How can I find the dimensions of a matrix in Python. Len(A) returns only one variable.
Edit:
close = dataobj.get_data(timestamps, symbols, closefield) Is (I assume) generating a matrix of integers (less likely strings). I need to find the size of that matrix, so I can run some tests without having to iterate through all of the elements. As far as the data type goes, I assume it's an array of arrays (or list of lists).
410 Answers
The number of rows of a list of lists would be: len(A) and the number of columns len(A[0]) given that all rows have the same number of columns, i.e. all lists in each index are of the same size.
If you are using NumPy arrays, shape can be used. For example
>>> a = numpy.array([[[1,2,3],[1,2,3]],[[12,3,4],[2,1,3]]]) >>> a array([[[ 1, 2, 3], [ 1, 2, 3]], [[12, 3, 4], [ 2, 1, 3]]]) >>> a.shape (2, 2, 3) As Ayman farhat mentioned you can use the simple method len(matrix) to get the length of rows and get the length of the first row to get the no. of columns using len(matrix[0]) :
>>> a=[[1,5,6,8],[1,2,5,9],[7,5,6,2]] >>> len(a) 3 >>> len(a[0]) 4 Also you can use a library that helps you with matrices "numpy":
>>> import numpy >>> numpy.shape(a) (3,4) To get just a correct number of dimensions in NumPy:
len(a.shape) In the first case:
import numpy as np a = np.array([[[1,2,3],[1,2,3]],[[12,3,4],[2,1,3]]]) print("shape = ",np.shape(a)) print("dimensions = ",len(a.shape)) The output will be:
shape = (2, 2, 3) dimensions = 3 The correct answer is the following:
import numpy numpy.shape(a) m = [[1, 1, 1, 0],[0, 5, 0, 1],[2, 1, 3, 10]] print(len(m),len(m[0])) Output
(3 4) Suppose you have a which is an array. to get the dimensions of an array you should use shape.
import numpy as np a = np.array([[3,20,99],[-13,4.5,26],[0,-1,20],[5,78,-19]]) a.shape The output of this will be
(4,3) You may use as following to get Height and Weight of an Numpy array:
int height = arr.shape[0] int weight = arr.shape[1] If your array has multiple dimensions, you can increase the index to access them.
You simply can find a matrix dimension by using Numpy:
import numpy as np x = np.arange(24).reshape((6, 4)) x.ndim output will be:
2 It means this matrix is a 2 dimensional matrix.
x.shape Will show you the size of each dimension. The shape for x is equal to:
(6, 4) A simple way I look at it: example:
h=np.array([[[[1,2,3],[3,4,5]],[[5,6,7],[7,8,9]],[[9,10,11],[12,13,14]]]]) h.ndim 4 h array([[[[ 1, 2, 3], [ 3, 4, 5]], [[ 5, 6, 7], [ 7, 8, 9]], [[ 9, 10, 11], [12, 13, 14]]]]) If you closely observe, the number of opening square brackets at the beginning is what defines the dimension of the array. In the above array to access 7, the below indexing is used, h[0,1,1,0]
However if we change the array to 3 dimensions as below,
h=np.array([[[1,2,3],[3,4,5]],[[5,6,7],[7,8,9]],[[9,10,11],[12,13,14]]]) h.ndim 3 h array([[[ 1, 2, 3], [ 3, 4, 5]], [[ 5, 6, 7], [ 7, 8, 9]], [[ 9, 10, 11], [12, 13, 14]]]) To access element 7 in the above array, the index is h[1,1,0]
