add

esphome/components/sensor/__init__.py

@@ -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(

tests/integration/fixtures/sensor_filters_batch_window.yaml

@@ -0,0 +1,58 @@
+esphome:
+  name: test-batch-window-filters
+
+host:
+api:
+  batch_delay: 0ms  # Disable batching to receive all state updates
+logger:
+  level: DEBUG
+
+# Template sensor that we'll use to publish values
+sensor:
+  - platform: template
+    name: "Source Sensor"
+    id: source_sensor
+    accuracy_decimals: 2
+
+  # Batch window filters (window_size == send_every) - use streaming filters
+  - platform: copy
+    source_id: source_sensor
+    name: "Min Sensor"
+    id: min_sensor
+    filters:
+      - min:
+          window_size: 5
+          send_every: 5
+          send_first_at: 1
+
+  - platform: copy
+    source_id: source_sensor
+    name: "Max Sensor"
+    id: max_sensor
+    filters:
+      - max:
+          window_size: 5
+          send_every: 5
+          send_first_at: 1
+
+  - platform: copy
+    source_id: source_sensor
+    name: "Moving Avg Sensor"
+    id: moving_avg_sensor
+    filters:
+      - sliding_window_moving_average:
+          window_size: 5
+          send_every: 5
+          send_first_at: 1
+
+# Button to trigger publishing test values
+button:
+  - platform: template
+    name: "Publish Values Button"
+    id: publish_button
+    on_press:
+      - lambda: |-
+          // Publish 10 values: 1.0, 2.0, ..., 10.0
+          for (int i = 1; i <= 10; i++) {
+            id(source_sensor).publish_state(float(i));
+          }

tests/integration/fixtures/sensor_filters_ring_buffer.yaml

@@ -0,0 +1,75 @@
+esphome:
+  name: test-sliding-window-filters
+
+host:
+api:
+  batch_delay: 0ms  # Disable batching to receive all state updates
+logger:
+  level: DEBUG
+
+# Template sensor that we'll use to publish values
+sensor:
+  - platform: template
+    name: "Source Sensor"
+    id: source_sensor
+    accuracy_decimals: 2
+
+  # ACTUAL sliding window filters (window_size != send_every) - use ring buffers
+  # Window of 5, send every 2 values
+  - platform: copy
+    source_id: source_sensor
+    name: "Sliding Min Sensor"
+    id: sliding_min_sensor
+    filters:
+      - min:
+          window_size: 5
+          send_every: 2
+          send_first_at: 1
+
+  - platform: copy
+    source_id: source_sensor
+    name: "Sliding Max Sensor"
+    id: sliding_max_sensor
+    filters:
+      - max:
+          window_size: 5
+          send_every: 2
+          send_first_at: 1
+
+  - platform: copy
+    source_id: source_sensor
+    name: "Sliding Median Sensor"
+    id: sliding_median_sensor
+    filters:
+      - median:
+          window_size: 5
+          send_every: 2
+          send_first_at: 1
+
+  - platform: copy
+    source_id: source_sensor
+    name: "Sliding Moving Avg Sensor"
+    id: sliding_moving_avg_sensor
+    filters:
+      - sliding_window_moving_average:
+          window_size: 5
+          send_every: 2
+          send_first_at: 1
+
+# Button to trigger publishing test values
+button:
+  - platform: template
+    name: "Publish Values Button"
+    id: publish_button
+    on_press:
+      - lambda: |-
+          // Publish 10 values: 1.0, 2.0, ..., 10.0
+          // With window_size=5, send_every=2, send_first_at=1:
+          // - Output at position 1: window=[1], min=1, max=1, median=1, avg=1
+          // - Output at position 3: window=[1,2,3], min=1, max=3, median=2, avg=2
+          // - Output at position 5: window=[1,2,3,4,5], min=1, max=5, median=3, avg=3
+          // - Output at position 7: window=[3,4,5,6,7], min=3, max=7, median=5, avg=5
+          // - Output at position 9: window=[5,6,7,8,9], min=5, max=9, median=7, avg=7
+          for (int i = 1; i <= 10; i++) {
+            id(source_sensor).publish_state(float(i));
+          }