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我正在运行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，但有两个气候模型会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，尝试运行观察到的数据时出现此错误（cru_ts4.00.1901.2015.tmp.dat.nc）

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？

4

1 回答 1

1

我收到了来自 Iris User Google Group 的 Andrew Dawson 的回复。在这里发帖以防对其他人有任何帮助。这对我有帮助！

函数 iris.load_cube 用于从给定文件中准确加载 1 个且仅 1 个与给定约束匹配的立方体。您没有提供约束，这意味着您期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。从错误看来，这些模型的输入文件中有多个变量。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 应该是加载多维数据集的名称，即cube.name() 的结果。这与 netcdf 变量名称不同。要弄清楚您需要如何执行此操作，我建议从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())
于 2017-08-16T15:06:32.783 回答