FEat: add comments
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@ -6,7 +6,9 @@ import numpy as np
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from math import ceil, floor
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from math import ceil, floor
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from .config import COLUMNS, VALIDSCORE
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from .config import COLUMNS, VALIDSCORE
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# Values manipulations
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"""
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Functions for manipulate score dataframes
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"""
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def round_half_point(val):
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def round_half_point(val):
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@ -25,6 +27,7 @@ def score_to_mark(x):
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otherwise it copies the score
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otherwise it copies the score
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:param x: dictionnary with COLUMNS["is_leveled"], COLUMNS["score"] and COLUMNS["score_rate"] keys
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:param x: dictionnary with COLUMNS["is_leveled"], COLUMNS["score"] and COLUMNS["score_rate"] keys
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:return: the mark
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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@ -43,7 +46,9 @@ def score_to_mark(x):
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if x[COLUMNS["is_leveled"]]:
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if x[COLUMNS["is_leveled"]]:
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if x[COLUMNS["score"]] not in [0, 1, 2, 3]:
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if x[COLUMNS["score"]] not in [0, 1, 2, 3]:
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raise ValueError(f"The evaluation is out of range: {x[COLUMNS['score']]} at {x}")
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raise ValueError(
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f"The evaluation is out of range: {x[COLUMNS['score']]} at {x}"
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)
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return round_half_point(x[COLUMNS["score"]] * x[COLUMNS["score_rate"]] / 3)
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return round_half_point(x[COLUMNS["score"]] * x[COLUMNS["score_rate"]] / 3)
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if x[COLUMNS["score"]] > x[COLUMNS["score_rate"]]:
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if x[COLUMNS["score"]] > x[COLUMNS["score_rate"]]:
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@ -57,6 +62,7 @@ def score_to_level(x):
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"""Compute the level (".",0,1,2,3).
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"""Compute the level (".",0,1,2,3).
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:param x: dictionnary with COLUMNS["is_leveled"], COLUMNS["score"] and COLUMNS["score_rate"] keys
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:param x: dictionnary with COLUMNS["is_leveled"], COLUMNS["score"] and COLUMNS["score_rate"] keys
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:return: the level
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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@ -91,7 +97,9 @@ def score_to_level(x):
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def compute_mark(df):
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def compute_mark(df):
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""" Add Mark column to df
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"""Compute the mark for the dataframe
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apply score_to_mark to each row
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:param df: DataFrame with COLUMNS["score"], COLUMNS["is_leveled"] and COLUMNS["score_rate"] columns.
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:param df: DataFrame with COLUMNS["score"], COLUMNS["is_leveled"] and COLUMNS["score_rate"] columns.
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@ -122,9 +130,12 @@ def compute_mark(df):
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def compute_level(df):
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def compute_level(df):
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""" Add Mark column to df
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"""Compute level for the dataframe
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Applies score_to_level to each row
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:param df: DataFrame with COLUMNS["score"], COLUMNS["is_leveled"] and COLUMNS["score_rate"] columns.
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:param df: DataFrame with COLUMNS["score"], COLUMNS["is_leveled"] and COLUMNS["score_rate"] columns.
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:return: Columns with level
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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@ -156,6 +167,7 @@ def compute_normalized(df):
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"""Compute the normalized mark (Mark / score_rate)
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"""Compute the normalized mark (Mark / score_rate)
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:param df: DataFrame with "Mark" and COLUMNS["score_rate"] columns
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:param df: DataFrame with "Mark" and COLUMNS["score_rate"] columns
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:return: column with normalized mark
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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>>> d = {"Eleve":["E1"]*6 + ["E2"]*6,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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... COLUMNS["score_rate"]:[1]*2+[2]*2+[2]*2 + [1]*2+[2]*2+[2]*2,
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@ -188,6 +200,8 @@ def compute_normalized(df):
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def pp_q_scores(df):
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def pp_q_scores(df):
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"""Postprocessing questions scores dataframe
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"""Postprocessing questions scores dataframe
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Add 3 columns: mark, level and normalized
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:param df: questions-scores dataframe
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:param df: questions-scores dataframe
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:return: same data frame with mark, level and normalize columns
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:return: same data frame with mark, level and normalize columns
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"""
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"""
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