 1

# range argument must have one entry per dimension

Package: numpy 18118
Exception Class:
ValueError

## Raise code

``````        # bins is an integer
bins = D*[bins]

# normalize the range argument
if range is None:
range = (None,) * D
elif len(range) != D:
raise ValueError('range argument must have one entry per dimension')

# Create edge arrays
for i in _range(D):
if np.ndim(bins[i]) == 0:
if bins[i] < 1:
raise ValueError(
'`bins[{}]` must be positive, when an integer'.format(i))``````
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## Ways to fix 1 The range argument should be the same shape as the shape of the data and it should also have a value in each dimension.

Code to reproduce the exception:

``` import numpy as np
d = np.linspace(0, 100, 200000).reshape((-1,2))
np.histogramdd(d, (10000, 10000), range=[ [0, 100]])
```

```---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-44-0f3eb828f48b> in <module>()  1 import numpy as np  2 d = np.linspace(0, 100, 200000).reshape((-1,2)) ----> 3 np.histogramdd(d, (10000, 10000), range=[ [0, 100]])
<__array_function__ internals> in histogramdd(*args, **kwargs)
/usr/local/lib/python3.7/dist-packages/numpy/lib/histograms.py in histogramdd(sample, bins, range, normed, weights, density)  1040 range = (None,) * D  1041 elif len(range) != D: -> 1042 raise ValueError('range argument must have one entry per dimension')  1043   1044 # Create edge arrays
ValueError: range argument must have one entry per dimension
```

Fixed version of the code:

``` import numpy as np
d = np.linspace(0, 100, 200000).reshape((-1,2))
np.histogramdd(d, (10000, 10000), range=[[0, 100], [0, 100]])
```