resultObjects Package

op2_Objects Module

class pyNastran.op2.resultObjects.op2_Objects.BaseScalarObject

Bases: pyNastran.op2.op2Codes.Op2Codes

_write_f06_transient(header, page_stamp, page_num=1, f=None, is_mag_phase=False)

get_stats()

name()

write_f06(header, page_stamp, page_num=1, f=None, is_mag_phase=False)

class pyNastran.op2.resultObjects.op2_Objects.ScalarObject(data_code, isubcase, apply_data_code=True)

Bases: pyNastran.op2.resultObjects.op2_Objects.BaseScalarObject

append_data_member(var_name, value_name)

this appends a data member to a variable that may or may not exist

apply_data_code()

cast_grid_type(grid_type)

converts a grid_type string to an integer

getUnsteadyValue()

getVar(name)

get_data_code()

isImaginary()

print_data_members()

Prints out the “unique” vals of the case. Uses a provided list of data_code[‘dataNames’] to set the values for each subcase. Then populates a list of self.name+’s‘ (by using setattr) with the current value. For example, if the variable name is ‘mode’, we make self.modes. Then to extract the values, we build a list of of the variables that were set like this and then loop over them to print their values.

This way there is no dependency on one result type having [‘mode’] and another result type having [‘mode’,’eigr’,’eigi’].

recast_gridtype_as_string(grid_type)

converts a grid_type integer to a string

set_data_members()

set_var(name, value)

start_data_member(var_name, value_name)

update_data_code(data_code)

update_dt(data_code, dt)

This method is called if the object already exits and a new time/freq/load step is found

tableObject Module

class pyNastran.op2.resultObjects.tableObject.ComplexTableArray(data_code, is_sort1, isubcase, dt)

Bases: pyNastran.op2.resultObjects.tableObject.TableArray

_write_f06_transient_block(words, header, page_stamp, page_num, f, is_mag_phase)

data_type()

is_complex()

is_real()

class pyNastran.op2.resultObjects.tableObject.ComplexTableObject(data_code, is_sort1, isubcase, dt)

Bases: pyNastran.op2.resultObjects.op2_Objects.ScalarObject

_write_f06_block(words, header, page_stamp, page_num=1, f=None, is_mag_phase=False)

_write_f06_transient_block(words, header, page_stamp, page_num=1, f=None, is_mag_phase=False)

add(dt, nodeID, grid_type, v1, v2, v3, v4, v5, v6)

add_complex_f06_data(data, transient)

add_f06_data(data, transient)

add_new_transient(dt)

initializes the transient variables

add_sort1(dt, nodeID, grid_type, v1, v2, v3, v4, v5, v6)

add_sort2(nodeID, data)

delete_transient(dt)

get_stats()

get_transients()

isImaginary()

update_dt(data_code, dt)

class pyNastran.op2.resultObjects.tableObject.RealTableArray(data_code, is_sort1, isubcase, dt)

Bases: pyNastran.op2.resultObjects.tableObject.TableArray

_write_f06_block(words, header, page_stamp, page_num, f, write_words=True)

_write_f06_transient_block(words, header, page_stamp, page_num, f, write_words=True)

_write_op2_header(f, table_num, i)

data_type()

is_complex()

is_real()

write_op2(f, is_mag_phase=False)

class pyNastran.op2.resultObjects.tableObject.RealTableObject(data_code, is_sort1, isubcase, dt)

Bases: pyNastran.op2.resultObjects.op2_Objects.ScalarObject

ATO_words()

CRM_words()

PSD_words()

RMS_words()

ZERO_words()

_write_f06_block(words, header, page_stamp, page_num=1, f=None)

_write_f06_transient_block(words, header, page_stamp, page_num=1, f=None)

add(dt, node_id, grid_type, v1, v2, v3, v4, v5, v6)

add_f06_data(data, transient)

add_new_transient(dt)

initializes the transient variables

add_sort1(dt, node_id, grid_type, v1, v2, v3, v4, v5, v6)

add_sort2(node_id, dt, grid_type, v1, v2, v3, v4, v5, v6)

delete_transient(dt)

get_as_sort1()

get_as_sort2()

returns translations and rotations in sort2 format

get_stats()

get_table_marker()

get_transients()

isATO()

Auto-Correlation Function

isCRM()

Correlated Root-Mean Square

isImaginary()

isPSD()

Power Spectral Density

isRMS()

Root-Mean Square

isZERO()

Zero Crossings

update_dt(data_code, dt)

class pyNastran.op2.resultObjects.tableObject.TableArray(data_code, is_sort1, isubcase, dt)

Bases: pyNastran.op2.resultObjects.op2_Objects.ScalarObject

_get_msgs(is_mag_phase)

_reset_indices()

add(dt, node_id, grid_type, v1, v2, v3, v4, v5, v6)

add_sort1(dt, node_id, grid_type, v1, v2, v3, v4, v5, v6)

build()

data_type()

get_stats()