Python CameraDisplay.set_limits_percent方法代码示例

# 需要导入模块: from ctapipe.visualization import CameraDisplay [as 别名]
# 或者: from ctapipe.visualization.CameraDisplay import set_limits_percent [as 别名]
def display_event(event, geoms):
    """an extremely inefficient display. It creates new instances of
    CameraDisplay for every event and every camera, and also new axes
    for each event. It's hacked, but it works
    """
    print("Displaying... please wait (this is an inefficient implementation)")
    global fig
    ntels = len(event.r0.tels_with_data)
    fig.clear()

    plt.suptitle("EVENT {}".format(event.r0.event_id))

    disps = []

    for ii, tel_id in enumerate(event.r0.tels_with_data):
        print("\t draw cam {}...".format(tel_id))
        nn = int(ceil(sqrt(ntels)))
        ax = plt.subplot(nn, nn, ii + 1)

        x, y = event.inst.pixel_pos[tel_id]
        geom = geoms[tel_id]
        disp = CameraDisplay(geom, ax=ax, title="CT{0}".format(tel_id))
        disp.pixels.set_antialiaseds(False)
        disp.autoupdate = False
        disp.cmap = 'afmhot'
        chan = 0
        signals = event.r0.tel[tel_id].adc_sums[chan].astype(float)
        signals -= signals.mean()
        disp.image = signals
        disp.set_limits_percent(95)
        disp.add_colorbar()
        disps.append(disp)

    return disps

# 需要导入模块: from ctapipe.visualization import CameraDisplay [as 别名]
# 或者: from ctapipe.visualization.CameraDisplay import set_limits_percent [as 别名]
def draw_several_cams(geom, ncams=4):

    cmaps = ['jet', 'afmhot', 'terrain', 'autumn']
    fig, axs = plt.subplots(
        1, ncams, figsize=(15, 4),
    )

    for ii in range(ncams):
        disp = CameraDisplay(
            geom,
            ax=axs[ii],
            title="CT{}".format(ii + 1),
        )
        disp.cmap = cmaps[ii]

        model = toymodel.generate_2d_shower_model(
            centroid=(0.2 - ii * 0.1, -ii * 0.05),
            width=0.05 + 0.001 * ii,
            length=0.15 + 0.05 * ii,
            psi=ii * 20 * u.deg,
        )

        image, sig, bg = toymodel.make_toymodel_shower_image(
            geom,
            model.pdf,
            intensity=1500,
            nsb_level_pe=5,
        )

        mask = tailcuts_clean(
            geom,
            image,
            picture_thresh=6 * image.mean(),
            boundary_thresh=4 * image.mean()
        )
        cleaned = image.copy()
        cleaned[~mask] = 0

        hillas = hillas_parameters(geom, cleaned)

        disp.image = image
        disp.add_colorbar(ax=axs[ii])

        disp.set_limits_percent(95)
        disp.overlay_moments(hillas, linewidth=3, color='blue')

# 需要导入模块: from ctapipe.visualization import CameraDisplay [as 别名]
# 或者: from ctapipe.visualization.CameraDisplay import set_limits_percent [as 别名]
    def start(self):

        disp = None

        for event in tqdm(self.source,
                          desc='Tel{}'.format(self.tel),
                          total=self.reader.max_events,
                          disable=~self.progress):

            self.log.debug(event.trig)
            self.log.debug("Energy: {}".format(event.mc.energy))

            self.calibrator.calibrate(event)

            if disp is None:
                x, y = event.inst.pixel_pos[self.tel]
                focal_len = event.inst.optical_foclen[self.tel]
                geom = CameraGeometry.guess(x, y, focal_len)
                self.log.info(geom)
                disp = CameraDisplay(geom)
                # disp.enable_pixel_picker()
                disp.add_colorbar()
                if self.display:
                    plt.show(block=False)

            # display the event
            disp.axes.set_title('CT{:03d} ({}), event {:06d}'.format(
                self.tel, geom.cam_id, event.r0.event_id)
            )

            if self.samples:
                # display time-varying event
                data = event.dl0.tel[self.tel].pe_samples[self.channel]
                for ii in range(data.shape[1]):
                    disp.image = data[:, ii]
                    disp.set_limits_percent(70)
                    plt.suptitle("Sample {:03d}".format(ii))
                    if self.display:
                        plt.pause(self.delay)
                    if self.write:
                        plt.savefig('CT{:03d}_EV{:10d}_S{:02d}.png'
                                    .format(self.tel, event.r0.event_id, ii))
            else:
                # display integrated event:
                im = event.dl1.tel[self.tel].image[self.channel]

                if self.clean:
                    mask = tailcuts_clean(geom, im, picture_thresh=10,
                                          boundary_thresh=7)
                    im[~mask] = 0.0

                disp.image = im

                if self.hillas:
                    try:
                        ellipses = disp.axes.findobj(Ellipse)
                        if len(ellipses) > 0:
                            ellipses[0].remove()

                        params = hillas_parameters(pix_x=geom.pix_x,
                                                   pix_y=geom.pix_y, image=im)
                        disp.overlay_moments(params, color='pink', lw=3,
                                             with_label=False)
                    except HillasParameterizationError:
                        pass

                if self.display:
                    plt.pause(self.delay)
                if self.write:
                    plt.savefig('CT{:03d}_EV{:010d}.png'
                                .format(self.tel, event.r0.event_id))

        self.log.info("FINISHED READING DATA FILE")

        if disp is None:
            self.log.warning('No events for tel {} were found in {}. Try a '
                             'different EventIO file or another telescope'
                             .format(self.tel, self.infile),
                             )

        pass