Comments (1)
Hi @kyrylosh !
Apologize for a long response.
This method returns a copy of the original graph subgraph. So, it doesn't change the original graph and returns new object which is independent from the original.
As a rule of thumb, get_* methods do not change the original graph.
Here is a little bit modified example from the documentation tutorial 1:
...
sm.remove_edges_below_threshold(0.8)
print(sm.adj)
>> {'address': {'absences': {'origin': 'learned', 'weight': 1.0401114250815813}, 'G1': {'origin': 'learned', 'weight': 1.0067951058436733}}, 'famsize': {}, 'Pstatus': {'famrel': {'origin': 'learned', 'weight': 0.8414079152414446}, 'absences': {'origin': 'learned', 'weight': -1.0538608943790326}, 'G1': {'origin': 'learned', 'weight': 1.2634829976324862}}, 'Medu': {}, 'Fedu': {}, 'traveltime': {}, 'studytime': {'G1': {'origin': 'learned', 'weight': 0.8625899070681395}}, 'failures': {'absences': {'origin': 'learned', 'weight': 0.9395908769320622}}, 'schoolsup': {'G1': {'origin': 'learned', 'weight': -0.8004284975411484}}, 'famsup': {}, 'paid': {'absences': {'origin': 'learned', 'weight': -1.053462507125605}}, 'activities': {}, 'nursery': {}, 'higher': {'Medu': {'origin': 'learned', 'weight': 0.9849012357123937}, 'G1': {'origin': 'learned', 'weight': 2.692412347274737}}, 'internet': {'absences': {'origin': 'learned', 'weight': 0.8368980995953069}}, 'romantic': {}, 'famrel': {}, 'freetime': {}, 'goout': {}, 'Dalc': {'Walc': {'origin': 'learned', 'weight': 0.8621481174505992}}, 'Walc': {}, 'health': {}, 'absences': {}, 'G1': {'G2': {'origin': 'learned', 'weight': 0.890172428823507}}, 'G2': {'G3': {'origin': 'learned', 'weight': 0.8856269211850833}}, 'G3': {}}
Compare with the following
sm.get_target_subgraph("Walc").adj
>> AdjacencyView({'Dalc': {'Walc': {'origin': 'learned', 'weight': 0.8621481174505992}}, 'Walc': {}})
Feel free to ask any questions on this or add your suggestions.
from causalnex.
Related Issues (20)
- the same process different results HOT 1
- Can't install causalnex using poetry on new Apple M1 chip HOT 1
- EMSingleLatentVariable is producing random error at random times HOT 1
- Add GitHub Actions installation jobs across environments HOT 1
- Unsuitability of Notears for causal inference HOT 3
- How do I save the fitted Bayesian model locally HOT 2
- vis.show() UnicodeEncodeError HOT 9
- Find out the number of cycles HOT 1
- 01_first_tutorial.ipynb hangs on `from_pandas(...)`
- [Feature Request]: Support pandas >= 2.0
- [Bug]: Pycharm cannot use causalnex HOT 1
- [help]: I am unable to display images while using viz. show() HOT 1
- [Feature Request]: batch_size for notears with GPU
- [Bug]: Inconsistent Use of CUDA Devices When Using GPU with notears
- [Bug]: Classification Model always predicting 0 HOT 1
- [Bug]: fix typo in 04_user_guide.md
- [Feature Request]: Support Python 3.11
- [Bug]: causalnex.discretiser.MDLPSupervisedDiscretiserMethod does not import MDLP
- An issue with plotting[Bug]: HOT 1
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 causalnex.