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116 lines
4 KiB
Python
116 lines
4 KiB
Python
from dataclasses import dataclass
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from typing import Tuple, List
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import numpy as np
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from scipy.interpolate import RectBivariateSpline, CubicSpline
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@dataclass
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class Measurepoint():
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def __init__(self, coord: Tuple[float, float], filename: str, name: str):
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self.coord = coord
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self.filename = filename
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self.name = name
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self.brightnesses = self.load_horizontal_sky_brightness()
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self.brightnesses2d = self.load_2d_sky_brightness()
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self.spline = self.load_spline(self.brightnesses2d)
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self.horizon_spline = self.load_horizon_spline()
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def load_horizontal_sky_brightness(self) -> List[float]:
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brightnesses = []
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mags = []
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with open(f"../rohdaten/{self.filename} - Horizontal Sky Brightness Graph.csv") as f:
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for _ in range(29):
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next(f)
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for line in f:
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if line == "\n":
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continue
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azimuth, sky_brightness, luminance, cct = map(float, line.split(","))
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brightnesses.append(luminance)
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mags.append(10 ** (-0.4 * sky_brightness) * 108e6)
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# plt.plot(range(len(brightnesses)), brightnesses)
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# plt.show()
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assert len(brightnesses) == 360
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brightnesses = np.array(brightnesses)
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# mags = np.array(mags)
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# print(brightnesses, mags)
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# print(brightnesses / mags)
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# plt.plot(brightnesses, mags)
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# plt.show()
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brightnesses = np.roll(brightnesses, 180)
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return brightnesses
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@property
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def filename2d(self):
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return f"../rohdaten/{self.filename}-2D-matrix.csv"
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def load_2d_sky_brightness(self):
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data = np.loadtxt(
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self.filename2d,
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skiprows=241,
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delimiter=",",
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max_rows=92,
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usecols=range(1, 361)
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)
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data = np.roll(data, 180, axis=1)
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data = np.flipud(data)
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return 10 ** (-0.4 * data) * 108e6
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def load_horizon_spline(self) -> CubicSpline:
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horizon = np.loadtxt(
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self.filename2d,
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skiprows=57,
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delimiter=",",
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max_rows=237 - 58,
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usecols=(0, 1)
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)
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horizon[:, 1] = 90 - horizon[:, 1] # degrees are upside down
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cs = CubicSpline(horizon[:, 0], horizon[:, 1])
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# x = np.linspace(0, 360, 1000)
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# plt.plot(horizon[:, 0], horizon[:, 1])
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# plt.plot(x, cs(x))
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# plt.show()
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return cs
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def load_spline(self, data2d: np.ndarray) -> RectBivariateSpline:
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x, y = np.arange(data2d.shape[0]), np.arange(data2d.shape[1])
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return RectBivariateSpline(x, y, data2d)
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points = [
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Measurepoint(filename="IMG_0172", name="Mistelbach-Süd", coord=(48.5232506, 16.5654793)),
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Measurepoint(filename="IMG_0176", name="Mistelbach-West", coord=(48.5747355, 16.498188)),
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Measurepoint(filename="IMG_0182", name="Mistelbach-Nordwest", coord=(48.5945091, 16.5278206)),
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Measurepoint(filename="IMG_0186", name="Mistelbach-Nord", coord=(48.6069419, 16.5606171)),
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Measurepoint(filename="IMG_0190", name="Mistelbach-Nordost", coord=(48.5913925, 16.6311699)),
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Measurepoint(filename="IMG_0194", name="Mistelbach-Südost", coord=(48.5471377, 16.6404243)),
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]
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# interpolator = points[0].load_interpolation(points[0].brightnesses2d)
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# zoom = 5
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# z = np.zeros((93 * zoom, 360 * zoom))
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# for x in range(93 * zoom):
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# print(x)
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# for y in range(360 * zoom):
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# z[x, y] = interpolator(x / zoom, y / zoom)
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# plt.imshow(z, origin="lower")
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# plt.colorbar()
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# plt.show()
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#
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# plt.imshow(points[0].brightnesses2d, origin="lower")
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# plt.colorbar()
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# plt.show()
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bounds = {
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"lon": {
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"upper": max(p.coord[0] for p in points) + 0.2,
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"lower": min(p.coord[0] for p in points) - 0.2
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},
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"lat": {
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"upper": max(p.coord[1] for p in points) + 0.2,
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"lower": min(p.coord[1] for p in points) - 0.2
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}
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}
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# bounds["x"]["width"] = bounds["x"]["upper"] - bounds["x"]["lower"]
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# bounds["y"]["width"] = bounds["y"]["upper"] - bounds["y"]["lower"]
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