tests should pass

[pre-commit.ci] auto fixes from pre-commit.com hooks

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string-based constraints and more dedubpe in builders

pyflakes

[pre-commit.ci] auto fixes from pre-commit.com hooks

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src/pyhf/cli/spec.py

@@ -7,6 +7,7 @@
 from pyhf.workspace import Workspace
 from pyhf import modifiers
 from pyhf import utils
+from pyhf import parameters
 
 log = logging.getLogger(__name__)
 
@@ -81,10 +82,7 @@ def inspect(workspace, output_file, measurement):
     model = ws.model()
 
     result['parameters'] = sorted(
-        [
-            (k, parset_descr[type(v['paramset'])])
-            for k, v in model.config.par_map.items()
-        ]
+        (k, parset_descr[type(v['paramset'])]) for k, v in model.config.par_map.items()
     )
     result['systematics'] = [
         (

src/pyhf/modifiers/__init__.py

@@ -4,7 +4,37 @@
 from .shapefactor import shapefactor_builder, shapefactor_combined
 from .normsys import normsys_builder, normsys_combined
 from .shapesys import shapesys_builder, shapesys_combined
-from .staterror import staterr_builder, staterror_combined
+from .staterror import staterror_builder, staterror_combined
+
+__all__ = [
+    'histosys',
+    'histosys_builder',
+    'histosys_combined',
+    'lumi',
+    'lumi_builder',
+    'lumi_combined',
+    'normfactor',
+    'normfactor_builder',
+    'normfactor_combined',
+    'normsys',
+    'normsys_builder',
+    'normsys_combined',
+    'pyhfset',
+    'shapefactor',
+    'shapefactor_builder',
+    'shapefactor_combined',
+    'shapesys',
+    'shapesys_builder',
+    'shapesys_combined',
+    'staterror',
+    'staterror_builder',
+    'staterror_combined',
+]
+
+
+def __dir__():
+    return __all__
+
 
 pyhfset = {
     'histosys': (histosys_builder, histosys_combined),
@@ -13,5 +43,5 @@
     'normsys': (normsys_builder, normsys_combined),
     'shapefactor': (shapefactor_builder, shapefactor_combined),
     'shapesys': (shapesys_builder, shapesys_combined),
-    'staterror': (staterr_builder, staterror_combined),
+    'staterror': (staterror_builder, staterror_combined),
 }

src/pyhf/modifiers/histosys.py

@@ -2,16 +2,17 @@
 
 from pyhf import get_backend, events
 from pyhf import interpolators
-from pyhf.parameters import constrained_by_normal, ParamViewer
+from pyhf.parameters import ParamViewer
 
 log = logging.getLogger(__name__)
 
 
 def required_parset(sample_data, modifier_data):
     return {
-        'paramset_type': constrained_by_normal,
+        'paramset_type': 'constrained_by_normal',
         'n_parameters': 1,
         'is_shared': True,
+        'is_scalar': True,
         'inits': (0.0,),
         'bounds': ((-5.0, 5.0),),
         'fixed': False,
@@ -48,20 +49,22 @@ def append(self, key, channel, sample, thismod, defined_samp):
         self._mega_mods[key][sample]['data']['mask'] += moddata['mask']
 
         if thismod:
-            self.required_parsets.setdefault(thismod['name'], []).append(
-                required_parset(defined_samp['data'], thismod['data'])
+            self.required_parsets.setdefault(
+                thismod['name'],
+                [required_parset(defined_samp['data'], thismod['data'])],
             )
 
     def finalize(self):
         return self._mega_mods
 
 
 class histosys_combined:
+    name = 'histosys'
+    op_code = 'addition'
+
     def __init__(
         self, modifiers, pdfconfig, builder_data, interpcode='code0', batch_size=None
     ):
-        self.name = 'histosys'
-        self.op_code = 'addition'
         self.batch_size = batch_size
         self.interpcode = interpcode
         assert self.interpcode in ['code0', 'code2', 'code4p']

src/pyhf/modifiers/lumi.py

@@ -1,16 +1,17 @@
 import logging
 
 from pyhf import get_backend, events
-from pyhf.parameters import constrained_by_normal, ParamViewer
+from pyhf.parameters import ParamViewer
 
 log = logging.getLogger(__name__)
 
 
 def required_parset(sample_data, modifier_data):
     return {
-        'paramset_type': constrained_by_normal,
+        'paramset_type': 'constrained_by_normal',
         'n_parameters': 1,
         'is_shared': True,
+        'is_scalar': True,
         'inits': None,  # lumi
         'bounds': None,  # (0, 10*lumi)
         'fixed': False,
@@ -42,19 +43,21 @@ def append(self, key, channel, sample, thismod, defined_samp):
         moddata = self.collect(thismod, nom)
         self._mega_mods[key][sample]['data']['mask'] += moddata['mask']
         if thismod:
-            self.required_parsets.setdefault(thismod['name'], []).append(
-                required_parset(defined_samp['data'], thismod['data'])
+            self.required_parsets.setdefault(
+                thismod['name'],
+                [required_parset(defined_samp['data'], thismod['data'])],
             )
 
     def finalize(self):
         return self._mega_mods
 
 
 class lumi_combined:
+    name = 'lumi'
+    op_code = 'multiplication'
+
     def __init__(self, modifiers, pdfconfig, builder_data, batch_size=None):
         self.batch_size = batch_size
-        self.name = 'lumi'
-        self.op_code = 'multiplication'
 
         keys = [f'{mtype}/{m}' for m, mtype in modifiers]
         lumi_mods = [m for m, _ in modifiers]

src/pyhf/modifiers/normfactor.py

@@ -1,16 +1,17 @@
 import logging
 
 from pyhf import get_backend, events
-from pyhf.parameters import unconstrained, ParamViewer
+from pyhf.parameters import ParamViewer
 
 log = logging.getLogger(__name__)
 
 
 def required_parset(sample_data, modifier_data):
     return {
-        'paramset_type': unconstrained,
+        'paramset_type': 'unconstrained',
         'n_parameters': 1,
         'is_shared': True,
+        'is_scalar': True,
         'inits': (1.0,),
         'bounds': ((0, 10),),
         'fixed': False,
@@ -40,19 +41,21 @@ def append(self, key, channel, sample, thismod, defined_samp):
         moddata = self.collect(thismod, nom)
         self._mega_mods[key][sample]['data']['mask'] += moddata['mask']
         if thismod:
-            self.required_parsets.setdefault(thismod['name'], []).append(
-                required_parset(defined_samp['data'], thismod['data'])
+            self.required_parsets.setdefault(
+                thismod['name'],
+                [required_parset(defined_samp['data'], thismod['data'])],
             )
 
     def finalize(self):
         return self._mega_mods
 
 
 class normfactor_combined:
+    name = 'normfactor'
+    op_code = 'multiplication'
+
     def __init__(self, modifiers, pdfconfig, builder_data, batch_size=None):
         self.batch_size = batch_size
-        self.name = 'normfactor'
-        self.op_code = 'multiplication'
 
         keys = [f'{mtype}/{m}' for m, mtype in modifiers]
         normfactor_mods = [m for m, _ in modifiers]

src/pyhf/modifiers/normsys.py

@@ -2,16 +2,17 @@
 
 from pyhf import get_backend, events
 from pyhf import interpolators
-from pyhf.parameters import constrained_by_normal, ParamViewer
+from pyhf.parameters import ParamViewer
 
 log = logging.getLogger(__name__)
 
 
 def required_parset(sample_data, modifier_data):
     return {
-        'paramset_type': constrained_by_normal,
+        'paramset_type': 'constrained_by_normal',
         'n_parameters': 1,
         'is_shared': True,
+        'is_scalar': True,
         'inits': (0.0,),
         'bounds': ((-5.0, 5.0),),
         'fixed': False,
@@ -52,20 +53,22 @@ def append(self, key, channel, sample, thismod, defined_samp):
         self._mega_mods[key][sample]['data']['mask'] += moddata['mask']
 
         if thismod:
-            self.required_parsets.setdefault(thismod['name'], []).append(
-                required_parset(defined_samp['data'], thismod['data'])
+            self.required_parsets.setdefault(
+                thismod['name'],
+                [required_parset(defined_samp['data'], thismod['data'])],
             )
 
     def finalize(self):
         return self._mega_mods
 
 
 class normsys_combined:
+    name = 'normsys'
+    op_code = 'multiplication'
+
     def __init__(
         self, modifiers, pdfconfig, builder_data, interpcode='code1', batch_size=None
     ):
-        self.name = 'normsys'
-        self.op_code = 'multiplication'
 
         self.interpcode = interpcode
         assert self.interpcode in ['code1', 'code4']

src/pyhf/modifiers/shapefactor.py

@@ -1,16 +1,17 @@
 import logging
 
 from pyhf import get_backend, default_backend, events
-from pyhf.parameters import unconstrained, ParamViewer
+from pyhf.parameters import ParamViewer
 
 log = logging.getLogger(__name__)
 
 
 def required_parset(sample_data, modifier_data):
     return {
-        'paramset_type': unconstrained,
+        'paramset_type': 'unconstrained',
         'n_parameters': len(sample_data),
         'is_shared': True,
+        'is_scalar': False,
         'inits': (1.0,) * len(sample_data),
         'bounds': ((0.0, 10.0),) * len(sample_data),
         'fixed': False,
@@ -40,15 +41,19 @@ def append(self, key, channel, sample, thismod, defined_samp):
         moddata = self.collect(thismod, nom)
         self._mega_mods[key][sample]['data']['mask'] += moddata['mask']
         if thismod:
-            self.required_parsets.setdefault(thismod['name'], []).append(
-                required_parset(defined_samp['data'], thismod['data'])
+            self.required_parsets.setdefault(
+                thismod['name'],
+                [required_parset(defined_samp['data'], thismod['data'])],
             )
 
     def finalize(self):
         return self._mega_mods
 
 
 class shapefactor_combined:
+    name = 'shapefactor'
+    op_code = 'multiplication'
+
     def __init__(self, modifiers, pdfconfig, builder_data, batch_size=None):
         """
         Imagine a situation where we have 2 channels (SR, CR), 3 samples (sig1,
@@ -87,8 +92,6 @@ def __init__(self, modifiers, pdfconfig, builder_data, batch_size=None):
 
         and at that point can be used to compute the effect of shapefactor.
         """
-        self.name = 'shapefactor'
-        self.op_code = 'multiplication'
 
         self.batch_size = batch_size
         keys = [f'{mtype}/{m}' for m, mtype in modifiers]

src/pyhf/modifiers/shapesys.py

@@ -1,7 +1,7 @@
 import logging
 
 from pyhf import get_backend, default_backend, events
-from pyhf.parameters import constrained_by_poisson, ParamViewer
+from pyhf.parameters import ParamViewer
 
 log = logging.getLogger(__name__)
 
@@ -14,9 +14,10 @@ def required_parset(sample_data, modifier_data):
     ]
     n_parameters = sum(valid_bins)
     return {
-        'paramset_type': constrained_by_poisson,
+        'paramset_type': 'constrained_by_poisson',
         'n_parameters': n_parameters,
         'is_shared': False,
+        'is_scalar': False,
         'inits': (1.0,) * n_parameters,
         'bounds': ((1e-10, 10.0),) * n_parameters,
         'fixed': False,
@@ -53,18 +54,20 @@ def append(self, key, channel, sample, thismod, defined_samp):
         self._mega_mods[key][sample]['data']['nom_data'] += moddata['nom_data']
 
         if thismod:
-            self.required_parsets.setdefault(thismod['name'], []).append(
-                required_parset(defined_samp['data'], thismod['data'])
+            self.required_parsets.setdefault(
+                thismod['name'],
+                [required_parset(defined_samp['data'], thismod['data'])],
             )
 
     def finalize(self):
         return self._mega_mods
 
 
 class shapesys_combined:
+    name = 'shapesys'
+    op_code = 'multiplication'
+
     def __init__(self, modifiers, pdfconfig, builder_data, batch_size=None):
-        self.name = 'shapesys'
-        self.op_code = 'multiplication'
         self.batch_size = batch_size
 
         keys = [f'{mtype}/{m}' for m, mtype in modifiers]