add dockerfile

henrysky · Aug 10, 2024 · 68791f9 · 68791f9
1 parent b77c89a
commit 68791f9
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diff --git a/ASPCAP_Normalization.ipynb b/ASPCAP_Normalization.ipynb
@@ -376,12 +376,12 @@
     "compiler_aspcap_train.vscattercut = 1  # Velocity Scattering Upper\n",
     "compiler_aspcap_train.starflagcut = True  # STARFLAG == 0\n",
     "compiler_aspcap_train.aspcapflagcut = True  # ASPCAPFALG == 0\n",
-    "compiler_aspcap_train.ironlow = -10000.  # [Fe/H] Lower\n",
+    "compiler_aspcap_train.ironlow = -10000.0  # [Fe/H] Lower\n",
     "compiler_aspcap_train.continuum = False  # use aspcap normalization\n",
     "compiler_aspcap_train.SNR_low = 200  # SNR Lower\n",
     "compiler_aspcap_train.SNR_high = 99999  # SNR Upper\n",
     "\n",
-    "compiler_aspcap_train.filename = 'aspcap_norm_train'\n",
+    "compiler_aspcap_train.filename = \"aspcap_norm_train\"\n",
     "\n",
     "# To compile a .h5 datasets, use .compile() method\n",
     "compiler_aspcap_train.compile()"
@@ -715,12 +715,12 @@
     "compiler_aspcap_test.vscattercut = 1  # Velocity Scattering Upper\n",
     "compiler_aspcap_test.starflagcut = True  # STARFLAG == 0\n",
     "compiler_aspcap_test.aspcapflagcut = True  # ASPCAPFALG == 0\n",
-    "compiler_aspcap_test.ironlow = -10000.  # [Fe/H] Lower\n",
+    "compiler_aspcap_test.ironlow = -10000.0  # [Fe/H] Lower\n",
     "compiler_aspcap_test.continuum = False  # use aspcap normalization\n",
     "compiler_aspcap_test.SNR_low = 100  # SNR Lower\n",
     "compiler_aspcap_test.SNR_high = 200  # SNR Upper\n",
     "\n",
-    "compiler_aspcap_test.filename = 'aspcap_norm_test'\n",
+    "compiler_aspcap_test.filename = \"aspcap_norm_test\"\n",
     "\n",
     "# To compile a .h5 datasets, use .compile() method\n",
     "compiler_aspcap_test.compile()"
@@ -941,17 +941,39 @@
     "from utils_h5 import H5Loader\n",
     "from astroNN.models import ApogeeBCNNCensored\n",
     "\n",
-    "loader = H5Loader('aspcap_norm_train')  # continuum normalized dataset\n",
+    "loader = H5Loader(\"aspcap_norm_train\")  # continuum normalized dataset\n",
     "loader.load_err = True\n",
-    "loader.target = ['teff', 'logg', 'C', 'C1', 'N', 'O', 'Na', 'Mg', 'Al', 'Si', 'P', 'S', 'K',\n",
-    "                 'Ca', 'Ti', 'Ti2', 'V', 'Cr', 'Mn', 'Fe','Co', 'Ni']\n",
+    "loader.target = [\n",
+    "    \"teff\",\n",
+    "    \"logg\",\n",
+    "    \"C\",\n",
+    "    \"C1\",\n",
+    "    \"N\",\n",
+    "    \"O\",\n",
+    "    \"Na\",\n",
+    "    \"Mg\",\n",
+    "    \"Al\",\n",
+    "    \"Si\",\n",
+    "    \"P\",\n",
+    "    \"S\",\n",
+    "    \"K\",\n",
+    "    \"Ca\",\n",
+    "    \"Ti\",\n",
+    "    \"Ti2\",\n",
+    "    \"V\",\n",
+    "    \"Cr\",\n",
+    "    \"Mn\",\n",
+    "    \"Fe\",\n",
+    "    \"Co\",\n",
+    "    \"Ni\",\n",
+    "]\n",
     "x, y, x_err, y_err = loader.load()\n",
     "\n",
     "bcnn = ApogeeBCNNCensored()\n",
     "bcnn.num_hidden = [192, 64, 32, 16, 2]  # default model size used in the paper\n",
     "bcnn.max_epochs = 60  # default max epochs used in the paper\n",
     "bcnn.autosave = True\n",
-    "bcnn.folder_name = 'aspcapStar_BCNNCensored'\n",
+    "bcnn.folder_name = \"aspcapStar_BCNNCensored\"\n",
     "\n",
     "bcnn.train(x, y, labels_err=y_err)"
    ]
@@ -1181,22 +1203,48 @@
     "from utils_h5 import H5Loader\n",
     "from astroNN.models import ApogeeBCNNCensored, load_folder\n",
     "\n",
-    "loader = H5Loader('aspcap_norm_test')  # continuum normalized dataset\n",
+    "loader = H5Loader(\"aspcap_norm_test\")  # continuum normalized dataset\n",
     "loader.load_err = True\n",
-    "loader.target = ['teff', 'logg', 'C', 'C1', 'N', 'O', 'Na', 'Mg', 'Al', 'Si', 'P', 'S', 'K',\n",
-    "                 'Ca', 'Ti', 'Ti2', 'V', 'Cr', 'Mn', 'Fe','Co', 'Ni']\n",
+    "loader.target = [\n",
+    "    \"teff\",\n",
+    "    \"logg\",\n",
+    "    \"C\",\n",
+    "    \"C1\",\n",
+    "    \"N\",\n",
+    "    \"O\",\n",
+    "    \"Na\",\n",
+    "    \"Mg\",\n",
+    "    \"Al\",\n",
+    "    \"Si\",\n",
+    "    \"P\",\n",
+    "    \"S\",\n",
+    "    \"K\",\n",
+    "    \"Ca\",\n",
+    "    \"Ti\",\n",
+    "    \"Ti2\",\n",
+    "    \"V\",\n",
+    "    \"Cr\",\n",
+    "    \"Mn\",\n",
+    "    \"Fe\",\n",
+    "    \"Co\",\n",
+    "    \"Ni\",\n",
+    "]\n",
     "x, y, x_err, y_err = loader.load()\n",
     "\n",
-    "bcnn = load_folder('aspcapStar_BCNNCensored')\n",
+    "bcnn = load_folder(\"aspcapStar_BCNNCensored\")\n",
     "\n",
     "pred, pred_error = bcnn.test(x, y)\n",
     "\n",
-    "residue = (pred - y)\n",
+    "residue = pred - y\n",
     "\n",
-    "bias = np.ma.median(np.ma.array(residue, mask=[y == -9999.]), axis=0)\n",
-    "scatter = mad(np.ma.array(residue, mask=[y == -9999.]), axis=0)\n",
+    "bias = np.ma.median(np.ma.array(residue, mask=[y == -9999.0]), axis=0)\n",
+    "scatter = mad(np.ma.array(residue, mask=[y == -9999.0]), axis=0)\n",
     "\n",
-    "d = {'Name': bcnn.targetname, 'Bias': [f'{bias_single:.{3}f}' for bias_single in bias], 'Scatter': [f'{scatter_single:.{3}f}' for scatter_single in scatter]}\n",
+    "d = {\n",
+    "    \"Name\": bcnn.targetname,\n",
+    "    \"Bias\": [f\"{bias_single:.{3}f}\" for bias_single in bias],\n",
+    "    \"Scatter\": [f\"{scatter_single:.{3}f}\" for scatter_single in scatter],\n",
+    "}\n",
     "df = pd.DataFrame(data=d)\n",
     "df"
    ]