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Commitabdaba5

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Change constrained_layout=True to layout='constrained'
as the former is discouraged, seehttps://matplotlib.org/3.5.0/api/figure_api.html#matplotlib.figure.Figure
1 parent2a62854 commitabdaba5

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-11
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+11
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‎tutorials/introductory/usage.py‎

Lines changed: 11 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -120,7 +120,7 @@
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data['b']=data['a']+10*np.random.randn(50)
121121
data['d']=np.abs(data['d'])*100
122122

123-
fig,ax=plt.subplots(figsize=(5,2.7),constrained_layout=True)
123+
fig,ax=plt.subplots(figsize=(5,2.7),layout='constrained')
124124
ax.scatter('a','b',c='c',s='d',data=data)
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ax.set_xlabel('entry a')
126126
ax.set_ylabel('entry b');
@@ -147,7 +147,7 @@
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148148
# Note that even in the explicit style, we use `.pyplot.figure` to create the
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# Figure.
150-
fig,ax=plt.subplots(figsize=(5,2.7),constrained_layout=True)
150+
fig,ax=plt.subplots(figsize=(5,2.7),layout='constrained')
151151
ax.plot(x,x,label='linear')# Plot some data on the axes.
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ax.plot(x,x**2,label='quadratic')# Plot more data on the axes...
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ax.plot(x,x**3,label='cubic')# ... and some more.
@@ -161,7 +161,7 @@
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162162
x=np.linspace(0,2,100)# Sample data.
163163

164-
plt.figure(figsize=(5,2.7),constrained_layout=True)
164+
plt.figure(figsize=(5,2.7),layout='constrained')
165165
plt.plot(x,x,label='linear')# Plot some data on the (implicit) axes.
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plt.plot(x,x**2,label='quadratic')# etc.
167167
plt.plot(x,x**3,label='cubic')
@@ -284,7 +284,7 @@ def my_plotter(ax, data1, data2, param_dict):
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285285
mu,sigma=115,15
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x=mu+sigma*np.random.randn(10000)
287-
fig,ax=plt.subplots(figsize=(5,2.7),constrained_layout=True)
287+
fig,ax=plt.subplots(figsize=(5,2.7),layout='constrained')
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# the histogram of the data
289289
n,bins,patches=ax.hist(x,50,density=1,facecolor='C0',alpha=0.75)
290290

@@ -380,7 +380,7 @@ def my_plotter(ax, data1, data2, param_dict):
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# :doc:`/gallery/scales/scales` for other examples). Here we set the scale
381381
# manually:
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383-
fig,axs=plt.subplots(1,2,figsize=(5,2.7),constrained_layout=True)
383+
fig,axs=plt.subplots(1,2,figsize=(5,2.7),layout='constrained')
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xdata=np.arange(len(data1))# make an ordinal for this
385385
data=10**data1
386386
axs[0].plot(xdata,data)
@@ -401,7 +401,7 @@ def my_plotter(ax, data1, data2, param_dict):
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# Axis objects to put tick marks. A simple interface to this is
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# `~.Axes.set_xticks`:
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404-
fig,axs=plt.subplots(2,1,constrained_layout=True)
404+
fig,axs=plt.subplots(2,1,layout='constrained')
405405
axs[0].plot(xdata,data1)
406406
axs[0].set_title('Automatic ticks')
407407

@@ -424,7 +424,7 @@ def my_plotter(ax, data1, data2, param_dict):
424424
# well as floating point numbers. These get special locators and formatters
425425
# as appropriate. For dates:
426426

427-
fig,ax=plt.subplots(figsize=(5,2.7),constrained_layout=True)
427+
fig,ax=plt.subplots(figsize=(5,2.7),layout='constrained')
428428
dates=np.arange(np.datetime64('2021-11-15'),np.datetime64('2021-12-25'),
429429
np.timedelta64(1,'h'))
430430
data=np.cumsum(np.random.randn(len(dates)))
@@ -439,7 +439,7 @@ def my_plotter(ax, data1, data2, param_dict):
439439
# For strings, we get categorical plotting (see:
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# :doc:`/gallery/lines_bars_and_markers/categorical_variables`).
441441

442-
fig,ax=plt.subplots(figsize=(5,2.7),constrained_layout=True)
442+
fig,ax=plt.subplots(figsize=(5,2.7),layout='constrained')
443443
categories= ['turnips','rutabaga','cucumber','pumpkins']
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445445
ax.bar(categories,np.random.rand(len(categories)));
@@ -464,7 +464,7 @@ def my_plotter(ax, data1, data2, param_dict):
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# represent the data in different scales or units.
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466466

467-
fig, (ax1,ax3)=plt.subplots(1,2,figsize=(8,2.7),constrained_layout=True)
467+
fig, (ax1,ax3)=plt.subplots(1,2,figsize=(8,2.7),layout='constrained')
468468
l1,=ax1.plot(t,s)
469469
ax2=ax1.twinx()
470470
l2,=ax2.plot(t,range(len(t)),'C1')
@@ -485,7 +485,7 @@ def my_plotter(ax, data1, data2, param_dict):
485485
X,Y=np.meshgrid(np.linspace(-3,3,128),np.linspace(-3,3,128))
486486
Z= (1-X/2+X**5+Y**3)*np.exp(-X**2-Y**2)
487487

488-
fig,axs=plt.subplots(2,2,constrained_layout=True)
488+
fig,axs=plt.subplots(2,2,layout='constrained')
489489
pc=axs[0,0].pcolormesh(X,Y,Z,vmin=-1,vmax=1,cmap='RdBu_r')
490490
fig.colorbar(pc,ax=axs[0,0])
491491
axs[0,0].set_title('pcolormesh()')
@@ -551,7 +551,7 @@ def my_plotter(ax, data1, data2, param_dict):
551551
# with Axes objects spanning columns or rows, using `~.pyplot.subplot_mosaic`.
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553553
fig,axd=plt.subplot_mosaic([['upleft','right'],
554-
['lowleft','right']],constrained_layout=True)
554+
['lowleft','right']],layout='constrained')
555555
axd['upleft'].set_title('upleft')
556556
axd['lowleft'].set_title('lowleft')
557557
axd['right'].set_title('right');

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