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eteq/LeoT1_example_zspec.ipynb

Created April 1, 2020 16:49
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LeoT1_example_zspec.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.insert(1, '/Users/erik/src/specutils')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pathlib\n",
"import collections\n",
"from glob import glob\n",
"\n",
"import numpy as np\n",
"\n",
"from astropy import units as u\n",
"from astropy.constants import c\n",
"from astropy.io import fits\n",
"from astropy import nddata, visualization\n",
"visualization.quantity_support()\n",
"\n",
"from IPython import display\n",
"import ipywidgets\n",
"from ipyevents import Event \n",
"\n",
"import specutils\n",
"\n",
"import tqdm\n",
"\n",
"first = lambda x:next(iter(x))\n",
"\n",
"%matplotlib inline\n",
"from matplotlib import style, pyplot as plt\n",
"from matplotlib.backends.backend_agg import FigureCanvasAgg"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"cat_lines = [8498, 8542, 8662]*u.angstrom"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"datadir = pathlib.Path('/Users/erik/astrodata/DEIMOS/LeoT1')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Allslits0.LeoT1.fits.gz\n",
"Allslits1.LeoT1.fits.gz\n",
"LeoT1.bintabs.fits\n",
"LeoT1.log\n",
"LeoT1.plan\n",
"LeoT1_1d.log\n",
"LeoT1_mcerr.log\n",
"arcwave_qa1.fits\n",
"arcwave_qa2.fits\n",
"arcwave_qa3.fits\n",
"arcwave_qa4.fits\n",
"arcwave_qa5.fits\n",
"arcwave_qa6.fits\n",
"arcwave_qa7.fits\n",
"arcwave_qa8.fits\n",
"calibSlit.LeoT1.000B.fits.gz\n",
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"doneprocessing.txt\n",
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"zspec1d.LeoT1.065.serendip1.fits.gz\n",
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"zspec1d.LeoT1.076.serendip1.fits.gz\n",
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"zspec1d.LeoT1.089.serendip1.fits.gz\n",
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"zspec1d.LeoT1.099.serendip1.fits.gz\n",
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"zspec1d.LeoT1.102.serendip1.fits.gz\n",
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"zspec1d.LeoT1.116.s67782280806558.fits.gz\n",
"zspec1d.LeoT1.117.s67735028564202.fits.gz\n"
]
}
],
"source": [
"ls $datadir"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-6-a698f4fff297>:2: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
"Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`\n",
" for fn in tqdm.tqdm_notebook(glob(str(datadir / 'zspec1d.LeoT1.*.fits.gz'))):\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "0b60d976429d4561a01096c591380cb2",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(FloatProgress(value=0.0, max=129.0), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"zspecs = {}\n",
"for fn in tqdm.tqdm_notebook(glob(str(datadir / 'zspec1d.LeoT1.*.fits.gz'))):\n",
" nm = fn.split('LeoT1.')[-1].replace('.fits.gz', '')\n",
" d = fits.getdata(fn, 1)\n",
" zspecs[nm] = specutils.Spectrum1D(spectral_axis=d[0]['LAMBDA']*u.angstrom, flux=d[0]['SPEC']*u.count,\n",
" uncertainty=nddata.InverseVariance(d[0]['IVAR']))\n",
" for dnm in d.dtype.names:\n",
" if dnm not in ('SPEC', 'LAMBDA', 'IVAR'):\n",
" zspecs[nm].meta[dnm] = d[dnm][0]"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-7-e793a316b3c0>:2: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
"Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`\n",
" for fn in tqdm.tqdm_notebook(glob(str(datadir / 'slit.LeoT1.*.fits.gz'))):\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "7cf4da5eb5d14cdb99424e3435e0ba56",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(FloatProgress(value=0.0, max=230.0), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"slits_temp = {}\n",
"for fn in tqdm.tqdm_notebook(glob(str(datadir / 'slit.LeoT1.*.fits.gz'))):\n",
" nm = fn.split('LeoT1.')[-1].replace('.fits.gz', '')\n",
" slits_temp[nm] = fits.getdata(fn, 1)\n",
"\n",
"slits = {}\n",
"for i in range(len(slits_temp)):\n",
" rstr = '{:03}R'.format(i)\n",
" bstr = '{:03}B'.format(i)\n",
" if bstr not in slits_temp and rstr not in slits_temp:\n",
" continue\n",
" slits[i] = (slits_temp[bstr], slits_temp[rstr])\n",
"del slits_temp"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"stemp = fits.open('templates/deimos-021507.fits')[0]\n",
"wl = 10**(stemp.header['COEFF0'] + np.arange(stemp.data.shape[1])*stemp.header['COEFF1'])*u.angstrom\n",
"\n",
"template_specs = {}\n",
"for i, val in enumerate(stemp.data):\n",
" template_specs[stemp.header[f'NAME{i}']] = specutils.Spectrum1D(spectral_axis=wl, flux=val*u.dimensionless_unscaled)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Ipywidgets zspeccer"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"zspec_vals = collections.defaultdict(lambda:'uncategorized')\n",
"spec_comments = collections.defaultdict(lambda:'')\n",
"\n",
"KEY_TO_QUALITY = {\n",
" '0': 'uncategorized',\n",
" '`' : 'bad',\n",
" '1': 'galaxy/other',\n",
" '2' : 'marginal',\n",
" '3' : 'good',\n",
"}\n",
"\n",
"imshow_norm_kwargs = dict(stretch='log', min_percent=5, max_percent=99.)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-14-fb1d44242235>:58: DeprecationWarning: on_trait_change is deprecated in traitlets 4.1: use observe instead\n",
" dropdown.on_trait_change(update_dropdown, 'value')\n",
"<ipython-input-14-fb1d44242235>:76: DeprecationWarning: on_trait_change is deprecated in traitlets 4.1: use observe instead\n",
" zspec.on_trait_change(update_zspec, 'value')\n",
"<ipython-input-14-fb1d44242235>:81: DeprecationWarning: on_trait_change is deprecated in traitlets 4.1: use observe instead\n",
" comments.on_trait_change(update_comments, 'value')\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "daf232af99a64e77af12e9917fa8b974",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(HBox(children=(Button(description='<', style=ButtonStyle()), Dropdown(options=('000.s6778228074…"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d2d37a5d52894e46969359929d09623d",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Output()"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-14-fb1d44242235>:151: DeprecationWarning: on_trait_change is deprecated in traitlets 4.1: use observe instead\n",
" widget.on_trait_change(update_fig, 'value')\n"
]
}
],
"source": [
"def make_fig(specname, templname, v, output, new_canvas=True):\n",
" if new_canvas:\n",
" fig = plt.Figure(figsize=(15, 10))\n",
" canvas = FigureCanvasAgg(fig)\n",
" else:\n",
" fig = plt.figure(figsize=(15, 10))\n",
" \n",
" (ax1, ax2), (ax3, ax4) = fig.subplots(2, 2)\n",
" \n",
" zline = (v*u.km/u.s/c + 1).decompose().value\n",
" \n",
" spec = zspecs[specname]\n",
" specnum = int(specname.split('.')[0])\n",
" slit = slits[specnum]\n",
" \n",
" if templname is not None:\n",
" tspec = template_specs[templname]\n",
" for ax in [ax1, ax2]:\n",
" ax.cla()\n",
" ax.step(spec.wavelength, spec.flux, lw=1)\n",
" data_yls = ax.get_ylim()\n",
" if templname is None:\n",
" ax.step([]*first(template_specs.values()).wavelength.unit, \n",
" [], alpha=.5, lw=1)\n",
" else:\n",
" ax.step(tspec.wavelength, tspec.flux.value*np.median(spec.flux))\n",
" ax.set_ylim(*data_yls)\n",
" \n",
" snormb = visualization.simple_norm(slit[0]['FLUX'][0], **imshow_norm_kwargs)\n",
" ax3.imshow(slit[0]['FLUX'][0], extent=(slit[0]['LAMBDA0'][0][0], slit[0]['LAMBDA0'][0][-1],0, 50), \n",
" aspect=15, norm=snormb)\n",
" snormr = visualization.simple_norm(slit[1]['FLUX'][0], **imshow_norm_kwargs)\n",
" ax3.imshow(slit[1]['FLUX'][0], extent=(slit[1]['LAMBDA0'][0][0], slit[1]['LAMBDA0'][0][-1],0, 50), \n",
" aspect=15, norm=snormr)\n",
" ax4.imshow(slit[1]['FLUX'][0], extent=(slit[1]['LAMBDA0'][0][0], slit[1]['LAMBDA0'][0][-1],0, 50), \n",
" aspect=2, norm=snormr)\n",
" \n",
" ax1.set_title(specname)\n",
" ax2.set_xlim(cat_lines[0]*zline-20*u.angstrom, cat_lines[-1]*zline+20*u.angstrom)\n",
" ax4.set_xlim(cat_lines[0]*zline-20*u.angstrom, cat_lines[-1]*zline+20*u.angstrom)\n",
" \n",
" msk2 = (ax2.get_xlim()[0]<spec.wavelength.value)&(spec.wavelength.value<ax2.get_xlim()[1])\n",
" ax2.set_ylim(np.min(spec.flux[msk2]), np.max(spec.flux[msk2]))\n",
" for line in cat_lines:\n",
" ax2.axvline(line*zline, c='k', ls=':')\n",
" \n",
" if output is not None:\n",
" with output:\n",
" display.display(fig)\n",
" \n",
" return fig, ax1, ax2, ax3, ax4\n",
"\n",
"\n",
"dropdown = ipywidgets.Dropdown(options=zspecs.keys())\n",
"def update_dropdown(change):\n",
" zspec.value = zspec_vals[dropdown.value]\n",
" comments.value = spec_comments[dropdown.value]\n",
"dropdown.on_trait_change(update_dropdown, 'value')\n",
"\n",
"left = ipywidgets.Button(description='<')\n",
"right = ipywidgets.Button(description='>')\n",
"@left.on_click\n",
"def on_left_clicked(b):\n",
" idx = dropdown.options.index(dropdown.value)\n",
" if idx > 0:\n",
" dropdown.value = dropdown.options[idx-1]\n",
"@right.on_click\n",
"def on_right_clicked(b):\n",
" idx = dropdown.options.index(dropdown.value)\n",
" if idx < len(dropdown.options)-1:\n",
" dropdown.value = dropdown.options[idx+1]\n",
"\n",
"zspec = ipywidgets.Dropdown(options=['uncategorized', 'bad', 'galaxy/other', 'marginal', 'good'], description='zspec:')\n",
"def update_zspec(change):\n",
" zspec_vals[dropdown.value] = zspec.value\n",
"zspec.on_trait_change(update_zspec, 'value')\n",
"\n",
"comments = ipywidgets.Text(description='Comments:')\n",
"def update_comments(change):\n",
" spec_comments[dropdown.value] = comments.value\n",
"comments.on_trait_change(update_comments, 'value')\n",
"\n",
"template = ipywidgets.Dropdown(description='template', options=[None]+list(template_specs.keys()))\n",
"vval = ipywidgets.FloatText(value=35, description='v (km/s)')\n",
"\n",
" \n",
"top = ipywidgets.HBox([left, dropdown, right])\n",
"middle = ipywidgets.HBox([zspec, comments])\n",
"lower = ipywidgets.HBox([template, vval])\n",
"\n",
"ui = ipywidgets.VBox([top, middle, lower])\n",
"\n",
"out = ipywidgets.Output()\n",
" \n",
"d = Event(source=out, watched_events=['keydown'])\n",
"def handle_event(event):\n",
" try:\n",
" if event['key'] in KEY_TO_QUALITY.keys():\n",
" zspec.value = KEY_TO_QUALITY[event['key']]\n",
" elif event['key'] in ('-', '[',','):\n",
" left.click()\n",
" elif event['key'] in ('+', ']','.'):\n",
" right.click()\n",
" except Exception as e:\n",
" comments.value = repr(e)\n",
"d.on_dom_event(handle_event)\n",
"\n",
"display.display(ui, out)\n",
"\n",
"\n",
"fig, ax1, ax2, ax3, ax4 = make_fig(dropdown.value, template.value, vval.value, out)\n",
"def update_fig(change):\n",
" specname = dropdown.value\n",
" templname = template.value\n",
" v = vval.value\n",
" \n",
" zline = (v*u.km/u.s/c + 1).decompose().value\n",
" spec = zspecs[specname]\n",
" if templname is not None:\n",
" tspec = template_specs[templname]\n",
" specnum = int(specname.split('.')[0])\n",
" slit = slits[specnum]\n",
" \n",
" for ax in [ax1, ax2]:\n",
" ax.get_children()[0].set_data(spec.wavelength, spec.flux)\n",
" if templname is not None:\n",
" ax.get_children()[1].set_data(tspec.wavelength, tspec.flux.value*np.median(spec.flux))\n",
" ax.set_ylim(np.min(spec.flux), np.max(spec.flux))\n",
" \n",
" ax3.get_children()[-2].set_array(slit[0]['FLUX'][0])\n",
" ax3.get_children()[-2].set_norm(visualization.simple_norm(slit[0]['FLUX'][0], **imshow_norm_kwargs))\n",
" ax4.get_children()[-2].set_array(slit[1]['FLUX'][0])\n",
" ax4.get_children()[-2].set_norm(visualization.simple_norm(slit[1]['FLUX'][0], **imshow_norm_kwargs))\n",
" \n",
" ax1.set_title(specname)\n",
" ax2.set_xlim(cat_lines[0]*zline-20*u.angstrom, cat_lines[-1]*zline+20*u.angstrom)\n",
" ax4.set_xlim(cat_lines[0]*zline-20*u.angstrom, cat_lines[-1]*zline+20*u.angstrom)\n",
" \n",
" msk2 = (ax2.get_xlim()[0]<spec.wavelength.value)&(spec.wavelength.value<ax2.get_xlim()[1])\n",
" ax2.set_ylim(np.min(spec.flux[msk2]), np.max(spec.flux[msk2]))\n",
" \n",
" with out:\n",
" display.clear_output(True)\n",
" display.display(fig)\n",
" \n",
"def get_current_spec():\n",
" specname = dropdown.value\n",
" return zspecs[specname]\n",
" \n",
"for widget in (dropdown, template, vval):\n",
" widget.on_trait_change(update_fig, 'value')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(1, 1)\n",
"ax.imshow(np.random.randn(10, 10))\n",
"p = ax.get_children()[-2]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(defaultdict(<function __main__.<lambda>()>, {}),\n",
" defaultdict(<function __main__.<lambda>()>, {}))"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"zspec_vals, spec_comments"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Marla requests:\n",
"\n",
"* Fast enough to go fast\n",
"* hit number buttons for zspeccing (ipyevents)\n",
"* 2D slit\n",
"\n",
"* (some quality plots/chi^2 surfaces - understandable interface to Marla)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.0"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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