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