Merge branch 'master' into zfind_dirs

bin/copyprod.py

@@ -28,6 +28,7 @@
 #- Copy exposures
 for indir, subdirs, filenames in os.walk(inroot+'/exposures'):
     outdir = indir.replace(inroot, outroot)
+    print outdir
     if not os.path.exists(outdir):
         os.makedirs(outdir)
 

bin/desi_zfind.py

@@ -19,7 +19,7 @@
 parser.add_option("-b", "--brick", type=str,  help="input brickname")
 parser.add_option("-n", "--nspec", type=int,  help="number of spectra to fit [default: all]")
 parser.add_option("-o", "--outfile", type=str,  help="output file name")
-parser.add_option("--zspec",   help="Write a zspec file with resampled spectra used for zfind", action="store_true")
+parser.add_option("--zspec",   help="also include spectra in output file", action="store_true")
 
 opts, args = parser.parse_args()
 

py/desispec/fluxcalibration.py

@@ -5,7 +5,7 @@
 
 
 import numpy as np
-from desispec.io.frame import resolution_data_to_sparse_matrix
+from desispec.resolution import Resolution
 from desispec.linalg import cholesky_solve
 from desispec.linalg import cholesky_solve_and_invert
 from desispec.linalg import spline_fit
@@ -234,7 +234,7 @@ def compute_flux_calibration(wave,flux,ivar,resolution_data,input_model_wave,inp
         # pylab.plot(input_model_wave,input_model_flux[fiber])
         # pylab.plot(wave,model_flux[fiber],c="g")
 
-        R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+        R = Resolution(resolution_data[fiber])
         model_flux[fiber]=R.dot(model_flux[fiber])
 
         # debug
@@ -269,7 +269,7 @@ def compute_flux_calibration(wave,flux,ivar,resolution_data,input_model_wave,inp
         for fiber in range(nfibers) :
             if fiber%10==0 :
                 log.info("iter %d fiber %d"%(iteration,fiber))
-            R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+            R = Resolution(resolution_data[fiber])
 
             # diagonal sparse matrix with content = sqrt(ivar)*flat
             SD.setdiag(sqrtwmodel[fiber])
@@ -293,7 +293,7 @@ def compute_flux_calibration(wave,flux,ivar,resolution_data,input_model_wave,inp
             if fiber%10==0 :
                 log.info("iter %d fiber %d(smooth)"%(iteration,fiber))
 
-            R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+            R = Resolution(resolution_data[fiber])
 
             #M = np.array(np.dot(R.todense(),mean_spectrum)).flatten()
             M = R.dot(calibration)*model_flux[fiber]
@@ -378,7 +378,7 @@ def compute_flux_calibration(wave,flux,ivar,resolution_data,input_model_wave,inp
     # we also want to save the convolved calibration and calibration variance
     # first compute average resolution
     mean_res_data=np.mean(resolution_data,axis=0)
-    R = resolution_data_to_sparse_matrix(mean_res_data,0)
+    R = Resolution(mean_res_data)
     # compute convolved calib and ivar
     ccalibration=R.dot(calibration)
     ccalibcovar=R.dot(calibcovar).dot(R.T.todense())
@@ -410,7 +410,7 @@ def apply_flux_calibration(flux,ivar,resolution_data,wave,calibration,civar,cmas
 
     for fiber in range(nfibers) :
 
-        R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+        R = Resolution(resolution_data[fiber])
         C = R.dot(calibration)
 
         """

py/desispec/sky.py

@@ -4,7 +4,7 @@
 
 
 import numpy as np
-from desispec.io.frame import resolution_data_to_sparse_matrix
+from desispec.resolution import Resolution
 from desispec.linalg import cholesky_solve
 from desispec.linalg import cholesky_solve_and_invert
 from desispec.linalg import spline_fit
@@ -57,7 +57,7 @@ def compute_sky(wave,flux,ivar,resolution_data,nsig_clipping=4.) :
         for fiber in range(nfibers) :
             if fiber%10==0 :
                 log.info("iter %d fiber %d"%(iteration,fiber))
-            R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+            R = Resolution(resolution_data[fiber])
 
             # diagonal sparse matrix with content = sqrt(ivar)
             SD.setdiag(sqrtw[fiber])
@@ -75,7 +75,7 @@ def compute_sky(wave,flux,ivar,resolution_data,nsig_clipping=4.) :
 
         for fiber in range(nfibers) :
 
-            R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+            R = Resolution(resolution_data[fiber])
             S = R.dot(skyflux)
             chi2[fiber]=current_ivar[fiber]*(flux[fiber]-S)**2
 
@@ -129,7 +129,7 @@ def compute_sky(wave,flux,ivar,resolution_data,nsig_clipping=4.) :
 
     # first compute average resolution
     mean_res_data=np.mean(resolution_data,axis=0)
-    R = resolution_data_to_sparse_matrix(mean_res_data,0)
+    R = Resolution(mean_res_data)
     # compute convolved sky and ivar
     cskyflux=R.dot(skyflux)
     cskycovar=R.dot(skycovar).dot(R.T.todense())
@@ -165,7 +165,7 @@ def subtract_sky(flux,ivar,resolution_data,wave,skyflux,convolved_skyivar,skymas
         #if fiber%10==0 :
         #    log.info("fiber %d"%fiber)
 
-        R = resolution_data_to_sparse_matrix(resolution_data,fiber)
+        R = Resolution(resolution_data[fiber])
         S = R.dot(skyflux)
         flux[fiber] -= S
 

py/desispec/zfind/redmonster.py

@@ -46,7 +46,7 @@ def __init__(self, wave, flux, ivar, R=None, dloglam=1e-4):
         self.nspec = nspec
 
         #- list of (templatename, zmin, zmax) to fix
-        self.template_dir = os.getenv('REDMONSTER_DIR')+'/templates/'
+        self.template_dir = os.getenv('REDMONSTER')+'/templates/'
         self.templates = [
             ('ndArch-spEigenStar-55734.fits', -0.005, 0.005),
             ('ndArch-ssp_em_galaxy-v000.fits', 0.6, 1.6),
@@ -155,4 +155,4 @@ def __init__(self, wave, flux, ivar, dof=None):
 
 #     return wave, xwave[ii], xflux[ii], xivar[ii]
 
-
+