Comments (1)
By modifying the DimensionalData.jl printing code, I'm getting close to something here.
julia> Counts([50, 44, 33], ["cake", "meat", "veggie"])
Counts{Int64,1} over 3 outcomes
"cake" 50
"meat" 44
"veggie" 33
julia> Counts(rand(1:3, 5, 2))
5×2 Counts{Int64,2}
Outcome(1) Outcome(2)
Outcome(1) 3 1
Outcome(2) 3 1
Outcome(3) 3 1
Outcome(4) 1 1
Outcome(5) 3 3
julia> Counts(rand(1:10, 4), ["o1", "o2", 56, 2])
Counts{Int64,1} over 4 outcomes
"o1" 5
"o2" 5
56 8
2 10
julia> c = Counts(rand(1:30, 2, 3, 3), (['a', 'e'], 2:2:6, [(1, 2), (2, 1), (3, 1)]))
2×3×3 Counts{Int64,3}
[:, :, 1]
2 4 6
'a' 15 18 27
'e' 23 13 17
[and 2 more slices...]
I just need to get rid of the extra spaces that sometimes occur, and I think this is good to go.
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
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