remove stale tests
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@@ -219,7 +219,7 @@ class ExecutionEngine:
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) -> None:
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"""Wire up broadcast callbacks on display node classes."""
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from backend.nodes.display import PreviewImage, PrintTable, View3D, ValueDisplay, Markup
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from backend.nodes.analysis import CrossSection, LineCursors, TableMath, Stats, Histogram
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from backend.nodes.analysis import CrossSection, LineCursors, Stats, Histogram
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from backend.nodes.modify import CropResizeField, RotateField
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from backend.nodes.mask import ThresholdMask, MaskMorphology, MaskInvert, MaskCombine, DrawMask
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from backend.nodes.io import SaveImage, Image, ImageDemo
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@@ -233,7 +233,6 @@ class ExecutionEngine:
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View3D._broadcast_mesh_fn = on_mesh
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PrintTable._broadcast_table_fn = on_table
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ValueDisplay._broadcast_value_fn = on_value
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TableMath._broadcast_value_fn = on_value
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Stats._broadcast_value_fn = on_value
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Histogram._broadcast_overlay_fn = on_overlay
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CrossSection._broadcast_overlay_fn = on_overlay
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@@ -248,11 +247,11 @@ class ExecutionEngine:
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def _set_node_id_on_display(self, cls: type, node_id: str) -> None:
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"""Inform display nodes of their current node_id for WS tagging."""
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from backend.nodes.display import PreviewImage, PrintTable, View3D, ValueDisplay, Markup
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from backend.nodes.analysis import CrossSection, LineCursors, TableMath, Stats, Histogram
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from backend.nodes.analysis import CrossSection, LineCursors, Stats, Histogram
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from backend.nodes.modify import CropResizeField, RotateField
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from backend.nodes.mask import ThresholdMask, MaskMorphology, MaskInvert, MaskCombine, DrawMask
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from backend.nodes.io import Image, ImageDemo, SaveImage
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if cls in (PreviewImage, PrintTable, View3D, ValueDisplay, TableMath, Stats, Histogram, CrossSection, LineCursors, CropResizeField, RotateField, Markup,
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if cls in (PreviewImage, PrintTable, View3D, ValueDisplay, Stats, Histogram, CrossSection, LineCursors, CropResizeField, RotateField, Markup,
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ThresholdMask, MaskMorphology, MaskInvert, MaskCombine, DrawMask,
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Image, ImageDemo, SaveImage):
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cls._current_node_id = node_id
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@@ -651,7 +651,7 @@ class CrossSection:
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# ---------------------------------------------------------------------------
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# LineMath — single scalar measurement from a LINE profile
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# Shared line-stat helpers used by Stats
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# ---------------------------------------------------------------------------
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def _safe_rq(d):
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@@ -755,7 +755,7 @@ def _op_da(z):
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# ---------------------------------------------------------------------------
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# TableMath — scalar measurement from a numeric record-table column
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# Shared record-table helpers used by Stats
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# ---------------------------------------------------------------------------
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TABLE_OPS: dict[str, Callable[[np.ndarray], float]] = {
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@@ -879,9 +879,9 @@ def resolve_table_column_name(table: list, column: str) -> str:
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if len(numeric_columns) == 1:
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return numeric_columns[0]
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if not numeric_columns:
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raise ValueError("Table Math could not find any numeric columns in the input table.")
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raise ValueError("Stats could not find any numeric columns in the input table.")
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raise ValueError(
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"Table Math found multiple numeric columns; set the column name explicitly."
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"Stats found multiple numeric columns; set the column name explicitly."
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)
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@@ -830,14 +830,14 @@ def test_particle_analysis():
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def test_load_file():
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print("=== Test: Image ===")
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from backend.nodes.io import Image
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from PIL import Image
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node = Image()
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from backend.nodes.io import Image as ImageNode
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from PIL import Image as PILImage
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node = ImageNode()
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with tempfile.TemporaryDirectory() as tmpdir:
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# Test loading a grayscale PNG → single DataField output
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arr = np.random.default_rng(1).integers(0, 256, (48, 64), dtype=np.uint8)
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img = Image.fromarray(arr, mode="L")
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img = PILImage.fromarray(arr, mode="L")
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path = os.path.join(tmpdir, "test_gray.png")
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img.save(path)
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@@ -849,7 +849,7 @@ def test_load_file():
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# Test loading an RGB PNG (should average to grayscale)
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arr_rgb = np.random.default_rng(2).integers(0, 256, (32, 32, 3), dtype=np.uint8)
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img_rgb = Image.fromarray(arr_rgb, mode="RGB")
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img_rgb = PILImage.fromarray(arr_rgb, mode="RGB")
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path_rgb = os.path.join(tmpdir, "test_rgb.png")
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img_rgb.save(path_rgb)
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@@ -1333,17 +1333,17 @@ def test_load_file_unsupported():
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def test_load_file_warning():
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print("=== Test: Image warning for uncalibrated data ===")
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from backend.nodes.io import Image
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from PIL import Image
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from backend.nodes.io import Image as ImageNode
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from PIL import Image as PILImage
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node = Image()
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node = ImageNode()
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warnings = []
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Image._broadcast_warning_fn = lambda nid, msg: warnings.append(msg)
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Image._current_node_id = "test"
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ImageNode._broadcast_warning_fn = lambda nid, msg: warnings.append(msg)
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ImageNode._current_node_id = "test"
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with tempfile.TemporaryDirectory() as tmpdir:
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arr = np.random.default_rng(10).integers(0, 256, (16, 16), dtype=np.uint8)
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img = Image.fromarray(arr)
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img = PILImage.fromarray(arr)
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path = os.path.join(tmpdir, "test.png")
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img.save(path)
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@@ -1352,7 +1352,7 @@ def test_load_file_warning():
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assert len(warnings) == 1
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assert "Uncalibrated" in warnings[0]
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Image._broadcast_warning_fn = None
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ImageNode._broadcast_warning_fn = None
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print(" PASS\n")
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@@ -1724,159 +1724,6 @@ def test_fft2d():
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print(" PASS\n")
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# =========================================================================
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# Analysis — LineMath
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# =========================================================================
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def test_line_math():
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print("=== Test: LineMath ===")
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from backend.nodes.analysis import LineMath
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node = LineMath()
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line = np.array([1.0, 2.0, 3.0, 4.0, 5.0])
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# Basic stats
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table, = node.process(line, operation="min")
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assert table[0]["value"] == 1.0
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table, = node.process(line, operation="max")
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assert table[0]["value"] == 5.0
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table, = node.process(line, operation="mean")
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assert table[0]["value"] == 3.0
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table, = node.process(line, operation="median")
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assert table[0]["value"] == 3.0
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table, = node.process(line, operation="sum")
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assert table[0]["value"] == 15.0
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table, = node.process(line, operation="range")
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assert table[0]["value"] == 4.0
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table, = node.process(line, operation="length")
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assert table[0]["value"] == 5.0
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# RMS of [1,2,3,4,5]
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table, = node.process(line, operation="rms")
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expected_rms = np.sqrt(np.mean(line ** 2))
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assert abs(table[0]["value"] - expected_rms) < 1e-10
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# Roughness parameters
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table, = node.process(line, operation="Ra")
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d = line - line.mean()
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expected_ra = float(np.mean(np.abs(d)))
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assert abs(table[0]["value"] - expected_ra) < 1e-10
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table, = node.process(line, operation="Rq")
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expected_rq = float(np.sqrt(np.mean(d ** 2)))
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assert abs(table[0]["value"] - expected_rq) < 1e-10
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# Rp = max of (z - mean)
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table, = node.process(line, operation="Rp")
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assert abs(table[0]["value"] - d.max()) < 1e-10
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# Rv = -(min of (z - mean))
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table, = node.process(line, operation="Rv")
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assert abs(table[0]["value"] - (-d.min())) < 1e-10
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# Rt = Rp + Rv = range of (z - mean)
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table, = node.process(line, operation="Rt")
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assert abs(table[0]["value"] - (d.max() - d.min())) < 1e-10
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# Constant line: roughness parameters should all be zero
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const_line = np.ones(10) * 7.0
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table, = node.process(const_line, operation="Ra")
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assert table[0]["value"] == 0.0
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table, = node.process(const_line, operation="Rq")
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assert table[0]["value"] == 0.0
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table, = node.process(const_line, operation="Rsk")
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assert table[0]["value"] == 0.0
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table, = node.process(const_line, operation="Rku")
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assert table[0]["value"] == 0.0
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# Slope-based: Dq and Da
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table, = node.process(line, operation="Dq")
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dz = np.diff(line)
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expected_dq = float(np.sqrt(np.mean(dz * dz)))
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assert abs(table[0]["value"] - expected_dq) < 1e-10
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table, = node.process(line, operation="Da")
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expected_da = float(np.mean(np.abs(dz)))
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assert abs(table[0]["value"] - expected_da) < 1e-10
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print(" PASS\n")
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# =========================================================================
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# Analysis — TableMath
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# =========================================================================
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def test_table_math():
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print("=== Test: TableMath ===")
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from backend.nodes.analysis import TableMath
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node = TableMath()
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captured = []
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TableMath._broadcast_value_fn = lambda node_id, value: captured.append((node_id, value))
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TableMath._current_node_id = "test"
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table = RecordTable([
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{"label": "a", "value": 1.0, "other": 10},
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{"label": "b", "value": 5.0, "other": 20},
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{"label": "c", "value": "3.0", "other": 30},
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{"label": "d", "value": "bad", "other": 40},
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])
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result, = node.process(table, column="value", operation="max")
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assert result == 5.0
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assert captured[-1] == ("test", 5.0)
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result, = node.process(table, column="value", operation="min")
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assert result == 1.0
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result, = node.process(table, column="value", operation="avg")
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assert np.isclose(result, 3.0)
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result, = node.process(table, column="value", operation="median")
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assert np.isclose(result, 3.0)
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result, = node.process(table, column="other", operation="sum")
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assert result == 100.0
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result, = node.process(table, column="other", operation="count")
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assert result == 4.0
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# Blank column name should fall back to the common "value" column.
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result, = node.process(table, column="", operation="range")
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assert result == 4.0
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try:
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node.process(table, column="missing", operation="max")
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raise AssertionError("Expected missing numeric column to raise ValueError")
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except ValueError:
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pass
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try:
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node.process([{"label": "only text"}], column="label", operation="max")
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raise AssertionError("Expected non-numeric column to raise ValueError")
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except ValueError:
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pass
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try:
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node.process(
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MeasureTable([{"quantity": "A position", "value": 1.0, "unit": "m"}]),
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column="value",
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operation="max",
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)
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raise AssertionError("Expected measurement table input to raise ValueError")
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except ValueError:
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pass
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TableMath._broadcast_value_fn = None
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print(" PASS\n")
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# =========================================================================
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# Analysis — Stats
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# =========================================================================
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@@ -1894,6 +1741,8 @@ def test_stats():
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result, = node.process(line, operation="mean", column="value")
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assert np.isclose(result, 2.5)
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assert captured[-1] == ("test", {"value": result})
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roughness, = node.process(line, operation="Rq", column="value")
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assert np.isclose(roughness, np.sqrt(np.mean((line - line.mean()) ** 2)))
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table = RecordTable([
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{"name": "a", "value": 3.0, "unit": "m", "other": 10.0},
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@@ -1902,6 +1751,10 @@ def test_stats():
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result, = node.process(table, operation="max", column="value")
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assert result == 7.0
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assert captured[-1] == ("test", {"value": 7.0, "unit": "m"})
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count, = node.process(table, operation="count", column="other")
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assert count == 2.0
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auto_column_range, = node.process(table, operation="range", column="")
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assert auto_column_range == 4.0
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field = make_field(data=np.array([[1.0, 5.0], [2.0, 4.0]], dtype=np.float64))
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result, = node.process(field, operation="range", column="value")
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@@ -1919,6 +1772,12 @@ def test_stats():
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except ValueError:
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pass
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try:
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node.process([{"label": "only text"}], operation="max", column="label")
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raise AssertionError("Expected non-numeric record-table input to raise ValueError")
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except ValueError:
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pass
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try:
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node.process(
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MeasureTable([{"quantity": "min", "value": 1.0, "unit": "m"}]),
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@@ -2008,8 +1867,6 @@ if __name__ == "__main__":
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test_cross_section()
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test_line_cursors()
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test_fft2d()
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test_line_math()
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test_table_math()
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test_stats()
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# Mask
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