Replace analysisObj.getResults() with results property

bifacial_radiance/data/module.json

@@ -63,35 +63,25 @@
         "zgap": 0.1
     },
     "test": {
-        "bifi": 0.8,
+        "bifi": 1,
         "glass": false,
         "modulefile": "objects\\test.rad",
         "modulematerial": "black",
         "numpanels": 1,
         "offsetfromaxis": 0,
-        "scenex": 1.01,
-        "sceney": 2.0,
+        "scenex": 1.6,
+        "sceney": 0.95,
         "scenez": 0.1,
-        "text": "! genbox black test 1 2 0.02 | xform -t -0.5 -1.0 0 -a 1 -t 0 2.0 0",
-        "x": 1,
+        "text": "! genbox black test 1.59 0.95 0.02 | xform -t -0.795 -0.475 0 -a 1 -t 0 0.95 0",
+        "x": 1.59,
         "xgap": 0.01,
-        "y": 2,
+        "y": 0.95,
         "ygap": 0.0,
         "z": 0.02,
         "zgap": 0.1
     },
     "test-module": {
-        "CECMod": {
-            "Adjust": "22.9092",
-            "I_L_ref": "6.05373",
-            "I_o_ref": "8.36043e-11",
-            "R_s": "0.30812",
-            "R_sh_ref": "500.069",
-            "a_ref": "2.57764",
-            "alpha_sc": "0.00373527",
-            "name": "SunPower SPR-E19-310-COM"
-        },
-        "bifi": 0.9,
+        "bifi": 1,
         "glass": false,
         "modulefile": "objects\\test-module.rad",
         "modulematerial": "black",

bifacial_radiance/load.py

@@ -319,9 +319,7 @@ def _printRow(analysisobj, key):
         else:
             keyname = 'timestamp'
         return pd.concat([pd.DataFrame({keyname:key},index=[0]),
-                         analysisobj.getResults(),
-                         analysisobj.power_data 
-                         ], axis=1)
+                         analysisobj.results], axis=1)
 
     for key in trackerdict:
         try:

bifacial_radiance/main.py

@@ -2800,8 +2800,9 @@ def analysis1axis(self, trackerdict=None, singleindex=None, accuracy='low',
             for each timestamp:
     
         trackerdict.key.'AnalysisObj'  : analysis object for this tracker theta
-            to get a dictionary of results, run :py:class:`bifacial_radiance.AnalysisObj`.getResults
-        :py:class:`bifacial_radiance.AnalysisObj`.getResults returns the following keys:
+            to get a dictionary of results, run :py:class:`bifacial_radiance.AnalysisObj`.results
+        :py:class:`bifacial_radiance.AnalysisObj`.results returns the following df:
+            'name', 'modNum', 'rowNum', 'sceneNum', 'x','y','z', 'mattype', 'rearMat', 
             'Wm2Front'     : np.array of front Wm-2 irradiances, len=sensorsy_back
             'Wm2Back'      : np.array of rear Wm-2 irradiances, len=sensorsy_back
             'backRatio'    : np.array of rear irradiance ratios, len=sensorsy_back
@@ -2928,8 +2929,8 @@ def analysis1axisground(self, trackerdict=None, singleindex=None, accuracy='low'
             for each timestamp:
     
         trackerdict.key.'AnalysisObj'  : analysis object for this tracker theta
-            to get a dictionary of results, run :py:class:`bifacial_radiance.AnalysisObj`.getResults
-        :py:class:`bifacial_radiance.AnalysisObj`.getResults returns the following keys:
+            to get a dictionary of results, run :py:class:`bifacial_radiance.AnalysisObj`.results
+        :py:class:`bifacial_radiance.AnalysisObj`.results returns the following keys:
             'Wm2Ground'     : np.array of Wm-2 irradiances along the ground, len=sensorsground
             'sensorsground'      : int of number of ground scan points
 
@@ -3052,9 +3053,7 @@ def _printRow(analysisobj, key):
                 else:
                     keyname = 'timestamp'
                 return pd.concat([pd.DataFrame({keyname:key},index=[0]),
-                                 analysisobj.getResults(),
-                                 analysisobj.power_data 
-                                 ], axis=1)
+                                 analysisobj.results], axis=1)
 
 
 
@@ -3084,7 +3083,7 @@ def _printRow(analysisobj, key):
                                 module_local = trackerdict[key]['scenes'][analysis.sceneNum].module
                             else:
                                 module_local = module
-                            power_data = analysis.calculatePerformance(meteo_data=meteo_data, 
+                            analysis.calculatePerformance(meteo_data=meteo_data, 
                                                           module=module_local,
                                                           cumulativesky=self.cumulativesky,   
                                                            CECMod2=CECMod2, 
@@ -4346,8 +4345,26 @@ def _makeTrackerCSV(self, theta_list, trackingdata):
 class AnalysisObj(SuperClass):
     """
     Analysis class for performing raytrace to obtain irradiance measurements
-    at the array, as well plotting and reporting results.
+    at the array, as well as plotting and reporting results.
     """
+    @property
+    def results(self):
+        """
+        go through the AnalysisObj and return a DF of irradiance result keys.
+        """
+        try:
+            keylist = ['rowWanted', 'modWanted', 'sceneNum', 'name', 'x', 'y','z',
+                        'Wm2Front', 'Wm2Back', 'Wm2Ground', 'backRatio', 'mattype', 'rearMat' ]
+            resultdict = {k: v for k, v in self.__dict__.items() if k in keylist}
+            results = pd.DataFrame.from_dict(resultdict, orient='index').T.rename(
+                columns={'modWanted':'modNum', 'rowWanted':'rowNum'})
+            if getattr(self, 'power_data', None) is not None:
+                return pd.concat([results, self.power_data], axis=1)
+            else:    
+                return results
+        except AttributeError:
+            return None
+
     def __printval__(self, attr):
         try:
             t = getattr(self,attr, None)[0]
@@ -4359,7 +4376,7 @@ def __printval__(self, attr):
             return getattr(self,attr)
 
     def __repr__(self):
-        return str(type(self)) + ' : ' +  str({key:  self.__printval__(key) for key in self.columns})  
+        return str(type(self)) + ' : ' +  str({key:  self.__printval__(key) for key in self.columns if key != 'results'})  
     def __init__(self, octfile=None, name=None, hpc=False):
         """
         Initialize AnalysisObj by pointing to the octfile.  Scan information
@@ -4384,25 +4401,17 @@ def __init__(self, octfile=None, name=None, hpc=False):
         self.rowWanted = None
         self.sceneNum = 0 # should this be 0 or None by default??
         self.power_data = None  # results from self.calculatePerformance() stored here
-
-
 
+    """
+    def getResults(self):   ### REPLACED BY `results` PROPERTY
 
-    def getResults(self):
-        """
-        go through the AnalysisObj and return a dict of irradiance result keys.
-
-        Returns
-        -------
-        Results : dict.  irradiance scan results
-        """
         #TODO (optional?) Merge power_data to returned values??
         keylist = ['rowWanted', 'modWanted', 'sceneNum', 'name', 'x', 'y','z',
                     'Wm2Front', 'Wm2Back', 'Wm2Ground', 'backRatio', 'mattype', 'rearMat' ]
         resultdict = {k: v for k, v in self.__dict__.items() if k in keylist}
         return pd.DataFrame.from_dict(resultdict, orient='index').T.rename(
             columns={'modWanted':'modNum', 'rowWanted':'rowNum'})
-
+    """
 
 
     def makeImage(self, viewfile, octfile=None, name=None):
@@ -5476,14 +5485,14 @@ def calculatePerformance(self, meteo_data, cumulativesky, module,
                 raise TypeError('ModuleObj input required for AnalysisObj.calculatePerformance. '+\
                                 f'type passed: {type(module)}')           
 
-            self.power_data = performance.calculatePerformance(module=module, results=self.getResults(),
+            self.power_data = performance.calculatePerformance(module=module, results=self.results,
                                                CECMod2=CECMod2, agriPV=agriPV,
                                                **meteo_data)
 
         else:
             # TODO HERE: SUM all keys for rows that have the same rowWanted/modWanted
 
-            self.power_data = performance.calculatePerformanceGencumsky(results=self.getResults(),
+            self.power_data = performance.calculatePerformanceGencumsky(results=self.results,
                                                                  agriPV=agriPV)
             #results.to_csv(os.path.join('results', 'Cumulative_Results.csv'))
 

docs/sphinx/source/whatsnew/v0.5.0.rst

@@ -41,7 +41,7 @@ Deprecations
 
 API Changes
 ~~~~~~~~~~~~
-* A new function can now be called to compile results and report out final irradiance and performance data: :py:class:`~bifacial_radiance.RadianceObj.getResults`.
+* A new function can now be called to compile results and report out final irradiance and performance data: :py:class:`~bifacial_radiance.AnalysisObj.results` and :py:class:`~bifacial_radiance.RadianceObj.getResults`.
 * Results generated with the above can be saved with the :py:class:`~bifacial_radiance.RadianceObj.exportTrackerDict`, which saves an Hourly, Monthly and Yearly .csvs in the results folder.
 * NSRDB weather data can now be loaded using :py:class:`~bifacial_radiance.RadianceObj.NSRDBWeatherData`.
 * :py:class:`~bifacial_radiance.AnalysisObj.analysis` updated to allow single (front-only) scans in support of AgriPV modeling.  Pass `None` to `backscan` for single-sided scan. (:pull:`499`)
@@ -59,7 +59,7 @@ Enhancements
 * New function :py:class:`~bifacial_radiance.AnalysisObj.calculatePerformance` and :py:class:`~bifacial_radiance.ModuleObj.calculatePerformance` to call CEC performance calculation from within the AnalysisObj
 * New function :py:class:`~bifacial_radiance.RadianceObj.calculatePerformance1axis` to call CEC performance calculation for every entry of a trackerdict
 * :py:class:`~bifacial_radiance.AnalysisObj` has new attribute `power_data` to store CEC performance data
-* :py:class:`~bifacial_radiance.AnalysisObj` has new function `getResults` to bundle and return irradiance scan results in dataframe form. 
+* :py:class:`~bifacial_radiance.AnalysisObj` has new property `results` to bundle and return irradiance scan results in dataframe form. 
 * :py:class:`~bifacial_radiance.AnalysisObj` has new function `groundAnalysis` to run a ground scan under the row-row pitch of the scene to support AgriPV applications. (:pull:`499`)
 * :py:class:`~bifacial_radiance.RadianceObj` has new function `analysis1axisground` to run a ground scan under the row-row pitch of the scene for 1-axis tracked scenes. (:pull:`499`)
 * :py:class:`~bifacial_radiance.RadianceObj` has new intermediate function `readWeatherData` which can take raw metdata time series and metadata dict to generate a :py:class:`~bifacial_radiance.MetObj`. Useful for e.g. bringing in raw NSRDB data. (:pull:`496`)

docs/tutorials/2 - Single Axis Tracking Yearly Simulation.ipynb

@@ -862,8 +862,7 @@
     "\n",
     "<div class=\"alert alert-warning\">\n",
     "Important: If you have torquetubes and y-gap values, make sure you clean your results.\n",
-    "</div>\n",
-    ""
+    "</div>\n"
    ]
   },
   {
@@ -1311,7 +1310,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "res = demo.calculateResults(bifacialityfactor=1.0)"
+    "res = demo.calculatePerformance1axis()"
    ]
   },
   {

docs/tutorials/2 - Single Axis Tracking Yearly Simulation.py

@@ -363,7 +363,7 @@
 # In[21]:
 
 
-res = demo.calculateResults(bifacialityfactor=1.0)
+res = demo.calculatePerformance1axis()
 
 
 # In[22]:

docs/tutorials/3 - Single Axis Tracking Hourly.ipynb

@@ -673,7 +673,7 @@
    "source": [
     "demo.makeOct1axis(singleindex='2021-01-13_0800')\n",
     "results = demo.analysis1axis(singleindex='2021-01-13_0800')\n",
-    "temp = results['2021-01-13_0800']['AnalysisObj'][0].getResults()\n",
+    "temp = results['2021-01-13_0800']['AnalysisObj'][0].results\n",
     "print('\\n\\nHourly bifi gain: {:0.3}'.format(sum(temp['Wm2Back'][0]) / sum(temp['Wm2Front'][0])))"
    ]
   },

docs/tutorials/3 - Single Axis Tracking Hourly.py

@@ -301,7 +301,7 @@
 
 demo.makeOct1axis(singleindex='2021-01-13_0800')
 results = demo.analysis1axis(singleindex='2021-01-13_0800')
-temp = results['2021-01-13_0800']['AnalysisObj'][0].getResults()
+temp = results['2021-01-13_0800']['AnalysisObj'][0].results
 print('\n\nHourly bifi gain: {:0.3}'.format(sum(temp['Wm2Back'][0]) / sum(temp['Wm2Front'][0])))
 
 

docs/tutorials/4 - Debugging with Custom Objects.ipynb

@@ -857,7 +857,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
+   "version": "3.9.13"
   }
  },
  "nbformat": 4,

docs/tutorials/4 - Debugging with Custom Objects.py

@@ -141,15 +141,15 @@
 # </div>
 # 
 
-# In[4]:
+# In[5]:
 
 
 # Some tracking parameters that won't be needed after getting this angle:
 axis_azimuth = 180
 axis_tilt = 0
 limit_angle = 60
 backtrack = True
-tilt = demo.getSingleTimestampTrackerAngle(metdata, timestamp, gcr, axis_azimuth, axis_tilt,limit_angle, backtrack)
+tilt = demo.getSingleTimestampTrackerAngle(timeindex=timestamp, gcr=gcr, azimuth=axis_azimuth, axis_tilt=axis_tilt, limit_angle=limit_angle, backtrack=backtrack)
 
 print ("\n NEW Calculated Tilt: %s " % tilt)
 
@@ -158,7 +158,7 @@
 
 # ## 5. Making the Module & the Scene, Visualize and run Analysis
 
-# In[5]:
+# In[6]:
 
 
 # Making module with all the variables
@@ -185,7 +185,8 @@
 # ***rvu -vf views\front.vp -e .01 -pe 0.02 -vp -2 -12 14.5 tutorial_4.oct****
 # 
 
-# In[6]:
+# In[ ]:
+
 
 
 ## Comment the line below to run rvu from the Jupyter notebook instead of your terminal.
@@ -196,7 +197,7 @@
 
 # And then proceed happily with your analysis:
 
-# In[7]:
+# In[ ]:
 
 
 analysis = bifacial_radiance.AnalysisObj(octfile, demo.name)  # return an analysis object including the scan dimensions for back irradiance
@@ -218,7 +219,7 @@
 # Although we could calculate a bifacial ratio average at this point, this value would be misleading, since some of the sensors generated will fall on the torque tube, the sky, and/or the ground since we have torquetube and ygap in the scene. To calculate the real bifacial ratio average, we must use the clean routines.
 # 
 
-# In[8]:
+# In[ ]:
 
 
 resultFile='results/irr_tutorial_4.csv'
@@ -227,7 +228,7 @@
 results_loaded
 
 
-# In[9]:
+# In[ ]:
 
 
 print("Looking at only 1 sensor in the middle -- position 100 out of the 200 sensors sampled:")
@@ -238,28 +239,27 @@
 # 
 # This might take some time in the current version. 
 
-# In[10]:
+# In[ ]:
 
 
 # Cleaning Results:
 # remove invalid materials and sets the irradiance values to NaN
 clean_results = bifacial_radiance.load.cleanResult(results_loaded)  
 
 
-# In[11]:
+# In[ ]:
 
 
 print("Sampling the same location as before to see what the results are now:")
 clean_results.loc[100]
 
 
-# In[12]:
+# In[ ]:
 
 
 print('CORRECT Annual bifacial ratio average:  %0.3f' %( clean_results['Wm2Back'].sum() / clean_results['Wm2Front'].sum() ))
 
-print ("\n(If we had not done the cleaning routine, the bifacial ratio would have been ", \
-      "calculated to %0.3f  <-- THIS VALUE IS WRONG)" %( sum(analysis.Wm2Back) / sum(analysis.Wm2Front) )) 
+print ("\n(If we had not done the cleaning routine, the bifacial ratio would have been ",       "calculated to %0.3f  <-- THIS VALUE IS WRONG)" %( sum(analysis.Wm2Back) / sum(analysis.Wm2Front) )) 
 
 
 # <a id='step7'></a>
@@ -275,7 +275,7 @@
 # Its sides are going to be 0.5x0.5x0.5 m 
 # and We are going to leave its bottom surface coincident with the plane z=0, but going to center on X and Y.
 
-# In[13]:
+# In[ ]:
 
 
 name='MyMarker'
@@ -289,7 +289,7 @@
 # 
 # I am passing a rotation 0 because xform has to have something (I think) otherwise it gets confused.
 
-# In[14]:
+# In[ ]:
 
 
 demo.appendtoScene(scene.radfiles, customObject, '!xform -rz 0')
@@ -301,7 +301,8 @@
 # 
 # At this point you should be able to go into a command window (cmd.exe) and check the geometry, and the marker should be there.  
 
-# In[15]:
+# In[ ]:
+
 
 
 ## Comment the line below to run rvu from the Jupyter notebook instead of your terminal.

docs/tutorials/5 - Bifacial Carports and Canopies.ipynb

@@ -505,7 +505,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
+   "version": "3.9.13"
   }
  },
  "nbformat": 4,