El progtwig se cuelga cuando se usa “matplotlib.mlab.griddata”

He escrito un script (Python 2.6) para cuadrar datos en x, y, z (formato .csv) y mostrar un gráfico de contorno de los datos.

La secuencia de comandos funciona para algunos conjuntos de datos pero no para otros, incluso aunque ambos conjuntos de datos se crearon utilizando la misma secuencia de comandos.

Los conjuntos de datos que se van a trazar se crean mediante submuestreo a partir de un conjunto de datos maestro.

Este es un ejemplo de every_4.csv (conjunto de datos maestro submuestreado por cada 4 filas).

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 

Estos datos se trazan correctamente utilizando mi script.

“every_3.csv” que tiene la misma forma que every_4.csv hace que mi script se cuelgue (no aparece ningún mensaje de error) cuando intenta ejecutarse:

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

Aquí está el script que estoy usando:

 ### 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() 

No puedo entender por qué este script se bloquea para algunos archivos y no otros.

Nota: Si abro every_3.csv en Excel y borro algunas filas (por ejemplo, el 50% de las filas del archivo) puedo hacer que se ejecute el script …

Actualizar

Aquí hay un conjunto de datos más completo:

 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 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5253984.7 62072.4 526617.1 5253984.7 62055.3 

Lo siento por las entradas mal alineadas, esto viene de copiar fuera de MS Excel …

Los datos se organizan como una serie de líneas que, cuando se combinan, constituyen una lista de coordenadas de una cuadrícula sobre un área delimitada por los valores más altos e inferiores de ” x ‘e’ y ‘.

El problema que hizo que mi secuencia de comandos se colgara fue que el conjunto de datos de la sub-muestra, que estaba tratando de cuadrar para comparar una imagen de contorno con el conjunto de datos maestro, tenía puntos de inicio y final de línea mal alineados. Esto fue cierto para todos los conjuntos de datos de submuestreo que se crearon utilizando un intervalo de sub de un número impar.

Solucioné el problema utilizando una verificación adicional en un bucle ‘for’ que tomó una muestra secundaria del conjunto de datos.

Aquí está el código ‘sub-muestra’ fijo.

  - Note: The plotting code works seamlessly. def sub_sample(): print "" print " - This program will sub-sample a dataset for every  datapoint." print " -  should realistically should be between 1 and 10." print " - If  > 10, interpretation confidence is reduced significantly." print "" n = raw_input(" - What value should  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 ." print " - Please try again." sub_sample() 

Está fallando porque estás tratando de interpolar sobre una región muy extraña.

Mire sus coordenadas de entrada, sus datos están todos en una línea, pero está intentando interpolar en 2D. ¡Tus coordenadas yi son todas iguales!

introduzca la descripción de la imagen aquí

Si desea interpolación 1D, entonces use una de las muchas rutinas de interpolación 1D … ( numpy.interp si solo quiere interpolación lineal o scipy.interp1d si necesita splines de algún tipo. También hay varias otras opciones … .).

¿Cómo se ve el conjunto de datos completo?

griddata usa la triangulación delauney por defecto. Cada vez que termine haciendo triangularjs muy finos, cerca del área cero entre sus puntos de entrada, este algoritmo tendrá problemas.

Si realmente desea interpolar en 2D sobre una región con un área de cero (¡Vea los problemas aquí!) Intente con otro algoritmo de interpolación (preferiblemente 1D). Si quieres ayuda házmelo saber.

Si realmente desea una interpolación “pseudo-2D”, scipy.interpolate.Rbf utilizando una función de distancia lineal sería una opción. Solo tenga en cuenta que los resultados (2D) pueden no ser lo que espera ya que no tiene absolutamente ninguna variación en la dirección y …

Alternativamente, puede simplemente colocar los resultados de la interpolación 1D en la dirección y si desea que todo sea igual en la dirección y.