Supported datasets

More info on specific datasets can be obtained here.

Prepare function showcase

Prepare functions are used for preparing the dictionaries for writing UFF files.

Parameters labeled optional designate optional fields, that are not needed when writing to a file, as they have a default value. Parameters labeled ignored designate fields that are not needed at all, as these fields are defined automatically.

Some fields are data dependent, meaning they are only used/available for some specific data-type. For example modal_damp_vis in dataset 55.

Parameter return_full_dict determines if all keys or only specified arguments are returned.

import pyuff

pyuff.prepare_151(model_name='NewModel', date_db_created='17-Jun-21', time_db_created='12:49:33', version_db1= 0, version_db2= 0, file_type= 0)

Dataset 15

pyuff.prepare_15(node_nums=None, def_cs=None, disp_cs=None, color=None, x=None, y=None, z=None, return_full_dict=False)[source]

Name: Nodes

R-Record, F-Field

Parameters:
  • node_nums – R1 F1, node label

  • def_cs – R1 F2, deformation coordinate system numbers, optional

  • disp_cs – R1 F3, displacement coordinate system numbers, optional

  • color – R1 F4, color, optional

  • x – R1 F5, Dimensional coordinate of node in the definition system

  • y – R1 F6, Dimensional coordinate of node in the definition system

  • z – R1 F7, Dimensional coordinate of node in the definition system

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_15

>>> save_to_file = 'test_pyuff'
>>> dataset = pyuff.prepare_15(
>>>     node_nums=[16, 17, 18, 19, 20],
>>>     def_cs=[11, 11, 11, 12, 12],
>>>     disp_cs=[16, 16, 17, 18, 19],
>>>     color=[1, 3, 4, 5, 6],  # I10,
>>>     x=[0.0, 1.53, 0.0, 1.53, 0.0],
>>>     y=[0.0, 0.0, 3.84, 3.84, 0.0],
>>>     z=[0.0, 0.0, 0.0, 0.0, 1.83])
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>>     uffwrite = pyuff.UFF(save_to_file)
>>>     uffwrite._write_set(dataset, 'add')
>>> dataset

Dataset 55

pyuff.prepare_55(id1=None, id2=None, id3=None, id4=None, id5=None, model_type=None, analysis_type=None, data_ch=None, spec_data_type=None, data_type=None, n_data_per_node=None, r1=None, r2=None, r3=None, r4=None, r5=None, r6=None, load_case=None, mode_n=None, freq=None, modal_m=None, modal_damp_vis=None, modal_damp_his=None, eig=None, modal_a=None, modal_b=None, freq_step_n=None, node_nums=None, return_full_dict=False)[source]

Name: Data at Nodes

R-Record, F-Field

Parameters:
  • id1 – R1 F1, ID Line 1, optional

  • id2 – R2 F1, ID Line 2, optional

  • id3 – R3 F1, ID Line 3, optional

  • id4 – R4 F1, ID Line 4, optional

  • id5 – R5 F1, ID Line 5, optional

  • model_type – R6 F1, Model type, optional

  • analysis_type – R6 F2, Analysis type; currently only only normal mode (2), complex eigenvalue first order (displacement) (3), frequency response and (5) and complex eigenvalue second order (velocity) (7) are supported

  • data_ch – R6 F3, Data characteristic number

  • spec_data_type – R6 F4, Specific data type

  • data_type – R6 F5, Data type, ignored

  • n_data_per_node – R6 F6, Number of data values per node, ignored

R7 and R8 are analysis type specific:

Parameters:
  • r1 – Response array for DOF 1,

  • r2 – Response array for DOF 2,

  • r3 – Response array for DOF 3,

  • r4 – Response array for DOF 4,

  • r5 – Response array for DOF 5,

  • r6 – Response array for DOF 6,

  • load_case – R7 F3, Load case number

  • mode_n – R7 F4, Mode number

  • freq – R8 F1, Frequency (Hertz)

  • modal_m – R8 F2, Modal mass, optional

  • modal_damp_vis – R8 F3, Modal viscous damping ratio, optional

  • modal_damp_his – R8 F4, Modal hysteric damping ratio, optional

  • eig – R8 F1: Real part Eigenvalue, R8 F2: Imaginary part Eigenvalue

  • modal_a – R8 F3: Real part of Modal A, R8 F4: Imaginary part of Modal A, optional

  • modal_b – R8 F5: Real part of Modal B, R8 F6: Imaginary part of Modal B, optional

  • freq_step_n – R7 F4, Frequency step number

  • node_nums – R9 F1 Node number

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_55

>>> save_to_file = 'test_pyuff'
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>> uff_datasets = []
>>> modes = [1, 2, 3]
>>> node_nums = [1, 2, 3, 4]
>>> freqs = [10.0, 12.0, 13.0]
>>> for i, b in enumerate(modes):
>>>     mode_shape = np.random.normal(size=len(node_nums))
>>>     name = 'TestCase'
>>>     data = pyuff.prepare_55(
>>>         model_type=1,
>>>         id1='NONE',
>>>         id2='NONE',
>>>         id3='NONE',
>>>         id4='NONE',
>>>         id5='NONE',
>>>         analysis_type=2,
>>>         data_ch=2,
>>>         spec_data_type=8,
>>>         data_type=2,
>>>         r1=mode_shape,
>>>         r2=mode_shape,
>>>         r3=mode_shape,
>>>         n_data_per_node=3,
>>>         node_nums=[1, 2, 3, 4],
>>>         load_case=1,
>>>         mode_n=i + 1,
>>>         modal_m=0,
>>>         freq=freqs[i],
>>>         modal_damp_vis=0.,
>>>         modal_damp_his=0.)
>>>     uff_datasets.append(data.copy())
>>>     if save_to_file:
>>>         uffwrite = pyuff.UFF(save_to_file)
>>>         uffwrite._write_set(data, 'add')
>>> uff_datasets

Dataset 58 and 58b

pyuff.prepare_58(binary=None, id1=None, id2=None, id3=None, id4=None, id5=None, func_type=None, ver_num=None, load_case_id=None, rsp_ent_name=None, rsp_node=None, rsp_dir=None, ref_ent_name=None, ref_node=None, ref_dir=None, ord_data_type=None, num_pts=None, abscissa_spacing=None, abscissa_min=None, abscissa_inc=None, z_axis_value=None, abscissa_spec_data_type=None, abscissa_len_unit_exp=None, abscissa_force_unit_exp=None, abscissa_temp_unit_exp=None, abscissa_axis_units_lab=None, ordinate_spec_data_type=None, ordinate_len_unit_exp=None, ordinate_force_unit_exp=None, ordinate_temp_unit_exp=None, ordinate_axis_units_lab=None, orddenom_spec_data_type=None, orddenom_len_unit_exp=None, orddenom_force_unit_exp=None, orddenom_temp_unit_exp=None, orddenom_axis_units_lab=None, z_axis_spec_data_type=None, z_axis_len_unit_exp=None, z_axis_force_unit_exp=None, z_axis_temp_unit_exp=None, z_axis_axis_units_lab=None, data=None, x=None, spec_data_type=None, byte_ordering=None, fp_format=None, n_ascii_lines=None, n_bytes=None, return_full_dict=False)[source]

Name: Function at Nodal DOF

R-Record, F-Field

Parameters:
  • binary – 1 for binary, 0 for ascii, optional

  • id1 – R1 F1, ID Line 1, optional

  • id2 – R2 F1, ID Line 2, optional

  • id3 – R3 F1, ID Line 3, optional

  • id4 – R4 F1, ID Line 4, optional

  • id5 – R5 F1, ID Line 5, optional

DOF identification

Parameters:
  • func_type – R6 F1, Function type

  • ver_num – R6 F3, Version number, optional

  • load_case_id – R6 F4, Load case identification number, optional

  • rsp_ent_name – R6 F5, Response entity name, optional

  • rsp_node – R6 F6, Response node

  • rsp_dir – R6 F7, Responde direction

  • ref_ent_name – R6 F8, Reference entity name, optional

  • ref_node – R6 F9, Reference node

  • ref_dir – R6 F10, Reference direction

Data form

Parameters:
  • ord_data_type – R7 F1, Ordinate data type, ignored

  • num_pts – R7 F2, number of data pairs for uneven abscissa or number of data values for even abscissa, ignored

  • abscissa_spacing – R7 F3, Abscissa spacing (0- uneven, 1-even), ignored

  • abscissa_min – R7 F4, Abscissa minimum (0.0 if spacing uneven), ignored

  • abscissa_inc – R7 F5, Abscissa increment (0.0 if spacing uneven), ignored

  • z_axis_value – R7 F6, Z-axis value (0.0 if unused), optional

Abscissa data characteristics

Parameters:
  • abscissa_spec_data_type – R8 F1, Abscissa specific data type, optional

  • abscissa_len_unit_exp – R8 F2, Abscissa length units exponent, optional

  • abscissa_force_unit_exp – R8 F3, Abscissa force units exponent, optional

  • abscissa_temp_unit_exp – R8 F4, Abscissa temperature units exponent, optional

  • abscissa_axis_units_lab – R8 F6, Abscissa units label, optional

Ordinate (or ordinate numerator) data characteristics

Parameters:
  • ordinate_spec_data_type – R9 F1, Ordinate specific data type, optional

  • ordinate_len_unit_exp – R9 F2, Ordinate length units exponent, optional

  • ordinate_force_unit_exp – R9 F3, Ordinate force units exponent, optional

  • ordinate_temp_unit_exp – R9 F4, Ordinate temperature units exponent, optional

  • ordinate_axis_units_lab – R9 F6, Ordinate units label, optional

Ordinate denominator data characteristics

Parameters:
  • orddenom_spec_data_type – R10 F1, Ordinate Denominator specific data type, optional

  • orddenom_len_unit_exp – R10 F2, Ordinate Denominator length units exponent, optional

  • orddenom_force_unit_exp – R10 F3, Ordinate Denominator force units exponent, optional

  • orddenom_temp_unit_exp – R10 F4, Ordinate Denominator temperature units exponent, optional

  • orddenom_axis_units_lab – R10 F6, Ordinate Denominator units label, optional

Z-axis data characteristics

Parameters:
  • z_axis_spec_data_type – R11 F1, Z-axis specific data type, optional

  • z_axis_len_unit_exp – R11 F2, Z-axis length units exponent, optional

  • z_axis_force_unit_exp – R11 F3, Z-axis force units exponent, optional

  • z_axis_temp_unit_exp – R11 F4, Z-axis temperature units exponent, optional

  • z_axis_axis_units_lab – R11 F6, Z-axis units label, optional

Data values

Parameters:
  • data – R12 F1, Data values

  • x – Abscissa array

  • spec_data_type – Specific data type, optional

  • byte_ordering – R1 F3, Byte ordering (only for binary), ignored

  • fp_format – R1 F4 Floating-point format (only for binary), ignored

  • n_ascii_lines – R1 F5, Number of ascii lines (only for binary), ignored

  • n_bytes – R1 F6, Number of bytes (only for binary), ignored

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_58

>>> save_to_file = 'test_pyuff'
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>> uff_datasets = []
>>> binary = [0, 1, 0]  # ascii of binary
>>> frequency = np.arange(10)
>>> np.random.seed(0)
>>> for i, b in enumerate(binary):
>>>     print('Adding point {}'.format(i + 1))
>>>     response_node = 1
>>>     response_direction = 1
>>>     reference_node = i + 1
>>>     reference_direction = 1
>>>     # this is an artificial 'frf'
>>>     acceleration_complex = np.random.normal(size=len(frequency)) + 1j * np.random.normal(size=len(frequency))
>>>     name = 'TestCase'
>>>     data = pyuff.prepare_58(
>>>         binary=binary[i],
>>>         func_type=4,
>>>         rsp_node=response_node,
>>>         rsp_dir=response_direction,
>>>         ref_dir=reference_direction,
>>>         ref_node=reference_node,
>>>         data=acceleration_complex,
>>>         x=frequency,
>>>         id1='id1',
>>>         rsp_ent_name=name,
>>>         ref_ent_name=name,
>>>         abscissa_spacing=1,
>>>         abscissa_spec_data_type=18,
>>>         ordinate_spec_data_type=12,
>>>         orddenom_spec_data_type=13)
>>>     uff_datasets.append(data.copy())
>>>     if save_to_file:
>>>         uffwrite = pyuff.UFF(save_to_file)
>>>         uffwrite._write_set(data, 'add')
>>> uff_datasets

Dataset 82

pyuff.prepare_82(trace_num=None, n_nodes=None, color=None, id=None, nodes=None, return_full_dict=False)[source]

Name: Tracelines

R-Record, F-Field

Parameters:
  • trace_num – R1 F1, Trace line number

  • n_nodes – R1 F2, number of nodes defining trace line (maximum of 250), ignored

  • color – R1 F3, color, optional

  • id – R2 F1, identification line, optional

  • nodes – R3 F1, nodes defining trace line (0 move to node, >0 draw line to node)

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_82

>>> save_to_file = 'test_pyuff'
>>> dataset = pyuff.prepare_82(
>>>     trace_num=2,
>>>     n_nodes=7,
>>>     color=30,
>>>     id='Identification line',
>>>     nodes=np.array([0, 10, 13, 14, 15, 16, 17]))
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>>     uffwrite = pyuff.UFF(save_to_file)
>>>     uffwrite._write_set(dataset, 'add')
>>> dataset

Dataset 151

pyuff.prepare_151(model_name=None, description=None, db_app=None, date_db_created=None, time_db_created=None, version_db1=None, version_db2=None, file_type=None, date_db_saved=None, time_db_saved=None, program=None, date_db_written=None, time_db_written=None, return_full_dict=False)[source]

Name: Header

R-Record, F-Field

Parameters:
  • model_name – R1 F1, Model file name

  • description – R2 F1, Model file description

  • db_app – R3 F1, Name of the application that created database

  • date_db_created – R4 F1, Date database created, optional

  • time_db_created – R4 F2, Time database created, optional

  • version_db1 – R4 F3, Version string 1 of the database, optional

  • version_db2 – R4 F4, Version string 2 of the database, optional

  • file_type – R4 F5, File type. 0:Universal, 1:Archive, 2:Other, optional

  • date_db_saved – R5 F1, Date database last saved, optional

  • time_db_saved – R5 F2, Time database last saved, optional

  • program – R6 F1, Program which created universal file

  • date_db_written – R7 F1, Date universal file was written, optional

  • time_db_written – R7 F2 Time universal file was written, optional

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_151

>>> save_to_file = 'test_pyuff'
>>> dataset = pyuff.prepare_151(
>>>     model_name='Model file name',
>>>     description='Model file description',
>>>     db_app='Program which created DB',
>>>     date_db_created='27-Jan-16',
>>>     time_db_created='14:38:15',
>>>     version_db1=1,
>>>     version_db2=2,
>>>     file_type=0,
>>>     date_db_saved='28-Jan-16',
>>>     time_db_saved='14:38:16',
>>>     program='OpenModal',
>>>     date_db_written='29-Jan-16',
>>>     time_db_written='14:38:17')
>>> dataset
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>>     uffwrite = pyuff.UFF(save_to_file)
>>>     uffwrite._write_set(dataset, 'add')
>>> dataset

Dataset 164

pyuff.prepare_164(units_code=None, units_description=None, temp_mode=None, length=None, force=None, temp=None, temp_offset=None, return_full_dict=False)[source]

Name: Units

R-Record, F-Field

Parameters:
  • units_code – R1 F1, Units code: 1 - SI: Meter (newton), 2 - BG: Foot (pound f), 3 - MG: Meter (kilogram f), 4 - BA: Foot (poundal), 5 - MM: mm (milli newton), 6 - CM: cm (centi newton), 7 - IN: Inch (pound f), 8 - GM: mm (kilogram f), 9 - US: USER_DEFINED

  • units_description – R1 F2, Units cription, optional

  • temp_mode – R1 F3, Temperature mode (1-absolute, 2-relative), optional

  • length – R2 F1, Length

  • force – R2 F2, Force

  • temp – R2 F3, Temperature

  • temp_offset – R2 F4, Temperature offset

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_164

>>> save_to_file = 'test_pyuff'
>>> dataset = pyuff.prepare_164(
>>>     units_code=1,
>>>     units_description='SI units',
>>>     temp_mode=1,
>>>     length=3.28083989501312334,
>>>     force=2.24808943099710480e-01,
>>>     temp=1.8,
>>>     temp_offset=459.67)
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>>     uffwrite = pyuff.UFF(save_to_file)
>>>     uffwrite._write_set(dataset, 'add')
>>> dataset

Dataset 2411

pyuff.prepare_2411(node_nums=None, def_cs=None, disp_cs=None, color=None, x=None, y=None, z=None, return_full_dict=False)[source]

Name: Nodes - Double Precision

R-Record, F-Field

Parameters:
  • node_nums – R1 F1, Node label

  • def_cs – R1 F2, Export coordinate system number

  • disp_cs – R1 F3, Displacement coordinate system number

  • color – R1 F4, Color

  • x – R2 F1, Node coordinates in the part coordinate system

  • y – R2 F2, Node coordinates in the part coordinate system

  • z – R2 F3, Node coordinates in the part coordinate system

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Records 1 and 2 are repeated for each node in the model.

Dataset 2412

pyuff.prepare_2412(element_nums=None, fe_descriptor=None, phys_table=None, mat_table=None, color=None, num_nodes=None, nodes_nums=None, beam_orientation=None, beam_foreend_cross=None, beam_aftend_cross=None, return_full_dict=False)[source]

Name: Elements

R-Record, F-Field

Parameters:
  • element_nums – R1 F1, List of n element numbers

  • fe_descriptor – R1 F2, Fe descriptor id

  • phys_table – R1 F3, Physical property table number

  • mat_table – R1 F4, Material property table number

  • color – R1 F5, Color, optional

  • num_nodes – R1 F6, Number of nodes on element

  • nodes_nums – R2 F1 (R3 FOR RODS), Node labels defining element

  • beam_orientation – R2 F1 FOR RODS ONLY, beam orientation node number

  • beam_foreend_cross – R2 F2 FOR RODS ONLY, beam fore-end cross section number

  • beam_aftend_cross – R2 F3 FOR RODS ONLY, beam aft-end cross section number

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_2412

>>> save_to_file = 'test_pyuff'
>>> data = pyuff.prepare_2412(
>>>     element_nums=np.array([69552, 98919, 69304]),
>>>     fe_descriptor=np.array([94, 94, 94]),
>>>     phys_table=np.array([2, 2, 2]),
>>>     mat_table=np.array([1, 1, 1]),
>>>     color=np.array([2, 2, 2]),
>>>     nodes_nums=np.array([[   29,  2218,  2219,30],[81619, 83403,  2218,    29],[   30,  2219,  2119,    31],[  31, 2119, 1659,   32]]))
>>> dataset = {'type':2412, 'quad':data}
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>>     uffwrite = pyuff.UFF(save_to_file)
>>>     uffwrite.write_sets(dataset, mode='add')
>>> dataset

Dataset 2414

pyuff.prepare_2414(analysis_dataset_label=None, analysis_dataset_name=None, dataset_location=None, id1=None, id2=None, id3=None, id4=None, id5=None, model_type=None, analysis_type=None, data_characteristic=None, result_type=None, data_type=None, number_of_data_values_for_the_data_component=None, design_set_id=None, iteration_number=None, solution_set_id=None, boundary_condition=None, load_set=None, mode_number=None, time_step_number=None, frequency_number=None, creation_option=None, number_retained=None, time=None, frequency=None, eigenvalue=None, modal_mass=None, viscous_damping=None, hysteretic_damping=None, real_part_eigenvalue=None, imaginary_part_eigenvalue=None, real_part_of_modal_A_or_modal_mass=None, imaginary_part_of_modal_A_or_modal_mass=None, real_part_of_modal_B_or_modal_mass=None, imaginary_part_of_modal_B_or_modal_mass=None, d=None, node_nums=None, x=None, y=None, z=None, return_full_dict=False)[source]

Name: Analysis Data

R-Record, F-Field

Parameters:
  • analysis_dataset_label – R1 F1, Analysis dataset label

  • analysis_dataset_name – R2 F1, Analysis dataset name

  • dataset_location – R3 F1, Dataset location, 1:Data at nodes, 2:Data on elements, 3:Data at nodes on elements, 5:Data at points

  • id1 – R4 F1, ID line 1

  • id2 – R5 F1, ID line 2

  • id3 – R6 F1, ID line 3

  • id4 – R7 F1, ID line 4

  • id5 – R8 F1, ID line 5

  • model_type – R9 F1, Model type

  • analysis_type – R9 F2, Analysis type

  • data_characteristic – R9 F3, Data characteristic

  • result_type – R9 F4, Result type

  • data_type – R9 F5, Data type

  • number_of_data_values_for_the_data_component – R9 F6, Number of data values for the data component (NVALDC)

Integer analysis type specific data

Parameters:
  • design_set_id – R10 F1,

  • iteration_number – R10 F1,

  • solution_set_id – R10 F1,

  • boundary_condition – R10 F1,

  • load_set – R10 F1,

  • mode_number – R10 F1,

  • time_step_number – R10 F1,

  • frequency_number – R10 F1,

  • creation_option – R11 F1,

  • number_retained – R11 F1,

Real analysis type specific data

Parameters:
  • time – R12 F1,

  • frequency – R12 F1,

  • eigenvalue – R12 F1,

  • modal_mass – R12 F1,

  • viscous_damping – R12 F1,

  • hysteretic_damping – R12 F1,

  • real_part_eigenvalue – R13 F1,

  • imaginary_part_eigenvalue – R13 F1,

  • real_part_of_modal_A_or_modal_mass – R13 F1,

  • imaginary_part_of_modal_A_or_modal_mass – R13 F1,

  • real_part_of_modal_B_or_modal_mass, – R13 F1,

  • imaginary_part_of_modal_B_or_modal_mass – R13 F1,

  • node_nums – R14 F1, Node number

  • d – R15 F1, Data at this node (NDVAL real or complex values)

  • x – R15 F1,

  • y – R15 F1,

  • z – R15 F1,

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included

Test prepare_2414

>>> save_to_file = 'test_pyuff'
>>> dataset = pyuff.prepare_2414(
>>>     analysis_dataset_label=1,
>>>     analysis_dataset_name='Solid displacement at 1.00000e+02 Hz',
>>>     dataset_location=1,
>>>     id1='FEMTown to UNV output driver',
>>>     id2=' Analysis',
>>>     id3='Solid displacement at 1.00000e+02 Hz',
>>>     id4='LoadCase 1',
>>>     id5='none',
>>>     model_type=0,
>>>     analysis_type=5,
>>>     data_characteristic=2,
>>>     result_type=8,
>>>     data_type=5,
>>>     number_of_data_values_for_the_data_component=3,
>>>     design_set_id=1,
>>>     iteration_number=0,
>>>     solution_set_id=1,
>>>     boundary_condition=0,
>>>     load_set=1,
>>>     mode_number=0,
>>>     time_step_number=0,
>>>     frequency_number=0,
>>>     creation_option=1,
>>>     number_retained=1,
>>>     time=0.0,
>>>     frequency=100.0,
>>>     eigenvalue=100.0,
>>>     modal_mass=0.0,
>>>     viscous_damping=0.0,
>>>     hysteretic_damping=0.0,
>>>     real_part_eigenvalue=0.0,
>>>     imaginary_part_eigenvalue=0.0,
>>>     real_part_of_modal_A_or_modal_mass=0.0,
>>>     imaginary_part_of_modal_A_or_modal_mass=0.0,
>>>     real_part_of_modal_B_or_modal_mass=0.0,
>>>     imaginary_part_of_modal_B_or_modal_mass=0.0,
>>>     node_nums=np.array([29, 30, 31]),
>>>     x=np.array([2.84811e-09+1.73733e-09j, 3.11873e-09+1.19904e-09j, 3.28182e-09+6.12300e-10j]),
>>>     y=np.array([-7.13813e-10+6.53419e-10j, -4.95859e-10+8.07390e-10j, -2.52772e-10+9.05991e-10j]),
>>>     z=np.array([4.28828e-10+2.47563e-10j, 4.65334e-10+1.70107e-10j, 4.87383e-10+8.66597e-11j]))
>>> if save_to_file:
>>>     if os.path.exists(save_to_file):
>>>         os.remove(save_to_file)
>>>     uffwrite = pyuff.UFF(save_to_file)
>>>     uffwrite.write_sets(dataset, mode='add')
>>> dataset

Dataset 2420

pyuff.prepare_2420(Part_UID=None, Part_Name=None, CS_sys_labels=None, CS_types=None, CS_colors=None, CS_names=None, CS_matrices=None, return_full_dict=False)[source]

Name: Coordinate Systems

R-Record, F-Field

Parameters:
  • Part_UID – R1 F1, Part UID

  • Part_Name – R2 F1, Part Name

  • CS_sys_labels – R3 F1, Coordinate System Label

  • CS_types – R3 F2, Coordinate System Type (0-Cartesian, 1-Cylindrical, 2-Spherical)

  • CS_colors – R3 F3, Coordinate System Color

  • CS_names – R4 F1, Coordinate System Name

  • CS_matrices – R5-8 F1-3, Transformation Matrix

  • return_full_dict – If True full dict with all keys is returned, else only specified arguments are included