getting closer

py/specter/extract/ex2d.py

@@ -150,6 +150,13 @@ def ex2d(image, imageivar, psf, specmin, nspec, wavelengths, xyrange=None,
                 wmin, wmax = ww[0], ww[-1]
                 nw = len(ww)
 
+                #for now let's assume we want the cached version, fix later!
+                ####################################33
+                iwave_cache = np.arange(nw)
+                #iwave_cache = None
+                #print("iwave_cache is")
+                #print(iwave_cache)
+
                 #- include \r carriage return to prevent scrolling
                 if verbose:
                     sys.stdout.write("\rSpectra {specrange} wavelengths ({wmin:.2f}, {wmax:.2f}) -> ({wlo:.2f}, {whi:.2f})".format(\
@@ -161,7 +168,7 @@ def ex2d(image, imageivar, psf, specmin, nspec, wavelengths, xyrange=None,
                     ex2d_patch(subimg, subivar, psf,
                         specmin=speclo, nspec=spechi-speclo, wavelengths=ww,
                         xyrange=[xlo,xhi,ylo,yhi], regularize=regularize, ndecorr=ndecorr,
-                        full_output=True)
+                        full_output=True, iwave_cache=iwave_cache)
 
                 specflux = results['flux']
                 specivar = results['ivar']
@@ -246,7 +253,7 @@ def ex2d(image, imageivar, psf, specmin, nspec, wavelengths, xyrange=None,
 
 
 def ex2d_patch(image, ivar, psf, specmin, nspec, wavelengths, xyrange=None,
-         full_output=False, regularize=0.0, ndecorr=False):
+         full_output=False, regularize=0.0, ndecorr=False, iwave_cache=None):
     """
     2D PSF extraction of flux from image patch given pixel inverse variance.
     
@@ -292,14 +299,8 @@ def ex2d_patch(image, ivar, psf, specmin, nspec, wavelengths, xyrange=None,
     #print(nwave)
     #- Solve AT W pix = (AT W A)flux
 
-    #for now let's assume we want the cached version, fix later!
-    ####################################33
-    iwave_cache = np.arange(nwave)    
-    #print("iwave_cache is")
-    #print(iwave_cache)
-
     #- Projection matrix and inverse covariance
-    A = psf.projection_matrix(specrange, wavelengths, xyrange)
+    A = psf.projection_matrix(specrange, wavelengths, xyrange, iwave_cache=iwave_cache)
 
     #- Pixel weights matrix
     w = ivar.ravel()
@@ -401,6 +402,9 @@ def cache_params(psf, spec_range, wavelengths):
     psf.tailcore_cache = legval_cache(psf, psf.coeff['TAILCORE'], spec_range, wavelengths)
     psf.tailinde_cache = legval_cache(psf, psf.coeff['TAILINDE'], spec_range, wavelengths)
 
+    #print("psf.x_cache.shape")
+    #print(psf.x_cache.shape)
+
 #modified version of eval in specter/traceset that can handle 
 #multiple spectra hopefully?
 def legval_cache(psf, traceset, spec_range, wavelengths):
@@ -430,6 +434,9 @@ def legval_cache(psf, traceset, spec_range, wavelengths):
     for i in ispec:
         y[i,:]=legval_numba(xx, cc_numba[i])
 
+
+    #print("y.shape")
+    #print(y.shape)
     return y