From 54ba7230d6c092ef874678c7160e6a1ac133618e Mon Sep 17 00:00:00 2001
From: Cameron Scott Bodine <CameronBodine@nau.edu>
Date: Thu, 11 May 2023 08:42:46 -0700
Subject: [PATCH] Speedup wcp_src (#66) Thx @dbuscombe-usgs !!

---
 src/class_sonObj.py | 9 ++++++---
 src/funcs_common.py | 1 +
 2 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/src/class_sonObj.py b/src/class_sonObj.py
index a39955e..f584fb7 100644
--- a/src/class_sonObj.py
+++ b/src/class_sonObj.py
@@ -1570,15 +1570,18 @@ def _WCR_SRC(self, sonMeta, son=True):
         #Iterate each ping
         for j in range(self.sonDat.shape[1]):
             depth = bedPick[j] # Get depth (in pixels) at nadir
+            dd = depth**2
             # Create 1d array to store relocated bed pixels.  Set to -9999 so we
             ## can later interpolate over gaps.
-            pingDat = (np.ones((self.sonDat.shape[0])).astype(np.float32)) * -9999
+            # pingDat = (np.ones((self.sonDat.shape[0])).astype(np.float32)) * -9999
+            pingDat = (np.ones((self.sonDat.shape[0])).astype(np.float32)) * np.nan
             dataExtent = 0
             #Iterate each sonar/ping return
             for i in range(self.sonDat.shape[0]):
                 if i >= depth:
                     intensity = self.sonDat[i,j] # Get the intensity value
-                    srcIndex = round(np.sqrt(i**2 - depth**2),0).astype(int) #Calculate horizontal range (in pixels) using pathagorean theorem
+                    # srcIndex = round(np.sqrt(i**2 - depth**2),0).astype(int) #Calculate horizontal range (in pixels) using pathagorean theorem
+                    srcIndex = int(round(math.sqrt(i**2 - dd),0)) #Calculate horizontal range (in pixels) using pathagorean theorem
                     pingDat[srcIndex] = intensity # Store intensity at appropriate horizontal range
                     dataExtent = srcIndex # Store range extent (max range) of ping
                 else:
@@ -1587,7 +1590,7 @@ def _WCR_SRC(self, sonMeta, son=True):
 
             # Process of relocating bed pixels will introduce across track gaps
             ## in the array so we will interpolate over gaps to fill them.
-            pingDat[pingDat==-9999] = np.nan
+            # pingDat[pingDat==-9999] = np.nan
             nans, x = np.isnan(pingDat), lambda z: z.nonzero()[0]
             pingDat[nans] = np.interp(x(nans), x(~nans), pingDat[~nans])
 
diff --git a/src/funcs_common.py b/src/funcs_common.py
index a262235..5e30cf5 100644
--- a/src/funcs_common.py
+++ b/src/funcs_common.py
@@ -44,6 +44,7 @@
 from numpy.lib.stride_tricks import as_strided as ast
 
 import pandas as pd
+import math
 
 from collections import defaultdict
 from copy import deepcopy