package tensor

import (
	"fmt"
)

func ExampleDense_Slice() {
	var T Tensor
	T = New(WithBacking(Range(Float64, 0, 9)), WithShape(3, 3))
	fmt.Printf("T:\n%v\n", T)

	// T[0:2, 0:2]
	T, _ = T.Slice(makeRS(0, 2), makeRS(0, 2)) // makeRS is an unexported function that creates a Slice.
	fmt.Printf("T[0:2, 0:2]:\n%v\n", T)

	// T[:, 1]
	T, _ = T.(Slicer).Slice(nil, ss(1)) // ss is unexported
	fmt.Printf("T[:, 1]:\n%v\n", T)

	// Output:
	// T:
	// ⎡0  1  2⎤
	// ⎢3  4  5⎥
	// ⎣6  7  8⎦
	//
	// T[0:2, 0:2]:
	// ⎡0  1⎤
	// ⎣3  4⎦
	//
	// T[:, 1]:
	// [1  4]
}

// Slicing works on one dimensional arrays too:
func ExampleDense_Slice_oneDimension() {
	var T Tensor
	T = New(WithBacking(Range(Float64, 0, 9)))
	fmt.Printf("T:\n%v\n\n", T)

	T, _ = T.Slice(makeRS(0, 5))
	fmt.Printf("T[0:5]:\n%v\n", T)

	// Output:
	// T:
	// [0  1  2  3  ... 5  6  7  8]
	//
	// T[0:5]:
	// [0  1  2  3  4]

}

// Any modifications to the sliced value modifies the original slice as well
func ExampleDense_Slice_viewMutation() {
	var T, V Tensor
	T = New(WithBacking(Range(Int, 0, 16)), WithShape(4, 4))
	fmt.Printf("T:\n%v\n", T)
	V, _ = T.Slice(makeRS(1, 3), makeRS(1, 3))
	fmt.Printf("V:\n%v\n", V)

	// Now we modify V's 0th value
	V.(*Dense).Set(0, 1000)
	fmt.Printf("V[0] = 1000:\n%v\n", V)
	fmt.Printf("T is also mutated:\n%v", T)

	// Output:
	// T:
	// ⎡ 0   1   2   3⎤
	// ⎢ 4   5   6   7⎥
	// ⎢ 8   9  10  11⎥
	// ⎣12  13  14  15⎦
	//
	// V:
	// ⎡ 5   6⎤
	// ⎣ 9  10⎦
	//
	// V[0] = 1000:
	// ⎡1000     6⎤
	// ⎣   9    10⎦
	//
	// T is also mutated:
	// ⎡   0     1     2     3⎤
	// ⎢   4  1000     6     7⎥
	// ⎢   8     9    10    11⎥
	// ⎣  12    13    14    15⎦
	//
}

func ExampleView() {
	// Slicing creates a "view" on the original tensor
	T := New(WithBacking(Range(Int, 0, 16)), WithShape(4, 4))
	fmt.Printf("T:\n%v\n", T)
	V, _ := T.Slice(makeRS(1, 3), makeRS(1, 3))
	fmt.Printf("V:\n%v\n", V)

	// Now we modify V's 0th value
	V.(*Dense).Set(0, 1000)
	fmt.Printf("V[0] = 1000:\n%v\n", V)
	fmt.Printf("T is also mutated:\n%v\n", T)

	// Now we materialize the views
	fmt.Printf("V is Materializable: %v\n", V.IsMaterializable())
	T2 := V.Materialize()
	fmt.Printf("T2 == V:\n%v\n", T2)

	// Once materialized, it is decoupled from the original tensor
	T2.(*Dense).Set(0, 999)
	fmt.Printf("T2 is mutated:\n%v\nBut T is not mutated:\n%v\nNeither is V:\n%v", T2, T, V)
	// Output:
	// T:
	// ⎡ 0   1   2   3⎤
	// ⎢ 4   5   6   7⎥
	// ⎢ 8   9  10  11⎥
	// ⎣12  13  14  15⎦
	//
	// V:
	// ⎡ 5   6⎤
	// ⎣ 9  10⎦
	//
	// V[0] = 1000:
	// ⎡1000     6⎤
	// ⎣   9    10⎦
	//
	// T is also mutated:
	// ⎡   0     1     2     3⎤
	// ⎢   4  1000     6     7⎥
	// ⎢   8     9    10    11⎥
	// ⎣  12    13    14    15⎦
	//
	// V is Materializable: true
	// T2 == V:
	// ⎡1000     6⎤
	// ⎣   9    10⎦
	//
	// T2 is mutated:
	// ⎡999    6⎤
	// ⎣  9   10⎦
	//
	// But T is not mutated:
	// ⎡   0     1     2     3⎤
	// ⎢   4  1000     6     7⎥
	// ⎢   8     9    10    11⎥
	// ⎣  12    13    14    15⎦
	//
	// Neither is V:
	// ⎡1000     6⎤
	// ⎣   9    10⎦

}

func ExampleDense_Hstack() {
	var T, T1, T2, T3 *Dense
	var err error
	T = New(WithBacking(Range(Float64, 0, 4)), WithShape(2, 2))
	T1 = New(WithBacking([]float64{1000, 2000}), WithShape(2, 1))

	// Simple example
	if T2, err = T.Hstack(T1); err == nil {
		fmt.Printf("T.Hstack(T1):\n%v\n", T2)
	}

	// This fails, because they are not the same shape
	T1.Reshape(2)
	if _, err = T.Hstack(T1); err != nil {
		fmt.Printf("Error: %v\n\n", err)
	}

	// You can stack more than one, as long as all the tensors have the same shape
	T1.Reshape(2, 1)
	T3 = T1.Clone().(*Dense)
	if T2, err = T.Hstack(T1, T3); err == nil {
		fmt.Printf("T.Hstack(T1, T3):\n%v\n", T2)
	}

	// Compatible shapes can be stacked
	T1 = New(Of(Float64), WithShape(2, 3))
	if T2, err = T.Hstack(T1); err == nil {
		fmt.Printf("Hstacking (2,2) with (2,3):\n%v\n", T2)
	}

	// Special attention to vectors - vectors can only be stacked with vectors
	T = New(WithBacking([]float64{1000, 2000}))
	T1 = New(WithBacking([]float64{0, 1}), WithShape(1, 2))
	if _, err = T.Hstack(T1); err != nil {
		fmt.Printf("Hstacking (2) with (1,2): %v\n", err)
	}

	// Now let's look at failure conditions, or unhandled situations

	// Incompatible shapes cannot be stacked
	T1.Reshape(3, 2)
	if _, err = T.Hstack(T1); err != nil {
		fmt.Printf("Hstacking (2,2) with (3,2): %v\n", err)
	}

	// Obviously you can't stack a scalar onto tensors (or the other way around)
	T1 = New(FromScalar(1.0))
	if _, err = T.Hstack(T1); err != nil {
		fmt.Printf("Hstacking a scalar onto a tensor: %v\n", err)
	}
	if _, err = T1.Hstack(T); err != nil {
		fmt.Printf("Hstacking a tensor onto a scalar: %v\n", err)
	}

	// Output:
	// T.Hstack(T1):
	// ⎡   0     1  1000⎤
	// ⎣   2     3  2000⎦
	//
	// Error: Failed to perform Concat: Unable to find new shape that results from concatenation: Dimension mismatch. Expected 2, got 1
	//
	// T.Hstack(T1, T3):
	// ⎡   0     1  1000  1000⎤
	// ⎣   2     3  2000  2000⎦
	//
	// Hstacking (2,2) with (2,3):
	// ⎡0  1  0  0  0⎤
	// ⎣2  3  0  0  0⎦
	//
	// Hstacking (2) with (1,2): Failed to perform Concat: Unable to find new shape that results from concatenation: Dimension mismatch. Expected 1, got 2
	// Hstacking (2,2) with (3,2): Failed to perform Concat: Unable to find new shape that results from concatenation: Dimension mismatch. Expected 1, got 2
	// Hstacking a scalar onto a tensor: Tensor has to be at least 1 dimensions
	// Hstacking a tensor onto a scalar: Tensor has to be at least 1 dimensions
}

func ExampleDense_Vstack() {
	var T, T1, T2, T3 *Dense
	var err error

	T = New(WithBacking(Range(Float64, 0, 4)), WithShape(2, 2))
	T1 = New(WithBacking([]float64{1000, 2000}), WithShape(1, 2))

	// Simple example
	if T2, err = T.Vstack(T1); err == nil {
		fmt.Printf("T.Vstack(T1):\n%v\n", T2)
	} else {
		fmt.Printf("%+v", err)
	}

	// You can stack more than one, as long as all the tensors have the same shape
	T3 = T1.Clone().(*Dense)
	if T2, err = T.Vstack(T1, T3); err == nil {
		fmt.Printf("T.Vstack(T1, T3):\n%v\n", T2)
	} else {
		fmt.Printf("====\nerr %v\n%v\n===\n", err, T3.Shape())
	}

	// Let's look at failure conditions
	// All tensors must be at least 2D
	T.Reshape(4)
	if _, err = T.Vstack(T1); err != nil {
		fmt.Printf("Vstacking (4) with (1, 2): %v\n", err)
	}
	if _, err = T1.Vstack(T); err != nil {
		fmt.Printf("Vstacking (1, 2) with (4): %v\n", err)
	}

	// Output:
	// T.Vstack(T1):
	// ⎡   0     1⎤
	// ⎢   2     3⎥
	// ⎣1000  2000⎦
	//
	// T.Vstack(T1, T3):
	// ⎡   0     1⎤
	// ⎢   2     3⎥
	// ⎢1000  2000⎥
	// ⎣1000  2000⎦
	//
	// Vstacking (4) with (1, 2): Tensor has to be at least 2 dimensions
	// Vstacking (1, 2) with (4): Tensor has to be at least 2 dimensions
}

func ExampleRepeatReuse() {
	var T, T1 *Dense
	T = New(WithBacking([]float64{1, 2, 3, 4}), WithShape(1, 4))
	T1 = New(Of(Float64), WithShape(3, 4))

	var T2 Tensor
	var err error
	if T2, err = RepeatReuse(T, T1, 0, 3); err != nil {
		fmt.Printf("Err %v", err)
	}
	fmt.Printf("RepeatReuse(T, T1):\n%v", T2)
	fmt.Printf("T1 == T2: %t\n", T1 == T2)

	// But if your reuse is wrongly shaped, an error occurs
	T1 = New(Of(Float64), WithShape(1, 4)) // too small
	if _, err = RepeatReuse(T, T1, 0, 3); err != nil {
		fmt.Printf("Expected Error: %v\n", err)
	}

	// Output:
	// RepeatReuse(T, T1):
	// ⎡1  2  3  4⎤
	// ⎢1  2  3  4⎥
	// ⎣1  2  3  4⎦
	// T1 == T2: true
	// Expected Error: Reuse shape is (1, 4). Expected shape is (3, 4)
}

func ExampleRepeat_uncommonUses() {
	T := New(WithBacking([]int{1, 2, 3, 4, 5, 6}), WithShape(2, 3))
	fmt.Printf("T:\n%v", T)

	fmt.Println("Axis 0 has 2 elements. So we will need to write the number of times each element is to be repeated")
	fmt.Println("Here, Repeat(T, 0, 3, 2) results in this:")
	T1, err := Repeat(T, 0, 3, 2)
	if err != nil {
		fmt.Printf("Err %v", err)
	}
	fmt.Printf("%v", T1)
	fmt.Println("Observe the 0th element ([1 2 3]) has been repeated 3 times, and the 1st element ([4 5 6]) has been repeated twice")
	fmt.Println("")

	fmt.Println("We can also repeat on Axis 1. Now along Axis 1 there are 3 elements: ([1 4], [2 5], [3 6])")
	fmt.Println("So we have to specify how many times to repeat each element.")
	fmt.Println("Repeat(T, 1, 2, 3, 2) yields the following result:")
	T1, err = Repeat(T, 1, 2, 3, 2)
	if err != nil {
		fmt.Printf("Err %v", err)
	}
	fmt.Printf("%v", T1)
	fmt.Println("Once again, observe that the 1st element ([2 5]) has been repeated 3 times, while the rest have been repeated twice")
	/*
	   // TODO break this out to another example
	   	T1, err = Repeat(T, AllAxes, 2, 3, 2, 2, 2, 2)
	   	if err != nil {
	   		fmt.Printf("Err %v", err)
	   	}
	   	fmt.Printf("%#v", T1)
	*/

	// Output:
	// T:
	// ⎡1  2  3⎤
	// ⎣4  5  6⎦
	// Axis 0 has 2 elements. So we will need to write the number of times each element is to be repeated
	// Here, Repeat(T, 0, 3, 2) results in this:
	// ⎡1  2  3⎤
	// ⎢1  2  3⎥
	// ⎢1  2  3⎥
	// ⎢4  5  6⎥
	// ⎣4  5  6⎦
	// Observe the 0th element ([1 2 3]) has been repeated 3 times, and the 1st element ([4 5 6]) has been repeated twice
	//
	// We can also repeat on Axis 1. Now along Axis 1 there are 3 elements: ([1 4], [2 5], [3 6])
	// So we have to specify how many times to repeat each element.
	// Repeat(T, 1, 2, 3, 2) yields the following result:
	// ⎡1  1  2  2  2  3  3⎤
	// ⎣4  4  5  5  5  6  6⎦
	// Once again, observe that the 1st element ([2 5]) has been repeated 3 times, while the rest have been repeated twice

}

func ExampleT() {
	// Usual example of 2D matrix being transposed:
	M := New(WithBacking([]int{1, 2, 3, 4, 5, 6}), WithShape(2, 3))
	M2, err := T(M)
	if err != nil {
		fmt.Printf("Err: %v\n", err)
	}
	fmt.Printf("M:\n%v\nM2:\n%v\n", M, M2)

	// T accepts optional parameters describing the permutation of axes.
	// In a 2D case, there are only two options: (0, 1) or (1, 0).
	// The latter is default if no parameters are passed in.
	// The former is a no-op as rearranging a matrix so that the 0th axis becomes the 0th axis
	// and the first axis becomes the first axis is not going to do anything.
	//
	// However, note that M3 is a different result.
	M3, err := T(M, 0, 1)
	if err != nil {
		fmt.Printf("Err: %v\n", err)
	}
	fmt.Printf("M3:\n%v\nM == M3: %t", M3, M == M3)

	// Output:
	// M:
	// ⎡1  2  3⎤
	// ⎣4  5  6⎦
	//
	// M2:
	// ⎡1  4⎤
	// ⎢2  5⎥
	// ⎣3  6⎦
	//
	// M3:
	// ⎡1  2  3⎤
	// ⎣4  5  6⎦
	//
	// M == M3: false

}

func ExampleT_scalarlike() {
	// Be aware when dealing with scalarlike tensors
	// scalar/scalarlikes have no effect when calling T()
	// but the result is put into a new tensor
	S := New(WithBacking([]float32{3.14}), WithShape())
	S2, err := T(S)
	if err != nil {
		fmt.Printf("Err %v", err)
	}
	fmt.Printf("S: %v S2 %v S == S2: %t\n", S, S2, S == S2)

	// however do note that scalars and scalarlikes are not the same thing.
	// for example, consider this:
	_, err = T(S, 1, 0)
	fmt.Printf("error when the axes are more than the shape's dims: %v\n", err)

	// but if you have a tensor that is a scalar-like:
	S.Reshape(1, 1)
	S2, err = T(S, 1, 0)
	if err != nil {
		fmt.Printf("Err: %v\n", err)
	}
	fmt.Printf("S:\n%v\nS2:\n%v\nS == S2: %t\n", S, S2, S == S2)

	// Output:
	// S: 3.14 S2 3.14 S == S2: false
	// error when the axes are more than the shape's dims: Dimension mismatch. Expected 0, got 2
	// S:
	// [[3.14]]
	// S2:
	// [[3.14]]
	// S == S2: false

}