basic ploting for skills
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@ -19,7 +19,7 @@ def includegraphics(fig_ax, document_path="./", fig_path="fig/",
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"""
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try:
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fig, ax = fig_ax
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except TypeError:
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except (TypeError, ValueError):
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ax = fig_ax
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fig = ax.figure
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@ -18,6 +18,11 @@
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\Var{e["quest"] | radar_on("Competence") | includegraphics(document_path=directory, scale=0.6)}
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\Var{e["quest"] | radar_on("Domaine") | includegraphics(document_path=directory, scale=0.6)}
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\vfill
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\hspace{-2cm}
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\Var{e["quest"] | pies_skills_level("Competence") | includegraphics(document_path=directory, scale=0.3)}
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\vfill
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%#\Var{conn_df}
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%- if not conn_df.empty
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@ -31,10 +31,12 @@ texenv = jinja2.Environment(
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from .filters import includegraphics
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texenv.filters['includegraphics'] = includegraphics
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from notes_tools.tools.marks_plottings import radar_on, marks_hist, parallele_on
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from notes_tools.tools.marks_plottings import *
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texenv.filters['radar_on'] = radar_on
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texenv.filters['marks_hist'] = marks_hist
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texenv.filters['parallele_on'] = parallele_on
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texenv.filters['pie_skill_evaluation'] = pie_skill_evaluation
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texenv.filters['pies_skills_level'] = pies_skills_level
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def feed_template(target, datas, template):
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""" Get the template and feed it to create reports
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@ -2,10 +2,17 @@
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# encoding: utf-8
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from .plottings import radar_graph
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from .skills_tools import count_levels, count_skill_evaluation
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import matplotlib.pyplot as plt
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import pandas as pd
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import numpy as np
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__all__ = ["radar_on", "marks_hist", "parallele_on"]
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__all__ = ["radar_on",
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"pie_skill_evaluation",
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"pies_skills_level",
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"marks_hist",
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"parallele_on",
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]
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def radar_on(df, index, optimum = None):
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""" Plot the radar graph concerning index column of the df
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@ -26,6 +33,19 @@ def radar_on(df, index, optimum = None):
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fig, ax = radar_graph(labels, values, optimum)
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return fig, ax
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def pie_skill_evaluation(df, skill):
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""" Plot a pie plot with the repartition of skill evaluations
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"""
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ax = count_skill_evaluation(df, skill).plot.pie(autopct='%.0f')
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return ax
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def pies_skills_level(df, skill):
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""" Plot series of pies (one by different skill) with level repartition """
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levels_counts = count_levels(df, skill)
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fig, ax = plt.subplots(nrows=1, ncols=len(levels_counts), figsize=(16,3))
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plots = levels_counts.T.plot(ax=ax ,kind="pie", subplots=True, legend=False)
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return fig, ax
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def marks_hist(df):
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""" Return axe for the histogramme of the dataframe
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