使用"matplotlib.mlab.griddata"时程序卡住了。

3

我已经编写了一个脚本(Python 2.6),用于对x、y、z (.csv 格式) 数据进行网格化,并显示数据的等高线图。

该脚本对某些数据集有效,但对其他数据集无效 - 即使这些数据集都是使用同一脚本创建的。

要绘制的数据集是通过从主数据集中进行子采样而创建的。

以下是 every_4.csv 的示例(每 4 行进行一次主数据集的子采样)。

Easting Northing    TMI_nT 
526243.0    5254128.9   62278.8
526259.4    5254128.9   62352.3
526275.9    5254128.9   62303.3
526292.3    5254128.9   62361.9
526308.8    5254128.9   62667.8
526325.2    5254128.9   62668.6
526341.7    5254128.9   61700.1
526358.1    5254128.9   62029.6
526374.6    5254128.9   62042.7

使用我的脚本,这个数据可以正确绘图。

"every_3.csv" 和 "every_4.csv" 的格式相同,但当尝试执行以下命令时,会导致我的脚本挂起(没有错误信息):

zi = griddata(x, y, z, xi, yi)

下面是我使用的脚本:

### program to test gridding and contouring

import numpy as N
import scipy as S
from matplotlib.mlab import griddata
import matplotlib.pyplot as P
import matplotlib.cm as CM

longarray = N.loadtxt('every_3.csv', skiprows=1, delimiter=',')
x = longarray[:,0]
y = longarray[:,1]
z = longarray[:,2]

max_x = max(x)
min_x = min(x)
max_y = max(y)
min_y = min(y)

##print max_y
##print min_x
##print max_x
##print min_y

xi = N.linspace(min_x, max_x)
yi = N.linspace(min_y, max_y)

zi = griddata(x, y, z, xi, yi)
print zi
CS = P.contourf(xi,yi,zi,15,cmap=CM.RdYlBu)

P.show()

我无法理解为什么这个脚本会在某些文件上卡住而在其他文件上不会。

注意:如果我在excel中打开every_3.csv并删除一些行(例如文件中50%的行),我就可以运行该脚本...

更新

以下是更完整的数据集:

Easting Northing    TMI_nT
526243  5254128.9   62278.8
526247.1    5254128.9   62413.3
526251.2    5254128.9   62398.6
526255.3    5254128.9   62355.7
526259.4    5254128.9   62352.3
526263.6    5254128.9   62327.8
526267.7    5254128.9   62279.6
526271.8    5254128.9   62322.1
526275.9    5254128.9   62303.3
526280  5254128.9   62375.1
526284.1    5254128.9   62561.4
526288.2    5254128.9   62302.4
526292.3    5254128.9   62361.9
526374.6    5254128.9   62042.7
526378.7    5254128.9   62139.6
526382.8    5254128.9   61891.5
526386.9    5254128.9   61937.2
526391  5254128.9   62238.7
526395.1    5254128.9   62344.9
526399.2    5254128.9   62220.4
526403.3    5254128.9   62027
526407.4    5254128.9   62392.2
526411.6    5254128.9   63252.4
526415.7    5254128.9   62951.8
526419.8    5254128.9   62504.5
526423.9    5254128.9   62927.6
526428  5254128.9   62813.9
526432.1    5254128.9   63381.4
526436.2    5254128.9   63458.5
526440.3    5254128.9   63273
526444.4    5254128.9   62945
526448.6    5254128.9   62466.2
526452.7    5254128.9   62300.3
526456.8    5254128.9   62164.3
526460.9    5254128.9   62144.7
526465  5254128.9   62216.7
526469.1    5254128.9   62307.3
526473.2    5254128.9   62437.6
526477.3    5254128.9   62495
526481.4    5254128.9   62256.1
526485.6    5254128.9   61951.2
526489.7    5254128.9   61632
526493.8    5254128.9   61221.6
526497.9    5254128.9   62414.3
526502  5254128.9   64152.7
526506.1    5254128.9   61964.7
526510.2    5254128.9   61952.5
526514.3    5254128.9   62104.2
526518.4    5254128.9   62190.4
526522.6    5254128.9   62334.8
526526.7    5254128.9   62468.8
526530.8    5254128.9   62437.3
526296.4    5253951.8   62138
526300.6    5253951.8   62283.3
526304.7    5253951.8   62336
526308.8    5253951.8   62367.6
526312.9    5253951.8   62416
526317  5253951.8   62395.3
526321.1    5253951.8   62364.1
526325.2    5253951.8   62363.2
526329.3    5253951.8   62292.6
526333.4    5253951.8   62252
526337.6    5253951.8   62179.1
526341.7    5253951.8   62086.8
526345.8    5253951.8   62069.6
526349.9    5253951.8   62108.4
526354  5253951.8   61994
526358.1    5253951.8   61909.1
526362.2    5253951.8   61943.1
526366.3    5253951.8   61918.6
526370.4    5253951.8   61895.9
526374.6    5253951.8   61871.6
526378.7    5253951.8   61821.4
526382.8    5253951.8   61778.1
526386.9    5253951.8   61738.2
526391  5253951.8   61644.5
526395.1    5253951.8   61555.8
526399.2    5253951.8   61540
526403.3    5253951.8   61549.6
526407.4    5253951.8   61596.4
526411.6    5253951.8   61566.5
526415.7    5253951.8   61565.1
526419.8    5253951.8   61287.6
526423.9    5253951.8   61368
526428  5253951.8   61481.5
526432.1    5253951.8   61228.8
526436.2    5253951.8   61024.6
526440.3    5253951.8   60960.9
526444.4    5253951.8   61146.7
526448.6    5253951.8   61240.8
526452.7    5253951.8   61396.5
526456.8    5253951.8   61536.9
526460.9    5253951.8   61677.1
526465  5253951.8   61715.6
526469.1    5253951.8   61749.8
526473.2    5253951.8   61809.1
526477.3    5253951.8   61939.2
526481.4    5253951.8   61913.3
526485.6    5253951.8   62035.7
526489.7    5253951.8   62108.9
526493.8    5253951.8   62025.4
526497.9    5253951.8   61929.1
526502  5253951.8   61947.2
526506.1    5253951.8   62182.8
526510.2    5253951.8   62239.3
526514.3    5253951.8   62071.7
526518.4    5253951.8   62054.5
526522.6    5253951.8   62001.3
526526.7    5253951.8   61993.5
526530.8    5253951.8   62009.3
526534.9    5253951.8   61966.5
526539  5253951.8   61947.2
526543.1    5253951.8   61936.4
526547.2    5253951.8   61974
526551.3    5253951.8   62023.6
526555.4    5253951.8   62068.7
526559.6    5253951.8   62096.1
526563.7    5253951.8   62113.4
526567.8    5253951.8   62085.1
526571.9    5253951.8   62100.7
526576  5253951.8   62180.1
526580.1    5253951.8   62231.8
526584.2    5253951.8   62142.9
526588.3    5253951.8   62137.1
526592.4    5253951.8   62135.4
526596.6    5253951.8   62118.5
526600.7    5253951.8   62104.9
526604.8    5253951.8   62126.5
526608.9    5253951.8   62129.7
526613  5253951.8   62127
526617.1    5253951.8   62122.8
526621.2    5253951.8   62091.5
526625.3    5253951.8   62143.7
526629.4    5253951.8   62144.2
526633.6    5253951.8   62148.1
526637.7    5253951.8   62145.6
526641.8    5253951.8   62247.1
526645.9    5253951.8   62267.5
526650  5253951.8   62131.8
526243  5253955.9   62073.3
526247.1    5253955.9   62018.5
526251.2    5253955.9   61948.4
526255.3    5253955.9   61965.1
526259.4    5253955.9   61980.3
526263.6    5253955.9   61982.2
526267.7    5253955.9   61985.3
526271.8    5253955.9   61979.6
526275.9    5253955.9   61999.4
526280  5253955.9   62025.7
526284.1    5253955.9   62064.8
526288.2    5253955.9   62068.6
526292.3    5253955.9   62099.2
526296.4    5253955.9   62172.6
526300.6    5253955.9   62283.8
526304.7    5253955.9   62440.8
526308.8    5253955.9   62458.1
526312.9    5253955.9   62588.3
526317  5253955.9   62521.1
526321.1    5253955.9   62390.8
526325.2    5253955.9   62310.4
526329.3    5253955.9   62271
526333.4    5253955.9   62214.3
526337.6    5253955.9   62118.8
526341.7    5253955.9   62024.5
526345.8    5253955.9   61989.4
526349.9    5253955.9   61943.5
526354  5253955.9   61835.8

526506.1    5253955.9   61915.8
526510.2    5253955.9   62043
526514.3    5253955.9   62039.2
526518.4    5253955.9   62021.1
526522.6    5253955.9   62014
526526.7    5253955.9   61930.3
526530.8    5253955.9   61880.7
526534.9    5253955.9   61758.4
526539  5253955.9   61733.5
526543.1    5253955.9   61787.5
526547.2    5253955.9   61862.6
526551.3    5253955.9   61934.6
526555.4    5253955.9   61990.5
526559.6    5253955.9   62059.5
526563.7    5253955.9   62092
526567.8    5253955.9   62104.3
526571.9    5253955.9   62146.3
526576  5253955.9   62242.9
526580.1    5253955.9   62420.5
526584.2    5253955.9   62204.1
526588.3    5253955.9   62178.4
526592.4    5253955.9   62159
526596.6    5253955.9   62147.1
526600.7    5253955.9   62159.6
526604.8    5253955.9   62144.3
526608.9    5253955.9   62131.1
526613  5253955.9   62121.7
526617.1    5253955.9   62117.9
526621.2    5253955.9   62084.7
526625.3    5253955.9   62139.2
526629.4    5253955.9   62136.5
526633.6    5253955.9   62142
526637.7    5253955.9   62144.3
526641.8    5253955.9   62250.2
526645.9    5253955.9   62274.5
526650  5253955.9   62119
526243  5253960 62104
526247.1    5253960 62041.8
526251.2    5253960 61978.7
526255.3    5253960 61993.8
526259.4    5253960 61998.6
526263.6    5253960 61981
526267.7    5253960 61982
526271.8    5253960 61995.3
526275.9    5253960 62010.1
526280  5253960 62030.7
526284.1    5253960 62061.3
526288.2    5253960 62089.9
526292.3    5253960 62115.6
526296.4    5253960 62205.4
526300.6    5253960 62319.9
526304.7    5253960 62392.1
526308.8    5253960 62434.8
526312.9    5253960 62466.7
526317  5253960 62479.9
526321.1    5253960 62358.1
526325.2    5253960 62281.7
526329.3    5253960 62214.8
526333.4    5253960 62131.9
526382.8    5253960 61613.3
526386.9    5253960 61591.6
526391  5253960 61406.2
526395.1    5253960 61179.4
526399.2    5253960 61291.8
526403.3    5253960 61307.2
526407.4    5253960 61304.3
526411.6    5253960 61320.5
526415.7    5253960 61376.8
526419.8    5253960 61160.5
526423.9    5253960 61045.8
526428  5253960 61138.2
526432.1    5253960 61113.1
526436.2    5253960 60926.6
526440.3    5253960 60793.8
526444.4    5253960 60775.6
526448.6    5253960 60776.9
526452.7    5253960 60979.6
526456.8    5253960 61309.1
526460.9    5253960 61772.9
526465  5253960 61665.1
526469.1    5253960 61554.1
526473.2    5253960 61569.5
526477.3    5253960 61725.2
526481.4    5253960 61846
526485.6    5253960 61948.4
526489.7    5253960 61944.3
526493.8    5253960 61848
526497.9    5253960 61677.3
526502  5253960 61516.1
526506.1    5253960 61634.4
526510.2    5253960 61884.9
526514.3    5253960 61975.8
526518.4    5253960 61909.8
526522.6    5253960 61905.6
526526.7    5253960 61835
526530.8    5253960 61692.3
526534.9    5253960 61408.4
526539  5253960 61533.9
526543.1    5253960 61670.4
526547.2    5253960 61785.9
526551.3    5253960 61878.6
526555.4    5253960 61963.3
526559.6    5253960 62048.6
526563.7    5253960 62070.7
526567.8    5253960 62099.5
526571.9    5253960 62140.9
526576  5253960 62242.6
526580.1    5253960 62255
526584.2    5253960 62171.5
526588.3    5253960 62180.7
526592.4    5253960 62164.1
526596.6    5253960 62158.9
526600.7    5253960 62147.7
526604.8    5253960 62146.6
526608.9    5253960 62129
526613  5253960 62122.5
526617.1    5253960 62114.6
526621.2    5253960 62080.8
526625.3    5253960 62140.4
526629.4    5253960 62142.5
526633.6    5253960 62149.3
526637.7    5253960 62152
526641.8    5253960 62263.4
526645.9    5253960 62291.9
526650  5253960 62286.3
526243  5253964.1   62092
526247.1    5253964.1   62041.8
526251.2    5253964.1   61978.3
526255.3    5253964.1   62000.1
526259.4    5253964.1   62012.2
526263.6    5253964.1   62027.1
526267.7    5253964.1   62001.6
526271.8    5253964.1   62003.2
526275.9    5253964.1   61988.3
526280  5253964.1   62028.8
526284.1    5253964.1   62056.9
526288.2    5253964.1   62075.6
526292.3    5253964.1   62149.4
526296.4    5253964.1   62248
526300.6    5253964.1   62365.5
526555.4    5253964.1   61980.9
526559.6    5253964.1   62035.4
526563.7    5253964.1   62055.7
526567.8    5253964.1   62100.7
526571.9    5253964.1   62146.3
526576  5253964.1   62199
526580.1    5253964.1   62195.8
526584.2    5253964.1   62152.1
526588.3    5253964.1   62147.5
526592.4    5253964.1   62192.7
526596.6    5253964.1   62123.1
526600.7    5253964.1   62114
526604.8    5253964.1   62115.9
526608.9    5253964.1   62108.7
526613  5253964.1   62106.3
526617.1    5253964.1   62101.6
526621.2    5253964.1   62065.8
526625.3    5253964.1   62131
526629.4    5253964.1   62133.5
526633.6    5253964.1   62139.8
526637.7    5253964.1   62143
526641.8    5253964.1   62245.9
526645.9    5253964.1   62265.8
526650  5253964.1   62302.6
526243  5253968.3   62086
526247.1    5253968.3   62035.9
526251.2    5253968.3   61980
526255.3    5253968.3   61995.1
526259.4    5253968.3   62021.7
526263.6    5253968.3   62012.6
526267.7    5253968.3   61992.3
526271.8    5253968.3   62024.4
526275.9    5253968.3   61968.1
526280  5253968.3   62030.8
526284.1    5253968.3   62045.5
526288.2    5253968.3   62092.9
526292.3    5253968.3   62189.2
526296.4    5253968.3   62316.8
526300.6    5253968.3   62476.9
526304.7    5253968.3   62513.2
526308.8    5253968.3   62437.8
526312.9    5253968.3   62356.8
526317  5253968.3   62305.8
526321.1    5253968.3   62248.8
526325.2    5253968.3   62187.3
526329.3    5253968.3   62115.2
526333.4    5253968.3   62031
526337.6    5253968.3   62028.7
526341.7    5253968.3   61980.8
526345.8    5253968.3   61979.9
526349.9    5253968.3   61825.2
526354  5253968.3   61721.9
526358.1    5253968.3   61733.8
526362.2    5253968.3   61654.4
526366.3    5253968.3   61493.2
526370.4    5253968.3   61363.9
526374.6    5253968.3   61270.6
526378.7    5253968.3   61302.3
526382.8    5253968.3   61352.9
526386.9    5253968.3   61309
526391  5253968.3   61151.5
526395.1    5253968.3   60971.2
526399.2    5253968.3   60867.7
526403.3    5253968.3   60888.3
526407.4    5253968.3   60935
526411.6    5253968.3   60938.5
526415.7    5253968.3   61003.7
526419.8    5253968.3   61103.4
526423.9    5253968.3   60876.9
526428  5253968.3   60551.8
526432.1    5253968.3   60572.6
526436.2    5253968.3   60717
526440.3    5253968.3   60755.9
526444.4    5253968.3   60572.4
526448.6    5253968.3   60121.9
526563.7    5253968.3   62039.3
526567.8    5253968.3   62088.7
526571.9    5253968.3   62134.1
526576  5253968.3   62154.3
526580.1    5253968.3   62181.4
526584.2    5253968.3   62209.6
526588.3    5253968.3   62200.7
526592.4    5253968.3   62210.8
526596.6    5253968.3   62184.9
526600.7    5253968.3   62175.3
526604.8    5253968.3   62120.9
526608.9    5253968.3   62105.4
526613  5253968.3   62100.4
526617.1    5253968.3   62089.4
526621.2    5253968.3   62048.4
526625.3    5253968.3   62109.9
526629.4    5253968.3   62118.6
526633.6    5253968.3   62114.2
526637.7    5253968.3   62122.6
526641.8    5253968.3   62244.9
526645.9    5253968.3   62267.5
526650  5253968.3   62310.7
526243  5253972.4   62069.2
526247.1    5253972.4   62038.8
526251.2    5253972.4   62000.6
526255.3    5253972.4   62021.2
526259.4    5253972.4   62007
526263.6    5253972.4   62003.1
526267.7    5253972.4   62021.6
526271.8    5253972.4   62052.7
526275.9    5253972.4   62073.4
526280  5253972.4   62056.2
526284.1    5253972.4   62089.7
526288.2    5253972.4   62148.2
526292.3    5253972.4   62244.1
526296.4    5253972.4   62372
526300.6    5253972.4   62451.7
526304.7    5253972.4   62476
526308.8    5253972.4   62392.1
526312.9    5253972.4   62354.4
526317  5253972.4   62276.2
526321.1    5253972.4   62209.1
526325.2    5253972.4   62164.2
526329.3    5253972.4   62089.1
526333.4    5253972.4   62038.1
526337.6    5253972.4   61983.1
526341.7    5253972.4   61910.2
526345.8    5253972.4   61794.9
526349.9    5253972.4   61654
526354  5253972.4   61547
526358.1    5253972.4   61532.1
526362.2    5253972.4   61464.3
526366.3    5253972.4   61343.5
526370.4    5253972.4   61173
526374.6    5253972.4   61061.3
526378.7    5253972.4   61041.7
526382.8    5253972.4   61234.2
526386.9    5253972.4   61196.5
526391  5253972.4   61047.1
526395.1    5253972.4   60856.4
526399.2    5253972.4   60764.9
526403.3    5253972.4   60778.6
526407.4    5253972.4   60836.6
526411.6    5253972.4   60887.4
526415.7    5253972.4   61012
526419.8    5253972.4   61134.9
526423.9    5253972.4   60972.7
526428  5253972.4   60599.3
526432.1    5253972.4   60154.9
526436.2    5253972.4   60802.8
526440.3    5253972.4   60958.2
526444.4    5253972.4   60530.1
526448.6    5253972.4   60229.9
526452.7    5253972.4   60197.6
526456.8    5253972.4   60425.8
526460.9    5253972.4   60450.8
526465  5253972.4   59787.6
526469.1    5253972.4   59404.4
526473.2    5253972.4   60447.7
526477.3    5253972.4   61011.9
526481.4    5253972.4   61304
526485.6    5253972.4   61404
526489.7    5253972.4   61431.8
526493.8    5253972.4   61455.5
526497.9    5253972.4   61489.8
526502  5253972.4   61445.9
526506.1    5253972.4   61581.3
526510.2    5253972.4   61723.1
526514.3    5253972.4   61744.5
526518.4    5253972.4   61759.3
526522.6    5253972.4   61651.6
526526.7    5253972.4   61357.4
526530.8    5253972.4   61088.1
526534.9    5253972.4   61505.6
526539  5253972.4   61793.5
526543.1    5253972.4   61846.8
526547.2    5253972.4   61890.7
526551.3    5253972.4   61929
526555.4    5253972.4   61953.5
526559.6    5253972.4   62004
526563.7    5253972.4   62017.1
526567.8    5253972.4   62069.5
526571.9    5253972.4   62119.6
526576  5253972.4   62142.3
526580.1    5253972.4   62190.1
526584.2    5253972.4   62239.9
526588.3    5253972.4   62268.3
526592.4    5253972.4   62257.5
526596.6    5253972.4   62212.8
526600.7    5253972.4   62193.3
526604.8    5253972.4   62137
526608.9    5253972.4   62084.3
526613  5253972.4   62075.9
526617.1    5253972.4   62072.8
526621.2    5253972.4   62030.6
526625.3    5253972.4   62100.9
526629.4    5253972.4   62107.4
526633.6    5253972.4   62124.6
526637.7    5253972.4   62140.9
526641.8    5253972.4   62249.8
526645.9    5253972.4   62275.2
526650  5253972.4   62325
526243  5253976.5   62069.2
526247.1    5253976.5   62037.5
526251.2    5253976.5   61984.2
526255.3    5253976.5   62000.4
526259.4    5253976.5   62020.3
526263.6    5253976.5   62019.6
526267.7    5253976.5   62028.1
526271.8    5253976.5   62079.9
526275.9    5253976.5   62095.9
526280  5253976.5   62084.5
526284.1    5253976.5   62129.4
526288.2    5253976.5   62203.6
526292.3    5253976.5   62304.3
526296.4    5253976.5   62380.6
526300.6    5253976.5   62398
526304.7    5253976.5   62358.6
526308.8    5253976.5   62323.8
526312.9    5253976.5   62283
526317  5253976.5   62240.6
526321.1    5253976.5   62175.5
526325.2    5253976.5   62113.9
526329.3    5253976.5   62021.2
526333.4    5253976.5   61958.1
526337.6    5253976.5   61902.3
526341.7    5253976.5   61846.7
526345.8    5253976.5   61647.2
526349.9    5253976.5   61442.7
526354  5253976.5   61346.2
526358.1    5253976.5   61387.1
526362.2    5253976.5   61324.2
526366.3    5253976.5   61168.7
526370.4    5253976.5   61043.5
526374.6    5253976.5   60854.9
526378.7    5253976.5   60797.1
526382.8    5253976.5   60889.2
526386.9    5253976.5   60915.6
526391  5253976.5   60822.2
526395.1    5253976.5   60760.4
526399.2    5253976.5   60700.1
526403.3    5253976.5   60540.3
526407.4    5253976.5   60525.5
526411.6    5253976.5   60693.8
526415.7    5253976.5   60905.6
526419.8    5253976.5   61065.2
526423.9    5253976.5   60992.9
526428  5253976.5   60873.2
526432.1    5253976.5   60135.2
526436.2    5253976.5   60421.8
526440.3    5253976.5   60699.9
526444.4    5253976.5   60422.8
526448.6    5253976.5   60075.5
526452.7    5253976.5   59948.4
526456.8    5253976.5   60170.3
526460.9    5253976.5   60534
526465  5253976.5   59849.7
526469.1    5253976.5   59221.9
526473.2    5253976.5   59961.2
526477.3    5253976.5   60589
526481.4    5253976.5   60958.8
526485.6    5253976.5   61166
526489.7    5253976.5   61296.1
526493.8    5253976.5   61335.3
526497.9    5253976.5   61448
526502  5253976.5   61423.1
526506.1    5253976.5   61574.7
526510.2    5253976.5   61769.1
526514.3    5253976.5   61774.9
526518.4    5253976.5   61847.8
526522.6    5253976.5   61888.6
526526.7    5253976.5   61915.7
526530.8    5253976.5   61965.2
526534.9    5253976.5   61939
526539  5253976.5   61954.5
526543.1    5253976.5   61935.2
526547.2    5253976.5   61942.9
526551.3    5253976.5   61951.1
526555.4    5253976.5   61998.7
526559.6    5253976.5   61981.4
526563.7    5253976.5   61991.2
526567.8    5253976.5   62052.1
526571.9    5253976.5   62141.2
526576  5253976.5   62167.5
526580.1    5253976.5   62175.5
526584.2    5253976.5   62277.2
526588.3    5253976.5   62363.1
526592.4    5253976.5   62262.3
526596.6    5253976.5   62178.3
526600.7    5253976.5   62151.2
526604.8    5253976.5   62143.3
526608.9    5253976.5   62092.3
526613  5253976.5   62073.4
526617.1    5253976.5   62072.3
526621.2    5253976.5   62030.2
526625.3    5253976.5   62096.5
526629.4    5253976.5   62110.7
526633.6    5253976.5   62115.6
526637.7    5253976.5   62139
526641.8    5253976.5   62251.8
526645.9    5253976.5   62277.1
526650  5253976.5   62337.3
526243  5253980.6   62066.3
526247.1    5253980.6   62048
526251.2    5253980.6   62002.1
526255.3    5253980.6   62005.9
526259.4    5253980.6   62016.9
526263.6    5253980.6   62024
526267.7    5253980.6   62054.9
526271.8    5253980.6   62109.2
526275.9    5253980.6   62090.7
526280  5253980.6   62121.7
526284.1    5253980.6   62169.8
526288.2    5253980.6   62245.1
526292.3    5253980.6   62311.2
526296.4    5253980.6   62336.4
526300.6    5253980.6   62305.7
526304.7    5253980.6   62294.3
526308.8    5253980.6   62252.1
526312.9    5253980.6   62203
526317  5253980.6   62172.3
526321.1    5253980.6   62097.8
526325.2    5253980.6   62031.2
526329.3    5253980.6   61944.4
526333.4    5253980.6   61889.2
526337.6    5253980.6   61820.7
526341.7    5253980.6   61742.6
526345.8    5253980.6   61514
526349.9    5253980.6   61344.2
526354  5253980.6   61245.2
526358.1    5253980.6   61238.2
526362.2    5253980.6   61181.5
526366.3    5253980.6   61034
526370.4    5253980.6   60946.3
526374.6    5253980.6   60761.3
526378.7    5253980.6   60579.3
526382.8    5253980.6   60575.5
526386.9    5253980.6   60797.7
526391  5253980.6   60773.6
526395.1    5253980.6   60771.5
526399.2    5253980.6   60727.6
526403.3    5253980.6   60545.5
526407.4    5253980.6   60405.8
526411.6    5253980.6   60482.8
526415.7    5253980.6   60903.6
526419.8    5253980.6   61087.6
526423.9    5253980.6   61206.6
526428  5253980.6   61175.3
526432.1    5253980.6   60749.5
526436.2    5253980.6   60558.7
526440.3    5253980.6   60418
526444.4    5253980.6   60293.5
526448.6    5253980.6   60012
526452.7    5253980.6   59445.5
526456.8    5253980.6   59617.3
526460.9    5253980.6   60258.1
526465  5253980.6   60222.1
526469.1    5253980.6   59939.5
526473.2    5253980.6   60081.4
526477.3    5253980.6   60348.9
526481.4    5253980.6   60695.2
526485.6    5253980.6   60930.1
526489.7    5253980.6   61133.6
526493.8    5253980.6   61264.2
526497.9    5253980.6   61349.5
526502  5253980.6   61355.8
526506.1    5253980.6   61398.3
526510.2    5253980.6   61698.9
526514.3    5253980.6   61786.7
526518.4    5253980.6   61866.2
526522.6    5253980.6   62075.3
526526.7    5253980.6   62405.3
526530.8    5253980.6   62759.8
526534.9    5253980.6   62307.7
526539  5253980.6   62091.4
526543.1    5253980.6   61996.8
526547.2    5253980.6   61953.2
526551.3    5253980.6   61935.6
526555.4    5253980.6   61932.6
526559.6    5253980.6   61922.5
526563.7    5253980.6   61940.6
526567.8    5253980.6   61991.2
526571.9    5253980.6   62040.7
526576  5253980.6   62075.9
526580.1    5253980.6   62104.3
526584.2    5253980.6   62151.5
526588.3    5253980.6   62193.7
526592.4    5253980.6   62166.6
526596.6    5253980.6   62121.4
526600.7    5253980.6   62098.5
526604.8    5253980.6   62100
526608.9    5253980.6   62070.9
526613  5253980.6   62061.9
526617.1    5253980.6   62064.2
526621.2    5253980.6   62018.3
526625.3    5253980.6   62088.8
526629.4    5253980.6   62102.2
526633.6    5253980.6   62107.7
526637.7    5253980.6   62133.7
526641.8    5253980.6   62251.3
526645.9    5253980.6   62280.6
526650  5253980.6   62348
526243  5253984.7   62070.5
526247.1    5253984.7   62032.9
526251.2    5253984.7   61995.8
526255.3    5253984.7   62013.9
526259.4    5253984.7   62021.1
526263.6    5253984.7   62031.5
526267.7    5253984.7   62062.8
526271.8    5253984.7   62111.6
526275.9    5253984.7   62114.9
526280  5253984.7   62139
526284.1    5253984.7   62200.9
526288.2    5253984.7   62248.8
526292.3    5253984.7   62278.6
526296.4    5253984.7   62268.5
526300.6    5253984.7   62259.9
526304.7    5253984.7   62234.8
526308.8    5253984.7   62189.8
526312.9    5253984.7   62159.2
526317  5253984.7   62085
526321.1    5253984.7   62005
526325.2    5253984.7   61934.3
526329.3    5253984.7   61855.4
526333.4    5253984.7   61811.4
526337.6    5253984.7   61785.8
526341.7    5253984.7   61567.1
526345.8    5253984.7   61412.7
526349.9    5253984.7   61300.2
526354  5253984.7   61168
526358.1    5253984.7   61129.6
526362.2    5253984.7   61029.5
526366.3    5253984.7   60792.3
526370.4    5253984.7   60739
526374.6    5253984.7   60601.2
526378.7    5253984.7   60352.3
526382.8    5253984.7   60250.4
526386.9    5253984.7   60371.7
526391  5253984.7   60576.7
526395.1    5253984.7   60709.4
526399.2    5253984.7   60647.8
526403.3    5253984.7   60407.7
526407.4    5253984.7   60270.3
526411.6    5253984.7   60235.8
526415.7    5253984.7   60576.9
526419.8    5253984.7   60782.5
526423.9    5253984.7   61177.2
526428  5253984.7   61308.1
526432.1    5253984.7   61268.4
526436.2    5253984.7   60831.1
526440.3    5253984.7   60244.9
526444.4    5253984.7   60060.9
526448.6    5253984.7   60139.4
526452.7    5253984.7   59810.3
526456.8    5253984.7   59954
526460.9    5253984.7   60277.9
526465  5253984.7   60327.2
526469.1    5253984.7   60454.4
526473.2    5253984.7   60387.6
526477.3    5253984.7   60202.1
526481.4    5253984.7   60292.2
526485.6    5253984.7   60657.1
526489.7    5253984.7   60909
526493.8    5253984.7   61070.8
526497.9    5253984.7   61128.9
526502  5253984.7   61233.6
526506.1    5253984.7   61286.2
526510.2    5253984.7   61543.5
526514.3    5253984.7   61691.4
526518.4    5253984.7   61822.6
526522.6    5253984.7   62016.1
526526.7    5253984.7   62274.3
526530.8    5253984.7   62299.4
526534.9    5253984.7   62263.7
526539  5253984.7   62161.4
526543.1    5253984.7   62070.3
526547.2    5253984.7   61992.3
526551.3    5253984.7   61919.4
526555.4    5253984.7   61842.4
526559.6    5253984.7   61810.8
526563.7    5253984.7   61862.3
526567.8    5253984.7   61926.4
526571.9    5253984.7   61919
526576  5253984.7   61948.4
526580.1    5253984.7   61989.3
526584.2    5253984.7   62017
526588.3    5253984.7   62065.8
526592.4    5253984.7   62058.4
526596.6    5253984.7   62053.2
526600.7    5253984.7   62041.8
526604.8    5253984.7   62066.9
526608.9    5253984.7   62072.8
526613  5253984.7   62072.4
526617.1    5253984.7   62055.3

抱歉由于从MS Excel复制导致的不对齐条目问题...

数据被排列成一系列线,当组合在一起时,构成了一个由最上方和最下方点的“x”和“y”值所限定的区域网格坐标列表。

导致我的脚本停顿的问题是,我试图将子采样数据集进行网格化,以便将其轮廓图像与主数据集进行比较,但子采样数据集的线起点和终点错位。这对所有使用奇数子间隔创建的子采样数据集都是如此。

我通过在子采样数据集上使用'for'循环中的附加检查来解决了这个问题。

以下是修复后的“子采样”代码。

 - Note: The plotting code works seamlessly.

    def sub_sample():
        print ""
        print " - This program will sub-sample a dataset for every <n> datapoint."
        print " - <n> should realistically should be between 1 and 10."
        print " - If <n> > 10, interpretation confidence is reduced significantly."
        print ""
        n = raw_input(" - What value should <n> take?: ")

        if int(n) > 0 and int(n) < 2001:
            print ""
            print " - You have chosen to subsample the data every "+str(n)+" datapoints."

            perc = (float(1)/float(n)*int(100))
            print " - This corresponds to "+str(perc)+" percent of the data."

            indataarray = numpy.loadtxt("out.csv", skiprows=1, delimiter=',')

            out_name = "every_"+str(n)+".csv"     

            t = indataarray.shape
            totalrows = t[0]
            totalcolumns = t[1]
            holding_array = numpy.zeros( [totalrows, totalcolumns] )

            for i in range(totalrows):

                if ((i % 100) % int(n) == 0):
                    for j in range(totalcolumns):
                        holding_array[i,j] = indataarray[i,j] 

            no_zeros = (holding_array == 0).sum(1)
            new_holding = holding_array[no_zeros == 0, :]
            numpy.savetxt(out_name, new_holding, delimiter=',', fmt='%f')

            hdr_c1 = 'Easting,'
            hdr_c2 = 'Northing,'
            hdr_c3 = 'TMI_nT'

            f = open(out_name)
            text = f.read()
            f.close()

            f = open(out_name, 'w')
            f.write(hdr_c1+hdr_c2+hdr_c3+'\n')
            f.write(text)
            f.close
            print " - The file "+out_name+" has been created."

        else:
            print ""
            print " - You have entered an unrealistic value for <n>."
            print " - Please try again."
            sub_sample()

我可以使用脚本绘制 every_3.csv 的缩减版本... 我遇到了错误: 致命 Python 错误:PyEval_RestoreThread:NULL tstate该应用程序已请求运行时以不寻常的方式终止。 请联系应用程序的支持团队以获取更多信息。 - enargee
顺便提一下,没有必要手动编辑csv文件以保留每4行...您只需执行every_4 = longarray[::4]即可。 - Joe Kington
我已经合并了您的两个未注册账户,现在您可以编辑您的问题并留下评论。请注意,为了使您的总帖子数量不超过大小限制,我不得不从您的第二个样本数据集中删除最后8行。请不要将更多信息发布为答案,答案仅用于解决您的问题。 - Tim Post
1个回答

4
它失败了,因为您试图在一个非常奇怪的区域进行插值。请查看您的输入坐标,您的数据都在一条直线上,但您正在尝试进行二维插值。您的yi坐标都是相同的!
如果您想要1D插值,那么只需使用众多的1D插值例程之一...(如果您只需要线性插值,则使用numpy.interp;如果您需要某些类型的样条曲线,则使用scipy.interp1d。还有其他几个选项...)。
完整数据集是什么样子?
griddata默认使用delauney三角剖分。每当您在输入点之间形成非常薄的、接近零面积的三角形时,此算法将会出现问题。
如果您真的想要在面积为零的2D区域内进行插值(请注意这里的问题!!),请尝试另一种(最好是1D)插值算法。如果您需要帮助,请让我知道。
如果您真的想要“伪2D”插值,则可以使用scipy.interpolate.Rbf并使用线性距离函数。只需注意,(2D)结果可能不是您所期望的,因为在y方向上没有任何变化...
或者,如果您希望在y方向上保持一致,也可以在y方向上平铺1D插值结果。

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