I am trying to get the values intercept of two lines, t70_bot_inf and t70_top_0, and would like to mark it with a horizontal and vertical line. Are there any modules with could help me with this? I have tried Shapley which was unfortunately unsuccessful. Cheers!
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
#global values
sigma_ct_inf = 0
sigma_ct_0 = 0
sigma_c_inf = 30
sigma_c_0 = 12
beta = 0.8
#values T 70
A = 359000
Wb = 40830202.33
Wt = 72079066.94
Mmin = 701.17
Mmax = 978.52
#Magnel Diagram
e = np.arange(-200, 1001)
t70_top_0 = pd.Series({'y': ((e - (Wt / A)) / ((Mmin * 10 ** 6) + sigma_ct_0 * Wt)) * 10 ** 6})
t70_bot_0 = pd.Series({'y': ((e + (Wb / A)) / ((Mmin * 10 ** 6) + sigma_c_0 * Wb)) * 10 ** 6})
t70_top_inf = pd.Series({'y': (((e - (Wt / A)) * beta) / ((Mmax * 10 ** 6) - sigma_c_inf * Wt)) * 10 ** 6})
t70_bot_inf = pd.Series({'y': (((e + (Wb / A)) * beta) / ((Mmax * 10 ** 6) - sigma_ct_inf * Wb)) * 10 ** 6})
bot = np.min([t70_bot_0['y'], t70_bot_inf['y']], axis=0)
top = np.max([t70_top_0['y'], t70_top_inf['y']], axis=0)
fig, ax = plt.subplots()
ax.set_title('Magnel Diagram, T-70')
ax.plot(e, t70_top_0['y'], lw=0.5, label='Top, t = 0')
ax.plot(e, t70_bot_0['y'], lw=0.5, label='Bottom, t = 0')
ax.plot(e, t70_top_inf['y'], lw=0.5, label='Top, t = \u221E')
ax.plot(e, t70_bot_inf['y'], lw=0.5, label='Bottom, t = \u221E')
ax.fill_between(e, bot, top, where=top < bot, color='r', alpha=0.4)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.ylabel('1/P0 [1/MN]')
plt.xlabel('Eccentricity [mm]')
ax.grid()
plt.legend()
plt.show()
Related
I have this script:
strategy("My strategy")
var float start_price = na
var float end_price = na
var float[] start_prices = array.new_float(0)
var float[] end_prices = array.new_float(0)
var float p = na
f(x) => math.round(x / 500) * 500
lo = (high + close) / 2
var i = 0
if bar_index == 1
start_price := f(lo)
end_price := f(start_price * 1.015)
else
if close <= start_price
strategy.entry(str.format("Long {0}",i), strategy.long)
array.push(end_prices, end_price)
array.push(start_prices, end_price)
i := i + 1
start_price := start_price - 500
end_price := f(start_price * 1.015)
for j = 0 to (array.size(end_prices) == 0 ? na : array.size(end_prices) - 1)
p := array.get(end_prices, j)
if close >= p
strategy.exit(str.format("Long {0}",j), limit=end_price)
I want to console/debug/display the values in start_prices array
But I can't figure out for the life of me how to do that, there's no console.log or anything like that. I'm a somewhat competent python programmer, but I always use the print()... Anyway, how do people debug in this language?
You can use the tostring() function (str.tostring() in v5) to generate a string of your array. You can then output it into a label or table.
eg.
start_prices_string = str.tostring(start_prices)
debug = label.new(x = bar_index, y = close, style = label.style_label_left, text = start_prices_string)
label.delete(debug[1])
I found 2 scripts in tradingview and added them to my script, however, it didn't work. I lost a lot of time. Can someone help me convert them to version 4? Thank you. Have a nice day!!!
//#version=2
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 09/03/2018
// Linear Regression Intercept is one of the indicators calculated by using the
// Linear Regression technique. Linear regression indicates the value of the Y
// (generally the price) when the value of X (the time series) is 0. Linear
// Regression Intercept is used along with the Linear Regression Slope to create
// the Linear Regression Line. The Linear Regression Intercept along with the Slope
// creates the Regression line.
////////////////////////////////////////////////////////////
study(title="Line Regression Intercept", overlay = true)
Length = input(14, minval=1)
xSeria = input(title="Source", type=source, defval=close)
xX = Length * (Length - 1) * 0.5
xDivisor = xX * xX - Length * Length * (Length - 1) * (2 * Length - 1) / 6
xXY = 0
for i = 0 to Length-1
xXY := xXY + (i * xSeria[i])
xSlope = (Length * xXY - xX * sum(xSeria, Length)) / xDivisor
xLRI = (sum(xSeria, Length) - xSlope * xX) / Length
plot(xLRI, color=blue, title="LRI")
//Author - Rajandran R
//www.marketcalls.in
study("Supertrend V1.0 - Buy or Sell Signal", overlay = true)
Factor=input(3, minval=1,maxval = 100)
Pd=input(7, minval=1,maxval = 100)
Up=hl2-(Factor*atr(Pd))
Dn=hl2+(Factor*atr(Pd))
TrendUp=close[1]>TrendUp[1]? max(Up,TrendUp[1]) : Up
TrendDown=close[1]<TrendDown[1]? min(Dn,TrendDown[1]) : Dn
Trend = close > TrendDown[1] ? 1: close< TrendUp[1]? -1: nz(Trend[1],1)
Tsl = Trend==1? TrendUp: TrendDown
linecolor = Trend == 1 ? green : red
plot(Tsl, color = linecolor , style = line , linewidth = 2,title = "SuperTrend")
plotshape(cross(close,Tsl) and close>Tsl , "Up Arrow", shape.triangleup,location.belowbar,green,0,0)
plotshape(cross(Tsl,close) and close<Tsl , "Down Arrow", shape.triangledown , location.abovebar, red,0,0)
//plot(Trend==1 and Trend[1]==-1,color = linecolor, style = circles, linewidth = 3,title="Trend")
plotarrow(Trend == 1 and Trend[1] == -1 ? Trend : na, title="Up Entry Arrow", colorup=lime, maxheight=60, minheight=50, transp=0)
plotarrow(Trend == -1 and Trend[1] == 1 ? Trend : na, title="Down Entry Arrow", colordown=red, maxheight=60, minheight=50, transp=0)
//#version=4
////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 09/03/2018
// Linear Regression Intercept is one of the indicators calculated by using the
// Linear Regression technique. Linear regression indicates the value of the Y
// (generally the price) when the value of X (the time series) is 0. Linear
// Regression Intercept is used along with the Linear Regression Slope to create
// the Linear Regression Line. The Linear Regression Intercept along with the Slope
// creates the Regression line.
////////////////////////////////////////////////////////////
study(title="Line Regression Intercept", overlay=true)
Length = input(14, minval=1)
xSeria = input(title="Source", type=input.source, defval=close)
xX = Length * (Length - 1) * 0.5
xDivisor = xX * xX - Length * Length * (Length - 1) * (2 * Length - 1) / 6
xXY = 0.
for i = 0 to Length - 1 by 1
xXY := xXY + i * xSeria[i]
xXY
xSlope = (Length * xXY - xX * sum(xSeria, Length)) / xDivisor
xLRI = (sum(xSeria, Length) - xSlope * xX) / Length
plot(xLRI, color=color.blue, title="LRI")
//#version=4
//Author - Rajandran R
//www.marketcalls.in
study("Supertrend V1.0 - Buy or Sell Signal", overlay=true)
Factor = input(3, minval=1, maxval=100)
Pd = input(7, minval=1, maxval=100)
Up = hl2 - Factor * atr(Pd)
Dn = hl2 + Factor * atr(Pd)
TrendUp = Up
TrendUp := close[1] > TrendUp[1] ? max(Up, TrendUp[1]) : Up
TrendDown = Dn
TrendDown := close[1] < TrendDown[1] ? min(Dn, TrendDown[1]) : Dn
Trend = int(na)
Trend := close > TrendDown[1] ? 1 : close < TrendUp[1] ? -1 : nz(Trend[1], 1)
Tsl = Trend == 1 ? TrendUp : TrendDown
linecolor = Trend == 1 ? color.green : color.red
plot(Tsl, color=linecolor, style=plot.style_line, linewidth=2, title="SuperTrend")
plotshape(cross(close, Tsl) and close > Tsl, "Up Arrow", shape.triangleup, location.belowbar, color.green, 0, 0)
plotshape(cross(Tsl, close) and close < Tsl, "Down Arrow", shape.triangledown, location.abovebar, color.red, 0, 0)
//plot(Trend==1 and Trend[1]==-1,color = linecolor, style = circles, linewidth = 3,title="Trend")
plotarrow(Trend == 1 and Trend[1] == -1 ? Trend : na, title="Up Entry Arrow", colorup=color.lime, maxheight=60, minheight=50, transp=0)
plotarrow(Trend == -1 and Trend[1] == 1 ? Trend : na, title="Down Entry Arrow", colordown=color.red, maxheight=60, minheight=50, transp=0)
I'm using faceting heatmap on a spatial field which then returns a 2d array like this
"counts_ints2D",
[
null,
null,
null,
null,
[
0,
8,
4,
0,
0,
0,
0,
0,
0,
...
I want to locate those cluster on the map but the problem is that I don't know how to convert that 2d array in geo coordinates.
There's absolutely no documentation out there showing what to do with those integer.
Can somebody give some guidance ?
Going with the data you gave for Glasgow, and using the formula given in the comments, lets explore the coordinates in a python repl:
# setup
>>> minX = -180
>>> maxX = 180
>>> minY = -53.4375
>>> maxY = 74.53125
>>> columns = 256
>>> rows = 91
# calculate widths
>>> bucket_width = (maxX - minX) / columns
>>> bucket_width
1.40625
>>> bucket_height = (maxY - minY) / rows
>>> bucket_height
1.40625
# calculate area for bucket in heatmap facet for x = 124, y = 13
# point in lower left coordinate
>>> lower_left = {
... 'lat': maxY - (13 + 1) * bucket_height,
... 'lon': minX + 124 * bucket_width,
... }
>>> lower_left
{'lat': 54.84375, 'lon': -5.625}
# point in upper right
>>> upper_right = {
... 'lat': maxY - (13 + 1) * bucket_height + bucket_height,
... 'lon': minX + 124 * bucket_width + bucket_width,
... }
>>> upper_right
{'lat': 56.25, 'lon': -4.21875}
Let's graph these points on a map, courtesy of open street map. We generate a small CSV snippet we can import on umap (select the up arrow, choose 'csv' as the type and enter content into the text box). To our coordinates to show:
>>> bbox = [
... "lat,lon,description",
... str(lower_left['lat']) + "," + str(lower_left['lon']) + ",ll",
... str(upper_right['lat']) + "," + str(lower_left['lon']) + ",ul",
... str(upper_right['lat']) + "," + str(upper_right['lon']) + ",uu",
... str(lower_left['lat']) + "," + str(upper_right['lon']) + ",lu",
... ]
>>> print("\n".join(bbox))
lat,lon,description
54.84375,-5.625,ll
56.25,-5.625,ul
56.25,-4.21875,uu
54.84375,-4.21875,lu
After pasting these points into the import box creating the layer, we get this map:
Map based on Open Street Map data through uMap. This area encloses Glasgow as you expected.
Here's some code that takes 180th meridian (date line) wrapping into account:
$columns = $heatmap['columns'];
$rows = $heatmap['rows'];
$minX = $heatmap['minX'];
$maxX = $heatmap['maxX'];
$minY = $heatmap['minY'];
$maxY = $heatmap['maxY'];
$counts = $heatmap['counts_ints2D'];
// If our min longitude is greater than max longitude, we're crossing
// the 180th meridian (date line).
$crosses_meridian = $minX > $maxX;
// Bucket width needs to be calculated differently when crossing the
// meridian since it wraps.
$bucket_width = $crosses_meridian
? $bucket_width = (360 - abs($maxX - $minX)) / $columns
: $bucket_width = ($maxX - $minX) / $columns;
$bucket_height = ($maxY - $minY) / $rows;
$points = [];
foreach ($counts as $rowIndex => $row) {
if (!$row) continue;
foreach ($row as $columnIndex => $column) {
if (!$column) continue;
$point = []
$point['count'] = $column;
// Put the count in the middle of the bucket (adding a half height and width).
$point['lat'] = $maxY - (($rowIndex + 1) * $bucket_height) + ($bucket_height / 2);
$point['lng'] = $minX + ($columnIndex * $bucket_width) + ($bucket_width / 2);
// We crossed the meridian, so wrap back around to negative.
if ($point['lng'] > 180) {
$point['lng'] = -1 * (180 - ($point['lng'] % 180));
}
$points[] = $point;
}
}
I am writing a simple c 4x4 matrix math library and wanted some feedback, especially from people with opengl experience.
Typically there's two ways to do matrix multiplication. I tested this code and it works, according to results from wolfram alpha but my main concern is that this matrix is in the right order.
My matrix is just an array of 16 doubles.
The code to do the multiplication is below
out->m[0] = ( a->m[0] * b->m[0]) + (a->m[1] * b->m[4]) + (a->m[2] * b->m[8]) + (a->m[3] * b->m[12] );
out->m[4] = ( a->m[4] * b->m[0]) + (a->m[5] * b->m[4]) + (a->m[6] * b->m[8]) + (a->m[7] * b->m[12] );
out->m[8] = ( a->m[8] * b->m[0]) + (a->m[9] * b->m[4]) + (a->m[10] * b->m[8]) + (a->m[11] * b->m[12] );
out->m[12] = ( a->m[12] * b->m[0]) + (a->m[13] * b->m[4]) + (a->m[14] * b->m[8]) + (a->m[15] * b->m[12] );
out->m[1] = ( a->m[0] * b->m[1]) + (a->m[1] * b->m[5]) + (a->m[2] * b->m[9]) + (a->m[3] * b->m[13] );
out->m[5] = ( a->m[4] * b->m[1]) + (a->m[5] * b->m[5]) + (a->m[6] * b->m[9]) + (a->m[7] * b->m[13] );
out->m[9] = ( a->m[8] * b->m[1]) + (a->m[9] * b->m[5]) + (a->m[10] * b->m[9]) + (a->m[11] * b->m[13] );
out->m[13] = ( a->m[12] * b->m[1]) + (a->m[13] * b->m[5]) + (a->m[14] * b->m[9]) + (a->m[15] * b->m[13] );
out->m[2] = ( a->m[0] * b->m[2]) + (a->m[1] * b->m[6]) + (a->m[2] * b->m[10]) + (a->m[3] * b->m[14] );
out->m[6] = ( a->m[4] * b->m[2]) + (a->m[5] * b->m[6]) + (a->m[6] * b->m[10]) + (a->m[7] * b->m[14] );
out->m[10] = ( a->m[8] * b->m[2]) + (a->m[9] * b->m[6]) + (a->m[10] * b->m[10]) + (a->m[11] * b->m[14] );
out->m[14] = ( a->m[12] * b->m[2]) + (a->m[13] * b->m[6]) + (a->m[14] * b->m[10]) + (a->m[15] * b->m[14] );
out->m[3] = ( a->m[0] * b->m[3]) + (a->m[1] * b->m[7]) + (a->m[2] * b->m[11]) + (a->m[3] * b->m[15] );
out->m[7] = ( a->m[4] * b->m[3]) + (a->m[5] * b->m[7]) + (a->m[6] * b->m[11]) + (a->m[7] * b->m[15] );
out->m[11] = ( a->m[8] * b->m[3]) + (a->m[9] * b->m[7]) + (a->m[10] * b->m[11]) + (a->m[11] * b->m[15] );
out->m[15] = ( a->m[12] * b->m[3]) + (a->m[13] * b->m[7]) + (a->m[14] * b->m[11]) + (a->m[15] * b->m[15] );
I wanted to make sure that this will give me the correct results for setting up my transformation matrix.
matrix m = 1,3,4,-1,5,6,7,-1,8,8,8,-1,0,0,0,1
which is arranged in memory like this:
1,3,4,-1
5,6,7,-1
8,8,8,-1
0,0,0,1
which I think is the way opengl lays out it's matrix as 16 numbers.
using my code my answer comes out to be
[ 48.000000 53.000000 57.000000 -9.000000 ]
[ 91.000000 107.000000 118.000000 -19.000000 ]
[ 112.000000 136.000000 152.000000 -25.000000 ]
[ 0.000000 0.000000 0.000000 1.000000 ]
which is the transpose of wolfram alpha's answer.
(48 | 91 | 112 | 0
53 | 107 | 136 | 0
57 | 118 | 152 | 0
-9 | -19 | -25 | 1)
Typically it looks like this, vertex point v model, view, projection matrices
position = projection * view * model * v
I can't say you why your results differ but one help is, if you send the matrix into a GLSL uniform dMat4, you can use the build in transpose functionallity of OpenGL to get the right matrix alignment:
glUniformMatrix4fv( Uniform_Location, 1, GL_TRUE, MatrixPointer );
The third parameter means, if OpenGL should transpose the matrix before setting the uniform.
This question already has an answer here:
MATLAB : What is the mistake in my Ramachandran plot?
(1 answer)
Closed 8 years ago.
I am trying matlab to plot ramachandran plot, without using built in command. I have succeeded too. Now I wanted to spot the GLYCINEs alone in the scatter array. Any ideas how to do this? (link to 1UBQ.pdb file : http://www.rcsb.org/pdb/download/downloadFile.do?fileFormat=pdb&compression=NO&structureId=1UBQ)
% Program to plot Ramanchandran plot of Ubiquitin
close all; clear ; clc; % close all figure windows, clear variables, clear screen
pdb1 ='/home/devanandt/Documents/VMD/1UBQ.pdb';
p=pdbread(pdb1); % read pdb file corresponding to ubiquitin protein
atom={p.Model.Atom.AtomName};
n_i=find(strcmp(atom,'N')); % Find indices of atoms
ca_i=find(strcmp(atom,'CA'));
c_i=find(strcmp(atom,'C'));
X = [p.Model.Atom.X];
Y = [p.Model.Atom.Y];
Z = [p.Model.Atom.Z];
X_n = X(n_i(2:end)); % X Y Z coordinates of atoms
Y_n = Y(n_i(2:end));
Z_n = Z(n_i(2:end));
X_ca = X(ca_i(2:end));
Y_ca = Y(ca_i(2:end));
Z_ca = Z(ca_i(2:end));
X_c = X(c_i(2:end));
Y_c = Y(c_i(2:end));
Z_c = Z(c_i(2:end));
X_c_ = X(c_i(1:end-1)); % the n-1 th C (C of cabonyl)
Y_c_ = Y(c_i(1:end-1));
Z_c_ = Z(c_i(1:end-1));
V_c_ = [X_c_' Y_c_' Z_c_'];
V_n = [X_n' Y_n' Z_n'];
V_ca = [X_ca' Y_ca' Z_ca'];
V_c = [X_c' Y_c' Z_c'];
V_ab = V_n - V_c_;
V_bc = V_ca - V_n;
V_cd = V_c - V_ca;
phi=0;
for k=1:numel(X_c)
n1=cross(V_ab(k,:),V_bc(k,:))/norm(cross(V_ab(k,:),V_bc(k,:)));
n2=cross(V_bc(k,:),V_cd(k,:))/norm(cross(V_bc(k,:),V_cd(k,:)));
x=dot(n1,n2);
m1=cross(n1,(V_bc(k,:)/norm(V_bc(k,:))));
y=dot(m1,n2);
phi=cat(2,phi,-atan2d(y,x));
end
phi=phi(1,2:end);
X_n_ = X(n_i(2:end)); % (n+1) nitrogens
Y_n_ = Y(n_i(2:end));
Z_n_ = Z(n_i(2:end));
X_ca = X(ca_i(1:end-1));
Y_ca = Y(ca_i(1:end-1));
Z_ca = Z(ca_i(1:end-1));
X_n = X(n_i(1:end-1));
Y_n = Y(n_i(1:end-1));
Z_n = Z(n_i(1:end-1));
X_c = X(c_i(1:end-1));
Y_c = Y(c_i(1:end-1));
Z_c = Z(c_i(1:end-1));
V_n_ = [X_n_' Y_n_' Z_n_'];
V_n = [X_n' Y_n' Z_n'];
V_ca = [X_ca' Y_ca' Z_ca'];
V_c = [X_c' Y_c' Z_c'];
V_ab = V_ca - V_n;
V_bc = V_c - V_ca;
V_cd = V_n_ - V_c;
psi=0;
for k=1:numel(X_c)
n1=cross(V_ab(k,:),V_bc(k,:))/norm(cross(V_ab(k,:),V_bc(k,:)));
n2=cross(V_bc(k,:),V_cd(k,:))/norm(cross(V_bc(k,:),V_cd(k,:)));
x=dot(n1,n2);
m1=cross(n1,(V_bc(k,:)/norm(V_bc(k,:))));
y=dot(m1,n2);
psi=cat(2,psi,-atan2d(y,x));
end
psi=psi(1,2:end);
scatter(phi,psi)
box on
axis([-180 180 -180 180])
title('Ramachandran Plot for Ubiquitn Protein','FontSize',16)
xlabel('\Phi^o','FontSize',20)
ylabel('\Psi^o','FontSize',20)
grid
The output is :
EDIT : Is my plot correct? Biopython: How to avoid particular amino acid sequences from a protein so as to plot Ramachandran plot? has an answer which has slightly different plot.
The modified code is as below :
% Program to plot Ramanchandran plot of Ubiquitin with no glycines
close all; clear ; clc; % close all figure windows, clear variables, clear screen
pdb1 ='/home/devanandt/Documents/VMD/1UBQ.pdb';
p=pdbread(pdb1); % read pdb file corresponding to ubiquitin protein
atom={p.Model.Atom.AtomName};
n_i=find(strcmp(atom,'N')); % Find indices of atoms
ca_i=find(strcmp(atom,'CA'));
c_i=find(strcmp(atom,'C'));
X = [p.Model.Atom.X];
Y = [p.Model.Atom.Y];
Z = [p.Model.Atom.Z];
X_n = X(n_i(2:end)); % X Y Z coordinates of atoms
Y_n = Y(n_i(2:end));
Z_n = Z(n_i(2:end));
X_ca = X(ca_i(2:end));
Y_ca = Y(ca_i(2:end));
Z_ca = Z(ca_i(2:end));
X_c = X(c_i(2:end));
Y_c = Y(c_i(2:end));
Z_c = Z(c_i(2:end));
X_c_ = X(c_i(1:end-1)); % the n-1 th C (C of cabonyl)
Y_c_ = Y(c_i(1:end-1));
Z_c_ = Z(c_i(1:end-1));
V_c_ = [X_c_' Y_c_' Z_c_'];
V_n = [X_n' Y_n' Z_n'];
V_ca = [X_ca' Y_ca' Z_ca'];
V_c = [X_c' Y_c' Z_c'];
V_ab = V_n - V_c_;
V_bc = V_ca - V_n;
V_cd = V_c - V_ca;
phi=0;
for k=1:numel(X_c)
n1=cross(V_ab(k,:),V_bc(k,:))/norm(cross(V_ab(k,:),V_bc(k,:)));
n2=cross(V_bc(k,:),V_cd(k,:))/norm(cross(V_bc(k,:),V_cd(k,:)));
x=dot(n1,n2);
m1=cross(n1,(V_bc(k,:)/norm(V_bc(k,:))));
y=dot(m1,n2);
phi=cat(2,phi,-atan2d(y,x));
end
phi=phi(1,2:end);
X_n_ = X(n_i(2:end)); % (n+1) nitrogens
Y_n_ = Y(n_i(2:end));
Z_n_ = Z(n_i(2:end));
X_ca = X(ca_i(1:end-1));
Y_ca = Y(ca_i(1:end-1));
Z_ca = Z(ca_i(1:end-1));
X_n = X(n_i(1:end-1));
Y_n = Y(n_i(1:end-1));
Z_n = Z(n_i(1:end-1));
X_c = X(c_i(1:end-1));
Y_c = Y(c_i(1:end-1));
Z_c = Z(c_i(1:end-1));
V_n_ = [X_n_' Y_n_' Z_n_'];
V_n = [X_n' Y_n' Z_n'];
V_ca = [X_ca' Y_ca' Z_ca'];
V_c = [X_c' Y_c' Z_c'];
V_ab = V_ca - V_n;
V_bc = V_c - V_ca;
V_cd = V_n_ - V_c;
psi=0;
for k=1:numel(X_c)
n1=cross(V_ab(k,:),V_bc(k,:))/norm(cross(V_ab(k,:),V_bc(k,:)));
n2=cross(V_bc(k,:),V_cd(k,:))/norm(cross(V_bc(k,:),V_cd(k,:)));
x=dot(n1,n2);
m1=cross(n1,(V_bc(k,:)/norm(V_bc(k,:))));
y=dot(m1,n2);
psi=cat(2,psi,-atan2d(y,x));
end
psi=psi(1,2:end);
res=strsplit(p.Sequence.ResidueNames,' ');
angle =[phi;psi];
angle(:,find(strcmp(res,'GLY'))-1)=[];
scatter(angle(1,:),angle(2,:))
box on
axis([-180 180 -180 180])
title('Ramachandran Plot for Ubiquitn Protein','FontSize',16)
xlabel('\Phi^o','FontSize',20)
ylabel('\Psi^o','FontSize',20)
grid
which gives output (with no GLY) as below :
I would change this code block to use logical indexing
res=strsplit(p.Sequence.ResidueNames,' ');
angle =[phi;psi];
angle(:,find(strcmp(res,'GLY'))-1)=[];
Instead:
residues = strsplit(p.Sequency.ResidueNames,' ');
glycine = ismember(residues,'GLY');
angle = [phi;psi];
angleNoGLY= angle(:,~glycine);
Doing it this way, if you wanted to highlight glycine (or any other residue) you can easily call it out:
angleGLY = angle(:,glycine);
plot(angleNoGLY(1,:),angleNoGLY(2,:),'ob')
line(angleGLY(1,:),angleGLY(2,:),'Marker','o','Color','r','LineStyle','none')