add min_l_logl_sampling to set_accuracy

camb/__init__.py

@@ -7,7 +7,7 @@
 __author__ = "Antony Lewis"
 __contact__ = "antony at cosmologist dot info"
 __url__ = "https://camb.readthedocs.io"
-__version__ = "1.4.1"
+__version__ = "1.4.2"
 
 from . import baseconfig
 

camb/model.py

@@ -236,6 +236,7 @@ class in model.py to add the new parameter in the corresponding location of the
         ("Log_lvalues", c_bool, "Use log spacing for sampling in L"),
         ("use_cl_spline_template", c_bool,
          "When interpolating use a fiducial spectrum shape to define ratio to spline"),
+        ("min_l_logl_sampling", c_int, "Minimum L to use log sampling for L"),
         ("SourceWindows", AllocatableObjectArray(SourceWindow)),
         ("CustomSources", CustomSources)
     ]
@@ -262,7 +263,8 @@ def validate(self):
         """
         return self.f_Validate() != 0
 
-    def set_accuracy(self, AccuracyBoost=1., lSampleBoost=1., lAccuracyBoost=1., DoLateRadTruncation=True):
+    def set_accuracy(self, AccuracyBoost=1., lSampleBoost=1., lAccuracyBoost=1., DoLateRadTruncation=True,
+                     min_l_logl_sampling=None):
         """
         Set parameters determining overall calculation accuracy (large values may give big slow down).
         For finer control you can set individual accuracy parameters by changing CAMBParams.Accuracy
@@ -273,12 +275,16 @@ def set_accuracy(self, AccuracyBoost=1., lSampleBoost=1., lAccuracyBoost=1., DoL
         :param lSampleBoost: increase lSampleBoost to increase density of L sampling for CMB
         :param lAccuracyBoost: increase lAccuracyBoost to increase the maximum L included in the Boltzmann hierarchies
         :param DoLateRadTruncation: If True, use approximation to radiation perturbation evolution at late times
+        :param min_l_logl_sampling: at L>min_l_logl_sampling uses sparser log sampling for L interpolation;
+                                    increase above 5000 for better accuracy at L > 5000
         :return: self
         """
         self.Accuracy.lSampleBoost = lSampleBoost
         self.Accuracy.AccuracyBoost = AccuracyBoost
         self.Accuracy.lAccuracyBoost = lAccuracyBoost
         self.DoLateRadTruncation = DoLateRadTruncation
+        if min_l_logl_sampling:
+            self.min_l_logl_sampling = min_l_logl_sampling
         return self
 
     def set_initial_power_function(self, P_scalar, P_tensor=None, kmin=1e-6, kmax=100., N_min=200, rtol=5e-5,

fortran/config.f90

@@ -3,7 +3,7 @@ module config
     use constants, only: const_twopi
     implicit none
 
-    character(LEN=*), parameter :: version = '1.4.1'
+    character(LEN=*), parameter :: version = '1.4.2'
 
     integer :: FeedbackLevel = 0 !if >0 print out useful information about the model
 

fortran/model.f90

@@ -58,7 +58,7 @@ module model
         !Reionization settings - used if Reion%Reionization=.true.
         logical   :: AccurateReionization = .true.
         !Do you care about pecent level accuracy on EE signal from reionization?
-
+       
         !The following allow separate tweaking (all also affected by AccuracyBoost above)
 
         real(dl) :: TimeStepBoost = 1._dl !sampling timesteps
@@ -182,8 +182,9 @@ module model
         logical :: Do21cm = .false.
         logical :: transfer_21cm_cl = .false.
         logical :: Log_lvalues  = .false. !useful for smooth results at very high L
-        logical :: use_cl_spline_template = .true.
-
+        logical :: use_cl_spline_template = .true.    
+        integer :: min_l_logl_sampling = 5000 ! increase to use linear sampling for longer
+
         Type(TSourceWindowHolder), allocatable :: SourceWindows(:)
 
         Type(TCustomSourceParams) :: CustomSources

fortran/results.f90

@@ -1329,14 +1329,15 @@ subroutine lSamples_init(this, State, lmin, max_l)
     class(lSamples) :: this
     class(CAMBdata), target :: State
     integer, intent(IN) :: lmin,max_l
-    integer lind, lvar, step, top, bot
+    integer lind, lvar, step, top, bot, lmin_log
     integer, allocatable :: ls(:)
     real(dl) AScale
 
     allocate(ls(max_l))
     if (allocated(this%l)) deallocate(this%l)
     this%lmin = lmin
     this%use_spline_template = State%CP%use_cl_spline_template
+    lmin_log = State%CP%min_l_logl_sampling
     associate(Accuracy => State%CP%Accuracy)
         Ascale=State%scale/Accuracy%lSampleBoost
 
@@ -1457,14 +1458,14 @@ subroutine lSamples_init(this, State, lmin, max_l)
                         step=max(nint(50*Ascale),7)
                     end if
                     bot=ls(lind)+step
-                    top=min(5000,max_l)
+                    top=min(lmin_log,max_l)
 
                     do lvar = bot,top,step
                         lind=lind+1
                         ls(lind)=lvar
                     end do
 
-                    if (max_l > 5000) then
+                    if (max_l > lmin_log) then
                         !Should be pretty smooth or tiny out here
                         step=max(nint(400*Ascale),50)
                         lvar = ls(lind)
@@ -1488,7 +1489,7 @@ subroutine lSamples_init(this, State, lmin, max_l)
                     lind=lind+1
                     ls(lind)=max_l
                 end if
-                if (.not. State%flat .and. max_l<=5000) ls(lind-1)=int(max_l+ls(lind-2))/2
+                if (.not. State%flat .and. max_l<=lmin_log) ls(lind-1)=int(max_l+ls(lind-2))/2
                 !Not in flat case so interpolation table is the same when using lower l_max
             end if
         end if