# linear_combination Tactic #

In this file, the `linear_combination`

tactic is created. This tactic, which
works over `Ring`

s, attempts to simplify the target by creating a linear combination
of a list of equalities and subtracting it from the target. This file also includes a
definition for `linear_combination_config`

. A `linear_combination_config`

object can be passed into the tactic, allowing the user to specify a
normalization tactic.

## Implementation Notes #

This tactic works by creating a weighted sum of the given equations with the given coefficients. Then, it subtracts the right side of the weighted sum from the left side so that the right side equals 0, and it does the same with the target. Afterwards, it sets the goal to be the equality between the lefthand side of the new goal and the lefthand side of the new weighted sum. Lastly, calls a normalization tactic on this target.

## References #

Performs macro expansion of a linear combination expression,
using `+`

/`-`

/`*`

/`/`

on equations and values.

`some p`

means that`p`

is a syntax corresponding to a proof of an equation. For example, if`h : a = b`

then`expandLinearCombo (2 * h)`

returns`some (c_add_pf 2 h)`

which is a proof of`2 * a = 2 * b`

.`none`

means that the input expression is not an equation but a value; the input syntax itself is used in this case.

- normalize : Bool
whether or not the normalization step should be used

- twoGoals : Bool
whether to make separate subgoals for both sides or just one for

`lhs - rhs = 0`

- normTac : Lean.Syntax.Tactic
the tactic used for normalization when checking if the weighted sum is equivalent to the goal (when

`normalize`

is`true`

).

A configuration object for `linear_combination`

.

## Instances For

Function elaborating `LinearCombination.Config`

## Instances For

Implementation of `linear_combination`

and `linear_combination2`

.

## Instances For

The `(norm := $tac)`

syntax says to use `tac`

as a normalization postprocessor for
`linear_combination`

. The default normalizer is `ring1`

, but you can override it with `ring_nf`

to get subgoals from `linear_combination`

or with `skip`

to disable normalization.

## Instances For

`linear_combination`

attempts to simplify the target by creating a linear combination
of a list of equalities and subtracting it from the target.
The tactic will create a linear
combination by adding the equalities together from left to right, so the order
of the input hypotheses does matter. If the `normalize`

field of the
configuration is set to false, then the tactic will simply set the user up to
prove their target using the linear combination instead of normalizing the subtraction.

Note: The left and right sides of all the equalities should have the same
type, and the coefficients should also have this type. There must be
instances of `Mul`

and `AddGroup`

for this type.

- The input
`e`

in`linear_combination e`

is a linear combination of proofs of equalities, given as a sum/difference of coefficients multiplied by expressions. The coefficients may be arbitrary expressions. The expressions can be arbitrary proof terms proving equalities. Most commonly they are hypothesis names`h1, h2, ...`

. `linear_combination (norm := tac) e`

runs the "normalization tactic"`tac`

on the subgoal(s) after constructing the linear combination.- The default normalization tactic is
`ring1`

, which closes the goal or fails. - To get a subgoal in the case that it is not immediately provable, use
`ring_nf`

as the normalization tactic. - To avoid normalization entirely, use
`skip`

as the normalization tactic.

- The default normalization tactic is
`linear_combination2 e`

is the same as`linear_combination e`

but it produces two subgoals instead of one: rather than proving that`(a - b) - (a' - b') = 0`

where`a' = b'`

is the linear combination from`e`

and`a = b`

is the goal, it instead attempts to prove`a = a'`

and`b = b'`

. Because it does not use subtraction, this form is applicable also to semirings.- Note that a goal which is provable by
`linear_combination e`

may not be provable by`linear_combination2 e`

; in general you may need to add a coefficient to`e`

to make both sides match, as in`linear_combination2 e + c`

. - You can also reverse equalities using
`← h`

, so for example if`h₁ : a = b`

then`2 * (← h)`

is a proof of`2 * b = 2 * a`

.

- Note that a goal which is provable by

Example Usage:

```
example (x y : ℤ) (h1 : x*y + 2*x = 1) (h2 : x = y) : x*y = -2*y + 1 := by
linear_combination 1*h1 - 2*h2
example (x y : ℤ) (h1 : x*y + 2*x = 1) (h2 : x = y) : x*y = -2*y + 1 := by
linear_combination h1 - 2*h2
example (x y : ℤ) (h1 : x*y + 2*x = 1) (h2 : x = y) : x*y = -2*y + 1 := by
linear_combination (norm := ring_nf) -2*h2
/- Goal: x * y + x * 2 - 1 = 0 -/
example (x y z : ℝ) (ha : x + 2*y - z = 4) (hb : 2*x + y + z = -2)
(hc : x + 2*y + z = 2) :
-3*x - 3*y - 4*z = 2 := by
linear_combination ha - hb - 2*hc
example (x y : ℚ) (h1 : x + y = 3) (h2 : 3*x = 7) :
x*x*y + y*x*y + 6*x = 3*x*y + 14 := by
linear_combination x*y*h1 + 2*h2
example (x y : ℤ) (h1 : x = -3) (h2 : y = 10) : 2*x = -6 := by
linear_combination (norm := skip) 2*h1
simp
axiom qc : ℚ
axiom hqc : qc = 2*qc
example (a b : ℚ) (h : ∀ p q : ℚ, p = q) : 3*a + qc = 3*b + 2*qc := by
linear_combination 3 * h a b + hqc
```

## Instances For

`linear_combination`

attempts to simplify the target by creating a linear combination
of a list of equalities and subtracting it from the target.
The tactic will create a linear
combination by adding the equalities together from left to right, so the order
of the input hypotheses does matter. If the `normalize`

field of the
configuration is set to false, then the tactic will simply set the user up to
prove their target using the linear combination instead of normalizing the subtraction.

Note: The left and right sides of all the equalities should have the same
type, and the coefficients should also have this type. There must be
instances of `Mul`

and `AddGroup`

for this type.

- The input
`e`

in`linear_combination e`

is a linear combination of proofs of equalities, given as a sum/difference of coefficients multiplied by expressions. The coefficients may be arbitrary expressions. The expressions can be arbitrary proof terms proving equalities. Most commonly they are hypothesis names`h1, h2, ...`

. `linear_combination (norm := tac) e`

runs the "normalization tactic"`tac`

on the subgoal(s) after constructing the linear combination.- The default normalization tactic is
`ring1`

, which closes the goal or fails. - To get a subgoal in the case that it is not immediately provable, use
`ring_nf`

as the normalization tactic. - To avoid normalization entirely, use
`skip`

as the normalization tactic.

- The default normalization tactic is
`linear_combination2 e`

is the same as`linear_combination e`

but it produces two subgoals instead of one: rather than proving that`(a - b) - (a' - b') = 0`

where`a' = b'`

is the linear combination from`e`

and`a = b`

is the goal, it instead attempts to prove`a = a'`

and`b = b'`

. Because it does not use subtraction, this form is applicable also to semirings.- Note that a goal which is provable by
`linear_combination e`

may not be provable by`linear_combination2 e`

; in general you may need to add a coefficient to`e`

to make both sides match, as in`linear_combination2 e + c`

. - You can also reverse equalities using
`← h`

, so for example if`h₁ : a = b`

then`2 * (← h)`

is a proof of`2 * b = 2 * a`

.

- Note that a goal which is provable by

Example Usage:

```
example (x y : ℤ) (h1 : x*y + 2*x = 1) (h2 : x = y) : x*y = -2*y + 1 := by
linear_combination 1*h1 - 2*h2
example (x y : ℤ) (h1 : x*y + 2*x = 1) (h2 : x = y) : x*y = -2*y + 1 := by
linear_combination h1 - 2*h2
example (x y : ℤ) (h1 : x*y + 2*x = 1) (h2 : x = y) : x*y = -2*y + 1 := by
linear_combination (norm := ring_nf) -2*h2
/- Goal: x * y + x * 2 - 1 = 0 -/
example (x y z : ℝ) (ha : x + 2*y - z = 4) (hb : 2*x + y + z = -2)
(hc : x + 2*y + z = 2) :
-3*x - 3*y - 4*z = 2 := by
linear_combination ha - hb - 2*hc
example (x y : ℚ) (h1 : x + y = 3) (h2 : 3*x = 7) :
x*x*y + y*x*y + 6*x = 3*x*y + 14 := by
linear_combination x*y*h1 + 2*h2
example (x y : ℤ) (h1 : x = -3) (h2 : y = 10) : 2*x = -6 := by
linear_combination (norm := skip) 2*h1
simp
axiom qc : ℚ
axiom hqc : qc = 2*qc
example (a b : ℚ) (h : ∀ p q : ℚ, p = q) : 3*a + qc = 3*b + 2*qc := by
linear_combination 3 * h a b + hqc
```