def summarize_csv(specs):
first_run = True
general_csv = output_handle('summary')
rh_csv = output_handle('rh-thresholds')
check_csv = output_handle('checking')
rh_by_runtime_csv = output_handle('daily-rh-runtime')
for desc, scenario_path in specs:
name = desc[-1]
if exists(scenario_path):
print("loading {0} from {1}".format(name, scenario_path))
hourly = hourly_data(scenario_path)
print("summarizing {0}".format(name))
output_row(desc, summarize_run, hourly, general_csv, first_run)
output_row(desc, rh_stats, hourly, rh_csv, first_run)
output_row(desc, check_loads, hourly, check_csv, first_run)
output_row(desc, rh_by_runtime, hourly, rh_by_runtime_csv, first_run)
for k in ['SOLN', 'SOLE', 'SOLS', 'SOLW', 'QWALLS', 'QCEIL', 'QFLR', ]:
if not hasattr(hourly, k):
print("missing {0}".format(k))
first_run = False # flag, never becomes true again in this call
if graphs:
print("graphing {0}".format(name))
plot_TRH(hourly, name)
plot_humidity_ratio(hourly, name)
#plot_Wrt(name, hourly)
plot_rh_hist_daily(hourly, name)
#plot_t_hist(name, hourly)
plot_daily_psychrometric(hourly, name)
ac_bal_point(hourly, name)
else:
# scenario path does not exist
print( "skipping {0}: path {1} does not exist".format(name, scenario_path))
def dir_to_json(path):
h = hourly_data(path).__dict__
for key in h.keys():
if key == "name":
continue
handle = open(join(path, "{0}-{1}.json".format(basename(path), key)), "w")
handle.write("[ ")
handle.write(", ".join(map(float_to_str, h[key].tolist())))
handle.write("]\n")
handle.close()
from pandas import *
from parametrics import hourly_data
import os
from os.path import join, isdir
from numpy import arange
DIR = '/home/bergey/Library/rp-1449-results/'
dates = arange(1,8761)
for system in os.listdir(DIR):
store = HDFStore('{0}.h5'.format(system))
n = len(os.listdir(join(DIR,system)))-1
i = 0
print("entering directory {0}".format(system))
for sim in os.listdir(join(DIR,system)):
if not isdir(join(DIR,system, sim)):
continue
i += 1
print("{0}/{1}: {2}".format(i,n,sim))
h = hourly_data(join(DIR,system,sim))
df = DataFrame(h.__dict__, index=dates)
store[sim] = df
