前端进度条性能优化、仿真结束后后处理优化；后端C代码生成流程优化：先识别来源，再按照已知未知量需求排序，最后局部求解

app/simulation/native_codegen/schedule.py

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+"""Dependency ordering and local algebraic blocks for generated C expressions.
+
+This module only arranges reviewed C computations. It never evaluates a model
+numerically and has no dependency on the retired Python numerical backend.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass
+import heapq
+import re
+
+from .compiler import NativeCapabilityError
+
+
+# Only compiler-owned array expressions are inspected, never arbitrary user C.
+_REFERENCE = re.compile(r"\b(?:[phqw]|fb)\[\d+\]|\bg\[\d+\]\.[A-Za-z_]\w*")
+
+
+def references(expression: str) -> frozenset[str]:
+    return frozenset(_REFERENCE.findall(expression))
+
+
+@dataclass(frozen=True)
+class Computation:
+    key: str
+    outputs: tuple[str, ...]
+    inputs: frozenset[str]
+    code: tuple[str, ...]
+    kind: str = "flow"
+    residual: str | None = None
+
+    @classmethod
+    def assignment(cls, key, target, expression, kind="flow"):
+        return cls(key, (target,), references(expression), (f'{target}={expression};',), kind)
+
+
+@dataclass(frozen=True)
+class Block:
+    members: tuple[int, ...]
+    cyclic: bool
+
+
+class EvaluationSchedule:
+    def __init__(self, computations, known, labels=None):
+        self.computations = tuple(computations)
+        self.labels = labels or {}
+        self.producers = {}
+        for i, op in enumerate(self.computations):
+            for output in op.outputs:
+                if output in self.producers:
+                    raise NativeCapabilityError(f'Multiple native producers for {self.label(output)}')
+                self.producers[output] = i
+        # An iterative initial guess is not a known source if an equation owns it.
+        used = set().union(*(op.inputs for op in self.computations)) if self.computations else set()
+        self.known = {key: value for key, value in known.items() if key not in self.producers and key in used}
+        self.dependencies = []
+        for op in self.computations:
+            missing = op.inputs - self.producers.keys() - self.known.keys()
+            if missing:
+                raise NativeCapabilityError(f'{op.key}: missing native input sources: {sorted(map(self.label, missing))}')
+            self.dependencies.append({self.producers[key] for key in op.inputs if key in self.producers})
+        self.blocks = self._blocks()
+
+    def label(self, key):
+        return self.labels.get(key, key)
+
+    def _blocks(self):
+        """Iterative SCC discovery followed by deterministic topological order."""
+        count = len(self.computations)
+        consumers = [set() for _ in range(count)]
+        for target, sources in enumerate(self.dependencies):
+            for source in sources:
+                consumers[source].add(target)
+        visited, finish = set(), []
+        for start in range(count):
+            if start in visited:
+                continue
+            visited.add(start)
+            stack = [(start, iter(sorted(consumers[start])))]
+            while stack:
+                node, edges = stack[-1]
+                child = next(edges, None)
+                if child is None:
+                    finish.append(node)
+                    stack.pop()
+                elif child not in visited:
+                    visited.add(child)
+                    stack.append((child, iter(sorted(consumers[child]))))
+        groups, owner = [], {}
+        for start in reversed(finish):
+            if start in owner:
+                continue
+            index = len(groups)
+            owner[start] = index
+            members, stack = [], [start]
+            while stack:
+                node = stack.pop()
+                members.append(node)
+                for child in sorted(self.dependencies[node]):
+                    if child not in owner:
+                        owner[child] = index
+                        stack.append(child)
+            groups.append(tuple(sorted(members)))
+        incoming = [set() for _ in groups]
+        outgoing = [set() for _ in groups]
+        for target, sources in enumerate(self.dependencies):
+            for source in sources:
+                a, b = owner[source], owner[target]
+                if a != b:
+                    incoming[b].add(a)
+                    outgoing[a].add(b)
+        ready = [(min(groups[i]), i) for i, inputs in enumerate(incoming) if not inputs]
+        heapq.heapify(ready)
+        blocks = []
+        while ready:
+            _, index = heapq.heappop(ready)
+            members = groups[index]
+            cyclic = len(members) > 1 or members[0] in self.dependencies[members[0]]
+            blocks.append(Block(members, cyclic))
+            for child in sorted(outgoing[index]):
+                incoming[child].remove(index)
+                if not incoming[child]:
+                    heapq.heappush(ready, (min(groups[child]), child))
+        return tuple(blocks)
+
+    def ordered_subset(self, members):
+        """Order a trial's computations while pressure/stream guesses are fixed."""
+        pending = set(members)
+        result = []
+        while pending:
+            ready = sorted(i for i in pending if not self.dependencies[i] & pending)
+            if not ready:
+                raise NativeCapabilityError('Unsupported cycle within native flow expressions')
+            result.extend(ready)
+            pending.difference_update(ready)
+        return result
+
+    def ancestors(self, inputs, allowed):
+        pending = [self.producers[key] for key in inputs if key in self.producers]
+        found = set()
+        while pending:
+            index = pending.pop()
+            if index in found or index not in allowed:
+                continue
+            found.add(index)
+            pending.extend(self.dependencies[index])
+        return self.ordered_subset(found)
+
+    def report(self):
+        result = []
+        sources = {key: {str(origin)} for key, origin in self.known.items()}
+        for block in self.blocks:
+            outputs = {key for i in block.members for key in self.computations[i].outputs}
+            inputs = {key for i in block.members for key in self.computations[i].inputs} - outputs
+            origins = set().union(*(sources[key] for key in inputs)) if inputs else set()
+            for key in outputs:
+                sources[key] = origins
+            result.append({
+                'cyclic': block.cyclic,
+                'inputs': sorted(map(self.label, inputs)),
+                'outputs': sorted(map(self.label, outputs)),
+                'origins': sorted(origins),
+                'operations': [self.computations[i].key for i in block.members],
+                'pressureUnknowns': [self.label(key) for i in block.members
+                                     if self.computations[i].kind == 'pressure'
+                                     for key in self.computations[i].outputs],
+            })
+        return {
+            'strategy': 'dependency-blocks',
+            'operationCount': len(self.computations),
+            'cyclicBlockCount': sum(b.cyclic for b in self.blocks),
+            'knownSources': {self.label(key): value for key, value in self.known.items()},
+            'blocks': result,
+            'operations': [{'key': op.key, 'kind': op.kind,
+                            'inputs': sorted(map(self.label, op.inputs)),
+                            'outputs': list(map(self.label, op.outputs))}
+                           for op in self.computations],
+        }
+
+    def emit(self):
+        """Return C helper definitions and a straight-line/local-block schedule.
+
+        Existing scalar pressure bisection and stream convergence tolerances are
+        retained. Only the computations in the relevant SCC participate in each
+        closure; a pressure trial further restricts work to its residual inputs.
+        """
+        helpers, lines = [], []
+        args = 'p,h,g,w,q,fb,pipe_cache'
+        signature = ('double *p,double *h,const NativeGas *g,double *w,double *q,'
+                     'double *fb,NativePipeCache *pipe_cache')
+
+        def code(indices):
+            return [line for i in indices for line in
+                    (f'/* schedule operation {i}: {self.computations[i].kind} */', *self.computations[i].code)]
+
+        def helper(name, indices):
+            helpers.extend([f'static int {name}({signature}) {{',
+                            '(void)p;(void)h;(void)g;(void)w;(void)q;(void)fb;(void)pipe_cache;',
+                            *code(indices), 'return 1;', '}'])
+            return f'if(!{name}({args})) return 0;'
+
+        for number, block in enumerate(self.blocks):
+            if not block.cyclic:
+                if self.computations[block.members[0]].kind == 'pressure':
+                    raise NativeCapabilityError('Pressure balance has no pressure-dependent flow relation')
+                lines.extend(code(block.members))
+                continue
+            pressures = [i for i in block.members if self.computations[i].kind == 'pressure']
+            streams = [i for i in block.members if self.computations[i].kind in ('stream', 'alias')]
+            flows = set(block.members) - set(pressures) - set(streams)
+            if all(self.computations[i].kind == 'alias' for i in block.members):
+                raise NativeCapabilityError('Enthalpy reference cycle has no thermodynamic source: ' +
+                                            ', '.join(self.computations[i].key for i in block.members))
+            refresh = helper(f'model_block_{number}_flows', self.ordered_subset(flows)) if flows else ''
+            lines.append(f'{{ /* local algebraic block {number} */')
+            hvars = [key for i in streams for key in self.computations[i].outputs]
+            outputs = {key for i in block.members for key in self.computations[i].outputs}
+            inputs = sorted({key for i in block.members for key in self.computations[i].inputs} - outputs)
+            if hvars:
+                seeds = [key for key in inputs if key.startswith('h[') or key.endswith('.h')]
+                if not seeds:
+                    raise NativeCapabilityError('Local stream loop has no supplied thermodynamic state')
+                lines.extend([*[f'{key}={seeds[0]};' for key in hvars], 'int closure_ok=0;',
+                              f'for(int closure=0;closure<{max(64,4*len(hvars))};closure++) {{',
+                              'double previous[]={' + ','.join(hvars) + '};'])
+            if pressures:
+                pressure_bounds = [key for key in inputs if key.startswith('p[') or key.endswith('.p')]
+                if not pressure_bounds:
+                    raise NativeCapabilityError('Local pressure block has no pressure boundary')
+                lines.extend(['double plo=INFINITY,phi=0;',
+                              *[f'plo=fmin(plo,{p});phi=fmax(phi,{p});' for p in pressure_bounds],
+                              *[f'{self.computations[i].outputs[0]}=.5*(plo+phi);' for i in pressures],
+                              'int pressure_ok=0;', 'for(int sweep=0;sweep<256;sweep++) {'])
+                for i in pressures:
+                    op = self.computations[i]
+                    p = op.outputs[0]
+                    trial = helper(f'model_block_{number}_pressure_{i}', self.ancestors(op.inputs, flows))
+                    lines.extend(['{ double lo=plo,hi=phi;', 'for(int bisect=0;bisect<48;bisect++) {',
+                                  f'{p}=.5*(lo+hi);', trial,
+                                  f'double balance={op.residual};if(!isfinite(balance)) return 0;',
+                                  f'if(balance>0) hi={p};else lo={p};', '}}'])
+                lines.extend([refresh, 'double residual=0;',
+                              *[f'{{double balance={self.computations[i].residual};if(!isfinite(balance)) return 0;residual=fmax(residual,fabs(balance));}}' for i in pressures],
+                              'if(residual<1e-11) {pressure_ok=1;break;}', '}',
+                              'if(!pressure_ok) return 0;'])
+            elif refresh:
+                lines.append(refresh)
+            if hvars:
+                # Gauss-Seidel within a genuine stream loop, in stable emission order.
+                lines.extend([*code(streams), 'double change=0;',
+                              *[line for j,key in enumerate(hvars) for line in
+                                (f'if(!isfinite({key})) return 0;',
+                                 f'change=fmax(change,fabs({key}-previous[{j}])/fmax(1,fabs({key})));')],
+                              'if(change<1e-12) {closure_ok=1;break;}', '}',
+                              'if(!closure_ok) return 0;', refresh])
+            lines.append('}')
+        return helpers, lines