measure_productivity_details.py

#
# Measure Productivity Details
#
# Peter Turney, August 21, 2020
#
# Productivity is the number of ashes observed.
#
import golly as g
import model_classes as mclass
import model_functions as mfunc
import model_parameters as mparam
import apgsearch_repurposed as apg
import pickle
import glob
from statistics import mean
#
# Specify the layer to process.
#
layer_num = "4"
#
# Specify the generation to process
#
generation_num = 100
#
# Log file for reporting the results (output).
#
log_file = "C:/Users/peter/Peter's Projects/autopoiesis" + \
    "/Paper Sections/Part 3 - Productivity/layer_" + layer_num + \
    "_productivity_details.txt"
#
# The layer of pickles to process (input).
#
pickle_layer = "C:/Users/peter/Peter's Projects/autopoiesis/" + \
    "Pickles/Layer " + layer_num
#
# Some parameters.
#
elite_size = 50 # number of seeds in a pickle
num_runs = 12 # runs range from 1 to 12
#
# Specify rule and symmetry.
#
rulestring = "B3/S23" # Game of Life
symmstring = "C1" # C1 means the soup is asymmetric
numsoups = 1 # soup count
#
# Open log file.
#
f = open(log_file, "w", 0) # 0 means no buffer, so instant results
f.write("\n\nLog File for Productivity Report\n\n")
f.write("generation number\trun number\tavg seed productivity\n")
#
# Iterate over the runs
#
for run in range(1, num_runs + 1):
    #
    # Look in the directory pickle_layer for the file
    # with the current run number. The file will match
    # the pattern "run[run]/log-...-pickle-[gen].bin". Note
    # that glob.glob returns a list, since there may be many
    # matching files, but we hope there is only one matching
    # file.
    #
    pickle_paths = glob.glob(pickle_layer + "/run" + \
        str(run) + "/log-*-pickle-" + str(generation_num) + ".bin")
    assert len(pickle_paths) == 1 # should be exactly one match
    pickle_path = pickle_paths[0] # extract the match from the list
    #
    # Load the pickle.
    # 
    pickle_handle = open(pickle_path, "rb") # rb = read binary
    seed_list = pickle.load(pickle_handle)
    pickle_handle.close()
    #
    # Iterate over the seeds in the pickle.
    #
    seed_productivity = list() # a list of type counts for seeds
    #
    for seed in seed_list:
        soup = apg.Soup()
        soup.rg.setrule(rulestring)
        soup.rg.saveAllRules()
        soup.stabilise_seed(seed)
        [objects, frequencies] = soup.basic_census()
        total_ash_count = sum(frequencies) # number of tokens of ash
        seed_productivity.append(total_ash_count)
    #
    avg_seed_productivity = mean(seed_productivity)
    #
    # Report the statistics for the given generation.
    #
    f.write("{:5d}\t{:5d}\t{:8.2f}\n".format( \
        generation_num, run, avg_seed_productivity))
    #
#
# Close file.
#
f.close()
#
#
#