Traditional I/O
Handling traditional way of data input and output used by
QHA and thermo.f code
- cij.io.traditional.read_elast_data(fname)
Read static elastic coefficients from data file.
- Parameters
fname (
str) – the name or path of the input file.- Return type
- cij.io.traditional.read_energy(fname)
Read \(E\), \(V\), \(\omega\) etc., from QHA data file
- Parameters
fname (
str) – The path of the input file- Return type
Traditional QHA input: qha_input
- class cij.io.traditional.qha_input.QHAInputData(nv, nq, np, nm, na, weights, volumes)
Bases:
NamedTuple-
na:
int Alias for field number 4
-
nm:
int Alias for field number 3
-
np:
int Alias for field number 2
-
nq:
int Alias for field number 1
-
nv:
int Alias for field number 0
-
volumes:
List[VolumeData] Alias for field number 6
-
weights:
List[Tuple[Tuple[float,float,float],float]] Alias for field number 5
-
na:
- class cij.io.traditional.qha_input.QPointData(coord, modes)
Bases:
NamedTuple-
coord:
Tuple[float,float,float] Alias for field number 0
-
modes:
List[float] Alias for field number 1
-
coord:
- class cij.io.traditional.qha_input.QPointWeight(coord, weight)
Bases:
NamedTuple-
coord:
Tuple[float,float,float] Alias for field number 0
-
weight:
float Alias for field number 1
-
coord:
- class cij.io.traditional.qha_input.VolumeData(pressure, volume, energy, q_points)
Bases:
NamedTuple-
energy:
float Alias for field number 2
-
pressure:
float Alias for field number 0
-
q_points:
List[QPointData] Alias for field number 3
-
volume:
float Alias for field number 1
-
energy:
- cij.io.traditional.qha_input.read_energy(fname)
Read \(E\), \(V\), \(\omega\) etc., from QHA data file
- Parameters
fname (
str) – The path of the input file- Return type
- cij.io.traditional.qha_input.write_energy(fname, input_data, comment='QHA Input data')
Write QHA input data to file
- Parameters
fname (
str) –input_data (
QHAInputData) –comment (
str) – The comment line
Traditional QHA tabular output: qha_output
These methods are imported and is therfore identical to what is provided in the QHA distribution.
- cij.io.traditional.qha_output.save_x_pt(df, t, desired_pressures_gpa, t_sample, outfile_name)
- cij.io.traditional.qha_output.save_x_tp(df, t, desired_pressures_gpa, p_sample_gpa, outfile_name)
- cij.io.traditional.qha_output.save_x_tv(x, t, volume_grid, t_sample, outfile_name)
- cij.io.traditional.qha_output.save_x_vt(x, t, volume_grid, t_sample, outfile_name)
Traditional elast tabular output: elast_dat
- class cij.io.traditional.elast_dat.ElastData(vref, nv, cellmass, volumes, lattice_parmeters)
Bases:
NamedTuple-
cellmass:
float Alias for field number 2
-
lattice_parmeters:
List[Tuple[float,float,float]] Alias for field number 4
-
nv:
int Alias for field number 1
-
volumes:
List[ElastVolumeData] Alias for field number 3
-
vref:
float Alias for field number 0
-
cellmass:
- class cij.io.traditional.elast_dat.ElastVolumeData(volume, static_elastic_modulus)
Bases:
NamedTuple-
static_elastic_modulus:
OrderedDict Alias for field number 1
-
volume:
float Alias for field number 0
-
static_elastic_modulus:
- cij.io.traditional.elast_dat.apply_symetry_on_elast_data(input, symmetry)
- Return type
None