{
"cells": [
{
"cell_type": "markdown",
"id": "ea30f0c1-8e35-4b94-a315-ffc812bde023",
"metadata": {
"tags": []
},
"source": [
"# Overlappogram Simulation Workflow\n",
"\n",
"Demo workflow for producing a simulated overlappogram.\n",
"This is the first conception of the MOXSI overlappogram pipeline.\n",
"\n",
"1. Compute DEM from AIA+XRT data\n",
"2. Compute spectral table as function of $\\lambda$ and $T_e$ from CHIANTI\n",
"3. Compute spectral cube by taking outer product of DEM and spectral table\n",
"4. Compute instrument intensities by convolving \n",
"5. Reproject to detector geometry"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "87821435-123f-4c0d-bb47-261d21b5f696",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jovyan/users_conda_envs/mocksipipeline/lib/python3.9/site-packages/dask_gateway/client.py:21: FutureWarning: format_bytes is deprecated and will be removed in a future release. Please use dask.utils.format_bytes instead.\n",
" from distributed.utils import LoopRunner, format_bytes\n",
"WARNING: SunpyDeprecationWarning: The `sunpy.io.fits` module is deprecated, as it was designed for internal use. Use the `astropy.fits.io` module instead for more generic functionality to read FITS files. [sunpy.io.fits]\n"
]
}
],
"source": [
"import sys\n",
"import glob\n",
"import copy\n",
"\n",
"import numpy as np\n",
"#import jax\n",
"#import jax.scipy\n",
"#import cupy\n",
"#import cupyx.scipy\n",
"from scipy.interpolate import interp1d\n",
"import astropy.units as u\n",
"import astropy.time\n",
"import astropy.wcs\n",
"import astropy.io.fits\n",
"from astropy.coordinates import SkyCoord\n",
"import astropy.constants\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
"import matplotlib.ticker\n",
"from sunpy.map import Map, make_fitswcs_header\n",
"from sunpy.net import Fido, attrs as a\n",
"from sunpy.net.attr import and_,or_\n",
"from sunpy.time import TimeRange\n",
"from sunpy.coordinates import Helioprojective\n",
"import sunpy.io\n",
"import sunpy.map.maputils\n",
"from ndcube import NDCube, NDCollection\n",
"from astropy.nddata import StdDevUncertainty\n",
"from astropy.visualization import (ImageNormalize, LogStretch, SqrtStretch, AsinhStretch,\n",
" PowerStretch, quantity_support, AsymmetricPercentileInterval)\n",
"from aiapy.calibrate import register, estimate_error, correct_degradation\n",
"from sunkit_dem import Model\n",
"from sunkit_dem.models import HK12Model\n",
"import reproject\n",
"\n",
"import dask\n",
"import distributed\n",
"import dask.array\n",
"from dask.distributed import PipInstall\n",
"from dask_gateway import Gateway, GatewayCluster\n",
"\n",
"from overlappy.reproject import reproject_to_overlappogram\n",
"from overlappy.wcs import pcij_matrix, overlappogram_fits_wcs\n",
"from overlappy.util import color_lat_lon_axes, strided_array\n",
"from overlappy.io import read_overlappogram, write_overlappogram\n",
"\n",
"sys.path.append('physics/dem')\n",
"from dem_models import (get_aia_temperature_response,\n",
" get_xrt_temperature_response,\n",
" PlowmanModel)\n",
"sys.path.append('physics/spectral')\n",
"from spectral_utils import read_spectral_table\n",
"sys.path.append('detector')\n",
"from response import SpectrogramChannel, Channel\n",
"\n",
"#%load_ext snakeviz"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "2eb42da4-0c8e-4364-bf88-9fcd2ef42f57",
"metadata": {},
"outputs": [],
"source": [
"# The following numbers are from Jake and Albert:\n",
"CDELT_SPACE = 5.66 * u.arcsec / u.pix\n",
"CDELT_WAVE = 55 * u.milliangstrom / u.pix\n",
"# This comes from the proposal:\n",
"DETECTOR_SHAPE_DISPERSED = (750, 2000)\n",
"DETECTOR_SHAPE_PINHOLE = (750, 475)"
]
},
{
"cell_type": "markdown",
"id": "6b7dcbe4-753a-481f-a4ca-8c930d31a55c",
"metadata": {},
"source": [
"## Setup Dask Client\n",
"\n",
"Useful for reprojection and DEM computation"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "73248b61-d66e-4360-8f74-cf39ab1359bb",
"metadata": {},
"outputs": [],
"source": [
"gateway = Gateway()\n",
"options = gateway.cluster_options()\n",
"options.worker_cores=4\n",
"options.worker_memory=8"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b5279f5a-2f65-4435-bc89-efe922177a11",
"metadata": {
"tags": []
},
"outputs": [
{
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"VBox(children=(HTML(value='GatewayCluster
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