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Simplify examples

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This commit is contained in:
allegroai 2019-08-19 21:26:29 +03:00
parent d4358af1e8
commit f663add27d
2 changed files with 24 additions and 8 deletions
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19
examples/joblib_example.py
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@ -6,6 +6,8 @@ except ImportError:
from sklearn import datasets
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
import numpy as np
import matplotlib.pyplot as plt
from trains import Task
@ -25,4 +27,19 @@ joblib.dump(model, 'model.pkl', compress=True)
loaded_model = joblib.load('model.pkl')
result = loaded_model.score(X_test, y_test)
print(result)
x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5
h = .02 # step size in the mesh
xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
plt.figure(1, figsize=(4, 3))
plt.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k', cmap=plt.cm.Paired)
plt.xlabel('Sepal length')
plt.ylabel('Sepal width')
plt.xlim(xx.min(), xx.max())
plt.ylim(yy.min(), yy.max())
plt.xticks(())
plt.yticks(())
plt.show()

13
examples/manual_reporting.py
View File

@ -8,17 +8,12 @@ from trains import Task
task = Task.init(project_name='examples', task_name='Manual reporting')
# standard python logging
logging.getLogger().setLevel('DEBUG')
logging.debug('This is a debug message')
logging.info('This is an info message')
logging.warning('This is a warning message')
logging.error('This is an error message')
logging.critical('This is a critical message')
# this is loguru test example
try:
from loguru import logger
logger.debug("That's it, beautiful and simple logging! (using ANSI colors)")
logger.info("That's it, beautiful and simple logging! (using ANSI colors)")
except ImportError:
pass
@ -40,6 +35,10 @@ logger.report_histogram("example_histogram", "random histogram", iteration=1, va
confusion = np.random.randint(10, size=(10, 10))
logger.report_matrix("example_confusion", "ignored", iteration=1, matrix=confusion)
# report 3d surface
logger.report_surface("example_surface", "series1", iteration=1, matrix=confusion,
xtitle='title X', ytitle='title Y', ztitle='title Z')
# report 2d scatter plot
scatter2d = np.hstack((np.atleast_2d(np.arange(0, 10)).T, np.random.randint(10, size=(10, 1))))
logger.report_scatter2d("example_scatter", "series_xy", iteration=1, scatter=scatter2d)
@ -48,7 +47,7 @@ logger.report_scatter2d("example_scatter", "series_xy", iteration=1, scatter=sca
scatter3d = np.random.randint(10, size=(10, 3))
logger.report_scatter3d("example_scatter_3d", "series_xyz", iteration=1, scatter=scatter3d)
# report images
# reporting images
m = np.eye(256, 256, dtype=np.float)
logger.report_image_and_upload("test case", "image float", iteration=1, matrix=m)
m = np.eye(256, 256, dtype=np.uint8)*255