from gef_parser import read_gef_file
# Example 1: Parse a single file
file_path = './sample_cptu_file.GEF.txt'
cpt_header, measurement_columns_and_units, measurements = read_gef_file(file_path)

print(measurements)
print(cpt_header)
print(measurement_columns_and_units)

import pandas as pd
import matplotlib.pyplot as plt

file_path = './sample_cptu_file.GEF.txt'
cpt_header, measurement_columns_and_units, measurements = read_gef_file(file_path)

# ## Create a pandas df from it and plot qc vs. depth
df = pd.DataFrame.from_dict(measurements)

# ## Data can easily be plotted
plt.plot(df['qc'], df['Tiefe'])
plt.gca().invert_yaxis()
plt.xlabel("qc [MPa]")
plt.ylabel("Depth [m]")
plt.show()

# Parse all *.gef.txt files in the GEF_SAMPLES folder
from glob import glob
folder_path = './GEF_SAMPLES/**/*.GEF.txt'
all_measurements = []
all_cpt_header_info = []
for file_path in glob(folder_path):
    cpt_header, measurement_columns_and_units, measurements = read_gef_file(file_path)
    measurements = [dict(item, **{'aufschluss_name':cpt_header['aufschluss_name']}) for item in measurements] # add aufschluss_name to the measurements
    all_measurements += measurements
    all_cpt_header_info.append(cpt_header)

## optionally add them to a pd.Dataframe and export it to a single excel file
import pandas as pd
header_df = pd.DataFrame.from_dict(all_cpt_header_info)
measurements_df = pd.DataFrame.from_dict(all_measurements)
excel_outpath = './CPT_Summary.xlsx'

# depending on the ampount of cpt measurement data the excel file can take some time
with pd.ExcelWriter(excel_outpath) as writer:
    header_df.to_excel(writer, sheet_name="Sheet0_cpt_header_info", index=False)
    measurements_df.to_excel(writer, sheet_name="Sheet1_cpt_measurements", index=False)

# optionally export the data into two csv files that can be imported into Leapfrog Works
header_df.to_csv('collar.csv')
measurements_df.to_csv('intervals.csv')

# Example 4: Create Thiessen Polygons and a Delauny triangulation from CPT xyz-Coordinates
from glob import glob
folder_path = './GEF_SAMPLES/**/*.GEF.txt'
all_measurements = []
all_cpt_header_info = []
for file_path in glob(folder_path):
    cpt_header, measurement_columns_and_units, measurements = read_gef_file(file_path)
    measurements = [dict(item, **{'aufschluss_name':cpt_header['aufschluss_name']}) for item in measurements] # add aufschluss_name to the measurements
    all_measurements += measurements
    all_cpt_header_info.append(cpt_header)

# Create Delauny and Thiessen Polygons
default_points = [(0,0,0),(5,5,0),(5,0,0), (10,3,2)]
points = [(cpt.get('RW'), cpt.get('HW')) for cpt in all_cpt_header_info if(cpt.get('RW') is not None and cpt.get('HW') is not None)]
if(len(points)==0):
    points = default_points

triangle_polygons = pytess_triangulate(points)
print(triangle_polygons)

thiessen_polygons = pytess_voronoi(points, buffer_percent=100)
print(thiessen_polygons)

print("...do some stuff with the triangulation")