python - imshow and plot side by side -
i'm trying put side-by-side numpy array displayed image , seaborn distplot of same array. i've came following function:
def visualize(arr): f, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw = {'width_ratios': [1, 3]}) ax1.imshow(arr) flat = arr.flatten() x = flat[~np.isnan(flat)] sns.distplot(x, ax=ax2) plt.show() which produces: 
as can see, image has smaller height plot. how can modify function in order have same height plot , imshow?
i want following placement of image , plot: 
there many ways tackle this. of following give more or less same image
a. reduce available space
you may reduce available space such both plots constrained same vertical margins. can done by
reducing figure height
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(6,2.3), ...)
using
subplots_adjustlimit marginsfig.subplots_adjust(top=0.7, bottom=0.3)
b. use insetposition
you may use mpl_toolkits.axes_grid1.inset_locator.insetposition adjust coordinates of second axes match of first one.
import seaborn sns import numpy np import matplotlib.pyplot plt mpl_toolkits.axes_grid1.inset_locator import insetposition def visualize(arr): fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw = {'width_ratios': [1, 3]}) ax1.imshow(arr) flat = arr.flatten() x = flat[~np.isnan(flat)] sns.distplot(x, ax=ax2) ip = insetposition(ax1, [1.5,0,3,1]) ax2.set_axes_locator(ip) plt.show() arr = np.random.randn(200,120) visualize(arr) c. use axes divider
you may create axes image , use mpl_toolkits.axes_grid1.make_axes_locatable create new axes next it.
import seaborn sns import numpy np import matplotlib.pyplot plt mpl_toolkits.axes_grid1 import make_axes_locatable def visualize(arr): fig, ax = plt.subplots() divider = make_axes_locatable(ax) ax2 = divider.new_horizontal(size="300%", pad=0.5) fig.add_axes(ax2) ax.imshow(arr) flat = arr.flatten() x = flat[~np.isnan(flat)] sns.distplot(x, ax=ax2) plt.show() arr = np.random.randn(200,120) visualize(arr) d. calculate desired aspect ratio
import seaborn sns import numpy np import matplotlib.pyplot plt def visualize(arr): gkw = {'width_ratios':[1, 3] } fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw = gkw ) ax1.imshow(arr) flat = arr.flatten() x = flat[~np.isnan(flat)] sns.distplot(x, ax=ax2) ya = np.diff(np.array(ax2.get_ylim()))[0] xa = np.diff(np.array(ax2.get_xlim()))[0] wa = gkw['width_ratios'][0]/float(gkw['width_ratios'][1]) ia = arr.shape[0]/float(arr.shape[1]) ax2.set_aspect(float(wa*ia/(ya/xa))) plt.show() arr = np.random.randn(200,120) visualize(arr)
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