Question

我试图用cartopy和matplotlib.tri绘制三角形网格。我使用matplotlib.tri.Triangulation对象，并希望用matplotlib.pyplot.triplot绘制它。

当我通过transform=projection将形图投影作为转换传递到triplot时，正如我绘制线条所做的那样，并非所有三角形都被绘制，并且在尝试保存图形时我得到IndexError

另一方面，当我手动转换三角测量中的所有点并调用triplot时，它可以工作。

在下面的第一个示例中，绘制了所有三角形，Line2D个对象没有差异。但是试图保存这个数字会引发IndexError。

在第二个示例中，来自具有Line2D的triplot和来自手动转换后的triplot的结果transform=projection对象在应用于其数据的转换结果方面不同。也许这可能是组合转换顺序的问题。

N.B。：我选择PlateCarree让它尽可能简单。我对其他轴和数据投影组合也有同样的问题。

import matplotlib.pyplot as plt
import numpy as np
from cartopy.crs import PlateCarree
from matplotlib.tri import Triangulation

plt.interactive(False)

# NB. plt.triplot returns a list of two Line2D objects in both cases
# the second of which is empty, therefore only the first is returned

def triplot_with_transform(triangulation):
    """
    triangulation: matplotlib.tri.Triangulation

    """
    plt.figure()
    plt.subplot(projection=PlateCarree())
    lines = plt.triplot(triangulation, transform=PlateCarree())
    return plt.gcf(), lines[0]


def transform_before_triplot(triangulation):
    """
    triangulation: matplotlib.tri.Triangulation

    """
    plt.figure()
    plt.subplot(projection=PlateCarree())
    [x_tr, y_tr, _] = PlateCarree().transform_points(PlateCarree(),
                                                     triangulation.x,
                                                     triangulation.y).T
    triangulation_tr = Triangulation(x_tr, y_tr, triangulation.triangles)
    lines = plt.triplot(triangulation_tr)
    return plt.gcf(), lines[0]


def compare_line2d(line1, line2):
    """
    line1, line2 : matplotlib.lines.Line2D

    """
    data1 = line1.get_xydata()
    transform1 = line1.get_transform()
    data2 = line2.get_xydata()
    transform2 = line2.get_transform()
    data1_ma = np.ma.masked_invalid(data1)
    data2_ma = np.ma.masked_invalid(data2)
    data1_tr = transform1.transform(data1)
    data2_tr = transform2.transform(data2)
    data1_tr_ma = np.ma.masked_invalid(data1_tr)
    data2_tr_ma = np.ma.masked_invalid(data2_tr)

    print 'NaNs in line data match ', np.all(data1_ma.mask == data2_ma.mask)
    print 'Line data mismatch', abs(data1_ma-data2_ma).max()

    print 'NaNs in transformed line data match ', np.all(data1_tr_ma.mask ==
                                                         data2_tr_ma.mask)
    print 'Transformed line data mismatch', abs(data1_tr_ma-data2_tr_ma).max()


def try_so_save(fig):
    try:
        fig.savefig('triangulation.pdf')
    except Exception as e:
        print "Exception while saving figure\n", e.__repr__()


# First example, 100 vertices.
x, y = np.meshgrid(np.arange(0, 50, 5), np.arange(0, 50, 5))
tri = Triangulation(x.ravel(), y.ravel())
fig1, line1 = triplot_with_transform(tri)
fig2, line2 = transform_before_triplot(tri)

# Second example, 2500 vertices.
x, y = np.meshgrid(np.arange(0, 50), np.arange(0, 50))
tri = Triangulation(x.ravel(), y.ravel())
fig3, line3 = triplot_with_transform(tri)
fig4, line4 = transform_before_triplot(tri)

# Compare Line2D objects; since we transform from PlateCarree to
# PlateCarree, the lines should be (almost) equal.
print "Line2D objects from first example"
compare_line2d(line1, line2)
print "Line2D objects from second example"
compare_line2d(line3, line4)

# Try to save the figures.
print "Save fig1 from first example."
try_so_save(fig1)
print "Save fig3 from second example."
try_so_save(fig3) 

# failing plt.savefig command to produce full traceback
fig1.savefig('triangulation.pdf')

输出

Line2D objects from first example
NaNs in line data match  True
Line data mismatch 3.5527136788e-15
NaNs in transformed line data match  True
Transformed line data mismatch 0.0
Line2D objects from second example
NaNs in line data match  True
Line data mismatch 7.1054273576e-15
NaNs in transformed line data match  True
Transformed line data mismatch 3545.955
Save fig1 from first example.
Exception while saving figure
IndexError('Out of bounds on buffer access (axis 0)',)
Save fig3 from second example.
Exception while saving figure
IndexError('Out of bounds on buffer access (axis 0)',)

尝试保存使用transform=projection创建的任何数字时，cartopy._crs.CRS.transform_points会提升IndexError。

这是cartopy或matplotlib.tri的问题吗？有没有办法避免手动转换并将transform参数传递给triplot？

编辑：

在pp-mo的回答之后，我发现在triplot命令中添加带有标记的格式字符串（如'o-'）可以使其正常工作。但是，改变颜色（'g-）无济于事。

编辑2：

在示例代码中添加了fig1.savefig以生成完整的回溯。

Answer 1

我试过这个，并且似乎并不是机制的根本问题。这是一个简单的工作示例...

"""
Example shamelessly poached from http://matplotlib.org/mpl_examples/pylab_examples/triplot_demo.py

We just add a mapping transform to the second figure there...

"""
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import math

import cartopy.crs as ccrs

# Some points defining a triangulation over (roughly) Britain.
xy = np.asarray([
    [-0.101, 0.872], [-0.080, 0.883], [-0.069, 0.888], [-0.054, 0.890],
    [-0.045, 0.897], [-0.057, 0.895], [-0.073, 0.900], [-0.087, 0.898],
    [-0.090, 0.904], [-0.069, 0.907], [-0.069, 0.921], [-0.080, 0.919],
    [-0.073, 0.928], [-0.052, 0.930], [-0.048, 0.942], [-0.062, 0.949],
    [-0.054, 0.958], [-0.069, 0.954], [-0.087, 0.952], [-0.087, 0.959],
    [-0.080, 0.966], [-0.085, 0.973], [-0.087, 0.965], [-0.097, 0.965],
    [-0.097, 0.975], [-0.092, 0.984], [-0.101, 0.980], [-0.108, 0.980],
    [-0.104, 0.987], [-0.102, 0.993], [-0.115, 1.001], [-0.099, 0.996],
    [-0.101, 1.007], [-0.090, 1.010], [-0.087, 1.021], [-0.069, 1.021],
    [-0.052, 1.022], [-0.052, 1.017], [-0.069, 1.010], [-0.064, 1.005],
    [-0.048, 1.005], [-0.031, 1.005], [-0.031, 0.996], [-0.040, 0.987],
    [-0.045, 0.980], [-0.052, 0.975], [-0.040, 0.973], [-0.026, 0.968],
    [-0.020, 0.954], [-0.006, 0.947], [ 0.003, 0.935], [ 0.006, 0.926],
    [ 0.005, 0.921], [ 0.022, 0.923], [ 0.033, 0.912], [ 0.029, 0.905],
    [ 0.017, 0.900], [ 0.012, 0.895], [ 0.027, 0.893], [ 0.019, 0.886],
    [ 0.001, 0.883], [-0.012, 0.884], [-0.029, 0.883], [-0.038, 0.879],
    [-0.057, 0.881], [-0.062, 0.876], [-0.078, 0.876], [-0.087, 0.872],
    [-0.030, 0.907], [-0.007, 0.905], [-0.057, 0.916], [-0.025, 0.933],
    [-0.077, 0.990], [-0.059, 0.993]])
# Make lats + lons
x = xy[:, 0]*180/3.14159
y = xy[:, 1]*180/3.14159

# A selected triangulation of the points.
triangles = np.asarray([
    [67, 66,  1], [65,  2, 66], [ 1, 66,  2], [64,  2, 65], [63,  3, 64],
    [60, 59, 57], [ 2, 64,  3], [ 3, 63,  4], [ 0, 67,  1], [62,  4, 63],
    [57, 59, 56], [59, 58, 56], [61, 60, 69], [57, 69, 60], [ 4, 62, 68],
    [ 6,  5,  9], [61, 68, 62], [69, 68, 61], [ 9,  5, 70], [ 6,  8,  7],
    [ 4, 70,  5], [ 8,  6,  9], [56, 69, 57], [69, 56, 52], [70, 10,  9],
    [54, 53, 55], [56, 55, 53], [68, 70,  4], [52, 56, 53], [11, 10, 12],
    [69, 71, 68], [68, 13, 70], [10, 70, 13], [51, 50, 52], [13, 68, 71],
    [52, 71, 69], [12, 10, 13], [71, 52, 50], [71, 14, 13], [50, 49, 71],
    [49, 48, 71], [14, 16, 15], [14, 71, 48], [17, 19, 18], [17, 20, 19],
    [48, 16, 14], [48, 47, 16], [47, 46, 16], [16, 46, 45], [23, 22, 24],
    [21, 24, 22], [17, 16, 45], [20, 17, 45], [21, 25, 24], [27, 26, 28],
    [20, 72, 21], [25, 21, 72], [45, 72, 20], [25, 28, 26], [44, 73, 45],
    [72, 45, 73], [28, 25, 29], [29, 25, 31], [43, 73, 44], [73, 43, 40],
    [72, 73, 39], [72, 31, 25], [42, 40, 43], [31, 30, 29], [39, 73, 40],
    [42, 41, 40], [72, 33, 31], [32, 31, 33], [39, 38, 72], [33, 72, 38],
    [33, 38, 34], [37, 35, 38], [34, 38, 35], [35, 37, 36]])

# Make a triangulation object
my_tris = tri.Triangulation(x, y, triangles)

# Plot over an OSGB map with a coastline.
crs_pc = ccrs.PlateCarree()
crs_uk = ccrs.OSGB()
plt.figure()
ax = plt.axes(projection=crs_uk)
ax.coastlines(color='red', linewidth=1.5)
plt.triplot(my_tris,
            'go-',
            transform=ccrs.PlateCarree())
plt.show()

输出：

所以... 的
我只是猜测你的问题可能是你的实际三角测量（哪些点以三角形连接）在点已经通过变换时不再适用。
最明显的原因是三角形穿过了一条缝线＆＃34;在投影中。例如，您可能拥有-30到+30之间的经度，但想要绘制从0到360度的地图。

这是可能的原因吗？

用cartopy和matplotlib.tri绘制三角形网格

1 个答案: