def main():
print(sys.argv)
if len(sys.argv) < 3:
print('Expected "show/save/html" then type of analysis')
return
fig_option = sys.argv[1]
if fig_option not in ["show", "save", "html"]:
print('Expected "show/save/html" as first option')
return
analyze_option = sys.argv[2]
data = read_data()
fig = analyze.get_fig(analyze_option, data)
if fig_option == "show":
fig.show()
elif fig_option == "html":
fig.write_html("index.html")
elif fig_option == "save":
if len(sys.argv) < 4:
print("Expected filename to save")
return
name = sys.argv[3]
filepath = os.path.join(constants.IMAGE_FOLDER, name)
fig.write_image(filepath)
plt.errorbar((data['postsamples']),
data['medium'],
yerr=data['std_dev'],
label=label)
plt.xscale('log')
plt.legend(loc='best')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.tight_layout(pad=0)
meas_path = '/home/milosz/Projects/master/measurements/transport_measurements/'
save_path = '/home/milosz/Projects/master/figures/measurements/'
file_name = meas_path + 'XMLRPC/XMLRPC_efficiency_ZMQRPC.txt'
XML_dat_4_chan = read_data(file_name)[3]
file_name = meas_path + 'ZMQ/ZMQ_pickle.txt'
ZMQ_pickle_dat_4_chan = read_data(file_name)[3]
file_name = meas_path + 'numpy/ZMQ/ZMQ_pickle_numpy.txt'
ZMQ_pickle_numpy_dat_4_chan = read_data(file_name)[3]
file_name = meas_path + 'ZMQ/ZMQ_json.txt'
ZMQ_json_dat_4_chan = read_data(file_name)[3]
file_name = meas_path + 'ZMQ/ZMQ_protobuf.txt'
ZMQ_protobuf_dat_4_chan = read_data(file_name)[3]
file_name = meas_path + 'TCP/TCP_pickle.txt'
TCP_pickle_dat_4_chan = read_data(file_name)[3]
from __future__ import print_function
from builtins import range
from pareto import *
import parse
names, values = parse.read_data('../data/results_10000_a.out')
#names, values = parse.read_data('../data/20161207_results_100k.out')
vals = [[v[i] for i in range(len(v)) if names[2][i].endswith('_abserr')]
for idx, p, v in values]
#timing(pareto_bruteforce)(vals)
pareto_vals = timing(pareto)(vals)
print(len(vals), len(pareto_vals))
('s', 's0', 's00', 'e', 'e0', 'e1', 'e2', 'e3', 'e4', 'e5'): (10., 2.1),
('sa', 'sa0', 'sa00', 's0a'): (6.2, 1.1),
('sab', 'sabc', 'sabb', 'sabbc', 'sabd', 'sam', 'sb', 'sbab', 'sbb', 'sba', 'sb0', 'sb0a'): (6.5, 0.5),
('sbc', 'sbbc', 'sb0', 'sc'): (4.7, 0.4),
('scd', 'sd', 'cd'): (3.9, 0.6),
('sdm', 'irr'): (1.7, 0.6)
}
def clean_type(gtype):
cleaned = gtype.lower().replace('?', '').replace('(r)', '').replace('(s)', '').replace('(r\')', '').replace('(rs)', '')
cleaned = cleaned.replace('edge-on', '').replace('pec', '')
cleaned = re.sub('[/^+-]', '', cleaned)
return cleaned.strip()
def get_mass_estimate(luminosity, gtype):
cleaned_type = clean_type(gtype)
for typeset in M_LUM_RATIOS:
if cleaned_type in typeset:
lum_ratio, err = M_LUM_RATIOS[typeset]
return SOLAR_MASS * lum_ratio * luminosity, SOLAR_MASS * err * luminosity
return SOLAR_MASS * DEFAULT_RATIO[0] * luminosity, SOLAR_MASS * DEFAULT_RATIO[1] * luminosity
if __name__=='__main__':
data_list = read_data()
gtypes = set()
for data in data_list:
if data[LUM] and data[GTYPE]:
gtypes.add(clean_type(data[GTYPE]))
for gtype in gtypes:
if not any([gtype in k for k in M_LUM_RATIOS]):
print gtype
def save_histogram(data, name):
mean, var, sigma = calculate_statistics(data)
fig, ax = plt.subplots()
ax.hist(data, bins=100)
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
text = "Mean: {:<1.2f}\n".format(mean) +\
"Sigma: {:<1.2f}\n".format(sigma)
ax.text(0.80,
0.95,
text,
transform=ax.transAxes,
fontsize=10,
verticalalignment='top',
bbox=props)
plt.xlabel('ns')
plt.savefig('/home/milosz/Projects/master/figures/measurements/' + name +
'.svg',
format='svg')
meas_path = '/home/milosz/Projects/master/measurements/precision/'
save_path = '/home/milosz/Projects/master/figures/measurements/'
#for file in os.listdir(meas_path):
# if file.endswith('.txt'):
# data = read_data(meas_path + file)
# save_histogram(data, file.replace('.txt', ''))
file = 'WRTD_other_day.txt'
data = read_data(meas_path + file)
save_histogram(data, file.replace('.txt', ''))
label=label)
plt.legend(loc='best')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.subplot(212)
plt.errorbar((data['postsamples']),
data['medium'],
yerr=data['std_dev'],
label=label)
plt.xscale('log')
plt.legend(loc='best')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.tight_layout(pad=0)
meas_path = '/home/milosz/Projects/master/measurements/freq_meas/'
save_path = '/home/milosz/Projects/master/figures/measurements/'
file_name = meas_path + 'loop_adc/frequency_meas.txt'
loop_adc = read_data(file_name)[3]
file_name = meas_path + 'loop_server/frequency_meas.txt'
loop_server = read_data(file_name)[3]
add_data_to_fig(loop_adc, 'ADC loop', 'postsamples',
'acquisition frequency[Hz]')
add_data_to_fig(loop_server, 'Server loop', 'postsamples',
'acquisition frequency[Hz]')
plt.savefig(save_path + 'loop_adc_server_comparison.svg', format='svg')