miri_lrs_slit_end2end.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "MIRI LRS Slit Mode: Pipeline Reprocessing Demo\n",
    "================================================\n",
    "\n",
    "This notebook will demonstrate how to reprocess MIRI LRS slit mode data, in case changes need to be made to the pipeline settings. The goal of this notebook is to provide code to reprocess the data using default settings. We will provide tips for how to modify settings, however we do not delve into any particular steps. \n",
    "\n",
    "To learn more about specific steps of the pipeline for LRS and how to optimize the data reduction, please see the accompanying notebooks in this repository. \n",
    "\n",
    "\n",
    "### Dependencies\n",
    "- os\n",
    "- jwst\n",
    "- astropy\n",
    "- glob \n",
    "\n",
    "### Assumptions\n",
    "- we will start from the `rate.fits` file stage, assuming the Detector1Pipeline has executed successfully. LRS slit data generally do not require custom settings or changes to the Stage 1 pipeline. \n",
    "- we assume the data were executed with the ALONG SLIT NOD dither pattern, and that the nods will be mutually subtracted for background subtraction\n",
    "\n",
    "\n",
    "### Versions\n",
    "The notebook was developed using JWST calibration pipeline version 1.12.3 and CRDS context jwst_1147.pmap. \n",
    "\n",
    "### Getting help\n",
    "If you have questions or feedback about this notebook, please contact the MIRI team via the [JWST Helpdesk](https://jwsthelp.stsci.edu/), directing the query to the MIRI team. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import os\n",
    "os.environ['CRDS_CONTEXT'] = 'jwst_1147.pmap'\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Importing JWST pipeline version 1.12.3\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import astropy\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import jwst\n",
    "print('Importing JWST pipeline version {}'.format(jwst.__version__))\n",
    "from jwst.pipeline import Spec2Pipeline, Spec3Pipeline\n",
    "from jwst.associations.asn_from_list import asn_from_list\n",
    "from jwst.associations.lib.rules_level2_base import DMSLevel2bBase\n",
    "from jwst.associations.lib.rules_level3_base import DMS_Level3_Base\n",
    "from jwst import datamodels\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.  Loading data and Creating the Level 2 Association. \n",
    "\n",
    "First of all we will locate the data. This notebook uses a flux calibrator observation (PID 1538, Obs 21), but you can replace the file identifications below with your own files. \n",
    "\n",
    "For datasets where the 2 nod exposures will be used as each other's backgrounds, we have to build an association indicating the relationship between the files. Association files can also be retrieved from MAST for your program. \n",
    "\n",
    "**Alternative strategy**: individual nods can also be run through the Spec2Pipeline to be processed and calibrated as individual files. In this case, no association file is needed, and each individual file can be passed to teh Spec2Pipeline. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "nod1_file = 'data/jw01538021001_05101_00001_mirimage_rate.fits'\n",
    "nod2_file = 'data/jw01538021001_05101_00002_mirimage_rate.fits'\n",
    "nods_list = [nod1_file, nod2_file]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Association jw01538-o999_none_00002_asn\n",
      "    Parameters:        Product type: indetermined        Rule:         indetermined        Program:      indetermined        Target:       indetermined        Pool:         indetermined\n",
      "        \n",
      "\tdata/jw01538021001_05101_00001_mirimage with 1 members\n",
      "\tdata/jw01538021001_05101_00002_mirimage with 1 members\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# The metdata for the association file is optional\n",
    "asn = asn_from_list(nods_list, rule=DMSLevel2bBase, meta={'program':'01538', 'asn_id': 'o021', 'target':'GSPC P330E', 'asn_pool':'None'})\n",
    "print(asn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The association now contains 2 _members_. We now associate each member with the opposing nod, assigning it as background. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-13 19:03:40,926 - stpipe - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:40,926 - stpipe - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:40,927 - stpipe - WARNING - \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Association jw01538-o999_none_00002_asn\n",
      "    Parameters:        Product type: indetermined        Rule:         indetermined        Program:      indetermined        Target:       indetermined        Pool:         indetermined\n",
      "        \n",
      "\tjw01538021001_05101_00001_mirimage with 2 members\n",
      "\tjw01538021001_05101_00002_mirimage with 2 members\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "asn['products'][0]['name'] = (nod1_file.split('/')[-1]).replace('_rate.fits', '')\n",
    "asn['products'][1]['name'] = (nod2_file.split('/')[-1]).replace('_rate.fits', '')\n",
    "asn['products'][0]['members'].append({'expname': nod2_file, 'exptype':'background'})\n",
    "asn['products'][1]['members'].append({'expname': nod1_file, 'exptype':'background'})\n",
    "\n",
    "print(asn)\n",
    "\n",
    "# write this out to a json file\n",
    "with open('lrs_slit_end2end_spec2asn.json', 'w') as fp:\n",
    "    fp.write(asn.dump()[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Running the Spec2Pipeline\n",
    "\n",
    "The Spec2Pipeline takes the association file as input, and performs the following operations:\n",
    "* `assign_wcs`: assigns the WCS information, as well as the wavelength calibration (reference file: specwcs). This step also assigns a bounding box region over which the data will be calibrated.\n",
    "* `bkg_subtract`: subtracts the background. in our demo case, this will subtract the nods from each other, resulting in 2 files, each with a negative and a positive trace. \n",
    "* `srctype`: assigns the source type. this information is inherited from the target info in APT and this determines the aperture settings for spectral extraction. for MIRI LRS the default is 'point'. \n",
    "* `flat_field`: the flat field is divided out (reference file: flat)\n",
    "* `pathloss`: the data are corrected for slit losses. **see the miri_lrs_pathloss.ipynb notebook for additional comments about the path loss step**. (reference file: pathloss)\n",
    "* `photom`: photometric calibration factors are applied (reference file: photom)\n",
    "* `pixel_replace`: pixels set to DO_NOT_USE in the DQ array within the bounding box region are replaced by interpolation to prevent spurious spikes in the extracted products. \n",
    "* `resample_spec`: the spectrum is resampled and rectified. At this step the output product contains the bounding box region only, not the full array. \n",
    "* `extract_1d`: the spectrum is extracted from the 2D spectral image.\n",
    "\n",
    "These steps are all run by default for MIRI LRS data. We will put them all explicitly in the call for clarity. \n",
    "\n",
    "**NOTE: at this pipeline stage, the resampled and extracted data products are for \"sanity check\" purposes only. For this end to end demo, we will set these steps to be skipped. To run the steps and inspect the outputs, set 'skip' for each step to 'True' in the call below.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-13 19:03:41,379 - stpipe - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:41,379 - stpipe - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:41,380 - stpipe - WARNING - \n",
      "2023-11-13 19:03:42,814 - CRDS - ERROR -  Error determining best reference for 'pars-pixelreplacestep'  =   Unknown reference type 'pars-pixelreplacestep'\n",
      "2023-11-13 19:03:42,818 - stpipe - INFO - PARS-SPEC2PIPELINE parameters found: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_pars-spec2pipeline_0006.asdf\n",
      "2023-11-13 19:03:42,837 - stpipe.Spec2Pipeline - INFO - Spec2Pipeline instance created.\n",
      "2023-11-13 19:03:42,838 - stpipe.Spec2Pipeline.bkg_subtract - INFO - BackgroundStep instance created.\n",
      "2023-11-13 19:03:42,839 - stpipe.Spec2Pipeline.assign_wcs - INFO - AssignWcsStep instance created.\n",
      "2023-11-13 19:03:42,840 - stpipe.Spec2Pipeline.imprint_subtract - INFO - ImprintStep instance created.\n",
      "2023-11-13 19:03:42,840 - stpipe.Spec2Pipeline.msa_flagging - INFO - MSAFlagOpenStep instance created.\n",
      "2023-11-13 19:03:42,841 - stpipe.Spec2Pipeline.extract_2d - INFO - Extract2dStep instance created.\n",
      "2023-11-13 19:03:42,843 - stpipe.Spec2Pipeline.master_background_mos - INFO - MasterBackgroundMosStep instance created.\n",
      "2023-11-13 19:03:42,844 - stpipe.Spec2Pipeline.master_background_mos.flat_field - INFO - FlatFieldStep instance created.\n",
      "2023-11-13 19:03:42,844 - stpipe.Spec2Pipeline.master_background_mos.pathloss - INFO - PathLossStep instance created.\n",
      "2023-11-13 19:03:42,845 - stpipe.Spec2Pipeline.master_background_mos.barshadow - INFO - BarShadowStep instance created.\n",
      "2023-11-13 19:03:42,846 - stpipe.Spec2Pipeline.master_background_mos.photom - INFO - PhotomStep instance created.\n",
      "2023-11-13 19:03:42,846 - stpipe.Spec2Pipeline.wavecorr - INFO - WavecorrStep instance created.\n",
      "2023-11-13 19:03:42,847 - stpipe.Spec2Pipeline.flat_field - INFO - FlatFieldStep instance created.\n",
      "2023-11-13 19:03:42,848 - stpipe.Spec2Pipeline.srctype - INFO - SourceTypeStep instance created.\n",
      "2023-11-13 19:03:42,848 - stpipe.Spec2Pipeline.straylight - INFO - StraylightStep instance created.\n",
      "2023-11-13 19:03:42,849 - stpipe.Spec2Pipeline.fringe - INFO - FringeStep instance created.\n",
      "2023-11-13 19:03:42,850 - stpipe.Spec2Pipeline.residual_fringe - INFO - ResidualFringeStep instance created.\n",
      "2023-11-13 19:03:42,850 - stpipe.Spec2Pipeline.pathloss - INFO - PathLossStep instance created.\n",
      "2023-11-13 19:03:42,851 - stpipe.Spec2Pipeline.barshadow - INFO - BarShadowStep instance created.\n",
      "2023-11-13 19:03:42,852 - stpipe.Spec2Pipeline.wfss_contam - INFO - WfssContamStep instance created.\n",
      "2023-11-13 19:03:42,852 - stpipe.Spec2Pipeline.photom - INFO - PhotomStep instance created.\n",
      "2023-11-13 19:03:42,853 - stpipe.Spec2Pipeline.pixel_replace - INFO - PixelReplaceStep instance created.\n",
      "2023-11-13 19:03:42,854 - stpipe.Spec2Pipeline.resample_spec - INFO - ResampleSpecStep instance created.\n",
      "2023-11-13 19:03:42,855 - stpipe.Spec2Pipeline.cube_build - INFO - CubeBuildStep instance created.\n",
      "2023-11-13 19:03:42,856 - stpipe.Spec2Pipeline.extract_1d - INFO - Extract1dStep instance created.\n",
      "2023-11-13 19:03:42,908 - stpipe.Spec2Pipeline - INFO - Step Spec2Pipeline running with args ('lrs_slit_end2end_spec2asn.json',).\n",
      "2023-11-13 19:03:42,918 - stpipe.Spec2Pipeline - INFO - Step Spec2Pipeline parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': 'data/', 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'save_bsub': False, 'fail_on_exception': True, 'save_wfss_esec': False, 'steps': {'bkg_subtract': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'save_combined_background': False, 'sigma': 3.0, 'maxiters': None, 'wfss_mmag_extract': None}, 'assign_wcs': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'sip_approx': True, 'sip_max_pix_error': 0.1, 'sip_degree': None, 'sip_max_inv_pix_error': 0.1, 'sip_inv_degree': None, 'sip_npoints': 12, 'slit_y_low': -0.55, 'slit_y_high': 0.55}, 'imprint_subtract': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': ''}, 'msa_flagging': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': ''}, 'extract_2d': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'slit_name': None, 'extract_orders': None, 'grism_objects': None, 'tsgrism_extract_height': None, 'wfss_extract_half_height': 5, 'wfss_mmag_extract': None, 'wfss_nbright': 1000}, 'master_background_mos': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': True, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'force_subtract': False, 'save_background': False, 'user_background': None, 'inverse': False, 'steps': {'flat_field': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'save_interpolated_flat': False, 'user_supplied_flat': None, 'inverse': False}, 'pathloss': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'user_slit_loc': None}, 'barshadow': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None}, 'photom': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'mrs_time_correction': True}}}, 'wavecorr': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': ''}, 'flat_field': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'save_interpolated_flat': False, 'user_supplied_flat': None, 'inverse': False}, 'srctype': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'source_type': None}, 'straylight': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': ''}, 'fringe': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': ''}, 'residual_fringe': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'residual_fringe', 'search_output_file': False, 'input_dir': '', 'save_intermediate_results': False, 'ignore_region_min': None, 'ignore_region_max': None}, 'pathloss': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'user_slit_loc': None}, 'barshadow': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None}, 'wfss_contam': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'save_simulated_image': False, 'save_contam_images': False, 'maximum_cores': 'none'}, 'photom': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'mrs_time_correction': True}, 'pixel_replace': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'algorithm': 'fit_profile', 'n_adjacent_cols': 3}, 'resample_spec': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'weight_type': 'ivm', 'output_shape': None, 'crpix': None, 'crval': None, 'rotation': None, 'pixel_scale_ratio': 1.0, 'pixel_scale': None, 'output_wcs': '', 'single': False, 'blendheaders': True, 'allowed_memory': None, 'in_memory': True}, 'cube_build': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': True, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 's3d', 'search_output_file': False, 'input_dir': '', 'channel': 'all', 'band': 'all', 'grating': 'all', 'filter': 'all', 'output_type': None, 'scalexy': 0.0, 'scalew': 0.0, 'weighting': 'drizzle', 'coord_system': 'skyalign', 'ra_center': None, 'dec_center': None, 'cube_pa': None, 'nspax_x': None, 'nspax_y': None, 'rois': 0.0, 'roiw': 0.0, 'weight_power': 2.0, 'wavemin': None, 'wavemax': None, 'single': False, 'skip_dqflagging': False, 'debug_spaxel': '-1 -1 -1'}, 'extract_1d': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'smoothing_length': None, 'bkg_fit': None, 'bkg_order': None, 'bkg_sigma_clip': 3.0, 'log_increment': 50, 'subtract_background': None, 'use_source_posn': None, 'center_xy': None, 'apply_apcorr': True, 'ifu_autocen': False, 'ifu_rfcorr': False, 'ifu_set_srctype': None, 'ifu_rscale': None, 'soss_atoca': True, 'soss_threshold': 0.01, 'soss_n_os': 2, 'soss_wave_grid_in': None, 'soss_wave_grid_out': None, 'soss_estimate': None, 'soss_rtol': 0.0001, 'soss_max_grid_size': 20000, 'soss_transform': None, 'soss_tikfac': None, 'soss_width': 40.0, 'soss_bad_pix': 'masking', 'soss_modelname': None}}}\n",
      "2023-11-13 19:03:42,931 - stpipe.Spec2Pipeline - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:42,931 - stpipe.Spec2Pipeline - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:42,932 - stpipe.Spec2Pipeline - WARNING - \n",
      "2023-11-13 19:03:43,119 - stpipe.Spec2Pipeline - INFO - Prefetching reference files for dataset: 'jw01538021001_05101_00001_mirimage_rate.fits' reftypes = ['area', 'barshadow', 'camera', 'collimator', 'cubepar', 'dflat', 'disperser', 'distortion', 'fflat', 'filteroffset', 'flat', 'fore', 'fpa', 'fringe', 'ifufore', 'ifupost', 'ifuslicer', 'mrsxartcorr', 'msa', 'msaoper', 'ote', 'pathloss', 'photom', 'regions', 'sflat', 'specwcs', 'wavecorr', 'wavelengthrange', 'wfssbkg']\n",
      "2023-11-13 19:03:43,124 - stpipe.Spec2Pipeline - INFO - Prefetch for AREA reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,125 - stpipe.Spec2Pipeline - INFO - Prefetch for BARSHADOW reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,125 - stpipe.Spec2Pipeline - INFO - Prefetch for CAMERA reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,125 - stpipe.Spec2Pipeline - INFO - Prefetch for COLLIMATOR reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,125 - stpipe.Spec2Pipeline - INFO - Prefetch for CUBEPAR reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,126 - stpipe.Spec2Pipeline - INFO - Prefetch for DFLAT reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,126 - stpipe.Spec2Pipeline - INFO - Prefetch for DISPERSER reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,126 - stpipe.Spec2Pipeline - INFO - Prefetch for DISTORTION reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_distortion_0047.asdf'.\n",
      "2023-11-13 19:03:43,127 - stpipe.Spec2Pipeline - INFO - Prefetch for FFLAT reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,127 - stpipe.Spec2Pipeline - INFO - Prefetch for FILTEROFFSET reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,127 - stpipe.Spec2Pipeline - INFO - Prefetch for FLAT reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_flat_0790.fits'.\n",
      "2023-11-13 19:03:43,127 - stpipe.Spec2Pipeline - INFO - Prefetch for FORE reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,128 - stpipe.Spec2Pipeline - INFO - Prefetch for FPA reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,128 - stpipe.Spec2Pipeline - INFO - Prefetch for FRINGE reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,128 - stpipe.Spec2Pipeline - INFO - Prefetch for IFUFORE reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,129 - stpipe.Spec2Pipeline - INFO - Prefetch for IFUPOST reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,129 - stpipe.Spec2Pipeline - INFO - Prefetch for IFUSLICER reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,129 - stpipe.Spec2Pipeline - INFO - Prefetch for MRSXARTCORR reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,129 - stpipe.Spec2Pipeline - INFO - Prefetch for MSA reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,130 - stpipe.Spec2Pipeline - INFO - Prefetch for MSAOPER reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,130 - stpipe.Spec2Pipeline - INFO - Prefetch for OTE reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,130 - stpipe.Spec2Pipeline - INFO - Prefetch for PATHLOSS reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_pathloss_0002.fits'.\n",
      "2023-11-13 19:03:43,130 - stpipe.Spec2Pipeline - INFO - Prefetch for PHOTOM reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_photom_0085.fits'.\n",
      "2023-11-13 19:03:43,131 - stpipe.Spec2Pipeline - INFO - Prefetch for REGIONS reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,131 - stpipe.Spec2Pipeline - INFO - Prefetch for SFLAT reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,131 - stpipe.Spec2Pipeline - INFO - Prefetch for SPECWCS reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_specwcs_0005.fits'.\n",
      "2023-11-13 19:03:43,132 - stpipe.Spec2Pipeline - INFO - Prefetch for WAVECORR reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,132 - stpipe.Spec2Pipeline - INFO - Prefetch for WAVELENGTHRANGE reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,132 - stpipe.Spec2Pipeline - INFO - Prefetch for WFSSBKG reference file is 'N/A'.\n",
      "2023-11-13 19:03:43,133 - stpipe.Spec2Pipeline - INFO - Starting calwebb_spec2 ...\n",
      "2023-11-13 19:03:43,139 - stpipe.Spec2Pipeline - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:43,139 - stpipe.Spec2Pipeline - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:43,139 - stpipe.Spec2Pipeline - WARNING - \n",
      "2023-11-13 19:03:43,140 - stpipe.Spec2Pipeline - INFO - Processing product jw01538021001_05101_00001_mirimage\n",
      "2023-11-13 19:03:43,140 - stpipe.Spec2Pipeline - INFO - Working on input data/jw01538021001_05101_00001_mirimage_rate.fits ...\n",
      "2023-11-13 19:03:43,372 - stpipe.Spec2Pipeline.assign_wcs - INFO - Step assign_wcs running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:43,373 - stpipe.Spec2Pipeline.assign_wcs - INFO - Step assign_wcs parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'sip_approx': True, 'sip_max_pix_error': 0.1, 'sip_degree': None, 'sip_max_inv_pix_error': 0.1, 'sip_inv_degree': None, 'sip_npoints': 12, 'slit_y_low': -0.55, 'slit_y_high': 0.55}\n",
      "2023-11-13 19:03:43,637 - stpipe.Spec2Pipeline.assign_wcs - INFO - Applied Barycentric velocity correction : 0.9999389757046011\n",
      "2023-11-13 19:03:43,642 - stpipe.Spec2Pipeline.assign_wcs - INFO - Created a MIRI mir_lrs-fixedslit pipeline with references {'distortion': '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_distortion_0047.asdf', 'filteroffset': None, 'specwcs': '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_specwcs_0005.fits', 'regions': None, 'wavelengthrange': None, 'camera': None, 'collimator': None, 'disperser': None, 'fore': None, 'fpa': None, 'msa': None, 'ote': None, 'ifupost': None, 'ifufore': None, 'ifuslicer': None}\n",
      "2023-11-13 19:03:43,709 - stpipe.Spec2Pipeline.assign_wcs - INFO - Update S_REGION to POLYGON ICRS  247.890598109 30.145575432 247.890598109 30.146903971 247.891163506 30.146903971 247.891163506 30.145575432\n",
      "2023-11-13 19:03:43,710 - stpipe.Spec2Pipeline.assign_wcs - INFO - assign_wcs updated S_REGION to POLYGON ICRS  247.890598109 30.145575432 247.890598109 30.146903971 247.891163506 30.146903971 247.891163506 30.145575432\n",
      "2023-11-13 19:03:43,712 - stpipe.Spec2Pipeline.assign_wcs - INFO - COMPLETED assign_wcs\n",
      "2023-11-13 19:03:43,725 - stpipe.Spec2Pipeline.assign_wcs - INFO - Step assign_wcs done\n",
      "2023-11-13 19:03:43,780 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>, []).\n",
      "2023-11-13 19:03:43,781 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:43,781 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step skipped.\n",
      "2023-11-13 19:03:43,783 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract done\n",
      "2023-11-13 19:03:43,839 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract running with args ('data/jw01538021001_05101_00002_mirimage_rate.fits', []).\n",
      "2023-11-13 19:03:43,839 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'imprint_subtract', 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:43,840 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step skipped.\n",
      "2023-11-13 19:03:43,840 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract done\n",
      "2023-11-13 19:03:43,893 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Step bkg_subtract running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>, ['data/jw01538021001_05101_00002_mirimage_rate.fits']).\n",
      "2023-11-13 19:03:43,894 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Step bkg_subtract parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'bsub', 'search_output_file': True, 'input_dir': '', 'save_combined_background': False, 'sigma': 3.0, 'maxiters': None, 'wfss_mmag_extract': None}\n",
      "2023-11-13 19:03:43,917 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Accumulate bkg from data/jw01538021001_05101_00002_mirimage_rate.fits\n",
      "2023-11-13 19:03:44,118 - stpipe.Spec2Pipeline.bkg_subtract - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/astropy/stats/sigma_clipping.py:364: AstropyUserWarning: Input data contains invalid values (NaNs or infs), which were automatically clipped.\n",
      "2023-11-13 19:03:44,119 - stpipe.Spec2Pipeline.bkg_subtract - WARNING -   warnings.warn(\n",
      "2023-11-13 19:03:44,119 - stpipe.Spec2Pipeline.bkg_subtract - WARNING - \n",
      "2023-11-13 19:03:44,280 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Step bkg_subtract done\n",
      "2023-11-13 19:03:44,348 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step msa_flagging running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:44,350 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step msa_flagging parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:44,350 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step skipped.\n",
      "2023-11-13 19:03:44,353 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step msa_flagging done\n",
      "2023-11-13 19:03:44,412 - stpipe.Spec2Pipeline.srctype - INFO - Step srctype running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:44,413 - stpipe.Spec2Pipeline.srctype - INFO - Step srctype parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'source_type': None}\n",
      "2023-11-13 19:03:44,419 - stpipe.Spec2Pipeline.srctype - INFO - Input EXP_TYPE is MIR_LRS-FIXEDSLIT\n",
      "2023-11-13 19:03:44,420 - stpipe.Spec2Pipeline.srctype - INFO - Input SRCTYAPT = POINT\n",
      "2023-11-13 19:03:44,420 - stpipe.Spec2Pipeline.srctype - INFO - Using input source type = POINT\n",
      "2023-11-13 19:03:44,423 - stpipe.Spec2Pipeline.srctype - INFO - Step srctype done\n",
      "2023-11-13 19:03:44,481 - stpipe.Spec2Pipeline.straylight - INFO - Step straylight running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:44,482 - stpipe.Spec2Pipeline.straylight - INFO - Step straylight parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:44,483 - stpipe.Spec2Pipeline.straylight - INFO - Step skipped.\n",
      "2023-11-13 19:03:44,485 - stpipe.Spec2Pipeline.straylight - INFO - Step straylight done\n",
      "2023-11-13 19:03:44,539 - stpipe.Spec2Pipeline.flat_field - INFO - Step flat_field running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:44,540 - stpipe.Spec2Pipeline.flat_field - INFO - Step flat_field parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'save_interpolated_flat': False, 'user_supplied_flat': None, 'inverse': False}\n",
      "2023-11-13 19:03:44,619 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword CDP_PARTIAL_DATA does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:44,620 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword CDP_LOW_QUAL does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:44,620 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword CDP_UNRELIABLE_ERROR does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:44,622 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword DIFF_PATTERN does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:44,624 - stpipe.Spec2Pipeline.flat_field - INFO - Using FLAT reference file: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_flat_0790.fits\n",
      "2023-11-13 19:03:44,625 - stpipe.Spec2Pipeline.flat_field - INFO - No reference found for type FFLAT\n",
      "2023-11-13 19:03:44,625 - stpipe.Spec2Pipeline.flat_field - INFO - No reference found for type SFLAT\n",
      "2023-11-13 19:03:44,625 - stpipe.Spec2Pipeline.flat_field - INFO - No reference found for type DFLAT\n",
      "2023-11-13 19:03:44,767 - stpipe.Spec2Pipeline.flat_field - INFO - Step flat_field done\n",
      "2023-11-13 19:03:44,823 - stpipe.Spec2Pipeline.fringe - INFO - Step fringe running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:44,824 - stpipe.Spec2Pipeline.fringe - INFO - Step fringe parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:44,825 - stpipe.Spec2Pipeline.fringe - INFO - Step skipped.\n",
      "2023-11-13 19:03:44,827 - stpipe.Spec2Pipeline.fringe - INFO - Step fringe done\n",
      "2023-11-13 19:03:44,883 - stpipe.Spec2Pipeline.pathloss - INFO - Step pathloss running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:44,883 - stpipe.Spec2Pipeline.pathloss - INFO - Step pathloss parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'user_slit_loc': None}\n",
      "2023-11-13 19:03:44,897 - stpipe.Spec2Pipeline.pathloss - INFO - Using PATHLOSS reference file /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_pathloss_0002.fits\n",
      "2023-11-13 19:03:44,934 - stpipe.Spec2Pipeline.pathloss - INFO - Input exposure type is MIR_LRS-FIXEDSLIT\n",
      "2023-11-13 19:03:45,100 - stpipe.Spec2Pipeline.pathloss - INFO - Step pathloss done\n",
      "2023-11-13 19:03:45,158 - stpipe.Spec2Pipeline.barshadow - INFO - Step barshadow running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:45,159 - stpipe.Spec2Pipeline.barshadow - INFO - Step barshadow parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None}\n",
      "2023-11-13 19:03:45,159 - stpipe.Spec2Pipeline.barshadow - INFO - Step skipped.\n",
      "2023-11-13 19:03:45,162 - stpipe.Spec2Pipeline.barshadow - INFO - Step barshadow done\n",
      "2023-11-13 19:03:45,218 - stpipe.Spec2Pipeline.photom - INFO - Step photom running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:45,218 - stpipe.Spec2Pipeline.photom - INFO - Step photom parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'mrs_time_correction': True}\n",
      "2023-11-13 19:03:45,238 - stpipe.Spec2Pipeline.photom - INFO - Using photom reference file: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_photom_0085.fits\n",
      "2023-11-13 19:03:45,239 - stpipe.Spec2Pipeline.photom - INFO - Using area reference file: N/A\n",
      "2023-11-13 19:03:45,321 - stpipe.Spec2Pipeline.photom - INFO - Using instrument: MIRI\n",
      "2023-11-13 19:03:45,321 - stpipe.Spec2Pipeline.photom - INFO -  detector: MIRIMAGE\n",
      "2023-11-13 19:03:45,322 - stpipe.Spec2Pipeline.photom - INFO -  exp_type: MIR_LRS-FIXEDSLIT\n",
      "2023-11-13 19:03:45,322 - stpipe.Spec2Pipeline.photom - INFO -  filter: P750L\n",
      "2023-11-13 19:03:45,348 - stpipe.Spec2Pipeline.photom - INFO -  subarray: FULL\n",
      "2023-11-13 19:03:45,349 - stpipe.Spec2Pipeline.photom - INFO - PHOTMJSR value: 13.7913\n",
      "2023-11-13 19:03:45,400 - stpipe.Spec2Pipeline.photom - INFO - Step photom done\n",
      "2023-11-13 19:03:45,468 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step residual_fringe running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:45,469 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step residual_fringe parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'residual_fringe', 'search_output_file': False, 'input_dir': '', 'save_intermediate_results': False, 'ignore_region_min': None, 'ignore_region_max': None}\n",
      "2023-11-13 19:03:45,470 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step skipped.\n",
      "2023-11-13 19:03:45,472 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step residual_fringe done\n",
      "2023-11-13 19:03:45,540 - stpipe.Spec2Pipeline.pixel_replace - INFO - Step pixel_replace running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00001_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:45,541 - stpipe.Spec2Pipeline.pixel_replace - INFO - Step pixel_replace parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'algorithm': 'fit_profile', 'n_adjacent_cols': 3}\n",
      "2023-11-13 19:03:45,886 - stpipe.Spec2Pipeline.pixel_replace - INFO - Input model had 112 pixels replaced.\n",
      "2023-11-13 19:03:45,888 - stpipe.Spec2Pipeline.pixel_replace - INFO - Step pixel_replace done\n",
      "2023-11-13 19:03:46,034 - stpipe.Spec2Pipeline.resample_spec - INFO - Step resample_spec running with args (<ImageModel(1024, 1032) from data/jw01538021001_05101_00001_mirimage_cal.fits>,).\n",
      "2023-11-13 19:03:46,035 - stpipe.Spec2Pipeline.resample_spec - INFO - Step resample_spec parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': True, 'suffix': 's2d', 'search_output_file': True, 'input_dir': '', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'weight_type': 'ivm', 'output_shape': None, 'crpix': None, 'crval': None, 'rotation': None, 'pixel_scale_ratio': 1.0, 'pixel_scale': None, 'output_wcs': '', 'single': False, 'blendheaders': True, 'allowed_memory': None, 'in_memory': True}\n",
      "2023-11-13 19:03:46,036 - stpipe.Spec2Pipeline.resample_spec - INFO - Step skipped.\n",
      "2023-11-13 19:03:46,038 - stpipe.Spec2Pipeline.resample_spec - INFO - Step resample_spec done\n",
      "2023-11-13 19:03:46,187 - stpipe.Spec2Pipeline.extract_1d - INFO - Step extract_1d running with args (<ImageModel(1024, 1032) from data/jw01538021001_05101_00001_mirimage_cal.fits>,).\n",
      "2023-11-13 19:03:46,188 - stpipe.Spec2Pipeline.extract_1d - INFO - Step extract_1d parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': True, 'suffix': 'x1d', 'search_output_file': True, 'input_dir': '', 'smoothing_length': None, 'bkg_fit': None, 'bkg_order': None, 'bkg_sigma_clip': 3.0, 'log_increment': 50, 'subtract_background': None, 'use_source_posn': None, 'center_xy': None, 'apply_apcorr': True, 'ifu_autocen': False, 'ifu_rfcorr': False, 'ifu_set_srctype': None, 'ifu_rscale': None, 'soss_atoca': True, 'soss_threshold': 0.01, 'soss_n_os': 2, 'soss_wave_grid_in': None, 'soss_wave_grid_out': None, 'soss_estimate': None, 'soss_rtol': 0.0001, 'soss_max_grid_size': 20000, 'soss_transform': None, 'soss_tikfac': None, 'soss_width': 40.0, 'soss_bad_pix': 'masking', 'soss_modelname': None}\n",
      "2023-11-13 19:03:46,189 - stpipe.Spec2Pipeline.extract_1d - INFO - Step skipped.\n",
      "2023-11-13 19:03:46,191 - stpipe.Spec2Pipeline.extract_1d - INFO - Step extract_1d done\n",
      "2023-11-13 19:03:46,191 - stpipe.Spec2Pipeline - INFO - Finished processing product jw01538021001_05101_00001_mirimage\n",
      "2023-11-13 19:03:46,192 - stpipe.Spec2Pipeline - INFO - Processing product jw01538021001_05101_00002_mirimage\n",
      "2023-11-13 19:03:46,192 - stpipe.Spec2Pipeline - INFO - Working on input data/jw01538021001_05101_00002_mirimage_rate.fits ...\n",
      "2023-11-13 19:03:46,429 - stpipe.Spec2Pipeline.assign_wcs - INFO - Step assign_wcs running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:46,430 - stpipe.Spec2Pipeline.assign_wcs - INFO - Step assign_wcs parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'assign_wcs', 'search_output_file': True, 'input_dir': '', 'sip_approx': True, 'sip_max_pix_error': 0.1, 'sip_degree': None, 'sip_max_inv_pix_error': 0.1, 'sip_inv_degree': None, 'sip_npoints': 12, 'slit_y_low': -0.55, 'slit_y_high': 0.55}\n",
      "2023-11-13 19:03:46,681 - stpipe.Spec2Pipeline.assign_wcs - INFO - Applied Barycentric velocity correction : 0.9999389707017504\n",
      "2023-11-13 19:03:46,686 - stpipe.Spec2Pipeline.assign_wcs - INFO - Created a MIRI mir_lrs-fixedslit pipeline with references {'distortion': '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_distortion_0047.asdf', 'filteroffset': None, 'specwcs': '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_specwcs_0005.fits', 'regions': None, 'wavelengthrange': None, 'camera': None, 'collimator': None, 'disperser': None, 'fore': None, 'fpa': None, 'msa': None, 'ote': None, 'ifupost': None, 'ifufore': None, 'ifuslicer': None}\n",
      "2023-11-13 19:03:46,751 - stpipe.Spec2Pipeline.assign_wcs - INFO - Update S_REGION to POLYGON ICRS  247.890387207 30.145083114 247.890387207 30.146411654 247.890952597 30.146411654 247.890952597 30.145083114\n",
      "2023-11-13 19:03:46,751 - stpipe.Spec2Pipeline.assign_wcs - INFO - assign_wcs updated S_REGION to POLYGON ICRS  247.890387207 30.145083114 247.890387207 30.146411654 247.890952597 30.146411654 247.890952597 30.145083114\n",
      "2023-11-13 19:03:46,754 - stpipe.Spec2Pipeline.assign_wcs - INFO - COMPLETED assign_wcs\n",
      "2023-11-13 19:03:46,767 - stpipe.Spec2Pipeline.assign_wcs - INFO - Step assign_wcs done\n",
      "2023-11-13 19:03:46,827 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>, []).\n",
      "2023-11-13 19:03:46,828 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'imprint_subtract', 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:46,829 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step skipped.\n",
      "2023-11-13 19:03:46,831 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract done\n",
      "2023-11-13 19:03:46,890 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract running with args ('data/jw01538021001_05101_00001_mirimage_rate.fits', []).\n",
      "2023-11-13 19:03:46,891 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'imprint_subtract', 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:46,891 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step skipped.\n",
      "2023-11-13 19:03:46,891 - stpipe.Spec2Pipeline.imprint_subtract - INFO - Step imprint_subtract done\n",
      "2023-11-13 19:03:46,948 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Step bkg_subtract running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>, ['data/jw01538021001_05101_00001_mirimage_rate.fits']).\n",
      "2023-11-13 19:03:46,949 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Step bkg_subtract parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'bsub', 'search_output_file': True, 'input_dir': '', 'save_combined_background': False, 'sigma': 3.0, 'maxiters': None, 'wfss_mmag_extract': None}\n",
      "2023-11-13 19:03:46,968 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Accumulate bkg from data/jw01538021001_05101_00001_mirimage_rate.fits\n",
      "2023-11-13 19:03:47,150 - stpipe.Spec2Pipeline.bkg_subtract - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/astropy/stats/sigma_clipping.py:364: AstropyUserWarning: Input data contains invalid values (NaNs or infs), which were automatically clipped.\n",
      "2023-11-13 19:03:47,151 - stpipe.Spec2Pipeline.bkg_subtract - WARNING -   warnings.warn(\n",
      "2023-11-13 19:03:47,151 - stpipe.Spec2Pipeline.bkg_subtract - WARNING - \n",
      "2023-11-13 19:03:47,283 - stpipe.Spec2Pipeline.bkg_subtract - INFO - Step bkg_subtract done\n",
      "2023-11-13 19:03:47,344 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step msa_flagging running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:47,345 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step msa_flagging parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'msa_flagging', 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:47,345 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step skipped.\n",
      "2023-11-13 19:03:47,347 - stpipe.Spec2Pipeline.msa_flagging - INFO - Step msa_flagging done\n",
      "2023-11-13 19:03:47,405 - stpipe.Spec2Pipeline.srctype - INFO - Step srctype running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:47,406 - stpipe.Spec2Pipeline.srctype - INFO - Step srctype parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'srctype', 'search_output_file': True, 'input_dir': '', 'source_type': None}\n",
      "2023-11-13 19:03:47,411 - stpipe.Spec2Pipeline.srctype - INFO - Input EXP_TYPE is MIR_LRS-FIXEDSLIT\n",
      "2023-11-13 19:03:47,412 - stpipe.Spec2Pipeline.srctype - INFO - Input SRCTYAPT = POINT\n",
      "2023-11-13 19:03:47,412 - stpipe.Spec2Pipeline.srctype - INFO - Using input source type = POINT\n",
      "2023-11-13 19:03:47,415 - stpipe.Spec2Pipeline.srctype - INFO - Step srctype done\n",
      "2023-11-13 19:03:47,474 - stpipe.Spec2Pipeline.straylight - INFO - Step straylight running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:47,475 - stpipe.Spec2Pipeline.straylight - INFO - Step straylight parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'straylight', 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:47,475 - stpipe.Spec2Pipeline.straylight - INFO - Step skipped.\n",
      "2023-11-13 19:03:47,478 - stpipe.Spec2Pipeline.straylight - INFO - Step straylight done\n",
      "2023-11-13 19:03:47,535 - stpipe.Spec2Pipeline.flat_field - INFO - Step flat_field running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:47,536 - stpipe.Spec2Pipeline.flat_field - INFO - Step flat_field parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'flat_field', 'search_output_file': True, 'input_dir': '', 'save_interpolated_flat': False, 'user_supplied_flat': None, 'inverse': False}\n",
      "2023-11-13 19:03:47,609 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword CDP_PARTIAL_DATA does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:47,609 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword CDP_LOW_QUAL does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:47,609 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword CDP_UNRELIABLE_ERROR does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:47,613 - stpipe.Spec2Pipeline.flat_field - WARNING - Keyword DIFF_PATTERN does not correspond to an existing DQ mnemonic, so will be ignored\n",
      "2023-11-13 19:03:47,615 - stpipe.Spec2Pipeline.flat_field - INFO - Using FLAT reference file: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_flat_0790.fits\n",
      "2023-11-13 19:03:47,615 - stpipe.Spec2Pipeline.flat_field - INFO - No reference found for type FFLAT\n",
      "2023-11-13 19:03:47,615 - stpipe.Spec2Pipeline.flat_field - INFO - No reference found for type SFLAT\n",
      "2023-11-13 19:03:47,616 - stpipe.Spec2Pipeline.flat_field - INFO - No reference found for type DFLAT\n",
      "2023-11-13 19:03:47,748 - stpipe.Spec2Pipeline.flat_field - INFO - Step flat_field done\n",
      "2023-11-13 19:03:47,809 - stpipe.Spec2Pipeline.fringe - INFO - Step fringe running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:47,810 - stpipe.Spec2Pipeline.fringe - INFO - Step fringe parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'fringe', 'search_output_file': True, 'input_dir': ''}\n",
      "2023-11-13 19:03:47,810 - stpipe.Spec2Pipeline.fringe - INFO - Step skipped.\n",
      "2023-11-13 19:03:47,813 - stpipe.Spec2Pipeline.fringe - INFO - Step fringe done\n",
      "2023-11-13 19:03:47,873 - stpipe.Spec2Pipeline.pathloss - INFO - Step pathloss running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:47,874 - stpipe.Spec2Pipeline.pathloss - INFO - Step pathloss parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'pathloss', 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'user_slit_loc': None}\n",
      "2023-11-13 19:03:47,887 - stpipe.Spec2Pipeline.pathloss - INFO - Using PATHLOSS reference file /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_pathloss_0002.fits\n",
      "2023-11-13 19:03:47,922 - stpipe.Spec2Pipeline.pathloss - INFO - Input exposure type is MIR_LRS-FIXEDSLIT\n",
      "2023-11-13 19:03:48,073 - stpipe.Spec2Pipeline.pathloss - INFO - Step pathloss done\n",
      "2023-11-13 19:03:48,135 - stpipe.Spec2Pipeline.barshadow - INFO - Step barshadow running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:48,136 - stpipe.Spec2Pipeline.barshadow - INFO - Step barshadow parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'barshadow', 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None}\n",
      "2023-11-13 19:03:48,136 - stpipe.Spec2Pipeline.barshadow - INFO - Step skipped.\n",
      "2023-11-13 19:03:48,139 - stpipe.Spec2Pipeline.barshadow - INFO - Step barshadow done\n",
      "2023-11-13 19:03:48,199 - stpipe.Spec2Pipeline.photom - INFO - Step photom running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:48,199 - stpipe.Spec2Pipeline.photom - INFO - Step photom parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'photom', 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'mrs_time_correction': True}\n",
      "2023-11-13 19:03:48,219 - stpipe.Spec2Pipeline.photom - INFO - Using photom reference file: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_photom_0085.fits\n",
      "2023-11-13 19:03:48,219 - stpipe.Spec2Pipeline.photom - INFO - Using area reference file: N/A\n",
      "2023-11-13 19:03:48,305 - stpipe.Spec2Pipeline.photom - INFO - Using instrument: MIRI\n",
      "2023-11-13 19:03:48,306 - stpipe.Spec2Pipeline.photom - INFO -  detector: MIRIMAGE\n",
      "2023-11-13 19:03:48,306 - stpipe.Spec2Pipeline.photom - INFO -  exp_type: MIR_LRS-FIXEDSLIT\n",
      "2023-11-13 19:03:48,306 - stpipe.Spec2Pipeline.photom - INFO -  filter: P750L\n",
      "2023-11-13 19:03:48,330 - stpipe.Spec2Pipeline.photom - INFO -  subarray: FULL\n",
      "2023-11-13 19:03:48,331 - stpipe.Spec2Pipeline.photom - INFO - PHOTMJSR value: 13.7913\n",
      "2023-11-13 19:03:48,374 - stpipe.Spec2Pipeline.photom - INFO - Step photom done\n",
      "2023-11-13 19:03:48,438 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step residual_fringe running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:48,439 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step residual_fringe parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': 'residual_fringe', 'search_output_file': False, 'input_dir': '', 'save_intermediate_results': False, 'ignore_region_min': None, 'ignore_region_max': None}\n",
      "2023-11-13 19:03:48,439 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step skipped.\n",
      "2023-11-13 19:03:48,442 - stpipe.Spec2Pipeline.residual_fringe - INFO - Step residual_fringe done\n",
      "2023-11-13 19:03:48,501 - stpipe.Spec2Pipeline.pixel_replace - INFO - Step pixel_replace running with args (<ImageModel(1024, 1032) from jw01538021001_05101_00002_mirimage_rate.fits>,).\n",
      "2023-11-13 19:03:48,502 - stpipe.Spec2Pipeline.pixel_replace - INFO - Step pixel_replace parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'pixel_replace', 'search_output_file': True, 'input_dir': '', 'algorithm': 'fit_profile', 'n_adjacent_cols': 3}\n",
      "2023-11-13 19:03:48,837 - stpipe.Spec2Pipeline.pixel_replace - INFO - Input model had 112 pixels replaced.\n",
      "2023-11-13 19:03:48,839 - stpipe.Spec2Pipeline.pixel_replace - INFO - Step pixel_replace done\n",
      "2023-11-13 19:03:48,985 - stpipe.Spec2Pipeline.resample_spec - INFO - Step resample_spec running with args (<ImageModel(1024, 1032) from data/jw01538021001_05101_00002_mirimage_cal.fits>,).\n",
      "2023-11-13 19:03:48,986 - stpipe.Spec2Pipeline.resample_spec - INFO - Step resample_spec parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': True, 'suffix': 's2d', 'search_output_file': True, 'input_dir': '', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'weight_type': 'ivm', 'output_shape': None, 'crpix': None, 'crval': None, 'rotation': None, 'pixel_scale_ratio': 1.0, 'pixel_scale': None, 'output_wcs': '', 'single': False, 'blendheaders': True, 'allowed_memory': None, 'in_memory': True}\n",
      "2023-11-13 19:03:48,986 - stpipe.Spec2Pipeline.resample_spec - INFO - Step skipped.\n",
      "2023-11-13 19:03:48,989 - stpipe.Spec2Pipeline.resample_spec - INFO - Step resample_spec done\n",
      "2023-11-13 19:03:49,135 - stpipe.Spec2Pipeline.extract_1d - INFO - Step extract_1d running with args (<ImageModel(1024, 1032) from data/jw01538021001_05101_00002_mirimage_cal.fits>,).\n",
      "2023-11-13 19:03:49,137 - stpipe.Spec2Pipeline.extract_1d - INFO - Step extract_1d parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': True, 'suffix': 'x1d', 'search_output_file': True, 'input_dir': '', 'smoothing_length': None, 'bkg_fit': None, 'bkg_order': None, 'bkg_sigma_clip': 3.0, 'log_increment': 50, 'subtract_background': None, 'use_source_posn': None, 'center_xy': None, 'apply_apcorr': True, 'ifu_autocen': False, 'ifu_rfcorr': False, 'ifu_set_srctype': None, 'ifu_rscale': None, 'soss_atoca': True, 'soss_threshold': 0.01, 'soss_n_os': 2, 'soss_wave_grid_in': None, 'soss_wave_grid_out': None, 'soss_estimate': None, 'soss_rtol': 0.0001, 'soss_max_grid_size': 20000, 'soss_transform': None, 'soss_tikfac': None, 'soss_width': 40.0, 'soss_bad_pix': 'masking', 'soss_modelname': None}\n",
      "2023-11-13 19:03:49,137 - stpipe.Spec2Pipeline.extract_1d - INFO - Step skipped.\n",
      "2023-11-13 19:03:49,139 - stpipe.Spec2Pipeline.extract_1d - INFO - Step extract_1d done\n",
      "2023-11-13 19:03:49,140 - stpipe.Spec2Pipeline - INFO - Finished processing product jw01538021001_05101_00002_mirimage\n",
      "2023-11-13 19:03:49,140 - stpipe.Spec2Pipeline - INFO - Ending calwebb_spec2\n",
      "2023-11-13 19:03:49,141 - stpipe.Spec2Pipeline - INFO - Results used CRDS context: jwst_1147.pmap\n",
      "2023-11-13 19:03:49,141 - stpipe.Spec2Pipeline - INFO - Results used CRDS context: jwst_1147.pmap\n",
      "2023-11-13 19:03:49,353 - stpipe.Spec2Pipeline - INFO - Saved model in data/jw01538021001_05101_00001_mirimage_cal.fits\n",
      "2023-11-13 19:03:49,543 - stpipe.Spec2Pipeline - INFO - Saved model in data/jw01538021001_05101_00002_mirimage_cal.fits\n",
      "2023-11-13 19:03:49,544 - stpipe.Spec2Pipeline - INFO - Step Spec2Pipeline done\n"
     ]
    }
   ],
   "source": [
    "sp2_asnfile = 'lrs_slit_end2end_spec2asn.json'\n",
    "sp2_out = Spec2Pipeline.call(sp2_asnfile, save_results=True, output_dir='data/', steps={\n",
    "                                'assign_wcs': {'skip': False},\n",
    "                                'bkg_subtract': {'skip': False},\n",
    "                                'srctype': {'skip': False},\n",
    "                                'flat_field': {'skip': False},\n",
    "                                'pathloss': {'skip': False},\n",
    "                                'photom': {'skip': False},\n",
    "                                'pixel_replace': {'skip': False},\n",
    "                                'resample_spec': {'skip': True},\n",
    "                                'extract_1d': {'skip': True}})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we skipped the resampling and extraction steps, the final output products are `cal.fits` files, which are wavelength calibrated and photometrically calibrated, still in FULL array format. Let's visualize the output. \n",
    "\n",
    "The output variable `sp2_out` is a list of 2 ImageModels representing these 2 calibrated output files. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-13 19:03:49,575 - stpipe - WARNING - /var/folders/9l/lthyqbnd6md29c4bpkgdp_980001p3/T/ipykernel_99104/2002496584.py:7: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "2023-11-13 19:03:49,576 - stpipe - WARNING -   fig.show()\n",
      "2023-11-13 19:03:49,576 - stpipe - WARNING - \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(ncols=2, nrows=1, figsize=[8,8])\n",
    "for sp,ax in zip(sp2_out, axes):\n",
    "    ax.imshow(sp.data, origin='lower', interpolation='None', cmap='Greys')\n",
    "    ax.set_xlim(300,350)\n",
    "    ax.set_ylim(0,400)\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Suggested modifications\n",
    "\n",
    "* As we are only modifying the default setting for the `resample_spec` and `extract_1d` steps in the above call, a simpler way to run the above is this:\n",
    "\n",
    "sp2_out = Spec2Pipeline.call(sp2_asnfile, save_results=True, output_dir='data/', steps={\n",
    "    'resample_spec': {'skip': True},\n",
    "    'extract_1d': {'skip': True}})\n",
    "\n",
    "* To run an individual file through the Spec2Pipeline, replace the above call by this:\n",
    "\n",
    "sp2_out = Spec2Pipeline.call(**your_file_here_rate.fits**, save_results=True, output_dir='data/', steps={\n",
    "                                'assign_wcs': {'skip': False},\n",
    "                                'bkg_subtract': {'skip': False},\n",
    "                                'srctype': {'skip': False},\n",
    "                                'flat_field': {'skip': False},\n",
    "                                'pathloss': {'skip': False},\n",
    "                                'photom': {'skip': False},\n",
    "                                'pixel_replace': {'skip': False},\n",
    "                                'resample_spec': {'skip': True},\n",
    "                                'extract_1d': {'skip': True}})\n",
    "\n",
    "* To run the Spec2Pipeline with a new wavelength calibration reference file, replace the above call by this:\n",
    "\n",
    "sp2_out = Spec2Pipeline.call(sp2_asnfile, save_results=True, output_dir='data/', steps={\n",
    "                                'assign_wcs': {'skip': False, **override_specwcs='your_new_file.fits'**},\n",
    "                                'bkg_subtract': {'skip': False},\n",
    "                                'srctype': {'skip': False},\n",
    "                                'flat_field': {'skip': False},\n",
    "                                'pathloss': {'skip': False},\n",
    "                                'photom': {'skip': False},\n",
    "                                'pixel_replace': {'skip': False},\n",
    "                                'resample_spec': {'skip': True},\n",
    "                                'extract_1d': {'skip': True}})\n",
    "\n",
    "Similar overrides exist for steps `flat_field`, `photom`, `pathloss` and `extract_1d`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Building the Level 3 Association\n",
    "\n",
    "The Spec3Pipeline **only** accepts an association as input. So even if you want to take a single file through to Level 3, you have to create an association with a single member, and pass that to the step call. In our case, we want to combine the nods, so we add both cal files into an association. \n",
    "\n",
    "The Spec3Pipeline executes the following steps by default:\n",
    "* `outlier_detection`: the nods are analysed together to identify any remaining outlier pixels\n",
    "* `resample_spec`: nods are combined and resampled into a single, rectified 2D image\n",
    "* `extract_1d`: the spectrum is extracted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-13 19:03:49,731 - stpipe - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:49,731 - stpipe - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:49,732 - stpipe - WARNING - \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['data/jw01538021001_05101_00001_mirimage_cal.fits', 'data/jw01538021001_05101_00002_mirimage_cal.fits']\n"
     ]
    }
   ],
   "source": [
    "cal_files = [os.path.join('data/', sp.meta.filename) for sp in sp2_out]\n",
    "print(cal_files)\n",
    "\n",
    "asn3 = asn_from_list(cal_files, rule=DMS_Level3_Base, product_name='PID1538_Obs21_end2end_demo', meta={'program':'01538', 'asn_id': 'o021', 'target':'GSPC P330E', 'asn_pool':'None'})\n",
    "\n",
    "with open('lrs_slit_end2end_spec3asn.json', 'w') as fp:\n",
    "    fp.write(asn3.dump()[1])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-13 19:03:49,874 - stpipe - INFO - PARS-SPEC3PIPELINE parameters found: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_pars-spec3pipeline_0001.asdf\n",
      "2023-11-13 19:03:49,889 - stpipe.Spec3Pipeline - INFO - Spec3Pipeline instance created.\n",
      "2023-11-13 19:03:49,890 - stpipe.Spec3Pipeline.assign_mtwcs - INFO - AssignMTWcsStep instance created.\n",
      "2023-11-13 19:03:49,890 - stpipe.Spec3Pipeline.master_background - INFO - MasterBackgroundStep instance created.\n",
      "2023-11-13 19:03:49,891 - stpipe.Spec3Pipeline.mrs_imatch - INFO - MRSIMatchStep instance created.\n",
      "2023-11-13 19:03:49,892 - stpipe.Spec3Pipeline.outlier_detection - INFO - OutlierDetectionStep instance created.\n",
      "2023-11-13 19:03:49,893 - stpipe.Spec3Pipeline.resample_spec - INFO - ResampleSpecStep instance created.\n",
      "2023-11-13 19:03:49,894 - stpipe.Spec3Pipeline.cube_build - INFO - CubeBuildStep instance created.\n",
      "2023-11-13 19:03:49,895 - stpipe.Spec3Pipeline.extract_1d - INFO - Extract1dStep instance created.\n",
      "2023-11-13 19:03:49,896 - stpipe.Spec3Pipeline.photom - INFO - PhotomStep instance created.\n",
      "2023-11-13 19:03:49,897 - stpipe.Spec3Pipeline.combine_1d - INFO - Combine1dStep instance created.\n",
      "2023-11-13 19:03:49,964 - stpipe.Spec3Pipeline - INFO - Step Spec3Pipeline running with args ('lrs_slit_end2end_spec3asn.json',).\n",
      "2023-11-13 19:03:49,970 - stpipe.Spec3Pipeline - INFO - Step Spec3Pipeline parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': 'data/', 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'steps': {'assign_mtwcs': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': True, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 'assign_mtwcs', 'search_output_file': True, 'input_dir': ''}, 'master_background': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': True, 'output_use_index': True, 'save_results': False, 'skip': True, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'user_background': None, 'save_background': False, 'force_subtract': False}, 'mrs_imatch': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'bkg_degree': 1, 'subtract': False}, 'outlier_detection': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': False, 'input_dir': '', 'weight_type': 'ivm', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'nlow': 0, 'nhigh': 0, 'maskpt': 0.7, 'grow': 1, 'snr': '5.0 4.0', 'scale': '1.2 0.7', 'backg': 0.0, 'kernel_size': '7 7', 'threshold_percent': 99.8, 'ifu_second_check': False, 'save_intermediate_results': False, 'resample_data': True, 'good_bits': '~DO_NOT_USE', 'scale_detection': False, 'allowed_memory': None, 'in_memory': False}, 'resample_spec': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'weight_type': 'ivm', 'output_shape': None, 'crpix': None, 'crval': None, 'rotation': None, 'pixel_scale_ratio': 1.0, 'pixel_scale': None, 'output_wcs': '', 'single': False, 'blendheaders': True, 'allowed_memory': None, 'in_memory': True}, 'cube_build': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': True, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': 's3d', 'search_output_file': False, 'input_dir': '', 'channel': 'all', 'band': 'all', 'grating': 'all', 'filter': 'all', 'output_type': None, 'scalexy': 0.0, 'scalew': 0.0, 'weighting': 'drizzle', 'coord_system': 'skyalign', 'ra_center': None, 'dec_center': None, 'cube_pa': None, 'nspax_x': None, 'nspax_y': None, 'rois': 0.0, 'roiw': 0.0, 'weight_power': 2.0, 'wavemin': None, 'wavemax': None, 'single': False, 'skip_dqflagging': False, 'debug_spaxel': '-1 -1 -1'}, 'extract_1d': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'smoothing_length': None, 'bkg_fit': None, 'bkg_order': None, 'bkg_sigma_clip': 3.0, 'log_increment': 50, 'subtract_background': None, 'use_source_posn': None, 'center_xy': None, 'apply_apcorr': True, 'ifu_autocen': False, 'ifu_rfcorr': False, 'ifu_set_srctype': None, 'ifu_rscale': None, 'soss_atoca': True, 'soss_threshold': 0.01, 'soss_n_os': 2, 'soss_wave_grid_in': None, 'soss_wave_grid_out': None, 'soss_estimate': None, 'soss_rtol': 0.0001, 'soss_max_grid_size': 20000, 'soss_transform': None, 'soss_tikfac': None, 'soss_width': 40.0, 'soss_bad_pix': 'masking', 'soss_modelname': None}, 'photom': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'inverse': False, 'source_type': None, 'mrs_time_correction': True}, 'combine_1d': {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': False, 'skip': False, 'suffix': None, 'search_output_file': True, 'input_dir': '', 'exptime_key': 'exposure_time'}}}\n",
      "2023-11-13 19:03:49,982 - stpipe.Spec3Pipeline - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:49,982 - stpipe.Spec3Pipeline - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:49,982 - stpipe.Spec3Pipeline - WARNING - \n",
      "2023-11-13 19:03:50,095 - stpipe.Spec3Pipeline - INFO - Prefetching reference files for dataset: 'jw01538021001_05101_00001_mirimage_cal.fits' reftypes = ['apcorr', 'area', 'cubepar', 'drizpars', 'extract1d', 'photom', 'speckernel', 'specprofile', 'spectrace', 'wavemap']\n",
      "2023-11-13 19:03:50,103 - stpipe.Spec3Pipeline - INFO - Prefetch for APCORR reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_apcorr_0007.fits'.\n",
      "2023-11-13 19:03:50,103 - stpipe.Spec3Pipeline - INFO - Prefetch for AREA reference file is 'N/A'.\n",
      "2023-11-13 19:03:50,103 - stpipe.Spec3Pipeline - INFO - Prefetch for CUBEPAR reference file is 'N/A'.\n",
      "2023-11-13 19:03:50,104 - stpipe.Spec3Pipeline - INFO - Prefetch for DRIZPARS reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_drizpars_0001.fits'.\n",
      "2023-11-13 19:03:50,104 - stpipe.Spec3Pipeline - INFO - Prefetch for EXTRACT1D reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_extract1d_0005.json'.\n",
      "2023-11-13 19:03:50,104 - stpipe.Spec3Pipeline - INFO - Prefetch for PHOTOM reference file is '/Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_photom_0085.fits'.\n",
      "2023-11-13 19:03:50,105 - stpipe.Spec3Pipeline - INFO - Prefetch for SPECKERNEL reference file is 'N/A'.\n",
      "2023-11-13 19:03:50,105 - stpipe.Spec3Pipeline - INFO - Prefetch for SPECPROFILE reference file is 'N/A'.\n",
      "2023-11-13 19:03:50,105 - stpipe.Spec3Pipeline - INFO - Prefetch for SPECTRACE reference file is 'N/A'.\n",
      "2023-11-13 19:03:50,105 - stpipe.Spec3Pipeline - INFO - Prefetch for WAVEMAP reference file is 'N/A'.\n",
      "2023-11-13 19:03:50,106 - stpipe.Spec3Pipeline - INFO - Starting calwebb_spec3 ...\n",
      "2023-11-13 19:03:50,118 - stpipe.Spec3Pipeline - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/jwst/associations/association.py:215: UserWarning: 'expname' contains path, but should only be a filename.  All input files should be in a single directory, so no path is needed.\n",
      "2023-11-13 19:03:50,118 - stpipe.Spec3Pipeline - WARNING -   warnings.warn(err_str, UserWarning)\n",
      "2023-11-13 19:03:50,118 - stpipe.Spec3Pipeline - WARNING - \n",
      "2023-11-13 19:03:50,407 - stpipe.Spec3Pipeline.outlier_detection - INFO - Step outlier_detection running with args (<ModelContainer>,).\n",
      "2023-11-13 19:03:50,408 - stpipe.Spec3Pipeline.outlier_detection - INFO - Step outlier_detection parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': False, 'suffix': 'crf', 'search_output_file': False, 'input_dir': '', 'weight_type': 'ivm', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'nlow': 0, 'nhigh': 0, 'maskpt': 0.7, 'grow': 1, 'snr': '5.0 4.0', 'scale': '1.2 0.7', 'backg': 0.0, 'kernel_size': '7 7', 'threshold_percent': 99.8, 'ifu_second_check': False, 'save_intermediate_results': False, 'resample_data': True, 'good_bits': '~DO_NOT_USE', 'scale_detection': False, 'allowed_memory': None, 'in_memory': False}\n",
      "2023-11-13 19:03:50,413 - stpipe.Spec3Pipeline.outlier_detection - INFO - Performing outlier detection on 2 inputs\n",
      "2023-11-13 19:03:50,588 - stpipe.Spec3Pipeline.outlier_detection - INFO - Driz parameter kernal: square\n",
      "2023-11-13 19:03:50,589 - stpipe.Spec3Pipeline.outlier_detection - INFO - Driz parameter pixfrac: 1.0\n",
      "2023-11-13 19:03:50,589 - stpipe.Spec3Pipeline.outlier_detection - INFO - Driz parameter fillval: INDEF\n",
      "2023-11-13 19:03:50,589 - stpipe.Spec3Pipeline.outlier_detection - INFO - Driz parameter weight_type: ivm\n",
      "2023-11-13 19:03:50,604 - stpipe.Spec3Pipeline.outlier_detection - INFO - 1 exposures to drizzle together\n",
      "2023-11-13 19:03:50,902 - stpipe.Spec3Pipeline.outlier_detection - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:50,984 - stpipe.Spec3Pipeline.outlier_detection - INFO - Saved model in jw01538021001_05101_00001_mirimage_outlier_i2d.fits\n",
      "2023-11-13 19:03:50,990 - stpipe.Spec3Pipeline.outlier_detection - INFO - 1 exposures to drizzle together\n",
      "2023-11-13 19:03:51,268 - stpipe.Spec3Pipeline.outlier_detection - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:51,345 - stpipe.Spec3Pipeline.outlier_detection - INFO - Saved model in jw01538021001_05101_00002_mirimage_outlier_i2d.fits\n",
      "2023-11-13 19:03:51,460 - stpipe.Spec3Pipeline.outlier_detection - INFO - Computing median\n",
      "2023-11-13 19:03:51,741 - stpipe.Spec3Pipeline.outlier_detection - INFO - Blotting median\n",
      "2023-11-13 19:03:52,080 - stpipe.Spec3Pipeline.outlier_detection - INFO - Blotting (1024, 1032) <-- (388, 63)\n",
      "2023-11-13 19:03:52,271 - stpipe.Spec3Pipeline.outlier_detection - INFO - Saved model in data/jw01538021001_05101_00001_mirimage_a3001_blot.fits\n",
      "2023-11-13 19:03:52,614 - stpipe.Spec3Pipeline.outlier_detection - INFO - Blotting (1024, 1032) <-- (388, 63)\n",
      "2023-11-13 19:03:52,805 - stpipe.Spec3Pipeline.outlier_detection - INFO - Saved model in data/jw01538021001_05101_00002_mirimage_a3001_blot.fits\n",
      "2023-11-13 19:03:52,806 - stpipe.Spec3Pipeline.outlier_detection - INFO - Flagging outliers\n",
      "2023-11-13 19:03:52,956 - stpipe.Spec3Pipeline.outlier_detection - INFO - New pixels flagged as outliers: 921 (0.09%)\n",
      "2023-11-13 19:03:53,180 - stpipe.Spec3Pipeline.outlier_detection - INFO - New pixels flagged as outliers: 854 (0.08%)\n",
      "2023-11-13 19:03:53,368 - stpipe.Spec3Pipeline.outlier_detection - INFO - Saved model in data/jw01538021001_05101_00001_mirimage_a3001_crf.fits\n",
      "2023-11-13 19:03:53,551 - stpipe.Spec3Pipeline.outlier_detection - INFO - Saved model in data/jw01538021001_05101_00002_mirimage_a3001_crf.fits\n",
      "2023-11-13 19:03:53,552 - stpipe.Spec3Pipeline.outlier_detection - INFO - Step outlier_detection done\n",
      "2023-11-13 19:03:53,627 - stpipe.Spec3Pipeline.resample_spec - INFO - Step resample_spec running with args (<ModelContainer>,).\n",
      "2023-11-13 19:03:53,628 - stpipe.Spec3Pipeline.resample_spec - INFO - Step resample_spec parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': False, 'suffix': 's2d', 'search_output_file': True, 'input_dir': '', 'pixfrac': 1.0, 'kernel': 'square', 'fillval': 'INDEF', 'weight_type': 'ivm', 'output_shape': None, 'crpix': None, 'crval': None, 'rotation': None, 'pixel_scale_ratio': 1.0, 'pixel_scale': None, 'output_wcs': '', 'single': False, 'blendheaders': True, 'allowed_memory': None, 'in_memory': True}\n",
      "2023-11-13 19:03:53,641 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizpars reference file: /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_drizpars_0001.fits\n",
      "2023-11-13 19:03:53,819 - stpipe.Spec3Pipeline.resample_spec - INFO - Driz parameter kernal: square\n",
      "2023-11-13 19:03:53,820 - stpipe.Spec3Pipeline.resample_spec - INFO - Driz parameter pixfrac: 1.0\n",
      "2023-11-13 19:03:53,820 - stpipe.Spec3Pipeline.resample_spec - INFO - Driz parameter fillval: INDEF\n",
      "2023-11-13 19:03:53,820 - stpipe.Spec3Pipeline.resample_spec - INFO - Driz parameter weight_type: ivm\n",
      "2023-11-13 19:03:53,856 - stpipe.Spec3Pipeline.resample_spec - INFO - Blending metadata for PID1538_Obs21_end2end_demo\n",
      "2023-11-13 19:03:54,554 - stpipe.Spec3Pipeline.resample_spec - INFO - Resampling science data\n",
      "2023-11-13 19:03:54,810 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:55,075 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:55,082 - stpipe.Spec3Pipeline.resample_spec - INFO - Resampling var_rnoise\n",
      "2023-11-13 19:03:55,344 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:55,608 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:55,616 - stpipe.Spec3Pipeline.resample_spec - INFO - Resampling var_poisson\n",
      "2023-11-13 19:03:55,874 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:56,151 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:56,160 - stpipe.Spec3Pipeline.resample_spec - INFO - Resampling var_flat\n",
      "2023-11-13 19:03:56,422 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:56,700 - stpipe.Spec3Pipeline.resample_spec - INFO - Drizzling (1024, 1032) --> (388, 63)\n",
      "2023-11-13 19:03:56,725 - stpipe.Spec3Pipeline.resample_spec - INFO - Update S_REGION to POLYGON ICRS  247.890389008 30.145359528 247.891149511 30.145359528 247.891149511 30.147146500 247.890389008 30.147146500\n",
      "2023-11-13 19:03:57,047 - stpipe.Spec3Pipeline.resample_spec - INFO - Saved model in data/PID1538_Obs21_end2end_demo_s2d.fits\n",
      "2023-11-13 19:03:57,048 - stpipe.Spec3Pipeline.resample_spec - INFO - Step resample_spec done\n",
      "2023-11-13 19:03:57,129 - stpipe.Spec3Pipeline.extract_1d - INFO - Step extract_1d running with args (<SlitModel(388, 63) from PID1538_Obs21_end2end_demo_s2d.fits>,).\n",
      "2023-11-13 19:03:57,130 - stpipe.Spec3Pipeline.extract_1d - INFO - Step extract_1d parameters are: {'pre_hooks': [], 'post_hooks': [], 'output_file': None, 'output_dir': None, 'output_ext': '.fits', 'output_use_model': False, 'output_use_index': True, 'save_results': True, 'skip': False, 'suffix': 'x1d', 'search_output_file': True, 'input_dir': '', 'smoothing_length': None, 'bkg_fit': None, 'bkg_order': None, 'bkg_sigma_clip': 3.0, 'log_increment': 50, 'subtract_background': None, 'use_source_posn': None, 'center_xy': None, 'apply_apcorr': True, 'ifu_autocen': False, 'ifu_rfcorr': False, 'ifu_set_srctype': None, 'ifu_rscale': None, 'soss_atoca': True, 'soss_threshold': 0.01, 'soss_n_os': 2, 'soss_wave_grid_in': None, 'soss_wave_grid_out': None, 'soss_estimate': None, 'soss_rtol': 0.0001, 'soss_max_grid_size': 20000, 'soss_transform': None, 'soss_tikfac': None, 'soss_width': 40.0, 'soss_bad_pix': 'masking', 'soss_modelname': None}\n",
      "2023-11-13 19:03:57,206 - stpipe.Spec3Pipeline.extract_1d - INFO - Using EXTRACT1D reference file /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_extract1d_0005.json\n",
      "2023-11-13 19:03:57,244 - stpipe.Spec3Pipeline.extract_1d - INFO - Using APCORR file /Users/skendrew//crds_cache/references/jwst/miri/jwst_miri_apcorr_0007.fits\n",
      "2023-11-13 19:03:57,285 - stpipe.Spec3Pipeline.extract_1d - WARNING - spectral_order is None; using 1\n",
      "2023-11-13 19:03:57,286 - stpipe.Spec3Pipeline.extract_1d - INFO - Processing spectral order 1\n",
      "2023-11-13 19:03:57,292 - stpipe.Spec3Pipeline.extract_1d - INFO - Using extraction limits: xstart=27, xstop=34, ystart=0, ystop=387\n",
      "2023-11-13 19:03:57,371 - stpipe.Spec3Pipeline.extract_1d - INFO - Applying Aperture correction.\n",
      "2023-11-13 19:03:57,375 - stpipe.Spec3Pipeline.extract_1d - WARNING - /Users/skendrew/anaconda3/envs/jwst1.12.3/lib/python3.11/site-packages/astropy/io/fits/fitsrec.py:103: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "2023-11-13 19:03:57,375 - stpipe.Spec3Pipeline.extract_1d - WARNING -   self.array.field(indx)[self.row] = value\n",
      "2023-11-13 19:03:57,376 - stpipe.Spec3Pipeline.extract_1d - WARNING - \n",
      "2023-11-13 19:03:57,637 - stpipe.Spec3Pipeline.extract_1d - INFO - Saved model in data/PID1538_Obs21_end2end_demo_x1d.fits\n",
      "2023-11-13 19:03:57,637 - stpipe.Spec3Pipeline.extract_1d - INFO - Step extract_1d done\n",
      "2023-11-13 19:03:57,640 - stpipe.Spec3Pipeline - INFO - Ending calwebb_spec3\n",
      "2023-11-13 19:03:57,641 - stpipe.Spec3Pipeline - INFO - Step Spec3Pipeline done\n"
     ]
    }
   ],
   "source": [
    "sp3_asnfile = 'lrs_slit_end2end_spec3asn.json'\n",
    "\n",
    "sp3_out = Spec3Pipeline.call(sp3_asnfile, save_results=True, output_dir='data/', steps={\n",
    "                             'outlier_detection': {'skip': False, 'weight_type': 'ivm'},\n",
    "                             'resample_spec': {'skip': False, 'weight_type': 'ivm'},\n",
    "                             'extract_1d': {'skip': False}})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['data/PID1538_Obs21_end2end_demo_x1d.fits']\n"
     ]
    }
   ],
   "source": [
    "x1ds = glob.glob('data/PID1538_Obs21_end2end*x1d.fits')\n",
    "print(x1ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-13 19:03:57,707 - stpipe - WARNING - /var/folders/9l/lthyqbnd6md29c4bpkgdp_980001p3/T/ipykernel_99104/806937497.py:8: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "2023-11-13 19:03:57,708 - stpipe - WARNING -   fig.show()\n",
      "2023-11-13 19:03:57,708 - stpipe - WARNING - \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x1d = datamodels.open(x1ds[0])\n",
    "\n",
    "fig, ax = plt.subplots(figsize=[10,4])\n",
    "ax.plot(x1d.spec[0].spec_table['WAVELENGTH'], x1d.spec[0].spec_table['FLUX'], 'b-')\n",
    "ax.set_xlabel('wavelength')\n",
    "ax.set_ylabel('Jy')\n",
    "ax.set_title('PID1538_Obs21 Level 3 extracted spectrum')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
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    "### Suggested modifications\n",
    "\n",
    "* There is evidence that the variance arrays for LRS spectroscopy data is not being correctly computed by the calibration pipeline; at the time of writing this is under careful investigation (see [this page](https://jwst-docs.stsci.edu/jwst-calibration-pipeline-caveats/known-issues-with-jwst-data-products#KnownIssueswithJWSTDataProducts-MIRIlowresolutionspectroscopy(LRS)) for latest updates). As a result, however, the 'ivm' ('ivm' = inverse variance mapping) weighting setting in the `resample_spec` step may be introducing spurious noise. If the `s2d` output product looks noisy or contains unusual structure, it is worthwhile re-running the Spec3Pipeline with the 'exptime' weighing set. \n",
    "\n",
    "* The `extract_1d` uses a simple fixed-width rectangular extraction aperture, however the calibration pipeline has more advanced capabilities. For demonstrations of additional extraction methods, see the `miri_lrs_pipeline_extraction` notebook in this repository.  \n",
    "\n",
    "END\n",
    "\n",
    "-- Last Updated: 13 Nov 2023 (S. Kendrew)"
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