1Var_RandSupport_FixedLength_-3to3_-5.0to-3.0-3.0to5.0_30Points

.gitattributes

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 *.jpg filter=lfs diff=lfs merge=lfs -text
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+1Var_RandSupport_FixedLength_-3to3_-5.0to-3.0-3.0to5.0_30Points/Train/0_1_0_14062021_193012.json filter=lfs diff=lfs merge=lfs -text

1Var_RandSupport_FixedLength_-3to3_-5.0to-3.0-3.0to5.0_30Points/Train/0_1_0_14062021_193012.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dc83e2936950457653266d1cd1f10a8650cd96f235a059e5d1ac22aa6f076d40
+size 477948920

1Var_RandSupport_FixedLength_-3to3_-5.0to-3.0-3.0to5.0_30Points/config.txt

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+# Config
+    seed = 2021 # 2021 Train, 2022 Val, 2023 Test, you have to change the generateData.py seed as well
+    #from GenerateData import seed
+    import random
+    random.seed(seed)
+    np.random.seed(seed=seed) # fix the seed for reproducibility
+
+    #NOTE: For linux you can only use unique numVars, in Windows, it is possible to use [1,2,3,4] * 10!
+    numVars = [1] #list(range(31)) #[1,2,3,4,5]
+    decimals = 8
+    numberofPoints = [30,31] # only usable if support points has not been provided
+    numSamples = 10000 # number of generated samples
+    folder = './Dataset'
+    dataPath = folder +'/{}_{}_{}.json'
+
+    testPoints = False
+    trainRange = [-3.0,3.0] 
+    testRange = [[-5.0, 3.0],[-3.0, 5.0]] # this means Union((-5,-1),(1,5))
+
+    supportPoints = None
+    #supportPoints = np.linspace(xRange[0],xRange[1],numberofPoints[1])
+    #supportPoints = [[np.round(p,decimals)] for p in supportPoints]
+    #supportPoints = [[np.round(p,decimals), np.round(p,decimals)] for p in supportPoints]
+    #supportPoints = [[np.round(p,decimals) for i in range(numVars[0])] for p in supportPoints]
+
+    supportPointsTest = None
+    #supportPoints = None # uncomment this line if you don't want to use support points
+    #supportPointsTest = np.linspace(xRange[0],xRange[1],numberofPoints[1])
+    #supportPointsTest = [[np.round(p,decimals) for i in range(numVars[0])] for p in supportPointsTest]
+    
+    n_levels = 4
+    allow_constants = True
+    const_range = [-2.1, 2.1]
+    const_ratio = 0.5
+    op_list=[
+                "id", "add", "mul",
+                "sin", "pow", "cos", 
+                "exp", "div", "sub", "log"
+            ]
+    exponents=[3, 4, 5, 6]
+
+    sortY = False # if the data is sorted based on y
+    numSamplesEachEq = 50
+    threshold = 5000
+    templatesEQs = None