Image problem

I'm not sure what the underlying problem is, but some of the Image objects generated by the transfer functions don't work as valid inputs to the other transfer functions, even though they visualize fine.

```
import math

import numpy as np
import pandas as pd
import holoviews as hv
import fastparquet as fp

import datashader as ds
import datashader.transfer_functions as tf
from datashader.layout import random_layout, circular_layout

np.random.seed(0)
n=100

nodes = pd.DataFrame(["node"+str(i) for i in range(n)], columns=['name'])
randomloc = random_layout(nodes,None)
circular = circular_layout(nodes,None, uniform=False)

c1 = ds.Canvas(plot_height=100, plot_width=100, x_range=(0.0,1.0), y_range=(0.0,1.0))
c2 = ds.Canvas(plot_height=100, plot_width=100)

def nodesplot(nodes, canvas, name):
return tf.spread(tf.shade(canvas.points(nodes, 'x','y')), px=3, name=name)

plots = (nodesplot(randomloc,c1,"Random"),
nodesplot(circular, c1,"Circular"))

tf.Images(*plots)
```

```
tf.stack(*plots)
```

```
plots = (nodesplot(randomloc,c2,"Random"),
nodesplot(circular, c2,"Circular"))

tf.Images(*plots)
```


```
tf.stack(*plots)
```

```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
in ()
----> 1 tf.stack(*plots)

~/datashader_git/datashader/transfer_functions.py in stack(*imgs, **kwargs)
104 imgs = xr.align(*imgs, copy=False, join='outer')
105 with np.errstate(divide='ignore', invalid='ignore'):
--> 106 out = tz.reduce(tz.flip(op), [i.data for i in imgs])
107 return Image(out, coords=imgs[0].coords, dims=imgs[0].dims, name=name)
108

~/anaconda/envs/ds/lib/python3.6/site-packages/toolz/functoolz.py in __call__(self, *args, **kwargs)
281 def __call__(self, *args, **kwargs):
282 try:
--> 283 return self._partial(*args, **kwargs)
284 except TypeError as exc:
285 if self._should_curry(args, kwargs, exc):

~/anaconda/envs/ds/lib/python3.6/site-packages/toolz/functoolz.py in flip(func, a, b)
653 [1, 2, 3]
654 """
--> 655 return func(b, a)
656
657

TypeError: ufunc 'over' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
```

Here I'm calling stack on two different images, which works fine when I specify a range that leaves a small buffer around all the points when the images are created (first case above), but fails when stacking two images that used auto-ranging instead.

The message is a bit inscrutable, so I poked around a bit, and I *thought* that it could have something to do with spread reaching the boundary of the array, and I *thought* that I was seeing xarray types of object and values of NaNs, instead of the expected type of `uint32` and numeric values. But that's all hearsay, because when I actually isolated the example above, it all looks like `uint32` and no NaNs, and I see the same results with and without spreading, so I'll just leave it as "the example above works in one case and not the other, and I have no idea why".

Start with transfer_functions.py at stack, where the traceback points to xr.align and tz.reduce, then run the supplied Python example comparing explicit ranges with auto-ranging. Done means the auto-ranged Images can be passed to tf.stack without the reported ufunc 'over' TypeError, with regression coverage for both cases.

Written by the indexing model from the issue text.