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 copy
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7 | import time as timelib
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8 | from PIL import Image, ImageDraw, ImageFont
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9 | from scipy import stats
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10 | from matplotlib import colors
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11 | import numpy as np
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12 |
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13 | class LoadingError(Exception):
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14 | pass
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15 |
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16 | class Drawer:
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17 |
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18 | def __init__(self, design, config_file, w=600, h=800, w_margin=10, h_margin=20):
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19 | self.design = design
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20 | self.width = w
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21 | self.height = h
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22 | self.w_margin = w_margin
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23 | self.h_margin = h_margin
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24 | self.w_no_margs = w - 2* w_margin
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25 | self.h_no_margs = h - 2* h_margin
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26 |
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27 | self.color_converter = colors.ColorConverter()
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28 |
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29 | self.settings = {
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30 | 'colors_of_kinds': ['red', 'green', 'blue', 'magenta', 'yellow', 'cyan', 'orange', 'purple'],
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31 | 'dots': {
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32 | 'color': {
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33 | 'meaning': 'Lifespan',
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34 | 'normalize_cmap': False,
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35 | 'cmap': {},
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36 | 'start': 'red',
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37 | 'end': 'green',
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38 | 'bias': 1
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39 | },
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40 | 'size': {
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41 | 'meaning': 'EnergyEaten',
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42 | 'start': 1,
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43 | 'end': 6,
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44 | 'bias': 0.5
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45 | },
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46 | 'opacity': {
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47 | 'meaning': 'EnergyEaten',
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48 | 'start': 0.2,
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49 | 'end': 1,
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50 | 'bias': 1
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51 | }
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52 | },
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53 | 'lines': {
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54 | 'color': {
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55 | 'meaning': 'adepth',
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56 | 'normalize_cmap': False,
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57 | 'cmap': {},
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58 | 'start': 'black',
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59 | 'end': 'red',
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60 | 'bias': 3
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61 | },
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62 | 'width': {
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63 | 'meaning': 'adepth',
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64 | 'start': 0.1,
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65 | 'end': 4,
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66 | 'bias': 3
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67 | },
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68 | 'opacity': {
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69 | 'meaning': 'adepth',
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70 | 'start': 0.1,
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71 | 'end': 0.8,
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72 | 'bias': 5
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73 | }
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74 | }
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75 | }
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76 |
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77 | def merge(source, destination):
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78 | for key, value in source.items():
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79 | if isinstance(value, dict):
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80 | node = destination.setdefault(key, {})
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81 | merge(value, node)
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82 | else:
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83 | destination[key] = value
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84 | return destination
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85 |
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86 | if config_file != "":
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87 | with open(config_file) as config:
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88 | c = json.load(config)
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89 | self.settings = merge(c, self.settings)
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90 | #print(json.dumps(self.settings, indent=4, sort_keys=True))
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91 |
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92 | self.compile_cmaps()
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93 |
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94 | def compile_cmaps(self):
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95 | def normalize_and_compile_cmap(cmap):
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96 | for key in cmap:
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97 | for arr in cmap[key]:
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98 | arr[0] = (arr[0] - cmap[key][0][0]) / (cmap[key][-1][0] - cmap[key][0][0])
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99 | return colors.LinearSegmentedColormap('Custom', cmap)
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100 |
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101 | for part in ['dots', 'lines']:
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102 | if self.settings[part]['color']['cmap']:
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103 | if self.settings[part]['color']['normalize_cmap']:
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104 | cmap = self.settings[part]['color']['cmap']
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105 | min = self.design.props[self.settings[part]['color']['meaning'] + "_min"]
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106 | max = self.design.props[self.settings[part]['color']['meaning'] + "_max"]
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107 |
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108 | for key in cmap:
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109 | if cmap[key][0][0] > min:
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110 | cmap[key].insert(0, cmap[key][0][:])
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111 | cmap[key][0][0] = min
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112 | if cmap[key][-1][0] < max:
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113 | cmap[key].append(cmap[key][-1][:])
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114 | cmap[key][-1][0] = max
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115 |
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116 | og_cmap = normalize_and_compile_cmap(copy.deepcopy(cmap))
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117 |
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118 | col2key = {'red':0, 'green':1, 'blue':2}
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119 | for key in cmap:
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120 | # for color from (r/g/b) #n's should be the same for all keys!
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121 | n_min = (min - cmap[key][0][0]) / (cmap[key][-1][0] - cmap[key][0][0])
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122 | n_max = (max - cmap[key][0][0]) / (cmap[key][-1][0] - cmap[key][0][0])
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123 |
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124 | min_col = og_cmap(n_min)
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125 | max_col = og_cmap(n_max)
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126 |
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127 | cmap[key][0] = [min, min_col[col2key[key]], min_col[col2key[key]]]
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128 | cmap[key][-1] = [max, max_col[col2key[key]], max_col[col2key[key]]]
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129 | print(self.settings[part]['color']['cmap'])
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130 | self.settings[part]['color']['cmap'] = normalize_and_compile_cmap(self.settings[part]['color']['cmap'])
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131 |
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132 | def draw_dots(self, file, min_width, max_width, max_height):
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133 | for i in range(len(self.design.positions)):
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134 | node = self.design.positions[i]
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135 | if 'x' not in node:
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136 | continue
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137 | dot_style = self.compute_dot_style(node=i)
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138 | self.add_dot(file, (self.w_margin+self.w_no_margs*(node['x']-min_width)/(max_width-min_width),
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139 | self.h_margin+self.h_no_margs*node['y']/max_height), dot_style)
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140 |
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141 | def draw_lines(self, file, min_width, max_width, max_height):
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142 | for parent in range(len(self.design.positions)):
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143 | par_pos = self.design.positions[parent]
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144 | if not 'x' in par_pos:
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145 | continue
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146 | for child in self.design.tree.children[parent]:
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147 | chi_pos = self.design.positions[child]
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148 | if 'x' not in chi_pos:
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149 | continue
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150 | line_style = self.compute_line_style(parent, child)
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151 | self.add_line(file, (self.w_margin+self.w_no_margs*(par_pos['x']-min_width)/(max_width-min_width),
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152 | self.h_margin+self.h_no_margs*par_pos['y']/max_height),
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153 | (self.w_margin+self.w_no_margs*(chi_pos['x']-min_width)/(max_width-min_width),
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154 | self.h_margin+self.h_no_margs*chi_pos['y']/max_height), line_style)
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155 |
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156 | def draw_scale(self, file, filenames):
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157 | self.add_text(file, "Generated from " + filenames[0].split("\\")[-1]
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158 | + (" and " + str(len(filenames)-1) + " more" if len(filenames) > 1 else ""), (5, 5), "start")
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159 |
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160 | start_text = ""
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161 | end_text = ""
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162 | if self.design.TIME == "BIRTHS":
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163 | start_text = "Birth #0"
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164 | end_text = "Birth #" + str(len(self.design.positions)-1)
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165 | if self.design.TIME == "REAL":
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166 | start_text = "Time " + str(min(self.design.tree.time))
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167 | end_text = "Time " + str(max(self.design.tree.time))
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168 | if self.design.TIME == "GENERATIONAL":
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169 | start_text = "Depth " + str(self.design.props['adepth_min'])
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170 | end_text = "Depth " + str(self.design.props['adepth_max'])
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171 |
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172 | self.add_dashed_line(file, (self.width*0.7, self.h_margin), (self.width, self.h_margin))
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173 | self.add_text(file, start_text, (self.width, self.h_margin), "end")
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174 | 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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175 | self.add_text(file, end_text, (self.width, self.height-self.h_margin), "end")
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176 |
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177 | def compute_property(self, part, prop, node):
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178 | start = self.settings[part][prop]['start']
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179 | end = self.settings[part][prop]['end']
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180 | value = (self.design.props[self.settings[part][prop]['meaning']][node]
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181 | if self.settings[part][prop]['meaning'] in self.design.props else 0 )
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182 | bias = self.settings[part][prop]['bias']
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183 | if prop == "color":
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184 | if not self.settings[part][prop]['cmap']:
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185 | return self.compute_color(start, end, value, bias)
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186 | else:
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187 | return self.compute_color_from_cmap(self.settings[part][prop]['cmap'], value, bias)
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188 | else:
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189 | return self.compute_value(start, end, value, bias)
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190 |
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191 | def compute_color_from_cmap(self, cmap, value, bias=1):
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192 | value = 1 - (1-value)**bias
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193 | rgba = cmap(value)
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194 | return (100*rgba[0], 100*rgba[1], 100*rgba[2])
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195 |
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196 |
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197 | def compute_color(self, start, end, value, bias=1):
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198 | if isinstance(value, str):
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199 | value = int(value)
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200 | r, g, b = self.color_converter.to_rgb(self.settings['colors_of_kinds'][value])
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201 | else:
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202 | start_color = self.color_converter.to_rgb(start)
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203 | end_color = self.color_converter.to_rgb(end)
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204 | value = 1 - (1-value)**bias
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205 | r = start_color[0]*(1-value)+end_color[0]*value
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206 | g = start_color[1]*(1-value)+end_color[1]*value
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207 | b = start_color[2]*(1-value)+end_color[2]*value
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208 | return (100*r, 100*g, 100*b)
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209 |
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210 | def compute_value(self, start, end, value, bias=1):
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211 | value = 1 - (1-value)**bias
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212 | return start*(1-value) + end*value
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213 |
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214 | class PngDrawer(Drawer):
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215 |
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216 | def scale_up(self):
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217 | self.width *= self.multi
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218 | self.height *= self.multi
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219 | self.w_margin *= self.multi
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220 | self.h_margin *= self.multi
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221 | self.h_no_margs *= self.multi
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222 | self.w_no_margs *= self.multi
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223 |
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224 | def scale_down(self):
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225 | self.width /= self.multi
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226 | self.height /= self.multi
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227 | self.w_margin /= self.multi
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228 | self.h_margin /= self.multi
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229 | self.h_no_margs /= self.multi
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230 | self.w_no_margs /= self.multi
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231 |
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232 | def draw_design(self, filename, input_filename, multi=1, scale="SIMPLE"):
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233 | print("Drawing...")
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234 |
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235 | self.multi=multi
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236 | self.scale_up()
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237 |
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238 | back = Image.new('RGBA', (self.width, self.height), (255,255,255,0))
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239 |
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240 | min_width = min([x['x'] for x in self.design.positions if 'x' in x])
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241 | max_width = max([x['x'] for x in self.design.positions if 'x' in x])
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242 | max_height = max([x['y'] for x in self.design.positions if 'y' in x])
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243 |
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244 | self.draw_lines(back, min_width, max_width, max_height)
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245 | self.draw_dots(back, min_width, max_width, max_height)
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246 |
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247 | if scale == "SIMPLE":
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248 | self.draw_scale(back, input_filename)
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249 |
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250 | #back.show()
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251 | self.scale_down()
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252 |
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253 | back.thumbnail((self.width, self.height), Image.ANTIALIAS)
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254 |
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255 | back.save(filename)
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256 |
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257 | def add_dot(self, file, pos, style):
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258 | x, y = int(pos[0]), int(pos[1])
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259 | r = style['r']*self.multi
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260 | offset = (int(x - r), int(y - r))
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261 | size = (2*int(r), 2*int(r))
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262 |
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263 | c = style['color']
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264 |
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265 | img = Image.new('RGBA', size)
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266 | ImageDraw.Draw(img).ellipse((1, 1, size[0]-1, size[1]-1),
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267 | (int(2.55*c[0]), int(2.55*c[1]), int(2.55*c[2]), int(255*style['opacity'])))
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268 | file.paste(img, offset, mask=img)
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269 |
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270 | def add_line(self, file, from_pos, to_pos, style):
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271 | fx, fy, tx, ty = int(from_pos[0]), int(from_pos[1]), int(to_pos[0]), int(to_pos[1])
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272 | w = int(style['width'])*self.multi
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273 |
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274 | offset = (min(fx-w, tx-w), min(fy-w, ty-w))
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275 | size = (abs(fx-tx)+2*w, abs(fy-ty)+2*w)
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276 | if size[0] == 0 or size[1] == 0:
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277 | return
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278 |
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279 | c = style['color']
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280 |
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281 | img = Image.new('RGBA', size)
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282 | 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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283 | (int(2.55*c[0]), int(2.55*c[1]), int(2.55*c[2]), int(255*style['opacity'])), w)
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284 | file.paste(img, offset, mask=img)
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285 |
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286 | def add_dashed_line(self, file, from_pos, to_pos):
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287 | style = {'color': (0,0,0), 'width': 1, 'opacity': 1}
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288 | sublines = 50
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289 | # TODO could be faster: compute delta and only add delta each time (but currently we do not use it often)
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290 | normdiv = 2*sublines-1
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291 | for i in range(sublines):
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292 | from_pos_sub = (self.compute_value(from_pos[0], to_pos[0], 2*i/normdiv, 1),
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293 | self.compute_value(from_pos[1], to_pos[1], 2*i/normdiv, 1))
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294 | to_pos_sub = (self.compute_value(from_pos[0], to_pos[0], (2*i+1)/normdiv, 1),
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295 | self.compute_value(from_pos[1], to_pos[1], (2*i+1)/normdiv, 1))
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296 | self.add_line(file, from_pos_sub, to_pos_sub, style)
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297 |
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298 | def add_text(self, file, text, pos, anchor, style=''):
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299 | font = ImageFont.truetype("Vera.ttf", 16*self.multi)
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300 |
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301 | img = Image.new('RGBA', (self.width, self.height))
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302 | draw = ImageDraw.Draw(img)
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303 | txtsize = draw.textsize(text, font=font)
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304 | pos = pos if anchor == "start" else (pos[0]-txtsize[0], pos[1])
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305 | draw.text(pos, text, (0,0,0), font=font)
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306 | file.paste(img, (0,0), mask=img)
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307 |
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308 | def compute_line_style(self, parent, child):
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309 | return {'color': self.compute_property('lines', 'color', child),
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310 | 'width': self.compute_property('lines', 'width', child),
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311 | 'opacity': self.compute_property('lines', 'opacity', child)}
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312 |
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313 | def compute_dot_style(self, node):
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314 | return {'color': self.compute_property('dots', 'color', node),
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315 | 'r': self.compute_property('dots', 'size', node),
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316 | 'opacity': self.compute_property('dots', 'opacity', node)}
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317 |
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318 | class SvgDrawer(Drawer):
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319 | def draw_design(self, filename, input_filename, multi=1, scale="SIMPLE"):
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320 | print("Drawing...")
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321 | file = open(filename, "w")
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322 |
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323 | min_width = min([x['x'] for x in self.design.positions if 'x' in x])
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324 | max_width = max([x['x'] for x in self.design.positions if 'x' in x])
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325 | max_height = max([x['y'] for x in self.design.positions if 'y' in x])
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326 |
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327 | file.write('<svg xmlns:svg="http://www.w3.org/2000/svg" xmlns="http://www.w3.org/2000/svg" '
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328 | 'xmlns:xlink="http://www.w3.org/1999/xlink" version="1.0" '
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329 | 'width="' + str(self.width) + '" height="' + str(self.height) + '">')
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330 |
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331 | self.draw_lines(file, min_width, max_width, max_height)
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332 | self.draw_dots(file, min_width, max_width, max_height)
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333 |
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334 | if scale == "SIMPLE":
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335 | self.draw_scale(file, input_filename)
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336 |
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337 | file.write("</svg>")
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338 | file.close()
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339 |
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340 | def add_text(self, file, text, pos, anchor, style=''):
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341 | style = (style if style != '' else 'style="font-family: Arial; font-size: 12; fill: #000000;"')
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342 | # assuming font size 12, it should be taken from the style string!
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343 | file.write('<text ' + style + ' text-anchor="' + anchor + '" x="' + str(pos[0]) + '" y="' + str(pos[1]+12) + '" >' + text + '</text>')
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344 |
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345 | def add_dot(self, file, pos, style):
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346 | file.write('<circle ' + style + ' cx="' + str(pos[0]) + '" cy="' + str(pos[1]) + '" />')
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347 |
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348 | def add_line(self, file, from_pos, to_pos, style):
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349 | file.write('<line ' + style + ' x1="' + str(from_pos[0]) + '" x2="' + str(to_pos[0]) +
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350 | '" y1="' + str(from_pos[1]) + '" y2="' + str(to_pos[1]) + '" fill="none"/>')
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351 |
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352 | def add_dashed_line(self, file, from_pos, to_pos):
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353 | style = 'stroke="black" stroke-width="0.5" stroke-opacity="1" stroke-dasharray="5, 5"'
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354 | self.add_line(file, from_pos, to_pos, style)
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355 |
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356 | def compute_line_style(self, parent, child):
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357 | return self.compute_stroke_color('lines', child) + ' ' \
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358 | + self.compute_stroke_width('lines', child) + ' ' \
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359 | + self.compute_stroke_opacity(child)
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360 |
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361 | def compute_dot_style(self, node):
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362 | return self.compute_dot_size(node) + ' ' \
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363 | + self.compute_fill_opacity(node) + ' ' \
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364 | + self.compute_dot_fill(node)
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365 |
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366 | def compute_stroke_color(self, part, node):
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367 | color = self.compute_property(part, 'color', node)
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368 | return 'stroke="rgb(' + str(color[0]) + '%,' + str(color[1]) + '%,' + str(color[2]) + '%)"'
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369 |
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370 | def compute_stroke_width(self, part, node):
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371 | return 'stroke-width="' + str(self.compute_property(part, 'width', node)) + '"'
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372 |
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373 | def compute_stroke_opacity(self, node):
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374 | return 'stroke-opacity="' + str(self.compute_property('lines', 'opacity', node)) + '"'
|
---|
375 |
|
---|
376 | def compute_fill_opacity(self, node):
|
---|
377 | return 'fill-opacity="' + str(self.compute_property('dots', 'opacity', node)) + '"'
|
---|
378 |
|
---|
379 | def compute_dot_size(self, node):
|
---|
380 | return 'r="' + str(self.compute_property('dots', 'size', node)) + '"'
|
---|
381 |
|
---|
382 | def compute_dot_fill(self, node):
|
---|
383 | color = self.compute_property('dots', 'color', node)
|
---|
384 | return 'fill="rgb(' + str(color[0]) + '%,' + str(color[1]) + '%,' + str(color[2]) + '%)"'
|
---|
385 |
|
---|
386 | class Designer:
|
---|
387 |
|
---|
388 | def __init__(self, tree, jitter=False, time="GENERATIONAL", balance="DENSITY"):
|
---|
389 | self.props = {}
|
---|
390 |
|
---|
391 | self.tree = tree
|
---|
392 |
|
---|
393 | self.TIME = time
|
---|
394 | self.JITTER = jitter
|
---|
395 |
|
---|
396 | if balance == "RANDOM":
|
---|
397 | self.xmin_crowd = self.xmin_crowd_random
|
---|
398 | elif balance == "MIN":
|
---|
399 | self.xmin_crowd = self.xmin_crowd_min
|
---|
400 | elif balance == "DENSITY":
|
---|
401 | self.xmin_crowd = self.xmin_crowd_density
|
---|
402 | else:
|
---|
403 | raise ValueError("Error, the value of BALANCE does not match any expected value.")
|
---|
404 |
|
---|
405 | def calculate_measures(self):
|
---|
406 | print("Calculating measures...")
|
---|
407 | self.compute_depth()
|
---|
408 | self.compute_maxdepth()
|
---|
409 | self.compute_adepth()
|
---|
410 | self.compute_children()
|
---|
411 | self.compute_kind()
|
---|
412 | self.compute_time()
|
---|
413 | self.compute_progress()
|
---|
414 | self.compute_custom()
|
---|
415 |
|
---|
416 | def xmin_crowd_random(self, x1, x2, y):
|
---|
417 | return (x1 if random.randrange(2) == 0 else x2)
|
---|
418 |
|
---|
419 | def xmin_crowd_min(self, x1, x2, y):
|
---|
420 | x1_closest = 999999
|
---|
421 | x2_closest = 999999
|
---|
422 | miny = y-3
|
---|
423 | maxy = y+3
|
---|
424 | i = bisect.bisect_left(self.y_sorted, miny)
|
---|
425 | while True:
|
---|
426 | if len(self.positions_sorted) <= i or self.positions_sorted[i]['y'] > maxy:
|
---|
427 | break
|
---|
428 | pos = self.positions_sorted[i]
|
---|
429 |
|
---|
430 | x1_closest = min(x1_closest, abs(x1-pos['x']))
|
---|
431 | x2_closest = min(x2_closest, abs(x2-pos['x']))
|
---|
432 |
|
---|
433 | i += 1
|
---|
434 | return (x1 if x1_closest > x2_closest else x2)
|
---|
435 |
|
---|
436 | def xmin_crowd_density(self, x1, x2, y):
|
---|
437 | # TODO experimental - requires further work to make it less 'jumpy' and more predictable
|
---|
438 | CONST_LOCAL_AREA_RADIUS = 5
|
---|
439 | CONST_GLOBAL_AREA_RADIUS = 10
|
---|
440 | CONST_WINDOW_SIZE = 20000 #TODO should depend on the maxY ?
|
---|
441 | x1_dist_loc = 0
|
---|
442 | x2_dist_loc = 0
|
---|
443 | count_loc = 1
|
---|
444 | x1_dist_glob = 0
|
---|
445 | x2_dist_glob = 0
|
---|
446 | count_glob = 1
|
---|
447 | miny = y-CONST_WINDOW_SIZE
|
---|
448 | maxy = y+CONST_WINDOW_SIZE
|
---|
449 | i_left = bisect.bisect_left(self.y_sorted, miny)
|
---|
450 | i_right = bisect.bisect_right(self.y_sorted, maxy)
|
---|
451 | #TODO test: maxy=y should give the same results, right?
|
---|
452 |
|
---|
453 | def include_pos(pos):
|
---|
454 | nonlocal x1_dist_loc, x2_dist_loc, x1_dist_glob, x2_dist_glob, count_loc, count_glob
|
---|
455 |
|
---|
456 | dysq = (pos['y']-y)**2 + 1 #+1 so 1/dysq is at most 1
|
---|
457 | dx1 = math.fabs(pos['x']-x1)
|
---|
458 | dx2 = math.fabs(pos['x']-x2)
|
---|
459 |
|
---|
460 | d = math.fabs(pos['x'] - (x1+x2)/2)
|
---|
461 |
|
---|
462 | if d < CONST_LOCAL_AREA_RADIUS:
|
---|
463 | x1_dist_loc += math.sqrt(dx1/dysq + dx1**2)
|
---|
464 | x2_dist_loc += math.sqrt(dx2/dysq + dx2**2)
|
---|
465 | count_loc += 1
|
---|
466 | elif d > CONST_GLOBAL_AREA_RADIUS:
|
---|
467 | x1_dist_glob += math.sqrt(dx1/dysq + dx1**2)
|
---|
468 | x2_dist_glob += math.sqrt(dx2/dysq + dx2**2)
|
---|
469 | count_glob += 1
|
---|
470 |
|
---|
471 | # optimized to draw from all the nodes, if less than 10 nodes in the range
|
---|
472 | if len(self.positions_sorted) > i_left:
|
---|
473 | if i_right - i_left < 10:
|
---|
474 | for j in range(i_left, i_right):
|
---|
475 | include_pos(self.positions_sorted[j])
|
---|
476 | else:
|
---|
477 | for j in range(10):
|
---|
478 | pos = self.positions_sorted[random.randrange(i_left, i_right)]
|
---|
479 | include_pos(pos)
|
---|
480 |
|
---|
481 | return (x1 if (x1_dist_loc-x2_dist_loc)/count_loc-(x1_dist_glob-x2_dist_glob)/count_glob > 0 else x2)
|
---|
482 | #return (x1 if x1_dist +random.gauss(0, 0.00001) > x2_dist +random.gauss(0, 0.00001) else x2)
|
---|
483 | #print(x1_dist, x2_dist)
|
---|
484 | #x1_dist = x1_dist**2
|
---|
485 | #x2_dist = x2_dist**2
|
---|
486 | #return x1 if x1_dist+x2_dist==0 else (x1*x1_dist + x2*x2_dist) / (x1_dist+x2_dist) + random.gauss(0, 0.01)
|
---|
487 | #return (x1 if random.randint(0, int(x1_dist+x2_dist)) < x1_dist else x2)
|
---|
488 |
|
---|
489 | def calculate_node_positions(self, ignore_last=0):
|
---|
490 | print("Calculating positions...")
|
---|
491 |
|
---|
492 | def add_node(node):
|
---|
493 | index = bisect.bisect_left(self.y_sorted, node['y'])
|
---|
494 | self.y_sorted.insert(index, node['y'])
|
---|
495 | self.positions_sorted.insert(index, node)
|
---|
496 | self.positions[node['id']] = node
|
---|
497 |
|
---|
498 | self.positions_sorted = [{'x':0, 'y':0, 'id':0}]
|
---|
499 | self.y_sorted = [0]
|
---|
500 | self.positions = [{} for x in range(len(self.tree.parents))]
|
---|
501 | self.positions[0] = {'x':0, 'y':0, 'id':0}
|
---|
502 |
|
---|
503 | # order by maximum depth of the parent guarantees that co child is evaluated before its parent
|
---|
504 | visiting_order = [i for i in range(0, len(self.tree.parents))]
|
---|
505 | visiting_order = sorted(visiting_order, key=lambda q:\
|
---|
506 | 0 if q == 0 else self.props["maxdepth"][q])
|
---|
507 |
|
---|
508 | start_time = timelib.time()
|
---|
509 |
|
---|
510 | # for each child of the current node
|
---|
511 | for node_counter,child in enumerate(visiting_order, start=1):
|
---|
512 | # debug info - elapsed time
|
---|
513 | if node_counter % 100000 == 0:
|
---|
514 | print("%d%%\t%d\t%g" % (node_counter*100/len(self.tree.parents), node_counter, timelib.time()-start_time))
|
---|
515 | start_time = timelib.time()
|
---|
516 |
|
---|
517 | # using normalized adepth
|
---|
518 | if self.props['adepth'][child] >= ignore_last/self.props['adepth_max']:
|
---|
519 |
|
---|
520 | ypos = 0
|
---|
521 | if self.TIME == "BIRTHS":
|
---|
522 | ypos = child
|
---|
523 | elif self.TIME == "GENERATIONAL":
|
---|
524 | # one more than its parent (what if more than one parent?)
|
---|
525 | ypos = max([self.positions[par]['y'] for par, v in self.tree.parents[child].items()])+1 \
|
---|
526 | if self.tree.parents[child] else 0
|
---|
527 | elif self.TIME == "REAL":
|
---|
528 | ypos = self.tree.time[child]
|
---|
529 |
|
---|
530 | if len(self.tree.parents[child]) == 1:
|
---|
531 | # if current_node is the only parent
|
---|
532 | parent, similarity = [(par, v) for par, v in self.tree.parents[child].items()][0]
|
---|
533 |
|
---|
534 | if self.JITTER:
|
---|
535 | dissimilarity = (1-similarity) + random.gauss(0, 0.01) + 0.001
|
---|
536 | else:
|
---|
537 | dissimilarity = (1-similarity) + 0.001
|
---|
538 | add_node({'id':child, 'y':ypos, 'x':
|
---|
539 | self.xmin_crowd(self.positions[parent]['x']-dissimilarity,
|
---|
540 | self.positions[parent]['x']+dissimilarity, ypos)})
|
---|
541 | else:
|
---|
542 | # position weighted by the degree of inheritence from each parent
|
---|
543 | total_inheretance = sum([v for k, v in self.tree.parents[child].items()])
|
---|
544 | xpos = sum([self.positions[k]['x']*v/total_inheretance
|
---|
545 | for k, v in self.tree.parents[child].items()])
|
---|
546 | if self.JITTER:
|
---|
547 | add_node({'id':child, 'y':ypos, 'x':xpos + random.gauss(0, 0.1)})
|
---|
548 | else:
|
---|
549 | add_node({'id':child, 'y':ypos, 'x':xpos})
|
---|
550 |
|
---|
551 |
|
---|
552 | def compute_custom(self):
|
---|
553 | for prop in self.tree.props:
|
---|
554 | self.props[prop] = [None for x in range(len(self.tree.children))]
|
---|
555 |
|
---|
556 | for i in range(len(self.props[prop])):
|
---|
557 | self.props[prop][i] = self.tree.props[prop][i]
|
---|
558 |
|
---|
559 | self.normalize_prop(prop)
|
---|
560 |
|
---|
561 | def compute_time(self):
|
---|
562 | # simple rewrite from the tree
|
---|
563 | self.props["time"] = [0 for x in range(len(self.tree.children))]
|
---|
564 |
|
---|
565 | for i in range(len(self.props['time'])):
|
---|
566 | self.props['time'][i] = self.tree.time[i]
|
---|
567 |
|
---|
568 | self.normalize_prop('time')
|
---|
569 |
|
---|
570 | def compute_kind(self):
|
---|
571 | # simple rewrite from the tree
|
---|
572 | self.props["kind"] = [0 for x in range(len(self.tree.children))]
|
---|
573 |
|
---|
574 | for i in range (len(self.props['kind'])):
|
---|
575 | self.props['kind'][i] = str(self.tree.kind[i])
|
---|
576 |
|
---|
577 | def compute_depth(self):
|
---|
578 | self.props["depth"] = [999999999 for x in range(len(self.tree.children))]
|
---|
579 | visited = [0 for x in range(len(self.tree.children))]
|
---|
580 |
|
---|
581 | nodes_to_visit = [0]
|
---|
582 | visited[0] = 1
|
---|
583 | self.props["depth"][0] = 0
|
---|
584 | while True:
|
---|
585 | current_node = nodes_to_visit[0]
|
---|
586 |
|
---|
587 | for child in self.tree.children[current_node]:
|
---|
588 | if visited[child] == 0:
|
---|
589 | visited[child] = 1
|
---|
590 | nodes_to_visit.append(child)
|
---|
591 | self.props["depth"][child] = self.props["depth"][current_node]+1
|
---|
592 | nodes_to_visit = nodes_to_visit[1:]
|
---|
593 | if len(nodes_to_visit) == 0:
|
---|
594 | break
|
---|
595 |
|
---|
596 | self.normalize_prop('depth')
|
---|
597 |
|
---|
598 | def compute_maxdepth(self):
|
---|
599 | self.props["maxdepth"] = [999999999 for x in range(len(self.tree.children))]
|
---|
600 | visited = [0 for x in range(len(self.tree.children))]
|
---|
601 |
|
---|
602 | nodes_to_visit = [0]
|
---|
603 | visited[0] = 1
|
---|
604 | self.props["maxdepth"][0] = 0
|
---|
605 | while True:
|
---|
606 | current_node = nodes_to_visit[0]
|
---|
607 |
|
---|
608 | for child in self.tree.children[current_node]:
|
---|
609 | if visited[child] == 0:
|
---|
610 | visited[child] = 1
|
---|
611 | nodes_to_visit.append(child)
|
---|
612 | self.props["maxdepth"][child] = self.props["maxdepth"][current_node]+1
|
---|
613 | elif self.props["maxdepth"][child] < self.props["maxdepth"][current_node]+1:
|
---|
614 | self.props["maxdepth"][child] = self.props["maxdepth"][current_node]+1
|
---|
615 | if child not in nodes_to_visit:
|
---|
616 | nodes_to_visit.append(child)
|
---|
617 |
|
---|
618 | nodes_to_visit = nodes_to_visit[1:]
|
---|
619 | if len(nodes_to_visit) == 0:
|
---|
620 | break
|
---|
621 |
|
---|
622 | self.normalize_prop('maxdepth')
|
---|
623 |
|
---|
624 | def compute_adepth(self):
|
---|
625 | self.props["adepth"] = [0 for x in range(len(self.tree.children))]
|
---|
626 |
|
---|
627 | # order by maximum depth of the parent guarantees that co child is evaluated before its parent
|
---|
628 | visiting_order = [i for i in range(0, len(self.tree.parents))]
|
---|
629 | visiting_order = sorted(visiting_order, key=lambda q: self.props["maxdepth"][q])[::-1]
|
---|
630 |
|
---|
631 | for node in visiting_order:
|
---|
632 | children = self.tree.children[node]
|
---|
633 | if len(children) != 0:
|
---|
634 | # 0 by default
|
---|
635 | self.props["adepth"][node] = max([self.props["adepth"][child] for child in children])+1
|
---|
636 | self.normalize_prop('adepth')
|
---|
637 |
|
---|
638 | def compute_children(self):
|
---|
639 | self.props["children"] = [0 for x in range(len(self.tree.children))]
|
---|
640 | for i in range (len(self.props['children'])):
|
---|
641 | self.props['children'][i] = len(self.tree.children[i])
|
---|
642 |
|
---|
643 | self.normalize_prop('children')
|
---|
644 |
|
---|
645 | def compute_progress(self):
|
---|
646 | self.props["progress"] = [0 for x in range(len(self.tree.children))]
|
---|
647 | for i in range(len(self.props['children'])):
|
---|
648 | times = sorted([self.props["time"][self.tree.children[i][j]]*100000 for j in range(len(self.tree.children[i]))])
|
---|
649 | if len(times) > 4:
|
---|
650 | times = [times[i+1] - times[i] for i in range(len(times)-1)]
|
---|
651 | #print(times)
|
---|
652 | slope, intercept, r_value, p_value, std_err = stats.linregress(range(len(times)), times)
|
---|
653 | self.props['progress'][i] = slope if not np.isnan(slope) and not np.isinf(slope) else 0
|
---|
654 |
|
---|
655 | for i in range(0, 5):
|
---|
656 | self.props['progress'][self.props['progress'].index(min(self.props['progress']))] = 0
|
---|
657 | self.props['progress'][self.props['progress'].index(max(self.props['progress']))] = 0
|
---|
658 |
|
---|
659 | mini = min(self.props['progress'])
|
---|
660 | maxi = max(self.props['progress'])
|
---|
661 | for k in range(len(self.props['progress'])):
|
---|
662 | if self.props['progress'][k] == 0:
|
---|
663 | self.props['progress'][k] = mini
|
---|
664 |
|
---|
665 | #for k in range(len(self.props['progress'])):
|
---|
666 | # self.props['progress'][k] = 1-self.props['progress'][k]
|
---|
667 |
|
---|
668 | self.normalize_prop('progress')
|
---|
669 |
|
---|
670 | def normalize_prop(self, prop):
|
---|
671 | noneless = [v for v in self.props[prop] if (type(v)!=str and type(v)!=list)]
|
---|
672 | if len(noneless) > 0:
|
---|
673 | max_val = max(noneless)
|
---|
674 | min_val = min(noneless)
|
---|
675 | print("%s: [%g, %g]" % (prop, min_val, max_val))
|
---|
676 | self.props[prop +'_max'] = max_val
|
---|
677 | self.props[prop +'_min'] = min_val
|
---|
678 | for i in range(len(self.props[prop])):
|
---|
679 | if self.props[prop][i] is not None:
|
---|
680 | qqq = self.props[prop][i]
|
---|
681 | self.props[prop][i] = 0 if max_val == min_val else (self.props[prop][i] - min_val) / (max_val - min_val)
|
---|
682 |
|
---|
683 | class TreeData:
|
---|
684 | simple_data = None
|
---|
685 |
|
---|
686 | children = []
|
---|
687 | parents = []
|
---|
688 | time = []
|
---|
689 | kind = []
|
---|
690 |
|
---|
691 | def __init__(self): #, simple_data=False):
|
---|
692 | #self.simple_data = simple_data
|
---|
693 | pass
|
---|
694 |
|
---|
695 | def load(self, filenames, max_nodes=0):
|
---|
696 | print("Loading...")
|
---|
697 |
|
---|
698 | CLI_PREFIX = "Script.Message:"
|
---|
699 | default_props = ["Time", "FromIDs", "ID", "Operation", "Inherited"]
|
---|
700 |
|
---|
701 | merged_with_virtual_parent = [] #this list will contain individuals for which the parent could not be found
|
---|
702 |
|
---|
703 | self.ids = {}
|
---|
704 | def get_id(id, createOnError = True):
|
---|
705 | if createOnError:
|
---|
706 | if id not in self.ids:
|
---|
707 | self.ids[id] = len(self.ids)
|
---|
708 | else:
|
---|
709 | if id not in self.ids:
|
---|
710 | return None
|
---|
711 |
|
---|
712 | return self.ids[id]
|
---|
713 |
|
---|
714 | def try_to_load(input):
|
---|
715 | creature = False
|
---|
716 | try:
|
---|
717 | creature = json.loads(input)
|
---|
718 | except ValueError:
|
---|
719 | print("Json format error: the line cannot be read. Breaking the loading loop.")
|
---|
720 | # fixing arrays by removing the last element
|
---|
721 | # ! assuming that only the last line is broken !
|
---|
722 | self.parents.pop()
|
---|
723 | self.children.pop()
|
---|
724 | self.time.pop()
|
---|
725 | self.kind.pop()
|
---|
726 | self.life_lenght.pop()
|
---|
727 | return creature
|
---|
728 |
|
---|
729 | def load_creature_props(creature):
|
---|
730 | creature_id = get_id(creature["ID"])
|
---|
731 | for prop in creature:
|
---|
732 | if prop not in default_props:
|
---|
733 | if prop not in self.props:
|
---|
734 | self.props[prop] = [0 for i in range(nodes)]
|
---|
735 | self.props[prop][creature_id] = creature[prop]
|
---|
736 |
|
---|
737 | def load_born_props(creature):
|
---|
738 | nonlocal max_time
|
---|
739 | creature_id = get_id(creature["ID"])
|
---|
740 | if "Time" in creature:
|
---|
741 | self.time[creature_id] = creature["Time"] + time_offset
|
---|
742 | max_time = max(self.time[creature_id], max_time)
|
---|
743 |
|
---|
744 | def load_offspring_props(creature):
|
---|
745 | creature_id = get_id(creature["ID"])#, False)
|
---|
746 | if "FromIDs" in creature:
|
---|
747 | # make sure that ID's of parents are lower than that of their children
|
---|
748 | for i in range(0, len(creature["FromIDs"])):
|
---|
749 | if creature["FromIDs"][i] not in self.ids:
|
---|
750 | get_id("virtual_parent")
|
---|
751 |
|
---|
752 |
|
---|
753 | # we assign to each parent its contribution to the genotype of the child
|
---|
754 | for i in range(0, len(creature["FromIDs"])):
|
---|
755 | if creature["FromIDs"][i] in self.ids:
|
---|
756 | parent_id = get_id(creature["FromIDs"][i])
|
---|
757 | else:
|
---|
758 | if creature["FromIDs"][i] not in merged_with_virtual_parent:
|
---|
759 | merged_with_virtual_parent.append(creature["FromIDs"][i])
|
---|
760 | parent_id = get_id("virtual_parent")
|
---|
761 | inherited = (creature["Inherited"][i] if 'Inherited' in creature else 1)
|
---|
762 | self.parents[creature_id][parent_id] = inherited
|
---|
763 |
|
---|
764 | if "Kind" in creature:
|
---|
765 | self.kind[creature_id] = creature["Kind"]
|
---|
766 | else:
|
---|
767 | raise LoadingError("[OFFSPRING] misses the 'FromIDs' field!")
|
---|
768 |
|
---|
769 | # counting the number of expected nodes
|
---|
770 | nodes_born, nodes_offspring = 0, 0
|
---|
771 | for filename in filenames:
|
---|
772 | file = open(filename)
|
---|
773 | for line in file:
|
---|
774 | line_arr = line.split(' ', 1)
|
---|
775 | if len(line_arr) == 2:
|
---|
776 | if line_arr[0] == CLI_PREFIX:
|
---|
777 | line_arr = line_arr[1].split(' ', 1)
|
---|
778 | if line_arr[0] == "[BORN]":
|
---|
779 | nodes_born += 1
|
---|
780 | if line_arr[0] == "[OFFSPRING]":
|
---|
781 | nodes_offspring += 1
|
---|
782 | # assuming that either BORN or OFFSPRING, or both, are present for each individual
|
---|
783 | nodes = max(nodes_born, nodes_offspring)
|
---|
784 | nodes = min(nodes, max_nodes if max_nodes != 0 else nodes)+1
|
---|
785 |
|
---|
786 | self.parents = [{} for x in range(nodes)]
|
---|
787 | self.children = [[] for x in range(nodes)]
|
---|
788 | self.time = [0] * nodes
|
---|
789 | self.kind = [0] * nodes
|
---|
790 | self.life_lenght = [0] * nodes
|
---|
791 | self.props = {}
|
---|
792 |
|
---|
793 | print("nodes: %d" % len(self.parents))
|
---|
794 |
|
---|
795 |
|
---|
796 | get_id("virtual_parent")
|
---|
797 | loaded_so_far = 0
|
---|
798 | max_time = 0
|
---|
799 | # rewind the file
|
---|
800 |
|
---|
801 | for filename in filenames:
|
---|
802 | file = open(filename)
|
---|
803 | time_offset = max_time
|
---|
804 | if max_time != 0:
|
---|
805 | print("NOTE: merging files, assuming cumulative time offset for '%s' to be %d" % (filename, time_offset))
|
---|
806 |
|
---|
807 | lasttime = timelib.time()
|
---|
808 |
|
---|
809 | for line in file:
|
---|
810 | line_arr = line.split(' ', 1)
|
---|
811 | if len(line_arr) == 2:
|
---|
812 | if line_arr[0] == CLI_PREFIX:
|
---|
813 | line_arr = line_arr[1].split(' ', 1)
|
---|
814 | if line_arr[0] == "[BORN]":
|
---|
815 | creature = try_to_load(line_arr[1])
|
---|
816 | if not creature:
|
---|
817 | nodes -= 1
|
---|
818 | break
|
---|
819 |
|
---|
820 | if get_id(creature["ID"], False) is None:
|
---|
821 | loaded_so_far += 1
|
---|
822 |
|
---|
823 | load_born_props(creature)
|
---|
824 | load_creature_props(creature)
|
---|
825 |
|
---|
826 | if line_arr[0] == "[OFFSPRING]":
|
---|
827 | creature = try_to_load(line_arr[1])
|
---|
828 | if not creature:
|
---|
829 | nodes -= 1
|
---|
830 | break
|
---|
831 |
|
---|
832 | if get_id(creature["ID"], False) is None:
|
---|
833 | loaded_so_far += 1
|
---|
834 | # load time only if there was no [BORN] yet
|
---|
835 | load_born_props(creature)
|
---|
836 |
|
---|
837 | load_offspring_props(creature)
|
---|
838 |
|
---|
839 | if line_arr[0] == "[DIED]":
|
---|
840 | creature = try_to_load(line_arr[1])
|
---|
841 | if not creature:
|
---|
842 | nodes -= 1
|
---|
843 | break
|
---|
844 | if get_id(creature["ID"], False) is not None:
|
---|
845 | load_creature_props(creature)
|
---|
846 | else:
|
---|
847 | print("NOTE: encountered [DIED] entry for individual " + creature["ID"] + " before it was born")
|
---|
848 |
|
---|
849 | # debug
|
---|
850 | if loaded_so_far%1000 == 0:
|
---|
851 | #print(". " + str(creature_id) + " " + str(timelib.time() - lasttime))
|
---|
852 | lasttime = timelib.time()
|
---|
853 |
|
---|
854 | # breaking both loops
|
---|
855 | if loaded_so_far >= max_nodes and max_nodes != 0:
|
---|
856 | break
|
---|
857 | if loaded_so_far >= max_nodes and max_nodes != 0:
|
---|
858 | break
|
---|
859 |
|
---|
860 | print("NOTE: all individuals with parent not provided or missing were connected to a single 'virtual parent' node: " + str(merged_with_virtual_parent))
|
---|
861 |
|
---|
862 | for c_id in range(1, nodes):
|
---|
863 | if not self.parents[c_id]:
|
---|
864 | self.parents[c_id][get_id("virtual_parent")] = 1
|
---|
865 |
|
---|
866 | for k in range(len(self.parents)):
|
---|
867 | v = self.parents[k]
|
---|
868 | for val in self.parents[k]:
|
---|
869 | self.children[val].append(k)
|
---|
870 |
|
---|
871 | depth = {}
|
---|
872 | kind = {}
|
---|
873 |
|
---|
874 | def main():
|
---|
875 |
|
---|
876 | parser = argparse.ArgumentParser(description='Draws a genealogical tree (generates a SVG file) based on parent-child relationship '
|
---|
877 | 'information from a text file. Supports files generated by Framsticks experiments.')
|
---|
878 | parser.add_argument('-i', '--in', nargs='+', dest='input', required=True, help='input file name with stuctured evolutionary data (or a list of input files)')
|
---|
879 | parser.add_argument('-o', '--out', dest='output', required=True, help='output file name for the evolutionary tree (SVG/PNG/JPG/BMP)')
|
---|
880 | parser.add_argument('-c', '--config', dest='config', default="", help='config file name ')
|
---|
881 |
|
---|
882 | parser.add_argument('-W', '--width', default=600, type=int, dest='width', help='width of the output image (600 by default)')
|
---|
883 | parser.add_argument('-H', '--height', default=800, type=int, dest='height', help='height of the output image (800 by default)')
|
---|
884 | parser.add_argument('-m', '--multi', default=1, type=int, dest='multi', help='multisampling factor (applicable only for raster images)')
|
---|
885 |
|
---|
886 | parser.add_argument('-t', '--time', default='GENERATIONAL', dest='time', help='values on vertical axis (BIRTHS/GENERATIONAL(d)/REAL); '
|
---|
887 | 'BIRTHS: time measured as the number of births since the beginning; '
|
---|
888 | 'GENERATIONAL: time measured as number of ancestors; '
|
---|
889 | 'REAL: real time of the simulation')
|
---|
890 | parser.add_argument('-b', '--balance', default='DENSITY', dest='balance', help='method of placing nodes in the tree (RANDOM/MIN/DENSITY(d))')
|
---|
891 | parser.add_argument('-s', '--scale', default='SIMPLE', dest='scale', help='type of timescale added to the tree (NONE(d)/SIMPLE)')
|
---|
892 | parser.add_argument('-j', '--jitter', dest="jitter", action='store_true', help='draw horizontal positions of children from the normal distribution')
|
---|
893 | parser.add_argument('-p', '--skip', dest="skip", type=int, default=0, help='skip last P levels of the tree (0 by default)')
|
---|
894 | parser.add_argument('-x', '--max-nodes', type=int, default=0, dest='max_nodes', help='maximum number of nodes drawn (starting from the first one)')
|
---|
895 | parser.add_argument('--seed', type=int, dest='seed', help='seed for the random number generator (-1 for random)')
|
---|
896 |
|
---|
897 | parser.set_defaults(draw_tree=True)
|
---|
898 | parser.set_defaults(draw_skeleton=False)
|
---|
899 | parser.set_defaults(draw_spine=False)
|
---|
900 |
|
---|
901 | parser.set_defaults(seed=-1)
|
---|
902 |
|
---|
903 | args = parser.parse_args()
|
---|
904 |
|
---|
905 | TIME = args.time.upper()
|
---|
906 | BALANCE = args.balance.upper()
|
---|
907 | SCALE = args.scale.upper()
|
---|
908 | JITTER = args.jitter
|
---|
909 | if not TIME in ['BIRTHS', 'GENERATIONAL', 'REAL']\
|
---|
910 | or not BALANCE in ['RANDOM', 'MIN', 'DENSITY']\
|
---|
911 | or not SCALE in ['NONE', 'SIMPLE']:
|
---|
912 | print("Incorrect value of one of the parameters! (time or balance or scale).") #user has to figure out which parameter is wrong...
|
---|
913 | return
|
---|
914 |
|
---|
915 | dir = args.input
|
---|
916 |
|
---|
917 | seed = args.seed
|
---|
918 | if seed == -1:
|
---|
919 | seed = random.randint(0, 10000)
|
---|
920 | random.seed(seed)
|
---|
921 | print("randomseed:", seed)
|
---|
922 |
|
---|
923 | tree = TreeData()
|
---|
924 | tree.load(dir, max_nodes=args.max_nodes)
|
---|
925 |
|
---|
926 |
|
---|
927 | designer = Designer(tree, jitter=JITTER, time=TIME, balance=BALANCE)
|
---|
928 | designer.calculate_measures()
|
---|
929 | designer.calculate_node_positions(ignore_last=args.skip)
|
---|
930 |
|
---|
931 | if args.output.endswith(".svg"):
|
---|
932 | drawer = SvgDrawer(designer, args.config, w=args.width, h=args.height)
|
---|
933 | else:
|
---|
934 | drawer = PngDrawer(designer, args.config, w=args.width, h=args.height)
|
---|
935 | drawer.draw_design(args.output, args.input, multi=args.multi, scale=SCALE)
|
---|
936 |
|
---|
937 |
|
---|
938 | main()
|
---|