simplify tests

frontend/src/constants.ts

@@ -11,20 +11,20 @@ export const DATA_TYPES = new Set([
 export const SOCKET_WIDGET_TYPES = new Set(['FLOAT', 'INT']);
 
 export const TYPE_COLORS: Record<string, string> = {
-  DATA_FIELD:    '#0800ff',
+  DATA_FIELD:    '#7d8bdc',
-  IMAGE:         '#00ff08',
+  IMAGE:         '#69cc6c',
   LINE:          '#ffb300',
-  RECORD_TABLE: '#ff0000',
+  RECORD_TABLE: '#cf6868',
-  DATA_TABLE:  '#fbff00',
+  DATA_TABLE:  '#cbcd67',
-  COORD:         '#ea00ff',
+  COORD:         '#bb65c2',
-  COORDPAIR:     '#f0cbff',
+  COORDPAIR:     '#bababa',
-  FLOAT:         '#00bfff',
+  FLOAT:         '#76bcd4',
-  INT:           '#ffffff',
+  INT:           '#cf8e8e',
-  ANNOTATION_SOURCE: '#00ffbf',
+  ANNOTATION_SOURCE: '#79cab6',
-  COLORMAP:      '#000000',
+  COLORMAP:      '#905454',
   MESH_MODEL:    '#6e659e',
-  FONT:          '#936991',
+  FONT:          '#cccf7f',
-  FILE_PATH:     '#f1d19b',
+  FILE_PATH:     '#b87f7f',
   DIRECTORY:     '#90d294',
 };
 

scripts/fft_visual.py

@@ -2,7 +2,7 @@
 Generate test images and their FFT outputs for visual comparison with Gwyddion.
 Saves PNG files to tests/output/.
 
-Run: .venv/bin/python -m tests.test_fft_visual
+Run from project root: .venv/bin/python scripts/fft_visual.py
 """
 import sys
 import os
@@ -12,7 +12,7 @@ sys.path.insert(0, ".")
 from backend.data_types import DataField, datafield_to_uint8, encode_preview
 from backend.nodes.fft_2d import FFT2D
 
-OUT_DIR = os.path.join(os.path.dirname(__file__), "output")
+OUT_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "tests", "output")
 os.makedirs(OUT_DIR, exist_ok=True)
 
 

tests/node_tests/coordinate.py

@@ -1,14 +0,0 @@
-def test_coordinate():
-    from backend.nodes.coordinate import Coordinate
-
-    node = Coordinate()
-
-    result = node.process(x=0.3, y=0.7)
-    assert len(result) == 1
-    assert result[0] == (0.3, 0.7)
-
-    result_zero = node.process(x=0.0, y=0.0)
-    assert result_zero[0] == (0.0, 0.0)
-
-    result_one = node.process(x=1.0, y=1.0)
-    assert result_one[0] == (1.0, 1.0)

tests/node_tests/number.py

@@ -1,10 +0,0 @@
-def test_number():
-    from backend.nodes.number import Number
-
-    node = Number()
-
-    result = node.process(value=1.25)
-    assert result == (1.25,)
-
-    result_neg = node.process(value=-3.5)
-    assert result_neg == (-3.5,)

tests/test_fft.py

@@ -10,7 +10,6 @@ import numpy as np
 sys.path.insert(0, ".")
 from backend.data_types import DataField
 from backend.nodes.fft_2d import FFT2D
-from backend.nodes.fft_2d_inverse import FFT2DInverse
 
 
 def make_field(data, xreal=1e-6, yreal=1e-6):
@@ -247,91 +246,6 @@ def test_log_magnitude_visual_range():
     print("  PASS\n")
 
 
-def test_inverse_fft_reconstructs_from_magnitude_and_phase():
-    """Magnitude + phase from FFT2D should reconstruct the original image."""
-    print("=== Test: Inverse FFT from magnitude + phase ===")
-    rng = np.random.default_rng(123)
-    data = rng.standard_normal((64, 96))
-    field = make_field(data, xreal=2.4e-6, yreal=1.6e-6)
-
-    fft_node = FFT2D()
-    ifft_node = FFT2DInverse()
-
-    _, magnitude, phase, _ = fft_node.process(field, windowing="none", level="none")
-    reconstructed, = ifft_node.process(magnitude, representation="magnitude", phase=phase)
-
-    max_err = np.max(np.abs(reconstructed.data - field.data))
-    print(f"  Reconstruction max error: {max_err:.3e}")
-    assert reconstructed.domain == "spatial"
-    assert reconstructed.data.shape == field.data.shape
-    assert np.isclose(reconstructed.xreal, field.xreal)
-    assert np.isclose(reconstructed.yreal, field.yreal)
-    assert max_err < 1e-9, f"Expected near-exact reconstruction, got {max_err}"
-    print("  PASS\n")
-
-
-def test_inverse_fft_reconstructs_from_log_magnitude_and_phase():
-    """log(|F|) + phase should also reconstruct after expm1 inversion."""
-    print("=== Test: Inverse FFT from log magnitude + phase ===")
-    y, x = np.mgrid[0:72, 0:80] / 80.0
-    data = (
-        0.8 * np.sin(2 * np.pi * 6 * x)
-        + 0.35 * np.cos(2 * np.pi * 9 * y)
-        + 0.15 * np.sin(2 * np.pi * (4 * x + 3 * y))
-    )
-    field = make_field(data, xreal=1.6e-6, yreal=1.44e-6)
-
-    fft_node = FFT2D()
-    ifft_node = FFT2DInverse()
-
-    log_magnitude, _, phase, _ = fft_node.process(field, windowing="none", level="none")
-    reconstructed, = ifft_node.process(log_magnitude, representation="log_magnitude", phase=phase)
-
-    rms_err = np.sqrt(np.mean((reconstructed.data - field.data) ** 2))
-    print(f"  Reconstruction RMS error: {rms_err:.3e}")
-    assert rms_err < 1e-9, f"Expected near-exact reconstruction, got {rms_err}"
-    print("  PASS\n")
-
-
-def test_inverse_fft_reconstructs_from_psdf_and_phase():
-    """PSDF + phase should reconstruct after undoing PSDF scaling."""
-    print("=== Test: Inverse FFT from PSDF + phase ===")
-    rng = np.random.default_rng(321)
-    data = rng.standard_normal((48, 64))
-    field = make_field(data, xreal=3.2e-6, yreal=2.4e-6)
-
-    fft_node = FFT2D()
-    ifft_node = FFT2DInverse()
-
-    _, _, phase, psdf = fft_node.process(field, windowing="none", level="none")
-    reconstructed, = ifft_node.process(psdf, representation="psdf", phase=phase)
-
-    max_err = np.max(np.abs(reconstructed.data - field.data))
-    print(f"  Reconstruction max error: {max_err:.3e}")
-    assert reconstructed.si_unit_z == field.si_unit_z
-    assert max_err < 1e-8, f"Expected near-exact reconstruction, got {max_err}"
-    print("  PASS\n")
-
-
-def test_inverse_fft_zero_phase_mode_returns_valid_image():
-    """Spectrum-only inversion should return a finite spatial image with the right shape."""
-    print("=== Test: Inverse FFT zero-phase mode ===")
-    data = np.sin(2 * np.pi * 5 * np.mgrid[0:64, 0:64][1] / 64.0)
-    field = make_field(data, xreal=1e-6, yreal=1e-6)
-
-    fft_node = FFT2D()
-    ifft_node = FFT2DInverse()
-
-    _, magnitude, _, _ = fft_node.process(field, windowing="none", level="none")
-    reconstructed, = ifft_node.process(magnitude, representation="magnitude")
-
-    print(f"  Output shape: {reconstructed.data.shape}")
-    assert reconstructed.domain == "spatial"
-    assert reconstructed.data.shape == field.data.shape
-    assert np.all(np.isfinite(reconstructed.data))
-    print("  PASS\n")
-
-
 if __name__ == "__main__":
     test_dc_removal()
     test_single_frequency()
@@ -341,8 +255,4 @@ if __name__ == "__main__":
     test_plane_subtraction()
     test_non_square()
     test_log_magnitude_visual_range()
-    test_inverse_fft_reconstructs_from_magnitude_and_phase()
-    test_inverse_fft_reconstructs_from_log_magnitude_and_phase()
-    test_inverse_fft_reconstructs_from_psdf_and_phase()
-    test_inverse_fft_zero_phase_mode_returns_valid_image()
     print("All tests passed!")