[chronojump] Neuromuscular Profile moving two ec (no longer e,c,e,c)
- From: Xavier de Blas <xaviblas src gnome org>
- To: commits-list gnome org
- Cc:
- Subject: [chronojump] Neuromuscular Profile moving two ec (no longer e,c,e,c)
- Date: Sat, 26 Jul 2014 16:20:56 +0000 (UTC)
commit 832b43c76f03f5d56d32983cbf809add27402c9d
Author: Xavier de Blas <xaviblas gmail com>
Date: Sat Jul 26 18:20:04 2014 +0200
Neuromuscular Profile moving two ec (no longer e,c,e,c)
encoder/neuromuscularProfile.R | 111 ++++++++++++++-------------------------
src/encoder.cs | 20 +-------
src/gui/encoderTreeviews.cs | 42 +---------------
3 files changed, 43 insertions(+), 130 deletions(-)
---
diff --git a/encoder/neuromuscularProfile.R b/encoder/neuromuscularProfile.R
index 21ea856..1eaad80 100644
--- a/encoder/neuromuscularProfile.R
+++ b/encoder/neuromuscularProfile.R
@@ -24,14 +24,15 @@ g = 9.81
#comes with every jump of the three best (in flight time)
#e1, c, e2 are displacements
-neuromuscularProfileJump <- function(l.context, e1, c, e2, mass, smoothingC)
+
+neuromuscularProfileJump <- function(l.context, e1, c, mass, smoothingC)
{
- # /\
- # / \
- # _ c/ \e2
- # \ / \
- # e1\ / \
- # \/ \
+ # /
+ # /
+ # _ c/
+ # \ /
+ # e1\ /
+ # \/
weight <- mass * g
@@ -50,8 +51,8 @@ neuromuscularProfileJump <- function(l.context, e1, c, e2, mass, smoothingC)
e1.maxspeed.pos <- mean(which(abs(e1.speed$y) == max(abs(e1.speed$y))))
e1f <- e1[e1.maxspeed.pos:length(e1)]
-print(c("e max speed.t",e1.maxspeed.pos))
-print(c("length e1",length(e1)))
+ print(c("e max speed.t",e1.maxspeed.pos))
+ print(c("length e1",length(e1)))
#e1f.t duration of e1f (ms)
e1f.t <- length(e1f)
@@ -63,8 +64,8 @@ print(c("length e1",length(e1)))
e1f.force <- mass * (e1f.accel$y + g)
e1f.fmax <- max(e1f.force)
-print(c("e1f.t",e1f.t))
-print(c("mean(e1f.force)",mean(e1f.force)))
+ print(c("e1f.t",e1f.t))
+ print(c("mean(e1f.force)",mean(e1f.force)))
#e1f.rdf.avg
#average force on e1f / e1f.t (s)
@@ -124,8 +125,8 @@ print(c("mean(e1f.force)",mean(e1f.force)))
cl.accel$y <- cl.accel$y * 1000
cl.force <- mass * (cl.accel$y + g)
-print(c("cl.t",cl.t))
-print(c("mean clforce",mean(cl.force)))
+ print(c("cl.t",cl.t))
+ print(c("mean clforce",mean(cl.force)))
cl.rfd.avg <- mean(cl.force) / (cl.t / 1000) / mass
@@ -168,44 +169,7 @@ print(c("mean clforce",mean(cl.force)))
cl.p.avg = cl.p.avg, cl.p.max = cl.p.max
)
- #----------------
- #3.- e2 variables
- #----------------
-
- #get landing
- e2.speed <- getSpeed(e2, smoothingC)
- e2.accel = getAcceleration(e2.speed)
- #speed comes in mm/ms when derivate to accel its mm/ms^2 to convert it to m/s^2 need to *1000 because
it's quadratic
- e2.accel$y <- e2.accel$y * 1000
- e2.force <- mass * (e2.accel$y + g)
- e2.land.pos = max(which(e2.force <= weight))
-
- #e2f (when force is done)
- #is the same as contact phase (land on eccentric)
- e2f <- e2[e2.land.pos:length(e2)]
-
- #e2f.t duration of e2f
- e2f.t <- length(e2f)
-
- #for these variables, we use e2 instead of e2f because there's lot more force on e2f
- #so there's no need to use e2f
- #e2f.f.max = max force on e2f
- e2f.f.max <- max(e2.force)
-
- #e2fFmaxt = duration from land to max force
- e2f.f.max.t <- min(which(e2.force == e2f.f.max)) - e2.land.pos
-
- #e2f.rfd.max = e2f.f.max / e2f.f.max.t (s)
- e2f.rfd.max <- e2f.f.max / (e2f.f.max.t / 1000)
-
- e2.list = list(
- e2f.t = e2f.t,
- e2f.f.max = e2f.f.max,
- e2f.f.max.t = e2f.f.max.t,
- e2f.rfd.max = e2f.rfd.max
- )
-
- return (list(l.context = l.context, e1 = e1.list, c = c.list, e2 = e2.list))
+ return (list(l.context = l.context, e1 = e1.list, c = c.list))
}
#Manuel Lapuente analysis of 6 separate ABKs (e1, c, e2)
@@ -213,12 +177,12 @@ neuromuscularProfileGetData <- function(displacement, curves, mass, smoothingC)
{
weight=mass*g
- #get the maxheight of the 6 jumps
- #sequence is e,c,e,c for every jump. There are 6 jumps. Need the first c of every jump
+ #get the maxheight of the jumps
+ #sequence is e,c for every jump. Need the c of every jump
nums = NULL
heights = NULL
count = 1
- for(i in seq(2,22,length=6)) {
+ for(i in seq(2,length(curves[,1]),by=2)) {
d = displacement[curves[i,1]:curves[i,2]]
speed <- getSpeed(d, smoothingC)
@@ -241,10 +205,13 @@ neuromuscularProfileGetData <- function(displacement, curves, mass, smoothingC)
jumpHeight = (position[length(position)] - position[takeoff]) /10
print(paste("Jump Height =", jumpHeight))
- #store variables
- nums[count] = i
- heights[count] = jumpHeight
- count = count +1
+ if(! is.na(jumpHeight)) {
+ #store variables
+ print(c("Jump accepted count,i,height",count,i,jumpHeight))
+ nums[count] = i
+ heights[count] = jumpHeight
+ count = count +1
+ }
}
}
@@ -267,11 +234,14 @@ neuromuscularProfileGetData <- function(displacement, curves, mass, smoothingC)
npj <- list()
count = 1
for(i in df$nums[bests]) {
- numJump <- ((i-2)/4)+1 #this gets the concentric phase num and calculates which jump is
+ numJump <- i / 2 #this calculates which jump is this concentric phase
+
+ print(c("numJump",numJump,"height",heights[which(df$nums == i)]))
+
l.context <- list(numJump = numJump,
- jumpHeight = heights[numJump],
- start.e1 = curves[(i-1),1], #start of all (start of e1)
- end.e2 = curves[(i+1),2], #end of all (end of e2)
+ jumpHeight = heights[which(df$nums == i)],
+ start.e1 = curves[(i-1),1], #start of e1
+ end.e1 = curves[(i-1),2], #end of e1
start.c = curves[i,1], #start of c
end.c = curves[i,2] #end of c
)
@@ -279,7 +249,6 @@ neuromuscularProfileGetData <- function(displacement, curves, mass, smoothingC)
l.context,
displacement[curves[(i-1),1]:curves[(i-1),2]], #e1
displacement[curves[(i),1]:curves[(i),2]], #c
- displacement[curves[(i+1),1]:curves[(i+1),2]], #e2
mass, smoothingC)
count = count +1
@@ -355,9 +324,9 @@ neuromuscularProfilePlotBars <- function(title, load, explode, drive)
neuromuscularProfilePlotOther <- function(displacement, l.context, mass, smoothingC)
{
#plot
- #curve e1,c,e2 distance,speed,force /time of best jump
- #curve e1,c,e2 force/time (of the three best jumps)
- #to plot e1,c,e2 curves, just sent to paint() the xmin:xmax from start e1 to end of e2
+ #curve e1,c distance,speed,force /time of best jump
+ #curve e1,c force/time (of the three best jumps)
+ #to plot e1,c curves, just sent to paint() the xmin:xmax from start e1 to end of c
minimumForce = 0
maximumForce = 0
@@ -368,7 +337,7 @@ neuromuscularProfilePlotOther <- function(displacement, l.context, mass, smoothi
l.force.max.c.pos = NULL
for(i in 1:3) {
- d = displacement[as.integer(l.context[[i]]$start.e1):as.integer(l.context[[i]]$end.e2)]
+ d = displacement[as.integer(l.context[[i]]$start.e1):as.integer(l.context[[i]]$end.c)]
speed <- getSpeed(d, smoothingC)
accel = getAcceleration(speed)
@@ -429,12 +398,12 @@ neuromuscularProfilePlotOther <- function(displacement, l.context, mass, smoothi
neuromuscularProfileWriteData <- function(npj, outputData1)
{
#values of first, 2nd and 3d jumps
- jump1 <- as.numeric(c(npj[[1]]$e1, npj[[1]]$c, npj[[1]]$e2))
- jump2 <- as.numeric(c(npj[[2]]$e1, npj[[2]]$c, npj[[2]]$e2))
- jump3 <- as.numeric(c(npj[[3]]$e1, npj[[3]]$c, npj[[3]]$e2))
+ jump1 <- as.numeric(c(npj[[1]]$e1, npj[[1]]$c))
+ jump2 <- as.numeric(c(npj[[2]]$e1, npj[[2]]$c))
+ jump3 <- as.numeric(c(npj[[3]]$e1, npj[[3]]$c))
df <- data.frame(rbind(jump1,jump2,jump3))
- colnames(df) <- c(paste("e1.",names(npj[[1]]$e1),sep=""), names(npj[[1]]$c), names(npj[[1]]$e2))
+ colnames(df) <- c(paste("e1.",names(npj[[1]]$e1),sep=""), names(npj[[1]]$c))
rownames(df) <- c(
paste(translate("jump"),npj[[1]]$l.context$numJump),
paste(translate("jump"),npj[[2]]$l.context$numJump),
diff --git a/src/encoder.cs b/src/encoder.cs
index 9792ca8..4c2f97e 100644
--- a/src/encoder.cs
+++ b/src/encoder.cs
@@ -406,11 +406,6 @@ public class EncoderNeuromuscularData
public double cl_p_avg;
public double cl_p_max;
- public int e2f_t;
- public double e2f_f_max;
- public int e2f_f_max_t;
- public double e2f_rfd_max;
-
public EncoderNeuromuscularData () {
}
@@ -420,8 +415,7 @@ public class EncoderNeuromuscularData
int e1_range, int e1_t, double e1_fmax, double e1_rfd_avg, double e1_i,
int ca_range, int cl_t, double cl_rfd_avg, double cl_i,
double cl_f_avg, double cl_vf, double cl_f_max,
- double cl_s_avg, double cl_s_max, double cl_p_avg, double cl_p_max,
- int e2f_t, double e2f_f_max, int e2f_f_max_t, double e2f_rfd_max
+ double cl_s_avg, double cl_s_max, double cl_p_avg, double cl_p_max
)
{
this.n = n;
@@ -441,10 +435,6 @@ public class EncoderNeuromuscularData
this.cl_s_max = cl_s_max;
this.cl_p_avg = cl_p_avg;
this.cl_p_max = cl_p_max;
- this.e2f_t = e2f_t;
- this.e2f_f_max = e2f_f_max;
- this.e2f_f_max_t = e2f_f_max_t;
- this.e2f_rfd_max = e2f_rfd_max;
}
//reading contents file from graph.R
@@ -471,10 +461,6 @@ public class EncoderNeuromuscularData
this.cl_s_max = Convert.ToDouble(cells[14]);
this.cl_p_avg = Convert.ToDouble(cells[15]);
this.cl_p_max = Convert.ToDouble(cells[16]);
- this.e2f_t = Convert.ToInt32(cells[17]);
- this.e2f_f_max = Convert.ToDouble(cells[18]);
- this.e2f_f_max_t = Convert.ToInt32(cells[19]);
- this.e2f_rfd_max = Convert.ToDouble(cells[20]);
}
public string ToCSV() {
@@ -487,9 +473,7 @@ public class EncoderNeuromuscularData
cl_rfd_avg.ToString() + sep + cl_i.ToString() + sep +
cl_f_avg.ToString() + sep + cl_vf.ToString() + sep + cl_f_max.ToString() + sep +
cl_s_avg.ToString() + sep + cl_s_max.ToString() + sep +
- cl_p_avg.ToString() + sep + cl_p_max.ToString() + sep +
- e2f_t.ToString() + sep + e2f_f_max.ToString() + sep +
- e2f_f_max_t.ToString() + sep + e2f_rfd_max;
+ cl_p_avg.ToString() + sep + cl_p_max.ToString();
}
}
diff --git a/src/gui/encoderTreeviews.cs b/src/gui/encoderTreeviews.cs
index 744a95a..70731ad 100644
--- a/src/gui/encoderTreeviews.cs
+++ b/src/gui/encoderTreeviews.cs
@@ -606,11 +606,7 @@ public partial class ChronoJumpWindow
"cl s avg" + "\n (m/s)",
"cl s max" + "\n (m/s)",
"cl p avg" + "\n (W)",
- "cl p max" + "\n (W)",
- "e2f t" + "\n (ms)",
- "e2f f fmax" + "\n (N)",
- "e2f f fmax t" + "\n (ms)",
- "e2f rfd max" + "\n (N/s)"
+ "cl p max" + "\n (W)"
};
private int createTreeViewEncoderAnalyzeNeuromuscular(string contents) {
@@ -710,18 +706,6 @@ public partial class ChronoJumpWindow
case 16:
aColumn.SetCellDataFunc (aCell, new Gtk.TreeCellDataFunc
(Render_cl_p_max));
break;
- case 17:
- aColumn.SetCellDataFunc (aCell, new Gtk.TreeCellDataFunc
(Render_e2f_t));
- break;
- case 18:
- aColumn.SetCellDataFunc (aCell, new Gtk.TreeCellDataFunc
(Render_e2f_f_max));
- break;
- case 19:
- aColumn.SetCellDataFunc (aCell, new Gtk.TreeCellDataFunc
(Render_e2f_f_max_t));
- break;
- case 20:
- aColumn.SetCellDataFunc (aCell, new Gtk.TreeCellDataFunc
(Render_e2f_rfd_max));
- break;
}
treeview_encoder_analyze_curves.AppendColumn (aColumn);
@@ -1083,30 +1067,6 @@ public partial class ChronoJumpWindow
EncoderNeuromuscularData nm = (EncoderNeuromuscularData) model.GetValue (iter, 0);
(cell as Gtk.CellRendererText).Text = nm.cl_p_max.ToString();
}
-
- private void Render_e2f_t (Gtk.TreeViewColumn column, Gtk.CellRenderer cell, Gtk.TreeModel model,
Gtk.TreeIter iter)
- {
- EncoderNeuromuscularData nm = (EncoderNeuromuscularData) model.GetValue (iter, 0);
- (cell as Gtk.CellRendererText).Text = nm.e2f_t.ToString();
- }
-
- private void Render_e2f_f_max (Gtk.TreeViewColumn column, Gtk.CellRenderer cell, Gtk.TreeModel model,
Gtk.TreeIter iter)
- {
- EncoderNeuromuscularData nm = (EncoderNeuromuscularData) model.GetValue (iter, 0);
- (cell as Gtk.CellRendererText).Text = nm.e2f_f_max.ToString();
- }
-
- private void Render_e2f_f_max_t (Gtk.TreeViewColumn column, Gtk.CellRenderer cell, Gtk.TreeModel
model, Gtk.TreeIter iter)
- {
- EncoderNeuromuscularData nm = (EncoderNeuromuscularData) model.GetValue (iter, 0);
- (cell as Gtk.CellRendererText).Text = nm.e2f_f_max_t.ToString();
- }
-
- private void Render_e2f_rfd_max (Gtk.TreeViewColumn column, Gtk.CellRenderer cell, Gtk.TreeModel
model, Gtk.TreeIter iter)
- {
- EncoderNeuromuscularData nm = (EncoderNeuromuscularData) model.GetValue (iter, 0);
- (cell as Gtk.CellRendererText).Text = nm.e2f_rfd_max.ToString();
- }
/* end of rendering neuromuscular cols */
[
Date Prev][
Date Next] [
Thread Prev][
Thread Next]
[
Thread Index]
[
Date Index]
[
Author Index]
