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					@ -150,69 +150,7 @@ def extract_pts(las_in, cp_in, survey_date, keep_only_ground=True):
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					def process_tmp_csv(tmp_csv_file, survey_date, out_csv_loc, beach_name):
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					    #lascontrol does not output in a particularly useful format.
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					    #this processes its output to something useful
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					    tmp_csv=pd.read_csv(tmp_csv_file)
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					    profile=tmp_csv['ProfileNum']
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					    z=tmp_csv['lidar_z']
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					    x=tmp_csv['Easting']
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					    y=tmp_csv['Northing']
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					    chain=tmp_csv['Chainage']
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					    data={}
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					    i=0
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					    while i<len(profile):
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					        profile_now=profile[i]
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					        data[profile_now]={}
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					        easting=[]
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					        northing=[]
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					        chainage=[]
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					        elevation=[]
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					        while i<len(profile) and profile[i]==profile_now:
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					            easting.append(x[i])
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					            northing.append(y[i])
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					            elevation.append(z[i])
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					            chainage.append(chain[i])
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					            i=i+1
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					        data[profile_now]['Easting']=easting
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					        data[profile_now]['Northing']=northing
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					        data[profile_now]['Elevation']=elevation
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					        data[profile_now]['Chainage']=chainage
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					    for profile in data.keys():
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					        print(profile)
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					        if os.path.isfile("%s//%s.csv" % (out_csv_loc, profile)):
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					            #if the file already exists, check if our new date is there (if so, overwrite)
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					            file_check=pd.read_csv("%s//%s.csv" % (out_csv_loc, profile), dtype={'Date':str}) #
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					            if str(survey_date) in [str(file_check['Date'][i]) for i in range(0, len(file_check['Date']))]:
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					                file_check=file_check[file_check['Date']!=str(survey_date)]
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					                file_check.to_csv("%s//%s.csv" % (out_csv_loc,profile), index=False)
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					            #if the file exists, just append to the file
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					            f=open("%s//%s.csv" % (out_csv_loc, profile), 'a')
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					        else:
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					            #otherwise make a new file
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					            f=open("%s//%s.csv" % (out_csv_loc, profile), 'w')
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					            f.writelines("Beach,Profile,Date,Easting,Northing,Chainage,Elevation\n")
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					        for i in range(0, len(data[profile]['Easting'])):
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					            if data[profile]['Elevation'][i]=="-":
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					                z=""
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					            else:
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					                z=data[profile]['Elevation'][i]
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					            f.writelines("%s,%s,%s,%s,%s,%s,%s\n" % (beach_name, profile,survey_date, data[profile]['Easting'][i],data[profile]['Northing'][i],data[profile]['Chainage'][i], z))
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					        f.close()
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					    return None
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					def plot_profiles(profile_info, profile, output_loc, LL_limit):
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					def plot_profiles(profile_info, profile, output_loc, LL_limit):
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					    #plot the profile.  expects output from CC_split_profile
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					    #plot the profile.  expects output from CC_split_profile
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					@ -427,7 +365,8 @@ for i in range(0, len(params_file)): #0, len(params_file)
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					    make_raster(heatmap_las, output_raster, path_2_lastools, keep_only_ground=True)
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					    make_raster(heatmap_las, output_raster, path_2_lastools, keep_only_ground=True)
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					    #extract the points and get volumes
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					    #extract the points and get volumes
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					    extract_pts(final_las, input_csv, tmp_csv, path_2_lastools, keep_only_ground=True)
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					    df = extract_pts(final_las, input_csv, survey_date, keep_only_ground=True)
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					    update_survey_output(df, output_csv_dir)
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					    process_tmp_csv(tmp_csv, survey_date, csv_loc, beach)
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					    process_tmp_csv(tmp_csv, survey_date, csv_loc, beach)
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					    #colourise the point cloud
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					    #colourise the point cloud
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