Comments (4)
Why isn't it just called
OrdinalPatterns
andWeightedOrdinalPatterns
?
I wrote my answer too quickly: I like your suggestions better. OrdinalPatterns
, WeightedOrdinalPatterns
and AmplitudeAwareOrdinalPatterns
.
EDIT: However, skipping "patterns" makes the name shorted, and "ordinal" already implies some sort of ordering pattern, so perhaps the shorter alternatives proposed above work too. I'm not too attached to any of the names, as long as we drop the "Symbolic" part in favor of "Ordinal".
from complexitymeasures.jl.
me2
from complexitymeasures.jl.
I never quite understood why we are using different words to refer to the same thing. We have "ordinal pattern encoding" but the outcome space is called "symbolic permutation". Why? Why isn't it just called OrdinalPatterns and WeightedOrdinalPatterns?
Wouldn't this simplify things a lot? Alternative is to rename the encoding to be SymbolicPermutationEncoding. But I see no reason to use two different names for the same thing.
We went a bit back and forth on the naming, and I agree that we might have ended on a sub-par alternative. The Symbolic
prefix was there because it originated from the permutation entropy. But since SymbolicPermutation
and friends now are outcome spaces, there's no reason to keep this name. Moreover, every discretization scheme "symbolizes" - that is what happens when you discretise. I think Ordinal
-something is much more informative. I suggest the following outcome space renamings:
SymbolicPermutation
->Ordinal
SymbolicAmplitudeAwarePermutation
->OrdinalAmplitudeAware
SymbolicWeightedPermutation
->OrdinalWeighted
The OrdinalPatternEncoding
we can either keep, or rename to OrdinalEncoding
(btw: there will soon be OrdinalAmplitudeAwareEncoding
and OrdinalWeightedEncoding
too, which will allow us to explicitly use these outcome spaces in upstream functions such as transfer entropy).
from complexitymeasures.jl.
After my edit above:
Ordinal
/OrdinalWeighted
/OrdinalAmplitudeAware
OrdinalPatterns
/WeightedOrdinalPatterns
/AmplitudeAwareOrdinalPatterns
I vote for alternative 2. It's more intuitive.
from complexitymeasures.jl.
Related Issues (20)
- Dep compatibility issue between ComplexityMeasures (3.0.0) and DynamicalSystems (3.2.3). HOT 10
- ```genentropy``` is broken HOT 1
- Docstring and implementation for Statistical Complexity is wrong HOT 1
- `eachindex` for `Probabilities` is ambiguous HOT 3
- Signature for `Counts` and `Probabilities` docstrings has the wrong type parameter order HOT 3
- Missing deprecation for `OrdinalPatterns{m}(; τ)` HOT 10
- Some documentation issues for CI HOT 2
- The function `lt` in `OrdinalPatternEncoding` isn't actually used HOT 1
- Reproducibility for `OrdinalPatternEncoding` HOT 3
- It shouldn't be possible to construct an empty `CombinationEncoding` HOT 3
- Feature: "distribution entropy" HOT 3
- Feature: bubble entropy (description is WIP) HOT 4
- Feature: "increment entropy" HOT 1
- Feature: "attention entropy"
- `missing_probabilities` HOT 1
- `counts_and_outcomes` for `BubbleSortSwaps` should also accept state space sets
- Syntax with type parameter `{m}` in `OrdinalPatterns` is not harmonious with the rest of the library HOT 10
- Encoding using `Dispersion` is slower than necessary due to manual integration for normal cdf
- Encoding complex-valued data HOT 2
- [Q] How to calculate MI between two vectors? 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 complexitymeasures.jl.