get_prism_bar_correction

msaexp.utils.get_prism_bar_correction(scaled_yshutter, num_shutters=3, wrap='auto', wrap_pad=0.2, mask=True, bar_data=None)

Generate the msaexp prism bar-shadow correction

Parameters

scaled_yshutterarray-like

Cross-dispersion pixel coordinates, scaled by a factor of 1/5 to roughly have units of the MSA shutters

num_shutters[1,2,3]

Number of shutters in the slitlet

wrapbool, str

If auto, determine if the bounds of scaled_yshutter are more than 0.5 shutters outside of the (-1.5, 1.5) range used to determine the correction. If so, or if wrap=True, replicate the center shutter to all specified shutters.

wrap_padfloat

If wrap, pad the outer edges that are unilluminated and won’t be properly calibrated

maskbool

Apply mask where the bar correction is within the shutter pixels of the calibration

bar_dataNone, dict

Correction data. If not specified, read from prism_{num_shutters}_bar_coeffs_wave.yaml

Returns

bararray-like

The estimated bar throughput. To correct, divide by bar

is_wrappedbool

Was the bar profile wrapped using the single central shutter, e.g., from wrap='auto'?

Examples

import numpy as np
import matplotlib.pyplot as plt
from msaexp.utils import get_prism_bar_correction

scaled_yshutter = np.linspace(-1.6, 1.6, 512)

fig, ax = plt.subplots(1,1,figsize=(6,4))

for n in [1,2,3]:
    bar, _wrapped = get_prism_bar_correction(scaled_yshutter,
                                             num_shutters=n,
                                             wrap=False)
    ax.plot(scaled_yshutter, bar, label=f'{n}-shutter', alpha=0.5)

ax.legend(loc='lower right', fontsize=6)
ax.grid()

ax.set_xlabel('scaled_yshutter = cross-dispersion pixel / 5')
ax.set_ylabel('bar shadow factor')

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

(Source code, png, hires.png, pdf)

import numpy as np
import matplotlib.pyplot as plt
import msaexp.utils

# 5-shutter slitlet
scaled_yshutter = np.linspace(-2.51, 2.51, 1024)

fig, ax = plt.subplots(1,1,figsize=(6,4))
bar, _wrapped = msaexp.utils.get_prism_bar_correction(scaled_yshutter)
ax.plot(scaled_yshutter, bar, label=f'wrapped: {_wrapped}')
ax.grid()
ax.legend()

ax.set_xlabel('scaled_yshutter = cross-dispersion pixel / 5')
ax.set_ylabel('bar shadow factor')

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

(Source code, png, hires.png, pdf)

slit_file = 'jw04233006001_03101_00002_nrs2_phot.076.4233_75646.fits'
slit = jwst.datamodels.open(slit_file)
# get the trace center
_trace = msaexp.utils.slit_trace_center(
    slit,
    with_source_xpos=False,
    with_source_ypos=False
)
# scaled coordinates
yp, xp = np.indices(slit.data.shape)
scaled_yshutter = (yp - _trace[1]) / 5
bar, _wrapped = msaexp.utils.get_prism_bar_correction(scaled_yshutter)

plt.imshow(bar, aspect='auto')