Change organisation in term report to use POV

notes_tools/tools/plottings.py

@@ -80,8 +80,8 @@ def my_autopct(values):
 
 def pivot_table_to_pie(pv, pies_per_lines = 3):
     nbr_pies = len(pv.columns)
-    nbr_cols = min(pies_per_lines, nbr_pies)
-    nbr_rows = nbr_pies // nbr_cols 
+    nbr_cols = pies_per_lines
+    nbr_rows = nbr_pies // nbr_cols + 1
     f, axs = plt.subplots(nbr_rows, nbr_cols, figsize = (4*nbr_cols,4*nbr_rows))
     for (c, ax) in zip(pv, axs.flatten()):
         datas = pv[c]

notes_tools/tools/term_tools.py

@@ -3,35 +3,183 @@
 
 import pandas as pd
 import numpy as np
+from notes_tools.tools.marks_plottings import (pie_pivot_table,
+        parallel_on,
+        radar_on,
+        )
+
+__all__ = ["students_pov", "class_pov"]
+
+class Student(object):
+
+    """ 
+    Informations on a student which can be use inside template.
+    
+    Those informations should not be modify or use for compute analysis otherwise they won't be spread over other POV.
+    """
+
+    def __init__(self, quest_df, exo_df, eval_df):
+        """ 
+        Description of a student from quest, exo and eval
+
+        """
+        if len(quest_df["Eleve"].unique()) != 1:
+            raise ValueError("Can't initiate Student: quest_df contains different student names")
+        elif len(exo_df["Eleve"].unique()) != 1:
+            raise ValueError("Can't initiate Student: exo_df contains different student names")
+        elif len(eval_df["Eleve"].unique()) != 1:
+            raise ValueError("Can't initiate Student: eval_df contains different student names")
+        elif quest_df["Eleve"].iloc[0] != exo_df["Eleve"].iloc[0] or \
+                quest_df["Eleve"].iloc[0] != eval_df["Eleve"].iloc[0]:
+            raise ValueError("Can't initiate Student: dfs contains different student names")
+
+        self.name = quest_df["Eleve"].iloc[0]
+
+        self.quest_df = quest_df
+        self.exo_df = exo_df
+        self.eval_df = eval_df
+
+    @property
+    def marks_tabular(self):
+        """ Latex tabular with all of his marks of the term """
+        try:
+            self._marks_tabular
+        except AttributeError:
+            self._marks_tabular = self.eval_df[["Nom", "Mark_barem"]].to_latex()
+        return self._marks_tabular
+
+    @property
+    def pies_on_competence(self):
+        """ Pies chart on competences """
+        try:
+            self._pies_on_competence
+        except AttributeError:
+            self._pies_on_competence = pie_pivot_table(self.quest_df,
+                    index = "Level",
+                    columns = "Competence",
+                    values = "Eleve",
+                    aggfunc = len,
+                    fill_value = 0,
+                    )
+        return self._pies_on_competence
+
+    @property
+    def pies_on_domaine(self):
+        """ Pies chart on domaines """
+        try:
+            self._pies_on_domaine
+        except AttributeError:
+            self._pies_on_domaine = pie_pivot_table(self.quest_df,
+                    index = "Level",
+                    columns = "Domaine",
+                    values = "Eleve",
+                    aggfunc = len,
+                    fill_value = 0,
+                    )
+        return self._pies_on_domaine
+
+    @property
+    def radar_on_competence(self):
+        """ Radar plot on competence """
+        try:
+            self._radar_on_competence
+        except AttributeError:
+            self._radar_on_competence = radar_on(self.quest_df,
+                    "Competence")
+        return self._radar_on_competence
+
+    @property
+    def radar_on_domaine(self):
+        """ Radar plot on domaine """
+        try:
+            self._radar_on_domaine
+        except AttributeError:
+            self._radar_on_domaine = radar_on(self.quest_df,
+                    "Domaine")
+        return self._radar_on_domaine
 
 
-def select(quest_df, exo_df, eval_df, term):
-    """ Return quest, exo and eval rows which correspond to evalname
+    def parallel_on_evals(self, classe_evals):
+        """ Parallel coordinate plot of the class with student line highlight """
+        return parallel_on(classe_evals, "Nom", self.name)
+
+class Classe(object):
+
+    """ 
+    Informations on a class which can be use inside template.
+    
+    Those informations should not be modify or use for compute analysis otherwise they won't be spread over other POV.
+    """
+
+    def __init__(self, quest_df, exo_df, eval_df):
+        """ Init of a class from quest, exo and eval """
+        self.quest_df = quest_df
+        self.exo_df = exo_df
+        self.eval_df = eval_df
+
+    @property
+    def evals_tabular(self):
+        """ Summary of all evaluations for all students """
+        try:
+            self._evals_tabular
+        except AttributeError:
+            self._evals_tabular = pd.pivot_table(self.eval_df,
+                    index = "Eleve",
+                    columns = "Nom", 
+                    values = "Mark_barem",
+                    aggfunc = lambda x: " ".join(x)).to_latex()
+        return self._evals_tabular
+
+
+    @property
+    def parallel_on_evals(self):
+        """ Parallel coordinate plot of the class """
+        return parallel_on(self.eval_df, "Nom")
+
+    @property
+    def pies_eff_pts_on_competence(self):
+        """ Pie charts on competence with repartition of evaluated times and attributed points """
+        return pie_pivot_table(self.quest_df,
+                index = "Competence",
+                #columns = "Level",
+                values = "Bareme",
+                aggfunc=[len,np.sum],
+                fill_value=0)
+
+    @property
+    def pies_eff_pts_on_domaine(self):
+        """ Pie charts on domaine with repartition of evaluated times and attributed points """
+        return pie_pivot_table(self.quest_df,
+                index = "Domaine",
+                #columns = "Level",
+                values = "Bareme",
+                aggfunc=[len,np.sum],
+                fill_value=0)
+
+def select(quest_df, exo_df, eval_df, index, value):
+    """ Return quest, exo and eval rows which correspond index == value
 
     :param quest_df: TODO
     :param exo_df: TODO
     :param eval_df: TODO
 
     """
-    qu = quest_df[quest_df["Trimestre"] == term]
-    exo = exo_df[exo_df["Trimestre"] == term]
-    ev = eval_df[eval_df["Trimestre"] == term]
+    qu = quest_df[quest_df[index] == value]
+    exo = exo_df[exo_df[index] == value]
+    ev = eval_df[eval_df[index] == value]
     return qu, exo, ev
 
-
 def students_pov(quest_df, exo_df, eval_df):
     es = []
     for e in eval_df["Eleve"].unique():
-        eleve = {"Nom":e}
-        e_quest = quest_df[quest_df["Eleve"] == e]
-        eleve["quest"] = e_quest
-        e_exo = exo_df[exo_df["Eleve"] == e]
-        eleve["exo"] = e_exo
-        e_eval = eval_df[eval_df["Eleve"] == e]
-        eleve["eval"] = e_eval
+        d = select(quest_df, exo_df, eval_df, "Eleve", e)
+        eleve = Student(*d)
         es.append(eleve)
     return es
 
+def class_pov(quest_df, exo_df, eval_df):
+    return Classe(quest_df, exo_df, eval_df)
+
 
 # -----------------------------
 # Reglages pour 'vim'