CODEWITHSUNDEEP
pythonarraysnumpyslicenetcdf
Christophe
Christophe

Reputation: 507

Type of slice impacts mutability of numpy array

I create netCDF files using python. When I try to assign values (data) to parts (or slices) of variables, depending on what is the "type" of slice, I can or I cannot assign the values.

I don't know why. Any help to understand why that is would be appreciated.

E.g.: 

import numpy as np
from netCDF4 import Dataset

nb_steps = 2
nb_lat = 3
nb_lon = 4

# open/create file
f = Dataset('/home/ccorbel/Desktop/test.nc', 'w', format='NETCDF3_CLASSIC')
f.createDimension('lat', nb_lat)
f.createDimension('lon', nb_lon)
f.createDimension('time', nb_steps)

# create/fill variables
variables = {}
variables['t'] = f.createVariable('temperature', 'float64', ('time', 'lat', 'lon'))
variables['t'][...] = np.zeros((nb_steps, nb_lat, nb_lon))

# "equivalent" to [0, :, ::-1]
slc  = [0, slice(None, None, None), slice(None, None, -1)]    

# "equivalent" to [0, :, :]
slc2 = [0, slice(None, None, None), slice(None, None, None)] 

# "equivalent" to [:, ::-1]
slc3 = [   slice(None, None, None), slice(None, None, -1)]

print type(variables['t'])
# type 'netCDF4.Variable'
print type(variables['t'][slc])
# type 'numpy.ndarray'
print type(variables['t'][slc][...])
# type 'numpy.ndarray'
print np.shape(variables['t'][slc])
# (3, 4)

# variables['t'][slc] = np.random.random((nb_lat, nb_lon))
# return IndexError: too many indices

variables['t'][slc][...] = np.random.random((nb_lat, nb_lon))
print '\n', variables['t'][...]

# [[[ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]]
# 
#  [[ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]]]

variables['t'][...] = np.zeros((nb_steps, nb_lat, nb_lon)) # reset
variables['t'][slc2] = np.random.random((nb_lat, nb_lon))[slc3]
print '\n', variables['t'][...]

# [[[ 0.17502009  0.98414122  0.89686025  0.11072791]
#   [ 0.51351626  0.09234043  0.54314083  0.937711  ]
#   [ 0.98732418  0.22714407  0.87387761  0.44653219]]

#  [[ 0.          0.          0.          0.        ]
#   [ 0.          0.          0.          0.        ]
#   [ 0.          0.          0.          0.        ]]]

variables['t'][...] = np.zeros((nb_steps, nb_lat, nb_lon)) # reset
#variables['t'][0, :, ::-1] = np.random.random((nb_lat, nb_lon)) 
# return IndexError: too many indices

variables['t'][0, :, ::-1][...] = np.random.random((nb_lat, nb_lon))
print '\n', variables['t'][...]

# [[[ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]]

#  [[ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]
#   [ 0.  0.  0.  0.]]]

variables['t'][...] = np.zeros((nb_steps, nb_lat, nb_lon)) # reset
variables['t'][0, :, :] = np.random.random((nb_lat, nb_lon))[:, ::-1]
print '\n', variables['t'][...]

# [[[ 0.61406835  0.11069783  0.28667398  0.45018246]
#   [ 0.3833354   0.98871281  0.55559104  0.60415683]
#   [ 0.75200954  0.75106639  0.11688565  0.14264615]]

#  [[ 0.          0.          0.          0.        ]
#   [ 0.          0.          0.          0.        ]
#   [ 0.          0.          0.          0.        ]]]

variables['t'][...] = np.zeros((nb_steps, nb_lat, nb_lon)) # reset
variables['t'][0, :, :] = np.random.random((nb_lat, nb_lon))[slc3]
print '\n', variables['t'][...]

# [[[ 0.09437484  0.45757906  0.81116891  0.23580254]
#   [ 0.37316425  0.06768454  0.20259876  0.42127472]
#   [ 0.78879307  0.62535419  0.08942293  0.68789143]]

#  [[ 0.          0.          0.          0.        ]
#   [ 0.          0.          0.          0.        ]
#   [ 0.          0.          0.          0.        ]]]

f.close()

Upvotes: 3

Views: 818

Answers (1)

Bi Rico
Bi Rico

Reputation: 25833

Your example code seems to work on my machine, but I think you might be having a problem because you're using multiple index on the left side of your assignment. A[0, :, ::-1][...] = something where A is an array is weird, and even though it seems to work on my machine, I would try and avoid it. If that doesn't solve your issue can you either give us a cleaner example of the problem you're seeing (hopefully with only one indexing operation on the left of the =) or explain why you want to use two indexing operations.

Upvotes: 2

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