I have a module wrote in python to input a matrix that looks like that:
matrix = []
loop = True
while loop:
line = input()
if not line: #the way it works is that you enter value separated by a space and enter a blank line to finish inputing the matrix
loop = False
values = line.split()
row = [int(value) for value in values]
matrix.append(row)
print('\n'.join([' '.join(map(str, row)) for row in matrix]))
The last line is just to print the matrix like this
1 2 3
4 5 6
I would like to be able to transpose the matrix in another module,I tried this so far:
def transpose_matrix(matrix):
zip(*matrix)
return matrix
But it actually doesnt work it doesnt have any effect on the actual matrix,the matrix stays the same,and I dont get it.
Thanks!
First, I would get the matrix in the following manner, to avoid the empty list in the end:
matrix = []
while True:
line = input()
if not line:
break
values = line.split()
row = [int(value) for value in values]
matrix.append(row)
as for transposing it, the best way is to leave it to numpy:
import numpy as np
transposed_matrix = np.transpose(np.array(matrix))
if for any reason you would like to avoid numpy (which is not advisable), you can use:
transposed_matrix = []
for line in zip(*matrix):
transposed_matrix.append(line)
Related
Here I have this where import data as arrays then, operates on those arrays with a function
import numpy as np
n1 = an array of 999 numbers
mass1= an array of 999 numbers
x1= an array of 999 numbers
y1=an array of 999 numbers
z1=an array of 999 numbers
dt=.0001
npoints=len(n1)
xn=0
step=1
for timedt in xrange(0,npoints-1):
step=step
for l in xrange(0,npoints-1):
xn=xn
f=x1,y1,z1[xn]+x1,y1,z1[step]
xn=xn+1
step=step+1
print f
However, when I print out f, I just get a huge list set of numbers in the format
.....
-9.622302989262075e-07
0.00016890654402323984
2.261014843829707e-05
-0.00011706036947314393
-7.791712660429376e-05
1.0156155973842854e-05
0.00019244252361596046
-0.00019202953520118445
0.04082168851673397
-0.001675463103312094
-1.4584179607758451e-05
3.788355464183264
3.99516377369456e-05
But I want to make these numbers be one array. In additon if I print f outside of that loop, I only get the last number.
3.99516377369456e-05
But I want to be able to print all of them outside of the loop as an array.
np.asarray
doesn't work.
The easiest way would possibly be:
f_array = []
for ...:
...
for ...:
f = ...
f_array.append(f)
f_array = np.array(f_array)
I have a numpy array A of size 10 with values ranging from 0-4. I want to create a new 2-D array B from this with its ith column being a vector corresponding to the ith element of A.
For example, the value 1 as the first element of A would correspond to B having a column vector [0,1,0,0,0] as it's first column. A having 4 as its third element would correspond to B having it's 3rd column as [0,0,0,1,0]
I have the following code:
import numpy as np
A = np.random.randint(0,5,10)
B = np.ones((5,10))
iden = np.identity(5, dtype=np.float64)
for i in range(0,10):
a = A[i]
B[:,i:i+1] = iden[:,a:a+1]
print A
print B
The code is doing what it's supposed to be doing but I am sure there are more efficient ways of doing this. Can anyone please suggest some?
That could be solved by initializing an array of zeros and then integer-indexing into it with indices from A and assigning 1s, like so -
M,N = 5,10
A = np.random.randint(0,M,N)
B = np.zeros((M,N))
B[A,np.arange(len(A))] = 1
As a simplified example, suppose I have a dataset composed of 40 sorted values. The values of this example are all integers, though this is not necessarily the case for the actual dataset.
import numpy as np
data = np.linspace(1,40,40)
I am trying to find the maximum value inside the dataset for certain window sizes. The formula to compute the window sizes yields a pattern that is best executed with arrays (in my opinion). For simplicity sake, let's say the indices denoting the window sizes are a list [1,2,3,4,5]; this corresponds to window sizes of [2,4,8,16,32] (the pattern is 2**index).
## this code looks long because I've provided docstrings
## just in case the explanation was unclear
def shapeshifter(num_col, my_array=data):
"""
This function reshapes an array to have 'num_col' columns, where
'num_col' corresponds to index.
"""
return my_array.reshape(-1, num_col)
def looper(num_col, my_array=data):
"""
This function calls 'shapeshifter' and returns a list of the
MAXimum values of each row in 'my_array' for 'num_col' columns.
The length of each row (or the number of columns per row if you
prefer) denotes the size of each window.
EX:
num_col = 2
==> window_size = 2
==> check max( data[1], data[2] ),
max( data[3], data[4] ),
max( data[5], data[6] ),
.
.
.
max( data[39], data[40] )
for k rows, where k = len(my_array)//num_col
"""
my_array = shapeshifter(num_col=num_col, my_array=data)
rows = [my_array[index] for index in range(len(my_array))]
res = []
for index in range(len(rows)):
res.append( max(rows[index]) )
return res
So far, the code is fine. I checked it with the following:
check1 = looper(2)
check2 = looper(4)
print(check1)
>> [2.0, 4.0, ..., 38.0, 40.0]
print(len(check1))
>> 20
print(check2)
>> [4.0, 8.0, ..., 36.0, 40.0]
print(len(check2))
>> 10
So far so good. Now here is my problem.
def metalooper(col_ls, my_array=data):
"""
This function calls 'looper' - which calls
'shapeshifter' - for every 'col' in 'col_ls'.
EX:
j_list = [1,2,3,4,5]
==> col_ls = [2,4,8,16,32]
==> looper(2), looper(4),
looper(8), ..., looper(32)
==> shapeshifter(2), shapeshifter(4),
shapeshifter(8), ..., shapeshifter(32)
such that looper(2^j) ==> shapeshifter(2^j)
for j in j_list
"""
res = []
for col in col_ls:
res.append(looper(num_col=col))
return res
j_list = [2,4,8,16,32]
check3 = metalooper(j_list)
Running the code above provides this error:
ValueError: total size of new array must be unchanged
With 40 data points, the array can be reshaped into 2 columns of 20 rows, or 4 columns of 10 rows, or 8 columns of 5 rows, BUT at 16 columns, the array cannot be reshaped without clipping data since 40/16 ≠ integer. I believe this is the problem with my code, but I do not know how to fix it.
I am hoping there is a way to cutoff the last values in each row that do not fit in each window. If this is not possible, I am hoping I can append zeroes to fill the entries that maintain the size of the original array, so that I can remove the zeroes after. Or maybe even some complicated if - try - break block. What are some ways around this problem?
I think this will give you what you want in one step:
def windowFunc(a, window, f = np.max):
return np.array([f(i) for i in np.split(a, range(window, a.size, window))])
with default f, that will give you a array of maximums for your windows.
Generally, using np.split and range, this will let you split into a (possibly ragged) list of arrays:
def shapeshifter(num_col, my_array=data):
return np.split(my_array, range(num_col, my_array.size, num_col))
You need a list of arrays because a 2D array can't be ragged (every row needs the same number of columns)
If you really want to pad with zeros, you can use np.lib.pad:
def shapeshifter(num_col, my_array=data):
return np.lib.pad(my_array, (0, num_col - my.array.size % num_col), 'constant', constant_values = 0).reshape(-1, num_col)
Warning:
It is also technically possible to use, for example, a.resize(32,2) which will create an ndArray padded with zeros (as you requested). But there are some big caveats:
You would need to calculate the second axis because -1 tricks don't work with resize.
If the original array a is referenced by anything else, a.resize will fail with the following error:
ValueError: cannot resize an array that references or is referenced
by another array in this way. Use the resize function
The resize function (i.e. np.resize(a)) is not equivalent to a.resize, as instead of padding with zeros it will loop back to the beginning.
Since you seem to want to reference a by a number of windows, a.resize isn't very useful. But it's a rabbit hole that's easy to fall into.
EDIT:
Looping through a list is slow. If your input is long and windows are small, the windowFunc above will bog down in the for loops. This should be more efficient:
def windowFunc2(a, window, f = np.max):
tail = - (a.size % window)
if tail == 0:
return f(a.reshape(-1, window), axis = -1)
else:
body = a[:tail].reshape(-1, window)
return np.r_[f(body, axis = -1), f(a[tail:])]
Here's a generalized way to reshape with truncation:
def reshape_and_truncate(arr, shape):
desired_size_factor = np.prod([n for n in shape if n != -1])
if -1 in shape: # implicit array size
desired_size = arr.size // desired_size_factor * desired_size_factor
else:
desired_size = desired_size_factor
return arr.flat[:desired_size].reshape(shape)
Which your shapeshifter could use in place of reshape
I’m trying to take user input and compare that input to the values in array B. Should the user input match one of those values in array B, I capture the index it is at and replace array A with the user input at the same index it found it in array B.
In the code example if I enter 11 it finds 11 in array B and inserts it into the same index point in array A. But if I choose 22, 33, or 44 it does not replace anything.
What do you see wrong with the code below? Why does it recognize number 11 in array B and replaces it with 1 in array A, but not the others?
a = [1,2,3,4]
b = [11,22,33,44]
c = input("Enter a Number: ")
for i in b:
if c == i:
x = b.index(i)
a.pop(x)
a.insert(x,c)
break
else:
print "Not in list b"
break
print a
Try this:
a = [1,2,3,4]
b = [11,22,33,44]
c = input("Enter a Number: ")
for i in b:
if c == i:
x = b.index(i)
print x
a.pop(x)
a.insert(x,c)
break
else:
print "Not in list b"
print a
Putting the else statement outside of the for loop should make it work as expected. As it was, the loop would, 100% of the time, break after 1 iteration.
So my main objective is to take a matrix of form
matrix = [a, 1; b, 2; c, 3]
and a list of identifiers in matrix[:,1]
list = [a; c]
and generate a new matrix
new_matrix = [a, 1;c, 3]
My problem is I need to import the data that would be used in 'matrix' from a tab-delimited text file. To get this data into Matlab I use the code:
matrix_open = fopen(fn_matrix, 'r');
matrix = textscan(matrix_open, '%c %d', 'Delimiter', '\t');
which outputs a cell array of two 3x1 arrays. I want to get this into one 3x2 matrix where the first column is a character, and the second column an integer (these data formats will be different in my implementation).
So far I've tried the code:
matrix_1 = cell2mat(matrix(1,1));
matrix_2 = cell2mat(matrix(1,2));
matrix = horzcat(matrix_1, matrix_2)
but this is returning a 3x2 matrix where the second column is empty.
If I just use
cell2mat(matrix)
it says it can't do it because of the different data formats.
Thanks!
This is the help of matlab for the cell2mat function:
cell2mat Convert the contents of a cell array into a single matrix.
M = cell2mat(C) converts a multidimensional cell array with contents of
the same data type into a single matrix. The contents of C must be able
to concatenate into a hyperrectangle. Moreover, for each pair of
neighboring cells, the dimensions of the cell's contents must match,
excluding the dimension in which the cells are neighbors. This constraint
must hold true for neighboring cells along all of the cell array's
dimensions.
From what I understand the contents you want to put in a matrix should be of the same type otherwise why do you want a matrix? you could simply create a new cell array.
It's not possible to have a normal matrix with characters and numbers. That's why cell2mat won't work here. But you can store different datatypes in a cell-array. Use cellstr for the strings/characters and num2cell for the integers to convert the contents of matrix. If you have other datatypes, use an appropriate function for this step. Then assign them to the columns of an empty cell-array.
Here is the code:
fn_matrix = 'data.txt';
matrix_open = fopen(fn_matrix, 'r');
matrix = textscan(matrix_open, '%c %d', 'Delimiter', '\t');
X = cell(size(matrix{1},1),2);
X(:,1) = cellstr(matrix{1});
X(:,2) = num2cell(matrix{2});
The result:
X =
'a' [1]
'b' [2]
'c' [3]
Now we can do the second part of the question. Extracting the entries where the letter matches with one of the list. Therefore you can use ismember and logical indexing like this:
list = ['a'; 'c'];
sel = ismember(X(:,1),list);
Y(:,1) = X(sel,1);
Y(:,2) = X(sel,2);
The result here:
Y =
'a' [1]
'c' [3]