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generation.py
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generation.py
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import random
import math
from matplotlib import pyplot as plt, patches
import matplotlib.colors as mcolors
from IPython import display
import pylab as pl
import time
from collections import namedtuple
from util import *
## Test functions
def generate_unconnected_participants(amount : int, layout_zone : dict, maxX : int, maxY : int, seed : int) -> dict:
random.seed(seed)
colors = list(mcolors.CSS4_COLORS.keys())
participants = []
for i in range(amount):
xmin = random.randint(0,layout_zone.width)
ymin = random.randint(0,layout_zone.height)
width = random.randint(5,maxX)
height = random.randint(5,maxY)
participant = {
"idx" : 'p' + str(i),
"connections" : (), #('idx' : 2)
"xmin" : xmin,
"ymin" : ymin,
"width" : width,
"height" : height,
"clashes" : (), #('idx' : 100)
"aversions" : (), #('idx' : 17,5)
"interference" : 0,
"overlap_with_idx" : (),
"turmoil" : 0,
"relaxed_connections" : 0,
"protrusion_status" : '',
"protrusion_extend" : 0,
"protruded_zone_edges" : (),
"healthy" : True,
"compliant" : True,
"yield_polygon" : (),
"freespace" : (),
'secondary_freespace_north_east': (),
'secondary_freespace_south_east': (),
'secondary_freespace_south_west': (),
'secondary_freespace_north_west': (),
"last_move" : '',
"color" : random.choice(colors)
}
participants.append(participant)
# Create defaults for clashes and aversion
idx_list = [p['idx'] for p in participants]
idx_str = ' '.join(idx_list)
Clashes = namedtuple('Clashes', idx_str)
Aversions = namedtuple('Aversions', idx_str)
clashes_default = Clashes(*(len(participants) * [0]))
aversions_default = Aversions(*(len(participants) * [0]))
# Turn list of dictionaries to list of namedtuples
participants = [namedtuple('Participant', participant)(**participant) for participant in participants]
# Put in defaults for clashes and aversions
particpants_updated = [p._replace(clashes = clashes_default, aversions = aversions_default) for p in participants]
# Put participants into named tuple
Participants = namedtuple('Participants', idx_str)
all_participants = Participants(*particpants_updated)
return all_participants
def generate_connected_participants(amount : int, max_num_nets : int, max_num_connections : int, layout_zone : dict, maxX : int, maxY : int, seed : int) -> dict:
participants = generate_unconnected_participants(amount, layout_zone, maxX, maxY, seed)
# Create connections
for i in range(max_num_nets): # for every net
number_of_connected_participants = random.choice(list(range(2, max_num_connections)))
#print(number_of_connected_participants)
connected_participants = random.choices(list(range(amount)), k=number_of_connected_participants)
#print(connected_participants)
for idx in connected_participants: # for every participant in that net
#print(idx)
for idc in connected_participants: # write the id of all others into the connection dict
#print(idc)
if idx != idc:
participants[str(idx)]['connections'].update({str(idc) : 1})
return participants
def generate_unconnected_zone_filling_participants(rows : int, cols : int, layout_zone : dict, seed : int) -> dict:
random.seed(seed)
colors = list(mcolors.CSS4_COLORS.keys())
participants = {}
total_area = layout_zone["height"] * layout_zone["width"]
max_participant_height = layout_zone["height"]/rows
idx = 0
for i in range(rows):
xstart = 0
xend = layout_zone["width"]
for j in range(cols):
xmin = random.randint(0,layout_zone['width'])
ymin = random.randint(0,layout_zone['height'])
width = random.randint(xstart,xend) if j != cols-1 else (xend - xstart)
xstart = xstart + width
participant = {
"idx" : str(idx),
"connections" : {}, #{'idx' : 2}
"xmin" : xmin,
"ymin" : ymin,
"width" : width,
"height" : max_participant_height,
"clashes" : {}, #{'idx' : 100}
"aversions" : {}, #{'idx' : 17,5}
"interference" : 0,
"overlap-with-idx" : [],
"turmoil" : 0,
"relaxed-connections" : 0,
"protrusion-status" : '',
"protrusion-extend" : 0,
"protruded-zone-edges" : [],
"healthy" : True,
"compliant" : True,
"yield-polygon" : {},
"freespace" : {},
'secondary-freespace-north-east': {},
'secondary-freespace-south-east': {},
'secondary-freespace-south-west': {},
'secondary-freespace-north-west': {},
"last-move" : '',
"color" : random.choice(colors)
}
participants[str(idx)] = participant
idx += 1
return participants
def generate_unconnected_equal_quadratic_participants(amount : int, layout_zone : dict, edge_length : int, seed : int) -> dict:
random.seed(seed)
colors = list(mcolors.CSS4_COLORS.keys())
participants = {}
for i in range(amount):
xmin = random.randint(0,layout_zone['width'])
ymin = random.randint(0,layout_zone['height'])
width = edge_length
height = edge_length
participant = {
"idx" : str(i),
"connections" : {}, #{'idx' : 2}
"xmin" : xmin,
"ymin" : ymin,
"width" : width,
"height" : height,
"clashes" : {}, #{'idx' : 100}
"aversions" : {}, #{'idx' : 17,5}
"interference" : 0,
"overlap-with-idx" : [],
"turmoil" : 0,
"relaxed-connections" : 0,
"protrusion-status" : '',
"protrusion-extend" : 0,
"protruded-zone-edges" : [],
"healthy" : True,
"compliant" : True,
"yield-polygon" : {},
"freespace" : {},
'secondary-freespace-north-east': {},
'secondary-freespace-south-east': {},
'secondary-freespace-south-west': {},
'secondary-freespace-north-west': {},
"last-move" : '',
"color" : random.choice(colors)
}
participants[str(i)] = participant
return participants
def generate_unconnected_wheel_participants(layout_zone : dict, edge_length : int, seed : int) -> dict:
random.seed(seed)
colors = list(mcolors.CSS4_COLORS.keys())
participants = {}
for i in range(5):
xmin = random.randint(0,layout_zone['width'])
ymin = random.randint(0,layout_zone['height'])
width = 1.5 * edge_length if (i == 0) else 2 * edge_length
height = 1.5 * edge_length if (i == 0) else 0.5 * edge_length
participant = {
"idx" : str(i),
"connections" : {}, #{'idx' : 2}
"xmin" : xmin,
"ymin" : ymin,
"width" : width,
"height" : height,
"clashes" : {}, #{'idx' : 100}
"aversions" : {}, #{'idx' : 17,5}
"interference" : 0,
"overlap-with-idx" : [],
"turmoil" : 0,
"relaxed-connections" : 0,
"protrusion-status" : '',
"protrusion-extend" : 0,
"protruded-zone-edges" : [],
"healthy" : True,
"compliant" : True,
"yield-polygon" : {},
"freespace" : {},
'secondary-freespace-north-east': {},
'secondary-freespace-south-east': {},
'secondary-freespace-south-west': {},
'secondary-freespace-north-west': {},
"last-move" : '',
"color" : random.choice(colors)
}
participants[str(i)] = participant
return participants
def random_place_mcnc(participants_list : list, layout_zone : dict, seed : int) -> dict:
participants_list_pure = participants_list[:-1]
random.seed(seed)
participants_dict = {}
colors = list(mcolors.CSS4_COLORS.keys())
swarm_specifics = { "clashes" : (), #('idx' : 100)
"aversions" : (), #('idx' : 17,5)
"interference" : 0,
"overlap_with_idx" : (),
"turmoil" : 0,
"relaxed_connections" : 0,
"protrusion_status" : '',
"protrusion_extend" : 0,
"protruded_zone_edges" : (),
"healthy" : True,
"compliant" : True,
"yield_polygon" : (),
"freespace" : (),
'secondary_freespace_north_east': (),
'secondary_freespace_south_east': (),
'secondary_freespace_south_west': (),
'secondary_freespace_north_west': (),
"last_move" : ''}
# Create defaults for clashes and aversion
idx_list = [p['idx'] for p in participants_list_pure]
idx_str = ' '.join(idx_list)
Clashes = namedtuple('Clashes', idx_str)
Aversions = namedtuple('Aversions', idx_str)
clashes_default = Clashes(*(len(participants_list_pure) * [0]))
aversions_default = Aversions(*(len(participants_list_pure) * [0]))
swarm_specifics['clashes'] = clashes_default
swarm_specifics['aversions'] = aversions_default
# Merge yal input with swarm specifics
participants_updated_swarm = [p | swarm_specifics for p in participants_list_pure]
#print(participants_updated_swarm)
# Turn connections into namedtuple
# connections = {p.idx : namedtuple('Connections', p['connections'])(**p['connections']) for p in participants_updated_swarm}
# print(connections)
participants_updated_con = [p | {'connections' : namedtuple('Connections', p['connections'])(**p['connections'])} for p in participants_updated_swarm]
participants_updated_color = [p | {"color" : random.choice(colors)} for p in participants_updated_con]
#print(participants_updated_con)
participants_list_tuple = [namedtuple('Participant', p)(**p) for p in participants_updated_color]
#print(participants_list_dict)
Participants = namedtuple('Participants', idx_str)
participants_final = Participants(*participants_list_tuple)
#print(participants_final)
# # # Create complete dictionary
# # participants_dict = {p['idx'] : p for p in participants_updated_con}
# # print(participants_dict)
# participants_list_dict = [namedtuple('Participants', p)(**p) for p in participants_dict]
# # Create named tuple
# participants_final = namedtuple('Participants', participants_list_dict)(**participants_list_dict)
# for participant in participants_list[:-1]: # The last entry is the network
# participant_new = copy.deepcopy(participant)
# xmin = random.randint(0,layout_zone['width'])
# ymin = random.randint(0,layout_zone['height'])
# participant_new['xmin'] = xmin
# participant_new['ymin'] = ymin
# participant_new['color'] = random.choice(colors)
# participant_new = participant_new | swarm_specifics
# participants_dict.update({participant_new['idx'] : participant_new})
return participants_final
def plot_participants(layout_zone : namedtuple, participants : namedtuple, xmax : int, ymax : int, sleep_time = 0.0, plot_connections = False):
plt.rcParams["figure.figsize"] = [7.00, 7.00]
plt.rcParams["figure.autolayout"] = True
#colors = ['blue', 'orange', 'black']
figure, ax = plt.subplots(1)
ax.plot([0], c='white')
# Plot layout zone
origin = (layout_zone.xmin, layout_zone.ymin)
rectangle = patches.Rectangle(origin, layout_zone.width, layout_zone.height, edgecolor='red',
facecolor='red', linewidth=2, fill = False)
ax.add_patch(rectangle)
# Plot participants
for p in participants:
origin = (p.xmin, p.ymin)
rectangle = patches.Rectangle(origin, p.width, p.height, edgecolor=p.color,
facecolor=p.color, linewidth=0.5, fill = True, alpha = 0.9, hatch = 'x')
center_x = p.xmin + 0.5 * p.width
center_y = p.ymin + 0.5 * p.height
plt.text(center_x, center_y, p.idx)
ax.add_patch(rectangle)
#if plot_connections:
# for key in p['connections']: #TODO: Rethink connection plot
# center_x_other_one = participants[key]['xmin'] + 0.5 * participants[key]['width']
# center_y_other_one = participants[key]['ymin'] + 0.5 * participants[key]['height']
# dx = -(center_x - center_x_other_one)
# dy = -(center_y - center_y_other_one)
# plt.arrow(center_x, center_y, dx, dy)
plt.ylim(-10,ymax)
plt.xlim(-10,xmax)
plt.grid()
#plt.show()
display.clear_output(wait=True)
display.display(pl.gcf())
time.sleep(sleep_time)
plt.close()
return 0