plot with different order matrix in a function
By : Iurii Purych
Date : August 02 2020, 11:00 AM

I wish this helpful for you I want to plot E(on xaxis) vs f(on yaxis) for different VAlues of T but it show matrix not of same order. How to plot for T = 100,125,150,175,200,...,500 and plot with different color with linewidth thicker than normal say 2. Although i am getting the result when i put single value of T. But i need to know how to plot by for multiple value of T simultaneously and values of E = 0 to 10 are common to all T , You need implicit expansion to find all those values of f in onego. code :
x = 1./(k*T); % ./ for elementwise division
f = 1./ (exp((EEf) .* x.') + 1); % fermi function
% implicitexpansion^ ^fixing dimension order
%
% In <= R2016a, use bsxfun for implicit expansion as follows:
% f = 1./(exp(bsxfun(@times,EEf,x.')) + 1);
%Plotting the results
plot(E,f,'LineWidth',2); %Don't hardcode red color here if you need different colors
hold on;
plot(Ef,0.5,'o','MarkerSize',10,'MarkerFaceColor','b','MarkerEdgeColor','k');
legend("T="+T);
%In older versions without string data type, you can create your legend like this:
%legend(cellstr(strcat('T=',num2str(T.'))));
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Plot output of matrix function
By : H.Bk
Date : March 29 2020, 07:55 AM
will help you This is possible (as I knew it would be) using fplot. But the command has to be fplot('det([x,0;0,1])',[0,1000]) (note the quotes). In fact my ancient (matlab 5) paper manual says:

how to find order of rows in a matrix using order function
By : pooc
Date : March 29 2020, 07:55 AM
Any of those help d<matrix(1:25,5,5) (this is just an example, the numbers will be random essentially) , We can use rank code :
res < t(apply(d, 1, rank))
res
# [,1] [,2] [,3] [,4] [,5]
#[1,] 1 5 4 2 3
#[2,] 4 3 5 1 2
#[3,] 4 5 1 3 2
#[4,] 1 5 2 3 4
#[5,] 4 2 1 5 3

Plot eigenvalues of matrix as function of matrix element
By : 亲热小胖
Date : March 29 2020, 07:55 AM
Hope this helps There is many ways to loop over the values of x you are interested in. You could do an explicit for loop, or you can use a list comprehension. In the example below I compute a 2d array with 3 columns, one for each eigenvalue. The number of rows is the number of x values we are using. code :
import numpy as np
import matplotlib.pyplot as plt
xx = np.linspace(0,100,101) # consider x values 0, 1, .., 100
eigenvalues = np.array([np.sort(np.linalg.eigvals([[40,0,4],[0,0,4],[4,4,x]])) for x in xx])
plt.plot(xx, eigenvalues[:,2],label="largest")
plt.plot(xx, eigenvalues[:,1],label="medium")
plt.plot(xx, eigenvalues[:,0],label="smallest")
plt.legend()
plt.show()

Cannot plot my function : return array(a, dtype, copy=False, order=order) TypeError: float() argument must be a string o
By : Pavel Ivankov
Date : March 29 2020, 07:55 AM
should help you out There are lots of problems with your code, and your understanding of python and array operations. I'm just going to handle the first part of the code (and the error you get), and hopefully you can continue to fix it from there. This should fix the error you're getting and generate a plot: code :
# size = 209772
size = A1.size # I'm assuming that the size of the array is 209772
z = np.arange(1, size+1)/(size+1) # construct an array from [1/209773, 1.0]
# Calculate the x and y arrays
x = np.arctan((A1/A2)*z)
y = z*2*pi
# Plot x and y
plt.plot(x, y)
i=range(1,209773)
def x(i) :
return arctan((A1.item(i)/A2.item(i))*(i/209772))
def y(i) :
return i*2*pi/209772
plot(x, y)

Python seaborn line plot when i plot the x axis values are out of order (even though they are in order in dataframe)
By : user3419406
Date : March 29 2020, 07:55 AM
hop of those help? I guess the issue is that error_mean.index.values is a Series of type str. You need to convert it as int. Check the difference between: code :
import pandas as pd
import seaborn as sns
import matplotlib as plt
df1 = pd.DataFrame([
["10", 0.829440],
["20", 0.833747],
["100", 0.835182],
["40" , 0.837922],
["50", 0.835835]])
sns.lineplot(x=df1[0], y=df1[1])
df1 = pd.DataFrame([
["10", 0.829440],
["20", 0.833747],
["100", 0.835182],
["40" , 0.837922],
["50", 0.835835]])
sns.lineplot(x=(df1[0]).astype(int), y=df1[1])
plt.figure(figsize=(15,5))
sns.lineplot(x=error_mean.index.values.astype(int), y=error_mean['error_rate'])



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