def write_results(world, results_path, timestep):
"""
Function to periodically save model results to CSV (if this option is
selected in the rc file).
"""
if rcParams['save_psn_data']:
world.write_persons_to_csv(timestep, results_path)
if rcParams['save_lulc_data']:
output_file = os.path.join(results_path, "lulc_time_%s.tif"%timestep)
lulc, gt, prj = world.get_lulc_data()
write_single_band_raster(lulc, gt, prj, output_file)
def main(argv=None):
if argv is None:
argv = sys.argv
try:
rc_file = sys.argv[1]
print "\nWARNING: using default rc params. Custom rc_file use is not yet implemented.\n"
except IndexError:
pass
# Get machine hostname to print it in the results file and use in the
# run_ID_number.
hostname = socket.gethostname()
# The run_ID_number provides an ID number (built from the start time and
# machine name) to uniquely identify this model run.
run_ID_number = time.strftime("%Y%m%d-%H%M%S") + '_' + hostname
# First strip any trailing backslash from the model.resultspath value from
# rcparams, so that os.path.join-ing it to the scenario.name does not lead
# to having two backslashes in a row.
model_results_path_root = str.strip(rcParams['model.resultspath'], "/\\")
scenario_path = os.path.join(str(rcParams['model.resultspath']), rcParams['scenario.name'])
results_path = os.path.join(scenario_path, run_ID_number)
if not os.path.exists(scenario_path):
try:
os.mkdir(scenario_path)
except OSError:
raise OSError("error creating scenario directory %s"%(scenario_path))
try:
os.mkdir(results_path)
except OSError:
raise OSError("error creating results directory %s"%(results_path))
if rcParams['model.reinitialize']:
# Generate a new world (with new resampling, etc.)
world = generate_world()
else:
# Load a pickled World for use in the model.
input_data_file = rcParams['path.initialization_file']
file = open(input_data_file, "r")
try:
world = pickle.load(file)
except IOError:
raise IOError('error loading world data from %s'%input_data_file)
# Run the model loop
start_time = time.localtime()
start_time_string = time.strftime("%m/%d/%Y %I:%M:%S %p", start_time)
print """
************************************************************************************
%s: run %s started.
************************************************************************************
"""%(start_time_string, run_ID_number)
time_strings = main_loop(world, results_path) # This line actually runs the model.
end_time = time.localtime()
end_time_string = time.strftime("%m/%d/%Y %I:%M:%S %p", end_time)
print """
************************************************************************************
%s: run %s finished.
************************************************************************************
"""%(end_time_string, run_ID_number)
# Save the results
print "Saving result files..."
# Write out the world file and mask used to run the model. Update the
# rcparams to point to these files so they will be reused if this run is
# rerun.
#DEM_data_file = os.path.join(results_path, "AccraABM_DEM.tif")
#array, gt, prj = world.get_DEM_data()
#write_single_band_raster(array, gt, prj, DEM_data_file)
world_mask_data_file = os.path.join(results_path, "AccraABM_world_mask.tif")
array, gt, prj = world.get_world_mask_data()
write_single_band_raster(array, gt, prj, world_mask_data_file)
lulc_data_file = os.path.join(results_path, "AccraABM_land_cover.tif")
array, gt, prj = world.get_lulc_data()
write_single_band_raster(array, gt, prj, lulc_data_file)
# TODO: write a function to handle writing out a markov_matrix from the
# world/rcparams. Do this maybe after writing markov_matrix handling into
# the rcvalidation code.
# Save the SHA-1 of the commit used to run the model, along with any diffs
# from the commit (the output of the git diff command). sys.path[0] gives
# the path of the currently running AccraABM code.
git_diff_file = os.path.join(results_path, "git_diff.patch")
commit_hash = save_git_diff(sys.path[0], git_diff_file)
time_csv_file = os.path.join(results_path, "time.csv")
write_time_csv(time_strings, time_csv_file)
if rcParams['model.make_LULC_animations']:
print "Saving LULC plots..."
Rscript_binary = rcParams['path.Rscript_binary']
dev_null = open(os.devnull, 'w')
try:
subprocess.check_call([Rscript_binary, 'plot_LULC.R', results_path],
cwd=sys.path[0], stdout=dev_null, stderr=dev_null)
except:
print "WARNING: Error running plot_LULC.R."
dev_null.close()
if rcParams['model.make_health_animations']:
print "Saving health plots..."
Rscript_binary = rcParams['path.Rscript_binary']
dev_null = open(os.devnull, 'w')
try:
subprocess.check_call([Rscript_binary, 'plot_health.R', results_path],
cwd=sys.path[0], stdout=dev_null, stderr=dev_null)
except:
print "WARNING: Error running plot_health.R."
dev_null.close()
# Calculate the number of seconds per month the model took to run (to
# simplify choosing what machine to do model runs on). This is equal to the
# length of time_strings divided by the timestep size (in months).
speed = (time.mktime(end_time) - time.mktime(start_time)) / (len(time_strings['timestep']) / rcParams['model.timestep'])
# After running model, save rcParams to a file, along with the SHA-1 of the
# code version used to run it, and the start and finish times of the model
# run. Save this file in the same folder as the model output.
run_RC_file = os.path.join(results_path, "AccraABMrc")
RC_file_header = """# This file contains the parameters used for a AccraABM model run.
# Model run ID:\t%s
# Start time:\t%s
# End time:\t\t%s
# Run speed:\t%.4f
# Code version:\t%s"""%(run_ID_number, start_time_string, end_time_string,
speed, commit_hash)
write_RC_file(run_RC_file, RC_file_header, rcParams)
print "Results saved to %s"%results_path
print "\nFinished at", time.strftime("%m/%d/%Y %I:%M:%S %p") + "."
return 0