====================
+step(x, y, where=...)
+=====================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+np.random.seed(3)
+X = 0.5 + np.arange(8)
+Y = np.random.uniform(2, 7, len(X))
+
+# plot
+fig, ax = plt.subplots()
+
+ax.step(X, Y, linewidth=2.5)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+plt.show()
diff --git a/plot_types/A_basic/f_pie.py b/plot_types/A_basic/f_pie.py
@@ -0,0 +1,31 @@
+"""
+====================
+pie(X, explode, ...)
+====================
+"""
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+
+# make data
+X = [1, 2, 3, 4]
+    colors = np.zeros((len(X), 4))
+colors[:] = mpl.colors.to_rgba("C0")
+colors[:, 3] = np.linspace(0.25, 0.75, len(X))
+
+# plot
+fig, ax = plt.subplots()
+ax.pie(X, colors=["white"]*len(X), radius=3, center=(4, 4),
+        wedgeprops={"linewidth": 1, "edgecolor": "white"}, frame=True)
+ax.pie(X, colors=colors, radius=3, center=(4, 4),
+        wedgeprops={"linewidth": 1, "edgecolor": "white"}, frame=True)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+
+plt.show()
diff --git a/plot_types/A_basic/g_fill_between.py b/plot_types/A_basic/g_fill_between.py
@@ -0,0 +1,28 @@
+"""
+=================================
+fill[_between][x](X, Y1, Y2, ...)
+=================================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+np.random.seed(1)
+X = np.linspace(0, 8, 16)
+Y1 = 3 + 4*X/8 + np.random.uniform(0.0, 0.5, len(X))
+Y2 = 1 + 2*X/8 + np.random.uniform(0.0, 0.5, len(X))
+
+# plot
+fig, ax = plt.subplots()
+
+ax.fill_between(X, Y1, Y2, alpha=.5, linewidth=0)
+ax.plot(X, (Y1+Y2)/2, linewidth=2.5)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+
+plt.show()
diff --git a/plot_types/B_arrays/README.rst b/plot_types/B_arrays/README.rst
@@ -0,0 +1,6 @@
+.. _array_plots:
+
+Plots of arrays and fields
+--------------------------
+
+Plotting for arrays of data ``Z(x, y)`` and fields ``U(x, y), V(x, y)``
diff --git a/plot_types/B_arrays/a_imshow.py b/plot_types/B_arrays/a_imshow.py
@@ -0,0 +1,26 @@
+"""
+=======================
+imshow(Z, [cmap=], ...)
+=======================
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
+Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
+Z = Z - Z.min()
+Z = Z[::16, ::16]
+
+# plot
+fig, ax = plt.subplots()
+
+ax.imshow(Z, extent=[0, 8, 0, 8], interpolation="nearest",
+            cmap=plt.get_cmap('Blues'), vmin=0, vmax=1.6)
+
+ax.set_xticks([])
+ax.set_yticks([])
+plt.show()
diff --git a/plot_types/B_arrays/b_pcolormesh.py b/plot_types/B_arrays/b_pcolormesh.py
@@ -0,0 +1,33 @@
+"""
+===================================
+pcolormesh([X, Y], Z, [cmap=], ...)
+===================================
+
+`~.axes.Axes.pcolormesh` is more flexible than `~.axes.Axes.imshow` in that
+the x and y vectors need not be equally spaced (indeed they can be skewed).
+
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make full-res data
+X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
+Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
+Z = Z - Z.min()
+
+# sample unevenly in x:
+dx = np.sqrt((np.arange(16) - 8)**2) + 6
+dx = np.floor(dx / sum(dx) * 255)
+xint = np.cumsum(dx).astype('int')
+X = X[0, xint]
+Y = Y[::8, 0]
+Z = Z[::8, :][:, xint]
+
+# plot
+fig, ax = plt.subplots()
+
+ax.pcolormesh(X, Y, Z, vmin=0, vmax=1.5, shading='nearest')
+
+plt.show()
diff --git a/plot_types/B_arrays/c_contourf.py b/plot_types/B_arrays/c_contourf.py
@@ -0,0 +1,23 @@
+"""
+=====================================
+contour[f]([X, Y], Z, [levels=], ...)
+=====================================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
+Z = (1 - X/2. + X**5 + Y**3)*np.exp(-X**2-Y**2)
+Z = Z - Z.min()
+levs = np.linspace(np.min(Z), np.max(Z), 7)
+
+# plot
+fig, ax = plt.subplots()
+
+plt.contourf(X, Y, Z, levels=levs)
+plt.contour(X, Y, Z, levels=levs, colors="white", linewidths=0.5)
+
+plt.show()
diff --git a/plot_types/B_arrays/d_quiver.py b/plot_types/B_arrays/d_quiver.py
@@ -0,0 +1,27 @@
+"""
+=========================
+quiver([X, Y], U, V, ...)
+=========================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make data
+T = np.linspace(0, 2*np.pi, 8)
+X, Y = 4 + 1 * np.cos(T), 4 + 1 * np.sin(T)
+U, V = 1.5 * np.cos(T), 1.5 * np.sin(T)
+
+# plot
+fig, ax = plt.subplots()
+
+plt.quiver(X, Y, U, V, color="C0", angles='xy',
+            scale_units='xy', scale=0.5, width=.05)
+
+ax.set_xlim(0, 8)
+ax.set_xticks(np.arange(1, 8))
+ax.set_ylim(0, 8)
+ax.set_yticks(np.arange(1, 8))
+
+plt.show()
diff --git a/plot_types/B_arrays/e_streamplot.py b/plot_types/B_arrays/e_streamplot.py
@@ -0,0 +1,26 @@
+"""
+========================
+streamplot([X, Y], U, V)
+========================
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.style.use('mpl_plot_gallery')
+
+# make a stream function:
+X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
+Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
+Z = Z - Z.min()
+# make U and V out of the streamfunction:
+V = np.diff(Z[1:, :], axis=1)
+U = -np.diff(Z[:, 1:], axis=0)
+
+# plot:
+fig, ax = plt.subplots()
+# contour stream function
+ax.contour(X, Y, Z, colors='C1', alpha=0.5, zorder=1, linewidths=3)
+# plot stream plot
+ax.streamplot(X[1:, 1:], Y[1:, 1:], U, V, zorder=2)
+
+plt.show()
diff --git a/plot_types/C_stats/README.rst b/plot_types/C_stats/README.rst
@@ -0,0 +1,6 @@
+.. _stats_plots:
+
+Specialized statistics plots
+============================
+
+Matplotlib has some specialized plots for statistical analysis.