mirror of
https://github.com/RYDE-WORK/lnp_ml.git
synced 2026-03-21 09:36:32 +08:00
内外部数据LNP四组分比例统一为百分比数,可电离脂质与mRNA比例的搜索范围与四组分解耦
This commit is contained in:
RYDE-WORK
parent
60e082af55
commit
9e4800b77e
27
app/api.py
27
app/api.py
@ -31,17 +31,17 @@ from app.optimize import (
|
||||
# ============ Pydantic Models ============
|
||||
|
||||
class CompRangesRequest(BaseModel):
|
||||
"""组分范围配置"""
|
||||
weight_ratio_min: float = Field(default=0.05, ge=0.01, le=0.50, description="阳离子脂质/mRNA 重量比最小值")
|
||||
weight_ratio_max: float = Field(default=0.30, ge=0.01, le=0.50, description="阳离子脂质/mRNA 重量比最大值")
|
||||
cationic_mol_min: float = Field(default=0.05, ge=0.00, le=1.00, description="阳离子脂质 mol 比例最小值")
|
||||
cationic_mol_max: float = Field(default=0.80, ge=0.00, le=1.00, description="阳离子脂质 mol 比例最大值")
|
||||
phospholipid_mol_min: float = Field(default=0.00, ge=0.00, le=1.00, description="磷脂 mol 比例最小值")
|
||||
phospholipid_mol_max: float = Field(default=0.80, ge=0.00, le=1.00, description="磷脂 mol 比例最大值")
|
||||
cholesterol_mol_min: float = Field(default=0.00, ge=0.00, le=1.00, description="胆固醇 mol 比例最小值")
|
||||
cholesterol_mol_max: float = Field(default=0.80, ge=0.00, le=1.00, description="胆固醇 mol 比例最大值")
|
||||
peg_mol_min: float = Field(default=0.00, ge=0.00, le=0.20, description="PEG 脂质 mol 比例最小值")
|
||||
peg_mol_max: float = Field(default=0.05, ge=0.00, le=0.20, description="PEG 脂质 mol 比例最大值")
|
||||
"""组分范围配置（mol 比例为百分数 0-100）"""
|
||||
weight_ratio_min: float = Field(default=5.0, ge=1.0, le=50.0, description="阳离子脂质/mRNA 重量比最小值")
|
||||
weight_ratio_max: float = Field(default=30.0, ge=1.0, le=50.0, description="阳离子脂质/mRNA 重量比最大值")
|
||||
cationic_mol_min: float = Field(default=5.0, ge=0.0, le=100.0, description="阳离子脂质 mol 比例最小值 (%)")
|
||||
cationic_mol_max: float = Field(default=80.0, ge=0.0, le=100.0, description="阳离子脂质 mol 比例最大值 (%)")
|
||||
phospholipid_mol_min: float = Field(default=0.0, ge=0.0, le=100.0, description="磷脂 mol 比例最小值 (%)")
|
||||
phospholipid_mol_max: float = Field(default=80.0, ge=0.0, le=100.0, description="磷脂 mol 比例最大值 (%)")
|
||||
cholesterol_mol_min: float = Field(default=0.0, ge=0.0, le=100.0, description="胆固醇 mol 比例最小值 (%)")
|
||||
cholesterol_mol_max: float = Field(default=80.0, ge=0.0, le=100.0, description="胆固醇 mol 比例最大值 (%)")
|
||||
peg_mol_min: float = Field(default=0.0, ge=0.0, le=20.0, description="PEG 脂质 mol 比例最小值 (%)")
|
||||
peg_mol_max: float = Field(default=5.0, ge=0.0, le=20.0, description="PEG 脂质 mol 比例最大值 (%)")
|
||||
|
||||
def to_comp_ranges(self) -> CompRanges:
|
||||
"""转换为 CompRanges 对象"""
|
||||
@ -87,7 +87,8 @@ class OptimizeRequest(BaseModel):
|
||||
top_k: int = Field(default=20, ge=1, le=100, description="Number of top formulations to return")
|
||||
num_seeds: Optional[int] = Field(default=None, ge=1, le=500, description="Number of seed points from first iteration (default: top_k * 5)")
|
||||
top_per_seed: int = Field(default=1, ge=1, le=10, description="Number of local best to keep per seed in refinement")
|
||||
step_sizes: Optional[List[float]] = Field(default=None, description="Step sizes for each iteration (default: [0.10, 0.02, 0.01])")
|
||||
step_sizes: Optional[List[float]] = Field(default=None, description="Mol ratio step sizes for each iteration (default: [10, 2, 1])")
|
||||
wr_step_sizes: Optional[List[float]] = Field(default=None, description="Weight ratio step sizes for each iteration (default: [5, 2, 1])")
|
||||
comp_ranges: Optional[CompRangesRequest] = Field(default=None, description="组分范围配置（默认使用标准范围）")
|
||||
routes: Optional[List[str]] = Field(default=None, description="给药途径列表 (default: ['intravenous', 'intramuscular'])")
|
||||
scoring_weights: Optional[ScoringWeightsRequest] = Field(default=None, description="评分权重配置（默认仅按 biodist 排序）")
|
||||
@ -290,7 +291,6 @@ async def optimize_formulation(request: OptimizeRequest):
|
||||
scoring_weights = request.scoring_weights.to_scoring_weights()
|
||||
|
||||
try:
|
||||
# 执行优化（层级搜索策略）
|
||||
results = optimize(
|
||||
smiles=request.smiles,
|
||||
organ=request.organ,
|
||||
@ -300,6 +300,7 @@ async def optimize_formulation(request: OptimizeRequest):
|
||||
num_seeds=request.num_seeds,
|
||||
top_per_seed=request.top_per_seed,
|
||||
step_sizes=request.step_sizes,
|
||||
wr_step_sizes=request.wr_step_sizes,
|
||||
comp_ranges=comp_ranges,
|
||||
routes=request.routes,
|
||||
scoring_weights=scoring_weights,
|
||||
|
||||
111
app/app.py
111
app/app.py
@ -144,6 +144,7 @@ def call_optimize_api(
|
||||
num_seeds: int = None,
|
||||
top_per_seed: int = 1,
|
||||
step_sizes: list = None,
|
||||
wr_step_sizes: list = None,
|
||||
comp_ranges: dict = None,
|
||||
routes: list = None,
|
||||
scoring_weights: dict = None,
|
||||
@ -156,6 +157,7 @@ def call_optimize_api(
|
||||
"num_seeds": num_seeds,
|
||||
"top_per_seed": top_per_seed,
|
||||
"step_sizes": step_sizes,
|
||||
"wr_step_sizes": wr_step_sizes,
|
||||
"comp_ranges": comp_ranges,
|
||||
"routes": routes,
|
||||
"scoring_weights": scoring_weights,
|
||||
@ -354,48 +356,75 @@ def main():
|
||||
use_custom_steps = st.checkbox(
|
||||
"自定义迭代步长",
|
||||
value=False,
|
||||
help="默认步长为 [0.10, 0.02, 0.01]，共3轮逐步精细化搜索。将某轮步长设为0可减少迭代轮数。",
|
||||
help="默认 mol ratio 步长 [10, 2, 1]（百分数），weight ratio 步长 [5, 2, 1]，共3轮。将某轮步长设为0可减少迭代轮数。",
|
||||
)
|
||||
|
||||
if use_custom_steps:
|
||||
st.caption("**Mol ratio 步长 (%)**")
|
||||
col1, col2, col3 = st.columns(3)
|
||||
with col1:
|
||||
step1 = st.number_input(
|
||||
"第1轮步长",
|
||||
min_value=0.01, max_value=0.20, value=0.10,
|
||||
step=0.01, format="%.2f",
|
||||
help="第1轮为全局粗搜索，步长必须大于0",
|
||||
"第1轮 mol 步长",
|
||||
min_value=1, max_value=20, value=10,
|
||||
step=1,
|
||||
help="第1轮为全局粗搜索",
|
||||
key="mol_step1",
|
||||
)
|
||||
with col2:
|
||||
step2 = st.number_input(
|
||||
"第2轮步长",
|
||||
min_value=0.00, max_value=0.10, value=0.02,
|
||||
step=0.01, format="%.2f",
|
||||
"第2轮 mol 步长",
|
||||
min_value=0, max_value=10, value=2,
|
||||
step=1,
|
||||
help="设为0则只进行1轮搜索",
|
||||
key="mol_step2",
|
||||
)
|
||||
with col3:
|
||||
step3 = st.number_input(
|
||||
"第3轮步长",
|
||||
min_value=0.00, max_value=0.05, value=0.01,
|
||||
step=0.01, format="%.2f",
|
||||
"第3轮 mol 步长",
|
||||
min_value=0, max_value=5, value=1,
|
||||
step=1,
|
||||
help="设为0则只进行2轮搜索",
|
||||
key="mol_step3",
|
||||
)
|
||||
|
||||
# 根据步长值构建实际的 step_sizes 列表
|
||||
# step2 为 0 → 只保留 [step1]（1轮）
|
||||
# step3 为 0 → 只保留 [step1, step2]（2轮）
|
||||
# 都不为 0 → [step1, step2, step3]（3轮）
|
||||
if step2 == 0.0:
|
||||
step_sizes = [step1]
|
||||
elif step3 == 0.0:
|
||||
step_sizes = [step1, step2]
|
||||
else:
|
||||
step_sizes = [step1, step2, step3]
|
||||
st.caption("**Weight ratio 步长**")
|
||||
col1, col2, col3 = st.columns(3)
|
||||
with col1:
|
||||
wr_step1 = st.number_input(
|
||||
"第1轮 WR 步长",
|
||||
min_value=1.0, max_value=10.0, value=5.0,
|
||||
step=1.0, format="%.1f",
|
||||
key="wr_step1",
|
||||
)
|
||||
with col2:
|
||||
wr_step2 = st.number_input(
|
||||
"第2轮 WR 步长",
|
||||
min_value=0.0, max_value=5.0, value=2.0,
|
||||
step=0.5, format="%.1f",
|
||||
key="wr_step2",
|
||||
)
|
||||
with col3:
|
||||
wr_step3 = st.number_input(
|
||||
"第3轮 WR 步长",
|
||||
min_value=0.0, max_value=2.0, value=1.0,
|
||||
step=0.5, format="%.1f",
|
||||
key="wr_step3",
|
||||
)
|
||||
|
||||
# 显示实际迭代轮数提示
|
||||
st.caption(f"📌 实际迭代轮数: {len(step_sizes)} 轮，步长: {step_sizes}")
|
||||
if step2 == 0:
|
||||
step_sizes = [float(step1)]
|
||||
wr_step_sizes_val = [wr_step1]
|
||||
elif step3 == 0:
|
||||
step_sizes = [float(step1), float(step2)]
|
||||
wr_step_sizes_val = [wr_step1, wr_step2]
|
||||
else:
|
||||
step_sizes = None # 使用默认值
|
||||
step_sizes = [float(step1), float(step2), float(step3)]
|
||||
wr_step_sizes_val = [wr_step1, wr_step2, wr_step3]
|
||||
|
||||
st.caption(f"📌 实际迭代轮数: {len(step_sizes)} 轮，mol步长: {step_sizes}，WR步长: {wr_step_sizes_val}")
|
||||
else:
|
||||
step_sizes = None
|
||||
wr_step_sizes_val = None
|
||||
|
||||
st.markdown("**组分范围限制**")
|
||||
use_custom_ranges = st.checkbox(
|
||||
@ -408,37 +437,37 @@ def main():
|
||||
st.caption("阳离子脂质/mRNA 重量比")
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
weight_ratio_min = st.number_input("最小", min_value=0.01, max_value=0.50, value=0.05, step=0.01, format="%.2f", key="wr_min")
|
||||
weight_ratio_min = st.number_input("最小", min_value=1.0, max_value=50.0, value=5.0, step=1.0, format="%.1f", key="wr_min")
|
||||
with col2:
|
||||
weight_ratio_max = st.number_input("最大", min_value=0.01, max_value=0.50, value=0.30, step=0.01, format="%.2f", key="wr_max")
|
||||
weight_ratio_max = st.number_input("最大", min_value=1.0, max_value=50.0, value=30.0, step=1.0, format="%.1f", key="wr_max")
|
||||
|
||||
st.caption("阳离子脂质 mol 比例")
|
||||
st.caption("阳离子脂质 mol 比例 (%)")
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
cationic_mol_min = st.number_input("最小", min_value=0.00, max_value=1.00, value=0.05, step=0.05, format="%.2f", key="cat_min")
|
||||
cationic_mol_min = st.number_input("最小", min_value=0.0, max_value=100.0, value=5.0, step=5.0, format="%.1f", key="cat_min")
|
||||
with col2:
|
||||
cationic_mol_max = st.number_input("最大", min_value=0.00, max_value=1.00, value=0.80, step=0.05, format="%.2f", key="cat_max")
|
||||
cationic_mol_max = st.number_input("最大", min_value=0.0, max_value=100.0, value=80.0, step=5.0, format="%.1f", key="cat_max")
|
||||
|
||||
st.caption("磷脂 mol 比例")
|
||||
st.caption("磷脂 mol 比例 (%)")
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
phospholipid_mol_min = st.number_input("最小", min_value=0.00, max_value=1.00, value=0.00, step=0.05, format="%.2f", key="phos_min")
|
||||
phospholipid_mol_min = st.number_input("最小", min_value=0.0, max_value=100.0, value=0.0, step=5.0, format="%.1f", key="phos_min")
|
||||
with col2:
|
||||
phospholipid_mol_max = st.number_input("最大", min_value=0.00, max_value=1.00, value=0.80, step=0.05, format="%.2f", key="phos_max")
|
||||
phospholipid_mol_max = st.number_input("最大", min_value=0.0, max_value=100.0, value=80.0, step=5.0, format="%.1f", key="phos_max")
|
||||
|
||||
st.caption("胆固醇 mol 比例")
|
||||
st.caption("胆固醇 mol 比例 (%)")
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
cholesterol_mol_min = st.number_input("最小", min_value=0.00, max_value=1.00, value=0.00, step=0.05, format="%.2f", key="chol_min")
|
||||
cholesterol_mol_min = st.number_input("最小", min_value=0.0, max_value=100.0, value=0.0, step=5.0, format="%.1f", key="chol_min")
|
||||
with col2:
|
||||
cholesterol_mol_max = st.number_input("最大", min_value=0.00, max_value=1.00, value=0.80, step=0.05, format="%.2f", key="chol_max")
|
||||
cholesterol_mol_max = st.number_input("最大", min_value=0.0, max_value=100.0, value=80.0, step=5.0, format="%.1f", key="chol_max")
|
||||
|
||||
st.caption("PEG 脂质 mol 比例")
|
||||
st.caption("PEG 脂质 mol 比例 (%)")
|
||||
col1, col2 = st.columns(2)
|
||||
with col1:
|
||||
peg_mol_min = st.number_input("最小", min_value=0.00, max_value=0.20, value=0.00, step=0.01, format="%.2f", key="peg_min")
|
||||
peg_mol_min = st.number_input("最小", min_value=0.0, max_value=20.0, value=0.0, step=1.0, format="%.1f", key="peg_min")
|
||||
with col2:
|
||||
peg_mol_max = st.number_input("最大", min_value=0.00, max_value=0.20, value=0.05, step=0.01, format="%.2f", key="peg_max")
|
||||
peg_mol_max = st.number_input("最大", min_value=0.0, max_value=20.0, value=5.0, step=1.0, format="%.1f", key="peg_max")
|
||||
|
||||
comp_ranges = {
|
||||
"weight_ratio_min": weight_ratio_min,
|
||||
@ -453,13 +482,12 @@ def main():
|
||||
"peg_mol_max": peg_mol_max,
|
||||
}
|
||||
|
||||
# 简单验证
|
||||
min_sum = cationic_mol_min + phospholipid_mol_min + cholesterol_mol_min + peg_mol_min
|
||||
max_sum = cationic_mol_max + phospholipid_mol_max + cholesterol_mol_max + peg_mol_max
|
||||
if min_sum > 1.0 or max_sum < 1.0:
|
||||
if min_sum > 100.0 or max_sum < 100.0:
|
||||
st.warning("⚠️ 当前范围设置可能无法生成有效配方（mol 比例需加起来为 100%）")
|
||||
else:
|
||||
comp_ranges = None # 使用默认值
|
||||
comp_ranges = None
|
||||
|
||||
st.markdown("**评分/排序权重**")
|
||||
use_custom_scoring = st.checkbox(
|
||||
@ -575,6 +603,7 @@ def main():
|
||||
num_seeds=num_seeds,
|
||||
top_per_seed=top_per_seed,
|
||||
step_sizes=step_sizes,
|
||||
wr_step_sizes=wr_step_sizes_val,
|
||||
comp_ranges=comp_ranges,
|
||||
routes=selected_routes,
|
||||
scoring_weights=scoring_weights,
|
||||
|
||||
153
app/optimize.py
153
app/optimize.py
@ -44,22 +44,22 @@ AVAILABLE_ORGANS = ["lymph_nodes", "heart", "liver", "spleen", "lung", "kidney",
|
||||
|
||||
@dataclass
|
||||
class CompRanges:
|
||||
"""组分参数范围配置"""
|
||||
"""组分参数范围配置（mol 比例为百分数 0-100）"""
|
||||
# 阳离子脂质/mRNA 重量比
|
||||
weight_ratio_min: float = 0.05
|
||||
weight_ratio_max: float = 0.30
|
||||
# 阳离子脂质 mol 比例
|
||||
cationic_mol_min: float = 0.05
|
||||
cationic_mol_max: float = 0.80
|
||||
# 磷脂 mol 比例
|
||||
phospholipid_mol_min: float = 0.00
|
||||
phospholipid_mol_max: float = 0.80
|
||||
# 胆固醇 mol 比例
|
||||
cholesterol_mol_min: float = 0.00
|
||||
cholesterol_mol_max: float = 0.80
|
||||
# PEG 脂质 mol 比例
|
||||
peg_mol_min: float = 0.00
|
||||
peg_mol_max: float = 0.05
|
||||
weight_ratio_min: float = 5.0
|
||||
weight_ratio_max: float = 30.0
|
||||
# 阳离子脂质 mol 比例 (%)
|
||||
cationic_mol_min: float = 5.0
|
||||
cationic_mol_max: float = 80.0
|
||||
# 磷脂 mol 比例 (%)
|
||||
phospholipid_mol_min: float = 0.0
|
||||
phospholipid_mol_max: float = 80.0
|
||||
# 胆固醇 mol 比例 (%)
|
||||
cholesterol_mol_min: float = 0.0
|
||||
cholesterol_mol_max: float = 80.0
|
||||
# PEG 脂质 mol 比例 (%)
|
||||
peg_mol_min: float = 0.0
|
||||
peg_mol_max: float = 5.0
|
||||
|
||||
def to_dict(self) -> Dict:
|
||||
"""转换为字典"""
|
||||
@ -94,10 +94,10 @@ class CompRanges:
|
||||
min_sum = self.cationic_mol_min + self.phospholipid_mol_min + self.cholesterol_mol_min + self.peg_mol_min
|
||||
max_sum = self.cationic_mol_max + self.phospholipid_mol_max + self.cholesterol_mol_max + self.peg_mol_max
|
||||
|
||||
if min_sum > 1.0:
|
||||
return f"mol比例最小值之和({min_sum:.2f})超过100%，无法生成有效配方"
|
||||
if max_sum < 1.0:
|
||||
return f"mol比例最大值之和({max_sum:.2f})不足100%，无法生成有效配方"
|
||||
if min_sum > 100.0:
|
||||
return f"mol比例最小值之和({min_sum:.1f}%)超过100%，无法生成有效配方"
|
||||
if max_sum < 100.0:
|
||||
return f"mol比例最大值之和({max_sum:.1f}%)不足100%，无法生成有效配方"
|
||||
|
||||
return None
|
||||
|
||||
@ -109,11 +109,14 @@ class CompRanges:
|
||||
# 默认组分范围
|
||||
DEFAULT_COMP_RANGES = CompRanges()
|
||||
|
||||
# 最小 step size
|
||||
MIN_STEP_SIZE = 0.01
|
||||
# PEG 最小 step size (百分数)
|
||||
MIN_STEP_SIZE = 1
|
||||
|
||||
# 迭代策略：每个迭代的 step_size
|
||||
ITERATION_STEP_SIZES = [0.10, 0.02, 0.01]
|
||||
# 迭代策略：mol ratio 的 step_size (百分数)
|
||||
MOL_STEP_SIZES = [10, 2, 1]
|
||||
|
||||
# 迭代策略：weight ratio 的 step_size（与 mol ratio 解耦）
|
||||
WR_STEP_SIZES = [5, 2, 1]
|
||||
|
||||
# Helper lipid 选项（不包含 DOTAP）
|
||||
HELPER_LIPID_OPTIONS = ["DOPE", "DSPC"]
|
||||
@ -343,51 +346,46 @@ def generate_grid_values(
|
||||
|
||||
|
||||
def generate_initial_grid(
|
||||
step_size: float,
|
||||
mol_step: float,
|
||||
wr_step: float,
|
||||
comp_ranges: CompRanges = None,
|
||||
) -> List[Tuple[float, float, float, float, float]]:
|
||||
"""
|
||||
生成初始搜索网格（满足 mol ratio 和为 1 的约束）。
|
||||
生成初始搜索网格（满足 mol ratio 和为 100% 的约束）。
|
||||
|
||||
Args:
|
||||
step_size: 搜索步长
|
||||
mol_step: mol ratio 搜索步长 (百分数)
|
||||
wr_step: weight ratio 搜索步长
|
||||
comp_ranges: 组分范围配置（默认使用 DEFAULT_COMP_RANGES）
|
||||
|
||||
Returns:
|
||||
List of (cationic_ratio, cationic_mol, phospholipid_mol, cholesterol_mol, peg_mol)
|
||||
List of (weight_ratio, cationic_mol, phospholipid_mol, cholesterol_mol, peg_mol)
|
||||
"""
|
||||
if comp_ranges is None:
|
||||
comp_ranges = DEFAULT_COMP_RANGES
|
||||
|
||||
grid = []
|
||||
|
||||
# Cationic_Lipid_to_mRNA_weight_ratio
|
||||
weight_ratios = np.arange(
|
||||
comp_ranges.weight_ratio_min,
|
||||
comp_ranges.weight_ratio_max + 0.001,
|
||||
step_size
|
||||
wr_step
|
||||
)
|
||||
|
||||
# PEG: 单独处理，范围很小，始终用最小步长
|
||||
peg_values = np.arange(
|
||||
comp_ranges.peg_mol_min,
|
||||
comp_ranges.peg_mol_max + 0.001,
|
||||
MIN_STEP_SIZE
|
||||
)
|
||||
|
||||
# 其他三个 mol ratio 需要满足和为 1 - PEG
|
||||
mol_step = step_size
|
||||
|
||||
for weight_ratio in weight_ratios:
|
||||
for peg in peg_values:
|
||||
remaining = 1.0 - peg
|
||||
# 生成满足约束的组合
|
||||
remaining = 100.0 - peg
|
||||
cationic_max = min(comp_ranges.cationic_mol_max, remaining) + 0.001
|
||||
for cationic_mol in np.arange(comp_ranges.cationic_mol_min, cationic_max, mol_step):
|
||||
phospholipid_max = min(comp_ranges.phospholipid_mol_max, remaining - cationic_mol) + 0.001
|
||||
for phospholipid_mol in np.arange(comp_ranges.phospholipid_mol_min, phospholipid_max, mol_step):
|
||||
cholesterol_mol = remaining - cationic_mol - phospholipid_mol
|
||||
# 检查约束
|
||||
if (comp_ranges.cholesterol_mol_min <= cholesterol_mol <= comp_ranges.cholesterol_mol_max):
|
||||
grid.append((
|
||||
round(weight_ratio, 4),
|
||||
@ -402,7 +400,8 @@ def generate_initial_grid(
|
||||
|
||||
def generate_refined_grid(
|
||||
seeds: List[Formulation],
|
||||
step_size: float,
|
||||
mol_step: float,
|
||||
wr_step: float,
|
||||
radius: int = 2,
|
||||
comp_ranges: CompRanges = None,
|
||||
) -> List[Tuple[float, float, float, float, float]]:
|
||||
@ -411,7 +410,8 @@ def generate_refined_grid(
|
||||
|
||||
Args:
|
||||
seeds: 种子配方列表
|
||||
step_size: 步长
|
||||
mol_step: mol ratio 步长 (百分数)
|
||||
wr_step: weight ratio 步长
|
||||
radius: 扩展半径
|
||||
comp_ranges: 组分范围配置（默认使用 DEFAULT_COMP_RANGES）
|
||||
|
||||
@ -424,35 +424,31 @@ def generate_refined_grid(
|
||||
grid_set = set()
|
||||
|
||||
for seed in seeds:
|
||||
# Weight ratio
|
||||
weight_ratios = generate_grid_values(
|
||||
seed.cationic_lipid_to_mrna_ratio, step_size,
|
||||
seed.cationic_lipid_to_mrna_ratio, wr_step,
|
||||
comp_ranges.weight_ratio_min, comp_ranges.weight_ratio_max, radius
|
||||
)
|
||||
|
||||
# PEG (始终用最小步长)
|
||||
peg_values = generate_grid_values(
|
||||
seed.peg_lipid_mol_ratio, MIN_STEP_SIZE,
|
||||
comp_ranges.peg_mol_min, comp_ranges.peg_mol_max, radius
|
||||
)
|
||||
|
||||
# Mol ratios
|
||||
cationic_mols = generate_grid_values(
|
||||
seed.cationic_lipid_mol_ratio, step_size,
|
||||
seed.cationic_lipid_mol_ratio, mol_step,
|
||||
comp_ranges.cationic_mol_min, comp_ranges.cationic_mol_max, radius
|
||||
)
|
||||
phospholipid_mols = generate_grid_values(
|
||||
seed.phospholipid_mol_ratio, step_size,
|
||||
seed.phospholipid_mol_ratio, mol_step,
|
||||
comp_ranges.phospholipid_mol_min, comp_ranges.phospholipid_mol_max, radius
|
||||
)
|
||||
|
||||
for weight_ratio in weight_ratios:
|
||||
for peg in peg_values:
|
||||
remaining = 1.0 - peg
|
||||
remaining = 100.0 - peg
|
||||
for cationic_mol in cationic_mols:
|
||||
for phospholipid_mol in phospholipid_mols:
|
||||
cholesterol_mol = remaining - cationic_mol - phospholipid_mol
|
||||
# 检查约束
|
||||
if (comp_ranges.cationic_mol_min <= cationic_mol <= comp_ranges.cationic_mol_max and
|
||||
comp_ranges.phospholipid_mol_min <= phospholipid_mol <= comp_ranges.phospholipid_mol_max and
|
||||
comp_ranges.cholesterol_mol_min <= cholesterol_mol <= comp_ranges.cholesterol_mol_max and
|
||||
@ -677,7 +673,8 @@ def select_top_k(
|
||||
|
||||
def generate_single_seed_grid(
|
||||
seed: Formulation,
|
||||
step_size: float,
|
||||
mol_step: float,
|
||||
wr_step: float,
|
||||
radius: int = 2,
|
||||
comp_ranges: CompRanges = None,
|
||||
) -> List[Tuple[float, float, float, float, float]]:
|
||||
@ -686,7 +683,8 @@ def generate_single_seed_grid(
|
||||
|
||||
Args:
|
||||
seed: 种子配方
|
||||
step_size: 步长
|
||||
mol_step: mol ratio 步长 (百分数)
|
||||
wr_step: weight ratio 步长
|
||||
radius: 扩展半径
|
||||
comp_ranges: 组分范围配置（默认使用 DEFAULT_COMP_RANGES）
|
||||
|
||||
@ -698,35 +696,31 @@ def generate_single_seed_grid(
|
||||
|
||||
grid_set = set()
|
||||
|
||||
# Weight ratio
|
||||
weight_ratios = generate_grid_values(
|
||||
seed.cationic_lipid_to_mrna_ratio, step_size,
|
||||
seed.cationic_lipid_to_mrna_ratio, wr_step,
|
||||
comp_ranges.weight_ratio_min, comp_ranges.weight_ratio_max, radius
|
||||
)
|
||||
|
||||
# PEG (始终用最小步长)
|
||||
peg_values = generate_grid_values(
|
||||
seed.peg_lipid_mol_ratio, MIN_STEP_SIZE,
|
||||
comp_ranges.peg_mol_min, comp_ranges.peg_mol_max, radius
|
||||
)
|
||||
|
||||
# Mol ratios
|
||||
cationic_mols = generate_grid_values(
|
||||
seed.cationic_lipid_mol_ratio, step_size,
|
||||
seed.cationic_lipid_mol_ratio, mol_step,
|
||||
comp_ranges.cationic_mol_min, comp_ranges.cationic_mol_max, radius
|
||||
)
|
||||
phospholipid_mols = generate_grid_values(
|
||||
seed.phospholipid_mol_ratio, step_size,
|
||||
seed.phospholipid_mol_ratio, mol_step,
|
||||
comp_ranges.phospholipid_mol_min, comp_ranges.phospholipid_mol_max, radius
|
||||
)
|
||||
|
||||
for weight_ratio in weight_ratios:
|
||||
for peg in peg_values:
|
||||
remaining = 1.0 - peg
|
||||
remaining = 100.0 - peg
|
||||
for cationic_mol in cationic_mols:
|
||||
for phospholipid_mol in phospholipid_mols:
|
||||
cholesterol_mol = remaining - cationic_mol - phospholipid_mol
|
||||
# 检查约束
|
||||
if (comp_ranges.cationic_mol_min <= cationic_mol <= comp_ranges.cationic_mol_max and
|
||||
comp_ranges.phospholipid_mol_min <= phospholipid_mol <= comp_ranges.phospholipid_mol_max and
|
||||
comp_ranges.cholesterol_mol_min <= cholesterol_mol <= comp_ranges.cholesterol_mol_max and
|
||||
@ -751,6 +745,7 @@ def optimize(
|
||||
num_seeds: Optional[int] = None,
|
||||
top_per_seed: int = 1,
|
||||
step_sizes: Optional[List[float]] = None,
|
||||
wr_step_sizes: Optional[List[float]] = None,
|
||||
comp_ranges: Optional[CompRanges] = None,
|
||||
routes: Optional[List[str]] = None,
|
||||
scoring_weights: Optional[ScoringWeights] = None,
|
||||
@ -772,7 +767,8 @@ def optimize(
|
||||
top_k: 最终返回的最优配方数
|
||||
num_seeds: 第一次迭代后保留的种子点数量（默认为 top_k * 5）
|
||||
top_per_seed: 每个种子点的邻域搜索后保留的局部最优点数量
|
||||
step_sizes: 每轮迭代的步长列表（默认为 [0.10, 0.02, 0.01]）
|
||||
step_sizes: mol ratio 每轮迭代的步长列表 (百分数，默认 [10, 2, 1])
|
||||
wr_step_sizes: weight ratio 每轮迭代的步长列表 (默认 [5, 2, 1])
|
||||
comp_ranges: 组分范围配置（默认使用 DEFAULT_COMP_RANGES）
|
||||
routes: 给药途径列表（默认使用 ROUTE_OPTIONS）
|
||||
scoring_weights: 评分权重配置（默认仅按 biodist 排序）
|
||||
@ -781,49 +777,52 @@ def optimize(
|
||||
Returns:
|
||||
最终 top-k 配方列表
|
||||
"""
|
||||
# 默认 num_seeds 为 top_k * 5
|
||||
if num_seeds is None:
|
||||
num_seeds = top_k * 5
|
||||
|
||||
# 默认步长
|
||||
if step_sizes is None:
|
||||
step_sizes = ITERATION_STEP_SIZES
|
||||
step_sizes = MOL_STEP_SIZES
|
||||
|
||||
if wr_step_sizes is None:
|
||||
wr_step_sizes = WR_STEP_SIZES
|
||||
|
||||
# 两组步长长度必须一致
|
||||
if len(wr_step_sizes) != len(step_sizes):
|
||||
raise ValueError(
|
||||
f"step_sizes ({len(step_sizes)}) 和 wr_step_sizes ({len(wr_step_sizes)}) 长度不一致"
|
||||
)
|
||||
|
||||
# 默认组分范围
|
||||
if comp_ranges is None:
|
||||
comp_ranges = DEFAULT_COMP_RANGES
|
||||
|
||||
# 默认给药途径
|
||||
if routes is None:
|
||||
routes = ROUTE_OPTIONS
|
||||
|
||||
# 默认评分权重
|
||||
if scoring_weights is None:
|
||||
scoring_weights = DEFAULT_SCORING_WEIGHTS
|
||||
|
||||
# 评分函数（用于 Formulation 对象排序）
|
||||
def _score(f: Formulation) -> float:
|
||||
return compute_formulation_score(f, organ, scoring_weights)
|
||||
|
||||
logger.info(f"Starting optimization for organ: {organ}")
|
||||
logger.info(f"SMILES: {smiles}")
|
||||
logger.info(f"Strategy: num_seeds={num_seeds}, top_per_seed={top_per_seed}, top_k={top_k}")
|
||||
logger.info(f"Step sizes: {step_sizes}")
|
||||
logger.info(f"Mol step sizes: {step_sizes}, WR step sizes: {wr_step_sizes}")
|
||||
logger.info(f"Routes: {routes}")
|
||||
logger.info(f"Scoring weights: biodist={scoring_weights.biodist_weight}, delivery={scoring_weights.delivery_weight}, size={scoring_weights.size_weight}")
|
||||
logger.info(f"Comp ranges: {comp_ranges.to_dict()}")
|
||||
|
||||
seeds = None
|
||||
|
||||
for iteration, step_size in enumerate(step_sizes):
|
||||
for iteration, (mol_step, wr_step) in enumerate(zip(step_sizes, wr_step_sizes)):
|
||||
logger.info(f"\n{'='*60}")
|
||||
logger.info(f"Iteration {iteration + 1}/{len(step_sizes)}, step_size={step_size}")
|
||||
logger.info(f"Iteration {iteration + 1}/{len(step_sizes)}, mol_step={mol_step}, wr_step={wr_step}")
|
||||
logger.info(f"{'='*60}")
|
||||
|
||||
if seeds is None:
|
||||
# ==================== 第一次迭代：全局稀疏搜索 ====================
|
||||
logger.info("Generating initial grid (global sparse search)...")
|
||||
grid = generate_initial_grid(step_size, comp_ranges)
|
||||
grid = generate_initial_grid(mol_step, wr_step, comp_ranges)
|
||||
|
||||
logger.info(f"Grid size: {len(grid)} comp combinations")
|
||||
|
||||
@ -853,8 +852,7 @@ def optimize(
|
||||
all_local_best = []
|
||||
|
||||
for seed_idx, seed in enumerate(seeds):
|
||||
# 为当前种子点生成邻域网格
|
||||
local_grid = generate_single_seed_grid(seed, step_size, radius=2, comp_ranges=comp_ranges)
|
||||
local_grid = generate_single_seed_grid(seed, mol_step, wr_step, radius=2, comp_ranges=comp_ranges)
|
||||
|
||||
if len(local_grid) == 0:
|
||||
# 如果没有新的网格点，保留原种子
|
||||
@ -946,7 +944,8 @@ def main(
|
||||
top_k: int = typer.Option(20, "--top-k", "-k", help="Number of top formulations to return"),
|
||||
num_seeds: Optional[int] = typer.Option(None, "--num-seeds", "-n", help="Number of seed points from first iteration (default: top_k * 5)"),
|
||||
top_per_seed: int = typer.Option(1, "--top-per-seed", "-t", help="Number of local best to keep per seed"),
|
||||
step_sizes: Optional[str] = typer.Option(None, "--step-sizes", "-S", help="Comma-separated step sizes (e.g., '0.10,0.02,0.01')"),
|
||||
step_sizes: Optional[str] = typer.Option(None, "--step-sizes", "-S", help="Mol ratio step sizes, comma-separated (e.g., '10,2,1')"),
|
||||
wr_step_sizes: Optional[str] = typer.Option(None, "--wr-step-sizes", help="Weight ratio step sizes, comma-separated (e.g., '5,2,1')"),
|
||||
batch_size: int = typer.Option(256, "--batch-size", "-b", help="Prediction batch size"),
|
||||
device: str = typer.Option("cuda" if torch.cuda.is_available() else "cpu", "--device", "-d", help="Device"),
|
||||
):
|
||||
@ -961,7 +960,7 @@ def main(
|
||||
示例:
|
||||
python -m app.optimize --smiles "CC(C)..." --organ liver
|
||||
python -m app.optimize -s "CC(C)..." -o spleen -k 10 -n 30 -t 2
|
||||
python -m app.optimize -s "CC(C)..." -o liver -S "0.10,0.05,0.02"
|
||||
python -m app.optimize -s "CC(C)..." -o liver -S "10,2,1" --wr-step-sizes "5,2,1"
|
||||
"""
|
||||
# 验证器官
|
||||
if organ not in AVAILABLE_ORGANS:
|
||||
@ -977,12 +976,19 @@ def main(
|
||||
logger.error(f"Invalid step sizes format: {step_sizes}")
|
||||
raise typer.Exit(1)
|
||||
|
||||
parsed_wr_step_sizes = None
|
||||
if wr_step_sizes:
|
||||
try:
|
||||
parsed_wr_step_sizes = [float(s.strip()) for s in wr_step_sizes.split(",")]
|
||||
except ValueError:
|
||||
logger.error(f"Invalid wr step sizes format: {wr_step_sizes}")
|
||||
raise typer.Exit(1)
|
||||
|
||||
# 加载模型
|
||||
logger.info(f"Loading model from {model_path}")
|
||||
device = torch.device(device)
|
||||
model = load_model(model_path, device)
|
||||
|
||||
# 执行优化（层级搜索策略）
|
||||
results = optimize(
|
||||
smiles=smiles,
|
||||
organ=organ,
|
||||
@ -992,6 +998,7 @@ def main(
|
||||
num_seeds=num_seeds,
|
||||
top_per_seed=top_per_seed,
|
||||
step_sizes=parsed_step_sizes,
|
||||
wr_step_sizes=parsed_wr_step_sizes,
|
||||
batch_size=batch_size,
|
||||
)
|
||||
|
||||
|
||||
@ -37,10 +37,6 @@ def main(
|
||||
.transform(lambda x: (x - x.mean()) / x.std())
|
||||
)
|
||||
|
||||
# 将 Cationic_Lipid_Mol_Ratio,Phospholipid_Mol_Ratio,Cholesterol_Mol_Ratio,PEG_Lipid_Mol_Ratio 四列的百分数转换为小数
|
||||
logger.info("Converting percentage columns to decimal...")
|
||||
df[["Cationic_Lipid_Mol_Ratio", "Phospholipid_Mol_Ratio", "Cholesterol_Mol_Ratio", "PEG_Lipid_Mol_Ratio"]] = df[["Cationic_Lipid_Mol_Ratio", "Phospholipid_Mol_Ratio", "Cholesterol_Mol_Ratio", "PEG_Lipid_Mol_Ratio"]] / 100
|
||||
|
||||
# 对 size 列取 log
|
||||
logger.info("Log-transforming size column...")
|
||||
df["size"] = pd.to_numeric(df["size"], errors="coerce")
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user