Expression of type Function

from the theory of proveit.linear_algebra.tensors

import proveit
# Automation is not needed when building an expression:
proveit.defaults.automation = False # This will speed things up.
proveit.defaults.inline_pngs = False # Makes files smaller.
%load_expr # Load the stored expression as 'stored_expr'
# import Expression classes needed to build the expression
from proveit import Function
from proveit.core_expr_types import A_1_to_n, v_1_to_n
from proveit.linear_algebra import TensorProd

# build up the expression from sub-expressions
expr = Function(TensorProd(A_1_to_n), [TensorProd(v_1_to_n)])

expr:

# check that the built expression is the same as the stored expression
assert expr == stored_expr
assert expr._style_id == stored_expr._style_id
print("Passed sanity check: expr matches stored_expr")

Passed sanity check: expr matches stored_expr

# Show the LaTeX representation of the expression for convenience if you need it.
print(stored_expr.latex())

\left(A_{1} {\otimes}  A_{2} {\otimes}  \ldots {\otimes}  A_{n}\right)\left(v_{1} {\otimes}  v_{2} {\otimes}  \ldots {\otimes}  v_{n}\right)

stored_expr.style_options()

no style options

# display the expression information
stored_expr.expr_info()

	core type	sub-expressions	expression
0	Operation	operator: 1 operand: 4
1	Operation	operator: 6 operands: 3
2	ExprTuple	4
3	ExprTuple	5
4	Operation	operator: 6 operands: 7
5	ExprRange	lambda_map: 8 start_index: 12 end_index: 13
6	Literal
7	ExprTuple	9
8	Lambda	parameter: 18 body: 10
9	ExprRange	lambda_map: 11 start_index: 12 end_index: 13
10	IndexedVar	variable: 14 index: 18
11	Lambda	parameter: 18 body: 15
12	Literal
13	Variable
14	Variable
15	IndexedVar	variable: 16 index: 18
16	Variable
17	ExprTuple	18
18	Variable