SurfaceHeatTransferResultCSVModel#
- class SurfaceHeatTransferResultCSVModel[source]#
Bases:
PerEntityResultCSVModel,TimeSeriesResultCSVModelSurfaceHeatTransferResultCSVModel
Attributes
Properties
- entities#
Returns list of entity names available for this result
- x_columns#
Get x column
- raw_values#
Get the raw CSV data.
- Returns:
Dictionary containing the raw CSV data.
- Return type:
- 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:
Additional Constructors
- classmethod from_dict(data, group=None)#
Overloaded version of from_dict to store entity groups.
- by_boundary_condition(params)#
Group entities by boundary condition’s name and create a SurfaceForcesGroupResultCSVModel. Forces from different boundaries but with the same type and name will be summed together.
- Parameters:
params (SimulationParams)
- Return type:
PerEntityResultCSVModel
- by_body_group(params)#
Group entities by body group’s name and create a SurfaceForcesGroupResultCSVModel
- Parameters:
params (SimulationParams)
- Return type:
PerEntityResultCSVModel
Methods
- filter(include=None, exclude=None)#
Filters entities based on include and exclude lists.
- reload_data(filter_physical_steps_only=False, include_time=False)#
Change default behavior of data loader, reload
- load_from_local(filename)#
Load CSV data from a local file.
- Parameters:
filename (str) – Path to the local CSV file.
- load_from_remote(**kwargs_download)#
Load CSV data from a remote source.
- download(to_file=None, to_folder='.', overwrite=False, **kwargs)#
Download the CSV file.
- update(df)#
Update containing value to the given DataFrame
- Parameters:
df (DataFrame)
- 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.
- as_dict()#
Convert the data to a dictionary.
- Returns:
Dictionary containing the data.
- Return type:
- as_numpy()#
Convert the data to a NumPy array.
- Returns:
NumPy array containing the data.
- Return type:
numpy.ndarray
- as_dataframe()#
Convert the data to a Pandas DataFrame.
- Returns:
DataFrame containing the data.
- Return type:
pandas.DataFrame
- wait(timeout_minutes=60)#
Wait until the Case finishes processing, refresh periodically. Useful for postprocessing, eg sectional data
- include_time()#
Set the option to include time in the data
- filter_physical_steps_only()#
filters data to contain only last pseudo step data for every physical step
- get_averages(average_fraction)#
Computes the average of data