""" Implementation in progress. """
import numpy as np
from hed.tools.remodeling.operations.base_op import BaseOp
# TODO: This class is under development
[docs]class NumberRowsOp(BaseOp):
""" Implementation in progress. """
NAME = "number_rows"
PARAMS = {
"type": "object",
"properties": {
"number_column_name": {
"type": "string"
},
"overwrite": {
"type": "boolean"
},
"match_value": {
"type": "object",
"properties": {
"column": {
"type": "string"
},
"value": {
"type": [
"string",
"number"
]
}
},
"required": [
"column",
"value"
],
"additionalProperties": False
}
},
"required": [
"number_column_name"
],
"additionalProperties": False
}
[docs] def __init__(self, parameters):
super().__init__(parameters)
self.number_column_name = parameters['number_column_name']
self.overwrite = parameters.get('overwrite', False)
self.match_value = parameters.get('match_value', False)
[docs] def do_op(self, dispatcher, df, name, sidecar=None):
""" Add numbers events dataframe.
Parameters:
dispatcher (Dispatcher): Manages operation I/O.
df (DataFrame): - The DataFrame to be remodeled.
name (str): - Unique identifier for the dataframe -- often the original file path.
sidecar (Sidecar or file-like): Only needed for HED operations.
Returns:
Dataframe - a new dataframe after processing.
"""
if self.number_column_name in df.columns:
if self.overwrite is False:
raise ValueError("ExistingNumberColumn",
f"Column {self.number_column_name} already exists in event file.", "")
if self.match_value:
if self.match_value['column'] not in df.columns:
raise ValueError("MissingMatchColumn",
f"Column {self.match_value['column']} does not exist in event file.", "")
if self.match_value['value'] not in df[self.match_value['column']].tolist():
raise ValueError("MissingMatchValue",
f"Value {self.match_value['value']} does not exist in event file column"
f"{self.match_value['column']}.", "")
df_new = df.copy()
# df_new[self.number_column_name] = np.nan
# if self.match_value:
# filter = df[self.match_value['column']] == self.match_value['value']
# numbers = [*range(1, sum(filter)+1)]
# df_new.loc[filter, self.number_column_name] = numbers
# else:
# df_new[self.number_column_name] = df_new.index + 1
return df_new