Move axwidth/axheight/aspect-->refwidth/refheight/refaspect, width/height-->figwidth/figheight

Author: lukelbd

docs/1dplots.py

@@ -130,7 +130,7 @@
 
 # %%
 import proplot as plot
-fig, axs = plot.subplots(ncols=2, axwidth=2.2, share=0)
+fig, axs = plot.subplots(ncols=2, refwidth=2.2, share=0)
 axs.format(suptitle='Automatic subplot formatting')
 
 # Plot DataArray
@@ -223,7 +223,7 @@
 
 # Generate figure
 fig, axs = plot.subplots(
-    nrows=3, aspect=1.5, axwidth=4,
+    nrows=3, refaspect=1.5, refwidth=4,
     share=0, hratios=(2, 1, 1)
 )
 axs.format(suptitle='Indicating error bounds with various plotting commands')
@@ -306,7 +306,7 @@
 
 # Generate figure
 plot.rc.titleloc = 'uc'
-fig, axs = plot.subplots(nrows=2, aspect=2, axwidth=4.8, share=0, hratios=(3, 2))
+fig, axs = plot.subplots(nrows=2, refaspect=2, refwidth=4.8, share=0, hratios=(3, 2))
 
 # Side-by-side bars
 ax = axs[0]
@@ -337,7 +337,7 @@
 cycle = ('gray3', 'gray5', 'gray7')
 
 # Generate figure
-fig, axs = plot.subplots(ncols=2, axwidth=2.3, share=0)
+fig, axs = plot.subplots(ncols=2, refwidth=2.3, share=0)
 axs.format(grid=False, xlabel='xlabel', ylabel='ylabel', suptitle='Area plot demo')
 
 # Overlaid area patches
@@ -363,7 +363,7 @@
 data = 4 * (state.rand(50) - 0.5)
 
 # Generate figure
-fig, axs = plot.subplots(nrows=2, width=5, aspect=2)
+fig, axs = plot.subplots(nrows=2, refaspect=2, figwidth=5)
 axs.format(
     xmargin=0, xlabel='xlabel', ylabel='ylabel', grid=True,
     suptitle='Positive and negative colors demo',
@@ -408,7 +408,7 @@
 )
 
 # Generate figure
-fig, axs = plot.subplots(ncols=2, axwidth=2.5)
+fig, axs = plot.subplots(ncols=2, refwidth=2.5)
 axs.format(grid=False, suptitle='Boxes and violins demo')
 
 # Box plots
@@ -449,7 +449,7 @@
 import numpy as np
 fig, axs = plot.subplots(
     share=0, ncols=2, wratios=(2, 1),
-    width='16cm', aspect=(2, 1)
+    figwidth='16cm', refaspect=(2, 1)
 )
 axs.format(suptitle='Parametric plots demo')
 cmap = 'IceFire'

docs/2dplots.py

@@ -133,7 +133,7 @@
 
 # %%
 import proplot as plot
-fig, axs = plot.subplots(nrows=2, axwidth=2.5, share=0)
+fig, axs = plot.subplots(nrows=2, refwidth=2.5, share=0)
 axs.format(toplabels=('Automatic subplot formatting',))
 
 # Plot DataArray
@@ -220,7 +220,7 @@
 import numpy as np
 
 # Pcolor plot with and without distinct levels
-fig, axs = plot.subplots(ncols=2, axwidth=2)
+fig, axs = plot.subplots(ncols=2, refwidth=2)
 state = np.random.RandomState(51423)
 data = (state.normal(0, 1, size=(33, 33))).cumsum(axis=0).cumsum(axis=1)
 axs.format(suptitle='Pcolor plot with levels')
@@ -233,7 +233,7 @@
 import numpy as np
 fig, axs = plot.subplots(
     [[0, 0, 1, 1, 0, 0], [2, 3, 3, 4, 4, 5]],
-    wratios=(1.5, 0.5, 1, 1, 0.5, 1.5), axwidth=1.7, ref=1, right='2em'
+    wratios=(1.5, 0.5, 1, 1, 0.5, 1.5), refwidth=1.7, ref=1, right='2em'
 )
 axs.format(suptitle='DiscreteNorm color-range standardization')
 levels = plot.arange(0, 360, 45)
@@ -292,7 +292,7 @@
 # Linear segmented norm
 state = np.random.RandomState(51423)
 data = 10**(2 * state.rand(20, 20).cumsum(axis=0) / 7)
-fig, axs = plot.subplots(ncols=2, axwidth=2.4)
+fig, axs = plot.subplots(ncols=2, refwidth=2.4)
 ticks = [5, 10, 20, 50, 100, 200, 500, 1000]
 for i, (norm, title) in enumerate(zip(
     ('linear', 'segmented'),
@@ -314,7 +314,7 @@
 state = np.random.RandomState(51423)
 data1 = (state.rand(20, 20) - 0.43).cumsum(axis=0)
 data2 = (state.rand(20, 20) - 0.57).cumsum(axis=0)
-fig, axs = plot.subplots(nrows=2, ncols=2, axwidth=2.4, order='F')
+fig, axs = plot.subplots(nrows=2, ncols=2, refwidth=2.4, order='F')
 cmap = plot.Colormap('DryWet', cut=0.1)
 axs.format(suptitle='Diverging normalizer demo')
 i = 0
@@ -358,7 +358,7 @@
 import numpy as np
 fig, axs = plot.subplots(
     [[1, 1, 2, 2], [0, 3, 3, 0]],
-    axwidth=2.2, share=1, span=False, hratios=(1, 0.9)
+    refwidth=2.2, share=1, span=False, hratios=(1, 0.9)
 )
 state = np.random.RandomState(51423)
 data = state.rand(6, 6)
@@ -416,7 +416,7 @@
 data = pd.DataFrame(data, columns=list('abcdefghij'), index=list('abcdefghij'))
 
 # Covariance matrix plot
-fig, ax = plot.subplots(axwidth=4.5)
+fig, ax = plot.subplots(refwidth=4.5)
 m = ax.heatmap(
     data, cmap='ColdHot', vmin=-1, vmax=1, N=100,
     lw=0.5, edgecolor='k', labels=True, labels_kw={'weight': 'bold'},

docs/axis.py

@@ -64,7 +64,7 @@
     color='dark blue', suptitlecolor='dark blue',
     titleloc='upper center', titlecolor='dark blue', titleborder=False,
 )
-fig, axs = plot.subplots(nrows=8, axwidth=5, aspect=(8, 1), share=0)
+fig, axs = plot.subplots(nrows=8, refwidth=5, refaspect=(8, 1), share=0)
 axs.format(suptitle='Tick locators demo')
 
 # Step size for tick locations
@@ -163,7 +163,7 @@
     color='gray8', gridcolor='gray8', titlecolor='gray8', suptitlecolor='gray8',
     titleloc='upper center', titleborder=False,
 )
-fig, axs = plot.subplots(nrows=9, axwidth=5, aspect=(8, 1), share=0)
+fig, axs = plot.subplots(nrows=9, refwidth=5, refaspect=(8, 1), share=0)
 
 # Scientific notation
 axs[0].format(xlim=(0, 1e20), xformatter='sci', title='SciFormatter')
@@ -212,7 +212,7 @@
 plot.rc.linewidth = 2
 plot.rc.fontsize = 11
 locator = [0, 0.25, 0.5, 0.75, 1]
-fig, axs = plot.subplots(ncols=2, nrows=2, axwidth=1.5, share=0)
+fig, axs = plot.subplots(ncols=2, nrows=2, refwidth=1.5, share=0)
 
 # Formatter comparison
 axs[0].format(
@@ -264,7 +264,7 @@
     figurefacecolor='w', facecolor='pastel blue',
     titleloc='upper center', titleborder=False,
 )
-fig, axs = plot.subplots(nrows=5, axwidth=6, aspect=(8, 1), share=0)
+fig, axs = plot.subplots(nrows=5, refwidth=6, refaspect=(8, 1), share=0)
 axs[:4].format(xrotation=0)  # no rotation for these examples
 
 # Default date locator
@@ -347,7 +347,7 @@
 plot.rc.update({
     'linewidth': 1, 'ticklabelweight': 'bold', 'axeslabelweight': 'bold'
 })
-fig, axs = plot.subplots(ncols=2, nrows=2, axwidth=1.8, share=0)
+fig, axs = plot.subplots(ncols=2, nrows=2, refwidth=1.8, share=0)
 axs.format(suptitle='Axis scales demo', ytickminor=True)
 
 # Linear and log scales
@@ -387,7 +387,7 @@
 # %%
 import proplot as plot
 import numpy as np
-fig, axs = plot.subplots(width=6, nrows=4, aspect=(5, 1), sharex=False)
+fig, axs = plot.subplots(nrows=4, refaspect=(5, 1), figwidth=6, sharex=False)
 ax = axs[0]
 
 # Sample data
@@ -427,7 +427,7 @@
 import proplot as plot
 import numpy as np
 plot.rc.reset()
-fig, axs = plot.subplots(nrows=2, ncols=3, axwidth=1.7, share=0, order='F')
+fig, axs = plot.subplots(nrows=2, ncols=3, refwidth=1.7, share=0, order='F')
 axs.format(
     toplabels=('Power scales', 'Exponential scales', 'Cartographic scales'),
 )
@@ -502,7 +502,7 @@
 c2 = plot.scale_luminance('red', 0.5)
 fig, axs = plot.subplots(
     [[1, 1, 2, 2], [0, 3, 3, 0]],
-    share=0, aspect=2.2, axwidth=3
+    share=0, refaspect=2.2, refwidth=3
 )
 axs.format(
     suptitle='Duplicate axes with custom transformations',
@@ -540,7 +540,7 @@
 plot.rc.update({'grid.alpha': 0.4, 'linewidth': 1, 'grid.linewidth': 1})
 c1 = plot.scale_luminance('cerulean', 0.5)
 c2 = plot.scale_luminance('red', 0.5)
-fig, axs = plot.subplots(ncols=2, share=0, aspect=0.4, axwidth=1.8)
+fig, axs = plot.subplots(ncols=2, share=0, refaspect=0.4, refwidth=1.8)
 axs.format(suptitle='Duplicate axes with special transformations')
 
 # Pressure as the linear scale, height on opposite axis (scale height 7km)
@@ -570,7 +570,7 @@
 plot.rc.margin = 0
 c1 = plot.scale_luminance('cerulean', 0.5)
 c2 = plot.scale_luminance('red', 0.5)
-fig, ax = plot.subplots(aspect=(3, 1), width=6)
+fig, ax = plot.subplots(refaspect=(3, 1), figwidth=6)
 
 # Sample data
 cutoff = 1 / 5

docs/basics.py

@@ -113,7 +113,7 @@
     [1, 1, 2, 2],
     [0, 3, 3, 0],
 ]
-fig, axs = plot.subplots(array, axwidth=1.8)
+fig, axs = plot.subplots(array, refwidth=1.8)
 axs.format(
     abc=True, abcloc='ul', suptitle='Complex subplot grid',
     xlabel='xlabel', ylabel='ylabel'
@@ -130,7 +130,7 @@
     [3, 4, 4],
     [3, 5, 5],
 ]
-fig, axs = plot.subplots(array, width=5, span=False)
+fig, axs = plot.subplots(array, figwidth=5, span=False)
 axs.format(
     suptitle='Really complex subplot grid',
     xlabel='xlabel', ylabel='ylabel', abc=True
@@ -172,7 +172,7 @@
 
 # Example plots
 cycle = plot.Cycle('greys', left=0.2, N=5)
-fig, axs = plot.subplots(ncols=2, nrows=2, share=0, width=5)
+fig, axs = plot.subplots(ncols=2, nrows=2, figwidth=5, share=0)
 axs[0].plot(data[:, :5], linewidth=2, linestyle='--', cycle=cycle)
 axs[1].scatter(data[:, :5], marker='x', cycle=cycle)
 axs[2].pcolormesh(data, cmap='greys')
@@ -230,7 +230,7 @@
 # %%
 import proplot as plot
 import numpy as np
-fig, axs = plot.subplots(ncols=2, nrows=2, share=0, tight=True, axwidth=2)
+fig, axs = plot.subplots(ncols=2, nrows=2, share=0, tight=True, refwidth=2)
 state = np.random.RandomState(51423)
 N = 60
 x = np.linspace(1, 10, N)
@@ -285,7 +285,7 @@
 import proplot as plot
 import numpy as np
 state = np.random.RandomState(51423)
-fig, axs = plot.subplots(ncols=4, nrows=4, axwidth=1.2)
+fig, axs = plot.subplots(ncols=4, nrows=4, refwidth=1.2)
 axs.format(
     xlabel='xlabel', ylabel='ylabel', suptitle='SubplotsContainer demo',
     grid=False, xlim=(0, 50), ylim=(-4, 4)
@@ -340,7 +340,7 @@
 
 # Apply settings to figure with context()
 with plot.rc.context({'suptitle.size': 13}, toplabelcolor='gray6', linewidth=1.5):
-    fig, axs = plot.subplots(ncols=2, aspect=1, width=6, span=False, sharey=2)
+    fig, axs = plot.subplots(ncols=2, figwidth=6, sharey=2, span=False)
 
 # Plot lines
 N, M = 100, 6

docs/colorbars_legends.py

@@ -92,7 +92,7 @@
 # %%
 import proplot as plot
 import numpy as np
-fig, axs = plot.subplots(nrows=2, share=0, axwidth='55mm', panelpad='1em')
+fig, axs = plot.subplots(nrows=2, share=0, refwidth='55mm', panelpad='1em')
 axs.format(suptitle='Stacked colorbars demo')
 state = np.random.RandomState(51423)
 N = 10
@@ -139,7 +139,7 @@
 # %%
 import proplot as plot
 import numpy as np
-fig, axs = plot.subplots(ncols=3, nrows=3, axwidth=1.4)
+fig, axs = plot.subplots(ncols=3, nrows=3, refwidth=1.4)
 state = np.random.RandomState(51423)
 m = axs.pcolormesh(
     state.rand(20, 20), cmap='grays',
@@ -158,7 +158,7 @@
 import proplot as plot
 import numpy as np
 fig, axs = plot.subplots(
-    ncols=2, nrows=2, axwidth=1.7,
+    ncols=2, nrows=2, refwidth=1.7,
     share=0, wspace=0.3, order='F'
 )
 
@@ -210,7 +210,7 @@
 # %%
 import proplot as plot
 import numpy as np
-fig, axs = plot.subplots(share=0, ncols=2, axwidth=2)
+fig, axs = plot.subplots(share=0, ncols=2, refwidth=2)
 
 # Colorbars from lines
 ax = axs[0]
@@ -268,7 +268,7 @@
 import numpy as np
 plot.rc.cycle = '538'
 labels = ['a', 'bb', 'ccc', 'dddd', 'eeeee']
-fig, axs = plot.subplots(ncols=2, span=False, share=1, axwidth=2.3)
+fig, axs = plot.subplots(ncols=2, span=False, share=1, refwidth=2.3)
 hs1, hs2 = [], []
 
 # On-the-fly legends