约束不匹配错误
Constraint Mismatch Error
我正在运行使用以下代码来创建一个简单的折线图:
import matplotlib.pyplot as plt
import iris
import iris.coord_categorisation as iriscc
import iris.plot as iplt
import iris.quickplot as qplt
import iris.analysis.cartography
import matplotlib.dates as mdates
def main():
#bring in all the files we need and give them a name
TestFile= '/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/AFR_44_tas/Historical/1950-2005/tas_AFR-44_MOHC-HadGEM2-ES_historical_r1i1p1_CLMcom-CCLM4-8-17_v1_mon_194912-200512.nc'
#Load exactly one cube from given file
TestFile = iris.load_cube(TestFile)
print TestFile
#adjust longitude as data is out by 180degrees
#remove flat latitude and longitude and only use grid latitude and grid longitude which are in the 3rd and 4th column of the file
lats = iris.coords.DimCoord(TestFile.coords()[3].points[:,0], \
standard_name='latitude', units='degrees')
lons = TestFile.coords()[4].points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, \
standard_name='longitude', units='degrees')
TestFile.remove_coord('latitude')
TestFile.remove_coord('longitude')
TestFile.remove_coord('grid_latitude')
TestFile.remove_coord('grid_longitude')
TestFile.add_dim_coord(lats, 1)
TestFile.add_dim_coord(lons, 2)
#we are only interested in the latitude and longitude relevant to Malawi
Malawi = iris.Constraint(longitude=lambda v: 32.5 <= v <= 36., \
latitude=lambda v: -17. <= v <= -9.)
TestFile = TestFile.extract(Malawi)
#data is in Kelvin, but we would like to show it in Celcius
TestFile.convert_units('Celsius')
#We are interested in plotting the graph with time along the x ais, so we need a mean of all the coordinates, i.e. mean temperature across whole country
iriscc.add_year(TestFile, 'time')
TestFile = TestFile.aggregated_by('year', iris.analysis.MEAN)
TestFile.coord('latitude').guess_bounds()
TestFile.coord('longitude').guess_bounds()
TestFile_grid_areas = iris.analysis.cartography.area_weights(TestFile)
TestFile_mean = TestFile.collapsed(['latitude', 'longitude'],
iris.analysis.MEAN,
weights=TestFile_grid_areas)
#set major plot indicators for x-axis
plt.gca().xaxis.set_major_locator(mdates.YearLocator(5))
#assign the line colours
qplt.plot(TestFile_mean, label='TestFile', lw=1.5, color='blue')
#create a legend and set its location to under the graph
plt.legend(loc="upper center", bbox_to_anchor=(0.5,-0.05), fancybox=True, shadow=True, ncol=5)
#create a title
plt.title('Mean Near Surface Temperature for Malawi', fontsize=11)
#create the graph
plt.grid()
iplt.show()
if __name__ == '__main__':
main()
这适用于大多数文件,但两个气候模型出现约束不匹配错误:
runfile('/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py', wdir='/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images')
Traceback (most recent call last):
File "<ipython-input-83-4f4457568a8f>", line 1, in <module> runfile('/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py', wdir='/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images')
File "/usr/lib/python2.7/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 685, in runfile
execfile(filename, namespace)
File "/usr/lib/python2.7/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 78, in execfile
builtins.execfile(filename, *where)
File "/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py", line 84, in <module>
main()
File "/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py", line 21, in main
TestFile = iris.load_cube(TestFile)
File "/usr/lib64/python2.7/site-packages/iris/__init__.py", line 338, in load_cube
raise iris.exceptions.ConstraintMismatchError(str(e))
ConstraintMismatchError: failed to merge into a single cube.
cube.standard_name differs: None != u'air_temperature'
cube.long_name differs: None != u'Near-Surface Air Temperature'
cube.var_name differs: u'rotated_pole' != u'tas'
cube.units differs: Unit('no_unit') != Unit('K')
cube.attributes keys differ: 'grid_north_pole_latitude', 'grid_north_pole_longitude', 'grid_mapping_name'
cube.cell_methods differ
cube.shape differs: () != (660, 201, 194)
cube data dtype differs: |S1 != float32
cube data fill_value differs: '\x00' != 1e+20
同样,我在尝试 运行 观察到的数据 (cru_ts4.00.1901.2015.tmp.dat.nc)
时遇到此错误
ConstraintMismatchError: failed to merge into a single cube.
cube.long_name differs: u'near-surface temperature' != None
cube.var_name differs: u'tmp' != u'stn'
cube.units differs: Unit('degrees Celsius') != Unit('1')
cube.attributes keys differ: 'correlation_decay_distance', 'description'
cube data dtype differs: float32 != int32
cube data fill_value differs: 9.96921e+36 != -2147483647
关于如何解决这个问题的任何想法?
我收到了来自 Iris 用户 Google 组的 Andrew Dawson 的回复。在这里张贴以防对其他人有任何帮助。这对我有帮助!
函数iris.load_cube 用于从给定文件中匹配给定约束恰好加载 1 个且仅加载 1 个立方体。您没有提供约束,这意味着您希望加载的文件减少到恰好 1 个立方体。来自 iris.load_cube 的 ConstraintMismatchError 告诉您由于某些不匹配的数据这是不可能的。从错误来看,这些模型的输入文件中似乎有 1 个以上的变量。您应该考虑在加载时添加显式约束,例如:
iris.load_cube(filename, 'name_of_variable_here')
其中 name_of_variable 应该是多维数据集加载的名称,即 cube.name() 的结果。这与 netcdf 变量名不同。为了弄清楚您需要如何执行此操作,我建议使用
从一个有问题的数据集中加载所有多维数据集
cubes = iris.load(the_filename) # load all the cubes in the input file
然后打印立方体的名称
对于立方体中的立方体:
print(cube.name())
我正在运行使用以下代码来创建一个简单的折线图:
import matplotlib.pyplot as plt
import iris
import iris.coord_categorisation as iriscc
import iris.plot as iplt
import iris.quickplot as qplt
import iris.analysis.cartography
import matplotlib.dates as mdates
def main():
#bring in all the files we need and give them a name
TestFile= '/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/AFR_44_tas/Historical/1950-2005/tas_AFR-44_MOHC-HadGEM2-ES_historical_r1i1p1_CLMcom-CCLM4-8-17_v1_mon_194912-200512.nc'
#Load exactly one cube from given file
TestFile = iris.load_cube(TestFile)
print TestFile
#adjust longitude as data is out by 180degrees
#remove flat latitude and longitude and only use grid latitude and grid longitude which are in the 3rd and 4th column of the file
lats = iris.coords.DimCoord(TestFile.coords()[3].points[:,0], \
standard_name='latitude', units='degrees')
lons = TestFile.coords()[4].points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, \
standard_name='longitude', units='degrees')
TestFile.remove_coord('latitude')
TestFile.remove_coord('longitude')
TestFile.remove_coord('grid_latitude')
TestFile.remove_coord('grid_longitude')
TestFile.add_dim_coord(lats, 1)
TestFile.add_dim_coord(lons, 2)
#we are only interested in the latitude and longitude relevant to Malawi
Malawi = iris.Constraint(longitude=lambda v: 32.5 <= v <= 36., \
latitude=lambda v: -17. <= v <= -9.)
TestFile = TestFile.extract(Malawi)
#data is in Kelvin, but we would like to show it in Celcius
TestFile.convert_units('Celsius')
#We are interested in plotting the graph with time along the x ais, so we need a mean of all the coordinates, i.e. mean temperature across whole country
iriscc.add_year(TestFile, 'time')
TestFile = TestFile.aggregated_by('year', iris.analysis.MEAN)
TestFile.coord('latitude').guess_bounds()
TestFile.coord('longitude').guess_bounds()
TestFile_grid_areas = iris.analysis.cartography.area_weights(TestFile)
TestFile_mean = TestFile.collapsed(['latitude', 'longitude'],
iris.analysis.MEAN,
weights=TestFile_grid_areas)
#set major plot indicators for x-axis
plt.gca().xaxis.set_major_locator(mdates.YearLocator(5))
#assign the line colours
qplt.plot(TestFile_mean, label='TestFile', lw=1.5, color='blue')
#create a legend and set its location to under the graph
plt.legend(loc="upper center", bbox_to_anchor=(0.5,-0.05), fancybox=True, shadow=True, ncol=5)
#create a title
plt.title('Mean Near Surface Temperature for Malawi', fontsize=11)
#create the graph
plt.grid()
iplt.show()
if __name__ == '__main__':
main()
这适用于大多数文件,但两个气候模型出现约束不匹配错误:
runfile('/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py', wdir='/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images')
Traceback (most recent call last):
File "<ipython-input-83-4f4457568a8f>", line 1, in <module> runfile('/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py', wdir='/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images')
File "/usr/lib/python2.7/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 685, in runfile
execfile(filename, namespace)
File "/usr/lib/python2.7/site-packages/spyderlib/widgets/externalshell/sitecustomize.py", line 78, in execfile
builtins.execfile(filename, *where)
File "/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py", line 84, in <module>
main()
File "/exports/csce/datastore/geos/users/s0XXXX/Climate_Modelling/Python Code and Output Images/Line_Graph_Temp_Test.py", line 21, in main
TestFile = iris.load_cube(TestFile)
File "/usr/lib64/python2.7/site-packages/iris/__init__.py", line 338, in load_cube
raise iris.exceptions.ConstraintMismatchError(str(e))
ConstraintMismatchError: failed to merge into a single cube.
cube.standard_name differs: None != u'air_temperature'
cube.long_name differs: None != u'Near-Surface Air Temperature'
cube.var_name differs: u'rotated_pole' != u'tas'
cube.units differs: Unit('no_unit') != Unit('K')
cube.attributes keys differ: 'grid_north_pole_latitude', 'grid_north_pole_longitude', 'grid_mapping_name'
cube.cell_methods differ
cube.shape differs: () != (660, 201, 194)
cube data dtype differs: |S1 != float32
cube data fill_value differs: '\x00' != 1e+20
同样,我在尝试 运行 观察到的数据 (cru_ts4.00.1901.2015.tmp.dat.nc)
时遇到此错误ConstraintMismatchError: failed to merge into a single cube.
cube.long_name differs: u'near-surface temperature' != None
cube.var_name differs: u'tmp' != u'stn'
cube.units differs: Unit('degrees Celsius') != Unit('1')
cube.attributes keys differ: 'correlation_decay_distance', 'description'
cube data dtype differs: float32 != int32
cube data fill_value differs: 9.96921e+36 != -2147483647
关于如何解决这个问题的任何想法?
我收到了来自 Iris 用户 Google 组的 Andrew Dawson 的回复。在这里张贴以防对其他人有任何帮助。这对我有帮助!
函数iris.load_cube 用于从给定文件中匹配给定约束恰好加载 1 个且仅加载 1 个立方体。您没有提供约束,这意味着您希望加载的文件减少到恰好 1 个立方体。来自 iris.load_cube 的 ConstraintMismatchError 告诉您由于某些不匹配的数据这是不可能的。从错误来看,这些模型的输入文件中似乎有 1 个以上的变量。您应该考虑在加载时添加显式约束,例如:
iris.load_cube(filename, 'name_of_variable_here')
其中 name_of_variable 应该是多维数据集加载的名称,即 cube.name() 的结果。这与 netcdf 变量名不同。为了弄清楚您需要如何执行此操作,我建议使用
从一个有问题的数据集中加载所有多维数据集cubes = iris.load(the_filename) # load all the cubes in the input file
然后打印立方体的名称
对于立方体中的立方体:
print(cube.name())