from aiuna import *

d = file("iris.arff").data

print(d.Xd)
"""
['sepallength', 'sepalwidth', 'petallength', 'petalwidth']
"""

print(d.X[:5])
"""
[[5.1 3.5 1.4 0.2]
 [4.9 3.  1.4 0.2]
 [4.7 3.2 1.3 0.2]
 [4.6 3.1 1.5 0.2]
 [5.  3.6 1.4 0.2]]
"""

print(d.y[:5])
"""
['Iris-setosa' 'Iris-setosa' 'Iris-setosa' 'Iris-setosa' 'Iris-setosa']
"""

from pandas import DataFrame
print(DataFrame(d.y).value_counts())
"""
Iris-setosa        50
Iris-versicolor    50
Iris-virginica     50
dtype: int64
"""

#from aiuna import *

#d = dataset.data  # 'iris' is the default dataset
#df = d.X_pd
#print(df.head())
#...

#mycol = d.X_pd["petal length (cm)"]
#print(mycol[:5])
#...

from aiuna import *
import numpy as np

X = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
y = np.array([0, 1, 1])
d = new(X=X, y=y)
print(d)
"""
{
    "uuid": "06NLDM4mLEMrHPOaJvEBqdo",
    "uuids": {
        "changed": "3Sc2JjUPMlnNtlq3qdx9Afy",
        "X": "13zbQMwRwU3WB8IjMGaXbtf",
        "Y": "1IkmDz3ATFmgzeYnzygvwDu"
    },
    "step": {
        "id": "06NLDM4mLEMrHPOT2pd5lzo",
        "desc": {
            "name": "New",
            "path": "aiuna.step.new",
            "config": {
                "hashes": {
                    "X": "586962852295d584ec08e7214393f8b2",
                    "Y": "f043eb8b1ab0a9618ad1dc53a00d759e"
                }
            }
        }
    },
    "changed": [
        "X",
        "Y"
    ],
    "X": [
        "[[1 2 3]",
        " [4 5 6]",
        " [7 8 9]]"
    ],
    "Y": [
        "[[0]",
        " [1]",
        " [1]]"
    ]
}
"""

from aiuna import *

d = dataset.data  # 'iris' is the default dataset
print(d.history)
"""
{
    "02o8BsNH0fhOYFF6JqxwaLF": {
        "name": "New",
        "path": "aiuna.step.new",
        "config": {
            "hashes": {
                "X": "19b2d27779bc2d2444c11f5cc24c98ee",
                "Y": "8baa54c6c205d73f99bc1215b7d46c9c",
                "Xd": "0af9062dccbecaa0524ac71978aa79d3",
                "Yd": "04ceed329f7c3eb43f93efd981fde313",
                "Xt": "60d4f429fcd642bbaf1d976002479ea2",
                "Yt": "4660adc31e2c25d02cb751dcb96ecfd3"
            }
        }
    }
}
"""

del d["X"]
print(d.history)
"""
{
    "02o8BsNH0fhOYFF6JqxwaLF": {
        "name": "New",
        "path": "aiuna.step.new",
        "config": {
            "hashes": {
                "X": "19b2d27779bc2d2444c11f5cc24c98ee",
                "Y": "8baa54c6c205d73f99bc1215b7d46c9c",
                "Xd": "0af9062dccbecaa0524ac71978aa79d3",
                "Yd": "04ceed329f7c3eb43f93efd981fde313",
                "Xt": "60d4f429fcd642bbaf1d976002479ea2",
                "Yt": "4660adc31e2c25d02cb751dcb96ecfd3"
            }
        }
    },
    "06fV1rbQVC1WfPelDNTxEPI": {
        "name": "Del",
        "path": "aiuna.step.delete",
        "config": {
            "field": "X"
        }
    }
}
"""

d["Z"] = 42
print(d.Z, type(d.Z))
"""
[[42]] <class 'numpy.ndarray'>
"""

print(d.history)
"""
{
    "02o8BsNH0fhOYFF6JqxwaLF": {
        "name": "New",
        "path": "aiuna.step.new",
        "config": {
            "hashes": {
                "X": "19b2d27779bc2d2444c11f5cc24c98ee",
                "Y": "8baa54c6c205d73f99bc1215b7d46c9c",
                "Xd": "0af9062dccbecaa0524ac71978aa79d3",
                "Yd": "04ceed329f7c3eb43f93efd981fde313",
                "Xt": "60d4f429fcd642bbaf1d976002479ea2",
                "Yt": "4660adc31e2c25d02cb751dcb96ecfd3"
            }
        }
    },
    "06fV1rbQVC1WfPelDNTxEPI": {
        "name": "Del",
        "path": "aiuna.step.delete",
        "config": {
            "field": "X"
        }
    },
    "05eIWbfCJS7vWJsXBXjoUAh": {
        "name": "Let",
        "path": "aiuna.step.let",
        "config": {
            "field": "Z",
            "value": 42
        }
    }
}
"""