UserDefinedDynamicsCSVModel

UserDefinedDynamicsCSVModel

alias of TimeSeriesResultCSVModel

Attributes

UserDefinedDynamicsCSVModel.remote_file_name: str

UserDefinedDynamicsCSVModel.local_file_name: str

Default:

None

UserDefinedDynamicsCSVModel.do_download: bool, optional

Default:

None

UserDefinedDynamicsCSVModel.local_storage: str, optional

Default:

None

UserDefinedDynamicsCSVModel.temp_file: str

Default:

'/tmp/tmpx48idwvm/e97f5c4c-3d5f-4dd0-8fc8-f3b99b87b32b.csv'

Properties

UserDefinedDynamicsCSVModel.x_columns

Get x column

UserDefinedDynamicsCSVModel.raw_values

Get the raw CSV data.

Returns:

Dictionary containing the raw CSV data.

Return type:

dict

UserDefinedDynamicsCSVModel.values

Get the current data.

Returns:

Dictionary containing the current data.

Return type:

dict

UserDefinedDynamicsCSVModel.averages

Get average data over last 10%

Returns:

Dictionary containing CL, CD, CFx/y/z, CMx/y/z and other columns available in data

Return type:

dict

Additional Constructors

classmethod UserDefinedDynamicsCSVModel.from_dict(data)

Load from data dictionary

Parameters:

data (dict)

Methods

UserDefinedDynamicsCSVModel.load_from_local(filename)

Load CSV data from a local file.

Parameters:

filename (str) – Path to the local CSV file.

UserDefinedDynamicsCSVModel.load_from_remote(**kwargs_download)

Load CSV data from a remote source.

UserDefinedDynamicsCSVModel.reload_data(filter_physical_steps_only=False, include_time=False)

Change default behavior of data loader, reload

Parameters:

• filter_physical_steps_only (bool)

• include_time (bool)

UserDefinedDynamicsCSVModel.download(to_file=None, to_folder='.', overwrite=False, **kwargs)

Download the CSV file.

Parameters:

• to_file (str, optional) – The name of the file after downloading.

• to_folder (str, optional) – The folder where the file will be downloaded.

• overwrite (bool, optional) – Flag indicating whether to overwrite existing files.

UserDefinedDynamicsCSVModel.update(df)

Update containing value to the given DataFrame

Parameters:

df (DataFrame)

UserDefinedDynamicsCSVModel.to_file(filename=None)

Save the data to a CSV file.

Parameters:

filename (str, optional) – The name of the file to save the CSV data.

UserDefinedDynamicsCSVModel.as_dict()

Convert the data to a dictionary.

Returns:

Dictionary containing the data.

Return type:

dict

UserDefinedDynamicsCSVModel.as_numpy()

Convert the data to a NumPy array.

Returns:

NumPy array containing the data.

Return type:

numpy.ndarray

UserDefinedDynamicsCSVModel.as_dataframe()

Convert the data to a Pandas DataFrame.

Returns:

DataFrame containing the data.

Return type:

pandas.DataFrame

UserDefinedDynamicsCSVModel.wait(timeout_minutes=60)

Wait until the Case finishes processing, refresh periodically. Useful for postprocessing, eg sectional data

UserDefinedDynamicsCSVModel.include_time()

Set the option to include time in the data

UserDefinedDynamicsCSVModel.filter_physical_steps_only()

filters data to contain only last pseudo step data for every physical step

UserDefinedDynamicsCSVModel.get_averages(average_fraction)

Computes the average of data