WIP

Author: Leanne Guy

08_Interactive_Image_Visualization.ipynb

@@ -461,7 +461,15 @@
    "outputs": [],
    "source": [
     "# Use the bokeh plot style\n",
-    "plot_style = plot_style_bkh\n",
+    "plot_style = plot_style_bkh"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "hv.Scatter(data, \n",
     "           kdims=['gmi'], vdims=['mag_g_cModel']\n",
     "          ).opts(invert_yaxis=True,\n",
@@ -619,7 +627,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "LSST’s image classes (Image, Mask, MaskedImage, and Exposure) use a pixel indexing convention that is different from both the convention used by `numpy.ndarray` objects and the convention used in FITS images.  LSST typically labels the center of the lower left pixel of an image (0, 0). Consequently, we need to flip the image data array, "
+    "LSST’s image classes (Image, Mask, MaskedImage, and Exposure) use a pixel indexing convention that is different from both the convention used by `numpy.ndarray` objects and the convention used in FITS images.  LSST typically labels the center of the lower left pixel of an image (0, 0). Consequently, we need to flip the image data array."
    ]
   },
   {
@@ -629,7 +637,6 @@
    "outputs": [],
    "source": [
     "scaledImage = np.flipud(scaledImage)\n",
-    "# bounds_img = (0, calexp.getDimensions()[1], calexp.getDimensions()[0],0)\n",
     "bounds_img = (0, 0, calexp.getDimensions()[0], calexp.getDimensions()[1])"
    ]
   },
@@ -750,7 +757,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "rasterize(img).opts(cmap = 'Greys_r') * detections"
+    "rasterize(img) * detections"
    ]
   },
   {