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Add Bayesian type for binary_sensor_map component (#4640)

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* initial support for Bayesian type

* Cast bool state of binary_sensor to uint64_t

* Rename channels to observations with Bayesian

* Improve/standardize comments for all types

* Use black to correct sensor.py formatting

* Add SUM and BAYESIAN binary sensor map tests

* Remove unused variable

* Update esphome/components/binary_sensor_map/binary_sensor_map.cpp

Co-authored-by: Jesse Hills <3060199+jesserockz@users.noreply.github.com>

---------

Co-authored-by: Jesse Hills <3060199+jesserockz@users.noreply.github.com>
This commit is contained in:
kahrendt
2023-04-12 21:48:29 -04:00
committed by GitHub
parent cc1eb648f9
commit afc848bf22
4 changed files with 190 additions and 34 deletions
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esphome/components/binary_sensor_map/sensor.py
+41 -6
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@@ -20,16 +20,29 @@ BinarySensorMap = binary_sensor_map_ns.class_(
)
SensorMapType = binary_sensor_map_ns.enum("SensorMapType")
CONF_BAYESIAN = "bayesian"
CONF_PRIOR = "prior"
CONF_PROB_GIVEN_TRUE = "prob_given_true"
CONF_PROB_GIVEN_FALSE = "prob_given_false"
CONF_OBSERVATIONS = "observations"
SENSOR_MAP_TYPES = {
CONF_GROUP: SensorMapType.BINARY_SENSOR_MAP_TYPE_GROUP,
CONF_SUM: SensorMapType.BINARY_SENSOR_MAP_TYPE_SUM,
CONF_BAYESIAN: SensorMapType.BINARY_SENSOR_MAP_TYPE_BAYESIAN,
}
entry = {
entry_one_parameter = {
cv.Required(CONF_BINARY_SENSOR): cv.use_id(binary_sensor.BinarySensor),
cv.Required(CONF_VALUE): cv.float_,
}
entry_bayesian_parameters = {
cv.Required(CONF_BINARY_SENSOR): cv.use_id(binary_sensor.BinarySensor),
cv.Required(CONF_PROB_GIVEN_TRUE): cv.float_range(min=0, max=1),
cv.Required(CONF_PROB_GIVEN_FALSE): cv.float_range(min=0, max=1),
}
CONFIG_SCHEMA = cv.typed_schema(
{
CONF_GROUP: sensor.sensor_schema(
@@ -39,7 +52,7 @@ CONFIG_SCHEMA = cv.typed_schema(
).extend(
{
cv.Required(CONF_CHANNELS): cv.All(
cv.ensure_list(entry), cv.Length(min=1, max=64)
cv.ensure_list(entry_one_parameter), cv.Length(min=1, max=64)
),
}
),
@@ -50,7 +63,18 @@ CONFIG_SCHEMA = cv.typed_schema(
).extend(
{
cv.Required(CONF_CHANNELS): cv.All(
cv.ensure_list(entry), cv.Length(min=1, max=64)
cv.ensure_list(entry_one_parameter), cv.Length(min=1, max=64)
),
}
),
CONF_BAYESIAN: sensor.sensor_schema(
BinarySensorMap,
accuracy_decimals=2,
).extend(
{
cv.Required(CONF_PRIOR): cv.float_range(min=0, max=1),
cv.Required(CONF_OBSERVATIONS): cv.All(
cv.ensure_list(entry_bayesian_parameters), cv.Length(min=1, max=64)
),
}
),
@@ -66,6 +90,17 @@ async def to_code(config):
constant = SENSOR_MAP_TYPES[config[CONF_TYPE]]
cg.add(var.set_sensor_type(constant))
for ch in config[CONF_CHANNELS]:
input_var = await cg.get_variable(ch[CONF_BINARY_SENSOR])
cg.add(var.add_channel(input_var, ch[CONF_VALUE]))
if config[CONF_TYPE] == CONF_BAYESIAN:
cg.add(var.set_bayesian_prior(config[CONF_PRIOR]))
for obs in config[CONF_OBSERVATIONS]:
input_var = await cg.get_variable(obs[CONF_BINARY_SENSOR])
cg.add(
var.add_channel(
input_var, obs[CONF_PROB_GIVEN_TRUE], obs[CONF_PROB_GIVEN_FALSE]
)
)
else:
for ch in config[CONF_CHANNELS]:
input_var = await cg.get_variable(ch[CONF_BINARY_SENSOR])
cg.add(var.add_channel(input_var, ch[CONF_VALUE]))