adamspy.postprocess package¶

Subpackages¶

adamspy.postprocess.analysis package
- Module contents

Submodules¶

adamspy.postprocess.animation module¶

Code for generating animations automatically in Adams View

adamspy.postprocess.animation.create_animation(model_file: str, res_file: str, model_name: str, analysis_name: str, timeout=60)[source]¶

Creates an animation from the given model.

Parameters:	model_file (str) – Adams View model (.cmd) file res_file (str) – Adams results (.res) file model_name (str) – Name of the model analysis_name (str) – Name of the analysis wait (bool, optional) – If True, code execution will freeze until the animation script completes and the postprocessor closes. (the default is True)

adamspy.postprocess.exported module¶

adamspy.postprocess.exported.import_spreadsheet(filename, output_type='dict')[source]¶

Reads data from a file generated in Adams View using File>Export>Spreadsheet.

Parameters:	filename (str) – Name of file. output_type (str) – Type of object to return. Default is ‘DataFrame’ which returns a pandas :obj:DataFrame object. You can also select ‘dict’.
Returns:	Pandas :obj:Dataframe if output_type is ‘DataFrame’ or :obj:dict if output_type is ‘dict’
Return type:	DataFrame or dict

adamspy.postprocess.mode_tables module¶

class adamspy.postprocess.mode_tables.Modal(modes: Dict[int, adamspy.postprocess.mode_tables.Mode])[source]¶

Bases: object

filter_eigs(wn_min, wn_max)[source]¶

find_pairs(other: adamspy.postprocess.mode_tables.Modal)[source]¶

get_modes_where_parts_participate(part_suffix, table, column, threshold=0.9, sum_or_max='max')[source]¶

Returns a dictionary where the keys are mode numbers and the values are :obj:Mode objects in which any part with the suffix part_suffix has at least threshold percent of the total.

Parameters:	part_suffix (str) – Suffix of parts to check for table (str) – Table type. Options are ‘coords’, ‘kinetic_energy’, ‘strain_energy’, ‘dissipative_energy’ column (str) – Column name from the table threshold (float) – Part’s value must be greater than threshold multiplied the sum or max (depending on sum_or_max value) of the column in the table to be considered participating sum_or_max (str) – Must be ‘sum’ or ‘max’
Returns:	Dictionary where the keys are mode numbers and the values are :obj:Mode objects
Return type:	dict

remove_duplicate_eigs(tolerance=0.001)[source]¶

remove_zero_eigs(threshold=0.5)[source]¶

class adamspy.postprocess.mode_tables.Mode(scalars: dict, tables: dict)[source]¶

Bases: object

compare_coords(other_mode: adamspy.postprocess.mode_tables.Mode)[source]¶

adamspy.postprocess.mode_tables.parse_table_file(filename)[source]¶

adamspy.postprocess.msg module¶

This module contains tools for extracing data from the message file.

adamspy.postprocess.msg.check_for_errors(filename)[source]¶

adamspy.postprocess.msg.check_if_finished(filename)[source]¶

adamspy.postprocess.msg.convert_cpu_time(time_string)[source]¶

adamspy.postprocess.msg.get_errors(filename)[source]¶

adamspy.postprocess.msg.get_modes(filename, output_type='dict', i_analysis=0, underdamped_only=True, sort_by_wn=True)[source]¶

Gets the modes from an Adams Solver message file.

Parameters:	filename (str) – Name of Adams Solver message (.msg) file. output_type (str, optional) – If ‘DataFrame’, returns a pandas :obj:pd.DataFrame if ‘dict’, returns a :obj:dict. (Default is ‘dict’) i_analysis (int, (optional)) – If the Adams Solver message (.msg) file contains multiple eigensolutions, this specifies which one to get. (Default is 0 which takes the first analysis)
Returns:	` – Table of modes
Return type:	obj:pd.DataFrame` or :obj:dict

adamspy.postprocess.msg.get_process_id(filename: pathlib.Path)[source]¶

Returns the process ID of the Adams job that generated the given message file.

Parameters:	filename (Path) – Path to the message file.
Returns:	Process ID of the Adams job that generated the given message file.
Return type:	int

adamspy.postprocess.msg.get_runtime_summary(filename)[source]¶

Returns a list of timestamps from the Adams message (.msg) file. Each timestamp in the list is a list as follows [elapsed time, cpu time, percent speedup]

Parameters:	filename (str) – Filename of message file
Returns:	List of timestamps where each timestamp in the list is a list as follows [elapsed time, cpu time, percent speedup].
Return type:	list

adamspy.postprocess.msg.get_timestamps(filename)[source]¶

Returns a list of timestamps from the Adams message (.msg) file. Each timestamp in the list is a list as follows [simulation time, step size, Function evaluations, cumulative steps taken, integration order, simulation time]

Parameters:	filename (str) – Filename of message file
Returns:	List of timestamps where each timestamp in the list is a list as follows [simulation time, step size, Function evaluations, cumulative steps taken, integration order, simulation time].
Return type:	list

adamspy.postprocess.msg.uses_fortran_solver(filename)[source]¶

adamspy.postprocess.ppt module¶

This module is for sending scripts through Adams/PPT

adamspy.postprocess.ppt.edit_results(res_file, input_dict, new_res_file=None, _just_write_script=False, timeout=300)[source]¶

adamspy.postprocess.ppt.filter_results(res_file, reqs_to_clean, freq_cutoff, N_filter=5, reqs_to_check=None, t_min=None, t_max=None, _just_write_script=False, timeout=300, _inplace=False, return_raw=False)[source]¶

Similar to manually_remove_spikes, but allows user to plot the signals in batches. Instead of passing a dictionary for the reqs_to_check argument, pass a list of dictionaries and the results in each dictionary in the list will be plotted together.

Parameters:	res_file (str) – Adams Results (.res) filename reqs_to_clean (dict) – Nested dictionary of result sets and result components to clean freq_cutoff (float) – Cutoff freqency of filter in Hz N_filter (int) – Order of filter reqs_to_check (list of dicts) – list of nested dictionary of result sets and result components to check for spikes, by default same as reqs_to_clean t_min (float, optional) – Minumum simulation time to clean, by default None t_max (float, optional) – Maximum simulation time to clean, by default None timeout (float, optional) – Number of seconds to wait for results to load before timing out, by default _TIMEOUT
Returns:	Nested dictionary of cleaned results
Return type:	dict

adamspy.postprocess.ppt.get_lunar_results(res_files, reqs_to_get, t_min, t_max, output_file, _just_write_script=False, timeout=300)[source]¶

adamspy.postprocess.ppt.get_results(res_file, reqs_to_get, t_min=None, t_max=None, _just_write_script=False, timeout=300)[source]¶

Gets results from an Adams results (.res) file.

Example

>>> result_file = 'example.res'
>>> t_min = 70
>>> t_max = 80
>>> reqs_to_get = {}
>>> reqs_to_get['MSE'] = ['Instantaneous_Bottom_MSE', 'Filtered_Surface_MSE']
>>> reqs_to_get['ROP_controls'] = ['Command_ROP', 'True_WOB']
>>> requests, units = get_results(result_file, reqs_to_get, t_min, t_max)

Note

This funciton only works with Requests. It does not work with Result Sets.

Note

This function only works with xml results files.

Parameters:	result_file (str) – Filename of an Adams results (.res) file reqs_to_get (dict) – Dictionary of requests to extract (the default is None, which gets all results) t_min (float, optional) – Minimum time for which to extract results (the default is None) t_max (float, optional) – Maximum time for which to extract results (the default is None)
Returns:	Dictionary of request data
Return type:	dict

adamspy.postprocess.ppt.manually_remove_spikes(res_file, reqs_to_clean, reqs_to_check=None, t_min=None, t_max=None, _just_write_script=False, timeout=300, _inplace=False)[source]¶

Allows the user to manually scan through the result sets to pick out points to eliminate.

Parameters:	res_file (str) – Adams Results (.res) filename reqs_to_clean (dict, optional) – Nested dictionary of result sets and result components to clean reqs_to_check (dict) – Nested dictionary of result sets and result components to check for spikes, by default same as reqs_to_clean t_min (float, optional) – Minumum simulation time to clean, by default None t_max (float, optional) – Maximum simulation time to clean, by default None timeout (float, optional) – Number of seconds to wait for results to load before timing out, by default _TIMEOUT
Returns:	Nested dictionary of cleaned results
Return type:	dict

adamspy.postprocess.ppt.manually_remove_spikes_batch(res_file, reqs_to_clean, reqs_to_check=None, t_min=None, t_max=None, _just_write_script=False, timeout=300, _inplace=False)[source]¶

Similar to manually_remove_spikes, but allows user to plot the signals in batches. Instead of passing a dictionary for the reqs_to_check argument, pass a list of dictionaries and the results in each dictionary in the list will be plotted together.

Parameters:	res_file (str) – Adams Results (.res) filename reqs_to_clean (dict) – Nested dictionary of result sets and result components to clean reqs_to_check (list of dicts) – list of nested dictionary of result sets and result components to check for spikes, by default same as reqs_to_clean t_min (float, optional) – Minumum simulation time to clean, by default None t_max (float, optional) – Maximum simulation time to clean, by default None timeout (float, optional) – Number of seconds to wait for results to load before timing out, by default _TIMEOUT
Returns:	Nested dictionary of cleaned results
Return type:	dict

adamspy.postprocess.ppt.write_results(res_file, input_dict)[source]¶

adamspy.postprocess.xml module¶

adamspy.postprocess.xml.get_component(res_file, comp_name)[source]¶

Returns the numeric data in res_file associated with the result component comp_name.

Parameters:	res_file (str) – Result (.res) file comp_name (str) – Name of result component
Returns:	List of values from the result (.res) file.
Return type:	list
Raises:	`ValueError` – Raised if comp_name not found in res_file.

adamspy.postprocess.xml.get_results(result_file, reqs_to_get=None, t_min=None, t_max=None, return_units=False, overwrite_pickle=True, use_iterparse=False)[source]¶

Gets results from an Adams results (.res) file.

Example

>>> result_file = 'example.res'
>>> t_min = 70
>>> t_max = 80
>>> reqs_to_get = {}
>>> reqs_to_get['MSE'] = ['Instantaneous_Bottom_MSE', 'Filtered_Surface_MSE']
>>> reqs_to_get['ROP_controls'] = ['Command_ROP', 'True_WOB']
>>> requests, units = get_results(result_file, reqs_to_get, t_min, t_max)

Note

This funciton only works with Requests. It does not work with Result Sets.

Note

This function only works with xml results files.

Parameters:

result_file (str) – Filename of an Adams results (.res) file
reqs_to_get (dict) – Dictionary of requests to extract (the default is None, which gets all results)
t_min (float, optional) – Minimum time for which to extract results (the default is None)
t_max (float, optional) – Maximum time for which to extract results (the default is None)

Returns:

dict – Dictionary of request data
dict – Dictionary defining units for each request. NOTE: This is only returned if return_units=True

adamspy.postprocess.xml.get_stepmap_dictionary(file_name)[source]¶

Create dictionary where keys are result names and values are indices of components.

Note

Res names must be full, like: * time.time * part_2_xform.fx * part_3_xform.accy

Parameters:	file_name (str) – Results (.res) file
Returns:	Step map
Return type:	dict

adamspy.postprocess.xml.shrink_results(result_file, reqs_to_keep=None, t_min=None, t_max=None, new_result_file=None, in_place=False)[source]¶

Shrinks a results file by eliminating unwanted data.

Example

>>> result_file = 'example.res'
>>> t_min = 70
>>> t_max = 80
>>> reqs_to_keep = {}
>>> reqs_to_keep['MSE'] = ['Instantaneous_Bottom_MSE', 'Filtered_Surface_MSE']
>>> reqs_to_keep['ROP_controls'] = ['Command_ROP', 'True_WOB']
>>> shrink_results(result_file, reqs_to_keep, t_min, t_max)

Note

This funciton only works with Requests. It does not work with Result Sets.

Parameters:

result_file (str) – Filename of the results file
reqs_to_keep (dict) – Dictionary of requests and request components that should be saved.
t_min (float, optional) – Start time of period of interest (default is None which uses the first time step)
t_max (float, optional) – End time of period of interest (default is None which uses the last time step)
new_result_file (str) – Name that will be given to the new results file. (Default is None which adds a ‘_shrunk’ suffix to result_file if in_place=False or uses result_file if in_place=True.)
in_place (bool, optional) – If True, existing file will be deleted.

Module contents¶

Package for working with Adams Results

adamspy.postprocess.get_log_errors(log_file: pathlib.Path)[source]¶

Checks the log file for errors of the type AviewError.

Parameters:	log_file (str) – Filename of aview log file (usulally aview.log)

adamspy.postprocess.launch_ppt(res_file, cmd_file=None, wait=False, timeout=30, _terminate=False)[source]¶

Launches the Adams PostProcessor and reads in the specified results file.

Parameters:

res_file (str) – Filepath to an Adams Results file.
cmd_file (str, optional) – Adams View command (.cmd) file. If given, this will be loaded before the results file. This is necessary to view animations.
wait (bool, optional) – If True, code execution will freeze until the postprocessor is closed. (the default is False)
timeout (float, optional) – If wait`=`False, code execution will freeze until the postprocessor has started loading the results file or until timeout secodns have elapsed.
_terminate (bool, optional) – If True, the PostProcessor will close immediately. This is for testing purposes.