import numpy as np
import os
import matplotlib.pyplot as plt
from .source_pos import gauss
from ..lib.plots import figure_filetype
[docs]def lc_nodriftcorr(meta, wave_1d, optspec):
'''Plot a 2D light curve without drift correction. (Fig 3101)
Parameters
----------
meta : eureka.lib.readECF.MetaClass
The metadata object.
wave_1d : ndarray
Wavelength array with trimmed edges depending on xwindow and ywindow
which have been set in the S3 ecf
optspec : ndarray
The optimally extracted spectrum.
Returns
-------
None
'''
optspec = np.ma.masked_invalid(optspec)
plt.figure(3101, figsize=(8, 8))
plt.clf()
wmin = wave_1d.min()
wmax = wave_1d.max()
n_int, nx = optspec.shape
vmin = 0.97
vmax = 1.03
normspec = optspec / np.ma.mean(optspec, axis=0)
plt.imshow(normspec, origin='lower', aspect='auto',
extent=[wmin, wmax, 0, n_int], vmin=vmin, vmax=vmax,
cmap=plt.cm.RdYlBu_r)
plt.title("MAD = " + str(np.round(meta.mad_s3, 0).astype(int)) + " ppm")
plt.ylabel('Integration Number')
plt.xlabel(r'Wavelength ($\mu m$)')
plt.colorbar(label='Normalized Flux')
plt.tight_layout()
fname = 'figs'+os.sep+'fig3101-2D_LC'+figure_filetype
plt.savefig(meta.outputdir+fname, dpi=300)
if not meta.hide_plots:
plt.pause(0.2)
[docs]def image_and_background(data, meta, n, m):
'''Make image+background plot. (Figs 3301)
Parameters
----------
data : Xarray Dataset
The Dataset object.
meta : eureka.lib.readECF.MetaClass
The metadata object.
n : int
The integration number.
m : int
The file number.
Returns
-------
None
'''
intstart, subdata, submask, subbg = (data.attrs['intstart'],
data.flux.values, data.mask.values,
data.bg.values)
xmin, xmax = data.flux.x.min().values, data.flux.x.max().values
ymin, ymax = data.flux.y.min().values, data.flux.y.max().values
plt.figure(3301, figsize=(8, 8))
plt.clf()
plt.suptitle(f'Integration {intstart + n}')
plt.subplot(211)
plt.title('Background-Subtracted Flux')
max = np.max(subdata[n] * submask[n])
plt.imshow(subdata[n]*submask[n], origin='lower', aspect='auto',
vmin=0, vmax=max/10, extent=[xmin, xmax, ymin, ymax])
plt.colorbar()
plt.ylabel('Detector Pixel Position')
plt.subplot(212)
plt.title('Subtracted Background')
median = np.median(subbg[n])
std = np.std(subbg[n])
plt.imshow(subbg[n], origin='lower', aspect='auto', vmin=median-3*std,
vmax=median+3*std, extent=[xmin, xmax, ymin, ymax])
plt.colorbar()
plt.ylabel('Detector Pixel Position')
plt.xlabel('Detector Pixel Position')
plt.tight_layout()
file_number = str(m).zfill(int(np.floor(np.log10(meta.num_data_files))+1))
int_number = str(n).zfill(int(np.floor(np.log10(meta.n_int))+1))
fname = (f'figs{os.sep}fig3301_file{file_number}_int{int_number}' +
'_ImageAndBackground'+figure_filetype)
plt.savefig(meta.outputdir+fname, dpi=300)
if not meta.hide_plots:
plt.pause(0.2)
[docs]def optimal_spectrum(data, meta, n, m):
'''Make optimal spectrum plot. (Figs 3302)
Parameters
----------
data : Xarray Dataset
The Dataset object.
meta : eureka.lib.readECF.MetaClass
The metadata object.
n : int
The integration number.
m : int
The file number.
Returns
-------
None
'''
intstart, stdspec, optspec, opterr = (data.attrs['intstart'],
data.stdspec.values,
data.optspec.values,
data.opterr.values)
plt.figure(3302)
plt.clf()
plt.suptitle(f'1D Spectrum - Integration {intstart + n}')
plt.semilogy(data.stdspec.x.values, stdspec[n], '-', color='C1',
label='Standard Spec')
plt.errorbar(data.stdspec.x.values, optspec[n], yerr=opterr[n], fmt='-',
color='C2', ecolor='C2', label='Optimal Spec')
plt.ylabel('Flux')
plt.xlabel('Detector Pixel Position')
plt.legend(loc='best')
plt.tight_layout()
file_number = str(m).zfill(int(np.floor(np.log10(meta.num_data_files))+1))
int_number = str(n).zfill(int(np.floor(np.log10(meta.n_int))+1))
fname = (f'figs{os.sep}fig3302_file{file_number}_int{int_number}' +
'_Spectrum'+figure_filetype)
plt.savefig(meta.outputdir+fname, dpi=300)
if not meta.hide_plots:
plt.pause(0.2)
[docs]def source_position(meta, x_dim, pos_max, m,
isgauss=False, x=None, y=None, popt=None,
isFWM=False, y_pixels=None, sum_row=None, y_pos=None):
'''Plot source position for MIRI data. (Figs 3303)
Parameters
----------
meta : eureka.lib.readECF.MetaClass
The metadata object.
x_dim : int
The number of pixels in the y-direction in the image.
pos_max : float
The brightest row.
m : int
The file number.
isgauss : bool; optional
Used a guassian centring method.
x : type; optional
Unused.
y : type; optional
Unused.
popt : list; optional
The fitted Gaussian terms.
isFWM : bool; optional
Used a flux-weighted mean centring method.
y_pixels : 1darray; optional
The indices of the y-pixels.
sum_row : 1darray; optional
The sum over each row.
y_pos : float; optional
The FWM central position of the star.
Returns
-------
None
Notes
-----
History:
- 2021-07-14: Sebastian Zieba
Initial version.
- Oct 15, 2021: Taylor Bell
Tidied up the code a bit to reduce repeated code.
'''
plt.figure(3303)
plt.clf()
plt.plot(y_pixels, sum_row, 'o', label='Data')
if isgauss:
x_gaussian = np.linspace(0, x_dim, 500)
gaussian = gauss(x_gaussian, *popt)
plt.plot(x_gaussian, gaussian, '-', label='Gaussian Fit')
plt.axvline(popt[1], ls=':', label='Gaussian Center', c='C2')
plt.xlim(pos_max-meta.spec_hw, pos_max+meta.spec_hw)
elif isFWM:
plt.axvline(y_pos, ls='-', label='Weighted Row')
plt.axvline(pos_max, ls='--', label='Brightest Row', c='C3')
plt.ylabel('Row Flux')
plt.xlabel('Row Pixel Position')
plt.legend()
plt.tight_layout()
file_number = str(m).zfill(int(np.floor(np.log10(meta.num_data_files))+1))
fname = ('figs'+os.sep+f'fig3303_file{file_number}_source_pos' +
figure_filetype)
plt.savefig(meta.outputdir+fname, dpi=300)
if not meta.hide_plots:
plt.pause(0.2)
[docs]def profile(meta, profile, submask, n, m):
'''Plot weighting profile from optimal spectral extraction routine. (Figs 3304)
Parameters
----------
meta : eureka.lib.readECF.MetaClass
The metadata object.
profile : ndarray
Fitted profile in the same shape as the data array.
submask : ndarray
Outlier mask.
n : int
The current integration number.
m : int
The file number.
Returns
-------
None
'''
profile = np.ma.masked_invalid(profile)
submask = np.ma.masked_invalid(submask)
mask = np.logical_or(np.ma.getmaskarray(profile),
np.ma.getmaskarray(submask))
profile = np.ma.masked_where(mask, profile)
submask = np.ma.masked_where(mask, submask)
vmax = 0.05*np.ma.max(profile*submask)
vmin = np.ma.min(profile*submask)
plt.figure(3304)
plt.clf()
plt.suptitle(f"Profile - Integration {n}")
plt.imshow(profile*submask, aspect='auto', origin='lower',
vmax=vmax, vmin=vmin)
plt.ylabel('Relative Pixel Postion')
plt.xlabel('Relative Pixel Position')
plt.tight_layout()
file_number = str(m).zfill(int(np.floor(np.log10(meta.num_data_files))+1))
int_number = str(n).zfill(int(np.floor(np.log10(meta.n_int))+1))
fname = (f'figs{os.sep}fig3304_file{file_number}_int{int_number}_Profile' +
figure_filetype)
plt.savefig(meta.outputdir+fname, dpi=300)
if not meta.hide_plots:
plt.pause(0.2)
[docs]def subdata(meta, i, n, m, subdata, submask, expected, loc):
'''Show 1D view of profile for each column. (Figs 3501)
Parameters
----------
meta : eureka.lib.readECF.MetaClass
The metadata object.
i : int
The column number.
n : int
The current integration number.
m : int
The file number.
subdata : ndarray
Background subtracted data.
submask : ndarray
Outlier mask.
expected : ndarray
Expected profile
loc : ndarray
Location of worst outliers.
Returns
-------
None
'''
ny, nx = subdata.shape
plt.figure(3501)
plt.clf()
plt.suptitle(f'Integration {n}, Columns {i}/{nx}')
plt.plot(np.arange(ny)[np.where(submask[:, i])[0]],
subdata[np.where(submask[:, i])[0], i], 'bo')
plt.plot(np.arange(ny)[np.where(submask[:, i])[0]],
expected[np.where(submask[:, i])[0], i], 'g-')
plt.plot((loc[i]), (subdata[loc[i], i]), 'ro')
file_number = str(m).zfill(int(np.floor(np.log10(meta.num_data_files))+1))
int_number = str(n).zfill(int(np.floor(np.log10(meta.n_int))+1))
col_number = str(i).zfill(int(np.floor(np.log10(nx))+1))
fname = (f'figs{os.sep}fig3501_file{file_number}_int{int_number}' +
f'_col{col_number}_subdata'+figure_filetype)
plt.savefig(meta.outputdir+fname, dpi=300)
if not meta.hide_plots:
plt.pause(0.1)