def string(self):
'Convert the statistics of the array into a human readable string'
if self.num == 0:
return ''
else:
s = u'%9.3f \u00B1 %9.3f ' % (
self.mean/parse_unit(self.unit),
self.std/parse_unit(self.unit)) + \
self.unit + ' '*(15-len(self.unit)
)
return s.encode('utf-8')
def read_config_file(self, fn):
with open(fn, 'r') as f:
for iline, line in enumerate(f.readlines()):
line = line.split('#')[0].lstrip().rstrip().rstrip('\n')
if len(line)==0:
continue
elif not ':' in line:
raise IOError('Line %i in %s does not contain a colon' %(iline, fn))
else:
words = line.split(':')
key = words[0].lstrip().rstrip()
value = ':'.join(words[1:]).lstrip().rstrip()
if value.lower()=='none':
value = None
elif value.lower()=='true':
value = True
elif value.lower()=='false':
value = False
else:
dtypes = [int, float]
found_dtype = False
for dtype in dtypes:
try:
value = dtype(value)
found_dtype = True
break
except ValueError:
try:
value = parse_unit(value)
found_dtype = True
break
except ValueError:
pass
self.set(key, value)
def process_units(self, pardef):
'''Load parameter conversion information
**Arguments:**
pardef
An instance of the ParameterDefinition class.
Returns a dictionary with (name, converion) pairs.
'''
result = {}
expected_names = [name for name, dtype in self.par_info if dtype is float]
for counter, line in pardef:
words = line.split()
if len(words) != 2:
pardef.complain(counter, 'must have two arguments in UNIT suffix.')
name = words[0].upper()
if name not in expected_names:
pardef.complain(counter, 'specifies a unit for an unknown parameter. (Must be one of %s, but got %s.)' % (expected_names, name))
try:
result[name] = parse_unit(words[1])
except (NameError, ValueError):
pardef.complain(counter, 'has a UNIT suffix with an unknown unit.')
if len(result) != len(expected_names):
raise IOError('Not all units are specified for generator %s in file %s. Got %s, should have %s.' % (
self.prefix, pardef.complain.filename, result.keys(), expected_names
))
return result
def read_config_file(self, fn):
with open(fn, 'r') as f:
for iline, line in enumerate(f.readlines()):
line = line.split('#')[0].lstrip().rstrip().rstrip('\n')
if len(line)==0:
continue
elif not ':' in line:
raise IOError('Line %i in %s does not contain a colon' %(iline, fn))
else:
key, value = line.split(':')
key = key.lstrip().rstrip()
value = value.lstrip().rstrip()
value = value.lstrip().rstrip()
if value.lower()=='none':
value = None
elif value.lower()=='true':
value = True
elif value.lower()=='false':
value = False
else:
dtypes = [int, float]
found_dtype = False
for dtype in dtypes:
try:
value = dtype(value)
found_dtype = True
break
except ValueError:
try:
value = parse_unit(value)
found_dtype = True
break
except ValueError:
pass
self.set(key, value)
def iter_unit_cells(unit_cell_str, sub=None):
sub = fix_slice(sub)
if len(unit_cell_str) == 0:
uc = UnitCell(
numpy.array([[1,0,0],[0,1,0],[0,0,1]], float),
numpy.array([False,False,False]),
)
while True:
yield uc
if "," in unit_cell_str:
parameters = list(parse_unit(word) for word in unit_cell_str.split(",") if len(word) > 0)
if len(parameters) == 1:
a= parameters[0]
uc = UnitCell(
numpy.array([[a,0,0],[0,a,0],[0,0,a]], float),
numpy.array([True, True, True]),
)
elif len(parameters) == 3:
a,b,c = parameters
uc = UnitCell(
numpy.array([[a,0,0],[0,b,0],[0,0,c]], float),
numpy.array([True, True, True]),
)
elif len(parameters) == 6:
a,b,c,alpha,beta,gamma = parameters
uc = UnitCell.from_parameters3(
numpy.array([a,b,c]),
numpy.array([alpha,beta,gamma])
)
elif len(parameters) == 9:
uc = UnitCell(
numpy.array(parameters, float).reshape((3,3)),
numpy.array([True, True, True]),
)
else:
raise ValueError("If the --cell option contains comma's, one, three, six or nine value(s) are expected.")
while True:
yield uc
else:
filenames = ["%s.%s" % (unit_cell_str, suffix) for suffix in ["a.x", "a.y", "a.z", "b.x", "b.y", "b.z", "c.x", "c.y", "c.z"]]
dtype = numpy.dtype([("cell", float, (3,3))])
mtr = MultiTracksReader(filenames, dtype, sub=sub)
for row in mtr:
yield UnitCell(
numpy.array(row["cell"], float),
numpy.array([True, True, True]),
)
def plot(self, ic, trajectory, filename, eunit='kjmol'):
'''
Method to plot the energy contributions along a perturbation
trajectory associated to a given ic.
**Arguments**
ic
an instance of the class :class:`quickff.ic.IC` defining for
which ic the plot will be made.
trajectory
a (F,N,3) numpy array defining the perturbation trajectory
associated to the given ic. It contains F frames of
(N,3)-dimensional geometry arrays.
filename
a string defining the name of the figure
**Optional Arguments**
eunit
a string describing the conversion of the unit of energy. More
info regarding possible strings can be found in the
`MolMod documentation <http://molmod.github.io/molmod/reference/const.html#module-molmod.units>`_.
'''
import matplotlib.pyplot as pp
evaluators = [eval_ic(ic), eval_energy('ai'), eval_energy('ei'), eval_energy('vdw')]
qs, tot, ei, vdw = self.analyze(trajectory, evaluators)
label = {}
for (name, obs) in zip(['ai', 'ei', 'vdw', 'cov'], [tot, ei, vdw, tot-ei-vdw]):
pars = fitpar(qs, obs, rcond=1e-6)
k = 2*pars[0]
if k != 0.0:
q0 = -0.5*pars[1]/pars[0]
label[name] = '(K=%.0f q0=%.3f)' %(
k/parse_unit(ic.kunit),
q0/parse_unit(ic.qunit)
)
else:
label[name] = '(K=0.0 q0=None)'
if name=='cov':
cov = (pars[0]*qs**2+pars[1]*qs+pars[2])
fig, ax = pp.subplots()
ax.plot(
qs/parse_unit(ic.qunit), tot/parse_unit(eunit),
'k--', linewidth=4, label='AI total %s' %label['ai']
)
ax.plot(
qs/parse_unit(ic.qunit), ei/parse_unit(eunit),
'b--', linewidth=2, label='FF elec %s' %label['ei']
)
ax.plot(
qs/parse_unit(ic.qunit), vdw/parse_unit(eunit),
'g--', linewidth=2, label='FF vdW %s' %label['vdw']
)
ax.plot(
qs/parse_unit(ic.qunit), cov/parse_unit(eunit),
'r-', linewidth=2, label='FF cov %s' %label['cov']
)
ax.set_title(ic.name)
ax.set_xlabel('%s [%s]' % (ic.name.split('/')[0], ic.qunit), fontsize=16)
ax.set_ylabel('Energy [%s]' %eunit, fontsize=16)
ax.grid()
ax.legend(loc='best', fontsize=16)
fig.set_size_inches([8, 8])
fig.savefig(filename)
