prefilter implemented

hrt_pipe.py

@@ -5,6 +5,7 @@ from astropy.io import fits
 import subprocess
 from scipy.ndimage import gaussian_filter
 import time
+from operator import itemgetter
 
 from utils import *
 
@@ -290,6 +291,7 @@ def phihrt_pipe(data_f,dark_f,flat_f,norm_f = True, clean_f = False, sigma = 59,
     # TODO: Could check data dimensions? As an extra fail safe before progressing?
     #-----------------
     
+    print(voltagesData_arr)
 
     #-----------------
     # READ FLAT FIELDS
@@ -542,20 +544,33 @@ def phihrt_pipe(data_f,dark_f,flat_f,norm_f = True, clean_f = False, sigma = 59,
 
         prefilter = prefilter[:,652:1419,613:1380] #crop the helioseismology data
 
-        prefilter_array = np.tile(np.array(prefilter_voltages), (1,6,data_shape[-1]))
+        def get_v1_index1(x):
+            index1, v1 = min(enumerate([abs(i) for i in x]), key=itemgetter(1))
+            return  v1, index1
+
+        for scan in range(data_shape[-1]):
 
             voltage_list = voltagesData[scan]
             
-        vdif = np.array(voltage_list)[np.newaxis, ..., np.newaxis] - prefilter_array 
+            for wv in range(6):
+
+                v = voltage_list[wv]
 
-        def get_v1(x):
-            pass
-            #return min(abs(x),index1) #what is index1?
+                vdif = [v - pf for pf in prefilter_voltages]
                 
-        v1 = np.array(map(get_v1, vdif)) 
+                v1, index1 = get_v1_index1(vdif)
+                
+                if vdif[index1] >= 0:
+                    v2 = vdif[index1 + 1]
+                    index2 = index1 + 1
+                    
+                else:
+                    v2 = vdif[index1-1]
+                    index2 = index1 - 1
                     
-        v2 = np.copy(vdif)
+                imprefilter = (prefilter[index1,:,:]*v1 + prefilter[index2,:,:]*v2)/(v1+v2)
 
+                data[:,:,:,wv,scan] /= imprefilter
 
 
         printc('--------------------------------------------------------------',bcolors.OKGREEN)

requirements.txt

@@ -8,3 +8,4 @@ os
 random
 subprocess
 statistics
+operator
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run.py

@@ -7,6 +7,8 @@ darkfield_fits_filename = '../fits_files/solo_L0_phi-fdt-ilam_20200228T155100_V2
 
 sciencedata_fits_filenames = ['../fits_files/' + i for i in sciencedata_fits_filenames]
 
+prefilter_f = '../fits_files/fitted_prefilter.fits'
+
 c_talk_params = np.zeros((2,3))
 
 q_slope = 0.0038
@@ -25,5 +27,5 @@ c_talk_params[1,0] = q_int
 c_talk_params[1,1] = u_int
 c_talk_params[1,2] = v_int
 
-data = phihrt_pipe(sciencedata_fits_filenames[1:], darkfield_fits_filename, flatfield_fits_filename, norm_stokes = True, 
-                    clean_f = True, ctalk_params = c_talk_params, ItoQUV = True, out_demod_file = True, out_dir = '/data/slam/home/sinjan/hrt_pipe_results/stp-136_ctalk/', rte = 'RTE')
\ No newline at end of file
+data = phihrt_pipe(sciencedata_fits_filenames[1], darkfield_fits_filename, flatfield_fits_filename, norm_stokes = True, prefilter_f = prefilter_f, 
+                    clean_f = False, ctalk_params = c_talk_params, ItoQUV = False, out_demod_file = False, out_dir = '/data/slam/home/sinjan/hrt_pipe_results/stp-136_ctalk/', rte = 'False')
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