merged selected patches from master

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,23 @@
+---
+name: Bug report
+about: Create a report to help us improve
+
+---
+
+**Describe the bug**
+A clear and concise description of what the bug is.
+
+**To Reproduce**
+Steps to reproduce the behavior:
+
+**Expected behavior**
+A clear and concise description of what you expected to happen.
+
+**JSON script:**
+If applicable, add the script you are using.
+
+**EXOSIMS version:**
+ - Release or github commit/branch
+
+**Additional context**
+Add any other context about the problem here.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -0,0 +1,14 @@
+---
+name: Feature request
+about: Suggest an idea for this project
+
+---
+
+**Is your feature request related to a problem? Please describe.**
+A clear and concise description of what the problem is. 
+
+**Describe the solution you'd like**
+A clear and concise description of what you want to happen.
+
+**Additional context**
+Add any other context or screenshots about the feature request here.

.gitignore

@@ -80,6 +80,7 @@ EXOCATXLS.py*
 ToyCat1.py*
 de432s.bsp
 fitting_parameters.h5
+*.json
 *.comp
 *.so
 *.acomp
@@ -94,3 +95,4 @@ statsFun_C
 *.fits
 *.csv
 *.fZmax
+*.starkfZ

EXOSIMS/Prototypes/SurveySimulation.py

@@ -831,7 +831,11 @@ def observation_detection(self, sInd, intTime, mode):
             self.vprint(log_FA)
 
         #Schedule Target Revisit
+<<<<<<< HEAD
         self.scheduleRevisit(sInd,smin,det,pInds)
+=======
+        self.scheduleRevisit(sInd, smin, det, pInds)
+>>>>>>> master
 
         return detected.astype(int), fZ, systemParams, SNR, FA
 
@@ -848,7 +852,10 @@ def scheduleRevisit(self,sInd,smin,det,pInds):
         TK = self.TimeKeeping
         TL = self.TargetList
         SU = self.SimulatedUniverse
+<<<<<<< HEAD
 
+=======
+>>>>>>> master
         # in both cases (detection or false alarm), schedule a revisit 
         # based on minimum separation
         Ms = TL.MsTrue[sInd]

EXOSIMS/Prototypes/TargetList.py

@@ -84,10 +84,20 @@ def __init__(self, missionStart=60634, staticStars=True,
         assert isinstance(keepStarCatalog, bool), "keepStarCatalog must be a boolean."
         assert isinstance(fillPhotometry, bool), "fillPhotometry must be a boolean."
         assert isinstance(explainFiltering, bool), "explainFiltering must be a boolean."
+        assert isinstance(filterBinaries, bool), "filterBinaries must be a boolean."
         self.staticStars = bool(staticStars)
         self.keepStarCatalog = bool(keepStarCatalog)
         self.fillPhotometry = bool(fillPhotometry)
         self.explainFiltering = bool(explainFiltering)
+        self.filterBinaries = bool(filterBinaries)
+
+        # check if KnownRVPlanetsTargetList is using KnownRVPlanets
+        if specs['modules']['TargetList'] == 'KnownRVPlanetsTargetList':
+            assert specs['modules']['PlanetPopulation'] == 'KnownRVPlanets', \
+            'KnownRVPlanetsTargetList must use KnownRVPlanets'
+        else:
+            assert specs['modules']['PlanetPopulation'] != 'KnownRVPlanets', \
+            'This TargetList cannot use KnownRVPlanets'
 
         # check if KnownRVPlanetsTargetList is using KnownRVPlanets
         if specs['modules']['TargetList'] == 'KnownRVPlanetsTargetList':
@@ -346,9 +356,10 @@ def filter_target_list(self, **specs):
         """
 
         # filter out binary stars
-        self.binary_filter()
-        if self.explainFiltering:
-            print("%d targets remain after binary filter."%self.nStars)
+        if self.filterBinaries:
+            self.binary_filter()
+            if self.explainFiltering:
+                print("%d targets remain after binary filter."%self.nStars)
 
         # filter out systems with planets within the IWA
         self.outside_IWA_filter()

EXOSIMS/SurveySimulation/linearJScheduler.py

@@ -2,6 +2,8 @@
 import astropy.units as u
 import numpy as np
 import itertools
+import astropy.constants as const
+
 
 class linearJScheduler(SurveySimulation):
     """linearJScheduler 
@@ -18,7 +20,7 @@ class linearJScheduler(SurveySimulation):
     
     """
 
-    def __init__(self, coeffs=[1,1,2,1], **specs):
+    def __init__(self, coeffs=[1,1,2,1], revisit_wait=91.25*u.d, **specs):
 
         SurveySimulation.__init__(self, **specs)
 
@@ -32,6 +34,9 @@ def __init__(self, coeffs=[1,1,2,1], **specs):
 
         self.coeffs = coeffs
 
+        self.revisit_wait = revisit_wait
+        self.no_dets = np.ones(self.TargetList.nStars, dtype=bool)
+
     def choose_next_target(self, old_sInd, sInds, slewTimes, intTimes):
         """Choose next target based on truncated depth first search 
         of linear cost function.
@@ -114,3 +119,80 @@ def choose_next_target(self, old_sInd, sInds, slewTimes, intTimes):
         sInd = sInds[int(np.floor(tmp/float(nStars)))]
 
         return sInd, None
+
+    def revisitFilter(self, sInds, tmpCurrentTimeNorm):
+        """Helper method for Overloading Revisit Filtering
+
+        Args:
+            sInds - indices of stars still in observation list
+            tmpCurrentTimeNorm (MJD) - the simulation time after overhead was added in MJD form
+        Returns:
+            sInds - indices of stars still in observation list
+        """
+        tovisit = np.zeros(self.TargetList.nStars, dtype=bool)#tovisit is a boolean array containing the 
+        if len(sInds) > 0:#so long as there is at least 1 star left in sInds
+            tovisit[sInds] = ((self.starVisits[sInds] == min(self.starVisits[sInds])) \
+                    & (self.starVisits[sInds] < self.nVisitsMax))# Checks that no star has exceeded the number of revisits
+            if self.starRevisit.size != 0:#There is at least one revisit planned in starRevisit
+                dt_rev = self.starRevisit[:,1]*u.day - tmpCurrentTimeNorm#absolute temporal spacing between revisit and now.
+
+                #return indices of all revisits within a threshold dt_max of revisit day and indices of all revisits with no detections past the revisit time
+                ind_rev = [int(x) for x in self.starRevisit[np.abs(dt_rev) < self.dt_max, 0] if (x in sInds and self.no_dets[int(x)] == False)]
+                ind_rev2 = [int(x) for x in self.starRevisit[dt_rev < 0*u.d, 0] if (x in sInds and self.no_dets[int(x)] == True)]
+                tovisit[ind_rev] = (self.starVisits[ind_rev] < self.nVisitsMax)#IF duplicates exist in ind_rev, the second occurence takes priority
+                tovisit[ind_rev2] = (self.starVisits[ind_rev2] < self.nVisitsMax)
+            sInds = np.where(tovisit)[0]
+
+        return sInds
+
+    def scheduleRevisit(self, sInd, smin, det, pInds):
+        """A Helper Method for scheduling revisits after observation detection
+        Args:
+            sInd - sInd of the star just detected
+            smin - minimum separation of the planet to star of planet just detected
+            det - 
+            pInds - Indices of planets around target star
+        Return:
+            updates self.starRevisit attribute
+        """
+        TK = self.TimeKeeping
+        TL = self.TargetList
+        SU = self.SimulatedUniverse
+        # in both cases (detection or false alarm), schedule a revisit 
+        # based on minimum separation
+        Ms = TL.MsTrue[sInd]
+        if smin is not None and smin is not np.nan: #smin is None if no planet was detected
+            sp = smin
+            if np.any(det):
+                pInd_smin = pInds[det][np.argmin(SU.s[pInds[det]])]
+                Mp = SU.Mp[pInd_smin]
+            else:
+                Mp = SU.Mp.mean()
+            mu = const.G*(Mp + Ms)
+            T = 2.*np.pi*np.sqrt(sp**3/mu)
+            t_rev = TK.currentTimeNorm + T/2.
+        # otherwise, revisit based on average of population semi-major axis and mass
+        else:
+            sp = SU.s.mean()
+            Mp = SU.Mp.mean()
+            mu = const.G*(Mp + Ms)
+            T = 2.*np.pi*np.sqrt(sp**3/mu)
+            t_rev = TK.currentTimeNorm + 0.75*T
+        # if no detections then schedule revisit based off of revisit_weight
+        if not np.any(det):
+            t_rev = TK.currentTimeNorm + self.revisit_wait
+            self.no_dets[sInd] = True
+        else:
+            self.no_dets[sInd] = False
+
+        # finally, populate the revisit list (NOTE: sInd becomes a float)
+        revisit = np.array([sInd, t_rev.to('day').value])
+        if self.starRevisit.size == 0:#If starRevisit has nothing in it
+            self.starRevisit = np.array([revisit])#initialize sterRevisit
+        else:
+            revInd = np.where(self.starRevisit[:,0] == sInd)[0]#indices of the first column of the starRevisit list containing sInd 
+            if revInd.size == 0:
+                self.starRevisit = np.vstack((self.starRevisit, revisit))
+            else:
+                self.starRevisit[revInd,1] = revisit[1]#over
+