kinda neat ephemeral pdes

interview_kernel/interview_kernel.py

@@ -267,12 +267,15 @@ Otherwise, you can always answer with \LaTeX-type input.
             thynames = get_recursively(self.state_machine.simdata, "theoryname")
             # if thynames:
             #    url_args_dict["highlight"] = ",".join(thynames)
+            # for now, highlight the "persistent ephemeral" theories, cf https://github.com/UniFormal/MMT/issues/326
+            url_args_dict["highlight"] = "actual*,ephemeral*,u,q,α,SHE"
         else:
             model_name = self.state_machine.generate_mpd_theories()
-            if model_name is None:  # Fallback for now, because ephemeral theories are not yet accessible to tgview
+            if model_name is None:
                 model_name = "Model"
             url_args_dict = dict(type="mpd",
-                                 graphdata=self.state_machine.mmtinterface.namespace + "?" + model_name)
+                                 graphdata=self.state_machine.mmtinterface.namespace + "?" + model_name,
+                                 highlight="MPD_pde*")
 
         # have the side bars go away
         url_args_dict["viewOnlyMode"] = "true"

interview_kernel/pde_state_machine.py

@@ -381,7 +381,8 @@ class PDE_States:
                 self.new_theory(parameter_name)
                 # we might need the other parameters created so far, so use them
                 for otherparamentry in string_handling.get_recursively(self.simdata["parameters"], "theoryname"):
-                    self.include_in(parameter_name, otherparamentry)
+                    if otherparamentry in userstring:
+                        self.include_in(parameter_name, otherparamentry)
 
                 # sanitize userstring - check if this works for all cases
                 parsestring = string_handling.add_ods(userstring)
@@ -451,12 +452,13 @@ class PDE_States:
                 subdict["rhsstring_expanded"] = self.try_expand(subdict["rhsstring"])  # TODO expand properly
 
                 # to make the left-hand side a function on x, place " [ variablename : domainname ] " in front
+                lambda_x = " [ x : " + self.simdata["domain"]["name"] + " ] "
                 if "x" in parts[0]:
-                    parts[0] = " [ x : " + self.simdata["domain"]["name"] + " ] " + parts[0]
+                    parts[0] = lambda_x + parts[0]
                 # right-hand side: infer type, make function if not one yet
                 if not string_handling.type_is_function_from(self.get_inferred_type(subdict["theoryname"], parts[1]),
                                              self.simdata["domain"]["name"]):
-                    parts[1] = " [ x : " + self.simdata["domain"]["name"] + " ] " + parts[1]
+                    parts[1] = lambda_x + parts[1]
 
                 # in lhs replace all unknown names used by more generic ones and add lambda clause in front
                 for unkname in string_handling.get_recursively(self.simdata["unknowns"], "theoryname"):
@@ -821,18 +823,19 @@ class PDE_States:
                 self.mmtinterface.mmt_new_theory(mpd_theory_name)
                 self.include_in(mpd_theory_name, pde_names[pde_number])
 
-                # include all the mpd_unknowns, parameters and bcs
-                for unknownentry in string_handling.get_recursively(self.simdata["unknowns"], "theoryname"):
-                    self.include_in(mpd_theory_name, "MPD_" + unknownentry)
+                # include all the mpd_unknowns, and parameters
 
                 for paramentry in string_handling.get_recursively(self.simdata["parameters"], "theoryname"):
                     if paramentry in pde['string']:
                         self.include_in(mpd_theory_name, paramentry)
 
-                self.add_list_of_declarations(mpd_theory_name, [
-                    str("proof_" + str(pde_number) + " : ⊦ " + pde["lhsstring"] + " ≐ " + pde["rhsstring"] +
-                    string_handling.object_delimiter + " role Law")
-                ])
+                for unknownentry in string_handling.get_recursively(self.simdata["unknowns"], "theoryname"):
+                    # TODO make more robust + rework for more unknowns
+                    self.include_in(mpd_theory_name, "MPD_" + unknownentry)
+                    self.add_list_of_declarations(mpd_theory_name, [
+                        str("proof_" + str(pde_number) + " : ⊦ " + pde["lhsstring"].replace(unknownentry, " " + unknownentry)
+                            + " ≐ " + pde["rhsparsestring"] + string_handling.object_delimiter + " role Law")
+                    ])
 
         with CriticalSubdict(self.simdata[self.state], self.poutput):
             mpd_theory_name = "MPD_bcs"

setup.py

-# cf. https://pypi.python.org/pypi/twine
+# cf. https://pypi.python.org/pypi/twine:
+# $ python setup.py sdist bdist_wheel
+# $ twine upload --repository-url https://test.pypi.org/legacy/ dist/*
+# or
+# $ twine upload --repository testpypi dist/*
 
 from setuptools import setup
 
@@ -13,14 +17,16 @@ setup(
     description='A Jupyter kernel that interviews you for a PDE model and \
                     transforms it into an ExaStencils simulation.',
     python_requires=">=3.4",
-    # replicating contents of MANIFEST, cf.
+    # replicating contents of MANIFEST,
+    # cf.https://stackoverflow.com/questions/7522250/how-to-include-package-data-with-setuptools-distribute/14159430#14159430
     package_data={
         'interview_kernel/exastencils': ['interview_kernel/exastencils/compiler.jar',
                                             'interview_kernel/exastencils/generate_compile_and_run_list.sh',
                                             'interview_kernel/exastencils/lib/*.*'],
     },
+    zip_safe=False,
     # use_scm_version=True,
-    setup_requires=['setuptools_scm'],
+    setup_requires=['setuptools_scm'],  # or possibly https://pypi.python.org/pypi/setuptools-git
     install_requires=['transitions', 'bokeh', 'requests', 'pylatexenc', 'metakernel', 'lxml', 'IPython',
                       'jupyter_client', 'ipywidgets']
 )