docs: Rename doc folder to docs, update outline

docs/src/ed-lrr.md

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+---
+# Metadata
+title: ED_LRR
+author:
+- Daniel Seiller <earthnuker@gmail.com>
+subtitle: 'Elite Dangerous: Long-Range Router'
+
+# Formating
+toc: true
+lang: en
+colorlinks: true
+papersize: a4
+numbersections: true
+
+#Panflute options
+panflute-filters: [multifilter]
+panflute-path: 'filters'
+
+#Template options
+titlepage: true
+toc-own-page: false
+---
+
+# How it works
+
+## `stars.csv` format
+
+### Columns
+
+| Name      | Content                                                             |
+| --------- | ------------------------------------------------------------------- |
+| id        | unique ID-Number (not to be confused with EDSM id or id64)          |
+| star_type | Type of Star                                                        |
+| system    | Name of System                                                      |
+| body      | Name of Star                                                        |
+| mult      | Jump Range Multiplier (1.5 for White Dwarfs, 4.0 for Neutron Stars) |
+| distance  | Distance from arrival in Ls                                         |
+| x,y,z     | Position in Galactic Coordinates with Sol at (0,0,0)                |
+
+## `stars.idx` format
+
+## Routing Algorithms
+
+### Breadth-First Search (BFS)
+
+### A*-Search
+
+### Greedy Search
+
+## Optimizations
+
+## Routing Graphs
+
+# Usage
+
+## Preprocessing Data
+
+## Plotting a Route
+
+# [Changelog](https://gitlab.com/Earthnuker/ed_lrr/blob/pyqt_gui/CHANGELOG.md)

docs/src/img_out.py

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+import sys
+import pylab as PL
+import numpy as np
+from scipy.spatial.ckdtree import cKDTree
+import heapq
+
+exit()
+
+
+def vec(a, b):
+    return b - a
+
+
+def bfs(points):
+    return
+
+
+def in_ellipse(p, f1, f2, r, offset=0):
+    df = ((f1 - f2) ** 2).sum(0) ** 0.5
+    d_f1 = ((p - f1) ** 2).sum(1) ** 0.5
+    d_f2 = ((p - f2) ** 2).sum(1) ** 0.5
+    return (d_f1 + d_f2) < (df * (1 + r))
+
+
+num_points = 100000
+
+p_orig = np.random.normal(0, 10, size=(num_points, 2))
+tree = cKDTree(p_orig)
+f1 = np.array([0, -30])
+f2 = -f1  # np.random.normal(0, 20, (3,))
+# r = 2 ** ((n / cnt) - cnt)
+
+mask = in_ellipse(p_orig, f1, f2, 0.1)
+
+p = p_orig[mask]
+p_orig = p_orig[~mask]
+
+colors = np.random.random(p.shape[0])
+fig = PL.gcf()
+PL.scatter(
+    p_orig[:, 0],
+    p_orig[:, 1],
+    marker=".",
+    s=0.2,
+    edgecolor="None",
+    c=[(0.0, 0.0, 0.0)],
+    alpha=0.75,
+    rasterized=True,
+)
+PL.scatter(
+    p[:, 0], p[:, 1], marker="s", s=0.2, edgecolor="None", c=colors, rasterized=True
+)
+PL.plot(f1[0], f1[1], "r.", label="Source")
+PL.plot(f2[0], f2[1], "g.", label="Destination")
+
+max_v = max(p_orig[:, 0].max(), p_orig[:, 1].max(), f1[0], f1[1], f2[0], f2[1]) + 2
+min_v = min(p_orig[:, 0].min(), p_orig[:, 1].min(), f1[0], f1[1], f2[0], f2[1]) - 2
+
+
+PL.xlim(min_v, max_v)
+PL.ylim(min_v, max_v)
+
+PL.legend()
+PL.savefig(sys.argv[1], dpi=1200)