def make_label_fig()

in data_measurements/labels/labels.py [0:0]

• 25 lines of code
• 5 McCabe index (conditional complexity)

def make_label_fig(label_results, chart_type="pie"):
    try:
        label_names = label_results[LABEL_NAMES]
        label_measurement = label_results[LABEL_MEASUREMENT]
        label_sums = label_measurement[EVAL_LABEL_SUM]
        if chart_type == "bar":
            fig_labels = plt.bar(
                label_measurement[EVAL_LABEL_MEASURE][EVAL_LABEL_ID],
                label_measurement[EVAL_LABEL_MEASURE][EVAL_LABEL_FRAC])
        else:
            if chart_type != "pie":
                logs.info("Oops! Don't have that chart-type implemented.")
                logs.info("Making the default pie chart")
            # IMDB - unsupervised has a labels column where all values are -1,
            # which breaks the assumption that
            # the number of label_names == the number of label_sums.
            # This handles that case, assuming it will happen in other datasets.
            if len(label_names) != len(label_sums):
                logs.warning("Can't make a figure with the given label names: "
                             "We don't have the right amount of label types "
                             "to apply them to!")
                return False
            fig_labels = px.pie(names=label_names, values=label_sums)
    except KeyError:
        logs.info("Input label data missing required key(s).")
        logs.info("We require %s, %s" % (LABEL_NAMES, LABEL_MEASUREMENT))
        logs.info("We found: %s" % ",".join(label_results.keys()))
        return False
    return fig_labels