ChemLab-Assets / scripts /asset_runtime /agilent_1260infinity.py
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"""CHEM-094 Agilent 1260 Infinity III SFC system (G4301A SFC Control Module, G4782A SFC Binary Pump, G4767A SFC Multisampler,
G7116A Multicolumn Thermostat, G7115A DAD WR with SFC flow cell, solvent cabinet) - process runtime.
Physics (SI; the host's step(dt_s) is the only clock):
* CO2 path: host-connected cylinder (40-70 bar documented supply) -> control-module chiller (first order to a 278.15 K target inside the
documented -20...9 degC range) -> booster -> pump channel A; modifier from bottle B1/B2 on channel B (high-pressure binary mixing).
* Hydraulics: pump pressure = BPR set pressure + Kozeny-Carman column drop (log-blended CO2/modifier viscosity) + extra-column drop;
600 bar pump limit trips the pump (documented 600 bar); BPR 100-400 bar, 40-70 degC (documented G4301A ranges).
* Column oven: first-order heating / cooling with time constants derived from the documented MCT rates (ambient->40 degC ~5 min,
40->20 degC ~10 min).
* Retention: per analyte, column and modifier the intercept a of log10 k = a - m log10(phi) comes from the measured CC BY 4.0
retention times of the template library (back-solved, evidence 'derived'); the run integrates band migration
dz/dt = 1 / (t0 (1 + k(phi(t - t_D - z t0)))) for the configured program, with t0 = eps_T * column volume / flow, the documented
600-900 uL pump delay volume, and a density correction from a Peng-Robinson CO2 equation of state (NIST critical constants).
* Detection: DAD absorbance A = eps(lambda) * 10 mm * c(t) (documented SFC flow cell 10 mm / 13 uL); eps from NIST UV curves where the
library holds one, else an assumed 1e3 m^2/mol (flagged); documented +-0.7e-5 AU noise and 0.9e-3 AU/h drift.
* Ledgers: vial volume and species moles (vial -> column -> waste/exhaust), modifier volume (bottle -> waste), CO2 mass (cylinder -> vent).
Sessions filter visibility: agents never see the vial composition, process truths or ledgers; template.read only returns public reference
data. Matterix bridge: RECIPES module="asset_runtime.agilent_1260infinity", cls="Agilent1260infinityRuntime", instance_in_ctor=True, advance=STEP_DT.
"""
from __future__ import annotations
import copy
import hashlib
import json
import math
from functools import lru_cache
from pathlib import Path
import numpy as np
try:
from asset_runtime import _annotations as _ann
except ImportError: # pragma: no cover - imported as a plain module
_ann = None
PROTOCOL_VERSION = '1.0.0'
ASSET_TYPE_ID = 'instrument.agilent_1260infinity'
CATALOG_ID = 'CHEM-094'
ROOT = Path(__file__).resolve().parents[2]
LIBRARY_REL = 'assets/reactions/agilent_1260infinity_sfc_retention_library/sfc_retention_library.json'
# ------------------------------------------------------------------------------------------------ documented specifications
FLOW_MIN, FLOW_MAX = 0.001e-6 / 60, 5.0e-6 / 60 # m^3/s, G4782A settable 0.001-5 mL/min
PUMP_MAX_PA = 600e5 # G4782A / system: 600 bar up to 5 mL/min
BPR_MIN_PA, BPR_MAX_PA = 100e5, 400e5 # G4301A BPR settable 100-400 bar
BPR_T_MIN, BPR_T_MAX = 313.15, 343.15 # G4301A BPR thermal range 40-70 degC
SUPPLY_MIN_PA, SUPPLY_MAX_PA = 40e5, 70e5 # G4301A CO2 supply pressure 40-70 bar
CHILLER_TARGET_K = 278.15 # inside the documented -20...9 degC chiller range (assumption: 5 degC)
INJ_MIN, INJ_MAX, INJ_STEP = 0.1e-9, 90e-9, 0.1e-9 # G4767A SFC mode 0.1-90 uL in 0.1 uL steps
INJECT_CYCLE_S = 13.0 # G4767A SFC injection cycle < 13 s (1 uL)
COL_T_MAX = 358.15 # G7116A up to 85 degC; lower limit ambient - 10 K, >= 4 degC
COL_T_ABS_MIN = 277.15
N_COLUMN_POSITIONS = 4 # G7116A four columns up to 300 mm, 4-column selection valve
N_DRAWERS, N_VIAL_POSITIONS = 4, 108 # 4 x 2H drawers, 432 x 2 mL vials in total (G4767A)
VIAL_CAPACITY_M3 = 2e-6
LAMBDA_MIN, LAMBDA_MAX = 190e-9, 950e-9 # G7115A 190-950 nm
FLOW_CELL_PATH_M, FLOW_CELL_VOLUME_M3, FLOW_CELL_MAX_PA = 0.010, 13e-9, 400e5 # SFC flow cell 10 mm, 13 uL, 400 bar
DAD_NOISE_AU, DAD_DRIFT_AU_S = 0.7e-5, 0.9e-3 / 3600.0 # G7115A noise < +-0.7e-5 AU, drift < 0.9e-3 AU/h
DELAY_MIN_M3, DELAY_MAX_M3 = 600e-9, 900e-9 # G4782A delay volume 600-900 uL incl. 400 uL mixer, depending on back pressure
MAX_PROGRAM_ROWS = 20 # assumption: table length (G4301A documents 20 BPR timetable entries)
# derived from documented MCT rates: ambient(25)->40 degC in ~5 min, 40->20 degC in ~10 min (to within 0.5 K)
COL_TAU_HEAT_S = 300.0 / math.log(15.0 / 0.5)
COL_TAU_COOL_S = 600.0 / math.log(20.0 / 0.5)
# ------------------------------------------------------------------------------------------------ assumptions (flagged)
TOTAL_POROSITY = 0.65 # eps_T of fully porous packed columns (t0 = eps_T * V_column / F)
BED_POROSITY = 0.40 # interparticle porosity (Kozeny-Carman)
LOGLOG_SLOPE_M = 1.5 # log10 k vs log10(phi) slope (Snyder-Soczewinski type), same for all analytes
PHI_MIN = 0.01 # lower bound of the modifier fraction in the retention law
DENSITY_COEFF = 2.0 # d ln k / d(rho/rho_ref)
REF_FLOW_M3_S = 1.5e-6 / 60 # 1.5 mL/min of the source runs (documented in the articles)
REF_DWELL_S = 18.0 # UPC2 gradient delay of the source runs (0.45 mL at 1.5 mL/min) - not documented, assumption
REF_COLUMN_K, REF_BPR_PA = 313.15, 13.0e6 # source runs: 40 degC, BPR 13 MPa (documented)
PLATE_HEIGHT_DP = 3.0 # reduced plate height h = H / dp
ETA_CO2_PA_S = 6.5e-5 # CO2 viscosity near 40 degC / 150 bar (engineering value)
ETA_MEOH_PA_S = 5.44e-4 # methanol, 25 degC (CRC Handbook)
EXTRA_COLUMN_R = 4.0e13 # Pa s/m^3 per 1e-4 Pa s: tubing + flow cell drop (~10 bar at 1.5 mL/min)
PRESSURE_TAU_S, FLOW_TAU_S, BPR_HEAT_TAU_S, CHILLER_TAU_S = 3.0, 1.0, 60.0, 300.0
ASSUMED_EPSILON_M2_MOL = 1.0e3 # 1e4 L/(mol cm) when no NIST UV curve is available
VIAL_DEAD_VOLUME_M3 = 10e-9 # needle cannot draw the last 10 uL
READY_TOL_PA, READY_TOL_K, READY_FLOW_FRACTION = 5e5, 1.0, 0.98
CO2_PUMP_DENSITY_KG_M3 = 900.0 # chilled liquid CO2 at the pump head (approx., used for CO2 mass consumption)
# CO2 critical constants (NIST WebBook / Span & Wagner 1996) for the Peng-Robinson density
CO2_TC, CO2_PC, CO2_OMEGA, CO2_M = 304.1282, 7.3773e6, 0.22394, 0.0440095
R_GAS = 8.314462618
MODULES = ('control', 'pump', 'sampler', 'mct', 'dad')
MODIFIERS = ('methanol', 'methanol_ammonia_10mM', 'methanol_water_2pct')
PHASES = ('idle', 'injecting', 'running', 'succeeded', 'cancelled', 'failed')
MECH = { # mechanism -> (state id, unit, upper limit, component)
'sampler_door': ('sampler_door.angle_rad', 'rad', 1.75, 'sampler_door'),
'drawer_1': ('drawer_1.position_m', 'm', 0.30, 'drawer_1'),
'drawer_2': ('drawer_2.position_m', 'm', 0.30, 'drawer_2'),
'drawer_3': ('drawer_3.position_m', 'm', 0.30, 'drawer_3'),
'drawer_4': ('drawer_4.position_m', 'm', 0.30, 'drawer_4'),
'mct_door': ('mct_door.angle_rad', 'rad', 1.50, 'mct_door'),
}
class ActionRejected(ValueError):
"""Precondition / argument failure; the runtime state is unchanged. Messages never disclose sample identity."""
# --------------------------------------------------------------------------------------------------------------- schemas
def number(unit, lo=None, hi=None):
d = {'type': 'number', 'x-unit': unit}
if lo is not None:
d['minimum'] = lo
if hi is not None:
d['maximum'] = hi
return d
def integer(lo, hi):
return {'type': 'integer', 'x-unit': '1', 'minimum': lo, 'maximum': hi}
def obj(props, required=None):
return {'type': 'object', 'properties': props, 'required': list(props) if required is None else required, 'additionalProperties': False}
def arr(items, lo=None, hi=None):
d = {'type': 'array', 'items': items}
if lo is not None:
d['minItems'] = lo
if hi is not None:
d['maxItems'] = hi
return d
def nullable(s):
return {'anyOf': [s, {'type': 'null'}]}
def enum(values):
return {'type': 'string', 'enum': list(values)}
BOOL, TEXT = {'type': 'boolean'}, {'type': 'string'}
COLUMN_IDS = ('silica', 'bridged_ethylene_hybrid', 'diol', 'c18_hss_sb', 'pfp_csh', 'pgc')
PROGRAM_ROW = obj({'time_s': number('s', 0, 3600), 'modifier_fraction': number('1', 0.0, 1.0)})
METHOD = obj({
'flow_m3_s': number('m^3/s', FLOW_MIN, FLOW_MAX), 'modifier_channel': enum(['B1', 'B2']),
'program': arr(PROGRAM_ROW, 1, MAX_PROGRAM_ROWS), 'bpr_pa': number('Pa', BPR_MIN_PA, BPR_MAX_PA),
'bpr_temperature_k': number('K', BPR_T_MIN, BPR_T_MAX), 'column_temperature_k': number('K', COL_T_ABS_MIN, COL_T_MAX),
'column_position': integer(1, N_COLUMN_POSITIONS), 'injection_volume_m3': number('m^3', INJ_MIN, INJ_MAX),
'wavelength_m': number('m', LAMBDA_MIN, LAMBDA_MAX), 'run_time_s': number('s', 10, 3600), 'data_rate_hz': number('Hz', 0.5, 10)})
METHOD_EXAMPLE = dict(flow_m3_s=REF_FLOW_M3_S, modifier_channel='B1',
program=[dict(time_s=0.0, modifier_fraction=0.02), dict(time_s=60.0, modifier_fraction=0.02),
dict(time_s=300.0, modifier_fraction=0.45), dict(time_s=360.0, modifier_fraction=0.45)],
bpr_pa=REF_BPR_PA, bpr_temperature_k=333.15, column_temperature_k=REF_COLUMN_K, column_position=1,
injection_volume_m3=2e-9, wavelength_m=254e-9, run_time_s=420.0, data_rate_hz=5.0)
SUPPLY = obj({'connected': BOOL, 'supply_pa': number('Pa', 0, 80e5), 'cylinder_co2_kg': number('kg', 0, 60), 'ambient_k': number('K', 288.15, 303.15)})
SUPPLY_EXAMPLE = dict(connected=True, supply_pa=57e5, cylinder_co2_kg=10.0, ambient_k=298.15)
BOTTLE = obj({'channel': enum(['B1', 'B2']), 'modifier': enum(MODIFIERS), 'volume_m3': number('m^3', 0, 2e-3)})
BOTTLE_EXAMPLE = dict(channel='B1', modifier='methanol', volume_m3=1e-3)
COLUMN_INSTALL = obj({'position': integer(1, N_COLUMN_POSITIONS), 'column': enum(list(COLUMN_IDS) + ['none'])})
VIAL = obj({'drawer': integer(1, N_DRAWERS), 'position': integer(1, N_VIAL_POSITIONS), 'volume_m3': number('m^3', 1e-8, VIAL_CAPACITY_M3),
'composition_mol_m3': {'type': 'object', 'additionalProperties': number('mol/m^3', 0, 1000), 'maxProperties': 16}})
VIAL_EXAMPLE = dict(drawer=1, position=1, volume_m3=1e-6, composition_mol_m3={'caffeine': 0.257, 'vanillin': 0.329})
VIAL_REF = obj({'drawer': integer(1, N_DRAWERS), 'position': integer(1, N_VIAL_POSITIONS)})
PEAK = obj({'retention_time_s': number('s', 0), 'area_au_s': number('AU*s'), 'height_au': number('AU'), 'width_half_height_s': number('s', 0)})
CHROM = obj({'run_id': TEXT, 'phase': enum(PHASES), 'elapsed_s': number('s', 0), 'time_s': arr(number('s', 0)),
'absorbance_au': arr(number('AU')), 'peaks': arr(PEAK), 'complete': BOOL, 'wavelength_m': nullable(number('m')),
'template_source': TEXT, 'evidence': TEXT, 'warnings': arr(TEXT)})
QUANT_IN = obj({'calibration': arr(obj({'concentration_mol_m3': number('mol/m^3', 0, 1000), 'area_au_s': number('AU*s')}), 2, 20),
'retention_window_s': arr(number('s', 0, 3600), 2, 2)})
QUANT_OUT = obj({'slope_au_s_m3_mol': number('AU*s*m^3/mol'), 'intercept_au_s': number('AU*s'), 'r_squared': number('1', 0, 1),
'peak_area_au_s': nullable(number('AU*s')), 'concentration_mol_m3': nullable(number('mol/m^3')), 'quality': TEXT})
TEMPLATE_OUT = obj({'substance_id': TEXT, 'name': TEXT, 'cas': nullable(TEXT), 'molecular_weight_g_mol': nullable(number('g/mol')),
'reference_retention_s': {'type': 'object', 'additionalProperties': {'type': 'object', 'additionalProperties': nullable(number('s', 0))}},
'uv_curve': BOOL, 'template_source': TEXT, 'evidence': TEXT, 'licence': TEXT})
LEDGER = obj({'vial_volume_m3': number('m^3', 0), 'injected_volume_m3': number('m^3', 0), 'volume_residual_m3': number('m^3'),
'species_residual_mol': number('mol'), 'injected_mol': number('mol', 0), 'column_mol': number('mol', 0), 'eluted_mol': number('mol', 0),
'modifier_drawn_m3': number('m^3', 0), 'modifier_residual_m3': number('m^3'), 'co2_used_kg': number('kg', 0), 'co2_residual_kg': number('kg'),
'waste_m3': number('m^3', 0)})
EMPTY = obj({})
# capability -> (input, output, components, meaning, kind, visibility, example, effects)
CAPS = {}
def _cap(key, inp, out, comps, meaning, kind='device_command', vis='agent', example=None, effects=()):
CAPS[key] = (inp, out, list(comps), meaning, kind, vis, example if example is not None else {}, list(effects))
_cap('power.set', obj({'enabled': BOOL}), obj({'enabled': BOOL}), ['pump_power_switch', 'sampler_power_switch', 'mct_power_switch', 'dad_power_switch', 'control_power_switch'],
'整套五个模块统一通断电(软件/机器人整体操作);断电停泵、取消运行,保留已注入物质', example={'enabled': True},
effects=['power.enabled', 'pump.enabled', 'run.phase'] + [f'power.{m}' for m in MODULES])
_cap('power.toggle', obj({'module': enum(MODULES)}), obj({'module': enum(MODULES), 'enabled': BOOL}),
['pump_power_switch', 'sampler_power_switch', 'mct_power_switch', 'dad_power_switch', 'control_power_switch'],
'单个模块前面板(控制模块为背面)电源开关翻转;任一模块断电取消进行中的运行,仅泵或控制模块断电清除泵运行目标', example={'module': 'pump'},
effects=['power.enabled', 'pump.enabled', 'run.phase'] + [f'power.{m}' for m in MODULES])
_cap('supply.configure', SUPPLY, obj({'configured': BOOL}), ['co2_inlet', 'control_housing'],
'宿主连接CO2气瓶:供气表压、可用CO2质量与环境温度(实验室管路边界,非机器人动作)', 'configuration', 'evaluator', SUPPLY_EXAMPLE,
['supply.connected', 'supply.pressure_pa', 'co2.ready'])
_cap('solvent.configure', BOTTLE, obj({'configured': BOOL}), ['bottle_b1', 'bottle_b2', 'solvent_cabinet'],
'宿主在溶剂柜放置改性剂瓶B1/B2(甲醇、甲醇+10 mmol/L氨、甲醇+2%水)及体积', 'configuration', 'evaluator', BOTTLE_EXAMPLE, ['solvent.b1', 'solvent.b2'])
_cap('column.install', COLUMN_INSTALL, obj({'position': integer(1, N_COLUMN_POSITIONS), 'column': enum(list(COLUMN_IDS) + ['none'])}),
['column_1', 'column_2', 'column_3', 'column_4', 'mct_door'],
'在柱温箱四个柱位安装/拆下模板库六种固定相之一(100×3.0 mm);要求柱温箱门打开且泵停', 'configuration', 'evaluator',
{'position': 1, 'column': 'silica'}, ['column.installed'])
_cap('sample.register_vial', VIAL, obj({'registered': BOOL}), ['drawer_1', 'drawer_2', 'drawer_3', 'drawer_4', 'vial_tray_1'],
'宿主登记已放入抽屉托盘的样品瓶:体积与真值组成(物质为模板库substance_id);要求该抽屉拉出', 'configuration', 'evaluator', VIAL_EXAMPLE,
['sample.vial_count'])
_cap('sample.remove_vial', VIAL_REF, obj({'returned_m3': number('m^3', 0)}), ['drawer_1', 'drawer_2', 'drawer_3', 'drawer_4'],
'取走样品瓶(返还剩余液体,已注入部分留在账本中);要求抽屉拉出', 'configuration', 'evaluator', {'drawer': 1, 'position': 1}, ['sample.vial_count'])
_cap('method.configure', METHOD, obj({'configured': BOOL, 'delay_volume_m3': number('m^3', DELAY_MIN_M3, DELAY_MAX_M3)}),
['pump_head_a', 'pump_head_b', 'column_valve', 'bpr_unit', 'flow_cell', 'sampler_housing'],
'写入方法目标:流量、改性剂通道与梯度表、背压与背压阀温度、柱温、柱位、进样体积、检测波长、运行时间与采样率;只写目标,实际值随step演化',
'configuration', 'agent', METHOD_EXAMPLE,
['method.configured', 'pump.flow_target_m3_s', 'bpr.target_pa', 'bpr.temperature_target_k', 'column.target_k', 'column.selected', 'detector.wavelength_m'])
_cap('pump.set', obj({'enabled': BOOL}), obj({'enabled': BOOL}), ['pump_head_a', 'pump_head_b', 'booster_unit'],
'泵运行目标(平衡/冲洗按方法初始组成);需全部模块通电、CO2就绪、已配置方法且所选柱位有柱', example={'enabled': True}, effects=['pump.enabled'])
for _m, (_sid, _unit, _hi, _comp) in MECH.items():
_arg = 'angle_rad' if _unit == 'rad' else 'position_m'
_cap(f'{_m}.set', obj({_arg: number(_unit, 0, _hi)}), obj({_arg: number(_unit, 0, _hi)}), [_comp],
'宿主/场景权威机构位置(0=关闭);运行或进样中拒绝打开进样器门、抽屉与柱温箱门', example={_arg: 0.0}, effects=[_sid])
_cap('run.start', VIAL_REF, obj({'phase': enum(PHASES), 'operation_id': TEXT}), ['needle_assembly', 'sampler_housing', 'column_valve', 'flow_cell'],
'从指定抽屉/瓶位进样并开始采集:系统就绪(流量、背压、柱温在容差内)、门和该抽屉关闭、瓶内余量足够;异步,按step推进到运行时间结束',
example={'drawer': 1, 'position': 1}, effects=['run.phase', 'run.elapsed_s', 'sample.vial_count'])
_cap('run.abort', EMPTY, obj({'phase': enum(PHASES)}), ['needle_assembly', 'flow_cell'], '取消当前进样/采集,保留已采集数据与物料账本',
effects=['run.phase'])
_cap('chromatogram.read', obj({'max_points': integer(10, 40000)}, required=[]), CHROM, ['flow_cell', 'dad_housing'],
'读取最近一次运行已采集的色谱图与峰表(无物质身份);纯读取,不推进时钟', 'query', example={'max_points': 2000})
_cap('peaks.quantify', QUANT_IN, QUANT_OUT, ['flow_cell'],
'用调用者提供的外标点(浓度-峰面积)线性拟合,并对最近完成运行中保留时间窗内最大峰定量;不访问样品真值', 'analysis', example=dict(
calibration=[dict(concentration_mol_m3=0.1, area_au_s=0.01), dict(concentration_mol_m3=0.5, area_au_s=0.05)], retention_window_s=[100.0, 200.0]))
_cap('template.read', obj({'substance_id': TEXT}), TEMPLATE_OUT, ['flow_cell'],
'查询公开的SFC保留时间模板(参考方法下六种柱×三种改性剂的实测首次进样保留时间);与样品身份无关', 'query', example={'substance_id': 'caffeine'})
_cap('ledger.read', EMPTY, LEDGER, ['vial_tray_1', 'column_1', 'waste_port', 'co2_inlet'],
'私有物料账本:样品瓶体积与物质(瓶→柱→废液/排气)、改性剂、CO2与废液守恒残差', 'query', 'evaluator')
UNSUPPORTED = ('chiral.separate', 'ms.detect', 'hardware.connect', 'sample_thermostat.set')
for _k, _z in (('chiral.separate', '手性柱与对映体分离:模板库无手性固定相实测数据,未实现'),
('ms.detect', '质谱联用:本配置只有DAD,MS未实现'),
('hardware.connect', '真实仪器(OpenLab CDS/RC.NET)连接未实现'),
('sample_thermostat.set', '进样器样品恒温器为选配件,本配置未建模')):
_cap(_k, EMPTY, EMPTY, ['sampler_housing' if 'sample' in _k else 'control_housing'], _z)
# state slots: key -> (schema, unit, origin, visibility, components, write (cap, arg) or None, meaning_zh)
SLOTS = {}
def _slot(key, schema, unit, origin, vis, comps, write=None, meaning=''):
SLOTS[key] = (schema, unit, origin, vis, list(comps), write, meaning)
_slot('power.enabled', BOOL, '1', 'derived', 'agent', ['pump_power_switch'], None, '五个模块全部通电时为true')
for _m in MODULES:
_slot(f'power.{_m}', BOOL, '1', 'setpoint', 'agent', [f'{_m}_power_switch'], None, f'{_m}模块电源开关状态')
_slot(f'status.{_m}', enum(['off', 'not_ready', 'ready', 'run', 'error']), '1', 'derived', 'agent', [f'{_m}_status_led'], None,
f'{_m}模块状态指示灯代理(off/not_ready黄/ready绿/run/error红)')
_slot('supply.connected', BOOL, '1', 'scene', 'agent', ['co2_inlet'], None, 'CO2气瓶是否接到控制模块进口')
_slot('supply.pressure_pa', number('Pa', 0), 'Pa', 'derived', 'agent', ['co2_inlet'], None, 'CO2供气表压(气瓶空时为0)')
_slot('co2.ready', BOOL, '1', 'derived', 'agent', ['chiller_unit'], None, '供气压力在40–70 bar且冷却器≤9 °C时CO2调理就绪')
_slot('chiller.temperature_k', number('K', 0), 'K', 'process_truth', 'evaluator', ['chiller_unit'], None, 'CO2再液化冷却器温度真值')
_slot('booster.pressure_pa', number('Pa', 0), 'Pa', 'process_truth', 'evaluator', ['booster_unit'], None, '增压泵出口表压真值(略低于柱头压力)')
_slot('method.configured', BOOL, '1', 'setpoint', 'agent', ['sampler_housing'])
_slot('pump.enabled', BOOL, '1', 'setpoint', 'agent', ['pump_head_a'], ('pump.set', 'enabled'))
_slot('pump.flow_target_m3_s', nullable(number('m^3/s', FLOW_MIN, FLOW_MAX)), 'm^3/s', 'setpoint', 'agent', ['pump_head_a'])
_slot('pump.flow_m3_s', number('m^3/s', 0), 'm^3/s', 'derived', 'agent', ['pump_head_a'], None, '泵实际总体积流量(泵头条件,未作压缩性换算)')
_slot('pump.modifier_fraction', number('1', 0, 1), '1', 'derived', 'agent', ['pump_head_b'], None, '泵出口改性剂体积分数(梯度表当前值)')
_slot('pump.pressure_pa', number('Pa', 0), 'Pa', 'process_truth', 'evaluator', ['pump_head_a'], None, '泵出口表压真值')
_slot('pump.indicated_pressure_pa', number('Pa', 0), 'Pa', 'derived', 'agent', ['pump_head_a'], None, '泵压力显示(0.1 bar量化)')
_slot('bpr.target_pa', nullable(number('Pa', BPR_MIN_PA, BPR_MAX_PA)), 'Pa', 'setpoint', 'agent', ['bpr_unit'])
_slot('bpr.pressure_pa', number('Pa', 0), 'Pa', 'process_truth', 'evaluator', ['bpr_unit'], None, '背压阀入口表压真值(系统出口压力)')
_slot('bpr.indicated_pressure_pa', number('Pa', 0), 'Pa', 'derived', 'agent', ['bpr_unit'], None, '背压显示(±0.25 bar精度代理,0.01 bar量化)')
_slot('bpr.temperature_target_k', nullable(number('K', BPR_T_MIN, BPR_T_MAX)), 'K', 'setpoint', 'agent', ['bpr_unit'])
_slot('bpr.temperature_k', number('K', 0), 'K', 'process_truth', 'evaluator', ['bpr_unit'], None, '背压阀加热头温度真值')
_slot('column.target_k', nullable(number('K', COL_T_ABS_MIN, COL_T_MAX)), 'K', 'setpoint', 'agent', ['mct_housing'])
_slot('column.temperature_k', number('K', 0), 'K', 'process_truth', 'evaluator', ['mct_housing'], None, '柱温箱温区温度真值(单节点)')
_slot('column.indicated_k', number('K', 0), 'K', 'derived', 'agent', ['mct_housing'], None, '柱温显示(0.1 K量化)')
_slot('column.selected', nullable(integer(1, N_COLUMN_POSITIONS)), '1', 'setpoint', 'agent', ['column_valve'])
_slot('column.installed', {'type': 'array', 'items': enum(list(COLUMN_IDS) + ['none']), 'minItems': 4, 'maxItems': 4}, '1', 'scene', 'agent',
['column_1', 'column_2', 'column_3', 'column_4'], None, '四个柱位安装的固定相类型(实验室配置,agent可见)')
_slot('mobile_phase.co2_density_kg_m3', nullable(number('kg/m^3', 0)), 'kg/m^3', 'process_truth', 'evaluator', ['column_1'], None,
'柱温与背压下纯CO2密度(Peng-Robinson)')
_slot('detector.wavelength_m', nullable(number('m', LAMBDA_MIN, LAMBDA_MAX)), 'm', 'setpoint', 'agent', ['flow_cell'])
_slot('detector.absorbance_au', number('AU'), 'AU', 'derived', 'agent', ['flow_cell'], None, '流通池当前吸光度(含噪声与漂移)')
_slot('system.ready', BOOL, '1', 'derived', 'agent', ['control_status_led'], None, '流量、背压、柱温均到达方法目标容差内')
_slot('system.fault', TEXT, '1', 'derived', 'agent', ['control_status_led'], None, '最近故障代码(空串=无)')
_slot('run.phase', enum(PHASES), '1', 'derived', 'agent', ['dad_status_led'])
_slot('run.elapsed_s', number('s', 0), 's', 'derived', 'agent', ['dad_status_led'], None, '自进样阀切换(采集零点)起的运行时间')
_slot('run.count', integer(0, 10 ** 9), '1', 'derived', 'agent', ['dad_status_led'], None, '已启动的运行次数')
_slot('sample.vial_count', integer(0, N_DRAWERS * N_VIAL_POSITIONS), '1', 'scene', 'agent', ['vial_tray_1'], None, '已登记样品瓶数')
for _m, (_sid, _unit, _hi, _comp) in MECH.items():
_slot(_sid, number(_unit, 0, _hi), _unit, 'scene', 'agent', [_comp], (f'{_m}.set', 'angle_rad' if _unit == 'rad' else 'position_m'))
_slot('solvent.b1', nullable(enum(MODIFIERS)), '1', 'scene', 'agent', ['bottle_b1'], None, 'B1瓶改性剂类型')
_slot('solvent.b2', nullable(enum(MODIFIERS)), '1', 'scene', 'agent', ['bottle_b2'], None, 'B2瓶改性剂类型')
_slot('truth.bottle_b1_m3', number('m^3', 0), 'm^3', 'process_truth', 'evaluator', ['bottle_b1'], None, 'B1瓶剩余改性剂体积')
_slot('truth.bottle_b2_m3', number('m^3', 0), 'm^3', 'process_truth', 'evaluator', ['bottle_b2'], None, 'B2瓶剩余改性剂体积')
_slot('truth.cylinder_co2_kg', number('kg', 0), 'kg', 'process_truth', 'evaluator', ['co2_inlet'], None, '气瓶剩余CO2质量')
_slot('truth.vented_co2_kg', number('kg', 0), 'kg', 'process_truth', 'evaluator', ['exhaust_port'], None, '经背压阀排出的CO2累计质量')
_slot('truth.waste_m3', number('m^3', 0), 'm^3', 'process_truth', 'evaluator', ['waste_port'], None, '废液(改性剂+样品溶剂)累计体积')
_slot('truth.column_mol', number('mol', 0), 'mol', 'process_truth', 'evaluator', ['column_1'], None, '已注入但尚未流出色谱柱的物质总量')
_slot('truth.eluted_mol', number('mol', 0), 'mol', 'process_truth', 'evaluator', ['waste_port'], None, '已流出到废液/排气的物质总量')
REFERENCE_ZH = {
'supply.pressure_pa': '表压;CO2供气相对环境大气压。厂家40–70 bar(580–1000 psi)按表压解释,这是本资产的假设。',
'booster.pressure_pa': '表压;相对环境大气压。', 'pump.pressure_pa': '表压;相对环境大气压,=背压+柱压降+柱外压降。',
'pump.indicated_pressure_pa': '表压;相对环境大气压。厂家600 bar上限按表压解释。',
'bpr.target_pa': '表压;背压阀设定相对环境大气压(厂家100–400 bar)。', 'bpr.pressure_pa': '表压;相对环境大气压。',
'bpr.indicated_pressure_pa': '表压;相对环境大气压。',
'pump.flow_target_m3_s': '泵头条件下的总体积流量(CO2+改性剂),与厂家mL/min设定一致;未作可压缩性换算。',
'pump.flow_m3_s': '泵头条件下的总体积流量(CO2+改性剂);色谱模型按柱内体积流量近似使用。',
'mobile_phase.co2_density_kg_m3': '纯CO2在柱温与背压(绝压=表压+101325 Pa)下的Peng-Robinson密度;忽略改性剂对密度的影响。',
}
# ------------------------------------------------------------------------------------------------------ physical models
def co2_density(temperature_k, pressure_abs_pa):
"""Peng-Robinson density of pure CO2 (dense root). NIST critical constants; ~5-10 % below reference data in the dense region."""
a = 0.45724 * R_GAS ** 2 * CO2_TC ** 2 / CO2_PC
b = 0.07780 * R_GAS * CO2_TC / CO2_PC
kappa = 0.37464 + 1.54226 * CO2_OMEGA - 0.26992 * CO2_OMEGA ** 2
alpha = (1 + kappa * (1 - math.sqrt(temperature_k / CO2_TC))) ** 2
A = a * alpha * pressure_abs_pa / (R_GAS * temperature_k) ** 2
B = b * pressure_abs_pa / (R_GAS * temperature_k)
roots = np.roots([1.0, -(1 - B), A - 3 * B ** 2 - 2 * B, -(A * B - B ** 2 - B ** 3)])
real = sorted(r.real for r in roots if abs(r.imag) < 1e-9 and r.real > B)
z = real[0]
return float(pressure_abs_pa * CO2_M / (z * R_GAS * temperature_k))
@lru_cache(maxsize=1)
def _rho_ref():
return co2_density(REF_COLUMN_K, REF_BPR_PA + 101325.0)
def void_time_s(length_m, inner_diameter_m, flow_m3_s):
return TOTAL_POROSITY * math.pi * (inner_diameter_m / 2) ** 2 * length_m / flow_m3_s
def delay_volume_m3(bpr_pa):
"""Documented 600-900 uL 'depending on back pressure'; linear in the 100-400 bar BPR range (mapping is an assumption)."""
f = min(1.0, max(0.0, (bpr_pa - BPR_MIN_PA) / (BPR_MAX_PA - BPR_MIN_PA)))
return DELAY_MIN_M3 + f * (DELAY_MAX_M3 - DELAY_MIN_M3)
def mixture_viscosity(phi):
phi = min(1.0, max(0.0, phi))
return math.exp(phi * math.log(ETA_MEOH_PA_S) + (1 - phi) * math.log(ETA_CO2_PA_S))
def column_pressure_drop(flow_m3_s, phi, column):
"""Kozeny-Carman drop over the packed bed (Pa)."""
area = math.pi * (column['inner_diameter_m'] / 2) ** 2
u_s = flow_m3_s / area
e = BED_POROSITY
return 180.0 * mixture_viscosity(phi) * u_s * column['length_m'] * (1 - e) ** 2 / (e ** 3 * column['particle_m'] ** 2)
def program_value(program, t):
"""Piecewise-linear modifier fraction; holds the first value before t=0 and the last after the table."""
times = np.array([p[0] for p in program], float)
vals = np.array([p[1] for p in program], float)
return np.interp(t, times, vals)
def migrate(a, m, program, t0_s, delay_s, t_end_s, dt_s=0.05, extra_ln_k=0.0):
"""Vectorised band migration under a gradient. a: array of log10 k at phi = 1. Returns (t_R, k at elution, phi at elution);
NaN where the band has not left the column by t_end_s."""
a = np.atleast_1d(np.asarray(a, float))
z = np.zeros_like(a)
tr = np.full_like(a, np.nan)
ke = np.full_like(a, np.nan)
pe = np.full_like(a, np.nan)
times = np.array([p[0] for p in program], float)
vals = np.array([p[1] for p in program], float)
t = 0.0
while t < t_end_s and np.isnan(tr).any():
phi = np.interp(t - delay_s - z * t0_s, times, vals)
k = 10.0 ** (a - m * np.log10(np.maximum(phi, PHI_MIN))) * math.exp(extra_ln_k)
v = 1.0 / (t0_s * (1.0 + k))
z_new = z + v * dt_s
done = (z_new >= 1.0) & np.isnan(tr)
if done.any():
frac = (1.0 - z[done]) / (z_new[done] - z[done])
tr[done] = t + frac * dt_s
ke[done] = k[done]
pe[done] = phi[done]
z = np.where(np.isnan(tr), z_new, z)
t += dt_s
return tr, ke, pe
@lru_cache(maxsize=1)
def library():
data = json.loads((ROOT / LIBRARY_REL).read_text(encoding='utf-8'))
return data
@lru_cache(maxsize=1)
def library_sha256():
return hashlib.sha256((ROOT / LIBRARY_REL).read_bytes()).hexdigest()
@lru_cache(maxsize=1)
def columns():
"""Stationary phases of the source data by id (stored as a list in the library so that column ids are never mistaken for compound ids)."""
return {c['column_id']: c for c in library()['columns']}
@lru_cache(maxsize=1)
def templates():
return {r['substance_id']: r for r in library()['templates']}
def epsilon(sid, wavelength_m):
"""(epsilon m^2/mol, evidence) at the wavelength: NIST curve when the library has one covering it, else the flagged assumption."""
uv = templates()[sid].get('uv_vis')
if uv and uv['wavelength_m'][0] <= wavelength_m <= uv['wavelength_m'][-1]:
log_eps = float(np.interp(wavelength_m, uv['wavelength_m'], uv['log10_epsilon_l_mol_cm']))
return 10.0 ** log_eps * 0.1, 'measured_nist_uv' # L/(mol cm) -> m^2/mol
return ASSUMED_EPSILON_M2_MOL, 'assumption'
def baseline(time_s, signal, segment_s=30.0):
"""Slowly varying baseline: 20th percentile of each segment, linearly interpolated (removes detector drift before peak picking)."""
t = np.asarray(time_s, float)
y = np.asarray(signal, float)
if len(t) < 3:
return np.zeros_like(y)
edges = np.arange(t[0], t[-1] + segment_s, segment_s)
cx, cy = [], []
for lo, hi in zip(edges[:-1], edges[1:]):
sel = (t >= lo) & (t < hi)
if sel.sum() >= 3:
cx.append(float(t[sel].mean()))
cy.append(float(np.percentile(y[sel], 20)))
if not cx:
return np.full_like(y, float(np.percentile(y, 20)))
return np.interp(t, cx, cy)
def detect_peaks(time_s, signal, threshold):
"""Baseline-corrected local maxima above threshold; area by trapezoid between the neighbouring minima (or the trace ends)."""
t = np.asarray(time_s, float)
y = np.asarray(signal, float) - baseline(time_s, signal)
peaks = []
if len(y) < 5:
return peaks
i = 1
while i < len(y) - 1:
if y[i] >= threshold and y[i] >= y[i - 1] and y[i] > y[i + 1]:
lo = i
while lo > 0 and y[lo - 1] <= y[lo] and y[lo - 1] > threshold * 0.2:
lo -= 1
hi = i
while hi < len(y) - 1 and y[hi + 1] <= y[hi] and y[hi + 1] > threshold * 0.2:
hi += 1
seg_t, seg_y = t[max(0, lo - 1):hi + 2], y[max(0, lo - 1):hi + 2]
area = float(np.trapezoid(seg_y, seg_t)) if len(seg_t) > 1 else 0.0
half = y[i] / 2
above = np.where(seg_y >= half)[0]
width = float(seg_t[above[-1]] - seg_t[above[0]]) if len(above) > 1 else 0.0
peaks.append(dict(retention_time_s=float(t[i]), area_au_s=area, height_au=float(y[i]), width_half_height_s=width))
i = hi + 1
else:
i += 1
return peaks
def validate(schema, value):
if 'anyOf' in schema:
for s in schema['anyOf']:
try:
validate(s, value)
return
except ActionRejected:
pass
raise ActionRejected('INVALID_ARGUMENT')
t = schema.get('type')
if t in ('number', 'integer'):
if isinstance(value, bool) or not isinstance(value, (int, float)) or not math.isfinite(value):
raise ActionRejected('INVALID_ARGUMENT')
if t == 'integer' and (not isinstance(value, int)):
raise ActionRejected('INVALID_ARGUMENT')
if value < schema.get('minimum', -math.inf) or value > schema.get('maximum', math.inf):
raise ActionRejected('INVALID_ARGUMENT')
elif t == 'boolean':
if type(value) is not bool:
raise ActionRejected('INVALID_ARGUMENT')
elif t == 'string':
if not isinstance(value, str):
raise ActionRejected('INVALID_ARGUMENT')
elif t == 'null':
if value is not None:
raise ActionRejected('INVALID_ARGUMENT')
elif t == 'array':
if not isinstance(value, list) or not schema.get('minItems', 0) <= len(value) <= schema.get('maxItems', math.inf):
raise ActionRejected('INVALID_ARGUMENT')
for v in value:
validate(schema['items'], v)
elif t == 'object':
if not isinstance(value, dict) or not set(schema.get('required', [])) <= set(value):
raise ActionRejected('INVALID_ARGUMENT')
if len(value) > schema.get('maxProperties', math.inf):
raise ActionRejected('INVALID_ARGUMENT')
props = schema.get('properties', {})
for k, v in value.items():
if not isinstance(k, str):
raise ActionRejected('INVALID_ARGUMENT')
sub = props.get(k, schema.get('additionalProperties', True))
if sub is False:
raise ActionRejected('INVALID_ARGUMENT')
if isinstance(sub, dict):
validate(sub, v)
if 'enum' in schema and value not in schema['enum']:
raise ActionRejected('INVALID_ARGUMENT')
# --------------------------------------------------------------------------------------------------------------- runtime
class Agilent1260infinityRuntime:
"""Process model of one SFC system instance (host-owned clock)."""
def __init__(self, instance_id='sfc_01'):
self.instance_id = instance_id
self.time_s = 0.0
self.revision = 0
self.ambient_k = 298.15
self.power = {m: False for m in MODULES}
self.supply = dict(connected=False, supply_pa=0.0, cylinder_co2_kg=0.0)
self.co2_initial_kg = 0.0
self.vented_co2_kg = 0.0
self.bottles = {'B1': None, 'B2': None}
self.modifier_loaded_m3 = 0.0
self.modifier_drawn_m3 = 0.0
self.waste_m3 = 0.0
self.columns = {p: 'none' for p in range(1, N_COLUMN_POSITIONS + 1)}
self.mech = {m: 0.0 for m in MECH}
self.vials = {}
self.vial_loaded_m3 = 0.0
self.vial_returned_m3 = 0.0
self.injected_m3 = 0.0
self.method = None
self.pump_enabled = False
self.chiller_k = 298.15
self.booster_pa = 0.0
self.flow = 0.0
self.pump_pa = 0.0
self.bpr_pa = 0.0
self.bpr_k = 298.15
self.column_k = 298.15
self.fault = ''
self.phase = 'idle'
self.run = None
self.run_count = 0
self.operation_id = None
self.bands = [] # {'sid','mol','t_r','sigma','eluted'}
self.injected_mol = 0.0
self.eluted_mol = 0.0
self.absorbance = 0.0
self._principals = {'__public_agent__': 'agent'}
self._requests = {}
self._owners = {}
# ---- principals / sessions -------------------------------------------------------------------------
def register_principal(self, principal_id, visibility='agent'):
if visibility not in ('agent', 'evaluator', 'debug'):
raise ActionRejected('INVALID_ARGUMENT')
if principal_id in self._principals:
raise ActionRejected('REQUEST_CONFLICT')
self._principals[principal_id] = visibility
def session(self, principal_id='__public_agent__'):
if principal_id not in self._principals:
raise ActionRejected('ACCESS_DENIED')
return Agilent1260infinitySession(self, principal_id)
def describe(self):
return self.session().describe(instance_id=self.instance_id)
# ---- derived quantities ---------------------------------------------------------------------------------
def _column(self):
if not self.method:
return None
cid = self.columns[self.method['column_position']]
return None if cid == 'none' else dict(columns()[cid], id=cid)
def _program(self):
return [(r['time_s'], r['modifier_fraction']) for r in self.method['program']]
def _phi_now(self):
if not self.method:
return 0.0
prog = self._program()
if self.phase == 'running' and self.run:
return float(program_value(prog, self.run['elapsed']))
return float(prog[0][1])
def _all_powered(self):
return all(self.power.values())
def _co2_ready(self):
return (self.supply['connected'] and SUPPLY_MIN_PA <= self.supply['supply_pa'] <= SUPPLY_MAX_PA + 1e5
and self.supply['cylinder_co2_kg'] > 0 and self.chiller_k <= 282.15 and self.power['control'])
def _ready(self):
if not (self.method and self.pump_enabled and self._all_powered() and self._co2_ready() and not self.fault):
return False
m = self.method
return (self.flow >= READY_FLOW_FRACTION * m['flow_m3_s'] and abs(self.bpr_pa - m['bpr_pa']) <= READY_TOL_PA
and abs(self.column_k - m['column_temperature_k']) <= READY_TOL_K)
def _status(self, module):
if not self.power[module]:
return 'off'
if self.fault:
return 'error'
if self.phase in ('injecting', 'running'):
return 'run'
return 'ready' if self._ready() else 'not_ready'
def _density(self):
if not self.method:
return None
return co2_density(self.column_k, max(self.bpr_pa, 1e5) + 101325.0)
def _values(self):
m = self.method or {}
v = {'power.enabled': self._all_powered()}
for mod in MODULES:
v[f'power.{mod}'] = self.power[mod]
v[f'status.{mod}'] = self._status(mod)
v.update({
'supply.connected': self.supply['connected'],
'supply.pressure_pa': self.supply['supply_pa'] if self.supply['connected'] and self.supply['cylinder_co2_kg'] > 0 else 0.0,
'co2.ready': bool(self._co2_ready()), 'chiller.temperature_k': self.chiller_k, 'booster.pressure_pa': self.booster_pa,
'method.configured': self.method is not None, 'pump.enabled': self.pump_enabled,
'pump.flow_target_m3_s': m.get('flow_m3_s'), 'pump.flow_m3_s': self.flow,
'pump.modifier_fraction': self._phi_now() if self.pump_enabled else 0.0,
'pump.pressure_pa': self.pump_pa, 'pump.indicated_pressure_pa': round(self.pump_pa / 1e4) * 1e4,
'bpr.target_pa': m.get('bpr_pa'), 'bpr.pressure_pa': self.bpr_pa, 'bpr.indicated_pressure_pa': round(self.bpr_pa / 1e3) * 1e3,
'bpr.temperature_target_k': m.get('bpr_temperature_k'), 'bpr.temperature_k': self.bpr_k,
'column.target_k': m.get('column_temperature_k'), 'column.temperature_k': self.column_k,
'column.indicated_k': round(self.column_k * 10) / 10, 'column.selected': m.get('column_position'),
'column.installed': [self.columns[p] for p in range(1, N_COLUMN_POSITIONS + 1)],
'mobile_phase.co2_density_kg_m3': self._density(), 'detector.wavelength_m': m.get('wavelength_m'),
'detector.absorbance_au': self.absorbance, 'system.ready': self._ready(), 'system.fault': self.fault,
'run.phase': self.phase, 'run.elapsed_s': self.run['elapsed'] if self.run else 0.0, 'run.count': self.run_count,
'sample.vial_count': len(self.vials),
'solvent.b1': (self.bottles['B1'] or {}).get('modifier'), 'solvent.b2': (self.bottles['B2'] or {}).get('modifier'),
'truth.bottle_b1_m3': (self.bottles['B1'] or {}).get('volume_m3', 0.0), 'truth.bottle_b2_m3': (self.bottles['B2'] or {}).get('volume_m3', 0.0),
'truth.cylinder_co2_kg': self.supply['cylinder_co2_kg'], 'truth.vented_co2_kg': self.vented_co2_kg, 'truth.waste_m3': self.waste_m3,
'truth.column_mol': sum(b['mol'] for b in self.bands if not b['eluted']), 'truth.eluted_mol': self.eluted_mol})
for name, (sid, *_r) in MECH.items():
v[sid] = self.mech[name]
return v
def read(self, visibility='agent'):
return copy.deepcopy({k: val for k, val in self._values().items() if SLOTS[k][3] == 'agent' or visibility in ('evaluator', 'debug')})
def _ledger(self):
vial = sum(x['volume_m3'] for x in self.vials.values())
species_in_vials = sum(x['volume_m3'] * sum(x['composition'].values()) for x in self.vials.values())
column = sum(b['mol'] for b in self.bands if not b['eluted'])
bottles = sum((b or {}).get('volume_m3', 0.0) for b in self.bottles.values())
return dict(vial_volume_m3=vial, injected_volume_m3=self.injected_m3,
volume_residual_m3=self.vial_loaded_m3 - vial - self.injected_m3 - self.vial_returned_m3,
species_residual_mol=self._species_loaded - species_in_vials - self.injected_mol - self._species_returned,
injected_mol=self.injected_mol, column_mol=column, eluted_mol=self.eluted_mol,
modifier_drawn_m3=self.modifier_drawn_m3, modifier_residual_m3=self.modifier_loaded_m3 - bottles - self.modifier_drawn_m3,
co2_used_kg=self.vented_co2_kg, co2_residual_kg=self.co2_initial_kg - self.supply['cylinder_co2_kg'] - self.vented_co2_kg,
waste_m3=self.waste_m3)
_species_loaded = 0.0
_species_returned = 0.0
# ---- capabilities -----------------------------------------------------------------------------------------
def invoke(self, capability, **a):
if capability not in CAPS:
raise ActionRejected('UNKNOWN_CAPABILITY')
if capability in UNSUPPORTED:
raise ActionRejected('UNSUPPORTED')
validate(CAPS[capability][0], a)
if CAPS[capability][4] in ('query', 'analysis'): # pure reads / caller-data analysis: no state snapshot needed
result = self._invoke(capability, a)
validate(CAPS[capability][1], result)
return copy.deepcopy(result)
before = copy.deepcopy({k: v for k, v in self.__dict__.items() if k not in ('_principals', '_requests', '_owners')})
try:
result = self._invoke(capability, a)
validate(CAPS[capability][1], result)
except Exception:
self.__dict__.update(before)
raise
self.revision += 1
return copy.deepcopy(result)
def _busy(self):
return self.phase in ('injecting', 'running')
def _invoke(self, k, a):
if k == 'chromatogram.read':
return self._chromatogram(a.get('max_points', 2000))
if k == 'ledger.read':
return self._ledger()
if k == 'template.read':
return self._template(a['substance_id'])
if k == 'peaks.quantify':
return self._quantify(a)
if k == 'power.set':
for m in MODULES:
self.power[m] = a['enabled']
if not a['enabled']:
self._power_lost('control')
return {'enabled': a['enabled']}
if k == 'power.toggle':
self.power[a['module']] = not self.power[a['module']]
if not self.power[a['module']]:
self._power_lost(a['module'])
return {'module': a['module'], 'enabled': self.power[a['module']]}
if k == 'supply.configure':
if self.pump_enabled:
raise ActionRejected('PRECONDITION_FAILED')
if a['connected'] and not (SUPPLY_MIN_PA <= a['supply_pa'] <= SUPPLY_MAX_PA):
raise ActionRejected('INVALID_ARGUMENT')
self.supply = dict(connected=a['connected'], supply_pa=a['supply_pa'] if a['connected'] else 0.0, cylinder_co2_kg=a['cylinder_co2_kg'])
self.co2_initial_kg = a['cylinder_co2_kg'] + self.vented_co2_kg
if self.ambient_k != a['ambient_k'] and not any(self.power.values()):
self.chiller_k = self.bpr_k = self.column_k = a['ambient_k']
self.ambient_k = a['ambient_k']
return {'configured': True}
if k == 'solvent.configure':
if self.pump_enabled:
raise ActionRejected('PRECONDITION_FAILED')
old = (self.bottles[a['channel']] or {}).get('volume_m3', 0.0)
self.modifier_loaded_m3 += a['volume_m3'] - old
self.bottles[a['channel']] = dict(modifier=a['modifier'], volume_m3=a['volume_m3'])
return {'configured': True}
if k == 'column.install':
if self.pump_enabled or self._busy() or self.mech['mct_door'] < 0.5:
raise ActionRejected('PRECONDITION_FAILED')
self.columns[a['position']] = a['column']
return dict(a)
if k == 'sample.register_vial':
if self.mech[f"drawer_{a['drawer']}"] < 0.15 or (a['drawer'], a['position']) in self.vials:
raise ActionRejected('PRECONDITION_FAILED')
comp = a['composition_mol_m3']
if not comp or any(s not in templates() for s in comp):
raise ActionRejected('INVALID_ARGUMENT')
self.vials[(a['drawer'], a['position'])] = dict(volume_m3=a['volume_m3'], composition=dict(comp))
self.vial_loaded_m3 += a['volume_m3']
self._species_loaded += a['volume_m3'] * sum(comp.values())
return {'registered': True}
if k == 'sample.remove_vial':
key = (a['drawer'], a['position'])
if key not in self.vials or self.mech[f"drawer_{a['drawer']}"] < 0.15:
raise ActionRejected('PRECONDITION_FAILED')
v = self.vials.pop(key)
self.vial_returned_m3 += v['volume_m3']
self._species_returned += v['volume_m3'] * sum(v['composition'].values())
return {'returned_m3': v['volume_m3']}
if k == 'method.configure':
if self._busy():
raise ActionRejected('BUSY')
prog = a['program']
if prog[0]['time_s'] != 0.0 or any(prog[i + 1]['time_s'] <= prog[i]['time_s'] for i in range(len(prog) - 1)):
raise ActionRejected('INVALID_ARGUMENT')
if a['column_temperature_k'] < max(COL_T_ABS_MIN, self.ambient_k - 10.0):
raise ActionRejected('INVALID_ARGUMENT')
n = a['injection_volume_m3'] / INJ_STEP
if abs(n - round(n)) > 1e-6:
raise ActionRejected('INVALID_ARGUMENT')
if self.pump_enabled: # the running pump cannot be switched to an empty bottle or an empty column position
bottle = self.bottles[a['modifier_channel']]
if not bottle or bottle['volume_m3'] <= 0 or self.columns[a['column_position']] == 'none':
raise ActionRejected('PRECONDITION_FAILED')
self.method = copy.deepcopy(a)
return {'configured': True, 'delay_volume_m3': delay_volume_m3(a['bpr_pa'])}
if k == 'pump.set':
if a['enabled']:
if not (self._all_powered() and self._co2_ready() and self.method and self._column()):
raise ActionRejected('PRECONDITION_FAILED')
bottle = self.bottles[self.method['modifier_channel']]
if not bottle or bottle['volume_m3'] <= 0:
raise ActionRejected('PRECONDITION_FAILED')
self.fault = ''
elif self._busy():
self._finish('cancelled')
self.pump_enabled = a['enabled']
return {'enabled': a['enabled']}
if k.endswith('.set') and k[:-4] in MECH:
name = k[:-4]
arg = 'angle_rad' if MECH[name][1] == 'rad' else 'position_m'
opening = a[arg] > 1e-6
if opening and self._busy(): # doors / drawers / oven door stay closed while injecting or acquiring
raise ActionRejected('BUSY')
self.mech[name] = a[arg]
return dict(a)
if k == 'run.start':
return self._start(a)
if k == 'run.abort':
if self._busy():
self._finish('cancelled')
return {'phase': self.phase}
raise ActionRejected('UNKNOWN_CAPABILITY')
def _power_lost(self, module):
"""A module lost power: any run in progress is cancelled (every module takes part in a run); the pump target is cleared only when
the pump itself or the control module (CO2 conditioning, BPR) is off - the other modules are independent of the pump."""
if self._busy():
self._finish('cancelled')
if module in ('pump', 'control'):
self.pump_enabled = False
def _start(self, a):
if self._busy():
raise ActionRejected('BUSY')
key = (a['drawer'], a['position'])
if not self._ready() or self.mech['sampler_door'] > 1e-6 or self.mech[f"drawer_{a['drawer']}"] > 1e-6:
raise ActionRejected('PRECONDITION_FAILED')
vial = self.vials.get(key)
m = self.method
if vial is None or vial['volume_m3'] < m['injection_volume_m3'] + VIAL_DEAD_VOLUME_M3:
raise ActionRejected('PRECONDITION_FAILED')
bottle = self.bottles[m['modifier_channel']]
if not bottle or self._column() is None:
raise ActionRejected('PRECONDITION_FAILED')
need = sum(m['flow_m3_s'] * float(program_value(self._program(), t)) * 1.0 for t in np.arange(0, m['run_time_s'] + INJECT_CYCLE_S, 1.0))
if bottle['volume_m3'] < need:
raise ActionRejected('PRECONDITION_FAILED')
self.run_count += 1
self.operation_id = f'{self.instance_id}:run:{self.run_count}'
self.run = dict(run_id=self.operation_id, vial=key, elapsed=0.0, inject_left=INJECT_CYCLE_S, t=[], y=[], peaks=[], warnings=[],
wavelength=m['wavelength_m'], next_sample=0.0, rng=np.random.default_rng(
int(hashlib.sha256(self.operation_id.encode()).hexdigest()[:12], 16)), drift0=0.0)
self.phase = 'injecting'
return {'phase': self.phase, 'operation_id': self.operation_id}
def _inject(self):
"""End of the injection cycle: draw the volume, create the bands from the measured templates and the current conditions."""
m, run = self.method, self.run
vial = self.vials[run['vial']]
vol = m['injection_volume_m3']
vial['volume_m3'] -= vol
self.injected_m3 += vol
self.waste_m3 += vol # the sample solvent leaves with the mobile phase
col = self._column()
modifier = self.bottles[m['modifier_channel']]['modifier']
t0 = void_time_s(col['length_m'], col['inner_diameter_m'], m['flow_m3_s'])
delay = delay_volume_m3(m['bpr_pa']) / m['flow_m3_s']
rho = co2_density(self.column_k, m['bpr_pa'] + 101325.0)
extra = -DENSITY_COEFF * (rho / _rho_ref() - 1.0)
n_plates = col['length_m'] / (PLATE_HEIGHT_DP * col['particle_m'])
extra_var = ((FLOW_CELL_VOLUME_M3 / m['flow_m3_s']) ** 2 + (vol / m['flow_m3_s']) ** 2) / 12.0 # flow cell + injection plug (s^2)
sids, a_vals, mols = [], [], []
for sid, c in vial['composition'].items():
moles = c * vol
self.injected_mol += moles
entry = templates()[sid]['retention'][col['id']][modifier]
if entry['status'] != 'eluted' or 'model_fit' not in entry:
self.bands.append(dict(sid=sid, mol=moles, t_r=None, sigma=None, eps=0.0, eluted=False, done=True, run=run['run_id'],
evidence='not_eluted_in_source_data' if entry['status'] != 'eluted' else 'outside_reference_program'))
continue
sids.append(sid)
a_vals.append(entry['model_fit']['log10_k_at_phi_1'])
mols.append(moles)
if sids:
tr, ke, _ = migrate(np.array(a_vals), LOGLOG_SLOPE_M, self._program(), t0, delay, m['run_time_s'] + 600.0, dt_s=0.05, extra_ln_k=extra)
for sid, t_r, k_e, moles in zip(sids, tr, ke, mols):
eps, ev = epsilon(sid, m['wavelength_m'])
if np.isnan(t_r):
self.bands.append(dict(sid=sid, mol=moles, t_r=None, sigma=None, eps=eps, eluted=False, done=True, run=run['run_id'],
evidence='retained_beyond_run'))
continue
sigma = math.sqrt((t0 * (1.0 + float(k_e))) ** 2 / n_plates + extra_var)
# flow_s: flow-weighted time this band has travelled since injection (it keeps migrating whenever the pump delivers, also after
# its run ended -> late eluters reach the waste and appear as carry-over peaks in a later run)
self.bands.append(dict(sid=sid, mol=moles, t_r=float(t_r), sigma=sigma, eps=eps, wl=m['wavelength_m'], eluted=False, done=False,
flow_s=0.0, flow_ref=m['flow_m3_s'], evidence=ev, run=run['run_id']))
run['t0'] = t0
run['delay_s'] = delay
run['flow'] = m['flow_m3_s']
def _signal(self, t):
"""Absorbance at run time t (inside the current step): every migrating band, including carry-over from earlier runs."""
run = self.run
total = 0.0
lag = run['elapsed'] - t # sample time lies `lag` seconds before the end of this step
for b in self.bands:
if b['t_r'] is None or b['done']:
continue
fs = b['flow_s'] - lag * (self.flow / b['flow_ref'])
dz = (fs - b['t_r']) / b['sigma']
if abs(dz) < 8:
eps = b['eps'] if b['wl'] == run['wavelength'] else epsilon(b['sid'], run['wavelength'])[0]
c = b['mol'] / (run['flow'] * b['sigma'] * math.sqrt(2 * math.pi)) * math.exp(-0.5 * dz * dz)
total += eps * FLOW_CELL_PATH_M * c
noise = float(run['rng'].normal(0.0, DAD_NOISE_AU / 2.5))
return total + noise + DAD_DRIFT_AU_S * t
def _finish(self, phase):
run = self.run
self.phase = phase
if run is not None:
thr = 10 * DAD_NOISE_AU
run['peaks'] = detect_peaks(run['t'], run['y'], thr) if phase == 'succeeded' else []
self.absorbance = 0.0
def _chromatogram(self, max_points):
run = self.run
if run is None:
return dict(run_id='', phase=self.phase, elapsed_s=0.0, time_s=[], absorbance_au=[], peaks=[], complete=False, wavelength_m=None,
template_source=LIBRARY_REL, evidence='no run', warnings=[])
n = len(run['t'])
step = max(1, math.ceil(n / max_points))
return dict(run_id=run['run_id'], phase=self.phase, elapsed_s=run['elapsed'], time_s=list(run['t'][::step]), absorbance_au=list(run['y'][::step]),
peaks=copy.deepcopy(run['peaks']), complete=self.phase == 'succeeded', wavelength_m=run['wavelength'],
template_source=f'{LIBRARY_REL}#sha256={library_sha256()[:16]}',
evidence='retention: measured CC BY 4.0 SFC data (Waters UPC2) transferred with a derived migration model; '
'absorbance: NIST UV curves where available, else assumed; peak shape: assumed plate height',
warnings=list(run['warnings']) + ['retention transferred from another SFC system; dwell volume and column lot effects are modelled, not measured',
'peak responses use NIST UV curves where the template library holds one, otherwise an assumed molar '
'absorptivity; per-peak response evidence is evaluator-only',
'quantitation requires the caller\'s own external calibration'])
def _template(self, sid):
rec = templates().get(sid)
if rec is None:
raise ActionRejected('UNKNOWN_REFERENCE')
ref = {c: {m: v['t_r_first_s'] for m, v in mods.items()} for c, mods in rec['retention'].items()}
return dict(substance_id=sid, name=rec['name'], cas=rec['cas'], molecular_weight_g_mol=rec['molecular_weight_g_mol'], reference_retention_s=ref,
uv_curve=rec['uv_vis'] is not None, template_source=f'{LIBRARY_REL}#{sid}', evidence=rec['evidence'],
licence=rec['source']['licence'])
def _quantify(self, a):
x = np.array([p['concentration_mol_m3'] for p in a['calibration']], float)
y = np.array([p['area_au_s'] for p in a['calibration']], float)
if np.ptp(x) <= 0:
raise ActionRejected('INVALID_CALIBRATION')
slope, intercept = np.polyfit(x, y, 1)
ss = float(np.sum((y - y.mean()) ** 2))
r2 = 1.0 - float(np.sum((y - (slope * x + intercept)) ** 2)) / ss if ss > 0 else 0.0
if slope <= 0:
raise ActionRejected('INVALID_CALIBRATION')
lo, hi = sorted(a['retention_window_s'])
peaks = [p for p in (self.run['peaks'] if self.run and self.phase == 'succeeded' else []) if lo <= p['retention_time_s'] <= hi]
if not peaks:
return dict(slope_au_s_m3_mol=float(slope), intercept_au_s=float(intercept), r_squared=max(0.0, min(1.0, r2)), peak_area_au_s=None,
concentration_mol_m3=None, quality='no_peak_in_window_or_no_completed_run')
p = max(peaks, key=lambda q: q['area_au_s'])
conc = (p['area_au_s'] - intercept) / slope
quality = 'ok' if x.min() <= conc <= x.max() and r2 >= 0.99 else 'extrapolated_or_poor_fit'
return dict(slope_au_s_m3_mol=float(slope), intercept_au_s=float(intercept), r_squared=max(0.0, min(1.0, r2)), peak_area_au_s=p['area_au_s'],
concentration_mol_m3=float(conc), quality=quality)
# ---- clock ------------------------------------------------------------------------------------------------
def step(self, dt_s):
if isinstance(dt_s, bool) or not isinstance(dt_s, (int, float)) or not math.isfinite(dt_s) or dt_s <= 0:
raise ValueError('dt_s must be finite and positive')
left = float(dt_s)
while left > 1e-12:
h = min(left, 0.1 if self._busy() else 1.0)
self._advance(h)
left -= h
self.revision += 1
return self.read('evaluator')
def _advance(self, h):
amb = self.ambient_k
m = self.method
# control module: chiller + booster
target = CHILLER_TARGET_K if (self.power['control'] and self.supply['connected']) else amb
self.chiller_k = target + (self.chiller_k - target) * math.exp(-h / CHILLER_TAU_S)
# BPR heater and column oven
bt = m['bpr_temperature_k'] if (m and self.power['control']) else amb
self.bpr_k = bt + (self.bpr_k - bt) * math.exp(-h / BPR_HEAT_TAU_S)
ct = m['column_temperature_k'] if (m and self.power['mct']) else amb
if self.mech['mct_door'] > 0.05 and self.power['mct']:
ct = amb + 0.5 * (ct - amb) # door open: oven cannot hold its set point (assumption)
tau = COL_TAU_HEAT_S if ct > self.column_k else COL_TAU_COOL_S
self.column_k = ct + (self.column_k - ct) * math.exp(-h / tau)
# pump, pressures
running = self.pump_enabled and m is not None and self._all_powered()
if running and not self._co2_ready():
self.fault = 'CO2_SUPPLY'
self.pump_enabled = running = False
if self._busy():
self._finish('failed')
col = self._column()
f_target = m['flow_m3_s'] if running and col else 0.0
self.flow = f_target + (self.flow - f_target) * math.exp(-h / FLOW_TAU_S)
phi = self._phi_now()
if running and col:
bpr_target = m['bpr_pa']
drop = column_pressure_drop(self.flow, phi, col) + EXTRA_COLUMN_R * (mixture_viscosity(phi) / 1e-4) * self.flow
self.bpr_pa = bpr_target + (self.bpr_pa - bpr_target) * math.exp(-h / PRESSURE_TAU_S)
p_target = self.bpr_pa + drop
self.pump_pa = p_target + (self.pump_pa - p_target) * math.exp(-h / PRESSURE_TAU_S)
self.booster_pa = max(0.0, 0.95 * self.pump_pa)
if self.pump_pa > PUMP_MAX_PA:
self.fault = 'OVERPRESSURE'
self.pump_enabled = False
if self._busy():
self._finish('failed')
# consumption ledgers
vol = self.flow * h
bottle = self.bottles[m['modifier_channel']] or {'volume_m3': 0.0}
mod = min(bottle['volume_m3'], vol * phi)
bottle['volume_m3'] -= mod
self.modifier_drawn_m3 += mod
self.waste_m3 += mod
co2 = min(self.supply['cylinder_co2_kg'], vol * (1 - phi) * CO2_PUMP_DENSITY_KG_M3)
self.supply['cylinder_co2_kg'] -= co2
self.vented_co2_kg += co2
for b in self.bands: # bands migrate whenever the pump delivers
if b['t_r'] is None or b['done']:
continue
b['flow_s'] += h * self.flow / b['flow_ref']
if not b['eluted'] and b['flow_s'] >= b['t_r'] + 4 * b['sigma']:
b['eluted'] = True
self.eluted_mol += b['mol']
if b['flow_s'] >= b['t_r'] + 8 * b['sigma']:
b['done'] = True
if bottle['volume_m3'] <= 0.0 and (phi > 0 or self.bottles[m['modifier_channel']] is None):
self.fault = 'MODIFIER_EMPTY'
self.pump_enabled = False
if self._busy():
self._finish('failed')
else:
for attr in ('bpr_pa', 'pump_pa', 'booster_pa'):
setattr(self, attr, getattr(self, attr) * math.exp(-h / 30.0))
# run state machine
if self.phase == 'injecting':
self.run['inject_left'] -= h
if self.run['inject_left'] <= 1e-9:
self._inject()
self.phase = 'running'
elif self.phase == 'running':
run = self.run
run['elapsed'] += h
period = 1.0 / m['data_rate_hz']
while run['next_sample'] <= run['elapsed'] + 1e-9 and run['next_sample'] <= m['run_time_s'] + 1e-9:
y = self._signal(run['next_sample'])
run['t'].append(round(run['next_sample'], 6))
run['y'].append(y)
self.absorbance = y
run['next_sample'] += period
if run['elapsed'] >= m['run_time_s'] - 1e-9:
self._finish('succeeded')
self.time_s += h
class Agilent1260infinitySession:
"""Principal-bound protocol session: describe / read / invoke / write / poll / cancel with visibility filtering."""
def __init__(self, host, principal_id):
self._host = host
self._principal = principal_id
@property
def _role(self):
return self._host._principals[self._principal]
def _target(self, instance_id):
if instance_id != self._host.instance_id:
raise ActionRejected('UNKNOWN_INSTANCE')
def describe(self, *, instance_id=None, asset_type_id=None):
if (instance_id is None) == (asset_type_id is None):
raise ActionRejected('INVALID_ARGUMENT')
if instance_id is not None:
self._target(instance_id)
if asset_type_id is not None and asset_type_id != ASSET_TYPE_ID:
raise ActionRejected('UNKNOWN_INSTANCE')
meta = export_agilent_1260infinity_contract_metadata()
agent = self._role == 'agent'
return dict(protocol_version=PROTOCOL_VERSION, asset_type_id=ASSET_TYPE_ID, asset_version='1.0.0',
capabilities={k: v for k, v in meta['capabilities'].items() if v['visibility'] == 'agent' or not agent},
state_slots={k: v for k, v in meta['state_slots'].items() if v['visibility'] == 'agent' or not agent})
def read(self, *, instance_id, state_ids=None):
self._target(instance_id)
h = self._host
vals = h.read(self._role)
ids = list(vals) if state_ids is None else state_ids
if not isinstance(ids, list) or any(not isinstance(k, str) for k in ids):
raise ActionRejected('INVALID_ARGUMENT')
if any(k not in vals for k in ids):
raise ActionRejected('ACCESS_DENIED')
return dict(status='succeeded', instance_id=instance_id, state_revision=h.revision, clock={'domain': 'simulation', 'time_s': h.time_s},
observations={k: dict(value=copy.deepcopy(vals[k]), unit=SLOTS[k][1], quality='estimated' if SLOTS[k][2] == 'derived' else 'valid',
sample_time_s=h.time_s, sample_window_s=None) for k in ids})
def invoke(self, *, instance_id, capability_id, arguments, request_id):
try:
return self._invoke(instance_id=instance_id, capability_id=capability_id, arguments=arguments, request_id=request_id)
except ActionRejected as exc:
return dict(protocol_version=PROTOCOL_VERSION, instance_id=instance_id, request_id=request_id, operation_id=None, status='rejected',
state_revision=self._host.revision, clock={'domain': 'simulation', 'time_s': self._host.time_s}, result={}, observations={},
error=dict(code=str(exc), message=str(exc), retryable=False, side_effects='none'))
def _invoke(self, *, instance_id, capability_id, arguments, request_id):
self._target(instance_id)
h = self._host
if not isinstance(capability_id, str) or capability_id not in CAPS:
raise ActionRejected('UNKNOWN_CAPABILITY')
if self._role == 'agent' and CAPS[capability_id][5] != 'agent':
raise ActionRejected('ACCESS_DENIED')
if not isinstance(request_id, str) or not request_id or not isinstance(arguments, dict):
raise ActionRejected('INVALID_ARGUMENT')
key = (self._principal, instance_id, request_id)
try:
digest = json.dumps([capability_id, arguments], sort_keys=True, allow_nan=False)
except (TypeError, ValueError):
raise ActionRejected('INVALID_ARGUMENT')
if key in h._requests:
old, result = h._requests[key]
if old != digest:
raise ActionRejected('REQUEST_CONFLICT')
return copy.deepcopy(result)
result = h.invoke(capability_id, **arguments)
op = result.get('operation_id') if capability_id == 'run.start' else None
if op:
h._owners[op] = self._principal
response = dict(protocol_version=PROTOCOL_VERSION, instance_id=instance_id, request_id=request_id, operation_id=op,
status='accepted' if op else 'succeeded', state_revision=h.revision, clock={'domain': 'simulation', 'time_s': h.time_s},
result=result, observations={}, error=None)
if CAPS[capability_id][4] not in ('query', 'analysis'): # pure queries are recomputed on retry (no unbounded cache of large arrays)
h._requests[key] = (digest, copy.deepcopy(response))
return response
def write(self, *, instance_id, state_id, value, request_id):
self._target(instance_id)
if state_id not in SLOTS or not SLOTS[state_id][5]:
raise ActionRejected('ACCESS_DENIED')
cap, arg = SLOTS[state_id][5]
return self.invoke(instance_id=instance_id, capability_id=cap, arguments={arg: value}, request_id=request_id)
def poll(self, operation_id):
h = self._host
if operation_id != h.operation_id or h._owners.get(operation_id) != self._principal:
raise ActionRejected('ACCESS_DENIED')
return dict(operation_id=operation_id, status=h.phase, result=h._chromatogram(2000))
def cancel(self, operation_id, request_id):
self.poll(operation_id)
response = self.invoke(instance_id=self._host.instance_id, capability_id='run.abort', arguments={}, request_id=request_id)
return dict(operation_id=operation_id, status=self._host.phase, result=response['result'])
# ------------------------------------------------------------------------------------------------------ contract metadata
PRECONDITIONS = {
'pump.set': ('开泵:五模块通电、CO2就绪(供气40–70 bar且冷却器≤9 °C)、已配置方法、所选柱位已装柱、所用改性剂瓶有液',
['power.enabled', 'co2.ready', 'method.configured', 'column.installed', 'solvent.b1'], 'all_powered and co2_ready and method and column and bottle>0'),
'run.start': ('系统就绪(流量≥98%目标、背压±5 bar、柱温±1 K)、进样器门与该抽屉关闭、瓶内余量≥进样体积+10 µL、改性剂足够本次运行',
['system.ready', 'sampler_door.angle_rad', 'drawer_1.position_m', 'run.phase'], 'ready and door==0 and drawer==0 and vial>=inj+dead and phase not busy'),
'method.configure': ('运行中锁定方法;梯度表时间从0递增;柱温≥环境−10 K且≥4 °C;进样体积为0.1 µL整数倍;泵运行时不得切换到无液改性剂瓶或空柱位',
['run.phase', 'pump.enabled', 'solvent.b1', 'column.installed'], 'phase not busy and (not pump or (bottle>0 and column installed))'),
'column.install': ('柱温箱门打开(≥0.5 rad)、泵停且不在运行', ['mct_door.angle_rad', 'pump.enabled', 'run.phase'], 'mct_door>=0.5 and not pump and not busy'),
'sample.register_vial': ('目标抽屉拉出≥0.15 m、瓶位空、物质在模板库', ['drawer_1.position_m', 'sample.vial_count'], 'drawer>=0.15 and free and sid in library'),
'sample.remove_vial': ('目标抽屉拉出≥0.15 m且瓶位有瓶', ['drawer_1.position_m'], 'drawer>=0.15 and occupied'),
'supply.configure': ('泵停时才能更换气瓶;连接时供气40–70 bar', ['pump.enabled'], 'not pump and 40e5<=supply<=70e5'),
'solvent.configure': ('泵停时才能换瓶', ['pump.enabled'], 'not pump'),
'sampler_door.set': ('进样/采集中不得打开进样器门', ['run.phase'], 'opening -> phase not busy'),
'mct_door.set': ('进样/采集中不得打开柱温箱门(保留在进样时按当时条件计算)', ['run.phase'], 'opening -> phase not busy'),
}
for _i in range(1, 5):
PRECONDITIONS[f'drawer_{_i}.set'] = ('进样/采集中不得拉出抽屉', ['run.phase'], 'opening -> phase not busy')
def export_agilent_1260infinity_contract_metadata():
caps, slots = {}, {}
for key, (schema, unit, origin, vis, comps, write, meaning) in SLOTS.items():
slots[key] = dict(component_ids=comps, value_schema=copy.deepcopy(schema), unit=unit, reference_conditions=REFERENCE_ZH.get(key),
meaning_zh=meaning or None, origin=origin, visibility=vis, access='read_write' if write else 'read_only',
read_binding=dict(backend='host', artifact_id='runtime', accessor=f'Agilent1260infinitySession.read(state_ids=[{key!r}])'),
write_via=dict(capability_id=write[0], argument=write[1], fixed_arguments={}) if write else None,
sampling=dict(mode='instant', time_domain='simulation', window_description=None),
source_ids=['manufacturer_specs', 'simulation_assumption'])
for key, (inp, out, comps, meaning, kind, vis, example, effects) in CAPS.items():
unsupported = key in UNSUPPORTED
is_async = key == 'run.start'
pre = []
if key in PRECONDITIONS:
d, states, check = PRECONDITIONS[key]
pre = [dict(description_zh=d, state_ids=states, enforced_by='runtime', check=check)]
caps[key] = dict(
function_zh=meaning, kind=kind, visibility=vis, component_ids=comps, availability='unsupported' if unsupported else 'implemented',
input_schema=copy.deepcopy(inp), output_schema=copy.deepcopy(out),
implementation=dict(process='absent' if unsupported else 'implemented', scene='absent', robot='absent', hardware='absent',
host='absent' if unsupported else 'implemented'),
binding=None if unsupported else dict(backend='host', artifact_id='runtime', entrypoint='asset_runtime.agilent_1260infinity.Agilent1260infinitySession.invoke',
invocation=f'session.invoke(instance_id="sfc_01", capability_id={key!r}, arguments={example!r}, request_id="unique")'),
preconditions=pre, state_effects=[dict(state_id=s, timing='on_completion' if is_async else 'immediate', description_zh=meaning) for s in effects],
observes=[], model_effects=dict(mode='none', description_zh='过程层能力;几何联动由宿主另行绑定并在Matterix场景中验证。', binding_ids=[]),
execution=dict(mode='asynchronous' if is_async else 'synchronous', time_domain='simulation',
completion_criterion='run.phase=succeeded(运行时间结束);取消/失败保留已采集数据与物料账本' if is_async else
('返回只读结果,不推进时钟' if kind in ('query', 'analysis') else '设定写入;物理量只随step演化'),
completion_state_ids=['run.phase'] if is_async else list(effects), timeout_s=None,
cancellation='supported' if is_async else 'unsupported', retry='same_request_id',
resources=['target_instance', 'principal_request_cache'],
partial_failure_zh='拒绝时状态不变;取消/断电/故障不回滚已注入样品、已消耗改性剂与CO2。请求去重只在当前进程内存有效。'),
errors=[dict(code=e, meaning_zh=e, side_effects='none') for e in
['UNKNOWN_INSTANCE', 'UNKNOWN_CAPABILITY', 'ACCESS_DENIED', 'INVALID_ARGUMENT', 'PRECONDITION_FAILED', 'BUSY', 'REQUEST_CONFLICT',
'UNKNOWN_REFERENCE', 'INVALID_CALIBRATION', 'UNSUPPORTED']],
example_arguments=copy.deepcopy(example), verification=[],
limitations=['仿真过程模型,无真实硬件连接;进程内会话过滤不能替代文件与进程级部署隔离。'] if not unsupported else ['未实现;调用返回UNSUPPORTED。'],
source_ids=['manufacturer_specs', 'sfc_retention_data', 'simulation_assumption'])
p = lambda v, u, z, ev='assumption', src=('simulation_assumption',): dict(value=v, unit=u, meaning_zh=z, evidence=ev, source_ids=list(src), uncertainty=None) # noqa: E731
mechanisms = {
'retention': dict(
component_ids=['column_1', 'column_2', 'column_3', 'column_4', 'column_valve', 'mct_housing'],
state_ids=['column.temperature_k', 'mobile_phase.co2_density_kg_m3', 'run.phase', 'truth.column_mol', 'truth.eluted_mol'],
meaning_zh='梯度SFC谱带迁移:模板库实测保留时间反解的log-log保留截距,按配置梯度、流量、延迟体积、柱温与背压(CO2密度)积分出峰时间',
implementation='lumped',
equations=['log10 k = a - m*log10(max(phi, phi_min)) - c_rho*(rho/rho_ref - 1)/ln(10)',
'dz/dt = 1/(t0*(1+k(phi(t - t_D - z*t0)))),z=1时出峰',
't0 = eps_T*pi*r^2*L/F;t_D = V_delay(BPR)/F,V_delay 600–900 µL',
'sigma_t^2 = (t0*(1+k_e))^2/N + ((V_cell/F)^2 + (V_inj/F)^2)/12,N = L/(h*dp)'],
parameters={'loglog_slope_m': p(LOGLOG_SLOPE_M, '1', 'log k–log φ斜率,所有物质同一值'),
'total_porosity': p(TOTAL_POROSITY, '1', '柱总孔隙率(死时间)'),
'density_coefficient': p(DENSITY_COEFF, '1', 'ln k对CO2相对密度的系数'),
'reference_dwell_s': p(REF_DWELL_S, 's', '源数据UPC2系统梯度延迟(未公开,假设)'),
'reduced_plate_height': p(PLATE_HEIGHT_DP, '1', '折合塔板高度h'),
'phi_min': p(PHI_MIN, '1', '保留律中改性剂分数下限'),
'delay_volume_range': p([DELAY_MIN_M3, DELAY_MAX_M3], 'm^3', 'G4782A延迟体积600–900 µL(随背压,线性映射为假设)', 'documented', ['manufacturer_specs']),
'reference_method_flow': p(REF_FLOW_M3_S, 'm^3/s', '源数据方法流量1.5 mL/min', 'documented', ['sfc_retention_data'])},
source_ids=['sfc_retention_data', 'manufacturer_specs', 'simulation_assumption'],
limitations=['m、ε_T、密度系数与UPC2延迟为假设;参考方法下保留时间复现实测(残差<0.5 s),其它方法为外推。',
'保留时间与峰宽在进样时按当时流量/梯度/柱温/背压一次算定;运行中条件变化不改变已进样谱带(运行中门与方法均锁定)。'
'运行结束后泵继续输液时谱带继续迁移(按流量折算),晚出峰进入废液,或在下一次运行中作为残留峰出现。',
'源数据中未出峰/未检出、或晚于文献运行终点(2条,未拟合)的组合,按“留在柱上”处理,不代表真实色谱行为已知。',
'未建模柱老化(库中有12个月漂移数据但未驱动运行层)、对映体选择性、过载与峰拖尾。']),
'hydraulics': dict(
component_ids=['pump_head_a', 'pump_head_b', 'booster_unit', 'chiller_unit', 'bpr_unit', 'column_1'],
state_ids=['pump.pressure_pa', 'bpr.pressure_pa', 'pump.flow_m3_s', 'chiller.temperature_k', 'booster.pressure_pa'],
meaning_zh='泵压=背压+Kozeny-Carman柱压降+柱外压降;600 bar跳泵;CO2经冷却再液化与增压后供泵A,改性剂由泵B高压混合',
implementation='lumped',
equations=['dP_col = 180*eta_mix*u_s*L*(1-e)^2/(e^3*dp^2)', 'eta_mix = exp(phi*ln eta_MeOH + (1-phi)*ln eta_CO2)',
'P_pump -> P_BPR + dP_col + R_extra*(eta/1e-4)*F(一阶,tau=3 s)', 'P_pump > 600 bar -> OVERPRESSURE 停泵'],
parameters={'pump_max_pa': p(PUMP_MAX_PA, 'Pa', '系统/泵最高压力600 bar', 'documented', ['manufacturer_specs']),
'bpr_range_pa': p([BPR_MIN_PA, BPR_MAX_PA], 'Pa', 'BPR可设100–400 bar', 'documented', ['manufacturer_specs']),
'supply_range_pa': p([SUPPLY_MIN_PA, SUPPLY_MAX_PA], 'Pa', 'CO2供气40–70 bar', 'documented', ['manufacturer_specs']),
'eta_co2_pa_s': p(ETA_CO2_PA_S, 'Pa*s', 'CO2黏度(工程值)'), 'eta_methanol_pa_s': p(ETA_MEOH_PA_S, 'Pa*s', '甲醇25 °C黏度(常用手册值,本资产未列来源,按假设登记)'),
'bed_porosity': p(BED_POROSITY, '1', '床层孔隙率'), 'extra_column_resistance': p(EXTRA_COLUMN_R, 'Pa*s/m^3', '柱外阻力(每1e-4 Pa s)'),
'pressure_tau_s': p(PRESSURE_TAU_S, 's', '压力一阶时间常数'), 'chiller_target_k': p(CHILLER_TARGET_K, 'K', '冷却器目标(厂家范围−20…9 °C内取5 °C)')},
source_ids=['manufacturer_specs', 'simulation_assumption'],
limitations=['流量按泵头条件体积计,未做压缩性补偿;改性剂对CO2密度的影响忽略。']),
'thermal': dict(
component_ids=['mct_housing', 'mct_door', 'bpr_unit', 'chiller_unit'], state_ids=['column.temperature_k', 'bpr.temperature_k', 'chiller.temperature_k'],
meaning_zh='柱温箱一阶升降温,时间常数由厂家速率换算;门打开时只能维持目标与环境差的一半(假设)', implementation='lumped',
equations=['T -> T_target,升温tau=300 s/ln(30),降温tau=600 s/ln(40)'],
parameters={'tau_heat_s': p(COL_TAU_HEAT_S, 's', '由厂家“环境→40 °C约5 min”换算(一阶到0.5 K以内)', 'documented', ['manufacturer_specs']),
'tau_cool_s': p(COL_TAU_COOL_S, 's', '由厂家“40→20 °C约10 min”换算(一阶到0.5 K以内)', 'documented', ['manufacturer_specs'])},
source_ids=['manufacturer_specs'], limitations=['单节点温区;两个独立温区按同一温度处理。']),
'detection': dict(
component_ids=['flow_cell', 'dad_housing'], state_ids=['detector.absorbance_au', 'detector.wavelength_m'],
meaning_zh='DAD吸光度=ε(λ)·10 mm·c(t),高斯谱带;噪声与漂移取厂家规格', implementation='lumped',
equations=['c(t) = n/(F*sigma*sqrt(2pi))*exp(-(t-tR)^2/(2 sigma^2))', 'A = eps*l*c + N(0, 0.7e-5/2.5) + drift*t'],
parameters={'flow_cell_path_m': p(FLOW_CELL_PATH_M, 'm', 'SFC流通池光程10 mm', 'documented', ['manufacturer_specs']),
'noise_au': p(DAD_NOISE_AU, 'AU', '噪声<±0.7e-5 AU', 'documented', ['manufacturer_specs']),
'assumed_epsilon_m2_mol': p(ASSUMED_EPSILON_M2_MOL, 'm^2/mol', '无NIST紫外曲线时的假设摩尔吸光系数')},
source_ids=['manufacturer_specs', 'nist_uv', 'simulation_assumption'],
limitations=['多数物质无NIST紫外曲线,响应为假设(结果warnings中标出);无检测器饱和与带宽效应。']),
}
if _ann is not None:
_ann.annotate_export('agilent_1260infinity', caps, slots, mechanisms, inputs={'method.configure': (METHOD, METHOD_EXAMPLE), 'supply.configure': (SUPPLY, SUPPLY_EXAMPLE)})
return dict(asset_type_id=ASSET_TYPE_ID, catalog_id=CATALOG_ID, capabilities=caps, state_slots=slots, mechanisms=mechanisms)