From 3a9e035a275a6142eb78181534a8af277022b4d9 Mon Sep 17 00:00:00 2001
From: Dan Howe <d.howe@wrl.unsw.edu.au>
Date: Wed, 27 Jun 2018 12:24:40 +1000
Subject: [PATCH] Update 'extract_pts' and create 'update_survey_output'

---
 parse_stdout.py | 97 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 97 insertions(+)
 create mode 100644 parse_stdout.py

diff --git a/parse_stdout.py b/parse_stdout.py
new file mode 100644
index 0000000..c270a65
--- /dev/null
+++ b/parse_stdout.py
@@ -0,0 +1,97 @@
+import os
+import io
+import subprocess
+import pandas as pd
+import matplotlib.pyplot as plt
+
+survey_date = '20180517'
+beach = 'Avoca'
+output_csv_dir = 'csv'
+
+las_in = 'C:/Users/z3161860/Downloads/LASTools/XXFiles/S2_Delivery/avoca_20180517.las'
+cp_in = 'C:/Users/z3161860/Downloads/LASTools/XXFiles/CC_Profiles/Avoca_profiles.csv'
+
+
+def extract_pts(las_in, cp_in, survey_date, keep_only_ground=True):
+    """Extract elevations from a las surface based on x and y coordinates.
+
+       Requires lastools in system path.
+
+    Args:
+        las_in:            input point cloud (las)
+        cp_in:             point coordinates with columns: id, x, y, z (csv)
+        survey_date:       survey date string, e.g. '19700101'
+        keep_only_ground:  only keep points classified as 'ground' (boolean)
+
+    Returns:
+        Dataframe containing input coordinates with extracted elevations
+    """
+
+    cmd = ['lascontrol', '-i', las_in, '-cp', cp_in, '-parse', 'sxyz']
+
+    if keep_only_ground == True:
+        cmd += ['-keep_class', '2']
+
+    # Call lastools
+    process = subprocess.Popen(
+        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    stdout, stderr = process.communicate()
+    errcode = process.returncode
+
+    # Handle errors, if detected
+    if errcode != 0:
+        print("Error. lascontrol failed on {}".format(
+            os.path.basename(las_in)))
+        print(stderr.decode())
+
+    # Load result into pandas dataframe
+    df = pd.read_csv(io.BytesIO(stdout))
+
+    # Tidy up dataframe
+    df = df.drop(columns=['diff'])
+    df['lidar_z'] = pd.to_numeric(df['lidar_z'], errors='coerce')
+    df['Beach'] = beach
+    df = df[[
+        'Beach', 'ProfileNum', 'Easting', 'Northing', 'Chainage', 'lidar_z'
+    ]]
+
+    # Rename columns
+    new_names = {
+        'ProfileNum': 'Profile',
+        'lidar_z': 'Elevation_{}'.format(survey_date),
+    }
+    df = df.rename(columns=new_names)
+
+    return df
+
+
+def update_survey_output(df, output_dir):
+    """Update survey profile output csv files with current survey.
+
+    Args:
+        df:         dataframe containing current survey elevations
+        output_dir: directory where csv files are saved
+
+    Returns:
+        None
+    """
+    # Merge current survey with existing data
+    profiles = df['Profile'].unique()
+    for profile in profiles:
+        csv_name = os.path.join(output_csv_dir, profile + '.csv')
+        try:
+            # Load existing results
+            master = pd.read_csv(csv_name)
+        except FileNotFoundError:
+            master = df.copy()
+
+        # Add (or update) current survey
+        current_survey_col = df.columns[-1]
+        master[current_survey_col] = df[current_survey_col]
+
+        # Export updated results
+        master.to_csv(csv_name)
+
+
+df = extract_pts(las_in, cp_in, survey_date, keep_only_ground=True)
+update_survey_output(df, output_csv_dir)