/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

0 vote282 views1 answer
List variables in session tensorflow 1
Python
3 votes295 views2 answers
Spark add column to dataframe
Python
0 vote293 views1 answer
Python append many items to a list
Python
17 votes249 views1 answer
Strip all spaces python
Python
2 votes265 views2 answers
Pyqt5 qtwebenginewidgets not found
Python
4 votes285 views1 answer
How to add column headers in pandas
Python
0 vote293 views7 answers
Online python compailer
Python
0 vote296 views1 answer
Get timestamp with pyrhon
Python
4 votes279 views6 answers
Python rgb to hex
Python
0 vote306 views1 answer
Keep only min entries in dataframe grouped by one column
Python