| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import random | |
| import os | |
| def random_plot(): | |
| start_year = 2020 | |
| x = np.arange(start_year, start_year + random.randint(0, 10)) | |
| year_count = x.shape[0] | |
| plt_format = "-" | |
| fig = plt.figure() | |
| ax = fig.add_subplot(111) | |
| series = np.arange(0, year_count, dtype=float) | |
| series = series**2 | |
| series += np.random.rand(year_count) | |
| ax.plot(x, series, plt_format) | |
| return fig | |
| img_dir = os.path.join(os.path.dirname(__file__), "files") | |
| file_dir = os.path.join(os.path.dirname(__file__), "..", "kitchen_sink", "files") | |
| model3d_dir = os.path.join(os.path.dirname(__file__), "..", "model3D", "files") | |
| highlighted_text_output_1 = [ | |
| { | |
| "entity": "I-LOC", | |
| "score": 0.9988978, | |
| "index": 2, | |
| "word": "Chicago", | |
| "start": 5, | |
| "end": 12, | |
| }, | |
| { | |
| "entity": "I-MISC", | |
| "score": 0.9958592, | |
| "index": 5, | |
| "word": "Pakistani", | |
| "start": 22, | |
| "end": 31, | |
| }, | |
| ] | |
| highlighted_text_output_2 = [ | |
| { | |
| "entity": "I-LOC", | |
| "score": 0.9988978, | |
| "index": 2, | |
| "word": "Chicago", | |
| "start": 5, | |
| "end": 12, | |
| }, | |
| { | |
| "entity": "I-LOC", | |
| "score": 0.9958592, | |
| "index": 5, | |
| "word": "Pakistan", | |
| "start": 22, | |
| "end": 30, | |
| }, | |
| ] | |
| highlighted_text = "Does Chicago have any Pakistani restaurants" | |
| def random_model3d(): | |
| model_3d = random.choice( | |
| [os.path.join(model3d_dir, model) for model in os.listdir(model3d_dir) if model != "source.txt"] | |
| ) | |
| return model_3d | |