Add an imageseries adapter for arbitrary functions

This adds a highly customizable imageseries adapter that simply
accepts a function and a number of frames. The function takes a
single argument (an integer for the frame index), and returns a
2D numpy array for that frame.

This will be used for streaming in data, where the data is compressed
in memory (not on disk), and the custom function simply decompresses
the frame and returns it.

We will then use this to create a sparse data writer.

Signed-off-by: Patrick Avery <[email protected]>

hexrd/imageseries/load/__init__.py

@@ -19,7 +19,7 @@ class ImageSeriesAdapter(ImageSeriesABC, metaclass=_RegisterAdapterClass):
 # import all adapter modules
 
 from . import (
-    array, framecache, hdf5, imagefiles, rawimage, metadata, trivial
+    array, framecache, function, hdf5, imagefiles, rawimage, metadata, trivial
 )
 
 try:

hexrd/imageseries/load/function.py

@@ -0,0 +1,60 @@
+"""Adapter class for a custom function that takes an int as an argument
+and returns a 2D numpy array.
+"""
+from . import ImageSeriesAdapter
+from ..imageseriesiter import ImageSeriesIterator
+
+
+class FunctionImageSeriesAdapter(ImageSeriesAdapter):
+    """Collection of Images in numpy array
+
+    Parameters
+    ----------
+    fname: None
+       should be None
+    func: a function that returns a numpy array for a index
+    num_frames: the number of frames provided by the function
+    metadata: dict (optional)
+       the metadata dictionary
+    """
+    format = 'function'
+
+    def __init__(self, fname, **kwargs):
+        self._func = kwargs['func']
+        self._nframes = kwargs['num_frames']
+
+        self._meta = kwargs.pop('meta', {})
+
+        first_frame = self._first_frame
+        self._nxny = first_frame.shape
+        self._dtype = first_frame.dtype
+
+    @property
+    def metadata(self):
+        """Image sequence metadata"""
+        return self._meta
+
+    @property
+    def _first_frame(self):
+        return self._func(0)
+
+    @property
+    def shape(self):
+        return self._nxny
+
+    @property
+    def dtype(self):
+        return self._dtype
+
+    def __getitem__(self, key):
+        if not isinstance(key, int):
+            msg = f'Only int keys are supported, but "{key}" was provided'
+            raise Exception(msg)
+
+        return self._func(key)
+
+    def __iter__(self):
+        return ImageSeriesIterator(self)
+
+    def __len__(self):
+        return self._nframes