From 97a94e55d18f2b448864e016d8e821a9e4834a19 Mon Sep 17 00:00:00 2001
From: rmsare <robertmsare@gmail.com>
Date: Fri, 31 May 2019 11:25:56 -0700
Subject: [PATCH 1/2] Rename Python API functions for readability

---
 python/pymcc_lidar.pyx | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/python/pymcc_lidar.pyx b/python/pymcc_lidar.pyx
index f1ee578..678bbef 100644
--- a/python/pymcc_lidar.pyx
+++ b/python/pymcc_lidar.pyx
@@ -3,7 +3,7 @@ cimport pymcc_lidar
 cimport numpy as np
 from libc.stdlib cimport malloc, free
 
-def pymcc_classification(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scaleDomain2Spacing not None, curvatureThreshold not None):
+def classify(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scaleDomain2Spacing not None, curvatureThreshold not None):
 
   m_xyz = xyz.shape[0]
   n_xyz = xyz.shape[1]
@@ -22,8 +22,6 @@ def pymcc_classification(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None,
       x[i] = xyz[i, 0]
       y[i] = xyz[i, 1]
       z[i] = xyz[i, 2]
-      
-  
   
   with nogil: 
     classification = pymcc_classify(x, y, z, n, resolution, thresh);
@@ -34,7 +32,7 @@ def pymcc_classification(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None,
   
   return np_classification
   
-def pymcc_singlepass(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scaleDomainSpacing not None):
+def calculate_excess_height(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scaleDomainSpacing not None):
   
   m_xyz = xyz.shape[0]
   n_xyz = xyz.shape[1]
@@ -63,5 +61,3 @@ def pymcc_singlepass(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scal
   free(y);
   free(z);
   return np_h
-
-

From 98f221ada41c40f2b17caf2c9e2e5849b4f7c28f Mon Sep 17 00:00:00 2001
From: rmsare <robertmsare@gmail.com>
Date: Fri, 31 May 2019 11:30:22 -0700
Subject: [PATCH 2/2] Clean up formatting

---
 python/pymcc_lidar.pyx | 113 ++++++++++++++++++++++-------------------
 1 file changed, 60 insertions(+), 53 deletions(-)

diff --git a/python/pymcc_lidar.pyx b/python/pymcc_lidar.pyx
index 678bbef..3d32f05 100644
--- a/python/pymcc_lidar.pyx
+++ b/python/pymcc_lidar.pyx
@@ -3,61 +3,68 @@ cimport pymcc_lidar
 cimport numpy as np
 from libc.stdlib cimport malloc, free
 
-def classify(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scaleDomain2Spacing not None, curvatureThreshold not None):
 
-  m_xyz = xyz.shape[0]
-  n_xyz = xyz.shape[1]
-  
-  assert n_xyz == 3
-  
-  cdef int * classification;
-  cdef double resolution = scaleDomain2Spacing;
-  cdef double thresh = curvatureThreshold;
-  cdef int32_t n = m_xyz;
-  cdef double *x = <double *> malloc(n * sizeof(double));
-  cdef double *y = <double *> malloc(n * sizeof(double));
-  cdef double *z = <double *> malloc(n * sizeof(double));
-  
-  for i in range(n):
-      x[i] = xyz[i, 0]
-      y[i] = xyz[i, 1]
-      z[i] = xyz[i, 2]
-  
-  with nogil: 
-    classification = pymcc_classify(x, y, z, n, resolution, thresh);
+def classify(np.ndarray[double, ndim=2, mode='c'] xyz not None,
+             scaleDomain2Spacing not None,
+             curvatureThreshold not None):
 
-  cdef np.ndarray[int32_t, ndim=1] np_classification = np.empty(n, dtype=np.int32);
-  for i in range(n):
-    np_classification[i] = classification[i]
-  
-  return np_classification
-  
-def calculate_excess_height(np.ndarray[double, ndim = 2, mode = 'c'] xyz not None, scaleDomainSpacing not None):
-  
-  m_xyz = xyz.shape[0]
-  n_xyz = xyz.shape[1]
-  
-  assert n_xyz == 3
-  
-  cdef double *h;
-  cdef double resolution = scaleDomainSpacing;
-  cdef int32_t n = m_xyz;
-  cdef double *x = <double *> malloc(n * sizeof(double));
-  cdef double *y = <double *> malloc(n * sizeof(double));
-  cdef double *z = <double *> malloc(n * sizeof(double));
+    m_xyz = xyz.shape[0]
+    n_xyz = xyz.shape[1]
+
+    assert n_xyz == 3
+
+    cdef int * classification;
+    cdef double resolution = scaleDomain2Spacing;
+    cdef double thresh = curvatureThreshold;
+    cdef int32_t n = m_xyz;
+    cdef double *x = <double *> malloc(n * sizeof(double));
+    cdef double *y = <double *> malloc(n * sizeof(double));
+    cdef double *z = <double *> malloc(n * sizeof(double));
+
+    for i in range(n):
+        x[i] = xyz[i, 0]
+        y[i] = xyz[i, 1]
+        z[i] = xyz[i, 2]
+
+    with nogil:
+        classification = pymcc_classify(x, y, z, n, resolution, thresh);
   
-  for i in range(n):
-      x[i] = xyz[i, 0]
-      y[i] = xyz[i, 1]
-      z[i] = xyz[i, 2]
+    cdef np.ndarray[int32_t, ndim=1] np_classification = np.empty(n, dtype=np.int32);
+    for i in range(n):
+        np_classification[i] = classification[i]
+
+    return np_classification
+
+
+def calculate_excess_height(np.ndarray[double, ndim=2, mode='c'] xyz not None,
+                            scaleDomainSpacing not None):
   
-  with nogil: 
-    h = pymcc_pass(x, y, z, n, resolution);
-
-  cdef np.ndarray[double, ndim=1] np_h = np.empty(m_xyz);
-  for i in range(m_xyz):
-    np_h[i] = h[i]
-  free(x);
-  free(y);
-  free(z);
+    m_xyz = xyz.shape[0]
+    n_xyz = xyz.shape[1]
+
+    assert n_xyz == 3
+
+    cdef double *h;
+    cdef double resolution = scaleDomainSpacing;
+    cdef int32_t n = m_xyz;
+    cdef double *x = <double *> malloc(n * sizeof(double));
+    cdef double *y = <double *> malloc(n * sizeof(double));
+    cdef double *z = <double *> malloc(n * sizeof(double));
+
+    for i in range(n):
+        x[i] = xyz[i, 0]
+        y[i] = xyz[i, 1]
+        z[i] = xyz[i, 2]
+
+    with nogil:
+        h = pymcc_pass(x, y, z, n, resolution);
+
+    cdef np.ndarray[double, ndim=1] np_h = np.empty(m_xyz);
+    for i in range(m_xyz):
+        np_h[i] = h[i]
+
+    free(x);
+    free(y);
+    free(z);
+
   return np_h