I get TypeError: 'int' object is not iterable on the following code, why?
def temp_media(c, l):
c_ini = c
l_ini = l
res_vert = 0
res_horiz = 0
dim = dimensoes()
c_max = dim[0] // 2
l_max = dim[1]
for l in l_max:
for c in c_max:
res_vert = res_vert + calcula_temp(c, l)
res_horiz = res_horiz + calcula_temp(c, l)
return (((res_horiz / (c_max - c_ini)) + (res_vert / (l_max - l_ini))) / 2)
How can I fix this?
You need to use range (or xrange in python 2) in your for loops:
c_max = dim[0] // 2
l_max = dim[1]
for l in range(l_max):
for c in range(c_max):
Related
When substituting values into a SymPy sum, it doesn't seem to recognise that the variables are indexed, and simply factors out all the indexed variables, like so:
# Define variables.
z_tilde_i = sympy.IndexedBase('\\tilde{z}')
rho_i = sympy.IndexedBase('\\rho')
M = sympy.symbols('M')
n = sympy.symbols('n', integer = True)
i = sympy.Idx('i', n)
# Define equation M = sum(rho * deltaZ).
eq_total_mass = sympy.Eq(M, sympy.Sum(rho_i[i] * (z_tilde_i[i + 1] - z_tilde_i[i]), (i, 0, n - 1)))
# Try to substitute values.
print(eq_total_mass.rhs.subs(n, 3).doit())
>>> 3*(\tilde{z}[i + 1] - \tilde{z}[i])*\rho[i]
How to make the SymPy sum recognise the indexed variables?
For a workaround:
There is no need to define i as Idx:
>>> i = var('i')
>>> Sum(rho_i[i] * (z_tilde_i[i + 1] - z_tilde_i[i]), (i, 0, 1)).doit()
(-\tilde{z}[0] + \tilde{z}[1])*\rho[0] + (-\tilde{z}[1] + \tilde{z}[2])*\rho[1]
Or if you do, don't use the integer=True when defining n:
>>> n = var('n')
>>> i = sympy.Idx('i', n)
>>> Sum(rho_i[i] * (z_tilde_i[i + 1] - z_tilde_i[i]), (i, 0, 1)).doit()
(-\tilde{z}[0] + \tilde{z}[1])*\rho[0] + (-\tilde{z}[1] + \tilde{z}[2])*\rho[1]
Say, we have f(t) = v * t + A * sin(w * t). I call such functions "saw-like":
I want to solve saw(t) = C, that is, find a root of saw(t) - C (still "saw-like").
I tried writing down a ternary search for function abs(saw(t) - C) to find its minima. If we are lucky (or crafty), it would be the root. Unfortunately, my code does not always work: sometimes we get stuck in those places:
My code (python3):
def calculate(fun):
eps = 0.000000001
eps_l = 0.1
x = terns(fun, 0, 100000000000000)
t = terns(fun, 0, x)
cnt = 0
while fun(x) > eps:
t = x
x = terns(fun, 0, t)
if abs(t - x) < eps_l:
cnt += 1
# A sorry attempt pass some wrong value as a right one.
# Gets us out of an infinite loop at least.
if cnt == 10:
break
return t
def terns(f, l, r):
eps = 0.00000000001
while r - l > eps:
x_1 = l + (r - l) / 3
x_2 = r - (r - l) / 3
if f(x_1) < f(x_2):
r = x_2
else:
l = x_1
return (l + r) / 2
So, how is it done? Is using ternary search the right way?
My other idea was somehow sending the equation over to the net, passing it to Wolfram Alpha and fetching the answers. Yet, I don't how it's done, as I am not quite fluent at python.
How could this be done?
The Problem occurs in line 29:
It is a Type Error
I can't figure out where I went wrong with my parameters. It should assign every a[i][k] with a value but it just ends up with the following error message:
a[i][k].append(g * m[i] * dr[k]/d3)
TypeError: 'int' object is not subscriptable
Here the full code:
import numpy as np
from numpy import absolute
from numpy import power
r = [[1,1,1],[1,1,1],[0,0,0]]
v = [[0,0,0],[0,0,0],[0,0,0]]
a = [[0,0,0],[0,0,0],[0,0,0]]
m = [1,1,1]
O = -1
N = 3
def beschleunigung(O, N, m, r, a):
i = 0
k = 0
dr = [0,0,0]
d3 = 0
g = 1
for k in range(1,3):
a[i][k] = 0
for i in range(1,N):
if i != O:
for k in range(1,3):
a = (r[i][k])
b = (r[0][k])
dr[k] = a - b
d3 = np.power(np.absolute(dr),3)
for k in range(1,3):
a[i][k].append(g * m[i] * dr[k]/d3)
beschleunigung(O,N,m,r,a)
print(a[1])
When your code executes the line a = (r[i][k]), a becomes an integer, rather than a list of lists as it was in the input to this function. This causes your append to fail as you cannot append to an integer.
I expect that you intended to create another variable to use in your subtraction with b - make sure to use a name that is not already defined in your scope.
I want to detect and store outliers from a list and this is what I am doing
Code:
def outliers(y,thresh=3.5):
m = np.median(y)
abs_dev = np.abs(y - m)
left_mad = np.median(abs_dev[y <= m])
right_mad = np.median(abs_dev[y >= m])
y_mad = left_mad * np.ones(len(y))
y_mad[y > m] = right_mad
modified_z_score = 0.6745 * abs_dev / y_mad
modified_z_score[y == m] = 0
return modified_z_score > thresh
bids = [5000,5500,4500,1000,15000,5200,4900]
z = outliers(bids)
bidd = np.array(bids)
out_liers = bidd[z]
This gives results as:
out_liers = array([ 1000, 15000])
Is there a better way to do this, where I don't get the results in array but in a list?
Also please can someone explain me why we used
thresh=3.5
modified_z_score = 0.6745 * abs_dev / y_mad
This works:
def outliers_modified_z_score(ys, threshold=3.5):
ys_arr = np.array(ys)
median_y = np.median(ys_arr)
median_absolute_deviation_y = np.median(np.abs(ys_arr - median_y))
modified_z_scores = 0.6745 * (ys_arr - median_y) / median_absolute_deviation_y
return (ys_arr[np.abs(modified_z_scores) > threshold]).tolist()
That's because you are using numpy function. Default type used there is numpy.ndarray, which speeds up the computations. In the case you just need a list as output argument, use tolist() method.
z = outliers(bids)
bidd = np.array(bids)
out_liers = bidd[z].tolist()
Input code is:
# Input data:
S = pd.S = 2000 # Saturation flow
L = pd.L = 5 # Lost time
eb = pd.eb = 1000
wb = pd.wb = 600
sb = pd.sb = 400
nb = pd.nb = 500
# a) C_min = Minimum cycle length calculation
Y_eb = pd.Y_eb = eb / S
Y_wb = pd.Y_wb = wb / S
Y_sb = pd.Y_sb = sb / S
Y_nb = pd.Y_nb = nb / S
Y_eb_wb_sb_nb = [Y_eb,Y_wb,Y_sb,Y_nb]
Y_eb_wb_sb_nb
Output:
[0.5, 0.3, 0.2, 0.25]
Then
if Y_eb > Y_wb:
print(C_min = L / 1 - (Y_eb + Y_wb))
I want to:
Get maximum values from (Y_eb;Y_wb) and (Y_sb;Y_nb) and apply these values to formula:
C_min = L / (1- [max of (Y_eb;Y_wb)] + [max of (Y_sb;Y_nb)])
Use max built-in fuction:
C_min = L / (1- max(Y_eb,Y_wb) + max(Y_sb,Y_nb))
python has a built-in max function, that give the max of a list...
max(iterable, *[, key, default])
max(arg1, arg2, *args[, key])
"Return the largest item in an iterable or the largest of two or more
arguments"
https://docs.python.org/3/library/functions.html#max
Answer:
C_min = L / (1- max([Y_eb, Y_wb]) + max([Y_sb, Y_nb]))