def casewise_hist():
"""DEPRECATED"""
if debug:
e = test_events()
else:
e = pip2015events()
n_cases = e.events.paper.count()
fd, axarrd = subplots(n_cases)
fm, axarrm = subplots(n_cases)
fn, axarrn = subplots(n_cases)
for i, c in enumerate(e.events.paper.values):
print(c)
data = hist_data(c)
plots(data, axarrd[i], axarrm[i], axarrn[i], title=c.dtstr(), y=0.85,
fontdict={'verticalalignment': 'top', 'fontsize': 10})
del(e)
gc.collect()
for f in (fd, fm, fn):
sf.remove_subplot_gaps(f, axis='col')
fd.savefig(path.join(savedir, 'd0_cases' + tld), **savekws)
fm.savefig(path.join(savedir, 'mu_cases' + tld), **savekws)
fn.savefig(path.join(savedir, 'nw_cases' + tld), **savekws)
debug = False
unfiltered = False
legacy = False
tld = '.eps'
bnds = (0.25, 3.0, 0.5, 1.8)
savepath = path.join(paths['results'], 'vfits_density_ranges')
def dict2tuple(di):
return tuple(di[key] for key in sorted(di))
if debug:
e = test_events()
else:
e = pip2015events()
#plt.close('all')
plt.ioff()
hextent = np.array(bnds) + (-0.1, 0.1, -0.1, 0.1)
kws = {
'separate': True,
'source_style': 'hex',
'source_kws': {
'gridsize': 26,
'extent': hextent
},
'unfiltered': True
}
fitargs = {'force_flip': False, 'try_flip': False, 'fitclass': fit.PolFit}
"""
@author: Jussi Tiira
"""
from snowfall import *
import matplotlib.pyplot as plt
from os import path
import read
from scr_snowfall import pip2015events, test_events
debug = True
if debug:
e = test_events()
else:
e = pip2015events()
plt.close('all')
plt.ioff()
basepath = '../results/pip2015/vfit'
if debug:
basepath += '/test'
fname = '%Y%m%d_%H%M'
date_format = '%d. %m. %Y'
time_format = '%H:%M'
extent = (0.375, 5, 0.5, 2.5)
for c in e.events.paper.values:
c.density() # to initialize fits
