removed unused commands
This commit is contained in:
@@ -8,11 +8,7 @@ from linemeasurement.osa import open_file
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from linemeasurement.plotapp import PlotApp
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from linemeasurement.plotapp import PlotApp
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from linemeasurement.profiles import (
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from linemeasurement.profiles import (
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VoigtFitResult,
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VoigtFitResult,
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add_noise,
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convolve,
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elevated_gaussian,
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elevated_gaussian,
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fft_gaussian,
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fft_lorentzian,
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fft_voigt,
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fft_voigt,
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gaussian,
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gaussian,
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linear_direct_voigt_fit,
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linear_direct_voigt_fit,
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@@ -36,6 +32,11 @@ def alert(s: str):
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dlg.exec()
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dlg.exec()
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def file_as_title(s) -> str:
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p = Path(s).resolve()
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return f"LineMeasurement - {p.parent.name}/{p.name}"
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def setup_axes(n: int, lims=(-10, 10)) -> tuple[np.ndarray, float, np.ndarray, float]:
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def setup_axes(n: int, lims=(-10, 10)) -> tuple[np.ndarray, float, np.ndarray, float]:
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"""Creates a time-like and a frequency-like array and returns their respective spacing"""
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"""Creates a time-like and a frequency-like array and returns their respective spacing"""
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x, dx = np.linspace(*lims, n, retstep=True)
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x, dx = np.linspace(*lims, n, retstep=True)
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@@ -67,13 +68,13 @@ def open_new_measurement(
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if not file.exists():
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if not file.exists():
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alert(f"{file} does not exist")
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alert(f"{file} does not exist")
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return None
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raise FileNotFoundError(file)
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try:
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try:
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x, y = open_file(file)
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x, y = open_file(file)
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except Exception:
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except Exception:
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alert(f"Could not load {file}")
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alert(f"Could not load {file}")
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return None
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raise
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return file, x, y
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return file, x, y
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@@ -84,155 +85,31 @@ def default_values() -> tuple[np.ndarray, np.ndarray]:
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return raw_wl, raw_intens
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return raw_wl, raw_intens
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@click.group()
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def main():
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pass
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@main.command(help="fit a lorentzian with a gaussian")
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def demo1():
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x = np.linspace(-10, 10, 501)
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with PlotApp(
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FWHM=np.geomspace(0.1, 10),
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relative_noise=np.linspace(0, 2),
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absolute_noise=[0, *np.geomspace(0.001, 1)],
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) as app:
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app.set_antialiasing(True)
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app.params["FWHM"].value = 3.7
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@app.update
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def draw(FWHM, relative_noise, absolute_noise):
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lo = lorentzian(x, 1, FWHM, 0)
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lo = add_noise(lo, absolute_noise, relative_noise * 0.04)
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fit = single_func_fit(x, lo, gaussian)
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app[0].set_line_data("Lorentzian", x, lo, width=2)
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app[0].set_line_data(
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"gaus fit", x, fit.curve, width=2, label=f"Gaussian fit : FWHM = {fit.width}"
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)
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@main.command(name="default", help="illustrate the influence of noises and fit a voigt profile")
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def demo2():
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with PlotApp(
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n=np.arange(256, 2046),
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lorentz_fwhm=np.geomspace(0.1, 1),
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gauss_fwhm=np.linspace(1, 10),
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relative_noise=np.linspace(0, 2),
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absolute_noise=[0, *np.geomspace(1e-6, 1, 201)],
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) as app:
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app.set_antialiasing(True)
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v_ax = app["Voigt"]
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l_ax = app["Lorentz"]
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g_ax = app["Gauss"]
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l_ax.link_x(v_ax)
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g_ax.link_x(v_ax)
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app.params["gauss_fwhm"].value = 5
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app.params["n"].value = 1024
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app.params_layout.setSpacing(0)
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@app.update
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def draw(n, lorentz_fwhm, gauss_fwhm, absolute_noise, relative_noise):
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x, dx, f, df = setup_axes(n, (-20, 20))
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gaus = gaussian(x, 1, gauss_fwhm, 0)
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lore = lorentzian(x, 1, lorentz_fwhm, 0)
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g_ax.set_line_data("Gaussian", x, gaus / gaus.max(), width=2)
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l_ax.set_line_data("Lorentz", x, lore / lore.max(), width=2)
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conv = convolve(gaus, lore)
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conv /= conv.max()
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conv_noise = add_noise(conv, absolute_noise, relative_noise * 0.1)
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gaus_noise = add_noise(gaus, absolute_noise, relative_noise * 0.1)
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v_ax.set_line_data("Voigt", x, conv, width=2)
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v_ax.set_line_data("Noisy Voigt", x, conv_noise, width=2)
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g_ax.set_line_data("Noisy Gaussian", x, gaus_noise, width=2)
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lin_fit = linear_direct_voigt_fit(x, conv_noise)
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log_fit = log_direct_voigt_fit(x, conv_noise)
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transfo = np.fft.fft(np.fft.fftshift(conv_noise)).real
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fft_fit = linear_fft_voigt_fit(f, transfo, x, dx)
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for fit in lin_fit, log_fit, fft_fit:
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display_fit(x, fit)
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def display_fit(x: np.ndarray, fit: VoigtFitResult):
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v_ax.set_line_data(fit.name, x, fit.curve)
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g_ax.set_line_data(
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fit.name + "gauss",
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x,
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gaussian(x, fit.amp, fit.gaussian_width, 0),
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label=f"{fit.name} - Gaussian {fit.gaussian_width:.2f}",
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width=1.5,
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)
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l_ax.set_line_data(
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fit.name + "loren",
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x,
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lorentzian(x, fit.amp, fit.lorentzian_width, 0),
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label=f"{fit.name} - Lorentzian {fit.lorentzian_width:.2f}",
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width=1.5,
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)
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@main.command(help="Explore fft fitting")
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def demo3():
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x, dx, f, df = setup_axes(1001, (-20, 20))
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with PlotApp(
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lorentz_fwhm=np.geomspace(0.1, 1),
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gauss_fwhm=np.linspace(1, 10),
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relative_noise=np.linspace(0, 2),
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absolute_noise=[0, *np.geomspace(1e-6, 1, 201)],
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) as app:
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app.set_antialiasing(True)
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ax = app[0]
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ind = np.argsort(f)
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@app.update
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def draw(lorentz_fwhm, gauss_fwhm, absolute_noise, relative_noise):
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gaus_clean = gaussian(x, 1, gauss_fwhm, 0)
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lore_clean = lorentzian(x, 1, lorentz_fwhm, 0)
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voig_clean = convolve(gaus_clean, lore_clean)
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gaus = add_noise(gaus_clean, absolute_noise, relative_noise * 0.1)
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lore = add_noise(lore_clean, absolute_noise, relative_noise * 0.1)
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voig = add_noise(voig_clean, absolute_noise, relative_noise * 0.1)
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gaus_f = np.fft.fft(np.fft.fftshift(gaus)).real
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lore_f = np.fft.fft(np.fft.fftshift(lore)).real
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voig_f = np.fft.fft(np.fft.fftshift(voig)).real
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ax.set_line_data("Transformed Gaussian", f[ind], gaus_f[ind])
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ax.set_line_data("Transformed Lorentz", f[ind], lore_f[ind])
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ax.set_line_data("Transformed Voigt", f[ind], voig_f[ind])
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gaus_ff = fft_gaussian(f, dx, 1, gauss_fwhm)
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lore_ff = fft_lorentzian(f, dx, 1, lorentz_fwhm)
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voig_ff = fft_voigt(f, dx, gauss_fwhm, lorentz_fwhm) * voig_clean.sum()
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ax.set_line_data("Expected Gaussian", f[ind], gaus_ff[ind], width=1)
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ax.set_line_data("Expected Lorentz", f[ind], lore_ff[ind], width=1)
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ax.set_line_data("Expected Voigt", f[ind], voig_ff[ind], width=1)
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@click.option("--all/--no-all", "show_all", default=True, is_flag=True)
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@click.option("--all/--no-all", "show_all", default=True, is_flag=True)
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@click.option("--file", "-f", type=click.Path())
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@click.option("--file", "-f", type=click.Path())
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@main.command(name="fit")
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@click.command()
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def fit_measurement(file, show_all):
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def main(file, show_all):
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_ = pg.mkQApp()
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app = pg.mkQApp()
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raw_wl, raw_intens = default_values()
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def _load_new_measurement():
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nonlocal raw_wl, raw_intens, file
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res = open_new_measurement(file)
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if res is not None:
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file, raw_wl, raw_intens = res
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if file is None:
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if file is None:
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_load_new_measurement()
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while True:
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try:
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res = open_new_measurement(file)
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except Exception:
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continue
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if res is None:
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app.quit()
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return
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else:
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file, raw_wl, raw_intens = res
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break
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else:
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else:
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try:
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try:
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raw_wl, raw_intens = open_file(file)
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raw_wl, raw_intens = open_file(file)
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except Exception:
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except Exception:
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alert(f"Could not open {file}")
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print(f"Could not load {file}")
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app.quit()
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return
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with PlotApp(
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with PlotApp(
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center_wl=np.linspace(raw_wl.min(), raw_wl.max(), 8192),
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center_wl=np.linspace(raw_wl.min(), raw_wl.max(), 8192),
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@@ -241,10 +118,17 @@ def fit_measurement(file, show_all):
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) as app:
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) as app:
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def file_change():
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def file_change():
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_load_new_measurement()
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nonlocal raw_wl, raw_intens, file
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update_params()
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try:
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res = open_new_measurement(file)
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except Exception:
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return
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if res is not None:
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file, raw_wl, raw_intens = res
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update_params()
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def update_params():
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def update_params():
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app.window.setWindowTitle(file_as_title(file))
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app.params["span"].set_values(np.linspace(0.001, raw_wl[-1] - raw_wl[0], 1024))
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app.params["span"].set_values(np.linspace(0.001, raw_wl[-1] - raw_wl[0], 1024))
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app.params["center_wl"].set_values(np.linspace(raw_wl.min(), raw_wl.max(), 8192))
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app.params["center_wl"].set_values(np.linspace(raw_wl.min(), raw_wl.max(), 8192))
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app.params["span"].value = app.params["span"].values()[-1]
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app.params["span"].value = app.params["span"].values()[-1]
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@@ -331,30 +215,5 @@ def fit_measurement(file, show_all):
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)
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)
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@main.command(name="test", help="test scaling of voigt profile")
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def test_amp():
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x, dx, f, df = setup_axes(1001, (-20, 20))
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with PlotApp(
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lorentz_fwhm=np.geomspace(0.1, 1), gauss_fwhm=np.linspace(1, 10), amp=np.linspace(1, 7)
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) as app:
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app.set_antialiasing(True)
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ax1 = app["Main"]
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ax2 = app["Fourrier"]
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ind = np.argsort(f)
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@app.update
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def draw(lorentz_fwhm, gauss_fwhm, amp):
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vo = voigt(x, amp, gauss_fwhm, lorentz_fwhm)
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trans = np.fft.fft(np.fft.fftshift(vo))
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expected = fft_voigt(f, dx, amp, gauss_fwhm, lorentz_fwhm)
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back_transformed = np.fft.fftshift(np.fft.ifft(expected).real)
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ax1.set_line_data("original", x, vo)
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ax1.set_line_data("back tranformed", x, back_transformed)
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ax2.set_line_data("expected", f[ind], expected[ind])
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ax2.set_line_data("original transformed", f[ind], trans[ind].real)
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if __name__ == "__main__":
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if __name__ == "__main__":
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main()
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main()
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Reference in New Issue
Block a user