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tune.py
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tune.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Nov 12 22:10:26 2019
@author: thele
"""
import sys
import json
from Sampler_factory import Paper_sampler, Redo_sampler
from Investigation.Investigation_factory import Investigation_stage
from main_utils.utils import Timer, plot_conditional_idx_improvment
from main_utils.model_surf_utils import show_gpr_gpc, show_dummy_device
from Playground.mock_device import build_mock_device_with_json
def tune_with_pygor_from_file(config_file):
with open(config_file) as f:
configs = json.load(f)
pygor_path = configs.get('path_to_pygor',None)
if pygor_path is not None:
sys.path.insert(0,pygor_path)
import Pygor
pygor = Pygor.Experiment(xmlip=configs.get('ip',None))
gates = configs['gates']
plunger_gates = configs['plunger_gates']
chan_no = configs['chan_no']
grouped = any(isinstance(i, list) for i in gates)
if grouped:
def jump(params,plungers=False):
if plungers:
labels = plunger_gates
else:
labels = gates
for i,gate_group in enumerate(labels):
pygor.setvals(gate_group,[params[i]]*len(gate_group))
return params
else:
def jump(params,plungers=False):
#print(params)
if plungers:
labels = plunger_gates
else:
labels = gates
pygor.setvals(labels,params)
return params
def measure():
cvl = pygor.do0d()[chan_no][0]
return cvl
def check():
return pygor.getvals(plunger_gates)
assert len(gates) == len(configs['general']['origin'])
inv_timer = Timer()
investigation_stage = Investigation_stage(jump,measure,check,configs['investigation'],inv_timer)
return tune(jump,measure,investigation_stage,configs)
def tune_with_playground_from_file(config_file):
with open(config_file) as f:
configs = json.load(f)
device = build_mock_device_with_json(configs['playground'])
if configs['playground'].get('plot',False): show_dummy_device(device,configs)
plunger_gates = configs['plunger_gates']
def jump(params,inv=False):
if inv:
return params
else:
return device.jump(params)
measure = device.measure
check = lambda: device.check(plunger_gates)
inv_timer = Timer()
investigation_stage = Investigation_stage(jump,measure,check,configs['investigation'],inv_timer)
results,sampler = tune(jump,measure,investigation_stage,configs)
fields = ['vols_pinchoff','conditional_idx','origin']
if configs['playground'].get('plot',False):
show_gpr_gpc(sampler.gpr, configs, *sampler.t.get(*fields), gpc=sampler.gpc.predict_comb_prob)
plot_conditional_idx_improvment(sampler.t['conditional_idx'],configs)
return results,sampler
def redo_with_pygor_from_file(config_file, pointcloud):
with open(config_file) as f:
configs = json.load(f)
pygor_path = configs.get('path_to_pygor',None)
if pygor_path is not None:
sys.path.insert(0,pygor_path)
import Pygor
pygor = Pygor.Experiment(xmlip=configs.get('ip',None))
gates = configs['gates']
plunger_gates = configs['plunger_gates']
chan_no = configs['chan_no']
grouped = any(isinstance(i, list) for i in gates)
if grouped:
def jump(params,plungers=False):
if plungers:
labels = plunger_gates
else:
labels = gates
for i,gate_group in enumerate(labels):
pygor.setvals(gate_group,[params[i]]*len(gate_group))
return params
else:
def jump(params,plungers=False):
#print(params)
if plungers:
labels = plunger_gates
else:
labels = gates
pygor.setvals(labels,params)
return params
def measure():
cvl = pygor.do0d()[chan_no][0]
return cvl
def check():
return pygor.getvals(plunger_gates)
assert len(gates) == len(configs['general']['origin'])
inv_timer = Timer()
investigation_stage = Investigation_stage(jump,measure,check,configs['investigation'],inv_timer)
return redo(jump,measure,investigation_stage,configs)
def redo_with_playground_from_file(config_file,pointcloud):
with open(config_file) as f:
configs = json.load(f)
device = build_mock_device_with_json(configs['playground'])
if configs['playground'].get('plot',False): show_dummy_device(device,configs)
plunger_gates = configs['plunger_gates']
def jump(params,inv=False):
if inv:
return params
else:
return device.jump(params)
measure = device.measure
check = lambda: device.check(plunger_gates)
inv_timer = Timer()
investigation_stage = Investigation_stage(jump,measure,check,configs['investigation'],inv_timer)
results,sampler = redo(jump,measure,investigation_stage,configs,pointcloud)
fields = ['vols_pinchoff','conditional_idx','origin']
if configs['playground'].get('plot',False):
show_gpr_gpc(sampler.gpr, configs, *sampler.t.get(*fields), gpc=sampler.gpc.predict_comb_prob)
plot_conditional_idx_improvment(sampler.t['conditional_idx'],configs)
return results,sampler
def tune_from_file(jump,measure,check,config_file):
with open(config_file) as f:
configs = json.load(f)
inv_timer = Timer()
investigation_stage = Investigation_stage(jump,measure,check,configs['investigation'],inv_timer)
results,sampler = tune(jump,measure,investigation_stage,configs)
return results,sampler
def redo_from_file(jump,measure,check,config_file,pointcloud):
with open(config_file) as f:
configs = json.load(f)
inv_timer = Timer()
investigation_stage = Investigation_stage(jump,measure,check,configs['investigation'],inv_timer)
results,sampler = redo(jump,measure,investigation_stage,configs,pointcloud)
return results,sampler
def tune(jump,measure,investigation_stage,configs):
configs['jump'] = jump
configs['measure'] = measure
configs['investigation_stage_class'] = investigation_stage
ps = Paper_sampler(configs)
for i in range(configs['general']['num_samples']):
print("============### ITERATION %i ###============"%i)
results = ps.do_iter()
for key,item in results.items():
print("%s:"%(key),item[-1])
return results, ps
def tune_origin_variable(jump,measure,par_invstage,child_invstage,par_configs,child_configs):
par_configs['jump'],child_configs['jump'] = jump,jump
par_configs['measure'],child_configs['measure'] = measure,measure
par_configs['investigation_stage_class'], child_invstage['investigation_stage_class'] = par_invstage, child_invstage
par_ps = Paper_sampler(par_configs)
child_ps_list = []
ps = par_ps
par_flag = True
for i in range(par_configs['general']['num_samples']):
print("============### ITERATION %i ###============"%i)
results = ps.do_iter()
for key,item in results.items():
print("%s:"%(key),item[-1])
if par_flag:
if new_origin_condition(ps):
child_configs_new = config_constructor(child_configs,results)
child_ps_list+=[Paper_sampler(child_configs_new)]
ps,par_flag = task_selector(par_ps,child_ps_list,i)
def redo(jump, measure, investigation_stage, configs, pointcloud):
configs['jump'] = jump
configs['measure'] = measure
configs['investigation_stage_class'] = investigation_stage
ps = Redo_sampler(configs, pointcloud)
for i in range(configs['general']['num_samples']):
print("============### ITERATION %i ###============"%i)
results = ps.do_iter()
for key,item in results.items():
print("%s:"%(key),item[-1])
return results, ps
if __name__ == '__main__':
pass
#tune_with_pygor_from_file('tuning_config.json')