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@mpound
mpound committed Nov 20, 2023
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20 changes: 20 additions & 0 deletions .github/workflows/pre-commit.yml
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name: pre-commit

on:
pull_request:
push:
branches: [main, release*]


jobs:
pre-commit:
env:
SKIP: ruff
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
# must match the version in .pre-commit-config.yaml:default_language_version.python
python-version: '3.9'
- uses: pre-commit/[email protected]
1 change: 1 addition & 0 deletions .github/workflows/release.yml
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Expand Up @@ -4,6 +4,7 @@ on:
release:
types: [ published ]
workflow_dispatch:

jobs:
build:
runs-on: ${{ matrix.os }}
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2 changes: 1 addition & 1 deletion docs/source/for_developers/git_workflows.rst
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Expand Up @@ -43,7 +43,7 @@ Releases
Release branches will be locked once work on the next release begins.

Setting up your own development branch
========
======================================

In the directory you want to work in, set up the repo:

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3 changes: 3 additions & 0 deletions docs/source/getting_started/tutorials/GBT/tutorial-positionswitch.rst
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Expand Up @@ -44,6 +44,9 @@ In a `Python` instance, type
Keep the `Python` instance open, we will start working with `dysh` now.

.. note::
The data used for this tutorial is ~800 MB. Make sure you have enough disk space and bandwidth to download it.

Inspecting the raw data
-----------------------

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7 changes: 0 additions & 7 deletions docs/source/modules/dysh.spectra.rst
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Expand Up @@ -27,10 +27,3 @@ Scan
:members:
:undoc-members:
:show-inheritance:

Obsblock
--------
.. automodule:: dysh.spectra.obsblock
:members:
:undoc-members:
:show-inheritance:
241 changes: 241 additions & 0 deletions notebooks/developer/extract_blanked_rows.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "85effe3b-5328-412f-8957-5b606fed8c29",
"metadata": {},
"source": [
"Extracts the rows with blanked integrations and an additional `nints` integrations before the blank."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "732d3e8c-dfb0-4d32-8869-a8f2c05b9801",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"from astropy.io import fits\n",
"\n",
"from dysh import util\n",
"from dysh.fits.gbtfitsload import GBTFITSLoad"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "83e3fa86-c4be-4b8e-b5fa-7e90c7539e3a",
"metadata": {},
"outputs": [],
"source": [
"# Select the VEGAS banks to use,\n",
"# and the scan numbers you are interested in.\n",
"vbanks = [\"A\"]\n",
"scans = [156, 157]\n",
"nints = 2\n",
"\n",
"# Where do you find the original data?\n",
"example_data = \"/home/dysh/example_data/\" # @GBO\n",
"data_path = f\"{example_data}onoff-L/data/TGBT21A_501_11.raw.vegas/\"\n",
"data_file = lambda vbank : f\"{data_path}/TGBT21A_501_11.raw.vegas.{vbank}.fits\"\n",
"# Where will you put the smaller data?\n",
"# Use meaningful names.\n",
"output_path = f\"{util.get_project_testdata()}/TGBT21A_501_11/NGC2782_blanks/\"\n",
"output = lambda vbank : f\"{output_path}/NGC2782.raw.vegas.{vbank}.fits\""
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "6c394d08-a514-4585-850e-12fb1453fa31",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" SCAN IFNUM PLNUM CAL SIG EXPOSURE\n",
"45160 156 0 1 b'F' b'T' 1.976916\n",
"45161 156 0 1 b'T' b'T' 1.976916\n",
"45162 156 0 0 b'F' b'T' 1.976916\n",
"45163 156 0 0 b'T' b'T' 1.976916\n",
"45164 156 1 1 b'F' b'T' 1.976916\n",
"45165 156 1 1 b'T' b'T' 1.976916\n",
"45166 156 1 0 b'F' b'T' 1.976916\n",
"45167 156 1 0 b'T' b'T' 1.976916\n",
"45168 156 2 1 b'F' b'T' 1.976916\n",
"45169 156 2 1 b'T' b'T' 1.976916\n",
"45170 156 2 0 b'F' b'T' 1.976916\n",
"45171 156 2 0 b'T' b'T' 1.976916\n",
"45172 156 3 1 b'F' b'T' 1.976916\n",
"45173 156 3 1 b'T' b'T' 1.976916\n",
"45174 156 3 0 b'F' b'T' 1.976916\n",
"45175 156 3 0 b'T' b'T' 1.976916\n",
"45176 156 4 1 b'F' b'T' 1.976916\n",
"45177 156 4 1 b'T' b'T' 1.976916\n",
"45178 156 4 0 b'F' b'T' 1.976916\n",
"45179 156 4 0 b'T' b'T' 1.976916\n",
"\n",
"\n",
" SCAN IFNUM PLNUM CAL SIG EXPOSURE\n",
"45180 156 0 1 b'F' b'T' 0.121635\n",
"45181 156 0 1 b'T' b'T' 0.000000\n",
"45182 156 0 0 b'F' b'T' 0.121635\n",
"45183 156 0 0 b'T' b'T' 0.000000\n",
"45184 156 1 1 b'F' b'T' 0.121635\n",
"45185 156 1 1 b'T' b'T' 0.000000\n",
"45186 156 1 0 b'F' b'T' 0.121635\n",
"45187 156 1 0 b'T' b'T' 0.000000\n",
"45188 156 2 1 b'F' b'T' 0.121635\n",
"45189 156 2 1 b'T' b'T' 0.000000\n",
"45190 156 2 0 b'F' b'T' 0.121635\n",
"45191 156 2 0 b'T' b'T' 0.000000\n",
"45192 156 3 1 b'F' b'T' 0.121635\n",
"45193 156 3 1 b'T' b'T' 0.000000\n",
"45194 156 3 0 b'F' b'T' 0.121635\n",
"45195 156 3 0 b'T' b'T' 0.000000\n",
"45196 156 4 1 b'F' b'T' 0.121635\n",
"45197 156 4 1 b'T' b'T' 0.000000\n",
"45198 156 4 0 b'F' b'T' 0.121635\n",
"45199 156 4 0 b'T' b'T' 0.000000\n",
"\n",
"\n",
" SCAN IFNUM PLNUM CAL SIG EXPOSURE\n",
"46680 157 0 1 b'F' b'T' 1.957343\n",
"46681 157 0 1 b'T' b'T' 1.976916\n",
"46682 157 0 0 b'F' b'T' 1.957343\n",
"46683 157 0 0 b'T' b'T' 1.976916\n",
"46684 157 1 1 b'F' b'T' 1.957343\n",
"46685 157 1 1 b'T' b'T' 1.976916\n",
"46686 157 1 0 b'F' b'T' 1.957343\n",
"46687 157 1 0 b'T' b'T' 1.976916\n",
"46688 157 2 1 b'F' b'T' 1.957343\n",
"46689 157 2 1 b'T' b'T' 1.976916\n",
"46690 157 2 0 b'F' b'T' 1.957343\n",
"46691 157 2 0 b'T' b'T' 1.976916\n",
"46692 157 3 1 b'F' b'T' 1.957343\n",
"46693 157 3 1 b'T' b'T' 1.976916\n",
"46694 157 3 0 b'F' b'T' 1.957343\n",
"46695 157 3 0 b'T' b'T' 1.976916\n",
"46696 157 4 1 b'F' b'T' 1.957343\n",
"46697 157 4 1 b'T' b'T' 1.976916\n",
"46698 157 4 0 b'F' b'T' 1.957343\n",
"46699 157 4 0 b'T' b'T' 1.976916\n",
"\n",
"\n",
" SCAN IFNUM PLNUM CAL SIG EXPOSURE\n",
"46700 157 0 1 b'F' b'T' 0.121635\n",
"46701 157 0 1 b'T' b'T' 0.000000\n",
"46702 157 0 0 b'F' b'T' 0.121635\n",
"46703 157 0 0 b'T' b'T' 0.000000\n",
"46704 157 1 1 b'F' b'T' 0.121635\n",
"46705 157 1 1 b'T' b'T' 0.000000\n",
"46706 157 1 0 b'F' b'T' 0.121635\n",
"46707 157 1 0 b'T' b'T' 0.000000\n",
"46708 157 2 1 b'F' b'T' 0.121635\n",
"46709 157 2 1 b'T' b'T' 0.000000\n",
"46710 157 2 0 b'F' b'T' 0.121635\n",
"46711 157 2 0 b'T' b'T' 0.000000\n",
"46712 157 3 1 b'F' b'T' 0.121635\n",
"46713 157 3 1 b'T' b'T' 0.000000\n",
"46714 157 3 0 b'F' b'T' 0.121635\n",
"46715 157 3 0 b'T' b'T' 0.000000\n",
"46716 157 4 1 b'F' b'T' 0.121635\n",
"46717 157 4 1 b'T' b'T' 0.000000\n",
"46718 157 4 0 b'F' b'T' 0.121635\n",
"46719 157 4 0 b'T' b'T' 0.000000\n",
"\n",
"\n",
"Saved rows to /home/sandboxes/psalas/Dysh/dysh/testdata/TGBT21A_501_11/NGC2782_blanks//NGC2782.raw.vegas.A.fits\n"
]
}
],
"source": [
"for vbank in vbanks:\n",
"\n",
" file_in = data_file(vbank)\n",
" file_out = output(vbank)\n",
" \n",
" # Open.\n",
" hdu = fits.open(file_in)\n",
" table = hdu[1].data\n",
"\n",
" # Bookkeeping.\n",
" nif = len(list(set(table[\"IFNUM\"])))\n",
" npl = len(list(set(table[\"PLNUM\"])))\n",
" nnd = len(list(set(table[\"CAL\"])))\n",
" nsw = len(list(set(table[\"SIG\"])))\n",
"\n",
" orows = []\n",
" nrows = []\n",
" \n",
" for i,scan in enumerate(scans):\n",
"\n",
" # Bookkeeping.\n",
" nrows.append(nif * npl * nnd * nsw)\n",
"\n",
" # Row selection.\n",
" mask = np.all(np.isnan(table[\"DATA\"]), axis=1) & (table[\"SCAN\"] == scan)\n",
" rows = np.where(mask == True)[0]\n",
" for j in range(nints):\n",
" skip = j*nrows[i]\n",
" rowi = (rows[0] - 1) - skip\n",
" rowf = rows[-1] - skip\n",
" orows += list(np.arange(rowi, rowf+1))\n",
"\n",
" # Check results.\n",
" # The resulting data frame should have entries for all \n",
" # noise diode states in all polarizations, spectral windows\n",
" # and switching states.\n",
" table_ = np.lib.recfunctions.drop_fields(hdu[1].data, \"DATA\")\n",
" df = pd.DataFrame(table_)\n",
" for i,nrow in enumerate(nrows*nints):\n",
" irow = i*nrow\n",
" frow = (i+1)*nrow\n",
" print(df[[\"SCAN\", \"IFNUM\", \"PLNUM\", \"CAL\", \"SIG\", \"EXPOSURE\"]].iloc[np.sort(np.ravel(orows))[irow:frow]])\n",
" print(\"\\n\")\n",
" # If the results are correct\n",
" # save the rows for one VEGAS bank.\n",
" hdu0 = hdu[0].copy()\n",
" table = hdu[1].data[np.sort(np.ravel(orows))]\n",
" head = hdu[1].header\n",
" thdu = fits.BinTableHDU(table, header=head)\n",
" outhdu = fits.HDUList([hdu0, thdu])\n",
" outhdu.writeto(file_out, overwrite=True)\n",
" print(f\"Saved rows to {file_out}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7602f570-f969-42a3-85dc-bae1ac0c44be",
"metadata": {},
"outputs": [],
"source": []
}
],
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