Host prior merge

src/pyqsofit/HostDecomp.py

@@ -10,7 +10,7 @@
 """
 import os, glob
 from astropy.io import fits
-import pandas as pd
+from numpy import genfromtxt
 import numpy as np
 from lmfit import Minimizer, Parameters
 from scipy.interpolate import interp1d
@@ -88,9 +88,7 @@ def __init__(self, template_path, n_template=5, template_type='PCA'):
             self._read_PCA(template_path)
         elif template_type == 'BC03':
             self._read_BC03(template_path)
-        elif template_type == 'indo19':
-            self._read_INDO(template_path)
-        elif template_type == 'indo50':
+        elif template_type == 'indo':
             self._read_INDO(template_path)
         elif template_type == 'M09_17':
             self._read_M09(template_path)
@@ -155,6 +153,7 @@ def _read_INDO(self, template_path):
         return wave_gal, flux_gal
 
     def _read_M09(self, template_path):
+        import pandas as pd
         flux_temp = np.array([])
         wave_gal = np.array([])
         cc = 0
@@ -173,6 +172,7 @@ def _read_M09(self, template_path):
         return wave_gal, flux_gal
 
     def _read_MILES(self, template_path):
+        import pandas as pd
         flux_temp = np.array([])
         wave_gal = np.array([])
         cc = 0
@@ -498,7 +498,8 @@ def _residuals(self, param: Parameters, yval, err, reg_factor):
         return r0 + sig/nn
 
     def _read_prior(self, path2prior, n_pp):
-        prior = np.array(pd.read_csv(path2prior))
+        # prior = np.array(pd.read_csv(path2prior))
+        prior = genfromtxt(path2prior, delimiter=',', skip_header=1)
         return prior[:n_pp]
 
     def qso_model(self, param: list = None, wave=None):

src/pyqsofit/PyQSOFit.py

@@ -220,31 +220,50 @@ def Fit(self, name=None, nsmooth=1, and_mask=False, or_mask=False, reject_badpix
 
         host_prior: bool, optional
             This parameter is only useful when the decompose_host is True and BC03 is False. If True, the code will
-            adopt the prior parameters given in the pca file to perform host decomposition.
+            adopt the prior parameters given in the pca file to perform host decomposition. See arXiv:2406.17598 for
+            more description about the functionality of this prior.
 
         host_prior_scale: float, optional
             If the prior decomposition is performed, the code will use this parameter to scale the prior penalty to the
             original chi2. Default: 0.2
 
         host_line_mask: bool, optional
             If True, the line region of galaxy will be masked when subtracted from original spectra. Default: True
-
-        BC03: bool, optional
-            if True, it will use Bruzual1 & Charlot 2003 host model to fit spectrum, high shift host will be low resolution R ~ 300, the rest is R ~ 2000. Default: False
-
-        Mi: float, optional
-            i-band absolute magnitude. It only works when decompose_host is True. If not None, the Luminosity redshift binned PCA will be used to decompose
-            the spectrum. Default: None
-
+
+        decomp_na_mask: bool, optional
+            If True, the narrow line region will be masked when perform decomposition so that the model would not be
+            affected by the emission lines. In cases we are using PCA templates to perform the decomposition,
+            restricted by the template numbers, the model may not enough to recover all the emission lines with various
+            width and strength. For purpose for only separating host continuum, we suggest to set this option as True.
+
+        qso_type: str, optional
+            The name of quasar PCA templates used in the host decomposition. This parameter can be set as 'global' or
+            '{1}ZBIN{2}' where 1 is the luminosity bin from one of [A, B, C, D] and 2 is the redshift bin from one of
+            [1, 2, 3, 4, 5]. Yip et al. (2004) built a series sets of quasar PCA templates based on different redshift
+            and absolute i-band magnitude subsamples. Check https://doi.org/10.1086/425626 for more detail. If the
+            host_prior is set to True, then only 'global' and 'CZBIN1' is supported.
+
         npca_gal: int, optional
             the number of galaxy PCA components applied. It only works when decompose_host is True. The default is 5,
             which is already account for 98.37% galaxies.
-
+
+        host_type: str, optional
+            The name of galaxy templates used in the host decomposition. We have two tested build-in options for this
+            parameter: PCA, BC03. Only PCA option is allowed if host_prior=True. For pro user who want to customize
+            their own templates, please check Class host_template in HostDecomp.py.
+
         npca_qso: int, optional
             the number of QSO PCA components applied. It only works when decompose_host is True. The default is 20,
             No matter the global or luminosity-redshift binned PCA is used, it can reproduce > 92% QSOs. The binned PCA
             is better if have Mi information.
-
+
+        BC03: bool, optional -- Unavailable
+            if True, it will use Bruzual1 & Charlot 2003 host model to fit spectrum, high shift host will be low resolution R ~ 300, the rest is R ~ 2000. Default: False
+
+        Mi: float, optional -- Unavailable
+            i-band absolute magnitude. It only works when decompose_host is True. If not None, the Luminosity redshift binned PCA will be used to decompose
+            the spectrum. Default: None
+
         Fe_uv_op: bool, optional
             if True, fit continuum with UV and optical FeII template. Default: True
 

tests/test_dr7sample.py

@@ -309,10 +309,10 @@ def test_dr7(nqsofit=20):
                 q = QSOFit(lam, flux, err, z, ra=ra, dec=dec, plateid=plate, mjd=mjd, fiberid=fiber,  path=path_ex)
 
                 # Do the fitting
-                q.Fit(param_file_name='qsopar.fits', name=None, qso_type='global', host_type='BC03', save_fig=False, save_result=False)
+                q.Fit(param_file_name='qsopar.fits', name=None, qso_type='CZBIN1', host_type='BC03', save_fig=False, save_result=False)
 
                 # Test with host prior
-                q.Fit(param_file_name='qsopar.fits', name=None, host_prior=True, qso_type='global', host_type='PCA', save_fig=False, save_result=False)
+                q.Fit(param_file_name='qsopar.fits', name=None, host_prior=True, qso_type='CZBIN1', host_type='PCA', save_fig=False, save_result=False)
 
                 # Emission line loop
                 for j, line in enumerate(line_calc_names):