if !Code.ensure_loaded?(Kino.SmartCell) do
defmodule Evision.SmartCell.ML.RTrees do
end
else
defmodule Evision.SmartCell.ML.RTrees do
use Kino.JS, assets_path: "lib/assets"
use Kino.JS.Live
use Kino.SmartCell, name: "Evision: Random Forest"
alias Evision.SmartCell.Helper, as: ESCH
alias Evision.SmartCell.ML.DTrees
alias Evision.SmartCell.ML.TrainData
@smartcell_id "evision.ml.rtrees"
@properties %{
"data_from" => %{
:type => :string,
:opts => [must_in: ["traindata", "traindata_var"]],
:default => "traindata"
},
"traindata_var" => %{
:type => :string,
:default => "dataset"
},
# RTrees
"active_var_count" => %{
:type => :integer,
:opts => [minimum: 0],
:default => 0
},
"calculate_var_importance" => %{
:type => :boolean,
:default => false
},
"to_variable" => %{
:type => :string,
:default => "rtree"
},
# TermCriteria
"term_criteria_type" => %{
:type => :string,
:opts => [must_in: ["max_count", "eps", "max_count+eps"]],
:default => "max_count"
},
"term_criteria_count" => %{
:type => :integer,
:opts => [minimum: 0],
:default => 10
},
"term_criteria_eps" => %{
:type => :number,
:default => 0
}
}
@inner_to_module %{
"dtrees" => DTrees,
"traindata" => TrainData
}
@spec id :: String.t()
def id, do: @smartcell_id
@spec properties :: map()
def properties, do: @properties
@spec defaults :: map()
def defaults do
Map.new(
Enum.map(@properties, fn {field, field_specs} ->
{field, field_specs[:default]}
end)
)
end
@impl true
def init(attrs, ctx) do
# load from file or fill empty entries with default values
fields =
Map.new(
Enum.map(@properties, fn {field, field_specs} ->
{field, attrs[field] || field_specs[:default]}
end)
)
# traindata
key = "traindata"
fields =
ESCH.update_key_with_module(fields, key, @inner_to_module[key], fn fields, key ->
fields["data_from"] == key
end)
key = "dtrees"
fields =
ESCH.update_key_with_module(fields, key, @inner_to_module[key], fn _, _ -> true end)
info = [id: @smartcell_id, fields: fields]
{:ok, assign(ctx, info)}
end
@impl true
def handle_connect(ctx) do
{:ok, %{fields: ctx.assigns.fields, id: @smartcell_id}, ctx}
end
@impl true
def handle_event("update_field", %{"field" => field, "value" => value}, ctx) do
updated_fields =
case String.split(field, ".", parts: 2) do
[inner, forward] ->
ESCH.to_inner_updates(inner, @inner_to_module[inner], forward, value, ctx)
[field] ->
to_updates(ctx.assigns.fields, field, value)
end
ctx = update(ctx, :fields, &Map.merge(&1, updated_fields))
broadcast_event(ctx, "update", %{"fields" => updated_fields})
{:noreply, ctx}
end
def to_updates(_fields, name = "data_from", key = "traindata") do
%{name => key, key => @inner_to_module[key].defaults()}
end
def to_updates(_fields, name, value) do
property = @properties[name]
%{name => ESCH.to_update(value, property[:type], Access.get(property, :opts))}
end
@impl true
def to_attrs(%{assigns: %{fields: fields}}) do
fields
end
@impl true
def to_source(attrs) do
get_quoted_code(attrs)
|> Kino.SmartCell.quoted_to_string()
end
def get_quoted_code(attrs = %{"dtrees" => dtrees_attrs}) do
quote do
unquote(ESCH.quoted_var(attrs["to_variable"])) =
Evision.ML.RTrees.create()
|> Evision.ML.RTrees.setMaxDepth(unquote(dtrees_attrs["max_depth"]))
|> Evision.ML.RTrees.setMaxCategories(unquote(dtrees_attrs["max_categories"]))
|> Evision.ML.RTrees.setCVFolds(unquote(dtrees_attrs["cv_folds"]))
|> Evision.ML.RTrees.setMinSampleCount(unquote(dtrees_attrs["min_sample_count"]))
|> Evision.ML.RTrees.setActiveVarCount(unquote(attrs["active_var_count"]))
|> Evision.ML.RTrees.setCalculateVarImportance(
unquote(attrs["calculate_var_importance"])
)
unquote(set_term_criteria(attrs))
unquote(train_on_dataset(attrs))
end
end
defp set_term_criteria(
attrs = %{
"term_criteria_type" => "max_count",
"term_criteria_count" => count,
"term_criteria_eps" => eps
}
) do
quote do
unquote(ESCH.quoted_var(attrs["to_variable"])) =
Evision.ML.RTrees.setTermCriteria(
unquote(ESCH.quoted_var(attrs["to_variable"])),
{Evision.Constant.cv_MAX_ITER(), unquote(count), unquote(eps)}
)
end
end
defp set_term_criteria(
attrs = %{
"term_criteria_type" => "eps",
"term_criteria_count" => count,
"term_criteria_eps" => eps
}
) do
quote do
unquote(ESCH.quoted_var(attrs["to_variable"])) =
Evision.ML.RTrees.setTermCriteria(
unquote(ESCH.quoted_var(attrs["to_variable"])),
{Evision.Constant.cv_EPS(), unquote(count), unquote(eps)}
)
end
end
defp set_term_criteria(
attrs = %{
"term_criteria_type" => "max_count+eps",
"term_criteria_count" => count,
"term_criteria_eps" => eps
}
) do
quote do
unquote(ESCH.quoted_var(attrs["to_variable"])) =
Evision.ML.RTrees.setTermCriteria(
unquote(ESCH.quoted_var(attrs["to_variable"])),
{Evision.Constant.cv_MAX_ITER() + Evision.Constant.cv_EPS(), unquote(count),
unquote(eps)}
)
end
end
defp train_on_dataset(%{
"data_from" => "traindata_var",
"traindata_var" => traindata_var,
"to_variable" => to_variable
}) do
quote do
Evision.ML.RTrees.train(
unquote(ESCH.quoted_var(to_variable)),
unquote(ESCH.quoted_var(traindata_var))
)
unquote(TrainData.get_calc_error(Evision.ML.SVM, traindata_var, to_variable))
end
end
defp train_on_dataset(%{
"data_from" => "traindata",
"traindata" => traindata_attrs,
"to_variable" => to_variable
}) do
dataset_variable = traindata_attrs["to_variable"]
quote do
unquote(TrainData.get_quoted_code(traindata_attrs))
Evision.ML.RTrees.train(
unquote(ESCH.quoted_var(to_variable)),
unquote(ESCH.quoted_var(dataset_variable))
)
unquote(TrainData.get_calc_error(Evision.ML.SVM, dataset_variable, to_variable))
end
end
end
end