watex.utils.exmath.compute_lower_anomaly#
- watex.utils.exmath.compute_lower_anomaly(erp_array, station_position=None, step=None, **kws)[source]#
Function to get the minimum value on the ERP array.
If pk is provided wil give the index of pk.
- Parameters:
erp_array (array_like) β array of apparent resistivity profile
position (station) β array of station position (survey), if not given and step is known , set the step value and station_position will compute automatically
step β The distance between measurement im meter. If given will recompute the station_position
- Returns:
- bestSelectedDict: dict containing best anomalies
with the anomaly resistivities range.
anpks: Main positions of best select anomaly
collectanlyBounds: list of arrays of select anomaly values
min_pks: list of tuples (pk, minVal of best anomalies points.)
- Return type:
tuple
- Example:
>>> from watex.utils.exmath import compute_lower_anolamy >>> import pandas as pd >>> erp_data= 'data/l10_gbalo.xlsx' >>> dataRes=pd.read_excel(erp_data).to_numpy()[:,-1] >>> anomaly, *_ = compute_lower_anomaly(erp_array=data, step =10) >>> anomaly