2D Plots Reporting

The scatter_hist_confusion_mat_reporting.py example demonstrates reporting series data as 2D plots in histogram, confusion matrix, and 2D scatter plot formats.

ClearML reports these tables in the ClearML Web UI, experiment details, RESULTS tab, PLOTS sub-tab.

When the script runs, it creates an experiment named 2D plots reporting, which is associated with the examples project.

Histograms

Report histograms by calling the Logger.report_histogram method. To report more than one series on the same plot, use same the title argument. For different plots, use different title arguments. Set the mode parameter for the type of histogram. The mode values are group (the default), stack, and relative.

# report a single histogram
histogram = np.random.randint(10, size=10)
Logger.current_logger().report_histogram(
    "single_histogram",
    "random histogram",
    iteration=iteration,
    values=histogram,
    xaxis="title x",
    yaxis="title y",
)

# report a two histograms on the same graph (plot)
histogram1 = np.random.randint(13, size=10)
histogram2 = histogram * 0.75
Logger.current_logger().report_histogram(
    "two_histogram",
    "series 1",
    iteration=iteration,
    values=histogram1,
    xaxis="title x",
    yaxis="title y",
)

Logger.current_logger().report_histogram(
    "two_histogram",
    "series 2",
    iteration=iteration,
    values=histogram2,
    xaxis="title x",
    yaxis="title y",
    )

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Confusion Matrices

Report confusion matrices by calling the Logger.report_matrix method.

# report confusion matrix
confusion = np.random.randint(10, size=(10, 10))
Logger.current_logger().report_matrix(
    "example_confusion",
    "ignored",
    iteration=iteration,
    matrix=confusion,
    xaxis="title X",
    yaxis="title Y",
    )

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# report confusion matrix with 0,0 is at the top left
Logger.current_logger().report_matrix(
    "example_confusion_0_0_at_top",
    "ignored",
    iteration=iteration,
    matrix=confusion,
    xaxis="title X",
    yaxis="title Y",
    yaxis_reversed=True,
)

2D scatter plots

Report 2D scatter plots by calling the Logger.report_scatter2d method. Use the mode parameter to plot data points as markers, or both lines and markers.

scatter2d = np.hstack(
    (np.atleast_2d(np.arange(0, 10)).T, np.random.randint(10, size=(10, 1)))
)

# report 2d scatter plot with lines
Logger.current_logger().report_scatter2d(
    "example_scatter",
    "series_xy",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
    yaxis="title y",
)

# report 2d scatter plot with markers
Logger.current_logger().report_scatter2d(
    "example_scatter",
    "series_markers",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
    yaxis="title y",
    mode='markers'
)

# report 2d scatter plot with markers
Logger.current_logger().report_scatter2d(
    "example_scatter",
    "series_lines+markers",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
    yaxis="title y",
    mode='lines+markers'
)

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