Merge pull request #20509 from timhoffm/doc-plot-types-clean

QuLogic · web-flow · commit dab3974f745a · 2021-06-29T04:42:49.000-04:00
Cleanup plot types
diff --git a/plot_types/arrays/contourf.py b/plot_types/arrays/contourf.py
@@ -12,14 +12,14 @@
 
 # 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 = (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)
+levels = 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)
+ax.contourf(X, Y, Z, levels=levels)
+ax.contour(X, Y, Z, levels=levels, colors="white", linewidths=0.5)
 
 plt.show()
diff --git a/plot_types/arrays/imshow.py b/plot_types/arrays/imshow.py
@@ -19,10 +19,8 @@
 
 # plot
 fig, ax = plt.subplots()
+ax.grid(False)
 
-ax.imshow(Z, extent=[0, 8, 0, 8], interpolation="nearest",
-            cmap=plt.get_cmap('Blues'), vmin=0, vmax=1.6)
-
-ax.set(xticks=[], yticks=[])
+ax.imshow(Z)
 
 plt.show()
diff --git a/plot_types/arrays/pcolormesh.py b/plot_types/arrays/pcolormesh.py
@@ -27,7 +27,8 @@
 
 # plot
 fig, ax = plt.subplots()
+ax.grid(False)
 
-ax.pcolormesh(X, Y, Z, vmin=0, vmax=1.5, shading='nearest')
+ax.pcolormesh(X, Y, Z, vmin=0, vmax=1.5)
 
 plt.show()
diff --git a/plot_types/arrays/quiver.py b/plot_types/arrays/quiver.py
@@ -11,15 +11,15 @@
 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)
+phi = np.linspace(0, 2 * np.pi, 8)
+x, y = 4 + 1 * np.cos(phi), 4 + 1 * np.sin(phi)
+u, v = 1.5 * np.cos(phi), 1.5 * np.sin(phi)
 
 # plot
 fig, ax = plt.subplots()
 
-plt.quiver(X, Y, U, V, color="C0", angles='xy',
-            scale_units='xy', scale=0.5, width=.05)
+ax.quiver(x, y, u, v, color="C0", angles='xy',
+          scale_units='xy', scale=0.5, width=.05)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/basic/bar.py b/plot_types/basic/bar.py
@@ -11,13 +11,13 @@
 
 # make data:
 np.random.seed(3)
-X = 0.5 + np.arange(8)
-Y = np.random.uniform(2, 7, len(X))
+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.bar(x, y, width=1, edgecolor="white", linewidth=0.7)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/basic/pie.py b/plot_types/basic/pie.py
@@ -12,12 +12,12 @@
 
 
 # make data
-X = [1, 2, 3, 4]
-colors = plt.get_cmap('Blues')(np.linspace(0.2, 0.7, len(X)))
+x = [1, 2, 3, 4]
+colors = plt.get_cmap('Blues')(np.linspace(0.2, 0.7, len(x)))
 
 # plot
 fig, ax = plt.subplots()
-ax.pie(X, colors=colors, radius=3, center=(4, 4),
+ax.pie(x, colors=colors, radius=3, center=(4, 4),
        wedgeprops={"linewidth": 1, "edgecolor": "white"}, frame=True)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
diff --git a/plot_types/basic/plot.py b/plot_types/basic/plot.py
@@ -12,13 +12,13 @@
 plt.style.use('mpl_plot_gallery')
 
 # make data
-X = np.linspace(0, 10, 100)
-Y = 4 + 2 * np.sin(2 * X)
+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.plot(x, y, linewidth=2.0)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/basic/scatter_plot.py b/plot_types/basic/scatter_plot.py
@@ -12,15 +12,16 @@
 
 # make the data
 np.random.seed(3)
-X = 4 + np.random.normal(0, 2, 24)
-Y = 4 + np.random.normal(0, 2, len(X))
+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))
+sizes = np.random.uniform(15, 80, len(x))
+colors = 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.scatter(x, y, s=sizes, c=colors, vmin=-100, vmax=0)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/basic/stem.py b/plot_types/basic/stem.py
@@ -12,13 +12,13 @@
 
 # make data
 np.random.seed(3)
-X = 0.5 + np.arange(8)
-Y = np.random.uniform(2, 7, len(X))
+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.stem(x, y)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/basic/step.py b/plot_types/basic/step.py
@@ -12,13 +12,13 @@
 
 # make data
 np.random.seed(3)
-X = 0.5 + np.arange(8)
-Y = np.random.uniform(2, 7, len(X))
+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.step(x, y, linewidth=2.5)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/stats/barbs.py b/plot_types/stats/barbs.py
@@ -14,14 +14,13 @@
 np.random.seed(1)
 X = [[2, 4, 6]]
 Y = [[1.5, 3, 2]]
-U = -np.ones((1, 3)) * 0
-V = -np.ones((1, 3)) * np.linspace(50, 100, 3)
+U = np.zeros_like(X)
+V = -np.ones_like(X) * np.linspace(50, 100, 3)
 
 # plot:
 fig, ax = plt.subplots()
 
-ax.barbs(X, Y, U, V, barbcolor="C0", flagcolor="C0",
-            length=10, linewidth=1.5)
+ax.barbs(X, Y, U, V, barbcolor="C0", flagcolor="C0", length=10, linewidth=1.5)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/stats/errorbar_plot.py b/plot_types/stats/errorbar_plot.py
@@ -1,6 +1,6 @@
 """
 ==========================
-errorbar(X, Y, xerr, yerr)
+errorbar(x, y, yerr, xerr)
 ==========================
 
 See `~matplotlib.axes.Axes.errorbar`.
@@ -12,14 +12,14 @@
 
 # make data:
 np.random.seed(1)
-X = [2, 4, 6]
-Y = [4, 5, 4]
-E = np.random.uniform(0.5, 1.5, 3)
+x = [2, 4, 6]
+y = [4, 5, 4]
+yerr = np.random.uniform(0.5, 1.5, 3)
 
 # plot:
 fig, ax = plt.subplots()
 
-ax.errorbar(X, Y, E, linewidth=2, capsize=6)
+ax.errorbar(x, y, yerr, linewidth=2, capsize=6)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/stats/eventplot.py b/plot_types/stats/eventplot.py
@@ -12,13 +12,13 @@
 
 # make data:
 np.random.seed(1)
-X = [2, 4, 6]
+x = [2, 4, 6]
 D = np.random.gamma(4, size=(3, 50))
 
 # plot:
 fig, ax = plt.subplots()
 
-ax.eventplot(D, orientation="vertical", lineoffsets=X, linewidth=0.75)
+ax.eventplot(D, orientation="vertical", lineoffsets=x, linewidth=0.75)
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/stats/hexbin.py b/plot_types/stats/hexbin.py
@@ -13,7 +13,7 @@
 # make data: correlated + noise
 np.random.seed(1)
 x = np.random.randn(5000)
-y = 1.2 * x + np.random.randn(5000)/3
+y = 1.2 * x + np.random.randn(5000) / 3
 
 # plot:
 fig, ax = plt.subplots()
diff --git a/plot_types/stats/hist2d.py b/plot_types/stats/hist2d.py
@@ -13,7 +13,7 @@
 # make data: correlated + noise
 np.random.seed(1)
 x = np.random.randn(5000)
-y = 1.2 * x + np.random.randn(5000)/3
+y = 1.2 * x + np.random.randn(5000) / 3
 
 # plot:
 fig, ax = plt.subplots()
diff --git a/plot_types/stats/hist_plot.py b/plot_types/stats/hist_plot.py
@@ -1,6 +1,6 @@
 """
 =======
-hist(X)
+hist(x)
 =======
 
 See `~matplotlib.axes.Axes.hist`.
@@ -12,12 +12,12 @@
 
 # make data
 np.random.seed(1)
-X = 4 + np.random.normal(0, 1.5, 200)
+x = 4 + np.random.normal(0, 1.5, 200)
 
 # plot:
 fig, ax = plt.subplots()
 
-ax.hist(X, bins=8, linewidth=0.5, edgecolor="white")
+ax.hist(x, bins=8, linewidth=0.5, edgecolor="white")
 
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/stats/violin.py b/plot_types/stats/violin.py
@@ -17,10 +17,10 @@
 # plot:
 fig, ax = plt.subplots()
 
-VP = ax.violinplot(D, [2, 4, 6], widths=2,
-                    showmeans=False, showmedians=False, showextrema=False)
+vp = ax.violinplot(D, [2, 4, 6], widths=2,
+                   showmeans=False, showmedians=False, showextrema=False)
 # styling:
-for body in VP['bodies']:
+for body in vp['bodies']:
     body.set_alpha(0.9)
 ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
        ylim=(0, 8), yticks=np.arange(1, 8))
diff --git a/plot_types/unstructured/tricontour.py b/plot_types/unstructured/tricontour.py
@@ -12,13 +12,13 @@
 
 # make structured 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 = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 Z = Z - Z.min()
 
 # sample it to make unstructured x, y, z
 np.random.seed(1)
-ysamp = np.random.randint(0, high=256, size=250)
-xsamp = np.random.randint(0, high=256, size=250)
+ysamp = np.random.randint(0, 256, size=250)
+xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 z = Z[ysamp, xsamp]
@@ -27,8 +27,8 @@
 fig, ax = plt.subplots()
 
 ax.plot(x, y, '.k', alpha=0.5)
-levs = np.linspace(np.min(Z), np.max(Z), 7)
-ax.tricontourf(x, y, z, levels=levs)
+levels = np.linspace(np.min(Z), np.max(Z), 7)
+ax.tricontourf(x, y, z, levels=levels)
 
 ax.set(xlim=(-3, 3), ylim=(-3, 3))
 
diff --git a/plot_types/unstructured/tripcolor.py b/plot_types/unstructured/tripcolor.py
@@ -17,8 +17,8 @@
 
 # sample it to make unstructured x, y, z
 np.random.seed(1)
-ysamp = np.random.randint(0, high=256, size=250)
-xsamp = np.random.randint(0, high=256, size=250)
+ysamp = np.random.randint(0, 256, size=250)
+xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 z = Z[ysamp, xsamp]
diff --git a/plot_types/unstructured/triplot.py b/plot_types/unstructured/triplot.py
@@ -15,8 +15,8 @@
 
 # sample it to make x, y, z
 np.random.seed(1)
-ysamp = np.random.randint(0, high=256, size=250)
-xsamp = np.random.randint(0, high=256, size=250)
+ysamp = np.random.randint(0, 256, size=250)
+xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 
