def test_h5():
try:
import h5py
dct1 = \
{'/a': 'abcgs',
'/b/c/x1': 3,
'/b/c/x2': rand(2,3),
}
# writing a dct w/o leading slash will always be read back in *with*
# leading slash
dct2 = \
{'a': 'abciqo4iki',
'b/c/x1': 3,
'b/c/x2': rand(2,3),
}
for idx, dct in enumerate([dct1, dct2]):
h5fn = os.path.join(testdir, 'test_%i.h5' % idx)
io.write_h5(h5fn, dct)
read_dct = io.read_h5(h5fn)
for kk in list(read_dct.keys()):
assert kk.startswith('/')
for kk in list(dct.keys()):
key = '/' + kk if not kk.startswith('/') else kk
tools.assert_all_types_equal(dct[kk], read_dct[key])
# write mode='a', test appending
h5fn = os.path.join(testdir, 'test_append.h5')
io.write_h5(h5fn, {'/a': 1.0})
read_dct = io.read_h5(h5fn)
assert list(read_dct.keys()) == ['/a']
assert read_dct['/a'] == 1.0
# append '/b', using {'/a': 1.0, '/b': 2.0} would be an error since /a
# already exists, use mode='w' then, but this overwrites all!
io.write_h5(h5fn, {'/b': 2.0}, mode='a')
read_dct2 = io.read_h5(h5fn)
# sort(...): sort possible [/b, /a] -> [/a, /b]
assert np.sort(np.array(list(
read_dct2.keys()))).tolist() == ['/a', '/b']
assert read_dct2['/a'] == 1.0
assert read_dct2['/b'] == 2.0
# overwrite
io.write_h5(h5fn, {'/b': 22.0, '/c': 33.0}, mode='w')
read_dct3 = io.read_h5(h5fn)
assert np.sort(np.array(list(
read_dct3.keys()))).tolist() == ['/b', '/c']
except ImportError:
tools.skip("skipping test_h5, no h5py importable")
def test_h5():
try:
import h5py
dct1 = \
{'/a': 'abcgs',
'/b/c/x1': 3,
'/b/c/x2': rand(2,3),
}
# writing a dct w/o leading slash will always be read back in *with*
# leading slash
dct2 = \
{'a': 'abciqo4iki',
'b/c/x1': 3,
'b/c/x2': rand(2,3),
}
for idx,dct in enumerate([dct1, dct2]):
h5fn = os.path.join(testdir, 'test_%i.h5' %idx)
io.write_h5(h5fn, dct)
read_dct = io.read_h5(h5fn)
for kk in read_dct.keys():
assert kk.startswith('/')
for kk in dct.keys():
key = '/'+kk if not kk.startswith('/') else kk
tools.assert_all_types_equal(dct[kk], read_dct[key])
# write mode='a', test appending
h5fn = os.path.join(testdir, 'test_append.h5')
io.write_h5(h5fn, {'/a': 1.0})
read_dct = io.read_h5(h5fn)
assert read_dct.keys() == ['/a']
assert read_dct['/a'] == 1.0
# append '/b', using {'/a': 1.0, '/b': 2.0} would be an error since /a
# already exists, use mode='w' then, but this overwrites all!
io.write_h5(h5fn, {'/b': 2.0}, mode='a')
read_dct2 = io.read_h5(h5fn)
# sort(...): sort possible [/b, /a] -> [/a, /b]
assert np.sort(np.array(read_dct2.keys())).tolist() == ['/a', '/b']
assert read_dct2['/a'] == 1.0
assert read_dct2['/b'] == 2.0
# overwrite
io.write_h5(h5fn, {'/b': 22.0, '/c': 33.0}, mode='w')
read_dct3 = io.read_h5(h5fn)
assert np.sort(np.array(read_dct3.keys())).tolist() == ['/b', '/c']
except ImportError:
tools.skip("skipping test_h5, no h5py importable")
phdos.append(np.array([freq, gauss(freq - fc, 100) * 0.01]).T)
gibbs = Gibbs(T=T,
P=P,
etot=etot,
phdos=phdos,
axes_flat=axes_flat,
volfunc_ax=volfunc_ax,
case=case,
dosarea=None)
gibbs.set_fitfunc('C',
lambda x, y: num.Spline(x, y, s=None, k=5, eps=1e-5))
g = gibbs.calc_G(calc_all=True)
common.makedirs('../files/gibbs/2d')
io.write_h5('../files/gibbs/2d/%s.h5' % gethostname(),
filt_dct(g),
mode='w')
# 1d case
case = '1d'
V = np.linspace(10, 20, nax)
axes_flat = V**(1 / 3.) # cubic
volfunc_ax = lambda x: x[0]**3.0
etot = (V - V.mean())**2
fcenter = 450 + 100 * (axes_flat - axes_flat.min())
# fake phonon dos data (Gaussian), shift to lower freq for higher volume
phdos = [np.array([freq, gauss(freq - fc, 100)]).T for fc in fcenter[::-1]]
gibbs = Gibbs(T=T,
P=P,
etot=etot,
etot = np.array([(a-cell_a_mean)**2.0 + (c-cell_c_mean)**2.0 for a,c in axes_flat])
phdos = []
Vmax = V.max()
# phonon dos (just a gaussian) shifted to lower (higher) freqs for higher
# (lower) volume
for ii in range(axes_flat.shape[0]):
a,c = axes_flat[ii,:]
fc = 550 - 50 * V[ii] / Vmax
phdos.append(np.array([freq,gauss(freq-fc,100)*0.01]).T)
gibbs = Gibbs(T=T, P=P, etot=etot, phdos=phdos, axes_flat=axes_flat,
volfunc_ax=volfunc_ax, case=case, dosarea=None)
gibbs.set_fitfunc('C', lambda x,y: num.Spline(x,y,s=None,k=5, eps=1e-5))
g = gibbs.calc_G(calc_all=True)
common.makedirs('../files/gibbs/2d')
io.write_h5('../files/gibbs/2d/%s.h5' %gethostname(), filt_dct(g), mode='w')
# 1d case
case = '1d'
V = np.linspace(10,20,nax)
axes_flat = V**(1/3.) # cubic
volfunc_ax = lambda x: x[0]**3.0
etot = (V-V.mean())**2
fcenter = 450 + 100*(axes_flat - axes_flat.min())
# fake phonon dos data (Gaussian), shift to lower freq for higher volume
phdos = [np.array([freq,gauss(freq-fc, 100)]).T for fc in
fcenter[::-1]]
gibbs = Gibbs(T=T, P=P, etot=etot, phdos=phdos, axes_flat=axes_flat,
volfunc_ax=volfunc_ax, case=case, dosarea=None)
