| Class | Description |
|---|---|
| CUSIP_00206RCP5 |
CUSIP_00206RCP5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 00206RCP5.
|
| CUSIP_010632MT1 |
CUSIP_010632MT1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 010632MT1.
|
| CUSIP_010632MU8 |
CUSIP_010632MU8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 010632MU8.
|
| CUSIP_010632MV6 |
CUSIP_010632MV6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 010632MV6.
|
| CUSIP_013822AB7 |
CUSIP_013822AB7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 013822AB7.
|
| CUSIP_015271AC3 |
CUSIP_015271AC3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 015271AC3.
|
| CUSIP_02765UDB7 |
CUSIP_02765UDB7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 02765UDB7.
|
| CUSIP_032452BE3 |
CUSIP_032452BE3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 032452BE3.
|
| CUSIP_033636CL3 |
CUSIP_033636CL3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 033636CL3.
|
| CUSIP_03674PAL7 |
CUSIP_03674PAL7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 03674PAL7.
|
| CUSIP_03674XAF3 |
CUSIP_03674XAF3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 03674XAF3.
|
| CUSIP_037833BW9 |
CUSIP_037833BW9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 037833BW9.
|
| CUSIP_038222AK1 |
CUSIP_038222AK1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 038222AK1.
|
| CUSIP_03834AAA1 |
CUSIP_03834AAA1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 03834AAA1.
|
| CUSIP_04015CAA6 |
CUSIP_04015CAA6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 04015CAA6.
|
| CUSIP_04048RLN4 |
CUSIP_04048RLN4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 04048RLN4.
|
| CUSIP_050625CN0 |
CUSIP_050625CN0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 050625CN0.
|
| CUSIP_05565QDF2 |
CUSIP_05565QDF2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 05565QDF2.
|
| CUSIP_06652KAA1 |
CUSIP_06652KAA1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 06652KAA1.
|
| CUSIP_085209AD6 |
CUSIP_085209AD6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 085209AD6.
|
| CUSIP_10727YAU0 |
CUSIP_10727YAU0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 10727YAU0.
|
| CUSIP_112585AH7 |
CUSIP_112585AH7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 112585AH7.
|
| CUSIP_11271LAA0 |
CUSIP_11271LAA0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 11271LAA0.
|
| CUSIP_118230AN1 |
CUSIP_118230AN1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 118230AN1.
|
| CUSIP_118230AQ4 |
CUSIP_118230AQ4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 118230AQ4.
|
| CUSIP_120462AA4 |
CUSIP_120462AA4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 120462AA4.
|
| CUSIP_12505BAD2 |
CUSIP_12505BAD2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 12505BAD2.
|
| CUSIP_12508EAD3 |
CUSIP_12508EAD3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 12508EAD3.
|
| CUSIP_12665UAA2 |
CUSIP_12665UAA2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 12665UAA2.
|
| CUSIP_13063BFV9 |
CUSIP_13063BFV9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 13063BFV9.
|
| CUSIP_13063BJB9 |
CUSIP_13063BJB9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 13063BJB9.
|
| CUSIP_13281KTT5 |
CUSIP_13281KTT5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 13281KTT5.
|
| CUSIP_13281KTV0 |
CUSIP_13281KTV0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 13281KTV0.
|
| CUSIP_153527AL0 |
CUSIP_153527AL0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 153527AL0.
|
| CUSIP_18085PLL6 |
CUSIP_18085PLL6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 18085PLL6.
|
| CUSIP_19668QDZ5 |
CUSIP_19668QDZ5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 19668QDZ5.
|
| CUSIP_20030NBP5 |
CUSIP_20030NBP5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 20030NBP5.
|
| CUSIP_203233AA9 |
CUSIP_203233AA9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 203233AA9.
|
| CUSIP_205759GX5 |
CUSIP_205759GX5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 205759GX5.
|
| CUSIP_22822RBD1 |
CUSIP_22822RBD1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 22822RBD1.
|
| CUSIP_23311VAB3 |
CUSIP_23311VAB3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 23311VAB3.
|
| CUSIP_251130ED8 |
CUSIP_251130ED8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 251130ED8.
|
| CUSIP_251130EZ9 |
CUSIP_251130EZ9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 251130EZ9.
|
| CUSIP_251256CB7 |
CUSIP_251256CB7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 251256CB7.
|
| CUSIP_25389JAH9 |
CUSIP_25389JAH9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 25389JAH9.
|
| CUSIP_25389JAQ9 |
CUSIP_25389JAQ9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 25389JAQ9.
|
| CUSIP_26884UAA7 |
CUSIP_26884UAA7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 26884UAA7.
|
| CUSIP_283734NQ0 |
CUSIP_283734NQ0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 283734NQ0.
|
| CUSIP_29336UAB3 |
CUSIP_29336UAB3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 29336UAB3.
|
| CUSIP_299620EW0 |
CUSIP_299620EW0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 299620EW0.
|
| CUSIP_30190QAA7 |
CUSIP_30190QAA7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 30190QAA7.
|
| CUSIP_3130A6VH7 |
CUSIP_3130A6VH7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3130A6VH7.
|
| CUSIP_3130A73V5 |
CUSIP_3130A73V5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3130A73V5.
|
| CUSIP_3130A7AL9 |
CUSIP_3130A7AL9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3130A7AL9.
|
| CUSIP_3130A7AY1 |
CUSIP_3130A7AY1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3130A7AY1.
|
| CUSIP_3130A8M75 |
CUSIP_3130A8M75 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3130A8M75.
|
| CUSIP_3130A96V8 |
CUSIP_3130A96V8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3130A96V8.
|
| CUSIP_3133EDR95 |
CUSIP_3133EDR95 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EDR95.
|
| CUSIP_3133EDUA8 |
CUSIP_3133EDUA8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EDUA8.
|
| CUSIP_3133EF3G0 |
CUSIP_3133EF3G0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EF3G0.
|
| CUSIP_3133EF4M6 |
CUSIP_3133EF4M6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EF4M6.
|
| CUSIP_3133EF4X2 |
CUSIP_3133EF4X2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EF4X2.
|
| CUSIP_3133EFKT3 |
CUSIP_3133EFKT3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFKT3.
|
| CUSIP_3133EFQM2 |
CUSIP_3133EFQM2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFQM2.
|
| CUSIP_3133EFTS6 |
CUSIP_3133EFTS6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFTS6.
|
| CUSIP_3133EFUX3 |
CUSIP_3133EFUX3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFUX3.
|
| CUSIP_3133EFUY1 |
CUSIP_3133EFUY1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFUY1.
|
| CUSIP_3133EFV61 |
CUSIP_3133EFV61 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFV61.
|
| CUSIP_3133EFWJ2 |
CUSIP_3133EFWJ2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFWJ2.
|
| CUSIP_3133EFXD4 |
CUSIP_3133EFXD4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFXD4.
|
| CUSIP_3133EFYE1 |
CUSIP_3133EFYE1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFYE1.
|
| CUSIP_3133EFYL5 |
CUSIP_3133EFYL5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EFYL5.
|
| CUSIP_3133EGAK1 |
CUSIP_3133EGAK1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EGAK1.
|
| CUSIP_3133EGCS2 |
CUSIP_3133EGCS2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EGCS2.
|
| CUSIP_3133EGHJ7 |
CUSIP_3133EGHJ7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EGHJ7.
|
| CUSIP_3133EGKV6 |
CUSIP_3133EGKV6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3133EGKV6.
|
| CUSIP_3134G4GW2 |
CUSIP_3134G4GW2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3134G4GW2.
|
| CUSIP_3134G96R3 |
CUSIP_3134G96R3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3134G96R3.
|
| CUSIP_3134GAER1 |
CUSIP_3134GAER1 demonstrates EOS Fixed/Float Coupon Multi-flavor Pricing and Relative Value Measure
Generation for CUSIP 3134GAER1.
|
| CUSIP_3136G0W23 |
CUSIP_3136G0W23 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3136G0W23.
|
| CUSIP_3136G2ZM2 |
CUSIP_3136G2ZM2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3136G2ZM2.
|
| CUSIP_3136G3L29 |
CUSIP_3136G3L29 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 3136G3L29.
|
| CUSIP_31620MAR7 |
CUSIP_31620MAR7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 31620MAR7.
|
| CUSIP_340711AW0 |
CUSIP_340711AW0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 340711AW0.
|
| CUSIP_355514MD9 |
CUSIP_355514MD9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 355514MD9.
|
| CUSIP_36162JAA4 |
CUSIP_36162JAA4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 36162JAA4.
|
| CUSIP_36164YAA9 |
CUSIP_36164YAA9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 36164YAA9.
|
| CUSIP_375558BG7 |
CUSIP_375558BG7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 375558BG7.
|
| CUSIP_378460TM1 |
CUSIP_378460TM1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 378460TM1.
|
| CUSIP_378460TP4 |
CUSIP_378460TP4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 378460TP4.
|
| CUSIP_378460TS8 |
CUSIP_378460TS8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 378460TS8.
|
| CUSIP_378460TX7 |
CUSIP_378460TX7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 378460TX7.
|
| CUSIP_402740AD6 |
CUSIP_402740AD6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 402740AD6.
|
| CUSIP_40434JAD2 |
CUSIP_40434JAD2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 40434JAD2.
|
| CUSIP_40537QAH3 |
CUSIP_40537QAH3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 40537QAH3.
|
| CUSIP_406216BJ9 |
CUSIP_406216BJ9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 406216BJ9.
|
| CUSIP_413890EQ3 |
CUSIP_413890EQ3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 413890EQ3.
|
| CUSIP_413890ES9 |
CUSIP_413890ES9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 413890ES9.
|
| CUSIP_42217KBC9 |
CUSIP_42217KBC9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 42217KBC9.
|
| CUSIP_42809HAG2 |
CUSIP_42809HAG2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 42809HAG2.
|
| CUSIP_428291AM0 |
CUSIP_428291AM0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 428291AM0.
|
| CUSIP_432272DP4 |
CUSIP_432272DP4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 432272DP4.
|
| CUSIP_432272DR0 |
CUSIP_432272DR0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 432272DR0.
|
| CUSIP_440327AK0 |
CUSIP_440327AK0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 440327AK0.
|
| CUSIP_44106MAR3 |
CUSIP_44106MAR3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 44106MAR3.
|
| CUSIP_44106MAS1 |
CUSIP_44106MAS1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 44106MAS1.
|
| CUSIP_44106MAT9 |
CUSIP_44106MAT9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 44106MAT9.
|
| CUSIP_44106MAV4 |
CUSIP_44106MAV4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 44106MAV4.
|
| CUSIP_448055AJ2 |
CUSIP_448055AJ2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 448055AJ2.
|
| CUSIP_448055AK9 |
CUSIP_448055AK9 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 448055AK9.
|
| CUSIP_448579AD4 |
CUSIP_448579AD4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 448579AD4.
|
| CUSIP_45656TBP2 |
CUSIP_45656TBP2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 45656TBP2.
|
| CUSIP_45656TBQ0 |
CUSIP_45656TBQ0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 45656TBQ0.
|
| CUSIP_45656TCK2 |
CUSIP_45656TCK2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 45656TCK2.
|
| CUSIP_45672NAG6 |
CUSIP_45672NAG6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 45672NAG6.
|
| CUSIP_47102XAJ4 |
CUSIP_47102XAJ4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 47102XAJ4.
|
| CUSIP_47232MAA0 |
CUSIP_47232MAA0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 47232MAA0.
|
| CUSIP_472682QU0 |
CUSIP_472682QU0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 472682QU0.
|
| CUSIP_472682QW6 |
CUSIP_472682QW6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 472682QW6.
|
| CUSIP_48203RAJ3 |
CUSIP_48203RAJ3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 48203RAJ3.
|
| CUSIP_487526AA3 |
CUSIP_487526AA3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 487526AA3.
|
| CUSIP_488401AB6 |
CUSIP_488401AB6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 488401AB6.
|
| CUSIP_489399AG0 |
CUSIP_489399AG0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 489399AG0.
|
| CUSIP_494787DF8 |
CUSIP_494787DF8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 494787DF8.
|
| CUSIP_496902AJ6 |
CUSIP_496902AJ6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 496902AJ6.
|
| CUSIP_514014MB2 |
CUSIP_514014MB2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 514014MB2.
|
| CUSIP_517840Q80 |
CUSIP_517840Q80 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 517840Q80.
|
| CUSIP_522858EB1 |
CUSIP_522858EB1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 522858EB1.
|
| CUSIP_526057BT0 |
CUSIP_526057BT0 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 526057BT0.
|
| CUSIP_529043AC5 |
CUSIP_529043AC5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 529043AC5.
|
| CUSIP_542403AC4 |
CUSIP_542403AC4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 542403AC4.
|
| CUSIP_544495VZ4 |
CUSIP_544495VZ4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 544495VZ4.
|
| CUSIP_544495WB6 |
CUSIP_544495WB6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 544495WB6.
|
| CUSIP_544525PR3 |
CUSIP_544525PR3 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 544525PR3.
|
| CUSIP_552697AQ7 |
CUSIP_552697AQ7 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 552697AQ7.
|
| CUSIP_55336VAG5 |
CUSIP_55336VAG5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 55336VAG5.
|
| CUSIP_558090HQ2 |
CUSIP_558090HQ2 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 558090HQ2.
|
| CUSIP_580638AC8 |
CUSIP_580638AC8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 580638AC8.
|
| CUSIP_584556DZ4 |
CUSIP_584556DZ4 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 584556DZ4.
|
| CUSIP_584556EB6 |
CUSIP_584556EB6 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 584556EB6.
|
| CUSIP_591560AA5 |
CUSIP_591560AA5 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 591560AA5.
|
| CUSIP_59259YGG8 |
CUSIP_59259YGG8 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
for CUSIP 59259YGG8.
|
| CUSIP_59266TEC1 |
CUSIP_59266TEC1 demonstrates EOS Fixed Coupon Multi-flavor Pricing and Relative Value Measure Generation
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Deep Speech 2¶
Deep Speech 2¶
-
class
kospeech.models.deepspeech2.model.
DeepSpeech2
(input_size: int, num_classes: int, rnn_type='gru', num_rnn_layers: int = 5, rnn_hidden_dim: int = 512, dropout_p: float = 0.1, bidirectional: bool = True, activation: str = 'hardtanh', device: str = 'cuda')[source]¶ Deep Speech2 architecture with configurable encoder and decoder. Paper: https://arxiv.org/abs/1512.02595
Parameters: - input_size (int) – size of input
- num_classes (int) – number of classfication
- rnn_type (str, optional) – type of RNN cell (default: gru)
- num_rnn_layers (int, optional) – number of recurrent layers (default: 5)
- rnn_hidden_dim (int) – the number of features in the hidden state h
- dropout_p (float, optional) – dropout probability (default: 0.1)
- bidirectional (bool, optional) – if True, becomes a bidirectional encoder (defulat: True)
- activation (str) – type of activation function (default: hardtanh)
- device (torch.device) – device - ‘cuda’ or ‘cpu’
- Inputs: inputs, input_lengths
- inputs: list of sequences, whose length is the batch size and within which each sequence is list of tokens
- input_lengths: list of sequence lengths
- Returns: output
- output: tensor containing the encoded features of the input sequence
-
forward
(inputs: torch.Tensor, input_lengths: torch.Tensor) → Tuple[torch.Tensor, torch.Tensor][source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.


Using Drake from Python¶
A substantial subset of the Drake C++ functionality is available from Python.
The Drake Python bindings are generated using pybind11, which means that every function or
class which is exposed to C++ has been explicitly enumerated in one of the
source files inside the bindings/pydrake
folder. These bindings are
installed as a single package called pydrake
.
Warning
Drake is incompatible with the Python environment supplied by Anaconda.
Please uninstall Anaconda or remove the Anaconda bin
directory from the
PATH
before building or using the Drake Python bindings.
Installation¶
Before attempting installation, please review the supported configurations to know what versions of Python are supported for your platform.
Binary Installation for Python¶
First, download and extract an available binary package.
As an example, here is how to download and extract one of the latest releases
to /opt
(where <platform>
could be bionic
, focal
, or mac
):
curl -o drake.tar.gz https://drake-packages.csail.mit.edu/drake/nightly/drake-latest-<platform>.tar.gz
rm -rf /opt/drake
tar -xvzf drake.tar.gz -C /opt
Ensure that you have the system dependencies:
/opt/drake/share/drake/setup/install_prereqs
Next, ensure that your PYTHONPATH
is properly configured.
Ubuntu 18.04 (Bionic):
export PYTHONPATH=/opt/drake/lib/python3.6/site-packages:${PYTHONPATH}
Ubuntu 20.04 (Focal):
export PYTHONPATH=/opt/drake/lib/python3.8/site-packages:${PYTHONPATH}
macOS:
export PYTHONPATH=/opt/drake/lib/python3.8/site-packages:${PYTHONPATH}
See below for usage instructions.
Inside virtualenv
¶
At present, Drake is not installable via pip
. However, you can still
incorporate its install tree into a virtualenv
FHS-like
environment.
An example, where you should replace <venv_path>
and <platform>
:
# Setup drake, and run prerequisites.
curl -o drake.tar.gz https://drake-packages.csail.mit.edu/drake/nightly/drake-latest-<platform>.tar.gz
mkdir -p <venv_path>
tar -xvzf drake.tar.gz -C <venv_path> --strip-components=1
# - You may need `sudo` here.
<venv_path>/share/drake/setup/install_prereqs
# Setup a virtualenv over the drake install.
python3 -m virtualenv -p python3 <venv_path> --system-site-packages
Note
You can extract Drake into an existing virtualenv
tree if you have
already run install_prereqs
; however, you should ensure that you have
run install_prereqs
. Before you do this, you should capture / freeze
your current requirements to reproduce your environment if there are
conflicts.
To check if this worked, follow the instructions as shown below, but either:
- Use
<venv_path>/bin/python
instead ofpython3
, or - Source
<venv_path>/bin/activate
in your current shell session.
Building the Python Bindings¶
To use the Python bindings from Drake externally, we recommend using CMake. As an example:
git clone https://github.com/RobotLocomotion/drake.git
mkdir drake-build
cd drake-build
cmake ../drake
make -j
Please note the additional CMake options which affect the Python bindings:
-DWITH_GUROBI={ON, [OFF]}
- Build with Gurobi enabled.-DWITH_MOSEK={ON, [OFF]}
- Build with MOSEK enabled.-DWITH_SNOPT={ON, [OFF]}
- Build with SNOPT enabled.
{...}
means a list of options, and the option surrounded by [...]
is
the default option. An example of building pydrake
with both Gurobi and
MOSEK, without building tests:
cmake -DWITH_GUROBI=ON -DWITH_MOSEK=ON ../drake
You will also need to have your PYTHONPATH
configured correctly.
Ubuntu 18.04 (Bionic):
cd drake-build
export PYTHONPATH=${PWD}/install/lib/python3.6/site-packages:${PYTHONPATH}
Ubuntu 20.04 (Focal):
cd drake-build
export PYTHONPATH=${PWD}/install/lib/python3.8/site-packages:${PYTHONPATH}
macOS:
cd drake-build
export PYTHONPATH=${PWD}/install/lib/python3.8/site-packages:${PYTHONPATH}
Using the Python Bindings¶
Check Installation¶
After following the above install steps, check to ensure you can import
pydrake
.
python3 -c 'import pydrake; print(pydrake.__file__)'
Note
If you are using Gurobi, you must either have it installed in the suggested
location under /opt/...
mentioned in Gurobi 9.0.2, or you must ensure
that you define the ${GUROBI_HOME}
environment variable, or specify
${GUROBI_INCLUDE_DIR}
via CMake.
What’s Available from Python¶
You should first browse the Python API to see what
modules are available. The most up-to-date high-level demonstrations of what
can be done using pydrake
are in Drake’s Tutorials and
the Underactuated Robotics Textbook.
You can also see lower-level usages of the API in the pydrake
unit tests
themselves, which you can find inside of the
drake/bindings/python/pydrake/**/test
folders in the Drake source code.
Here’s an example snippet of code from pydrake
:
from pydrake.common import FindResourceOrThrow
from pydrake.multibody.parsing import Parser
from pydrake.multibody.plant import AddMultibodyPlantSceneGraph
from pydrake.systems.analysis import Simulator
from pydrake.systems.framework import DiagramBuilder
builder = DiagramBuilder()
plant, _ = AddMultibodyPlantSceneGraph(builder, 0.0)
Parser(plant).AddModelFromFile(
FindResourceOrThrow("drake/examples/pendulum/Pendulum.urdf"))
plant.Finalize()
diagram = builder.Build()
simulator = Simulator(diagram)
If you are prototyping code in a REPL environment (such as IPython / Jupyter)
and to reduce the number of import statements, consider using pydrake.all
to
import a subset of symbols from a flattened namespace or import all modules
automatically. If you are writing non-prototype code, avoid using
pydrake.all
; for more details, see help(pydrake.all)
.
In all cases, try to avoid using from pydrake.all import *
, as it may
introduce symbol collisions that are difficult to debug.
The above example, but using pydrake.all
:
from pydrake.all import (
AddMultibodyPlantSceneGraph, DiagramBuilder, FindResourceOrThrow,
Parser, Simulator)
builder = DiagramBuilder()
plant, _ = AddMultibodyPlantSceneGraph(builder, 0.0)
Parser(plant).AddModelFromFile(
FindResourceOrThrow("drake/examples/pendulum/Pendulum.urdf"))
plant.Finalize()
diagram = builder.Build()
simulator = Simulator(diagram)
An alternative is to use pydrake.all
to import all modules, but then
explicitly refer to each symbol:
import pydrake.all
builder = pydrake.systems.framework.DiagramBuilder()
plant, _ = pydrake.multibody.plant.AddMultibodyPlantSceneGraph(builder, 0.0)
pydrake.multibody.parsing.Parser(plant).AddModelFromFile(
pydrake.common.FindResourceOrThrow(
"drake/examples/pendulum/Pendulum.urdf"))
plant.Finalize()
diagram = builder.Build()
simulator = pydrake.systems.analysis.Simulator(diagram)
Differences with C++ API¶
In general, the Python API should be close to the C++ API. There are some exceptions:
C++ Class Template Instantiations in Python¶
When you define a general class template, e.g.
template <typename T> class Value
, something like Value<std::string>
is
called the instantiation.
For certain C++ templated types, they are exposed in Pythons also as templates;
the parameter types (in this case, T
) are the Python-equivalent types to the
C++ type. Some examples:
| C++ | Python |
|---|---|
std::string |
str |
double |
float , np.double ,
np.float64 , ctypes.c_double |
drake::AutoDiffXd |
pydrake.autodiffutils.AutoDiffXd |
drake::symbolic::Expression |
pydrake.symbolic.Expression |
Thus, the instantiation Value<std::string>
will be bound in Python as
Value[str]
.
Scalar Types¶
Most classes in the Systems framework and in the multibody dynamics
computational framework are templated on a scalar type, T
.
For convenience (and backwards compatibility) in Python, a slightly different
binding convention is used.
For example, Adder<T>
is a Systems primitive which has a user-defined
number of inputs and outputs a single port which is the sum of all of the
inputs.
In C++, you would access the instantiations using Adder<double>
,
Adder<AutoDiffXd>
, and Adder<Expression>
for common scalar types.
In Python, Adder
actually refers to the “default” instantiation, the
Adder<double>
C++ class. To access other instantiations, you should add an
_
to the end of the C++ class name to get the Python template and then
provide the parameters in square braces, [...]
. In this example, you should
use Adder_[T]
.
To illustrate, you can print out the string representations of Adder
,
Adder_
, and some of its instantiations in Python:
>>> from pydrake.systems.primitives import Adder, Adder_
>>> print(Adder)
<class 'pydrake.systems.primitives.Adder_[float]'>
>>> print(Adder_)
<TemplateClass pydrake.systems.primitives.Adder_>
>>> from pydrake.autodiffutils import AutoDiffXd
>>> from pydrake.symbolic import Expression
>>> print(Adder_[float])
<class 'pydrake.systems.primitives.Adder_[float]'>
>>> print(Adder_[AutoDiffXd])
<class 'pydrake.systems.primitives.Adder_[AutoDiffXd]'>
>>> print(Adder_[Expression])
<class 'pydrake.systems.primitives.Adder_[Expression]'>
Additionally, you may convert an instance (if the conversion is available) using
System_[T].ToAutoDiffXd
and System_[T].ToSymbolic
:
>>> adder = Adder(num_inputs=1, size=1)
>>> print(adder)
<pydrake.systems.primitives.Adder_[float] object at 0x...>
>>> print(adder.ToAutoDiffXd())
<pydrake.systems.primitives.Adder_[AutoDiffXd] object at 0x...>
>>> print(adder.ToSymbolic())
<pydrake.systems.primitives.Adder_[Expression] object at 0x...>
C++ Function and Method Template Instantiations in Python¶
The above section indicates that C++ types are generally registered with Python, and a similar approach could be used for function and method templates. However, these templates usually fit a certain pattern and can be Pythonized in such a way that simplifies implementation, but may change the “feel” of the signature.
Two common (non-metaprogramming) applications of templated functions and methods present in Drake are emplace-like functionality (using parameter packs) and type erasure. However, Python doesn’t literally support these C++ language features. So, in binding them, they get “Pythonized”.
C++ APIs which use parameter packs, such as:
DiagramBuilder<T>::AddSystem<SystemType>(args...)
MultibodyPlant<T>::AddJoint<JointType>(args...)
MultibodyPlant<T>::AddFrame<FrameType>(args...)
will become the following in Python:
DiagramBuilder_[T].AddSystem(SystemType(args, ...))
MultibodyPlant_[T].AddJoint(JointType(args, ...))
MultibodyPlant_[T].AddFrame(FrameType(args, ...))
where the *Type
tokens are replaced with the concrete type in question
(e.g. Adder_[T]
, RevoluteJoint_[T]
, FixedOffsetFrame_[T]
).
Similarly, type-erasure C++ APIs that look like:
InputPort<T>::Eval<ValueType>(context)
GeometryProperties::AddProperty<ValueType>(group_name, name, value)
will become the following in Python:
InputPort_[T].Eval(context)
GeometryProperties.AddProperty(group_name, name, value)
Debugging with the Python Bindings¶
You may encounter issues with the Python Bindings that may arise from the underlying C++ code, and it may not always be obvious what the root cause is.
The first step to debugging is to consider running your code using the
trace
module. It is best practice to always have a main()
function, and
have a if __name__ == "__main__"
clause. If you do this, then it is easy to
trace. As an example:
def reexecute_if_unbuffered():
"""Ensures that output is immediately flushed (e.g. for segfaults).
ONLY use this at your entrypoint. Otherwise, you may have code be
re-executed that will clutter your console."""
import os
import shlex
import sys
if os.environ.get("PYTHONUNBUFFERED") in (None, ""):
os.environ["PYTHONUNBUFFERED"] = "1"
argv = list(sys.argv)
if argv[0] != sys.executable:
argv.insert(0, sys.executable)
cmd = " ".join([shlex.quote(arg) for arg in argv])
sys.stdout.flush()
os.execv(argv[0], argv)
def traced(func, ignoredirs=None):
"""Decorates func such that its execution is traced, but filters out any
Python code outside of the system prefix."""
import functools
import sys
import trace
if ignoredirs is None:
ignoredirs = ["/usr", sys.prefix]
tracer = trace.Trace(trace=1, count=0, ignoredirs=ignoredirs)
@functools.wraps(func)
def wrapped(*args, **kwargs):
return tracer.runfunc(func, *args, **kwargs)
return wrapped
# NOTE: You don't have to trace all of your code. If you can identify a
# single function, then you can just decorate it with this. If you're
# decorating a class method, then be sure to declare these functions above
# it.
@traced
def main():
insert_awesome_code_here()
if __name__ == "__main__":
reexecute_if_unbuffered()
main()
Note
If you are developing in Drake and are using the drake_py_unittest
macro, you can specify the argument --trace=user
to get the same
behavior.
This generally should help you trace where the code is dying. However, if you
still need to dig in, you can build the bindings in debug mode, without symbol
stripping, so you can debug with gdb
or lldb
:
cmake -DCMAKE_BUILD_TYPE=Debug ../drake
Warning
If you have SNOPT enabled (either -DWITH_SNOPT=ON
or
-DWITH_ROBOTLOCOMOTION_SNOPT=ON
), symbols will still be stripped.
For Developers¶
If you are developing Python bindings, please see the Doxygen page Python Bindings which provides information on programming conventions, documentation, tips for debugging, and other advice.


Online Courses
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UseFLACSoundDecoder()
Syntax
UseFLACSoundDecoder()Description
Enables the FLAC (Free Lossless Audio Codec) sound support for CatchSound() and LoadSound(). Sound streaming is supported for this plug-in.
Parameters
None.
Return value
None.
Remarks
Since FLAC is a not destructive compression codec, the file size will remain quite large, especially compared to OGG for example. This allows for a reduction in file size, while still retaining all the original sound information.
For more information: Wikipedia - FLAC.
Supported OS
All


Polimorphism means that the same function name can be used for different types. This makes programming more intuitive and easier.
def times(x, y): """Return the product of arguments.""" # The arguments should support the * operator (the __mul__ method). return x * y times(2, 3) # 6, int * int times(2, 3.14) # 6.28, int * float times("Bum!", 3) # "Bum!Bum!Bum!", str * int
# Polymorphic len() function. # Based on the __len__ method. len("Python") # 6, the length of a string len(["Python", "C++", "Java"]) # 3, the number of items len({"Name": "Adam", "Age": 30}) # 2, the number of keys len(set([1, 3, 5, 7])) # 4, the number of elements
Polymorphism is a very important concept in Object-Oriented Programming. Polymorphism in class methods: different (unrelated) classes can have a method with the same name.


abstract fun importNlpPlainSentencesDump(dump: SentencesDump): Boolean
Imports a NLP sentences dump (only validated sentences) - format is simpler than ApplicationDump.
dump - the dump to import
dump
Return true if NLP model is modified, false either


[1]
as for breakfast i had the recommendation and hotel.
[2]
as for breakfast i had planned ahead and hotel.


Microsoft Applied Robotics Research Library
Open Source Samples for Service Robotics
Map Generation Instructions
HoloLens Spatial Mapping
The following step-by-step procedure provides a guide for capturing a 3D spatial map of the navigation space and processing it into a 2D navigation map compatible with the ROS navigation solution. The procedure assumes that all of the previous sections' setup and configuration instructions have been completed and a 2D floor map has already been generated and installed in the system.
Use the HoloLens device to perform a spatial mapping of the navigation environment. Map the floor up to at least your eye level and make sure to carefully trace along the floor edges to collect accurate readings.
For visual feedback of the map as it builds, compile and run the HoloLensNavigation application and complete the spatial mesh mapping.
Alternatively, compile and run the lighter weight Microsoft's Holographic spatial mapping sample at this link.
Create a floor plan image from HoloLens' Spatial Map in ROS
- launch the HoloLensNavigation app on your HoloLens device
- there are different ways to launch the application. Easiest way is to use the Device Portal to launch application. Alternatively wear the headset and launch from GUI, or launch from VisualStudio.
- launch the ROS map_server
$ rosrun map_server map_server src/navigation_launcher/params/map.yaml
- launch the HoloLens bridge in ROS
$ rosrun hololens_ros_bridge hololens_ros_bridge_node <hololens ip> 1234
- note that 1234 is the port number.
- launch the HoloLens localizer in ROS
$ rosrun hololens_localizer anchor_localizer
- launch the image saver node in ROS
$ rosrun image_view image_saver image:=/hololens/image
- launch rviz in ROS
$ rviz
- select "2D Pose Estimate" and then click anywhere on the map view to set initial position in any location and direction. This instructs image_saver to create a cross-section of the HoloLens' spatial map and save it as left000.jpg in the same folder the image_saver node was launched from.
-
open the output graphic file and edit for navigation
-
open the file left0000.jpg` with your favorite image editor. It will appear as a pattern of dots filtered by the 2D cross section of the 3D point cloud
-
using the depicted pointcloud outline, create a ROS compliant image map.
- save the modified left0000.jpg file in the folder: ~/catkin_ws/src/navigation_launcher/params/
-


---
layout: page
tags: [Jekyll, HADDOCK, Bonvin, Docking, Simulation, Molecular Dynamics, Structural Biology, Computational Biology, Modelling, Protein Structure]
modified: 2014-08-08T20:53:07.573882-04:00
comments: false
image:
feature: pages/banner_software.jpg
---
HADDOCK2.2 manual |
Download |
HADDOCK consists of a collection of python and
CNS scripts and other additional scripts and programs
(csh, awk, perl, c++). The HADDOCK distribution can be obtained free of charge for non commercial users
by completing and returning (via email) the license agreement form to:
Prof. Dr. A.M.J.J. Bonvin
Bijvoet Center of Biomolecular Research
University of Utrecht
Padualaan 8
NL-3584 CH Utrecht
The Netherlands
Fax: +31 30 2537623
Phone: +31 30 2533859
Email<EMAIL_ADDRESS>The HADDOCK2.2 distribution amounts to approximately 10MB
(gzipped tar file) and will be distributed by email unless otherwise
required.
The additional software and licenses required to run HADDOCK
(e.g. CNS) should be obtained directly from the distribution sites.
(see the software links).
Commercial users should contact us for enquiries.
Please send any suggestions or enquiries to Alexandre Bonvin


April 11, 2015
After watching Shereef's Fireside Chat video, I feel ready and excited about Dev Bootcamp. I'm going into this knowing it's not going to be easy, and that I'm going to learn a lot about myself, both good and bad. It's going to be up to me to take charge of my learning environment.
Dev Bootcamp is not the type of program that will give you "fast results." You will get out of the program only what you put into it. You have to be comfortable not knowing anything, ask for help when needed, and willing to take intitiave in your own learning. I've never been exposed to pair programming before, and I'm a little nervous about it. I'm pretty used to working alone, and sharing that control will take some getting used to. We have to be both teacher and learner. Software development is a team sport, and the immersion experience will very much be about that.
I also really like that Dev Bootcamp emphasizes the mind and body. I've read books by Alan Watts and Thich Nhat Hanh, but I've always failed at incorporating meditation into my daily life. Dev Bootcamp will be the best excuse to try and start again! I have so many thoughts running through my mind all the time, and it's going to be important to open up space in there. I'm super excited to get to know my cohort and start this journey! Til next time. Thanks for reading.


{# wf_include #}
This section explains how this audit is implemented, so that you can understand how the audit's score is calculated.


ExpLookitMoodQuestionnaire Class
A standard mood survey with questions about factors that might affect a child's responses. Includes Likert-type ratings of the CHILD's position on the following scales:
- Tired - Rested
- Sick - Healthy
- Fussy - Happy
- Calm - Active
and of the PARENT's position on:
- Tired - Energetic
- Overwhelmed - On top of things
- Upset - Happy
It also asks for a response in hours:minutes for:
- how long ago the child last woke up from sleep or a nap
- how long until he/she is due for another nap/sleep (if regular nap schedule)
- how long ago the child last ate/drank
and for what the child was doing just before this (free-response). Responses to all questions are required to move on.
This frame can be used as a starting point/example for other custom survey frames, or development of a customizable survey frame.
"frames": {
"mood-survey": {
"introText": "How are you two doing? We really want to know: we’re interested in how your child’s mood affects his or her looking preferences.",
"kind": "exp-lookit-mood-questionnaire"
}
}
Item Index
Properties
Methods
exitFullscreen
()
makeTimeEvent
-
eventName
-
[extra]
Create the time event payload for a particular frame / event. This can be overridden to add fields to every event sent by a particular frame
Parameters:
Returns:
Event type, time, and any additional metadata provided
serializeContent
-
rested
-
healthy
-
childHappy
-
active
-
energetic
-
ontopofstuff
-
healthy
-
napWakeUp
-
usualNapSchedule
-
nextNap
-
lastEat
-
doingBefore
Parameters captured and sent to the server
Parameters:
-
rested
StringRating for CHILD on tired - rested scale, '1' to '7' where '7' is rested
-
healthy
StringRating for CHILD on sick - healthy scale, '1' to '7' where '7' is healthy
-
childHappy
StringRating for CHILD on fussy - happy scale, '1' to '7' where '7' is happy
-
active
StringRating for CHILD on calm - active scale, '1' to '7' where '7' is active
-
energetic
StringRating for PARENT on tired - energetic scale, '1' to '7' where '7' is energetic
-
ontopofstuff
StringRating for PARENT on overwhelmed - on top of stuff scale, '1' to '7' where '7' is on top of stuff
-
healthy
StringRating for PARENT on upset - happy scale, '1' to '7' where '7' is happy
-
napWakeUp
Stringhow long since the child woke up from nap, HH:mm
-
usualNapSchedule
Stringwhether the child has a typical nap schedule: 'no', 'yes', or 'yes-overdue' if child is overdue for nap
-
nextNap
Stringonly valid if usualNapSchedule is 'yes'; how long until child is due to sleep again, HH:mm
-
lastEat
Stringhow long since the child ate/drank, HH:mm
-
doingBefore
Stringwhat the child was doing before this (free response)
Returns:
The payload sent to the server
showFullscreen
()
Properties
displayFullscreenOverride
String
fullScreenElementId
String
generateProperties
String
Function to generate additional properties for this frame (like {"kind": "exp-lookit-text"}) at the time the frame is initialized. Allows behavior of study to depend on what has happened so far (e.g., answers on a form or to previous test trials). Must be a valid Javascript function, returning an object, provided as a string.
Arguments that will be provided are: expData
, sequence
, child
, pastSessions
, conditions
.
expData
, sequence
, and conditions
are the same data as would be found in the session data shown
on the Lookit experimenter interface under 'Individual Responses', except that
they will only contain information up to this point in the study.
expData
is an object consisting of frameId
: frameData
pairs; the data associated
with a particular frame depends on the frame kind.
sequence
is an ordered list of frameIds, corresponding to the keys in expData
.
conditions
is an object representing the data stored by any randomizer frames;
keys are frameId
s for randomizer frames and data stored depends on the randomizer
used.
child
is an object that has the following properties - use child.get(propertyName)
to access:
additionalInformation
: String; additional information field from child formageAtBirth
: String; child's gestational age at birth in weeks. Possible values are "24" through "39", "na" (not sure or prefer not to answer), "<24" (under 24 weeks), and "40>" (40 or more weeks).birthday
: timestamp in format "Mon Apr 10 2017 20:00:00 GMT-0400 (Eastern Daylight Time)"gender
: "f" (female), "m" (male), "o" (other), or "na" (prefer not to answer)givenName
: String, child's given name/nicknameid
: String, child UUID
pastSessions
is a list of previous response objects for this child and this study,
ordered starting from most recent (at index 0 is this session!). Each has properties
(access as pastSessions[i].get(propertyName)):
completed
: Boolean, whether they submitted an exit surveycompletedConsentFrame
: Boolean, whether they got through at least a consent frameconditions
: Object representing any conditions assigned by randomizer framescreatedOn
: timestamp in format "Thu Apr 18 2019 12:33:26 GMT-0400 (Eastern Daylight Time)"expData
: Object consisting of frameId: frameData pairsglobalEventTimings
: list of any events stored outside of individual frames - currently just used for attempts to leave the study earlysequence
: ordered list of frameIds, corresponding to keys in expData
Example:
function(expData, sequence, child, pastSessions, conditions) {
return {
'blocks':
[
{
'text': 'Name: ' + child.get('givenName')
},
{
'text': 'Frame number: ' + sequence.length
},
{
'text': 'N past sessions: ' + pastSessions.length
}
]
};
}
(This example is split across lines for readability; when added to JSON it would need to be on one line.)
Default: null
introText
String
Intro paragraph describing why we want mood info
Default: 'How are you two doing? We really want to know: we’re interested in how your child’s mood affects his or her looking preferences.'
selectNextFrame
String
Function to select which frame index to go to when using the 'next' action on this frame. Allows flexible looping / short-circuiting based on what has happened so far in the study (e.g., once the child answers N questions correctly, move on to next segment). Must be a valid Javascript function, returning a number from 0 through frames.length - 1, provided as a string.
Arguments that will be provided are:
frames
, frameIndex
, expData
, sequence
, child
, pastSessions
frames
is an ordered list of frame configurations for this study; each element
is an object corresponding directly to a frame you defined in the
JSON document for this study (but with any randomizer frames resolved into the
particular frames that will be used this time).
frameIndex
is the index in frames
of the current frame
expData
is an object consisting of frameId
: frameData
pairs; the data associated
with a particular frame depends on the frame kind.
sequence
is an ordered list of frameIds, corresponding to the keys in expData
.
child
is an object that has the following properties - use child.get(propertyName)
to access:
additionalInformation
: String; additional information field from child formageAtBirth
: String; child's gestational age at birth in weeks. Possible values are "24" through "39", "na" (not sure or prefer not to answer), "<24" (under 24 weeks), and "40>" (40 or more weeks).birthday
: timestamp in format "Mon Apr 10 2017 20:00:00 GMT-0400 (Eastern Daylight Time)"gender
: "f" (female), "m" (male), "o" (other), or "na" (prefer not to answer)givenName
: String, child's given name/nicknameid
: String, child UUID
pastSessions
is a list of previous response objects for this child and this study,
ordered starting from most recent (at index 0 is this session!). Each has properties
(access as pastSessions[i].get(propertyName)):
completed
: Boolean, whether they submitted an exit surveycompletedConsentFrame
: Boolean, whether they got through at least a consent frameconditions
: Object representing any conditions assigned by randomizer framescreatedOn
: timestamp in format "Thu Apr 18 2019 12:33:26 GMT-0400 (Eastern Daylight Time)"expData
: Object consisting of frameId: frameData pairsglobalEventTimings
: list of any events stored outside of individual frames - currently just used for attempts to leave the study earlysequence
: ordered list of frameIds, corresponding to keys in expData
Example that just sends us to the last frame of the study no matter what:
`"function(frames, frameIndex, frameData, expData, sequence, child, pastSessions) {return frames.length - 1;}"
``
Default: null
Events
enteredFullscreen
leftFullscreen
nextFrame
Move to next frame
previousFrame
Move to previous frame


Macy's becomes the latest victim of a Magecart skimming attack
It claims only a 'small number' of customers were hit
by INQUIRER staffUS DEPARTMENT STORE Macy's has fallen victim to a Magecart attack that saw customers' payment card details stolen.
Macy's says it was alerted to the data breach on 15 October 2019. An initial investigation revealed that the company website, Macys.com, was inappropriately communicating with some remote website under the control of a hacking group.
The attack likely happened on 7 October 2019, according to Macy's, with an unauthorised third party adding malicious script on two web pages - the 'Checkout' and 'My Wallet' pages - enabling attackers to eavesdrop on sensitive information.
The Checkout page conveyed information to hackers when a customer entered credit card details and hit the "place order" button.
Similarly, the My Wallet page provided customers' private details, including their name, address, city, state, email address, phone number, debit/credit card number, card's security code, and more.
The malicious script on the website was removed on 15 October 2019. After that, Macy's informed law enforcement agencies, as well as credit card issuers.
Only a small number of customers were affected by the data breach, the company claimed. Those affected have been advised to monitor their payment card statements for any signs of fraudulent activity.
"There is no reason to believe that this incident could be used by cyber criminals to open new accounts in your name," the company added in its 'Notice of Data Breach'.
"Nonetheless, you should remain vigilant for incidents of financial fraud and identity theft by regularly reviewing your account statements and immediately reporting any suspicious activity to your card issuer."
The company is offering a free year of the Experian IdentityWorks credit monitoring service to affected users.
Macy's also stated that it has thoroughly investigated the matter and taken appropriate security measures to ensure that such incidents should not be repeated in future.
A few months back, cybersecurity firm Malwarebytes warned e-commerce companies of a summer surge in activity by web-skimming Magecart gangs, targeting organisations' online payments systems. The firm claimed that it had blocked 65,000 web-skimming Magecart data theft attempts in July alone. µ
Further reading
Devilish hackers breach domain name outfit Web.com
- 31 Oct 2019
BA customers given go-ahead to sue firm over 2018 mega-breach
- 07 Oct 2019
Teletext Holidays breach exposes 212,000 call recordings
- 02 Sep 2019
DoorDash has five million records swiped in unappetising breach
- 27 Sep 2019


For the fig-swirl: Melt butter over medium heat in a saucepan. Add brown sugar and stir to dissolve. Halve all of the figs and toss in the saucepan with water and lemon juice. Cook over medium hear, stirring frequently, until you have a chunky-jammy mixture. Add salt with one or two stirs, set aside and let cool completely.
Ice cream:In a small pot over medium heat, combine milk, and granulated sugar until sugar is completely dissolved and the milk is just barely lukewarm. Whisk in the egg yolks. Set mixture in the fridge and wait until the fig mixture is cooled.
Using an ice cream machine, pour liquids into the frozen basin and process according to manufacturer instructions,i.e., let spin and thinken for 20 minutes before adding mascarpone, fig jam mixture, and the nuts. Continue to process for +/- 10 minutes. Pour semi-frozen mixture into a pyrex dish or glass tupperware. Freeze for at least two hours before serving.
Vanessa Stevenson
Food enthusiast,photography fan.Add a pinch of raw foodism and that's pretty much who I am.


DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Primary academies are transforming attainment in primary schools.
The Department for Education today announced that more than 400 struggling primary schools were paired up with academy sponsors in the last year - exceeding a pledge made 12 months ago.
In 2012, 200 of the weakest primaries became sponsored academies - after which the government promised to go even further and faster in tackling underperformance, and pledged to broker sponsorship of 400 further failing primaries in 2013.
It means that 645 underperforming primary schools have now come under the wing of academy sponsors under this government - with their previous poor performance now being tackled and standards being raised.
In May 2010 there were 203 academies - all of them sponsored, none of them primary schools. In total there are now more than 3,500 academies.
The primary school tables, published last month, showed that sponsored academies had improved their performance by 3 percentage points, against an improvement in all schools of 1 percentage point.
Examples of some of the primary schools which became sponsored academies in 2012 when they were among the poorest in the country, but which are now thriving, include:
A Department for Education spokesman said:
The best way to turn around the stubborn underperformance that exists in some schools is to bring in a sponsor. These sponsors bring with them experience, strong leadership, know-how - and a track record of success.
It is vital we continue to raise standards so all children leave primary school with a thorough grounding in reading, writing and maths so they can thrive at secondary school.
The sponsored academy programme is in addition to the hundreds of schools which can convert to academy status (known as converter academies). The academy programme was previously focused only on underperforming secondary schools. This government is now using academies to tackle weak primary schools as well. It has also allowed schools to take advantage of the freedoms and autonomy on offer by academy status, by converting.
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 3 January 2014
From: Department for Education
Part of: Academies and free schools


Just a minute 'fore you leave, girl,
Just a minute 'fore you touch the door.
What is it that you're trying to achieve, girl?
Do you think we can talk about it some more?

Don't fall apart on me tonight,
I just don't think that I could handle it.
Don't fall apart on me tonight.
Yesterday's just a memory,
Tomorrow's never what it's supposed to be,
And I need you, yeah.
Come over here from over there, girl.
Sit down here, you can have my chair.
I can't see us going anywhere, girl --
The only place open is a thousand miles away and I can't take you there.
I wish I'd have been a doctor,
Maybe I'd'a saved some life that been lost,
Maybe I'd'a done some good in the world
'Steada burning every bridge I crossed.
Don't fall apart on me tonight,
I just don't think that I could handle it.
Don't fall apart on me tonight.
Yesterday is just a memory,
Tomorrow's never what it's supposed to be,
And I need you, ah, yeah.
I ain't too good at conversation, girl,
So you might not know exactly how I feel.
But, if I could, I'd bring you to the mountain-top, girl,
And build you a house made outta stainless steel.
But it's like I'm stuck inside a painting
That's a-hanging in the Louvre –
My throat starts to tickle and my nose itches,
But I know that I can't move.
Don't fall apart on me tonight,
I just don't think that I could handle it.
Don't fall apart on me tonight.
Yesterday's gone, but the past live on,
Tomorrow's just one step beyond,
And I need you, ah.
Who are these people that are walking towards you?
Do you know them or will there be a fight?
With their humorless smile so easy to see through,
Can they tell you what's wrong from what's right?
Or do you remember St. James Street,
Where you blew Jackie P.'s mind?
You were so fine Clark Gable would have fell at your feet
And laid his life on the line.
Let's try to get beneath the surface waste, girl,
No more booby traps and bombs, no more decadence and charm,
No more affection that's misplaced, girl,
No more mudcake creatures lying in your arms.
What about that millionaire
With the drumsticks in his pants?
He looked so baffled and so bewildered
When he played and we didn't dance.
Don't fall apart on me tonight,
I just don't think that I could handle it.
Don't fall apart on me tonight.
Yesterday's just a memory,
Tomorrow's never what it's supposed to be,
And I need you, yeah, you, ah, I need you.


Zimbra communication handler.
Bases: object
Zimbra communication handler.
Sends requests to the zimbra SOAP server and returns the responses in a dictionary.
Convenience method to quickly generate a token
| Parameters: |
|
|---|---|
| Returns: | The request |
Send the request.
| Parameters: |
|
|---|---|
| Raises : | pythonzimbra.exceptions.communication.SoapFailure or urllib2.HTTPError |
Timeout of the request
URL to the zimbra soap interface
Request handling and generation.
Bases: object
Zimbra SOAP request generation and handling.
Add a request.
This adds a request to the body or to the batchrequest-node if batch requesting is enabled. Has to update the self.batch_request_id after adding a batch request!
Implementing classes should call this first for checks.
| Parameters: |
|
|---|---|
| Returns: | The current request id (if batch processing) or None |
| Return type: | int or None |
Are we doing batch requests?
If so, keep the current request id
Enables batch request gathering.
Do this first and then consecutively call “add_request” to add more requests.
| Parameters: | onerror – “continue” (default) if one request fails (and response with soap Faults for the request) or “stop” processing. |
|---|
The specific request will set its request type (json, xml) here
Convenience function to inject the auth token into the header.
| Parameters: | token – Auth token |
|---|
Set header context parameters. Refer to the top of <Zimbra Server-Root>/docs/soap.txt about specifics.
The <format>-Parameter cannot be changed, because it is set by the implementing class.
Should be called by implementing method to check for valid context params.
| Parameters: | params – A Dict containing context parameters. |
|---|
Valid parameter name for Soap context
Zimbra request handling (JSON)
Request handling and generation (XML version).
Zimbra response access.
Bases: object
Unified access to Zimbra responses.
Returns an informative dictionary about a batch response.
Returns a dictionary containing the following information:
{
"hasFault": <bool wether the batch has at least one SoapFault
"idToName": {
<A dictionary mapping a response id to the corresponding
response name or Fault>
}
"nameToId": {
<A dictionary mapping response names (or Fault) to the
corresponding response id(s)
}
}
If the method is called with no batch response existing, returns None
| Returns: | Informative dictionary |
|---|---|
| Return type: | dict or None |
Return the body of the response.
| Returns: | The response body in the documented dictionary format |
|---|---|
| Return type: | dict |
Returns the fault error code of this response (overridden)
For batch responses, we return a dict of fault codes. The key is the request_id.
| Returns: | Fault code string |
|---|
Returns the fault error message of this response (overridden)
For batch responses, we return a dict of fault messages. The key is the request_id.
| Returns: | Fault code error message |
|---|
Return the header of the response.
| Returns: | The response header in the documented dictionary format |
|---|---|
| Return type: | dict |
Returns the response with the given request_id.
Returns the specific response. If “request_id” isn’t provided or 0, the first (or only one in a non-batch) response is returned.
Returns whether we have a BatchResponse.
| Returns: | Whether we have a BatchResponse |
|---|---|
| Return type: | bool |
Checks, wether this response has at least one fault response ( supports both batch and single responses)
The actual response will set its response type (xml, json) here
JSON-Response format
XML-Response format.


Be a Santa for a Senior
by Rob GibsonAn Okanagan company is teaming up with London Drugs to help seniors this holiday season.
Home Instead Senior Care is helping to make sure no Okanagan senior goes without a present or some companionship this season.
"Every year, the Kelowna community supports the Be a Santa to a Senior program, aiming to provide local seniors – particularly those in long-term care homes – with companionship and gifts during the holiday season," says Janine Karlsen, Owner of the Home Instead office serving Kelowna, West Kelowna and Penticton.
The program launches next Wednesday, November 27th and runs through until December 13th.
Karlsen tells Castanet the Okanagan has embraced the program and brought smiles to the faces of 850 seniors last year. The volunteers work like Santa's elves in the background, making the tags, picking up and wrapping the gifts and finally delivering the presents.
"This year the tags will go up on the 22nd of November and all gifts must be in by December 12th, delivery to the seniors will be between the 16th and 19th of December," says Karlsen.
The public can participate by visiting a Home Instead tree, which will have tags with seniors’ names and gift ideas at the following London Drugs locations:
- London Drugs, Kelowna (1950 Harvey Avenue)
- London Drugs, West Kelowna (2151 Louie Drive)
“The Be a Santa to a Senior program is all about including seniors in the joy of the holiday season,” Karlsen says, “a simple gift shows them they are a loved and vital member of our community.”