/Python/Best fit line python log log scale

Best fit line python log log scale

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 vote334 views1 answer
Sys.path.append python
Python
0 vote360 views1 answer
Scree plot sklearn
Python
3 votes357 views3 answers
How to make my jupyter prin full array
Python
15 votes361 views5 answers
Check empty dataframe
Python
0 vote357 views1 answer
Python for loop in range 01 02
Python
0 vote347 views1 answer
Quantile-quantile plot python
Python
0 vote322 views1 answer
How to make bot commands case insensitive in discord.py
Python
0 vote367 views1 answer
Django prepopulated_fields
Python
0 vote405 views1 answer
Flash not defined python flask
Python Flask
0 vote338 views1 answer
Str to tuple of float
Python