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{ |
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{ |
| 2 |
"metadata": { |
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"metadata": { |
| 3 |
"name": "ALTIMET_test" |
3 |
"name": "" |
| 4 |
}, |
4 |
}, |
| 5 |
"nbformat": 3, |
5 |
"nbformat": 3, |
| 6 |
"nbformat_minor": 0, |
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"nbformat_minor": 0, |
| 7 |
"worksheets": [ |
7 |
"worksheets": [ |
| 8 |
{ |
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{ |
| Line 33... |
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"outputs": [ |
33 |
"outputs": [ |
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{ |
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{ |
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"output_type": "stream", |
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"output_type": "stream", |
| 36 |
"stream": "stdout", |
36 |
"stream": "stdout", |
| 37 |
"text": [ |
37 |
"text": [ |
| 38 |
"i2c-0\tsmbus \tCP2112 SMBus Bridge on hiddev0 \tSMBus adapter\r\n", |
- |
|
| 39 |
"i2c-1\ti2c \ti2c-tiny-usb at bus 001 device 007\tI2C adapter\r\n", |
38 |
"i2c-5\ti2c \ti2c-tiny-usb at bus 002 device 008\tI2C adapter\r\n", |
| 40 |
"i2c-2\ti2c \ti915 gmbus ssc \tI2C adapter\r\n", |
- |
|
| 41 |
"i2c-3\ti2c \ti915 gmbus vga \tI2C adapter\r\n", |
39 |
"i2c-0\ti2c \tintel drm CRTDDC_A \tI2C adapter\r\n", |
| 42 |
"i2c-4\ti2c \ti915 gmbus panel \tI2C adapter\r\n", |
- |
|
| 43 |
"i2c-5\ti2c \ti915 gmbus dpc \tI2C adapter\r\n", |
40 |
"i2c-1\ti2c \tintel drm LVDSBLC_B \tI2C adapter\r\n", |
| 44 |
"i2c-6\ti2c \ti915 gmbus dpb \tI2C adapter\r\n", |
41 |
"i2c-2\ti2c \tintel drm LVDSDDC_C \tI2C adapter\r\n", |
| 45 |
"i2c-7\ti2c \ti915 gmbus dpd \tI2C adapter\r\n", |
42 |
"i2c-3\ti2c \tintel drm HDMIB \tI2C adapter\r\n", |
| 46 |
"i2c-8\ti2c \tDPDDC-B \tI2C adapter\r\n" |
43 |
"i2c-4\ti2c \tDPDDC-B \tI2C adapter\r\n" |
| 47 |
] |
44 |
] |
| 48 |
} |
45 |
} |
| 49 |
], |
46 |
], |
| 50 |
"prompt_number": 1 |
47 |
"prompt_number": 1 |
| 51 |
}, |
48 |
}, |
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}, |
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}, |
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{ |
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{ |
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"cell_type": "code", |
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"cell_type": "code", |
| 77 |
"collapsed": false, |
74 |
"collapsed": false, |
| 78 |
"input": [ |
75 |
"input": [ |
| 79 |
"port = 1" |
76 |
"port = 5" |
| 80 |
], |
77 |
], |
| 81 |
"language": "python", |
78 |
"language": "python", |
| 82 |
"metadata": {}, |
79 |
"metadata": {}, |
| 83 |
"outputs": [], |
80 |
"outputs": [], |
| 84 |
"prompt_number": 2 |
81 |
"prompt_number": 2 |
| Line 95... |
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"collapsed": false, |
92 |
"collapsed": false, |
| 96 |
"input": [ |
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"input": [ |
| 97 |
"import time\n", |
94 |
"import time\n", |
| 98 |
"import datetime\n", |
95 |
"import datetime\n", |
| 99 |
"import sys\n", |
96 |
"import sys\n", |
| 100 |
"import serial\n", |
- |
|
| 101 |
"\n", |
97 |
"\n", |
| 102 |
"from pymlab import config\n", |
98 |
"from pymlab import config\n", |
| 103 |
"import matplotlib.pyplot as plt\n", |
99 |
"import matplotlib.pyplot as plt\n", |
| 104 |
"import numpy as np" |
100 |
"import numpy as np" |
| 105 |
], |
101 |
], |
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"outputs": [ |
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"outputs": [ |
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{ |
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{ |
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"output_type": "stream", |
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"output_type": "stream", |
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"stream": "stdout", |
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"stream": "stdout", |
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"text": [ |
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"text": [ |
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"(0, 22.625, 94868.25)\n", |
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"(0, 22.0, 96976.25)\n", |
| 189 |
"(1, 22.625, 94868.25)" |
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"(1, 22.0, 96978.0)" |
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] |
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] |
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}, |
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}, |
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{ |
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{ |
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"output_type": "stream", |
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"stream": "stdout", |
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"stream": "stdout", |
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"text": [ |
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"\n", |
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"\n", |
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"(2, 22.625, 94868.25)" |
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"(2, 22.0, 96978.0)" |
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] |
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] |
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}, |
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}, |
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{ |
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{ |
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"output_type": "stream", |
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"stream": "stdout", |
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"stream": "stdout", |
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"text": [ |
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"\n", |
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"\n", |
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"(3, 22.625, 94870.0)" |
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"(3, 22.0, 96976.75)" |
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}, |
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{ |
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"output_type": "stream", |
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"\n", |
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"(4, 22.625, 94870.0)" |
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"(4, 22.0, 96976.75)" |
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] |
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}, |
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{ |
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"(5, 22.625, 94868.5)" |
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{ |
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"(6, 22.625, 94868.5)" |
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"(7, 22.5625, 94866.5)" |
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"(8, 22.5625, 94866.5)" |
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{ |
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"(9, 22.625, 94868.5)" |
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"(12, 22.5625, 94868.0)" |
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"(13, 22.5625, 94868.0)" |
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{ |
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{ |
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"(14, 22.5625, 94866.25)" |
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{ |
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{ |
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"(15, 22.625, 94866.25)" |
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{ |
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"(16, 22.625, 94868.5)" |
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{ |
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"(18, 22.625, 94870.75)" |
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{ |
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"(19, 22.625, 94870.75)" |
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"(19, 22.0, 96972.75)" |
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] |
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] |
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}, |
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{ |
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"(20, 22.5625, 94864.5)" |
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{ |
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"(21, 22.5625, 94864.5)" |
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{ |
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"(22, 22.625, 94868.5)" |
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{ |
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"(23, 22.625, 94868.5)" |
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"(24, 22.5625, 94870.25)" |
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{ |
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{ |
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"(25, 22.5625, 94866.25)" |
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{ |
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"(26, 22.5625, 94866.25)" |
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] |
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{ |
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"(27, 22.5625, 94864.75)" |
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{ |
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"(28, 22.5625, 94864.75)" |
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{ |
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"(29, 22.5625, 94868.0)" |
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"(30, 22.5625, 94868.0)" |
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"(30, 22.0, 96976.75)" |
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"(31, 22.5625, 94868.5)" |
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| 430 |
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"(32, 22.5625, 94868.5)" |
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| 438 |
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"(33, 22.5625, 94870.0)" |
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"(33, 22.0, 96976.75)" |
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448 |
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| 453 |
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449 |
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| 454 |
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450 |
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451 |
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452 |
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453 |
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454 |
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455 |
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| 460 |
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456 |
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"(35, 22.5625, 94864.25)" |
457 |
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| 462 |
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458 |
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459 |
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460 |
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461 |
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462 |
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463 |
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| 468 |
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464 |
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"(36, 22.5625, 94864.25)" |
465 |
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| 470 |
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466 |
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467 |
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468 |
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469 |
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470 |
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471 |
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| 476 |
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472 |
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"(37, 22.5625, 94866.75)" |
473 |
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| 478 |
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474 |
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475 |
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476 |
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477 |
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478 |
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479 |
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480 |
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"(38, 22.5625, 94866.75)" |
481 |
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482 |
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483 |
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484 |
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485 |
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486 |
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487 |
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488 |
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"(39, 22.5625, 94870.5)" |
489 |
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490 |
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491 |
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492 |
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493 |
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494 |
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495 |
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496 |
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"(40, 22.5625, 94870.5)" |
497 |
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498 |
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499 |
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500 |
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501 |
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503 |
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504 |
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"(41, 22.5625, 94870.5)" |
505 |
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506 |
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507 |
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508 |
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509 |
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510 |
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511 |
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512 |
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"(42, 22.5625, 94868.75)" |
513 |
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514 |
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515 |
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516 |
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517 |
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518 |
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519 |
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520 |
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"(43, 22.5625, 94868.75)" |
521 |
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522 |
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523 |
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524 |
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525 |
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526 |
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527 |
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528 |
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"(44, 22.5625, 94868.0)" |
529 |
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530 |
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531 |
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532 |
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533 |
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534 |
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535 |
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| 540 |
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536 |
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"(45, 22.5625, 94868.0)" |
537 |
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538 |
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539 |
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540 |
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541 |
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542 |
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543 |
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544 |
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"(46, 22.5625, 94870.0)" |
545 |
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546 |
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547 |
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548 |
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549 |
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550 |
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551 |
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552 |
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"(47, 22.5625, 94870.0)" |
553 |
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554 |
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555 |
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556 |
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557 |
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558 |
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559 |
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560 |
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"(48, 22.5625, 94868.5)" |
561 |
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562 |
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563 |
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564 |
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565 |
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567 |
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568 |
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"(49, 22.5625, 94868.5)" |
569 |
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570 |
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571 |
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572 |
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573 |
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574 |
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575 |
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576 |
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577 |
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578 |
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579 |
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580 |
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581 |
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582 |
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583 |
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584 |
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585 |
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586 |
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587 |
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588 |
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589 |
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590 |
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591 |
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592 |
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593 |
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594 |
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595 |
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596 |
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598 |
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599 |
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600 |
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601 |
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602 |
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603 |
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604 |
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607 |
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608 |
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609 |
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610 |
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611 |
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612 |
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613 |
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614 |
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615 |
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616 |
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"(55, 22.625, 94870.75)" |
617 |
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| 622 |
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618 |
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619 |
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620 |
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621 |
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622 |
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623 |
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624 |
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625 |
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626 |
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627 |
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628 |
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629 |
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630 |
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632 |
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633 |
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634 |
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635 |
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636 |
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637 |
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639 |
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640 |
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641 |
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642 |
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643 |
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644 |
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645 |
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648 |
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649 |
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650 |
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651 |
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652 |
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656 |
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657 |
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658 |
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659 |
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660 |
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663 |
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664 |
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665 |
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666 |
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667 |
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668 |
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669 |
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670 |
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671 |
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672 |
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673 |
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674 |
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675 |
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676 |
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680 |
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681 |
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682 |
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683 |
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684 |
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686 |
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688 |
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689 |
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690 |
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691 |
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692 |
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695 |
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696 |
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698 |
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699 |
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701 |
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703 |
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704 |
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705 |
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706 |
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707 |
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708 |
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709 |
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710 |
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711 |
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712 |
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713 |
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714 |
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715 |
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716 |
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717 |
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718 |
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719 |
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720 |
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721 |
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722 |
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723 |
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724 |
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725 |
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726 |
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727 |
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728 |
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729 |
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730 |
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731 |
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732 |
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733 |
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734 |
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735 |
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736 |
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737 |
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738 |
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739 |
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740 |
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741 |
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743 |
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744 |
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745 |
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746 |
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747 |
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748 |
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749 |
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750 |
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751 |
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752 |
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"(72, 22.5625, 94868.0)" |
753 |
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754 |
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755 |
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756 |
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757 |
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759 |
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760 |
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761 |
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762 |
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763 |
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764 |
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766 |
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767 |
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768 |
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"(74, 22.5625, 94870.25)" |
769 |
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770 |
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771 |
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772 |
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774 |
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775 |
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9XbqkLJrs6XFO5KK5GWvXrsXrr7+OqKgo5ObmYtOmTYiPjw96j5hD14rXyw5s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\ngQSdIAjCJZCgEwRBuAQSdIIgCJfw/31tYjp3QHiTAAAAAElFTkSuQmCC\n" 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1074 |
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lM5Md3A0Nxt5nV+TiJkE3WuEC2OPQ4+OZiFlxL1gRtchFa0yC0w5dPvhK3Ffk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\nHr14Uf2G0lLIoXMIL4Lety/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|
| - |
|
1075 |
"text": [ |
| - |
|
1076 |
"<matplotlib.figure.Figure at 0x9eb46cc>" |
| - |
|
1077 |
] |
| 1074 |
} |
1078 |
} |
| 1075 |
], |
1079 |
], |
| 1076 |
"prompt_number": 26 |
1080 |
"prompt_number": 9 |
| 1077 |
}, |
1081 |
}, |
| 1078 |
{ |
1082 |
{ |
| 1079 |
"cell_type": "code", |
1083 |
"cell_type": "code", |
| 1080 |
"collapsed": false, |
1084 |
"collapsed": false, |
| 1081 |
"input": [ |
1085 |
"input": [ |
| Line 1083... |
Line 1087... |
| 1083 |
], |
1087 |
], |
| 1084 |
"language": "python", |
1088 |
"language": "python", |
| 1085 |
"metadata": {}, |
1089 |
"metadata": {}, |
| 1086 |
"outputs": [ |
1090 |
"outputs": [ |
| 1087 |
{ |
1091 |
{ |
| - |
|
1092 |
"metadata": {}, |
| 1088 |
"output_type": "pyout", |
1093 |
"output_type": "pyout", |
| 1089 |
"prompt_number": 27, |
1094 |
"prompt_number": 11, |
| 1090 |
"text": [ |
1095 |
"text": [ |
| 1091 |
"[<matplotlib.lines.Line2D at 0x399a4d0>]" |
1096 |
"[<matplotlib.lines.Line2D at 0x9ee51ec>]" |
| 1092 |
] |
1097 |
] |
| 1093 |
}, |
1098 |
}, |
| 1094 |
{ |
1099 |
{ |
| - |
|
1100 |
"metadata": {}, |
| 1095 |
"output_type": "display_data", |
1101 |
"output_type": "display_data", |
| 1096 |
"png": 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EGqeGUQ8BrBWJJ6a2VVFRgYqKirD7HA5H2G2n0xlxbFtb2wKntjiJXvErClf8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\n" 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1102 |
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hISoqKlR5Lr4y3XM/c+ZMwhWT6eTprAQ/37QVc/78eaxfvx4tLS24+eabE+7T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\n", |
| - |
|
1103 |
"text": [ |
| - |
|
1104 |
"<matplotlib.figure.Figure at 0x9d764cc>" |
| - |
|
1105 |
] |
| 1097 |
} |
1106 |
} |
| 1098 |
], |
1107 |
], |
| 1099 |
"prompt_number": 27 |
1108 |
"prompt_number": 11 |
| 1100 |
}, |
1109 |
}, |
| 1101 |
{ |
1110 |
{ |
| 1102 |
"cell_type": "code", |
1111 |
"cell_type": "code", |
| 1103 |
"collapsed": false, |
1112 |
"collapsed": false, |
| 1104 |
"input": [], |
1113 |
"input": [], |