Added some tuning parameters, trying out a potential speedup

rapidtide/data/examples/src/testfmri

@@ -7,17 +7,17 @@ rapidtide \
     --simcalcrange 50 -1 \
     --outputlevel max \
     sub-RAPIDTIDETEST.nii.gz \
-    ../dst/sub-RAPIDTIDETEST_0deriv
+    ../dst/sub-RAPIDTIDETEST
 
 rapidtide \
     --spatialfilt 2 \
     --nprocs -1 \
     --passes 3 \
     --simcalcrange 50 -1 \
+    --padtype constant \
     --outputlevel max \
-    --glmderivs 1 \
     sub-RAPIDTIDETEST.nii.gz \
-    ../dst/sub-RAPIDTIDETEST_1deriv
+    ../dst/sub-RAPIDTIDETEST_constantpad
 
 #rapidtide \
 #    --spatialfilt 2 \

rapidtide/helper_classes.py

@@ -162,6 +162,7 @@ def __init__(
         reftc=None,
         reftcstart=0.0,
         detrendorder=1,
+        filterinputdata=True,
         debug=False,
     ):
         self.Fs = Fs
@@ -172,25 +173,41 @@ def __init__(
         self.negativegradient = negativegradient
         self.reftc = reftc
         self.detrendorder = detrendorder
+        self.filterinputdata = filterinputdata
         self.debug = debug
         if self.reftc is not None:
             self.setreftc(self.reftc)
             self.reftcstart = reftcstart
 
     def preptc(self, thetc, isreftc=False):
         # prepare timecourse by filtering, normalizing, detrending, and applying a window function
-        if isreftc or (not self.negativegradient):
+        if isreftc:
             thenormtc = tide_math.corrnormalize(
                 self.ncprefilter.apply(self.Fs, thetc),
                 detrendorder=self.detrendorder,
                 windowfunc=self.windowfunc,
             )
         else:
-            thenormtc = tide_math.corrnormalize(
-                -np.gradient(self.ncprefilter.apply(self.Fs, thetc)),
-                detrendorder=self.detrendorder,
-                windowfunc=self.windowfunc,
-            )
+            if self.negativegradient:
+                thenormtc = tide_math.corrnormalize(
+                    -np.gradient(self.ncprefilter.apply(self.Fs, thetc)),
+                    detrendorder=self.detrendorder,
+                    windowfunc=self.windowfunc,
+                )
+            else:
+                if self.filterinputdata:
+                    thenormtc = tide_math.corrnormalize(
+                        self.ncprefilter.apply(self.Fs, thetc),
+                        detrendorder=self.detrendorder,
+                        windowfunc=self.windowfunc,
+                    )
+                else:
+                    thenormtc = tide_math.corrnormalize(
+                        thetc,
+                        detrendorder=self.detrendorder,
+                        windowfunc=self.windowfunc,
+                    )
+
         return thenormtc
 
     def trim(self, vector):

rapidtide/workflows/parser_funcs.py

@@ -137,6 +137,7 @@ def is_valid_tag(parser, arg):
 
 DEFAULT_FILTER_ORDER = 6
 DEFAULT_PAD_SECONDS = 30.0
+DEFAULT_PREFILTERPADTYPE = "reflect"
 DEFAULT_PERMUTATIONMETHOD = "shuffle"
 DEFAULT_NORMTYPE = "stddev"
 DEFAULT_FILTERBAND = "lfo"
@@ -395,11 +396,24 @@ def addfilteropts(
             metavar="SECONDS",
             help=(
                 "The number of seconds of padding to add to each end of a "
-                "filtered timecourse "
+                "timecourse to be filtered "
                 f"to reduce end effects.  Default is {DEFAULT_PAD_SECONDS}."
             ),
             default=DEFAULT_PAD_SECONDS,
         )
+        filt_opts.add_argument(
+            "--padtype",
+            dest="ncfiltpadtype",
+            action="store",
+            type=str,
+            choices=["reflect", "zero", "constant"],
+            help=(
+                f"The type of padding at each end of a "
+                "timecourse to be filtered "
+                f'to reduce end effects.  Default is "{DEFAULT_PREFILTERPADTYPE}".'
+            ),
+            default=DEFAULT_PREFILTERPADTYPE,
+        )
 
 
 def postprocesssamplerateopts(args, debug=False):
@@ -428,6 +442,10 @@ def postprocessfilteropts(args, debug=False):
         thepadseconds = args.padseconds
     except AttributeError:
         args.padseconds = DEFAULT_PAD_SECONDS
+    try:
+        prefilterpadtype = args.prefilterpadtype
+    except AttributeError:
+        args.prefilterpadtype = DEFAULT_PREFILTERPADTYPE
 
     # if passvec, or passvec and stopvec, are set, we are going set up an arbpass filter
     args.arbvec = None
@@ -456,13 +474,16 @@ def postprocessfilteropts(args, debug=False):
         theprefilter = tide_filt.NoncausalFilter(
             "arb",
             transferfunc=args.filtertype,
+            padtime=args.padseconds,
+            padtype=args.prefilterpadtype,
         )
         theprefilter.setfreqs(args.arbvec[2], args.arbvec[0], args.arbvec[1], args.arbvec[3])
     else:
         theprefilter = tide_filt.NoncausalFilter(
             args.filterband,
             transferfunc=args.filtertype,
             padtime=args.padseconds,
+            padtype=args.prefilterpadtype,
         )
 
     # set the butterworth order

rapidtide/workflows/rapidtide.py

@@ -1470,6 +1470,7 @@ def rapidtide_main(argparsingfunc):
         ncprefilter=theprefilter,
         negativegradient=optiondict["negativegradient"],
         detrendorder=optiondict["detrendorder"],
+        filterinputdata=optiondict["filterinputdata"],
         windowfunc=optiondict["windowfunc"],
         corrweighting=optiondict["corrweighting"],
         corrpadding=optiondict["corrpadding"],
@@ -1499,6 +1500,7 @@ def rapidtide_main(argparsingfunc):
         ncprefilter=theprefilter,
         negativegradient=optiondict["negativegradient"],
         detrendorder=optiondict["detrendorder"],
+        filterinputdata=optiondict["filterinputdata"],
         windowfunc=optiondict["windowfunc"],
         madnorm=False,
         lagmininpts=lagmininpts,

rapidtide/workflows/rapidtide_parser.py

@@ -1514,6 +1514,15 @@ def _get_parser():
         ),
         default=False,
     )
+    experimental.add_argument(
+        "--donotfilterinputdata",
+        dest="filterinputdata",
+        action="store_false",
+        help=(
+            "Do not filter input data prior to similarity calculation.  May make processing faster."
+        ),
+        default=True,
+    )
     experimental.add_argument(
         "--dispersioncalc",
         dest="dodispersioncalc",