Dispersed Image Trade Study#

[1]:

import pathlib

import astropy.units as u
import numpy as np
import matplotlib.pyplot as plt
from astropy.visualization import quantity_support, ImageNormalize, LogStretch
from astropy.coordinates import SkyCoord
from astropy.wcs.utils import wcs_to_celestial_frame
import ndcube
from sunpy.map import extract_along_coord
from overlappy.io import read_overlappogram
from overlappy.util import color_lat_lon_axes

from mocksipipeline.detector.response import SpectrogramChannel
from mocksipipeline.detector.filter import ThinFilmFilter

Effective Area Curves#

The different configurations are:

Al, 100 nm w/o Au-Cr layer
Al, 100 nm
Al oxide, 100 nm
Al oxide, 200 nm
Al oxide with polymide, 200 nm
Al oxide with polymide, 300 nm

For case 0, we consider the case where there is no Au/Cr layer on the grating.

[2]:

al_thin = ThinFilmFilter(elements='Al', thickness=100*u.nm)

[3]:

al_thin_oxide = [
    ThinFilmFilter(elements='Al', thickness=93*u.nm),
    ThinFilmFilter(elements=['Al','O'], quantities=[2,3], thickness=7*u.nm),
]

[4]:

al_thick_oxide = [
    ThinFilmFilter(elements='Al', thickness=192*u.nm),
    ThinFilmFilter(elements=['Al','O'], quantities=[2,3], thickness=8*u.nm),
]

[5]:

polymide = ThinFilmFilter(elements=['C','H','N','O'],
                          quantities=[22,10,2,5],
                          density=1.43*u.g/u.cm**3,
                          thickness = 100*u.nm)

[6]:

al_poly_thin_oxide = al_thin_oxide + [polymide]

[7]:

al_poly_thick_oxide = al_thick_oxide + [polymide]

[15]:

plt.figure(figsize=(10,6))
with quantity_support():
    ch_no_au_cr = SpectrogramChannel(0, al_thin, include_au_cr=False)
    plt.plot(ch_no_au_cr.wavelength, ch_no_au_cr.wavelength_response, label=ch_no_au_cr.filter_label+', no Au-Cr layer')
    for filt in [al_thin, al_thin_oxide, al_thick_oxide, al_poly_thin_oxide, al_poly_thick_oxide]:
        ch = SpectrogramChannel(0, filt)
        plt.plot(ch.wavelength, ch.wavelength_response, label=ch.filter_label)
plt.yscale('log')
plt.legend()

[15]:

<matplotlib.legend.Legend at 0x7f9fffcb1720>

../_images/reports_dispersed-filter-trade-study_10_1.png

[12]:

case_labels = {
    'Case 0': SpectrogramChannel(0, al_thin).filter_label+', no Au-Cr layer',
    'Case 1': SpectrogramChannel(0, al_thin).filter_label,
    'Case 2': SpectrogramChannel(0, al_thin_oxide).filter_label,
    'Case 3': SpectrogramChannel(0, al_thick_oxide).filter_label,
    'Case 4': SpectrogramChannel(0, al_poly_thin_oxide).filter_label,
    'Case 5': SpectrogramChannel(0, al_poly_thick_oxide).filter_label,
}

Dispersed Images#

[10]:

from overlappy.io import read_overlappogram
from overlappy.util import strided_array
from ndcube import NDCube


def stack_components(components, wcs_index=0):
    layers = []
    for c in components:
        if isinstance(c, ndcube.NDCube):
            layers.append(c)
        else:
            layers.append(read_overlappogram(pathlib.Path(c)))
    data = np.array([l.data[0] for l in layers]).sum(axis=0)
    wcs = layers[wcs_index].wcs
    data_strided = strided_array(data, layers[wcs_index].data.shape[0])
    return NDCube(data_strided,
                  wcs=wcs,
                  unit=layers[wcs_index].unit,
                  meta=layers[wcs_index].meta)

[11]:

top_dir = pathlib.Path('/home/ubuntu/pipeline-runs/dispersed-filter-trade-study')

Case 0–Al thin, no Au-Cr coating#

This is the nominal case.

[12]:

dispersed_case0 = stack_components(
    sorted(list((top_dir / 'Al_100.000nm_no_au_cr/').glob('*.fits'))),
    wcs_index=2
)

[13]:

norm = ImageNormalize(vmin=0,vmax=50,stretch=LogStretch())
fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case0[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)

[13]:

(<astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592bbc3a60>,
 <astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592bbda050>)

../_images/reports_dispersed-filter-trade-study_17_1.png

Case 1#

Include Au-Cr coating on grating

[14]:

dispersed_case1 = stack_components(
    sorted(list((top_dir / 'Al_100.000nm/').glob('*.fits'))),
    wcs_index=2
)

[15]:

fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case1[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)

[15]:

(<astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a2d6380>,
 <astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a2d7a30>)

../_images/reports_dispersed-filter-trade-study_21_1.png

Case 2#

100 nm of aluminum with oxidation layer

[17]:

dispersed_case2 = stack_components(
    sorted(list((top_dir / 'Al+Al2O3_100.000nm/').glob('*.fits'))),
    wcs_index=2
)

[18]:

fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case2[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)

[18]:

(<astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a19d750>,
 <astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a19f1f0>)

../_images/reports_dispersed-filter-trade-study_24_1.png

Case 3#

200 nm of aluminum with oxidation layer

[19]:

dispersed_case3 = stack_components(
    sorted(list((top_dir / 'Al+Al2O3_200.000nm/').glob('*.fits'))),
    wcs_index=2
)

[20]:

fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case3[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)

[20]:

(<astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a03e560>,
 <astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a066440>)

../_images/reports_dispersed-filter-trade-study_27_1.png

Case 4#

Al poly thin (100 nm of poly) with aluminum oxide

[21]:

dispersed_case4 = stack_components(
    sorted(list((top_dir / 'Al+Al2O3+C22H10N2O5_200.000nm/').glob('*.fits'))),
    wcs_index=2
)

[22]:

fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case4[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)

[22]:

(<astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f592a0faf80>,
 <astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f5928840f70>)

../_images/reports_dispersed-filter-trade-study_30_1.png

Case 5#

Al poly thick (200 nm) aluminum oxide

[23]:

dispersed_case5 = stack_components(
    sorted(list((top_dir / 'Al+Al2O3+C22H10N2O5_300.000nm/').glob('*.fits'))),
    wcs_index=2
)

[24]:

fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case5[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)

[24]:

(<astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f59288d7610>,
 <astropy.visualization.wcsaxes.coordinate_helpers.CoordinateHelper at 0x7f59288fee00>)

../_images/reports_dispersed-filter-trade-study_33_1.png

Now, compare line plots from all 5 cases

[25]:

hpc_frame = wcs_to_celestial_frame(dispersed_case0.wcs)
coord = SkyCoord(Tx=75*u.arcsec, Ty=[-5600,5600]*u.arcsec, frame=hpc_frame)

[26]:

fig = plt.figure(figsize=(15,5))
cropped_cube = dispersed_case0[0,:751,:]
ax = fig.add_subplot(111, projection=cropped_cube.wcs)
cropped_cube.plot(
    axes=ax,
    norm=norm,
    data_unit='ph / (pix h)',
    cmap='hinodexrt',
)
color_lat_lon_axes(ax)
ax.plot_coord(coord, color='w', ls='--')

[26]:

[<matplotlib.lines.Line2D at 0x7f592bbdae60>]

../_images/reports_dispersed-filter-trade-study_36_1.png

[27]:

fig = plt.figure(figsize=(15, 5))
ax = fig.add_subplot(111)
with quantity_support():
    for i,overlap in enumerate([dispersed_case0, dispersed_case1, dispersed_case2, dispersed_case3, dispersed_case4, dispersed_case5]):
        cropped_cube = overlap[0, :751, :]
        intensity, intensity_coord = extract_along_coord(cropped_cube, coord)
        ax.plot(intensity_coord.Ty, intensity.to('ph pix-1 h-1'), label=case_labels[f'Case {i}'])
    ax.legend()
    ax.set_yscale('log')

../_images/reports_dispersed-filter-trade-study_37_0.png

[28]:

fig = plt.figure(figsize=(15, 5))
ax = fig.add_subplot(111)
with quantity_support():
    for i,overlap in enumerate([dispersed_case0, dispersed_case1, dispersed_case2, dispersed_case3, dispersed_case4, dispersed_case5]):
        cropped_cube = overlap[0, :751, :]
        intensity, intensity_coord = extract_along_coord(cropped_cube, coord)
        ax.plot(intensity_coord.Ty, intensity.to('ph pix-1 h-1'), label=f'Case {i}')
    ax.legend()
    #ax.set_yscale('log')
    ax.set_xlim(2000,6000)
    ax.set_ylim(.1,5)

../_images/reports_dispersed-filter-trade-study_38_0.png

[ ]: