diff --git a/outputs_2017088_Survey2.py b/outputs_2017088_Survey2.py
index 8131f84..a389466 100644
--- a/outputs_2017088_Survey2.py
+++ b/outputs_2017088_Survey2.py
@@ -26,94 +26,6 @@ from cycler import cycler
 from survey_tools import call_lastools, extract_pts, update_survey_output
 
 
-def plot_profiles(profile_info, profile, output_loc, LL_limit):
-    #plot the profile.  expects output from CC_split_profile
-
-    YminorLocator=MultipleLocator(0.5)
-    XminorLocator=MultipleLocator(5)
-
-
-    fig,ax=plt.subplots(figsize=(8, 3))
-
-    num_plots=len(profile_info.keys())-1
-    colormap = plt.cm.jet
-    ax.set_prop_cycle(cycler('color', [colormap(i) for i in np.linspace(0, 0.9, num_plots)]))
-
-    max_y=0
-    for date in profile_info.keys():
-        if date!='info':
-
-            plt.plot(profile_info[date]['Chainage'], profile_info[date]['Elevation'], label=date)
-            try:
-                if max([i for i in profile_info[date]['Elevation'] if pd.isnull(i)==False])>max_y:
-                    max_y=max([i for i in profile_info[date]['Elevation'] if pd.isnull(i)==False])
-            except:
-                print("empty elevation section for  %s" %  date)
-
-
-    plt.plot([LL_limit,LL_limit], [-1,max_y], 'r--', alpha=0.5, label="Landward Limit")
-
-
-    plt.xlabel('Chainage (m)',weight='bold')
-    plt.ylabel('Elevation (m AHD)',weight='bold')
-    plt.legend(loc='upper right', bbox_to_anchor=(1.3,1))
-    plt.title(profile)
-    plt.rcParams['font.size']=8
-
-    ax.set_ylim([-1,math.ceil(max_y)])
-
-    ax.xaxis.set_minor_locator(XminorLocator)
-    ax.yaxis.set_minor_locator(YminorLocator)
-    ax.xaxis.grid(True, which='minor', color='k', linestyle='-', alpha=0.3)
-    ax.yaxis.grid(True,which='minor',color='k', linestyle='-', alpha=0.3)
-
-    plt.grid(which='major', color='k', linestyle='-')
-    today=datetime.datetime.now().date().strftime('%Y%m%d')
-    plt.savefig(os.path.join(output_loc, '%s_%s.png' % (today, profile)),bbox_inches='tight',dpi=900)
-    plt.clf()
-
-    return None
-
-
-def CC_split_profile(file2read):
-    # this reads the profile files and splits it into dates
-
-    file_master=pd.read_csv(file2read)
-
-    beach_original=file_master['Beach'].tolist()
-    profile_original=file_master['Profile'].tolist()
-    date_original=file_master['Date'].tolist()
-    chainage_original=file_master['Chainage'].tolist()
-    elevation_original=file_master['Elevation'].tolist()
-    easting_original=file_master['Easting'].tolist()
-    northing_original=file_master['Northing'].tolist()
-
-    data={}
-    i=0
-
-    #add info on the beach and profile number
-    data['info']={'Profile':profile_original[0], 'Beach':beach_original[0]}
-    date_now=date_original[0]
-
-    while i<len(file_master):
-        chainage_tmp=[]
-        elevation_tmp=[]
-        easting_tmp=[]
-        northing_tmp=[]
-        while i<len(file_master) and date_now==date_original[i]:
-            chainage_tmp.append(chainage_original[i])
-            elevation_tmp.append(elevation_original[i])
-            easting_tmp.append(easting_original[i])
-            northing_tmp.append(northing_original[i])
-            i=i+1
-
-        data[date_now]={'Beach': beach_original[i-1], 'Profile':profile_original[i-1],'Easting': easting_tmp, 'Northing':northing_tmp, 'Elevation':elevation_tmp, 'Chainage':chainage_tmp}
-
-        if i<len(file_master):
-            date_now=date_original[i]
-
-    return data
-
 def profile_plots_volume(csv_loc, LL_xlsx, output_xlsx, graph_location):
     #get a list of all csvs which will each be analysed
     file_list=[]
@@ -203,7 +115,7 @@ def remove_temp_files(directory):
     return None
 
 
-def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
+def plot_profiles(profile_name, survey_date, csv_output_dir, graph_loc, ch_limits):
     csv_name = profile_name + '.csv'
     profiles = pd.read_csv(os.path.join(csv_output_dir, csv_name))
 
@@ -216,8 +128,7 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
     ax = plt.axes()
     for col in profiles.columns:
         profile = profiles.loc[ch_min:, col]
-        date_str = col.split('_')[-1]
-        date = '{}-{}-{}'.format(date_str[:4], date_str[4:6], date_str[6:])
+        date = '{}-{}-{}'.format(survey_date[:4], survey_date[4:6], survey_date[6:])
 
         ax.plot(profile.index, profile, label=date)
 
@@ -232,6 +143,7 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
 
     png_name = os.path.join(graph_loc, profile_name + '.png')
     plt.savefig(png_name, bbox_inches='tight', dpi=300)
+    plt.close()
 
 
 input_file = 'Parameter Files/las-manipulation-survey-2.xlsx'
@@ -302,7 +214,7 @@ for i, row in params_file.iterrows():
     # Plot profiles of current beach
     profile_names = df['Profile'].unique()
     for profile_name in profile_names:
-        plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits)
+        plot_profiles(profile_name, survey_date, csv_output_dir, graph_loc, ch_limits)
 
 
     #delete the temp files from the tmp_dir and the interim_dir