Module themisasi.projections

Functions

def asi_projection(dat, projalt_m=None, min_el=10.0, ofn=None)

plots ASI projected to altitude

• dat: Xarray containing image stack and metadata (az, el, lat, lon)
• projalt_m: projection altitude in meters
• min_el: minimum elevation angle (degrees). Data near the horizon is poorly calibrated (large angular error).
• ofn: filename to write of plot (optional)

Source code

def asi_projection(dat: xarray.Dataset,
                   projalt_m: float = None,
                   min_el: float = 10.,
                   ofn: Path = None):
    """
    plots ASI projected to altitude

    * dat: Xarray containing image stack and metadata (az, el, lat, lon)
    * projalt_m: projection altitude in meters
    * min_el: minimum elevation angle (degrees). Data near the horizon is poorly calibrated (large angular error).
    * ofn: filename to write of plot (optional)
    """
    if projalt_m is None:
        logging.error('projection altitude must be specified')
        return

    if dat['imgs'].shape[0] == 0:
        return

    if ofn:
        ofn = Path(ofn).expanduser()
        odir = ofn.parent

# %% censor pixels near the horizon with large calibration error do to poor skymap fits
    badpix = dat['el'] < min_el
    az = dat['az'].values
    el = dat['el'].values
    az[badpix] = np.nan
    el[badpix] = np.nan
# %% coordinate transformation, let us know if error occurs
    slant_range = projalt_m / np.sin(np.radians(el))

    lat, lon, alt = pm.aer2geodetic(az, el, slant_range,
                                    dat.lat.item(), dat.lon.item(), dat.alt_m.item())
# %% plots
    fg = figure()
    ax = fg.gca()

    hi = pcolormesh_nan(lon, lat, dat['imgs'][0], cmap='gray', axis=ax)  # priming

    ttxt = f'Themis ASI {dat.site}  projected to altitude {projalt_m/1e3} km\n'  # FOV vs. HST0,HST1: green,red '
    ht = ax.set_title(ttxt, color='g')
    ax.set_xlabel('longitude')
    ax.set_ylabel('latitude')
    ax.autoscale(True, tight=True)
    ax.grid(False)
# %% plot narrow FOV outline
    if 'imgs2' in dat:
        overlayrowcol(ax, dat.rows, dat.cols)
# %% play video
    try:
        for im in dat['imgs']:
            ts = im.time.values.astype(str)[:-6]
            hi.set_array(im.values.ravel())  # for pcolormesh
            ht.set_text(ttxt + ts)
            draw()
            pause(0.01)
            if ofn:
                fn = odir / (ofn.stem + ts + ofn.suffix)
                print('saving', fn, end='\r')
                fg.savefig(fn, bbox_inches='tight', facecolor='k')
    except KeyboardInterrupt:
        return

def asi_radec(dat, min_el=10.0, ofn=None)

plots ASI projected to altitude

• min_el: minimum elevation angle (degrees). Data near the horizon is poorly calibrated (large angular error).
• ofn: filename to write of plot (optional)

Source code

def asi_radec(dat: xarray.Dataset,
              min_el: float = 10.,
              ofn: Path = None):
    """
    plots ASI projected to altitude

    * min_el: minimum elevation angle (degrees). Data near the horizon is poorly calibrated (large angular error).
    * ofn: filename to write of plot (optional)
    """

    if dat['imgs'].shape[0] == 0:
        return

    if ofn:
        ofn = Path(ofn).expanduser()

    az = dat.az.values
    el = dat.el.values
    az.setflags(write=True)
    el.setflags(write=True)

    bad = el < min_el  # low to horizon, calibration is very bad
    az[bad] = np.nan
    el[bad] = np.nan

    ra, dec = pm.azel2radec(az, el, dat.lat, dat.lon, dat.time)

    fg = figure()
    ax = fg.gca()

    pcolormesh_nan(ra, dec, dat['imgs'].values[0], cmap='gray', axis=ax)  # priming

    ttxt = f'Themis ASI {dat.site}  \n'
    ax.set_title(ttxt, color='g')
    ax.set_xlabel('right ascension [deg]')
    ax.set_ylabel('declination [deg]')
    ax.autoscale(True, tight=True)
    ax.grid(False)