Improved setUp with dummy data for logsum builders

py/core.py

@@ -4370,7 +4370,7 @@ def delete_data_fountain(self) -> "void":
     def change_data_fountain(self, datafile: 'Fountain') -> "void":
         return _core.Model2_change_data_fountain(self, datafile)
 
-    def setUp(self, and_load_data: 'bool'=True, force: 'bool'=False, cache: 'bool'=False) -> "void":
+    def setUp(self, and_load_data: 'bool'=True, force: 'bool'=False, cache: 'bool'=False, check_validity: 'bool'=True) -> "void":
 
         if self.logger(): self.logger().log(30, "Model.setUp...")
         if self._ref_to_db is not None and self.is_provisioned()==0 and and_load_data:
@@ -4379,7 +4379,7 @@ def setUp(self, and_load_data: 'bool'=True, force: 'bool'=False, cache: 'bool'=F
         	if self.logger(): self.logger().info("autoprovisioned data from database")
 
 
-        val = _core.Model2_setUp(self, and_load_data, force, cache)
+        val = _core.Model2_setUp(self, and_load_data, force, cache, check_validity)
 
         if self.logger(): self.logger().log(30, "Model.setUp complete")
 

py/dt.py

@@ -251,8 +251,10 @@ def __repr__(self):
 
 	@property
 	def h5caseids(self):
-		return _pytables_link_dereference(self.h5top.caseids)
-
+		try:
+			return _pytables_link_dereference(self.h5top.caseids)
+		except _tb.exceptions.NoSuchNodeError:
+			return numpy.zeros(0, dtype=numpy.int64)
 
 	def create_group(self, *arg, **kwargs):
 		return self.h5f.create_group(*arg, **kwargs)
@@ -384,6 +386,7 @@ def set_alternatives(self, altids, alt_labels=None):
 			alt_labels = ["a{}".format(a) for a in altids]
 		for an in alt_labels:
 			h5altnames.append( str(an) )
+		self._refresh_dna(self.alternative_names(), self.alternative_codes())
 
 	def alternative_codes(self):
 		try:
@@ -410,13 +413,22 @@ def alternative_code(self, name):
 		return self.alts.altids[idx]
 
 	def caseids(self):
-		return _pytables_link_dereference(self.h5top.caseids)[:]
+		try:
+			return _pytables_link_dereference(self.h5top.caseids)[:]
+		except _tb.exceptions.NoSuchNodeError:
+			return numpy.zeros(0, dtype=numpy.int64)
 
 	def array_caseids(self, screen=None):
 		screen, n_cases = self.process_proposed_screen(screen)
 		if isinstance(screen, str) and screen=="None":
-			return _pytables_link_dereference(self.h5top.caseids)[:]
-		return _pytables_link_dereference(self.h5top.caseids)[screen]
+			try:
+				return _pytables_link_dereference(self.h5top.caseids)[:]
+			except _tb.exceptions.NoSuchNodeError:
+				return numpy.zeros(0, dtype=numpy.int64)
+		try:
+			return _pytables_link_dereference(self.h5top.caseids)[screen]
+		except _tb.exceptions.NoSuchNodeError:
+			return numpy.zeros(0, dtype=numpy.int64)
 
 	@property
 	def caseindexes(self):
@@ -825,10 +837,13 @@ def array_weight(self, *, var=None, **kwargs):
 			return self.array_idco('_weight_', **kwargs)
 
 	def array_choice(self, **kwargs):
-		if isinstance(self.idca._choice_, (_tb.Group,GroupNode)):
-			##!stacktuple = self.idca._choice_._v_attrs.stack
-			stacktuple = self.from_vault('stack._choice_')
-			return numpy.expand_dims(self.array_idco(*stacktuple, **kwargs), axis=-1)
+		try:
+			if isinstance(self.idca._choice_, (_tb.Group,GroupNode)):
+				##!stacktuple = self.idca._choice_._v_attrs.stack
+				stacktuple = self.from_vault('stack._choice_')
+				return numpy.expand_dims(self.array_idco(*stacktuple, **kwargs), axis=-1)
+		except _tb.NoSuchNodeError:
+			return numpy.zeros([self.nCases(), self.nAlts(), 1], dtype=numpy.float64)
 		return self.array_idca('_choice_', **kwargs)
 
 	def array_avail(self, *, var=None, dtype=numpy.bool_, **kwargs):

py/model.py

@@ -388,6 +388,7 @@ def load(self, filename="@@@", *, echo=False, d=None):
 			filename = self
 			if d:
 				self = Model(d)
+				self.setUp(False)
 			else:
 				self = Model()
 		inf = numpy.inf
@@ -405,7 +406,7 @@ def handle_starttag(subself, tag, attrs):
 						if use:
 							for attrname,attrval in attrs:
 								if attrname=='content':
-									self.loads(attrval, use_base64=True, echo=echo)
+									self.loads(attrval, use_base64=True, echo=echo, d=self.df)
 			parser = LarchHTMLParser_ModelLoader()
 			with open(filename) as f:
 				parser.feed(f.read())
@@ -423,6 +424,7 @@ def loads(self, content="@@@", *, use_base64=False, echo=False, d=None):
 			content = self
 			if d:
 				self = Model(d)
+				self.setUp(False)
 			else:
 				self = Model()
 		inf = numpy.inf
@@ -1870,6 +1872,47 @@ def provision_without_utility(self):
 		except ProvisioningError:
 			pass
 
+	def provision_zeros(self, ncases=None, nalts=None, initializer=None, avail_initializer=None):
+		'''
+		Initialize input data arrays with zeros instead of loading from a data file.
+		
+		Parameters
+		----------
+		ncases : int
+			Override the number of cases provisioned.  You probably want to use this.
+		nalts : int
+			Override the nubmer of alternatives provisioned.  
+			Probably you don't want to do this, but just in case.
+		initializer : float64
+			Optionally fill utilityca and utilityco with this value instead of zero.
+		avail_initializer : bool
+			Optionally fill avail with this value instead of False
+		'''
+		need = self.needs()
+		ncases = ncases or self.nCases()
+		if ncases==0:
+			import warnings
+			warnings.warn("ncases is zero in provision_zeros")
+		if nalts==0:
+			import warnings
+			warnings.warn("nalts is zero in provision_zeros")
+		nalts = nalts or self.nAlts()
+		zer = {}
+		_shape = lambda req: (ncases, nalts, req.nVars() or 1) if req.dimty==3 else (ncases, req.nVars() or 1)
+		numpy_dtype_nums = {
+			7: numpy.int64,
+			12: numpy.float64,
+			0: numpy.bool,
+		}
+		for key,val in need.items():
+			if initializer is not None and key in ('UtilityCA','UtilityCO'):
+				zer[key] = numpy.full(_shape(val), initializer, dtype=numpy_dtype_nums[val.dtype])
+			elif avail_initializer is not None and key in ('Avail',):
+				zer[key] = numpy.full(_shape(val), avail_initializer, dtype=numpy_dtype_nums[val.dtype])
+			else:
+				zer[key] = numpy.zeros(_shape(val), dtype=numpy_dtype_nums[val.dtype])
+		self.provision( zer )
+
 	def provision(self, *args, idca_avail_ratio_floor=None, cache=False, **kwargs):
 		from .db import DB
 		from .dt import DT

src/model/elm_model2.h

@@ -536,9 +536,9 @@ namespace elm {
 //		void _setUp_availability_data();
 //		void _setUp_choice_data();
 //		void _setUp_weight_data();
-		void _setUp_utility_data_and_params();
-		void _setUp_quantity_data_and_params();
-		void _setUp_samplefactor_data_and_params();
+		void _setUp_utility_data_and_params(bool check_validity=true);
+		void _setUp_quantity_data_and_params(bool check_validity=true);
+		void _setUp_samplefactor_data_and_params(bool check_validity=true);
 		void _setUp_allocation_data_and_params();
 
 		void _setUp_MNL();
@@ -825,7 +825,7 @@ FOSWIG(	%rename(__repr__) representation; )
 		void change_data_fountain(elm::Fountain& datafile);
 
 	public:
-		void setUp(bool and_load_data=true, bool force=false, bool cache=false);
+		void setUp(bool and_load_data=true, bool force=false, bool cache=false, bool check_validity=true);
 		void _pull_graph_from_db();
 
 		std::string setUpMessage;

src/model/elm_model2_setup.cpp

@@ -185,6 +185,7 @@ void _setUp_linear_data_and_params
  ,	etk::logging_service*	msg
  ,  std::set< std::string >* cache_valid_ca=nullptr
  ,  std::set< std::string >* cache_valid_co=nullptr
+ ,  const bool&				check_validity=true
 )
 {
 	size_t slot, slot2;
@@ -212,7 +213,9 @@ void _setUp_linear_data_and_params
 	if (Input_UtilityCO && Params_UtilityCO) {
 		// First, populate the data_port
 		etk::strvec u_co = __identify_needs((*Input_UtilityCO));
-		__check_validity_of_needs(u_co, _fount, IDCO, msg, cache_valid_ca, cache_valid_co);
+		if (check_validity) {
+			__check_validity_of_needs(u_co, _fount, IDCO, msg, cache_valid_ca, cache_valid_co);
+		}
 
 		// Second, resize the paramArray
 		auto s = _fount ? _fount->nAlts() : Xylem.n_elemental();
@@ -299,7 +302,7 @@ void _setUp_linear_data_and_params_edges
 
 
 
-void elm::Model2::_setUp_utility_data_and_params()
+void elm::Model2::_setUp_utility_data_and_params(bool check_validity)
 {
 	BUGGER(msg) << "--Params_Utility--\n";
 
@@ -316,14 +319,15 @@ void elm::Model2::_setUp_utility_data_and_params()
 	 ,	&msg
 	 ,  &cache_valid_ca
 	 ,  &cache_valid_co
+	 ,  check_validity
 	);
 
 	BUGGER(msg) << "Params_UtilityCA \n" << Params_UtilityCA.__str__();
 	BUGGER(msg) << "Params_UtilityCO \n" << Params_UtilityCO.__str__();
 
 }
 
-void elm::Model2::_setUp_quantity_data_and_params()
+void elm::Model2::_setUp_quantity_data_and_params(bool check_validity)
 {
 	BUGGER(msg) << "--Params_Quantity--\n";
 
@@ -340,6 +344,7 @@ void elm::Model2::_setUp_quantity_data_and_params()
 	 ,	&msg
 	 ,  &cache_valid_ca
 	 ,  &cache_valid_co
+	 ,  check_validity
 	);
 
 	BUGGER(msg) << "Params_QuantityCA \n" << Params_QuantityCA.__str__();
@@ -355,7 +360,7 @@ void elm::Model2::_setUp_quantity_data_and_params()
 
 }
 
-void elm::Model2::_setUp_samplefactor_data_and_params()
+void elm::Model2::_setUp_samplefactor_data_and_params(bool check_validity)
 {
 	BUGGER(msg) << "--Params_Sampling--\n";
 
@@ -372,6 +377,7 @@ void elm::Model2::_setUp_samplefactor_data_and_params()
 	 ,	&msg
 	 ,  &cache_valid_ca
 	 ,  &cache_valid_co
+	 ,  check_validity
 	);
 
 	BUGGER(msg) << "Params_SamplingCA \n" << Params_SamplingCA.__str__();
@@ -491,7 +497,7 @@ void elm::Model2::_pull_graph_from_db()
 }
 
 
-void elm::Model2::setUp(bool and_load_data, bool force, bool cache)
+void elm::Model2::setUp(bool and_load_data, bool force, bool cache, bool check_validity)
 {
 
 	if (!force) {
@@ -528,7 +534,7 @@ void elm::Model2::setUp(bool and_load_data, bool force, bool cache)
 	}
 
 	BUGGER(msg) << "Setting up utility parameters...";
-	_setUp_utility_data_and_params();
+	_setUp_utility_data_and_params(check_validity);
 	if (features & MODELFEATURES_NESTING) {
 		if (!option.suspend_xylem_rebuild) {
 			elm::cellcode root = Xylem.root_cellcode();
@@ -549,15 +555,15 @@ void elm::Model2::setUp(bool and_load_data, bool force, bool cache)
 
 
 	if (Input_Sampling.ca.size() || Input_Sampling.co.metasize()) {
-		_setUp_samplefactor_data_and_params();
+		_setUp_samplefactor_data_and_params(check_validity);
 	}
 
 	if (features & MODELFEATURES_ALLOCATION) {
 		_setUp_allocation_data_and_params();
 	}
 
 	if (features & MODELFEATURES_QUANTITATIVE) {
-		_setUp_quantity_data_and_params();
+		_setUp_quantity_data_and_params(check_validity);
 	}
 
 	_setUp_coef_and_grad_arrays();