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-38
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‎.gitignore

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@@ -36,3 +36,5 @@ test-results
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lightning_logs
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jobs.csv
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*.parquet
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download_commands.txt
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_data

‎eotdl/eotdl/access/search.py

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@@ -19,8 +19,6 @@ def search_sentinel_imagery(
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evaluate_sentinel_parameters(
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sensor, time_interval, bounding_box, output_needed=False
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)
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client = SHClient()
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parameters = SH_PARAMETERS_DICT[sensor]()
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return client.search_data(bounding_box, time_interval, parameters)

‎tutorials/notebooks/10_search_sentinel_imagery.ipynb

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],
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"metadata": {
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"kernelspec": {
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"display_name": "sen12floods",
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"display_name": "eotdl",
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"language": "python",
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"name": "python3"
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},

‎tutorials/notebooks/11_download_sentinel_imagery.ipynb

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],
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"metadata": {
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"kernelspec": {
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"display_name": "sen12floods",
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"display_name": "eotdl",
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"language": "python",
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"name": "python3"
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},

‎tutorials/usecases/useCaseA/use-case-a-satellogic.ipynb

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],
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"metadata": {
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"kernelspec": {
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"display_name": "general3_12",
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
@@ -994160,7 +994160,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.12.7"
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}
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},
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"nbformat": 4,

‎tutorials/usecases/useCaseC/dataset.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"%load_ext autoreload\n",
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"%autoreload 2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'2024.11.07'"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import eotdl\n",
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"\n",
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"eotdl.__version__"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In this notebook we generate the dataset for the use case\n",
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"\n",
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"1. Generate list of Satellogic images to be used (containing bb and acquisition time)\n",
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"2. Explore available S1/S2 images with different criteria\n",
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"\t- bounding box overlap\n",
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"\t- acquisition time overlap\n",
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"3. Download matching S1/S2 at given resolution\n",
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"4. Generate metadata and ingest to EOTDL "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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"ename": "ImportError",
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"evalue": "Missing optional dependency 'pyarrow.parquet'. pyarrow is required for Parquet support. \"\n \"Use pip or conda to install pyarrow.parquet.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[16], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgeopandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mgpd\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m gdf \u001b[38;5;241m=\u001b[39m \u001b[43mgpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_parquet\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43msatellogic-earthview-items.parquet\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 5\u001b[0m gdf\u001b[38;5;241m.\u001b[39mhead()\n",
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"File \u001b[0;32m~/miniconda3/envs/eotdl/lib/python3.8/site-packages/geopandas/io/arrow.py:586\u001b[0m, in \u001b[0;36m_read_parquet\u001b[0;34m(path, columns, storage_options, **kwargs)\u001b[0m\n\u001b[1;32m 523\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_read_parquet\u001b[39m(path, columns\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, storage_options\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 524\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 525\u001b[0m \u001b[38;5;124;03m Load a Parquet object from the file path, returning a GeoDataFrame.\u001b[39;00m\n\u001b[1;32m 526\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 583\u001b[0m \u001b[38;5;124;03m ... ) # doctest: +SKIP\u001b[39;00m\n\u001b[1;32m 584\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 586\u001b[0m parquet \u001b[38;5;241m=\u001b[39m \u001b[43mimport_optional_dependency\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 587\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpyarrow.parquet\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpyarrow is required for Parquet support.\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m 588\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 589\u001b[0m \u001b[38;5;66;03m# TODO(https://github.com/pandas-dev/pandas/pull/41194): see if pandas\u001b[39;00m\n\u001b[1;32m 590\u001b[0m \u001b[38;5;66;03m# adds filesystem as a keyword and match that.\u001b[39;00m\n\u001b[1;32m 591\u001b[0m filesystem \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfilesystem\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n",
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"File \u001b[0;32m~/miniconda3/envs/eotdl/lib/python3.8/site-packages/geopandas/_compat.py:239\u001b[0m, in \u001b[0;36mimport_optional_dependency\u001b[0;34m(name, extra)\u001b[0m\n\u001b[1;32m 236\u001b[0m module \u001b[38;5;241m=\u001b[39m importlib\u001b[38;5;241m.\u001b[39mimport_module(name)\n\u001b[1;32m 238\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m:\n\u001b[0;32m--> 239\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 241\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\n",
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"\u001b[0;31mImportError\u001b[0m: Missing optional dependency 'pyarrow.parquet'. pyarrow is required for Parquet support. \"\n \"Use pip or conda to install pyarrow.parquet."
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]
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}
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],
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"source": [
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"import geopandas as gpd\n",
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"\n",
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"gdf = gpd.read_parquet('satellogic-earthview-items.parquet')\n",
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"\n",
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"gdf.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"data": {
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" json_path zone \\\n",
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"metadata": {},
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"output_type": "execute_result"
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}
236+
],
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"source": [
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"sample = gdf.sample(10)\n",
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"sample"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"('sentinel-1-grd', 'sentinel-2-l1c', 'sentinel-2-l2a', 'dem')"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from eotdl.access import SUPPORTED_SENSORS\n",
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"\n",
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"SUPPORTED_SENSORS"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'sample' is not defined",
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"output_type": "error",
273+
"traceback": [
274+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[15], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01meotdl\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01maccess\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m search_sentinel_imagery\n\u001b[1;32m 3\u001b[0m matches \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m----> 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m \u001b[43msample\u001b[49m:\n\u001b[1;32m 5\u001b[0m \tdates \u001b[38;5;241m=\u001b[39m item\u001b[38;5;241m.\u001b[39mdate\n\u001b[1;32m 6\u001b[0m \tbb \u001b[38;5;241m=\u001b[39m item\u001b[38;5;241m.\u001b[39mgeometry\n",
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"\u001b[0;31mNameError\u001b[0m: name 'sample' is not defined"
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]
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}
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],
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"source": [
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"from eotdl.access import search_sentinel_imagery\n",
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"\n",
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"matches = []\n",
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"for item in sample:\n",
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"\tdates = item.date\n",
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"\tbb = item.geometry\n",
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"\tr = search_sentinel_imagery(dates, bb, 'sentinel-2-l2a')\n",
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"\tlist(r)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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