Scale figures based on beach size

las_outputs.py

@@ -28,6 +28,25 @@ import nielsen_volumes
 from survey_tools import call_lastools, extract_pts, update_survey_output
 
 
+def get_datestring(x):
+    """Format a date integer into an ISO-8601 date string
+
+    Args:
+        x:  integer representation of date string
+
+    Returns:
+        formatted date string
+
+    Examples:
+
+    >> get_datestring(19700101)
+    '1970-01-01'
+    """
+    datestr = pd.datetime.strptime(str(x), '%Y%m%d').strftime('%Y-%m-%d')
+
+    return datestr
+
+
 def remove_temp_files(directory):
     for f in os.listdir(directory):
         os.unlink(os.path.join(directory, f))
@@ -45,20 +64,28 @@ def plot_profiles(profile_name, csv_output_dir, graph_loc, ch_limits, delta_vol)
     # Find landward limit of profile (behind beach)
     ch_min = ch_limits.loc[profile_name, 'Landward Limit']
 
-    ax = plt.axes()
+    # Set figure dimensions based on beach size
+    vertical_exag = 8
+    m_per_inch = 8
+    fig_h = profiles.dropna().values.max() / m_per_inch * vertical_exag
+    fig_w = (profiles.index.max() - ch_min) / m_per_inch
+
+    fig, ax = plt.subplots(figsize=(fig_w, fig_h))
     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 = get_datestring(date_str)
 
         ax.plot(profile.index, profile, label=date)
 
+    ax.set_aspect(vertical_exag)
+
     ax.set_xlabel('Chainage (m)', labelpad=10)
     ax.set_ylabel('Elevation (m AHD)', labelpad=10)
 
     # Show most recent volume change
     ax.annotate('Most recent\nvolume change:\n{:0.1f} m$^3$/m'.format(delta_vol),
-                (0.1, 0.15), xycoords='axes fraction', fontsize=8,
+                (0.05, 0.15), xycoords='axes fraction', fontsize=9,
                 backgroundcolor='#ffffff', linespacing=1.5)
     ax.legend(edgecolor='none', facecolor='#ffffff', fontsize=9)
 
@@ -91,8 +118,7 @@ def calculate_volumes(profile_name, survey_date, csv_output_dir, ch_limits, volu
         volumes = pd.DataFrame()
 
     # Format dates
-    date_str = str(survey_date)
+    date = get_datestring(survey_date)
-    date = '{}-{}-{}'.format(date_str[:4], date_str[4:6], date_str[6:])
 
     for current_date in profiles.columns:
         # Get Nielsen erosion volumes
@@ -216,7 +242,3 @@ def main():
 
 if __name__ == '__main__':
     main()
-
-if True:
-    plt.plot([], label='label')
-    plt.legend(facecolor='r')