From 68635fab73cffdece0ee88a352d966979709ea92 Mon Sep 17 00:00:00 2001
From: "Daniel.Frisinghelli" <daniel.frisinghelli@eurac.edu>
Date: Wed, 6 Oct 2021 15:11:22 +0000
Subject: [PATCH] Refactor.
---
Notebooks/check_predictors.ipynb | 103 ++++++++++++++++++++++++++++++-
Notebooks/eval_temperature.ipynb | 2 +-
2 files changed, 101 insertions(+), 4 deletions(-)
diff --git a/Notebooks/check_predictors.ipynb b/Notebooks/check_predictors.ipynb
index 4cb2f92..dd442c4 100644
--- a/Notebooks/check_predictors.ipynb
+++ b/Notebooks/check_predictors.ipynb
@@ -22,12 +22,15 @@
"import numpy as np\n",
"import pandas as pd\n",
"import xarray as xr\n",
- "from sklearn.linear_model import TweedieRegressor\n",
+ "from sklearn.model_selection import train_test_split\n",
"\n",
"# locals\n",
+ "from pysegcnn.core.utils import search_files\n",
"from climax.core.dataset import ERA5Dataset\n",
"from climax.core.constants import ERA5_VARIABLES\n",
- "from climax.core.utils import search_files"
+ "from climax.core.utils import search_files\n",
+ "from climax.main.config import CALIB_PERIOD\n",
+ "from climax.main.io import OBS_PATH"
]
},
{
@@ -169,7 +172,101 @@
"metadata": {},
"outputs": [],
"source": [
- "xr.merge([predictors, dem])"
+ "Era5_ds = xr.merge([predictors, dem])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "dd584313-8913-45b5-a379-2724d42bc99f",
+ "metadata": {},
+ "source": [
+ "## Read observations"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e982d6f9-ae6b-435e-917d-44118c6a09b1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "PREDICTAND = 'pr'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fe45a13d-d95d-4260-a3bc-0e6fd53db732",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# read in-situ gridded observations\n",
+ "Obs_ds = search_files(OBS_PATH.joinpath(PREDICTAND), 'OBS_{}(.*).nc$'.format(PREDICTAND)).pop()\n",
+ "Obs_ds = xr.open_dataset(Obs_ds)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "caaf0557-74a9-4c30-9697-bb58d68553aa",
+ "metadata": {},
+ "source": [
+ "## Group predictors by season"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c98896f5-7953-4bb3-af97-fd98740514d1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# split into training and validation set\n",
+ "train, valid = train_test_split(CALIB_PERIOD, shuffle=False, test_size=0.1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1a7295fd-3c57-4ca4-9c47-23a179db4829",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# training and validation dataset\n",
+ "Era5_train, Obs_train = Era5_ds.sel(time=train), Obs_ds.sel(time=train)\n",
+ "Era5_valid, Obs_valid = Era5_ds.sel(time=valid), Obs_ds.sel(time=valid)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "82a88472-7837-4fa6-a591-1f1952ea442b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# group predictors and predictand by season\n",
+ "season_indices_train = Era5_train.groupby('time.season').groups\n",
+ "season_indices_valid = Era5_valid.groupby('time.season').groups\n",
+ "\n",
+ "# group training and validation set by season\n",
+ "Era_season_train = {k: Era5_train.isel(time=v) for k, v in\n",
+ " season_indices_train.items()}\n",
+ "Obs_season_train = {k: Obs_train.isel(time=v) for k, v in\n",
+ " season_indices_train.items()}\n",
+ "Era_season_valid = {k: Era5_valid.isel(time=v) for k, v in\n",
+ " season_indices_valid.items()}\n",
+ "Obs_season_valid = {k: Obs_valid.isel(time=v) for k, v in\n",
+ " season_indices_valid.items()}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dde5735a-4633-452f-aada-22da3a15696e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "Era_season_train = {k: Era5_train.isel(time=v) for k, v in\n",
+ " season_indices_train.items()}"
]
}
],
diff --git a/Notebooks/eval_temperature.ipynb b/Notebooks/eval_temperature.ipynb
index 1193bc3..f315da9 100644
--- a/Notebooks/eval_temperature.ipynb
+++ b/Notebooks/eval_temperature.ipynb
@@ -498,7 +498,7 @@
"\n",
"# adjust figure\n",
"fig.suptitle('Average {}: 1991 - 2010'.format(NAMES[PREDICTAND]), fontsize=20);\n",
- "fig.subplots_adjust(hspace=0, wspace=0, top=0.85)\n",
+ "fig.subplots_adjust(hspace=0, wspace=0, top=0.85)c\n",
"\n",
"# add colorbar for bias\n",
"axes = axes.flatten()\n",
--
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