Add connect_segments parameter to get_chartdata service for visual segment connections

Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>

custom_components/tibber_prices/services.yaml

@@ -158,6 +158,14 @@ get_chartdata:
             - segments
             - all
           translation_key: insert_nulls
+    connect_segments:
+      name: Connect Segments
+      description: >-
+        [ONLY WITH insert_nulls='segments'] When enabled, adds connecting points at segment boundaries to visually connect different price level segments in stepline charts. When price goes DOWN at a boundary, adds a point with the lower price at the end of the current segment. When price goes UP, adds a hold point before the gap. This creates smooth visual transitions between segments instead of abrupt gaps.
+      required: false
+      default: false
+      selector:
+        boolean:
     # === OUTPUT FORMAT ===
     output_format:
       name: Output Format

custom_components/tibber_prices/services/get_chartdata.py

@@ -92,6 +92,7 @@ CHARTDATA_SERVICE_SCHEMA: Final = vol.Schema(
             [vol.In([PRICE_RATING_LOW, PRICE_RATING_NORMAL, PRICE_RATING_HIGH])],
         ),
         vol.Optional("insert_nulls", default="none"): vol.In(["none", "segments", "all"]),
+        vol.Optional("connect_segments", default=False): bool,
         vol.Optional("add_trailing_null", default=False): bool,
         vol.Optional("period_filter"): vol.In(["best_price", "peak_price"]),
         vol.Optional("start_time_field", default="start_time"): str,
@@ -156,6 +157,7 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]:  # noqa: PLR091
     include_rating_level = call.data.get("include_rating_level", False)
     include_average = call.data.get("include_average", False)
     insert_nulls = call.data.get("insert_nulls", "none")
+    connect_segments = call.data.get("connect_segments", False)
     add_trailing_null = call.data.get("add_trailing_null", False)
     period_filter = call.data.get("period_filter")
     # Filter values are already normalized to uppercase by schema validators
@@ -336,6 +338,7 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]:  # noqa: PLR091
 
                     start_time = interval.get("startsAt")
                     price = interval.get("total")
+                    next_price = next_interval.get("total")
                     next_start_time = next_interval.get("startsAt")
 
                     if start_time is None or price is None:
@@ -370,24 +373,70 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]:  # noqa: PLR091
 
                         # Check if next interval is different level (segment boundary)
                         if next_value != interval_value:
-                            # Hold current price until next timestamp (stepline effect)
                             next_start_serialized = (
                                 next_start_time.isoformat()
                                 if next_start_time and hasattr(next_start_time, "isoformat")
                                 else next_start_time
                             )
-                            hold_point = {start_time_field: next_start_serialized, price_field: converted_price}
-                            if include_level and "level" in interval:
-                                hold_point[level_field] = interval["level"]
-                            if include_rating_level and "rating_level" in interval:
-                                hold_point[rating_level_field] = interval["rating_level"]
-                            if include_average and day in day_averages:
-                                hold_point[average_field] = day_averages[day]
-                            chart_data.append(hold_point)
 
-                            # Add NULL point to create gap
+                            if connect_segments and next_price is not None:
-                            null_point = {start_time_field: next_start_serialized, price_field: None}
+                                # Connect segments visually by adding transition points
-                            chart_data.append(null_point)
+                                # Convert next price for comparison and use
+                                converted_next_price = (
+                                    round(next_price * 100, 2) if minor_currency else round(next_price, 4)
+                                )
+                                if round_decimals is not None:
+                                    converted_next_price = round(converted_next_price, round_decimals)
+
+                                if next_price < price:
+                                    # Price goes DOWN: Add point at end of current segment with lower price
+                                    # This draws the line downward from current level
+                                    connect_point = {
+                                        start_time_field: next_start_serialized,
+                                        price_field: converted_next_price,
+                                    }
+                                    if include_level and "level" in interval:
+                                        connect_point[level_field] = interval["level"]
+                                    if include_rating_level and "rating_level" in interval:
+                                        connect_point[rating_level_field] = interval["rating_level"]
+                                    if include_average and day in day_averages:
+                                        connect_point[average_field] = day_averages[day]
+                                    chart_data.append(connect_point)
+                                else:
+                                    # Price goes UP or stays same: Add hold point with current price
+                                    # Then add connect point at next level with higher price
+                                    hold_point = {
+                                        start_time_field: next_start_serialized,
+                                        price_field: converted_price,
+                                    }
+                                    if include_level and "level" in interval:
+                                        hold_point[level_field] = interval["level"]
+                                    if include_rating_level and "rating_level" in interval:
+                                        hold_point[rating_level_field] = interval["rating_level"]
+                                    if include_average and day in day_averages:
+                                        hold_point[average_field] = day_averages[day]
+                                    chart_data.append(hold_point)
+
+                                # Add NULL point to create gap after transition
+                                null_point = {start_time_field: next_start_serialized, price_field: None}
+                                chart_data.append(null_point)
+                            else:
+                                # Original behavior: Hold current price until next timestamp
+                                hold_point = {
+                                    start_time_field: next_start_serialized,
+                                    price_field: converted_price,
+                                }
+                                if include_level and "level" in interval:
+                                    hold_point[level_field] = interval["level"]
+                                if include_rating_level and "rating_level" in interval:
+                                    hold_point[rating_level_field] = interval["rating_level"]
+                                if include_average and day in day_averages:
+                                    hold_point[average_field] = day_averages[day]
+                                chart_data.append(hold_point)
+
+                                # Add NULL point to create gap
+                                null_point = {start_time_field: next_start_serialized, price_field: None}
+                                chart_data.append(null_point)
 
                 # Handle last interval of the day - extend to midnight
                 if day_prices:

custom_components/tibber_prices/translations/en.json

@@ -873,6 +873,10 @@
                     "name": "Insert NULL Values",
                     "description": "Control NULL value insertion for filtered data. 'none' (default): No NULL values, only matching intervals. 'segments': Add NULL points at segment boundaries for clean gaps in charts (recommended for stepline charts). 'all': Insert NULL for all timestamps where filter doesn't match (useful for continuous time series visualization)."
                 },
+                "connect_segments": {
+                    "name": "Connect Segments",
+                    "description": "[ONLY WITH insert_nulls='segments'] When enabled, adds connecting points at segment boundaries to visually connect different price level segments in stepline charts. When price goes DOWN at a boundary, adds a point with the lower price at the end of the current segment. When price goes UP, adds a hold point before the gap. This creates smooth visual transitions between segments instead of abrupt gaps."
+                },
                 "add_trailing_null": {
                     "name": "Add Trailing Null Point",
                     "description": "[BOTH FORMATS] Add a final data point with null values (except timestamp) at the end. Some chart libraries need this to prevent extrapolation/interpolation to the viewport edge when using stepline rendering. Leave disabled unless your chart requires it."

tests/test_connect_segments.py

@@ -0,0 +1,158 @@
+"""Test connect_segments feature for ApexCharts segment boundaries."""
+
+from datetime import UTC, datetime, timedelta
+
+
+def make_interval(start_time: datetime, price: float, level: str) -> dict:
+    """Create a price interval for testing."""
+    return {
+        "startsAt": start_time,
+        "total": price,
+        "level": level,
+    }
+
+
+def make_day_prices(base_time: datetime) -> list[dict]:
+    """Create sample price data with level transitions."""
+    return [
+        # First segment: CHEAP at low price
+        make_interval(base_time, 0.10, "CHEAP"),
+        make_interval(base_time + timedelta(minutes=15), 0.11, "CHEAP"),
+        # Transition: CHEAP -> NORMAL (price goes UP)
+        make_interval(base_time + timedelta(minutes=30), 0.20, "NORMAL"),
+        make_interval(base_time + timedelta(minutes=45), 0.21, "NORMAL"),
+        # Transition: NORMAL -> CHEAP (price goes DOWN)
+        make_interval(base_time + timedelta(minutes=60), 0.12, "CHEAP"),
+        make_interval(base_time + timedelta(minutes=75), 0.13, "CHEAP"),
+    ]
+
+
+class TestConnectSegmentsLogic:
+    """Test the connect_segments transition logic."""
+
+    def test_price_direction_detection_down(self) -> None:
+        """Test that price going down is correctly detected."""
+        current_price = 0.20
+        next_price = 0.12
+        assert next_price < current_price, "Should detect price going down"
+
+    def test_price_direction_detection_up(self) -> None:
+        """Test that price going up is correctly detected."""
+        current_price = 0.11
+        next_price = 0.20
+        assert next_price > current_price, "Should detect price going up"
+
+    def test_price_direction_detection_same(self) -> None:
+        """Test that same price is handled correctly (treated as up)."""
+        current_price = 0.15
+        next_price = 0.15
+        assert not (next_price < current_price), "Same price should not be treated as 'down'"
+
+    def test_sample_data_structure(self) -> None:
+        """Test that sample data has expected structure."""
+        base_time = datetime(2025, 12, 1, 0, 0, tzinfo=UTC)
+        prices = make_day_prices(base_time)
+
+        assert len(prices) == 6, "Should have 6 intervals"
+
+        # Check first transition (CHEAP -> NORMAL at index 1->2)
+        assert prices[1]["level"] == "CHEAP"
+        assert prices[2]["level"] == "NORMAL"
+        assert prices[2]["total"] > prices[1]["total"], "Price should go UP at this transition"
+
+        # Check second transition (NORMAL -> CHEAP at index 3->4)
+        assert prices[3]["level"] == "NORMAL"
+        assert prices[4]["level"] == "CHEAP"
+        assert prices[4]["total"] < prices[3]["total"], "Price should go DOWN at this transition"
+
+
+class TestConnectSegmentsOutput:
+    """Test the expected output format with connect_segments enabled."""
+
+    def test_transition_point_down_has_lower_price(self) -> None:
+        """
+        When price goes DOWN at boundary, the transition point should have the lower price.
+
+        This creates a visual line going downward from the current segment level.
+        """
+        current_price = 0.20
+        next_price = 0.12
+
+        # With connect_segments=True and price going down:
+        # The transition point should use next_price (lower price)
+        transition_price = min(current_price, next_price)
+
+        assert transition_price == next_price
+        assert transition_price == 0.12
+
+    def test_transition_point_up_has_current_price(self) -> None:
+        """
+        When price goes UP at boundary, the hold point should have current price.
+
+        This creates a visual hold at current level before the gap.
+        """
+        current_price = 0.11
+        next_price = 0.20
+
+        # With connect_segments=True and price going up:
+        # The hold point should use current_price (extend current level)
+        hold_price = min(current_price, next_price)
+
+        assert hold_price == current_price
+        assert hold_price == 0.11
+
+
+class TestSegmentBoundaryDetection:
+    """Test detection of segment boundaries."""
+
+    def test_same_level_no_boundary(self) -> None:
+        """Intervals with same level should not create boundary."""
+        interval_value = "CHEAP"
+        next_value = "CHEAP"
+        is_boundary = next_value != interval_value
+        assert not is_boundary
+
+    def test_different_level_creates_boundary(self) -> None:
+        """Intervals with different level should create boundary."""
+        interval_value = "CHEAP"
+        next_value = "NORMAL"
+        is_boundary = next_value != interval_value
+        assert is_boundary
+
+    def test_filter_match_check(self) -> None:
+        """Test that filter matching works correctly."""
+        filter_values = ["CHEAP"]
+        interval_value = "CHEAP"
+        next_value = "NORMAL"
+
+        matches_filter = interval_value in filter_values
+        assert matches_filter, "CHEAP should match filter"
+
+        next_matches = next_value in filter_values
+        assert not next_matches, "NORMAL should not match filter"
+
+
+class TestPriceConversion:
+    """Test price conversion logic used in connect_segments."""
+
+    def test_minor_currency_conversion(self) -> None:
+        """Test conversion to minor currency (cents/øre)."""
+        price = 0.12  # EUR
+        minor_currency = True
+        converted = round(price * 100, 2) if minor_currency else round(price, 4)
+        assert converted == 12.0, "0.12 EUR should be 12 cents"
+
+    def test_major_currency_rounding(self) -> None:
+        """Test major currency precision."""
+        price = 0.123456
+        minor_currency = False
+        converted = round(price * 100, 2) if minor_currency else round(price, 4)
+        assert converted == 0.1235, "Should round to 4 decimal places"
+
+    def test_custom_rounding(self) -> None:
+        """Test custom decimal rounding."""
+        price = 0.12345
+        converted = round(price, 4)
+        round_decimals = 2
+        final = round(converted, round_decimals)
+        assert final == 0.12, "Should round to 2 decimal places"