From 2139d66d7b3cf7055696b269a8f06df46637354c Mon Sep 17 00:00:00 2001
From: Sam Yates <halfflat@gmail.com>
Date: Thu, 20 Oct 2016 12:35:47 +0200
Subject: [PATCH] Address comments on PR#33
* Expand comments, function documentation in Julia script.
* Use '#' for top level headers in `README.md`
---
scripts/PassiveCable.jl | 55 ++++++++++++++++++++++++++++++++++-------
scripts/README.md | 9 +++----
2 files changed, 49 insertions(+), 15 deletions(-)
diff --git a/scripts/PassiveCable.jl b/scripts/PassiveCable.jl
index 7c50a645..76450490 100644
--- a/scripts/PassiveCable.jl
+++ b/scripts/PassiveCable.jl
@@ -12,7 +12,12 @@ export cable_normalize, cable, rallpack1
# ∂g/∂x (0, t) = 1
# ∂g/∂x (L, t) = 0
#
-# (This implementation converges slowly for small t)
+# Parameters:
+# x, t, L: as described above
+# tol: absolute error tolerance in result
+#
+# Return:
+# g(x, t)
function cable_normalized(x, t, L; tol=1e-8)
if t<=0
@@ -32,7 +37,7 @@ function cable_normalized(x, t, L; tol=1e-8)
break
end
end
- return ginf+sum
+ return ginf+sum
end
end
@@ -56,18 +61,37 @@ end
#
# L: length of cable
# r: linear axial resistivity
-# g: linear membrane conductance
-# c: linear membrane capacitance.
+# g: linear membrane conductivity
+# c: linear membrane capacitance
# V: membrane reversal potential
-# I: injected current on the left end (x = 0) of the cable.
+# I: injected axial current on the left end (x = 0) of the cable.
+#
+# Note that r, g and c are specific 1-d quantities that differ from
+# the cable resistivity r_L, specific membrane conductivity ḡ and
+# specific membrane capacitance c_m as used elsewhere. If the
+# cross-sectional area is A and cable circumference is f, then
+# these quantities are related by:
+#
+# r = r_L/A
+# g = ḡ·f
+# c = c_m·f
+#
+# Parameters:
+# x: displacement along cable
+# t: time
+# L, lambda, tau, r, V, I: as described above
+# tol: absolute error tolerance in result
+#
+# Return:
+# computed potential at (x,t) on cable.
function cable(x, t, L, lambda, tau, r, V, I; tol=1e-8)
scale = I*r*lambda;
if scale == 0
- return V
+ return V
else
tol_n = abs(tol/scale)
- return scale*cable_normalized(x/lambda, t/tau, L/lambda, tol=tol_n) + V
+ return scale*cable_normalized(x/lambda, t/tau, L/lambda, tol=tol_n) + V
end
end
@@ -82,8 +106,21 @@ end
# d = 1 µm cable diameter
# EM = -65 mV reversal potential
# I = 0.1 nA injected current
-# L = 1 mm cable length
+# L = 1 mm cable length.
+#
+# (This notation aligns with that used in the Rallpacks paper.)
+#
+# Note that the injected current as described in the Rallpack model
+# is trans-membrane, not axial. Consequently we need to swap the
+# sign on I when passing to the cable function.
+#
+# Parameters:
+# x: displacement along cable [m]
+# t: time [s]
+# tol: absolute tolerance for reported potential.
#
+# Return:
+# computed potential at (x,t) on cable.
function rallpack1(x, t; tol=1e-8)
RA = 1
@@ -101,4 +138,4 @@ function rallpack1(x, t; tol=1e-8)
return cable(x, t, L, lambda, tau, r, EM, -I, tol=tol)
end
-end #module
+end # module PassiveCable
diff --git a/scripts/README.md b/scripts/README.md
index bd8c6111..373f9f13 100644
--- a/scripts/README.md
+++ b/scripts/README.md
@@ -1,5 +1,4 @@
-tsplot
-======
+#tsplot
The `tsplot` script is a wrapper around matplotlib for displaying a collection of
time series plots.
@@ -78,8 +77,7 @@ of the timeseries data.
Use the `-o` or `--output` option to save the plot as an image, instead of
displaying it interactively.
-profstats
-=========
+#profstats
`profstats` collects the profiling data output from multiple MPI ranks and performs
a simple statistical summary.
@@ -92,8 +90,7 @@ are reported instead.
Output is in CSV format.
-PassiveCable.jl
-===============
+#PassiveCable.jl
Compute analytic solutions to the simple passive cylindrical dendrite cable
model with step current injection at one end from t=0.
--
GitLab