-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathTaskGenerator_Class.py
337 lines (319 loc) · 15.9 KB
/
TaskGenerator_Class.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ##
# @brief [TaskGenerator] TaskGenerator file
# @author Hyuk Jun Yoo (yoohj9475@kist.re.kr)
# @version 3_2
# TEST 2021-11-21
# TEST 2022-04-11
# TEST 2024-06-14
import copy
import json
class TaskGenerator:
"""
TaskGenerator class get task sequence, allocate each task's value in json file (recipe)
class Template --> has template of recipe
class TCP_Class --> to request hardware information (pump) to use flexible system when we change our solution location or type, kinds
# Variables
------------
:param TaskLogger_obj (TaskLogger_obj): set logging object
:param ResourceManager_obj (object): resource manager object
"""
def __init__(self, TaskLogger_obj:object, ResourceManager_obj:object):
self.TaskLogger_obj=TaskLogger_obj
self.component_name="TaskGenerator"
self.ResourceManager_obj=ResourceManager_obj
self.task_device_info_dict = self.ResourceManager_obj.task_device_info_dict
with open(f"Task/Template_module.json", 'r', encoding='utf-8') as f:
self.Template_base=json.load(f)
def _allocateTaskInfo(self, big_process_module_dict:dict, task_templates:dict, task_device_action_dict:dict, input_task_name:str, integrated_parameter_dict:dict):
"""
allocate some value in recipe template
:param big_process_module_dict (dict):
:param task_templates (dict)
:param task_device_action_dict (dict)
:param input_task_name (str): BatchSynthesis_AddSolution=AgNO3 or BatchSynthesis_Stir...ElectroAnalysis_Electrochemical... etc...
:param integrated_parameter_dict (dict) --> dict(parameter_dict, **fixed_params_dict)
:return: template (dict),
"""
###############################
# split module name, task name, task content
###############################
module_name=""
task_name=""
task_content=""
if "=" in input_task_name:
module_task_name, task_content = input_task_name.split("=")
# input_task_name="BatchSynthesis_AddSolution=AgNO3"
# module_task_name="BatchSynthesis_AddSolution"
# task_content="AgNO3"
else:
module_task_name=input_task_name
# module_task_name --> BatchSynthesisModule_AddSolution
module_name, task_name = module_task_name.split("_")
# module_name --> BatchSynthesisModule // task_name --> AddSolution
###############################
# extract task template
###############################
task_template=task_templates[module_task_name]
###############################
# extract device information
###############################
# print(task_device_action_dict)
task_deviceaction_list=list(task_device_action_dict[module_task_name])
device_info_dict={}
# print("self.task_device_info_dict[module_name]", self.task_device_info_dict[module_name])
try:
for task_deviceaction in task_deviceaction_list:
device_name, action_type = task_deviceaction.split("_")
# print("device_name, action_type", device_name, action_type)
device_info_dict[device_name]=self.task_device_info_dict[module_name][device_name]
except KeyError as e:
print(f"module name keys :{list(self.task_device_info_dict.keys())} --> {module_name}")
print(f"module devices keys :{list(self.task_device_info_dict[module_name].keys())} --> {device_name}")
print(f"We don't have {module_name} or {device_name}")
raise KeyError(e)
# print("device_info_dict", device_info_dict)
##############################################
# allocate task information in task template #
##############################################
# print("task_content", task_content)
splitted_task=task_content.split("_")
# print("splitted_task:", splitted_task)
##############################################
# allocate task information in task template-1
# no hyperparameter, material name
##############################################
if splitted_task==['']:
for key, value in task_template["Data"].items():
if key=="Device":
task_template["Data"]["Device"]=device_info_dict
else:
if isinstance(value, dict):
task_template["Data"][key]["Value"]=integrated_parameter_dict[module_name+"_"+task_name+"="+key]
else:
raise ValueError(f"Please check parameter dict:{list(integrated_parameter_dict.keys())} --> key of parameter dict:{module_name}_{task_name}={key}")
##############################################
# allocate task information in task template-2
# has hyperparameter, material name
##############################################
else:
material = splitted_task[0]
for key, value in task_template["Data"].items():
if key=="Device":
task_template["Data"]["Device"]=device_info_dict
elif key=="Material":
task_template["Data"][key]["Type"]=material
else:
if isinstance(value, dict): # {"Value":0, "Dimension":"mL"}
task_template["Data"][key]["Value"]=integrated_parameter_dict[module_name+"_"+task_name+f"={material}_"+key]
else:
raise ValueError(f"Please check parameter dict:{list(integrated_parameter_dict.keys())} --> key of parameter dict:{module_name}_{task_name}={material}_{key}")
# if mid_key=="Hyperparameter":
# for key, value in task_template["Data"].items():
# if key=="Device":
# task_template["Data"]["Device"]=device_info_dict
# else:
# if isinstance(value, str):
# task_template["Data"][mid_key]=integrated_parameter_dict[module_name+"_"+task_name+"="+key]
# elif isinstance(value, dict): # mid_key="Hyperparameter", condition_name="WavelengthMin"...etc
# for bottom_key in task_template["Data"][mid_key].keys():
# task_template["Data"][mid_key][bottom_key]=integrated_parameter_dict[module_name+"_"+task_name+f"={mid_key}_"+bottom_key]
# else:
# raise ValueError(f"Please check parameter dict:{list(integrated_parameter_dict.keys())} --> key of parameter dict:{module_name}_{task_name}={mid_key}_{bottom_key}")
# else:
# for key, value in task_template["Data"].items():
# if key=="Device":
# task_template["Data"]["Device"]=device_info_dict
# else:
# if isinstance(value, str): # material
# task_template["Data"][key]=mid_key
# elif isinstance(value, dict): # {"Value":0, "Dimension":"mL"}
# task_template["Data"][key]["Value"]=integrated_parameter_dict[module_name+"_"+task_name+f"={mid_key}_"+condition_name]
# else:
# raise ValueError(f"Please check parameter dict:{list(integrated_parameter_dict.keys())} --> key of parameter dict:{module_name}_{task_name}={mid_key}_{condition_name}")
return task_template
def generateRecipe(self, recipe_dict:dict, input_next_point:dict={}):
"""
allocate synthesis sequence process in json file (recipe) depending on each task_sequence_list
:param recipe_dict (dict) : recipe information in config file
ex)
process_dict = {
"Synthesis":{
"BatchSynthesis":
{
"Sequence":["BatchSynthesisModule_AddSolution=Citrate","BatchSynthesisModule_AddSolution=NaBH4","BatchSynthesisModule_Stir","BatchSynthesisModule_Heat","BatchSynthesisModule_Mix", "BatchSynthesisModule_AddSolution=AgNO3", "BatchSynthesisModule_React"],
"fixedParams":
{
"BatchSynthesisModule_AddSolution=Citrate_Concentration" : 20,
"BatchSynthesisModule_AddSolution=Citrate_Volume" : 1200,
"BatchSynthesisModule_AddSolution=Citrate_Injectionrate" : 200,
"BatchSynthesisModule_AddSolution=NaBH4_Concentration" : 10,
"BatchSynthesisModule_AddSolution=NaBH4_Volume" : 3000,
"BatchSynthesisModule_AddSolution=NaBH4_Injectionrate" : 200,
"BatchSynthesisModule_Stir=StirRate":1000,
"BatchSynthesisModule_Heat=Temperature":25,
"BatchSynthesisModule_Mix=Time":300,
"BatchSynthesisModule_React=Time":1200
}
},
"FlowSynthesis":{}
},
"Preprocess":{
"Washing":{},
"Ink":{}
},
"Characterization":{
"UV":
{
"Sequence":["UVVisModule_GetAbs"],
"fixedParams":
{
"UVVisModule_GetAbs=Hyperparameter_WavelengthMin":300,
"UVVisModule_GetAbs=Hyperparameter_WavelengthMax":849,
"UVVisModule_GetAbs=Hyperparameter_BoxCarSize":10,
"UVVisModule_GetAbs=Hyperparameter_Prominence":0.01,
"UVVisModule_GetAbs=Hyperparameter_PeakWidth":20
}
}
},
"Evaluation":{
"RDE":{},
"Electrode":{}
}
}
:param input_next_point (dict) :result of algorithm value dict
:return temp_process_template (dict): total process_template
"""
with open(f"Task/Template_module.json", 'r', encoding='utf-8') as f:
temp_process_template=json.load(f)["process"]
"""
temp_process_template= {
"Synthesis":[],
"Preprocess":[],
"Characterization":[],
"Evaluation":[]
}
"""
module_seq_list=[]
big_process_module_dict={
"Synthesis":[],
"Preprocess":[],
"Characterization":[],
"Evaluation":[]
}
for big_process_name, big_process_dict in recipe_dict.items():
for module_name, module_dict in big_process_dict.items():
if len(module_dict)!=0:
module_seq_list.append(module_name)
big_process_module_dict[big_process_name].append(module_name)
for big_process_name, big_process_dict in recipe_dict.items(): # big_process_name = "Synthesis", "Preprocess", "Characterization", "Evaluation":
count=0
for module_name, module_dict in big_process_dict.items(): # module_name = "BatchSynthesis" or "FlowSynthesis"
if len(module_dict)!=0:
integrated_parameter_dict = dict(input_next_point, **module_dict["fixedParams"])
integrated_parameter_dict=copy.deepcopy(integrated_parameter_dict)
##########################
# upload module template #
##########################
with open(f"Task/Template_module.json", 'r', encoding='utf-8') as f:
module_template=json.load(f)[module_name]
###############################
# extract task template
###############################
with open(f"Task/Template/{module_name}.json", 'r', encoding='utf-8') as f:
task_templates=json.load(f)
###############################
# extract device information
###############################
with open(f"Task/ActionSequence/{module_name}.json", 'r', encoding='utf-8') as f:
task_device_action_dict=json.load(f)
########################################
# allocate task depending on sequences #
########################################
module_task_list=[]
try:
for task_name in module_dict["Sequence"]: # Allocate task_name according to the Sequence within the module.
temp_each_task_template=self._allocateTaskInfo(big_process_module_dict, task_templates, task_device_action_dict, task_name, integrated_parameter_dict)
module_task_list.append(temp_each_task_template)
except KeyError as e:
print(e)
raise KeyError("integrated_parameter_dict has no module_sequences")
##########################################
# attach task_list in template
##########################################
module_template["Data"]=module_task_list
temp_process_template[big_process_name].append(module_template)
else: # process is empty
count+=1
# if empty_process -> delete
if count==len(list(big_process_dict.keys())):
del temp_process_template[big_process_name]
return temp_process_template
if __name__ == "__main__":
from Log.Logging_Class import TaskLogger
input_next_point={
"AddSolution=AgNO3_Concentration" : 0.375,
"AddSolution=AgNO3_Volume" : 1200,
"AddSolution=AgNO3_Injectionrate" : 200
}
metadata_dict={
"subject":"Take_scneario",
"group":"KIST_CSRC",
"logLevel":"INFO",
"modeType":"real",
"todayIterNum":1,
"userName":"HJ",
"jobID":0,
"jobFileName":"USER/HJ/job_script/20230516_autonomous_test.json",
"batchSize":8
}
recipe_dict={
"Synthesis":{
"BatchSynthesis":
{
"fixedParams":
{
"BatchSynthesis=Sequence":["AddSolution_Citrate","AddSolution_H2O2", "AddSolution_NaBH4","Stir","Heat","Mix", "AddSolution_AgNO3", "React"],
"AddSolution=H2O2_Concentration" : 0.375,
"AddSolution=H2O2_Volume" : 1200,
"AddSolution=H2O2_Injectionrate" : 200,
"AddSolution=Citrate_Concentration" : 0.02,
"AddSolution=Citrate_Volume" : 1200,
"AddSolution=Citrate_Injectionrate" : 200,
"AddSolution=NaBH4_Concentration" : 0.01,
"AddSolution=NaBH4_Volume" : 3000,
"AddSolution=NaBH4_Injectionrate" : 200,
"Stir=StirRate":800,
"Heat=Temperature":25,
"Wait=Time":1,
"React=Time":1
},
},
"FlowSynthesis":{}
},
"Preprocess":{
"Washing":{},
"Ink":{}
},
"Characterization":{
"UV":
{
"fixedParams":
{
"UV=Sequence":["GetAbs"]
},
}
},
"Evaluation":{
"RDE":{},
"Electrode":{}
}
}
TaskLogger_obj=TaskLogger(metadata_dict)
TaskGenerator_obj=TaskGenerator(TaskLogger_obj)
import time
for i in range(2):
dict_obj = TaskGenerator_obj.allocateTaskSequence(recipe_dict, input_next_point)
time.sleep(2)
TaskGenerator_obj.saveRecipeToJSON(dict_obj=dict_obj, file_name="1234_{}.json".format(i), mode_type="virtual")