[Daily Statistics] [Hourly Statistics] [URLs] [Entry] [Exit] [Sites] [Referrers] [Search] [Users] [Agents] [Countries]
| Monthly Statistics for February 2005 | ||
|---|---|---|
| Total Hits | 20725 | |
| Total Files | 14893 | |
| Total Pages | 3039 | |
| Total Visits | 590 | |
| Total KBytes | 689004 | |
| Total Unique Sites | 732 | |
| Total Unique URLs | 487 | |
| Total Unique Referrers | 175 | |
| Total Unique Usernames | 1 | |
| Total Unique User Agents | 135 | |
| . | Avg | Max |
| Hits per Hour | 123 | 663 |
| Hits per Day | 2960 | 4738 |
| Files per Day | 2127 | 3390 |
| Pages per Day | 434 | 710 |
| Visits per Day | 84 | 119 |
| KBytes per Day | 98429 | 169346 |
| Hits by Response Code | ||
| Code 200 - OK | 14893 | |
| Code 206 - Partial Content | 347 | |
| Code 301 - Moved Permanently | 6 | |
| Code 304 - Not Modified | 4303 | |
| Code 400 - Bad Request | 16 | |
| Code 401 - Unauthorized | 6 | |
| Code 404 - Not Found | 1147 | |
| Code 405 - Method Not Allowed | 1 | |
| Code 408 - Request Timeout | 6 | |
| Daily Statistics for February 2005 | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Day | Hits | Files | Pages | Visits | Sites | KBytes | ||||||
| 1 | 3126 | 15.08% | 2200 | 14.77% | 497 | 16.35% | 119 | 20.17% | 181 | 24.73% | 119804 | 17.39% |
| 2 | 2421 | 11.68% | 1760 | 11.82% | 333 | 10.96% | 76 | 12.88% | 121 | 16.53% | 51453 | 7.47% |
| 3 | 3382 | 16.32% | 2526 | 16.96% | 479 | 15.76% | 97 | 16.44% | 176 | 24.04% | 169346 | 24.58% |
| 4 | 2748 | 13.26% | 2058 | 13.82% | 441 | 14.51% | 83 | 14.07% | 152 | 20.77% | 68580 | 9.95% |
| 5 | 4225 | 20.39% | 2884 | 19.36% | 570 | 18.76% | 105 | 17.80% | 171 | 23.36% | 114536 | 16.62% |
| 6 | 4738 | 22.86% | 3390 | 22.76% | 710 | 23.36% | 110 | 18.64% | 157 | 21.45% | 163699 | 23.76% |
| 7 | 85 | 0.41% | 75 | 0.50% | 9 | 0.30% | 2 | 0.34% | 4 | 0.55% | 1586 | 0.23% |
| Hourly Statistics for February 2005 | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Hour | Hits | Files | Pages | KBytes | ||||||||
| Avg | Total | Avg | Total | Avg | Total | Avg | Total | |||||
| 0 | 92 | 644 | 3.11% | 75 | 525 | 3.53% | 15 | 110 | 3.62% | 1634 | 11439 | 1.66% |
| 1 | 22 | 160 | 0.77% | 18 | 130 | 0.87% | 5 | 38 | 1.25% | 428 | 2997 | 0.43% |
| 2 | 29 | 208 | 1.00% | 24 | 174 | 1.17% | 8 | 62 | 2.04% | 513 | 3594 | 0.52% |
| 3 | 49 | 347 | 1.67% | 27 | 192 | 1.29% | 11 | 79 | 2.60% | 748 | 5234 | 0.76% |
| 4 | 45 | 320 | 1.54% | 30 | 216 | 1.45% | 9 | 64 | 2.11% | 1237 | 8658 | 1.26% |
| 5 | 53 | 373 | 1.80% | 46 | 323 | 2.17% | 8 | 61 | 2.01% | 1781 | 12465 | 1.81% |
| 6 | 107 | 749 | 3.61% | 62 | 438 | 2.94% | 13 | 91 | 2.99% | 1433 | 10033 | 1.46% |
| 7 | 154 | 1082 | 5.22% | 89 | 627 | 4.21% | 22 | 160 | 5.26% | 6390 | 44733 | 6.49% |
| 8 | 131 | 921 | 4.44% | 96 | 673 | 4.52% | 19 | 134 | 4.41% | 4588 | 32119 | 4.66% |
| 9 | 106 | 745 | 3.59% | 70 | 493 | 3.31% | 19 | 134 | 4.41% | 6130 | 42911 | 6.23% |
| 10 | 88 | 622 | 3.00% | 63 | 443 | 2.97% | 13 | 95 | 3.13% | 3928 | 27498 | 3.99% |
| 11 | 147 | 1033 | 4.98% | 107 | 754 | 5.06% | 21 | 150 | 4.94% | 3231 | 22615 | 3.28% |
| 12 | 99 | 693 | 3.34% | 77 | 543 | 3.65% | 13 | 91 | 2.99% | 4104 | 28725 | 4.17% |
| 13 | 184 | 1288 | 6.21% | 138 | 969 | 6.51% | 22 | 154 | 5.07% | 4302 | 30113 | 4.37% |
| 14 | 159 | 1116 | 5.38% | 107 | 752 | 5.05% | 24 | 169 | 5.56% | 6256 | 43790 | 6.36% |
| 15 | 107 | 751 | 3.62% | 83 | 581 | 3.90% | 14 | 99 | 3.26% | 1198 | 8388 | 1.22% |
| 16 | 221 | 1553 | 7.49% | 164 | 1148 | 7.71% | 27 | 195 | 6.42% | 5907 | 41350 | 6.00% |
| 17 | 152 | 1069 | 5.16% | 97 | 684 | 4.59% | 20 | 146 | 4.80% | 5560 | 38920 | 5.65% |
| 18 | 101 | 710 | 3.43% | 68 | 480 | 3.22% | 14 | 103 | 3.39% | 3696 | 25873 | 3.76% |
| 19 | 189 | 1325 | 6.39% | 147 | 1035 | 6.95% | 27 | 195 | 6.42% | 7600 | 53197 | 7.72% |
| 20 | 225 | 1579 | 7.62% | 181 | 1272 | 8.54% | 32 | 226 | 7.44% | 4184 | 29291 | 4.25% |
| 21 | 177 | 1242 | 5.99% | 135 | 951 | 6.39% | 23 | 167 | 5.50% | 4264 | 29846 | 4.33% |
| 22 | 187 | 1311 | 6.33% | 129 | 909 | 6.10% | 29 | 206 | 6.78% | 12042 | 84293 | 12.23% |
| 23 | 126 | 884 | 4.27% | 83 | 581 | 3.90% | 15 | 110 | 3.62% | 7274 | 50921 | 7.39% |
| Top 10 of 487 Total URLs By KBytes | |||||
|---|---|---|---|---|---|
| # | Hits | KBytes | URL | ||
| 1 | 23 | 0.11% | 137568 | 19.97% | /picsandmedia/In this Life.mpg |
| 2 | 19 | 0.09% | 39670 | 5.76% | /sounds/The Class Notes - Uninvited.mp3 |
| 3 | 44 | 0.21% | 31933 | 4.63% | /sounds/Break the Silence/The Class Notes - Criminal.mp3 |
| 4 | 11 | 0.05% | 29880 | 4.34% | /sounds/The Class Notes (Live) - Always Be My Baby.mp3 |
| 5 | 8 | 0.04% | 26413 | 3.83% | /sounds/The Class Notes (Live) - White Flag.mp3 |
| 6 | 8 | 0.04% | 21319 | 3.09% | /sounds/The Class Notes (Live) - In This Life.mp3 |
| 7 | 56 | 0.27% | 15957 | 2.32% | /sounds/Unfolded/The Class Notes - A Thousand Miles.mp3 |
| 8 | 2 | 0.01% | 12308 | 1.79% | /sounds/The Class Notes (Live) - Underwater.mp3 |
| 9 | 4 | 0.02% | 10360 | 1.50% | /sounds/The Class Notes (Live) - Amazing.mp3 |
| 10 | 30 | 0.14% | 9198 | 1.34% | /sounds/Break the Silence/The Class Notes - Sunny Came Home.mp3 |
| Top 10 of 64 Total Entry Pages | |||||
|---|---|---|---|---|---|
| # | Hits | Visits | URL | ||
| 1 | 306 | 1.48% | 272 | 46.42% | / |
| 2 | 35 | 0.17% | 30 | 5.12% | /index2.html |
| 3 | 311 | 1.50% | 26 | 4.44% | /welcome.html |
| 4 | 52 | 0.25% | 18 | 3.07% | /afterhours.html |
| 5 | 37 | 0.18% | 18 | 3.07% | /breakthesilence.html |
| 6 | 93 | 0.45% | 17 | 2.90% | /unfolded.html |
| 7 | 21 | 0.10% | 14 | 2.39% | /candids0203.html |
| 8 | 33 | 0.16% | 13 | 2.22% | /alumni.html |
| 9 | 298 | 1.44% | 12 | 2.05% | /cgi-sys/Count.cgi |
| 10 | 20 | 0.10% | 11 | 1.88% | /candids0304.html |
| Top 10 of 70 Total Exit Pages | |||||
|---|---|---|---|---|---|
| # | Hits | Visits | URL | ||
| 1 | 298 | 1.44% | 138 | 23.55% | /cgi-sys/Count.cgi |
| 2 | 306 | 1.48% | 39 | 6.66% | / |
| 3 | 281 | 1.36% | 30 | 5.12% | /timeline_collage.html |
| 4 | 93 | 0.45% | 27 | 4.61% | /unfolded.html |
| 5 | 54 | 0.26% | 22 | 3.75% | /picsmedia.html |
| 6 | 37 | 0.18% | 21 | 3.58% | /breakthesilence.html |
| 7 | 46 | 0.22% | 19 | 3.24% | /concerts.html |
| 8 | 52 | 0.25% | 18 | 3.07% | /afterhours.html |
| 9 | 117 | 0.56% | 16 | 2.73% | /members.html |
| 10 | 33 | 0.16% | 15 | 2.56% | /alumni.html |
| Top 30 of 732 Total Sites | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| # | Hits | Files | KBytes | Visits | Hostname | ||||
| 1 | 651 | 3.14% | 297 | 1.99% | 6043 | 0.88% | 10 | 1.69% | <IP_ADDRESS>.up.mi.chartermi.net |
| 2 | 540 | 2.61% | 55 | 0.37% | 42546 | 6.18% | 10 | 1.69% | r253153109.resnet.cornell.edu |
| 3 | 497 | 2.40% | 191 | 1.28% | 2677 | 0.39% | 8 | 1.36% | ool-182ea6c3.dyn.optonline.net |
| 4 | 460 | 2.22% | 78 | 0.52% | 943 | 0.14% | 10 | 1.69% | 24-229-238-104.cmts.snh.ptd.net |
| 5 | 440 | 2.12% | 220 | 1.48% | 2047 | 0.30% | 1 | 0.17% | <IP_ADDRESS> |
| 6 | 424 | 2.05% | 423 | 2.84% | 8544 | 1.24% | 1 | 0.17% | r253237181.resnet.cornell.edu |
| 7 | 366 | 1.77% | 141 | 0.95% | 18799 | 2.73% | 5 | 0.85% | cpe-69-202-75-76.twcny.res.rr.com |
| 8 | 362 | 1.75% | 306 | 2.05% | 5041 | 0.73% | 4 | 0.68% | r253240108.resnet.cornell.edu |
| 9 | 342 | 1.65% | 284 | 1.91% | 6294 | 0.91% | 6 | 1.02% | cpe-69-202-74-183.twcny.res.rr.com |
| 10 | 334 | 1.61% | 267 | 1.79% | 3788 | 0.55% | 1 | 0.17% | cpe-24-58-15-89.twcny.res.rr.com |
| 11 | 317 | 1.53% | 315 | 2.12% | 14638 | 2.12% | 1 | 0.17% | c-24-126-70-133.we.client2.attbi.com |
| 12 | 299 | 1.44% | 12 | 0.08% | 353 | 0.05% | 6 | 1.02% | pcp0011264069pcs.arlngt01.va.comcast.net |
| 13 | 281 | 1.36% | 62 | 0.42% | 1203 | 0.17% | 6 | 1.02% | pax.nmu.edu |
| 14 | 234 | 1.13% | 187 | 1.26% | 29474 | 4.28% | 1 | 0.17% | tsteinbach.rh.rit.edu |
| 15 | 231 | 1.11% | 149 | 1.00% | 22192 | 3.22% | 5 | 0.85% | r253175165.resnet.cornell.edu |
| 16 | 213 | 1.03% | 78 | 0.52% | 1308 | 0.19% | 5 | 0.85% | cuinfo10.cit.cornell.edu |
| 17 | 207 | 1.00% | 135 | 0.91% | 6907 | 1.00% | 2 | 0.34% | c-24-23-97-108.client.comcast.net |
| 18 | 204 | 0.98% | 134 | 0.90% | 1383 | 0.20% | 1 | 0.17% | <IP_ADDRESS> |
| 19 | 201 | 0.97% | 105 | 0.71% | 1626 | 0.24% | 3 | 0.51% | r253228022.resnet.cornell.edu |
| 20 | 195 | 0.94% | 194 | 1.30% | 5511 | 0.80% | 1 | 0.17% | r253228157.resnet.cornell.edu |
| 21 | 173 | 0.83% | 133 | 0.89% | 23020 | 3.34% | 2 | 0.34% | crawl-66-249-65-49.googlebot.com |
| 22 | 173 | 0.83% | 159 | 1.07% | 5481 | 0.80% | 1 | 0.17% | pool-151-201-135-37.pitt.east.verizon.net |
| 23 | 171 | 0.83% | 101 | 0.68% | 12754 | 1.85% | 1 | 0.17% | pcp06580080pcs.nrockv01.md.comcast.net |
| 24 | 170 | 0.82% | 18 | 0.12% | 346 | 0.05% | 3 | 0.51% | r253006146.resnet.cornell.edu |
| 25 | 169 | 0.82% | 69 | 0.46% | 1257 | 0.18% | 5 | 0.85% | cpe-69-202-73-96.twcny.res.rr.com |
| 26 | 168 | 0.81% | 68 | 0.46% | 1637 | 0.24% | 1 | 0.17% | dynamic-addr-138-27.resnet.rochester.edu |
| 27 | 159 | 0.77% | 3 | 0.02% | 11 | 0.00% | 2 | 0.34% | r253108210.resnet.cornell.edu |
| 28 | 154 | 0.74% | 11 | 0.07% | 275 | 0.04% | 3 | 0.51% | r253006149.resnet.cornell.edu |
| 29 | 145 | 0.70% | 142 | 0.95% | 2365 | 0.34% | 1 | 0.17% | ool-4357ef15.dyn.optonline.net |
| 30 | 145 | 0.70% | 135 | 0.91% | 1443 | 0.21% | 1 | 0.17% | r253197068.resnet.cornell.edu |
| Top 10 of 732 Total Sites By KBytes | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| # | Hits | Files | KBytes | Visits | Hostname | ||||
| 1 | 133 | 0.64% | 91 | 0.61% | 49528 | 7.19% | 1 | 0.17% | cpe-24-58-5-84.twcny.res.rr.com |
| 2 | 540 | 2.61% | 55 | 0.37% | 42546 | 6.18% | 10 | 1.69% | r253153109.resnet.cornell.edu |
| 3 | 234 | 1.13% | 187 | 1.26% | 29474 | 4.28% | 1 | 0.17% | tsteinbach.rh.rit.edu |
| 4 | 173 | 0.83% | 133 | 0.89% | 23020 | 3.34% | 2 | 0.34% | crawl-66-249-65-49.googlebot.com |
| 5 | 231 | 1.11% | 149 | 1.00% | 22192 | 3.22% | 5 | 0.85% | r253175165.resnet.cornell.edu |
| 6 | 56 | 0.27% | 55 | 0.37% | 21173 | 3.07% | 1 | 0.17% | <IP_ADDRESS> |
| 7 | 102 | 0.49% | 61 | 0.41% | 19588 | 2.84% | 1 | 0.17% | x1-6-00-02-a5-d6-e0-bc.resnet.jhu.edu |
| 8 | 366 | 1.77% | 141 | 0.95% | 18799 | 2.73% | 5 | 0.85% | cpe-69-202-75-76.twcny.res.rr.com |
| 9 | 110 | 0.53% | 60 | 0.40% | 16146 | 2.34% | 1 | 0.17% | r084028148.resnet.cornell.edu |
| 10 | 33 | 0.16% | 24 | 0.16% | 14960 | 2.17% | 1 | 0.17% | volera.leo.itesm.mx |
| Top 20 of 40 Total Search Strings | |||
|---|---|---|---|
| # | Hits | Search String | |
| 1 | 22 | 27.85% | class notes |
| 2 | 8 | 10.13% | baby got back |
| 3 | 3 | 3.80% | Class Notes |
| 4 | 3 | 3.80% | candid girls |
| 5 | 3 | 3.80% | class notes cornell |
| 6 | 2 | 2.53% | Alee Cavanagh |
| 7 | 2 | 2.53% | Class notes |
| 8 | 2 | 2.53% | Marcel Lopez |
| 9 | 2 | 2.53% | cornell a cappella |
| 10 | 2 | 2.53% | cornell class notes |
| 11 | 1 | 1.27% | Annie Lennox Sweet |
| 12 | 1 | 1.27% | Party Up |
| 13 | 1 | 1.27% | The Cornell Class Notes |
| 14 | 1 | 1.27% | Tracy Bornstein |
| 15 | 1 | 1.27% | ari friedland |
| 16 | 1 | 1.27% | class notes lafayette |
| 17 | 1 | 1.27% | class notes store |
| 18 | 1 | 1.27% | classnotes cornell |
| 19 | 1 | 1.27% | cornell Class Notes |
| 20 | 1 | 1.27% | cornell classnotes |
| Top 1 of 1 Total Usernames | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| # | Hits | Files | KBytes | Visits | Username | ||||
| 1 | 95 | 0.46% | 14 | 0.09% | 324 | 0.05% | 2 | 0.34% | classnot |
| Top 15 of 135 Total User Agents | |||
|---|---|---|---|
| # | Hits | User Agent | |
| 1 | 3256 | 15.71% | Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET |
| 2 | 2944 | 14.21% | Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1) |
| 3 | 2457 | 11.86% | Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1) |
| 4 | 2287 | 11.03% | Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.5) Gec |
| 5 | 1742 | 8.41% | Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; .NET CLR 1 |
| 6 | 659 | 3.18% | Mozilla/4.0 (compatible; MSIE 6.0; Windows 98; .NET CLR 1.1.4 |
| 7 | 454 | 2.19% | Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/125. |
| 8 | 410 | 1.98% | Mozilla/5.0 (Windows; U; Windows NT 5.1; rv:1.7.3) Gecko/2004 |
| 9 | 388 | 1.87% | Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; NMU; SV1; |
| 10 | 348 | 1.68% | Mozilla/5.0 |
| 11 | 309 | 1.49% | Mozilla/5.0 (Macintosh; U; PPC Mac OS X Mach-O; en-US; rv:1.7 |
| 12 | 303 | 1.46% | Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.4) Gecko |
| 13 | 276 | 1.33% | Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7) Gecko |
| 14 | 270 | 1.30% | Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en-US; rv:1.0.2) Gec |
| 15 | 213 | 1.03% | Inktomi Search |
| Top 30 of 41 Total Countries | |||||||
|---|---|---|---|---|---|---|---|
| # | Hits | Files | KBytes | Country | |||
| 1 | 6814 | 32.88% | 4756 | 31.93% | 237439 | 34.46% | US Educational |
| 2 | 6219 | 30.01% | 4380 | 29.41% | 134803 | 19.56% | Network |
| 3 | 4813 | 23.22% | 3862 | 25.93% | 210365 | 30.53% | US Commercial |
| 4 | 1984 | 9.57% | 1462 | 9.82% | 53942 | 7.83% | Unresolved/Unknown |
| 5 | 136 | 0.66% | 132 | 0.89% | 2213 | 0.32% | Canada |
| 6 | 121 | 0.58% | 99 | 0.66% | 10832 | 1.57% | Czech Republic |
| 7 | 99 | 0.48% | 95 | 0.64% | 1740 | 0.25% | United Kingdom |
| 8 | 71 | 0.34% | 54 | 0.36% | 1648 | 0.24% | France |
| 9 | 61 | 0.29% | 58 | 0.39% | 1068 | 0.16% | Turkey |
| 10 | 51 | 0.25% | 42 | 0.28% | 16039 | 2.33% | Mexico |
| 11 | 43 | 0.21% | 35 | 0.24% | 304 | 0.04% | Hungary |
| 12 | 41 | 0.20% | 27 | 0.18% | 943 | 0.14% | Poland |
| 13 | 35 | 0.17% | 35 | 0.24% | 1953 | 0.28% | Malaysia |
| 14 | 30 | 0.14% | 27 | 0.18% | 409 | 0.06% | Germany |
| 15 | 26 | 0.13% | 19 | 0.13% | 268 | 0.04% | Non-Profit Organization |
| 16 | 20 | 0.10% | 11 | 0.07% | 2094 | 0.30% | Netherlands |
| 17 | 18 | 0.09% | 17 | 0.11% | 1008 | 0.15% | Israel |
| 18 | 18 | 0.09% | 18 | 0.12% | 302 | 0.04% | South Africa |
| 19 | 16 | 0.08% | 15 | 0.10% | 480 | 0.07% | Slovak Republic |
| 20 | 15 | 0.07% | 15 | 0.10% | 4172 | 0.61% | Brazil |
| 21 | 12 | 0.06% | 12 | 0.08% | 112 | 0.02% | Australia |
| 22 | 11 | 0.05% | 11 | 0.07% | 145 | 0.02% | Argentina |
| 23 | 11 | 0.05% | 11 | 0.07% | 1547 | 0.22% | Finland |
| 24 | 9 | 0.04% | 8 | 0.05% | 370 | 0.05% | Austria |
| 25 | 9 | 0.04% | 9 | 0.06% | 612 | 0.09% | Switzerland |
| 26 | 9 | 0.04% | 9 | 0.06% | 742 | 0.11% | United States |
| 27 | 4 | 0.02% | 4 | 0.03% | 10 | 0.00% | Saudi Arabia |
| 28 | 4 | 0.02% | 3 | 0.02% | 0 | 0.00% | Sweden |
| 29 | 4 | 0.02% | 0 | 0.00% | 1 | 0.00% | Uruguay |
| 30 | 3 | 0.01% | 0 | 0.00% | 1 | 0.00% | Belgium |
| Generated by Webalizer Version 2.01 |


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John Doe
commented on
What Makes Good Code Good
.
3 h
Merge request #42
has been approved by
Jessica Lori
.
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Greg Wilson
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Server fail level raises above normal.
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dwr.util.getValue(id, options)
is the read version of setValue()
. This gets the values out of the HTML elements without you needing to worry about how a selection list differs from a div.
By default DWR protects against XSS in dwr.util.getValue by escaping potentially dangerous characters. The optional options object parameter allows output escaping to be disabled. Please see the escapeHtml page for more information.
This method works for most HTML elements including selects (where the option with a matching value and not text is selected), input elements (including textareas) divs and spans.
For example:
dwr.util.getValue
(
)
Returns " " (Press 'getValue').
HTML Test Elements
| Text area (id="textarea"): | Selection list (id="select"): | ||
| Text input (id="text"): | Password input (id="password"): | ||
| Form button (id="formbutton"): | Fancy button (id="button"): |


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Item
Control
Data
Re-exports
TableItemControlData
Tools
Props
Modifier
Re-exports
ToolsPropsModifier
Variant
Re-exports
Variant
Variant
Props
Re-exports
VariantProps
Exports
index
Category
Component
Component
Preview
Component
Preview
Props
Component
Props
Control
Input
Handler
Control
Json
Handler
Control
Select
Handler
Control
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Handler
Control
Union
Handler
Dev
Support
Initial
Hook
Status
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Previews
Props
Control
Types
Props
Edit
Info
Props
Modifier
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Item
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Data
Tools
Props
Modifier
Variant
Variant
Props
Generated using
TypeDoc


Ballard Neighborhood Veterinary
Pet Name:
Street Address:
City:
State:
Zip Code:
Chipped:
Create New Patient


Box Office: ‘Dil Bechara’ confirmed for cinema release in May 2020
by Raj BaddhanAfter rumours earlier of a digital-exclusive release of Sushant Singh Rajput’s next ‘Dil Bechara’, makers have today denied the speculation, instead announcing a new cinema release date.
The film, which is based on the Hollywood film ‘The Fault in Our Stars’, also stars Sanjana Sanghi. It is directed by Mukesh Chhabra, with music by AR Rahman. The Fox Star Studios production, releases on 8th May 2020 at cinemas.
Keep it with BizAsiaLive.com for more.


Next: unintern, Previous: with-package-iterator, Up: Packages Dictionary
unexport
symbols &optional package ⇒ t
symbols—a designator for a list of symbols.
package—a package designator.
The default is the current package.
unexport reverts external symbols in package to internal status; it undoes the effect of export.
unexport works only on symbols present in package, switching them back to internal status. If unexport is given a symbol that is already accessible as an internal symbol in package, it does nothing.
(in-package "COMMON-LISP-USER") ⇒ #<PACKAGE "COMMON-LISP-USER"> (export (intern "CONTRABAND" (make-package 'temp)) 'temp) ⇒ T (find-symbol "CONTRABAND") ⇒ NIL, NIL (use-package 'temp) ⇒ T (find-symbol "CONTRABAND") ⇒ CONTRABAND, :INHERITED (unexport 'contraband 'temp) ⇒ T (find-symbol "CONTRABAND") ⇒ NIL, NIL
Package system is modified.
Current state of the package system.
If unexport is given a symbol not accessible in package at all, an error of type package-error is signaled.
The consequences are undefined if package is the KEYWORD package or the COMMON-LISP package.


CSI Test
Include 1
- Within DIV
Loading...
Include 2
- Replace DIV
Loading...
Include 3
- Within DIV
Loading...
Log


I confirm that I Student Name have been duly appointed by Student Name, have permission to act on their behalf and confirm that to the best of my knowledge all the details supplied are accurate and correct. I understand that the giving of false or incomplete information may lead to the misguidance in college counselling process or refusal of admissions to colleges or cancellation of the applicant’s enrolment. I confirm that the applicant has received a copy of the terms and conditions.


{% assign words = include.content | strip_html | number_of_words %} {{ words | divided_by: 265 | plus: 1 }} min read


Instructions for "Thing" hand
The e-Nable Raptor is always an impressive
thing to behold, but the plan here is to make it move.
-
Check to see if Arduino is installed, and install if necessary
-
Check to see if Arduino IDE has the Adafruit Feather 32u4 board included by looking in the "tools >> board" menu of
the IDE. If the board is not included in your installation of the Arduino IDE (likely if you just installed it) then
you should follow these instructions from
Adafruit.com to include it.
-
Check to see if Arduino IDE has the Adafruit PWM/Servo Driver Library included by look in the "Files >> Examples" area
of the menu to see if the library is already installed in the IDE. IF the Library is installed, you will see it named
in that section of the menu. If the library is not included in your installation of the Arduino IDE (likely if you just
installed it) then you should follow
these instructions from Adafruit.com to include it.
-
Next you should open the arduino file and connect the feather board to the computer. Be
careful to make sure that you connect the 'Feather 32u4' board and not the PowerBoost 1000 Charge' board to the computer
via microUSB. [Note: Some USB cables are just intended for charging, and don't have a data connection. Avoid These...]
-
At this point you can make any changes you would like to make to the code. Save the changed file with a new name (so as to
not to alter the original).
-
Make sure that the correct port is selected, and then upload (CTRL+U) the sketch to the Feather board.
-
Open up the serial monitor (CTRL+SHIFT+M) and see the serial ouput from the board, if you are interested in debugging or
checking up on things.


Apps That Give You Money - Really!
 Seriously! I made a round up of my favorite apps that give you money and included links and quick reviews.
Of course, these apps aren’t necessarily going to be a huge windfall in your bank account - but they may let you treat yourself to an extra latte a month, or help stretch your paycheck when money is tight.
You’ve probably heard of apps that promise free money, and a lot of times they are just too good to be true. With these apps, I’ll attempt to explain what you can get and why it’s free. Some companies are willing to pay you for your opinion because they are doing market research. Other companies just want to show you ads on your phone’s lockscreen. Each app has a reason of it’s own so without further ado, here are the best apps that give you money.
S’more
Most of these apps are going to make you work for a buck. S’more actually pays you for just sitting there! S’more displays ads on your lockscreen - silent, unobtrusive display ads - and then lets you cash out points at the end of the month.
You need an Android phone to use S’more (Apple’s terms and conditions won’t allow this type of ad network) But once you’ve installed it, that’s it! You’re ready to start accumulating points.
Typical payout is between $3 and 5 per month, which really adds up! Points can be exchanged for gift cards to Amazon and other popular retailers.
You can downloaded the S’more app here in the Google Play store.
Fiverr
If you’re good at anything, (and even if you’re not), you should check out Fiverr.
Fiverr lets you connect with other people around the world in need of a specific service. Usually they are one-off gigs. People come to Fiverr when they need a writer for a blog post, and artist that makes logos out of food, a e-book cover design of a unicorn, a musician for a jingle, etc. Just like the name suggests, the jobs usually pay $5 each.
Obviously you can’t make a fortune on $5 jobs, but it can help pad your wallet a bit. It also may give you an outlet to exercise hobbies you don’t usually get to do.
Field Agent
If you love filling out surveys, this app is your you. It’s called “Field Agent” because users with the app act as agents for large companies, helping them with grassroots research to collect photos, video, and information from stores and other locations. This information is used by those businesses to better serve their customers. Oh and the best part is, you can get paid!
This app is also great for people who live in bigger cities, since most of the jobs are typically concentrated in metro areas.
Check out the Field Agent website for more info on how it works.
Foap
Foap is like Fiverr for amateur photographers.
If you have a camera roll with over 10,000 photos on it that you’ve never posted online, this app is for you. You can upload those high quality that have never seen the light of day to Foap and maybe get paid for them! The idea of foap is that content creators are looking for cheaper alternatives to stock photography, at the same time that mobile phone cameras are getting better and better. If your photos sell, you’ll get a percentage of the payout. Additionally you can earn extra rewards for highly rated images.
It’s no secret that the Internet is full of “fauxtographers,” so if you’re even halfway decent at capturing beautiful images, you have a pretty good chance of standing out on Foap. Many major companies rely on Foap for images to be used in their catalogs and websites. If your photography skills go beyond the “everyday” photographer’s, you might end up making a connection that could lead to a much better-paying gig.
Ibotta
Ibotta is a service that, quite frankly, should be used by everyone.
Ibbotta allows you to collect returns on things you already buy - i.e. groceries. The app organizes and shows you rebates for specific grocery-related items bought at either supermarkets or retail stores, but only if you keep the receipt!
After a trip to the grocery store, you’ll upload a picture of your receipt to Ibotta. The app scans your receipts and finds any available rebates for you.
Even better, you have the option of joining “teams” with specific shopping goals. Once your team reaches a goal, you’ll receive the predetermined monthly bonus reward.
You can have your earnings transferred either to your PayPal or Venmo account, or, if you choose, you can purchase gift cards for various retailers with your money.
Grocery shopping is getting more and more expensive every year. Ibotta can help put a little bit of that change back in your pocket.


{% extends "sharkdata_doc_base.html" %} {% block title %}SHARKdata - Documentation{% endblock%} {% block header %}Documentation{% endblock%} {% block doc-content %}
SHARKdata is a web service with a REST API to be used for accessing marine environmental monitoring data from the seas surrounding Sweden. SHARKdata also have a web site for documentation and administration where it is possible to access some parts of the data directly.
SHARKdata is build on the concept of datasets. A dataset is a collection of data with a unique identifier and connected metadata that describes the dataset. Is should be possible to assign a version stamp to a dataset. Metadata can, for example, be used by data catalogues like ECDS.
Requests via the REST API are made by URL:s, for example http://sharkdata.se/datasets/table.txt to get a text table containing all available datasets.
The response format will vary depending on client needs. Text and JSON formats are always available. Text files can always be opened in standard text editors or spreadsheet programs. JSON is easy to use if the client software is written in JavaScript or Python, but parsers are available for other languages as well. Other formats like KML, XML, WFS, etc. will be developed in cooperation with clients when needed.
SHARKdata is based on modules and new modules will be developed over time. Species observations is a module where observations are extracted from other datasets. Special response formats are available like KML and simple maps. The module Resources contains administrative data. It can contain files for header translations, screening of data, taxonomic information, etc.
SHARKdata is currently under development and only a limited number of datasets and response formats are available for test.
There is no full API description yet, but these examples can be a start. Click on the links below to test the API.
SHARKdata is written in Python 2.7 and based on the Django web framework. All code developed in the project is open source and published under the MIT license. The code repository can be found here: http://dev.sharkdata.se. Please contact us on<EMAIL_ADDRESS>if you are developing a client application and want to be notified when we are planning changes to the API.
{% endblock doc-content%}


WITNESS LIST
Finance-S/C on Fiscal Matters
April 15, 2013 9:00 AM
FOR:
Hansen, Tommy Law Enforcement (also providing written testimony) (Tx. Assoc. of
Vehicle Theft Investigators), Galveston, TX
ON:
Parks, Ursula (LBB)
Registering, but not testifying:
FOR:
Canady, Joey (Texas Association of Vehicle Theft Inu.), Marble Falls, TX
Craft, Lon Dir. Legislative Affairs (Texas Municipal Police Assoc)
Jones, Sgt. James D. Police Officer (San Antonio Police Dept.), San Antonio, TX
Kenderdine, Marshall consultant (City of San Antonio), Austin, TX
Nicholes, Laura Legislative Liaison (Texas Association of Counties), Austin
Wooley, Tommy Texas Association of Vehicle Theft Inu (TAUTi) (Sheriffs Combined
Auto Theft Task Force)
ON:
Caldwell, Charles Auto Theft Prevention Authority- Director (ABTPA), Cedar Park, TX
FOR:
Lavine, Dick Fiscal Analyst (Center For Public Policy Priorities), Austin
Registering, but not testifying:
FOR:
Davis, Melissa Legislative Intern (National Association of Social Workers- Texas Chapter),
Austin, TX
Quinzi, Patty Legislative Counsel (TX- AFT), Austin, TX
ON:
Riggs, Brendon LLB Staff (LBB)
FOR:
Yates, Maura Director, Government Affairs (also providing written testimony) (Sun
Edison), Austin, TX
Registering, but not testifying:
FOR:
Gonzalez, Daniel Consultant (Texas Association of Realtors), Austin, TX
Haverlah, Sandra consultant (Environmental Defense Fund), Austin, TX
Kemptner, Sara consultant (NRG Energy), Austin, TX
Metzger, Luke Director (Environment Texas), Austin, TX
Power, David Deputy Director (Public Citizen), Austin, TX
Smith, Russel E. Association Management (Texas Renewable Energy Industries
Association), Austin, TX
Townsend, Trent Lobbyist (First Solar), Austin, TX
Weinberg, David Executive Director (Texas League of Conservation Voters), Austin, TX
White, Kaiba Policy & Outreach Specialist (Public Citizen)
WITNESS LIST
Finance-S/C on Fiscal Matters
April 15, 2013 9:00 AM
FOR:
Haverlah, Sandra President/ non profit (also providing written testimony) (Texas
Consumer Association)
Howden, Robert Chairman (also providing written testimony) (Texans for Economic
Progress), Austin, TX
Kennedy, John Senior Analyst (Texas Taxpayers & Research Association), Austin
Lawson, Richard Vice President (also providing written testimony) (Verizon), Austin, TX
Mackey, Scott Economist/ Partner = KSE Partners LLP (also providing written testimony)
(Wireless Telecommunications Providers), Montpelier, VT
Peacock, William policy analyst (also providing written testimony) (Texas Public Policy
Foundation), Austin
Ward, Leslie External Affairs (also providing written testimony) (AT&T), Austin, TX
Registering, but not testifying:
FOR:
Belcher, Nora Executive Director (Texas e-Health Alliance), Austin
Bergland, Jennifer Dir. of Government Affairs (Texas Computer Education Association)
Bogue, Donna Education Technology (SUPERNet / NETNet), Tyler, TX
Burdett, Jeff (Texas Cable Association), Sunset Valley, TX
Camacho, Jose A. Lobbyist (Texas Telephone Association), Austin
Connett, Brent (Texas Conservative Coalition), Austin, TX
Cruz, Velma Government Affairs Manager (SPRINT), Austin, TX
Flores, Robert Gov't Affairs Consultant (Texas Association of Mexican-American
Chambers of Commerce), SA, TX
Giles, Deborah Government Relations (SH1 International, Inc), Austin, TX
Gray, CPA, Weldon R. Telcom (Texas Statewide Telephone Cooperative, Inc. (TSTCI)),
Henderson, TX
Hogan, Pat Executive Director (Texas Technology Consortium)
Jones, Max Government Affairs Manager (The Greater Houston Partnership), Houston, TX
Lavine, Dick Fiscal Analyst (Center For Public Policy Priorities), Austin, TX
Lucero, Homero Manager (CenturyLink), Austin, TX
Reilly, Wendy Director, State Gov. Affairs (The Technology Association of America (Tech
America)), Austin, TX
Wurzel, Geoff Director (TechNet)
AGAINST:
Kenderdine, Marshall consultant (City of San Antonio), Austin, TX
FOR:
Brock, Kay Asst. Travis Co. Attorney (Travis County), Austin
Eckstein, Deece Intergovernmental Relations Ofcr. (Travis County Commissioners Court)
Registering, but not testifying:
FOR:
Clark, Catherine Director, Governmental Relations (Texas Association of School Boards)
WITNESS LIST
Finance-S/C on Fiscal Matters
April 15, 2013 9:00 AM
Lawson, Revlynn Govt Affairs (Linebarger Goggan Blair Sampson, LLP), Austin
Lee, Donald Executive Director (Texas Conference of Urban Counties), Austin, TX
Ramirez, Melissa Attorney, Popp Hutcheson (Myself & Popp Hutcheson)
Sugg, Paul Legislative Director (Texas Association of Counties)
FOR:
Gonzalez, Daniel Consultant (Texas Association of Realtors), Austin, TX
Nash, Windy Litigation Specialist (Texas Association of Appraisal Districts; Dallas CAD),
Dallas, TX
South, Brent Chief Appraiser (Hunt County Appraisal Dist. & Texas Assc. of Appraisal
Dist.), Greenville, TX
ON:
Cartwright, Deborah Director, Property Tax Assistance Division (Comptroller of Public
Accounts)


| thor::Action | Class for dynamic actions that are connected with SFML events |
| thor::ActionContext< ActionId > | Structure containing information about the context in which an action has occurred |
| thor::ActionMap< ActionId > | Class template that associates identifiers with dynamic actions |
| thor::AnimationAffector | Affector that animates particles using a function |
| thor::Animator< Animated, Id > | Class that stores the progress of an object's animation |
| thor::Arrow | Drawable arrow class |
| thor::BigSprite | Sprite using big textures |
| thor::BigTexture | Class for textures which are too big for sf::Texture |
| thor::CallbackTimer | Advanced timer with the ability to trigger function calls |
| thor::ColorAnimation | Changes an object's color smoothly over time |
| thor::ColorGradient | Class to implement color gradients |
| thor::ConcaveShape | Concave shape class |
| thor::Connection | Class that maintains control over a registered object |
| thor::Distribution< T > | Class holding a rule to create values with predefined properties |
| thor::Edge< V > | Edge that contains two vertices (its endpoints or corners) |
| thor::EmissionInterface | Class that connects emitters with their corresponding particle system |
| thor::EventSystem< Event, EventId > | Class for object-oriented handling of user-defined events |
| thor::FadeAnimation | Lets an object fade in or out |
| thor::ForceAffector | Applies a translational acceleration to particles over time |
| thor::FrameAnimation | Changes a sprite's subrect over time |
| thor::JoystickAxis | Contains information about a joystick number, an axis and its threshold |
| thor::JoystickButton | Contains information about a joystick number and button number |
| thor::Particle | Particle class |
| thor::ParticleSystem | Class for particle systems |
| thor::PolarVector2< T > | Vector in polar coordinate system |
| thor::RefAnimation< Animation > | Class to reference another animation |
| thor::ResourceAccessException | Exception class for invalid resource access |
| thor::ResourceHolder< R, I, O > | Class that is responsible of the management of resources like images, fonts or music |
| thor::ResourceLoader< R > | Class storing loading information for resources |
| thor::ResourceLoadingException | Exception class for failed resource allocation |
| thor::Resources::CentralOwner | Centralized ownership policy |
| thor::Resources::RefCounted | Reference-counted ownership policy |
| thor::ScaleAffector | Scales particles over time |
| thor::ScopedConnection | RAII style connection with automatic disconnect |
| thor::StopWatch | Pausable clock class that measures elapsed time |
| thor::StringConversionException | Exception class for failed string conversions |
| thor::Timer | Clock class that has the semantics of a countdown timer |
| thor::TorqueAffector | Applies a rotational acceleration to particles over time |
| thor::Triangle< V > | Triangle class consisting of 3 vertices (its corners) |
| thor::TriangulationTraits< V > | Traits template to implement the Vertex concept |
| thor::TrigonometricTraits< T > | Trigonometric traits template |
| thor::UniversalEmitter | Class that emits particles with customizable initial conditions |


Volkswagen to debut ID. Space Vizzion concept
The latest Volkswagen ID. concept is a svelte station wagon – maybe the classic wagon has plenty of life in it yet.
by William Stopford- shares
Could Volkswagen be trying to make the station wagon cool again?
The company is debuting the ID. Space Vizzion concept at this year’s Los Angeles motor show. It’s a rather strange debut location for a station wagon as the US is virtually enemy territory for the body style, arguably even more so than Australia.
The ID. Space Vizzion is another vehicle based on Volkswagen’s Modular Electric Drive (MEB) platform. It previews a production model which will “come in different versions” and arrive in the North American, Chinese and European markets in 2021.
The ID. Space Vizzion is said to achieve an electric range of 590km under the more stringent WLTP measures. For comparison, the top-spec ID.3 with its 77kWh battery has 550km of range.
To enthusiasts, a station wagon is an utterly logical and often highly desirable body style. Nevertheless, they’ve waned in popularity in markets like Australia and the US.
In its press release, Volkswagen appears to appeal to SUV buyers, touting the ID. Space Vizzion as combining the “aerodynamic characteristics of a Gran Turismo with the spaciousness of an SUV”.
The last ID. Vizzion branded concept was a sedan which debuted at last year’s Geneva show. That Vizzion had a very, uhh, visionary interior, lacking a steering wheel and a conventional dashboard and was designed for Level 5 autonomous driving.
The ID. Space Vizzion isn’t quite so forward-thinking but its interior is still resolutely modern with a Tesla Model 3-style, landscape-oriented touchscreen. It also features AppleSkin trim, an artificial leather partially made of the residual matter from apple juice production.
Though Volkswagen hasn’t released dimensions of the ID. Space Vizzion yet, the ID. Vizzion was a big ‘un – measuring 5164mm long and 1948mm wide, it was bigger than a Tesla Model S and almost exactly the same size as the regular-length Audi A8.
As the ID. Space Vizzion is set to debut on 19 November, it may also be the unspecified, new ID. concept set to appear at the Petersen Automotive Museum the following day.
Once the family chariot of choice for US buyers, minivans left wagons in the weeds in the 1980s and SUVs drove the final nail into their coffin in the 1990s. The remaining station wagons on sale there, such as the Volvo V90, are largely niche, luxury-branded models that attract a select few of the monied elite.
Volkswagen offers one of the tiny handful of mainstream-branded wagons on sale there, the Golf SportWagen, but has recently announced it’d be discontinued. On the other end of the spectrum, they’re reintroducing the magnificent Audi RS6 Avant there. Perhaps Volkswagen sees an opportunity there for more upscale wagons, even as mainstream options continue to be whittled down.
1
5
nextprevious
Volkswagen to debut ID. Space Vizzion concept


Shopyoapi¶
Shopyo has some api which eases your life
shopyoapi.cmd¶
commandline utilities functions
-
shopyoapi.cmd.
clean
(app)[source]¶ Deletes shopyo.db and migrations/ if present in current working directory. Deletes all __pycache__ folders starting from current working directory all the way to leaf directory.
- Parameters
app (-) –
- Returns
…
- Return type
None
-
shopyoapi.cmd.
collectstatic
(target_module=None)[source]¶ Copies module/static into /static/modules/module in static it becomes like static/
- modules/
- box_something/
modulename
modulename2
- Parameters
target_module (str) – name of module, in alphanumeric-underscore, supports module or box__name/module
- Returns
- Return type
None
-
shopyoapi.cmd.
create_box
(name)[source]¶ creates box with box_info.json
- Parameters
name (str) – name of box, in alphanumeric-underscore
- Returns
- Return type
None
-
shopyoapi.cmd.
create_module
(modulename, base_path=None)[source]¶ creates module with the structure defined in the modules section in docs
- Parameters
modulename (str) – name of module, in alphanumeric-underscore
- Returns
- Return type
None
-
shopyoapi.cmd.
create_module_in_box
(modulename, boxname)[source]¶ creates module with the structure defined in the modules section in docs in a box
- Parameters
modulename (str) – name of module, in alphanumeric-underscore
boxname (str) – name of box, in alphanumeric-underscore
- Returns
- Return type
None
shopyoapi.database¶
shopyoapi.enhance¶
shopyoapi.file¶
-
shopyoapi.file.
absdiroffile
(filepath)[source]¶ Gives absolute directory of file, normally expects __file__ as param
- Parameters
filepath (str) – path of file
- Returns
Absolute dir path of file
- Return type
str
-
shopyoapi.file.
trycopy
(source, dest)[source]¶ Non-ecursive copy of folder
- Parameters
source (str) – source folder path
dest (str) – destination folder path
- Returns
- Return type
None
-
shopyoapi.file.
trycopytree
(source, dest)[source]¶ Recursive copy of folder
- Parameters
source (str) – source folder path
dest (str) – destination folder path
- Returns
- Return type
None
-
shopyoapi.file.
trymkdir
(path)[source]¶ Creates dir at destination
- Parameters
path (str) – path with folder already in
- Returns
- Return type
None
shopyoapi.forms¶
shopyoapi.html¶
Used on flash flash(notify_success(‘mail sent!’))
shopyoapi.init¶
All initialisations like db = SQLAlchemy in this file


Arrays and hashes are two data types we can use to store vast amounts of information. An array is very flexible because we can store a wide variety of objects inside of it, and we can also store multiple object types in a single array! Elements of an array are indexed by integers in ascending order, beginning with 0. We typically initialize an array using the following code:
our_array = [1,3,"Peter"]A hash is a series of key/value pairs where every key points to a unique value. Hashes are valuable when we have an object with a number of variable properties. For example, if we are creating a database which stores the address, age, and gender of someone it might be a good idea to use hashes. The syntax for hashes is a bit more complex, and the following code provides an example:
characteristics = {age: 27, gender: "Male", address: "Berkeley"}Both arrays and hashes are very valuable and useful data types that I am sure I will learn a lot more about in the coming weeks.


Data Sci Hacks
Imagine a world where patient data becomes a treasure trove of insights for doctors, enabling them to unlock the secrets behind complex diseases.
That's exactly what "Data Sci Hacks" aims to achieve! This revolutionary system empowers patients to input their real-life parameters, transforming mundane data into a valuable resource. With an intuitive interface, doctors can navigate this treasure map, unraveling the hidden causes behind diseases and providing accurate diagnoses. By merging data science and healthcare, "Data Sci Hacks" enables doctors to embark on a thrilling journey of discovery, revolutionizing the way we understand and treat medical conditions.
Check my project now: Github Link for ProjectCheck this link to get to know about Interface
Technologies:
- -Python
- -Data Science
- -ML
- -Django + Django REST Framework
- -React JS


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Reflections
Block, Procs, and Lambdas? They're all ways to contain chunks of code that you want to run.
Here are some examples of each:
numbers = [2,4,6] #----Blocks------------------------------------------- numbers.map! {|x| x} #curly braces above or the do/end below contain the block p numbers numbers.map! do|x| x / 2 end p numbers #=> [2, 4, 6] [1, 2, 3]
Blocks are contained with curly braces "{ }" I'm sure you've seen these already if you've used .each or .map methods.
They can also be contained within a "do / end"
We can do that by adding this line outside the class and running it:
#-----Procs-------------------------------------------- pro = Proc.new{|x| 3 * x} p numbers.map!(&pro) #converts pro into block before using it with .map! pops = Proc.new { |x| x + 5} puts "Calling pops Proc with an argument, returns: #{pops.call(3)}" #=> [3, 6, 9] Calling pops Proc with an argument, returns: 8
Procs must be created with a "Proc.new" before the block. Procs are blocks that can be saved and called later on.
Here I defined a new Proc called "pro" that multiplies the variable by 3.

The "&" symbol before the proc converts the proc into a block before using it with the map! method.
You can call Procs with the ".call(arguments)". The arguments, if any, are placed in parentheses after the call.
#--------Lambdas-------------------------------------- delta = lambda{|x|p x * 2} numbers.each(&delta) p pro.inspect p delta.inspect #=> 6 12 18 "# Proc:0x0000000242e3a0@solution.rb:13 " "# Proc:0x0000000242de00@solution.rb:23 (lambda)>"
Lambdas are created almost like Procs except without the ".new"
If I inspect the proc and lambda I've created. It shows that both are Proc objects.
The lambda has a special (lambda) annotation at end. Lambas are Procs but are a specialized form.
Here's an example of a way to implement Procs / Lambdas in to methods. :
#------------method call --------------- def adding_procs(x, y, proc1, proc2) puts proc1.call(x,y) + proc2.call(x,y) end adding = Proc.new{ |x,y| x + y } subtracting = lambda{ |a,b| a - b } adding_procs(10, 5, adding, subtracting) #=> 20 3
Here I created a method that adds the output of 2 blocks of code. It takes in a 2 variables and 2 blocks of code.
Within the method, I call each block with 2 arguments that are the variables of the first two arguments of the method.
I then add those blocks together.
"adding" is a Proc that adds 2 numbers
"subtracting" is a Lambda that adds 2 numbers
Calling the "adding_procs" method with (10, 5, adding, subtracting) yields 20.
One difference between Procs and Lambdas is that Lambdas are stricter in the number of arguments called.
Procs won't be as picky when extra arguments are given.
#-------number of arguments - -------- p adding.call(1,2,3) #no error p subtracting.call(1,2,3) #returns wrong number of arguments (3 for 2) #=> 3 ArgumentError: wrong number of arguments (3 for 2) from solution.rb:38:in `block in'
Here "subtracting.call(1,2,3)" returns ArgumentError: wrong number of arguments (3 for 2).
This means that you gave 3 arguments when only 2 was expected.
"adding.call(1,2,3)" doesn't give any errors even though it has 3 for 2 arguments.
It will give an error if only 1 argument is given when it's expecting 2 arguments.
Another difference between Procs and Lambdas is the way they "return" when called in a method.
#-----------return procs and lambdas--------- def test_returnlam lam_ret = lambda do puts "in lambda then return" return end lam_ret.call puts "end of test_return method" end test_returnlam puts "" def test_returnproc proc_ret = Proc.new do puts "in Proc then return" return end proc_ret.call puts "end of test_return method" #this line doesn't get printed end test_returnproc #=> in lambda then return end of test_return method in Proc then return
In test_returnlam method, I create a lambda that prints text then "return"
The lambda is then called and on the next line, it should print out some more text.
When this method is called, it returns the text as expected.
I created another method test_returnproc that is the exact same as the other method except a proc is used and called.
When this new method is called, it only printed the text in the proc and not the text at the end of the method.
What happened was when the "return" in the Proc was executed, it completely exited out of the block
and the method in which it was called. Lambdas behave differently in that when the return, they only exit
back to where the lambda was called and the next line of code runs.
After learning about Lambdas, Procs, and blocks, it seems beneficial to use Lambdas over Procs due to the
extra strictness of number of arguments and they way it returns. Rarely would you want to completely exit
out of the method that contains it. Blocks are used when you don't need to repeat that block of code
somewhere else in the program. Procs and especially lambdas are definitely useful in the DRY
(Don't Repeat Yourself) format. It allows you to save a block for later use and can be called
later on anywhere else in the program. Using these will help clean up your code and also let you
call multiple blocks at one time. You can call a lambda/proc with an argument of another lambda / proc.
You can create some intricate methods with procs and lambdas.


{% extends 'base.html' %} {% set active_menu = "dgame" %} {% set active_submenu = "period-rewards" %} {% block title %}Viewly Distribution Game Rewards{% endblock %} {% block content %}
{{ period.end | humanDate}}
| Video ID | Creator Rewards | Voter Rewards | Votes |
|---|---|---|---|
| {{ video_id }} | {{ creator_rewards | readableNumber }} VIEW | {{ voter_rewards | readableNumber }} VIEW | {{ votes }} |
| Voter | Video ID | Vote Stake | Creator Reward | Voter Reward | Payouts |
|---|---|---|---|---|---|
| {{ vote.eth_address }} | {{ reward.video_id }} | {{ ((vote.token_amount + vote.delegated_amount) * vote.weight / 100) | readableNumber }} VIEW | {{ reward.creator_reward | readableNumber }} VIEW | {{ reward.voter_reward | readableNumber }} VIEW | {% if reward.creator_txid %} Creator {% endif %} {% if reward.voter_txid %} Voter {% endif %} |
This period has no rewards.
{% endif %}


Bubble Sort is one of the simplest sorting algorithms that compares two elements at a time and swaps them if they are in the wrong order. This process is repeated until the entire sequence is in order.
O(n ^ 2)
for average case; O(n)
for best case.O(n)
; note that iterative bubble sort has space complexity as O(1)
.Base case: If the size of the array is 1, return.
Let the given array be: {5, 3, 2, 1, 4}
First Iteration:
5
, 3
, 2, 1, 4} -> {3
, 5
, 2, 1, 4} Swap since 5 > 3
5
, 2
, 1, 4} -> {3, 2
, 5
, 1, 4} Swap since 5 > 2
5
, 1
, 4} -> {3, 2, 1
, 5
, 4} Swap since 5 > 1
5
, 4
} -> {3, 2, 1, 4
, 5
} Swap since 5 > 4
This iteration has fixed the position of 5. Now, we will consider the array up to index 3.
Second Iteration:
3
, 2
, 1, 4, 5} -> {2
, 3
, 1, 4, 5} Swap since 3 > 2
3
, 1
, 4, 5} -> {2, 1
, 3
, 4, 5} Swap since 3 > 1
3
, 4
, 5}; As 3 < 4
, do not swapNote: As we check one less element with every iteration, we do not need elements at index 3 and 4 i.e., 4
and 5
, as 5 is already in order. Formally, for an array with n
integers, we consider elements only up to index n - i
, where i
is the iteration number.
Third Iteration:
2
, 1
, 3, 4, 5} -> {1
, 2
, 3, 4, 5} Swap since 1 > 2
2
, 3
, 4, 5}; As 2 < 3
, do not swapFourth Iteration:
1
, 2
, 3, 4, 5}; As 1 < 2
, do not swapFifth Iteration:
1
, 2, 3, 4, 5}; As the size of the array is 1, return.Note: This is the base case.
void bubbleSort(arr[], n)
if(n==1)
return;
for(i = 0; i<n-1; i++)
if(arr[i] > arr[i+1])
swap(arr[i], arr[i+1])
bubbleSort(arr, n-1)
A video explaining iterative as well as recursive bubble sort


This project is a low-level introduction to the world of SEO (search engine optimization).
If you want to learn more in-depth information about search engine optimization, you can
explore more with this video from the SEO guru Google themself.
Back
Works cited
START OVER


This page is an archive of past meeting agendas, their minutes and IRC logs, for the year shown above.
For current information, see the Governance Meeting Agenda page.
December 12th Meeting
WHEN December 12th 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's items
- Authorizing SSL certificate renewal (Unknown User (kohsuke))
- Renewing jenkins-ci.org domain (Unknown User (rtyler))
- Website banner usage guideline for people in the events list. (Unknown User (kohsuke))
- like maybe giving automatic 1 week access to future events
- Donation status and what can we do more? (Unknown User (kohsuke))
- Adding Unknown User (larrys) to the admin to combat spam.
November 14th Meeting
WHEN November 14th 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's items
- Balancing personal information of JUC attendees vs cost (Unknown User (kohsuke))
- Forming the Events subgroup in the community for the purpose of coordinating and running event (Unknown User (lisawells)/Unknown User (kohsuke))
- Initial task – define model for user events so we can attract others to run them
- Improve oversight of JUC – define conditions, expectations, involve community
- Streamline approvals for event publications on Jenkins-ci.org, blog, & Twitter
- let this group handle CIA program
- Status of moving Jenkins to java 6 as minimal runtime (Unknown User (ndeloof))
October 31th Meeting
WHEN October 31th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's items
- Take over "Jenkins users and developers" group at meetup.com? (costs $144 per year)
- Check on budget for buying stickers for next year's SCaLE11x and FOSDEM conferences (Unknown User (rtyler))
- Accepting donations in Europe (Unknown User (orrc))
- I spoke to the Euro-friends-of-SPI and it seems we could become affiliated. Would be nice to get working before FOSDEM
October 17th Meeting
WHEN October 17th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's items
- Picking next LTS (Unknown User (vjuranek))
- Advertising survey on http://jenkins-ci.org/ (for 2 more weeks until it closes) (Unknown User (kohsuke))
Jenkins User Conference Meeting @ San Francisco
We'll have the project meeting in the meat-space at Jenkins User Conference San Francisco. While we are still working on logistics, the event will be transcribed to IRC and get broadcasted live. So if you aren't physically in the event, please join us in our usual IRC channel.
WHEN September 30th 18:00 PDT, which should be 9pm EDT, Oct 1st 1am UTC, Oct 1st 10am Tokyo.
Please suggest your agenda. Unlike regular project meetings, order here is irrelevant because we'll decide what to cover before the meeting. Please try to come up with the agenda items that take advantages of unusual audience demographic.
- Discussion about future funding source/plan / fiance report
- What are the pain points? (from 10000ft perspective, not individual bugs or features.)
- What should the development team focus on? Are we working on the right things? (from 10000ft perspective, not individual bugs or features.)
- What are the barriers to participation?
Topic suggestions
who |
suggestion |
first thoughts |
|---|---|---|
Decommissioning "cabbage" and migrating some new services to OSUOSL VMs |
||
Domi |
There are to many plugins doing (nearly) the same, its really hard for users to decide which one fits his need the best |
- although we want to keep the barriers for new participants low, we should not blindly clone every repo. |
Domi |
Think bigger… many features are implemented in a way they work with small to midrange side installations, but when you have 100+ Salves, 1000+ Users, 1000+ Jobs - things get more complicated. e.g.: |
- which plugins are actually in use? how many times? where? |
Domi |
Think security… plugin developers should think about what features compromise security. |
- e.g. blindly providing groovy access to Jenkins internals is a security hole |
Domi |
There is more work done to improve the UI (separate branch): [https://github.com/jenkinsci/jenkins/tree/ui-changes |
- we should reactivate that work |
Tonylampada |
Speaking of funding, please don't forget mention FreedomSponsors |
- If people there have any feedback about the JIRA plugin, or the platform in general, I'm very interested! |
September 19th Meeting
WHEN September 19th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's items
- Discussion about future funding source/plan
- Add more hackers to the SECURITY project to give more visibility/opportunity for security issues to be addressed (Unknown User (rtyler))
- Review survey questions for JUC San Francisco (Lisa Wells)
September 5th Meeting
WHEN September 5th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Should the "Sponsor this issue" link be ommited for closed issues? (Unknown User (tonylampada))
- Discussion about the Board Election Process (Unknown User (kohsuke))
- Help wanted: spams are on the rise (Unknown User (kohsuke))
- FOSDEM travel grant
August 22th Meeting
WHEN August 22nd 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's action items
- Travel grant for FOSDEM? context (Unknown User (rtyler))
August 8th Meeting
WHEN August 8th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Commercial use of the name "Jenkins". Do we need to take any actions? (Unknown User (kohsuke))
- Demoing the FreedomSponsors JIRA plugin - live demo / installation instructions (Unknown User (tonylampada))
- Upcoming event planning and brainstorming link1 link2 (Unknown User (kohsuke)).
- Documentation of jenkins-admin IRC-bot infra, so that community can manage restart. (Unknown User (ndeloof))
July 25th Meeting
WHEN July 25th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Commercial use of the name "Jenkins". Do we need to take any actions? (Unknown User (kohsuke))
- Installing the FreedomSponsors JIRA plugin - when it's finished development. (Unknown User (tonylampada))
July 11th Meeting
WHEN July 11th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's action items
- How much if any advertisement is acceptable on plugin pages (ex. Warnings Plugin) (Unknown User (rtyler))
June 27th Meeting
WHEN June 27th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Baseline for next major LTS release (vjuranek)
June 13th Meeting
WHEN June 13th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Selenium tests, switch to Cucumber/Capybara (vjuranek)
- New home for wiki.jenkins-ci.org (Unknown User (kohsuke))
- maven.jenkins-ci.org to repo.jenkins-ci.org switch voer (Unknown User (kohsuke))
May 30th Meeting
WHEN May 30th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Moving Subversion repository to GitHub Unknown User (kohsuke)
- Improving JonJ and IRC bot stability - JonJ gets stuck very often recently, IRC bot also seems to get stuck when forking repo (vjuranek, unfortunately cannot attend but can offer some help)
- Plugin JonJ on DEV@ or BuildHive Unknown User (jieryn)
May 2nd Meeting
WHEN May 2nd 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's action items
Apr 14th Meeting
WHEN April 14th 04:00 UTC, which should be 13th Fri 9pm PDT, 13th Fri midnight EDT, 14th Sat 5am CEST, 14th Sat 1pm Tokyo.
This is a one off time different from the usual schedule
- Recap last meeting's action items
- JUC Tokyo status updates (Unknown User (ikikko), Unknown User (kohsuke), and others)
- Anything we can do for bridging the Japanese community?
Apr 4th Meeting
WHEN April 4th 18:00 UTC, which should be 11am PDT, 2pm EDT, 8pm CEST, 3am Tokyo.
- Recap last meeting's action items
- Move plugin CI jobs to jenkins.ci.cloudbees.com (Unknown User (ndeloof))
- Proposal : ask for FOSS JProfiler licenses -> http://www.ej-technologies.com/buy/jprofiler/openSource (Unknown User (ndeloof))
- Migrate plugins to get rid of glassfish repo (Unknown User (ndeloof))
Mar 21st Meeting
WHEN March 21st 18:00 UTC, which should be 11am PDT, 2pm EDT, 7pm CET, 3am Tokyo.
- Recap last meeting's action items
- Please sign CLAs (Unknown User (kohsuke))
- Officially launching Jenkins CIA Program (Unknown User (kohsuke))
- "Jenkins@cloud for GitHub" and "Jenkins@cloud by CloudBees" name usage approval (Unknown User (kohsuke))
Mar 7th Meeting
WHEN March 7th 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's action items
- Review current status and plans for The new EMailer (Unknown User (slide.o.mix@gmail.com))
- Last-minute discussion on Google SoC mentors (Unknown User (rtyler))
- Baseline for next major LTS release (vjuranek)
- Cut-over from http://maven.jenkins-ci.org/ to http://repo.jenkins-ci.org/ : PoC demo (Unknown User (kohsuke))
Feb 22nd Meeting
WHEN Feburary 22nd 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's action items
- Proposal: Move away from Drupal to a Git repository powered by Jekyll for the community site (Unknown User (rtyler))
- It's been a year, should we elect a new board, how/when/etc? (Unknown User (rtyler))
- JUC promotion ideas
Feb 8th Meeting
WHEN Feburary 8th 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's action items
- Pull requests and inbound contributor funnel discussion
Jan 25th Meeting
WHEN January 25th 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's action items
- #jenkins IRC status update - @jieryn
- please review Cloaks section of https://wiki.jenkins-ci.org/display/JENKINS/IRC+Channel
- Consider using cloudbees FOSS, http://www.cloudbees.com/foss/ - @jieryn
Jan 11th Meeting
WHEN January 11th 19:00 UTC, which should be 11am PST, 2pm EST, 8pm CET, 4am Tokyo.
- Recap last meeting's action items
- Would it make sense to populate the Affects Version/s and Fix Version/s fields in the Jenkins JIRA (automatically)? (Might include talking about the long pending plan of separating core and plugins in JIRA) (Unknown User (fredg))
- Funding for give-aways in events (stickers and T-shirts)
- Start collecting CLAs


I have seen kaggle mentioned on twitter a lot; mostly by the data scientists and researchers I look up to, but there’s never been much confidence that the site was for me in any way—mostly because I was a long way from my dream data science job with yet so much to learn. Notwithstanding, I cannot help but try and hack my way to my destination! I think it’s a part of my learning process: thrust myself in the midst of something I don’t understand, get stuck, try to get unstuck, finish with some understanding of what I was doing.
So, when I saw this post by Chris Clark, I thought that it was about time I try and hack my way from recently learning Python to machine learning with SciKit-Learn&—why not!?&—I thought.
It reminded me of when I decided to sign up with an account at GitHub; I was initially intimidated because it was new to me. Now, I use git in the command line, host my website there, and use it for almost everything (still learning new things about git everyday as well).
Chris’s post was excellent but there was one problem: the code was aimed at Python 2.7 users and I had just spent the previous semester learning Python 3 (which means I don’t really know 2.7; and avoid it all the time “where are the parens for this print statement??”). As a personal challenge, I decided to use the code and update it to Python 3, which was both fun and challenging (I’m measuring ‘update’ to mean, ‘running in my Python 3.4 interpreter without error messages’). This may be an easy task but there were a few snags for me.
In the spirit of trying to document the things I learn, I’ve decided to chronical my results here&—if there are any errors or issues with this code, please let me know so I can try to correct, learn, and grow! I also found Chris’s updated code on GitHub, which uses Pandas and I’ve been trying to get started with Pandas as well so; win, win.
As an aside, I use Anaconda and Vim for the enviornment and editing, respectively. My code can be found on GitHub.
The Submission was a part of the Predicting a Biological Response competition, and the training, test, and benchmark data sets are provided.
Since the competition wants us to predict binary values, Chris notes that this data set is a good introduction to ensemble classifiers, because the prediction is a binary value (0 or 1). It was also great to take a closer look at both the Pandas and SciKit-Learn’s documentation to troubleshoot. I tried to use the comments to explain as much as possible so future me will not be baffled, which I can say is helpful since I’m looking at this one month out and it makes total sense (at least to me).
### Kaggle Submission Code
"""
//kaggle submission
//Biological Response
--> random forest classifier
Author: Robertmitchellv
Date: Dec 16, 2104
Revised: Dec 22, 2014
"""
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
def main():
# create the training + test sets
try:
data = pd.read_csv('Data/train.csv')
except IOError:
print("io ERROR-->Could not locate file.")
target = data.Activity.values
train = data.drop('Activity', axis = 1).values
test = pd.read_csv('Data/test.csv').values
# create and train the random forest and call it 'rf'
# --> n_estimators = the number of trees in this forest, viz.
# 100 trees of forest
# --> n_jobs set to -1 will use the number of cores present on your system.
rf = RandomForestClassifier(n_estimators = 100, n_jobs = -1)
# fit(X, y[, sample_weight]) = build a forest of tress from the
# training set (X, y)
rf.fit(train, target)
# predict_proba(X) predict class probabilities for X as list
predicted_probs = [x[1] for x in rf.predict_proba(test)]
# prep data for use in pd.Series
molID, predictProbs = prepData(predicted_probs)
# use a dictionary with keys as col headers and values as lists pulled from
# previous prep function
df = {'MoleculeID': molID, 'PredictedProbability': predictProbs}
# pandas DataFrame = a tabular datastructure like a SQL table
predicted_probs = pd.DataFrame(df)
# write predicted_probs to file with pandas method .to_csv()--add header
# for submission
try:
predicted_probs.to_csv('Data/submission.csv', index = False)
print("File successfully written; check 'Data' folder")
except IOError:
print("io ERROR-->Could not write data to file.")
# preparing data for conversion to pd.DataFrame
def prepData(alist):
# prepare list to be converted to pandas Series
colOne = []
colTwo = []
idx = 1
# for loop to set MoleculeID to match the benchmark;
# place values into list for easier wrangling as pd.Series
for i in alist:
colOne.append(idx)
colTwo.append(i)
idx += 1
return colOne, colTwo
# call the main function
main()
After performing this–Chris suggested to submit to kaggle; being an extra careful person by nature, I just had to perform the evaluation and cross validation first (I don’t know if any of you feel the same way). Unfortunately, I don’t really understand how the code works–this is one of the problems when hacking through tutorials.
### Evaluation/Logloss
"""
//kaggle submission
//Biological Response
--> evaluation function (from Grunthus' post)
"""
import scipy as sp
def logloss(act, pred):
""" Vectorised computation of logloss """
#cap in official Kaggle implementation,
#per forums/t/1576/r-code-for-logloss
epsilon = 1e-15
pred = sp.maximum(epsilon, pred)
pred = sp.minimum(1-epsilon, pred)
#compute logloss function (vectorised)
ll = sum( act*sp.log(pred) +
sp.subtract(1,act)*sp.log(sp.subtract(1,pred)))
ll = ll * -1.0/len(act)
return ll
The cross validation was trickier to understand, which I think is mostly due to my not really understanding what ensemble classifiers do, how the random forest classifier works, and more specifically; what training, test, and target data do within machine learning. This gave chase through the SciKit-Learn documentation and other resources online to get a better understanding of what the code was doing&—there’s a lot to learn! The interesting aspect is how the SciKit-Learn reserves some actual data that it can test against the classifier’s predicted values. I tried to show in the comments how I was understanding what the code did at the time.
### Cross Validation
"""
//kaggle submission
//Biological Response
--> cross validation
"""
from sklearn.ensemble import RandomForestClassifier
from sklearn.cross_validation import KFold
import numpy as np
import pandas as pd
import logloss
def main():
#read data from csv; use nparray to create the training + target sets
try:
train = pd.read_csv('Data/train.csv')
except IOError:
print("io ERROR-->Could not locate file.")
target = np.array([x[0] for x in train])
train = np.array([x[1:] for x in train])
# in this case we'll use a random forest, but this could be any classifier
model = RandomForestClassifier(n_estimators = 100, n_jobs = -1)
# simple K-Fold cross validation. 10 folds.
cv = KFold(n = len(train), n_folds = 10, indices = False)
#iterate through the training and test cross validation segments and
#run the classifier on each one, aggregating the results into a list
results = []
for traincv, testcv in cv:
prob = model.fit(train[traincv], target[traincv]).predict_proba(train[testcv])
results.append(logloss.llfun(target[testcv], [x[1] for x in prob]))
#print out the mean of the cross-validated results
print('Results: ', str(np.array(results).mean()))
# call main function
main()
After I was able to execute the submission, logloss, and cross validation code without any errors, I submitted my code to kaggle. It was an exciting moment waiting to see what kind of score I would have recieved had I actually participated in the competition. I would have placed at 325 (well, I would have tied with another user for 325th); check out my results below.
Well, that wraps up my first submission to kaggle. I really hope this is the first of many. Right now I’m working through the Think Stats + Think Bayes books to refresh my stats knowledge. I’m trying to find time to work on the Titanic tutorial through kaggle as well as perhaps throw a hat in the ring for Booz Hamilton’s Data Science Bowl. There’s so much to learn and I can’t wait for these concepts to become more natural and familiar.


{% extends "base.html" %} {% block content %}
Here you can configure the applications security preferences and the IDP information.


I succeeded to have inputs in Emoncms.org as shown below. However, after I reviewed all docs, i am still confused.
The following is I quoted from Jerome's reply :"Instead of using a OemGatewayRFM2PiListener, you'll use a OemGatewaySerialListener. The only parameter is the COM port.
Make sure that the TX formats the data like this:
NodeID val1 val2
NodeID val1 val2
Example for temperature and relative humidity fluctuating around 19°C and 60%:
12 19.2 60.1
12 19.5 60.0
12 19.3 60.4"
But, I didn't find any place to add something like "NodeID val1 val2" in my emonTX V3 sketch - "emonTxV3_DirectSerial.ino".
All docs show the default node ID for emonTX is 10, but I get 0. I don't know where this 0 comes from.
One more question, how to check the output from emonTX V3 by using Arduino IDE + USB-to-UART programmer?
Re: What is the node ID if using direct serial connection
If you are using the emonTxV3_DirectSerial.ino sketch, you can add a node id quite easily by inserting a new line (at line 17)
and another new line (at line 68) before the values print,
to see the serial output via the programmer lead you need to have the arduino ide installed then just select tools -> serial monitor, (you may also need to set the baud to 9600) after selecting the correct serial port and board etc which I'm guessing you've done if you can upload sketches.
Paul
Re: What is the node ID if using direct serial connection
Thank you, Paul
It works now.


Search the named access table for the sender name, domains, address, or networks obtained by stripping least significant octets.
The access_map_reject_code parameter specifies the response code for REJECT results (default: 550).


Uncanny Valley
do not be afraid
there is nothing to fear
start but no end
the end is only ours
just lend in the ,,, .. ,,, .. ,,,, . and so
1.
2. GIVE IN YOUR SOUL
Accept join agreement


{% extends 'core/base.html' %} {% load static %} {% block content %}
The following jobs were used as direct input for this {{ cjob.job.job_type_family }} type.
| Input Job Name | Job Type Family | Job Type | Record Count |
|---|---|---|---|
| {{ input_job.input_job.name }} | {{ input_job.input_job.job_type_family }} | {{ input_job.input_job.job_type }} | {{ input_job.input_job.record_count }} |
| Total: | {{ record_count_details.input_jobs.total_input_records }} |
The following table shows details about input records, successes, and failures. Below that is a table with all records and errors for this job, searchable and sortable.
| Job Name | Job Type Family | Job Type | Total Input Records | Sucesssful Records | Errors | Success Percentage |
|---|---|---|---|---|---|---|
| {{ cjob.job.name }} | {{ cjob.job.job_type_family }} | {{ cjob.job.job_type }} | {{ record_count_details.input_jobs.total_input_records }} | {{ record_count_details.records }} | {{ record_count_details.errors }} | {{ record_count_details.success_percentage }} |
The following validation scenarios were run for this job:
| Validation Name | Validation Type | Record Validation Failure Count | Actions |
|---|---|---|---|
| {{ jv.validation_scenario.name }} | {{ jv.validation_scenario.validation_type }} | {{ jv.validation_failure_count }} | {% if jv.validation_failure_count > 0 %}See Failures{% endif %} |
To get a sense of how fields are used and distributed across a job, each record is mapped to a flat representation of its metadata, and then indexed in ElasticSearch. The field names should suggest that corresponding metadata field from the original XML.
| Total records for indexing | Indexed | Percentage of total records | Actions |
|---|---|---|---|
| {{ record_count_details.records }} | {{ field_counts.total_docs }} | {{ field_counts.indexed_percentage }} | Browse Index / View Errors |


{% load static %}
Installing the Cannlytics Engine into your lab is as easy as 1, 2, 3. You can simply use an installer or you can clone the source code and follow the included guides. You can quickly configure your installation to perfectly fit your lab.
git clone https://github.com/cannlytics/cannlytics.git
Once you have your copy of Cannlytics, you can pick and choose engine components as you need them. Perhaps you need an addition to your existing software. Simply grab what you need and you're free to use it.
from cannlytics import lims
result = lims.get_lab_results(lab_id="xyz")
If you need a hosted solution, then you can take advantage of the ready to use Cannlytics Portal for hosting, analysis, and data and file storage. You can manage your lab results and provide your clients with a simple yet complete client portal.
Do you have a technical staff? Than you can utilize the Cannlytics API to programmatically manage your operations and interface with your data. You have all of your data and the power of all laboratory software at your finger tips.
{
analyses: [...],
lab_id: "cann 001",
sample_name: "Super Easy",
results: [...],
}


Class KHRCreateContext
- java.lang.Object
-
- org.lwjgl.egl.KHRCreateContext
-
public final class KHRCreateContext extends java.lang.Object
Native bindings to the KHR_create_context extension.With the advent of new versions of OpenGL which deprecate features and/or break backward compatibility with older versions, there is a need and desire to indicate at context creation which interface will be used. This extension adds a new context creation routine with attributes specifying the OpenGL version, context properties, and profile requested for the context. It also allows making an OpenGL 3.0 or later context (or other client API context supporting the ability) current without providing a default framebuffer. The new context creation attributes are also defined to work for OpenGL ES context creation when that makes sense, and the extension has been augmented to allow configs to advertise support for creating OpenGL ES 3.0 contexts.
Requires
EGL L.1
.
-
-
Field Summary
-
-
-
Field Detail
-
EGL_CONTEXT_MAJOR_VERSION_KHR
public static final int EGL_CONTEXT_MAJOR_VERSION_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_MINOR_VERSION_KHR
public static final int EGL_CONTEXT_MINOR_VERSION_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_FLAGS_KHR
public static final int EGL_CONTEXT_FLAGS_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_OPENGL_PROFILE_MASK_KHR
public static final int EGL_CONTEXT_OPENGL_PROFILE_MASK_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_OPENGL_RESET_NOTIFICATION_STRATEGY_KHR
public static final int EGL_CONTEXT_OPENGL_RESET_NOTIFICATION_STRATEGY_KHR
- See Also:
- Constant Field Values
-
EGL_NO_RESET_NOTIFICATION_KHR
public static final int EGL_NO_RESET_NOTIFICATION_KHR
- See Also:
- Constant Field Values
-
EGL_LOSE_CONTEXT_ON_RESET_KHR
public static final int EGL_LOSE_CONTEXT_ON_RESET_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_OPENGL_DEBUG_BIT_KHR
public static final int EGL_CONTEXT_OPENGL_DEBUG_BIT_KHR
- See Also:
- Constant Field Values
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EGL_CONTEXT_OPENGL_FORWARD_COMPATIBLE_BIT_KHR
public static final int EGL_CONTEXT_OPENGL_FORWARD_COMPATIBLE_BIT_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_OPENGL_ROBUST_ACCESS_BIT_KHR
public static final int EGL_CONTEXT_OPENGL_ROBUST_ACCESS_BIT_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_OPENGL_CORE_PROFILE_BIT_KHR
public static final int EGL_CONTEXT_OPENGL_CORE_PROFILE_BIT_KHR
- See Also:
- Constant Field Values
-
EGL_CONTEXT_OPENGL_COMPATIBILITY_PROFILE_BIT_KHR
public static final int EGL_CONTEXT_OPENGL_COMPATIBILITY_PROFILE_BIT_KHR
- See Also:
- Constant Field Values
-
EGL_OPENGL_ES3_BIT
public static final int EGL_OPENGL_ES3_BIT
- See Also:
- Constant Field Values
-
EGL_OPENGL_ES3_BIT_KHR
public static final int EGL_OPENGL_ES3_BIT_KHR
- See Also:
- Constant Field Values
-
-


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Configuring IntelliJad
There are two levels of configuration in IntelliJad - IDE-level, and project-level. Both
are accessible via the settings panel, in the relevant sections.
The IDE-level configuration persists across multiple projects, and is the most useful place
to set up IntelliJad. In here, you can for instance define automatic decompilation to memory
and then never have to change the settings to have this type of decompilation occur
in all your projects.
Project-level decompilation applies only to the current project.


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Yes, I know how crazy it is that you have to find an old Windows machine to update a brand new KL25Z. Unfortunately, the factory firmware installed on new KL25Z boards was written when Windows 7 was current, and Microsoft made changes in Windows 8 that are incompatible with that old firmware.
Once you complete the upgrade, the KL25Z will work with Windows 8 and later. But it's a catch-22, because you can't perform the upgrade that makes it work with Windows 8 or 10 from Windows 8 or 10!
The easiest way to deal with this is to find an old machine running Windows 7 or XP. But if there's no way you can do that, there are two solutions. Both require some extra work, but they'll let you do the upgrade with your existing machine.
The firmware incompatibility in Windows 8+ is related to the disk search features that Microsoft added in Windows 8. When you plug in a USB disk, Windows automatically writes to the disk to create a hidden search index file. The older KL25Z boot loader mistakes this for an attempt to install new firmware onto the device. But since the index file isn't a valid firmware file, the boot loader rejects it, which puts it in an error mode where it refuses to accept any more requests. This blocks any subsequent attempts to download legitimate firmware files.
One way to solve this is to disable the Windows search indexing service that causes the trouble. This requires messing around with your Windows system settings, so if RegEdit makes you queasy, you might want to skip this approach and try a different option.
This method was first described (as far as I know) by Erich Styger on his MCU on Eclipse blog. Please see that article for a more thorough explanation.
Here are the steps:
Now you're ready to attempt the firmware upgrade on the KL25Z. Be warned, though: you have to do the file copy as quickly as possible after plugging in the KL25Z. Apparently, the steps above prevent Windows from writing the drive right after you plug it in, but Windows might still try to do a write if you leave the drive plugged in long enough. So you should try to move quickly.
Other than this race against time, the upgrade itself works just like in the main instructions.
You can now verify the upgrade. Plug the programming port back in (without pressing the Reset button). The KL25Z thumb drive should appear. Open the file SDA_INFO.HTM. Check that the reported firmware version matches what you just downloaded.
If you don't want to make the changes to your system settings described above, or you can't get that approach to work, you can solve the upgrade problem by running a virtual copy of XP or Windows 7 on your existing operating system. This approach is fairly complicated, but it doesn't require any changes to your system settings and doesn't require any special timing.
The first thing you should do is print out the instructions that the Pinscape config tool displays for doing the firmware update. The config tool won't run on XP. That's okay, because the config tool doesn't really do anything during the update process anyway except display the instructions. But you can't run it to view the instructions in XP, so you'll want to have a copy handy before you start. To do this, go to the "Set up a new KL25Z" page, click past the warning about Windows versions, then click "Show All". You can now print the page (there's a button at the bottom to do this). If you have a two-monitor setup, no need to print; just leave the instructions on one screen while you run the XP VM on the other screen.
The next step is to download and install VirtualBox, which is a free Virtual Machine manager. Start here: virtualbox.org. Download the latest version and go through the setup procedure to install the product on your computer.
Now we get to the really time-consuming and difficult part. You need to create an XP or Win 7 VM for VirtualBox.  Wait for the VM to shut down. The VM window will close when it's done.
Now go back to the VirtualBox VM manager window. Right-click the VM in the list and select Settings. In the Settings window, select the USB page. There should be a checkbox at the top labeled "Enable USB Controller". Make sure it's checked.
Plug in the KL25Z via the programming port. Click the "+" button next to the "USB Device Filters" list. You should see an entry in the pop-up list starting with "PE Microcomputer Systems Inc". That's the KL25Z programming port. Click it to add it to the list. Click OK.
Unplug the KL25Z.
Launch the VM by double-clicking it. Wait for it to finish booting. The XP/Win 7 desktop window should be showing and the disk should be done grinding away at startup tasks. Now plug in the KL25Z. If all went well, it should appear on the XP/7 desktop and not on your real Windows desktop.
Now get out that printout we made back at the beginning of this whole mess! Follow the instructions to download and install the first .SDA file within the XP/7 box.
At this point in the printed instructions, you'll be asked to unplug and re-plug the KL25Z. Things get a little hazy here. You might need to add a new VirtualBox USB filter. Try re-plugging the KL25Z and see which desktop it connects to. If it connects to the XP/7 desktop, all is good. If it connects to your regular Windows desktop, go to the USB device menu in the VirtualBox controls, find the un-checked "PE Microcomputer Systems" item, and check it. After you check it, unplug the KL25Z and plug it back in. This time it will hopefully connect to the XP/7 desktop rather than your ordinary desktop. If not, you might have to shut down the VM and repeat the USB Filter process we did earlier from the VirtualBox Settings dialog.
Once you get through the whole procedure within the XP/7 VM, disconnect the KL25Z and shut down the VM (Use "Turn off computer" from the Start menu within the VM window, and wait for the VM window to close). Now plug the KL25Z back in, via the programming port.
If all went well, you should have a drive on your Windows desktop labeled FRDM-KL25Z. The drive label is very important. If it's FRDM-KL25Z, everything worked and the device should be ready to use in your modern Windows version! If the label isn't FRDM-KL25Z, something must have gone wrong somewhere along the way. Try going back through the process above again. If you can't get it to work after carefully repeating all the steps, post on vpforums.org and hopefully I or someone else will be able to help you troubleshoot.


VA operates the nation's largest integrated health care system, with more than 1,700 hospitals, clinics, community living centers, domiciliaries, readjustment counseling centers, and other facilities.
VA administers a variety of benefits and services that provide financial and other forms of assistance to Servicemembers, Veterans, their dependents and survivors.
VA operates 135 national cemeteries in the U.S. and Puerto Rico. Burial and memorial benefits are available for eligible service members, Veterans, and family members.


--- layout: post title: Roof fight date: '2018-02-06T11:30:24+01:00' categories: - Storyboards - Sketches picture_url: https://film-Storyboards.tumblr.com/post/170578996264 ---


Like many Open Source packages, Mapserver relies on external libraries to handle much of the heavy lifting. This is both a good thing and a bad thing. The good thing is that the Mapserver folks don't have to program all the needed functionality, the bad thing is that you can reach dependency-hell with this setup. For our purposes, we will only build with Proj.4 support, but you can rebuild mapserver later to link with other libraries for more functionality.
Proj.4 provides projection and reprojection support for Mapserver. Building and installing is hopefully simple, if you have ever built an open source package before. Make sure that /usr/local/lib is included in /etc/ld.so.conf, so that Mapserver can link to that library without special configuration.
$ wget ftp://ftp.remotesensing.org/pub/proj/proj-4.4.8.tar.gz
$ tar -zxvf proj-4.4.8.tar.gz
$ cd proj-4.4.8
$ ./configure; make
$ su -l
# make install #(as root, to install in /usr/local!)
# /sbin/ldconfig
# exit
$ make clean
If everything went well, you should notice a libproj in /usr/local/lib that mapserver can link to.
As I write this (28 Jul 2004), Mapserver is at version 4.2.1 . It is preferable that you be running this version for this HOWTO, but it is not required. For our purposes, the only difference between the current version 4.2.1 and the old 3.6.x versions is the 'OFFSITE' keyword in the .map file. In Mapserver 4.x, this is a RGB value and in Mapserver 3.x, this is a color map index value.
$ wget http://cvs.gis.umn.edu/dist/mapserver-4.2.1.tar.gz
$ tar -zxvf mapserver-4.2.1.tar.gz
$ cd mapserver-4.2.1
$ ./configure --with-proj --with-png
$ make
$ cp -i mapserv /var/www/cgi-bin/mapserv
Now, if the build process worked, you should have a binary called 'mapserv' if your current working directory. Verify that the mapserv binary is okay by executing
$ ./mapserv -v
This command will spit out the capabilities of Mapserver. For this demo,
we need support for SHAPEFILES and the TIFF file format. The output from the
above command should contain OUTPUT=PNG INPUT=TIFF INPUT=SHAPEFILE.
If you got this far with these instructions, you are much smarter than I am. Since I couldn't even get this to work following my own instructions. Anyway, we now have a CGI application that we can install on our webserver and begin building a web mapping application! Yeah!


--- title: "The Garden Misses You" date: "2020-04-22 00:00:00 -06:00" categories: - whats-blooming layout: "post" blog-banner: "whats-blooming-now-spring.jpg" post-date: "April 22, 2020" post-time: "12:00 PM" blog-image: "2020-04-22-wbn.jpg" published: true ---
While it is beautiful and peaceful in the Garden right now, there is one thing obviously missing... Your presence. And it leaves a large hole in the Garden's heart. We know you miss the Garden too, so this will be a longer post for your viewing pleasure.
Here is an occasional Tulip you might see in the Garden. We don't have many because the squirrels love to eat them.
This ground level plant can be easy to miss when not in bloom.
If you are ever near this plant and smell a skunk, chances are it might be this flower.
Another Tulip! This Tulip is growing in the Water Conservation Garden.
These flowers are tiny but in mass plantings they sure do stand out.
I like big buds! This is a leaf bud about to open up.
Most of what you see here, with the daisy-like purple and white flowers, are Windflower. The taller, white-flowered clump is Roundlobe Hepatica.
As seen in the Water Conservation Garden. A personal favorite of mine because it keeps its cool all year round.
Between the wonderfully fragrant smell of these Blireana Plum blossoms (Prunus x blireana) and the stunning scene, I think I'll stand here for a while.
I have no words for how cute these are. They are growing in the Herb Garden.
Take care of yourselves and we look forward to having your presence in the Garden again.


10 February 1998
Disease Outbreak Reported
Up to 7 February a total of 193 cases with 8 deaths (CFR 4.14%) had been reported on Grande Comore Island. Although the first cases were recorded in Mbéni, 77 of the 193 cases have occurred in Moroni and 12 districts and villages in and around the capital.
Measures to prevent further spread and for the effective treatment of cases have been implemented by the cholera task force which was recently set-up by the Ministry of Health and WHO.


Welcome to LivingSocial's Documentation.
Update Recommendations for the resource page can be viewed at the link here.
New Recommendations for the feed itself can be found here.
Competitor Overview
Current Monocle Page
- Basic single-page documentation
- Goes over basic queries and formatting of queries and returns
- No Q&A section, personalization
Groupon Partner Page
- Overview includes intro, link guide, payments, FAQ, and terms of use
- API documentation includes branding, deal API, and division API
- Has two versions of reporting (newer one is more extensive)
Gilt Documentation Page
- Requires users to sign in with login information
- Documentation defines terminology which I believe may be helpful
- Has a playground feature that allows users to test API calls
- Public disscussion board on Google Groups that allows for public Q&A. Could be useful
- Custom codecademy course that teaches users how to use the Gilt API
- Three
Current Recommendations
- Have a resource page with complete documentation, FAQ, and contact information
- Include concrete examples of queries and return types
- Test.
Future Steps


--- title: An Interview Question on Statistics author: Chunji Wang date: '2018-07-02' slug: an-interview-question-on-statistics categories: [] tags: - statistics comments: no showcomments: yes showpagemeta: yes description: "How many draws are needed to paint M balls red in N white balls?" ---
The question is provided by Yueyan Wang. The two solutions are provided by Yueyan Wang and Rongpeng Li
一个箱子里有N个白色的球，每次从中随机抽取一个。 如果球是白色的，则涂成红色后放回去； 如果抽到已经涂成红色的球，就直接放回去，再抽。 如此重复，直到M个球涂成红色。 请问一共需要抽取多少回？
The events of painting each ball are independent events from eath other. Therefore we can calculate the expectation of number of draws associated with each red ball, and take a sum.
 To paint the \((m+1)\)-th white ball, there is \(m/N\) chance that we pick one of the red balls, in which case we need to draw again; there is \(\frac{N-m}{N}\) chance that we pick one of the white balls, in which case we don’t need to draw anymore. So the probability of drawing \(i\) times is \[ \Big(\frac{m}{N}\Big)^{i - 1} \frac{N-m}{N} \] So the expectation number of draws to paint the \((m + 1)\)-th ball is \[ \frac{N-m}{N} \sum_{i = 1}^\infty i\Big(\frac{m}{N}\Big)^{i - 1} = \frac{N}{N-m} \] Then the total number of draws should be \[ T(M) = \sum_{m=0}^{M-1} \frac{N}{N-m} \]
Assume we know \(T(m)\), how do we get \(T(m+1)\)? After \(m\) balls are painted red, the next draw have two possibilities:
So, \[ T(m+1) = \frac{N-m}{N}(1+T(m)) + \frac{m}{N}(1 + T(m+1)) \\ = 1 + \frac{N-m}{N}T(m) + \frac{m}{N}T(m+1) \] This is essentially \[ T(m + 1) = T(m) + \frac{N}{N-m} \] Which is the same as Method 1.


The Helperbit platform is unable to connect to the device; please be sure to connect the device, unlock with the pin and select the Bitcoin app.


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My dataset is part of a dataset created by the population division of the United Nations Department of Economic and Social Affairs. 'Part of' because I decided to scale it down to make it more manageable for the course, which introduces issues of subjectivity and uncertainty, though I have tried to be geographically fair!
The dataset is interesting in many ways; Comparing how populations have changed over the last 65 years to what they're predicted to over the next 85; the differences between population patterns in countries around the world. It is always interesting to see what further 'truth' a dataset can reveal, and how you can best communicate that truth
As someone new to coding I've encountered a few tricky moments so thanks to everyone on the forum who's helped me out!
Looking forward to next week