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Datenstrukturen und Auswertung angepasst

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This commit is contained in:
Markus Clauß
2023-03-17 14:54:19 +01:00
parent ecaf97bbb3
commit 471fa8dabf
42 changed files with 613 additions and 131 deletions
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0
src/paveit/__init__.py Normal file → Executable file
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0
src/paveit/analysis/__init__.py Normal file → Executable file
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0
src/paveit/analysis/regression.py Normal file → Executable file
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4
src/paveit/datamodels/__init__.py Normal file → Executable file
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@@ -1,7 +1,11 @@
from .citt import *
from .data import *
from .enumeration import *
from .infrastructure import *
from .material import *
from .metrics import *
from .project import *
from .sheartest import *
from .taskmanager import *
from .usermanagement import *
from .workpackage import *

100
src/paveit/datamodels/citt.py Normal file → Executable file
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@@ -2,10 +2,7 @@ import datetime
from mongoengine import *
from .material import Material
from .project import Project
from .usermanagement import Organisation, User
from .workpackage import Workpackage
from .taskmanager import TaskManagerBase
class CyclicIndirectTensileTest(Document):
@@ -17,19 +14,16 @@ class CyclicIndirectTensileTest(Document):
standard = StringField(default='TP Asphalt Teil 24')
org_id = LazyReferenceField(Organisation, required=True)
project_id = LazyReferenceField(Project, required=True)
workpackage_id = LazyReferenceField(Workpackage, required=False)
#org_id = LazyReferenceField(Organisation, required=True)
user_id = LazyReferenceField(User,
required=True,
reverse_delete_rule=DO_NOTHING)
#user_id = LazyReferenceField(User,
# required=True,
# reverse_delete_rule=DO_NOTHING)
material = LazyReferenceField(Material, required=True)
task_id = LazyReferenceField(TaskManagerBase, required=True)
tags = ListField(StringField())
machine = StringField(default=None)
filehash = StringField(required=True)
speciment_name = StringField()
@@ -69,8 +63,23 @@ class CITTSiffnessResults(CyclicIndirectTensileTest):
F_offset = FloatField()
F_slope = FloatField()
F_r2 = FloatField()
F_cycle_min = ListField(FloatField())
F_min = FloatField()
F_min_std = FloatField()
F_min_diff_rel = FloatField()
F_cycle_max = ListField(FloatField())
F_max = FloatField()
F_max_std = FloatField()
F_max_diff_rel = FloatField()
F_cycle_mean = ListField(FloatField())
F_mean = FloatField()
F_mean_std = FloatField()
F_mean_diff_rel = FloatField()
F_cycle_diff = ListField(FloatField())
F_diff = FloatField()
F_diff_std = FloatField()
F_diff_diff_rel= FloatField()
## S1
s_hor_1_amp = FloatField()
s_hor_1_freq = FloatField()
@@ -78,8 +87,22 @@ class CITTSiffnessResults(CyclicIndirectTensileTest):
s_hor_1_offset = FloatField()
s_hor_1_slope = FloatField()
s_hor_1_r2 = FloatField()
s_hor_1_cycle_min = ListField(FloatField())
s_hor_1_min = FloatField()
s_hor_1_min_std = FloatField()
s_hor_1_min_diff_rel = FloatField()
s_hor_1_cycle_max = ListField(FloatField())
s_hor_1_max = FloatField()
s_hor_1_max_std = FloatField()
s_hor_1_max_diff_rel = FloatField()
s_hor_1_cycle_mean = ListField(FloatField())
s_hor_1_mean = FloatField()
s_hor_1_mean_std = FloatField()
s_hor_1_mean_diff_rel = FloatField()
s_hor_1_cycle_diff = ListField(FloatField())
s_hor_1_diff = FloatField()
s_hor_1_diff_std = FloatField()
s_hor_1_diff_diff_rel = FloatField()
## S2
s_hor_2_amp = FloatField()
s_hor_2_freq = FloatField()
@@ -87,8 +110,22 @@ class CITTSiffnessResults(CyclicIndirectTensileTest):
s_hor_2_offset = FloatField()
s_hor_2_slope = FloatField()
s_hor_2_r2 = FloatField()
s_hor_2_cycle_min = ListField(FloatField())
s_hor_2_min = FloatField()
s_hor_2_min_std = FloatField()
s_hor_2_min_diff_rel = FloatField()
s_hor_2_cycle_max = ListField(FloatField())
s_hor_2_max = FloatField()
s_hor_2_max_std = FloatField()
s_hor_2_max_diff_rel = FloatField()
s_hor_2_cycle_mean = ListField(FloatField())
s_hor_2_mean = FloatField()
s_hor_2_mean_std = FloatField()
s_hor_2_mean_diff_rel = FloatField()
s_hor_2_cycle_diff = ListField(FloatField())
s_hor_2_diff = FloatField()
s_hor_2_diff_std = FloatField()
s_hor_2_diff_diff_rel = FloatField()
## S-Sum
s_hor_sum_amp = FloatField()
s_hor_sum_freq = FloatField()
@@ -96,7 +133,44 @@ class CITTSiffnessResults(CyclicIndirectTensileTest):
s_hor_sum_offset = FloatField()
s_hor_sum_slope = FloatField()
s_hor_sum_r2 = FloatField()
s_hor_sum_cycle_min = ListField(FloatField())
s_hor_sum_min = FloatField()
s_hor_sum_min_std = FloatField()
s_hor_sum_min_diff_rel = FloatField()
s_hor_sum_cycle_max = ListField(FloatField())
s_hor_sum_max = FloatField()
s_hor_sum_max_std = FloatField()
s_hor_sum_max_diff_rel = FloatField()
s_hor_sum_cycle_mean = ListField(FloatField())
s_hor_sum_mean = FloatField()
s_hor_sum_mean_std = FloatField()
s_hor_sum_mean_diff_rel = FloatField()
s_hor_sum_cycle_diff = ListField(FloatField())
s_hor_sum_diff = FloatField()
s_hor_sum_diff_std = FloatField()
s_hor_sum_diff_diff_rel = FloatField()
#optional parameter
#optional parameter
## Piston
s_hor_piston_amp = FloatField(required=False)
s_hor_piston_freq = FloatField(required=False)
s_hor_piston_phase = FloatField(required=False)
s_hor_piston_offset = FloatField(required=False)
s_hor_piston_slope = FloatField(required=False)
s_hor_piston_r2 = FloatField(required=False)
s_hor_piston_cycle_min = ListField(FloatField(),required=False)
s_hor_piston_min = FloatField(required=False)
s_hor_piston_min_std = FloatField(required=False)
s_hor_piston_min_diff_rel = FloatField(required=False)
s_hor_piston_cycle_max = ListField(FloatField(),required=False)
s_hor_piston_max = FloatField(required=False)
s_hor_piston_max_std = FloatField(required=False)
s_hor_piston_max_dif_rel = FloatField(required=False)
s_hor_piston_cycle_mean = ListField(FloatField(),required=False)
s_hor_piston_mean = FloatField(required=False)
s_hor_piston_mean_std = FloatField(required=False)
s_hor_piston_mean_diff_rel = FloatField(required=False)
s_hor_piston_cycle_diff = ListField(FloatField(),required=False)
s_hor_piston_diff = FloatField(required=False)
s_hor_piston_diff_std = FloatField(required=False)
s_hor_piston_diff_diff_rel = FloatField(required=False)

15
src/paveit/datamodels/client.py Normal file
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@@ -0,0 +1,15 @@
import datetime
from mongoengine import *
from .usermanagement import Organisation, User
class Client(Document):
org_id = LazyReferenceField(Organisation, required=True)
user_id = LazyReferenceField(User,
required=True,
reverse_delete_rule=DO_NOTHING)
clientid = StringField(max_length=100)

10
src/paveit/datamodels/data.py Normal file → Executable file
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@@ -13,6 +13,10 @@ class RawData(Document):
"step": "60"
}})
time = ListField(FloatField())
F = ListField(FloatField())
N = ListField(IntField())
meta = {
'allow_inheritance': True,
'index_opts': {},
@@ -32,9 +36,6 @@ class DataSheartest(RawData):
reverse_delete_rule=CASCADE)
# data
time = ListField(FloatField())
F = ListField(FloatField())
N = ListField(IntField())
s_vert_1 = ListField(FloatField())
s_vert_2 = ListField(FloatField())
s_piston = ListField(FloatField(), required=False)
@@ -49,9 +50,6 @@ class CITTSiffness(RawData):
reverse_delete_rule=CASCADE)
# data
time = ListField(FloatField())
F = ListField(FloatField())
N = ListField(IntField())
s_hor_1 = ListField(FloatField())
s_hor_2 = ListField(FloatField())
s_hor_sum = ListField(FloatField())

6
src/paveit/datamodels/enumeration.py Normal file
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@@ -0,0 +1,6 @@
from enum import Enum
class LabtestsEnum(Enum):
CITTStiffness = 'CITTStiffness'
SHEARStiffness = 'SheartestStiffness'

16
src/paveit/datamodels/infrastructure.py Normal file
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@@ -0,0 +1,16 @@
from mongoengine import *
class MachineBase(Document):
name = StringField(default=None)
meta = {
'allow_inheritance': True,
'index_opts': {},
'index_background': True,
'index_cls': False,
'auto_create_index': True,
'collection': 'infrastructure',
"db_alias": 'dblabtests',
}

1
src/paveit/datamodels/material.py Normal file → Executable file
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@@ -37,6 +37,7 @@ class Material(Document):
'index_cls': False,
'auto_create_index': True,
'collection': 'materials',
"db_alias": 'dblabtests',
'indexes': [
[("material", 1)],
[("name", 1)],

50
src/paveit/datamodels/metrics.py Normal file
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@@ -0,0 +1,50 @@
import datetime
from mongoengine import *
from .project import Project
from .usermanagement import User, Organisation
from .workpackage import Workpackage
class MetricsBase(Document):
date = DateTimeField(default=datetime.datetime.now,
wtf_options={"render_kw": {
"step": "60"
}})
app = StringField(required=True, default='backend')
method = StringField(required=True)
url = StringField(required=False)
client = StringField(required=False)
status_code = IntField(required=False)
meta = {
'allow_inheritance': True,
'index_opts': {},
'index_background': True,
'index_cls': False,
'auto_create_index': True,
'collection': 'metrics',
"db_alias": 'dblabtests',
}
class MetricsBackend(MetricsBase):
project_id = LazyReferenceField(Project, required=False)
user_id = LazyReferenceField(User,required=False)
workpackage_id = LazyReferenceField(Workpackage, required=False)
org_id = LazyReferenceField(Organisation, required=False)
runtime = FloatField() # in s
task = StringField(max_length=30)

13
src/paveit/datamodels/project.py Normal file → Executable file
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@@ -2,15 +2,17 @@ import datetime
from mongoengine import *
from .client import Client
from .usermanagement import Organisation, User
class Project(Document):
name = StringField(required=True)
name_short = StringField(required=False)
project_id = StringField(required=True)
client = StringField(required=False)
client = LazyReferenceField(Client,
required=True,
reverse_delete_rule=CASCADE)
date = DateTimeField(default=datetime.datetime.now,
wtf_options={"render_kw": {
@@ -24,6 +26,10 @@ class Project(Document):
user_id = LazyReferenceField(User,
required=False,
reverse_delete_rule=DO_NOTHING)
name = StringField(required=True)
name_short = StringField(required=False)
tags = ListField(StringField())
@@ -34,6 +40,7 @@ class Project(Document):
'index_cls': False,
'auto_create_index': True,
'collection': 'projects',
"db_alias": 'dblabtests',
'indexes': [
[("name_short", 1)],
[("name", 1)],

204
src/paveit/datamodels/sheartest.py Normal file → Executable file
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@@ -2,10 +2,7 @@ import datetime
from mongoengine import *
from .material import Material
from .project import Project
from .usermanagement import Organisation, User
from .workpackage import Workpackage
from .taskmanager import TaskManagerBase
class DynamicShearTest(Document):
@@ -14,26 +11,14 @@ class DynamicShearTest(Document):
wtf_options={"render_kw": {
"step": "60"
}})
org_id = LazyReferenceField(Organisation, required=True)
project_id = LazyReferenceField(Project, required=True)
workpackage_id = LazyReferenceField(Workpackage, required=False)
user_id = LazyReferenceField(User,
required=True,
reverse_delete_rule=DO_NOTHING)
material1 = LazyReferenceField(Material, required=True)
material2 = LazyReferenceField(Material, required=True)
bounding = LazyReferenceField(Material, required=True)
task_id = LazyReferenceField(TaskManagerBase, required=True)
gap_width = FloatField(default=1.0)
tags = ListField(StringField())
standard = StringField(default='TP Asphalt Teil 24')
machine = StringField(default=None)
standard = StringField(default='TP Asphalt Teil 48 C')
filehash = StringField(required=True)
speciment_name = StringField()
@@ -79,6 +64,8 @@ class DynamicShearTestExtension(DynamicShearTest):
G = FloatField(required=True)
broken = BooleanField(required=True)
phase = FloatField()
#fit parameter
## required parameters
@@ -89,55 +76,117 @@ class DynamicShearTestExtension(DynamicShearTest):
F_offset = FloatField(required=True)
F_slope = FloatField(required=True)
F_r2 = FloatField(required=True)
F_max = FloatField(required=True)
F_min = FloatField(required=True)
F_cycle_min = ListField(FloatField())
F_min = FloatField()
F_min_std = FloatField()
F_min_diff_rel = FloatField()
F_cycle_max = ListField(FloatField())
F_max = FloatField()
F_max_std = FloatField()
F_max_diff_rel = FloatField()
F_cycle_mean = ListField(FloatField())
F_mean = FloatField()
F_mean_std = FloatField()
F_mean_diff_rel = FloatField()
F_cycle_diff = ListField(FloatField())
F_diff = FloatField()
F_diff_std = FloatField()
F_diff_diff_rel= FloatField()
## S1
s_vert_1_amp = FloatField(required=True)
s_vert_1_freq = FloatField(required=True)
s_vert_1_phase = FloatField(required=True)
s_vert_1_offset = FloatField(required=True)
s_vert_1_slope = FloatField(required=True)
s_vert_1_r2 = FloatField(required=True)
s_vert_1_max = FloatField(required=True)
s_vert_1_min = FloatField(required=True)
s_vert_1_amp = FloatField()
s_vert_1_freq = FloatField()
s_vert_1_phase = FloatField()
s_vert_1_offset = FloatField()
s_vert_1_slope = FloatField()
s_vert_1_r2 = FloatField()
s_vert_1_cycle_min = ListField(FloatField())
s_vert_1_min = FloatField()
s_vert_1_min_std = FloatField()
s_vert_1_min_diff_rel = FloatField()
s_vert_1_cycle_max = ListField(FloatField())
s_vert_1_max = FloatField()
s_vert_1_max_std = FloatField()
s_vert_1_max_diff_rel = FloatField()
s_vert_1_cycle_mean = ListField(FloatField())
s_vert_1_mean = FloatField()
s_vert_1_mean_std = FloatField()
s_vert_1_mean_diff_rel = FloatField()
s_vert_1_cycle_diff = ListField(FloatField())
s_vert_1_diff = FloatField()
s_vert_1_diff_std = FloatField()
s_vert_1_diff_diff_rel = FloatField()
## S2
s_vert_2_amp = FloatField(required=True)
s_vert_2_freq = FloatField(required=True)
s_vert_2_phase = FloatField(required=True)
s_vert_2_offset = FloatField(required=True)
s_vert_2_slope = FloatField(required=True)
s_vert_2_r2 = FloatField(required=True)
s_vert_2_max = FloatField(required=True)
s_vert_2_min = FloatField(required=True)
s_vert_2_amp = FloatField()
s_vert_2_freq = FloatField()
s_vert_2_phase = FloatField()
s_vert_2_offset = FloatField()
s_vert_2_slope = FloatField()
s_vert_2_r2 = FloatField()
s_vert_2_cycle_min = ListField(FloatField())
s_vert_2_min = FloatField()
s_vert_2_min_std = FloatField()
s_vert_2_min_diff_rel = FloatField()
s_vert_2_cycle_max = ListField(FloatField())
s_vert_2_max = FloatField()
s_vert_2_max_std = FloatField()
s_vert_2_max_diff_rel = FloatField()
s_vert_2_cycle_mean = ListField(FloatField())
s_vert_2_mean = FloatField()
s_vert_2_mean_std = FloatField()
s_vert_2_mean_diff_rel = FloatField()
s_vert_2_cycle_diff = ListField(FloatField())
s_vert_2_diff = FloatField()
s_vert_2_diff_std = FloatField()
s_vert_2_diff_diff_rel = FloatField()
## S-Sum
s_vert_sum_amp = FloatField()
s_vert_sum_freq = FloatField()
s_vert_sum_phase = FloatField()
s_vert_sum_offset = FloatField()
s_vert_sum_slope = FloatField()
s_vert_sum_r2 = FloatField()
s_vert_sum_cycle_min = ListField(FloatField())
s_vert_sum_min = FloatField()
s_vert_sum_min_std = FloatField()
s_vert_sum_min_diff_rel = FloatField()
s_vert_sum_cycle_max = ListField(FloatField())
s_vert_sum_max = FloatField()
s_vert_sum_max_std = FloatField()
s_vert_sum_max_diff_rel = FloatField()
s_vert_sum_cycle_mean = ListField(FloatField())
s_vert_sum_mean = FloatField()
s_vert_sum_mean_std = FloatField()
s_vert_sum_mean_diff_rel = FloatField()
s_vert_sum_cycle_diff = ListField(FloatField())
s_vert_sum_diff = FloatField()
s_vert_sum_diff_std = FloatField()
s_vert_sum_diff_diff_rel = FloatField()
## optional parameters
s_vert_sum_amp = FloatField(required=False)
s_vert_sum_freq = FloatField(required=False)
s_vert_sum_phase = FloatField(required=False)
s_vert_sum_offset = FloatField(required=False)
s_vert_sum_slope = FloatField(required=False)
s_vert_sum_r2 = FloatField(required=False)
s_vert_sum_max = FloatField(required=False)
s_vert_sum_min = FloatField(required=False)
s_hor_sum_amp = FloatField(required=False)
s_hor_sum_freq = FloatField(required=False)
s_hor_sum_phase = FloatField(required=False)
s_hor_sum_offset = FloatField(required=False)
s_hor_sum_slope = FloatField(required=False)
s_hor_sum_r2 = FloatField(required=False)
s_hor_sum_max = FloatField(required=False)
s_hor_sum_min = FloatField(required=False)
## S1
s_hor_1_amp = FloatField(required=False)
s_hor_1_freq = FloatField(required=False)
s_hor_1_phase = FloatField(required=False)
s_hor_1_offset = FloatField(required=False)
s_hor_1_slope = FloatField(required=False)
s_hor_1_r2 = FloatField(required=False)
s_hor_1_max = FloatField(required=False)
s_hor_1_cycle_min = ListField(FloatField(),required=False)
s_hor_1_min = FloatField(required=False)
s_hor_1_min_std = FloatField(required=False)
s_hor_1_min_diff_rel = FloatField(required=False)
s_hor_1_cycle_max = ListField(FloatField(),required=False)
s_hor_1_max = FloatField(required=False)
s_hor_1_max_std = FloatField(required=False)
s_hor_1_max_diff_rel = FloatField(required=False)
s_hor_1_cycle_mean = ListField(FloatField(),required=False)
s_hor_1_mean = FloatField(required=False)
s_hor_1_mean_std = FloatField(required=False)
s_hor_1_mean_diff_rel = FloatField(required=False)
s_hor_1_cycle_diff = ListField(FloatField(),required=False)
s_hor_1_diff = FloatField(required=False)
s_hor_1_diff_std = FloatField(required=False)
s_hor_1_diff_diff_rel = FloatField(required=False)
## S2
s_hor_2_amp = FloatField(required=False)
s_hor_2_freq = FloatField(required=False)
@@ -145,5 +194,42 @@ class DynamicShearTestExtension(DynamicShearTest):
s_hor_2_offset = FloatField(required=False)
s_hor_2_slope = FloatField(required=False)
s_hor_2_r2 = FloatField(required=False)
s_hor_2_cycle_min = ListField(FloatField(),required=False)
s_hor_2_min = FloatField(required=False)
s_hor_2_min_std = FloatField(required=False)
s_hor_2_min_diff_rel = FloatField(required=False)
s_hor_2_cycle_max = ListField(FloatField(),required=False)
s_hor_2_max = FloatField(required=False)
s_hor_2_min = FloatField(required=False)
s_hor_2_max_std = FloatField(required=False)
s_hor_2_max_diff_rel = FloatField(required=False)
s_hor_2_cycle_mean = ListField(FloatField(), required=False)
s_hor_2_mean = FloatField(required=False)
s_hor_2_mean_std = FloatField(required=False)
s_hor_2_mean_diff_rel = FloatField(required=False)
s_hor_2_cycle_diff = ListField(FloatField(), required=False)
s_hor_2_diff = FloatField(required=False)
s_hor_2_diff_std = FloatField(required=False)
s_hor_2_diff_diff_rel = FloatField(required=False)
## Piston
s_hor_piston_amp = FloatField(required=False)
s_hor_piston_freq = FloatField(required=False)
s_hor_piston_phase = FloatField(required=False)
s_hor_piston_offset = FloatField(required=False)
s_hor_piston_slope = FloatField(required=False)
s_hor_piston_r2 = FloatField(required=False)
s_hor_piston_cycle_min = ListField(FloatField(),required=False)
s_hor_piston_min = FloatField(required=False)
s_hor_piston_min_std = FloatField(required=False)
s_hor_piston_min_diff_rel = FloatField(required=False)
s_hor_piston_cycle_max = ListField(FloatField(),required=False)
s_hor_piston_max = FloatField(required=False)
s_hor_piston_max_std = FloatField(required=False)
s_hor_piston_max_dif_rel = FloatField(required=False)
s_hor_piston_cycle_mean = ListField(FloatField(),required=False)
s_hor_piston_mean = FloatField(required=False)
s_hor_piston_mean_std = FloatField(required=False)
s_hor_piston_mean_diff_rel = FloatField(required=False)
s_hor_piston_cycle_diff = ListField(FloatField(),required=False)
s_hor_piston_diff = FloatField(required=False)
s_hor_piston_diff_std = FloatField(required=False)
s_hor_piston_diff_diff_rel = FloatField(required=False)

54
src/paveit/datamodels/taskmanager.py Normal file
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@@ -0,0 +1,54 @@
import datetime
from mongoengine import *
from .infrastructure import MachineBase
from .material import Material
from .project import Project
from .usermanagement import Organisation, User
from .workpackage import Workpackage
class TaskManagerBase(Document):
org_id = LazyReferenceField(Organisation, required=True)
user_id = LazyReferenceField(User, required=True)
project_id = LazyReferenceField(Project, required=True)
wp_id = LazyReferenceField(Workpackage, required=False)
finieshed = BooleanField(default=False)
task_added = DateTimeField(default=datetime.datetime.now,
wtf_options={"r ender_kw": {
"step": "60"
}})
task_finished = DateTimeField(required=False)
assign_users = ListField(LazyReferenceField(User), required=False)
assign_machines = ListField(LazyReferenceField(MachineBase), required=False)
series = StringField(default='Serie 01')
meta = {
'allow_inheritance': True,
'index_opts': {},
'index_background': True,
'index_cls': False,
'auto_create_index': True,
'collection': 'taskmanager',
"db_alias": 'dblabtests',
}
class TaskCITTStiffness(TaskManagerBase):
material = LazyReferenceField(Material, required=True)
class TaskDynShearStiffness(TaskManagerBase):
material1 = LazyReferenceField(Material, required=True)
material2 = LazyReferenceField(Material, required=True)
bounding = LazyReferenceField(Material, required=True)

11
src/paveit/datamodels/usermanagement.py Normal file → Executable file
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@@ -23,7 +23,7 @@ class Organisation(Document):
'index_cls': False,
'auto_create_index': True,
'collection': 'organisation',
'db_alias': 'dbusers',
'db_alias': 'dblabtests',
}
@@ -40,7 +40,11 @@ class User(Document):
"step": "60"
}})
name = StringField(required=True)
name = StringField(required=False)
email = EmailField(required=True)
password = StringField(required=True)
meta = {
'allow_inheritance': True,
@@ -48,5 +52,6 @@ class User(Document):
'index_background': True,
'index_cls': False,
'auto_create_index': True,
'collection': 'user'
'collection': 'user',
'db_alias': 'dblabtests',
}

3
src/paveit/datamodels/workpackage.py Normal file → Executable file
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@@ -29,5 +29,6 @@ class Workpackage(Document):
'index_background': True,
'index_cls': False,
'auto_create_index': True,
'collection': 'workpackages'
'collection': 'workpackages',
"db_alias": 'dblabtests',
}

0
src/paveit/functions/__init__.py Normal file → Executable file
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0
src/paveit/functions/citt.py Normal file → Executable file
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0
src/paveit/helper/__init__.py Normal file → Executable file
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0
src/paveit/helper/filehandling.py Normal file → Executable file
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0
src/paveit/helper/filehasher.py Normal file → Executable file
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0
src/paveit/helper/minio.py Normal file → Executable file
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0
src/paveit/helper/mongo.py Normal file → Executable file
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0
src/paveit/io/__init__.py Normal file → Executable file
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0
src/paveit/io/geosys.py Normal file → Executable file
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0
src/paveit/labtest/__init__.py Normal file → Executable file
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20
src/paveit/labtest/base.py Normal file → Executable file
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@@ -118,6 +118,19 @@ class DataSineLoad():
self.filehash = calc_hash_of_bytes(self.data)
self.data.seek(0)
self._logger.debug(f'Hash of file: {self.filehash}')
def _define_data_models(self):
pass
def _data_in_db(self):
nsamples = self._datamodel.objects(filehash = self.filehash).count()
if nsamples>0:
self.file_in_db = True
else:
self.file_in_db = False
def _process_data(self):
""" convert self.data (BytesIO) to pandas.DataFrame, update
@@ -194,8 +207,11 @@ class DataSineLoad():
return
for col in sel.columns:
self.data[col] = pd.to_numeric(self.data[col].str.replace(
try:
self.data[col] = pd.to_numeric(self.data[col].str.replace(
',', '.'))
except:
pass
def _post_apply_units(self):
@@ -342,6 +358,8 @@ class DataSineLoad():
self._read_from_s3_to_bytesio()
self._calc_hash_of_bytesio()
self._define_data_models()
self._data_in_db()
self._which_machine()
self._set_parameter()
self.update_parameter()

159
src/paveit/labtest/citt.py Normal file → Executable file
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@@ -5,6 +5,7 @@ from csv import reader
import numpy as np
import pandas as pd
from bson import ObjectId
from paveit import calc_nu, fit_cos
from paveit.datamodels import CITTSiffness, CITTSiffnessResults
from paveit.io import read_geosys
@@ -135,14 +136,43 @@ class CITTBase(DataSineLoad):
if not col in data.columns: continue
y = data[col].values
res = fit_cos(x, y, freq=freq)
for key, value in res.items():
res_temp[f'fit_{col}_{key}'] = value
res_temp[f'fit_{col}_max'] = max(y)
res_temp[f'fit_{col}_min'] = min(y)
# analyse cycle data
cycle_min = []
cycle_max = []
cycle_mean = []
cycle_diff = []
for N, data_cycle in data.groupby('N'):
y = data_cycle[col].values
cycle_min.append(y.min())
cycle_max.append(y.max())
cycle_mean.append(y.mean())
cycle_diff.append(cycle_max[-1] - cycle_min[-1])
res_temp[f'fit_{col}_cycle_min'] = cycle_min
res_temp[f'fit_{col}_min'] = np.mean(cycle_min)
res_temp[f'fit_{col}_min_std'] = np.std(cycle_min)
res_temp[f'fit_{col}_min_diff_rel'] = (np.max(cycle_min) - np.min(cycle_min))/np.mean(cycle_min)
res_temp[f'fit_{col}_cycle_max'] = cycle_max
res_temp[f'fit_{col}_max'] = np.mean(cycle_max)
res_temp[f'fit_{col}_max_std'] = np.std(cycle_max)
res_temp[f'fit_{col}_max_diff_rel'] = (np.max(cycle_max) - np.min(cycle_max))/np.mean(cycle_max)
res_temp[f'fit_{col}_cycle_mean'] = cycle_mean
res_temp[f'fit_{col}_mean'] = np.mean(cycle_mean)
res_temp[f'fit_{col}_mean_std'] = np.std(cycle_mean)
res_temp[f'fit_{col}_mean_diff_rel'] = (np.max(cycle_mean) - np.min(cycle_mean))/np.mean(cycle_mean)
res_temp[f'fit_{col}_cycle_diff'] = cycle_diff
res_temp[f'fit_{col}_diff'] = np.mean(cycle_diff)
res_temp[f'fit_{col}_diff_std'] = np.std(cycle_diff)
res_temp[f'fit_{col}_diff_diff_rel'] = (np.max(cycle_diff) - np.min(cycle_diff))/np.mean(cycle_diff)
# add more metadata
res_temp['f_set'] = freq
@@ -186,12 +216,9 @@ class CITTBase(DataSineLoad):
self._logger.debug(self.fit['stiffness'])
def save(self,
org_id: ObjectId,
project_id: ObjectId,
material_id: ObjectId,
user_id: ObjectId,
meta: dict = {},
wp_id: ObjectId | None = None):
task_id: ObjectId,
meta: dict = {}
):
"""
save results to mongodb
"""
@@ -200,16 +227,13 @@ class CITTBase(DataSineLoad):
raise
# precheck data and results
assert len(self.data) == len(self.fit)
#assert len(self.data) == len(self.fit)
for idx_fit, fit in self.fit.iterrows():
data = self.data[idx_fit]
meta['filehash'] = self.filehash
meta['org_id'] = org_id
meta['project_id'] = project_id
meta['material'] = material_id
meta['user_id'] = user_id
meta['task_id'] = task_id
#check if result in db
#n = CITTSiffness.objects(**meta).count()
@@ -726,11 +750,13 @@ class CITT_LaborHart(CITTBase):
data.columns = head
# FIX: Sigma nicht in Metadaten oder Messdaten enthalten
sigma = float(
os.path.split(self.filename)[-1].split('MPa')[0].strip().replace(
',', '.'))
print(meta)
if not "sigma" in self.metadata:
sigma = float(
os.path.split(self.filename)[-1].split('MPa')[0].strip().replace(
',', '.'))
meta['sigma'] = sigma
meta['sigma'] = sigma
#clean data
data = data.dropna(axis=1)
@@ -847,3 +873,100 @@ class CITT_BAGKoeln(CITTBase):
# log infos
self._logger.info(self.metadata)
self._logger.info(self.data.head())
class CITT_Braunschweig(CITTBase):
def _define_units(self):
self.unit_s = 1.0 #mm
self.unit_F = -1000.0 #N
self.unit_t = 1.0
def update_parameter(self):
self.meta_names_of_parameter = {
't': ['t [s]'],
} #list of names
self.data_column_names = {
'time': ['t [s]'],
'f': [ 'FREQUENZ_x10'],
'F': [ 'F act [kN]'],
's_hor_1': ['r 1A [mm]'],
's_hor_2': ['r 1B [mm]'],
's_piston': ['s piston [mm]'],
}
def _process_data(self):
self._logger.info(self.metadata)
meta = {}
encoding = 'latin-1'
self.data.seek(0)
head = pd.read_csv(self.data,
skiprows=14,
sep=';',
nrows=1,
encoding=encoding,
decimal=',',
thousands='.',
skip_blank_lines=True).columns
head = [h.strip() for h in head]
self.data.seek(0)
data = pd.read_csv(self.data,
skiprows=20,
sep=';',
encoding=encoding,
decimal=',',
thousands='.',
header=None,
skip_blank_lines=True)
data.columns = head
# add frequency
## [start, ncycles]
sel = {0.1: [0, 11], 1.0: [11, 20], 5.0: [30, 100], 10: [130, 111]}
N_f_dict = {}
Ns = 0
for freq in sel.keys():
par = sel[freq]
N = par[0]
dN = par[1]
for i in range(N, N + dN):
N_f_dict[Ns] = freq
Ns += 1
data['f'] = data['N'].replace(N_f_dict)
data = data[data['f'] <= 10.0]
#sigma
data['sigma'] = self.metadata['sigma']
data['T'] = self.metadata['temperature']
#clean data
#data = data.dropna(axis=0)
#data = data.dropna(axis=1)
data = data.drop(columns=['Date Time'])
#define in class
self.data = data
self.metadata.update(meta)
# log infos
self._logger.info(self.metadata)
self._logger.info(self.data.head())

77
src/paveit/labtest/sheartest.py Normal file → Executable file
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@@ -6,6 +6,7 @@ import lmfit as lm
import numpy as np
import pandas as pd
from bson import ObjectId
from paveit import calc_nu, fit_cos
from paveit.datamodels import DataSheartest, DynamicShearTestExtension
from paveit.io import read_geosys
@@ -107,19 +108,20 @@ class ShearTest(DataSineLoad):
class ShearTestExtension(ShearTest):
def _define_data_models(self):
self._datamodel = DynamicShearTestExtension
self._datamodel_raw = DataSheartest
def save(
self,
org_id: ObjectId,
project_id: ObjectId,
material_1_id: ObjectId,
material_2_id: ObjectId,
material_boundary_id: ObjectId,
user_id: ObjectId,
task_id: ObjectId,
broken: bool,
gap_width: float, #mm
meta: dict = {},
wp_id: ObjectId | None = None,
broken: bool = False,
gap_width: float = 1.0, #mm
):
"""
save results to mongodb
@@ -133,20 +135,11 @@ class ShearTestExtension(ShearTest):
for idx_fit, fit in self.fit.iterrows():
data = self.data[idx_fit]
meta['task_id'] = org_id
meta['gap_width'] = gap_width
meta['filehash'] = self.filehash
meta['org_id'] = org_id
meta['project_id'] = project_id
meta['workpackage_id'] = wp_id
meta['user_id'] = user_id
meta['material1'] = material_1_id
meta['material2'] = material_2_id
meta['bounding'] = material_boundary_id
#check if result in db
#n = CITTSiffness.objects(**meta).count()
#print(n)
meta['speciment_name'] = self.filename
# write data
data_dict = fit.to_dict()
@@ -164,7 +157,7 @@ class ShearTestExtension(ShearTest):
d[new] = d[old]
d.pop(old)
f = DynamicShearTestExtension(**data_dict).save()
f = self._datamodel (**data_dict).save()
# required data
data_out = dict(
@@ -180,7 +173,7 @@ class ShearTestExtension(ShearTest):
if col in data.columns:
data_out[col] = list(data[col])
g = DataSheartest(result=f.id, **data_out).save()
g = self._datamodel_raw(result=f.id, **data_out).save()
def _fit_select_data(self):
"""
@@ -261,8 +254,38 @@ class ShearTestExtension(ShearTest):
for key, value in res.items():
res_temp[f'fit_{col}_{key}'] = value
res_temp[f'fit_{col}_max'] = max(y)
res_temp[f'fit_{col}_min'] = min(y)
# analyse cycle data
cycle_min = []
cycle_max = []
cycle_mean = []
cycle_diff = []
for N, data_cycle in data.groupby('N'):
y = data_cycle[col].values
cycle_min.append(y.min())
cycle_max.append(y.max())
cycle_mean.append(y.mean())
cycle_diff.append(cycle_max[-1] - cycle_min[-1])
res_temp[f'fit_{col}_cycle_min'] = cycle_min
res_temp[f'fit_{col}_min'] = np.mean(cycle_min)
res_temp[f'fit_{col}_min_std'] = np.std(cycle_min)
res_temp[f'fit_{col}_min_diff_rel'] = abs((np.max(cycle_min) - np.min(cycle_min))/np.mean(cycle_min))
res_temp[f'fit_{col}_cycle_max'] = cycle_max
res_temp[f'fit_{col}_max'] = np.mean(cycle_max)
res_temp[f'fit_{col}_max_std'] = np.std(cycle_max)
res_temp[f'fit_{col}_max_diff_rel'] = abs((np.max(cycle_max) - np.min(cycle_max))/np.mean(cycle_max))
res_temp[f'fit_{col}_cycle_mean'] = cycle_mean
res_temp[f'fit_{col}_mean'] = np.mean(cycle_mean)
res_temp[f'fit_{col}_mean_std'] = np.std(cycle_mean)
res_temp[f'fit_{col}_mean_diff_rel'] = abs((np.max(cycle_mean) - np.min(cycle_mean))/np.mean(cycle_mean))
res_temp[f'fit_{col}_cycle_diff'] = cycle_diff
res_temp[f'fit_{col}_diff'] = np.mean(cycle_diff)
res_temp[f'fit_{col}_diff_std'] = np.std(cycle_diff)
res_temp[f'fit_{col}_diff_diff_rel'] = abs((np.max(cycle_diff) - np.min(cycle_diff))/np.mean(cycle_diff))
# add more metadata
res_temp['f_set'] = freq
@@ -288,9 +311,9 @@ class ShearTestExtension(ShearTest):
res_temp['G'] = tau / gamma
#metadaten
#for c in ['T', 'extension', 'sigma_normal', 'f']:
# res_temp[c] = res_temp[c][0]
# TODO: Überarbeiten und erweitern (ISSUE #2)
res_temp['phase'] = res_temp['fit_F_phase'] - res_temp[
'fit_s_vert_sum_phase']
self.fit.append(res_temp)