Final clean up, use generate cube.

example_notebooks/cube_4d.ipynb

@@ -135,19 +135,26 @@
    ]
   },
   {
-   "cell_type": "raw",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "import numpy as np\n",
     "\n",
     "pf = None  # Not using FITS file pointer\n",
-    "cube4d = np.random.random((2, 5, 100, 200)).astype(np.float32)\n",
+    "cube4d = np.random.random((1, 10, 2048, 2048)).astype(np.float32)\n",
+    "\n",
+    "# Insert something \"interesting\"\n",
+    "for i in range(cube4d.shape[1]):\n",
+    "    j = i * 10\n",
+    "    cube4d[0, i, :j, :j] = 1.\n",
     "\n",
     "# Convert to NDData.\n",
     "im = NDData(cube4d, wcs=WCS(naxis=4))\n",
     "\n",
     "# Memory footprint\n",
-    "print((cube4d.size * 32 * u.bit).to(u.kB))"
+    "print((cube4d.size * 32 * u.bit).to(u.MB))"
    ]
   },
   {
@@ -160,23 +167,19 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "raw",
    "metadata": {},
-   "outputs": [],
    "source": [
     "from astropy.io import fits\n",
     "\n",
     "# This is a large cube.\n",
-    "filename = '/redkeep/ironthrone/ssb/stginga/test_data/NRCN815A_LIN_20160115_uncal.fits'\n",
+    "filename = 'my_big_cube.fits'\n",
     "pf = fits.open(filename, memmap=True)\n",
     "\n",
-    "# There is no WCS assigned for UNCAL file yet.\n",
-    "# This is a dummy WCS.\n",
+    "# Grab WCS from EXT 1.\n",
     "im_wcs = WCS(pf[1].header)\n",
     "\n",
     "# Pass memmap-ed FITS data into NDData.\n",
-    "# Shape is (1, 190, 2048, 2048)\n",
     "im = NDData(pf[1].data, wcs=im_wcs)\n",
     "\n",
     "# Memory footprint\n",
@@ -361,7 +364,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.8.3"
   }
  },
  "nbformat": 4,