Add coverage for the LID_USAGE section

swmmio/core.py

@@ -19,6 +19,7 @@
 
 from swmmio.utils.functions import trim_section_to_nodes
 from swmmio.utils.text import get_inp_sections_details, get_rpt_sections_details, get_rpt_metadata
+import swmmio.utils.text
 
 pd.set_option('display.max_columns', 5)
 
@@ -498,6 +499,20 @@ def headers(self):
 
         return self._rpt_section_details
 
+    @property
+    def external_outflow_volume(self):
+        """
+        Return the external outflow from rpt file in mm or inches
+        """
+        return float(swmmio.utils.text.get_rpt_value(self.path, "External Outflow"))
+
+    @property
+    def flooding_loss_volume(self):
+        """
+        Return the flooding loss from rpt file in mm or inches
+        """
+        return float(swmmio.utils.text.get_rpt_value(self.path, "Flooding Loss"))
+
 
 # setattr(rpt, 'link_flow_summary', property(get_rpt_df('Link Flow Summary')))
 
@@ -515,6 +530,7 @@ def __init__(self, file_path):
         self._report_df = None
         self._conduits_df = None
         self._xsections_df = None
+        self._lid_usage_df = None
         self._pollutants_df = None
         self._landuses_df = None
         self._buildup_df = None
@@ -586,6 +602,7 @@ def __init__(self, file_path):
             '[INFLOWS]',
             '[Polygons]',
             '[TIMESERIES]',
+            '[LID_USAGE]',
             '[TAGS]',
             '[STREETS]',
             '[INLETS]',
@@ -611,10 +628,12 @@ def save(self, target_path=None):
         else:
             target_path = self.path
 
+
         for section in self._sections:
             # reformate the [SECTION] to section (and _section_df)
             sect_id = section.translate({ord(i): None for i in '[]'}).lower()
             sect_id_private = '_{}_df'.format(sect_id)
+            #print(sect_id_private)
             data = getattr(self, sect_id_private)
             if data is not None:
                 replace_inp_section(target_path, section, data)
@@ -857,6 +876,31 @@ def xsections(self, df):
         """Set inp.xsections DataFrame."""
         self._xsections_df = df
 
+
+    @property
+    def lid_usage(self):
+        """
+        Get/set LID_USAGE section of the INP file.
+        """
+        if self._lid_usage_df is None:
+            self._lid_usage_df = dataframe_from_inp(self.path, "[LID_USAGE]")
+        return self._lid_usage_df
+
+    @property
+    def raingages(self):
+        """
+        Get/set RAINGAGES section of the INP file.
+        """
+        if self._raingages_df is None:
+            self._raingages_df = dataframe_from_inp(self.path, "[RAINGAGES]")
+        return self._raingages_df
+
+
+    @lid_usage.setter
+    def lid_usage(self, df):
+        """Set inp.lid_usage DataFrame."""
+        self._lid_usage_df = df
+
     @property
     def pollutants(self):
         """

swmmio/defs/inp_sections.yml

@@ -63,7 +63,9 @@ inp_file_objects:
   XSECTIONS: [Link, Shape, Geom1, Geom2, Geom3, Geom4, Barrels, XX]
   POLLUTANTS: [Name, MassUnits, RainConcen, GWConcen, I&IConcen, DecayCoeff, SnowOnly,
                CoPollutName, CoPollutFraction, DWFConcen, InitConcen]
+
   INFLOWS: [Node, Constituent, Time Series, Type, Mfactor, Sfactor, Baseline, Pattern]
+  LID_USAGE: [Subcatchment,   'LID_Process',      Number,  Area,       Width,      InitSat,    FromImp,    ToPerv,     RptFile,                  DrainTo,          FromPerv,]
 
   TIMESERIES: [Name, Date, Time, Value]
   COORDINATES: [Name, X, Y]
@@ -82,7 +84,7 @@ inp_file_objects:
 
 
 inp_section_tags:
-  ['[TITLE', '[OPTION', '[FILE', '[RAINGAGE', '[TEMPERATURE', '[EVAP',
+  ['[TITLE', '[OPTION', '[FILE', '[RAINGAGES', '[TEMPERATURE', '[EVAP',
   '[SUBCATCHMENT', '[SUBAREA', '[INFIL', '[AQUIFER', '[GROUNDWATER', '[SNOWPACK',
   '[JUNC', '[OUTFALL', '[STORAGE', '[DIVIDER', '[CONDUIT', '[PUMP', '[ORIFICE', '[WEIR',
   '[OUTLET', '[XSECT', '[TRANSECT', '[LOSS', '[CONTROL', '[POLLUT', '[LANDUSE', '[BUILDUP',

swmmio/utils/text.py

@@ -137,6 +137,19 @@ def extract_section_of_file(file_path, start_strings, end_strings, comment=';',
     return out_string
 
 
+def get_rpt_value(file_path, value_type):
+    """
+    scan rpt file and find the line starting with value_type and return the last numeric value
+
+    """
+
+    with open(file_path,"r") as fi:
+        for ln in fi:
+            if ln.strip().startswith(value_type):
+                #print(ln)
+                return ln.split()[-1]
+        return None
+
 def get_rpt_metadata(file_path):
     """
     Scan rpt file and extract meta data