CoryKramer - 2 months ago 19

Python Question

I have a simple

`Point`

`class Point(object):`

def __init__(self, x=0.0, y=0.0, z=0.0):

self.x = x

self.y = y

self.z = z

I would like to use

`scipy.interpolate.interp1d`

`x,y,z = f(t)`

However when I try the following small example

`import numpy as np`

from scipy.interpolate import interp1d

times = np.array([0.0, 0.1, 0.2])

points = np.array([Point(0.0, 0.0, 0.0),

Point(1.0, 1.0, 1.0),

Point(2.0, 2.0, 2.0)])

function = interp1d(times, points)

new_point = function(0.05)

I get the following error

`Traceback (most recent call last):`

File "D:/example.py", line 31, in <module>

function = interp1d(times, points)

File "C:\long_path\scipy\interpolate\interpolate.py", line 439, in __init__

y = y.astype(np.float_)

TypeError: float() argument must be a string or a number, not 'Point'

I've also tried overloading the arithmetic operators for the

`Point`

`__add__`

`__sub__`

`__truediv__`

Is there a way I can use

`scipy.interpolate.interp1d`

Answer

Since python object are internally dicts instead of contiguous buffer, numpy/scipy will fail to use certain methods when custom typed objects are inside `numpy.ndarray`

.

A simple solution would be putting all `Point`

inside one single `ndarray`

with built-in type:

```
from __future__ import print_function
import numpy as np
import scipy.interpolate as sp_interp
points = np.array([[0.0, 0.0, 0.0],
[1.0, 1.0, 1.0],
[2.0, 2.0, 2.0]], dtype='float64')
times = np.linspace(0.,.2, len(points))
fn_interp = sp_interp.interp1d(times, points, axis=0)
print(fn_interp(0.05))
```

If you are dedicated to class based approach, you might want to define custom `dtype`

or make subclass of `ndarray`

, as answered here