How to plot a logaritmic graph with given data in Python?

Question

Well, I really didnt know how to ask this properly but here is the question. I have some code which produces data for me. I have 100 Reynolds Number from 0.1 to 2017 and at every Reynolds Number there will be shear stress values for 10.000 element. So I want Reynolds Numbers on x-axis and my shear stress(from 0.001 to 10) values on y-axis both will be on logarithmic scale and those 10.000 elements will be dots on the graph. So I will have totaly 100.000 points on the graph.

In this code I produce Re from 0.1 to 2017 and 10 element's shear stress values for every Reynolds Numbers. So at 0.1 on x-axis I need to have 10 points. So i looked for it but couldn't figure it out. So how can I do it ?

n = np.random.normal(mean, sd, 100)
for i in range(0, 105):
    Re = 0.1 * (1.1**i)  
    B = e ** (-0.08 * Re) * (2.5 * np.log(Re) + 5.25) + 8.5 * (1 - e ** (-0.08 * Re))  
    C = 0.8+0.9*((e**(-0.08*Re)/(Re**2))+((1-e**(-0.08*Re))/(B**2)))**(-0.5)  
    F = 0.31*Re*e**(-0.1*Re)+1.8*e**(-0.88*d50/D)*(1-e**(-0.1*Re)) 
    A = F/C   
    for j in range(10):
        Dcbss = 0.52*math.tan(fi) / (((1 + (abs(n[j])*A))**2)*(1+(1/2.5)*((abs(n[j])*F)**2)*math.tan(fi)))

You are using the variables mean and sd to create some data. Could you include some suitable values for those in your example? — wwii
– wwii, Commented May 19, 2019 at 13:37
Have you looked through the matplotlib gallery? Do you just need to know how to create a logarithmic scale — wwii
– wwii, Commented May 19, 2019 at 13:41
@wwii they arent so important in this question. mean is 0 and sd is 1. — mryellow61
– mryellow61, Commented May 19, 2019 at 13:46
I guess it isn't clear what your asking. Do you just need to know how to plot the data? 10 y values for every x value? — wwii
– wwii, Commented May 19, 2019 at 13:50
kinda yeah. i just couldnt figure out how those datas will match . when i look at the examples they write them seperately. but in this i cant write them seperately because they are random and too much. — mryellow61
– mryellow61, Commented May 19, 2019 at 13:56

wwii · Accepted Answer · 2019-05-19 14:34:53Z

Use a scatter plot. For each Reynolds Number you have n stress values. The scatter plot needs as many x values as there are y values so you have to create a sequence of x values the same length as the y values.

x = [1,1,1,1]
y = [1,2,3,4]

If you have multiple sets of x/y data you can plot it manually like this

x = [1,1,1,1]
y = [1,2,3,4]
plt.scatter(x,y)

x = [2,2,2,2]
y = [1.1,2.1,3.1,4.1]
plt.scatter(x,y)

plt.show()
plt.close()

For your case you want to accumulate x and y values in the inner loop, and plot them when the inner loop terminates.

from matplotlib import pyplot as plt
for i in range(0, 105):
    x = []
    y = []
    Re = 0.1 * (1.1**i)  
    B = e ** (-0.08 * Re) * (2.5 * np.log(Re) + 5.25) + 8.5 * (1 - e ** (-0.08 * Re))  
    C = 0.8+0.9*((e**(-0.08*Re)/(Re**2))+((1-e**(-0.08*Re))/(B**2)))**(-0.5)  
    F = 0.31*Re*e**(-0.1*Re)+1.8*e**(-0.88*d50/D)*(1-e**(-0.1*Re)) 
    A = F/C   
    for j in range(10):
        Dcbss = 0.52*math.tan(fi) / (((1 + (abs(n[j])*A))**2)*(1+(1/2.5)*((abs(n[j])*F)**2)*math.tan(fi)))
        x.append(i)
        y.append(Dcbss)
    plt.scatter(x,y)
plt.show()
plt.close()

From the docs: The plot function will be faster for scatterplots where markers don't vary in size or color.. If that is the case just use .plot() and specify a marker shape - plt.plot(x,y,'ro') instead of plt.scatter(x,y).

matplotlib.pyplot.scatter()
matplotlib.pyplot.plot()

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