Adding downloaded MODIS data to array - arrays

I am downloading MODIS LST data in Matlab. The outputted data I have appears like this:
I have no problems with downloading the data, just how can I save this data into a new array. I want this data to just go into the first column, next set into the second etc...

First, you have to convert your matrix from class Uint16/unit8 to double.
lst =double(your_matrix_name);
then, you can arrange the data into an array of desired columns and rows.
lst1=reshape(lst, [rows columns]);
eg: lst1=reshape(lst, [365 1]); for 365 rows and 1 column

Related

Leave Rows before Outputting Array Results

I would like to create a summary sheet that draws from arrays in two work sheets. I would like the summary sheet (Result) contains two filtered arrays, one below the other (see the attached Desired Summary Page
This works well if the number of rows output by the array does not overlap with the formula for the second array. However, as the arrays are both dynamic the length changes depending on the filter criteria producing an Error (see attached)Overlapping Array Error
Is there any way to count the rows numbers produced by the first array and then get the second array to start after it is complete, so the two don't overlap - i.e. the output from the second array formula may need to be mapped to a remote cell (not containing the formula).
Here is an example spreadsheet
https://docs.google.com/spreadsheets/d/1Rt-Pp4gUYu8jGnXOQn0f2xpEKxoi_74Fqh5WSS-uF7A/edit?usp=sharing
I have tried adding blank rows to the second Array by using Flatten however this overwrites the results of the first Array. I have also tried a query function, but my knowledge of the syntax is not sufficient.
Any suggestions would be welcome.
Combine you two filtered result into one array. Try-
={filter('Sheet 1'!A3:D25,'Sheet 1'!D3:D25=TRUE);SPLIT(REPT(" |",4),"|");filter(Sheet2!A3:D25,Sheet2!D3:D25=TRUE)}
SPLIT(REPT(" |",4),"|") this part is for blank row between two filtered result.
You can stack the data with {} in googlesheet as long as they have the same array-length.
the filters are named as FILTER1 and FILTER2 with LAMBDA(),
added a title line to both filter with QUERY(),
get the 1st row of FILTER1 by INDEX(),
get the length of a row of data by COUNTA(),
set an array with specified rows and cols by MAKEARRAY and name it EMPTYROW,
stack the data created above with {} and ;.
=LAMBDA(FILTER1,FILTER2,
LAMBDA(ROWLEN,
LAMBDA(EMPTYROW,
{
FILTER1;
EMPTYROW;
FILTER2
}
)(MAKEARRAY(1,ROWLEN,LAMBDA(ROW,COL,"")))
)(COUNTA(INDEX(FILTER1,1,)))
)(
QUERY(filter('Sheet 1'!A3:D25,'Sheet 1'!D3:D25=TRUE),
"LABEL Col1'SHEET 1',Col2'',Col3'',Col4''"
),
QUERY(filter('Sheet 2'!A3:D25,'Sheet 2'!D3:D25=TRUE),
"LABEL Col1'SHEET 2',Col2'',Col3'',Col4''"
)
)

How to write a List(of String) into a SQL Server table where each string is a comma separated list of values

We have survey data for each survey on a server. The data is separated with one method I can download the column names (via pooling) and with another I can download the data (via SSE). I have accomplished to write a procedure that creates a datatable dynamically for each survey I choose to download. Now I have to get the data into that table. For this I have streamed the data via SSE into a List(of String) where each element comprises a comma separated string.
This looks like
For Each x As String In stringList
Console.WriteLine(x)
Next
would give me
(1)data:[1,2,1,5,2,6,John,Winchester,234]
(2)data:[5,3,2,4,1,6,Mike,Lenchester,555]
...
Each Element of the List is a dataset I have to put into one column of my datatable. So I guess I have to loop through the List Object and the pick each element between the comma and write them into the columns.
So my problem now is to get the data into the database.
Usually I provide an approach but this time I have no clue how to start.
I tried to experiment with this
.Parameters.Add("#id", SqlDbType.varchar(max)).Value = x
but ended up in frustration.
Could anyone give me something to start with? The data size is up to 500MB if I store it in a .txt file.

Inserting array into listobjects().listcolums().databodyrange

A fast way of transfering data between Excel tables is to read the data into an array by looping thru the source table and then insert them into the destination table in one command. This works fine for the table databodyrange; listobjects().databodyrange = aTransfer. But when trying out doing the same for listcolumns; listobjects().listcolumns().databodyrange = aTransfer, the first number in the column is repeated down to the end of the column.
This is demonstrated in this example: Transfering data between tables
Is there a way of getting around this?
You'll need to transpose your one-dimensional horizontal array into a vertical one using the Transpose method of the Application object. Here's an example...
Worksheets("Sheet1").ListObjects("Table1").ListColumns(1).DataBodyRange.Value = application.transpose(aTransfer)

Make cells that were populated with Concentrate function have standalone data instead of the formula

Below I have linked my CSV for a store (woocommerce), I have columns C and D pulling data from other columns. So when I export as CSV and upload to woocommerce the data from those cells isn't represented correctly, what I need to do is make those cells actually contain the text that is displayed using the concentrate function.
Is there an easy way to go about this, or am I bound to copy paste from two columns and add text that repeats?
https://docs.google.com/spreadsheets/d/189DoiV2LwV5JrXqPVAZTL9ww5hAq2Ws7_IdWqsd7mqo/edit?usp=sharing
I have figured it out. I have selected the whole column that used the formula to generate the value (text) and copied it, then I have pasted it somewhere else in the same document, deleted the original column and pasted the value column in its place.

Select specific rows from a column in a MATLAB workspace into an array

I have a column filled with data in those rows and i would like to select the 1st row from that column but skipping the 2nd row and choosing the 3rd row after and insert them into an array.
Example of the row:
'153:154:155:156:157:158:159:160:161:162:163:164:165:166:167:168:169:170:171:172:173:174:175:176:177:178:179:180:181:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:201:202:203:204:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:223:224:225:226:227:228:229:230:231:232:233:234:235:236:237:238:239:240:241:242:243:244:245:246:247:248:249:250:251:252:253:254:255:256:257:258:259:260:261:262:263:264:265:266:267:268:269:270:271:272:273:274:275:276:277:278:279:280:281:282'
'153:154:155:156:157:158:159:160:161:162:163:164:165:166:167:168:169:170:171:172:173:174:175:176:177:178:179:180:181:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:201:202:203:204:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:223:224:225:226:227:228:229:230:231:232:233:234:235:236:237:238:239:240:241:242:243:244:245:246:247:248:249:250:251:252:253:254:255:256:257:258:259:260:261:262:263:264:265:266:267:268:269:270:271:272:273:274:275:276:277:278:279:280:281:282'
'30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:131:132:133:134:135:136:137:138:139:140:141:142:143:144:145:146:147:148:149:150:151:152:153:154:155:156:157:158:159:160:161:162:163:164:165:166:167:168:169:170:171:172:173:174:175:176:177:178:179:180:181:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:201:202:203:204:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:223:224:225:226:227:228:229:230:231:232:233:234:235:236:237:238:239:240:241:242:243:244:245:246:247:248:249:250:251:252:253:254:255:256:257:258:259:260:261:262:263:264:265:266:267:268:269:270:271:272:273:274:275:276:277:278:279:280:281:282:283:284:285:286:287:288:289:290:291:292:293:294:295:296:297:298:299:300:301:302:303:304:305:306:307:308:309:310:311:312:313:314:315:316:317:318:319:320:321:322:323:324:325:326:327:328:329:330:331:332:333:334:335:336:337:338:339:340:341:342:343:344:345:346:347:348:349:350:351:352:353:354:355:356:357:358:359:360:361:362:363:364:365:366:367:368:369:370:371:372:373:374:375:376:377:378:379:380:381:382:383:384:385:386:387:388:389:390:391:392:393:394:395:396:397:398:399:400:401:402:403:404:405:406:407:408:409:410:411:412:413:414:415:416:417:418:419:420:421:422:423:424:425:426:427:428:429:430:431:432:433:434:435:436:437:438:439:440:441:442:443:444:445:446:447:448:449:450:451:452:453:454:455:456:457:458:459:460:461:462:463:464:465:466:467:468:469:470:471:472:473:474:475:476:477:478:479:480:481:482:483:484:485:486:487:488:489:490:491:492:493:494:495:496:497:498:499:500:501:502:503:504:505:506:507:508:509:510:511:512:513:514:515:516:517:518:519:520:521:522:523:524:525:526:527:528:529:530:531:532:533:534:535:536:537:538:539:540:541:542:543:544:545:546:547:548:549:550:551:552:553:554:555:556:557:558:559:560:561:562:563:564:565:566:567:568:569:570:571:572:573:574:575:576:577:578:579:580:581:582:583:584:585:586:587:588:589:590:591:592:593:594:595:596:597:598:599:600:601:602:603:604:605:606:607:608:609:610:611:612:613:614:615:616:617:618:619:620:621:622:623:624:625:626:627:628:629:630:631:632:633:634:635:636:637:638:639:640:641:642:643:644:645:646:647:648:649:650:651:652:653:654:655:656:657:658:659:660:661:662:670:671:672:673:674:675:676:677:678:679:680:681:682:683:684:685:686:687:688:689:690:691:692:693:694:695:696:697:698:699:700:701:702:703:704:705:706:707:708:709:710:711:712:713:714:715:716:717:718:719:720:721:722:723:724:725:726:727:728:729:730:731:732:733:734:735:736:737:738:739:740:741:742:750:751:752:753:754:755:756:757:758:759:760:761:762:763:764:765:766:767:768:769:770:771:772:773:774:775:776:777:778:779:780:781:782:783:784:785:786:787:788:789:790:791:792:793:794:795:796:797:798:799:800:801:802:803:804:805:806:807:808:809:810:811:812:813:814:815:816:817:818:819:820:821:822:823:824:825:826:827:828:829:830:831:832:833:834:835:836:837:838:839:840:841:842:843:844:845:846:847:848:849:850:851:852:853:854:855:856:857:858:859:860:861:862:863:864:865:866:867:868:869:870:871:872:873:874:875:876:877:878:879:880:881:882:883:884:885:886:887:888:889:890:891:892:893:894:895:896:897:898:899:900:901:902:903:904:905:906:907:908:909:910:911:912:913:914:915:916:917:918:919:920:921:922:923:924:925:926:927:928:929:930:931:932:933:934:935:936:937:938:939:940:941:942:943:944:945:946:947:948:949:950:951:952:953:954:955:956:957:958:959:960:961:962:963:964:965:966:967:968:969:970:971:972:973:974:975:976:977:978:979:980:981:982:983:984:985:986:987:988:989:990:991:992:993:994:995:996:997:998:999:1000:1001:1002:1003:1004:1005:1006:1007:1008:1009:1010:1011:1012:1013:1014:1015:1016:1017:1018:1019:1020:1021:1022:1023:1024:1025:1026:1027:1028:1029:1030:1031:1032:1033:1034:1035:1036:1037:1038:1039:1040:1041:1042:1043:1044:1045:1046:1047:1048:1049:1050:1051:1052:1053:1054:1055:1056:1057:1058:1059:1060:1061:1062:1063:1064:1065:1066:1067:1068:1069:1070:1071:1072:1073:1074:1075:1076:1077:1078:1079:1080:1081:1082:1083:1084:1085:1086:1087:1088:1089:1090:1091:1092:1093:1094:1095:1096:1097:1098:1099:1100:1101:1102:1103:1104:1105:1106:1107:1108:1109:1110:1111:1112:1113:1114:1115:1116:1117:1118:1119:1120:1121:1122:1123:1124:1125:1126:1127:1128:1129:1130:1131:1132:1133:1134:1135:1136:1137:1138:1139:1140:1141:1142:1143:1144:1145:1146:1147:1148:1149:1150:1151:1152:1153:1154:1155:1156:1157:1158:1159:1160:1161:1162:1163:1164:1165:1166:1167:1168:1169:1170:1171:1172:1173:1174:1175:1176:1177:1178:1179:1180:1181:1182:1183:1184:1185:1186:1187:1188:1189:1190:1191:1192:1193:1194:1195:1196:1197:1198:1199:1200:1201:1202:1203:1204:1205:1206:1207:1208:1209:1210:1211:1212:1213:1214:1215:1216:1217:1218:1219:1220:1221:1222:1223:1224:1225:1226:1227:1228:1229:1230:1231:1232:1233:1234:1235:1236:1237:1238:1239:1240:1241:1242:1243:1244:1245:1246:1247:1248:1249:1250:1251:1252:1253:1254:1255:1256:1257:1258:1259:1260:1261:1262:1263:1264:1265:1266:1267:1268:1269:1270:1271:1272:1273:1274:1275:1276:1277:1278:1279:1280:1281:1282:1283:1284:1285:1286:1287:1288:1289:1290:1291:1292:1293:1294:1295:1296:1297:1298:1299:1300:1301:1302:1303:1304:1305:1306:1307:1308:1309:1310:1311:1312:1313:1314:1315:1316:1317:1318:1319:1320:1321:1322:1323:1324:1325:1326:1327:1328:1329:1330:1331:1332:1333:1334:1335:1336:1337:1338:1339:1340:1341:1342:1343:1344:1345:1346:1347:1348:1349:1350:1351:1352:1353:1354:1355:1356:1357:1358:1359:1360:1361:1362:1363:1364:1365:1366:1367:1368:1369:1370:1371:1372:1373:1374:1375:1376:1377:1378:1379:1380:1381:1382:1383:1384:1385:1386:1387:1388:1389:1390:1391:1392:1393:1394:1395:1396:1397:1398:1399:1400:1401:1402:1403:1404:1405:1406:1407:1408:1409:1410:1411:1412:1413:1414:1415:1416:1417:1418:1419:1420:1421:1422:1423:1424:1425:1426:1427:1428:1429:1430:1431:1432:1433:1434:1435:1436:1437:1438:1439:1440:1441:1442:1443:1444:1445:1446:1447:1448:1449:1450:1451:1452:1453:1454:1455:1456:1457:1458:1459:1460:1461:1462:1463:1464:1465:1466:1467:1468:1469:1470:1471:1472:1473:1474:1475:1476:1477:1478:1479:1480:1481:1482:1483:1484:1485:1486:1487:1488:1489:1490:1491:1492:1493:1494:1495:1496:1497:1498:1499:1500:1501:1502:1503:1504:1505:1506:1507:1508:1509:1510:1511:1512:1513:1514:1515:1516:1517:1526:1527:1528:1529:1530:1531:1532:1533:1534:1535:1536:1537:1538:1539:1540:1541:1542:1543:1544:1545:1546:1547:1548:1549:1550:1551:1552:1553:1554:1555:1556:1557:1558:1559:1560:1561:1562:1563:1564:1565:1566:1567:1568:1569:1570:1571:1572:1573:1574:1575:1576:1577:1578:1579:1580:1581:1582:1583:1584:1585:1586:1587:1588:1589:1590:1591:1592:1593:1594:1595:1596:1597:1598:1599:1600:1601:1602:1603:1604:1605:1606:1607:1608:1609:1610:1611:1612:1613:1614:1615:1616:1617:1618:1619:1620:1621:1622:1623:1624:1625:1626:1627:1628:1629:1630:1631:1632:1633:1634:1635:1636:1637:1638:1639:1640:1641:1642:1643:1644:1645:1646:1647:1648:1649:1650:1651:1652:1653:1654:1655:1656:1657:1658:1659:1660:1661'
'30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:131:132:133:134:135:136:137:138:139:140:141:142:143:144:145:146:147:148:149:150:151:152:153:154:155:156:157:158:159:160:161:162:163:164:165:166:167:168:169:170:171:172:173:174:175:176:177:178:179:180:181:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:201:202:203:204:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:223:224:225:226:227:228:229:230:231:232:233:234:235:236:237:238:239:240:241:242:243:244:245:246:247:248:249:250:251:252:253:254:255:256:257:258:259:260:261:262:263:264:265:266:267:268:269:270:271:272:273:274:275:276:277:278:279:280:281:282:283:284:285:286:287:288:289:290:291:292:293:294:295:296:297:298:299:300:301:302:303:304:305:306:307:308:309:310:311:312:313:314:315:316:317:318:319:320:321:322:323:324:325:326:327:328:329:330:331:332:333:334:335:336:337:338:339:340:341:342:343:344:345:346:347:348:349:350:351:352:353:354:355:356:357:358:359:360:361:362:363:364:365:366:367:368:369:370:371:372:373:374:375:376:377:378:379:380:381:382:383:384:385:386:387:388:389:390:391:392:393:394:395:396:397:398:399:400:401:402:403:404:405:406:407:408:409:410:411:412:413:414:415:416:417:418:419:420:421:422:423:424:425:426:427:428:429:430:431:432:433:434:435:436:437:438:439:440:441:442:443:444:445:446:447:448:449:450:451:452:453:454:455:456:457:458:459:460:461:462:463:464:465:466:467:468:469:470:471:472:473:474:475:476:477:478:479:480:481:482:483:484:485:486:487:488:489:490:491:492:493:494:495:496:497:498:499:500:501:502:503:504:505:506:507:508:509:510:511:512:513:514:515:516:517:518:519:520:521:522:523:524:525:526:527:528:529:530:531:532:533:534:535:536:537:538:539:540:541:542:543:544:545:546:547:548:549:550:551:552:553:554:555:556:557:558:559:560:561:562:563:564:565:566:567:568:569:570:571:572:573:574:575:576:577:578:579:580:581:582:583:584:585:586:587:588:589:590:591:592:593:594:595:596:597:598:599:600:601:602:603:604:605:606:607:608:609:610:611:612:613:614:615:616:617:618:619:620:621:622:623:624:625:626:627:628:629:630:631:632:633:634:635:636:637:638:639:640:641:642:643:644:645:646:647:648:649:650:651:652:653:654:655:656:657:658:659:660:661:662:670:671:672:673:674:675:676:677:678:679:680:681:682:683:684:685:686:687:688:689:690:691:692:693:694:695:696:697:698:699:700:701:702:703:704:705:706:707:708:709:710:711:712:713:714:715:716:717:718:719:720:721:722:723:724:725:726:727:728:729:730:731:732:733:734:735:736:737:738:739:740:741:742:750:751:752:753:754:755:756:757:758:759:760:761:762:763:764:765:766:767:768:769:770:771:772:773:774:775:776:777:778:779:780:781:782:783:784:785:786:787:788:789:790:791:792:793:794:795:796:797:798:799:800:801:802:803:804:805:806:807:808:809:810:811:812:813:814:815:816:817:818:819:820:821:822:823:824:825:826:827:828:829:830:831:832:833:834:835:836:837:838:839:840:841:842:843:844:845:846:847:848:849:850:851:852:853:854:855:856:857:858:859:860:861:862:863:864:865:866:867:868:869:870:871:872:873:874:875:876:877:878:879:880:881:882:883:884:885:886:887:888:889:890:891:892:893:894:895:896:897:898:899:900:901:902:903:904:905:906:907:908:909:910:911:912:913:914:915:916:917:918:919:920:921:922:923:924:925:926:927:928:929:930:931:932:933:934:935:936:937:938:939:940:941:942:943:944:945:946:947:948:949:950:951:952:953:954:955:956:957:958:959:960:961:962:963:964:965:966:967:968:969:970:971:972:973:974:975:976:977:978:979:980:981:982:983:984:985:986:987:988:989:990:991:992:993:994:995:996:997:998:999:1000:1001:1002:1003:1004:1005:1006:1007:1008:1009:1010:1011:1012:1013:1014:1015:1016:1017:1018:1019:1020:1021:1022:1023:1024:1025:1026:1027:1028:1029:1030:1031:1032:1033:1034:1035:1036:1037:1038:1039:1040:1041:1042:1043:1044:1045:1046:1047:1048:1049:1050:1051:1052:1053:1054:1055:1056:1057:1058:1059:1060:1061:1062:1063:1064:1065:1066:1067:1068:1069:1070:1071:1072:1073:1074:1075:1076:1077:1078:1079:1080:1081:1082:1083:1084:1085:1086:1087:1088:1089:1090:1091:1092:1093:1094:1095:1096:1097:1098:1099:1100:1101:1102:1103:1104:1105:1106:1107:1108:1109:1110:1111:1112:1113:1114:1115:1116:1117:1118:1119:1120:1121:1122:1123:1124:1125:1126:1127:1128:1129:1130:1131:1132:1133:1134:1135:1136:1137:1138:1139:1140:1141:1142:1143:1144:1145:1146:1147:1148:1149:1150:1151:1152:1153:1154:1155:1156:1157:1158:1159:1160:1161:1162:1163:1164:1165:1166:1167:1168:1169:1170:1171:1172:1173:1174:1175:1176:1177:1178:1179:1180:1181:1182:1183:1184:1185:1186:1187:1188:1189:1190:1191:1192:1193:1194:1195:1196:1197:1198:1199:1200:1201:1202:1203:1204:1205:1206:1207:1208:1209:1210:1211:1212:1213:1214:1215:1216:1217:1218:1219:1220:1221:1222:1223:1224:1225:1226:1227:1228:1229:1230:1231:1232:1233:1234:1235:1236:1237:1238:1239:1240:1241:1242:1243:1244:1245:1246:1247:1248:1249:1250:1251:1252:1253:1254:1255:1256:1257:1258:1259:1260:1261:1262:1263:1264:1265:1266:1267:1268:1269:1270:1271:1272:1273:1274:1275:1276:1277:1278:1279:1280:1281:1282:1283:1284:1285:1286:1287:1288:1289:1290:1291:1292:1293:1294:1295:1296:1297:1298:1299:1300:1301:1302:1303:1304:1305:1306:1307:1308:1309:1310:1311:1312:1313:1314:1315:1316:1317:1318:1319:1320:1321:1322:1323:1324:1325:1326:1327:1328:1329:1330:1331:1332:1333:1334:1335:1336:1337:1338:1339:1340:1341:1342:1343:1344:1345:1346:1347:1348:1349:1350:1351:1352:1353:1354:1355:1356:1357:1358:1359:1360:1361:1362:1363:1364:1365:1366:1367:1368:1369:1370:1371:1372:1373:1374:1375:1376:1377:1378:1379:1380:1381:1382:1383:1384:1385:1386:1387:1388:1389:1390:1391:1392:1393:1394:1395:1396:1397:1398:1399:1400:1401:1402:1403:1404:1405:1406:1407:1408:1409:1410:1411:1412:1413:1414:1415:1416:1417:1418:1419:1420:1421:1422:1423:1424:1425:1426:1427:1428:1429:1430:1431:1432:1433:1434:1435:1436:1437:1438:1439:1440:1441:1442:1443:1444:1445:1446:1447:1448:1449:1450:1451:1452:1453:1454:1455:1456:1457:1458:1459:1460:1461:1462:1463:1464:1465:1466:1467:1468:1469:1470:1471:1472:1473:1474:1475:1476:1477:1478:1479:1480:1481:1482:1483:1484:1485:1486:1487:1488:1489:1490:1491:1492:1493:1494:1495:1496:1497:1498:1499:1500:1501:1502:1503:1504:1505:1506:1507:1508:1509:1510:1511:1512:1513:1514:1515:1516:1517:1526:1527:1528:1529:1530:1531:1532:1533:1534:1535:1536:1537:1538:1539:1540:1541:1542:1543:1544:1545:1546:1547:1548:1549:1550:1551:1552:1553:1554:1555:1556:1557:1558:1559:1560:1561:1562:1563:1564:1565:1566:1567:1568:1569:1570:1571:1572:1573:1574:1575:1576:1577:1578:1579:1580:1581:1582:1583:1584:1585:1586:1587:1588:1589:1590:1591:1592:1593:1594:1595:1596:1597:1598:1599:1600:1601:1602:1603:1604:1605:1606:1607:1608:1609:1610:1611:1612:1613:1614:1615:1616:1617:1618:1619:1620:1621:1622:1623:1624:1625:1626:1627:1628:1629:1630:1631:1632:1633:1634:1635:1636:1637:1638:1639:1640:1641:1642:1643:1644:1645:1646:1647:1648:1649:1650:1651:1652:1653:1654:1655:1656:1657:1658:1659:1660:1661'
'2:3:4:5:6:7:8:9:10:11:12:13:14:15:16:17:18:19:20:21:22:23:24:25:26:27:28:29:30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:131:132:133:134:135:136'
'1:2:3:4:5:6:7:8:9:10:11:12:13:14:15:16:17:18:19:20:21:22:23:24:25:26:27:28:29:30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:131:132:133:134:135:136:137:138:139:140:141'
'1:2:3:4:5:6:7:8:9:10:11:12:13:14:15:16:17:18:19:20:21:22:23:24:25:26:27:28:29:30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:52A:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:82A:82B:82C:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:100A:100B:100C:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:133:134:135:136:137:138:139:140:141:142:143:144:145:146:147:148:149:150:151:152:153:154:156:157:162:163:164:165:166:167:168:169:171:172:173:174:175:176:177:178:179:180:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:203:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:225:226:227'
'1:2:3:4:5:6:7:8:9:10:11:12:13:14:15:16:17:18:19:20:21:22:23:24:25:26:27:28:29:30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:52A:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:82A:82B:82C:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:100A:100B:100C:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:133:134:135:136:137:138:139:140:141:142:143:144:145:146:147:148:149:150:151:152:153:154:156:157:162:163:164:165:166:167:168:169:171:172:173:174:175:176:177:178:179:180:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:203:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:225:226:227'
'1:2:3:4:5:6:7:8:9:13:14:15:16:17:18:19:20:21:22:23:24:25:26:27:28:29:30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:53:54:55:56:57:58:59:60:61:62:63:64:65:66:67:68:69:70:71:72:73:74:75:76:77:78:79:80:81:82:83:84:85:86:87:88:89:90:91:92:93:94:95:96:97:98:99:100:101:102:103:104:105:106:107:108:109:110:111:112:113:114:115:116:117:118:119:120:121:122:123:124:125:126:127:128:129:130:131:132:133:134:135:136:137:138:139:140:141:142:143:144:145:146:147:148:149:150:151:152:153:154:155:156:157:158:159:160:161:162:163:164:165:166:167:168:169:170:171:172:173:174:175:176:177:178:179:180:181:182:183:184:185:186:187:188:189:190:191:192:193:194:195:196:197:198:199:200:201:202:203:204:205:206:207:208:209:210:211:212:213:214:215:216:217:218:219:220:221:222:223:224:225:226:227:228:229:230:231:232:233:234:235:236:237:238:239:240:241:242:243:244:245:246:247:248:249:250:251:252:253:254:255:256:257:258:259:260:261:262:263:264:265:266:267:268:269:270:271:272:273:274:275:276:277:278:279:280:281:282:283:284:285:286:287:288:289:290:291:292:293:294:295:296:297:298:299:300:301:302:303:304:305:306:307:308:309:310:311:312:313:314:315:316:317:318:319:320:321:322:323'
Basically, i would want to select the first row, which is 153....282 and then select the 3rd row which is 30...1661 and repeat this process for all other rows accordingly. From there i would like to then insert those data into an array.
The source of these data are from a PostgreSQL database which i have imported into my workspace.
Is this possible to do?
If I understand correctly, this should work:
output = data([1 3],:);
This selects the 1st and 3rd rows of data, and adds them to a new variable called output. To select every odd row, use the colon notation and the end keyword, like this:
output = data(1:2:end, :);
This starts at the first row selects every 2nd row until the end.
One solution would be to dump it all to a text file and then use importdata() which will allow you to specify the delimiter character, as in data = importdata(file.txt,':'). This will give you a MATLAB array data full of numbers, which you can then process as you please.
Let's assume that after you import your data, it is a cell array of strings, called A (this is what it appears to be in your question, because of the single quotes on each line).
First, let's get rid of the the letters appearing in the data, since we probably want just the numbers. We do this with a regular expression replacement:
A = cellfun(#(x) regexprep(x, '[^\d:]', ''), A,'UniformOutput',0);
Next, we use the strread function to parse each line into an array of integers
B = cellfun(#(x) strread(x, '%d:', -1), A, 'UniformOutput',0);
Now each element of B is the array form of the corresponding element of A. So you can get the 3rd row, for example with
B{3}

Resources