# `Monty.Frameworks.Models.EvidenceMatching.GraphMemory.EvidenceGraphMemory`
[🔗](https://github.com/d-led/ex.tbp.monty/blob/v0.1.0/packages/ex_tbp_monty_core/lib/monty/frameworks/models/evidence_matching/graph_memory/evidence_graph_memory.ex#L1)

Memory that stores grid models, which is what an evidence-based learning
module learns into.

Mirrors `tbp/monty/frameworks/models/evidence_matching/graph_memory.py
::EvidenceGraphMemory`, whose whole content is a different object model plus
what follows from it. Evidence matching compares one observation against every
node of every object at once, so memory that stored every observation as a
node would be both slow and enormous; the grid keeps a bounded number of
nodes per object and is the reason a pretrained YCB model fits in memory at
all.

## Inheritance became configuration

In Python this class exists to subclass `GraphMemory` and override the three
places where a model is constructed — build, extend, and load. There is no
inheritance to override in Elixir, and there does not need to be: memory
already takes the object model as a module and its options as a keyword list,
so the same three places build a `GridObjectModel` when memory is made here
and a `GraphObjectModel` when it is made by `GraphMemory.new/1` directly. One
struct, one set of functions, two configurations.

## What the three numbers mean

  * `:max_nodes_per_graph` — how many nodes an object thins down to, which
    bounds the cost of every matching step;
  * `:max_graph_size` — how large an object may be, in metres, before the
    model refuses it with `GridTooSmallError`;
  * `:num_model_voxels_per_dim` — the resolution, hence the smallest detail a
    model can hold: `max_graph_size / num_model_voxels_per_dim` per voxel.

# `get_initial_hypotheses`

```elixir
@spec get_initial_hypotheses(Monty.Frameworks.Models.GraphMatching.GraphMemory.t()) ::
  [
    Monty.Frameworks.Models.GraphMatching.GraphMemory.graph_id()
  ]
```

What a learning module starts from: the id of every object in memory.

Nothing is ruled out at the first step, so every stored object is a candidate.
Monty's base memory answers with its models instead; evidence matching wants
ids, because its hypotheses are per object and its evidence lives per graph.

# `new`

```elixir
@spec new(keyword()) :: Monty.Frameworks.Models.GraphMatching.GraphMemory.t()
```

An empty memory of grid models, configured by the three numbers Monty's
learning-module config sets.

---

*Consult [api-reference.md](api-reference.md) for complete listing*