从投影的2d直方图绘制对齐的x，y 1d直方图

Question

我需要生成类似于this example中显示的图像：

不同之处在于，我没有在二维中得到散点，而是使用numpy的histogram2d生成二维直方图，并使用gridspec和import numpy as np import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec data = # Uploaded to http://pastebin.com/tjLqM9gQ # Create a meshgrid of coordinates (0,1,...,N) times (0,1,...,N) y, x = np.mgrid[:len(data[0, :, 0]), :len(data[0, 0, :])] # duplicating the grids xcoord, ycoord = np.array([x] * len(data)), np.array([y] * len(data)) # compute histogram with coordinates as x,y h, xe, ye = np.histogram2d( xcoord.ravel(), ycoord.ravel(), bins=[len(data[0, 0, :]), len(data[0, :, 0])], weights=stars.ravel()) # Projected histograms inx and y hx, hy = h.sum(axis=0), h.sum(axis=1) # Define size of figure fig = plt.figure(figsize=(20, 15)) gs = gridspec.GridSpec(10, 12) # Define the positions of the subplots. ax0 = plt.subplot(gs[6:10, 5:9]) axx = plt.subplot(gs[5:6, 5:9]) axy = plt.subplot(gs[6:10, 9:10]) ax0.imshow(h, cmap=plt.cm.viridis, interpolation='nearest', origin='lower', vmin=0.) # Remove tick labels nullfmt = NullFormatter() axx.xaxis.set_major_formatter(nullfmt) axx.yaxis.set_major_formatter(nullfmt) axy.xaxis.set_major_formatter(nullfmt) axy.yaxis.set_major_formatter(nullfmt) # Top plot axx.plot(hx) axx.set_xlim(ax0.get_xlim()) # Right plot axy.plot(hy, range(len(hy))) axy.set_ylim(ax0.get_ylim()) fig.tight_layout() plt.savefig('del.png') 绘制：< / p>

如何将这个2D直方图投影到水平和垂直直方图（或曲线）中，使其看起来像第一张图像一样对齐？

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Answer 1

如果你认为边际分布都是直立的，你可以使用 corner

例如：

import corner
import numpy as np
import pandas as pd

N = 1000

CORNER_KWARGS = dict(
    smooth=0.9,
    label_kwargs=dict(fontsize=30),
    title_kwargs=dict(fontsize=16),
    truth_color="tab:orange",
    quantiles=[0.16, 0.84],
    levels=(1 - np.exp(-0.5), 1 - np.exp(-2), 1 - np.exp(-9 / 2.0)),
    plot_density=False,
    plot_datapoints=False,
    fill_contours=True,
    max_n_ticks=3,
    verbose=False,
    use_math_text=True,
)


def generate_data():
    return pd.DataFrame(dict(
        x=np.random.normal(0, 1, N),
        y=np.random.normal(0, 1, N)
    ))


def main():
    data = generate_data()
    fig = corner.corner(data, **CORNER_KWARGS)
    fig.show()


if __name__ == "__main__":
    main()