# HG changeset patch
# User Iannis <i.binietoglou@impworks.gr>
# Date 1571659668 -10800
# Node ID 26551701d0137cd9ba1e48d33942b2904fa5dabf
# Parent  804313c093a8215f4223ebddd12395dde1eaf118
Simplistic first signal bin correction when calculating range-corrected signal for plotting.

diff -r 804313c093a8 -r 26551701d013 atmospheric_lidar/generic.py
--- a/atmospheric_lidar/generic.py	Fri May 31 14:52:42 2019 +0300
+++ b/atmospheric_lidar/generic.py	Mon Oct 21 15:07:48 2019 +0300
@@ -712,7 +712,7 @@
         duration = np.array(durations)
         return duration
 
-    def calculate_rc(self, idx_min=-2000, idx_max=-500):
+    def calculate_rc(self, idx_min=-2000, idx_max=-500, first_signal_bin=0):
         """ Calculate range corrected signal.
         
         The background signal is estimated as the mean signal between idx_min and idx_max. 
@@ -725,9 +725,14 @@
            Minimum index to calculate background signal.
         idx_max : int
            Maximum index to calculate background signal.
+        first_signal_bin : int
+           First bin with useful signal. Positive integer.
         """
         background = np.mean(self.matrix[:, idx_min:idx_max], axis=1)
-        self.rc = (self.matrix.transpose() - background).transpose() * (self.z ** 2)
+        background_corrected = (self.matrix.transpose() - background).transpose()
+        background_corrected = np.roll(background_corrected, -first_signal_bin, axis=1)
+        background_corrected[:, -9:] = 0
+        self.rc = background_corrected * (self.z ** 2)
 
     def noise_mask(self, idx_min=-2000, idx_max=-500, threshold=1.):
         """ Calculate points that are probably noise.