python numpy ValueError operands could not be broadcast together with shapes

Question

In numpy  I have two  arrays   X is  m n  and y is a vector  n 1   using   X y   I am getting the error  ValueError  operands could not be broadcast together with shapes  97 2   2 1     When   97 2 x 2 1  is clearly a legal matrix operation and should give me a  97 1  vector  EDIT   I have corrected this using X dot y  but the original question still remains

User · Answer

Convert the arrays to matrices  and then perform the multiplication  X   np matrix X   y   np matrix y   X y

User · Answer

It s possible that the error didn t occur in the dot product  but after  For example try this  a   np random randn 12 1  b   np random randn 1 5  c   np random randn 5 12  d   np dot a b    c   np dot a b  will be fine  however np dot a  b    c is clearly wrong  12x1 X 1x5   12x5 which cannot element-wise multiply 5x12  but numpy will give you  ValueError  operands could not be broadcast together with shapes  12 1   1 5    The error is misleading  however there is an issue on that line

User · Answer

Per numpy docs      When operating on two arrays  NumPy compares their shapes element-wise  It starts with the trailing dimensions  and works its way forward  Two dimensions are compatible when          they are equal  or   one of them is 1      In other words  if you are trying to multiply two matrices  in the linear algebra sense  then you want X dot y  but if you are trying to broadcast scalars from matrix y onto X then you need to perform X   y T     Example    gt  gt  gt  import numpy as np  gt  gt  gt   gt  gt  gt  X   np arange 8  reshape 4  2   gt  gt  gt  y   np arange 2  reshape 1  2     create a 1x2 matrix  gt  gt  gt  X   y array   0 1           0 3           0 5           0 7

User · Answer

We might confuse ourselves that a   b is a dot product    But in fact  it is broadcast    Dot Product        a dot b   Broadcast      The term broadcasting refers to how numpy treats arrays with different   dimensions during arithmetic operations which lead to certain   constraints  the smaller array is broadcast across the larger array so   that they have compatible shapes     m n   -    1 n     m n     the operation will be applied to m rows

User · Answer

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

User · Answer

Use np mat x    np mat y   that ll work

User · Answer

You are looking for np matmul X  y   In Python 3 5  you can use X   y

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

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