casefoam.loadData.posField_to_timeSeries¶

casefoam.loadData.posField_to_timeSeries(solutionDir, file, postFunction, caseStructure=None, baseCase='.', **kwargs)[source]¶

Converts multiple posionalFields to timeSeries with a function

Load all postional Fields of a given case, manipulate the data for each time step and save the manipulated results into one pandas.DataFrame for all times.

Parameters:

solutionDir : str

Solution directory in the OpenFOAM case postProcessing directory.

file : str

File name of the solution file.

postFunction : function

User function to manipulate the solution data ['x', 'y', 'z', 'values', ...]. The function must return output DataFrame should has and has to have the parameters (caseComb, time, currentDataFrame)

caseStructure : list, optional

List of parent, child and grandchild names:

[[parent1, parent2],
 [child1, child2, child3],
 [grandchild1, grandchild2]]

baseCase : str, optional

Root directory of all cases.

**kwargs

Keyword arguments if needed by postFunction.

Returns:

outputDf : pandas.DataFrame: pandas.DataFrame with solutions for all times.

Examples

Define a user postFunction.

>>> def userFunction(caseComb, time, currentDataFrame):
    t = time
    minimum = currentDataFrame.iloc[:, 1].min()
    mean = currentDataFrame.iloc[:, 1].mean()
    maximum = currentDataFrame.iloc[:, 1].max()
    df = pd.DataFrame(np.array([time, minimum, mean, maximum],
                      ndmin=2),
                      columns=['time', 'min', 'mean', 'max'])
    df = df.set_index('time')
    return df