Add essential scripts

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*,cover
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+*.DS_Store

README.md

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+
+This repository contains the analysis scripts for Koch et al. (2019). We compare the HI and CO spectral properties in M33.
+
+HI data products are available [here](https://doi.org/10.11570/18.0003). Use of these data should cite [Koch et al. (2018)](https://ui.adsabs.harvard.edu/#abs/2018MNRAS.479.2505K/abstract).
+
+The CO data is hosted by IRAM [here](http://www.iram-institute.org/EN/content-page-329-7-158-240-329-0.html). The link refers to the papers that should be cited when using these data.
+
+Scripts to reproduce the HI reduction and imaging can be found [here](https://github.com/e-koch/VLA_Lband).
+
+These analyses scripts are setup to run from this directory and rely on paths to the data defined in `paths.py`. The disc parameters (inclination, position angle, etc) are required for some script and are loaded through the `galaxy_params.py` script. The file that is loaded in this script is available from the HI data link above (`DR1/HI/rotation_curve/rad.out.params.csv`).
+
+These scripts rely on two personal python packages that require installing from the source code:
+
+* [galaxies](https://github.com/low-sky/galaxies)
+* [CubeAnalysis](https://github.com/e-koch/CubeAnalysis)
+

constants.py

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+
+'''
+Define HI frequency once.
+'''
+
+import astropy.units as u
+
+distance = 840 * u.kpc
+
+
+def ang_to_phys(ang_size, distance=distance):
+    '''
+    Convert from angular to physical scales
+    '''
+    return (ang_size.to(u.rad).value * distance).to(u.pc)
+
+
+hi_freq = 1.42040575177 * u.GHz
+
+pb_lim = 0.5
+
+co21_mass_conversion = 6.7 * (u.Msun / u.pc ** 2) / (u.K * u.km / u.s)
+beam_eff_30m_druard = 56 / 92.
+
+# Note that the top two conversions contain a 1.4x correction for He.
+# So they will give the atomic mass, not the HI mass!
+hi_mass_conversion = 0.019 * (u.M_sun / u.pc ** 2) / (u.K * u.km / u.s)
+hi_mass_conversion_Jy = 2.36e5 * 1.4 * (u.M_sun / u.Mpc ** 2) / (u.Jy * u.km / u.s)
+
+# This does not have the He correction
+hi_coldens_Kkms = 1.82e18 * u.cm**-2 / (u.K * u.km / u.s)

galaxy_params.py

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+
+'''
+Use parameters from Diskfit in the Galaxy class
+'''
+
+from galaxies import Galaxy
+from astropy.table import Table
+import astropy.units as u
+
+from cube_analysis.rotation_curves import update_galaxy_params
+
+from paths import fourteenB_HI_data_path, fourteenB_HI_data_wGBT_path
+
+# The models from the peak velocity aren't as biased, based on comparing
+# the VLA and VLA+GBT velocity curves. Using these as the defaults
+
+folder_name = "diskfit_peakvels_noasymm_noradial_nowarp_output"
+
+param_name = \
+    fourteenB_HI_data_path("{}/rad.out.params.csv".format(folder_name))
+
+param_table = Table.read(param_name)
+
+gal = Galaxy("M33")
+
+update_galaxy_params(gal, param_table)
+
+# Load in the model from the feathered data as well.
+folder_name = "diskfit_peakvels_noasymm_noradial_nowarp_output"
+
+param_name = \
+    fourteenB_HI_data_wGBT_path("{}/rad.out.params.csv".format(folder_name))
+
+param_table = Table.read(param_name)
+
+gal_feath = Galaxy("M33")
+
+update_galaxy_params(gal_feath, param_table)
+
+# Force 840 kpc for the distance
+
+gal.distance = 840 * u.kpc
+gal_feath.distance = 840 * u.kpc

plotting_styles.py

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+
+import seaborn as sb
+
+'''
+Set style for figures.
+'''
+
+
+def default_figure(font_scale=1.0):
+    sb.set(font='Times New Roman', style='ticks',
+           rc={'text.usetex': True})
+    sb.set_context("poster", font_scale=font_scale)
+    sb.set_palette("colorblind")
+
+
+def twocolumn_figure(fig_ratio=None, font_scale=1.25):
+    default_figure()
+
+    width = 8.4
+    # Keep the default ratio used in seaborn. This can get overwritten.
+    height = (4.4 / 6.4) * width
+
+    figsize = (width, height)
+
+    if fig_ratio is not None:
+        figsize = (width, width * fig_ratio)
+
+    sb.set_context("paper", font_scale=font_scale,
+                   rc={"figure.figsize": figsize})
+    sb.set_palette("colorblind")
+
+
+def twocolumn_twopanel_figure(fig_ratio=None, **kwargs):
+
+    # Use half the ratio of a one column figure.
+    if fig_ratio is None:
+        fig_ratio = (4.4 / 6.4) / 2
+
+    twocolumn_figure(fig_ratio=fig_ratio, **kwargs)
+
+
+def onecolumn_figure(fig_ratio=None, font_scale=1.2):
+    '''
+    fig_ratio is width / height.
+    '''
+    default_figure()
+
+    # About the width (in inches) of a column
+    width = 4.2
+    # Keep the default ratio used in seaborn. This can get overwritten.
+    height = (4.4 / 6.4) * width
+
+    figsize = (width, height)
+
+    if fig_ratio is not None:
+        figsize = (width, width * fig_ratio)
+
+    sb.set_context("paper", font_scale=font_scale,
+                   rc={"figure.figsize": figsize})
+    sb.set_palette("colorblind")
+
+
+def onecolumn_Npanel_figure(N, font_scale=1.2):
+
+    width = 4.2
+
+    height = (4.4 / 6.4) * N * width
+
+    onecolumn_figure(fig_ratio=height / width, font_scale=font_scale)
+
+
+def onecolumn_twopanel_figure(font_scale=1.2):
+
+    onecolumn_Npanel_figure(N=2, font_scale=font_scale)
+
+
+def image_shape_ratio(shape):
+    '''
+    Return the width / height for adjusting figure sizes.
+    '''
+
+    return shape[0] / float(shape[1])
+
+
+def align_yaxis(ax1, v1, ax2, v2):
+    """adjust ax2 ylimit so that v2 in ax2 is aligned to v1 in ax1"""
+    _, y1 = ax1.transData.transform((0, v1))
+    _, y2 = ax2.transData.transform((0, v2))
+    adjust_yaxis(ax2, (y1 - y2) / 2, v2)
+    adjust_yaxis(ax1, (y2 - y1) / 2, v1)
+
+
+def adjust_yaxis(ax, ydif, v):
+    """shift axis ax by ydiff, maintaining point v at the same location"""
+    inv = ax.transData.inverted()
+    _, dy = inv.transform((0, 0)) - inv.transform((0, ydif))
+    miny, maxy = ax.get_ylim()
+    miny, maxy = miny - v, maxy - v
+    if -miny > maxy or (-miny == maxy and dy > 0):
+        nminy = miny
+        nmaxy = miny * (maxy + dy) / (miny + dy)
+    else:
+        nmaxy = maxy
+        nminy = maxy * (miny + dy) / (maxy + dy)
+    ax.set_ylim(nminy + v, nmaxy + v)