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# Decode and plot Waveform Data

This example illustrates how to plot waveforms from a Waveform Sequence using matplotlib.

    import numpy as np
    import matplotlib.pyplot as plt

    from pydicom import dcmread
    from pydicom.data import get_testdata_file
    from pydicom.waveforms import generate_multiplex

    fpath = get_testdata_file("waveform_ecg.dcm")
    ds = dcmread(fpath)

    # Plot the first channel of each multiplex
    ch_idx = 0
    # We could also use ds.waveform_array()
    fig, axes = plt.subplots(len(ds.WaveformSequence))
    generator = generate_multiplex(ds, as_raw=False)
    for ax, mplx, arr in zip(axes, ds.WaveformSequence, generator):
        nr_channels = mplx.NumberOfWaveformChannels
        nr_samples = mplx.NumberOfWaveformSamples
        sampling_fq = mplx.SamplingFrequency  # in Hz
        mplx_label = mplx.MultiplexGroupLabel

        ch_item = mplx.ChannelDefinitionSequence[ch_idx]

        x = np.arange(0, nr_samples / sampling_fq, 1 / sampling_fq)
        x_units = "seconds"

        # ChannelSensitivityUnitsSequence is type 1C, so check it's there
        if "ChannelSensitivityUnitsSequence" in ch_item:
            y_units = ch_item.ChannelSensitivityUnitsSequence[0].CodeMeaning
        else:
            y_units = "unitless"

        # Description of the channel source
        ch_source = ch_item.ChannelSourceSequence[0].CodeMeaning

        ax.plot(x, arr[..., ch_idx])
        ax.set_title(f"{mplx_label}: {ch_source}")
        ax.set_xlabel(f"({x_units})")
        ax.set_ylabel(f"({y_units})")

    fig.tight_layout(pad=1)
    plt.show()

Total running time of the script: ( 0 minutes 0.146 seconds)

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