diff options
Diffstat (limited to 'lib/dfatool.py')
| -rw-r--r-- | lib/dfatool.py | 11 |
1 files changed, 5 insertions, 6 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index a3d5c0f..363c2a2 100644 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -1505,7 +1505,7 @@ class PTAModel: - rel_energy_next: transition energy relative to next state mean power in pJ """ - def __init__(self, by_name, parameters, arg_count, traces = [], ignore_trace_indexes = [], discard_outliers = None, function_override = {}, verbose = True, use_corrcoef = False, hwmodel = None): + def __init__(self, by_name, parameters, arg_count, traces = [], ignore_trace_indexes = [], discard_outliers = None, function_override = {}, verbose = True, use_corrcoef = False, pta = None): """ Prepare a new PTA energy model. @@ -1534,7 +1534,7 @@ class PTAModel: verbose -- print informative output, e.g. when removing an outlier use_corrcoef -- use correlation coefficient instead of stddev comparison to detect whether a model attribute depends on a parameter - hwmodel -- hardware model suitable for PTA.from_hwmodel + pta -- hardware model as `PTA` object """ self.by_name = by_name self.by_param = by_name_to_by_param(by_name) @@ -1548,7 +1548,7 @@ class PTAModel: self._outlier_threshold = discard_outliers self.function_override = function_override.copy() self.verbose = verbose - self.hwmodel = hwmodel + self.pta = pta self.ignore_trace_indexes = ignore_trace_indexes self._aggregate_to_ndarray(self.by_name) @@ -1715,9 +1715,8 @@ class PTAModel: def to_json(self): static_model = self.get_static() _, param_info = self.get_fitted() - pta = PTA.from_json(self.hwmodel) - pta.update(static_model, param_info) - return pta.to_json() + self.pta.update(static_model, param_info) + return self.pta.to_json() def states(self): return sorted(list(filter(lambda k: self.by_name[k]['isa'] == 'state', self.by_name.keys()))) |