Measures as real-valued functions #
Given a measure μ
, we have defined μ.real
as the function sending a set s
to (μ s).toReal
.
In this file, we develop a basic API around this notion.
We essentially copy relevant lemmas from the files MeasureSpaceDef.lean
, NullMeasurable.lean
and
MeasureSpace.lean
, and adapt them by replacing in their name measure
with measureReal
.
Many lemmas require an assumption that some set has finite measure. These assumptions are written
in the form (h : μ s ≠ ∞ := by finiteness)
, where finiteness
is a tactic for goals of
the form ≠ ∞
.
There are certainly many missing lemmas. The missing ones should be added as they are needed.
There are no lemmas on infinite sums, as summability issues are really more painful with reals than nonnegative extended reals. They should probably be added in the long run.
If s
is a Finset
, then the measure of its preimage can be found as the sum of measures
of the fibers f ⁻¹' {y}
.
If s
is a Finset
, then the sums of the real measures of the singletons in the set is the
real measure of the set.
Pigeonhole principle for measure spaces: if s
is a Finset
and
∑ i ∈ s, μ.real (t i) > μ.real univ
, then one of the intersections t i ∩ t j
is not empty.
If two sets s
and t
are included in a set u
of finite measure,
and μ.real s + μ.real t > μ.real u
, then s
intersects t
.
Version assuming that t
is measurable.
If two sets s
and t
are included in a set u
of finite measure,
and μ.real s + μ.real t > μ.real u
, then s
intersects t
.
Version assuming that s
is measurable.
Extension for the positivity
tactic: applications of μ.real
are nonnegative.
Equations
- One or more equations did not get rendered due to their size.