69 lines
1.7 KiB
Python
69 lines
1.7 KiB
Python
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#! /usr/bin/env python
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# -*- coding: utf-8 -*-
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# vim:fenc=utf-8
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#
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# Copyright © 2017 lafrite <lafrite@Poivre>
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#
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# Distributed under terms of the MIT license.
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"""
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Manipulating rating scale of an evaluation.
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Those functions are made to be applied over eval_df
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"""
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from .df_marks_manip import round_half_point, compute_mark_barem
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__all__ = []
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def new_scale_min(x):
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""" Change the scale by selecting min between scale and mark """
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return min(x["Mark_old"], x["Bareme"])
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def new_scale_proportionnal(x):
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""" Changing the scale proportionally """
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return round_half_point(x["Mark_old"] * x["Bareme"] / x["Bareme_old"])
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def tranform_scale(eval_df, new_scale, method):
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""" Change the rating scale of the exam
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It backups Bareme, Mark, Mark_barem columns adding "_old". The backup is done once then it is ignored.
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It changes Bareme value to new_scale, applies method to marks and remake mark_bareme
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:param eval_df: dataframe on evaluations
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:param new_scale: replacement scale value
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:param method: "min", "prop" or a function on eval_df rows
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:returns: the transformed eval_df
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"""
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for c in ["Bareme", "Mark", "Mark_barem"]:
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try:
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eval_df[c+"_old"]
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except KeyError:
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eval_df[c+"_old"] = eval_df[c]
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eval_df["Bareme"] = new_scale
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TRANFS = {"min": new_scale_min,
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"prop": new_scale_proportionnal,
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}
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try:
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t = TRANFS[method]
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except KeyError:
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eval_df["Mark"] = eval_df.apply(method)
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else:
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eval_df["Mark"] = eval_df.apply(t, axis=1)
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eval_df["Mark_barem"] = compute_mark_barem(eval_df)
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return eval_df
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# -----------------------------
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# Reglages pour 'vim'
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# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
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# cursor: 16 del
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