/Python/Logarithmic scale fitting python

Logarithmic scale fitting python

fig=plt.figure()
ax = fig.add_subplot(111)

z=np.arange(1, len(x)+1) #start at 1, to avoid error from log(0)

logA = np.log(z) #no need for list comprehension since all z values >= 1
logB = np.log(y)

m, c = np.polyfit(logA, logB, 1, w=np.sqrt(y)) # fit log(y) = m*log(x) + c
y_fit = np.exp(m*logA + c) # calculate the fitted values of y 

plt.plot(z, y, color = 'r')
plt.plot(z, y_fit, ':')

ax.set_yscale('symlog')
ax.set_xscale('symlog')
#slope, intercept = np.polyfit(logA, logB, 1)
plt.xlabel("Pre_referer")
plt.ylabel("Popularity")
ax.set_title('Pre Referral URL Popularity distribution')
plt.show()

Source: stackoverflow.com

Similar codes

1 vote149 views1 answer
Python display text in label on new line
Python
3 votes145 views4 answers
Django setup in windows
Python
76 votes184 views6 answers
Python iterate through list
Python
0 vote198 views1 answer
How to get the current url path in django template
Python Django
0 vote146 views1 answer
Adding attributes and metadata to a dataset using xarray
Python
0 vote144 views1 answer
User passes test django
Python
0 vote159 views1 answer
Train_ttest_split()
Python
1 vote143 views3 answers
Typeerror:
Python
1 vote144 views2 answers
Python leetcode
Python
2 votes141 views2 answers
Choice random word in python from a text file
Python