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ghca_plot.py
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import numpy as np
from matplotlib import colors
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import ghca_main as ca
import ghca_core as cacore
def run_config_id(pair,core,config_id,T=1,emb=True,return_str=False):
"""
"""
active = pair[0] ; passive = pair[1] ; n_states = active+passive+1
str_state = cacore.base_conv(config_id,n_states);str_state = str_state.rjust(core,'0')
if emb:
grid_size = np.sqrt(core)+4
p = np.zeros((int(grid_size),int(grid_size)))
q = cacore.str_to_state(str_state,n_states)
if int(np.sqrt(core))%2==0:
p[int(grid_size/2)-int(np.sqrt(core)/2):int(grid_size/2)+int(np.sqrt(core)/2),
int(grid_size/2)-int(np.sqrt(core)/2):int(grid_size/2)+int(np.sqrt(core)/2)]=q
else:
p[int(grid_size/2)-int(np.sqrt(core)/2):int(grid_size/2)+int(np.sqrt(core)/2)+1,
int(grid_size/2)-int(np.sqrt(core)/2):int(grid_size/2)+int(np.sqrt(core)/2)+1]=q
else:
grid_size = np.sqrt(core)
p = cacore.str_to_state(str_state,n_states)
com = [ca.Population(p=np.copy(p),act=active,pas=passive)]
states=np.empty((T,int(grid_size),int(grid_size)),dtype=np.int8);str_states = []
for t in range(T):
states[t] = np.copy(np.array(com[0].p,dtype=np.int8))
state = cacore.state_to_str(com[0].p,n_states)
str_states.append(state)
com = ca.run(com)
if return_str:
return str_states,p
else:
return states,p
def plot_perst_prob(core,flag,anchor=1,show=True):
"""
"""
cycle_set = list(range(1,18))
fixed_len_pairs = [(i,j) for i in cycle_set for j in cycle_set if i+j==cycle]
fixed_passive = anchor ; inc_act_pairs = [(i,fixed_passive) for i in cycle_set]
fixed_active = anchor ; inc_pas_pairs = [(fixed_active,i) for i in cycle_set]
plt.ylim(-0.1,1.1)
plt.ylabel("$P_{perst}$")
if flag=='Fixed\ cycle':
param_pair=fixed_len_pairs
plt.xticks(range(len(param_pair)),labels=param_pair)
plt.xlabel("$States\ -\ (Active,Passive)$")
plt.title("$Core\ Size:\ {0},\ Cycle\ Length:\ {1}$".format(core,cycle))
elif flag=='Fixed\ passive':
param_pair=inc_act_pairs
plt.xticks(range(len(param_pair)),labels=[i[0] for i in param_pair])
plt.xlabel("$Active$")
plt.title("$Core\ Size:\ {0}$".format(core))
elif flag=='Fixed\ active':
param_pair=inc_pas_pairs
plt.xticks(range(len(param_pair)),labels=[i[1] for i in param_pair])
plt.xlabel("$Passive$")
plt.title("$Core\ Size:\ {0}$".format(core))
else:
print("Incorrect flag!")
act_frac = {}
for pair in param_pair:
act_config_ids = np.load(data_path+"act_config_ids_states-({0:02d},{1:02d})_core-{2:02d}.npy".format(*pair,core))
frac = len(act_config_ids)/(sum(pair)+1)**core
act_frac[pair]=frac
act_conf_frac = list(act_frac.values())
plt.plot(range(len(param_pair)),act_conf_frac,'-o',label="${0:01d}$".format(anchor))
plt.legend(loc='best',title="${}$".format(flag))
if show:
plt.show()
return
def plot_param_space(core):
"""
Fraction of init configs that persist (for given core size) = basin[passive-1,active-1]
"""
max_cyc = 18
len_set = list(range(1,max_cyc))
param_pairs=[(i,j) for i in len_set for j in len_set]
param_space = np.zeros((max_cyc-1,max_cyc-1))
for pair in param_pairs:
act = pair[0];pas=pair[1]
conf_id = np.load(data_path+"act_config_ids_states-({0:02d},{1:02d})_core-{2:02d}.npy".format(act,pas,core))
param_space[pas-1,act-1] = len(conf_id)/(np.sum(pair)+1)**core
plt.xticks(range(max_cyc-1),labels=len_set);plt.yticks(range(max_cyc-1),labels=len_set)
plt.xlabel("$Active$");plt.ylabel("$Passive$")
plt.imshow(param_space,cmap='jet',origin='lower',interpolation='none')
plt.title("$Core\ Size:\ {0}$".format(core))
plt.colorbar()
plt.show()
return
if __name__=='__main__':
T=50
active=6; passive=17
cycle=active+passive; num_states=cycle+1
core_len = 2; core_size = np.square(core_len)
## emb_core_len = core_len+2; emb_core_size=np.square(emb_core_len)
cmap = colors.ListedColormap(['xkcd:pale grey','xkcd:darkish red','xkcd:almost black'])
bounds = [0,0.99,active+0.99,cycle+0.99]
norm = colors.BoundaryNorm(bounds,cmap.N)
data_path = "./result/"
config_ids = np.load(data_path+"act_config_ids_states-({0:02d},{1:02d})_core-{2:02d}.npy".format(active,passive,core_size))
print('Total configs =',num_states**core_size,'\nActive configs = ',len(config_ids))
print("Persistent config IDs for (active,passive) = ({0:02d},{1:02d}) and core size = {2:02d}\n".format(active,passive,core_size),config_ids)
conf_id = 1496#config_ids[73]
s,p = run_config_id((active,passive),core_size,conf_id,T=T)#,emb=True,return_str=False)
com = [ca.Population(p=p,act=active,pas=passive)]
ca.plot(com,cid=conf_id,cbar='v',txt='True')
ca.animate(com,s,T=T,interval=500,txt=True)
## flag='Fixed\ active';anch = 17
## plot_perst_prob(core_size,flag,anch)
for i in range(1,18):
flag='Fixed\ active'
## flag='Fixed\ passive'
plot_perst_prob(core_size,flag,i,show=False)
plt.legend(loc='best',title="${}$".format(flag))
plt.show()
plot_param_space(core_size)