pyprecag.table_ops

pyprecag.table_ops.calculate_strip_stats(input_table, treatment_column, control_columns=[], size=5)

Calculate statistics for a strip

A moving window is used for some of the statistics. This window is centred so for a window size of 5, 2 NAN or blanks will be added to start and end of the output column.

Statistics include (output column names):

controls_mean - row by row mean of the control columns treat_diff - row by row difference between the treatment and controls_mean columns av_treat_diff - calculate mean of values using a moving window using the treat_diff column p_value - calculate p_value using a moving window using treatment and controls_mean columns RI - Response Index using the treatment and controls_mean columns

Parameters:

• input_table (pandas.core.frame.DataFrame) – the table to calculate statistics for
• treatment_column (str) – The column containing the treatment values
• control_columns (List[str]) – The column containing the control values. This can be one or two columns
• size (int) – The size of the moving window.

Returns:

The output table containing new statistics columns control_mean (str): The column used as the control mean.

Return type:

pandas.core.frame.DataFrame

pyprecag.table_ops.response_index(arr)

Moving window response index function to get two columns in to the function, one must be set as the index. .. rubric:: Example

input_table = input_table.set_index(treatment_column, drop=False) input_table[‘RI’] = input_table[‘controls_mean’].rolling(

window=size, center=True).apply(response_index, raw=False)

pyprecag.table_ops.t_test(arr)

Moving window t-test function. to get two columns in to the function, one must be set as the index.

Example

input_table = input_table.set_index(treatment_column, drop=False)

input_table[‘p_value’] = input_table[‘controls_mean’].rolling(

window=size, center=True).apply(t_test, raw=False)