How to call numpy solver to minimize a obj_func with constraints
0
I'm trying to solve a linear equation problem with constraints but I have no idea of how to call the solver.
I'm using a function that I wrote called covariancia but there's no problem with it, so I'll not post it here.
from funcs import covariancia
from math import sqrt
def main():
print("Iniciando Moneta...")
evo_val =
with open("evo_val.txt") as my_file:
evo_val = [line.split() for line in my_file]
#Montando array de Médias
medias =
for papel in evo_val:
media_atual = 0
for valor in papel:
media_atual += float(valor)
media_atual /= len(papel)
medias.append(media_atual)
#Calculating Covariance
co_x = co_y = len(evo_val)
co_var = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if (j < i):
co_var[i][j] = co_var[j][i]
else:
co_var[i][j] = covariancia(evo_val[i], evo_val[j], medias[i], medias[j])
#Calculating Correlation
co_rel = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if i == j:
co_rel[i][j] = 1
elif j < i:
co_rel[i][j] = co_rel[j][i]
else:
co_rel[i][j] = co_var[i][j] / (sqrt(co_var[i][i] * co_var[j][j]))
#Linear Solver
func_obj = [0.0 for i in range(co_x)]
DPRE = 0.0
RE = sum([func_obj[i]*medias[i] for i in range(len(evo_val))])
for i in range(co_x):
for j in range(co_x):
DPRE += func_obj[i]*func_obj[j]*co_var[i][j]
const = sum(func_obj) # must be equal to 1
What must I do? I need to minimize (DPRE/RE) with the constraints that sum(func_obj) must be equal to 1.
How can I call the solver? How can I tell the solver that my variables are in the array func_obj?
Thanks for the help!
python python-3.x numpy linear-programming solver
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
add a comment |
0
I'm trying to solve a linear equation problem with constraints but I have no idea of how to call the solver.
I'm using a function that I wrote called covariancia but there's no problem with it, so I'll not post it here.
from funcs import covariancia
from math import sqrt
def main():
print("Iniciando Moneta...")
evo_val =
with open("evo_val.txt") as my_file:
evo_val = [line.split() for line in my_file]
#Montando array de Médias
medias =
for papel in evo_val:
media_atual = 0
for valor in papel:
media_atual += float(valor)
media_atual /= len(papel)
medias.append(media_atual)
#Calculating Covariance
co_x = co_y = len(evo_val)
co_var = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if (j < i):
co_var[i][j] = co_var[j][i]
else:
co_var[i][j] = covariancia(evo_val[i], evo_val[j], medias[i], medias[j])
#Calculating Correlation
co_rel = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if i == j:
co_rel[i][j] = 1
elif j < i:
co_rel[i][j] = co_rel[j][i]
else:
co_rel[i][j] = co_var[i][j] / (sqrt(co_var[i][i] * co_var[j][j]))
#Linear Solver
func_obj = [0.0 for i in range(co_x)]
DPRE = 0.0
RE = sum([func_obj[i]*medias[i] for i in range(len(evo_val))])
for i in range(co_x):
for j in range(co_x):
DPRE += func_obj[i]*func_obj[j]*co_var[i][j]
const = sum(func_obj) # must be equal to 1
What must I do? I need to minimize (DPRE/RE) with the constraints that sum(func_obj) must be equal to 1.
How can I call the solver? How can I tell the solver that my variables are in the array func_obj?
Thanks for the help!
python python-3.x numpy linear-programming solver
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
Did you have a look at the documentation on NumPy minimization? This may be of help here...
– sophros
Nov 18 '18 at 15:27
@sophros Yes i did. The problem is i'm not used to work with optmizations and research problems, linear algs, etc... i don't know which func of the linalg should I use, i don't know how to tell the variables, the constraints. I didn't find and example that's close enough to my problem i guess.
– Thomas Leick
Nov 18 '18 at 16:32
add a comment |
0
0
0
I'm trying to solve a linear equation problem with constraints but I have no idea of how to call the solver.
I'm using a function that I wrote called covariancia but there's no problem with it, so I'll not post it here.
from funcs import covariancia
from math import sqrt
def main():
print("Iniciando Moneta...")
evo_val =
with open("evo_val.txt") as my_file:
evo_val = [line.split() for line in my_file]
#Montando array de Médias
medias =
for papel in evo_val:
media_atual = 0
for valor in papel:
media_atual += float(valor)
media_atual /= len(papel)
medias.append(media_atual)
#Calculating Covariance
co_x = co_y = len(evo_val)
co_var = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if (j < i):
co_var[i][j] = co_var[j][i]
else:
co_var[i][j] = covariancia(evo_val[i], evo_val[j], medias[i], medias[j])
#Calculating Correlation
co_rel = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if i == j:
co_rel[i][j] = 1
elif j < i:
co_rel[i][j] = co_rel[j][i]
else:
co_rel[i][j] = co_var[i][j] / (sqrt(co_var[i][i] * co_var[j][j]))
#Linear Solver
func_obj = [0.0 for i in range(co_x)]
DPRE = 0.0
RE = sum([func_obj[i]*medias[i] for i in range(len(evo_val))])
for i in range(co_x):
for j in range(co_x):
DPRE += func_obj[i]*func_obj[j]*co_var[i][j]
const = sum(func_obj) # must be equal to 1
What must I do? I need to minimize (DPRE/RE) with the constraints that sum(func_obj) must be equal to 1.
How can I call the solver? How can I tell the solver that my variables are in the array func_obj?
Thanks for the help!
python python-3.x numpy linear-programming solver
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
I'm trying to solve a linear equation problem with constraints but I have no idea of how to call the solver.
I'm using a function that I wrote called covariancia but there's no problem with it, so I'll not post it here.
from funcs import covariancia
from math import sqrt
def main():
print("Iniciando Moneta...")
evo_val =
with open("evo_val.txt") as my_file:
evo_val = [line.split() for line in my_file]
#Montando array de Médias
medias =
for papel in evo_val:
media_atual = 0
for valor in papel:
media_atual += float(valor)
media_atual /= len(papel)
medias.append(media_atual)
#Calculating Covariance
co_x = co_y = len(evo_val)
co_var = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if (j < i):
co_var[i][j] = co_var[j][i]
else:
co_var[i][j] = covariancia(evo_val[i], evo_val[j], medias[i], medias[j])
#Calculating Correlation
co_rel = [[0]*co_y for i in range(co_x)]
for i in range(len(evo_val)):
for j in range(len(evo_val)):
if i == j:
co_rel[i][j] = 1
elif j < i:
co_rel[i][j] = co_rel[j][i]
else:
co_rel[i][j] = co_var[i][j] / (sqrt(co_var[i][i] * co_var[j][j]))
#Linear Solver
func_obj = [0.0 for i in range(co_x)]
DPRE = 0.0
RE = sum([func_obj[i]*medias[i] for i in range(len(evo_val))])
for i in range(co_x):
for j in range(co_x):
DPRE += func_obj[i]*func_obj[j]*co_var[i][j]
const = sum(func_obj) # must be equal to 1
What must I do? I need to minimize (DPRE/RE) with the constraints that sum(func_obj) must be equal to 1.
How can I call the solver? How can I tell the solver that my variables are in the array func_obj?
Thanks for the help!
python python-3.x numpy linear-programming solver
python python-3.x numpy linear-programming solver
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
edited Nov 18 '18 at 15:22
Thomas Leick
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
asked Nov 18 '18 at 5:54
Thomas LeickThomas Leick
13
13
Did you have a look at the documentation on NumPy minimization? This may be of help here...
– sophros
Nov 18 '18 at 15:27
@sophros Yes i did. The problem is i'm not used to work with optmizations and research problems, linear algs, etc... i don't know which func of the linalg should I use, i don't know how to tell the variables, the constraints. I didn't find and example that's close enough to my problem i guess.
– Thomas Leick
Nov 18 '18 at 16:32
add a comment |
Did you have a look at the documentation on NumPy minimization? This may be of help here...
– sophros
Nov 18 '18 at 15:27
@sophros Yes i did. The problem is i'm not used to work with optmizations and research problems, linear algs, etc... i don't know which func of the linalg should I use, i don't know how to tell the variables, the constraints. I didn't find and example that's close enough to my problem i guess.
– Thomas Leick
Nov 18 '18 at 16:32
Did you have a look at the documentation on NumPy minimization? This may be of help here...
– sophros
Nov 18 '18 at 15:27
Did you have a look at the documentation on NumPy minimization? This may be of help here...
– sophros
Nov 18 '18 at 15:27
@sophros Yes i did. The problem is i'm not used to work with optmizations and research problems, linear algs, etc... i don't know which func of the linalg should I use, i don't know how to tell the variables, the constraints. I didn't find and example that's close enough to my problem i guess.
– Thomas Leick
Nov 18 '18 at 16:32
@sophros Yes i did. The problem is i'm not used to work with optmizations and research problems, linear algs, etc... i don't know which func of the linalg should I use, i don't know how to tell the variables, the constraints. I didn't find and example that's close enough to my problem i guess.
– Thomas Leick
Nov 18 '18 at 16:32
add a comment |
0
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Did you have a look at the documentation on NumPy minimization? This may be of help here...
– sophros
Nov 18 '18 at 15:27
@sophros Yes i did. The problem is i'm not used to work with optmizations and research problems, linear algs, etc... i don't know which func of the linalg should I use, i don't know how to tell the variables, the constraints. I didn't find and example that's close enough to my problem i guess.
– Thomas Leick
Nov 18 '18 at 16:32