Add plot_profiles() function

outputs_2017088_Survey2.py

@@ -195,12 +195,45 @@ def profile_plots_volume(csv_loc, LL_xlsx, output_xlsx, graph_location):
         row=row+1
     return results_volume
 
+
 def remove_temp_files(directory):
     for f in os.listdir(directory):
         os.unlink(os.path.join(directory, f))
 
     return None
 
+
+def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits):
+    csv_name = profile_name + '.csv'
+    profiles = pd.read_csv(os.path.join(csv_output_dir, csv_name))
+
+    # Remove metadata, and extract profile coordinates
+    profiles = profiles.loc[:, 'Chainage':].set_index('Chainage')
+
+    # Find landward limit of profile (behind beach)
+    ch_min = ch_limits.loc[profile_name, 'Landward Limit']
+
+    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:])
+
+        ax.plot(profile.index, profile, label=date)
+
+    ax.set_xlabel('Chainage (m)', labelpad=10)
+    ax.set_ylabel('Elevation (m AHD)', labelpad=10)
+    ax.legend(frameon=False, fontsize=9)
+
+    ax.xaxis.set_minor_locator(MultipleLocator(5))
+    ax.yaxis.set_minor_locator(MultipleLocator(0.5))
+    ax.xaxis.grid(True, which='minor', color='k', linewidth=0.5, alpha=0.3)
+    ax.yaxis.grid(True,which='minor',color='k', linewidth=0.5, alpha=0.3)
+
+    png_name = os.path.join(graph_loc, profile_name + '.png')
+    plt.savefig(png_name, bbox_inches='tight', dpi=300)
+
+
 input_file = 'Parameter Files/las-manipulation-survey-2.xlsx'
 params_file=pd.read_excel(input_file, sheet_name="PARAMS")
 
@@ -263,45 +296,18 @@ for i, row in params_file.iterrows():
         verbose=False)
     update_survey_output(df, csv_output_dir)
 
+    # Get landward limit of surveys
+    ch_limits = pd.read_excel(profile_limit_file, index_col='Profile')
 
-
-    #colourise the point cloud
+    # 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)
 
 
     #delete the temp files from the tmp_dir and the interim_dir
     remove_temp_files(tmp_dir)
     #remove_temp_files(int_dir)
 
-csv_names = [f for f in os.listdir(csv_output_dir) if f.endswith('.csv')]
-ch_limits = pd.read_excel(profile_limit_file, index_col='Profile')
-
-for csv_name in csv_names:
-    profile_name = os.path.splitext(csv_name)[0]
-    profiles = pd.read_csv(os.path.join(csv_output_dir, csv_name))
-
-    # Remove metadata, and extract profile coordinates
-    profiles = profiles.loc[:, 'Chainage':].set_index('Chainage')
-
-    # Find landward limit of profile (behind beach)
-    ch_min = ch_limits.loc[profile_name, 'Landward Limit']
-
-    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:])
-
-        ax.plot(profile.index, profile, label=date)
-
-    ax.set_xlabel('Chainage (m)', labelpad=10)
-    ax.set_ylabel('Elevation (m AHD)', labelpad=10)
-    ax.legend(frameon=False)
-    plt.show()
-
-
-
-
-
-
 print("doing the volume analysis")
 # test=profile_plots_volume(csv_output_dir, profile_limit_file, volume_output, graph_loc)