pytomography.io.simind#

Module Contents#

Functions#

find_first_entry_containing_header(list_of_attributes, ...)

Finds the first entry in a SIMIND Interfile output corresponding to the header (header).

simind_projections_to_data(headerfile[, distance])

Obtains ObjectMeta, ImageMeta, and projections from a SIMIND header file.

simind_MEW_to_data(headerfiles[, distance])

Opens multiple projection files corresponding to the primary, lower scatter, and upper scatter windows

simind_CT_to_data(headerfile)

Opens attenuation data from SIMIND output

Attributes#

pytomography.io.simind.relation_dict#
pytomography.io.simind.find_first_entry_containing_header(list_of_attributes, header, dtype=np.float32)#

Finds the first entry in a SIMIND Interfile output corresponding to the header (header).

Parameters:
  • list_of_attributes (list[str]) – Simind data file, as a list of lines.

  • header (str) – The header looked for

  • dtype (type, optional) – The data type to be returned corresponding to the value of the header. Defaults to np.float32.

Returns:

The value corresponding to the header (header).

Return type:

float|str|int

pytomography.io.simind.simind_projections_to_data(headerfile, distance='cm')#

Obtains ObjectMeta, ImageMeta, and projections from a SIMIND header file.

Parameters:
  • headerfile (str) – Path to the header file

  • distance (str, optional) – The units of measurements in the SIMIND file (this is required as input, since SIMIND uses mm/cm but doesn’t specify). Defaults to ‘cm’.

Returns:

Required information for reconstruction in PyTomography.

Return type:

(ObjectMeta, ImageMeta, torch.Tensor[1, Ltheta, Lr, Lz])

pytomography.io.simind.simind_MEW_to_data(headerfiles, distance='cm')#

Opens multiple projection files corresponding to the primary, lower scatter, and upper scatter windows

Parameters:
  • headerfiles (list[str]) – List of file paths to required files. Must be in order of: 1. Primary, 2. Lower Scatter, 3. Upper scatter

  • distance (str, optional) – The units of measurements in the SIMIND file (this is required as input, since SIMIND uses mm/cm but doesn’t specify). Defaults to ‘cm’.

Returns:

Required information for reconstruction in PyTomography. First returned tensor contains primary data, and second returned tensor returns estimated scatter using the triple energy window method.

Return type:

(ObjectMeta, ImageMeta, torch.Tensor[1, Ltheta, Lr, Lz], torch.Tensor[1, Ltheta, Lr, Lz])

pytomography.io.simind.simind_CT_to_data(headerfile)#

Opens attenuation data from SIMIND output

Parameters:

headerfile (str) – Path to header file

Returns:

Tensor containing CT data.

Return type:

torch.tensor[Lx,Ly,Lz]