Related
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'm a new learner of python programming. Recently I'm trying to write a "tool" program of "dynamic programming" algorithm. However, the last part of my programe -- a while loop, failed to loop. the code is like
import numpy as np
beta, rho, B, M = 0.5, 0.9, 10, 5
S = range(B + M + 1) # State space = 0,...,B + M
Z = range(B + 1) # Shock space = 0,...,B
def U(c):
"Utility function."
return c**beta
def phi(z):
"Probability mass function, uniform distribution."
return 1.0 / len(Z) if 0 <= z <= B else 0
def Gamma(x):
"The correspondence of feasible actions."
return range(min(x, M) + 1)
def T(v):
"""An implementation of the Bellman operator.
Parameters: v is a sequence representing a function on S.
Returns: Tv, a list."""
Tv = []
for x in S:
# Compute the value of the objective function for each
# a in Gamma(x), and store the result in vals (n*m matrix)
vals = []
for a in Gamma(x):
y = U(x - a) + rho * sum(v[a + z]*phi(z) for z in Z)
# the place v comes into play, v is array for each state
vals.append(y)
# Store the maximum reward for this x in the list Tv
Tv.append(max(vals))
return Tv
# create initial value
def v_init():
v = []
for i in S:
val = []
for j in Gamma(i):
# deterministic
y = U(i-j)
val.append(y)
v.append(max(val))
return v
# Create an instance of value function
v = v_init()
# parameters
max_iter = 10000
tol = 0.0001
num_iter = 0
diff = 1.0
N = len(S)
# value iteration
value = np.empty([max_iter,N])
while (diff>=tol and num_iter<max_iter ):
v = T(v)
value[num_iter] = v
diff = np.abs(value[-1] - value[-2]).max()
num_iter = num_iter + 1
As you can see, the while loop at the bottom is used to iterate over "value function" and find the right answer. However, the while fails to loop, and just return num_iter=1. As for I know, the while loop "repeats a sequence of statements until some condition becomes false", clearly, this condition will not be satisfied until the diff converge to near 0
The major part of code works just fine, as far as I use the following for loop
value = np.empty([num_iter,N])
for x in range(num_iter):
v = T(v)
value[x] = v
diff = np.abs(value[-1] - value[-2]).max()
print(diff)
You define value as np.empty(...). That means that it is composed completely of zeros. The difference, therefore, between the last element and the second-to-last element will be zero. 0 is not >= 0.0001, so that expression will be False. Therefore, your loop breaks.
Write a function that accepts 3 numbers and calculates the average of the 3 numbers and raises the average to the second power (returns the average squared).
Write a loop that finds 3 random uniform numbers (0 to 1); sends the 3 numbers to the function and stops the loop when the value of the function is greater than 0.5625
I tried to figure out this 2 things but I am confused a little bit.
import random
a = random.random ()
b = random.random ()
c = random.random ()
def avenum(x1,x2,x3): # the average of the 3 numbers
z = (x1+x2+x3)/3.0
return z
y = avenum(a,b,c)
print 'the average of the 3 numbers = ',y
def avesec(x1,x2,x3): # the average of the second power
d = ((x1**2)+(x2**2)+(x3**2))/3.0
return d
y1 = avesec(a,b,c)
print 'the average of the second power = ',y1
The first question:
Write a function that accepts 3 numbers and calculates the average of the 3 numbers and raises the average to the second power (returns the average squared).
def square_of_average(x1, x2, x3):
z = (x1 + x2 + x3) / 3
return z ** 2 # This returns the square of the average
Your second question:
Write a loop that finds 3 random uniform numbers (0 to 1); sends the 3 numbers to the function and stops the loop when the value of the function is greater than 0.5625.
Assuming you want to write this in another function:
import random
def three_random_square_average():
z = 0 # initialize your answer
while(z <= 0.5625): # While the answer is less or equal than 0.5625...
# Generate three random numbers:
a, b, c = random.random(), random.random(), random.random()
# Assign the square of the average to your answer variable
z = square_of_average(a, b, c)
# When the loop exits, return the answer
return z
Another option:
import random
def three_random_squared_average():
while(True):
a, b, c = random.random(), random.random(), random.random()
z = square_of_average(a, b, c)
if(z > 0.5625):
break
return z
If you don't want a function:
import random
z = 0
while(z < 0.5625):
z = square_of_average(random.random(), random.random(), random.random())
print z
Firstly for 1) - you're raising the average to the second power... not each value. Otherwise you want the average of the second powers of the input values.
import random
a = random.random ()
b = random.random ()
c = random.random ()
def avenum1(x1,x2,x3): # the average of the 3 numbers
z = ((x1+x2+x3)/3.0)**2
return z
For 2): There are better ways but this is the most obvious.
def avenum1(x1,x2,x3): # the average of the 3 numbers
z = ((x1+x2+x3)/3.0)**2
return z
avg = 0:
while avg<0.5625:
a = random.random ()
b = random.random ()
c = random.random ()
avg = avenum1(a,b,c)
The better way:
avg = 0
while avg<0.5625:
list_ = [random.random() for i in range(3)]
avg = (sum(list_)/3.0)**2
What is the difference between the following Python expressions:
# First:
x,y = y,x+y
# Second:
x = y
y = x+y
First gives different results than Second.
e.g.,
First:
>>> x = 1
>>> y = 2
>>> x,y = y,x+y
>>> x
2
>>> y
3
Second:
>>> x = 1
>>> y = 2
>>> x = y
>>> y = x+y
>>> x
2
>>> y
4
y is 3 in First and 4 in Second
In an assignment statement, the right-hand side is always evaluated fully before doing the actual setting of variables. So,
x, y = y, x + y
evaluates y (let's call the result ham), evaluates x + y (call that spam), then sets x to ham and y to spam. I.e., it's like
ham = y
spam = x + y
x = ham
y = spam
By contrast,
x = y
y = x + y
sets x to y, then sets y to x (which == y) plus y, so it's equivalent to
x = y
y = y + y
It is explained in the docs in the section entitled "Evaluation order":
... while evaluating an assignment, the right-hand side is evaluated
before the left-hand side.
The first expression:
Creates a temporary tuple with value y,x+y
Assigned in to another temporary tuple
Extract the tuple to variables x and y
The second statement is actually two expressions, without the tuple usage.
The surprise is, the first expression is actually:
temp=x
x=y
y=temp+y
You can learn more about the usage of comma in "Parenthesized forms".
An observation regarding the left-hand side as well: the order of assignments is guaranteed to be the order of their appearance, in other words:
a, b = c, d
is equivalent functionally to precisely (besides t creation):
t = (c, d)
a = t[0] # done before 'b' assignment
b = t[1] # done after 'a' assignment
This matters in cases like object attribute assignment, e.g.:
class dummy:
def __init__(self): self.x = 0
a = dummy(); a_save = a
a.x, a = 5, dummy()
print(a_save.x, a.x) # prints "5 0" because above is equivalent to "a = dummy(); a_save = a; t = (5, dummy()); a.x = t[0]; a = t[1]"
a = dummy(); a_save = a
a, a.x = dummy(), 5
print(a_save.x, a.x) # prints "0 5" because above is equivalent to "a = dummy(); a_save = a; t = (dummy(), 5); a = t[0]; a.x = t[1]"
This also implies that you can do things like object creation and access using one-liners, e.g.:
class dummy:
def __init__(self): self.x = 0
# Create a = dummy() and assign 5 to a.x
a, a.x = dummy(), 5
I've recently started using Python and this "feature" baffled me. Although there are many answers given, I'll post my understanding anyway.
If I want to swap the values of two variables, in JavaScipt, I'd do the following:
var a = 0;
var b = 1;
var temp = a;
a = b;
b = temp;
I'd need a third variable to temporarily hold one of the values. A very straightforward swap wouldn't work, because both of the variables would end up with the same value.
var a = 0;
var b = 1;
a = b; // b = 1 => a = 1
b = a; // a = 1 => b = 1
Imagine having two different (red and blue) buckets and having two different liquids (water and oil) in them, respectively. Now, try to swap the buckets/liquids (water in blue, and oil in red bucket). You can't do it unless you have an extra bucket.
Python deals with this with a "cleaner" way/solution: Tuple Assignment.
a = 0
b = 1
print(a, b) # 0 1
# temp = a
# a = b
# b = temp
a, b = b, a # values are swapped
print(a, b) # 1 0
I guess, this way Python is creating the "temp" variables automatically and we don't have to worry about them.
In the second case, you assign x+y to x
In the first case, the second result (x+y) is assigned to y
This is why you obtain different results.
After your edit
This happen because, in the statement
x,y = y,x+y
all variables at the right member are evaluated and, then, are stored in the left members. So first proceed with right member, and second with the left member.
In the second statement
x = y
y = x + y
yo first evaluated y and assign it to x; in that way, the sum of x+y is equivalent to a sum of y+y and not of x+x wich is the first case.
The first one is a tuple-like assignment:
x,y = y,x+y
Where x is the first element of the tuple, and y is the second element, thus what you are doing is:
x = y
y = x+y
Wheras the second is doing a straight assign:
x=y
x=x+y
Other answers have already explained how it works, but I want to add a really concrete example.
x = 1
y = 2
x, y = y, x+y
In the last line, first the names are dereferenced like this:
x, y = 2, 1+2
Then the expression is evaluated:
x, y = 2, 3
Then the tuples are expanded and then the assignment happens, equivalent to:
x = 2; y = 3
For newbies, I came across this example that can help explain this:
# Fibonacci series:
# the sum of two elements defines the next
a, b = 0, 1
while a < 10:
print(a)
a, b = b, a+b
With the multiple assignment, set initial values as a=0, b=1.
In the while loop, both elements are assigned new values (hence called 'multiple' assignment). View it as (a,b) = (b,a+b). So a = b, b = a+b at each iteration of the loop. This continues while a<10.
RESULTS:
0
1
1
2
3
5
8
Let's grok the difference.
x, y = y, x + y
It's x tuple xssignment, mexns (x, y) = (y, x + y), just like (x, y) = (y, x)
Stxrt from x quick example:
x, y = 0, 1
#equivxlent to
(x, y) = (0, 1)
#implement xs
x = 0
y = 1
When comes to (x, y) = (y, x + y)
ExFP, have x try directly
x, y = 0, 1
x = y #x=y=1
y = x + y #y=1+1
#output
In [87]: x
Out[87]: 1
In [88]: y
Out[88]: 2
However,
In [93]: x, y = y, x+y
In [94]: x
Out[94]: 3
In [95]: y
Out[95]: 5
The result is different from the first try.
Thx's because Python firstly evaluates the right-hand x+y
So it equivxlent to:
old_x = x
old_y = y
c = old_x + old_y
x = old_y
y = c
In summary, x, y = y, x+y means,
x exchanges to get old_value of y,
y exchanges to get the sum of old value x and old value y,
a, b = 0, 1
while b < 10:
print(b)
a, b = b, a+b
Output
1
1
2
3
5
8
the variables a and b simultaneously get the new values 0 and 1, the same a, b = b, a+b, a and b are assigned simultaneously.
What is the difference between the following Python expressions:
# First:
x,y = y,x+y
# Second:
x = y
y = x+y
First gives different results than Second.
e.g.,
First:
>>> x = 1
>>> y = 2
>>> x,y = y,x+y
>>> x
2
>>> y
3
Second:
>>> x = 1
>>> y = 2
>>> x = y
>>> y = x+y
>>> x
2
>>> y
4
y is 3 in First and 4 in Second
In an assignment statement, the right-hand side is always evaluated fully before doing the actual setting of variables. So,
x, y = y, x + y
evaluates y (let's call the result ham), evaluates x + y (call that spam), then sets x to ham and y to spam. I.e., it's like
ham = y
spam = x + y
x = ham
y = spam
By contrast,
x = y
y = x + y
sets x to y, then sets y to x (which == y) plus y, so it's equivalent to
x = y
y = y + y
It is explained in the docs in the section entitled "Evaluation order":
... while evaluating an assignment, the right-hand side is evaluated
before the left-hand side.
The first expression:
Creates a temporary tuple with value y,x+y
Assigned in to another temporary tuple
Extract the tuple to variables x and y
The second statement is actually two expressions, without the tuple usage.
The surprise is, the first expression is actually:
temp=x
x=y
y=temp+y
You can learn more about the usage of comma in "Parenthesized forms".
An observation regarding the left-hand side as well: the order of assignments is guaranteed to be the order of their appearance, in other words:
a, b = c, d
is equivalent functionally to precisely (besides t creation):
t = (c, d)
a = t[0] # done before 'b' assignment
b = t[1] # done after 'a' assignment
This matters in cases like object attribute assignment, e.g.:
class dummy:
def __init__(self): self.x = 0
a = dummy(); a_save = a
a.x, a = 5, dummy()
print(a_save.x, a.x) # prints "5 0" because above is equivalent to "a = dummy(); a_save = a; t = (5, dummy()); a.x = t[0]; a = t[1]"
a = dummy(); a_save = a
a, a.x = dummy(), 5
print(a_save.x, a.x) # prints "0 5" because above is equivalent to "a = dummy(); a_save = a; t = (dummy(), 5); a = t[0]; a.x = t[1]"
This also implies that you can do things like object creation and access using one-liners, e.g.:
class dummy:
def __init__(self): self.x = 0
# Create a = dummy() and assign 5 to a.x
a, a.x = dummy(), 5
I've recently started using Python and this "feature" baffled me. Although there are many answers given, I'll post my understanding anyway.
If I want to swap the values of two variables, in JavaScipt, I'd do the following:
var a = 0;
var b = 1;
var temp = a;
a = b;
b = temp;
I'd need a third variable to temporarily hold one of the values. A very straightforward swap wouldn't work, because both of the variables would end up with the same value.
var a = 0;
var b = 1;
a = b; // b = 1 => a = 1
b = a; // a = 1 => b = 1
Imagine having two different (red and blue) buckets and having two different liquids (water and oil) in them, respectively. Now, try to swap the buckets/liquids (water in blue, and oil in red bucket). You can't do it unless you have an extra bucket.
Python deals with this with a "cleaner" way/solution: Tuple Assignment.
a = 0
b = 1
print(a, b) # 0 1
# temp = a
# a = b
# b = temp
a, b = b, a # values are swapped
print(a, b) # 1 0
I guess, this way Python is creating the "temp" variables automatically and we don't have to worry about them.
In the second case, you assign x+y to x
In the first case, the second result (x+y) is assigned to y
This is why you obtain different results.
After your edit
This happen because, in the statement
x,y = y,x+y
all variables at the right member are evaluated and, then, are stored in the left members. So first proceed with right member, and second with the left member.
In the second statement
x = y
y = x + y
yo first evaluated y and assign it to x; in that way, the sum of x+y is equivalent to a sum of y+y and not of x+x wich is the first case.
The first one is a tuple-like assignment:
x,y = y,x+y
Where x is the first element of the tuple, and y is the second element, thus what you are doing is:
x = y
y = x+y
Wheras the second is doing a straight assign:
x=y
x=x+y
Other answers have already explained how it works, but I want to add a really concrete example.
x = 1
y = 2
x, y = y, x+y
In the last line, first the names are dereferenced like this:
x, y = 2, 1+2
Then the expression is evaluated:
x, y = 2, 3
Then the tuples are expanded and then the assignment happens, equivalent to:
x = 2; y = 3
For newbies, I came across this example that can help explain this:
# Fibonacci series:
# the sum of two elements defines the next
a, b = 0, 1
while a < 10:
print(a)
a, b = b, a+b
With the multiple assignment, set initial values as a=0, b=1.
In the while loop, both elements are assigned new values (hence called 'multiple' assignment). View it as (a,b) = (b,a+b). So a = b, b = a+b at each iteration of the loop. This continues while a<10.
RESULTS:
0
1
1
2
3
5
8
Let's grok the difference.
x, y = y, x + y
It's x tuple xssignment, mexns (x, y) = (y, x + y), just like (x, y) = (y, x)
Stxrt from x quick example:
x, y = 0, 1
#equivxlent to
(x, y) = (0, 1)
#implement xs
x = 0
y = 1
When comes to (x, y) = (y, x + y)
ExFP, have x try directly
x, y = 0, 1
x = y #x=y=1
y = x + y #y=1+1
#output
In [87]: x
Out[87]: 1
In [88]: y
Out[88]: 2
However,
In [93]: x, y = y, x+y
In [94]: x
Out[94]: 3
In [95]: y
Out[95]: 5
The result is different from the first try.
Thx's because Python firstly evaluates the right-hand x+y
So it equivxlent to:
old_x = x
old_y = y
c = old_x + old_y
x = old_y
y = c
In summary, x, y = y, x+y means,
x exchanges to get old_value of y,
y exchanges to get the sum of old value x and old value y,
a, b = 0, 1
while b < 10:
print(b)
a, b = b, a+b
Output
1
1
2
3
5
8
the variables a and b simultaneously get the new values 0 and 1, the same a, b = b, a+b, a and b are assigned simultaneously.