Merge pull request #169 from LSSTDESC/issues/167

Issues/167
LSSTDESC · Mar 1, 2024 · 0fa29ed · 0fa29ed
2 parents 33a3a9c + 37a99c5
commit 0fa29ed
Showing 1 changed file with 26 additions and 12 deletions.
diff --git a/tutorials/extragalactic_gcr_redshift_dist.ipynb b/tutorials/extragalactic_gcr_redshift_dist.ipynb
@@ -7,7 +7,7 @@
     "# Plot N versus z Distributions in the extragalactic catalogs\n",
     "\n",
     "<br>Owner: **Eve Kovacs** ([@evevkovacs](https://github.com/LSSTDESC/DC2-analysis/issues/new?body=@evevkovacs))\n",
-    "<br>Last Verified to Run: Nov 30, 2018 by @yymao\n",
+    "<br>Last Verified to Run: March 1, 2024 by @fjaviersanchez\n",
     "\n",
     "This notebook demonstrates how to make number-density versus redshift plots from the extragalactic catalog (protoDC2, cosmoDC2).\n",
     "\n",
@@ -26,7 +26,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "from itertools import zip_longest\n",
@@ -49,7 +51,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "gc = GCRCatalogs.load_catalog('cosmoDC2_v1.1.4_small')"
@@ -71,7 +75,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def get_mags_and_redshift(gc, mag_lo, mag_hi, band='r', z='redshift_true', zlo=0., zhi=1.1, \n",
@@ -86,7 +92,7 @@
     "    filters = [(lambda z: (z > zlo) & (z < zhi), z)]  # Filter on selected redshift range\n",
     "    \n",
     "    # Initialize arrays for storing histogram sums\n",
-    "    N_array = np.zeros((nrows, ncolumns, len(zbins)-1), dtype=np.int)\n",
+    "    N_array = np.zeros((nrows, ncolumns, len(zbins)-1), dtype=np.int32)\n",
     "    sumz_array = np.zeros((nrows, ncolumns, len(zbins)-1))\n",
     "    # Get catalog data by looping over data iterator (needed for large catalogs) and aggregate histograms\n",
     "    for catalog_data in gc.get_quantities(required_quantities, filters=filters, return_iterator=True):\n",
@@ -122,14 +128,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# Select some magnitude cuts and fill the histogram arrays for 2-column plots\n",
     "mlo = 25\n",
     "mhi = 19\n",
     "\n",
-    "mag_lo = 1 + np.arange(mhi, mlo, dtype=np.float)\n",
+    "mag_lo = 1 + np.arange(mhi, mlo, dtype=np.float64)\n",
     "mag_hi = mhi + np.zeros_like(mag_lo)\n",
     "\n",
     "ncolumns = 2\n",
@@ -149,7 +157,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def plot_N_vs_z(mag_lo, mag_hi, N_array, sumz_array, zbins, band='r', normed=True,\n",
@@ -187,7 +197,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "def decorate_subplot(ax, nplot, nrows, ncolumns, ylabel, xlabel):\n",
@@ -211,7 +223,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "plot_N_vs_z(mag_lo, mag_hi, N_array, sumz_array, zbins, nrows=nrows, ncolumns=ncolumns, normed=True)"
@@ -258,9 +272,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.10.13"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }