Writing strided numpy arrays

There seems to be an issue when writing numpy arrays with non-standard strides. Consider the following example of me writing a multi-channel image
```import OpenEXR
import numpy as np
shape = (4,4)

channels_np = np.zeros((*shape, 10), dtype=np.float32)
channels_np += np.arange(10)
channels = {}
for i in range(channels_np.shape[-1]):
channels[f"chan{i}"] = channels_np[:, :, i]

print("chan1 before writing\n", channels["chan1"])
header = {"compression" : OpenEXR.RLE_COMPRESSION, "type" : OpenEXR.scanlineimage}
with OpenEXR.File(header, channels) as outfile:
outfile.write("tmp.exr")

with OpenEXR.File("tmp.exr") as infile:
print("chan1 read from file\n", infile.channels()["chan1"].pixels)
```

This prints
```
chan1 before writing
[[1. 1. 1. 1.]
[1. 1. 1. 1.]
[1. 1. 1. 1.]
[1. 1. 1. 1.]]
chan1 read from file
[[1. 2. 3. 4.]
[5. 6. 7. 8.]
[9. 0. 1. 2.]
[3. 4. 5. 6.]]
```
If I `.copy()` the arrays before adding them to the `channels` dict, this goes away, but it took me a long time to track down the error.
Ideally it should perform this copy internally if necessary, or at least warn the user that the strides are not supported.