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2D Plots Reporting

The scatter_hist_confusion_mat_reporting.py example demonstrates reporting series data in the following 2D formats:

ClearML reports these tables in the ClearML Web UI > task's PLOTS tab.

When the script runs, it creates a task named 2D plots reporting in the examples project.

Histograms​

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

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

Single histogram Single histogram

Double histogram Double histogram

Confusion Matrices​

Report confusion matrices by calling Logger.report_confusion_matrix().

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

Confusion matrix Confusion matrix

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

Confusion matrix Confusion matrix

2D Scatter Plots​

Report 2D scatter plots by calling Logger.report_scatter2d(). Use the mode parameter to plot data points with lines (by default), 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(
    title="example_scatter",
    series="series_xy",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
    yaxis="title y",
)
    
# report 2d scatter plot with markers
Logger.current_logger().report_scatter2d(
    title="example_scatter",
    series="series_markers",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
    yaxis="title y",
    mode='markers'
)
    
# report 2d scatter plot with lines and markers
Logger.current_logger().report_scatter2d(
    title="example_scatter",
    series="series_lines+markers",
    iteration=iteration,
    scatter=scatter2d,
    xaxis="title x",
    yaxis="title y",
    mode='lines+markers'
)

Scatter plot Scatter plot