Comments (7)
You can ignore the warnings as long as there's a fit. As long as the
resulting parameters don't have nan
s or inf
s, it's a valid fit.
On Wed, Oct 7, 2015 at 8:46 PM, Roberto [email protected] wrote:
Should I safely ignore these warnings as long as a fit is produce? Which
would be the error when the package fail to produce a good fit and, then, I
should discard the result? Is it possible at all that the program fail
generating an appropriate fit?I don't really mind the warning as long as there is an accompanying
message indicated that the package successfully generated the fit.—
Reply to this email directly or view it on GitHub
#25 (comment)
.
from powerlaw.
@trungdong Done.
from powerlaw.
Hey @jeffalstott, thanks for making this. Related question: can I shut up the message:
Calculating best minimal value for power law fit
?
from powerlaw.
Hi @albertocottica,
I've just added an option to Fit()
, verbose
, that can be set to False
to turn off that message and the message that data <=0 is dropped. If that works for you, I can update the package on PyPi.
from powerlaw.
Should I safely ignore these warnings as long as a fit is produce? Which would be the error when the package fail to produce a good fit and, then, I should discard the result? Is it possible at all that the program fail generating an appropriate fit?
I don't really mind the warning as long as there is an accompanying message indicated that the package successfully generated the fit.
from powerlaw.
Hey, that was quick. Thanks a lot.
from powerlaw.
It would be really nice if the fix for the above is released on PyPi.
I'm running the powerlaw fittings on thousands of distributions and seeing that many "Calculating..." messages clogging the screen and drowning out all other application messages is no fun.
Thank you!
from powerlaw.
Related Issues (20)
- `estimate_discrete` should be False by default or raise a warning for x_min < 6 HOT 1
- p_value not computed from normalizes R HOT 6
- Issue with the x_min
- Curve fitted using power law is far from the data points
- Version label
- Added xmin computation does not work for distributions != power_law/truncated_power_law HOT 1
- power law plot showing fit and all data, not just data from xmin HOT 1
- New user: Why the curvature in power_law.plot_ccdf fit? HOT 14
- Defunct scipy import HOT 1
- threshold in powerlaw fit HOT 1
- Remove or make optional xmin fitting print
- Fitting a powerlaw with the xmax parameter HOT 17
- How to improve the efficiency of the fit.
- Get the estimates when i only have an probability distribution from empirical data
- Some issues in lognormal fit
- how to calculate the R value properly for discrete data
- Feature Request: Return the normalization constant HOT 9
- Please remove print statement on line 341 of powerlaw.py
- parameter1 attribute not set for fit.powerlaw HOT 1
- Can not pass 'bins' keyword to `plot_pdf` HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from powerlaw.