def test_function_1(empty_folders):
in_folder, out_folder, rep_folder = empty_folders
in_folder = in_folder.strpath
out_folder = out_folder.strpath
rep_folder = rep_folder.strpath
# Ass this folders are not parameters of the function, mock them.
with mock.patch('functions.OUTPUT_FOLDER', out_folder):
with mock.patch('functions.REPORTS_FOLDER', rep_folder):
function1()
def metBissecao(a, b):
iterations = 0
while abs(a - b) > 7e-6:
m = abs(a + b) / 2.0
print(
str(iterations) + ". M: " + str(m) + "\t a: " + str(a) + "\t b:" +
str(b))
if (f.function1(a) * f.function1(m)) < 0:
b = m
else:
a = m
iterations += 1
print("Total de iteracoes: " + str(iterations))
print("Melhor apoximacao: " + str(m))
return (str(iterations), str(m))
def test_function_1_2(empty_folders):
in_folder, out_folder, rep_folder = empty_folders
in_folder = in_folder.strpath
out_folder = out_folder.strpath
rep_folder = rep_folder.strpath
# With this mock imported constant
with mock.patch('functions.OUTPUT_FOLDER', out_folder):
# With this, patch arguments default values
# Python 2
# function2.func_defaults = (out_folder, in_folder)
# Python 3
function2.__defaults__ = (out_folder, rep_folder)
function1.__defaults__ = (out_folder, )
function1()
def metTangente(x):
iterations = 0
old_x = 0
while abs(old_x - x) > 7e-6:
old_x = x
x = (x - f.function1(x) / f.derived_function1(x))
print(str(iterations) + ". M: " + str(x))
iterations += 1
print("Total de iteracoes: " + str(iterations))
print("Melhor apoximacao: " + str(x))
return (str(iterations), str(x))
def metCorda(a, b):
iterations = 0
zero = (a + b) / 2
old_a = a
while abs(old_a - zero) > 7e-6:
old_a = a
zero = (a * f.function1(b) - b * f.function1(a)) / (f.function1(b) -
f.function1(a))
print(
str(iterations) + ". M: " + str(zero) + "\t a: " + str(a) +
"\t b:" + str(b))
if (f.function1(a) * f.function1(zero)) < 0:
b = zero
else:
a = zero
iterations += 1
print("Total de iteracoes: " + str(iterations))
print("Melhor apoximacao: " + str(zero))
return (str(iterations), str(zero))
from functions import function1, function2 function1() function2()
from __future__ import division
import numpy as np
from matplotlib import pyplot as plt
from functions import function1, taninv, trapezoid_integrate, trapezoid_integrate_for_loop
# Step 2
start = 0.0
stop = 5.0
num = 51 # to include the last element and avoid obo error
vector = np.linspace(start, stop, num) # calling x vector
values = function1(vector)
##########
# Step 3
plt.plot(vector, values, "bo")
plt.xlabel("x")
plt.ylabel("$f(x)$")
plt.title("""Plot of $f(x) = 1/(1+x^2) $""")
plt.show()
plt.close()
###########
# Step 4
taninv_calculated = np.array(taninv(
vector)[:, 0]) # remember that the quad function returns (integral, error)
taninv_actual = np.arctan(vector)
#with open("table.txt","w") as f:
viv_data = pd.read_csv(viv_file_path, usecols=['U_MPIO', 'VA1_ESTRATO', 'VB_ACU', 'VF_INTERNET'])
health_providers_data = pd.read_csv(health_providers_file, usecols=['depa_nombre', 'muni_nombre','nombre_prestador'])
#####################################################################################################
# Inicio del código
#####################################################################################################
state_code = int(states[i][0:2])
state_name = normalize(states[i][2:].upper())
#####################################################################################################
# Se van a encontrar las variables posibles en el archivo de 'Personas' y 'Viviendas'
#####################################################################################################
# s será la matriz de salida de tamaño (N°deMunicipios,26)
s = function1(people_data, viv_data)
#######################################################################################
# Ahora se va a calcular el numero de hospitales por km2 y el numero de hogares por km2
#######################################################################################
s[:,24:26] = function2(state_code, state_name, municipality_data, health_providers_data, municipality_area_data, houses_data)
# Redondeamos todos los resultados a dos decimales y se escriben como porcentaje, menos las ultimas dos filas
s[:,1:-8] = np.round(s[:,1:-8]*100,2)
s[:,-8:] = np.round(s[:,-8:],6)
# Se ajustan los codigos de cada municipio para el merge final
s[:,0] = s[:,0] + state_code*1000
#####################################################################################################
# Merging with the main file
#####################################################################################################
def test_three_items(self):
input = [1, 9, 9, 10, 10, 10, 10, 11]
output = [-7.75, .25, .25, 1.25, 1.25, 1.25, 1.25, 2.25]
self.assertEquals(output, function1(input))
def test_two_items(self):
self.assertEquals([-.5, .5], function1([0, 1]))
self.assertEquals([-2.5, 2.5], function1([3, 8]))
def test_one_item(self):
self.assertEquals([0], function1([0]))
self.assertEquals([0], function1([9]))
self.assertEquals([0], function1([-10]))
def test_blank_list(self):
self.assertEquals([], function1([]))
def evaluate(self, agent):
self.fitness = fun.function1(self.x, agent)
