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This commit is contained in:
J. Nick Koston
2025-10-15 19:57:29 -10:00
parent a999349fa5
commit f75f11b550
3 changed files with 148 additions and 12 deletions
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27
esphome/components/sensor/__init__.py
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@@ -453,7 +453,7 @@ async def skip_initial_filter_to_code(config, filter_id):
return cg.new_Pvariable(filter_id, config)
@FILTER_REGISTRY.register("min", MinFilter, MIN_SCHEMA)
@FILTER_REGISTRY.register("min", Filter, MIN_SCHEMA)
async def min_filter_to_code(config, filter_id):
window_size: int = config[CONF_WINDOW_SIZE]
send_every: int = config[CONF_SEND_EVERY]
@@ -463,10 +463,11 @@ async def min_filter_to_code(config, filter_id):
# Saves 99.98% memory for large windows (e.g., 20KB → 4 bytes for window_size=5000)
if window_size == send_every:
# Use streaming filter - O(1) memory instead of O(n)
rhs = cg.new_Pvariable(StreamingMinFilter, window_size, send_first_at)
return cg.Pvariable(filter_id, rhs)
rhs = StreamingMinFilter.new(window_size, send_first_at)
return cg.Pvariable(filter_id, rhs, StreamingMinFilter)
# Use sliding window filter - maintains ring buffer
return cg.new_Pvariable(filter_id, window_size, send_every, send_first_at)
rhs = MinFilter.new(window_size, send_every, send_first_at)
return cg.Pvariable(filter_id, rhs, MinFilter)
MAX_SCHEMA = cv.All(
@@ -481,7 +482,7 @@ MAX_SCHEMA = cv.All(
)
@FILTER_REGISTRY.register("max", MaxFilter, MAX_SCHEMA)
@FILTER_REGISTRY.register("max", Filter, MAX_SCHEMA)
async def max_filter_to_code(config, filter_id):
window_size: int = config[CONF_WINDOW_SIZE]
send_every: int = config[CONF_SEND_EVERY]
@@ -489,9 +490,10 @@ async def max_filter_to_code(config, filter_id):
# Optimization: Use streaming filter for batch windows (window_size == send_every)
if window_size == send_every:
rhs = cg.new_Pvariable(StreamingMaxFilter, window_size, send_first_at)
return cg.Pvariable(filter_id, rhs)
return cg.new_Pvariable(filter_id, window_size, send_every, send_first_at)
rhs = StreamingMaxFilter.new(window_size, send_first_at)
return cg.Pvariable(filter_id, rhs, StreamingMaxFilter)
rhs = MaxFilter.new(window_size, send_every, send_first_at)
return cg.Pvariable(filter_id, rhs, MaxFilter)
SLIDING_AVERAGE_SCHEMA = cv.All(
@@ -508,7 +510,7 @@ SLIDING_AVERAGE_SCHEMA = cv.All(
@FILTER_REGISTRY.register(
"sliding_window_moving_average",
SlidingWindowMovingAverageFilter,
Filter,
SLIDING_AVERAGE_SCHEMA,
)
async def sliding_window_moving_average_filter_to_code(config, filter_id):
@@ -518,9 +520,10 @@ async def sliding_window_moving_average_filter_to_code(config, filter_id):
# Optimization: Use streaming filter for batch windows (window_size == send_every)
if window_size == send_every:
rhs = cg.new_Pvariable(StreamingMovingAverageFilter, window_size, send_first_at)
return cg.Pvariable(filter_id, rhs)
return cg.new_Pvariable(filter_id, window_size, send_every, send_first_at)
rhs = StreamingMovingAverageFilter.new(window_size, send_first_at)
return cg.Pvariable(filter_id, rhs, StreamingMovingAverageFilter)
rhs = SlidingWindowMovingAverageFilter.new(window_size, send_every, send_first_at)
return cg.Pvariable(filter_id, rhs, SlidingWindowMovingAverageFilter)
EXPONENTIAL_AVERAGE_SCHEMA = cv.All(