HAlphaAnomalyzer._cell_range_calculator
Module Contents
Functions
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Calculate the lower and upper percentage values of a grid cell pixel |
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Calculate candidate upper and lower percentage values for each grid cell |
- HAlphaAnomalyzer._cell_range_calculator._calculate_range_values(data_cells, lower_range=2, upper_range=98)[source]
Calculate the lower and upper percentage values of a grid cell pixel averages from the training image data.
Parameters
- data_cellspd.DataFrame
The DataFrame containing the grid cell pixel averages from the training image data.
- lower_rangefloat, optional
The lower percentage to calculate, by default 2.
- upper_rangefloat, optional
The upper percentage to calculate, by default 98.
Returns
- lower_range_valfloat
The lower percentage value of the grid cell pixel averages from the training image data.
- upper_range_valfloat
The upper percentage value of the grid cell pixel averages from the training image data.
- HAlphaAnomalyzer._cell_range_calculator._calculate_cell_wise_ranges(images_data, grid_size=8, lower_range_end=20, upper_range_start=80, step_size=2)[source]
Calculate candidate upper and lower percentage values for each grid cell of the training images data for the One-way ANOVA F-test.
Parameters
- images_datapd.DataFrame
The DataFrame containing the training images data.
- grid_sizeint, optional
The number of rows and columns to divide each image into, by default 8.
- lower_range_endint, optional
The end of candidate lower ranges, by default 20.
- upper_range_startint, optional
The start of candidate upper ranges, by default 80.
- step_sizeint, optional
The step size for candidate ranges, by default 2.
Returns
- df_all_rangespd.DataFrame
A DataFrame with candidate ranges for each grid cell of the training images data.