Question

我试图将我的数据集x和y（通过numpy.genfromtxt('/Users/.../somedata.csv', delimiter=',', unpack=True)生成的csv文件）绘制为简单的密度图。为了确保这是自包含的，我将在这里定义它们：

x = [ 0.2933215   0.2336305   0.2898058   0.2563835   0.1539951   0.1790058
  0.1957057   0.5048573   0.3302402   0.2896122   0.4154893   0.4948401
  0.4688092   0.4404935   0.2901995   0.3793949   0.6343423   0.6786809
  0.5126349   0.4326627   0.2318232   0.538646    0.1351541   0.2044524
  0.3063099   0.2760263   0.1577156   0.2980986   0.2507897   0.1445099
  0.2279241   0.4229934   0.1657194   0.321832    0.2290785   0.2676585
  0.2478505   0.3810182   0.2535708   0.157562    0.1618909   0.2194217
  0.1888698   0.2614876   0.1894155   0.4802076   0.1059326   0.3837571
  0.3609228   0.2827142   0.2705508   0.6498625   0.2392224   0.1541462
  0.4540277   0.1624592   0.160438    0.109423    0.146836    0.4896905
  0.2052707   0.2668798   0.2506224   0.5041728   0.201774    0.14907
  0.21835     0.1609169   0.1609169   0.205676    0.4500787   0.2504743
  0.1906289   0.3447547   0.1223678   0.112275    0.2269951   0.1616036
  0.1532181   0.1940938   0.1457424   0.1094261   0.1636615   0.1622345
  0.705272    0.3158471   0.1416916   0.1290324   0.3139713   0.2422002
  0.1593835   0.08493619  0.08358301  0.09691083  0.2580497   0.1805554 ]

y = [ 1.395807  1.31553   1.333902  1.253527  1.292779  1.10401   1.42933
  1.525589  1.274508  1.16183   1.403394  1.588711  1.346775  1.606438
  1.296017  1.767366  1.460237  1.401834  1.172348  1.341594  1.3845
  1.479691  1.484053  1.468544  1.405156  1.653604  1.648146  1.417261
  1.311939  1.200763  1.647532  1.610222  1.355913  1.538724  1.319192
  1.265142  1.494068  1.268721  1.411822  1.580606  1.622305  1.40986
  1.529142  1.33644   1.37585   1.589704  1.563133  1.753167  1.382264
  1.771445  1.425574  1.374936  1.147079  1.626975  1.351203  1.356176
  1.534271  1.405485  1.266821  1.647927  1.28254   1.529214  1.586097
  1.357731  1.530607  1.307063  1.432288  1.525117  1.525117  1.510123
  1.653006  1.37388   1.247077  1.752948  1.396821  1.578571  1.546904
  1.483029  1.441626  1.750374  1.498266  1.571477  1.659957  1.640285
  1.599326  1.743292  1.225557  1.664379  1.787492  1.364079  1.53362
  1.294213  1.831521  1.19443   1.726312  1.84324 ]

现在，我已尝试使用以下变体绘制轮廓的许多尝试：

delta = 0.025
OII_OIII_sAGN_sorted = numpy.arange(numpy.min(OII_OIII_sAGN), numpy.max(OII_OIII_sAGN), delta)
Dn4000_sAGN_sorted = numpy.arange(numpy.min(Dn4000_sAGN), numpy.max(Dn4000_sAGN), delta)
OII_OIII_sAGN_X, Dn4000_sAGN_Y = np.meshgrid(OII_OIII_sAGN_sorted, Dn4000_sAGN_sorted)

Z1 = matplotlib.mlab.bivariate_normal(OII_OIII_sAGN_X, Dn4000_sAGN_Y, 1.0, 1.0, 0.0, 0.0)
Z2 = matplotlib.mlab.bivariate_normal(OII_OIII_sAGN_X, Dn4000_sAGN_Y, 0.5, 1.5, 1, 1)
# difference of Gaussians
Z = 0.2 * (Z2 - Z1)
pyplot_middle.contour(OII_OIII_sAGN_X, Dn4000_sAGN_Y, Z, 12, colors='k')

这似乎没有给出所需的输出。我也尝试过：

H, xedges, yedges = np.histogram2d(OII_OIII_sAGN,Dn4000_sAGN)
extent = [xedges[0],xedges[-1],yedges[0],yedges[-1]]
ax.contour(H, extent=extent)

不是我想要的工作。基本上，我正在寻找类似的东西：

如果有人可以帮助我，我将非常感激，无论是建议一个全新的方法还是修改我现有的代码。如果您有一些有用的技巧或想法，请附上您的输出图像。

Answer 1

似乎histogram2d需要一些摆弄才能在正确的位置绘制轮廓。我对直方图矩阵进行了转置，并且还采用了xedges和yedges中元素的平均值，而不是从末尾删除一个。

from matplotlib import pyplot as plt
import numpy as np
fig = plt.figure()
h, xedges, yedges = np.histogram2d(x, y, bins=9)
xbins = xedges[:-1] + (xedges[1] - xedges[0]) / 2
ybins = yedges[:-1] + (yedges[1] - yedges[0]) / 2

h = h.T
CS = plt.contour(xbins, ybins, h)
plt.scatter(x, y)
plt.show()

Answer 2

seaborn开箱即用密度图：

import seaborn as sns
import matplotlib.pyplot as plt

sns.kdeplot(x, y)
plt.show()

使用matplotlib的2d密度等值线图

2 个答案: