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2d density contour plot with matplotlib

I'm attempting to plot my dataset, x and y (generated from a csv file via numpy.genfromtxt('/Users/.../somedata.csv', delimiter=',', unpack=True)) as a simple density plot. To ensure this is self containing I will define them here:

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 ]

Now, I have used many attempts to plot my contours using variations on:

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')

This doesn't seem to give the desired output.I have also tried:

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

Not quite working as I wanted either. Essentially, I am looking for something similar to this:

enter image description here

If anyone could help me with this I would be very grateful, either by suggesting a totally new method or modifying my existing code. Please also attach images of your output if you have some useful techniques or ideas.

like image 853
GCien Avatar asked Jan 07 '23 18:01

GCien


2 Answers

seaborn does density plots right out of the box:

import seaborn as sns
import matplotlib.pyplot as plt

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

kdeplot

like image 115
σηγ Avatar answered Jan 16 '23 00:01

σηγ


It seems that histogram2d takes some fiddling to plot the contour in the right place. I took the transpose of the histogram matrix and also took the mean values of the elements in xedges and yedges instead of just removing one from the end.

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()

Contour density plot

like image 45
Amy Teegarden Avatar answered Jan 16 '23 02:01

Amy Teegarden