diff --git a/SYNOP/01-Preparation-of-data.ipynb b/SYNOP/01-Preparation-of-data.ipynb
index 3bcfd9486a14567a88a205374ce52c26d9dfb616..be9fa921dea501a6b0f15b4dae8a2c0611a25905 100644
--- a/SYNOP/01-Preparation-of-data.ipynb
+++ b/SYNOP/01-Preparation-of-data.ipynb
@@ -90,8 +90,8 @@
"text": [
"\n",
"FIDLE 2020 - Practical Work Module\n",
- "Version : 0.4.3\n",
- "Run time : Saturday 29 February 2020, 14:34:21\n",
+ "Version : 0.4.4\n",
+ "Run time : Saturday 29 February 2020, 17:20:30\n",
"TensorFlow version : 2.0.0\n",
"Keras version : 2.2.4-tf\n"
]
@@ -113,13 +113,10 @@
"\n",
"sys.path.append('..')\n",
"import fidle.pwk as ooo\n",
+ "from fidle.pwk import subtitle\n",
"\n",
"ooo.init()\n",
- "pd.set_option('display.max_rows',200)\n",
- "\n",
- "def subtitle(t):\n",
- " ooo.display_md(f'<br>**{t}**')\n",
- " "
+ "pd.set_option('display.max_rows',200)\n"
]
},
{
@@ -138,8 +135,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Well, we should be at HOME !\n",
- "We are going to use: /home/pjluc/datasets/SYNOP\n"
+ "Well, we should be at GRICAD !\n",
+ "We are going to use: /bettik/PROJECTS/pr-fidle/datasets/SYNOP\n"
]
}
],
@@ -606,983 +603,983 @@
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- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow27_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow27_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow27_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow27_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow28_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow28_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow28_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow28_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow28_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow28_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow29_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow29_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow29_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow29_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow29_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow29_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow30_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow30_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow30_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow30_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow30_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow30_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow31_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow31_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow31_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow31_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow31_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow31_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow32_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow32_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow32_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow32_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow32_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow32_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow33_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow33_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow33_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow33_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow33_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow33_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow34_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow34_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow34_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow34_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow34_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow34_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow35_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow35_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow35_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow35_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow35_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow35_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow36_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow36_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow36_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow36_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow36_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow36_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow37_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow37_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow37_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow37_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow37_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow37_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow38_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow38_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow38_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow38_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow38_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow38_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow39_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow39_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow39_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow39_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow39_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow39_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow40_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow40_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow40_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow40_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow40_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow40_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow41_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow41_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow41_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow41_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow41_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow41_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow42_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow42_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow42_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow42_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow42_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow42_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow43_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow43_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow43_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow43_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow43_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow43_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow44_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow44_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow44_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow44_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow44_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow44_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow45_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow45_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow45_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow45_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow45_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow45_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow46_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow46_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow46_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow46_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow46_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow46_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow47_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow47_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow47_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow47_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow47_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow47_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow48_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow48_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow48_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow48_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow48_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow48_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow49_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow49_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow49_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow49_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow49_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow49_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow50_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow50_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow50_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow50_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow50_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow50_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow51_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow51_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow51_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow51_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow51_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow51_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow52_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow52_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow52_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow52_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow52_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow52_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow53_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow53_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow53_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow53_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow53_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow53_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow54_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow54_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow54_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow54_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow54_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow54_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow55_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow55_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow55_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow55_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow55_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow55_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow56_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow56_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow56_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow56_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow56_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow56_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow57_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow57_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow57_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow57_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow57_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow57_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow58_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow58_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow58_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow58_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow58_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow58_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow59_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow59_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow59_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow59_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow59_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow59_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow60_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow60_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow60_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow60_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow60_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow60_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow61_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow61_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow61_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow61_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow61_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow61_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow62_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow62_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow62_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow62_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow62_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow62_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow63_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow63_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow63_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow63_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow63_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow63_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow64_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow64_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow64_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow64_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow64_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow64_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow65_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow65_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow65_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow65_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow65_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow65_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow66_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow66_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow66_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow66_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow66_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow66_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow67_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow67_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow67_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow67_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow67_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow67_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow68_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow68_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow68_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow68_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow68_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow68_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow69_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow69_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow69_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow69_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow69_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow69_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow70_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow70_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow70_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow70_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow70_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow70_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow71_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow71_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow71_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow71_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow71_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow71_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow72_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow72_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow72_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow72_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow72_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow72_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow73_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow73_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow73_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow73_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow73_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow73_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow74_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow74_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow74_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow74_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow74_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow74_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow75_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow75_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow75_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow75_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow75_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow75_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow76_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow76_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow76_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow76_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow76_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow76_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow77_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow77_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow77_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow77_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow77_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow77_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow78_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow78_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow78_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow78_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow78_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow78_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow79_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow79_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow79_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow79_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow79_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow79_col2 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow80_col0 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow80_col0 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow80_col1 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow80_col1 {\n",
" text-align: left;\n",
- " } #T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow80_col2 {\n",
+ " } #T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow80_col2 {\n",
" text-align: left;\n",
- " }</style><table id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686b\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >Code</th> <th class=\"col_heading level0 col1\" >Description</th> <th class=\"col_heading level0 col2\" >Na</th> </tr></thead><tbody>\n",
+ " }</style><table id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeb\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >Code</th> <th class=\"col_heading level0 col1\" >Description</th> <th class=\"col_heading level0 col2\" >Na</th> </tr></thead><tbody>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow0_col0\" class=\"data row0 col0\" >numer_sta</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow0_col1\" class=\"data row0 col1\" >ID OMM station</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow0_col2\" class=\"data row0 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow0_col0\" class=\"data row0 col0\" >numer_sta</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow0_col1\" class=\"data row0 col1\" >ID OMM station</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow0_col2\" class=\"data row0 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow1_col0\" class=\"data row1 col0\" >date</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow1_col1\" class=\"data row1 col1\" >Date</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow1_col2\" class=\"data row1 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow1_col0\" class=\"data row1 col0\" >date</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow1_col1\" class=\"data row1 col1\" >Date</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow1_col2\" class=\"data row1 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow2_col0\" class=\"data row2 col0\" >pmer</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow2_col1\" class=\"data row2 col1\" >Pression au niveau mer</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow2_col2\" class=\"data row2 col2\" >17</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow2_col0\" class=\"data row2 col0\" >pmer</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow2_col1\" class=\"data row2 col1\" >Pression au niveau mer</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow2_col2\" class=\"data row2 col2\" >17</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow3_col0\" class=\"data row3 col0\" >tend</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow3_col1\" class=\"data row3 col1\" >Variation de pression en 3 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow3_col2\" class=\"data row3 col2\" >2</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow3_col0\" class=\"data row3 col0\" >tend</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow3_col1\" class=\"data row3 col1\" >Variation de pression en 3 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow3_col2\" class=\"data row3 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow4_col0\" class=\"data row4 col0\" >cod_tend</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow4_col1\" class=\"data row4 col1\" >Type de tendance barométrique</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow4_col2\" class=\"data row4 col2\" >2</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow4_col0\" class=\"data row4 col0\" >cod_tend</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow4_col1\" class=\"data row4 col1\" >Type de tendance barométrique</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow4_col2\" class=\"data row4 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow5_col0\" class=\"data row5 col0\" >dd</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow5_col1\" class=\"data row5 col1\" >Direction du vent moyen 10 mn</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow5_col2\" class=\"data row5 col2\" >3</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow5_col0\" class=\"data row5 col0\" >dd</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow5_col1\" class=\"data row5 col1\" >Direction du vent moyen 10 mn</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow5_col2\" class=\"data row5 col2\" >3</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow6_col0\" class=\"data row6 col0\" >ff</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow6_col1\" class=\"data row6 col1\" >Vitesse du vent moyen 10 mn</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow6_col2\" class=\"data row6 col2\" >2</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow6_col0\" class=\"data row6 col0\" >ff</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow6_col1\" class=\"data row6 col1\" >Vitesse du vent moyen 10 mn</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow6_col2\" class=\"data row6 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow7_col0\" class=\"data row7 col0\" >t</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow7_col1\" class=\"data row7 col1\" >Température</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow7_col2\" class=\"data row7 col2\" >14</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow7_col0\" class=\"data row7 col0\" >t</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow7_col1\" class=\"data row7 col1\" >Température</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow7_col2\" class=\"data row7 col2\" >14</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow8_col0\" class=\"data row8 col0\" >td</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow8_col1\" class=\"data row8 col1\" >Point de rosée</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow8_col2\" class=\"data row8 col2\" >17</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow8_col0\" class=\"data row8 col0\" >td</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow8_col1\" class=\"data row8 col1\" >Point de rosée</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow8_col2\" class=\"data row8 col2\" >17</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow9_col0\" class=\"data row9 col0\" >u</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow9_col1\" class=\"data row9 col1\" >Humidité</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow9_col2\" class=\"data row9 col2\" >17</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow9_col0\" class=\"data row9 col0\" >u</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow9_col1\" class=\"data row9 col1\" >Humidité</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow9_col2\" class=\"data row9 col2\" >17</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow10_col0\" class=\"data row10 col0\" >vv</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow10_col1\" class=\"data row10 col1\" >Visibilité horizontale</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow10_col2\" class=\"data row10 col2\" >31</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow10_col0\" class=\"data row10 col0\" >vv</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow10_col1\" class=\"data row10 col1\" >Visibilité horizontale</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow10_col2\" class=\"data row10 col2\" >31</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow11_col0\" class=\"data row11 col0\" >ww</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow11_col1\" class=\"data row11 col1\" >Temps présent</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow11_col2\" class=\"data row11 col2\" >1</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow11_col0\" class=\"data row11 col0\" >ww</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow11_col1\" class=\"data row11 col1\" >Temps présent</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow11_col2\" class=\"data row11 col2\" >1</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow12_col0\" class=\"data row12 col0\" >w1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow12_col1\" class=\"data row12 col1\" >Temps passé 1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow12_col2\" class=\"data row12 col2\" >542</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow12_col0\" class=\"data row12 col0\" >w1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow12_col1\" class=\"data row12 col1\" >Temps passé 1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow12_col2\" class=\"data row12 col2\" >542</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow13_col0\" class=\"data row13 col0\" >w2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow13_col1\" class=\"data row13 col1\" >Temps passé 2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow13_col2\" class=\"data row13 col2\" >552</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow13_col0\" class=\"data row13 col0\" >w2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow13_col1\" class=\"data row13 col1\" >Temps passé 2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow13_col2\" class=\"data row13 col2\" >552</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow14_col0\" class=\"data row14 col0\" >n</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow14_col1\" class=\"data row14 col1\" >Nebulosité totale</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow14_col2\" class=\"data row14 col2\" >801</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow14_col0\" class=\"data row14 col0\" >n</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow14_col1\" class=\"data row14 col1\" >Nebulosité totale</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow14_col2\" class=\"data row14 col2\" >801</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow15_col0\" class=\"data row15 col0\" >nbas</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow15_col1\" class=\"data row15 col1\" >Nébulosité des nuages de l' étage inférieur</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow15_col2\" class=\"data row15 col2\" >2381</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow15_col0\" class=\"data row15 col0\" >nbas</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow15_col1\" class=\"data row15 col1\" >Nébulosité des nuages de l' étage inférieur</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow15_col2\" class=\"data row15 col2\" >2381</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow16_col0\" class=\"data row16 col0\" >hbas</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow16_col1\" class=\"data row16 col1\" >Hauteur de la base des nuages de l'étage inférieur</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow16_col2\" class=\"data row16 col2\" >8861</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow16_col0\" class=\"data row16 col0\" >hbas</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow16_col1\" class=\"data row16 col1\" >Hauteur de la base des nuages de l'étage inférieur</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow16_col2\" class=\"data row16 col2\" >8861</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow17_col0\" class=\"data row17 col0\" >cl</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow17_col1\" class=\"data row17 col1\" >Type des nuages de l'étage inférieur</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow17_col2\" class=\"data row17 col2\" >3377</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow17_col0\" class=\"data row17 col0\" >cl</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow17_col1\" class=\"data row17 col1\" >Type des nuages de l'étage inférieur</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow17_col2\" class=\"data row17 col2\" >3377</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow18_col0\" class=\"data row18 col0\" >cm</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow18_col1\" class=\"data row18 col1\" >Type des nuages de l'étage moyen</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow18_col2\" class=\"data row18 col2\" >6912</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow18_col0\" class=\"data row18 col0\" >cm</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow18_col1\" class=\"data row18 col1\" >Type des nuages de l'étage moyen</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow18_col2\" class=\"data row18 col2\" >6912</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow19_col0\" class=\"data row19 col0\" >ch</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow19_col1\" class=\"data row19 col1\" >Type des nuages de l'étage supérieur</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow19_col2\" class=\"data row19 col2\" >8494</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow19_col0\" class=\"data row19 col0\" >ch</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow19_col1\" class=\"data row19 col1\" >Type des nuages de l'étage supérieur</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow19_col2\" class=\"data row19 col2\" >8494</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow20_col0\" class=\"data row20 col0\" >pres</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow20_col1\" class=\"data row20 col1\" >Pression station</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow20_col2\" class=\"data row20 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow20_col0\" class=\"data row20 col0\" >pres</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow20_col1\" class=\"data row20 col1\" >Pression station</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow20_col2\" class=\"data row20 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow21_col0\" class=\"data row21 col0\" >niv_bar</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow21_col1\" class=\"data row21 col1\" >Niveau barométrique</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow21_col2\" class=\"data row21 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow21_col0\" class=\"data row21 col0\" >niv_bar</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow21_col1\" class=\"data row21 col1\" >Niveau barométrique</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow21_col2\" class=\"data row21 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow22_col0\" class=\"data row22 col0\" >geop</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow22_col1\" class=\"data row22 col1\" >Géopotentiel</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow22_col2\" class=\"data row22 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow22_col0\" class=\"data row22 col0\" >geop</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow22_col1\" class=\"data row22 col1\" >Géopotentiel</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow22_col2\" class=\"data row22 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow23_col0\" class=\"data row23 col0\" >tend24</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow23_col1\" class=\"data row23 col1\" >Variation de pression en 24 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow23_col2\" class=\"data row23 col2\" >14443</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow23_col0\" class=\"data row23 col0\" >tend24</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow23_col1\" class=\"data row23 col1\" >Variation de pression en 24 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow23_col2\" class=\"data row23 col2\" >14443</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow24_col0\" class=\"data row24 col0\" >tn12</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow24_col1\" class=\"data row24 col1\" >Température minimale sur 12 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow24_col2\" class=\"data row24 col2\" >21883</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow24_col0\" class=\"data row24 col0\" >tn12</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow24_col1\" class=\"data row24 col1\" >Température minimale sur 12 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow24_col2\" class=\"data row24 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow25_col0\" class=\"data row25 col0\" >tn24</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow25_col1\" class=\"data row25 col1\" >Température minimale sur 24 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow25_col2\" class=\"data row25 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow25_col0\" class=\"data row25 col0\" >tn24</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow25_col1\" class=\"data row25 col1\" >Température minimale sur 24 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow25_col2\" class=\"data row25 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow26_col0\" class=\"data row26 col0\" >tx12</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow26_col1\" class=\"data row26 col1\" >Température maximale sur 12 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow26_col2\" class=\"data row26 col2\" >21883</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow26_col0\" class=\"data row26 col0\" >tx12</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow26_col1\" class=\"data row26 col1\" >Température maximale sur 12 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow26_col2\" class=\"data row26 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow27_col0\" class=\"data row27 col0\" >tx24</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow27_col1\" class=\"data row27 col1\" >Température maximale sur 24 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow27_col2\" class=\"data row27 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow27_col0\" class=\"data row27 col0\" >tx24</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow27_col1\" class=\"data row27 col1\" >Température maximale sur 24 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow27_col2\" class=\"data row27 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow28_col0\" class=\"data row28 col0\" >tminsol</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow28_col1\" class=\"data row28 col1\" >Température minimale du sol sur 12 heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow28_col2\" class=\"data row28 col2\" >27364</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow28_col0\" class=\"data row28 col0\" >tminsol</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow28_col1\" class=\"data row28 col1\" >Température minimale du sol sur 12 heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow28_col2\" class=\"data row28 col2\" >27364</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow29_col0\" class=\"data row29 col0\" >sw</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow29_col1\" class=\"data row29 col1\" >Méthode de mesure Température du thermomètre mouillé</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow29_col2\" class=\"data row29 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow29_col0\" class=\"data row29 col0\" >sw</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow29_col1\" class=\"data row29 col1\" >Méthode de mesure Température du thermomètre mouillé</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow29_col2\" class=\"data row29 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow30_col0\" class=\"data row30 col0\" >tw</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow30_col1\" class=\"data row30 col1\" >Température du thermomètre mouillé</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow30_col2\" class=\"data row30 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow30_col0\" class=\"data row30 col0\" >tw</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow30_col1\" class=\"data row30 col1\" >Température du thermomètre mouillé</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow30_col2\" class=\"data row30 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow31_col0\" class=\"data row31 col0\" >raf10</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow31_col1\" class=\"data row31 col1\" >Rafale sur les 10 dernières minutes</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow31_col2\" class=\"data row31 col2\" >14127</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow31_col0\" class=\"data row31 col0\" >raf10</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow31_col1\" class=\"data row31 col1\" >Rafale sur les 10 dernières minutes</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow31_col2\" class=\"data row31 col2\" >14127</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow32_col0\" class=\"data row32 col0\" >rafper</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow32_col1\" class=\"data row32 col1\" >Rafales sur une période</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow32_col2\" class=\"data row32 col2\" >9</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow32_col0\" class=\"data row32 col0\" >rafper</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow32_col1\" class=\"data row32 col1\" >Rafales sur une période</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow32_col2\" class=\"data row32 col2\" >9</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow33_col0\" class=\"data row33 col0\" >per</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow33_col1\" class=\"data row33 col1\" >Periode de mesure de la rafale</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow33_col2\" class=\"data row33 col2\" >8</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow33_col0\" class=\"data row33 col0\" >per</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow33_col1\" class=\"data row33 col1\" >Periode de mesure de la rafale</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow33_col2\" class=\"data row33 col2\" >8</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow34_col0\" class=\"data row34 col0\" >etat_sol</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow34_col1\" class=\"data row34 col1\" >Etat du sol</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow34_col2\" class=\"data row34 col2\" >12278</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow34_col0\" class=\"data row34 col0\" >etat_sol</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow34_col1\" class=\"data row34 col1\" >Etat du sol</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow34_col2\" class=\"data row34 col2\" >12278</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow35_col0\" class=\"data row35 col0\" >ht_neige</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow35_col1\" class=\"data row35 col1\" >Hauteur totale de la couche de neige, glace, autre au sol</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow35_col2\" class=\"data row35 col2\" >12083</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow35_col0\" class=\"data row35 col0\" >ht_neige</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow35_col1\" class=\"data row35 col1\" >Hauteur totale de la couche de neige, glace, autre au sol</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow35_col2\" class=\"data row35 col2\" >12083</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow36_col0\" class=\"data row36 col0\" >ssfrai</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow36_col1\" class=\"data row36 col1\" >Hauteur de la neige fraîche</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow36_col2\" class=\"data row36 col2\" >2914</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow36_col0\" class=\"data row36 col0\" >ssfrai</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow36_col1\" class=\"data row36 col1\" >Hauteur de la neige fraîche</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow36_col2\" class=\"data row36 col2\" >2914</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow37_col0\" class=\"data row37 col0\" >perssfrai</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow37_col1\" class=\"data row37 col1\" >Periode de mesure de la neige fraiche</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow37_col2\" class=\"data row37 col2\" >4489</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow37_col0\" class=\"data row37 col0\" >perssfrai</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow37_col1\" class=\"data row37 col1\" >Periode de mesure de la neige fraiche</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow37_col2\" class=\"data row37 col2\" >4489</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow38_col0\" class=\"data row38 col0\" >rr1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow38_col1\" class=\"data row38 col1\" >Précipitations dans la dernière heure</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow38_col2\" class=\"data row38 col2\" >95</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow38_col0\" class=\"data row38 col0\" >rr1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow38_col1\" class=\"data row38 col1\" >Précipitations dans la dernière heure</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow38_col2\" class=\"data row38 col2\" >95</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow39_col0\" class=\"data row39 col0\" >rr3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow39_col1\" class=\"data row39 col1\" >Précipitations dans les 3 dernières heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow39_col2\" class=\"data row39 col2\" >73</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow39_col0\" class=\"data row39 col0\" >rr3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow39_col1\" class=\"data row39 col1\" >Précipitations dans les 3 dernières heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow39_col2\" class=\"data row39 col2\" >73</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow40_col0\" class=\"data row40 col0\" >rr6</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow40_col1\" class=\"data row40 col1\" >Précipitations dans les 6 dernières heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow40_col2\" class=\"data row40 col2\" >10869</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow40_col0\" class=\"data row40 col0\" >rr6</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow40_col1\" class=\"data row40 col1\" >Précipitations dans les 6 dernières heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow40_col2\" class=\"data row40 col2\" >10869</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow41_col0\" class=\"data row41 col0\" >rr12</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow41_col1\" class=\"data row41 col1\" >Précipitations dans les 12 dernières heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow41_col2\" class=\"data row41 col2\" >10919</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow41_col0\" class=\"data row41 col0\" >rr12</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow41_col1\" class=\"data row41 col1\" >Précipitations dans les 12 dernières heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow41_col2\" class=\"data row41 col2\" >10919</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow42_col0\" class=\"data row42 col0\" >rr24</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow42_col1\" class=\"data row42 col1\" >Précipitations dans les 24 dernières heures</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow42_col2\" class=\"data row42 col2\" >12730</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow42_col0\" class=\"data row42 col0\" >rr24</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow42_col1\" class=\"data row42 col1\" >Précipitations dans les 24 dernières heures</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow42_col2\" class=\"data row42 col2\" >12730</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow43_col0\" class=\"data row43 col0\" >phenspe1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow43_col1\" class=\"data row43 col1\" >Phénomène spécial 1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow43_col2\" class=\"data row43 col2\" >14818</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow43_col0\" class=\"data row43 col0\" >phenspe1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow43_col1\" class=\"data row43 col1\" >Phénomène spécial 1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow43_col2\" class=\"data row43 col2\" >14818</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow44_col0\" class=\"data row44 col0\" >phenspe2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow44_col1\" class=\"data row44 col1\" >Phénomène spécial 2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow44_col2\" class=\"data row44 col2\" >14826</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow44_col0\" class=\"data row44 col0\" >phenspe2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow44_col1\" class=\"data row44 col1\" >Phénomène spécial 2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow44_col2\" class=\"data row44 col2\" >14826</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow45_col0\" class=\"data row45 col0\" >phenspe3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow45_col1\" class=\"data row45 col1\" >Phénomène spécial 3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow45_col2\" class=\"data row45 col2\" >15515</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow45_col0\" class=\"data row45 col0\" >phenspe3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow45_col1\" class=\"data row45 col1\" >Phénomène spécial 3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow45_col2\" class=\"data row45 col2\" >15515</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow46_col0\" class=\"data row46 col0\" >phenspe4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow46_col1\" class=\"data row46 col1\" >Phénomène spécial 4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow46_col2\" class=\"data row46 col2\" >28869</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow46_col0\" class=\"data row46 col0\" >phenspe4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow46_col1\" class=\"data row46 col1\" >Phénomène spécial 4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow46_col2\" class=\"data row46 col2\" >28869</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow47_col0\" class=\"data row47 col0\" >nnuage1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow47_col1\" class=\"data row47 col1\" >Nébulosité couche nuageuse 1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow47_col2\" class=\"data row47 col2\" >4753</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow47_col0\" class=\"data row47 col0\" >nnuage1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow47_col1\" class=\"data row47 col1\" >Nébulosité couche nuageuse 1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow47_col2\" class=\"data row47 col2\" >4753</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow48_col0\" class=\"data row48 col0\" >ctype1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow48_col1\" class=\"data row48 col1\" >Type nuage 1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow48_col2\" class=\"data row48 col2\" >5699</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow48_col0\" class=\"data row48 col0\" >ctype1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow48_col1\" class=\"data row48 col1\" >Type nuage 1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow48_col2\" class=\"data row48 col2\" >5699</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow49_col0\" class=\"data row49 col0\" >hnuage1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow49_col1\" class=\"data row49 col1\" >Hauteur de base 1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow49_col2\" class=\"data row49 col2\" >5439</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow49_col0\" class=\"data row49 col0\" >hnuage1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow49_col1\" class=\"data row49 col1\" >Hauteur de base 1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow49_col2\" class=\"data row49 col2\" >5439</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow50_col0\" class=\"data row50 col0\" >nnuage2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow50_col1\" class=\"data row50 col1\" >Nébulosité couche nuageuse 2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow50_col2\" class=\"data row50 col2\" >16112</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow50_col0\" class=\"data row50 col0\" >nnuage2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow50_col1\" class=\"data row50 col1\" >Nébulosité couche nuageuse 2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow50_col2\" class=\"data row50 col2\" >16112</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow51_col0\" class=\"data row51 col0\" >ctype2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow51_col1\" class=\"data row51 col1\" >Type nuage 2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow51_col2\" class=\"data row51 col2\" >16643</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow51_col0\" class=\"data row51 col0\" >ctype2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow51_col1\" class=\"data row51 col1\" >Type nuage 2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow51_col2\" class=\"data row51 col2\" >16643</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow52_col0\" class=\"data row52 col0\" >hnuage2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow52_col1\" class=\"data row52 col1\" >Hauteur de base 2</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow52_col2\" class=\"data row52 col2\" >16317</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow52_col0\" class=\"data row52 col0\" >hnuage2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow52_col1\" class=\"data row52 col1\" >Hauteur de base 2</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow52_col2\" class=\"data row52 col2\" >16317</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow53_col0\" class=\"data row53 col0\" >nnuage3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow53_col1\" class=\"data row53 col1\" >Nébulosité couche nuageuse 3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow53_col2\" class=\"data row53 col2\" >25387</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow53_col0\" class=\"data row53 col0\" >nnuage3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow53_col1\" class=\"data row53 col1\" >Nébulosité couche nuageuse 3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow53_col2\" class=\"data row53 col2\" >25387</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow54_col0\" class=\"data row54 col0\" >ctype3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow54_col1\" class=\"data row54 col1\" >Type nuage 3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow54_col2\" class=\"data row54 col2\" >25642</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow54_col0\" class=\"data row54 col0\" >ctype3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow54_col1\" class=\"data row54 col1\" >Type nuage 3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow54_col2\" class=\"data row54 col2\" >25642</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow55_col0\" class=\"data row55 col0\" >hnuage3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow55_col1\" class=\"data row55 col1\" >Hauteur de base 3</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow55_col2\" class=\"data row55 col2\" >25431</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow55_col0\" class=\"data row55 col0\" >hnuage3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow55_col1\" class=\"data row55 col1\" >Hauteur de base 3</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow55_col2\" class=\"data row55 col2\" >25431</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow56_col0\" class=\"data row56 col0\" >nnuage4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow56_col1\" class=\"data row56 col1\" >Nébulosité couche nuageuse 4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow56_col2\" class=\"data row56 col2\" >28850</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow56_col0\" class=\"data row56 col0\" >nnuage4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow56_col1\" class=\"data row56 col1\" >Nébulosité couche nuageuse 4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow56_col2\" class=\"data row56 col2\" >28850</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow57_col0\" class=\"data row57 col0\" >ctype4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow57_col1\" class=\"data row57 col1\" >Type nuage 4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow57_col2\" class=\"data row57 col2\" >28780</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow57_col0\" class=\"data row57 col0\" >ctype4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow57_col1\" class=\"data row57 col1\" >Type nuage 4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow57_col2\" class=\"data row57 col2\" >28780</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow58_col0\" class=\"data row58 col0\" >hnuage4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow58_col1\" class=\"data row58 col1\" >Hauteur de base 4</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow58_col2\" class=\"data row58 col2\" >28850</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow58_col0\" class=\"data row58 col0\" >hnuage4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow58_col1\" class=\"data row58 col1\" >Hauteur de base 4</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow58_col2\" class=\"data row58 col2\" >28850</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow59_col0\" class=\"data row59 col0\" >coordonnees</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow59_col1\" class=\"data row59 col1\" >Coordonnees</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow59_col2\" class=\"data row59 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow59_col0\" class=\"data row59 col0\" >coordonnees</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow59_col1\" class=\"data row59 col1\" >Coordonnees</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow59_col2\" class=\"data row59 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow60_col0\" class=\"data row60 col0\" >nom</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow60_col1\" class=\"data row60 col1\" >Nom</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow60_col2\" class=\"data row60 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow60_col0\" class=\"data row60 col0\" >nom</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow60_col1\" class=\"data row60 col1\" >Nom</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow60_col2\" class=\"data row60 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow61_col0\" class=\"data row61 col0\" >type_de_tendance_barometrique</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow61_col1\" class=\"data row61 col1\" >Type de tendance barométrique.1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow61_col2\" class=\"data row61 col2\" >2</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow61_col0\" class=\"data row61 col0\" >type_de_tendance_barometrique</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow61_col1\" class=\"data row61 col1\" >Type de tendance barométrique.1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow61_col2\" class=\"data row61 col2\" >2</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow62_col0\" class=\"data row62 col0\" >temps_passe_1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow62_col1\" class=\"data row62 col1\" >Temps passé 1.1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow62_col2\" class=\"data row62 col2\" >542</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow62_col0\" class=\"data row62 col0\" >temps_passe_1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow62_col1\" class=\"data row62 col1\" >Temps passé 1.1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow62_col2\" class=\"data row62 col2\" >542</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow63_col0\" class=\"data row63 col0\" >temps_present</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow63_col1\" class=\"data row63 col1\" >Temps présent.1</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow63_col2\" class=\"data row63 col2\" >1</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow63_col0\" class=\"data row63 col0\" >temps_present</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow63_col1\" class=\"data row63 col1\" >Temps présent.1</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow63_col2\" class=\"data row63 col2\" >1</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow64_col0\" class=\"data row64 col0\" >tc</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow64_col1\" class=\"data row64 col1\" >Température (°C)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow64_col2\" class=\"data row64 col2\" >14</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow64_col0\" class=\"data row64 col0\" >tc</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow64_col1\" class=\"data row64 col1\" >Température (°C)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow64_col2\" class=\"data row64 col2\" >14</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow65_col0\" class=\"data row65 col0\" >tn12c</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow65_col1\" class=\"data row65 col1\" >Température minimale sur 12 heures (°C)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow65_col2\" class=\"data row65 col2\" >21883</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow65_col0\" class=\"data row65 col0\" >tn12c</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow65_col1\" class=\"data row65 col1\" >Température minimale sur 12 heures (°C)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow65_col2\" class=\"data row65 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow66_col0\" class=\"data row66 col0\" >tn24c</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow66_col1\" class=\"data row66 col1\" >Température minimale sur 24 heures (°C)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow66_col2\" class=\"data row66 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow66_col0\" class=\"data row66 col0\" >tn24c</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow66_col1\" class=\"data row66 col1\" >Température minimale sur 24 heures (°C)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow66_col2\" class=\"data row66 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow67_col0\" class=\"data row67 col0\" >tx12c</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow67_col1\" class=\"data row67 col1\" >Température maximale sur 12 heures (°C)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow67_col2\" class=\"data row67 col2\" >21883</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow67_col0\" class=\"data row67 col0\" >tx12c</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow67_col1\" class=\"data row67 col1\" >Température maximale sur 12 heures (°C)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow67_col2\" class=\"data row67 col2\" >21883</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow68_col0\" class=\"data row68 col0\" >tx24c</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow68_col1\" class=\"data row68 col1\" >Température maximale sur 24 heures (°C)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow68_col2\" class=\"data row68 col2\" >29165</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow68_col0\" class=\"data row68 col0\" >tx24c</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow68_col1\" class=\"data row68 col1\" >Température maximale sur 24 heures (°C)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow68_col2\" class=\"data row68 col2\" >29165</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow69_col0\" class=\"data row69 col0\" >tminsolc</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow69_col1\" class=\"data row69 col1\" >Température minimale du sol sur 12 heures (en °C)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow69_col2\" class=\"data row69 col2\" >27364</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow69_col0\" class=\"data row69 col0\" >tminsolc</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow69_col1\" class=\"data row69 col1\" >Température minimale du sol sur 12 heures (en °C)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow69_col2\" class=\"data row69 col2\" >27364</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow70_col0\" class=\"data row70 col0\" >altitude</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow70_col1\" class=\"data row70 col1\" >Altitude</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow70_col2\" class=\"data row70 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow70_col0\" class=\"data row70 col0\" >altitude</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow70_col1\" class=\"data row70 col1\" >Altitude</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow70_col2\" class=\"data row70 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow71_col0\" class=\"data row71 col0\" >longitude</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow71_col1\" class=\"data row71 col1\" >Longitude</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow71_col2\" class=\"data row71 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow71_col0\" class=\"data row71 col0\" >longitude</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow71_col1\" class=\"data row71 col1\" >Longitude</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow71_col2\" class=\"data row71 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow72_col0\" class=\"data row72 col0\" >latitude</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow72_col1\" class=\"data row72 col1\" >Latitude</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow72_col2\" class=\"data row72 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow72_col0\" class=\"data row72 col0\" >latitude</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow72_col1\" class=\"data row72 col1\" >Latitude</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow72_col2\" class=\"data row72 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow73_col0\" class=\"data row73 col0\" >libgeo</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow73_col1\" class=\"data row73 col1\" >communes (name)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow73_col2\" class=\"data row73 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow73_col0\" class=\"data row73 col0\" >libgeo</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow73_col1\" class=\"data row73 col1\" >communes (name)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow73_col2\" class=\"data row73 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow74_col0\" class=\"data row74 col0\" >codegeo</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow74_col1\" class=\"data row74 col1\" >communes (code)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow74_col2\" class=\"data row74 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow74_col0\" class=\"data row74 col0\" >codegeo</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow74_col1\" class=\"data row74 col1\" >communes (code)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow74_col2\" class=\"data row74 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow75_col0\" class=\"data row75 col0\" >nom_epci</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow75_col1\" class=\"data row75 col1\" >EPCI (name)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow75_col2\" class=\"data row75 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow75_col0\" class=\"data row75 col0\" >nom_epci</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow75_col1\" class=\"data row75 col1\" >EPCI (name)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow75_col2\" class=\"data row75 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow76_col0\" class=\"data row76 col0\" >code_epci</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow76_col1\" class=\"data row76 col1\" >EPCI (code)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow76_col2\" class=\"data row76 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow76_col0\" class=\"data row76 col0\" >code_epci</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow76_col1\" class=\"data row76 col1\" >EPCI (code)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow76_col2\" class=\"data row76 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow77_col0\" class=\"data row77 col0\" >nom_dept</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow77_col1\" class=\"data row77 col1\" >department (name)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow77_col2\" class=\"data row77 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow77_col0\" class=\"data row77 col0\" >nom_dept</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow77_col1\" class=\"data row77 col1\" >department (name)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow77_col2\" class=\"data row77 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow78_col0\" class=\"data row78 col0\" >code_dep</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow78_col1\" class=\"data row78 col1\" >department (code)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow78_col2\" class=\"data row78 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow78_col0\" class=\"data row78 col0\" >code_dep</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow78_col1\" class=\"data row78 col1\" >department (code)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow78_col2\" class=\"data row78 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow79_col0\" class=\"data row79 col0\" >nom_reg</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow79_col1\" class=\"data row79 col1\" >region (name)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow79_col2\" class=\"data row79 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow79_col0\" class=\"data row79 col0\" >nom_reg</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow79_col1\" class=\"data row79 col1\" >region (name)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow79_col2\" class=\"data row79 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686blevel0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow80_col0\" class=\"data row80 col0\" >code_reg</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow80_col1\" class=\"data row80 col1\" >region (code)</td>\n",
- " <td id=\"T_31b1d594_5af8_11ea_a5d4_4b0d3ead686brow80_col2\" class=\"data row80 col2\" >0</td>\n",
+ " <th id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eeblevel0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow80_col0\" class=\"data row80 col0\" >code_reg</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow80_col1\" class=\"data row80 col1\" >region (code)</td>\n",
+ " <td id=\"T_67bd8d6a_5b0f_11ea_9093_7504dab42eebrow80_col2\" class=\"data row80 col2\" >0</td>\n",
" </tr>\n",
" </tbody></table>"
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- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow7_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow7_col2 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow8_col0 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow8_col0 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow8_col1 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow8_col1 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow8_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow8_col2 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow9_col0 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow9_col0 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow9_col1 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow9_col1 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow9_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow9_col2 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow10_col0 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow10_col0 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow10_col1 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow10_col1 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow10_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow10_col2 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow11_col0 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow11_col0 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow11_col1 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow11_col1 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow11_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow11_col2 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow12_col0 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow12_col0 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow12_col1 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow12_col1 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow12_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow12_col2 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow13_col0 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow13_col0 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow13_col1 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow13_col1 {\n",
" text-align: left;\n",
- " } #T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow13_col2 {\n",
+ " } #T_689614a0_5b0f_11ea_9093_7504dab42eebrow13_col2 {\n",
" text-align: left;\n",
- " }</style><table id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686b\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >Columns</th> <th class=\"col_heading level0 col1\" >Description</th> <th class=\"col_heading level0 col2\" >Na</th> </tr></thead><tbody>\n",
+ " }</style><table id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeb\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >Columns</th> <th class=\"col_heading level0 col1\" >Description</th> <th class=\"col_heading level0 col2\" >Na</th> </tr></thead><tbody>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow0_col0\" class=\"data row0 col0\" >date</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow0_col1\" class=\"data row0 col1\" >Date</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow0_col2\" class=\"data row0 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow0_col0\" class=\"data row0 col0\" >date</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow0_col1\" class=\"data row0 col1\" >Date</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow0_col2\" class=\"data row0 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow1_col0\" class=\"data row1 col0\" >pmer</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow1_col1\" class=\"data row1 col1\" >Pression au niveau mer</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow1_col2\" class=\"data row1 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow1_col0\" class=\"data row1 col0\" >pmer</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow1_col1\" class=\"data row1 col1\" >Pression au niveau mer</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow1_col2\" class=\"data row1 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow2_col0\" class=\"data row2 col0\" >tend</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow2_col1\" class=\"data row2 col1\" >Variation de pression en 3 heures</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow2_col2\" class=\"data row2 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow2_col0\" class=\"data row2 col0\" >tend</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow2_col1\" class=\"data row2 col1\" >Variation de pression en 3 heures</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow2_col2\" class=\"data row2 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow3_col0\" class=\"data row3 col0\" >cod_tend</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow3_col1\" class=\"data row3 col1\" >Type de tendance barométrique</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow3_col2\" class=\"data row3 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow3_col0\" class=\"data row3 col0\" >cod_tend</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow3_col1\" class=\"data row3 col1\" >Type de tendance barométrique</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow3_col2\" class=\"data row3 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow4_col0\" class=\"data row4 col0\" >dd</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow4_col1\" class=\"data row4 col1\" >Direction du vent moyen 10 mn</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow4_col2\" class=\"data row4 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow4_col0\" class=\"data row4 col0\" >dd</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow4_col1\" class=\"data row4 col1\" >Direction du vent moyen 10 mn</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow4_col2\" class=\"data row4 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow5_col0\" class=\"data row5 col0\" >ff</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow5_col1\" class=\"data row5 col1\" >Vitesse du vent moyen 10 mn</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow5_col2\" class=\"data row5 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow5_col0\" class=\"data row5 col0\" >ff</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow5_col1\" class=\"data row5 col1\" >Vitesse du vent moyen 10 mn</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow5_col2\" class=\"data row5 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow6_col0\" class=\"data row6 col0\" >td</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow6_col1\" class=\"data row6 col1\" >Point de rosée</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow6_col2\" class=\"data row6 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow6_col0\" class=\"data row6 col0\" >td</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow6_col1\" class=\"data row6 col1\" >Point de rosée</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow6_col2\" class=\"data row6 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow7_col0\" class=\"data row7 col0\" >u</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow7_col1\" class=\"data row7 col1\" >Humidité</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow7_col2\" class=\"data row7 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow7_col0\" class=\"data row7 col0\" >u</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow7_col1\" class=\"data row7 col1\" >Humidité</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow7_col2\" class=\"data row7 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow8_col0\" class=\"data row8 col0\" >ww</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow8_col1\" class=\"data row8 col1\" >Temps présent</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow8_col2\" class=\"data row8 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow8_col0\" class=\"data row8 col0\" >ww</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow8_col1\" class=\"data row8 col1\" >Temps présent</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow8_col2\" class=\"data row8 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow9_col0\" class=\"data row9 col0\" >pres</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow9_col1\" class=\"data row9 col1\" >Pression station</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow9_col2\" class=\"data row9 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow9_col0\" class=\"data row9 col0\" >pres</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow9_col1\" class=\"data row9 col1\" >Pression station</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow9_col2\" class=\"data row9 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow10_col0\" class=\"data row10 col0\" >rafper</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow10_col1\" class=\"data row10 col1\" >Rafales sur une période</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow10_col2\" class=\"data row10 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow10_col0\" class=\"data row10 col0\" >rafper</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow10_col1\" class=\"data row10 col1\" >Rafales sur une période</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow10_col2\" class=\"data row10 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow11_col0\" class=\"data row11 col0\" >rr1</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow11_col1\" class=\"data row11 col1\" >Précipitations dans la dernière heure</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow11_col2\" class=\"data row11 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow11_col0\" class=\"data row11 col0\" >rr1</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow11_col1\" class=\"data row11 col1\" >Précipitations dans la dernière heure</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow11_col2\" class=\"data row11 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow12_col0\" class=\"data row12 col0\" >rr3</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow12_col1\" class=\"data row12 col1\" >Précipitations dans les 3 dernières heures</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow12_col2\" class=\"data row12 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow12_col0\" class=\"data row12 col0\" >rr3</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow12_col1\" class=\"data row12 col1\" >Précipitations dans les 3 dernières heures</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow12_col2\" class=\"data row12 col2\" >0</td>\n",
" </tr>\n",
" <tr>\n",
- " <th id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686blevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow13_col0\" class=\"data row13 col0\" >tc</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow13_col1\" class=\"data row13 col1\" >Température (°C)</td>\n",
- " <td id=\"T_32667f8a_5af8_11ea_a5d4_4b0d3ead686brow13_col2\" class=\"data row13 col2\" >0</td>\n",
+ " <th id=\"T_689614a0_5b0f_11ea_9093_7504dab42eeblevel0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow13_col0\" class=\"data row13 col0\" >tc</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow13_col1\" class=\"data row13 col1\" >Température (°C)</td>\n",
+ " <td id=\"T_689614a0_5b0f_11ea_9093_7504dab42eebrow13_col2\" class=\"data row13 col2\" >0</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
- "<pandas.io.formats.style.Styler at 0x7f5a93ef0510>"
+ "<pandas.io.formats.style.Styler at 0x7ff8e1020d50>"
]
},
"metadata": {},
diff --git a/SYNOP/01-Try-a-peediction.ipynb b/SYNOP/01-Try-a-peediction.ipynb
index a13e3801dd9b948be154e7b80157fc510403da00..4acca916a5867e609d2d6f6822e02e8b0c4aa46b 100644
--- a/SYNOP/01-Try-a-peediction.ipynb
+++ b/SYNOP/01-Try-a-peediction.ipynb
@@ -28,7 +28,7 @@
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": 19,
"metadata": {},
"outputs": [
{
@@ -90,8 +90,8 @@
"text": [
"\n",
"FIDLE 2020 - Practical Work Module\n",
- "Version : 0.4.3\n",
- "Run time : Saturday 29 February 2020, 15:36:57\n",
+ "Version : 0.4.4\n",
+ "Run time : Saturday 29 February 2020, 18:43:44\n",
"TensorFlow version : 2.0.0\n",
"Keras version : 2.2.4-tf\n"
]
@@ -104,6 +104,7 @@
"from tensorflow.keras.preprocessing.sequence import TimeseriesGenerator\n",
"\n",
"import numpy as np\n",
+ "import math, random\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import pandas as pd\n",
@@ -132,15 +133,15 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Well, we should be at HOME !\n",
- "We are going to use: /home/pjluc/datasets/SYNOP\n"
+ "Well, we should be at GRICAD !\n",
+ "We are going to use: /bettik/PROJECTS/pr-fidle/datasets/SYNOP\n"
]
}
],
@@ -160,9 +161,21 @@
},
{
"cell_type": "code",
- "execution_count": 74,
+ "execution_count": 3,
"metadata": {},
"outputs": [
+ {
+ "data": {
+ "text/markdown": [
+ "<br>**Train dataset example :**"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Markdown object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
{
"data": {
"text/html": [
@@ -184,8 +197,6 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
- " <th>date</th>\n",
- " <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
@@ -203,8 +214,6 @@
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
- " <td>2010-01-01T01:00:00+01:00</td>\n",
- " <td>99080.0</td>\n",
" <td>-120.0</td>\n",
" <td>6.0</td>\n",
" <td>0.0</td>\n",
@@ -220,8 +229,6 @@
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
- " <td>2010-01-01T04:00:00+01:00</td>\n",
- " <td>98940.0</td>\n",
" <td>-150.0</td>\n",
" <td>6.0</td>\n",
" <td>60.0</td>\n",
@@ -237,8 +244,6 @@
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
- " <td>2010-01-01T07:00:00+01:00</td>\n",
- " <td>98950.0</td>\n",
" <td>10.0</td>\n",
" <td>3.0</td>\n",
" <td>280.0</td>\n",
@@ -254,8 +259,6 @@
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
- " <td>2010-01-01T10:00:00+01:00</td>\n",
- " <td>99180.0</td>\n",
" <td>230.0</td>\n",
" <td>3.0</td>\n",
" <td>310.0</td>\n",
@@ -271,8 +274,6 @@
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
- " <td>2010-01-01T13:00:00+01:00</td>\n",
- " <td>99480.0</td>\n",
" <td>280.0</td>\n",
" <td>1.0</td>\n",
" <td>330.0</td>\n",
@@ -288,8 +289,6 @@
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
- " <td>2010-01-01T16:00:00+01:00</td>\n",
- " <td>99980.0</td>\n",
" <td>480.0</td>\n",
" <td>3.0</td>\n",
" <td>350.0</td>\n",
@@ -305,8 +304,6 @@
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
- " <td>2010-01-01T19:00:00+01:00</td>\n",
- " <td>100550.0</td>\n",
" <td>530.0</td>\n",
" <td>2.0</td>\n",
" <td>350.0</td>\n",
@@ -322,8 +319,6 @@
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
- " <td>2010-01-01T22:00:00+01:00</td>\n",
- " <td>101030.0</td>\n",
" <td>450.0</td>\n",
" <td>2.0</td>\n",
" <td>340.0</td>\n",
@@ -339,8 +334,6 @@
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
- " <td>2010-01-02T01:00:00+01:00</td>\n",
- " <td>101330.0</td>\n",
" <td>280.0</td>\n",
" <td>1.0</td>\n",
" <td>320.0</td>\n",
@@ -356,8 +349,6 @@
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
- " <td>2010-01-02T04:00:00+01:00</td>\n",
- " <td>101560.0</td>\n",
" <td>220.0</td>\n",
" <td>1.0</td>\n",
" <td>290.0</td>\n",
@@ -373,8 +364,6 @@
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
- " <td>2010-01-02T07:00:00+01:00</td>\n",
- " <td>101660.0</td>\n",
" <td>100.0</td>\n",
" <td>1.0</td>\n",
" <td>350.0</td>\n",
@@ -390,8 +379,6 @@
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
- " <td>2010-01-02T10:00:00+01:00</td>\n",
- " <td>101980.0</td>\n",
" <td>300.0</td>\n",
" <td>3.0</td>\n",
" <td>350.0</td>\n",
@@ -407,8 +394,6 @@
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
- " <td>2010-01-02T13:00:00+01:00</td>\n",
- " <td>102100.0</td>\n",
" <td>130.0</td>\n",
" <td>1.0</td>\n",
" <td>10.0</td>\n",
@@ -424,8 +409,6 @@
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
- " <td>2010-01-02T16:00:00+01:00</td>\n",
- " <td>102250.0</td>\n",
" <td>150.0</td>\n",
" <td>3.0</td>\n",
" <td>10.0</td>\n",
@@ -441,8 +424,6 @@
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
- " <td>2010-01-02T19:00:00+01:00</td>\n",
- " <td>102420.0</td>\n",
" <td>140.0</td>\n",
" <td>1.0</td>\n",
" <td>50.0</td>\n",
@@ -461,39 +442,185 @@
"</div>"
],
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- "1 2010-01-01T04:00:00+01:00 98940.0 -150.0 6.0 60.0 1.0 278.65 \n",
- "2 2010-01-01T07:00:00+01:00 98950.0 10.0 3.0 280.0 2.1 278.85 \n",
- "3 2010-01-01T10:00:00+01:00 99180.0 230.0 3.0 310.0 2.6 279.15 \n",
- "4 2010-01-01T13:00:00+01:00 99480.0 280.0 1.0 330.0 4.6 278.15 \n",
- "5 2010-01-01T16:00:00+01:00 99980.0 480.0 3.0 350.0 5.1 276.95 \n",
- "6 2010-01-01T19:00:00+01:00 100550.0 530.0 2.0 350.0 3.1 274.05 \n",
- "7 2010-01-01T22:00:00+01:00 101030.0 450.0 2.0 340.0 6.2 272.15 \n",
- "8 2010-01-02T01:00:00+01:00 101330.0 280.0 1.0 320.0 6.2 270.15 \n",
- "9 2010-01-02T04:00:00+01:00 101560.0 220.0 1.0 290.0 2.6 269.65 \n",
- "10 2010-01-02T07:00:00+01:00 101660.0 100.0 1.0 350.0 3.1 270.45 \n",
- "11 2010-01-02T10:00:00+01:00 101980.0 300.0 3.0 350.0 5.1 268.55 \n",
- "12 2010-01-02T13:00:00+01:00 102100.0 130.0 1.0 10.0 4.6 267.45 \n",
- "13 2010-01-02T16:00:00+01:00 102250.0 150.0 3.0 10.0 5.7 267.45 \n",
- "14 2010-01-02T19:00:00+01:00 102420.0 140.0 1.0 50.0 2.6 268.15 \n",
+ " tend cod_tend dd ff td u ww pres rafper rr1 \\\n",
+ "0 -120.0 6.0 0.0 0.0 278.75 88.0 60.0 96250.0 4.1 0.0 \n",
+ "1 -150.0 6.0 60.0 1.0 278.65 93.0 61.0 96100.0 2.6 0.2 \n",
+ "2 10.0 3.0 280.0 2.1 278.85 95.0 58.0 96110.0 2.6 0.0 \n",
+ "3 230.0 3.0 310.0 2.6 279.15 96.0 50.0 96340.0 5.7 0.0 \n",
+ "4 280.0 1.0 330.0 4.6 278.15 94.0 21.0 96620.0 8.7 0.4 \n",
+ "5 480.0 3.0 350.0 5.1 276.95 91.0 60.0 97100.0 8.2 0.2 \n",
+ "6 530.0 2.0 350.0 3.1 274.05 83.0 21.0 97630.0 7.2 0.0 \n",
+ "7 450.0 2.0 340.0 6.2 272.15 81.0 2.0 98080.0 9.3 0.0 \n",
+ "8 280.0 1.0 320.0 6.2 270.15 74.0 2.0 98360.0 10.3 0.0 \n",
+ "9 220.0 1.0 290.0 2.6 269.65 72.0 2.0 98580.0 5.1 0.0 \n",
+ "10 100.0 1.0 350.0 3.1 270.45 79.0 2.0 98680.0 4.1 0.0 \n",
+ "11 300.0 3.0 350.0 5.1 268.55 70.0 2.0 98980.0 6.7 0.0 \n",
+ "12 130.0 1.0 10.0 4.6 267.45 60.0 2.0 99110.0 7.7 0.0 \n",
+ "13 150.0 3.0 10.0 5.7 267.45 59.0 2.0 99260.0 8.7 0.0 \n",
+ "14 140.0 1.0 50.0 2.6 268.15 70.0 2.0 99400.0 5.7 0.0 \n",
"\n",
- " u ww pres rafper rr1 rr3 tc \n",
- "0 88.0 60.0 96250.0 4.1 0.0 0.0 7.5 \n",
- "1 93.0 61.0 96100.0 2.6 0.2 0.6 6.6 \n",
- "2 95.0 58.0 96110.0 2.6 0.0 0.4 6.4 \n",
- "3 96.0 50.0 96340.0 5.7 0.0 3.0 6.6 \n",
- "4 94.0 21.0 96620.0 8.7 0.4 0.8 5.9 \n",
- "5 91.0 60.0 97100.0 8.2 0.2 0.4 5.2 \n",
- "6 83.0 21.0 97630.0 7.2 0.0 0.0 3.5 \n",
- "7 81.0 2.0 98080.0 9.3 0.0 0.0 1.9 \n",
- "8 74.0 2.0 98360.0 10.3 0.0 0.0 1.1 \n",
- "9 72.0 2.0 98580.0 5.1 0.0 0.0 1.0 \n",
- "10 79.0 2.0 98680.0 4.1 0.0 0.0 0.5 \n",
- "11 70.0 2.0 98980.0 6.7 0.0 0.0 -0.3 \n",
- "12 60.0 2.0 99110.0 7.7 0.0 0.0 1.2 \n",
- "13 59.0 2.0 99260.0 8.7 0.0 0.0 1.5 \n",
- "14 70.0 2.0 99400.0 5.7 0.0 0.0 -0.8 "
+ " rr3 tc \n",
+ "0 0.0 7.5 \n",
+ "1 0.6 6.6 \n",
+ "2 0.4 6.4 \n",
+ "3 3.0 6.6 \n",
+ "4 0.8 5.9 \n",
+ "5 0.4 5.2 \n",
+ "6 0.0 3.5 \n",
+ "7 0.0 1.9 \n",
+ "8 0.0 1.1 \n",
+ "9 0.0 1.0 \n",
+ "10 0.0 0.5 \n",
+ "11 0.0 -0.3 \n",
+ "12 0.0 1.2 \n",
+ "13 0.0 1.5 \n",
+ "14 0.0 -0.8 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/markdown": [
+ "<br>**After normalization :**"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Markdown object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
+ "<style type=\"text/css\" >\n",
+ "</style><table id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77\" ><thead> <tr> <th class=\"blank level0\" ></th> <th class=\"col_heading level0 col0\" >tend</th> <th class=\"col_heading level0 col1\" >cod_tend</th> <th class=\"col_heading level0 col2\" >dd</th> <th class=\"col_heading level0 col3\" >ff</th> <th class=\"col_heading level0 col4\" >td</th> <th class=\"col_heading level0 col5\" >u</th> <th class=\"col_heading level0 col6\" >ww</th> <th class=\"col_heading level0 col7\" >pres</th> <th class=\"col_heading level0 col8\" >rafper</th> <th class=\"col_heading level0 col9\" >rr1</th> <th class=\"col_heading level0 col10\" >rr3</th> <th class=\"col_heading level0 col11\" >tc</th> </tr></thead><tbody>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row0\" class=\"row_heading level0 row0\" >count</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col0\" class=\"data row0 col0\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col1\" class=\"data row0 col1\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col2\" class=\"data row0 col2\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col3\" class=\"data row0 col3\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col4\" class=\"data row0 col4\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col5\" class=\"data row0 col5\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col6\" class=\"data row0 col6\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col7\" class=\"data row0 col7\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col8\" class=\"data row0 col8\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col9\" class=\"data row0 col9\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col10\" class=\"data row0 col10\" >25000.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row0_col11\" class=\"data row0 col11\" >25000.00</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row1\" class=\"row_heading level0 row1\" >mean</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col0\" class=\"data row1 col0\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col1\" class=\"data row1 col1\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col2\" class=\"data row1 col2\" >0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col3\" class=\"data row1 col3\" >0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col4\" class=\"data row1 col4\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col5\" class=\"data row1 col5\" >0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col6\" class=\"data row1 col6\" >0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col7\" class=\"data row1 col7\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col8\" class=\"data row1 col8\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col9\" class=\"data row1 col9\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col10\" class=\"data row1 col10\" >0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row1_col11\" class=\"data row1 col11\" >-0.00</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row2\" class=\"row_heading level0 row2\" >std</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col0\" class=\"data row2 col0\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col1\" class=\"data row2 col1\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col2\" class=\"data row2 col2\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col3\" class=\"data row2 col3\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col4\" class=\"data row2 col4\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col5\" class=\"data row2 col5\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col6\" class=\"data row2 col6\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col7\" class=\"data row2 col7\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col8\" class=\"data row2 col8\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col9\" class=\"data row2 col9\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col10\" class=\"data row2 col10\" >1.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row2_col11\" class=\"data row2 col11\" >1.00</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row3\" class=\"row_heading level0 row3\" >min</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col0\" class=\"data row3 col0\" >-6.80</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col1\" class=\"data row3 col1\" >-1.59</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col2\" class=\"data row3 col2\" >-1.75</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col3\" class=\"data row3 col3\" >-1.37</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col4\" class=\"data row3 col4\" >-5.18</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col5\" class=\"data row3 col5\" >-3.82</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col6\" class=\"data row3 col6\" >-0.52</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col7\" class=\"data row3 col7\" >-4.94</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col8\" class=\"data row3 col8\" >-1.64</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col9\" class=\"data row3 col9\" >-0.31</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col10\" class=\"data row3 col10\" >-0.27</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row3_col11\" class=\"data row3 col11\" >-3.03</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row4\" class=\"row_heading level0 row4\" >25%</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col0\" class=\"data row4 col0\" >-0.64</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col1\" class=\"data row4 col1\" >-0.85</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col2\" class=\"data row4 col2\" >-0.64</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col3\" class=\"data row4 col3\" >-0.76</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col4\" class=\"data row4 col4\" >-0.72</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col5\" class=\"data row4 col5\" >-0.71</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col6\" class=\"data row4 col6\" >-0.42</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col7\" class=\"data row4 col7\" >-0.55</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col8\" class=\"data row4 col8\" >-0.69</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col9\" class=\"data row4 col9\" >-0.15</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col10\" class=\"data row4 col10\" >-0.20</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row4_col11\" class=\"data row4 col11\" >-0.75</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row5\" class=\"row_heading level0 row5\" >50%</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col0\" class=\"data row5 col0\" >-0.00</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col1\" class=\"data row5 col1\" >-0.48</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col2\" class=\"data row5 col2\" >-0.12</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col3\" class=\"data row5 col3\" >-0.19</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col4\" class=\"data row5 col4\" >0.05</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col5\" class=\"data row5 col5\" >0.18</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col6\" class=\"data row5 col6\" >-0.42</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col7\" class=\"data row5 col7\" >0.03</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col8\" class=\"data row5 col8\" >-0.27</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col9\" class=\"data row5 col9\" >-0.15</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col10\" class=\"data row5 col10\" >-0.20</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row5_col11\" class=\"data row5 col11\" >-0.01</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row6\" class=\"row_heading level0 row6\" >75%</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col0\" class=\"data row6 col0\" >0.63</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col1\" class=\"data row6 col1\" >0.99</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col2\" class=\"data row6 col2\" >1.08</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col3\" class=\"data row6 col3\" >0.50</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col4\" class=\"data row6 col4\" >0.79</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col5\" class=\"data row6 col5\" >0.84</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col6\" class=\"data row6 col6\" >-0.37</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col7\" class=\"data row6 col7\" >0.61</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col8\" class=\"data row6 col8\" >0.52</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col9\" class=\"data row6 col9\" >-0.15</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col10\" class=\"data row6 col10\" >-0.20</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row6_col11\" class=\"data row6 col11\" >0.72</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77level0_row7\" class=\"row_heading level0 row7\" >max</th>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col0\" class=\"data row7 col0\" >7.16</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col1\" class=\"data row7 col1\" >1.36</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col2\" class=\"data row7 col2\" >1.34</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col3\" class=\"data row7 col3\" >6.28</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col4\" class=\"data row7 col4\" >2.40</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col5\" class=\"data row7 col5\" >1.62</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col6\" class=\"data row7 col6\" >4.46</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col7\" class=\"data row7 col7\" >3.10</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col8\" class=\"data row7 col8\" >6.29</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col9\" class=\"data row7 col9\" >30.36</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col10\" class=\"data row7 col10\" >31.27</td>\n",
+ " <td id=\"T_a846fcc2_5b19_11ea_a983_a374076bdc77row7_col11\" class=\"data row7 col11\" >3.02</td>\n",
+ " </tr>\n",
+ " </tbody></table>"
+ ],
+ "text/plain": [
+ "<pandas.io.formats.style.Styler at 0x7fc05b6ef6d0>"
]
},
"metadata": {},
@@ -504,10 +631,8 @@
"output_type": "stream",
"text": [
"Dataset : (29165, 14)\n",
- "x_train : (25000, 12)\n",
- "y_train : (25000, 5)\n",
- "x_test : (4165, 14)\n",
- "y_test : (4165, 5)\n"
+ "Train dataset : (25000, 12)\n",
+ "Test dataset : (4165, 12)\n"
]
}
],
@@ -515,21 +640,37 @@
"dataset_filename = 'synop-LYS.csv'\n",
"schema_filename = 'synop.json'\n",
"train_len = 25000\n",
+ "features = ['tend', 'cod_tend', 'dd', 'ff', 'td', 'u', 'ww', 'pres', 'rafper', 'rr1', 'rr3', 'tc']\n",
+ "features_len = len(features)\n",
+ "\n",
+ "# ---- Read dataset\n",
"\n",
"df = pd.read_csv(f'{dataset_dir}/{dataset_filename}', header=0, sep=';')\n",
- "display(df.head(15))\n",
"\n",
- "x_train = df.loc[ :train_len-1, ['tend', 'cod_tend', 'dd', 'ff', 'td', 'u', 'ww', 'pres', 'rafper', 'rr1', 'rr3', 'tc'] ].to_numpy()\n",
- "y_train = x_train\n",
+ "# ---- Train / Test\n",
+ "\n",
+ "dataset_train = df.loc[ :train_len-1, features ]\n",
+ "dataset_test = df.loc[train_len:, features ]\n",
+ "ooo.subtitle('Train dataset example :')\n",
+ "display(dataset_train.head(15))\n",
+ "\n",
+ "# ---- Normalize, and convert to numpy array\n",
+ "\n",
+ "mean = dataset_train.mean()\n",
+ "std = dataset_train.std()\n",
+ "dataset_train = (dataset_train - mean) / std\n",
+ "dataset_test = (dataset_test - mean) / std\n",
+ "\n",
+ "ooo.subtitle('After normalization :')\n",
+ "display(dataset_train.describe().style.format(\"{0:.2f}\"))\n",
+ "\n",
+ "dataset_train = dataset_train.to_numpy()\n",
+ "dataset_test = dataset_test.to_numpy()\n",
"\n",
- "x_test = df.loc[train_len:].to_numpy()\n",
- "y_test = df.loc[train_len:, ['pmer','td','u','rr3','tc'] ].to_numpy()\n",
"\n",
"print('Dataset : ',df.shape)\n",
- "print('x_train : ',x_train.shape)\n",
- "print('y_train : ',y_train.shape)\n",
- "print('x_test : ',x_test.shape)\n",
- "print('y_test : ',y_test.shape)"
+ "print('Train dataset : ',dataset_train.shape)\n",
+ "print('Test dataset : ',dataset_test.shape)\n"
]
},
{
@@ -541,32 +682,37 @@
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Nombre de batchs disponibles : 781\n",
- "batch x shape : (32, 10, 12)\n",
- "batch y shape : (32, 5)\n"
+ "Nombre de train batchs disponibles : 781\n",
+ "batch x shape : (32, 16, 12)\n",
+ "batch y shape : (32, 12)\n"
]
}
],
"source": [
- "sequence_len = 10\n",
+ "sequence_len = 16\n",
"batch_size = 32\n",
- "n_features = x_train.shape[1]\n",
"\n",
- "train_generator = TimeseriesGenerator(x_train, y_train, length=sequence_len, batch_size=batch_size)\n",
+ "# ---- Train generator\n",
+ "train_generator = TimeseriesGenerator(dataset_train, dataset_train, length=sequence_len, batch_size=batch_size)\n",
+ "test_generator = TimeseriesGenerator(dataset_test, dataset_test, length=sequence_len, batch_size=batch_size)\n",
"\n",
"# ---- About\n",
"\n",
- "print(f'Nombre de batchs disponibles : ', len(train_generator))\n",
"x,y=train_generator[0]\n",
+ "print(f'Nombre de train batchs disponibles : ', len(train_generator))\n",
"print('batch x shape : ',x.shape)\n",
- "print('batch y shape : ',y.shape)"
+ "print('batch y shape : ',y.shape)\n",
+ "\n",
+ "# x,y=train_generator[0]\n",
+ "# np_print(x[0])\n",
+ "# np_print(y[0])"
]
},
{
@@ -578,23 +724,23 @@
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Model: \"sequential_5\"\n",
+ "Model: \"sequential\"\n",
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
- "lstm_5 (LSTM) (None, 100) 45200 \n",
+ "lstm (LSTM) (None, 100) 45200 \n",
"_________________________________________________________________\n",
- "dense_5 (Dense) (None, 5) 505 \n",
+ "dense (Dense) (None, 12) 1212 \n",
"=================================================================\n",
- "Total params: 45,705\n",
- "Trainable params: 45,705\n",
+ "Total params: 46,412\n",
+ "Trainable params: 46,412\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
@@ -602,9 +748,8 @@
],
"source": [
"model = keras.models.Sequential()\n",
- "model.add(keras.layers.LSTM(100, activation='relu', input_shape=(sequence_len, n_features)))\n",
- "model.add(keras.layers.Dense(5))\n",
- "model.compile(optimizer='adam', loss='mse')\n",
+ "model.add(keras.layers.LSTM(100, activation='relu', input_shape=(sequence_len, features_len)))\n",
+ "model.add(keras.layers.Dense(features_len))\n",
"\n",
"model.summary()"
]
@@ -616,18 +761,52 @@
"# Step 4 - Compile and run"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 4.1 - Callback"
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 84,
+ "execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
- "model.compile(optimizer='adam', loss='mse')"
+ "os.makedirs('./run/models', mode=0o750, exist_ok=True)\n",
+ "save_dir = \"./run/models/best_model.h5\"\n",
+ "bestmodel_callback = tf.keras.callbacks.ModelCheckpoint(filepath=save_dir, verbose=0, save_best_only=True)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 4.2 - Compile"
]
},
{
"cell_type": "code",
- "execution_count": 85,
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "model.compile(optimizer='adam', \n",
+ " loss='mse', \n",
+ " metrics = ['mae'] )"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### 4.3 - Fit"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -635,40 +814,195 @@
"output_type": "stream",
"text": [
"Epoch 1/10\n",
- "781/781 [==============================] - 21s 26ms/step - loss: 31682770.0197\n",
+ "781/781 [==============================] - 37s 47ms/step - loss: 0.5673 - mae: 0.4757 - val_loss: 0.4621 - val_mae: 0.4176\n",
"Epoch 2/10\n",
- "781/781 [==============================] - 21s 26ms/step - loss: 35062.0715\n",
+ "781/781 [==============================] - 35s 45ms/step - loss: 0.4701 - mae: 0.4017 - val_loss: 0.4395 - val_mae: 0.3954\n",
"Epoch 3/10\n",
- "781/781 [==============================] - 22s 28ms/step - loss: 33620.7899\n",
+ "781/781 [==============================] - 36s 46ms/step - loss: 0.4481 - mae: 0.3842 - val_loss: 0.4278 - val_mae: 0.3829\n",
"Epoch 4/10\n",
- "781/781 [==============================] - 22s 28ms/step - loss: 32147.1692\n",
+ "781/781 [==============================] - 39s 51ms/step - loss: 0.4363 - mae: 0.3735 - val_loss: 0.4135 - val_mae: 0.3881\n",
"Epoch 5/10\n",
- "781/781 [==============================] - 22s 28ms/step - loss: 28707.0891\n",
+ "781/781 [==============================] - 39s 50ms/step - loss: 0.4275 - mae: 0.3672 - val_loss: 0.4116 - val_mae: 0.3765\n",
"Epoch 6/10\n",
- "781/781 [==============================] - 21s 27ms/step - loss: 25355.2240\n",
+ "781/781 [==============================] - 35s 45ms/step - loss: 0.4210 - mae: 0.3634 - val_loss: 0.4023 - val_mae: 0.3650\n",
"Epoch 7/10\n",
- "781/781 [==============================] - 22s 29ms/step - loss: 23080.5806\n",
+ "781/781 [==============================] - 36s 46ms/step - loss: 0.4146 - mae: 0.3597 - val_loss: 0.4009 - val_mae: 0.3660\n",
"Epoch 8/10\n",
- "781/781 [==============================] - 21s 27ms/step - loss: 137364.9778\n",
+ "781/781 [==============================] - 37s 47ms/step - loss: 0.4117 - mae: 0.3584 - val_loss: 0.3998 - val_mae: 0.3618\n",
"Epoch 9/10\n",
- "781/781 [==============================] - 21s 26ms/step - loss: 16633.4028\n",
+ "781/781 [==============================] - 35s 45ms/step - loss: 0.4067 - mae: 0.3561 - val_loss: 0.4066 - val_mae: 0.3694\n",
"Epoch 10/10\n",
- "781/781 [==============================] - 21s 26ms/step - loss: 15468.7664\n"
+ "781/781 [==============================] - 36s 46ms/step - loss: 0.4043 - mae: 0.3562 - val_loss: 0.4012 - val_mae: 0.3654\n"
]
+ }
+ ],
+ "source": [
+ "%%time\n",
+ "\n",
+ "history=model.fit_generator(train_generator, \n",
+ " epochs=10, \n",
+ " verbose=1,\n",
+ " validation_data = test_generator,\n",
+ " callbacks = [bestmodel_callback])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
},
{
"data": {
+ "image/png": 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\n",
"text/plain": [
- "<tensorflow.python.keras.callbacks.History at 0x7fcadb275710>"
+ "<Figure size 576x432 with 1 Axes>"
]
},
- "execution_count": 85,
- "metadata": {},
- "output_type": "execute_result"
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
}
],
"source": [
- "model.fit_generator(train_generator, epochs=10, verbose=1)"
+ "ooo.plot_history(history,plot={'loss':['loss','val_loss'], 'mae':['mae','val_mae']})"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Step 5 - Predict"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "loaded_model = tf.keras.models.load_model('./run/models/best_model.h5')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 1080x1252.8 with 12 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# ---- Get a sequence\n",
+ "\n",
+ "i=random.randint(0,len(dataset_test)-sequence_len)\n",
+ "sequence = dataset_test[i:i+sequence_len]\n",
+ "sequence_true = dataset_test[i:i+sequence_len+1]\n",
+ "\n",
+ "\n",
+ "pred = loaded_model.predict( np.array([sequence]) )\n",
+ "\n",
+ "t=np.arange(sequence_len+1)\n",
+ "\n",
+ "columns = 3\n",
+ "width=5\n",
+ "height=4\n",
+ "\n",
+ "rows = math.ceil(features_len/columns)\n",
+ "fig = plt.figure(figsize=(columns*width, rows*(height+0.35)))\n",
+ "fig.subplots_adjust(wspace=0.3,hspace=0.2)\n",
+ "n=1\n",
+ "for i in range(features_len):\n",
+ " ax=fig.add_subplot(rows, columns, n)\n",
+ " ax.plot(t, sequence_true[:,i], '-', linewidth=1, color='steelblue', label=features[i])\n",
+ " ax.plot(t[-1], sequence_true[-1:,i], 'o', fillstyle='full', markersize=8, color='steelblue') # ce qui nous interesse\n",
+ " ax.plot(t[-1], [pred[0][i]], 'o', fillstyle='full', markersize=8, color='red') # ce qui nous interesse\n",
+ "\n",
+ " ax.legend(loc=\"upper left\")\n",
+ " n+=1\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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V4vtda4yZ3XAJRUQkFE3LzWdED21NWFvGGG48rQ9vfruSHXuKXccR8QRPlnDgL8AwYKy1NrfqSWPMCCpHUH53hBGWallrn7fWDmr4mCIiEip27TvI2vw9ZKRrM666SEtJ4PTMNJ7/bKnrKCKe4LkSbowZD9wEPG+tnXDI81HA34HPrbVvusonIiKhafqKfDI7pRIVEe46SsC64PiuLN+yizlrtruOIuKcp0q4MeY+4B7gZeD6w16+EegB/NkY06XqC6jaqDXdGNPJb2FFRCSkZOfmM0KnZNZLTGQ4Waf25unJSygp074KEto8U8KNMeOAccAk4Gprf3TObQcq804GVh7ydbbv9ZnAQv+kFRGRULL/YBmL1u9kaNcWrqMEvGHdWtI+JYF3c9a4jiLiVITrAADGmLHAfcBrwBXW2ur2MHoZ+K6a528ERlF56I82IRURkQY3Z/V2erZrRnxMpOsoQeGGU3tx0wvf8ZM+bWmdFOc6jogTzku4MeZG4H5gA/A5cOFhp5DlW2s/s9YuABZU8/6f+375H2vtjsbOKyIioWdabp4O6GlArZrF8athnZg4ZTEP/HqwTh+VkOS8hAODfY9pwKvVvD4V+Mx/cURERL5XWl7BrFXbueaUnq6jBJVzhnfi84WbyNEJpBKinM+EW2svt9aao3yNquH7tQouIiINbuG6Atonx5PcJMZ1lKASGR7GTaf14ZlPl1JcUuY6jojfOS/hIiIiXjYtN4/h3bVS2xgGpKfQu30Sz3++jIof7ccgEtxUwkVERI6gwlpycvMZqVMyG80Np/ZmTf4eHnx3Lge0Ii4hRCVcRETkCHI37yIhJpJ2yQmuowStpnFRPHrJMOKiI7jl5Wzydu13HUnEL1TCRUREjkAH9PhHVEQ4t57Rj58OaM8tL2ezaMNO15FEGp1KuIiISDWstWQv19aE/mKM4eyh6dx2Zn8efHcOH8/d4DqSSKNSCRcREanGxh1FFJeW0611U9dRQsrAzqn86bLhvDd9DU9PWUxZeXXn94kEPpVwERGRakzLzWd495Y6SMaBdskJ/O3KkWwt3M/db8xkz/4S15FEGpxKuIiISDWyc/MYqVEUZ+JjIrn//MF0bd2U37w0jXXb9rqOJNKgVMJFREQOs33PAbYW7qdvWnPXUUJaeJjh6lN6cskJXbnjtelMX5HvOpJIg/HCsfUiIiKekpObz5AuLYgI11qVF5zcrx1tkxMY/84c1m3by/kjO2tMSAKe/nYRERE5zDSNonhOj7bN+OuVI5mWm8cj/5pPcWm560gi9aISLiIicoi9B0pZsXk3AzuluI4ih0lJjOHxS4cTZuC2V3PYvueA60gidaYSLiIicogZK/Pp3zGZmChNbHpRdGQ4d5w1gBN6tea3L01j6aZC15FE6kQlXERE5BDZufmM6KFTMr3MGMN5Izrz25/15b63Z/PZgk2uI4nUmkq4iIiIz8HScuat3cGwrirhgWBo15Y8fukw3vhuJc99tpTyCh3sI4FDJVxERMRn7poddGmVSGJclOsoUkNpqU3465UjWZu/l3vfmk1RcanrSCI1ohIuIiLio11RAlNibBQPXTiY9snx/PbFaWzcUeQ6ksgxqYSLiIgA5RUVzFiRz/BuGkUJROFhYdxwam/OHdGJW1/NYdaqba4jiRyVbv0WEREBFm8opEXTWFo2i3MdRephTEYa7VMSePDduZwzrBPnDEvXwT7iSVoJFxERAbJz8xjRXaMowaB3++b89cqRfLloM3/6cCElZTrYR7xHJVxEREKetZbs3HzNgweRFk1j+fPlwykuLeeOSdMp2FvsOpLID6iEi4hIyFuVt4fwMEOH1ATXUaQBxURFcPc5GQzp2oLfvjSNFVt2uY4k8j8q4SIiEvKyfbuiaHY4+BhjuPD4rtxwam/ueXMWXy3e7DqSCKASLiIiQvbyfEZ0164owWxkj1b88eKhvPJVLi99uZwKa11HkhCnEi4iIiFt88597N5fQs92Sa6jSCNLb5nI3646jmWbCrn/7dnsO6iDfcQd5yXcGNPNGPOAMWa6MWa7MWavMWa+MeZuY0z8IdcZY8zFxpi3jDGrjDH7jTEbjDEfGmOGuvzfICIigSs7N4/h3VsSplGUkNA0LooJFw0lJTGG/3spmy0797mOJCHKeQkHrgRuAVYDDwC3A7nAg0C2MSbWd1008BrQHXgLuBl4HsgEcowxF/s5t4iIBIGcXI2ihJqI8DBuPr0vZw7uyO9eyWHe2h2uI0kI8sJhPe8CE6y1uw957lljzErgbuAq4CmgDBhlrZ166JuNMX8HlgB/Msa8Ya2t8FNuEREJcIVFB1m3bS/9Oya7jiIOnDGoA2kpCUx4fx4XHN+FMwd10M254jfOV8KttbMPK+BV3vY99vFdV3Z4Afc9nw9MBVr4vkRERGokZ0U+gzqnEhUR7jqKONK/YzJ/uWIEH8/ZwF//u4jScq3liX84L+FH0c73mF/Da0sAbQAqIiI1lp2bxwgd0BPyWiXF8cQVI9i9v4TfvzadXfsOuo4kIcCTJdwYEw6MpXIE5Y1jXHs6MAR421pb7XFYxphrjTGzGzyoiIgErH0HS1myoZDBXVJdRxEPiIuO4N5zB9K/YzK/eXEaq/Oq+5BepOF4soQDfwGGAWOttblHusgY05XKmzU3A7ce6Tpr7fPW2kENnlJERALWrFXb6Z2WRHx0pOso4hFhxnDZqO5cdXIP7vrHTHJya/JhvEjdeOHGzB8wxowHbgKet9ZOOMp16cAXgAVOs9Zu91NEEREJApW7omgURX7sxN5taBoXxd8+Xsxw7ZwjjcRTK+HGmPuAe4CXgeuPcl1H4CsgARhtrV3kh3giIhIkSsrKmb16G8O66X5+qV6/jskUFZeSv2u/6ygSpDxTwo0x44BxwCTgamurP0/WGNOBygLelMoCPs9/KUVEJBgsWFdAWkoTmifEuI4iHhVmDBnpKdpDXBqNJ0q4MWYscB+V891XHGmvb18B/xpIAn5qrZ3jr4wiIhI8snPzGdFDYwZydBnpycxbW+A6hgQp5zPhxpgbgfuBDcDnwIWHbZSfb639zBjThMoV8I7Ak0B3Y0z3w77dZ759w0VERKpVXmHJyc3nT5cPdx1FPC6zUyovfZlLhbWE6RAfaWDOSzgw2PeYBrxazetTgc+AZCDd99zNR/heP6Fm+4qLiEiIWr65kKZxUbRtHu86inhci6axJMREsjZ/D51bNXUdR4KM8xJurb0cuLwG160D9M9QERGpl+zcfEZoxwupocxOKcxdu0MlXBqcJ2bCRQLBzqJi3vh2JXm6U14kYFlrmbZcp2RKzWWkpzBvjW7OlIanEi5yDBt3FPGXjxZyzTPfMGfNDp6evNh1JBGpo/XbiyivsHRpleg6igSI/h2TWbqpkJKyctdRJMiohIscwbJNhTzwz9nc+moOyU1ieDHrRB65eChbdu5n+grdeiASiLJz8xjRvSVGN9lJDSXERNIhtQlLNxW6jiJBxvlMuIiXVFjLzJXbeCdnDdv3HOCcYZ2446wBxER9/5/KDWN689TkxWR2SiEqItxhWhGprWnL87h2dC/XMSTAZKSnMHfNDgZ0THEdRYKISrgIUFpewdeLt/BOzmoiwsI4d0QnTujVmvCwH39YNKhzKh1Tm/BuzhouPL6rg7QiUhfbdh9g2+4D9ElLch1FAkxmpxT+/vky1zEkyKiES0jbd7CUyXM38q+Za2mfnMB1P+1FZnrKMT+qvu6nvbj5xe84pV87WjSN9VNaEamP7Nw8hnZrWe0/rkWOpkfbZmzasY89B0pIjI1yHUeChP4mkpBUsLeYl75YzuVPfsXKrbu577xBPHLxUAZ2Sq3RrGjrpDjOHNRRKyMiAURbE0pdRUWE06t9EgvW6fRMaTgq4RJSNu4o4omPFnLts1PZX1LG3646jrvOzqBr69rv/3reyM7kbt7F/HXaukrE6/bsL2Hl1t0M7JTqOooEqMxOKcxbq7/vpeFoHEVCwrJNhbyTvZrFGws5Y1AHXswaRbP46Hp9z5jIcK4Z3ZOJU5Yw8ZrjiQjXv2lFvGrGym1kdEwmOlI3U0vdZKSn8J/Z613HkCCiEi5BqyY7ndTXcT1a8dGc9fxn9np+OTS9wb6viDSsacvzOK6nDuiRuktv0YQDJWXkFe6nVVKc6zgSBFTCJeiUllfw1eLNvJO9hsjwo+90Ul/GGLJO7c3tk6YzqncbkhLqt7ouIg2vuLScBesK+N2Z/VxHkQBmjKk8PXPdDk5LSnMdR4KASrgEjf/tdDJjLe1TErj+1JrtdFJfHVKbcHK/trz05XJuPbN/o/5ZIlJ7c1Zvp1vbptrVQuotIz2F2au3c1qGSrjUn0q4BLyCvcX8e+Y6Js/bQGanVO47f1CdbrSsj4tP6MrVE6eyfHMhPdpqD2IRL5m2PI8R3TWKIvWXkZ7CC58vo8JawnTqqtST7iSTgNWQO53UV3x0JFee1IOnJy+hwlq///kiUr2y8gpmrtrG8G7amlDqr0XTWBLjolidt8d1FAkCWgmXgNMYO500hJP7teW/c9fzyfyN+qhSxCMWbdhJ62ZxOlRLGkzVVoUuFnwkuKiES0Dwx04n9RVmDDeO6cO9b87iuB6taRIb6TqSSMjLzs1jRA+NokjDqdqq8LwRnV1HkQDnnQYjUo3Ddzo5b0Rnju/VyrPHTndt3ZTh3Vvy2tQVZI3p7TqOSEiz1pKdm8/DFw5xHUWCSP8OyTz6wXxKysqJitC+81J3KuHiSfsOlvLx3A18MGOdX3c6aQhX/KQ7Vz8zlTEZ7enUMtF1HJGQtXLrbmIiwklLSXAdRYJIfEwkHVs0YcnGQjLSU1zHkQDmzeVECWmbCoq4/rlvWbllN/edP4hHLh7KwE6pAVHAARLjorjkxK5MnLIEq5s0RZyZtjyP4d1bBszfHRI4MtJTmLtGR9hL/aiEi6ds2L6XO16bzkXHd+EP52QG7I0vp2d2YP/BMqYu2eo6ikjIys7NZ6TmwaURZHZKZd5alXCpH5Vw8Yy1+Xv4/eszuPKkHowJ8N1FwsMMWWN68/cvlnGgpMx1HJGQs6mgiKLiUrq3beY6igShHm2bsblgH3v2l7iOIgFMJVw8YdXW3dz1j5lc99NenNKvnes4DaJPWnP6pTXnzW9XuY4iEnKyc/MZ3r2lDlSRRhEZHkaftCTmrytwHUUCmEq4OLd88y7ufnMmN53Wm1G927iO06CuPqUnk+dtYHPBPtdRREJK9vI8RuqUTGlEGRpJkXpSCRenlmzcydi3ZnHLz/txXM/WruM0uOQmMZw3ojPPfKqbNEX8pWBvMRsLiujXMdl1FAlimekpzF2z3XUMCWAq4eLMovUF3P/POdz+i/4MC+Ijpc8ams7Wwv3MWLnNdRSRkJCzIp/BXVoQGa4fcdJ4OqQmUFJWwdbC/a6jSIBy/jeUMaabMeYBY8x0Y8x2Y8xeY8x8Y8zdxpj4aq7vboz5wBhTaIzZZ4z51hhzkovsUnfz1u5g/LtzuevsDAZ3aeE6TqOKDA/jhlN78+ynSykpK3cdRyToZefmM0KjKNLIjDFkpKdoJEXqzHkJB64EbgFWAw8AtwO5wINAtjEmtupCY0xnIBsYDjzquzYB+MQYc4qfc0sdzVq1jQnvz+PeX2WGzEEHgzqnkt6iCe/mrHEdRSSo7SsuZdnGQgZ1TnUdRUJAhkZSpB68UMLfBdpZay+y1j5prX3WWns+8BDQD7jqkGsnAM2AU621E6y1E4HjgS3A00YnMnje9BX5PPbvBYw7byB9O4TWvOZ1o3vxrxlr2bb7gOsoIkFr5qpt9OnQnLhoHQgtjS8jPYX56woor9A9P1J7zku4tXa2tXZ3NS+97XvsA+AbTTkT+NpaO/+Q9xcBLwDdgMGNHFfq4dtlW3nio4WMv2Awvds3dx3H71olxXHGoI48/9ky11FEgta05fmM7B6895iIt6QkxpAUH83qvOpqjMjROS/hR1G1WXS+77EfEA3kVHPtdN+jSrhHfb14C09PXsJDFwyhe5vQPTzjvJGdWbFlF/M1QyjS4ErKypm7ZntQ3+gt3qO5cKkrT5ZwY0w4MBYoA97wPV21gfTmat5S9VzbI3y/a3JapPoAACAASURBVI0xsxs0pNTYZws28dxnS5lw0RC6BOgx9A0lJjKca0f3ZOInSygrr3AdRySozFu7g/SWiTSLj3YdRUJIZqcU5qqESx14soQDfwGGAWOttbm+5+J8jwerub74sGt+wFr7vLV2UMNGlJqYMm8Dr3yVyx8vHkp6y0TXcTxhZI9WNE+I4cPZ611HEQkq2cvzGaFRFPGzvh2ak7t5FwdLtfuV1I7nSrgxZjxwE/C8tXbCIS9VbcRZ3RJHzGHXiAf8Z/Y6Xv9mJY9eMoy01Cau43iGMYasU3vx5rcrKSyq7t+UIlJb5RWWnBXamlD8Lz46kk4tE1m8cafrKBJgPFXCjTH3AfcALwPXH/byFt9jdSMnVc9VN6oiDrw/Yy3v5KzhsUuH0zb5R9u9h7y01CaM7t+Ol75c7jqKSFBYuqmQ5gnRtE6q9gNRkUaVkZ7CvDUaSZHa8UwJN8aMA8YBk4Cr7Y/P+F5E5SjK8GrePsz3qLlvD/hn9mo+nLWOxy4Zph+IR3HRCV2ZvXo7yzYVuo4iEvCyc/MY2UOr4OKGbs6UuvBECTfGjAXuA14DrrDW/uiONd9WhP8BRhlj+h/y3gTgamAlMNMvgeWI/vHNSj6Zt5HHLx1Oy2Yq4EcTHx3JlSf1YOKUJVT86N+cIlJT1lqyl+dpFEWc6dG2GVsK97N7f4nrKBJAnJdwY8yNwP3ABuBz4EJjzMWHfI0+5PK7gN3Ap8aYO40xWcC3VI6j3FzN6rn4ibWWV7/K5eslW3jssmGkJMYc+03Cyf3aEhEexifzN7qOIhKw1m7biwU6tdS9J+JGRHgYfdOaazVcasULR4pV7e2dBrxazetTgc8ArLWrjDEjgUeAO4EoYC4wxlr7uR+ySjWstbz4xXJmr97OY5cO0/ZgtRBmDFljenPvm7M4rkdrmsRGuo4kEnCyl+cxsnsrdGiyuJTZqXIkZVTvNse+WAQPrIRbay+31pqjfI067Ppl1tpfWGubWWvjrLXHqYC7Y63l2U+XMm/tDh69RAW8Lrq2bsrw7i2ZNDX32BeLyI9k52prQnGv6uZMfSgvNeW8hEvgqrCWpyYvZtmmXfzxkmEkxkW5jhSwrvhJd6Yu2cqa/D2uo4gElLzC/ezYW0yv9s1dR5EQl5aSQFlFBVsKtVuy1IxKuNRJeYXlrx8tYu22vUy4eAgJMRqjqI/EuCguObEbE6cs0SqKSC1kr8hnWLcWhIdpFEXcMsZolxSpFZVwqbXyigr+9OECthTu46ELhxAfrQLeEE7PTGP/wTK+XrLl2BeLCIB2RRFPyUhPYa72C5caqtWNmVlZWScDFwH3TJw48UdNISsrqw3wIDBp4sSJXzdIQvGUsvIKHv1gPnsOlDL+giHERIa7jhQ0wsMqb9Kc8P48hnVrSWyUF+6bFvGuXfsOsjp/D5mdUlxHEQEqS/gznyylvMLq0xk5ptquhN8MjKiugAP4nh/uu06CTGl5BQ+/N5f9JWU88OtBKuCNoE9ac/p3TObNb1e5jiLieTNWbiMzPYWoCP1dJN6Q3CSG5CbRrMrb7TqKBIDalvBMIPsY13wHDKpbHPGqkrJyxr8zhwoLY88dqB96jeiqk3swed4GNhUUuY4i4mnz1u5gcJdU1zFEfkAjKVJTtS3hLYBjDazm+66TIHGwtJz7/jmHqIgw7vlVpgp4I0tuEsN5Izrz7KdLdZOmyBFYa1m4voB+HZJdRxH5gar9wkWOpbYlfDfQ/hjXtAf21S2OeE1xSRlj35pFk5hI7jo7g4hw3cvrD2cNTWdr4X5mrNzmOoqIJ23ZuR9jDK2T4lxHEfmBvmnJrNiyi+LSctdRxONq26hmAmdlZWVVeyu678bMs3zXSYDbf7CMu9+cRWpiLHecNYDwMBVwf4kMDyPr1N48++lSSsr0F7nI4RasL6B/h2SdkimeExcdQedWTVm8YafrKOJxtW1VTwJNgG+zsrLOzMrKigbIysqKzsrK+gXwDZAA/K1hY4q/7Ssu5Q9vzKB9cjy/O7Of7vJ2YGDnVNJbNOHdnDWuo4h4TuUoig7oEW/SfuFSE7Uq4RMnTvwUGA90Bv4F7MvKytpO5fjJ+0An4MGJEydOaeig4j97D5Ry5+sz6NKqKb/5WV/CtNLkzHWje/GvGWvZtvuA6yginqF5cPG6jPRk3Zwpx1Tr+YKJEyeOA8YAHwM7gaa+x/8Cp/pelwC1e38Jv39tOn3SmnPjmN4q4I61SorjzMEdef6zZa6jiHiG5sHF63q0bUb+rv3s2nfQdRTxsNoe1nMpMN+3Iv7pEa7pA2ROnDhxUgPkEz8qLDrIna/PYGjXFlxxUnfNWnrEeSM6c80zU5m3dgcZ6TqURETz4OJ14WFh9O2QzLy1O/hJn7au44hH1XYl/BUqb7w8ml8AL9cpjThTsLeY2yflcFzPVirgHhMdGc61o3syccoSysorXMcRcU7z4BIItFWhHEtjbHcRDmhz4wCybfcBbpuUw8n92nHJid1UwD1oZI9WpCTG8OHs9a6jiDileXAJFFWH9ui8BzmSxijh3YDCRvi+0gjydu3n9kk5/CyzAxcc18V1HDkCYww3nNqbN79dSWGRZgwldGkeXAJF++R4rIXNO3V0ilTvmDPhWVlZLx321FlZWVkdq7k0HEgDjqfyJk3xuC0793Hn6zM4e1g6Zw1Jdx1HjiEtJYHR/dvx4pfLue3M/q7jiDiheXAJFMYYMnwjKe2SE1zHEQ+qyY2Zlx/yawsM8H1VxwIzgFvqF0sa28YdRdz5jxlceFwXfjawg+s4UkMXndCVa56ZyrJNhfRsl+Q6jojfLVxfwICOGkWRwJCZnsK3y7ZyxqCOrqOIB9WkhFctkRpgDfAX4K/VXFcOFE6cOFGfu3jcum17+cMbM7hsVHdOHdDedRyphfjoSK48qQdPT1nCX68cqUOUJKRUzYNfemI311FEaiQjPYWnpyymvKJCp07LjxyzhE+cOPF/d4JlZWXdD3x16HMSWFbn7eGeN2dy9ck9OLlfO9dxpA5O7tuW/87ZwCfzN3J6ZprrOCJ+o3lwCTRJCdGkJsaycutuerTVp5fyQ7XaJ3zixIn3N1YQaXwrt+7m3jdnccOpvTixdxvXcaSOjDHcOKY397w5i+N7tqZJbKTrSCJ+oXlwCURVu6SohMvh9NlIiFi+uZC735jJzaf3UQEPAl1aN2VEj5ZMmprrOoqI32h/cAlE2i9cjkQlPAQs3rCTsW/N5ndn9GNkj1au40gDuXxUd6Yu2crqvD2uo4g0Ou0PLoGqT1pzVmzZzYGSMtdRxGNUwoPcgnUFPPDOHH5/1gCGdWvpOo40oMS4KC4d1Y2JnyzRYRAS9DQPLoEqNiqCrq2bsnjDTtdRxGNUwoPY3DU7eOi9ufzh7AwGdk51HUcawWkZaRSXlPH1ki2uo4g0Ks2DSyDL7JTCXI2kyGGcl3BjzF3GmHeMMWuMMdYYs+4Y159mjPnCGJNnjNlnjMk1xjxujNEy7yFmrtzGI/+ax73nDmRAeorrONJIwsMMWWN688Lny9l/UB91SvDSPLgEsoz0FOatUQmXH3JewoGHgZOA1RzjuHtjzDXAx0BT4I9UHgr0DfB/QI4xJr5xowaG7Nw8Hv9wAfedP4i+afqhFex6t2/OkK4teOCdORSXlruOI9LgNA8uga5bm6Zs33OAnUXFrqOIh3ihhHe21iZba0cDx/pM/TZgK3CctfYJa+3z1tprgEeoPFRodCNn9bxvlm7lr/9dxIMXDKaXTlQMGTed1ofmCdHc++ZM3fwjQUfz4BLowsPC6NchmflrC1xHEQ9xXsKttWtqcXkiUGitPfyfklXlPaRP6/xy0Wae+WQJD184hG5tmrmOI34UHma49cz+tEmK5+43ZrLvYKnrSCINRvPgEgwy0jUXLj/kvITX0idAL2PMn4wxPY0x7Y0xZwP3AlOBL93Gc+ezBZt44YtlTLhoKJ1bNXUdRxwIDzP89ud9SW/RhD/8YyZFxSriEhw0Dy7BoGq/cO1mJVUCrYT/FnjH97gU2AC8B0wGRltrqx2INcZca4yZ7beUfvbx3A288lUuj1w8jI4tmriOIw6FGcNNp/WhR9tm/P616ezZX+I6kki9aB5cgkXb5vEYYGNBSH9oL4cItBJeSmXx/hdwGXAu8ILv1xOP9Cbf7PggvyT0sw9nrePN71bx6CXDSEtJcB1HPMAYw/U/7UVGegp3vDadXfsOuo4kUmeaB5dgYYzR6ZnyAwFTwo0xYcAUYARwnrV2krX2Xd+NmY8BVxtjTnEa0s/en76Gd6ev4bFLhtE2WRvDyPeMMVx1cg+Gd2/J7ZOm6458CViaB5dgkpGewlxtVSg+AVPCgeOA44H37I8Hqt7xPZ7o30juvD1tFf+Zs57HLx1OK60QSTWMMVw2qjujerfh9knT2bFHRVwCj+bBJZhkpKewaH0B5RUVrqOIBwRSCW/rewyv5rWIwx6DlrWW179ZyacLNvH4pcNp0TTWdSTxuItO6MqpA9pz26Qctu0+4DqOSI1pHlyCTbP4aFo2iyN3y27XUcQDAqmEL/U9XmSMiTzstct9j7P8F8f/rLW88lUu3yzdwuOXDie5SYzrSBIgzhvRmTMHd+S2STlsLdzvOo5IjWgeXIJRRnqyRlIE8MDKsTHmEqCD77epQJQx5h7f79dba18DsNYuMMa8B5wDzDbGvA7sB04FzgCmA//2a3g/stbywhfLmbtmB49eMoxm8dGuI0mAOXtoOpHhYdw+KYc/Xqz7CMT7NA8uwSizUypvfreKi0/o6jqKOOa8hANX8eNZ7vG+x6nAa4c8fyGVR9RfBDxA5Ur+emAC8NCRtigMdNZanv10KUs2FvLHS4aSGBvlOpIEqDMGdSAy3HDHa9OZcNEQ0lK1paV418L1BQzoqFEUCS592iexautu9h8sIy7aCzVMXHE+jmKtHWWtNUf4GnXYtSXW2kettf2ttbHW2mhrbTdr7R+stUG58WaFtfzt48Xkbt7FIxergEv9jclI44qTuvP712ewbtte13FEqqV5cAlWMVERdGvTlEUbdIR9qHNewuXIyissT/xnIeu37+Whi4aQEHP4KLxI3ZzSrx3Xje7Fna/PYNVW3SAk3qN5cAlmmZ1SmbdWJTzUqYR7VHlFBY//ez75uw/w0IVDiI9WAZeGNapPG248rTd3vzmT3C27XMcR+QHNg0swq9wvfLvrGOKYSrgHlZVX8Mi/5rNrfwkP/HowsVGaGZPGcXzP1tzy836MfWsWSzcVuo4j8j/aH1yCWdfWTSnYe5CCvTq/IZSphHtMaXkFD783l+LScu4/fxAxkdVtiy7ScIZ1a8ltZ/bnvrdns2i9Ph4V9zQPLsEuPMzQv2My83WEfUhTCfeQkrJyHnhnDhYYe+5AoiJUwMU/BndpwV1nZzD+3bnM0w8FcUzz4BIKMtJTmKu/b0OaSrhHHCwt5763ZxMdEc7d52QSGa7/a8S/MtJTuOdXmUx4fx6zV2tWUdzRPLiEgsxOKcxbuwNrreso4oiangcUl5Rx71uzaBoXxV1nDyBCBVwc6dchmXHnDeTRD+YzfUW+6zgSojQPLqGgTVIcEWFhbNhR5DqKOKK259j+g2Xc/eYsWjSN5bZfDCA8TP+XiFu92zfngV8P5omPFjJteZ7rOBJiNA8uocIYQ4ZvNVxCkxqfQ0XFpfzhHzNIS0ngd2f0IzxMH72KN/Ro24wHLxjCkx8v5uslW1zHkRCieXAJJRnpKcxboxIeqlTCHdlzoIQ7X59BtzbN+M3pfQjT7KN4TNfWTZlw0RCe+3Qpny/c5DqOhAjNg0soGdAxmYUbdlJWXuE6ijigEu7A7v0l/P61GfTr0JwbTu2lHzbiWektE3nk4qG8/GUun8zf6DqOhADNg0soaRYfTZukOB2YFqJUwv2ssOggt0/KYUiXVK45pacKuHheh9Qm/PGSobw2dQUfzVnvOo4EMc2DSyiqPD1TIymhSCXcjwr2FnP7pBxO6NWGy3/SXQVcAka75AQeu3Q4/5y2mg9mrnUdR4KU5sElFOnmzNClEu4n23Yf4LZJOYzu346LT+iqAi4Bp3VSHI9dOowPZq7jnezVruNIENI8uISiPu2bszpvD/sOlrqOIn6mEu4HFdZy39uzOWNgB84f2cV1HJE6a9mssohPmbeRN75d6TqOBBnNg0soio4Mp0fbZixav9N1FPEzlXA/CDOGhy8awtnDOrmOIlJvqYmxPHrpML5avIVXv87VaW/SIDQPLqEsUyMpIUkl3E+axUe7jiDSYJKbxPDYpcPIyc3npS9VxKX+NA8uoUw3Z4YmlXARqZNm8dE8eskw5q7ZznOfLVMRl3rRPLiEss6tmlK47yA79hS7jiJ+pBIuInWWGBfFIxcPY+nGQp6esoQKFXGpI82DSygLDzMM6JiskZQQoxIuIvXSJDaSCRcPYXXeHv7630Uq4lJrmgcX8R1hrxIeUlTCRaTe4qMjefiiIWzZuY8/f7iQ8goVcak5zYOLQGanVOat3aHRvhCiEi4iDSI2KoLxFwxhx95iHv1gPuUVFa4jSYDQPLhI5VkMURFhrN9e5DqK+IlKuIg0mJjIcO4/fxBFxaU8/N48SstVxOXYNA8uUikjPYW5GkkJGSrhItKgoiPDGXfeQMoqLA++M4eSsnLXkcTDNA8u8r2qkRQJDSrhItLgoiLCuedXmYSHGR79YIFu1pQj0jy4yPcGdExm8Yad+hQxRDgv4caYu4wx7xhj1hhjrDFmXQ3ec4kxZpoxZo8xpsgYs9gYc68f4opIDUWGh3Hn2Rns2neQ5z9b5jqOeJTmwUW+lxgXRdvm8SzfvMt1FPED5yUceBg4CVgNFB7rYmPMS8ArwGbgTuBW4COgQ+NFFJG6iIoIZ9x5g5i7ZjvvTV/jOo54kObBRX6o8vTM7a5jiB94oYR3ttYmW2tHA1uOdqEx5irgCuBya+151tqJ1trnrLV3Wmuv9ktaEamVJrGRPHjBEN6fsZavlxz1P3EJMZoHF/kx7RceOpyXcGttjZbHTOVnlXcBc621r/mea2L0GaaI57VoGsv4Xw9m4pQlLFhX4DqOeITmwUV+rE9aEuu27WVfcanrKNLInJfwWugOdAayjTH3GmMKgD3ALmPMs8aYBLfxRORoOrVM5A9nZ/Dw+3NZt22v6zjiAZoHF/mxqIhwerRNYsF6LVgEu0Ar4QDnUzkHPgH4FfA+cB3wnyOtihtjrjXGzPZLShE5ogHpKVw3uhf3vDmT7XsOuI4jjmkeXKR6mZ00khIKAqmEN/E9pgK/stY+bq19z1p7BfAqMAoYU90brbXPW2sH+SemiBzNSX3bcubgjtz75ix93BrCNA8ucmSVN2eqhAe7QCrhVctmm621nx/22qu+x1H+iyMidXXu8E707dCc+3WYT8jSPLjIkXVulcie/SVs261PDINZIJXwTb7HvGpe2+p7TPJTFhGpB2MM1/+0NwnREfzpw4U6zCcEaR5c5MjCjGFAegrz12k1PJgFUglfROVqeNtqXmvne9zmvzgiUh/hYYbf/zKD7XsO8NIXy13HET/TPLjI0WkkJfgFTAm31u6n8ibMVsaYXx728g2+x4/9m0pE6iM6Mpz7zhtEzop8/j1zres44ieaBxc5tqqbM60+KQxaEa4DGGMu4fvTLlOBKGPMPb7fr6/aE9znD8ApwBvGmCeBdcDpwM+ASdbabP+kFpGGkhgXxUMXDuF3r2TTvEkMx/ds7TqSNDLNg4scW6tmccRGRbB22146tUx0HUcagfMSDlwFnHjYc+N9j1OB/5Vwa+0GY8ww4CEqT85sSuVx97cDf278qCLSGFo1i+OB8wfzhzdmkhQfTZ80jSkEM82Di9RM1emZKuHByfk4irV2lLXWHOFrVDXXr7PWXmStTbXWRllre/q2K6xwEF9EGkiX1k35/VkDGP/uHDZs12E+wUzz4CI1o/3Cg5vzEi4iUmVg51SuPrkn97w1i4K9xa7jSCPQPLhIzfXvmMySDYXayjVIqYSLiKeM7t+OMQPaVx7mc1CH+QQbzYOL1FxibBTtUuJZvnmX6yjSCFTCRcRzLjiuC93bNuPBd+dSWq5Js2CieXCR2slIT2GetioMSirhIuI5xhhuOq03UeFh/OWjhdqiK4gsWKd5cJHayExPYa7mwoOSSriIeFJ4WBh3nZPJpoJ9vPJVrus40gA0Dy5Se73aJ7F++16KijWeF2xUwkXEs2Iiw7n//EF8s2wrH81Z7zqO1NPmnfsIC9M8uEhtREWE06tdEgvWFbiOIg1MJVxEPK1ZfDQPXTCEf3yzkpzcfNdxpB4Wrt+peXCROqjaL1yCi0q4iHhem+bx3Hf+IJ74aCHLNhW6jiN1pHlwkbrJ7KSbM4ORSriIBITubZpx65n9eOCdOWwu2Oc6jtSS5sFF6i69ZSJ7i0vZtvuA6yiBo6gIxo2D1FQIC6t8HDeu8nmPUAkXkYAxtGtLLh3VjbvfnElh0UHXcaQWNA8uUndhxmgkpTaKimDYMHj0UdixA6ytfHz00crnPVLEVcJFJKCclpHGSX3aMvatWRwoKXMdR2pI8+Ai9ZORnsxcjaTUzGOPwerVUHzYycvFxZXPP/aYm1yHUQkXkYBzyYldSW/ZhIffm0t5hQ7zCQSaBxepn6qV8Aqdm3BsEyf+uIBXKS6GZ57xb54jUAkXkYBjjOE3p/elwsLf/rtYh/l4nObBReqvZbM4EmIiWZu/13UU7ys4xnaOx3rdT1TCRSQgRYSHcc+vMlmdv4d/fLPSdRw5Cs2DizSMjPRk5q7d7jqG9yUf4x/8x3rdT1TCRSRgxUZFMP7Xg/ls4SamzNvgOo4cgebBRRpGZqdU5q31xiqup2VlQUxM9a/FxMANN/g3zxGohItIQEtKiOahC4fwylcrmLlym+s4Uo0F6wro39EbK08igaxfh2SWbtxJSVm56yjedvvt0Lnzj4t4TEzl87ff7ibXYVTCRSTgtUtOYOx5A3n8wwWs2LLLdRw5hObBRRpOk9hI0lKasFSHlh1dQgJMnw533PHDfcLvuKPy+YQE1wkBlXARCRK92iXxfz/vy7i3Z7O1cL/rOOKzeec+wsMMrZrFuo4iEhR0emYNJSTA/ffDtm1QXl75eP/9ningoBIuIkFkRPdWXHh8V+5+Yya79ukwHy9YuH4n/TQPLtJghnZtwSfzNzFrlcbvAp1KuIgElTMGdeC4nq0Y9/Zsiks1N+ma5sFFGlbPdkn8/pcDeHLyYv78nwUUFZe6jiR1pBIuIkHnip90p23zeCa8P0+H+TikeXCRxpGRnsKz155ARHgY1z33jVbFA5RKuIgEHWMMt5zRj4Ol5Tw9ZYkO83FE8+AijScuOoLfnN6X287sr1XxAKUSLiJBKTI8jHvPzWT5pl28NW216zghSfPgIo1Pq+KBSyVcRIJWfHQk4y8YzOS5G/hswSbXcUKO5sFF/EOr4oFJJVxEglpykxgevGAwL3yxjDmrddyzv2geXMT/tCoeWJyXcGPMXcaYd4wxa4wx1hizrhbvfdT3nqJGjCgiAS4ttQn3/mogf/xgPqu27nYdJyRoHlzEjcNXxf/0oVbFvcp5CQceBk4CVgM1PgLKGDMAuAVQAReRY+qT1pybT+/D2LdnkbdLh/k0Ns2Di7hVtSoeGaFVca/yQgnvbK1NttaOBrbU5A3GmHDg78BkYE5jhhOR4HF8z9acN6Iz97wxkz37S1zHCWqaBxdxT6vi3ua8hFtr19Thbb8BegE3N3AcEQlyZw1JZ0SPVtz6ag75WhFvFJoHF/GWqlXxKK2Ke4rzEl5bxpgOwHjgfmvtetd5RCTwXHlSD07PTOOWV7JZqRnxBqd5cBHviYuO4ObT+3K7VsU9I+BKOPAMsBb4c03fYIy51hgzu/EiiUig+eXQdG4c04e735jJjJX5ruMEFc2Di3jXAK2Ke0ZAlXBjzAXAGOA6a21ZTd9nrX3eWjuo8ZKJSCAa2aMV958/iL98tIj/zNYHaw1F8+Ai3qZVcW8ImBJujGkO/AV40Vqb7TqPiASHnu2S+NNlw/lgxlpe+HwZFTrivl40Dy4SOLQq7lbAlHBgHBAP/N0Y06XqC4gFjO/37d1GFJFA1KZ5PE9cMYKlmwqZ8P48SsrKXUcKWJoHFwksWhV3J5BKeAcqS/gMYOUhX0OAON+vJztLJyIBLTEuikcuHgrAna/P0BaGdaR5cJHApFVx/wukEv5H4NxqvpYCxb5f3+IsnYgEvKiIcO46O4Ne7ZK45eVstuzc5zpSwNE8uEjg0qq4f0W4DmCMuYTKVW6AVCDKGHOP7/frrbWvAVhrc47w/puADtbadxs9rIgEvTBjuPqUnrRsFsetr+Yw9tyB9GyX5DpWQKiaB7/8J91dRxGReqhaFX/xi2Vc99w3/N/P+jK4SwvXsYKO8xIOXAWceNhz432PU4HX/BtHRATOGNSB1MQYxr09m9/+rC8je7RyHcnzNA8uEjyqVsWPX7uDP3+0kP4dkrnup71IiIl0HS1oOB9HsdaOstaaI3yNquH7E/wQVURCzLBuLXnowiE8PWUx789Y6zqO52keXCT4HD4rPnOlZsUbivMSLiLiZV1bN+WJy0cwee4GnvlkCeUV2sLwSDQPLhKcDp0Vf2rKYh7XrHiDUAkXETmGls3ieOKKEazJ38OD786huFRbGB5O+4OLBL+qVfForYo3CJVwEZEaSIiJ5KELhxAbFcEdk6aza99B15E8RfPgIqFBq+INRyVcRKSGoiLCuf0X/RnYKYX/ezmbjTuKXEfyDM2Di4QWrYrXn0q4iEgtGGO47CfdueC4Ltw2KYdFG3a6juQJmgcXCT0/WhX/9wJ266CzGlMJFxGpg1MHtOeOXwxg/Dtz+HrJFtdxnNI8uEhoq1oVj4+J4NpnpzJl3gYqrG5iPxaVcBGRtGPgOAAAFMdJREFUOhrYOZUJFw3lhc+X8fa01dgQ/aGjeXARiYuO4IZTe/PQBUP4eO5Gbns1h7X5e1zH8jSVcBGReujcKpEnrhjBV4s38+TkxZRXVLiO5HeaBxeRKl1aN+WJK0ZwUt+2/P71Gbzw+TKKS8pcx/IklXARkXpKTYzlT5cPZ2vhfu57ezYHQuwHjubBReRQ4WGGnw/swHPXncDOooNc8//t3XuYFOWVx/HvGYYBBhBBiNwUGBSEKKKAgVECqLms0dzImOiKF0xYrUBWkl0TXe8aY4wY1Ni6ElRkiSFEUXMhiSSg4kgQBYV4I8CoAVEgyJ0gcvaPqtZx6IEZnK6qZn6f5+Gp6arqmeNrd9fpt06duvtJKl9dk3RYqaMkXESkAbRs1pTrvzGItq2a8V9TnmH95h1JhxQL1YOLSG3atmrGpV/uz/fO6MfkP7/C1dMX8va725IOKzWUhIuINJDiJkWMP70fJx7VkfH3VVL1zuakQ8o71YOLyL7079Geu8YMpXfnNoz9+Tx+VbmcXe83vtK9mpSEi4g0IDPj7KFHct7wXlw6dT6LV65LOqS8Uj24iNRFSXETzh56JLeNPpEXqtYTTHqq0bd4VRIuIpIHp/TryuUjj+PGhxcx+8V/JB1O3qgeXETqo3O7ltxw1iBGfboXNz28iAmPNd7e4krCRUTypH/39tw8ajAPzH2NaU8uO+BaGKoeXET2h5kxtG8n7rn407Rs3rTR9hZXEi4ikkfdP9Gan15QTuWra7j1Ny8eUHWQqgcXkY+jZbOmXPTZvh/0Fv/e/Y2rt7iScBGRPDukdXNuOW8I727byRUPPsvWHe8lHVKDUD24iDSEbG/xU/qFvcUnzX65UbR6VRIuIhKDFiXFXHPmALq0K+V7U55h7abtSYf0sakeXEQaSvXe4hu2/IsxjaC3uJJwEZGYNCkqYuy/Hc3Jx3ThkvsqWb5mY9Ih7TfVg4tIPuzRW/yXzx6wvcWVhIuIxMjMOLO8J2NO7cNl0xawcPnapEPaL6oHF5F8+qC3eJeDGfvzeUx/+sDrLa4kXEQkAcM+2ZmrKgbwk0cXM2vRG0mHU2+qBxeRfMv2Fr/9wpNY8saB11tcSbiISEKOPrwdt5w7hOlPL+f+Oa8WVAtD1YOLSFw6tS3l+m8MYtSwXtw088DpLa4kXEQkQYe1b8XEC8pZtHIdP35kMTt3vZ90SPukenARiZuZMbRPJyZdNOyA6S2uJFxEJGEHt2zGj0cNZtf7u/nmXU/w6LNV7Ehxey7Vg4tIUkqbFX/QW3zWosLuLa4kXEQkBZo3bcIVXxvAD75yHC+sXMe5d8xh6hOvpfKUq+rBRSRp2d7ipxZwb/HipAMQEZEP9e3alqvOHMib67bw0PwVjL5zDiOO7sLIwWV0aluadHhAWA9+fFn7pMMQkUauyIwvDOhGee+OTJr9MmPufpKLP9eX8t4d2b5zFzMql/Ob515n87b3aF3alDMGdKOivCctStKR/lrSFwKZ2WXA8cAAoAfwurt3z7Ffc2AUcDpwLHAo8BbwV+A6d395X38rCAIHyGQyDRW+iEherd+8g0cXVDFr0RscX9aBrw0p48hObRKLx905e+KfufX88tR8KRARAVhctY47fr+UTge3YPWG7azdtJ2duz5sa1hSXESntqXcNvrEOBPxWk8ZpqEc5UbgZGA5sGEv+3UH7gHaAZOBscCDwOeAxWY2Ir9hiojE75DWzRl9ylHcP24ER3ZqwzXTF/KD//srz61Ym0g3FdWDi0ha9e8e9hb/167drPrn1o8k4AA7d+3mrQ3bmFG5PKEIPyoN8/E93X0FgJktBVrVst9a4Dh3X1x9pZlNAxYBPwEG5jNQEZGktGzWlK8NKeNLJ3Rn7tLV3P3HlygpLqJiSE+G9u1Ik6J45lRUDy4iaVZS3ISqtZtr3b5z125++9wbnDu8d4xR5ZZ4Ep5NwOuw33pgfY71L0XJ+9ENHZuISNo0bVLEZ47tyin9urBg2TvMeGYF9855hZGDy/jcsV1pnudTrKoHF5G027ztvb1u35SSC94TT8I/LjMrAjoBbycdi4hIXIrMGNzrUAb3OpSX/rGBX1cuZ9qTyzhjYDe+OKg7bUpLGvxvZvuDnz8i+RkkEZHatC5tyqa9JOIH5eHzcX+koSb847qYMAmfUtsOZjbGzBbGF5KISHyyHVUmnDeE9Zt3MPrOOfxs1lLWbNjWoH9H9eAiUgjOGNCNkuLcKW5JcRGnDzg85ohyK+gk3MzKgQnAi4QXeObk7ve4u+rFReSAdlj7Vlxyej/uuWgYpSXFjJs8jx89vIhlb21skN+venARKQQV5T3p1LZ0j0Q82x2lorxnQpF9VMEm4WY2APgdsBo4zd13JBySiEgq5KujygtV6zm2u25VLyLp1qKkmNtGn0jFkDLalJZgQJvSEiqGlMXdnnCv0hFFPZnZ8cDjwEZghLuvSjgkEZHUaciOKqoHF5FC0qKkmHOH905FF5TaFFwSbmbHESbgmwkT8NcTDklEJNUaoqOK6sFFRBpWQSXhUQI+G9hKmICvTDgkEZGC8XE6qqgeXESkYSWehJvZKKBb9LADUGJmV0SPX3f3qdF+3QhnwNsCtwPl0YWZ1c10960xhC0iUtCyHVXeXLeFh+avYPSdczn5mM6M/FQZHXPcjl79wUVEGlbiSThwITCsxrrro+UTwNTo5x5A9oqga2r5XT0IZ8lFRKQOsh1VRg3rxaMLqhg3eR7Hl3WgYkgZR3RqA6geXEQkHxJPwt19eB33mwvoPKiISB5kO6p8/aSezHr+Ta6evpDDO7SiYkhPOhzUXPXgIiINLPEkXERE0qNmR5W7/vg3Nm7bycCeHVQPLiLSgJSEi4jIHqp3VFn497UcqllwEZEGpSRcRERqVWTGCUd+IukwREQOOAV7x0wRERERkUKlJFxEREREJGZKwkVEREREYqYkXEREREQkZkrCRURERERipiRcRERERCRmSsJFRERERGKmJFxEREREJGZKwkVEREREYqYkXEREREQkZkrCRURERERipiRcRERERCRmxUkHkIQgCJIOQUREREQOfJ7JZCzXBs2Ei4iIiIjEzNw96RgaDTNb6O4Dk46jUGi86kfjVT8ar/rReNWPxqt+NF71o/Gqn7SOl2bCRURERERipiRcRERERCRmSsLjdU/SARQYjVf9aLzqR+NVPxqv+tF41Y/Gq340XvWTyvFSTbiIiIiISMw0Ey4iIiIiEjMl4SIiIiIiMVMSnkdmVmRm483sFTPbYWZvmtkEM2uZdGxpY2a9zOw6M5tvZmvNbLOZLTaz/9F41Y2ZlZrZSjNzM/tZ0vGkkZm1M7NbzOzv0XtyrZnNMbOhSceWRmbWyswuN7Ml0XtynZlVmtn5Zpbz5hONgZldZmYzzGxF9H6r2sf+nzKz2dEYbjKzP5hZ/5jCTVxdx8vMmpvZt8zsUTOrMrPt0XMeNLM+MYedmPq+vmo89+boOVvyGGKq7M94mdkoM3s6ej9uMbOlZnZlDOF+NA7VhOePmd0GfAeYCcwC+gDjgKeAU919d4LhpYqZ3QR8G3gMmA+8B4wAzgReBAa7+/bkIkw/M7sF+A+gFXCnu49NOKRUMbNuwFzC8ZkMvAa0AfoBf3T3XyYXXfqYWRHwBFAOTCF8X5YCZwEnADe7+/eTizA5ZubAP4HngQHAJnfvXsu+gwlfd6uA7JfjscAngHJ3X5LveJNW1/Eys6OAl4F5wJ+A1UAZcDHQEvi8u8+JKezE1Of1VeN5/YFngR2E+V2rfMaZFvUdLzO7FzgPeIjwvfk+0ANo7+7fzHe8H4lFSXh+mNkngSXATHcfWW39OOB24N/d/RdJxZc2ZjYQWObuG2usvwH4H2Ccu2t2txZmdjywALgUmICS8D2Y2VNAd+AEd38r4XBSz8yGAJXARHcfX219CfAK0M7dD04qviSZWZm7r4h+Xgq02ksSvgA4Cujj7quidV0Ik8357v7ZeKJOTl3Hy8wOAQ5z98U11vcFFgFL0njDlYZWn9dXtec0Ifyi/BZwEDCwESXh9Xk/Xgj8HDjX3afGF2VuKkfJn7MAAybWWD8J2AacE3tEKebuC2sm4JHp0fLoOOMpJNGH7yTgD8DDCYeTSmb2aeAkwtnbt8ysqZmVJh1Xyh0ULVdXX+nuO4F1wNbYI0qJ7AF/X8zsCGAQMCObgEfPXwXMAE41s475iTI96jpe7r6+ZgIerX8JWEojOQ7Udbxq+A7Ql/Bse6NSj/ejAZcBz2cTcDNrnWRpnZLw/BkE7CacnfyAu+8AFkfbZd+6Rsu3E40i3cYTzrRp5rt2p0XLN8zsN8B2YKuZvWZm+kKc2wLgXeBSM6sws8PNrLeZ/YjwlO81iUZXGLKf88/k2DafcKJmQHzhFKaoNKoTOg7kFJXaXQ9c6+6vJx1PivUGegKVZnalma0HNgHvmtndZhb7mYPiuP9gI9IZWOfu/8qxbRVQbmYl0ayS5BDN8F4F7AJUupODmfUArgWuc/cqM+uebESp1TtaTgKWEdYDNgO+C0w1s6bufl9SwaWRu28wsy8Snrr9VbVNm4GR7v5IMpEVlM7RclWObdl1XWKKpZBdTJiEX590ICl1F7ASuDXpQFIuexz4OlAC3EA4bqcTXk/V28xO9hjrtJWE508pkCsBh/Ciiew+SsJrNxEYDFzu7q8mHUxK6cO3blpHy83AiOyXXzObCawAbjSzKbpYeg9bCMsAHiOsD29HeAH1L8zsS+7+eJLBFYBsyVOuY8GOGvtIDmZWTnidy4vAjQmHkzpmdhbweeAkd9+VdDwplz0OdAA+4+6zo8cPRSUp5xGO5ay4AlI5Sv5sI5xpy6V5tX0kBzO7nrC84h53/1HS8aRRVEbxWeAid38v6XhSLttZ58HqZ5/cfQNhgtmRD2dJBDCzYwgT78fd/b/dfaa7TyasrV8DTIrOVkntsp/xuY4FOg7sg5kNAH5HeF3CaVE5p0TMrB3hZNVkd69MOp4CkD0OrKqWgGdNiZbD4wtHSXg+rQbam1muD98uhKUqmgXPwcyuAa4A7gMuSjaadIpeV7cCvwfWmNkR0UVg3aJd2kTrGmX3ihz+ES3X5NiW7ZTSNqZYCsV4wkRxRvWV7r6NMDHqRthtRmqXvag1V8lJdl2uUpVGL+r49DiwkfDslcZpT1cTtm6clD0GRMeBFoTXIR5hZoclG2KqpO44oCQ8f54lHN8Tqq80s+ZAf2BhEkGlnZldTfjB8gDwzThrswpMC8JTal8grHHO/psbbT8nehxrz9MUy14g3TXHtuy6d2KKpVBkk8Rcs93FNZaS27PRckiObYMBB56LL5zCYGbHESbg2fIxXWyYWzfCJPyvfPQ4cAJhmdMyYiytKABLCGfDc30pTuQ4oCQ8f6YTfsBeUmP9twjfHNNijyjlzOwqwo4LU4ELVJ+7V1uBihz/gmj7H6LHjyUSXfo8QnhAP6f6FfBm1gn4MmGP+r8nFVxKvRQtz6++Mjq78iVgA7A85pgKSvSaWghUmFn2Ik2inyuAv7h7rlm5RitKwGcTfsaNcPeVCYeUZj8m93HgJcJrDioIz2gJH5zFexjoaGZfqbH54mj5+zhj0s168sjM7iCsa55J+D+2D2Evz6eBk5VkfsjMvk14N7k3gCsJ2ztW97YuAtu3qDvKSnSznj2Y2Rjgf4G/AfcSXh2f7bpwurv/KcHwUidqe/Y84enZaYSfW+0IJxK6A99290xiASbIzEbxYenXOMLX0oTo8evVbwISXVg4h/BU+B3VnnMocKK7vxBL0Amq63hFr7nnCF9n15L7S95Mdz+ge9TX5/VVy/Pn0rhu1lOf9+PhhGdG2xC+H6sIW9h+AXjA3c+LKewwHiXh+RNdtHQJMIbwoLWOcIb8KnffkmBoqWNm9xNemVybJ9x9eDzRFC4l4XtnZl8lvKvoMYRf9J4h7K37dKKBpZSZ9SRsE3oKYdK4nfA+BxPdvdHeGCpKcobVsnmPz6ro7qM3AJ8iPENaCVzm7s/nMczUqOt4mdlwwi8se9PD3asaKrY0qu/rq5bnN6YkfC71ez92B35I2NigDeGXvcnArXFPjioJFxERERGJmWrCRURERERipiRcRERERCRmSsJFRERERGKmJFxEREREJGZKwkVEREREYqYkXEREREQkZkrCRURERERipiRcRKSRCoJgbhAEulmEiEgCipMOQEREPp79SKQvyGQy9+cjFhERqRsl4SIihe/aHOsuIbwl823AuzW2LY6W5wKleYxLRERqodvWi4gcgIIgqAK6AT0ymUxVstGIiEhNmgkXEWmkgiCYCwzLZDJWbd1wYA7h7PpvgRuAIcBu4C/AJZlM5s0gCMqAG4FTgFbA/GjbCzn+Tinwn8DXgSMBB5YAt2cymQfz9d8nIpJmujBTRERyGQQ8Ff08CVgAfBX4cxAER0WPuwIPAL8DhgGPB0HQqvovCYLgYGAeYcL+PnAvMAXoAPwiCIIb8v+fIiKSPpoJFxGRXE4DzslkMtOyK4IgmAyMBiqBCZlM5ofVtl0JXAdcSFiHnjUROA74fiaTubna/s2BR4DLgyD4dSaTWYyISCOimXAREcllXvUEPDIlWm4Ebqqx7YFo2T+7IgiCQ4BzgIXVE3CATCazA/g+YMDZDRW0iEih0Ey4iIjksjDHutXRcnEmk3m/xrZV0bJrtXWDgCaAB0FwTY7f1zRa9tnfIEVECpWScBERyWVjjnW7atuWyWR2BUEAHybWAIdEy0HRv9q02ss2EZEDkpJwERHJl2yy/tNMJvPdRCMREUkZ1YSLiEi+LCBsbTg06UBERNJGSbiIiORFJpN5B5gGDAyC4MogCPY4+xoEQc8gCHrEH52ISLJUjiIiIvk0lvAGPdcBo4IgmAe8DXQmvCBzEHAWsDKxCEVEEqCZcBERyZtMJrOJ8EY+44B1wEjgu8AIYDMwHng8sQBFRBJi7p50DCIiIiIijYpmwkVEREREYqYkXEREREQkZkrCRURERERipiRcRERERCRmSsJFRERERGKmJFxEREREJGZKwkVEREREYqYkXEREREQkZkrCRURERERipiRcRERERCRm/w8hsQaPD7qRsAAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# ---- Get a sequence\n",
+ "\n",
+ "\n",
+ "i=random.randint(0,len(dataset_test)-sequence_len)\n",
+ "\n",
+ "sequence = dataset_test[i:i+sequence_len]\n",
+ "sequence_true = dataset_test[i:i+sequence_len+1]\n",
+ "\n",
+ "pred = loaded_model.predict( np.array([sequence]) )\n",
+ "\n",
+ "for i,s in enumerate(sequence_true):\n",
+ " s = s*std + mean\n",
+ " sequence_true[i]=s\n",
+ "\n",
+ "for i,s in enumerate(pred):\n",
+ " s = s*std + mean\n",
+ " pred[i]=s\n",
+ "\n",
+ "\n",
+ " \n",
+ "c=11\n",
+ "\n",
+ "t=np.arange(sequence_len+1)\n",
+ "\n",
+ "plt.figure(figsize=(12,6))\n",
+ "plt.title(features[c])\n",
+ "plt.ylabel(features[c])\n",
+ "plt.xlabel('Time')\n",
+ "plt.plot(t, sequence_true[:,c], '-', linewidth=1, color='steelblue')\n",
+ "plt.plot(t[-1], sequence_true[-1:,c], 'o', fillstyle='full', markersize=8, color='steelblue') # ce qui nous interesse\n",
+ "plt.plot(t[-1], [pred[0][c]], 'o', fillstyle='full', markersize=8, color='red') # ce qui nous interesse\n",
+ "plt.show()"
]
},
{
diff --git a/fidle/pwk.py b/fidle/pwk.py
index 99a3651a9f4dbfd89d6c69d3aa437936d1fad287..abbeea09107b7c5df49caf3726aba9494be786be 100644
--- a/fidle/pwk.py
+++ b/fidle/pwk.py
@@ -30,7 +30,7 @@ import matplotlib.pyplot as plt
import seaborn as sn #IDRIS : module en cours d'installation
from IPython.display import display,Image,Markdown,HTML
-VERSION='0.4.3'
+VERSION='0.4.4'
_save_figs = False
_figs_dir = './figs'
@@ -420,7 +420,10 @@ def save_fig(filename='auto', png=True, svg=False):
if png : plt.savefig( f'{path}.png')
if svg : plt.savefig( f'{path}.png')
if filename=='auto': _figs_id+=1
-
+
+
+def subtitle(t):
+ display(Markdown(f'<br>**{t}**'))
def display_md(md_text):
display(Markdown(md_text))