our_package package¶
Submodules¶
our_package.analysis module¶
Analysis module.
@Team 1, 03/23
- analysis.calc_auto(wavef)¶
- analysis.check_if_significant(data, thresh)¶
Check variance of columns and select the ones above a threshold.
- Parameters
data – dataframe to inspect
thresh – threshold for variance
- analysis.check_if_significant_np(data, thresh)¶
- analysis.do_DFT(data, tmax)¶
- analysis.do_fft(data, tmax)¶
- analysis.euclidean_distance(list_ref, list_comp, vectors)¶
- analysis.get_correlation_measure(df)¶
Get correlations within columns of a dataframe.
- Parameters
df (pandas dataframe) – dataframe
our_package.data_handling module¶
Data import routines
- data_handling.plot_columns(data, titlestr)¶
Plot the data for visiual inspection.
- data_handling.read_in_df(filedir, filename)¶
Load data from testfile using pandas
- data_handling.read_in_np(filedir, filename)¶
Load data from testfile using numpy
our_package.main module¶
This is the main routine of our package!
Here, all the subroutines are executed and the results are stored whereever…
- main.numerical(plot=False)¶
our_package.settings module¶
Global settings for package
our_package.statistics module¶
- statistics.plot_correlation(df, threshv, output_path, output_name)¶
Plots correlation of significant data in heatmap and save plot as PDF
- Parameters
df – Pandas DataFrame object with numerical values
threshv – the threshhold value that filters out insignificant data
output_path – to which directory will the PDF be saved
output_name – the name of the PDF
- Returns
A dataframe with significant data
- statistics.plot_relevant(df, threshv, output_path: str, output_name: str)¶
Plots significant data in pairplot and save plot as PDF
- Parameters
df – Pandas DataFrame object with numerical values
threshv – the threshhold value that filters out insignificant data
output_path – to which directory will the PDF be saved
output_name – the name of the PDF
- Returns
A dataframe with significant data