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tono/backend/nodes/fft_2d.py

116 lines
4.0 KiB
Python

from __future__ import annotations
import numpy as np
from backend.node_registry import register_node
from backend.data_types import DataField
@register_node(display_name="2D FFT")
class FFT2D:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"field": ("DATA_FIELD",),
"windowing": (["hann", "hamming", "blackman", "none"],),
"level": (["mean", "plane", "none"],),
}
}
RETURN_TYPES = ("DATA_FIELD", "DATA_FIELD", "DATA_FIELD", "DATA_FIELD")
RETURN_NAMES = ("log_magnitude", "magnitude", "phase", "psdf")
FUNCTION = "process"
DESCRIPTION = (
"Compute the 2D FFT with optional windowing and mean/plane subtraction. "
"Outputs log magnitude, magnitude, phase, and PSDF as separate channels. "
"Equivalent to gwy_data_field_2dfft / gwy_data_field_2dpsdf."
)
def process(self, field: DataField, windowing: str, level: str) -> tuple:
data = field.data.copy()
yres, xres = data.shape
if level == "mean":
data -= data.mean()
elif level == "plane":
yy, xx = np.mgrid[0:yres, 0:xres]
xx_f = xx.ravel().astype(np.float64)
yy_f = yy.ravel().astype(np.float64)
zz_f = data.ravel()
A = np.column_stack([np.ones_like(xx_f), xx_f, yy_f])
coeffs, _, _, _ = np.linalg.lstsq(A, zz_f, rcond=None)
plane = (coeffs[0] + coeffs[1] * xx + coeffs[2] * yy)
data -= plane
if windowing != "none":
t_y = (np.arange(yres) + 0.5) / yres
t_x = (np.arange(xres) + 0.5) / xres
if windowing == "hann":
wy = 0.5 - 0.5 * np.cos(2 * np.pi * t_y)
wx = 0.5 - 0.5 * np.cos(2 * np.pi * t_x)
elif windowing == "hamming":
wy = 0.54 - 0.46 * np.cos(2 * np.pi * t_y)
wx = 0.54 - 0.46 * np.cos(2 * np.pi * t_x)
elif windowing == "blackman":
wy = 0.42 - 0.5 * np.cos(2 * np.pi * t_y) + 0.08 * np.cos(4 * np.pi * t_y)
wx = 0.42 - 0.5 * np.cos(2 * np.pi * t_x) + 0.08 * np.cos(4 * np.pi * t_x)
else:
wy = np.ones(yres)
wx = np.ones(xres)
data *= np.outer(wy, wx)
F = np.fft.fftshift(np.fft.fft2(data))
n = xres * yres
magnitude = np.abs(F)
log_magnitude = np.log1p(magnitude)
phase = np.angle(F)
dx = field.xreal / xres
dy = field.yreal / yres
psdf = (magnitude ** 2) * dx * dy / (n * 4.0 * np.pi ** 2)
spatial_freq_xreal = xres / field.xreal
spatial_freq_yreal = yres / field.yreal
angular_freq_xreal = 2.0 * np.pi * xres / field.xreal
angular_freq_yreal = 2.0 * np.pi * yres / field.yreal
return (
DataField(
data=log_magnitude,
xreal=spatial_freq_xreal,
yreal=spatial_freq_yreal,
si_unit_xy="1/m",
si_unit_z=field.si_unit_z,
domain="frequency",
colormap=field.colormap,
),
DataField(
data=magnitude,
xreal=spatial_freq_xreal,
yreal=spatial_freq_yreal,
si_unit_xy="1/m",
si_unit_z=field.si_unit_z,
domain="frequency",
colormap=field.colormap,
),
DataField(
data=phase,
xreal=spatial_freq_xreal,
yreal=spatial_freq_yreal,
si_unit_xy="1/m",
si_unit_z=field.si_unit_z,
domain="frequency",
colormap=field.colormap,
),
DataField(
data=psdf,
xreal=angular_freq_xreal,
yreal=angular_freq_yreal,
si_unit_xy="1/m",
si_unit_z=f"({field.si_unit_z})^2 m^2",
domain="frequency",
colormap=field.colormap,
),
)