splitting imagewidget into two classes

fastplotlib · kushalkolar · Dec 11, 2022 · Dec 2, 2022 · Dec 2, 2022 · Dec 2, 2022
commit 5cc91ae74aad3deb3ac5fd3b95732ca382b2d33d
diff --git a/examples/imagewidget.ipynb b/examples/imagewidget.ipynb
@@ -0,0 +1,97 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "111354d5-36ee-4bd5-9376-aaece6eb5b4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8404aaae-ba87-426c-a3cf-f3968640b8e3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2253ccaa-670c-4c6a-9e81-48963bd1d964",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fastplotlib.widgets import ImageWidget\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "9775a1f0-34c3-4583-8dcc-00707095150b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a = np.random.rand(1000, 512, 512)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "8b910f06-2cf4-4363-8b58-71c32d6f9c64",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "'t' is not in list",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m iw \u001b[38;5;241m=\u001b[39m \u001b[43mImageWidget\u001b[49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcmap\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgnuplot2\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/repos/fastplotlib/fastplotlib/widgets/image.py:98\u001b[0m, in \u001b[0;36mImageWidget.__init__\u001b[0;34m(self, data, axes_order, slider_sync, slider_axes, slice_avg, frame_apply, grid_shape, **kwargs)\u001b[0m\n\u001b[1;32m     96\u001b[0m \u001b[38;5;66;03m# make a slider for \"t\", the time dimension, if slider_axes is not provided\u001b[39;00m\n\u001b[1;32m     97\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m slider_axes \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 98\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_slider_axes \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43maxes_order\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    100\u001b[0m \u001b[38;5;66;03m# if a single axes is provided for the slider\u001b[39;00m\n\u001b[1;32m    101\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(slider_axes, (\u001b[38;5;28mint\u001b[39m, \u001b[38;5;28mstr\u001b[39m)):\n",
+      "\u001b[0;31mValueError\u001b[0m: 't' is not in list"
+     ]
+    }
+   ],
+   "source": [
+    "iw = ImageWidget(a, cmap=\"gnuplot2\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f1be6cd2-9263-4da0-9280-48444dd74c1f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/fastplotlib/widgets/image.py b/fastplotlib/widgets/image.py
@@ -12,7 +12,7 @@
         2: "xy",
         3: "txy",
         4: "tzxy",
-        5: "tczxy",
+        # 5: "tczxy",  # no 5 dim stuff for now
     }
 
 
@@ -30,6 +30,14 @@ def get_indexer(ndim: int, dim_index: int, slice_index: int) -> slice:
     return tuple(indexer)
 
 
+def is_arraylike(obj) -> bool:
+    """
+    Checks if the object is array-like.
+    For now just checks if obj has `__getitem__()`
+    """
+    return hasattr(obj, "__getitem__")
+
+
 class ImageWidget:
     """
     A high level for displaying n-dimensional image data in conjunction with automatically generated sliders for
@@ -40,9 +48,10 @@ class ImageWidget:
     def __init__(
             self,
             data: Union[np.ndarray, List[np.ndarray]],
-            axes_order: str = None,
+            axes_order: [str, dict] = None,
             slider_sync: bool = True,
             slider_axes: Union[int, str, dict] = None,
+            slice_avg: Union[int, dict] = None,
             frame_apply: Union[callable, dict] = None,
             grid_shape: Tuple[int, int] = None,
             **kwargs
@@ -87,14 +96,14 @@ def __init__(
 
         # default axes order if not passed
         if axes_order is None:
-            self.axes_order: List[str] = [DEFAULT_AXES_ORDER[ndim] for i in range(len(data))]
+            self.axes_order: str = [DEFAULT_AXES_ORDER[ndim] for i in range(len(data))]
 
         else:
             self.axes_order = axes_order
 
         # make a slider for "t", the time dimension, if slider_axes is not provided
         if slider_axes is None:
-            slider_axes = self.axes_order.index("t")
+            self._slider_axes = self.axes_order.index("t")
 
         # if a single axes is provided for the slider
         if isinstance(slider_axes, (int, str)):
@@ -190,3 +199,31 @@ def slider_changed(self):
     def show(self):
         self.plot.show()
         return self.widget
+
+
+class _ImageWidget:
+    """Single n-dimension image with slider(s)"""
+    def __init__(
+            self,
+            data: np.ndarray,
+            axes_order: str = None,
+            slider_axes: Union[str, int, List[Union[str, int]]] = None,
+            slice_average: Dict[Union[int, str], int] = None,
+            frame_apply: Union[callable, Dict[Union[int, str], callable]] = None,
+            **kwargs
+    ):
+        if not is_arraylike(data):
+            raise TypeError(
+                f"`data` must be an array-like object"
+            )
+
+        self.data = data
+        self.ndim = self.data.ndim
+
+        if axes_order is None:
+            self.axes_order: str = DEFAULT_AXES_ORDER[self.ndim]
+        else:
+            if not type(axes_order) is str:
+                raise TypeError(f"`axes_order` must be a <str>, you have passed a: <{type(axes_order)}>")
+            self.axes_order = axes_order
+