{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NEXTMap One - Elevation Data (Streaming) and Viewshed\n",
    "In this exmaple we show how to use NEXTMap One digital elevation model following by a pocessing call (viewshed). Since NEXTMap One digital elevation model is a Streaming block which does not allow downloading or storing the original images, only the analytics results\n",
    "This is the next generation global 3D terrain dataset by Intermap. It provides seamless data at one-meter resolution enabling precise spatial analysis. NEXTMap One is a comprehensive worldwide offering that is available as a digital surface model (DSM) and digital terrain model (DTM).\n",
    "\n",
    "Viewshed block determines everywhere visible from a specific location. The algorithm's input is a DEM, an observer location, height above the ground for the observation, and a range of azimuth angles defining the observation direction. Based on a calculated maximum target distance and target height the algorithm determines whether every potential target within the maximum distance will be visible. Output of this block is the geographical area that is visible from a location. It includes all surrounding points that are in line-of-sight with that location and excludes points that are beyond the horizon or obstructed by terrain and other features (e.g., buildings, trees).\n",
    "\n",
    "In the example, the workflow, the area of interest and the workflow parameters are defined. After running the job, the results are downloaded and visualized. For more information, refer to the block's [UP42 Marketplace page](https://marketplace.up42.com/block/1f09fcb0-7f5c-4e91-b059-36df7f64d2c9) and [Documentation](https://docs.up42.com/up42-blocks/data/nextmap-1m.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import up42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "rental-spokesman",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-11 13:33:28,729 - Authentication with UP42 successful!\n",
      "2021-03-11 13:33:29,389 - Initialized Project(name: nextmap, project_id: 74faca4e-bbf5-480b-ac67-6edf10b31643, description: , createdAt: 2020-07-28T14:46:43.620Z)\n"
     ]
    }
   ],
   "source": [
    "up42.authenticate(project_id=\"1234\", \n",
    "                  project_api_key=\"abcd\")\n",
    "project = up42.initialize_project()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "square-atmosphere",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-11 13:33:30,210 - Getting existing workflows in project ...\n",
      "2021-03-11 13:33:30,540 - Got 3 workflows for project 74faca4e-bbf5-480b-ac67-6edf10b31643.\n",
      "100%|██████████| 3/3 [00:01<00:00,  2.93it/s]\n",
      "2021-03-11 13:33:31,582 - Using existing workflow: NEXTMap-One-example - 3d334cb9-be35-4663-a96e-c58f2a31da7e\n",
      "2021-03-11 13:33:35,230 - Added tasks to workflow: [{'name': 'nextmapone-1m:1', 'parentName': None, 'blockId': '1f09fcb0-7f5c-4e91-b059-36df7f64d2c9'}, {'name': 'viewshed:1', 'parentName': 'nextmapone-1m:1', 'blockId': '52060864-1346-40ba-b340-f47083bb2d8a'}]\n"
     ]
    }
   ],
   "source": [
    "# Construct workflow\n",
    "workflow = project.create_workflow(name=\"NEXTMap-One-example\", use_existing=True)\n",
    "input_tasks = [\"nextmapone-1m\", \"viewshed\"]\n",
    "workflow.add_workflow_tasks(input_tasks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "nextmap_example_aoi = {\"type\": \"FeatureCollection\",\"features\": [{\"type\": \"Feature\",\"properties\": {},\n",
    "      \"geometry\": {\"type\": \"Polygon\",\"coordinates\": [[[-105.29594,40.049061],\n",
    "                                                      [-105.283048,40.049061],\n",
    "                                                      [-105.283048,40.061953],\n",
    "                                                      [-105.29594,40.061953],\n",
    "                                                      [-105.29594,40.049061]]]}}]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_parameters = workflow.construct_parameters(geometry=nextmap_example_aoi, geometry_operation=\"bbox\")\n",
    "input_parameters[\"viewshed:1\"].update({\n",
    "    \"observer_latitude\": 40.0556926967,\n",
    "    \"observer_longitude\": -105.2884229696,\n",
    "    \"observer_height_meters\": 3,\n",
    "    \"target_height_meters\": 2,\n",
    "    \"start_azimuth_degrees\": 0})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "virtual-duration",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-11 13:33:46,484 - Estimated: 2664-2664 Credits, Duration: 0-0 min.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'nextmapone-1m:1': {'blockConsumption': {'resources': {'unit': 'SQUARE_KM',\n",
       "    'min': 1.576462,\n",
       "    'max': 1.576462},\n",
       "   'credit': {'min': 2562, 'max': 2562}},\n",
       "  'machineConsumption': {'duration': {'min': 0, 'max': 0},\n",
       "   'credit': {'min': 1, 'max': 1}}},\n",
       " 'viewshed:1': {'blockConsumption': {'resources': {'unit': 'SCENE',\n",
       "    'min': 1,\n",
       "    'max': 1},\n",
       "   'credit': {'min': 100, 'max': 100}},\n",
       "  'machineConsumption': {'duration': {'min': 0, 'max': 0},\n",
       "   'credit': {'min': 1, 'max': 1}}}}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Price estimation\n",
    "workflow.estimate_job(input_parameters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "instant-fundamentals",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-11 13:34:39,526 - +++++++++++++++++++++++++++++++++\n",
      "2021-03-11 13:34:39,527 - Running this job as Test Query...\n",
      "2021-03-11 13:34:39,528 - +++++++++++++++++++++++++++++++++\n",
      "2021-03-11 13:34:39,529 - Selected input_parameters: {'nextmapone-1m:1': {'clip_to_aoi': True, 'bbox': [-105.29594, 40.049061, -105.283048, 40.061953]}, 'viewshed:1': {'end_azimuth_degrees': 360.0, 'max_distance_meters': 200.0, 'target_height_meters': 2, 'start_azimuth_degrees': 0, 'observer_height_meters': 3, 'observer_latitude': 40.0556926967, 'observer_longitude': -105.2884229696}, 'config': {'mode': 'DRY_RUN'}}\n",
      "2021-03-11 13:34:40,757 - Created and running new job: 2ad90de7-3f97-4744-b282-72761d0dbc02.\n",
      "2021-03-11 13:34:41,084 - Tracking job status continuously, reporting every 30 seconds...\n",
      "2021-03-11 13:35:02,829 - Job finished successfully! - 2ad90de7-3f97-4744-b282-72761d0dbc02\n"
     ]
    }
   ],
   "source": [
    "# Run a test job to query data availability and check the configuration.\n",
    "test_job = workflow.test_job(input_parameters, track_status=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "driving-pastor",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-03-11 13:35:10,143 - Selected input_parameters: {'nextmapone-1m:1': {'clip_to_aoi': True, 'bbox': [-105.29594, 40.049061, -105.283048, 40.061953]}, 'viewshed:1': {'end_azimuth_degrees': 360.0, 'max_distance_meters': 200.0, 'target_height_meters': 2, 'start_azimuth_degrees': 0, 'observer_height_meters': 3, 'observer_latitude': 40.0556926967, 'observer_longitude': -105.2884229696}}\n",
      "2021-03-11 13:35:15,371 - Created and running new job: e0492bbf-c852-40f6-91ae-41abf3eef8cc.\n",
      "2021-03-11 13:35:15,704 - Tracking job status continuously, reporting every 30 seconds...\n",
      "2021-03-11 13:35:48,168 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:36:20,349 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:36:52,371 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:37:24,503 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:37:56,514 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:38:28,525 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:39:00,611 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:39:32,648 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:40:04,791 - Job is RUNNING! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n",
      "2021-03-11 13:40:20,806 - Job finished successfully! - e0492bbf-c852-40f6-91ae-41abf3eef8cc\n"
     ]
    }
   ],
   "source": [
    "# Run the actual job.\n",
    "job = workflow.run_job(input_parameters, track_status=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "job.download_results()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "toxic-reality",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "job.plot_results(figsize=(6,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "sacred-christmas",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "up42-pydev",
   "language": "python",
   "name": "up42-pydev"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}