Python中数组的二维和三维散点直方图

Question

你有什么想法,我怎么能把3个数组bin到直方图.我的阵列看起来像

Temperature = [4,   3,   1,   4,   6,   7,   8,   3,   1]
Radius      = [0,   2,   3,   4,   0,   1,   2,  10,   7]
Density     = [1,  10,   2,  24,   7,  10,  21, 102, 203]

并且1D图应该看起来:

Density

     |           X
10^2-|               X
     |       X
10^1-|   
     |   X
10^0-|
     |___|___|___|___|___   Radius
         0  3.3 6.6  10

二维图应该(定性)看起来像:

Density

     |           2      | |
10^2-|      11249       | |
     |     233          | | Radius
10^1-|    12            | |
     |   1              | |
10^0-|
     |___|___|___|___|___   Temperature
         0   3   5   8

所以我想用python/numpy将一个或两个字段分区,然后绘制它们以分析它们的对应关系.

Answer 1

这里有两个功能:hist2d_bubble和hist3d_bubble; 这可能适合您的目的:

import numpy as np
import matplotlib.pyplot as pyplot
from mpl_toolkits.mplot3d import Axes3D


def hist2d_bubble(x_data, y_data, bins=10):
    ax = np.histogram2d(x_data, y_data, bins=bins)
    xs = ax[1]
    ys = ax[2]
    points = []
    for (i, j), v in np.ndenumerate(ax[0]):
        points.append((xs[i], ys[j], v))

    points = np.array(points)
    fig = pyplot.figure()
    sub = pyplot.scatter(points[:, 0],points[:, 1],
                         color='black', marker='o', s=128*points[:, 2])
    sub.axes.set_xticks(xs)
    sub.axes.set_yticks(ys)
    pyplot.ion()
    pyplot.grid()
    pyplot.show()
    return points, sub


def hist3d_bubble(x_data, y_data, z_data, bins=10):
    ax1 = np.histogram2d(x_data, y_data, bins=bins)
    ax2 = np.histogram2d(x_data, z_data, bins=bins)
    ax3 = np.histogram2d(z_data, y_data, bins=bins)
    xs, ys, zs = ax1[1], ax1[2], ax3[1]
    smart = np.zeros((bins, bins, bins),dtype=int)
    for (i1, j1), v1 in np.ndenumerate(ax1[0]):
        if v1 == 0:
            continue
        for k2, v2 in enumerate(ax2[0][i1]):
            v3 = ax3[0][k2][j1]
            if v1 == 0 or v2 == 0 or v3 == 0:
                continue
            num = min(v1, v2, v3)
            smart[i1, j1, k2] += num
            v1 -= num
            v2 -= num
            v3 -= num
    points = []
    for (i, j, k), v in np.ndenumerate(smart):
        points.append((xs[i], ys[j], zs[k], v))
    points = np.array(points)
    fig = pyplot.figure()
    sub = fig.add_subplot(111, projection='3d')
    sub.scatter(points[:, 0], points[:, 1], points[:, 2],
                color='black', marker='o', s=128*points[:, 3])
    sub.axes.set_xticks(xs)
    sub.axes.set_yticks(ys)
    sub.axes.set_zticks(zs)
    pyplot.ion()
    pyplot.grid()
    pyplot.show()
    return points, sub

以上两个数字是使用以下方式创建的

temperature = [4,   3,   1,   4,   6,   7,   8,   3,   1]
radius      = [0,   2,   3,   4,   0,   1,   2,  10,   7]
density     = [1,  10,   2,  24,   7,  10,  21, 102, 203]
import matplotlib
matplotlib.rcParams.update({'font.size':14})

points, sub = hist2d_bubble(radius, density, bins=4)
sub.axes.set_xlabel('radius')
sub.axes.set_ylabel('density')

points, sub = hist3d_bubble(temperature, density, radius, bins=4)
sub.axes.set_xlabel('temperature')
sub.axes.set_ylabel('density')
sub.axes.set_zlabel('radius')

有关:

如何在Python中将bin系列浮点值转换为直方图？

如何使用python中内置函数的numpy或matplotlib正确生成3d直方图？

使用Python的2D直方图