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Expression of type TensorProd

from the theory of proveit.linear_algebra.tensors

In [1]:
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, s
from proveit.core_expr_types import Q__b_1_to_j, a_1_to_i, b_1_to_j, c_1_to_k, f__b_1_to_j
from proveit.linear_algebra import ScalarMult, TensorProd, VecSum
In [2]:
# build up the expression from sub-expressions
sub_expr1 = [b_1_to_j]
expr = TensorProd(a_1_to_i, VecSum(index_or_indices = sub_expr1, summand = ScalarMult(Function(s, sub_expr1), f__b_1_to_j), condition = Q__b_1_to_j), c_1_to_k)
expr:
In [3]:
# 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
In [4]:
# Show the LaTeX representation of the expression for convenience if you need it.
print(stored_expr.latex())
a_{1} {\otimes}  a_{2} {\otimes}  \ldots {\otimes}  a_{i} {\otimes} \left[\sum_{b_{1}, b_{2}, \ldots, b_{j}~|~Q\left(b_{1}, b_{2}, \ldots, b_{j}\right)}~\left(s\left(b_{1}, b_{2}, \ldots, b_{j}\right) \cdot f\left(b_{1}, b_{2}, \ldots, b_{j}\right)\right)\right]{\otimes} c_{1} {\otimes}  c_{2} {\otimes}  \ldots {\otimes}  c_{k}
In [5]:
stored_expr.style_options()
namedescriptiondefaultcurrent valuerelated methods
operation'infix' or 'function' style formattinginfixinfix
wrap_positionsposition(s) at which wrapping is to occur; '2 n - 1' is after the nth operand, '2 n' is after the nth operation.()()('with_wrapping_at', 'with_wrap_before_operator', 'with_wrap_after_operator', 'without_wrapping', 'wrap_positions')
justificationif any wrap positions are set, justify to the 'left', 'center', or 'right'centercenter('with_justification',)
In [6]:
# display the expression information
stored_expr.expr_info()
 core typesub-expressionsexpression
0Operationoperator: 1
operands: 2
1Literal
2ExprTuple3, 4, 5
3ExprRangelambda_map: 6
start_index: 30
end_index: 7
4Operationoperator: 8
operand: 13
5ExprRangelambda_map: 10
start_index: 30
end_index: 11
6Lambdaparameter: 35
body: 12
7Variable
8Literal
9ExprTuple13
10Lambdaparameter: 35
body: 14
11Variable
12IndexedVarvariable: 15
index: 35
13Lambdaparameters: 27
body: 16
14IndexedVarvariable: 17
index: 35
15Variable
16Conditionalvalue: 18
condition: 19
17Variable
18Operationoperator: 20
operands: 21
19Operationoperator: 22
operands: 27
20Literal
21ExprTuple23, 24
22Variable
23Operationoperator: 25
operands: 27
24Operationoperator: 26
operands: 27
25Variable
26Variable
27ExprTuple28
28ExprRangelambda_map: 29
start_index: 30
end_index: 31
29Lambdaparameter: 35
body: 32
30Literal
31Variable
32IndexedVarvariable: 33
index: 35
33Variable
34ExprTuple35
35Variable