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visualize_in_model_natural_heat_capacity.py
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visualize_in_model_natural_heat_capacity.py
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from helper_functions.automatic_plot_helper import load_isings_attributes_from_list
import matplotlib.pyplot as plt
import pickle
from os import path, makedirs
def plot_heat_cap(heat_cap_vecs, gen, sim_name):
beta_facs = load_beta_facs(sim_name)
savefolder = 'save/{}/figs/nat_heat_cap/'.format(sim_name)
savefilename = savefolder + 'nat_heat_cap' + '-Nbetas_' + str(len(heat_cap_vecs[0])) + '-gen_' + str(gen) + '.png'
if not path.exists(savefolder):
makedirs(savefolder)
plt.rcParams.update({'font.size': 22})
fig, ax = plt.subplots(1, 1, figsize=(11, 10), sharex=True)
fig.text(0.51, 0.035, r'$\beta_{\mathrm{fac}}$', ha='center', fontsize=28)
fig.text(0.005, 0.5, r'$C/N$', va='center', rotation='vertical', fontsize=28)
title = 'Natural Specific Heat of Foraging Community\n Generation: ' + str(gen)
title = ''
fig.suptitle(title, fontsize=28)
for heat_cap_vec in heat_cap_vecs[:5]:
#plt.scatter(beta_facs, heat_cap_vec)
# ax.scatter(beta_facs, heat_cap_vec, s=6, alpha=0.5, marker='o', label=None)
ax.scatter(beta_facs, heat_cap_vec, s=10, alpha=1, marker='o', label=None)
# xticks = [0.1, 0.5, 1, 2, 4, 10]
ax.set_xscale("log", nonposx='clip')
# ax.set_xticks(xticks)
# ax.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())
plt.ylim(0, 1)
upperbound = 0.4
#plt.axis([0.1, 10, 0, upperbound])
print('Saving nat heat capacity plot: {}'.format(savefilename))
plt.savefig(savefilename, bbox_inches='tight', dpi=300)
def load_and_plot(sim_name, gens):
heat_cap_vecs_gens = load_isings_attributes_from_list(sim_name, gens, 'heat_capacity_vec')
beta_vecs_gens = load_isings_attributes_from_list(sim_name, gens, 'beta_vec')
for heat_cap_vecs, gen in zip(heat_cap_vecs_gens, gens):
plot_heat_cap(heat_cap_vecs, gen, sim_name)
def plot_all_possible_gens(sim_name):
'''
This is MAIN FUNCTION
'''
all_heat_capacity_gens = load_gens_with_heat_cap(sim_name)
load_and_plot(sim_name, all_heat_capacity_gens)
def load_gens_with_heat_cap(sim_name):
#dir = 'save/{}/generations_nat_heat_capacity_calculated.pickle'.format(sim_name)
dir = 'save/{}/nat_heat_capacity_data/generations_nat_heat_capacity_calculated.pickle'.format(sim_name)
file = open(dir, 'rb')
all_heat_capacity_gens = pickle.load(file)
file.close()
return all_heat_capacity_gens
def load_beta_facs(sim_name):
'''
Loads beta_facs: factors that organisms original beta value has been multiplied with
'''
dir = 'save/{}/nat_heat_capacity_data/beta_facs.pickle'.format(sim_name)
file = open(dir, 'rb')
beta_facs = pickle.load(file)
file.close()
return beta_facs
if __name__ == '__main__':
#sims = ['sim-20200416-003618-g_2000_-t_2000_-c_gen_200_-ref_200_-b_10_-c_props_-10_10_102_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003611-g_2000_-t_2000_-c_gen_200_-ref_200_-b_0.1_-c_props_-10_10_102_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003603-g_2000_-t_2000_-c_gen_200_-ref_200_-b_1_-c_props_-5_5_102_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003527-g_2000_-t_2000_-c_gen_200_-ref_200_-b_1_-c_props_-10_10_102_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003407-g_2000_-t_2000_-c_gen_200_-ref_200_-b_0.1_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003357-g_2000_-t_2000_-c_gen_200_-ref_200_-b_10_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003347-g_2000_-t_2000_-c_gen_200_-ref_200_-b_1_-n_first_nat_C_test_reset_line_enabled', 'sim-20200416-003238-g_2000_-t_2000_-c_gen_200_-ref_200_-b_10_-n_first_nat_C_test_reset_line_disabled', 'sim-20200416-003227-g_2000_-t_2000_-c_gen_200_-ref_200_-b_0.1_-n_first_nat_C_test_reset_line_disabled', 'sim-20200416-003217-g_2000_-t_2000_-c_gen_200_-ref_200_-b_1_-n_first_nat_C_test_reset_line_disabled']
sims=['sim-20200724-152938-g_1_-b_1_-nat_c_1_-nat_c_props_-1_1_100_-noplt_-n_nat_c_for_report_big_dots']
for sim in sims:
plot_all_possible_gens(sim)
# sim = 'sim-20200416-003618-g_2000_-t_2000_-c_gen_200_-ref_200_-b_10_-c_props_-10_10_102_-n_first_nat_C_test_reset_line_enabled'
# plot_all_possible_gens(sim)