python numpy ValueError: operands could not be broadcast together with shapes

by

dot is matrix multiplication, but * does something else.

We have two arrays:

  • X, shape (97,2)
  • y, shape (2,1)

With Numpy arrays, the operation

X * y

is done element-wise, but one or both of the values can be expanded in one or more dimensions to make them compatible. This operation is called broadcasting. Dimensions, where size is 1 or which are missing, can be used in broadcasting.

In the example above the dimensions are incompatible, because:

97   2
 2   1

Here there are conflicting numbers in the first dimension (97 and 2). That is what the ValueError above is complaining about. The second dimension would be ok, as number 1 does not conflict with anything.

For more information on broadcasting rules: http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html

(Please note that if X and y are of type numpy.matrix, then asterisk can be used as matrix multiplication. My recommendation is to keep away from numpy.matrix, it tends to complicate more than simplifying things.)

Your arrays should be fine with numpy.dot; if you get an error on numpy.dot, you must have some other bug. If the shapes are wrong for numpy.dot, you get a different exception:

ValueError: matrices are not aligned

If you still get this error, please post a minimal example of the problem. An example multiplication with arrays shaped like yours succeeds:

In [1]: import numpy

In [2]: numpy.dot(numpy.ones([97, 2]), numpy.ones([2, 1])).shape
Out[2]: (97, 1)

More Related Contents:

  1. Fast punctuation removal with pandas
  2. Efficiently Using Multiple Numpy Slices for Random Image Cropping
  3. Computing the correlation coefficient between two multi-dimensional arrays
  4. Why is numpy’s einsum faster than numpy’s built in functions?
  5. Using a pre-trained word embedding (word2vec or Glove) in TensorFlow
  6. How to return 0 with divide by zero
  7. Numpy: find first index of value fast
  8. How to save and load numpy.array() data properly?
  9. Import Error: No module named numpy
  10. How do I create a view onto a NumPy array?
  11. How to use `cv2.findContours` in different OpenCV versions?
  12. ImportError: cannot import name NUMPY_MKL
  13. Is there a multi-dimensional version of arange/linspace in numpy?
  14. How to add a new row to an empty numpy array
  15. Fitting a line in 3D
  16. convert nan value to zero
  17. Numpy: Should I use newaxis or None?
  18. Using Numpy stride_tricks to get non-overlapping array blocks
  19. how to perform max/mean pooling on a 2d array using numpy
  20. How to find the index of a value in 2d array in Python?
  21. Filtering (reducing) a NumPy Array
  22. How can I upgrade NumPy?
  23. How to replicate array to specific length array
  24. Zero pad numpy array
  25. How to install matplotlib with Python3.2
  26. Plotting implicit equations in 3d
  27. Cannot get minor grid lines to appear in matplotlib figure
  28. Split Python sequence (time series/array) into subsequences with overlap
  29. numpy arange: how to make “precise” array of floats?
  30. Sort array’s rows by another array in Python

Leave a Comment