Inspect¶
BEEP inspect is a debugging and analysis command which can be used to examine any serialized beep object directly from the command line.
The objects that can be inspected are:
- Raw cycler files compatible with BEEP, which will be ingested and represented as a
BEEPDatapath. Example: Inspect Raw Files - Structured cycler files serialized by BEEP to disk as json, represented as a
BEEPDatapath. Example: Inspect Structured Files - Feature matrices serialized to disk as json. Example: Inspect Feature Matrices
- Individual
BEEPFeaturizers serialized to disk as json. Example: Inspect Featurizers - Linear
BEEPLinearModelExperiments serialized to disk as json. Example: Inspect Models
Inspect help dialog¶
$: beep inspect --help
Usage: beep inspect [OPTIONS] FILE
View BEEP files for debugging and analysis.
Options:
--help Show this message and exit.
Inspect Raw Files¶
Example:
S: beep inspect PreDiag_000287_000128.092
2021-09-22 16:01:33 DEBUG Loaded potential raw file beep/tests/test_files/PreDiag_000287_000128.092 as Datapath.
2021-09-22 16:01:34 INFO Loaded beep/tests/test_files/PreDiag_000287_000128.092 as type <class 'beep.structure.maccor.MaccorDatapath'>.
BEEP Datapath: beep/tests/test_files/PreDiag_000287_000128.092
Semiunique id: 'barcode:000128-channel:92-protocol:PreDiag_000287.000-schema:beep/validation_schemas/schema-maccor-2170.yaml-structured:False-legacy:False-raw_path:beep/tests/test_files/PreDiag_000287_000128.092-structured_path:None'
File paths
{'metadata': 'beep/tests/test_files/PreDiag_000287_000128.092',
'raw': 'beep/tests/test_files/PreDiag_000287_000128.092'}
File metadata:
{'_today_datetime': '12/17/2019',
'barcode': '000128',
'channel_id': 92,
'filename': 'C:\\Users\\Maccor Tester User\\Documents\\Backup\\STANFORD '
'LOANER #1\\STANFORD LOANER #1\\PreDiag_000287_000128.092',
'protocol': 'PreDiag_000287.000',
'start_datetime': '12/17/2019'}
Validation schema: beep/validation_schemas/schema-maccor-2170.yaml
Structuring parameters:
{}
Structured attributes:
structured_summary:
No object.
structured_data:
No object.
diagnostic_data:
No object.
diagnostic_summary:
No object.
raw_data:
data_point cycle_index step_index test_time step_time _capacity _energy current voltage _state _ending_status date_time loop1 loop2 loop3 loop4 ac_impedence internal_resistance _wf_chg_cap _wf_dis_cap ... _var2 _var3 _var4 _var5 _var6 _var7 _var8 _var9 _var10 _var11 _var12 _var13 _var14 _var15 charge_capacity discharge_capacity charge_energy discharge_energy date_time_iso temperature
0 1 0 1 0.00 0.000000 0.000000 0.000000 0.000000 3.458076 R 0 12/17/2019 09:51:51 0 0 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.000000 2019-12-17T17:51:51+00:00 NaN
1 2 0 1 30.00 30.000000 0.000000 0.000000 0.000000 3.457999 R 1 12/17/2019 09:52:20 0 0 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.000000 2019-12-17T17:52:20+00:00 NaN
2 3 0 1 60.00 60.000000 0.000000 0.000000 0.000000 3.457999 R 1 12/17/2019 09:52:50 0 0 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.000000 2019-12-17T17:52:50+00:00 NaN
3 4 0 1 89.42 89.419998 0.000000 0.000000 0.000000 3.458152 S 192 12/17/2019 09:53:20 0 0 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.000000 2019-12-17T17:53:20+00:00 NaN
4 5 0 1 89.42 89.419998 0.000000 0.000000 0.000000 3.458228 R 192 12/17/2019 11:15:57 0 0 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.000000 2019-12-17T19:15:57+00:00 NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
546943 546944 246 39 1958303.97 23211.070312 4.459139 16.402617 -0.691691 2.700771 D 5 01/09/2020 03:18:48 64541 22 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.011044 4.459139 8.126739 16.402617 2020-01-09T11:18:48+00:00 NaN
546944 546945 246 39 1958305.13 23212.230469 4.459362 16.403219 -0.691691 2.700008 D 133 01/09/2020 03:18:49 64541 22 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.011044 4.459362 8.126739 16.403219 2020-01-09T11:18:49+00:00 NaN
546945 546946 247 41 1958305.16 0.030000 0.000006 0.000016 1.618448 2.760967 C 0 01/09/2020 03:18:49 64541 22 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.011050 4.459362 8.126755 16.403219 2020-01-09T11:18:49+00:00 NaN
546946 546947 247 41 1958305.32 0.190000 0.000078 0.000215 1.612268 2.777752 C 5 01/09/2020 03:18:49 64541 22 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.011122 4.459362 8.126954 16.403219 2020-01-09T11:18:49+00:00 NaN
546947 546948 247 41 1958305.42 0.290000 0.000122 0.000340 1.612039 2.784771 C 5 01/09/2020 03:18:49 64541 22 0 0 0.0 0.0 NaN NaN ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.011167 4.459362 8.127079 16.403219 2020-01-09T11:18:49+00:00 NaN
[546948 rows x 44 columns]
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 546948 entries, 0 to 546947
Data columns (total 44 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 data_point 546948 non-null int32
1 cycle_index 546948 non-null int32
2 step_index 546948 non-null int16
3 test_time 546948 non-null float64
4 step_time 546948 non-null float32
5 _capacity 546948 non-null float64
6 _energy 546948 non-null float64
7 current 546948 non-null float32
8 voltage 546948 non-null float32
9 _state 546948 non-null object
10 _ending_status 546948 non-null category
11 date_time 546948 non-null object
12 loop1 546948 non-null int64
13 loop2 546948 non-null int64
14 loop3 546948 non-null int64
15 loop4 546948 non-null int64
16 ac_impedence 546948 non-null float32
17 internal_resistance 546948 non-null float32
18 _wf_chg_cap 0 non-null float32
19 _wf_dis_cap 0 non-null float32
20 _wf_chg_e 0 non-null float32
21 _wf_dis_e 0 non-null float32
22 _range 546948 non-null uint8
23 _var1 546948 non-null float16
24 _var2 546948 non-null float16
25 _var3 546948 non-null float16
26 _var4 546948 non-null float16
27 _var5 546948 non-null float16
28 _var6 546948 non-null float16
29 _var7 546948 non-null float16
30 _var8 546948 non-null float16
31 _var9 546948 non-null float16
32 _var10 546948 non-null float16
33 _var11 546948 non-null float16
34 _var12 546948 non-null float16
35 _var13 546948 non-null float16
36 _var14 546948 non-null float16
37 _var15 546948 non-null float16
38 charge_capacity 546948 non-null float64
39 discharge_capacity 546948 non-null float64
40 charge_energy 546948 non-null float64
41 discharge_energy 546948 non-null float64
42 date_time_iso 546948 non-null object
43 temperature 0 non-null float64
dtypes: category(1), float16(15), float32(9), float64(8), int16(1), int32(2), int64(4), object(3), uint8(1)
memory usage: 103.3+ MB
Inspect Structured Files¶
Example:
$: beep inspect 2017-12-04_4_65C-69per_6C_CH29_structured_new.json.gz
2021-09-22 16:04:01 INFO Loaded beep/tests/test_files/2017-12-04_4_65C-69per_6C_CH29_structured_new.json.gz as type <class 'beep.structure.arbin.ArbinDatapath'>.
BEEP Datapath: beep/tests/test_files/2017-12-04_4_65C-69per_6C_CH29_structured_new.json.gz
Semiunique id: 'barcode:EL151000429559-channel:28-protocol:2017-12-04_tests\20170630-4_65C_69per_6C.sdu-schema:beep/validation_schemas/schema-arbin-lfp.yaml-structured:True-legacy:True-raw_path:beep/tests/test_files/2017-12-04_4_65C-69per_6C_CH29.csv-structured_path:None'
File paths
{'metadata': 'beep/tests/test_files/2017-12-04_4_65C-69per_6C_CH29_Metadata.csv',
'raw': 'beep/tests/test_files/2017-12-04_4_65C-69per_6C_CH29.csv'}
File metadata:
{'barcode': 'EL151000429559',
'channel_id': 28,
'protocol': '2017-12-04_tests\\20170630-4_65C_69per_6C.sdu'}
Validation schema: beep/validation_schemas/schema-arbin-lfp.yaml
Structuring parameters:
{'charge_axis': 'charge_capacity',
'diagnostic_available': False,
'diagnostic_resolution': 500,
'discharge_axis': 'voltage',
'full_fast_charge': 0.8,
'nominal_capacity': 1.1,
'resolution': 1000,
'v_range': None}
Structured attributes:
structured_summary:
cycle_index discharge_capacity charge_capacity discharge_energy charge_energy dc_internal_resistance temperature_maximum temperature_average temperature_minimum date_time_iso energy_efficiency charge_throughput energy_throughput charge_duration time_temperature_integrated paused CV_time CV_current
0 0 1.940235 1.432850 6.142979 4.725729 0.029954 34.222515 32.666893 20.699526 2017-12-05T03:37:36+00:00 1.299901 1.432850 4.725729 32768.0 48977.078333 13312 50158.164062 0.000029
1 1 1.060343 1.061786 3.219735 3.703581 0.017906 35.375809 32.387295 30.235437 2017-12-06T04:33:04+00:00 0.869357 2.494636 8.429310 640.0 1927.509119 0 1577.987427 0.062837
2 2 1.065412 1.065450 3.235807 3.708392 0.017649 35.384602 32.472481 30.254265 2017-12-06T05:32:48+00:00 0.872563 3.560086 12.137702 640.0 1931.514632 0 1570.970459 0.046215
3 3 1.066605 1.066726 3.238866 3.711425 0.017506 35.265358 32.420013 30.159765 2017-12-06T06:32:32+00:00 0.872675 4.626812 15.849127 640.0 1995.445402 0 1552.032471 0.045087
4 4 1.066988 1.067148 3.239955 3.712645 0.017409 35.280449 32.407478 30.157305 2017-12-06T07:34:24+00:00 0.872681 5.693960 19.561773 512.0 1926.752726 0 1548.414551 0.052290
.. ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
183 183 1.033595 1.033812 3.046869 3.615792 0.016889 37.566158 32.988796 30.226278 2017-12-13T19:12:00+00:00 0.842656 194.065491 676.183533 640.0 2026.858687 0 1590.061523 0.034429
184 184 1.033454 1.033584 3.042845 3.613951 0.016827 37.129795 32.981796 30.181578 2017-12-13T20:13:52+00:00 0.841972 195.099075 679.797485 640.0 1955.320325 0 1589.661377 0.031118
185 185 1.032677 1.032898 3.040163 3.612450 0.016875 37.126766 32.851368 30.145836 2017-12-13T21:13:36+00:00 0.841579 196.131973 683.409912 640.0 1950.674312 0 1530.225342 0.021825
186 186 1.032823 1.033198 3.041561 3.613732 0.016875 37.236954 32.925690 30.300278 2017-12-13T22:13:20+00:00 0.841668 197.165176 687.023682 640.0 1954.338322 0 1590.264771 0.026628
187 187 1.032616 1.032862 3.039321 3.612212 0.016840 37.159687 32.952461 30.114653 2017-12-13T23:13:04+00:00 0.841402 198.198029 690.635864 640.0 1955.141357 0 1590.173706 0.025024
[188 rows x 18 columns]
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 188 entries, 0 to 187
Data columns (total 18 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 cycle_index 188 non-null int32
1 discharge_capacity 188 non-null float64
2 charge_capacity 188 non-null float64
3 discharge_energy 188 non-null float64
4 charge_energy 188 non-null float64
5 dc_internal_resistance 188 non-null float32
6 temperature_maximum 188 non-null float32
7 temperature_average 188 non-null float32
8 temperature_minimum 188 non-null float32
9 date_time_iso 188 non-null object
10 energy_efficiency 188 non-null float32
11 charge_throughput 188 non-null float32
12 energy_throughput 188 non-null float32
13 charge_duration 188 non-null float32
14 time_temperature_integrated 188 non-null float64
15 paused 188 non-null int32
16 CV_time 188 non-null float32
17 CV_current 188 non-null float32
dtypes: float32(10), float64(5), int32(2), object(1)
memory usage: 17.8+ KB
None
structured_data:
voltage test_time current charge_capacity discharge_capacity charge_energy discharge_energy internal_resistance temperature cycle_index step_type
0 2.800000 88438.740972 -3.070090 1.319212 1.788713 4.354456 5.709161 0.028598 31.529890 0 discharge
1 2.800701 85441.894275 -4.256237 1.370451 1.831461 4.519928 5.826991 0.029763 32.309685 0 discharge
2 2.801401 58527.144191 -3.221379 0.921136 1.386086 3.038029 4.406347 0.028391 32.847729 0 discharge
3 2.802102 31612.394108 -2.186522 0.471821 0.940710 1.556129 2.985704 0.027020 33.385773 0 discharge
4 2.802803 4697.644024 -1.151665 0.022506 0.495335 0.074230 1.565060 0.025648 33.923817 0 discharge
... ... ... ... ... ... ... ... ... ... ... ...
375995 NaN NaN NaN 1.427113 NaN NaN NaN NaN NaN 187 charge
375996 NaN NaN NaN 1.428547 NaN NaN NaN NaN NaN 187 charge
375997 NaN NaN NaN 1.429981 NaN NaN NaN NaN NaN 187 charge
375998 NaN NaN NaN 1.431416 NaN NaN NaN NaN NaN 187 charge
375999 NaN NaN NaN 1.432850 NaN NaN NaN NaN NaN 187 charge
[376000 rows x 11 columns]
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 376000 entries, 0 to 375999
Data columns (total 11 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 voltage 325974 non-null float32
1 test_time 325974 non-null float64
2 current 325974 non-null float32
3 charge_capacity 376000 non-null float32
4 discharge_capacity 325974 non-null float32
5 charge_energy 325974 non-null float32
6 discharge_energy 325974 non-null float32
7 internal_resistance 325974 non-null float32
8 temperature 325974 non-null float32
9 cycle_index 376000 non-null int32
10 step_type 376000 non-null category
dtypes: category(1), float32(8), float64(1), int32(1)
memory usage: 16.1 MB
None
diagnostic_data:
No object.
diagnostic_summary:
No object.
raw_data:
No object.
Inspect Feature Matrices¶
Example:
S: beep inspect FeatureMatrix-2021-21-09_20.50.32.550211.json.gz
2021-09-22 15:54:23 INFO Loaded FeatureMatrix-2021-21-09_20.50.32.550211.json.gz as type <class 'beep.features.base.BEEPFeatureMatrix'>.
BEEP Feature Matrix: FeatureMatrix-2021-21-09_20.50.32.550211.json.gz
Featurizers:
Featurizer beep.features.core HPPCResistanceVoltageFeatures
{'@class': 'HPPCResistanceVoltageFeatures',
'@module': 'beep.features.core',
'hyperparameters': {'cycle_index_filter': 6,
'diag_pos': 1,
'parameters_path': 'beep/protocol_parameters',
'soc_window': 8,
'test_time_filter_sec': 1000000},
'linked_datapath_semiunique_id': 'barcode:0000FB-channel:50-protocol:PreDiag_000440.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/tests/test_files/PreDiag_000440_0000FB_structure.json',
'metadata': {'barcode': '0000FB',
'channel_id': 50,
'protocol': 'PreDiag_000440.000'},
'paths': {'structured': 'beep/tests/test_files/PreDiag_000440_0000FB_structure.json'}}
Featurizer beep.features.core CycleSummaryStats
{'@class': 'CycleSummaryStats',
'@module': 'beep.features.core',
'hyperparameters': {'cycle_comp_num': [10, 100],
'statistics': ['var',
'min',
'mean',
'skew',
'kurtosis',
'abs',
'square']},
'linked_datapath_semiunique_id': 'barcode:0000FB-channel:50-protocol:PreDiag_000440.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/tests/test_files/PreDiag_000440_0000FB_structure.json',
'metadata': {'barcode': '0000FB',
'channel_id': 50,
'protocol': 'PreDiag_000440.000'},
'paths': {'structured': 'beep/tests/test_files/PreDiag_000440_0000FB_structure.json'}}
Featurizer beep.features.core CycleSummaryStats
{'@class': 'CycleSummaryStats',
'@module': 'beep.features.core',
'hyperparameters': {'cycle_comp_num': [11, 101],
'statistics': ['var',
'min',
'mean',
'skew',
'kurtosis',
'abs',
'square']},
'linked_datapath_semiunique_id': 'barcode:0000FB-channel:50-protocol:PreDiag_000440.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/tests/test_files/PreDiag_000440_0000FB_structure.json',
'metadata': {'barcode': '0000FB',
'channel_id': 50,
'protocol': 'PreDiag_000440.000'},
'paths': {'structured': 'beep/tests/test_files/PreDiag_000440_0000FB_structure.json'}}
Featurizer beep.features.core HPPCResistanceVoltageFeatures
{'@class': 'HPPCResistanceVoltageFeatures',
'@module': 'beep.features.core',
'hyperparameters': {'cycle_index_filter': 6,
'diag_pos': 1,
'parameters_path': 'beep/protocol_parameters',
'soc_window': 8,
'test_time_filter_sec': 1000000},
'linked_datapath_semiunique_id': 'barcode:00004C-channel:33-protocol:PredictionDiagnostics_000132.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json',
'metadata': {'barcode': '00004C',
'channel_id': 33,
'protocol': 'PredictionDiagnostics_000132.000'},
'paths': {'structured': 'beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json'}}
Featurizer beep.features.core CycleSummaryStats
{'@class': 'CycleSummaryStats',
'@module': 'beep.features.core',
'hyperparameters': {'cycle_comp_num': [10, 100],
'statistics': ['var',
'min',
'mean',
'skew',
'kurtosis',
'abs',
'square']},
'linked_datapath_semiunique_id': 'barcode:00004C-channel:33-protocol:PredictionDiagnostics_000132.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json',
'metadata': {'barcode': '00004C',
'channel_id': 33,
'protocol': 'PredictionDiagnostics_000132.000'},
'paths': {'structured': 'beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json'}}
Featurizer beep.features.core CycleSummaryStats
{'@class': 'CycleSummaryStats',
'@module': 'beep.features.core',
'hyperparameters': {'cycle_comp_num': [11, 101],
'statistics': ['var',
'min',
'mean',
'skew',
'kurtosis',
'abs',
'square']},
'linked_datapath_semiunique_id': 'barcode:00004C-channel:33-protocol:PredictionDiagnostics_000132.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json',
'metadata': {'barcode': '00004C',
'channel_id': 33,
'protocol': 'PredictionDiagnostics_000132.000'},
'paths': {'structured': 'beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json'}}
Matrix:
D_1::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2 ... var_v_diff::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2
filename ...
beep/tests/tes... -0.075467 ... 0.000186
beep/tests/tes... -0.090097 ... 0.002462
[2 rows x 132 columns]
<class 'pandas.core.frame.DataFrame'>
Index: 2 entries, beep/tests/test_files/PreDiag_000440_0000FB_structure.json to beep/tests/test_files/PredictionDiagnostics_000132_00004C_structure.json
Columns: 132 entries, D_1::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2 to var_v_diff::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2
dtypes: float64(132)
memory usage: 2.1+ KB
Inspect Featurizers¶
Example:
$: beep inspect HPPCFeaturizer.json.gz
2021-09-22 16:06:42 INFO Loaded beep/tests/test_files/modelling_test_files/HPPCFeaturizer.json.gz as type <class 'beep.features.core.HPPCResistanceVoltageFeatures'>.
BEEP Featurizer: beep/tests/test_files/modelling_test_files/HPPCFeaturizer.json.gz
File paths:
{'structured': 'beep/CLI_TEST_FILES_FEATURIZATION/PreDiag_000440_0000FB_structure.json'}
Linked datapath semiunique id: barcode:0000FB-channel:50-protocol:PreDiag_000440.000-schema:None-structured:True-legacy:True-raw_path:None-structured_path:beep/CLI_TEST_FILES_FEATURIZATION/PreDiag_000440_0000FB_structure.json
Hyperparameters:
{'cycle_index_filter': 6,
'diag_pos': 1,
'parameters_path': 'beep/protocol_parameters',
'soc_window': 8,
'test_time_filter_sec': 1000000}
Metadata:
{'barcode': '0000FB', 'channel_id': 50, 'protocol': 'PreDiag_000440.000'}
Features:
r_c_0s_00 r_c_0s_10 r_c_0s_20 r_c_0s_30 r_c_0s_40 r_c_0s_50 r_c_0s_60 r_c_0s_70 r_c_0s_80 r_c_3s_00 r_c_3s_10 r_c_3s_20 r_c_3s_30 r_c_3s_40 r_c_3s_50 r_c_3s_60 r_c_3s_70 r_c_3s_80 r_c_end_00 ... skew_ocv kurtosis_ocv sum_ocv sum_square_ocv var_v_diff min_v_diff mean_v_diff skew_v_diff kurtosis_v_diff sum_v_diff sum_square_v_diff D_1 D_2 D_3 D_4 D_5 D_6 D_7 D_8
0 -0.056034 -0.063766 -0.07963 -0.105001 -0.091609 -0.095464 -0.073553 -0.06692 -0.064657 -0.037199 -0.071951 -0.077876 -0.128588 -0.103652 -0.106871 -0.096638 -0.066802 -0.074038 -0.053153 ... 1.674431 7.472183 0.045535 0.000641 0.000186 -0.00181 0.012954 0.887649 2.940287 14.16811 0.373482 -0.075467 -0.097516 -0.230871 -0.163967 -0.158305 -0.137443 0.070989 0.098653
[1 rows x 76 columns]
Inspect Models¶
Example:
$: beep inspect model-src.json.gz
2021-09-22 16:06:04 WARNING Number of samples (4) less than number of features (179); may cause overfitting.
2021-09-22 16:06:04 INFO Loaded beep/tests/test_files/modelling_test_files/model-src.json.gz as type <class 'beep.model.BEEPLinearModelExperiment'>.
BEEP Linear Model Experiment: beep/tests/test_files/modelling_test_files/model-src.json.gz
Targets: ['capacity_0.92::TrajectoryFastCharge']
Model name: lasso
Impute strategy: median
Homogenize features: True
NaN Thresholds:
-train_feature_drop_nan_thresh: 0.95
-train_sample_drop_nan_thresh: 0.5
-predict_sample_nan_thresh: 0.75
Model parameters:
- coef_: [0.0, 0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, 0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, -0.0, -0.0, -0.0, -0.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, 0.0, -0.0, -0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, 0.0, 0.0, -0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, -0.0, 0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, 0.0, -0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, 0.0, -0.0, -0.0, -0.0]
- intercept_: 113.25
- optimal_hyperparameters: {'alpha': 98.35818271439722}
Matrices:
feature_matrix
D_1::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2 ... var_v_diff::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2
filename ...
beep/CLI_TEST_... -0.075467 ... 0.000186
beep/CLI_TEST_... -0.090097 ... 0.002462
beep/CLI_TEST_... -0.145030 ... 0.002416
beep/CLI_TEST_... -0.052108 ... 0.000848
[4 rows x 179 columns]
<class 'pandas.core.frame.DataFrame'>
Index: 4 entries, beep/CLI_TEST_FILES_FEATURIZATION/PreDiag_000440_0000FB_structure.json to beep/CLI_TEST_FILES_FEATURIZATION/PredictionDiagnostics_000136_00002D_structure.json
Columns: 179 entries, D_1::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2 to var_v_diff::HPPCResistanceVoltageFeatures::6262aa8b2c9ce9530d53f73943e5b465a1946f39be2ad2a3ede05f49e6f9f2d2
dtypes: float64(179)
memory usage: 5.6+ KB
None
target_matrix
capacity_0.83::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 ... rpt_1Cdischarge_energy0.8_real_regular_throughput::DiagnosticProperties::9fb32356773f0c4f8c27fc9528ca4a986dc928fbadbd859b67a8892e7daac72e
filename ...
beep/CLI_TEST_... 284 ... NaN
beep/CLI_TEST_... 58 ... 1266.108637
beep/CLI_TEST_... 85 ... NaN
beep/CLI_TEST_... 101 ... NaN
[4 rows x 11 columns]
<class 'pandas.core.frame.DataFrame'>
Index: 4 entries, beep/CLI_TEST_FILES_FEATURIZATION/PreDiag_000440_0000FB_structure.json to beep/CLI_TEST_FILES_FEATURIZATION/PredictionDiagnostics_000136_00002D_structure.json
Data columns (total 11 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 capacity_0.83::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
1 capacity_0.86::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
2 capacity_0.89::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
3 capacity_0.8::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
4 capacity_0.92::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
5 capacity_0.95::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
6 capacity_0.98::TrajectoryFastCharge::319cec55cc030c1911b2530cae3fc2df8d3c24912ae01ee4172ea4ca4caddec8 4 non-null int64
7 initial_regular_throughput::DiagnosticProperties::9fb32356773f0c4f8c27fc9528ca4a986dc928fbadbd859b67a8892e7daac72e 1 non-null float64
8 rpt_1Cdischarge_energy0.8_cycle_index::DiagnosticProperties::9fb32356773f0c4f8c27fc9528ca4a986dc928fbadbd859b67a8892e7daac72e 1 non-null float64
9 rpt_1Cdischarge_energy0.8_normalized_regular_throughput::DiagnosticProperties::9fb32356773f0c4f8c27fc9528ca4a986dc928fbadbd859b67a8892e7daac72e 1 non-null float64
10 rpt_1Cdischarge_energy0.8_real_regular_throughput::DiagnosticProperties::9fb32356773f0c4f8c27fc9528ca4a986dc928fbadbd859b67a8892e7daac72e 1 non-null float64
dtypes: float64(4), int64(7)
memory usage: 556.0+ bytes