Save most recent profile images in 'latest' folder

las_outputs.py

@@ -32,7 +32,7 @@ def get_datestring(x):
     """Format a date integer into an ISO-8601 date string
 
     Args:
-        x:  integer representation of date string
+        x:  unformatted date
 
     Returns:
         formatted date string
@@ -54,13 +54,20 @@ def remove_temp_files(directory):
     return None
 
 
-def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits, delta_vol):
+def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits, delta_vol, survey_date):
     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')
 
+    # Determine if current survey is the latest
+    current_survey_col = 'Elevation_' + survey_date
+    is_latest = profiles.columns[-1] == current_survey_col
+
+    # Only plot profiles up to current survey date
+    profiles = profiles.loc[:, :current_survey_col]
+
     # Find landward limit of profile (behind beach)
     ch_min = ch_limits.loc[profile_name, 'Landward Limit']
 
@@ -84,9 +91,11 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits, delta_vol)
     ax.set_ylabel('Elevation (m AHD)', labelpad=10)
 
     # Show most recent volume change
+    if delta_vol is not None:
         ax.annotate('Most recent\nvolume change:\n{:0.1f} m$^3$/m'.format(delta_vol),
                     (0.05, 0.15), xycoords='axes fraction', fontsize=9,
                     backgroundcolor='#ffffff', linespacing=1.5)
+
     ax.legend(edgecolor='none', facecolor='#ffffff', fontsize=9)
 
     ax.xaxis.set_minor_locator(MultipleLocator(5))
@@ -94,7 +103,20 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits, delta_vol)
     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')
+    # Save in folder with current date
+    png_dirs = [os.path.join(graph_loc, get_datestring(survey_date))]
+    if is_latest:
+        # Save copy in'latest' if survey is most recent
+        png_dirs += [os.path.join(graph_loc, 'latest')]
+
+    for png_dir in png_dirs:
+        # Prepare output directory
+        try:
+            os.makedirs(png_dir)
+        except FileExistsError:
+            pass
+
+        png_name = os.path.join(png_dir, profile_name + '.png')
         plt.savefig(png_name, bbox_inches='tight', dpi=300)
     plt.close()
 
@@ -117,9 +139,6 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
     except FileNotFoundError:
         volumes = pd.DataFrame()
 
-    # Format dates
-    date = get_datestring(survey_date)
-
     for current_date in profiles.columns:
         # Get Nielsen erosion volumes
         chainage = profiles.loc[:, current_date].dropna().index
@@ -127,7 +146,7 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
         volume = nielsen_volumes.volume_available(chainage, elevation, ch_min)
 
         # Update spreadsheet
-        volumes.loc[profile_name, date] = volume
+        volumes.loc[profile_name, 'Volume_' + survey_date] = volume
 
     # Save updated volumes spreadsheet
     volumes = volumes[volumes.columns.sort_values()]
@@ -135,9 +154,13 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
     volumes.to_csv(csv_vol)
 
     # Get most recent volume difference for current profile
+    try:
         previous_vol = volumes.loc[profile_name].values[-2]
         current_vol = volumes.loc[profile_name].values[-1]
         delta_vol = current_vol - previous_vol
+    except IndexError:
+        # Return None if there is only one survey
+        delta_vol = None
 
     return delta_vol
 
@@ -164,7 +187,7 @@ def main():
     for i, row in params_file.iterrows():
         print("Starting to process %s" % row['Beach'])
         beach=row['Beach']
-        survey_date = row['SURVEY DATE']
+        survey_date = str(row['SURVEY DATE'])
         original_las = row['INPUT LAS']
         classified_las_dir = row['LAS CLASSIFIED FOLDER']
         shp_swash_dir = row['SHP SWASH FOLDER']
@@ -234,7 +257,7 @@ def main():
                                           csv_output_dir, ch_limits,
                                           volume_output_dir)
             plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits,
-                          delta_vol)
+                          delta_vol, survey_date)
 
         # Remove temprary files
         remove_temp_files(tmp_dir)