| 1 | import json
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| 2 | import math
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| 3 | import random
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| 4 | import argparse
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| 5 | import bisect
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| 6 | import time as timelib
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| 7 | from PIL import Image, ImageDraw, ImageFont
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| 8 | from scipy import stats
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| 9 | from matplotlib import colors
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| 10 | import numpy as np
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| 11 |
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| 12 | class LoadingError(Exception):
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| 13 | pass
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| 14 |
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| 15 | class Drawer:
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| 16 |
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| 17 | def __init__(self, design, config_file, w=600, h=800, w_margin=10, h_margin=20):
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| 18 | self.design = design
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| 19 | self.width = w
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| 20 | self.height = h
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| 21 | self.w_margin = w_margin
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| 22 | self.h_margin = h_margin
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| 23 | self.w_no_margs = w - 2* w_margin
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| 24 | self.h_no_margs = h - 2* h_margin
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| 25 |
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| 26 | self.color_converter = colors.ColorConverter()
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| 27 |
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| 28 | self.settings = {
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| 29 | 'colors_of_kinds': ['red', 'green', 'blue', 'magenta', 'yellow', 'cyan', 'orange', 'purple'],
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| 30 | 'dots': {
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| 31 | 'color': {
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| 32 | 'meaning': 'Lifespan',
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| 33 | 'normalize_cmap': False,
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| 34 | 'cmap': {},
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| 35 | 'start': 'red',
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| 36 | 'end': 'green',
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| 37 | 'bias': 1
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| 38 | },
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| 39 | 'size': {
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| 40 | 'meaning': 'EnergyEaten',
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| 41 | 'start': 1,
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| 42 | 'end': 6,
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| 43 | 'bias': 0.5
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| 44 | },
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| 45 | 'opacity': {
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| 46 | 'meaning': 'EnergyEaten',
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| 47 | 'start': 0.2,
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| 48 | 'end': 1,
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| 49 | 'bias': 1
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| 50 | }
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| 51 | },
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| 52 | 'lines': {
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| 53 | 'color': {
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| 54 | 'meaning': 'adepth',
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| 55 | 'normalize_cmap': False,
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| 56 | 'cmap': {},
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| 57 | 'start': 'black',
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| 58 | 'end': 'red',
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| 59 | 'bias': 3
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| 60 | },
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| 61 | 'width': {
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| 62 | 'meaning': 'adepth',
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| 63 | 'start': 0.1,
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| 64 | 'end': 4,
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| 65 | 'bias': 3
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| 66 | },
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| 67 | 'opacity': {
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| 68 | 'meaning': 'adepth',
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| 69 | 'start': 0.1,
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| 70 | 'end': 0.8,
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| 71 | 'bias': 5
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| 72 | }
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| 73 | }
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| 74 | }
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| 75 |
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| 76 | def merge(source, destination):
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| 77 | for key, value in source.items():
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| 78 | if isinstance(value, dict):
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| 79 | node = destination.setdefault(key, {})
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| 80 | merge(value, node)
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| 81 | else:
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| 82 | destination[key] = value
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| 83 | return destination
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| 84 |
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| 85 | if config_file != "":
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| 86 | with open(config_file) as config:
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| 87 | c = json.load(config)
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| 88 | self.settings = merge(c, self.settings)
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| 89 | #print(json.dumps(self.settings, indent=4, sort_keys=True))
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| 90 |
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| 91 | self.compile_cmaps()
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| 92 |
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| 93 | def compile_cmaps(self):
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| 94 |
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| 95 | # normalization of color breaking points
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| 96 | for part in ['dots', 'lines']:
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| 97 | if self.settings[part]['color']['cmap'] \
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| 98 | and self.settings[part]['color']['normalize_cmap']:
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| 99 | cmap = self.settings[part]['color']['cmap']
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| 100 | min = self.design.props[self.settings[part]['color']['meaning'] + "_min"]
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| 101 | max = self.design.props[self.settings[part]['color']['meaning'] + "_max"]
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| 102 | for key in cmap:
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| 103 | for arr in cmap[key]:
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| 104 | arr[0] = (arr[0] - min) / (max-min)
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| 105 | if cmap[key][0][0] != 0:
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| 106 | cmap[key].insert(0, cmap[key][0][:])
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| 107 | cmap[key][0][0] = 0
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| 108 | if cmap[key][-1][0] != 1:
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| 109 | cmap[key].append(cmap[key][-1][:])
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| 110 | cmap[key][-1][0] = 1
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| 111 |
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| 112 |
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| 113 | for part in ['dots', 'lines']:
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| 114 | if self.settings[part]['color']['cmap']:
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| 115 | cmap = self.settings[part]['color']['cmap']
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| 116 | for key in cmap:
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| 117 | new_arr = []
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| 118 | for arr in cmap[key]:
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| 119 | new_arr.append(tuple(arr))
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| 120 | cmap[key] = tuple(new_arr)
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| 121 | #print(cmap)
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| 122 | self.settings[part]['color']['cmap'] = colors.LinearSegmentedColormap('Custom', cmap)
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| 123 |
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| 124 | def draw_dots(self, file, min_width, max_width, max_height):
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| 125 | for i in range(len(self.design.positions)):
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| 126 | node = self.design.positions[i]
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| 127 | if 'x' not in node:
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| 128 | continue
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| 129 | dot_style = self.compute_dot_style(node=i)
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| 130 | self.add_dot(file, (self.w_margin+self.w_no_margs*(node['x']-min_width)/(max_width-min_width),
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| 131 | self.h_margin+self.h_no_margs*node['y']/max_height), dot_style)
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| 132 |
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| 133 | def draw_lines(self, file, min_width, max_width, max_height):
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| 134 | for parent in range(len(self.design.positions)):
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| 135 | par_pos = self.design.positions[parent]
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| 136 | if not 'x' in par_pos:
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| 137 | continue
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| 138 | for child in self.design.tree.children[parent]:
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| 139 | chi_pos = self.design.positions[child]
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| 140 | if 'x' not in chi_pos:
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| 141 | continue
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| 142 | line_style = self.compute_line_style(parent, child)
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| 143 | self.add_line(file, (self.w_margin+self.w_no_margs*(par_pos['x']-min_width)/(max_width-min_width),
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| 144 | self.h_margin+self.h_no_margs*par_pos['y']/max_height),
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| 145 | (self.w_margin+self.w_no_margs*(chi_pos['x']-min_width)/(max_width-min_width),
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| 146 | self.h_margin+self.h_no_margs*chi_pos['y']/max_height), line_style)
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| 147 |
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| 148 | def draw_scale(self, file, filename):
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| 149 | self.add_text(file, "Generated from " + filename.split("\\")[-1], (5, 5), "start")
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| 150 |
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| 151 | start_text = ""
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| 152 | end_text = ""
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| 153 | if self.design.TIME == "BIRTHS":
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| 154 | start_text = "Birth #0"
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| 155 | end_text = "Birth #" + str(len(self.design.positions)-1)
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| 156 | if self.design.TIME == "REAL":
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| 157 | start_text = "Time " + str(min(self.design.tree.time))
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| 158 | end_text = "Time " + str(max(self.design.tree.time))
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| 159 | if self.design.TIME == "GENERATIONAL":
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| 160 | start_text = "Depth " + str(self.design.props['adepth_min'])
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| 161 | end_text = "Depth " + str(self.design.props['adepth_max'])
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| 162 |
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| 163 | self.add_dashed_line(file, (self.width*0.7, self.h_margin), (self.width, self.h_margin))
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| 164 | self.add_text(file, start_text, (self.width, self.h_margin), "end")
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| 165 | self.add_dashed_line(file, (self.width*0.7, self.height-self.h_margin), (self.width, self.height-self.h_margin))
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| 166 | self.add_text(file, end_text, (self.width, self.height-self.h_margin), "end")
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| 167 |
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| 168 | def compute_property(self, part, prop, node):
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| 169 | start = self.settings[part][prop]['start']
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| 170 | end = self.settings[part][prop]['end']
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| 171 | value = (self.design.props[self.settings[part][prop]['meaning']][node]
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| 172 | if self.settings[part][prop]['meaning'] in self.design.props else 0 )
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| 173 | bias = self.settings[part][prop]['bias']
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| 174 | if prop == "color":
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| 175 | if not self.settings[part][prop]['cmap']:
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| 176 | return self.compute_color(start, end, value, bias)
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| 177 | else:
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| 178 | return self.compute_color_from_cmap(self.settings[part][prop]['cmap'], value, bias)
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| 179 | else:
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| 180 | return self.compute_value(start, end, value, bias)
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| 181 |
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| 182 | def compute_color_from_cmap(self, cmap, value, bias=1):
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| 183 | value = 1 - (1-value)**bias
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| 184 | rgba = cmap(value)
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| 185 | return (100*rgba[0], 100*rgba[1], 100*rgba[2])
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| 186 |
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| 187 |
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| 188 | def compute_color(self, start, end, value, bias=1):
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| 189 | if isinstance(value, str):
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| 190 | value = int(value)
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| 191 | r, g, b = self.color_converter.to_rgb(self.settings['colors_of_kinds'][value])
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| 192 | else:
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| 193 | start_color = self.color_converter.to_rgb(start)
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| 194 | end_color = self.color_converter.to_rgb(end)
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| 195 | value = 1 - (1-value)**bias
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| 196 | r = start_color[0]*(1-value)+end_color[0]*value
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| 197 | g = start_color[1]*(1-value)+end_color[1]*value
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| 198 | b = start_color[2]*(1-value)+end_color[2]*value
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| 199 | return (100*r, 100*g, 100*b)
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| 200 |
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| 201 | def compute_value(self, start, end, value, bias=1):
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| 202 | value = 1 - (1-value)**bias
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| 203 | return start*(1-value) + end*value
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| 204 |
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| 205 | class PngDrawer(Drawer):
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| 206 |
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| 207 | def scale_up(self):
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| 208 | self.width *= self.multi
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| 209 | self.height *= self.multi
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| 210 | self.w_margin *= self.multi
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| 211 | self.h_margin *= self.multi
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| 212 | self.h_no_margs *= self.multi
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| 213 | self.w_no_margs *= self.multi
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| 214 |
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| 215 | def scale_down(self):
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| 216 | self.width /= self.multi
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| 217 | self.height /= self.multi
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| 218 | self.w_margin /= self.multi
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| 219 | self.h_margin /= self.multi
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| 220 | self.h_no_margs /= self.multi
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| 221 | self.w_no_margs /= self.multi
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| 222 |
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| 223 | def draw_design(self, filename, input_filename, multi=1, scale="SIMPLE"):
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| 224 | print("Drawing...")
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| 225 |
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| 226 | self.multi=multi
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| 227 | self.scale_up()
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| 228 |
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| 229 | back = Image.new('RGBA', (self.width, self.height), (255,255,255,0))
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| 230 |
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| 231 | min_width = min([x['x'] for x in self.design.positions if 'x' in x])
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| 232 | max_width = max([x['x'] for x in self.design.positions if 'x' in x])
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| 233 | max_height = max([x['y'] for x in self.design.positions if 'y' in x])
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| 234 |
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| 235 | self.draw_lines(back, min_width, max_width, max_height)
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| 236 | self.draw_dots(back, min_width, max_width, max_height)
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| 237 |
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| 238 | if scale == "SIMPLE":
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| 239 | self.draw_scale(back, input_filename)
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| 240 |
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| 241 | #back.show()
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| 242 | self.scale_down()
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| 243 |
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| 244 | back.thumbnail((self.width, self.height), Image.ANTIALIAS)
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| 245 |
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| 246 | back.save(filename)
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| 247 |
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| 248 | def add_dot(self, file, pos, style):
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| 249 | x, y = int(pos[0]), int(pos[1])
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| 250 | r = style['r']*self.multi
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| 251 | offset = (int(x - r), int(y - r))
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| 252 | size = (2*int(r), 2*int(r))
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| 253 |
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| 254 | c = style['color']
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| 255 |
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| 256 | img = Image.new('RGBA', size)
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| 257 | ImageDraw.Draw(img).ellipse((1, 1, size[0]-1, size[1]-1),
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| 258 | (int(2.55*c[0]), int(2.55*c[1]), int(2.55*c[2]), int(255*style['opacity'])))
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| 259 | file.paste(img, offset, mask=img)
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| 260 |
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| 261 | def add_line(self, file, from_pos, to_pos, style):
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| 262 | fx, fy, tx, ty = int(from_pos[0]), int(from_pos[1]), int(to_pos[0]), int(to_pos[1])
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| 263 | w = int(style['width'])*self.multi
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| 264 |
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| 265 | offset = (min(fx-w, tx-w), min(fy-w, ty-w))
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| 266 | size = (abs(fx-tx)+2*w, abs(fy-ty)+2*w)
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| 267 | if size[0] == 0 or size[1] == 0:
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| 268 | return
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| 269 |
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| 270 | c = style['color']
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| 271 |
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| 272 | img = Image.new('RGBA', size)
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| 273 | ImageDraw.Draw(img).line((w, w, size[0]-w, size[1]-w) if (fx-tx)*(fy-ty)>0 else (size[0]-w, w, w, size[1]-w),
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| 274 | (int(2.55*c[0]), int(2.55*c[1]), int(2.55*c[2]), int(255*style['opacity'])), w)
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| 275 | file.paste(img, offset, mask=img)
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| 276 |
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| 277 | def add_dashed_line(self, file, from_pos, to_pos):
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| 278 | style = {'color': (0,0,0), 'width': 1, 'opacity': 1}
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| 279 | sublines = 50
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| 280 | # TODO could be faster: compute delta and only add delta each time (but currently we do not use it often)
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| 281 | normdiv = 2*sublines-1
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| 282 | for i in range(sublines):
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| 283 | from_pos_sub = (self.compute_value(from_pos[0], to_pos[0], 2*i/normdiv, 1),
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| 284 | self.compute_value(from_pos[1], to_pos[1], 2*i/normdiv, 1))
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| 285 | to_pos_sub = (self.compute_value(from_pos[0], to_pos[0], (2*i+1)/normdiv, 1),
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| 286 | self.compute_value(from_pos[1], to_pos[1], (2*i+1)/normdiv, 1))
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| 287 | self.add_line(file, from_pos_sub, to_pos_sub, style)
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| 288 |
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| 289 | def add_text(self, file, text, pos, anchor, style=''):
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| 290 | font = ImageFont.truetype("Vera.ttf", 16*self.multi)
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| 291 |
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| 292 | img = Image.new('RGBA', (self.width, self.height))
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| 293 | draw = ImageDraw.Draw(img)
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| 294 | txtsize = draw.textsize(text, font=font)
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| 295 | pos = pos if anchor == "start" else (pos[0]-txtsize[0], pos[1])
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| 296 | draw.text(pos, text, (0,0,0), font=font)
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| 297 | file.paste(img, (0,0), mask=img)
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| 298 |
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| 299 | def compute_line_style(self, parent, child):
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| 300 | return {'color': self.compute_property('lines', 'color', child),
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| 301 | 'width': self.compute_property('lines', 'width', child),
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| 302 | 'opacity': self.compute_property('lines', 'opacity', child)}
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| 303 |
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| 304 | def compute_dot_style(self, node):
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| 305 | return {'color': self.compute_property('dots', 'color', node),
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| 306 | 'r': self.compute_property('dots', 'size', node),
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| 307 | 'opacity': self.compute_property('dots', 'opacity', node)}
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| 308 |
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| 309 | class SvgDrawer(Drawer):
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| 310 | def draw_design(self, filename, input_filename, multi=1, scale="SIMPLE"):
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| 311 | print("Drawing...")
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| 312 | file = open(filename, "w")
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| 313 |
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| 314 | min_width = min([x['x'] for x in self.design.positions if 'x' in x])
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| 315 | max_width = max([x['x'] for x in self.design.positions if 'x' in x])
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| 316 | max_height = max([x['y'] for x in self.design.positions if 'y' in x])
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| 317 |
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| 318 | file.write('<svg xmlns:svg="http://www.w3.org/2000/svg" xmlns="http://www.w3.org/2000/svg" '
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| 319 | 'xmlns:xlink="http://www.w3.org/1999/xlink" version="1.0" '
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| 320 | 'width="' + str(self.width) + '" height="' + str(self.height) + '">')
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| 321 |
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| 322 | self.draw_lines(file, min_width, max_width, max_height)
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| 323 | self.draw_dots(file, min_width, max_width, max_height)
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| 324 |
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| 325 | if scale == "SIMPLE":
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| 326 | self.draw_scale(file, input_filename)
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| 327 |
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| 328 | file.write("</svg>")
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| 329 | file.close()
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| 330 |
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| 331 | def add_text(self, file, text, pos, anchor, style=''):
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| 332 | style = (style if style != '' else 'style="font-family: Arial; font-size: 12; fill: #000000;"')
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| 333 | # assuming font size 12, it should be taken from the style string!
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| 334 | file.write('<text ' + style + ' text-anchor="' + anchor + '" x="' + str(pos[0]) + '" y="' + str(pos[1]+12) + '" >' + text + '</text>')
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| 335 |
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| 336 | def add_dot(self, file, pos, style):
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| 337 | file.write('<circle ' + style + ' cx="' + str(pos[0]) + '" cy="' + str(pos[1]) + '" />')
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| 338 |
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| 339 | def add_line(self, file, from_pos, to_pos, style):
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| 340 | file.write('<line ' + style + ' x1="' + str(from_pos[0]) + '" x2="' + str(to_pos[0]) +
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| 341 | '" y1="' + str(from_pos[1]) + '" y2="' + str(to_pos[1]) + '" fill="none"/>')
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| 342 |
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| 343 | def add_dashed_line(self, file, from_pos, to_pos):
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| 344 | style = 'stroke="black" stroke-width="0.5" stroke-opacity="1" stroke-dasharray="5, 5"'
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| 345 | self.add_line(file, from_pos, to_pos, style)
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| 346 |
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| 347 | def compute_line_style(self, parent, child):
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| 348 | return self.compute_stroke_color('lines', child) + ' ' \
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| 349 | + self.compute_stroke_width('lines', child) + ' ' \
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| 350 | + self.compute_stroke_opacity(child)
|
|---|
| 351 |
|
|---|
| 352 | def compute_dot_style(self, node):
|
|---|
| 353 | return self.compute_dot_size(node) + ' ' \
|
|---|
| 354 | + self.compute_fill_opacity(node) + ' ' \
|
|---|
| 355 | + self.compute_dot_fill(node)
|
|---|
| 356 |
|
|---|
| 357 | def compute_stroke_color(self, part, node):
|
|---|
| 358 | color = self.compute_property(part, 'color', node)
|
|---|
| 359 | return 'stroke="rgb(' + str(color[0]) + '%,' + str(color[1]) + '%,' + str(color[2]) + '%)"'
|
|---|
| 360 |
|
|---|
| 361 | def compute_stroke_width(self, part, node):
|
|---|
| 362 | return 'stroke-width="' + str(self.compute_property(part, 'width', node)) + '"'
|
|---|
| 363 |
|
|---|
| 364 | def compute_stroke_opacity(self, node):
|
|---|
| 365 | return 'stroke-opacity="' + str(self.compute_property('lines', 'opacity', node)) + '"'
|
|---|
| 366 |
|
|---|
| 367 | def compute_fill_opacity(self, node):
|
|---|
| 368 | return 'fill-opacity="' + str(self.compute_property('dots', 'opacity', node)) + '"'
|
|---|
| 369 |
|
|---|
| 370 | def compute_dot_size(self, node):
|
|---|
| 371 | return 'r="' + str(self.compute_property('dots', 'size', node)) + '"'
|
|---|
| 372 |
|
|---|
| 373 | def compute_dot_fill(self, node):
|
|---|
| 374 | color = self.compute_property('dots', 'color', node)
|
|---|
| 375 | return 'fill="rgb(' + str(color[0]) + '%,' + str(color[1]) + '%,' + str(color[2]) + '%)"'
|
|---|
| 376 |
|
|---|
| 377 | class Designer:
|
|---|
| 378 |
|
|---|
| 379 | def __init__(self, tree, jitter=False, time="GENERATIONAL", balance="DENSITY"):
|
|---|
| 380 | self.props = {}
|
|---|
| 381 |
|
|---|
| 382 | self.tree = tree
|
|---|
| 383 |
|
|---|
| 384 | self.TIME = time
|
|---|
| 385 | self.JITTER = jitter
|
|---|
| 386 |
|
|---|
| 387 | if balance == "RANDOM":
|
|---|
| 388 | self.xmin_crowd = self.xmin_crowd_random
|
|---|
| 389 | elif balance == "MIN":
|
|---|
| 390 | self.xmin_crowd = self.xmin_crowd_min
|
|---|
| 391 | elif balance == "DENSITY":
|
|---|
| 392 | self.xmin_crowd = self.xmin_crowd_density
|
|---|
| 393 | else:
|
|---|
| 394 | raise ValueError("Error, the value of BALANCE does not match any expected value.")
|
|---|
| 395 |
|
|---|
| 396 | def calculate_measures(self):
|
|---|
| 397 | print("Calculating measures...")
|
|---|
| 398 | self.compute_depth()
|
|---|
| 399 | self.compute_adepth()
|
|---|
| 400 | self.compute_children()
|
|---|
| 401 | self.compute_kind()
|
|---|
| 402 | self.compute_time()
|
|---|
| 403 | self.compute_progress()
|
|---|
| 404 | self.compute_custom()
|
|---|
| 405 |
|
|---|
| 406 | def xmin_crowd_random(self, x1, x2, y):
|
|---|
| 407 | return (x1 if random.randrange(2) == 0 else x2)
|
|---|
| 408 |
|
|---|
| 409 | def xmin_crowd_min(self, x1, x2, y):
|
|---|
| 410 | x1_closest = 999999
|
|---|
| 411 | x2_closest = 999999
|
|---|
| 412 | miny = y-3
|
|---|
| 413 | maxy = y+3
|
|---|
| 414 | i = bisect.bisect_left(self.y_sorted, miny)
|
|---|
| 415 | while True:
|
|---|
| 416 | if len(self.positions_sorted) <= i or self.positions_sorted[i]['y'] > maxy:
|
|---|
| 417 | break
|
|---|
| 418 | pos = self.positions_sorted[i]
|
|---|
| 419 |
|
|---|
| 420 | x1_closest = min(x1_closest, abs(x1-pos['x']))
|
|---|
| 421 | x2_closest = min(x2_closest, abs(x2-pos['x']))
|
|---|
| 422 |
|
|---|
| 423 | i += 1
|
|---|
| 424 | return (x1 if x1_closest > x2_closest else x2)
|
|---|
| 425 |
|
|---|
| 426 | def xmin_crowd_density(self, x1, x2, y):
|
|---|
| 427 | # TODO experimental - requires further work to make it less 'jumpy' and more predictable
|
|---|
| 428 | CONST_LOCAL_AREA_RADIUS = 5
|
|---|
| 429 | CONST_GLOBAL_AREA_RADIUS = 10
|
|---|
| 430 | CONST_WINDOW_SIZE = 20000 #TODO should depend on the maxY ?
|
|---|
| 431 | x1_dist_loc = 0
|
|---|
| 432 | x2_dist_loc = 0
|
|---|
| 433 | count_loc = 1
|
|---|
| 434 | x1_dist_glob = 0
|
|---|
| 435 | x2_dist_glob = 0
|
|---|
| 436 | count_glob = 1
|
|---|
| 437 | miny = y-CONST_WINDOW_SIZE
|
|---|
| 438 | maxy = y+CONST_WINDOW_SIZE
|
|---|
| 439 | i_left = bisect.bisect_left(self.y_sorted, miny)
|
|---|
| 440 | i_right = bisect.bisect_right(self.y_sorted, maxy)
|
|---|
| 441 | #TODO test: maxy=y should give the same results, right?
|
|---|
| 442 |
|
|---|
| 443 | def include_pos(pos):
|
|---|
| 444 | nonlocal x1_dist_loc, x2_dist_loc, x1_dist_glob, x2_dist_glob, count_loc, count_glob
|
|---|
| 445 |
|
|---|
| 446 | dysq = (pos['y']-y)**2 + 1 #+1 so 1/dysq is at most 1
|
|---|
| 447 | dx1 = math.fabs(pos['x']-x1)
|
|---|
| 448 | dx2 = math.fabs(pos['x']-x2)
|
|---|
| 449 |
|
|---|
| 450 | d = math.fabs(pos['x'] - (x1+x2)/2)
|
|---|
| 451 |
|
|---|
| 452 | if d < CONST_LOCAL_AREA_RADIUS:
|
|---|
| 453 | x1_dist_loc += math.sqrt(dx1/dysq + dx1**2)
|
|---|
| 454 | x2_dist_loc += math.sqrt(dx2/dysq + dx2**2)
|
|---|
| 455 | count_loc += 1
|
|---|
| 456 | elif d > CONST_GLOBAL_AREA_RADIUS:
|
|---|
| 457 | x1_dist_glob += math.sqrt(dx1/dysq + dx1**2)
|
|---|
| 458 | x2_dist_glob += math.sqrt(dx2/dysq + dx2**2)
|
|---|
| 459 | count_glob += 1
|
|---|
| 460 |
|
|---|
| 461 | # optimized to draw from all the nodes, if less than 10 nodes in the range
|
|---|
| 462 | if len(self.positions_sorted) > i_left:
|
|---|
| 463 | if i_right - i_left < 10:
|
|---|
| 464 | for j in range(i_left, i_right):
|
|---|
| 465 | include_pos(self.positions_sorted[j])
|
|---|
| 466 | else:
|
|---|
| 467 | for j in range(10):
|
|---|
| 468 | pos = self.positions_sorted[random.randrange(i_left, i_right)]
|
|---|
| 469 | include_pos(pos)
|
|---|
| 470 |
|
|---|
| 471 | return (x1 if (x1_dist_loc-x2_dist_loc)/count_loc-(x1_dist_glob-x2_dist_glob)/count_glob > 0 else x2)
|
|---|
| 472 | #return (x1 if x1_dist +random.gauss(0, 0.00001) > x2_dist +random.gauss(0, 0.00001) else x2)
|
|---|
| 473 | #print(x1_dist, x2_dist)
|
|---|
| 474 | #x1_dist = x1_dist**2
|
|---|
| 475 | #x2_dist = x2_dist**2
|
|---|
| 476 | #return x1 if x1_dist+x2_dist==0 else (x1*x1_dist + x2*x2_dist) / (x1_dist+x2_dist) + random.gauss(0, 0.01)
|
|---|
| 477 | #return (x1 if random.randint(0, int(x1_dist+x2_dist)) < x1_dist else x2)
|
|---|
| 478 |
|
|---|
| 479 | def calculate_node_positions(self, ignore_last=0):
|
|---|
| 480 | print("Calculating positions...")
|
|---|
| 481 |
|
|---|
| 482 | def add_node(node):
|
|---|
| 483 | index = bisect.bisect_left(self.y_sorted, node['y'])
|
|---|
| 484 | self.y_sorted.insert(index, node['y'])
|
|---|
| 485 | self.positions_sorted.insert(index, node)
|
|---|
| 486 | self.positions[node['id']] = node
|
|---|
| 487 |
|
|---|
| 488 | self.positions_sorted = [{'x':0, 'y':0, 'id':0}]
|
|---|
| 489 | self.y_sorted = [0]
|
|---|
| 490 | self.positions = [{} for x in range(len(self.tree.parents))]
|
|---|
| 491 | self.positions[0] = {'x':0, 'y':0, 'id':0}
|
|---|
| 492 |
|
|---|
| 493 | # order by maximum depth of the parent guarantees that co child is evaluated before its parent
|
|---|
| 494 | visiting_order = [i for i in range(0, len(self.tree.parents))]
|
|---|
| 495 | visiting_order = sorted(visiting_order, key=lambda q:
|
|---|
| 496 | 0 if q == 0 else max([self.props["depth"][d] for d in self.tree.parents[q]]))
|
|---|
| 497 |
|
|---|
| 498 | start_time = timelib.time()
|
|---|
| 499 |
|
|---|
| 500 | # for each child of the current node
|
|---|
| 501 | for node_counter,child in enumerate(visiting_order, start=1):
|
|---|
| 502 | # debug info - elapsed time
|
|---|
| 503 | if node_counter % 100000 == 0:
|
|---|
| 504 | print("%d%%\t%d\t%g" % (node_counter*100/len(self.tree.parents), node_counter, timelib.time()-start_time))
|
|---|
| 505 | start_time = timelib.time()
|
|---|
| 506 |
|
|---|
| 507 | # using normalized adepth
|
|---|
| 508 | if self.props['adepth'][child] >= ignore_last/self.props['adepth_max']:
|
|---|
| 509 |
|
|---|
| 510 | ypos = 0
|
|---|
| 511 | if self.TIME == "BIRTHS":
|
|---|
| 512 | ypos = child
|
|---|
| 513 | elif self.TIME == "GENERATIONAL":
|
|---|
| 514 | # one more than its parent (what if more than one parent?)
|
|---|
| 515 | ypos = max([self.positions[par]['y'] for par, v in self.tree.parents[child].items()])+1 \
|
|---|
| 516 | if self.tree.parents[child] else 0
|
|---|
| 517 | elif self.TIME == "REAL":
|
|---|
| 518 | ypos = self.tree.time[child]
|
|---|
| 519 |
|
|---|
| 520 | if len(self.tree.parents[child]) == 1:
|
|---|
| 521 | # if current_node is the only parent
|
|---|
| 522 | parent, similarity = [(par, v) for par, v in self.tree.parents[child].items()][0]
|
|---|
| 523 |
|
|---|
| 524 | if self.JITTER:
|
|---|
| 525 | dissimilarity = (1-similarity) + random.gauss(0, 0.01) + 0.001
|
|---|
| 526 | else:
|
|---|
| 527 | dissimilarity = (1-similarity) + 0.001
|
|---|
| 528 | add_node({'id':child, 'y':ypos, 'x':
|
|---|
| 529 | self.xmin_crowd(self.positions[parent]['x']-dissimilarity,
|
|---|
| 530 | self.positions[parent]['x']+dissimilarity, ypos)})
|
|---|
| 531 | else:
|
|---|
| 532 | # position weighted by the degree of inheritence from each parent
|
|---|
| 533 | total_inheretance = sum([v for k, v in self.tree.parents[child].items()])
|
|---|
| 534 | xpos = sum([self.positions[k]['x']*v/total_inheretance
|
|---|
| 535 | for k, v in self.tree.parents[child].items()])
|
|---|
| 536 | if self.JITTER:
|
|---|
| 537 | add_node({'id':child, 'y':ypos, 'x':xpos + random.gauss(0, 0.1)})
|
|---|
| 538 | else:
|
|---|
| 539 | add_node({'id':child, 'y':ypos, 'x':xpos})
|
|---|
| 540 |
|
|---|
| 541 |
|
|---|
| 542 | def compute_custom(self):
|
|---|
| 543 | for prop in self.tree.props:
|
|---|
| 544 | self.props[prop] = [None for x in range(len(self.tree.children))]
|
|---|
| 545 |
|
|---|
| 546 | for i in range(len(self.props[prop])):
|
|---|
| 547 | self.props[prop][i] = self.tree.props[prop][i]
|
|---|
| 548 |
|
|---|
| 549 | self.normalize_prop(prop)
|
|---|
| 550 |
|
|---|
| 551 | def compute_time(self):
|
|---|
| 552 | # simple rewrite from the tree
|
|---|
| 553 | self.props["time"] = [0 for x in range(len(self.tree.children))]
|
|---|
| 554 |
|
|---|
| 555 | for i in range(len(self.props['time'])):
|
|---|
| 556 | self.props['time'][i] = self.tree.time[i]
|
|---|
| 557 |
|
|---|
| 558 | self.normalize_prop('time')
|
|---|
| 559 |
|
|---|
| 560 | def compute_kind(self):
|
|---|
| 561 | # simple rewrite from the tree
|
|---|
| 562 | self.props["kind"] = [0 for x in range(len(self.tree.children))]
|
|---|
| 563 |
|
|---|
| 564 | for i in range (len(self.props['kind'])):
|
|---|
| 565 | self.props['kind'][i] = str(self.tree.kind[i])
|
|---|
| 566 |
|
|---|
| 567 | def compute_depth(self):
|
|---|
| 568 | self.props["depth"] = [999999999 for x in range(len(self.tree.children))]
|
|---|
| 569 | visited = [0 for x in range(len(self.tree.children))]
|
|---|
| 570 |
|
|---|
| 571 | nodes_to_visit = [0]
|
|---|
| 572 | visited[0] = 1
|
|---|
| 573 | self.props["depth"][0] = 0
|
|---|
| 574 | while True:
|
|---|
| 575 | current_node = nodes_to_visit[0]
|
|---|
| 576 |
|
|---|
| 577 | for child in self.tree.children[current_node]:
|
|---|
| 578 | if visited[child] == 0:
|
|---|
| 579 | visited[child] = 1
|
|---|
| 580 | nodes_to_visit.append(child)
|
|---|
| 581 | self.props["depth"][child] = self.props["depth"][current_node]+1
|
|---|
| 582 | nodes_to_visit = nodes_to_visit[1:]
|
|---|
| 583 | if len(nodes_to_visit) == 0:
|
|---|
| 584 | break
|
|---|
| 585 |
|
|---|
| 586 | self.normalize_prop('depth')
|
|---|
| 587 |
|
|---|
| 588 | def compute_adepth(self):
|
|---|
| 589 | self.props["adepth"] = [0 for x in range(len(self.tree.children))]
|
|---|
| 590 |
|
|---|
| 591 | # order by maximum depth of the parent guarantees that co child is evaluated before its parent
|
|---|
| 592 | visiting_order = [i for i in range(0, len(self.tree.parents))]
|
|---|
| 593 | visiting_order = sorted(visiting_order, key=lambda q:
|
|---|
| 594 | 0 if q == 0 else max([self.props["depth"][d] for d in self.tree.parents[q]]))[::-1]
|
|---|
| 595 |
|
|---|
| 596 | for node in visiting_order:
|
|---|
| 597 | children = self.tree.children[node]
|
|---|
| 598 | if len(children) != 0:
|
|---|
| 599 | # 0 by default
|
|---|
| 600 | self.props["adepth"][node] = max([self.props["adepth"][child] for child in children])+1
|
|---|
| 601 | self.normalize_prop('adepth')
|
|---|
| 602 |
|
|---|
| 603 | def compute_children(self):
|
|---|
| 604 | self.props["children"] = [0 for x in range(len(self.tree.children))]
|
|---|
| 605 | for i in range (len(self.props['children'])):
|
|---|
| 606 | self.props['children'][i] = len(self.tree.children[i])
|
|---|
| 607 |
|
|---|
| 608 | self.normalize_prop('children')
|
|---|
| 609 |
|
|---|
| 610 | def compute_progress(self):
|
|---|
| 611 | self.props["progress"] = [0 for x in range(len(self.tree.children))]
|
|---|
| 612 | for i in range(len(self.props['children'])):
|
|---|
| 613 | times = sorted([self.props["time"][self.tree.children[i][j]]*100000 for j in range(len(self.tree.children[i]))])
|
|---|
| 614 | if len(times) > 4:
|
|---|
| 615 | times = [times[i+1] - times[i] for i in range(len(times)-1)]
|
|---|
| 616 | #print(times)
|
|---|
| 617 | slope, intercept, r_value, p_value, std_err = stats.linregress(range(len(times)), times)
|
|---|
| 618 | self.props['progress'][i] = slope if not np.isnan(slope) and not np.isinf(slope) else 0
|
|---|
| 619 |
|
|---|
| 620 | for i in range(0, 5):
|
|---|
| 621 | self.props['progress'][self.props['progress'].index(min(self.props['progress']))] = 0
|
|---|
| 622 | self.props['progress'][self.props['progress'].index(max(self.props['progress']))] = 0
|
|---|
| 623 |
|
|---|
| 624 | mini = min(self.props['progress'])
|
|---|
| 625 | maxi = max(self.props['progress'])
|
|---|
| 626 | for k in range(len(self.props['progress'])):
|
|---|
| 627 | if self.props['progress'][k] == 0:
|
|---|
| 628 | self.props['progress'][k] = mini
|
|---|
| 629 |
|
|---|
| 630 | #for k in range(len(self.props['progress'])):
|
|---|
| 631 | # self.props['progress'][k] = 1-self.props['progress'][k]
|
|---|
| 632 |
|
|---|
| 633 | self.normalize_prop('progress')
|
|---|
| 634 |
|
|---|
| 635 | def normalize_prop(self, prop):
|
|---|
| 636 | noneless = [v for v in self.props[prop] if (type(v)!=str and type(v)!=list)]
|
|---|
| 637 | if len(noneless) > 0:
|
|---|
| 638 | max_val = max(noneless)
|
|---|
| 639 | min_val = min(noneless)
|
|---|
| 640 | print("%s: [%g, %g]" % (prop, min_val, max_val))
|
|---|
| 641 | self.props[prop +'_max'] = max_val
|
|---|
| 642 | self.props[prop +'_min'] = min_val
|
|---|
| 643 | for i in range(len(self.props[prop])):
|
|---|
| 644 | if self.props[prop][i] is not None:
|
|---|
| 645 | qqq = self.props[prop][i]
|
|---|
| 646 | self.props[prop][i] = 0 if max_val == min_val else (self.props[prop][i] - min_val) / (max_val - min_val)
|
|---|
| 647 |
|
|---|
| 648 | class TreeData:
|
|---|
| 649 | simple_data = None
|
|---|
| 650 |
|
|---|
| 651 | children = []
|
|---|
| 652 | parents = []
|
|---|
| 653 | time = []
|
|---|
| 654 | kind = []
|
|---|
| 655 |
|
|---|
| 656 | def __init__(self): #, simple_data=False):
|
|---|
| 657 | #self.simple_data = simple_data
|
|---|
| 658 | pass
|
|---|
| 659 |
|
|---|
| 660 | def load(self, filename, max_nodes=0):
|
|---|
| 661 | print("Loading...")
|
|---|
| 662 |
|
|---|
| 663 | CLI_PREFIX = "Script.Message:"
|
|---|
| 664 | default_props = ["Time", "FromIDs", "ID", "Operation", "Inherited"]
|
|---|
| 665 |
|
|---|
| 666 | self.ids = {}
|
|---|
| 667 | def get_id(id, createOnError = True):
|
|---|
| 668 | if createOnError:
|
|---|
| 669 | if id not in self.ids:
|
|---|
| 670 | self.ids[id] = len(self.ids)
|
|---|
| 671 | else:
|
|---|
| 672 | if id not in self.ids:
|
|---|
| 673 | return None
|
|---|
| 674 | return self.ids[id]
|
|---|
| 675 |
|
|---|
| 676 | file = open(filename)
|
|---|
| 677 |
|
|---|
| 678 | # counting the number of expected nodes
|
|---|
| 679 | nodes = 0
|
|---|
| 680 | for line in file:
|
|---|
| 681 | line_arr = line.split(' ', 1)
|
|---|
| 682 | if len(line_arr) == 2:
|
|---|
| 683 | if line_arr[0] == CLI_PREFIX:
|
|---|
| 684 | line_arr = line_arr[1].split(' ', 1)
|
|---|
| 685 | if line_arr[0] == "[OFFSPRING]":
|
|---|
| 686 | nodes += 1
|
|---|
| 687 |
|
|---|
| 688 | nodes = min(nodes, max_nodes if max_nodes != 0 else nodes)+1
|
|---|
| 689 | self.parents = [{} for x in range(nodes)]
|
|---|
| 690 | self.children = [[] for x in range(nodes)]
|
|---|
| 691 | self.time = [0] * nodes
|
|---|
| 692 | self.kind = [0] * nodes
|
|---|
| 693 | self.life_lenght = [0] * nodes
|
|---|
| 694 | self.props = {}
|
|---|
| 695 |
|
|---|
| 696 | print("nodes: %d" % len(self.parents))
|
|---|
| 697 |
|
|---|
| 698 | file.seek(0)
|
|---|
| 699 | loaded_so_far = 0
|
|---|
| 700 | lasttime = timelib.time()
|
|---|
| 701 | for line in file:
|
|---|
| 702 | line_arr = line.split(' ', 1)
|
|---|
| 703 | if len(line_arr) == 2:
|
|---|
| 704 | if line_arr[0] == CLI_PREFIX:
|
|---|
| 705 | line_arr = line_arr[1].split(' ', 1)
|
|---|
| 706 | if line_arr[0] == "[OFFSPRING]":
|
|---|
| 707 | try:
|
|---|
| 708 | creature = json.loads(line_arr[1])
|
|---|
| 709 | except ValueError:
|
|---|
| 710 | print("Json format error - the line cannot be read. Breaking the loading loop.")
|
|---|
| 711 | # fixing arrays by removing the last element
|
|---|
| 712 | # ! assuming that only the last line is broken !
|
|---|
| 713 | self.parents.pop()
|
|---|
| 714 | self.children.pop()
|
|---|
| 715 | self.time.pop()
|
|---|
| 716 | self.kind.pop()
|
|---|
| 717 | self.life_lenght.pop()
|
|---|
| 718 | nodes -= 1
|
|---|
| 719 | break
|
|---|
| 720 |
|
|---|
| 721 | if "FromIDs" in creature:
|
|---|
| 722 |
|
|---|
| 723 | # make sure that ID's of parents are lower than that of their children
|
|---|
| 724 | for i in range(0, len(creature["FromIDs"])):
|
|---|
| 725 | if creature["FromIDs"][i] not in self.ids:
|
|---|
| 726 | get_id("virtual_parent")
|
|---|
| 727 |
|
|---|
| 728 | creature_id = get_id(creature["ID"])
|
|---|
| 729 |
|
|---|
| 730 | # debug
|
|---|
| 731 | if loaded_so_far%1000 == 0:
|
|---|
| 732 | #print(". " + str(creature_id) + " " + str(timelib.time() - lasttime))
|
|---|
| 733 | lasttime = timelib.time()
|
|---|
| 734 |
|
|---|
| 735 | # we assign to each parent its contribution to the genotype of the child
|
|---|
| 736 | for i in range(0, len(creature["FromIDs"])):
|
|---|
| 737 | if creature["FromIDs"][i] in self.ids:
|
|---|
| 738 | parent_id = get_id(creature["FromIDs"][i])
|
|---|
| 739 | else:
|
|---|
| 740 | parent_id = get_id("virtual_parent")
|
|---|
| 741 | inherited = (creature["Inherited"][i] if 'Inherited' in creature else 1)
|
|---|
| 742 | self.parents[creature_id][parent_id] = inherited
|
|---|
| 743 |
|
|---|
| 744 | if "Time" in creature:
|
|---|
| 745 | self.time[creature_id] = creature["Time"]
|
|---|
| 746 |
|
|---|
| 747 | if "Kind" in creature:
|
|---|
| 748 | self.kind[creature_id] = creature["Kind"]
|
|---|
| 749 |
|
|---|
| 750 | for prop in creature:
|
|---|
| 751 | if prop not in default_props:
|
|---|
| 752 | if prop not in self.props:
|
|---|
| 753 | self.props[prop] = [0 for i in range(nodes)]
|
|---|
| 754 | self.props[prop][creature_id] = creature[prop]
|
|---|
| 755 |
|
|---|
| 756 | loaded_so_far += 1
|
|---|
| 757 | else:
|
|---|
| 758 | raise LoadingError("[OFFSPRING] misses the 'FromIDs' field!")
|
|---|
| 759 | if line_arr[0] == "[DIED]":
|
|---|
| 760 | creature = json.loads(line_arr[1])
|
|---|
| 761 | creature_id = get_id(creature["ID"], False)
|
|---|
| 762 | if creature_id is not None:
|
|---|
| 763 | for prop in creature:
|
|---|
| 764 | if prop not in default_props:
|
|---|
| 765 | if prop not in self.props:
|
|---|
| 766 | self.props[prop] = [0 for i in range(nodes)]
|
|---|
| 767 | self.props[prop][creature_id] = creature[prop]
|
|---|
| 768 |
|
|---|
| 769 |
|
|---|
| 770 | if loaded_so_far >= max_nodes and max_nodes != 0:
|
|---|
| 771 | break
|
|---|
| 772 |
|
|---|
| 773 | for k in range(len(self.parents)):
|
|---|
| 774 | v = self.parents[k]
|
|---|
| 775 | for val in self.parents[k]:
|
|---|
| 776 | self.children[val].append(k)
|
|---|
| 777 |
|
|---|
| 778 | depth = {}
|
|---|
| 779 | kind = {}
|
|---|
| 780 |
|
|---|
| 781 | def main():
|
|---|
| 782 |
|
|---|
| 783 | parser = argparse.ArgumentParser(description='Draws a genealogical tree (generates a SVG file) based on parent-child relationship '
|
|---|
| 784 | 'information from a text file. Supports files generated by Framsticks experiments.')
|
|---|
| 785 | parser.add_argument('-i', '--in', dest='input', required=True, help='input file name with stuctured evolutionary data')
|
|---|
| 786 | parser.add_argument('-o', '--out', dest='output', required=True, help='output file name for the evolutionary tree (SVG/PNG/JPG/BMP)')
|
|---|
| 787 | parser.add_argument('-c', '--config', dest='config', default="", help='config file name ')
|
|---|
| 788 |
|
|---|
| 789 | parser.add_argument('-W', '--width', default=600, type=int, dest='width', help='width of the output image (600 by default)')
|
|---|
| 790 | parser.add_argument('-H', '--height', default=800, type=int, dest='height', help='height of the output image (800 by default)')
|
|---|
| 791 | parser.add_argument('-m', '--multi', default=1, type=int, dest='multi', help='multisampling factor (applicable only for raster images)')
|
|---|
| 792 |
|
|---|
| 793 | parser.add_argument('-t', '--time', default='GENERATIONAL', dest='time', help='values on vertical axis (BIRTHS/GENERATIONAL(d)/REAL); '
|
|---|
| 794 | 'BIRTHS: time measured as the number of births since the beginning; '
|
|---|
| 795 | 'GENERATIONAL: time measured as number of ancestors; '
|
|---|
| 796 | 'REAL: real time of the simulation')
|
|---|
| 797 | parser.add_argument('-b', '--balance', default='DENSITY', dest='balance', help='method of placing nodes in the tree (RANDOM/MIN/DENSITY(d))')
|
|---|
| 798 | parser.add_argument('-s', '--scale', default='SIMPLE', dest='scale', help='type of timescale added to the tree (NONE(d)/SIMPLE)')
|
|---|
| 799 | parser.add_argument('-j', '--jitter', dest="jitter", action='store_true', help='draw horizontal positions of children from the normal distribution')
|
|---|
| 800 | parser.add_argument('-p', '--skip', dest="skip", type=int, default=0, help='skip last P levels of the tree (0 by default)')
|
|---|
| 801 | parser.add_argument('-x', '--max-nodes', type=int, default=0, dest='max_nodes', help='maximum number of nodes drawn (starting from the first one)')
|
|---|
| 802 | parser.add_argument('--seed', type=int, dest='seed', help='seed for the random number generator (-1 for random)')
|
|---|
| 803 |
|
|---|
| 804 | parser.set_defaults(draw_tree=True)
|
|---|
| 805 | parser.set_defaults(draw_skeleton=False)
|
|---|
| 806 | parser.set_defaults(draw_spine=False)
|
|---|
| 807 |
|
|---|
| 808 | parser.set_defaults(seed=-1)
|
|---|
| 809 |
|
|---|
| 810 | args = parser.parse_args()
|
|---|
| 811 |
|
|---|
| 812 | TIME = args.time.upper()
|
|---|
| 813 | BALANCE = args.balance.upper()
|
|---|
| 814 | SCALE = args.scale.upper()
|
|---|
| 815 | JITTER = args.jitter
|
|---|
| 816 | if not TIME in ['BIRTHS', 'GENERATIONAL', 'REAL']\
|
|---|
| 817 | or not BALANCE in ['RANDOM', 'MIN', 'DENSITY']\
|
|---|
| 818 | or not SCALE in ['NONE', 'SIMPLE']:
|
|---|
| 819 | print("Incorrect value of one of the parameters! (time or balance or scale).") #user has to figure out which parameter is wrong...
|
|---|
| 820 | return
|
|---|
| 821 |
|
|---|
| 822 | dir = args.input
|
|---|
| 823 | seed = args.seed
|
|---|
| 824 | if seed == -1:
|
|---|
| 825 | seed = random.randint(0, 10000)
|
|---|
| 826 | random.seed(seed)
|
|---|
| 827 | print("randomseed:", seed)
|
|---|
| 828 |
|
|---|
| 829 | tree = TreeData()
|
|---|
| 830 | tree.load(dir, max_nodes=args.max_nodes)
|
|---|
| 831 |
|
|---|
| 832 |
|
|---|
| 833 | designer = Designer(tree, jitter=JITTER, time=TIME, balance=BALANCE)
|
|---|
| 834 | designer.calculate_measures()
|
|---|
| 835 | designer.calculate_node_positions(ignore_last=args.skip)
|
|---|
| 836 |
|
|---|
| 837 | if args.output.endswith(".svg"):
|
|---|
| 838 | drawer = SvgDrawer(designer, args.config, w=args.width, h=args.height)
|
|---|
| 839 | else:
|
|---|
| 840 | drawer = PngDrawer(designer, args.config, w=args.width, h=args.height)
|
|---|
| 841 | drawer.draw_design(args.output, args.input, multi=args.multi, scale=SCALE)
|
|---|
| 842 |
|
|---|
| 843 |
|
|---|
| 844 | main()
|
|---|
