def intersection(self, other):
"""TODO: method docstring."""
name = temperature = h_larmor_frq = p_total = l_total = None
if self.name == other.name:
name = self.name
nuclei = (peaks.Peak(self.nuclei).intersection(peaks.Peak(
other.nuclei)).assignment)
if not nuclei:
nuclei = None
if self.temperature == other.temperature:
temperature = self.temperature
if self.h_larmor_frq == other.h_larmor_frq:
h_larmor_frq = self.h_larmor_frq
if self.p_total == other.p_total:
p_total = self.p_total
if self.l_total == other.l_total:
l_total = self.l_total
return ParamName(
name=name,
nuclei=nuclei,
temperature=temperature,
h_larmor_frq=h_larmor_frq,
p_total=p_total,
l_total=l_total,
)
def __init__(
self,
name=None,
nuclei=None,
temperature=None,
h_larmor_frq=None,
p_total=None,
l_total=None,
):
self.name = self.nuclei = self.temperature = self.h_larmor_frq = None
self.p_total = self.l_total = None
if name is not None:
self.name = name.lower()
if nuclei is not None:
self.nuclei = peaks.Peak(nuclei).assignment
if temperature is not None:
self.temperature = round(float(temperature), 1)
if h_larmor_frq is not None:
self.h_larmor_frq = round(float(h_larmor_frq), 1)
if p_total is not None:
self.p_total = float(p_total)
if l_total is not None:
self.l_total = float(l_total)
def _shift(self, step):
self.index += step
self.index %= len(self.data)
self._profile = self.data[self.index]
self.name = peaks.Peak(self._profile.profile_name)
self._profile_to_curve()
self._clear_axis()
self._plot()
def group_data(dataset):
"""Group the data resonance specifically."""
data_grouped = dict()
for profile in dataset:
resonance_id = profile.name
peak = peaks.Peak(resonance_id)
data_grouped[peak] = profile
return data_grouped
def __lt__(self, other):
tuple_self = (
str(self.name),
str(self.temperature),
str(self.h_larmor_frq),
str(self.p_total),
str(self.l_total),
peaks.Peak(self.nuclei),
)
tuple_other = (
str(other.name),
str(other.temperature),
str(other.h_larmor_frq),
str(other.p_total),
str(other.l_total),
peaks.Peak(other.nuclei),
)
return tuple_self < tuple_other
def write_par(params, path):
"""Write the fitting parameters and their uncertainties to a file."""
filename = path / "parameters.fit"
print(f" * {filename}")
par_dict = {}
for name, param in params.items():
par_name = ParamName.from_fname(name)
if par_name.nuclei is None: # global parameter
name_print = par_name
section = "GLOBAL"
else: # residue-specific parameter
name_print = peaks.Peak(par_name.nuclei)
section = par_name.to_section_name()
if not param.vary and param.expr is None:
val_print = f"{param.value:.5e} ; fixed"
elif param.stderr is None:
val_print = f"{param.value:.5e} ; error not calculated"
elif param.expr:
val_print = f"{param.value:.5e} +/- {param.stderr:.5e} ; constrained"
else:
val_print = f"{param.value:.5e} +/- {param.stderr:.5e}"
par_dict.setdefault(section, []).append((name_print, val_print))
cfg = configparser.ConfigParser()
cfg.optionxform = str
section_global = par_dict.pop("GLOBAL", None)
if section_global is not None:
cfg.add_section("GLOBAL")
for name, val in sorted(section_global):
cfg.set("GLOBAL", str(name), val)
for section, name_vals in sorted(par_dict.items()):
cfg.add_section(section)
for peak, val in sorted(name_vals):
cfg.set(section, peak.assignment.upper(), val)
with open(filename, "w") as f:
cfg.write(f)
def plot_param(args):
params = configparser.ConfigParser()
params.read(str(args.parameters))
parname = args.parname
curves = {}
print("Plotting...")
for section in params.sections():
short_name = parameters.ParamName().from_section(section).name
if parname.lower() in short_name:
print("".join([" [", section, "]"]))
points = []
for key, value in params.items(section):
res = int(peaks.Peak(key).numbers["i"])
split = value.split()
value = float(split[0])
try:
error = float(split[2])
except ValueError:
error = 0.0
points.append((res, value, error))
curves[section] = zip(*points)
_, axis = plt.subplots(figsize=(12, 5))
axis.yaxis.grid(True)
for section, (res, vals, errors) in curves.items():
axis.errorbar(res, vals, yerr=errors, label=section, fmt=".", barsabove=True)
plt.legend()
plt.show()
return 0
def to_re(self):
"""TODO: method docstring."""
re_components = [NAME_MARKERS["name"].format(EXPAND(self.name))]
if self.nuclei is not None:
group_name = peaks.Peak(self.nuclei)._resonances["i"]["group"]
if not group_name:
all_res = "\D?[0-9]+[abd-gi-mopr-z]*"
else:
all_res = ""
re_components.append(NAME_MARKERS["nuclei"].format("".join(
[all_res, EXPAND(self.nuclei)])))
else:
re_components.append(".*")
if self.temperature is not None:
re_components.append(NAME_MARKERS["temperature"].format(
EXPAND(str(self.temperature))))
elif re_components[-1] != ".*":
re_components.append(".*")
if self.h_larmor_frq is not None:
re_components.append(NAME_MARKERS["h_larmor_frq"].format(
EXPAND(str(self.h_larmor_frq))))
elif re_components[-1] != ".*":
re_components.append(".*")
if self.p_total is not None:
re_components.append(NAME_MARKERS["p_total"].format(
EXPAND(str(self.p_total))))
elif re_components[-1] != ".*":
re_components.append(".*")
if self.l_total is not None:
re_components.append(NAME_MARKERS["l_total"].format(
EXPAND(str(self.l_total))))
elif re_components[-1] != ".*":
re_components.append(".*")
re_to_match = re.compile("".join(re_components), re.IGNORECASE)
return re_to_match
def __init__(self, data, path):
self.data = data
self.out = path
self.names = sorted([
peaks.Peak(profile.profile_name).names["i"]
for profile in self.data
])
self.curve, self.curve_sp = None, None
self.cs_a, self.cs_b = {}, {}
self.lines = []
self.cid = None
self.fig, self.axis = plt.subplots(figsize=(12, 5))
self.fig.subplots_adjust(left=0.07, bottom=0.1, right=0.8, top=0.9)
self.index = -1
self.next(None)
def get_pairs_from_file(filename, name):
"""Read residue specific values for fitting parameters from a file.
The file should be formatted like a Sparky peak list.
Examples:
* To set G23N to 105.0 and G23H to 8.0:
G23N-H 105.0 8.0
* To set a parameter depending on multiple nuclei (e.g., G23N and G23H):
G23N-H -93.0
"""
pairs = []
with open(filename) as f:
for line in f:
if "Assignment" in line:
continue
line = remove_comments(line, "#;")
line = re.sub("\s*\[\s*", "[", line)
line = re.sub("\s*\]\s*", "]", line)
elements = line.split()
if len(elements) > 1:
peak = peaks.Peak(elements[0])
n_resonances = len(peak)
n_cols = len(elements[1:])
if n_cols == n_resonances:
for nuc_name, value in zip(peak.names.values(),
elements[1:]):
name.update_nuclei(nuc_name)
pairs.append((copy.deepcopy(name), value))
else:
name.update_nuclei(peak.assignment)
pairs.append((copy.deepcopy(name), elements[1]))
return pairs
def __init__(self, name=None, data=None, exp_details=None, model=None):
"""TODO: method docstring."""
if name is None:
name = ""
self.conditions = self.check_exp_details(exp_details, self.CONDITIONS)
self.exp_details = self.check_exp_details(exp_details,
self.EXP_DETAILS)
self.name = name
self.peak = peaks.Peak(self.name)
self.model = util.parse_model(model)
self.experiment_name = self.exp_details["name"]
self.data = data
self.mask = np.ones(len(self.data), dtype=np.bool)
# Set the Liouvillian
self.liouv = basis.Liouvillian(
system=self.SPIN_SYSTEM,
state_nb=self.model.state_nb,
atoms=self.peak.atoms,
h_larmor_frq=self.conditions["h_larmor_frq"],
equilibrium=self.EQUILIBRIUM,
)
self.ppms_i = self.liouv.ppms["i"]
# Set the parameters this profile depends on
self.map_names, self.params = default.create_params(
basis=self.liouv,
model=self.model,
nuclei=self.peak.names,
conditions=self.conditions,
constraints=self.CONSTRAINTS,
)
self.calculate_unscaled_profile = lru_cache(256)(
self._calculate_unscaled_profile)
def update_nuclei(self, nuclei=None):
"""TODO: method docstring."""
if nuclei is not None:
self.nuclei = peaks.Peak(nuclei).assignment
return self
