Source code for nectarchain.display.display

import logging
from abc import ABC

import numpy as np
from ctapipe.visualization import CameraDisplay
from matplotlib import pyplot as plt

from ..data.container import ArrayDataContainer, ChargesContainer, WaveformsContainer

logging.basicConfig(format="%(asctime)s %(name)s %(levelname)s %(message)s")
log = logging.getLogger(__name__)
log.handlers = logging.getLogger("__main__").handlers

__all__ = ["ContainerDisplay"]




class ContainerDisplay(ABC):


    @staticmethod
    def display(container: ArrayDataContainer, evt, geometry, cmap="gnuplot2"):
        """plot camera display for HIGH GAIN channel

        Args:
            evt (int): event index
            cmap (str, optional): colormap. Defaults to 'gnuplot2'.

        Returns:
            CameraDisplay: thoe cameraDisplay plot
        """
        if isinstance(container, ChargesContainer):
            image = container.charges_hg
            pixels_id = container.pixels_id
        elif isinstance(container, WaveformsContainer):
            image = container.wfs_hg.mean(axis=2)
            pixels_id = container.pixels_id
        else:
            log.error(
                "container can't be displayed, must be a ChargesContainer or a\
                    WaveformsContainer"
            )
            raise Exception(
                "container can't be displayed, must be a ChargesContainer or a\
                WaveformsContainer"
            )

        highlighten_pixels = np.array([], dtype=int)
        if geometry.pix_id.value.shape[0] != image.shape[1]:
            mask = np.array([_id in pixels_id for _id in geometry.pix_id.value])
            missing_pixels = np.array(geometry.pix_id.value[~mask], dtype=int)

            missing_values = np.empty((image.shape[0], missing_pixels.shape[0]))
            missing_values.fill(np.nan)
            highlighten_pixels = np.concatenate((highlighten_pixels, missing_pixels))

            image = np.concatenate((missing_values, image), axis=1)
            pixels_id = np.concatenate((missing_pixels, pixels_id))
        sort_index = [np.where(pixels_id == pix)[0][0] for pix in geometry.pix_id.value]
        image = image.T[sort_index].T

        disp = CameraDisplay(geometry=geometry, image=image[evt], cmap=cmap)
        disp.highlight_pixels(highlighten_pixels, color="r", linewidth=2)
        disp.add_colorbar(label="ADC")
        return {"disp": disp, "highlighten_pixels": highlighten_pixels}




    @staticmethod
    def plot_waveform(waveformsContainer: WaveformsContainer, evt, **kwargs):
        """plot the waveform of the evt in the HIGH GAIN channel

        Args:
            evt (int): the event index

        Returns:
            tuple: the figure and axes
        """
        if "figure" in kwargs.keys() and "ax" in kwargs.keys():
            fig = kwargs.get("figure")
            ax = kwargs.get("ax")
        else:
            fig, ax = plt.subplots(1, 1)
        ax.plot(waveformsContainer.wfs_hg[evt].T)
        return fig, ax