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Lean Tutorial

This tutorial runs through all of the steps for doing a project with Marvin from start-to-finish with no extra fat. We recommend the use of ipython or jupyter notebook when using Marvin. You can start either from a terminal with ipython or jupyter notebook.

Project Description

Calculate the [NII]/H\(\alpha\) ratio for star-forming spaxels in galaxies with stellar mass between \(10^{10}\) and \(10^{11}\) .

Sample Selection

Marvin uses a simplified query syntax (in both Web and local queries) that understands the MaNGA database schema, so you don’t have to write complicated SQL queries.

Goal: Find galaxies with stellar mass between \(10^{10}\) and \(10^{11}\).

Create the query with doQuery() and run it (limit to only 3 results for demo purposes):

>>> from marvin.tools.query import doQuery
>>> q, r = doQuery(search_filter='nsa.sersic_logmass >= 10 and nsa.sersic_logmass <= 11', limit=3)

Tip: see Marvin Query to learn the basics of querying. See Example Queries and Marvin Query Syntax Tutorial for help with designing search filters.

View the Results. You may see a different set of results. That is ok as long as you see some set of results.:

>>> df = r.toDF()
>>> df
    mangaid     plateifu    sersic_logmass
0   1-109056        8077-6103       10.200446
1   1-109081        8077-12705      10.862523
2   1-109112        8078-1901       10.128309

Convert into Maps objects:

>>> r.convertToTool('maps')
>>> r.objects
>>> galaxies = r.objects

Get the Maps

Alternatively, maybe we already knew our galaxy IDs, which we can use to create Maps objects:

>>> from marvin.tools.maps import Maps
>>> mangaids = ['1-245458', '1-22301', '1-605884']
>>> galaxies = [Maps(mangaid=mangaid) for mangaid in mangaids]

Get the H\(\alpha\) maps:

>>> haflux_maps = [galaxy['emline_gflux_ha_6564'] for galaxy in galaxies]

Plot H\(\alpha\) map of the second galaxy:

>>> haflux_map = haflux_maps[1]
>>> fig, ax = haflux_map.plot()

(Source code)

Get Spectrum and Model Fit

Let’s take a look at the model fits a spaxel. The easiest way is to navigate to the Galaxy page for 7992-6101 and click on the red “Map/SpecView Off” button.

However, we can also plot the spectrum and model fits in Python. First, we can find the coordinates of a spaxel by moving our cursor around the interactive matplotlib plotting window. When the cursor is over the spaxel of interest, the coordinates will appear in the lower right.

Then we can create a Spaxel object by accessing the parent Maps object from the Map object (haflux_map.maps) and retrieve the model fit.

>>> spax = galaxies[1].getSpaxel(x=28, y=24, xyorig='lower', cube=True, modelcube=True)

Now let’s plot the spectrum and model fit:

>>> import matplotlib.pyplot as plt
>>> # Set matplotlib style sheet. Undo with matplotib.rcdefaults().
>>> plt.style.use('seaborn-darkgrid')

>>> ax = spax.flux.plot()
>>> ax.plot(spax.full_fit.wavelength, spax.full_fit.value)
>>> ax.legend(list(ax.get_lines()), ['observed', 'model'])
>>> ax.axis([7100, 7500, 0.3, 0.65])

(Source code)

Plot BPT Diagram

The get_bpt() returns masks for spaxels of different ionization types and the Figure object.

>>> masks, fig, axes = galaxies[1].get_bpt()

(Source code)

For a detailed description see BPT Diagrams.

Select Star-forming Spaxels

Select the star-forming spaxels that are in the star-forming region of each diagnostic diagram (hence the “global” keyword):

>>> sf = masks['sf']['global']

Return the complement of the BPT global star-forming mask (True means star-forming) using ~ and mark those spaxels as DONOTUSE since they are non-star-forming spaxels.

>>> mask_non_sf = ~sf * haflux_map.pixmask.labels_to_value('DONOTUSE')

Do a bitwise OR between the DAP mask and the non-star-forming mask:

>>> mask = haflux_map.mask | mask_non_sf

Plot with our new mask:

>>> haflux_map.plot(mask=mask)

(Source code)

Plot [NII]/H\(\alpha\) Flux Ratio for Star-forming Spaxels

Calculate [NII]6585/H\(\alpha\) flux ratio:

>>> maps_7992_6101 = galaxies[1]
>>> nii = maps_7992_6101['emline_gflux_nii_6585']
>>> ha = maps_7992_6101['emline_gflux_ha_6564']
>>> nii_ha = nii / ha

Plot the [NII]/H\(\alpha\) flux ratio for the star-forming spaxels:

>>> nii_ha.plot(mask=mask, cblabel='[NII]6585 / Halpha flux ratio')

(Source code)

Next Steps