zhuwq0 commited on
Commit
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1 Parent(s): f07f54a
Files changed (1) hide show
  1. example_fastapi.ipynb +46 -54
example_fastapi.ipynb CHANGED
@@ -27,11 +27,12 @@
27
  },
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  {
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  "cell_type": "code",
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- "execution_count": 2,
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  "metadata": {},
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  "outputs": [],
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  "source": [
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- "ADLOC_API_URL = \"http://127.0.0.1:8000\"\n"
 
35
  ]
36
  },
37
  {
@@ -1262,15 +1263,6 @@
1262
  "plt.show()"
1263
  ]
1264
  },
1265
- {
1266
- "cell_type": "code",
1267
- "execution_count": 13,
1268
- "metadata": {},
1269
- "outputs": [],
1270
- "source": [
1271
- "from app import run_gamma"
1272
- ]
1273
- },
1274
  {
1275
  "cell_type": "code",
1276
  "execution_count": 14,
@@ -1281,29 +1273,16 @@
1281
  "output_type": "stream",
1282
  "text": [
1283
  "Associating 108 picks with 1 CPUs\n",
1284
- "."
1285
  ]
1286
- }
1287
- ],
1288
- "source": [
1289
- "config[\"region\"] = \"Ridgecrest\"\n",
1290
- "config[\"event_index\"] = 1\n",
1291
- "\n",
1292
- "evengts_, picks_ = run_gamma(picks, stations, config)"
1293
- ]
1294
- },
1295
- {
1296
- "cell_type": "code",
1297
- "execution_count": 15,
1298
- "metadata": {},
1299
- "outputs": [
1300
  {
1301
  "data": {
1302
  "text/plain": [
1303
- "<matplotlib.collections.PathCollection at 0x31dd37040>"
1304
  ]
1305
  },
1306
- "execution_count": 15,
1307
  "metadata": {},
1308
  "output_type": "execute_result"
1309
  },
@@ -1319,18 +1298,24 @@
1319
  }
1320
  ],
1321
  "source": [
 
 
 
 
 
 
 
1322
  "plt.figure()\n",
1323
  "mapping_color = lambda x: f\"C{x}\" if x!= -1 else \"black\"\n",
1324
- "plt.scatter(picks_[\"timestamp\"], picks_[\"latitude\"], c=picks_[\"event_index\"].apply(mapping_color), s=10)"
1325
  ]
1326
  },
1327
  {
1328
  "cell_type": "code",
1329
- "execution_count": 28,
1330
  "metadata": {},
1331
  "outputs": [],
1332
  "source": [
1333
- "# call loalhost:8000/predict\n",
1334
  "picks_ = picks.copy()\n",
1335
  "picks_[\"phase_time\"] = picks_[\"phase_time\"].apply(lambda x: x.isoformat())\n",
1336
  "stations_ = stations.copy()\n",
@@ -1338,7 +1323,7 @@
1338
  "picks_ = picks_.to_dict(orient=\"records\")\n",
1339
  "stations_ = stations.to_dict(orient=\"records\")\n",
1340
  "\n",
1341
- "response = requests.post(f\"{ADLOC_API_URL}/predict/\", json={\"picks\": {\"data\":picks_}, \"stations\": {\"data\": stations_}, \"config\": config})\n",
1342
  "\n",
1343
  "if response.status_code == 200:\n",
1344
  " result = response.json()\n",
@@ -1350,16 +1335,16 @@
1350
  },
1351
  {
1352
  "cell_type": "code",
1353
- "execution_count": 29,
1354
  "metadata": {},
1355
  "outputs": [
1356
  {
1357
  "data": {
1358
  "text/plain": [
1359
- "<matplotlib.collections.PathCollection at 0x32d0aba00>"
1360
  ]
1361
  },
1362
- "execution_count": 29,
1363
  "metadata": {},
1364
  "output_type": "execute_result"
1365
  },
@@ -1386,7 +1371,7 @@
1386
  },
1387
  {
1388
  "cell_type": "code",
1389
- "execution_count": 31,
1390
  "metadata": {},
1391
  "outputs": [
1392
  {
@@ -1429,18 +1414,18 @@
1429
  " <tr>\n",
1430
  " <th>0</th>\n",
1431
  " <td>2019-07-04T17:02:55.008</td>\n",
1432
- " <td>4.33975</td>\n",
1433
  " <td>0.326146</td>\n",
1434
  " <td>0.328015</td>\n",
1435
  " <td>0.050179</td>\n",
1436
- " <td>97.999762</td>\n",
1437
  " <td>98</td>\n",
1438
  " <td>49</td>\n",
1439
  " <td>49</td>\n",
1440
  " <td>1</td>\n",
1441
- " <td>-117.495965</td>\n",
1442
  " <td>35.710353</td>\n",
1443
- " <td>16.201628</td>\n",
1444
  " </tr>\n",
1445
  " </tbody>\n",
1446
  "</table>\n",
@@ -1448,16 +1433,16 @@
1448
  ],
1449
  "text/plain": [
1450
  " time magnitude sigma_time sigma_amp cov_time_amp \\\n",
1451
- "0 2019-07-04T17:02:55.008 4.33975 0.326146 0.328015 0.050179 \n",
1452
  "\n",
1453
  " gamma_score num_picks num_p_picks num_s_picks event_index longitude \\\n",
1454
- "0 97.999762 98 49 49 1 -117.495965 \n",
1455
  "\n",
1456
  " latitude depth_km \n",
1457
- "0 35.710353 16.201628 "
1458
  ]
1459
  },
1460
- "execution_count": 31,
1461
  "metadata": {},
1462
  "output_type": "execute_result"
1463
  }
@@ -1468,7 +1453,7 @@
1468
  },
1469
  {
1470
  "cell_type": "code",
1471
- "execution_count": 30,
1472
  "metadata": {},
1473
  "outputs": [
1474
  {
@@ -1529,7 +1514,7 @@
1529
  " <td>-117.462</td>\n",
1530
  " <td>694.5</td>\n",
1531
  " <td>1</td>\n",
1532
- " <td>0.000156</td>\n",
1533
  " </tr>\n",
1534
  " <tr>\n",
1535
  " <th>2</th>\n",
@@ -1542,7 +1527,7 @@
1542
  " <td>-117.598</td>\n",
1543
  " <td>775.0</td>\n",
1544
  " <td>1</td>\n",
1545
- " <td>0.230912</td>\n",
1546
  " </tr>\n",
1547
  " <tr>\n",
1548
  " <th>3</th>\n",
@@ -1555,7 +1540,7 @@
1555
  " <td>-117.598</td>\n",
1556
  " <td>775.0</td>\n",
1557
  " <td>1</td>\n",
1558
- " <td>0.748432</td>\n",
1559
  " </tr>\n",
1560
  " <tr>\n",
1561
  " <th>4</th>\n",
@@ -1568,7 +1553,7 @@
1568
  " <td>-117.598</td>\n",
1569
  " <td>775.0</td>\n",
1570
  " <td>1</td>\n",
1571
- " <td>0.788955</td>\n",
1572
  " </tr>\n",
1573
  " <tr>\n",
1574
  " <th>...</th>\n",
@@ -1669,10 +1654,10 @@
1669
  "\n",
1670
  " phase_type latitude longitude elevation_m event_index gamma_score \n",
1671
  "0 S 36.025 -117.765 1143.0 -1 -1.000000 \n",
1672
- "1 P 35.587 -117.462 694.5 1 0.000156 \n",
1673
- "2 P 35.816 -117.598 775.0 1 0.230912 \n",
1674
- "3 P 35.816 -117.598 775.0 1 0.748432 \n",
1675
- "4 P 35.816 -117.598 775.0 1 0.788955 \n",
1676
  ".. ... ... ... ... ... ... \n",
1677
  "103 P 36.025 -117.765 1143.0 -1 -1.000000 \n",
1678
  "104 P 35.982 -117.809 1469.0 -1 -1.000000 \n",
@@ -1683,7 +1668,7 @@
1683
  "[108 rows x 10 columns]"
1684
  ]
1685
  },
1686
- "execution_count": 30,
1687
  "metadata": {},
1688
  "output_type": "execute_result"
1689
  }
@@ -1692,6 +1677,13 @@
1692
  "picks_"
1693
  ]
1694
  },
 
 
 
 
 
 
 
1695
  {
1696
  "cell_type": "code",
1697
  "execution_count": null,
 
27
  },
28
  {
29
  "cell_type": "code",
30
+ "execution_count": 24,
31
  "metadata": {},
32
  "outputs": [],
33
  "source": [
34
+ "# GAMMA_API_URL = \"http://127.0.0.1:8000\"\n",
35
+ "GAMMA_API_URL = \"https://ai4eps-gamma.hf.space\"\n"
36
  ]
37
  },
38
  {
 
1263
  "plt.show()"
1264
  ]
1265
  },
 
 
 
 
 
 
 
 
 
1266
  {
1267
  "cell_type": "code",
1268
  "execution_count": 14,
 
1273
  "output_type": "stream",
1274
  "text": [
1275
  "Associating 108 picks with 1 CPUs\n",
1276
+ ".[{'time': '2019-07-04T17:02:55.008', 'magnitude': 4.339747018742565, 'sigma_time': 0.32614604178710815, 'sigma_amp': 0.3280145301432932, 'cov_time_amp': 0.05017926672657749, 'gamma_score': 97.9995778560105, 'num_picks': 98, 'num_p_picks': 49, 'num_s_picks': 49, 'event_index': 1, 'x(km)': 0.7269972359810098, 'y(km)': 0.5939380031466018, 'z(km)': 16.20145420615579}]\n"
1277
  ]
1278
+ },
 
 
 
 
 
 
 
 
 
 
 
 
 
1279
  {
1280
  "data": {
1281
  "text/plain": [
1282
+ "<matplotlib.collections.PathCollection at 0x336b22740>"
1283
  ]
1284
  },
1285
+ "execution_count": 14,
1286
  "metadata": {},
1287
  "output_type": "execute_result"
1288
  },
 
1298
  }
1299
  ],
1300
  "source": [
1301
+ "from app import run_gamma\n",
1302
+ "\n",
1303
+ "config[\"region\"] = \"Ridgecrest\"\n",
1304
+ "config[\"event_index\"] = 1\n",
1305
+ "\n",
1306
+ "evengts_, picks_ = run_gamma(picks, stations, config)\n",
1307
+ "\n",
1308
  "plt.figure()\n",
1309
  "mapping_color = lambda x: f\"C{x}\" if x!= -1 else \"black\"\n",
1310
+ "plt.scatter(picks_[\"phase_time\"], picks_[\"latitude\"], c=picks_[\"event_index\"].apply(mapping_color), s=10)"
1311
  ]
1312
  },
1313
  {
1314
  "cell_type": "code",
1315
+ "execution_count": 31,
1316
  "metadata": {},
1317
  "outputs": [],
1318
  "source": [
 
1319
  "picks_ = picks.copy()\n",
1320
  "picks_[\"phase_time\"] = picks_[\"phase_time\"].apply(lambda x: x.isoformat())\n",
1321
  "stations_ = stations.copy()\n",
 
1323
  "picks_ = picks_.to_dict(orient=\"records\")\n",
1324
  "stations_ = stations.to_dict(orient=\"records\")\n",
1325
  "\n",
1326
+ "response = requests.post(f\"{GAMMA_API_URL}/predict/\", json={\"picks\": {\"data\":picks_}, \"stations\": {\"data\": stations_}, \"config\": config})\n",
1327
  "\n",
1328
  "if response.status_code == 200:\n",
1329
  " result = response.json()\n",
 
1335
  },
1336
  {
1337
  "cell_type": "code",
1338
+ "execution_count": 32,
1339
  "metadata": {},
1340
  "outputs": [
1341
  {
1342
  "data": {
1343
  "text/plain": [
1344
+ "<matplotlib.collections.PathCollection at 0x336e17fd0>"
1345
  ]
1346
  },
1347
+ "execution_count": 32,
1348
  "metadata": {},
1349
  "output_type": "execute_result"
1350
  },
 
1371
  },
1372
  {
1373
  "cell_type": "code",
1374
+ "execution_count": 33,
1375
  "metadata": {},
1376
  "outputs": [
1377
  {
 
1414
  " <tr>\n",
1415
  " <th>0</th>\n",
1416
  " <td>2019-07-04T17:02:55.008</td>\n",
1417
+ " <td>4.339747</td>\n",
1418
  " <td>0.326146</td>\n",
1419
  " <td>0.328015</td>\n",
1420
  " <td>0.050179</td>\n",
1421
+ " <td>97.999578</td>\n",
1422
  " <td>98</td>\n",
1423
  " <td>49</td>\n",
1424
  " <td>49</td>\n",
1425
  " <td>1</td>\n",
1426
+ " <td>-117.495966</td>\n",
1427
  " <td>35.710353</td>\n",
1428
+ " <td>16.201454</td>\n",
1429
  " </tr>\n",
1430
  " </tbody>\n",
1431
  "</table>\n",
 
1433
  ],
1434
  "text/plain": [
1435
  " time magnitude sigma_time sigma_amp cov_time_amp \\\n",
1436
+ "0 2019-07-04T17:02:55.008 4.339747 0.326146 0.328015 0.050179 \n",
1437
  "\n",
1438
  " gamma_score num_picks num_p_picks num_s_picks event_index longitude \\\n",
1439
+ "0 97.999578 98 49 49 1 -117.495966 \n",
1440
  "\n",
1441
  " latitude depth_km \n",
1442
+ "0 35.710353 16.201454 "
1443
  ]
1444
  },
1445
+ "execution_count": 33,
1446
  "metadata": {},
1447
  "output_type": "execute_result"
1448
  }
 
1453
  },
1454
  {
1455
  "cell_type": "code",
1456
+ "execution_count": 34,
1457
  "metadata": {},
1458
  "outputs": [
1459
  {
 
1514
  " <td>-117.462</td>\n",
1515
  " <td>694.5</td>\n",
1516
  " <td>1</td>\n",
1517
+ " <td>0.000016</td>\n",
1518
  " </tr>\n",
1519
  " <tr>\n",
1520
  " <th>2</th>\n",
 
1527
  " <td>-117.598</td>\n",
1528
  " <td>775.0</td>\n",
1529
  " <td>1</td>\n",
1530
+ " <td>0.185935</td>\n",
1531
  " </tr>\n",
1532
  " <tr>\n",
1533
  " <th>3</th>\n",
 
1540
  " <td>-117.598</td>\n",
1541
  " <td>775.0</td>\n",
1542
  " <td>1</td>\n",
1543
+ " <td>0.300784</td>\n",
1544
  " </tr>\n",
1545
  " <tr>\n",
1546
  " <th>4</th>\n",
 
1553
  " <td>-117.598</td>\n",
1554
  " <td>775.0</td>\n",
1555
  " <td>1</td>\n",
1556
+ " <td>0.306604</td>\n",
1557
  " </tr>\n",
1558
  " <tr>\n",
1559
  " <th>...</th>\n",
 
1654
  "\n",
1655
  " phase_type latitude longitude elevation_m event_index gamma_score \n",
1656
  "0 S 36.025 -117.765 1143.0 -1 -1.000000 \n",
1657
+ "1 P 35.587 -117.462 694.5 1 0.000016 \n",
1658
+ "2 P 35.816 -117.598 775.0 1 0.185935 \n",
1659
+ "3 P 35.816 -117.598 775.0 1 0.300784 \n",
1660
+ "4 P 35.816 -117.598 775.0 1 0.306604 \n",
1661
  ".. ... ... ... ... ... ... \n",
1662
  "103 P 36.025 -117.765 1143.0 -1 -1.000000 \n",
1663
  "104 P 35.982 -117.809 1469.0 -1 -1.000000 \n",
 
1668
  "[108 rows x 10 columns]"
1669
  ]
1670
  },
1671
+ "execution_count": 34,
1672
  "metadata": {},
1673
  "output_type": "execute_result"
1674
  }
 
1677
  "picks_"
1678
  ]
1679
  },
1680
+ {
1681
+ "cell_type": "code",
1682
+ "execution_count": null,
1683
+ "metadata": {},
1684
+ "outputs": [],
1685
+ "source": []
1686
+ },
1687
  {
1688
  "cell_type": "code",
1689
  "execution_count": null,