【发布时间】：2021-07-16 09:30:24
【问题描述】：
我正在使用 SciPy Griddata 以笛卡尔形式插入数据，然后使用带有极坐标投影的轮廓绘制这些数据。当使用 contourf 绘制笛卡尔插值数据时，没有伪影。但是，当投影是极性时，伪影会随着“级别”的增加而发展。
伪影是在陡峭梯度区域附近形成的多边形或射线。下面的代码绘制了月亮与天空的亮度。使用“12”的图形级别没有问题。工件以“25”的graphlevel 发展。我想要的等级是 80 或更高 - 这显示了可怕的伪影。以下是一晚的示例真实数据。这些伪影总是会发生。查看带有Levels = 12 和Levels = 80 的图片
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
gridsize =150
graphlevels =12
plt.figure(figsize=(12,10))
ax = plt.subplot(111,projection='polar')
x = [72.90,68.00,59.14,44.38,29.63,63.94,59.68,51.92,38.98,26.03,47.34,44.20,38.46,28.89,19.31,23.40,20.40,15.34,10.28,-0.18,-0.14,-0.09,-0.04,0.02,-25.39,-23.66,-20.57,-15.40,-10.23,-47.56,-44.34,-38.54,-28.89,-19.22,-64.01,-59.68,-51.89,-38.90,-25.90,-72.77,-67.84,-58.98,-44.21,-29.44,-72.75,-67.83,-58.96,-44.18,-29.41,-59.63,-51.82,-38.83,-25.84,-47.42,-44.20,-38.40,-28.76,-19.12,-23.40,-20.32,-15.19,-10.08,0.27,0.25,0.23,0.20,23.92,20.80,15.63,10.46,47.93,44.67,38.86,29.17,19.48,64.40,60.03,52.20,39.18,26.15,73.08,68.12,59.26,44.47,29.68,-4.81]
y = [12.93,12.01,10.38,7.67,4.99,37.03,34.49,29.93,22.33,14.77,56.60,52.75,45.82,34.26,22.72,64.60,56.14,42.02,27.90,73.66,68.67,59.68,44.68,29.68,69.12,64.45,56.00,41.92,27.84,56.26,52.45,45.56,34.08,22.61,36.59,34.11,29.61,22.11,14.62,12.48,11.62,10.04,7.43,4.83,-13.33,-12.31,-10.78,-8.21,-5.58,-34.84,-30.36,-22.87,-15.36,-57.04,-53.20,-46.31,-34.83,-23.34,-65.20,-56.72,-42.62,-28.53,-69.33,-60.31,-45.31,-30.31,-65.09,-56.63,-42.55,-28.47,-56.81,-52.99,-46.13,-34.69,-23.23,-36.99,-34.53,-30.08,-22.66,-15.22,-12.73,-11.93,-10.44,-7.94,-5.40,-1.22,]
skybrightness = [19.26,19.31,19.21,19.65,19.40,19.26,19.23,19.43,19.57,19.52,19.19,19.31,19.33,19.68,19.50,19.29,19.45,19.50,19.23,18.98,19.28,19.46,19.54,19.22,19.03,19.18,19.35,19.37,19.08,18.99,18.98,19.26,19.36,19.08,18.79,18.85,19.13,19.17,19.05,18.51,18.64,18.88,18.92,18.93,18.12,18.34,18.72,18.82,18.74,18.22,18.46,18.76,18.26,18.13,18.24,18.46,18.58,17.30,18.38,18.08,18.24,17.68,18.34,18.46,18.65,18.23,18.70,18.52,18.79,18.83,18.18,18.51,19.01,19.08,19.08,18.99,19.02,19.07,19.20,19.27,19.06,19.01,19.28,19.46,19.30,18.94]
xgrid = np.linspace(min(x), max(x),gridsize)
ygrid = np.linspace(min(y), max(y),gridsize)
xgrid, ygrid = np.meshgrid(xgrid, ygrid, indexing='ij')
nsb_grid = griddata((x,y),skybrightness,(xgrid, ygrid), method='linear')
r = np.sqrt(xgrid**2 + ygrid**2)
theta = np.arctan2(ygrid, xgrid)
plt.rc('ytick', labelsize=16)
ax.set_facecolor('#eeddcc')
colors = plt.cm.get_cmap('RdYlBu')
levels,steps = np.linspace(min(skybrightness), max(skybrightness)+0.3,graphlevels, retstep=True)
ticks = np.linspace(min(skybrightness), max(skybrightness)+0.3,12)
cax = ax.contourf(theta, r, nsb_grid, levels=levels, cmap=colors)
cbar = plt.colorbar(cax, fraction=0.046, pad=0.04, ticks=ticks)
cbar.set_label(r'mag/arcsec$^2$')
ax.set_theta_zero_location('N')
ax.set_theta_direction(-1)
ax.set_rmax(75)
ax.set_yticks(range(10, 80, 20))
ax.set_xticklabels([r'N', r'NE', r'E', r'SE', r'S', r'SW', r'W', r'NW'])
ax.grid(alpha=0.3)
plt.savefig('StackOverflowHELP.png')
【问题讨论】：
-
伪影是否也出现在笛卡尔（非极坐标）图中？ Contourf 也进行插值。 minimal reproducible example 将有助于调试。
-
不，工件不会出现在笛卡尔绘图中。 contourf 的所有方法似乎都不起作用。我认为确实做了一个最小的可复制示例！ :)
-
非常好的 MCVE！ （仍有一些样式可以删除，但这已经足够简洁了，很有用。）我不确定发生了什么，但其他人现在可以为您提供帮助。
-
谢谢安德拉斯。要创建笛卡尔结果 - 关闭 ax.set 极坐标样式并且 cax = ax.contourf(xgrid, ygrid, nsb_grid, levels=levels, cmap=colors)。无论轮廓水平如何，这都没有伪影。这就是为什么我将极地投影视为一个问题。
-
哦，是的，我明白了。我的意思是我不知道问题出在哪里。我尝试从插值数据中删除 nans（似乎没有帮助），我尝试直接插值极坐标值（我无法在我可以花在所有这些上的十分钟内得到它）。
标签： python matplotlib scipy interpolation contourf