import json
import math
import random
import argparse
import bisect
import time as timelib
from PIL import Image, ImageDraw, ImageFont
from scipy import stats
import numpy as np
class LoadingError(Exception):
pass
class Drawer:
def __init__(self, design, config_file, w=600, h=800, w_margin=10, h_margin=20):
self.design = design
self.width = w
self.height = h
self.w_margin = w_margin
self.h_margin = h_margin
self.w_no_margs = w - 2* w_margin
self.h_no_margs = h - 2* h_margin
self.colors = {
'white' : {'r':100, 'g':100, 'b':100},
'black' : {'r':0, 'g':0, 'b':0},
'red' : {'r':100, 'g':0, 'b':0},
'green' : {'r':0, 'g':100, 'b':0},
'blue' : {'r':0, 'g':0, 'b':100},
'yellow' : {'r':100, 'g':100, 'b':0},
'magenta' : {'r':100, 'g':0, 'b':100},
'cyan' : {'r':0, 'g':100, 'b':100},
'orange': {'r':100, 'g':50, 'b':0},
'purple': {'r':50, 'g':0, 'b':100}
}
self.settings = {
'colors_of_kinds': ['red', 'green', 'blue', 'magenta', 'yellow', 'cyan', 'orange', 'purple'],
'dots': {
'color': {
'meaning': 'Lifespan',
'start': 'red',
'end': 'green',
'bias': 1
},
'size': {
'meaning': 'EnergyEaten',
'start': 1,
'end': 6,
'bias': 0.5
},
'opacity': {
'meaning': 'EnergyEaten',
'start': 0.2,
'end': 1,
'bias': 1
}
},
'lines': {
'color': {
'meaning': 'adepth',
'start': 'black',
'end': 'red',
'bias': 3
},
'width': {
'meaning': 'adepth',
'start': 0.1,
'end': 4,
'bias': 3
},
'opacity': {
'meaning': 'adepth',
'start': 0.1,
'end': 0.8,
'bias': 5
}
}
}
def merge(source, destination):
for key, value in source.items():
if isinstance(value, dict):
node = destination.setdefault(key, {})
merge(value, node)
else:
destination[key] = value
return destination
if config_file != "":
with open(config_file) as config:
c = json.load(config)
self.settings = merge(c, self.settings)
#print(json.dumps(self.settings, indent=4, sort_keys=True))
def draw_dots(self, file, min_width, max_width, max_height):
for i in range(len(self.design.positions)):
node = self.design.positions[i]
if 'x' not in node:
continue
dot_style = self.compute_dot_style(node=i)
self.add_dot(file, (self.w_margin+self.w_no_margs*(node['x']-min_width)/(max_width-min_width),
self.h_margin+self.h_no_margs*node['y']/max_height), dot_style)
def draw_lines(self, file, min_width, max_width, max_height):
for parent in range(len(self.design.positions)):
par_pos = self.design.positions[parent]
if not 'x' in par_pos:
continue
for child in self.design.tree.children[parent]:
chi_pos = self.design.positions[child]
if 'x' not in chi_pos:
continue
line_style = self.compute_line_style(parent, child)
self.add_line(file, (self.w_margin+self.w_no_margs*(par_pos['x']-min_width)/(max_width-min_width),
self.h_margin+self.h_no_margs*par_pos['y']/max_height),
(self.w_margin+self.w_no_margs*(chi_pos['x']-min_width)/(max_width-min_width),
self.h_margin+self.h_no_margs*chi_pos['y']/max_height), line_style)
def draw_scale(self, file, filename):
self.add_text(file, "Generated from " + filename.split("\\")[-1], (5, 5), "start")
start_text = ""
end_text = ""
if self.design.TIME == "BIRTHS":
start_text = "Birth #0"
end_text = "Birth #" + str(len(self.design.positions)-1)
if self.design.TIME == "REAL":
start_text = "Time " + str(min(self.design.tree.time))
end_text = "Time " + str(max(self.design.tree.time))
if self.design.TIME == "GENERATIONAL":
start_text = "Depth " + str(self.design.props['adepth_min'])
end_text = "Depth " + str(self.design.props['adepth_max'])
self.add_dashed_line(file, (self.width*0.7, self.h_margin), (self.width, self.h_margin))
self.add_text(file, start_text, (self.width, self.h_margin), "end")
self.add_dashed_line(file, (self.width*0.7, self.height-self.h_margin), (self.width, self.height-self.h_margin))
self.add_text(file, end_text, (self.width, self.height-self.h_margin), "end")
def compute_property(self, part, prop, node):
start = self.settings[part][prop]['start']
end = self.settings[part][prop]['end']
value = (self.design.props[self.settings[part][prop]['meaning']][node]
if self.settings[part][prop]['meaning'] in self.design.props else 0 )
bias = self.settings[part][prop]['bias']
if prop == "color":
return self.compute_color(start, end, value, bias)
else:
return self.compute_value(start, end, value, bias)
def compute_color(self, start, end, value, bias=1):
if isinstance(value, str):
value = int(value)
r = self.colors[self.settings['colors_of_kinds'][value]]['r']
g = self.colors[self.settings['colors_of_kinds'][value]]['g']
b = self.colors[self.settings['colors_of_kinds'][value]]['b']
else:
start_color = self.colors[start]
end_color = self.colors[end]
value = 1 - (1-value)**bias
r = start_color['r']*(1-value)+end_color['r']*value
g = start_color['g']*(1-value)+end_color['g']*value
b = start_color['b']*(1-value)+end_color['b']*value
return (r, g, b)
def compute_value(self, start, end, value, bias=1):
value = 1 - (1-value)**bias
return start*(1-value) + end*value
class PngDrawer(Drawer):
def scale_up(self):
self.width *= self.multi
self.height *= self.multi
self.w_margin *= self.multi
self.h_margin *= self.multi
self.h_no_margs *= self.multi
self.w_no_margs *= self.multi
def scale_down(self):
self.width /= self.multi
self.height /= self.multi
self.w_margin /= self.multi
self.h_margin /= self.multi
self.h_no_margs /= self.multi
self.w_no_margs /= self.multi
def draw_design(self, filename, input_filename, multi=1, scale="SIMPLE"):
print("Drawing...")
self.multi=multi
self.scale_up()
back = Image.new('RGBA', (self.width, self.height), (255,255,255,0))
min_width = min([x['x'] for x in self.design.positions if 'x' in x])
max_width = max([x['x'] for x in self.design.positions if 'x' in x])
max_height = max([x['y'] for x in self.design.positions if 'y' in x])
self.draw_lines(back, min_width, max_width, max_height)
self.draw_dots(back, min_width, max_width, max_height)
if scale == "SIMPLE":
self.draw_scale(back, input_filename)
#back.show()
self.scale_down()
back.thumbnail((self.width, self.height), Image.ANTIALIAS)
back.save(filename)
def add_dot(self, file, pos, style):
x, y = int(pos[0]), int(pos[1])
r = style['r']*self.multi
offset = (int(x - r), int(y - r))
size = (2*int(r), 2*int(r))
c = style['color']
img = Image.new('RGBA', size)
ImageDraw.Draw(img).ellipse((1, 1, size[0]-1, size[1]-1),
(int(2.55*c[0]), int(2.55*c[1]), int(2.55*c[2]), int(255*style['opacity'])))
file.paste(img, offset, mask=img)
def add_line(self, file, from_pos, to_pos, style):
fx, fy, tx, ty = int(from_pos[0]), int(from_pos[1]), int(to_pos[0]), int(to_pos[1])
w = int(style['width'])*self.multi
offset = (min(fx-w, tx-w), min(fy-w, ty-w))
size = (abs(fx-tx)+2*w, abs(fy-ty)+2*w)
c = style['color']
img = Image.new('RGBA', size)
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),
(int(2.55*c[0]), int(2.55*c[1]), int(2.55*c[2]), int(255*style['opacity'])), w)
file.paste(img, offset, mask=img)
def add_dashed_line(self, file, from_pos, to_pos):
style = {'color': (0,0,0), 'width': 1, 'opacity': 1}
sublines = 50
# TODO could be faster: compute delta and only add delta each time (but currently we do not use it often)
normdiv = 2*sublines-1
for i in range(sublines):
from_pos_sub = (self.compute_value(from_pos[0], to_pos[0], 2*i/normdiv, 1),
self.compute_value(from_pos[1], to_pos[1], 2*i/normdiv, 1))
to_pos_sub = (self.compute_value(from_pos[0], to_pos[0], (2*i+1)/normdiv, 1),
self.compute_value(from_pos[1], to_pos[1], (2*i+1)/normdiv, 1))
self.add_line(file, from_pos_sub, to_pos_sub, style)
def add_text(self, file, text, pos, anchor, style=''):
font = ImageFont.truetype("Vera.ttf", 16*self.multi)
img = Image.new('RGBA', (self.width, self.height))
draw = ImageDraw.Draw(img)
txtsize = draw.textsize(text, font=font)
pos = pos if anchor == "start" else (pos[0]-txtsize[0], pos[1])
draw.text(pos, text, (0,0,0), font=font)
file.paste(img, (0,0), mask=img)
def compute_line_style(self, parent, child):
return {'color': self.compute_property('lines', 'color', child),
'width': self.compute_property('lines', 'width', child),
'opacity': self.compute_property('lines', 'opacity', child)}
def compute_dot_style(self, node):
return {'color': self.compute_property('dots', 'color', node),
'r': self.compute_property('dots', 'size', node),
'opacity': self.compute_property('dots', 'opacity', node)}
class SvgDrawer(Drawer):
def draw_design(self, filename, input_filename, multi=1, scale="SIMPLE"):
print("Drawing...")
file = open(filename, "w")
min_width = min([x['x'] for x in self.design.positions if 'x' in x])
max_width = max([x['x'] for x in self.design.positions if 'x' in x])
max_height = max([x['y'] for x in self.design.positions if 'y' in x])
file.write('")
file.close()
def add_text(self, file, text, pos, anchor, style=''):
style = (style if style != '' else 'style="font-family: Arial; font-size: 12; fill: #000000;"')
# assuming font size 12, it should be taken from the style string!
file.write('' + text + '')
def add_dot(self, file, pos, style):
file.write('')
def add_line(self, file, from_pos, to_pos, style):
file.write('')
def add_dashed_line(self, file, from_pos, to_pos):
style = 'stroke="black" stroke-width="0.5" stroke-opacity="1" stroke-dasharray="5, 5"'
self.add_line(file, from_pos, to_pos, style)
def compute_line_style(self, parent, child):
return self.compute_stroke_color('lines', child) + ' ' \
+ self.compute_stroke_width('lines', child) + ' ' \
+ self.compute_stroke_opacity(child)
def compute_dot_style(self, node):
return self.compute_dot_size(node) + ' ' \
+ self.compute_fill_opacity(node) + ' ' \
+ self.compute_dot_fill(node)
def compute_stroke_color(self, part, node):
color = self.compute_property(part, 'color', node)
return 'stroke="rgb(' + str(color[0]) + '%,' + str(color[1]) + '%,' + str(color[2]) + '%)"'
def compute_stroke_width(self, part, node):
return 'stroke-width="' + str(self.compute_property(part, 'width', node)) + '"'
def compute_stroke_opacity(self, node):
return 'stroke-opacity="' + str(self.compute_property('lines', 'opacity', node)) + '"'
def compute_fill_opacity(self, node):
return 'fill-opacity="' + str(self.compute_property('dots', 'opacity', node)) + '"'
def compute_dot_size(self, node):
return 'r="' + str(self.compute_property('dots', 'size', node)) + '"'
def compute_dot_fill(self, node):
color = self.compute_property('dots', 'color', node)
return 'fill="rgb(' + str(color[0]) + '%,' + str(color[1]) + '%,' + str(color[2]) + '%)"'
class Designer:
def __init__(self, tree, jitter=False, time="GENERATIONAL", balance="DENSITY"):
self.props = {}
self.tree = tree
self.TIME = time
self.JITTER = jitter
if balance == "RANDOM":
self.xmin_crowd = self.xmin_crowd_random
elif balance == "MIN":
self.xmin_crowd = self.xmin_crowd_min
elif balance == "DENSITY":
self.xmin_crowd = self.xmin_crowd_density
else:
raise ValueError("Error, the value of BALANCE does not match any expected value.")
def calculate_measures(self):
print("Calculating measures...")
self.compute_depth()
self.compute_adepth()
self.compute_children()
self.compute_kind()
self.compute_time()
self.compute_progress()
self.compute_custom()
def xmin_crowd_random(self, x1, x2, y):
return (x1 if random.randrange(2) == 0 else x2)
def xmin_crowd_min(self, x1, x2, y):
x1_closest = 999999
x2_closest = 999999
miny = y-3
maxy = y+3
i = bisect.bisect_left(self.y_sorted, miny)
while True:
if len(self.positions_sorted) <= i or self.positions_sorted[i]['y'] > maxy:
break
pos = self.positions_sorted[i]
x1_closest = min(x1_closest, abs(x1-pos['x']))
x2_closest = min(x2_closest, abs(x2-pos['x']))
i += 1
return (x1 if x1_closest > x2_closest else x2)
def xmin_crowd_density(self, x1, x2, y):
# TODO experimental - requires further work to make it less 'jumpy' and more predictable
x1_dist_loc = 0
x2_dist_loc = 0
count_loc = 1
x1_dist_glob = 0
x2_dist_glob = 0
count_glob = 1
miny = y-2000
maxy = y+2000
i_left = bisect.bisect_left(self.y_sorted, miny)
i_right = bisect.bisect_right(self.y_sorted, maxy)
# print("i " + str(i) + " len " + str(len(self.positions)))
#
# i = bisect.bisect_left(self.y_sorted, y)
# i_left = max(0, i - 25)
# i_right = min(len(self.y_sorted), i + 25)
def include_pos(pos):
nonlocal x1_dist_loc, x2_dist_loc, x1_dist_glob, x2_dist_glob, count_loc, count_glob
dysq = (pos['y']-y)**2
dx1 = pos['x']-x1
dx2 = pos['x']-x2
d = math.fabs(pos['x'] - (x1+x2)/2)
if d < 10:
x1_dist_loc += math.sqrt(dysq + dx1**2)
x2_dist_loc += math.sqrt(dysq + dx2**2)
count_loc += 1
elif d > 20:
x1_dist_glob += math.sqrt(dysq + dx1**2)
x2_dist_glob += math.sqrt(dysq + dx2**2)
count_glob += 1
# optimized to draw from all the nodes, if less than 10 nodes in the range
if len(self.positions_sorted) > i_left:
if i_right - i_left < 10:
for j in range(i_left, i_right):
include_pos(self.positions_sorted[j])
else:
for j in range(10):
pos = self.positions_sorted[random.randrange(i_left, i_right)]
include_pos(pos)
# return ((x1 if x1_dist > x2_dist else x2)
# if x1_dist < 10000 else
# (x1 if x1_dist < x2_dist else x2))
return (x1 if (x1_dist_loc-x2_dist_loc)/count_loc-(x1_dist_glob-x2_dist_glob)/count_glob > 0 else x2)
#return (x1 if x1_dist +random.gauss(0, 0.00001) > x2_dist +random.gauss(0, 0.00001) else x2)
#print(x1_dist, x2_dist)
#x1_dist = x1_dist**2
#x2_dist = x2_dist**2
#return x1 if x1_dist+x2_dist==0 else (x1*x1_dist + x2*x2_dist) / (x1_dist+x2_dist) + random.gauss(0, 0.01)
#return (x1 if random.randint(0, int(x1_dist+x2_dist)) < x1_dist else x2)
def calculate_node_positions(self, ignore_last=0):
print("Calculating positions...")
def add_node(node):
index = bisect.bisect_left(self.y_sorted, node['y'])
self.y_sorted.insert(index, node['y'])
self.positions_sorted.insert(index, node)
self.positions[node['id']] = node
self.positions_sorted = [{'x':0, 'y':0, 'id':0}]
self.y_sorted = [0]
self.positions = [{} for x in range(len(self.tree.parents))]
self.positions[0] = {'x':0, 'y':0, 'id':0}
# order by maximum depth of the parent guarantees that co child is evaluated before its parent
visiting_order = [i for i in range(0, len(self.tree.parents))]
visiting_order = sorted(visiting_order, key=lambda q:
0 if q == 0 else max([self.props["depth"][d] for d in self.tree.parents[q]]))
start_time = timelib.time()
# for each child of the current node
for node_counter,child in enumerate(visiting_order, start=1):
# debug info - elapsed time
if node_counter % 100000 == 0:
print("%d%%\t%d\t%g" % (node_counter*100/len(self.tree.parents), node_counter, timelib.time()-start_time))
start_time = timelib.time()
# using normalized adepth
if self.props['adepth'][child] >= ignore_last/self.props['adepth_max']:
ypos = 0
if self.TIME == "BIRTHS":
ypos = child
elif self.TIME == "GENERATIONAL":
# one more than its parent (what if more than one parent?)
ypos = max([self.positions[par]['y'] for par, v in self.tree.parents[child].items()])+1 \
if self.tree.parents[child] else 0
elif self.TIME == "REAL":
ypos = self.tree.time[child]
if len(self.tree.parents[child]) == 1:
# if current_node is the only parent
parent, similarity = [(par, v) for par, v in self.tree.parents[child].items()][0]
if self.JITTER:
dissimilarity = (1-similarity) + random.gauss(0, 0.01) + 0.001
else:
dissimilarity = (1-similarity) + 0.001
add_node({'id':child, 'y':ypos, 'x':
self.xmin_crowd(self.positions[parent]['x']-dissimilarity,
self.positions[parent]['x']+dissimilarity, ypos)})
else:
# position weighted by the degree of inheritence from each parent
total_inheretance = sum([v for k, v in self.tree.parents[child].items()])
xpos = sum([self.positions[k]['x']*v/total_inheretance
for k, v in self.tree.parents[child].items()])
if self.JITTER:
add_node({'id':child, 'y':ypos, 'x':xpos + random.gauss(0, 0.1)})
else:
add_node({'id':child, 'y':ypos, 'x':xpos})
def compute_custom(self):
for prop in self.tree.props:
self.props[prop] = [None for x in range(len(self.tree.children))]
for i in range(len(self.props[prop])):
self.props[prop][i] = self.tree.props[prop][i]
self.normalize_prop(prop)
def compute_time(self):
# simple rewrite from the tree
self.props["time"] = [0 for x in range(len(self.tree.children))]
for i in range(len(self.props['time'])):
self.props['time'][i] = self.tree.time[i]
self.normalize_prop('time')
def compute_kind(self):
# simple rewrite from the tree
self.props["kind"] = [0 for x in range(len(self.tree.children))]
for i in range (len(self.props['kind'])):
self.props['kind'][i] = str(self.tree.kind[i])
def compute_depth(self):
self.props["depth"] = [999999999 for x in range(len(self.tree.children))]
visited = [0 for x in range(len(self.tree.children))]
nodes_to_visit = [0]
visited[0] = 1
self.props["depth"][0] = 0
while True:
current_node = nodes_to_visit[0]
for child in self.tree.children[current_node]:
if visited[child] == 0:
visited[child] = 1
nodes_to_visit.append(child)
self.props["depth"][child] = self.props["depth"][current_node]+1
nodes_to_visit = nodes_to_visit[1:]
if len(nodes_to_visit) == 0:
break
self.normalize_prop('depth')
def compute_adepth(self):
self.props["adepth"] = [0 for x in range(len(self.tree.children))]
# order by maximum depth of the parent guarantees that co child is evaluated before its parent
visiting_order = [i for i in range(0, len(self.tree.parents))]
visiting_order = sorted(visiting_order, key=lambda q:
0 if q == 0 else max([self.props["depth"][d] for d in self.tree.parents[q]]))[::-1]
for node in visiting_order:
children = self.tree.children[node]
if len(children) != 0:
# 0 by default
self.props["adepth"][node] = max([self.props["adepth"][child] for child in children])+1
self.normalize_prop('adepth')
def compute_children(self):
self.props["children"] = [0 for x in range(len(self.tree.children))]
for i in range (len(self.props['children'])):
self.props['children'][i] = len(self.tree.children[i])
self.normalize_prop('children')
def compute_progress(self):
self.props["progress"] = [0 for x in range(len(self.tree.children))]
for i in range(len(self.props['children'])):
times = sorted([self.props["time"][self.tree.children[i][j]]*100000 for j in range(len(self.tree.children[i]))])
if len(times) > 4:
times = [times[i+1] - times[i] for i in range(len(times)-1)]
#print(times)
slope, intercept, r_value, p_value, std_err = stats.linregress(range(len(times)), times)
self.props['progress'][i] = slope if not np.isnan(slope) and not np.isinf(slope) else 0
for i in range(0, 5):
self.props['progress'][self.props['progress'].index(min(self.props['progress']))] = 0
self.props['progress'][self.props['progress'].index(max(self.props['progress']))] = 0
mini = min(self.props['progress'])
maxi = max(self.props['progress'])
for k in range(len(self.props['progress'])):
if self.props['progress'][k] == 0:
self.props['progress'][k] = mini
#for k in range(len(self.props['progress'])):
# self.props['progress'][k] = 1-self.props['progress'][k]
self.normalize_prop('progress')
def normalize_prop(self, prop):
noneless = [v for v in self.props[prop] if (type(v)!=str and type(v)!=list)]
if len(noneless) > 0:
max_val = max(noneless)
min_val = min(noneless)
print(prop, max_val, min_val)
self.props[prop +'_max'] = max_val
self.props[prop +'_min'] = min_val
for i in range(len(self.props[prop])):
if self.props[prop][i] is not None:
qqq = self.props[prop][i]
self.props[prop][i] = 0 if max_val == min_val else (self.props[prop][i] - min_val) / (max_val - min_val)
class TreeData:
simple_data = None
children = []
parents = []
time = []
kind = []
def __init__(self): #, simple_data=False):
#self.simple_data = simple_data
pass
def load(self, filename, max_nodes=0):
print("Loading...")
CLI_PREFIX = "Script.Message:"
default_props = ["Time", "FromIDs", "ID", "Operation", "Inherited"]
self.ids = {}
def get_id(id, createOnError = True):
if createOnError:
if id not in self.ids:
self.ids[id] = len(self.ids)
else:
if id not in self.ids:
return None
return self.ids[id]
file = open(filename)
# counting the number of expected nodes
nodes = 0
for line in file:
line_arr = line.split(' ', 1)
if len(line_arr) == 2:
if line_arr[0] == CLI_PREFIX:
line_arr = line_arr[1].split(' ', 1)
if line_arr[0] == "[OFFSPRING]":
nodes += 1
nodes = min(nodes, max_nodes if max_nodes != 0 else nodes)+1
self.parents = [{} for x in range(nodes)]
self.children = [[] for x in range(nodes)]
self.time = [0] * nodes
self.kind = [0] * nodes
self.life_lenght = [0] * nodes
self.props = {}
print("nodes: %d" % len(self.parents))
file.seek(0)
loaded_so_far = 0
lasttime = timelib.time()
for line in file:
line_arr = line.split(' ', 1)
if len(line_arr) == 2:
if line_arr[0] == CLI_PREFIX:
line_arr = line_arr[1].split(' ', 1)
if line_arr[0] == "[OFFSPRING]":
try:
creature = json.loads(line_arr[1])
except ValueError:
print("Json format error - the line cannot be read. Breaking the loading loop.")
# fixing arrays by removing the last element
# ! assuming that only the last line is broken !
self.parents.pop()
self.children.pop()
self.time.pop()
self.kind.pop()
self.life_lenght.pop()
nodes -= 1
break
if "FromIDs" in creature:
# make sure that ID's of parents are lower than that of their children
for i in range(0, len(creature["FromIDs"])):
if creature["FromIDs"][i] not in self.ids:
get_id("virtual_parent")
creature_id = get_id(creature["ID"])
# debug
if loaded_so_far%1000 == 0:
#print(". " + str(creature_id) + " " + str(timelib.time() - lasttime))
lasttime = timelib.time()
# we assign to each parent its contribution to the genotype of the child
for i in range(0, len(creature["FromIDs"])):
if creature["FromIDs"][i] in self.ids:
parent_id = get_id(creature["FromIDs"][i])
else:
parent_id = get_id("virtual_parent")
inherited = (creature["Inherited"][i] if 'Inherited' in creature else 1)
self.parents[creature_id][parent_id] = inherited
if "Time" in creature:
self.time[creature_id] = creature["Time"]
if "Kind" in creature:
self.kind[creature_id] = creature["Kind"]
for prop in creature:
if prop not in default_props:
if prop not in self.props:
self.props[prop] = [0 for i in range(nodes)]
self.props[prop][creature_id] = creature[prop]
loaded_so_far += 1
else:
raise LoadingError("[OFFSPRING] misses the 'FromIDs' field!")
if line_arr[0] == "[DIED]":
creature = json.loads(line_arr[1])
creature_id = get_id(creature["ID"], False)
if creature_id is not None:
for prop in creature:
if prop not in default_props:
if prop not in self.props:
self.props[prop] = [0 for i in range(nodes)]
self.props[prop][creature_id] = creature[prop]
if loaded_so_far >= max_nodes and max_nodes != 0:
break
for k in range(len(self.parents)):
v = self.parents[k]
for val in self.parents[k]:
self.children[val].append(k)
depth = {}
kind = {}
def main():
parser = argparse.ArgumentParser(description='Draws a genealogical tree (generates a SVG file) based on parent-child relationship '
'information from a text file. Supports files generated by Framsticks experiments.')
parser.add_argument('-i', '--in', dest='input', required=True, help='input file name with stuctured evolutionary data')
parser.add_argument('-o', '--out', dest='output', required=True, help='output file name for the evolutionary tree (SVG/PNG/JPG/BMP)')
parser.add_argument('-c', '--config', dest='config', default="", help='config file name ')
parser.add_argument('-W', '--width', default=600, type=int, dest='width', help='width of the output image (600 by default)')
parser.add_argument('-H', '--height', default=800, type=int, dest='height', help='height of the output image (800 by default)')
parser.add_argument('-m', '--multi', default=1, type=int, dest='multi', help='multisampling factor (applicable only for raster images)')
parser.add_argument('-t', '--time', default='GENERATIONAL', dest='time', help='values on vertical axis (BIRTHS/GENERATIONAL(d)/REAL); '
'BIRTHS: time measured as the number of births since the beginning; '
'GENERATIONAL: time measured as number of ancestors; '
'REAL: real time of the simulation')
parser.add_argument('-b', '--balance', default='DENSITY', dest='balance', help='method of placing nodes in the tree (RANDOM/MIN/DENSITY(d))')
parser.add_argument('-s', '--scale', default='SIMPLE', dest='scale', help='type of timescale added to the tree (NONE(d)/SIMPLE)')
parser.add_argument('-j', '--jitter', dest="jitter", action='store_true', help='draw horizontal positions of children from the normal distribution')
parser.add_argument('-p', '--skip', dest="skip", type=int, default=0, help='skip last P levels of the tree (0 by default)')
parser.add_argument('-x', '--max-nodes', type=int, default=0, dest='max_nodes', help='maximum number of nodes drawn (starting from the first one)')
parser.add_argument('--seed', type=int, dest='seed', help='seed for the random number generator (-1 for random)')
parser.set_defaults(draw_tree=True)
parser.set_defaults(draw_skeleton=False)
parser.set_defaults(draw_spine=False)
parser.set_defaults(seed=-1)
args = parser.parse_args()
TIME = args.time.upper()
BALANCE = args.balance.upper()
SCALE = args.scale.upper()
JITTER = args.jitter
if not TIME in ['BIRTHS', 'GENERATIONAL', 'REAL']\
or not BALANCE in ['RANDOM', 'MIN', 'DENSITY']\
or not SCALE in ['NONE', 'SIMPLE']:
print("Incorrect value of one of the parameters! (time or balance or scale).") #user has to figure out which parameter is wrong...
return
dir = args.input
seed = args.seed
if seed == -1:
seed = random.randint(0, 10000)
random.seed(seed)
print("randomseed:", seed)
tree = TreeData()
tree.load(dir, max_nodes=args.max_nodes)
designer = Designer(tree, jitter=JITTER, time=TIME, balance=BALANCE)
designer.calculate_measures()
designer.calculate_node_positions(ignore_last=args.skip)
if args.output.endswith(".svg"):
drawer = SvgDrawer(designer, args.config, w=args.width, h=args.height)
else:
drawer = PngDrawer(designer, args.config, w=args.width, h=args.height)
drawer.draw_design(args.output, args.input, multi=args.multi, scale=SCALE)
main()