Numpy universal functions are "vectorized" functions operating on elements (element by element) on a Numpy array.
Questions tagged [numpy-ufunc]
198 questions
5
votes
3 answers
NumPy ufuncs are 2x faster in one axis over the other
I was doing some computation, and measured the performance of ufuncs like np.cumsum over different axes, to make the code more performant.
In [51]: arr = np.arange(int(1E6)).reshape(int(1E3), -1)
In [52]: %timeit arr.cumsum(axis=1)
2.27 ms ± 10.5…
kmario23
- 57,311
- 13
- 161
- 150
5
votes
1 answer
"where" clause in numpy-1.13 ufuncs
I occasionally use the where clause in numpy's ufuncs. For example, the following:
import numpy as np
a = np.linspace(-1, 1, 10)
np.sqrt(a, where=a>0) * (a>0)
In Numpy 1.12 and earlier, this used to give me square root values where possible and…
Kessel
- 136
- 6
5
votes
3 answers
fastest way to obtain cross product
It looks like calculating the cross-product of an array of vectors explicitly is a lot faster than using np.cross. I've tried vector-first and vector-last, it doesn't seem to make a difference, though that was proposed in an answer to a similar…
uhoh
- 3,713
- 6
- 42
- 95
4
votes
1 answer
Why do I get the 'loop of ufunc does not support argument 0 of type numpy.ndarray' error for log method?
First, I used np.array to perform operations on multiple matrices, and it was successful.
import numpy as np
import matplotlib.pyplot as plt
f = np.array([[0.35, 0.65]])
e = np.array([[0.92, 0.08], [0.03, 0.97]])
r = np.array([[0.95, 0.05], [0.06,…
SYD
- 43
- 3
4
votes
3 answers
Python list reversed can't be accessed more than once
Can someone explain this to me?
import numpy as np
arr = reversed(np.arange(11))
print(list(arr))
print(list(arr))
print(list(arr))
the output of this code is :
why can't I access the arr variable more than once?
Hussain Wali
- 308
- 3
- 12
4
votes
2 answers
How to get "dot addition" in numpy similar to dot product?
I'm somewhat new to numpy and am strugging with this problem. I have two 2-dimensional numpy arrays:
array1 = [a1, a2, ..., an]
array2 = [b1, b2, ..., am]
a1, a2, b1, and b2 are all 1-d arrays with exactly 100 floats in them. However, array1 and…
Abs
- 1,726
- 2
- 17
- 28
4
votes
1 answer
Avoiding memory overflow while using xarray dask apply_ufunc
I need to apply a function along the time dimension of an xarray dask array of this shape:
dask.array
Monobakht
- 193
- 1
- 11
4
votes
1 answer
Iterating and accumulating over a numpy array with a custom function
There has been some related questions for over 7 years, but I raise this issue again as I could see no 'numpy' way iteration method provided.
The task is as follows:
If I have an numpy array 'arr' and have a custom function 'fn', how could I …
sdr2002
- 542
- 2
- 6
- 16
4
votes
2 answers
Can bessel functions (from scipy.special) be used with Numba
I'm trying to optimize evaluation of an integral (scipy.integrate.quad) over a function containing Bessel functions with Numba.
While Numba seems to work well for "common" numpy functions, it throws an error when I attempt to include the Bessel…
SLater01
- 459
- 1
- 6
- 17
4
votes
1 answer
Numpy index of the maximum with reduction - numpy.argmax.reduceat
I have a flat array b:
a = numpy.array([0, 1, 1, 2, 3, 1, 2])
And an array c of indices marking the start of each "chunk":
b = numpy.array([0, 4])
I know I can find the maximum in each "chunk" using a reduction:
m = numpy.maximum.reduceat(a,b)
>>>…
Benjamin
- 11,560
- 13
- 70
- 119
4
votes
1 answer
Use of __numpy_ufunc__()
I'm trying to use the __numpy_ufunc__() method explained here in the Numpy v1.11 docs, to override the behavior of numpy ufuncs on a subclass of ndarray, but it never seems to get called. Despite this use case being listed in the guide, I can't…
Sam Bader
- 185
- 1
- 7
4
votes
4 answers
Equivalent for np.add.at in tensorflow
How do I convert a np.add.at statement into tensorflow?
np.add.at(dW, self.x.ravel(), dout.reshape(-1, self.D))
Edit
self.dW.shape is (V, D), self.D.shape is (N, D) and self.x.size is N
Amey Agrawal
- 132
- 9
4
votes
3 answers
numpy dot or einsum with arbitrary operator
I would like to use something like np.dot or (preferably) np.einsum to efficiently perform their same function but with an alternate ufunc instead of np.multiply. For example, consider these two arrays:
>>> a
array([[0, 1],
[1, 1],
[1,…
bogatron
- 18,639
- 6
- 53
- 47
4
votes
1 answer
How to properly install a NumPy ufunc?
I am trying to install an example ufunc from the SciPy Docs but when I run python setup.py build or python setup.py install I get a few warnings about a deprecated NumPy API.
When I run python setup.py install this is the output:
$ python setup.py…
Will Norvelle
- 101
- 2
- 9
4
votes
2 answers
How to use numpy.frompyfunc to return an array of elements instead of array of arrays?
I am using the PLegendre function from the SHTOOLS package. It returns an array of Legendre polynomials for a particular argument. PLegendre(lmax,x) returns an array of Legendre polynomials P_0(x) to P_lmax(x). It works like this:
In [1]: from…
Jishnu
- 769
- 8
- 17