/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 vote314 views6 answers
Idl else
Python
1 vote276 views1 answer
Python change base function
Python
53 votes291 views4 answers
Python get filename from path
Python
68 votes246 views6 answers
How to sort values in python from dictionary to list
Python
0 vote260 views1 answer
Pandas dataframe from array of dict
Python
1 vote320 views1 answer
Print console sys.stdout
Python
22 votes274 views2 answers
Reset_index(drop=true)
Python
0 vote351 views1 answer
Np.eye(5)[list]
Python
12 votes295 views3 answers
Exit in python
Python
11 votes268 views6 answers
Start python server
Python