From 60bcdbba6feab9dccf87783d1e65610a2fb11744 Mon Sep 17 00:00:00 2001
From: Tenzin Chan <tenzin_chan@mymail.sutd.edu.sg>
Date: Mon, 13 May 2024 07:08:23 -0700
Subject: [PATCH] Updated to accomodate different learning rates

---
 scripts/blanche_expt.jl | 24 +++++++++++++-----------
 1 file changed, 13 insertions(+), 11 deletions(-)

diff --git a/scripts/blanche_expt.jl b/scripts/blanche_expt.jl
index 6b21071..f168d15 100644
--- a/scripts/blanche_expt.jl
+++ b/scripts/blanche_expt.jl
@@ -17,7 +17,7 @@ function modeltocpu(model)
 end
 
 
-function trainondata(data, maxiter, winsz, batchsize, arraycast)
+function trainondata(data, maxiter, winsz, batchsize, arraycast, lr)
     println("windowing")
     traindata, counts = window(data, winsz)
     bs, n = size(traindata)
@@ -67,7 +67,7 @@ function generatebernoulli(data)
 end
 
 
-function runexperiment(binsz, winszs, maxiter, path, batchsize, arraycast, params, basedir, numsplit, extract_fn)
+function runexperiment(binsz, winszs, maxiter, path, batchsize, arraycast, params, basedir, numsplit, extract_fn, lr)
     for winsz in winszs
         params["winsz"] = winsz
         # Only doing matrix for now
@@ -87,7 +87,7 @@ function runexperiment(binsz, winszs, maxiter, path, batchsize, arraycast, param
             if !isfile(saveloc)
                 println("processing $saveloc")
                 model, ininds, uniqueinput, inspkcnt, counts, outinds, combout, comboutspkcnt, comboutcnt, losses =
-                    trainondata(data_split[i], maxiter, winsz, batchsize, arraycast)
+                    trainondata(data_split[i], maxiter, winsz, batchsize, arraycast, lr)
                 savedata["$i"] = Dict("ininds"=>ininds, "outinds"=>outinds, "input"=>uniqueinput, "output"=>combout, "net"=>model, "inspikecnt"=>inspkcnt, "incount"=>counts, "outspikecnt"=>comboutspkcnt, "outcount"=>comboutcnt, "loss"=>losses)
                 MAT.matwrite(joinpath(cdmdir, "input", "$(DrWatson.savename(params))_$(i).mat"),
                              Dict("inspikecnt"=>inspkcnt, "counts"=>counts))
@@ -99,7 +99,7 @@ function runexperiment(binsz, winszs, maxiter, path, batchsize, arraycast, param
                 println("processing $nullloc")
                 nulldata = generatebernoulli(data_split[i])
                 model, ininds, uniqueinput, inspkcnt, counts, outinds, combout, comboutspkcnt, comboutcnt, losses =
-                    trainondata(nulldata, maxiter, winsz, batchsize, arraycast)
+                    trainondata(nulldata, maxiter, winsz, batchsize, arraycast, lr)
                 savenull["$i"] = Dict("ininds"=>ininds, "outinds"=>outinds, "input"=>uniqueinput, "output"=>combout, "net"=>model, "inspikecnt"=>inspkcnt, "incount"=>counts, "outspikecnt"=>comboutspkcnt, "outcount"=>comboutcnt, "loss"=>losses)
                 MAT.matwrite(joinpath(cdmdir, "null", "$(DrWatson.savename(params))_$(i).mat"),
                              Dict("cells"=>model.n, "spike_counts"=>comboutspkcnt, "counts"=>comboutcnt))
@@ -126,15 +126,17 @@ if abspath(PROGRAM_FILE) == @__FILE__
     binsz = params["binsz"]
 
     # For Blanche's data
-    path = DrWatson.datadir("exp_raw", "pvc3", "crcns_pvc3_cat_recordings", "spont_activity", "spike_data_area18")
-    extract_fn = extract_bin_spikes_blanche
+    #path = DrWatson.datadir("exp_raw", "pvc3", "crcns_pvc3_cat_recordings", "spont_activity", "spike_data_area18")
+    #extract_fn = extract_bin_spikes_blanche
+    #basedir = DrWatson.datadir("exp_pro", "matrix", "blanche", "full")
+    #lr = 0.1
     # For Joost's data
-    #path = DrWatson.datadir("exp_raw", "joost_data", "Long_recordings-stability_MaxEnt_and_CFP", "long_1_spontaneous_activity.jld2")
-    #extract_fn = extract_bin_spikes_joost
+    path = DrWatson.datadir("exp_raw", "joost_data", "Long_recordings-stability_MaxEnt_and_CFP", "long_1_spontaneous_activity.jld2")
+    extract_fn = extract_bin_spikes_joost
+    basedir = DrWatson.datadir("exp_pro", "matrix", "joost_long", "full")
+    lr = 0.01
 
 
-    basedir = DrWatson.datadir("exp_pro", "matrix", "blanche", "full")
-    #basedir = DrWatson.datadir("exp_pro", "matrix", "joost_long", "full")
     maxiter = params["maxiter"]
     numsplit = parse(Int, ARGS[3])
 
@@ -149,6 +151,6 @@ if abspath(PROGRAM_FILE) == @__FILE__
     #model = MEFK.MEF3T(n; array_cast=arraycast)
     println("starting")
 
-    runexperiment(binsz, winszs, maxiter, path, batchsize, arraycast, params, basedir, numsplit, extract_fn)
+    runexperiment(binsz, winszs, maxiter, path, batchsize, arraycast, params, basedir, numsplit, extract_fn, lr)
 end