def gr2summary_str(gr, ndigits=2):
summary = [
gr['model_name'].value,
gr.file.filename,
prnDict(gr2datadict(gr), braces=False),
_array_to_table(gr['summary'][:], gr['summary_rownames'][:],
gr['summary_colnames'][:], ndigits)
]
return '\n\n'.join(summary)
def gr2summary_str(gr, ndigits=2):
summary = [
gr['model_name'].value,
gr.file.filename,
prnDict(gr2datadict(gr), braces=False),
_array_to_table(gr['summary'][:], gr['summary_rownames'][:],
gr['summary_colnames'][:], ndigits)
]
return '\n\n'.join(summary)
def __init__(self, name, grs_or_fnames):
self.name = name
self.filenames = []
self.grs = []
for gr_or_fname in grs_or_fnames:
if isinstance(gr_or_fname, string_types):
self.filenames.append(gr_or_fname)
gr = h5py.File(gr_or_fname, 'r')
else:
self.filenames.append(None)
gr = gr_or_fname
self.grs.append(gr)
self.data = {key: val.value for key, val in gr['data'].items()}
self.y = self.data['y']
self.y_control = self.data['y_control']
self.t = self.data['t']
self._y_fit = [get_y_fit(gr) for gr in self.grs]
self.y_fit = [percentile_func(_y_fit) for _y_fit in self._y_fit]
self._sigma = [get_sigma(gr) for gr in self.grs]
self.sigma = [percentile_func(_sigma) for _sigma in self._sigma]
self.residuals = [self.y - y_fit(50) for y_fit in self.y_fit]
self.reduced_residuals = [residual / sigma(50) for residual, sigma in
zip(self.residuals, self.sigma)]
self.sorted_residuals = [np.sort(residuals) for residuals in
self.reduced_residuals]
self.popt_reduced_residuals = [fit_residuals(residuals) for residuals
in self.sorted_residuals]
self.summary_strs = [gr2summary_str(gr) for gr in self.grs]
self.data_strs = [{key: val.value for key, val in gr['data'].items() if not isinstance(val.value, np.ndarray)} for gr in self.grs]
self.data2print = [prnDict(d, braces=False) for d in self.data_strs]
self._df = [get_df(gr) for gr in self.grs]
self.df = [percentile_func(_df) for _df in self._df]
def __init__(self, name, grs_or_fnames):
self.name = name
self.filenames = []
self.grs = []
for gr_or_fname in grs_or_fnames:
if isinstance(gr_or_fname, string_types):
self.filenames.append(gr_or_fname)
gr = h5py.File(gr_or_fname, 'r')
else:
self.filenames.append(None)
gr = gr_or_fname
self.grs.append(gr)
self.data = {key: val.value for key, val in gr['data'].items()}
self.y = self.data['y']
self.y_control = self.data['y_control']
self.t = self.data['t']
self._y_fit = [get_y_fit(gr) for gr in self.grs]
self.y_fit = [percentile_func(_y_fit) for _y_fit in self._y_fit]
self._sigma = [get_sigma(gr) for gr in self.grs]
self.sigma = [percentile_func(_sigma) for _sigma in self._sigma]
self.residuals = [self.y - y_fit(50) for y_fit in self.y_fit]
self.reduced_residuals = [residual / sigma(50) for residual, sigma in
zip(self.residuals, self.sigma)]
self.sorted_residuals = [np.sort(residuals) for residuals in
self.reduced_residuals]
self.popt_reduced_residuals = [fit_residuals(residuals) for residuals
in self.sorted_residuals]
self.summary_strs = [gr2summary_str(gr) for gr in self.grs]
self.data_strs = [{key: val.value for key, val in gr['data'].items() if not isinstance(val.value, np.ndarray)} for gr in self.grs]
self.data2print = [prnDict(d, braces=False) for d in self.data_strs]
self._df = [get_df(gr) for gr in self.grs]
self.df = [percentile_func(_df) for _df in self._df]
