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90 lines
3.1 KiB
Python
90 lines
3.1 KiB
Python
# TRAINS - Example of manual graphs and statistics reporting
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#
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import os
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from PIL import Image
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import numpy as np
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import logging
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from trains import Task
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task = Task.init(project_name="examples", task_name="Manual reporting")
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# standard python logging
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logging.info("This is an info message")
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# this is loguru test example
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try:
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from loguru import logger
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logger.info("That's it, beautiful and simple logging! (using ANSI colors)")
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except ImportError:
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pass
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# get TRAINS logger object for any metrics / reports
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logger = Task.current_task().get_logger()
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# log text
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logger.report_text("hello")
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# report scalar values
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logger.report_scalar("example_scalar", "series A", iteration=0, value=100)
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logger.report_scalar("example_scalar", "series A", iteration=1, value=200)
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# report histogram
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histogram = np.random.randint(10, size=10)
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logger.report_histogram("example_histogram", "random histogram", iteration=1, values=histogram,
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xaxis="title x", yaxis="title y")
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# report confusion matrix
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confusion = np.random.randint(10, size=(10, 10))
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logger.report_matrix("example_confusion", "ignored", iteration=1, matrix=confusion, xaxis="title X", yaxis="title Y")
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# report 3d surface
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logger.report_surface("example_surface", "series1", iteration=1, matrix=confusion,
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xaxis="title X", yaxis="title Y", zaxis="title Z")
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# report 2d scatter plot
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scatter2d = np.hstack((np.atleast_2d(np.arange(0, 10)).T, np.random.randint(10, size=(10, 1))))
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logger.report_scatter2d("example_scatter", "series_xy", iteration=1, scatter=scatter2d,
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xaxis="title x", yaxis="title y")
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# report 3d scatter plot
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scatter3d = np.random.randint(10, size=(10, 3))
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logger.report_scatter3d("example_scatter_3d", "series_xyz", iteration=1, scatter=scatter3d,
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xaxis="title x", yaxis="title y", zaxis="title z")
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# reporting images
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m = np.eye(256, 256, dtype=np.float)
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logger.report_image("test case", "image float", iteration=1, image=m)
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m = np.eye(256, 256, dtype=np.uint8)*255
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logger.report_image("test case", "image uint8", iteration=1, image=m)
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m = np.concatenate((np.atleast_3d(m), np.zeros((256, 256, 2), dtype=np.uint8)), axis=2)
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logger.report_image("test case", "image color red", iteration=1, image=m)
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image_open = Image.open(os.path.join("samples", "picasso.jpg"))
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logger.report_image("test case", "image PIL", iteration=1, image=image_open)
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# reporting tables
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try:
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import pandas as pd
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# Report table - DataFrame with index
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df = pd.DataFrame(
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{
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'num_legs': [2, 4, 8, 0],
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'num_wings': [2, 0, 0, 0],
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'num_specimen_seen': [10, 2, 1, 8]
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},
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index=['falcon', 'dog', 'spider', 'fish']
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)
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df.index.name = 'id'
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logger.report_table("test table pd", "PD with index", 1, table_plot=df)
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# Report table - CSV from path
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csv_url = "https://raw.githubusercontent.com/plotly/datasets/master/Mining-BTC-180.csv"
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logger.report_table("test table csv", "remote csv", 1, url=csv_url)
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except ImportError:
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pass
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# flush reports (otherwise it will be flushed in the background, every couple of seconds)
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logger.flush()
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