Marvin

安装

• pip install sdss-marvin
• pip install -U sdss-marvin

配置

• 注意设置一些环境变量，关键是要找到dapall文件

setenv SAS_BASE_DIR $HOME/MaNGA
setenv MANGA_SPECTRO_REDUX $SAS_BASE_DIR/mangawork/manga/spectro/redux 
setenv MANGA_SPECTRO_ANALYSIS $SAS_BASE_DIR/mangawork/manga/spectro/analysis

• mode

import marvin
marvin.config.mode = 'local'   # or 'remote'，‘auto’
marvin.config.access = 'collab' # 'DR15'
marvin.config.setRelease("MPL-10")

• collab模式下要设置.netrc文件

功能

Maps

• 读取dap中的map

map的data model 可以参看 https://sdss-marvin.readthedocs.io/en/latest/datamodel/mpl10.html?highlight=property%20name#dap-datamodel

       ha = dapmap['gflux ha']
       gflux=dapmap.getMap('spx_mflux',channel=None)

• 速度弥散度的改正 inst_sigma_correction() #marvin.tools.quantities.map.Map.inst_sigma_correction

Ha_sig=dapmap.getMap('emline_gsigma',channel='ha')
#Ha_sigcorr=dapmap.getMap('emline_gsigmacorr',channel='ha')
Ha_vdis=Ha.inst_sigma_correction()
st_sig=dapmap.getMap('stellar_sigma')
#st_sigcorr=dapmap.getMap('stellar_sigmacorr',channel='fit')
st_vdis=st_sig.inst_sigma_correction()

Masks

pixmask

• DAP中的map类都有pixmap的类属性，可以help查看
• 比如获得ha的map之后，可以用ha.pixmask.schema查看

pixmask的第0位是'NOCOV'，就是是否天区覆盖,gflux 并没有设置这个bitmask，但是画图同样可以显示NOCOV天区，原因是因为用了ivar==0判据

np.where(gflux.ivar == 0)[0].shape

• ha.mask其实就是ha.pixmask.mask

manga_target1.mask

• 选源的时候的mask

from marvin.utils.general.maskbit import Maskbit
mngtarg1 = Maskbit('MANGA_TARGET1')
mngtarg1.schema

• map也可以查看这个mask

ha.manga_target1.mask
ha.manga_target1.bits
ha.manga_target1.labels 

Translating Amongst Mask Values, Bits, and labels

ha.pixmask.values_to_bits(1073741843)  # [0, 1, 4, 30]
ha.pixmask.values_to_labels(1073741843)  #['NOCOV', 'LOWCOV', 'NOVALUE', 'DONOTUSE']

• Translate one label

ha.pixmask.labels_to_value('NOCOV')  # 1
ha.pixmask.labels_to_bits('NOCOV')   # [0]

• Translate multiple labels

ha.pixmask.labels_to_value(['NOCOV', 'UNRELIABLE'])  # 33
ha.pixmask.labels_to_bits(['NOCOV', 'UNRELIABLE'])  # [0, 5]

Making a Custom Mask

• Mask of regions with no IFU coverage

nocov = ha.pixmask.get_mask('NOCOV')

• Mask of regions with low Halpha flux and marked as DONOTUSE

low_ha = (ha.value < 1e-17) * ha.pixmask.labels_to_value('DONOTUSE')

• Combine masks using bitwise OR (`|`)

my_mask = nocov | low_ha
fig, ax = ha.plot(mask=my_mask)