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Dataset heritate from list

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This commit is contained in:
Benjamin Bertrand 2016-01-08 17:01:39 +03:00
parent 79f2fa3c9e
commit 33f49edc6e
1 changed files with 13 additions and 16 deletions
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29
pymath/stat/dataset.py
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@ -7,9 +7,9 @@
#
#
from math import sqrt, cos, ceil
from math import sqrt, ceil
class Dataset():
class Dataset(list):
""" Classe réprésentant un série statistique avec rendu latex """
def __init__(self, data = [], data_name = "Valeurs"):
@ -19,9 +19,9 @@ class Dataset():
:param data: values of the data set
:param data_name: name of the data set
"""
self.data = list(data)
list.__init__(self, data)
self.data_name = data_name
self_name = data_name
def add_data(self, data):
"""Add datas to the data set
@ -29,19 +29,16 @@ class Dataset():
:param data: datas
"""
try:
self.data += data
self += data
except TypeError:
self.data += [data]
self += [data]
def sort(self, *args, **kwrds):
""" Apply sort to data """
self.data.sort(*args, **kwrds)
def __len__(self):
return len(self.data)
self.sort(*args, **kwrds)
def sum(self):
return sum(self.data)
return sum(self)
def mean(self):
return self.sum()/len(self)
@ -49,10 +46,10 @@ class Dataset():
def deviation(self):
""" Compute the deviation (not normalized) """
mean = self.mean()
return sum([(x - mean)**2 for x in self.data])
return sum([(x - mean)**2 for x in self])
def variance(self):
return self.deviation()/len(self.data)
return self.deviation()/len(self)
def sd(self):
""" Compute the standard deviation """
@ -64,7 +61,7 @@ class Dataset():
:return: (min, Q1, Me, Q3, Max)
"""
return (min(self.data) , self.quartile(1) , self.quartile(2) , self.quartile(3), max(self.data))
return (min(self) , self.quartile(1) , self.quartile(2) , self.quartile(3), max(self))
def quartile(self, quartile = 1):
"""
@ -82,7 +79,7 @@ class Dataset():
"""
position = self.posi_quartile(quartile)[0]
# À vérifier...
return self.data[position]
return self[position]
def posi_quartile(self, quartile = 1):
@ -215,7 +212,7 @@ On a ainsi $Q_{q} = {val_q}$
"""
d_per_line = len(self) // nbr_lines
d_last_line = len(self) % d_per_line
splited_data = [self.data[x:x+d_per_line] for x in range(0, len(self.data), d_per_line)]
splited_data = [self[x:x+d_per_line] for x in range(0, len(self), d_per_line)]
# On ajoute les éléments manquant pour la dernière line
if d_last_line:
splited_data[-1] += [' ']*(d_per_line - d_last_line)