Tensor in CSV format (`chemistry_files.csv_tensor`)

Internal (lossy) textual format for the storage of data.

class qcip_tools.chemistry_files.csv_tensor.CSVTensor

Special CSV input. Assume that the first cell contains CSV_TENSOR_IN, and that the first row contains different information:

In second column, the derivative type (i.e. FFF, GG, …) ;
In third column: spacial DOF, if needed ;
In fourth column: frequency, if needed ;
In fifth column: number of (excited) states, if needed.
For the latter rows, values of the first column does not matter.

Then, the rest correspond to the values of the last dimension of the tensor (F/D/X = 3, G = spacial DOF). The number of row is equal to the product of the dimensions of the tensor (except the last one).

New tensor starts with CSV_TENSOR_IN.

For example,

CSV_TENSOR_IN,G,6,,,
1,1,1,1,1,1
CSV_TENSOR_IN,GG,6
1,0,0,0,0,0
0,2,0,0,0,0
0,0,3,0,0,0
0,0,0,4,0,0
0,0,0,0,5,0
0,0,0,0,0,6

classmethod attempt_identification(f)

Check for “CSV_TENSOR_IN”

Return type:: bool

classmethod possible_file_extensions()

Return the common extention of this kind of files

Return type:: list

qcip_tools.chemistry_files.csv_tensor.csvtensor__property__electrical_derivatives(obj, *args, **kwargs)

Get the geometrical derivatives, if available

Parameters:: obj (CSVTensor) – object
Return type:: dict

qcip_tools.chemistry_files.csv_tensor.csvtensor__property__excitations(obj, *args, **kwargs)

Parameters:: obj (CSVTensor) – object
Return type:: dict

qcip_tools.chemistry_files.csv_tensor.csvtensor__property__geometrical_derivatives(obj, *args, **kwargs)

Get the geometrical derivatives, if available

Parameters:: obj (CSVTensor) – object
Return type:: dict

Tensor in CSV format (chemistry_files.csv_tensor)

Tensor in CSV format (`chemistry_files.csv_tensor`)