def d0_nw_paper(data, rholimits):
rhopairs = sf.limitslist(rholimits)
fig, axarr = plt.subplots(nrows=1,
ncols=3,
dpi=150,
figsize=(11, 4),
sharex=True,
sharey=True,
tight_layout=True)
for i, (rhomin, rhomax) in enumerate(rhopairs):
limitstr = rhorangestr % (rhomin * read.RHO_SCALE,
rhomax * read.RHO_SCALE)
ax = axarr[i]
datarho = data[data.rhomin == rhomin] #.loc['second']
datarho.plot.scatter(x=d0_col, y='log_nw', c='', ax=axarr[i])
lfit = fit.LinFit(x=datarho[d0_col], y=datarho.log_nw, xname='D_0')
lfit.find_fit()
lfit.plot(source_style=None, ax=ax)
#efit = fit.ExponentialFit(x=datarho.D_0, y=datarho.N_w)
#efit.find_fit()
#efit.plot(source_style='raw', ax=ax)
ax.legend()
ax.set_title(limitstr)
ax.set_xlabel('')
axarr[0].set_ylabel('$log(N_w)$')
axarr[1].set_xlabel('$D_0$, mm')
axarr[-1].set_title('$\\rho > %s$' % (rhomin * read.RHO_SCALE))
plt.axis([0, 5, 1, 6])
#remove_subplot_gaps(fig, axis='row')
return fig, axarr
def d0_nw_paper(data, rholimits):
rhopairs = sf.limitslist(rholimits)
fig, axarr = plt.subplots(nrows=1, ncols=3, dpi=150, figsize=(11,4),
sharex=True, sharey=True, tight_layout=True)
for i, (rhomin, rhomax) in enumerate(rhopairs):
limitstr = rhorangestr % (rhomin*read.RHO_SCALE, rhomax*read.RHO_SCALE)
ax = axarr[i]
datarho = data[data.rhomin==rhomin]#.loc['second']
datarho.plot.scatter(x=d0_col, y='log_nw', c='', ax=axarr[i])
lfit = fit.LinFit(x=datarho[d0_col], y=datarho.log_nw, xname='D_0')
lfit.find_fit()
lfit.plot(source_style=None, ax=ax)
#efit = fit.ExponentialFit(x=datarho.D_0, y=datarho.N_w)
#efit.find_fit()
#efit.plot(source_style='raw', ax=ax)
ax.legend()
ax.set_title(limitstr)
ax.set_xlabel('')
axarr[0].set_ylabel('$log(N_w)$')
axarr[1].set_xlabel('$D_0$, mm')
axarr[-1].set_title('$\\rho > %s$' % (rhomin*read.RHO_SCALE))
plt.axis([0, 5, 1, 6])
#remove_subplot_gaps(fig, axis='row')
return fig, axarr
import snowfall as sf
import read
import numpy as np
import matplotlib.pyplot as plt
from os import path
import fit
from scr_snowfall import param_table
plt.close('all')
plt.ioff()
debug = False
rholims = (0, 100, 200, 800)
#rholims = (0, 150, 300, 800)
limslist = sf.limitslist(rholims)
n_ranges = len(limslist)
separate = False
d0_col = 'D_0_gamma'
resultspath = '../results/pip2015'
paperpath = read.ensure_dir(path.join(resultspath, 'paper'))
savepath = path.join(resultspath, 'psd')
rhorangestr = '$%s < \\rho \leq %s$'
def d0_nw_paper(data, rholimits):
rhopairs = sf.limitslist(rholimits)
fig, axarr = plt.subplots(nrows=1,
ncols=3,
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}
limslist=sf.limitslist(rholimits)
data = param_table(e=e, debug=debug)
data.index = data.index.droplevel()
vdata = read.merge_series(e.pluv_grouper(), e.vel_data())
vtable = pd.merge(vdata, pd.DataFrame(data.rhomin), left_on='group', right_index=True)
# TODO: check duplicates
vfits = dict()
for rhomin in rholimits[:-1]:
pipv = read.PipV(data=vtable.query('rhomin=={0}'.format(rhomin)))
vfits[rhomin], std, etc = pipv.pickler('v-d_rho_range', pipv.find_fit, **fitargs)
fig, axarr = sf.plot_vfits_rho_intervals(dict2tuple(vfits), limslist, **kws)
axarr[0].axis(bnds)
for ax in axarr:
ax.tick_params(direction='out', top=False)
pc = pd.DataFrame(index=rholimits[:-1], columns=['count_all', 'count_hwfm', 'r_sq'])