some documentation

Author: jsharpna

emr_hosp/README.md

@@ -1,6 +1,9 @@
 # EMR Hospitalizations Indicator
 
 COVID-19 indicator using hospitalizations from electronic medical records (EMR). 
+Reads claims data (AGG) and EMR data (CMB) and combines into pandas dataframe.
+Makes appropriate date shifts, adjusts for backfilling, and smooths estimates.
+Writes results to csvs.
 
 
 ## Running the Indicator
@@ -56,3 +59,10 @@ The output will show the number of unit tests that passed and failed, along
 with the percentage of code covered by the tests. None of the tests should
 fail and the code lines that are not covered by unit tests should be small and
 should not include critical sub-routines.
+
+## Code tour
+
+- update_sensor.py: EMRHospSensorUpdator: reads the data, makes transformations, 
+- sensor.py: EMRHospSensor: methods for transforming data, including backfill and smoothing
+- load_data.py: methods for loading claims and EHR data
+- geo_maps.py: geo reindexing

emr_hosp/delphi_emr_hosp/update_sensor.py

@@ -97,23 +97,27 @@ def __init__(self,
 
 
     def shift_dates(self):
-        """shift estimates one day forward to account for a 1 day lag, e.g.
-        we want to produce estimates for the time range May 2 to May 20, inclusive
-        given a drop on May 20, we have data up until May 19.
-        we then train on data from Jan 1 until May 19, storing only the sensors
-        on May 1 to May 19. we then shift the dates forward by 1, giving us sensors
-        on May 2 to May 20. therefore, we will move the startdate back by one day
-        in order to get the proper estimate at May 1
+        """shift estimates forward to account for time lag, compute burnindates, sensordates
         """
-        ## JS: WILL USE DATETIMEINDEX FOR THIS...
+
         drange = lambda s, e: pd.date_range(start=s,periods=(e-s).days,freq='D')
         self.startdate = self.startdate - Config.DAY_SHIFT
         self.burnindate = self.startdate - Config.BURN_IN_PERIOD
         self.fit_dates = drange(Config.FIRST_DATA_DATE, self.dropdate)
         self.burn_in_dates = drange(self.burnindate, self.dropdate)
         self.sensor_dates = drange(self.startdate, self.enddate)
+        return True
 
     def geo_reindex(self,data,staticpath):
+        """Reindex based on geography, include all date, geo pairs
+
+        Args:
+            data: dataframe, the output of loadcombineddata
+            staticpath: path for the static geographic files
+
+        Returns:
+            dataframe
+        """
         # get right geography
         geo = self.geo
         geo_map = GeoMaps(staticpath)
@@ -207,7 +211,6 @@ def update_sensor(self,
                 pool_results = [proc.get() for proc in pool_results]
 
                 for res in pool_results:
-                    ## un-tested
                     geo_id = res["geo_id"]
                     res = pd.DataFrame(res)
                     sensor_rates[geo_id] = np.array(res.loc[final_sensor_idxs, "rate"])