diff --git a/examples/color/color_demo.py b/examples/color/color_demo.py index f46f52507352..8a161442184b 100644 --- a/examples/color/color_demo.py +++ b/examples/color/color_demo.py @@ -48,9 +48,9 @@ # 3) gray level string: ax.set_title('Voltage vs. time chart', color='0.7') # 4) single letter color string -ax.set_xlabel('time (s)', color='c') +ax.set_xlabel('Time [s]', color='c') # 5) a named color: -ax.set_ylabel('voltage (mV)', color='peachpuff') +ax.set_ylabel('Voltage [mV]', color='peachpuff') # 6) a named xkcd color: ax.plot(t, s, 'xkcd:crimson') # 7) Cn notation: diff --git a/examples/color/custom_cmap.py b/examples/color/custom_cmap.py index 21354fc3fd93..a99127d972e6 100644 --- a/examples/color/custom_cmap.py +++ b/examples/color/custom_cmap.py @@ -42,7 +42,7 @@ If, as in this example, there are no discontinuities in the r, g, and b components, then it is quite simple: the second and third element of -each tuple, above, is the same--call it "``y``". The first element ("``x``") +each tuple, above, is the same -- call it "``y``". The first element ("``x``") defines interpolation intervals over the full range of 0 to 1, and it must span that whole range. In other words, the values of ``x`` divide the 0-to-1 range into a set of segments, and ``y`` gives the end-point color diff --git a/examples/lines_bars_and_markers/cohere.py b/examples/lines_bars_and_markers/cohere.py index 370149695398..7881a0a31b1e 100644 --- a/examples/lines_bars_and_markers/cohere.py +++ b/examples/lines_bars_and_markers/cohere.py @@ -16,19 +16,19 @@ nse1 = np.random.randn(len(t)) # white noise 1 nse2 = np.random.randn(len(t)) # white noise 2 -# Two signals with a coherent part at 10Hz and a random part +# Two signals with a coherent part at 10 Hz and a random part s1 = np.sin(2 * np.pi * 10 * t) + nse1 s2 = np.sin(2 * np.pi * 10 * t) + nse2 fig, axs = plt.subplots(2, 1) axs[0].plot(t, s1, t, s2) axs[0].set_xlim(0, 2) -axs[0].set_xlabel('time') +axs[0].set_xlabel('Time') axs[0].set_ylabel('s1 and s2') axs[0].grid(True) cxy, f = axs[1].cohere(s1, s2, 256, 1. / dt) -axs[1].set_ylabel('coherence') +axs[1].set_ylabel('Coherence') fig.tight_layout() plt.show() diff --git a/examples/lines_bars_and_markers/csd_demo.py b/examples/lines_bars_and_markers/csd_demo.py index d4d1e1d7a967..8894333f94d0 100644 --- a/examples/lines_bars_and_markers/csd_demo.py +++ b/examples/lines_bars_and_markers/csd_demo.py @@ -33,7 +33,7 @@ ax1.plot(t, s1, t, s2) ax1.set_xlim(0, 5) -ax1.set_xlabel('time') +ax1.set_xlabel('Time') ax1.set_ylabel('s1 and s2') ax1.grid(True) diff --git a/examples/pyplots/fig_axes_labels_simple.py b/examples/pyplots/fig_axes_labels_simple.py index 41423b0b4845..353f09477dfd 100644 --- a/examples/pyplots/fig_axes_labels_simple.py +++ b/examples/pyplots/fig_axes_labels_simple.py @@ -11,8 +11,8 @@ fig = plt.figure() fig.subplots_adjust(top=0.8) ax1 = fig.add_subplot(211) -ax1.set_ylabel('volts') -ax1.set_title('a sine wave') +ax1.set_ylabel('Voltage [V]') +ax1.set_title('A sine wave') t = np.arange(0.0, 1.0, 0.01) s = np.sin(2 * np.pi * t) @@ -23,7 +23,7 @@ ax2 = fig.add_axes([0.15, 0.1, 0.7, 0.3]) n, bins, patches = ax2.hist(np.random.randn(1000), 50) -ax2.set_xlabel('time (s)') +ax2.set_xlabel('Time [s]') plt.show() diff --git a/examples/pyplots/pyplot_mathtext.py b/examples/pyplots/pyplot_mathtext.py index af4db39a4e95..a62dd6d95da0 100644 --- a/examples/pyplots/pyplot_mathtext.py +++ b/examples/pyplots/pyplot_mathtext.py @@ -16,8 +16,8 @@ plt.text(1, -0.6, r'$\sum_{i=0}^\infty x_i$', fontsize=20) plt.text(0.6, 0.6, r'$\mathcal{A}\mathrm{sin}(2 \omega t)$', fontsize=20) -plt.xlabel('time (s)') -plt.ylabel('volts (mV)') +plt.xlabel('Time [s]') +plt.ylabel('Voltage [mV]') plt.show() ############################################################################# diff --git a/tutorials/advanced/path_tutorial.py b/tutorials/advanced/path_tutorial.py index 19632ce42964..70bb5998cecb 100644 --- a/tutorials/advanced/path_tutorial.py +++ b/tutorials/advanced/path_tutorial.py @@ -76,11 +76,11 @@ # ============== # # Some of the path components require multiple vertices to specify them: -# for example CURVE 3 is a `bézier +# for example CURVE 3 is a `Bézier # `_ curve with one # control point and one end point, and CURVE4 has three vertices for the # two control points and the end point. The example below shows a -# CURVE4 Bézier spline -- the bézier curve will be contained in the +# CURVE4 Bézier spline -- the Bézier curve will be contained in the # convex hull of the start point, the two control points, and the end # point @@ -139,8 +139,8 @@ # for each histogram bar: the rectangle width is the bin width and the # rectangle height is the number of datapoints in that bin. First we'll # create some random normally distributed data and compute the -# histogram. Because numpy returns the bin edges and not centers, the -# length of ``bins`` is 1 greater than the length of ``n`` in the +# histogram. Because NumPy returns the bin edges and not centers, the +# length of ``bins`` is one greater than the length of ``n`` in the # example below:: # # # histogram our data with numpy @@ -159,10 +159,10 @@ # # Now we have to construct our compound path, which will consist of a # series of ``MOVETO``, ``LINETO`` and ``CLOSEPOLY`` for each rectangle. -# For each rectangle, we need 5 vertices: 1 for the ``MOVETO``, 3 for -# the ``LINETO``, and 1 for the ``CLOSEPOLY``. As indicated in the -# table above, the vertex for the closepoly is ignored but we still need -# it to keep the codes aligned with the vertices:: +# For each rectangle, we need five vertices: one for the ``MOVETO``, +# three for the ``LINETO``, and one for the ``CLOSEPOLY``. As indicated +# in the table above, the vertex for the closepoly is ignored but we still +# need it to keep the codes aligned with the vertices:: # # nverts = nrects*(1+3+1) # verts = np.zeros((nverts, 2)) diff --git a/tutorials/intermediate/artists.py b/tutorials/intermediate/artists.py index 22793ddd5fd0..e2cf55fd5992 100644 --- a/tutorials/intermediate/artists.py +++ b/tutorials/intermediate/artists.py @@ -123,8 +123,8 @@ class in the Matplotlib API, and the one you will be working with most fig = plt.figure() fig.subplots_adjust(top=0.8) ax1 = fig.add_subplot(211) -ax1.set_ylabel('volts') -ax1.set_title('a sine wave') +ax1.set_ylabel('Voltage [V]') +ax1.set_title('A sine wave') t = np.arange(0.0, 1.0, 0.01) s = np.sin(2*np.pi*t) @@ -136,7 +136,7 @@ class in the Matplotlib API, and the one you will be working with most ax2 = fig.add_axes([0.15, 0.1, 0.7, 0.3]) n, bins, patches = ax2.hist(np.random.randn(1000), 50, facecolor='yellow', edgecolor='yellow') -ax2.set_xlabel('time (s)') +ax2.set_xlabel('Time [s]') plt.show() diff --git a/tutorials/intermediate/constrainedlayout_guide.py b/tutorials/intermediate/constrainedlayout_guide.py index 84cbf8c0447f..3734df1bd5d6 100644 --- a/tutorials/intermediate/constrainedlayout_guide.py +++ b/tutorials/intermediate/constrainedlayout_guide.py @@ -263,7 +263,7 @@ def example_plot(ax, fontsize=12, hide_labels=False): ########################################## # If there are more than two columns, the *wspace* is shared between them, -# so here the wspace is divided in 2, with a *wspace* of 0.1 between each +# so here the wspace is divided in two, with a *wspace* of 0.1 between each # column: fig, axs = plt.subplots(2, 3, layout="constrained") diff --git a/tutorials/introductory/pyplot.py b/tutorials/introductory/pyplot.py index ebe49df9d3b0..9b15a956efb8 100644 --- a/tutorials/introductory/pyplot.py +++ b/tutorials/introductory/pyplot.py @@ -295,8 +295,10 @@ def f(t): # plt.figure(2) # a second figure # plt.plot([4, 5, 6]) # creates a subplot() by default # -# plt.figure(1) # figure 1 current; subplot(212) still current -# plt.subplot(211) # make subplot(211) in figure1 current +# plt.figure(1) # first figure current; +# # subplot(212) still current +# plt.subplot(211) # make subplot(211) in the first figure +# # current # plt.title('Easy as 1, 2, 3') # subplot 211 title # # You can clear the current figure with `~.pyplot.clf` diff --git a/tutorials/text/text_intro.py b/tutorials/text/text_intro.py index a32ddc800d10..1b0e60a37ab1 100644 --- a/tutorials/text/text_intro.py +++ b/tutorials/text/text_intro.py @@ -118,7 +118,7 @@ fig, ax = plt.subplots(figsize=(5, 3)) fig.subplots_adjust(bottom=0.15, left=0.2) ax.plot(x1, y1) -ax.set_xlabel('time [s]') +ax.set_xlabel('Time [s]') ax.set_ylabel('Damped oscillation [V]') plt.show() @@ -131,7 +131,7 @@ fig, ax = plt.subplots(figsize=(5, 3)) fig.subplots_adjust(bottom=0.15, left=0.2) ax.plot(x1, y1*10000) -ax.set_xlabel('time [s]') +ax.set_xlabel('Time [s]') ax.set_ylabel('Damped oscillation [V]') plt.show() @@ -144,7 +144,7 @@ fig, ax = plt.subplots(figsize=(5, 3)) fig.subplots_adjust(bottom=0.15, left=0.2) ax.plot(x1, y1*10000) -ax.set_xlabel('time [s]') +ax.set_xlabel('Time [s]') ax.set_ylabel('Damped oscillation [V]', labelpad=18) plt.show() @@ -159,7 +159,7 @@ fig, ax = plt.subplots(figsize=(5, 3)) fig.subplots_adjust(bottom=0.15, left=0.2) ax.plot(x1, y1) -ax.set_xlabel('time [s]', position=(0., 1e6), horizontalalignment='left') +ax.set_xlabel('Time [s]', position=(0., 1e6), horizontalalignment='left') ax.set_ylabel('Damped oscillation [V]') plt.show() @@ -179,7 +179,7 @@ fig, ax = plt.subplots(figsize=(5, 3)) fig.subplots_adjust(bottom=0.15, left=0.2) ax.plot(x1, y1) -ax.set_xlabel('time [s]', fontsize='large', fontweight='bold') +ax.set_xlabel('Time [s]', fontsize='large', fontweight='bold') ax.set_ylabel('Damped oscillation [V]', fontproperties=font) plt.show() @@ -191,7 +191,7 @@ fig, ax = plt.subplots(figsize=(5, 3)) fig.subplots_adjust(bottom=0.2, left=0.2) ax.plot(x1, np.cumsum(y1**2)) -ax.set_xlabel('time [s] \n This was a long experiment') +ax.set_xlabel('Time [s] \n This was a long experiment') ax.set_ylabel(r'$\int\ Y^2\ dt\ \ [V^2 s]$') plt.show() pFad - Phonifier reborn

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