From f2a3f95fa8432be8c60ba93cba8e61964a790073 Mon Sep 17 00:00:00 2001 From: saji Date: Thu, 22 Jun 2023 18:29:08 -0500 Subject: [PATCH] move things --- py/.idea/jupyter-settings.xml | 30 + py/notebooks/test_solar.ipynb | 314 +++++++ py/optimus.py | 10 - py/poetry.lock | 1671 ++++++++++++++++++++++++++++++++- py/pyproject.toml | 3 + py/{ => pytelem}/backend.py | 0 py/{ => pytelem}/gui.py | 0 py/pytelem/optimus.py | 578 ++++++++++++ py/{ => pytelem}/pytelem.py | 0 py/{ => pytelem}/skylab.py | 0 10 files changed, 2595 insertions(+), 11 deletions(-) create mode 100644 py/.idea/jupyter-settings.xml create mode 100644 py/notebooks/test_solar.ipynb delete mode 100644 py/optimus.py rename py/{ => pytelem}/backend.py (100%) rename py/{ => pytelem}/gui.py (100%) create mode 100644 py/pytelem/optimus.py rename py/{ => pytelem}/pytelem.py (100%) rename py/{ => pytelem}/skylab.py (100%) diff --git a/py/.idea/jupyter-settings.xml b/py/.idea/jupyter-settings.xml new file mode 100644 index 0000000..dcb4e0c --- /dev/null +++ b/py/.idea/jupyter-settings.xml @@ -0,0 +1,30 @@ + + + + + + + \ No newline at end of file diff --git a/py/notebooks/test_solar.ipynb b/py/notebooks/test_solar.ipynb new file mode 100644 index 0000000..2c7e63f --- /dev/null +++ b/py/notebooks/test_solar.ipynb @@ -0,0 +1,314 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2023-06-21T00:28:49.748311944Z", + "start_time": "2023-06-21T00:28:49.744946948Z" + }, + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" + ] + } + ], + "source": [ + "\n", + "from pytelem.optimus import *\n", + "from jax import jit" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2023-06-21T00:28:50.052452543Z", + "start_time": "2023-06-21T00:28:50.050159245Z" + }, + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'optim' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m ffast \u001b[39m=\u001b[39m jit(optim\u001b[39m.\u001b[39msolar_position)\n", + "\u001b[0;31mNameError\u001b[0m: name 'optim' is not defined" + ] + } + ], + "source": [ + "ffast = jit(optim.solar_position)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "ExecuteTime": { + "end_time": "2023-06-21T00:29:01.075229307Z", + "start_time": "2023-06-21T00:29:01.042571064Z" + }, + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [], + "source": [ + "timestamp = np.array(1687306901)\n", + "timestamps = np.array([1687306901, 1687306902, 1687306903, 1687306906])" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [], + "source": [ + "\n", + "jd = timestamps / 86400.0 + 2440587.5\n", + "jde = jd + DELTA_T / 86400.0\n", + "jce = (jde - 2451545) / 36525\n", + "\n", + "jme = jce / 10\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# todo: make more elegant?\n", + "# TODO: vectorize later? it's kinda complex\n", + "\n", + "# heliocentric longitude\n", + "l_rad = np.zeros_like(timestamp)\n", + "for idx, vec in enumerate(HELIO_L):\n", + " l_rad = l_rad + helio_vector(vec, jme) * jme ** idx\n", + "\n", + "l_rad = l_rad / 10e8\n", + "l_deg = np.rad2deg(l_rad) % 360\n", + "\n", + "# heliocentric latitude\n", + "b_rad = np.zeros_like(timestamp)\n", + "for idx, vec in enumerate(HELIO_B):\n", + " b_rad = b_rad + helio_vector(vec, jme) * jme ** idx\n", + "b_rad = b_rad / 10e8\n", + "b_deg = b_rad % 360\n", + "\n", + "# heliocentric radius\n", + "r_rad = np.zeros_like(timestamp)\n", + "for idx, vec in enumerate(HELIO_R):\n", + " r_rad = r_rad + helio_vector(vec, jme) * jme ** idx\n", + "r_rad = r_rad / 10e8\n", + "r_deg = r_rad % 360\n", + "\n", + "theta = (l_deg + 180) % 360\n", + "beta = -1 * b_deg\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 5)\n" + ] + } + ], + "source": [ + "\n", + "def cubic_poly(a,b,c,d):\n", + " return a + b * jce + c * jce ** 2 + (jce ** 3) / d\n", + "X0 = cubic_poly(297.85036, 445267.111480, -0.0019142, 189474)\n", + "X1 = cubic_poly(357.52772, 35999.050340, -0.0001603, -300000)\n", + "X2 = cubic_poly(134.96298, 477198.867398, 0.0086972, 56250)\n", + "X3 = cubic_poly(93.27191, 483202.017538, -0.0036825, 327270)\n", + "X4 = cubic_poly(125.04452, 1934.136261, 0.0020708, 450000)\n", + "\n", + "X = np.vstack([X0, X1, X2, X3, X4]).T\n", + "print(X.shape)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "nut = NUTATION_ABCD_ARRAY\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(4, 63)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(nut[:,0] + jce[..., np.newaxis] * nut[:,1])" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 5)\n", + "(63, 5)\n", + "d psi shape (4, 63)\n", + "[-0.00333032 -0.00333032 -0.00333032 -0.00333032]\n" + ] + } + ], + "source": [ + "\n", + "print(X.shape)\n", + "print(NUTATION_YTERM_ARRAY.shape)\n", + "d_psi = (nut[:,0] + jce[..., np.newaxis] * nut[:,1]) * np.sin(np.sum(X[:, np.newaxis, :] * NUTATION_YTERM_ARRAY[np.newaxis, ...], axis=-1))\n", + "\n", + "print(f\"d psi shape {d_psi.shape}\")\n", + "\n", + "nut_long = np.sum(d_psi, axis=-1) / 36,000,000\n", + "\n", + "print(nut_long)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4, 11)\n" + ] + } + ], + "source": [ + "u = timestamps[:, np.newaxis] ** np.arange(0,11)\n", + "print(u.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "epsilon_0 = np.array(\n", + " [[\n", + " 84381.448,\n", + " -4680.93,\n", + " 1.55,\n", + " 1999.25,\n", + " -51.38,\n", + " -249.67,\n", + " -39.05,\n", + " 7.12,\n", + " 27.87,\n", + " 5.79,\n", + " 2.45,\n", + " ]]\n", + " )\n", + "res = u * epsilon_0\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array([-8.6115017e+12, -5.7323689e+12, -6.4693841e+12, -1.1346544e+13], dtype=float32)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "res.sum(axis=-1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/py/optimus.py b/py/optimus.py deleted file mode 100644 index e949245..0000000 --- a/py/optimus.py +++ /dev/null @@ -1,10 +0,0 @@ -# hyperspeed analytics and planning - -import numpy as np -from scipy.integrate import solve_bvp, solve_ivp -from numba import njit, vectorize, guvectorize - - -def fsolve_discrete(): ... - - diff --git a/py/poetry.lock b/py/poetry.lock index 248266a..4194e9a 100644 --- a/py/poetry.lock +++ b/py/poetry.lock @@ -122,6 +122,124 @@ files = [ [package.dependencies] frozenlist = ">=1.1.0" +[[package]] +name = "anyio" +version = "3.7.0" +description = "High level compatibility layer for multiple asynchronous event loop implementations" +optional = false +python-versions = ">=3.7" +files = [ + {file = "anyio-3.7.0-py3-none-any.whl", hash = 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[tool.poetry.group.dev.dependencies] mypy = "^1.3.0" pytest = "^7.3.2" types-pyyaml = "^6.0.12.10" +ipykernel = "^6.23.2" +jupyter = "^1.0.0" [build-system] requires = ["poetry-core"] diff --git a/py/backend.py b/py/pytelem/backend.py similarity index 100% rename from py/backend.py rename to py/pytelem/backend.py diff --git a/py/gui.py b/py/pytelem/gui.py similarity index 100% rename from py/gui.py rename to py/pytelem/gui.py diff --git a/py/pytelem/optimus.py b/py/pytelem/optimus.py new file mode 100644 index 0000000..4e13a06 --- /dev/null +++ b/py/pytelem/optimus.py @@ -0,0 +1,578 @@ +# hyperspeed forward and backwards analytics engine + +import numpy.typing as npt +from scipy.integrate import solve_bvp, solve_ivp + +from jax import jit, grad, vmap + +import jax.numpy as np + + +# TODO: define 3d vector space - x,y,z oriented around car/world? +# solvers should not care about position but we should be able to convert +# transforms between car/world spaces. + +# let's define x as the forward-backward axis (with forward being positive) +# y as the lateral axis, with right being positive +# and z being the vertical, with up being positive. + +# for simplicities’ sake, the car only rotates on the y-axis (up and down hills). +# z rotation can be determined from distance along the route. + +# some data (wind) is only a 2d vector at a given time point. + + +def fsolve_discrete(): + ... + + +def dist_to_pos(dist: float): + "convert a distance along the race path to a position in 3d space" + + +### All units are BASE SI (no prefix except for kilogram) +ATM_MOLAR_MASS = 0.0289644 # kg/mol +STANDARD_TEMP = 288.15 # K +STANDARD_PRES = 101325.0 # Pa + +AIR_GAS_CONSTANT = 8.31432 # N*m/s^2 + +EARTH_TEMP_LAPSE = -0.0065 +EARTH_GRAVITY = 9.80665 # m/s^2 +EARTH_RADIUS = 6378140.0 # m +EARTH_AXIS_INCLINATION = 23.45 # degrees + + +# FIXME: use named constants here + + +@jit +def get_pressure_el( + el: float, + Ps=STANDARD_PRES, + Ts: float = STANDARD_TEMP, + T_lapse: float = EARTH_TEMP_LAPSE, +): + """Gets the pressure at a point given eleveation - assumes + standard pressure,temperature, gas constants, etc""" + + return Ps * (Ts / (Ts + T_lapse * el)) ** ( + (ATM_MOLAR_MASS * EARTH_GRAVITY) / (AIR_GAS_CONSTANT / T_lapse) + ) + + +@jit +def estimate_temp(el: float, Ts: float = STANDARD_TEMP, T_lapse=EARTH_TEMP_LAPSE): + return Ts + el * T_lapse + + +def make_cubic(a, b, c, d): + """returns a simple cubic function""" + + def poly(x): + return a + b * x + c * (x**2) + (x**3) / d + + return jit(poly) + + +@jit +@vmap +def get_radiation_direct(yday, altitude_deg): + """Calculate the direct radiation at a given day of the year given the angle of the sun + from the horizon.""" + + flux = 1160 + (75 * np.sin(2 * np.pi / 365 * (yday - 275))) + + optical_depth = 0.174 + (0.035 * np.sin(2 * np.pi / 365 * (yday - 100))) + + air_mass_ratio = 1 / np.sin(np.radians(altitude_deg)) + # from Masters, p. 412 + + return flux * np.exp(-1 * optical_depth * air_mass_ratio) * (altitude_deg > 0) + + +# We start by defining MANY constants. +# to skip this, Ctrl-F to END COEFF +# START COEFF + + +# heliocentric longitude, latitude, radius (section 3.2) coefficients + +# heliocentric longitude coefficients +L0_TABLE = np.array( + [ + [175347046.0, 0.0, 0.0], + [3341656.0, 4.6692568, 6283.07585], + [34894.0, 4.6261, 12566.1517], + [3497.0, 2.7441, 5753.3849], + [3418.0, 2.8289, 3.5231], + [3136.0, 3.6277, 77713.7715], + [2676.0, 4.4181, 7860.4194], + [2343.0, 6.1352, 3930.2097], + [1324.0, 0.7425, 11506.7698], + [1273.0, 2.0371, 529.691], + [1199.0, 1.1096, 1577.3435], + [990.0, 5.233, 5884.927], + [902.0, 2.045, 26.298], + [857.0, 3.508, 398.149], + [780.0, 1.179, 5223.694], + [753.0, 2.533, 5507.553], + [505.0, 4.583, 18849.228], + [492.0, 4.205, 775.523], + [357.0, 2.92, 0.067], + [317.0, 5.849, 11790.629], + [284.0, 1.899, 796.298], + [271.0, 0.315, 10977.079], + [243.0, 0.345, 5486.778], + [206.0, 4.806, 2544.314], + [205.0, 1.869, 5573.143], + [202.0, 2.458, 6069.777], + [156.0, 0.833, 213.299], + [132.0, 3.411, 2942.463], + [126.0, 1.083, 20.775], + [115.0, 0.645, 0.98], + [103.0, 0.636, 4694.003], + [102.0, 0.976, 15720.839], + [102.0, 4.267, 7.114], + [99.0, 6.21, 2146.17], + [98.0, 0.68, 155.42], + [86.0, 5.98, 161000.69], + [85.0, 1.3, 6275.96], + [85.0, 3.67, 71430.7], + [80.0, 1.81, 17260.15], + [79.0, 3.04, 12036.46], + [75.0, 1.76, 5088.63], + [74.0, 3.5, 3154.69], + [74.0, 4.68, 801.82], + [70.0, 0.83, 9437.76], + [62.0, 3.98, 8827.39], + [61.0, 1.82, 7084.9], + [57.0, 2.78, 6286.6], + [56.0, 4.39, 14143.5], + [56.0, 3.47, 6279.55], + [52.0, 0.19, 12139.55], + [52.0, 1.33, 1748.02], + [51.0, 0.28, 5856.48], + [49.0, 0.49, 1194.45], + [41.0, 5.37, 8429.24], + [41.0, 2.4, 19651.05], + [39.0, 6.17, 10447.39], + [37.0, 6.04, 10213.29], + [37.0, 2.57, 1059.38], + [36.0, 1.71, 2352.87], + [36.0, 1.78, 6812.77], + [33.0, 0.59, 17789.85], + [30.0, 0.44, 83996.85], + [30.0, 2.74, 1349.87], + [25.0, 3.16, 4690.48], + ] +) +L1_TABLE = np.array( + [ + [628331966747.0, 0.0, 0.0], + [206059.0, 2.678235, 6283.07585], + [4303.0, 2.6351, 12566.1517], + [425.0, 1.59, 3.523], + [119.0, 5.796, 26.298], + [109.0, 2.966, 1577.344], + [93.0, 2.59, 18849.23], + [72.0, 1.14, 529.69], + [68.0, 1.87, 398.15], + [67.0, 4.41, 5507.55], + [59.0, 2.89, 5223.69], + [56.0, 2.17, 155.42], + [45.0, 0.4, 796.3], + [36.0, 0.47, 775.52], + [29.0, 2.65, 7.11], + [21.0, 5.34, 0.98], + [19.0, 1.85, 5486.78], + [19.0, 4.97, 213.3], + [17.0, 2.99, 6275.96], + [16.0, 0.03, 2544.31], + [16.0, 1.43, 2146.17], + [15.0, 1.21, 10977.08], + [12.0, 2.83, 1748.02], + [12.0, 3.26, 5088.63], + [12.0, 5.27, 1194.45], + [12.0, 2.08, 4694.0], + [11.0, 0.77, 553.57], + [10.0, 1.3, 6286.6], + [10.0, 4.24, 1349.87], + [9.0, 2.7, 242.73], + [9.0, 5.64, 951.72], + [8.0, 5.3, 2352.87], + [6.0, 2.65, 9437.76], + [6.0, 4.67, 4690.48], + ] +) +L2_TABLE = np.array( + [ + [52919.0, 0.0, 0.0], + [8720.0, 1.0721, 6283.0758], + [309.0, 0.867, 12566.152], + [27.0, 0.05, 3.52], + [16.0, 5.19, 26.3], + [16.0, 3.68, 155.42], + [10.0, 0.76, 18849.23], + [9.0, 2.06, 77713.77], + [7.0, 0.83, 775.52], + [5.0, 4.66, 1577.34], + [4.0, 1.03, 7.11], + [4.0, 3.44, 5573.14], + [3.0, 5.14, 796.3], + [3.0, 6.05, 5507.55], + [3.0, 1.19, 242.73], + [3.0, 6.12, 529.69], + [3.0, 0.31, 398.15], + [3.0, 2.28, 553.57], + [2.0, 4.38, 5223.69], + [2.0, 3.75, 0.98], + ] +) +L3_TABLE = np.array( + [ + [289.0, 5.844, 6283.076], + [35.0, 0.0, 0.0], + [17.0, 5.49, 12566.15], + [3.0, 5.2, 155.42], + [1.0, 4.72, 3.52], + [1.0, 5.3, 18849.23], + [1.0, 5.97, 242.73], + ] +) +L4_TABLE = np.array([[114.0, 3.142, 0.0], [8.0, 4.13, 6283.08], [1.0, 3.84, 12566.15]]) +L5_TABLE = np.array([[1.0, 3.14, 0.0]]) + +HELIO_L = [L0_TABLE, L1_TABLE, L2_TABLE, L3_TABLE, L4_TABLE, L5_TABLE] + +# heliocentric latitude coefficients +B0_TABLE = np.array( + [ + [280.0, 3.199, 84334.662], + [102.0, 5.422, 5507.553], + [80.0, 3.88, 5223.69], + [44.0, 3.7, 2352.87], + [32.0, 4.0, 1577.34], + ] +) +B1_TABLE = np.array([[9.0, 3.9, 5507.55], [6.0, 1.73, 5223.69]]) + +HELIO_B = [B0_TABLE, B1_TABLE] + +# heliocentric radius coefficients +R0_TABLE = np.array( + [ + [100013989.0, 0.0, 0.0], + [1670700.0, 3.0984635, 6283.07585], + [13956.0, 3.05525, 12566.1517], + [3084.0, 5.1985, 77713.7715], + [1628.0, 1.1739, 5753.3849], + [1576.0, 2.8469, 7860.4194], + [925.0, 5.453, 11506.77], + [542.0, 4.564, 3930.21], + [472.0, 3.661, 5884.927], + [346.0, 0.964, 5507.553], + [329.0, 5.9, 5223.694], + [307.0, 0.299, 5573.143], + [243.0, 4.273, 11790.629], + [212.0, 5.847, 1577.344], + [186.0, 5.022, 10977.079], + [175.0, 3.012, 18849.228], + [110.0, 5.055, 5486.778], + [98.0, 0.89, 6069.78], + [86.0, 5.69, 15720.84], + [86.0, 1.27, 161000.69], + [65.0, 0.27, 17260.15], + [63.0, 0.92, 529.69], + [57.0, 2.01, 83996.85], + [56.0, 5.24, 71430.7], + [49.0, 3.25, 2544.31], + [47.0, 2.58, 775.52], + [45.0, 5.54, 9437.76], + [43.0, 6.01, 6275.96], + [39.0, 5.36, 4694.0], + [38.0, 2.39, 8827.39], + [37.0, 0.83, 19651.05], + [37.0, 4.9, 12139.55], + [36.0, 1.67, 12036.46], + [35.0, 1.84, 2942.46], + [33.0, 0.24, 7084.9], + [32.0, 0.18, 5088.63], + [32.0, 1.78, 398.15], + [28.0, 1.21, 6286.6], + [28.0, 1.9, 6279.55], + [26.0, 4.59, 10447.39], + ] +) +R1_TABLE = np.array( + [ + [103019.0, 1.10749, 6283.07585], + [1721.0, 1.0644, 12566.1517], + [702.0, 3.142, 0.0], + [32.0, 1.02, 18849.23], + [31.0, 2.84, 5507.55], + [25.0, 1.32, 5223.69], + [18.0, 1.42, 1577.34], + [10.0, 5.91, 10977.08], + [9.0, 1.42, 6275.96], + [9.0, 0.27, 5486.78], + ] +) +R2_TABLE = np.array( + [ + [4359.0, 5.7846, 6283.0758], + [124.0, 5.579, 12566.152], + [12.0, 3.14, 0.0], + [9.0, 3.63, 77713.77], + [6.0, 1.87, 5573.14], + [3.0, 5.47, 18849.23], + ] +) +R3_TABLE = np.array([[145.0, 4.273, 6283.076], [7.0, 3.92, 12566.15]]) +R4_TABLE = np.array([[4.0, 2.56, 6283.08]]) + +HELIO_R = [R0_TABLE, R1_TABLE, R2_TABLE, R3_TABLE, R4_TABLE] + +# longitude and obliquity nutation coefficients +NUTATION_ABCD_ARRAY = np.array( + [ + [-171996, -174.2, 92025, 8.9], + [-13187, -1.6, 5736, -3.1], + [-2274, -0.2, 977, -0.5], + [2062, 0.2, -895, 0.5], + [1426, -3.4, 54, -0.1], + [712, 0.1, -7, 0], + [-517, 1.2, 224, -0.6], + [-386, -0.4, 200, 0], + [-301, 0, 129, -0.1], + [217, -0.5, -95, 0.3], + [-158, 0, 0, 0], + [129, 0.1, -70, 0], + [123, 0, -53, 0], + [63, 0, 0, 0], + [63, 0.1, -33, 0], + [-59, 0, 26, 0], + [-58, -0.1, 32, 0], + [-51, 0, 27, 0], + [48, 0, 0, 0], + [46, 0, -24, 0], + [-38, 0, 16, 0], + [-31, 0, 13, 0], + [29, 0, 0, 0], + [29, 0, -12, 0], + [26, 0, 0, 0], + [-22, 0, 0, 0], + [21, 0, -10, 0], + [17, -0.1, 0, 0], + [16, 0, -8, 0], + [-16, 0.1, 7, 0], + [-15, 0, 9, 0], + [-13, 0, 7, 0], + [-12, 0, 6, 0], + [11, 0, 0, 0], + [-10, 0, 5, 0], + [-8, 0, 3, 0], + [7, 0, -3, 0], + [-7, 0, 0, 0], + [-7, 0, 3, 0], + [-7, 0, 3, 0], + [6, 0, 0, 0], + [6, 0, -3, 0], + [6, 0, -3, 0], + [-6, 0, 3, 0], + [-6, 0, 3, 0], + [5, 0, 0, 0], + [-5, 0, 3, 0], + [-5, 0, 3, 0], + [-5, 0, 3, 0], + [4, 0, 0, 0], + [4, 0, 0, 0], + [4, 0, 0, 0], + [-4, 0, 0, 0], + [-4, 0, 0, 0], + [-4, 0, 0, 0], + [3, 0, 0, 0], + [-3, 0, 0, 0], + [-3, 0, 0, 0], + [-3, 0, 0, 0], + [-3, 0, 0, 0], + [-3, 0, 0, 0], + [-3, 0, 0, 0], + [-3, 0, 0, 0], + ] +) + +NUTATION_YTERM_ARRAY = np.array( + [ + [0, 0, 0, 0, 1], + [-2, 0, 0, 2, 2], + [0, 0, 0, 2, 2], + [0, 0, 0, 0, 2], + [0, 1, 0, 0, 0], + [0, 0, 1, 0, 0], + [-2, 1, 0, 2, 2], + [0, 0, 0, 2, 1], + [0, 0, 1, 2, 2], + [-2, -1, 0, 2, 2], + [-2, 0, 1, 0, 0], + [-2, 0, 0, 2, 1], + [0, 0, -1, 2, 2], + [2, 0, 0, 0, 0], + [0, 0, 1, 0, 1], + [2, 0, -1, 2, 2], + [0, 0, -1, 0, 1], + [0, 0, 1, 2, 1], + [-2, 0, 2, 0, 0], + [0, 0, -2, 2, 1], + [2, 0, 0, 2, 2], + [0, 0, 2, 2, 2], + [0, 0, 2, 0, 0], + [-2, 0, 1, 2, 2], + [0, 0, 0, 2, 0], + [-2, 0, 0, 2, 0], + [0, 0, -1, 2, 1], + [0, 2, 0, 0, 0], + [2, 0, -1, 0, 1], + [-2, 2, 0, 2, 2], + [0, 1, 0, 0, 1], + [-2, 0, 1, 0, 1], + [0, -1, 0, 0, 1], + [0, 0, 2, -2, 0], + [2, 0, -1, 2, 1], + [2, 0, 1, 2, 2], + [0, 1, 0, 2, 2], + [-2, 1, 1, 0, 0], + [0, -1, 0, 2, 2], + [2, 0, 0, 2, 1], + [2, 0, 1, 0, 0], + [-2, 0, 2, 2, 2], + [-2, 0, 1, 2, 1], + [2, 0, -2, 0, 1], + [2, 0, 0, 0, 1], + [0, -1, 1, 0, 0], + [-2, -1, 0, 2, 1], + [-2, 0, 0, 0, 1], + [0, 0, 2, 2, 1], + [-2, 0, 2, 0, 1], + [-2, 1, 0, 2, 1], + [0, 0, 1, -2, 0], + [-1, 0, 1, 0, 0], + [-2, 1, 0, 0, 0], + [1, 0, 0, 0, 0], + [0, 0, 1, 2, 0], + [0, 0, -2, 2, 2], + [-1, -1, 1, 0, 0], + [0, 1, 1, 0, 0], + [0, -1, 1, 2, 2], + [2, -1, -1, 2, 2], + [0, 0, 3, 2, 2], + [2, -1, 0, 2, 2], + ] +) +# END COEFF + +# now, we write to the actual code + +DELTA_T = 67 + + +@jit +def helio_vector(vec, jme): + """This function calculates equation 9 across the vector""" + return np.sum( + vec[:, 0] * np.cos(vec[:, 1] + vec[:, 2] * jme[..., np.newaxis]), axis=-1 + ) + + +def solar_position(timestamp, latitude, longitude): + """Calculate the position of the sun at a given location and time. + + Args: + timestamp (array-like): The timestamp(s) to calculate. + + Returns: + ndarray: An array containing the altitude and azimuth for each timestamp. + """ + timestamp = np.array(timestamp) + jd = timestamp / 86400.0 + 2440587.5 + jc = (jd - 2451545) / 36525 + + jde = jd + DELTA_T / 86400.0 + jce = (jde - 2451545) / 36525 + + jm = jc / 10 + jme = jce / 10 + + # todo: make more elegant? + # TODO: vectorize later? it's kinda complex + + # heliocentric longitude + l_rad = np.zeros_like(timestamp) + for idx, vec in enumerate(HELIO_L): + l_rad = l_rad + helio_vector(vec, jme) * jme**idx + + l_rad = l_rad / 10e8 + l_deg = np.rad2deg(l_rad) % 360 + + # heliocentric latitude + b_rad = np.zeros_like(timestamp) + for idx, vec in enumerate(HELIO_B): + b_rad = b_rad + helio_vector(vec, jme) * jme**idx + b_rad = b_rad / 10e8 + b_deg = np.rad2deg(b_rad) % 360 + + # heliocentric radius + r_rad = np.zeros_like(timestamp) + for idx, vec in enumerate(HELIO_R): + r_rad = r_rad + helio_vector(vec, jme) * jme**idx + r_rad = r_rad / 10e8 + r_deg = np.rad2deg(r_rad) % 360 + + theta = (l_deg + 180) % 360 + beta = -1 * b_deg + + def cubic_poly(a, b, c, d): + return a + b * jce + c * jce**2 + (jce**3) / d + + X0 = cubic_poly(297.85036, 445267.111480, -0.0019142, 189474) + X1 = cubic_poly(357.52772, 35999.050340, -0.0001603, -300000) + X2 = cubic_poly(134.96298, 477198.867398, 0.0086972, 56250) + X3 = cubic_poly(93.27191, 483202.017538, -0.0036825, 327270) + X4 = cubic_poly(125.04452, 1934.136261, 0.0020708, 450000) + + X = np.vstack([X0, X1, X2, X3, X4]).T + + nut = NUTATION_ABCD_ARRAY + + ## TODO: these are gross - use loops instead of broadcasting? + d_psi = (nut[:, 0] + jce[..., np.newaxis] * nut[:, 1]) * np.sin( + np.sum(X[:, np.newaxis, :] * NUTATION_YTERM_ARRAY[np.newaxis, ...], axis=2) + ) + d_psi = np.sum(d_psi, axis=-1) / 36, 000, 000 + + + d_epsilon = (nut[:, 2] + jce[..., np.newaxis] * nut[:, 3]) * np.cos( + np.sum(X[:, np.newaxis, :] * NUTATION_YTERM_ARRAY[np.newaxis, ...], axis=2) + ) + d_epsilon = np.sum(d_epsilon, axis=-1) / 36, 000, 000 + + u = jme[:, np.newaxis] / 10 * np.arange(0,10).reshape((1,-1)) + epsilon_0 = np.array( + [ + 84381.448, + -4680.93, + 1.55, + 1999.25, + -51.38, + -249.67, + -39.05, + 7.12, + 27.87, + 5.79, + 2.45, + ] + ) + epsilon = np.sum(u * epsilon_0, axis=-1) / 3600 + d_epsilon + d_tau = -20.4898 / (3600 * r_deg) + sun_longitude = theta + d_psi + d_tau + \ No newline at end of file diff --git a/py/pytelem.py b/py/pytelem/pytelem.py similarity index 100% rename from py/pytelem.py rename to py/pytelem/pytelem.py diff --git a/py/skylab.py b/py/pytelem/skylab.py similarity index 100% rename from py/skylab.py rename to py/pytelem/skylab.py