Fix: Black does its job
This commit is contained in:
parent
02214b0f82
commit
d6bb61dc48
@ -1,9 +1,9 @@
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#!/usr/bin/env python
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# encoding: utf-8
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from .calculus import Expression#, Polynom, Fraction, random_str, txt, Equation
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from .calculus import Expression # , Polynom, Fraction, random_str, txt, Equation
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#Expression.set_render('tex')
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# Expression.set_render('tex')
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from .stat import Dataset, WeightedDataset
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from .geometry import random_pythagore
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@ -12,7 +12,13 @@ Expression
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"""
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from functools import partial
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from ..core import AssocialTree, Tree, compute, typing, TypingError
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from ..core.random import extract_rdleaf, extract_rv, random_generator, compute_leafs, replace_rdleaf
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from ..core.random import (
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extract_rdleaf,
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extract_rv,
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random_generator,
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compute_leafs,
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replace_rdleaf,
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)
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from ..core.MO import moify
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from .tokens import factory
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from .renders import renders
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@ -75,6 +81,7 @@ class Expression(object):
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>>> Expression.set_render('txt')
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"""
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from .tokens.token import Token
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Token.set_render(render)
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cls.RENDER = render
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@ -485,6 +492,7 @@ def extract_variable(leaf):
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except AttributeError:
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return None
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def replace(leaf, origin, dest):
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""" Recursively replace origin to dest in leaf """
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try:
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@ -497,6 +505,7 @@ def replace(leaf, origin, dest):
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replace_var = partial(replace, origin=origin, dest=dest)
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return leaf.tree.map_on_leaf(replace_var)
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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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@ -69,7 +69,7 @@ class Token(object):
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else:
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raise ValueError(f"Unknow render {self.RENDER}")
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#return renders[self.RENDER](self._mo)
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# return renders[self.RENDER](self._mo)
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@property
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def __txt__(self):
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@ -203,7 +203,6 @@ class Token(object):
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return self._get_soul() <= self._get_soul(other)
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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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@ -26,6 +26,7 @@ def moify(token):
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except MOError:
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return token
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@coroutine
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def moify_cor(target):
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""" Coroutine which try to convert a parsed token into an MO
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@ -101,7 +101,6 @@ class MO(ABC):
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raise NotImplementedError
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class Atom(MO):
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""" Base Math Object with only one component.
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@ -110,6 +110,7 @@ class MOstrPower(Molecule):
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'monome2'
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"""
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return f"monome{self.power}"
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def differentiate(self):
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""" differentiate a MOstrPower and get a tree
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@ -121,8 +122,10 @@ class MOstrPower(Molecule):
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> x^2
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"""
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if self._power > 2:
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return Tree('*', self.power, MOstrPower(self.variable, self._power._value-1))
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return Tree('*', self.power, MOstr(self.variable))
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return Tree(
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"*", self.power, MOstrPower(self.variable, self._power._value - 1)
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)
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return Tree("*", self.power, MOstr(self.variable))
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class MOMonomial(Molecule):
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@ -27,6 +27,7 @@ multiply_doc = """ Multiply MOs
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multiply = Dispatcher("multiply", doc=multiply_doc)
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def multiply_filter(left, right):
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""" Automatic multiply on MO
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@ -56,6 +57,7 @@ def multiply_filter(left, right):
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except TypeError:
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pass
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@multiply.register((MOnumber, MOFraction), MOstr)
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@special_case(multiply_filter)
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def moscalar_mostr(left, right):
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@ -102,7 +104,7 @@ def moscalar_mostrpower(left, right):
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>>> multiply(a, x)
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<MOstrPower x^4>
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"""
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#if left == 1:
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# if left == 1:
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# return right
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return MOMonomial(left, right)
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@ -5,7 +5,7 @@
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from random import randint
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def random_pythagore(v_min = 1, v_max = 10, nbr_format = lambda x : x) :
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def random_pythagore(v_min=1, v_max=10, nbr_format=lambda x: x):
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""" Generate a pythagore triplet
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:returns: (a,b,c) such that a^2 = b^2 + c^2
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@ -14,10 +14,11 @@ def random_pythagore(v_min = 1, v_max = 10, nbr_format = lambda x : x) :
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while u == v:
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u, v = randint(v_min, v_max), randint(v_min, v_max)
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u, v = max(u, v), min(u, v)
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triplet = (u**2+v**2, 2*u*v, u**2-v**2)
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triplet = (u ** 2 + v ** 2, 2 * u * v, u ** 2 - v ** 2)
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formated_triplet = [nbr_format(i) for i in triplet]
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return formated_triplet
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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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@ -1,4 +1,4 @@
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#/usr/bin/env python
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# /usr/bin/env python
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# -*- coding:Utf-8 -*-
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#
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@ -32,11 +32,17 @@ class Dataset(list):
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"""
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@classmethod
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def random(cls, length, data_name="Valeurs",
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distrib="gauss", rd_args=(0, 1),
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nbr_format=lambda x: round(x, 2),
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v_min=None, v_max=None,
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exact_mean=None):
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def random(
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cls,
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length,
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data_name="Valeurs",
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distrib="gauss",
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rd_args=(0, 1),
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nbr_format=lambda x: round(x, 2),
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v_min=None,
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v_max=None,
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exact_mean=None,
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):
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""" Generate a random list of value
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:param length: length of the dataset
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@ -47,11 +53,9 @@ class Dataset(list):
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:param v_max: maximum accepted value
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:param exact_mean: if set, the last generated number will be create in order that the computed mean is exacly equal to "exact_mean"
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"""
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data = random_generator(length,
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distrib, rd_args,
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nbr_format,
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v_min, v_max,
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exact_mean)
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data = random_generator(
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length, distrib, rd_args, nbr_format, v_min, v_max, exact_mean
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)
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return cls(data, data_name=data_name)
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@ -94,7 +98,7 @@ class Dataset(list):
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def deviation(self):
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""" Compute the deviation (not normalized) """
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mean = self.mean()
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return sum([(x - mean)**2 for x in self])
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return sum([(x - mean) ** 2 for x in self])
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@number_factory
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def variance(self):
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@ -120,7 +124,8 @@ class Dataset(list):
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self.quartile(1),
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self.quartile(2),
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self.quartile(3),
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max(self))
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max(self),
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)
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@number_factory
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def quartile(self, quartile=1):
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@ -173,18 +178,21 @@ class Dataset(list):
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""" Latex code to display dataset as a tabular """
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d_per_line = self.effectif_total() // nbr_lines
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d_last_line = self.effectif_total() % d_per_line
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splited_data = [self[x:x + d_per_line]
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for x in range(0, self.effectif_total(), d_per_line)]
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splited_data = [
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self[x : x + d_per_line]
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for x in range(0, self.effectif_total(), d_per_line)
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]
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# On ajoute les éléments manquant pour la dernière line
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if d_last_line:
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splited_data[-1] += [' '] * (d_per_line - d_last_line)
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splited_data[-1] += [" "] * (d_per_line - d_last_line)
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# Construction du tableau
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latex = "\\begin{{tabular}}{{|c|*{{{nbr_col}}}{{c|}}}} \n".format(
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nbr_col=d_per_line)
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nbr_col=d_per_line
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)
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latex += "\t\t \hline \n"
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d_lines = [' & '.join(map(str, l)) for l in splited_data]
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d_lines = [" & ".join(map(str, l)) for l in splited_data]
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latex += " \\\\ \n \\hline \n".join(d_lines)
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latex += " \\\\ \n \\hline \n"
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@ -1,4 +1,4 @@
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#/usr/bin/env python
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# /usr/bin/env python
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# -*- coding:Utf-8 -*-
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from functools import wraps
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@ -6,6 +6,7 @@ from functools import wraps
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def number_factory(fun):
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""" Decorator which format returned value """
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@wraps(fun)
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def wrapper(*args, **kwargs):
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ans = fun(*args, **kwargs)
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@ -16,6 +17,7 @@ def number_factory(fun):
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return round(ans, 2)
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except AttributeError:
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return ans
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return wrapper
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@ -1,14 +1,18 @@
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#/usr/bin/env python
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# /usr/bin/env python
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# -*- coding:Utf-8 -*-
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from random import randint, uniform, gauss, choice
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def random_generator(length,
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distrib=gauss, rd_args=(0, 1),
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nbr_format=lambda x: round(x, 2),
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v_min=None, v_max=None,
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exact_mean=None):
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def random_generator(
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length,
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distrib=gauss,
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rd_args=(0, 1),
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nbr_format=lambda x: round(x, 2),
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v_min=None,
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v_max=None,
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exact_mean=None,
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):
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""" Generate a random list of value
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:param length: length of the dataset
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@ -47,7 +51,8 @@ def random_generator(length,
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"gauss": gauss,
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"uniform": uniform,
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"randint": randint,
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"choice": choice}
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"choice": choice,
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}
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try:
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distrib(*rd_args)
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except TypeError:
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@ -67,11 +72,13 @@ def random_generator(length,
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last_v = nbr_format((length + 1) * exact_mean - sum(data))
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if not validate(last_v):
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raise ValueError(
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"Can't build the last value. Conflict between v_min/v_max and exact_mean")
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"Can't build the last value. Conflict between v_min/v_max and exact_mean"
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)
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data.append(last_v)
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return data
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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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@ -1,4 +1,4 @@
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#/usr/bin/env python
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# /usr/bin/env python
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# -*- coding:Utf-8 -*-
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"""
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@ -12,9 +12,11 @@ from .dataset import Dataset
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from itertools import chain
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from .number_tools import number_factory
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def flatten_list(l):
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return list(chain(*l))
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class WeightedDataset(dict):
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""" A weighted dataset with statistics and latex rendering methods
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@ -37,11 +39,8 @@ class WeightedDataset(dict):
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"""
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def __init__(
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self,
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datas=[],
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data_name="Valeurs",
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weights=[],
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weight_name="Effectifs"):
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self, datas=[], data_name="Valeurs", weights=[], weight_name="Effectifs"
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):
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"""
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Initiate the WeightedDataset
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"""
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@ -84,7 +83,7 @@ class WeightedDataset(dict):
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def deviation(self):
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""" Compute the deviation (not normalized) """
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mean = self.mean()
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return sum([v * (k - mean)**2 for (k, v) in self.items()])
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return sum([v * (k - mean) ** 2 for (k, v) in self.items()])
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@number_factory
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def variance(self):
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@ -109,11 +108,13 @@ class WeightedDataset(dict):
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(1, 3, 4, 5, 5)
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"""
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return (min(self.keys()),
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self.quartile(1),
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self.quartile(2),
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self.quartile(3),
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max(self.keys()))
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return (
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min(self.keys()),
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self.quartile(1),
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self.quartile(2),
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self.quartile(3),
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max(self.keys()),
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)
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@number_factory
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def quartile(self, quartile=1):
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@ -146,8 +147,9 @@ class WeightedDataset(dict):
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position = self.posi_quartile(quartile) - 1
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expanded_values = flatten_list([v * [k] for (k, v) in self.items()])
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if position.is_integer():
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return (expanded_values[int(position)] +
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expanded_values[int(position) + 1]) / 2
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return (
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expanded_values[int(position)] + expanded_values[int(position) + 1]
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) / 2
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else:
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return expanded_values[ceil(position)]
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@ -167,7 +169,8 @@ class WeightedDataset(dict):
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def tabular_latex(self):
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""" Latex code to display dataset as a tabular """
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latex = "\\begin{{tabular}}{{|c|*{{{nbr_col}}}{{c|}}}} \n".format(
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nbr_col=len(self.keys()))
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nbr_col=len(self.keys())
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)
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latex += "\t \hline \n"
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data_line = "\t {data_name} ".format(data_name=self.data_name)
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weight_line = "\t {weight_name} ".format(weight_name=self.weight_name)
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23
setup.py
23
setup.py
@ -6,17 +6,14 @@ except ImportError:
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from distutils.core import setup
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setup(
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name='mapytex',
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version='2.1',
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description='Computing like a student',
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author='Benjamin Bertrand',
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author_email='programming@opytex.org',
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url='http://git.opytex.org/lafrite/Mapytex',
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#packages=['mapytex'],
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name="mapytex",
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version="2.1",
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description="Computing like a student",
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author="Benjamin Bertrand",
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author_email="programming@opytex.org",
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url="http://git.opytex.org/lafrite/Mapytex",
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# packages=['mapytex'],
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packages=find_packages(),
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include_package_data = True,
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install_requires=[
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'multipledispatch',
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'tabulate',
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],
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)
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include_package_data=True,
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install_requires=["multipledispatch", "tabulate"],
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)
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Block a user