Closed
Description
I have a dataset with large gradients in a quantity I am plotting. In many cases, this results in mis-filled contours when I use many contouring levels. For example:
This does not occur on 2D axes, even with 2 orders of magnitude more contouring levels. I can reduce some of the fill errors by reducing the number of contouring levels or zooming in on the domain so the strong gradients aren't as relatively strong in figure space. If I don't fill the contours, e.g. calling contour rather than contourf there are no errors. This is restricted to the filling,
Here is a script that should reproduce the problem for you. Tested with matplotlib 1.4.3 and python 3.4.1.
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d.axes3d as p3
data=np.array([[53.9751, 51.5681, 50.7119, 51.1049, 51.5339, 51.4977, 51.2387,50.761, 50.1732, 49.8218, 49.5442, 48.936, 47.4498, 46.6484, 45.8542, 45.136, 44.5268, 44.071, 43.7665, 43.5928, 43.5269, 43.5385, 43.6053, 45.565, 47.0071, 46.8664, 47.372, 47.8324, 48.295, 48.731, 49.0522, 49.4001, 49.7111, 49.9919, 50.2527, 50.4928, 50.7135, 50.8831, 51.0806, 51.2683 ],
[55.6671, 52.53, 50.7764, 50.5632, 51.2095, 51.5659, 51.521, 51.2143, 50.653, 50.2371, 49.989, 49.8089, 49.6058, 47.8355, 47.3124, 46.7346, 46.1616, 45.6498, 45.2462, 44.967, 44.8005, 44.7284, 44.7295, 44.7869, 46.959, 45.0194, 46.73, 48.0766, 48.9395, 49.5325, 49.8498, 50.1887, 50.4798, 50.7406, 50.9808, 51.2003, 51.4074, 51.555, 51.7429, 51.9218 ],
[56.6513, 53.5919, 51.2774, 50.3133, 50.7705, 51.533, 51.8287, 51.7083, 51.2816, 50.7933, 50.4806, 50.2671, 50.1009, 50.0096, 49.9052, 49.4698, 47.4655, 47.0717, 46.6849, 46.3583, 46.1122, 45.952, 45.8678, 45.8485, 45.8811, 45.956, 46.0634, 47.2225, 49.4363, 50.2482, 50.527, 50.8558, 51.1358, 51.3809, 51.607, 51.8179, 52.0161, 52.1454, 52.3263, 52.497 ],
[57.078, 54.3224, 52.0759, 50.4679, 50.4677, 51.297, 52.0284, 52.1594, 51.9395, 51.5518, 51.1419, 50.8765, 50.6686, 50.5101, 50.4078, 50.3473, 50.3592, 50.3813, 49.7504, 47.55, 47.324, 47.1365, 46.9978, 46.9119, 46.8743, 46.8811, 46.9257, 47.0013, 50.0148, 50.9106, 51.1133, 51.4282, 51.7064, 51.943, 52.1587, 52.3597, 52.4789, 52.6631, 52.8359, 52.9966 ],
[57.3835, 54.9025, 52.8571, 50.9842, 50.5197, 51.1494, 52.0599, 52.4732, 52.4716, 52.2656, 51.9535, 51.6068, 51.3466, 51.1513, 50.9708, 50.8321, 50.7639, 50.7944, 50.8817, 49.8122, 48.2038, 48.086, 47.9704, 47.8735, 47.8035, 47.7644, 47.7574, 47.7803, 50.8194, 51.5486, 51.6645, 51.9745, 52.2349, 52.4508, 52.6481, 52.8317, 52.9412, 53.1097, 53.2699, 53.4171 ],
[57.9157, 55.6092, 53.6306, 51.8011, 50.9372, 51.2615, 52.1406, 52.7436, 52.8528, 52.7829, 52.6322, 52.403, 52.1149, 51.866, 51.6624, 51.4773, 51.317, 51.2183, 51.2153, 51.1367, 48.5913, 48.6216, 48.6218, 48.5951, 48.5589, 48.527, 48.5081, 50.5185, 51.6998, 51.905, 52.2258, 52.4891, 52.7062, 52.8926, 53.0655, 53.2251, 53.3262, 53.4755, 53.6169, 53.7471 ],
[58.6093, 56.432, 54.307, 52.6277, 51.584, 51.6482, 52.3762, 53.0685, 53.2545, 53.217, 53.1356, 53.0351, 52.8481, 52.6154, 52.39, 52.177, 51.9977, 51.843, 51.7172, 51.4587, 48.7481, 48.7984, 48.864, 48.9291, 48.9843, 49.0228, 50.496, 51.8667, 52.3404, 52.4759, 52.6889, 52.8851, 53.0525, 53.2072, 53.354, 53.4576, 53.5925, 53.7217, 53.8432, 53.956 ],
[58.9719, 56.9885, 54.8768, 53.3526, 52.3025, 52.2089, 52.7762, 53.4444, 53.6768, 53.6706, 53.5692, 53.5162, 53.4373, 53.2886, 53.1113, 52.9065, 52.6988, 52.5193, 52.3544, 52.0384, 48.9624, 48.9653, 49.0005, 49.0574, 49.1258, 50.692, 51.9726, 52.4309, 52.699, 52.8194, 52.9845, 53.1336, 53.2669, 53.393, 53.5118, 53.6086, 53.7213, 53.8293, 53.9308, 54.026 ],
[58.5754, 56.945, 55.068, 53.7798, 52.9469, 52.854, 53.3136,53.8929, 54.1205, 54.1178, 54.0128, 53.9289, 53.8906, 53.8239,53.717, 53.5724, 53.3818, 53.1892, 53.009, 49.3078, 49.2524,49.2165, 49.2032, 49.2187, 50.463, 51.9497, 52.4487, 52.7041,52.8358, 52.9776, 53.1101, 53.2293, 53.3419, 53.4487, 53.5401,53.6365, 53.7301, 53.8205, 53.9062, 53.9869 ],
[57.623, 56.547, 55.0117, 54.0512, 53.5372, 53.5246, 53.927,54.3868, 54.5828, 54.5811, 54.4501, 54.3235, 54.2626, 54.2334,54.1802, 54.1137, 53.9897, 53.8202, 49.796, 49.6864, 49.5946,49.5216, 49.4703, 49.4432, 51.8479, 52.5574, 52.8359, 52.9722,53.0827, 53.1826, 53.2747, 53.3597, 53.4405, 53.5138, 53.5944,53.6751, 53.7536, 53.829, 53.9019, 53.9721 ],
[56.902, 56.0005, 54.9159, 54.3352, 54.123, 54.2014, 54.5659,54.8917, 55.0307, 55.0139, 54.8838, 54.7044, 54.5863, 54.5548,54.5258, 54.4957, 54.4633, 51.4821, 50.1897, 50.0758, 49.9683,49.8704, 49.7842, 51.5064, 52.7625, 53.0724, 53.1926, 53.2682,53.3404, 53.4119, 53.4831, 53.5517, 53.6169, 53.6763, 53.7383,53.8009, 53.8644, 53.9281, 53.9905, 54.0517 ],
[56.3455, 55.5524, 54.9336, 54.6836, 54.703, 54.8657, 55.1749,55.3844, 55.4521, 55.4019, 55.2622, 55.0281, 54.8981, 54.6591,54.7866, 54.7678, 54.7654, 54.0436, 54.2302, 52.2533, 50.3305,50.2276, 50.1268, 52.9617, 53.4395, 53.5504, 53.5481, 53.5524,53.5699, 53.6014, 53.644, 53.6931, 53.7445, 53.7996, 53.8548,53.9097, 53.9655, 54.0229, 54.0813, 54.1393 ],
[55.7493, 55.3019, 55.1012, 55.0906, 55.234, 55.4751, 55.7134,55.8462, 55.8461, 55.7425, 55.5725, 55.3535, 55.1612, 54.958,55.0193, 54.9584, 54.9531, 54.8886, 54.8256, 54.2211, 50.6477,50.5564, 53.0546, 53.8592, 54.08, 54.0288, 53.9509, 53.8796,53.8307, 53.8073, 53.8034, 53.8142, 53.8383, 53.8725, 53.9128,53.9558, 54.0013, 54.0497, 54.103, 54.1597 ],
[55.2575, 55.1664, 55.3165, 55.5004, 55.7345, 55.9901, 56.1852,56.2599, 56.2027, 56.0454, 55.818, 55.5754, 55.302, 55.2083,55.0224, 55.1415, 55.0656, 55.0446, 55.0263, 54.7728, 50.8924,53.4671, 54.2587, 54.5146, 54.6171, 54.519, 54.3857, 54.2497,54.1355, 54.0509, 53.9932, 53.9584, 53.941, 53.939, 53.9527,53.9798, 54.0111, 54.0465, 54.0868, 54.1339 ],
[54.8665, 55.1533, 55.5095, 55.8512, 56.1541, 56.3995, 56.5593,56.6009, 56.5079, 56.3001, 56.0178, 55.7187, 55.448, 55.063,55.2016, 55.2116, 55.1817, 55.112, 55.1099, 55.0299, 54.3358,54.6966, 54.9199, 55.0156, 55.0728, 54.975, 54.8299, 54.6609,54.493, 54.3475, 54.2349, 54.1517, 54.0928, 54.0516, 54.0245,54.013, 54.0206, 54.0404, 54.0667, 54.0989 ],
[54.2676, 55.1132, 55.6112, 56.09, 56.428, 56.6661, 56.8056,56.8374, 56.7339, 56.4923, 56.1474, 55.7977, 55.4805, 55.2341,54.8999, 55.2662, 55.2927, 55.185, 55.1237, 55.1268, 54.9772,55.1418, 55.2612, 55.3333, 55.379, 55.3244, 55.2153, 55.0629,54.881, 54.6926, 54.523, 54.3866, 54.2855, 54.2118, 54.1583,54.1191, 54.0935, 54.0834, 54.0885, 54.1057 ],
[54.1771, 55.0795, 55.7075, 56.1772, 56.5183, 56.7522, 56.8898,56.9315, 56.8427, 56.6056, 56.2317, 55.8095, 55.4436, 55.183,55.0284, 54.9504, 55.2833, 55.2563, 55.1498, 55.1342, 55.1331,55.259, 55.3705, 55.4452, 55.4955, 55.5087, 55.4697, 55.3766,55.2324, 55.049, 54.8485, 54.6578, 54.4995, 54.3822, 54.3002,54.2427, 54.2022, 54.1749, 54.1598, 54.1561 ],
[53.9112, 54.85, 55.6641, 56.0844, 56.4062, 56.6232, 56.757,56.8149, 56.7669, 56.5754, 56.2311, 55.785, 55.366, 55.0104,54.812, 54.8845, 55.1273, 55.2339, 55.1976, 55.1049, 55.0913,55.1843, 55.3048, 55.4076, 55.4709, 55.518, 55.5455, 55.5329,55.4636, 55.3349, 55.1595, 54.9529, 54.7462, 54.5681, 54.4342,54.3439, 54.2848, 54.2446, 54.2222, 54.2135 ],
[53.9368, 54.9196, 55.4408, 55.7999, 56.0652, 56.2423, 56.348,56.4106, 56.4114, 56.3028, 56.0519, 55.6779, 55.2493, 54.8836,54.6592, 54.6347, 54.8341, 55.0606, 55.1396, 55.0967, 55.0325,55.0501, 55.1451, 55.2627, 55.3559, 55.4216, 55.4789, 55.5183,55.5245, 55.4779, 55.3701, 55.2072, 55.0029, 54.7876, 54.5915,54.4378, 54.3368, 54.2787, 54.2415, 54.2271 ],
[53.9325, 54.6506, 55.0421, 55.2926, 55.4603, 55.5679, 55.6285,55.6792, 55.7234, 55.731, 55.639, 55.3923, 55.043, 54.6845,54.4188, 54.3242, 54.4606, 54.7449, 54.9548, 55.0171, 55.0047,54.9454, 54.9666, 55.0651, 55.1828, 55.2677, 55.3308, 55.3914,55.438, 55.4544, 55.4277, 55.3385, 55.1907, 54.9981, 54.7786,54.5691, 54.4013, 54.2898, 54.233, 54.1994 ] ])
fig = plt.figure()
ax = fig.add_subplot(111,projection='3d')
X,Y = np.meshgrid(np.arange(-30.0,-20.0,0.25), np.arange(20.0,25,0.25))
ax.contourf(X,Y,data,zdir='z',offset=0, levels=np.arange(0,75,1))
ax.set_zlim(0.0,2.0)
plt.savefig('testfig.png')
plt.close()
which produces the image:
In this case, reducing the contouring level will fix the mis-fill but for the plots I want to produce this isn't a feasible option.