Merge pull request #9 from CDJellen/develop

Update for preprint

.gitignore

@@ -7,5 +7,9 @@
 .venv
 .coverage
 coverage.xml
-otb/cache/processed/*.pickle
+otbench/cache/processed/*.pickle
 doc/
+!notebooks/overview.ipynb
+!notebooks/forecasting/*.ipynb
+!notebooks/regression/*.ipynb
+!notebooks/pytorch/*.ipynb

conftest.py

@@ -3,7 +3,7 @@
 import pandas as pd
 import pytest
 
-from otb.tasks import TaskApi
+from otbench.tasks import TaskApi
 
 
 def pytest_addoption(parser):

notebooks/overview.ipynb

@@ -17,17 +17,6 @@
     "A similar interactive example focued on regression using the MLO $C_n^2$ dataset is provided [here](/notebooks/regression/mlo_cn2.ipynb)."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import sys\n",
-    "\n",
-    "sys.path.append('../../')"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -36,7 +25,7 @@
    "source": [
     "import pprint\n",
     "\n",
-    "from otb.tasks import TaskApi"
+    "from otbench.tasks import TaskApi"
    ]
   },
   {
@@ -151,12 +140,12 @@
     {
      "data": {
       "text/plain": [
-       "['regression.usna_cn2_sm.full.Cn2_3m',\n",
+       "['forecasting.usna_cn2_sm.full.Cn2_3m',\n",
+       " 'regression.usna_cn2_lg.full.Cn2_3m',\n",
        " 'forecasting.mlo_cn2.dropna.Cn2_15m',\n",
-       " 'regression.mlo_cn2.full.Cn2_15m',\n",
+       " 'regression.usna_cn2_sm.full.Cn2_3m',\n",
        " 'regression.mlo_cn2.dropna.Cn2_15m',\n",
-       " 'forecasting.usna_cn2_sm.full.Cn2_3m',\n",
-       " 'regression.usna_cn2_lg.full.Cn2_3m']"
+       " 'regression.mlo_cn2.full.Cn2_15m']"
       ]
      },
      "execution_count": 5,
@@ -291,7 +280,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "More information on using the `otb` package to evaluate new models can be found in the [regression overview](regression/modeling.ipynb) notebook and the [forecasting overview](forecasting/usna_cn2_sm.ipynb)."
+    "More information on using the `otbench` package to evaluate new models can be found in the [regression overview](regression/modeling.ipynb) notebook and the [forecasting overview](forecasting/usna_cn2_sm.ipynb)."
    ]
   }
  ],