Changeset 26539 for issm/trunk-jpl/src/m/classes/stochasticforcing.py
- Timestamp:
- 11/04/21 12:47:30 (3 years ago)
- File:
-
- 1 edited
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issm/trunk-jpl/src/m/classes/stochasticforcing.py
r26538 r26539 76 76 def marshall(self, prefix, md, fid): # {{{ 77 77 yts = md.constants.yts 78 num_fields = range(self.fields) 79 # Scaling covariance matrix (scale column-by-column and row-by-row) 80 scaledfields = ['SMBautoregression'] # list of fields that need scaling * 1/yts 81 for i in range(num_fields): 82 print(i) 83 if self.fields[i] in scaledfields: 84 print(self.fields[i]) 85 inds = range(1 + np.sum(self.dimensions[0:i]), np.sum(self.dimensions[0:i])) 86 for row in inds: # scale rows corresponding to scaled field 87 self.covariance[row, :] = 1 / yts * self.covariance[row, :] 88 for col in inds: # scale columns corresponding to scaled field 89 self.covariance[:, col] = 1 / yts * self.covariance[:, col] 78 if (type(self.fields) is list): 79 num_fields = len(self.fields) 80 # Scaling covariance matrix (scale column-by-column and row-by-row) 81 scaledfields = ['SMBautoregression'] # list of fields that need scaling * 1/yts 82 for i in range(num_fields): 83 if self.fields[i] in scaledfields: 84 inds = range(1 + np.sum(self.dimensions[0:i]), np.sum(self.dimensions[0:i])) 85 for row in inds: # scale rows corresponding to scaled field 86 self.covariance[row, :] = 1 / yts * self.covariance[row, :] 87 for col in inds: # scale columns corresponding to scaled field 88 self.covariance[:, col] = 1 / yts * self.covariance[:, col] 90 89 91 90 WriteData(fid, prefix, 'object', self, 'fieldname', 'isstochasticforcing', 'format', 'Boolean')
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