使用颜色栏在绘图中设置相等的长宽比 [英] Set equal aspect in plot with colorbar

问题描述

我需要生成一个在两个轴上都具有相同长宽比的图，并在右侧显示一个色条.我尝试设置 aspect ='auto'， aspect = 1 和 aspect ='equal'都没有很好的效果.有关示例和MWE，请参见下文.

I need to generate a plot with equal aspect in both axis and a colorbar to the right. I've tried setting aspect='auto', aspect=1, and aspect='equal' with no good results. See below for examples and the MWE.

使用 aspect ='auto'，颜色条的高度正确，但图形失真:

Using aspect='auto' the colorbars are of the correct height but the plots are distorted:

使用 aspect = 1 或 aspect ='equal'，这些图是正方形的(两个轴上的长宽比相等)，但是颜色条变形了:

Using aspect=1 or aspect='equal' the plots are square (equal aspect in both axis) but the colorbars are distorted:

在两个图中，由于某种原因，颜色条都位于右侧太远的位置.如何获得具有匹配高度的颜色条的正方形图?

In both plots the colorbars are positioned too far to the right for some reason. How can I get a square plot with colorbars of matching heights?

MWE

import numpy as np
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt

def col_plot(params):

    gs, i, data = params

    xarr, yarr, zarr = zip(*data)[0], zip(*data)[1], zip(*data)[2]

    xmin, xmax = min(xarr), max(xarr)
    ymin, ymax = min(yarr), max(yarr)

    #plt.subplot(gs[i], aspect='auto')
    plt.subplot(gs[i], aspect=1)
    #plt.subplot(gs[i], aspect='equal')

    plt.xlim(xmin, xmax)
    plt.ylim(xmin, xmax)
    plt.xlabel('$x axis$', fontsize=20)
    plt.ylabel('$y axis$', fontsize=20)
    # Scatter plot.
    cm = plt.cm.get_cmap('RdYlBu_r')
    SC = plt.scatter(xarr, yarr, marker='o', c=zarr, s=60, lw=0.25, cmap=cm,
        zorder=3)
    # Colorbar.
    ax0 = plt.subplot(gs[i + 1])
    cbar = plt.colorbar(SC, cax=ax0)
    cbar.set_label('$col bar$', fontsize=21, labelpad=-2)

# Generate data.
data0 = np.random.uniform(0., 1., size=(50, 3))
data1 = np.random.uniform(0., 1., size=(50, 3))

# Create the top-level container
fig = plt.figure(figsize=(14, 25))
gs = gridspec.GridSpec(4, 4, width_ratios=[1, 0.05, 1, 0.05])

# Generate plots.
par_lst = [[gs, 0, data0], [gs, 2, data1]]
for pl_params in par_lst:
    col_plot(pl_params)

# Output png file.
fig.tight_layout()
plt.savefig('colorbar_aspect.png', dpi=300)

推荐答案

您可以使用

You can use an AxesDivider to do that. I have modified your code a bit to make use of an AxesDivider.

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

def col_plot(data):

    xarr, yarr, zarr = zip(*data)[0], zip(*data)[1], zip(*data)[2]
    xarr = [2*x for x in xarr]

    xmin, xmax = min(xarr), max(xarr)
    ymin, ymax = min(yarr), max(yarr)

    fig = plt.figure()

    ax0 = fig.add_subplot(111, aspect='equal')

    plt.xlim(xmin, xmax)
    plt.ylim(ymin, ymax)
    plt.xlabel('$x axis$', fontsize=20)
    plt.ylabel('$y axis$', fontsize=20)
    # Scatter plot.
    cm = plt.cm.get_cmap('RdYlBu_r')
    SC = ax0.scatter(xarr, yarr, marker='o', c=zarr, s=60, lw=0.25, cmap=cm,
        zorder=3)

    the_divider = make_axes_locatable(ax0)
    color_axis = the_divider.append_axes("right", size="5%", pad=0.1)

    # Colorbar.
    cbar = plt.colorbar(SC, cax=color_axis)
    cbar.set_label('$col bar$', fontsize=21, labelpad=-2)

# Generate data.
data0 = np.random.uniform(0., 1., size=(20, 3))

col_plot(data0)

这是结果(出于演示目的，我更改了数据，因此它在x方向上跨越了[0，2]的范围):

And here is the result (I changed your data so it spans a range of [0, 2] in the x-direction for demonstration purposes):

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