Thank you very much everyone who helped answer. These all work as should and have been appendable. As no demonstrated below.
I am wanting to print working out of multiplication and addition.
import numpy as np
# [x, w] including bias
X = [[0.5, 0.15], [0.1, -0.3], [1, 0]]
in_str = 'in = '
for input in X:
substr = '('+str(input[0])+' x '+str(input[1])+') + '
in_str += substr
in_str = in_str[:-3]
print(in_str)
calcs = [x * y for x, y in X]
in_str = ' = '
for c in calcs:
substr = '('+str(c)+') + '
in_str += substr
in_str = in_str[:-3]
print(in_str)
ans = sum([x * y for x, y in X])
print(' = ' + str(ans))
Output:
in = (0.5 x 0.15) + (0.1 x -0.3) + (1 x 0)
= (0.075) + (-0.03) + (0)
= 0.045
Use list comprehension:
ans=sum([x*y for x,y in X])
If I understand your question correctly, You need value of product of elements in each sub list appended to a final list and sum of all elements in final list. Please find the below code. Traditional way
multiplier = 1
multiplier_list = []
final_sum = 0
for each_list in X:
for i in range(len(each_list)):
multiplier = multiplier * each_list[i]
#multiplier_list.append(multiplier) #If you need final list
final_sum = final_sum + multiplier
multiplier = 1
#print(multiplier_list)
print(final_sum)
X = [[0.5, 0.15], [0.1, -0.3], [1, 0]] # INPUT HERE
print(f"in X = {X}")
output =""
ans = 0
for input in X:
mul=0
mul = input[0]*input[1]
print(f"{input[0]} x {input[1]} = {mul}")
ans+=mul
output = output+f"{mul} + "
output = output[:-2]
output = output+f" = {ans}"
print(output)
Related
list = [[159.2213, 222.2223, 101.2122]
[359.2222, 22.2210, 301.2144]]
if list[1][0] < list[0][0]:
avg = (list[1][0] + list[0][0] - 200)/2
else:
avg = (list[1][0] + list[0][0] + 200)/2
Hello! I want to do this for every column and output the results in another list.
Fix
You may loop iterate the number of cols there is
values = [[159.2213, 222.2223, 101.2122], [359.2222, 22.2210, 301.2144]]
avgs = []
for idx_col in range(len(values[0])):
if values[1][idx_col] < values[0][idx_col]:
avg = (values[1][idx_col] + values[0][idx_col] - 200) / 2
else:
avg = (values[1][idx_col] + values[0][idx_col] + 200) / 2
avgs.append(avg)
Simplify
You can use zip to iterate on both rows at a time, and simplify the if/else condition
avgs = []
for first_row, second_row in zip(*values):
factor = -1 if second_row < first_row else 1
avgs.append((first_row + second_row + (200 * factor)) / 2)
Best with numpy
Easy syntax and best performance
import numpy as np
values = np.array(values)
res = values.sum(axis=0) / 2
res += np.where(values[1] < values[0], -100, 100)
A list comprehension would look like this:
avg = [(x + y + (200 if x <= y else -200)) / 2 for x, y in zip(*lst)]
Arguably easier if you use numpy:
arr = np.array(lst)
avg = 0.5 * (arr.sum(axis=0) + np.copysign(200, np.diff(arr, axis=0)))
lis = [[159.2213, 222.2223, 101.2122],
[359.2222, 22.2210, 301.2144]]
res = []
for i in range(len(lis[0])):
if lis[1][i] < lis[0][i]:
res.append((lis[1][i] + lis[0][i] - 200)/2)
else:
res.append((lis[1][i] + lis[0][i] + 200)/2)
This should work, however using numpy would be a better solution for these kind of problems.
You can do it like this:
list = [[159.2213, 222.2223, 101.2122]
[359.2222, 22.2210, 301.2144]]
results = []
for x,y in zip(list[0],list[1]):
if y < x:
avg = (y + x - 200)/2
else:
avg = (y + x + 200)/2
results.append(avg)
height = int(input("Enter the height of the triangle: \n"))
array = [1]
for ch in range(height):
print((str(array)[1:-1]))
newarray = []
newarray.append(array[0])
for ch in range(len(array) - 1):
(newarray.append(array[ch] + array[ch+1]))
str(newarray.append(array[-1]))[1:-1]
array = (newarray)
Use str.join before printing instead of str(array) and list comprehension to convert ints to strings ( or you can append strings to list initially), see example below:
array = [1, 2, 3]
print(str(array))
print(''.join([str(item) for item in array]))
Add this t = t.replace(',', ' '), This will replace your ',' into ' ' (spaces).
height = int(input("Enter the height of the triangle: \n"))
array = [1]
for ch in range(height):
t = (str(array)[1:-1])
t = t.replace(',', ' ')
print(t)
newarray = []
newarray.append(array[0])
for ch in range(len(array) - 1):
(newarray.append(array[ch] + array[ch+1]))
str(newarray.append(array[-1]))[1:-1]
array = (newarray)
I'm fairly new to this but will try and be as clear as possible.
Essentially I have 5 different lists of lists. 4 are imported from txt files and the 5th is a merger of the 4. Each inner list contains a value at index position 3. My objective is to maximize the sum by picking appropriately.
I also have a couple constraints:
The sum of the values at index 6 position can't exceed 50000
I pick 2 items from set C, 3 from set W, 2 from set D, 1 from set G, and 1 from set U (the combined) and I can't pick the same item for each set. Ie. each pick in W has to be different.
My code is below. I'm having trouble in that the optimizer just spits out my initial list of picks. Looking at the data though, I know for sure there are better solutions. I read that the issue may be related to late binding but I'm not sure if that's right and if it is, not sure how to update to fix error either. Appreciate any help. Thanks!
Read: Scipy.optimize.minimize SLSQP with linear constraints fails
import numpy as np
from scipy.optimize import minimize
C = open('C.txt','r').read().splitlines()
W = open('W.txt','r').read().splitlines()
D = open('D.txt','r').read().splitlines()
G = open('G.txt','r').read().splitlines()
def splitdata(file):
for index,line in enumerate(file):
file[index] = line.split('\t')
return(file)
def objective(x, sign=-1.0):
x = list(map(int, x))
pos = 3
Cvalue = float(C[x[0]][pos]) + float(C[x[1]][pos])
Wvalue = float(W[x[2]][pos]) + float(W[x[3]][pos]) + float(W[x[4]][pos])
Dvalue = float(D[x[5]][pos]) + float(D[x[6]][pos])
Gvalue = float(G[x[7]][pos])
Uvalue = float(U[x[8]][pos])
grand_value = sign*(Cvalue + Wvalue + Dvalue + Gvalue + Uvalue)
#print(grand_value)
return grand_value
def constraint_cost(x):
x = list(map(int, x))
pos = 6
Ccost = int(C[x[0]][pos]) + int(C[x[1]][pos])
Wcost = int(W[x[2]][pos]) + int(W[x[3]][pos]) + int(W[x[4]][pos])
Dcost = int(D[x[5]][pos]) + int(D[x[6]][pos])
Gcost = int(G[x[7]][pos])
Ucost = int(U[x[8]][pos])
grand_cost = 50000 - (Ccost + Wcost + Dcost + Gcost + Ucost)
#print(grand_cost)
return grand_cost
def constraint_C(x):
if x[0] == x[1]:
return 0
else:
return 1
def constraint_W(x):
if x[2] == x[3] or x[2] == x[4] or x[3] == x[4]:
return 0
else:
return 1
def constraint_D(x):
if x[5] == init[6]:
return 0
else:
return 1
con1 = {'type':'ineq','fun':constraint_cost}
con2 = {'type':'ineq','fun':constraint_C}
con3 = {'type':'ineq','fun':constraint_W}
con4 = {'type':'ineq','fun':constraint_D}
con = [con1, con2, con3, con4]
c0 = [0,1]
w0 = [0,1,2]
d0 = [0,1]
g0 = [0]
u0 = [0]
init = c0+w0+d0+g0+u0
C = splitdata(C)
W = splitdata(W)
D = splitdata(D)
G = splitdata(G)
U = C + W + D + G
sol = minimize(objective, init, method='SLSQP',constraints=con)
print(sol)
I have this python script to generate x,y,z lists and u,v,w lists such that u[i],v[i],w[i] is the gradient vector for point x[i],y[i],z[i].
It doesn't seem to be getting the right values. Does anyone know whats wrong?
from math import *
def coordinates(lst, f, gradx, grady, gradz):
lst = lst[1:-1].split(",")
lst = [float(x.strip()) for x in lst]
xlst = []
ylst = []
zlst = []
ulst = []
vlst = []
wlst = []
for x in lst:
for y in lst:
xlst.append(str(x))
ylst.append(str(y))
zlst.append(str(f(x,y)))
ulst.append(str(gradx(x,y)))
vlst.append(str(grady(x,y)))
wlst.append(str(gradz(x,y)))
string = "xlst=[" + ",".join(xlst) + "]\n" + \
"ylst=[" + ",".join(ylst) + "]\n" + \
"zlst=[" + ",".join(zlst) + "]\n" + \
"ulst=[" + ",".join(ulst) + "]\n" + \
"vlst=[" + ",".join(vlst) + "]\n" + \
"wlst=[" + ",".join(wlst) + "]\n"
return string
lst = "{0, 2, 4, 6, 8, 10}"
# get function in the form f(x,y)=z or here its y^2 - x^2 - z = 0
f = lambda x,y: y**2 - x**2
# get the three gradient functions (df/dx, df/dy, df/dz)
gx = lambda x,y: -2*x
gy = lambda x,y: 2*y
gz = lambda x,y: -1
c = coordinates(lst, f, gx, gy, gz)
print c
I want to apply the following function to multiple instances of a, b, c but it seems I can't apply this function to a list. The goal is to compute a few inequalities and finally plug them into a new z = ax + bx equation in order to find the lowest or highest ordered pair.
This is a cleaner code that omits the use of lists:
xMin,yMin = 0,0
a,b,c = 2,-3,12
enter code here
def FindVar(object):
x = (-b*yMin)/a + c/a
y = (-a*xMin)/b + c/b
print '(', FindVar.x, ',', yMin, ')'
print '(', xMin, ',', FindVar.y, ')'
This is a longer code that uses lists a bit more sloppily:
xMin = 0
yMin = 0
def i1():
a,b,c = 2,-3,12
#Create and append l1
global l1
l1 = []
l1.extend((a,b,c))
#Find X,Y
y = (-a*xMin)/b + (c/b)
x = (-b*yMin)/a + c/a
#Add to list
pair = []
pair.append((xMin,y))
pair.append((x,yMin))
print '%sx + %sy = %s' % (a,b,c)
print 'RETURNS'
print pair[0], z1
print pair[1], z2
def i2():
a,b,c = 1,1,5
#Create and append l2
global l2
l2 = []
l2.extend((a,b,c))
#Find X,Y
y = (-a*xMin)/b + c/b
x = (-b*yMin)/a + c/a
#Add to list
pair = []
pair.append((xMin,y))
pair.append((x,yMin))
print '%sx + %sy = %s' % (a,b,c)
print 'RETURNS'
print pair[0], z1
print pair[1], z2
So with the second bit of code I end up with 4 list items, each of which should be applied to a final equation, z = ax + by where a and b are independent from other functions.
EDIT: The purpose is to take an equation like "z = 2x + 7y" and subject it to the rules:
2x - 3y ≤ 12,
x + y ≤ 5,
3x + 4y ≥ 24,
x ≥ 0,
y ≥ 0.
I take these equations and put them into a list so that a,b,c = [2,-3,12],[1,1,5],[3,4,24] (where a = 2,1,3, b = -3,1,4, and c = 12,5,24). Then I can find (x,y) according to each of the three instances and plug each of those ordered pairs into my initial "z = 2x + 7y". The point of all of this is to take sets of data and find which set is the most efficient.
z1 and z2 were used in a prior version of the code to apply the "z=2x+7y" to the first and second ordered pairs of the first equation.
EDIT 2:
This is the much cleaner code I came up with.
xMin = 0
yMin = 0
a = [10,11,1]
b = [7,-8,1]
c = [200,63,42]
def findxy(a,b,c):
#Finds x,y for ax+by=c
x = (-b*yMin)/a + c/a
y = (-a*xMin)/b + c/b
#The results, followed by the z function "z = 15x + 15y"
if x >= xMin:
print '(%s, %s)' % (x,yMin), 15 * x + 15 * yMin
if y >= yMin:
print '(%s, %s)' % (xMin,y), 15 * xMin + 15 * y
map(findxy,a,b,c)
Results in
(20, 0) 300
(0, 28) 420
(5, 0) 75
(42, 0) 630
(0, 42) 630
Thanks!
To apply a function to each object in a list you can use the built in function map.
The list you pass to map can consist of primitives, class instances, tuples or lists.