|
67 | 67 | "cell_type": "markdown", |
68 | 68 | "metadata": {}, |
69 | 69 | "source": [ |
70 | | - "### Create a session and login" |
| 70 | + "### Create a session and log in" |
71 | 71 | ] |
72 | 72 | }, |
73 | 73 | { |
|
231 | 231 | "cell_type": "markdown", |
232 | 232 | "metadata": {}, |
233 | 233 | "source": [ |
234 | | - "The downloaded results file is a summary of all the operator output in the workflow. In particular, it's a json file that we can manipulate or save to disk." |
| 234 | + "The downloaded results file is a summary of all the operator output in the workflow. In particular, it is a JSON file that we can manipulate or save to disk." |
235 | 235 | ] |
236 | 236 | }, |
237 | 237 | { |
|
254 | 254 | "source": [ |
255 | 255 | "### Parsing workflow results\n", |
256 | 256 | "\n", |
257 | | - "When we convert the downloaded results to a Python object we get a nested dictionary/list object. I'm pulling two values out of the results: \n", |
| 257 | + "When we convert the downloaded results to a Python object we get a nested dictionary/list object. Here we're pulling two values out of the results: \n", |
258 | 258 | "\n", |
259 | 259 | "1. The overall prediction accuracy. This comes from the *Confusion Matrix* operator.\n", |
260 | 260 | "2. The number of trees. This comes from the *Alpine Forest Classification* operator.\n", |
|
290 | 290 | "source": [ |
291 | 291 | "### Workflow variables\n", |
292 | 292 | "\n", |
293 | | - "Variables with different values can be inserted into workflows. They have to be formatted as below and are passed as an optioned argument to workflow run method." |
| 293 | + "Variables with different values can be inserted into workflows. They have to be formatted as below and are passed as an optioned argument to the workflow run method." |
294 | 294 | ] |
295 | 295 | }, |
296 | 296 | { |
|
349 | 349 | "name": "stdout", |
350 | 350 | "output_type": "stream", |
351 | 351 | "text": [ |
352 | | - "Running with work flow variable: [{'name': '@n_trees', 'value': '5'}]\n", |
| 352 | + "Running with workflow variable: [{'name': '@n_trees', 'value': '5'}]\n", |
353 | 353 | "Workflow in progress for ~191.1 seconds. \n", |
354 | 354 | "For 5 trees, test accuracy is 0.8530647\n", |
355 | 355 | "\n", |
356 | | - "Running with work flow variable: [{'name': '@n_trees', 'value': '10'}]\n", |
| 356 | + "Running with workflow variable: [{'name': '@n_trees', 'value': '10'}]\n", |
357 | 357 | "Workflow in progress for ~207.0 seconds. \n", |
358 | 358 | "For 10 trees, test accuracy is 0.861461\n", |
359 | 359 | "\n", |
360 | | - "Running with work flow variable: [{'name': '@n_trees', 'value': '25'}]\n", |
| 360 | + "Running with workflow variable: [{'name': '@n_trees', 'value': '25'}]\n", |
361 | 361 | "Workflow in progress for ~250.3 seconds. \n", |
362 | 362 | "For 25 trees, test accuracy is 0.8709068\n", |
363 | 363 | "\n", |
364 | | - "Running with work flow variable: [{'name': '@n_trees', 'value': '50'}]\n", |
| 364 | + "Running with workflow variable: [{'name': '@n_trees', 'value': '50'}]\n", |
365 | 365 | "Workflow in progress for ~311.6 seconds. \n", |
366 | 366 | "For 50 trees, test accuracy is 0.875105\n", |
367 | 367 | "\n", |
368 | | - "Running with work flow variable: [{'name': '@n_trees', 'value': '75'}]\n", |
| 368 | + "Running with workflow variable: [{'name': '@n_trees', 'value': '75'}]\n", |
369 | 369 | "Workflow in progress for ~363.1 seconds. \n", |
370 | 370 | "For 75 trees, test accuracy is 0.877204\n", |
371 | 371 | "\n" |
|
376 | 376 | "test_acc = []\n", |
377 | 377 | "\n", |
378 | 378 | "for variable in variables:\n", |
379 | | - " print(\"Running with work flow variable: {}\".format(variable))\n", |
| 379 | + " print(\"Running with workflow variable: {}\".format(variable))\n", |
380 | 380 | " process_id = session.workfile.process.run(workflow_id, variables=variable)\n", |
381 | 381 | " session.workfile.process.wait_until_finished(workflow_id, process_id, verbose=True, query_time=5, timeout=1000)\n", |
382 | 382 | " \n", |
|
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