diff --git a/model_tools/__init__.py b/model_tools/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/model_tools/parameters_storage.py b/model_tools/parameters_storage.py
deleted file mode 100644
index 1c793c411a383bf72a1b3a3bd4ce1b9f6f689974..0000000000000000000000000000000000000000
--- a/model_tools/parameters_storage.py
+++ /dev/null
@@ -1,180 +0,0 @@
-from multikeydict.nestedmkdict import NestedMKDict
-from multikeydict.visitor import NestedMKDictVisitor
-from dagflow.output import Output
-
-from typing import Union, Tuple, List, Optional
-
-from tabulate import tabulate
-from pandas import DataFrame
-from LaTeXDatax import datax
-
-from numpy import nan
-import pandas as pd
-pd.set_option('display.max_rows', None)
-pd.set_option('display.max_colwidth', 100)
-
-from shutil import get_terminal_size
-
-def trunc(text: str, width: int) -> str:
- return '\n'.join(line[:width] for line in text.split('\n'))
-
-class ParametersStorage(NestedMKDict):
- def read_paths(self) -> None:
- for key, value in self.walkitems():
- labels = getattr(value, 'labels', None)
- if labels is None:
- continue
-
- key = '.'.join(key)
- labels.paths.append(key)
-
- def plot(
- self,
- *args,
- **kwargs
- ) -> None:
- from dagflow.plot import plot_auto
- for _, value in self.walkitems():
- if not isinstance(value, Output):
- continue
-
- plot_auto(value, *args, **kwargs)
-
- def to_list(self, **kwargs) -> list:
- return self.visit(ParametersVisitor(kwargs)).data_list
-
- def to_dict(self, **kwargs) -> NestedMKDict:
- return self.visit(ParametersVisitor(kwargs)).data_dict
-
- def to_df(self, *, columns: Optional[List[str]]=None, **kwargs) -> DataFrame:
- dct = self.to_list(**kwargs)
- if columns is None:
- columns = ['path', 'value', 'central', 'sigma', 'flags', 'label']
- df = DataFrame(dct, columns=columns)
-
- df.insert(4, 'sigma_rel_perc', df['sigma'])
- df['sigma_rel_perc'] = df['sigma']/df['central']*100.
- df['sigma_rel_perc'].mask(df['central']==0, nan, inplace=True)
-
- for key in ('central', 'sigma', 'sigma_rel_perc'):
- if df[key].isna().all():
- del df[key]
- else:
- df[key].fillna('-', inplace=True)
-
- df['value'].fillna('-', inplace=True)
- df['flags'].fillna('', inplace=True)
- df['label'].fillna('', inplace=True)
-
- if (df['flags']=='').all():
- del df['flags']
-
- return df
-
- def to_string(self, **kwargs) -> str:
- df = self.to_df()
- return df.to_string(**kwargs)
-
- def to_table(
- self,
- *,
- df_kwargs: dict={},
- truncate: Union[int, bool] = False,
- **kwargs
- ) -> str:
- df = self.to_df(**df_kwargs)
- kwargs.setdefault('headers', df.columns)
- ret = tabulate(df, **kwargs)
-
- if truncate:
- if isinstance(truncate, bool):
- truncate = get_terminal_size().columns
-
- return trunc(ret, width=truncate)
-
-
- return ret
-
- def to_latex(self, *, return_df: bool=False, **kwargs) -> Union[str, Tuple[str, DataFrame]]:
- df = self.to_df(label_from='latex', **kwargs)
- tex = df.to_latex(escape=False)
-
- if return_df:
- return tex, df
-
- return tex
-
- def to_datax(self, filename: str, **kwargs) -> None:
- data = self.to_dict(**kwargs)
- skip = {'path', 'label', 'flags'} # TODO, add LaTeX label
- odict = {'.'.join(k): v for k, v in data.walkitems() if not (k and k[-1] in skip)}
- datax(filename, **odict)
-
-class ParametersVisitor(NestedMKDictVisitor):
- __slots__ = ('_kwargs', '_data_list', '_localdata', '_path')
- _kwargs: dict
- _data_list: List[dict]
- _data_dict: NestedMKDict
- _localdata: List[dict]
- _paths: List[Tuple[str, ...]]
- _path: Tuple[str, ...]
- # _npars: List[int]
-
- def __init__(self, kwargs: dict):
- self._kwargs = kwargs
- # self._npars = []
-
- @property
- def data_list(self) -> List[dict]:
- return self._data_list
-
- @property
- def data_dict(self) -> NestedMKDict:
- return self._data_dict
-
- def start(self, dct):
- self._data_list = []
- self._data_dict = NestedMKDict({}, sep='.')
- self._path = ()
- self._paths = []
- self._localdata = []
-
- def enterdict(self, k, v):
- if self._localdata:
- self.exitdict(self._path, None)
- self._path = k
- self._paths.append(self._path)
- self._localdata = []
-
- def visit(self, key, value):
- try:
- dct = value.to_dict(**self._kwargs)
- except AttributeError:
- return
-
- subkey = key[len(self._path):]
- subkeystr = '.'.join(subkey)
-
- if self._path:
- dct['path'] = f'.. {subkeystr}'
- else:
- dct['path'] = subkeystr
-
- self._localdata.append(dct)
-
- self._data_dict[key]=dct
-
- def exitdict(self, k, v):
- if self._localdata:
- self._data_list.append({
- 'path': f"group: {'.'.join(self._path)} [{len(self._localdata)}]"
- })
- self._data_list.extend(self._localdata)
- self._localdata = []
- if self._paths:
- del self._paths[-1]
-
- self._path = self._paths[-1] if self._paths else ()
-
- def stop(self, dct):
- pass
diff --git a/models/dayabay_v0.py b/models/dayabay_v0.py
index e65912baba3450cfed8cba9ba7c0b4e52333a8be..b2e06e54d7f3b5c9d6d2a04c05f97d01698bbb50 100644
--- a/models/dayabay_v0.py
+++ b/models/dayabay_v0.py
@@ -6,10 +6,10 @@ from dagflow.graphviz import savegraph
from dagflow.lib.arithmetic import Sum
from dagflow.tools.schema import LoadYaml
from gindex import GNIndex
-from model_tools.parameters_storage import ParametersStorage
+from dagflow.storage import NodeStorage
def model_dayabay_v0():
- storage = ParametersStorage({}, sep='.')
+ storage = NodeStorage({}, sep='.')
datasource = Path('data/dayabay-v0')
index = GNIndex.from_dict({
@@ -27,25 +27,25 @@ def model_dayabay_v0():
list_dr = idx_rd.values
list_reactors_isotopes = idx_ri.values
- with Graph(close=True) as g:
+ with Graph(close=True) as graph, storage:
#
# Load parameters
#
- storage ^= load_parameters({'path': 'ibd' , 'load': datasource/'parameters/pdg2012.yaml'})
- storage ^= load_parameters({'path': 'ibd.csc' , 'load': datasource/'parameters/ibd_constants.yaml'})
- storage ^= load_parameters({'path': 'conversion' , 'load': datasource/'parameters/conversion_thermal_power.yaml'})
- storage ^= load_parameters({'path': 'conversion' , 'load': datasource/'parameters/conversion_oscprob_argument.yaml'})
+ load_parameters({'path': 'ibd' , 'load': datasource/'parameters/pdg2012.yaml'})
+ load_parameters({'path': 'ibd.csc' , 'load': datasource/'parameters/ibd_constants.yaml'})
+ load_parameters({'path': 'conversion' , 'load': datasource/'parameters/conversion_thermal_power.yaml'})
+ load_parameters({'path': 'conversion' , 'load': datasource/'parameters/conversion_oscprob_argument.yaml'})
- storage ^= load_parameters({ 'load': datasource/'parameters/baselines.yaml'})
+ load_parameters({ 'load': datasource/'parameters/baselines.yaml'})
- storage ^= load_parameters({'path': 'detector' , 'load': datasource/'parameters/detector_nprotons_correction.yaml'})
- storage ^= load_parameters({'path': 'detector' , 'load': datasource/'parameters/detector_eres.yaml'})
+ load_parameters({'path': 'detector' , 'load': datasource/'parameters/detector_nprotons_correction.yaml'})
+ load_parameters({'path': 'detector' , 'load': datasource/'parameters/detector_eres.yaml'})
- storage ^= load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_e_per_fission.yaml'})
- storage ^= load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_thermal_power_nominal.yaml' , 'replicate': list_reactors })
- storage ^= load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_snf.yaml' , 'replicate': list_reactors })
- storage ^= load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_offequilibrium_correction.yaml' , 'replicate': list_reactors_isotopes })
- storage ^= load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_fission_fraction_scale.yaml' , 'replicate': list_reactors , 'replica_key_offset': 1 })
+ load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_e_per_fission.yaml'})
+ load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_thermal_power_nominal.yaml' , 'replicate': list_reactors })
+ load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_snf.yaml' , 'replicate': list_reactors })
+ load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_offequilibrium_correction.yaml' , 'replicate': list_reactors_isotopes })
+ load_parameters({'path': 'reactor' , 'load': datasource/'parameters/reactor_fission_fraction_scale.yaml' , 'replicate': list_reactors , 'replica_key_offset': 1 })
# Create Nuisance parameters
nuisanceall = Sum('nuisance total')
@@ -103,7 +103,7 @@ def model_dayabay_v0():
storage.to_datax('output/dayabay_v0_data.tex')
from dagflow.graphviz import GraphDot
- GraphDot.from_graph(g, show='all').savegraph("output/dayabay_v0.dot")
+ GraphDot.from_graph(graph, show='all').savegraph("output/dayabay_v0.dot")
GraphDot.from_node(storage['parameter_node.constrained.reactor.fission_fraction_scale.DB1'].constraint._norm_node, show='all', minsize=2).savegraph("output/dayabay_v0_large.dot")
GraphDot.from_node(storage['stat.nuisance.all'], show='all', mindepth=-1, no_forward=True).savegraph("output/dayabay_v0_nuisance.dot")
GraphDot.from_output(storage['outputs.edges.energy_evis'], show='all', mindepth=-3, no_forward=True).savegraph("output/dayabay_v0_top.dot")
diff --git a/models/dayabay_v1.py b/models/dayabay_v1.py
index eeb37080c6da75150fb039e16c7ef08dca2dcef2..11398aa2b30fc565d92901b748615a13be84e9fc 100644
--- a/models/dayabay_v1.py
+++ b/models/dayabay_v1.py
@@ -7,10 +7,10 @@ from dagflow.lib.arithmetic import Sum
from gindex import GNIndex
-from model_tools.parameters_storage import ParametersStorage
+from dagflow.storage import NodeStorage
def model_dayabay_v1():
- storage = ParametersStorage({}, sep='.')
+ storage = NodeStorage({}, sep='.')
datasource = Path('data/dayabay-v1')
index = GNIndex.from_dict({