Comments (3)
Hi @vuillaut,
I re-organised the material in the sub-directories and the installation dependencies to be sure all the notebooks can run on binder.
In the main page there is now a link to launch the repo on binder.
The only tutorial not working is the external Compton one since it requires more memory than the one provided by Binder (2 GB - it does a very large multidimensional integration and it exceeds this limit - I'll try to fix this).
For the rest, I added a README.md in experiments
specifying that is a sub-directory for developers only.
And we discovered, thanks to @CerenOzen, that the unit issue you reported with units
is triggered by an old astropy
version.
I specified in the setup.py
to use a newer one.
So I think all the problems you reported have been fixed :) and I can close this.
Thanks for reporting them!
from agnpy.
Thanks a lot @vuillaut.
The only notebooks that should be accessible to users are those in docs/tutorials
.
Everything in experiments
is modified and circulated between developers for testing and discussing.
Shall I remove this material completely from the repo?
By the way, checking the notebooks in the binder I forgot to make a new release with the newest documentation (and newest notebooks). I will do it next week.
The issue you reported with Quantities
was also reported by @jsitarek in #74. I will check it.
Thank you!
from agnpy.
Thanks a lot @vuillaut.
The only notebooks that should be accessible to users are those indocs/tutorials
.
Everything inexperiments
is modified and circulated between developers for testing and discussing.
Shall I remove this material completely from the repo?
I would not pretend to tell you how to manage your project :)
As a user, it might be interesting to have a warning in these notebooks that they are for developpers.
By the way, checking the notebooks in the binder I forgot to make a new release with the newest documentation (and newest notebooks). I will do it next week.
The issue you reported with
Quantities
was also reported by @jsitarek in #74. I will check it.Thank you!
No problem
from agnpy.
Related Issues (20)
- Introducing a Particle class HOT 1
- Incompatibility between astropy 5.0.1 and agnpy 0.1.8 ? HOT 1
- bug when simulation of gammapy datasets with an agnpy spectrum model HOT 9
- Absorption calculation stability HOT 1
- Add sherpa and gammapy among the dependencies (add them to install_requires in setup.py) HOT 4
- Add a CITATION.cff file?
- TypeError: __init__() got an unexpected keyword argument 'is_norm' HOT 3
- Bullet points of lists disappear on Read the Docs HOT 1
- Error in the EBL absorption HOT 1
- Error in InterpolatedDistribution HOT 11
- Discrepancy between AGNpy and LeHa code in proton synchrotron
- Add the synchrotron proton to the models available for fitting
- Issue with fitting MWL SED using agnpy HOT 7
- Return the different SED components after a fit HOT 2
- Problem about load_absorption_table in class EBL HOT 2
- Problem about load_absorption_table in class EBL
- Move the tests to the subdirectory of each module. HOT 1
- Fitting of a MWL BL Lac SED: Fit doesn't converge. HOT 1
- d_L parameter in blob definition spoiling older code and examples
- Logging is silently disabled on agnpy import HOT 3
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 agnpy.