feat: Add pyhf.workspace.build

src/pyhf/mixins.py

@@ -42,3 +42,10 @@ def __init__(self, *args, **kwargs):
         self.samples = sorted(list(set(self.samples)))
         self.parameters = sorted(list(set(self.parameters)))
         self.modifiers = sorted(list(set(self.modifiers)))
+
+        self.channel_slices = {}
+        begin = 0
+        for c in self.channels:
+            end = begin + self.channel_nbins[c]
+            self.channel_slices[c] = slice(begin, end)
+            begin = end

src/pyhf/workspace.py

@@ -743,3 +743,28 @@ def sorted(cls, workspace):
         newspec['observations'].sort(key=lambda e: e['name'])
 
         return cls(newspec)
+
+    @classmethod
+    def build(cls, model, data, name='measurement'):
+        """
+        Build a workspace from model and data.
+
+        Args:
+            model (~pyhf.pdf.Model): A model to store into a workspace
+            data (tensor): A array holding observations to store into a workspace
+            name (str): The name of the workspace measurement
+
+        Returns:
+            ~pyhf.workspace.Workspace: A new workspace object
+
+        """
+        workspace = copy.deepcopy(model.spec)
+        workspace['version'] = utils.SCHEMA_VERSION
+        workspace['measurements'] = [
+            {'name': name, 'config': {'poi': model.config.poi_name, 'parameters': []}}
+        ]
+        workspace['observations'] = [
+            {'name': k, 'data': data[model.config.channel_slices[k]]}
+            for k in model.config.channels
+        ]
+        return cls(workspace)

tests/test_workspace.py

@@ -721,3 +721,21 @@ def test_sorted(workspace_factory):
     for channel in new_ws['channels']:
         # check sort
         assert channel['samples'][-1]['name'] == 'zzzzlast'
+
+
+def test_closure_over_workspace_build():
+    model = pyhf.simplemodels.hepdata_like(
+        signal_data=[12.0, 11.0], bkg_data=[50.0, 52.0], bkg_uncerts=[3.0, 7.0]
+    )
+    data = [51, 48]
+    one = pyhf.infer.hypotest(1.0, data + model.config.auxdata, model)
+
+    workspace = pyhf.Workspace.build(model, data)
+
+    assert json.dumps(workspace)
+
+    newmodel = workspace.model()
+    newdata = workspace.data(newmodel)
+    two = pyhf.infer.hypotest(1.0, newdata, newmodel)
+
+    assert one == two