From 56a0b294042af6f8be3a6d74c693dec8018d2017 Mon Sep 17 00:00:00 2001
From: Raymond Chia <rqchia@janus0.ihpc.uts.edu.au>
Date: Mon, 27 Nov 2023 11:06:18 +1100
Subject: [PATCH] added docs
---
logs/singularity_1096841.out | 489 ++++++++++++++++++++++++++++
logs/singularity_2810990.out | 458 +++++++++++++++++++++++++-
logs/singularity_4027803.out | 495 +++++++++++++++++++++++++++++
modules/digitalsignalprocessing.py | 4 +-
regress_rr.py | 125 +++++---
5 files changed, 1519 insertions(+), 52 deletions(-)
create mode 100644 logs/singularity_1096841.out
create mode 100644 logs/singularity_4027803.out
diff --git a/logs/singularity_1096841.out b/logs/singularity_1096841.out
new file mode 100644
index 0000000..47e6ce7
--- /dev/null
+++ b/logs/singularity_1096841.out
@@ -0,0 +1,489 @@
+2023-11-26 23:59:02.254525: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Using TensorFlow backend
+Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='elastic', overwrite=0, subject=3, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
+Using pre-set data id: 2
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-15.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+544 Pilot02 3 linreg ... -1.253991 -0.014203 0.616459
+545 Pilot02 3 linreg ... -1.973362 -0.015948 0.573832
+546 Pilot02 3 linreg ... -16.926541 -0.011023 0.697489
+547 Pilot02 3 linreg ... -0.948799 -0.007771 0.784065
+548 Pilot03 2 elastic ... -1.758438 -0.126951 0.000069
+
+[549 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-17.0
+train
+(100, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+545 Pilot02 3 linreg ... -1.973362 -0.015948 0.573832
+546 Pilot02 3 linreg ... -16.926541 -0.011023 0.697489
+547 Pilot02 3 linreg ... -0.948799 -0.007771 0.784065
+548 Pilot03 2 elastic ... -1.758438 -0.126951 0.000069
+549 Pilot03 2 elastic ... -1.925223 -0.070755 0.026920
+
+[550 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+547 Pilot02 3 linreg ... -0.948799 -0.007771 0.784065
+548 Pilot03 2 elastic ... -1.758438 -0.126951 0.000069
+549 Pilot03 2 elastic ... -1.925223 -0.070755 0.026920
+550 Pilot02 3 elastic ... -5.596573 0.107220 0.000150
+551 Pilot03 2 elastic ... -2.161178 -0.052695 0.099562
+
+[552 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+548 Pilot03 2 elastic ... -1.758438 -0.126951 0.000069
+549 Pilot03 2 elastic ... -1.925223 -0.070755 0.026920
+550 Pilot02 3 elastic ... -5.596573 0.107220 0.000150
+551 Pilot03 2 elastic ... -2.161178 -0.052695 0.099562
+552 Pilot03 2 elastic ... -1.996716 -0.129399 0.000049
+
+[553 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+550 Pilot02 3 elastic ... -5.596573 0.107220 0.000150
+551 Pilot03 2 elastic ... -2.161178 -0.052695 0.099562
+552 Pilot03 2 elastic ... -1.996716 -0.129399 0.000049
+553 Pilot02 3 elastic ... -7.182356 0.069423 0.014245
+554 Pilot03 2 elastic ... -2.473361 -0.103564 0.001181
+
+[555 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+551 Pilot03 2 elastic ... -2.161178 -0.052695 0.099562
+552 Pilot03 2 elastic ... -1.996716 -0.129399 0.000049
+553 Pilot02 3 elastic ... -7.182356 0.069423 0.014245
+554 Pilot03 2 elastic ... -2.473361 -0.103564 0.001181
+555 Pilot03 2 elastic ... -2.166505 -0.051172 0.109753
+
+[556 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+553 Pilot02 3 elastic ... -7.182356 0.069423 0.014245
+554 Pilot03 2 elastic ... -2.473361 -0.103564 0.001181
+555 Pilot03 2 elastic ... -2.166505 -0.051172 0.109753
+556 Pilot02 3 elastic ... -3.104293 NaN NaN
+557 Pilot03 2 elastic ... -1.913436 -0.117161 0.000241
+
+[558 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+555 Pilot03 2 elastic ... -2.166505 -0.051172 0.109753
+556 Pilot02 3 elastic ... -3.104293 NaN NaN
+557 Pilot03 2 elastic ... -1.913436 -0.117161 0.000241
+558 Pilot02 3 elastic ... -5.419605 0.029585 0.296716
+559 Pilot03 2 elastic ... -2.370444 -0.110486 0.000537
+
+[560 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+556 Pilot02 3 elastic ... -3.104293 NaN NaN
+557 Pilot03 2 elastic ... -1.913436 -0.117161 0.000241
+558 Pilot02 3 elastic ... -5.419605 0.029585 0.296716
+559 Pilot03 2 elastic ... -2.370444 -0.110486 0.000537
+560 Pilot03 2 elastic ... -2.268817 -0.092573 0.003761
+
+[561 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+557 Pilot03 2 elastic ... -1.913436 -0.117161 0.000241
+558 Pilot02 3 elastic ... -5.419605 0.029585 0.296716
+559 Pilot03 2 elastic ... -2.370444 -0.110486 0.000537
+560 Pilot03 2 elastic ... -2.268817 -0.092573 0.003761
+561 Pilot03 2 elastic ... -1.844984 -0.102995 0.001258
+
+[562 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+559 Pilot03 2 elastic ... -2.370444 -0.110486 0.000537
+560 Pilot03 2 elastic ... -2.268817 -0.092573 0.003761
+561 Pilot03 2 elastic ... -1.844984 -0.102995 0.001258
+562 Pilot02 3 elastic ... -1.737720 0.018534 0.513349
+563 Pilot03 2 elastic ... -2.074848 -0.111489 0.000478
+
+[564 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+560 Pilot03 2 elastic ... -2.268817 -0.092573 0.003761
+561 Pilot03 2 elastic ... -1.844984 -0.102995 0.001258
+562 Pilot02 3 elastic ... -1.737720 0.018534 0.513349
+563 Pilot03 2 elastic ... -2.074848 -0.111489 0.000478
+564 Pilot03 2 elastic ... -2.468988 -0.096367 0.002554
+
+[565 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+562 Pilot02 3 elastic ... -1.737720 0.018534 0.513349
+563 Pilot03 2 elastic ... -2.074848 -0.111489 0.000478
+564 Pilot03 2 elastic ... -2.468988 -0.096367 0.002554
+565 Pilot02 3 elastic ... -1.610216 -0.007174 0.800294
+566 Pilot03 2 elastic ... -2.274461 -0.073805 0.020982
+
+[567 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+563 Pilot03 2 elastic ... -2.074848 -0.111489 0.000478
+564 Pilot03 2 elastic ... -2.468988 -0.096367 0.002554
+565 Pilot02 3 elastic ... -1.610216 -0.007174 0.800294
+566 Pilot03 2 elastic ... -2.274461 -0.073805 0.020982
+567 Pilot03 2 elastic ... -1.732794 -0.102280 0.001360
+
+[568 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-12.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+565 Pilot02 3 elastic ... -1.610216 -0.007174 0.800294
+566 Pilot03 2 elastic ... -2.274461 -0.073805 0.020982
+567 Pilot03 2 elastic ... -1.732794 -0.102280 0.001360
+568 Pilot02 3 elastic ... -3.323004 0.042106 0.137421
+569 Pilot03 2 elastic ... -1.298003 -0.060662 0.057906
+
+[570 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+566 Pilot03 2 elastic ... -2.274461 -0.073805 2.098219e-02
+567 Pilot03 2 elastic ... -1.732794 -0.102280 1.360380e-03
+568 Pilot02 3 elastic ... -3.323004 0.042106 1.374214e-01
+569 Pilot03 2 elastic ... -1.298003 -0.060662 5.790618e-02
+570 Pilot03 2 elastic ... -1.030237 -0.161102 4.088040e-07
+
+[571 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+568 Pilot02 3 elastic ... -3.323004 0.042106 1.374214e-01
+569 Pilot03 2 elastic ... -1.298003 -0.060662 5.790618e-02
+570 Pilot03 2 elastic ... -1.030237 -0.161102 4.088040e-07
+571 Pilot02 3 elastic ... -2.548343 0.009285 7.433378e-01
+572 Pilot03 2 elastic ... -1.815615 -0.193334 1.087464e-09
+
+[573 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+570 Pilot03 2 elastic ... -1.030237 -0.161102 4.088040e-07
+571 Pilot02 3 elastic ... -2.548343 0.009285 7.433378e-01
+572 Pilot03 2 elastic ... -1.815615 -0.193334 1.087464e-09
+573 Pilot02 3 elastic ... -1.880238 -0.040916 1.488975e-01
+574 Pilot03 2 elastic ... -1.328308 -0.136510 1.838231e-05
+
+[575 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+571 Pilot02 3 elastic ... -2.548343 0.009285 7.433378e-01
+572 Pilot03 2 elastic ... -1.815615 -0.193334 1.087464e-09
+573 Pilot02 3 elastic ... -1.880238 -0.040916 1.488975e-01
+574 Pilot03 2 elastic ... -1.328308 -0.136510 1.838231e-05
+575 Pilot03 2 elastic ... -1.926497 -0.186432 4.243797e-09
+
+[576 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-12.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+573 Pilot02 3 elastic ... -1.880238 -0.040916 1.488975e-01
+574 Pilot03 2 elastic ... -1.328308 -0.136510 1.838231e-05
+575 Pilot03 2 elastic ... -1.926497 -0.186432 4.243797e-09
+576 Pilot02 3 elastic ... -2.947342 -0.007501 7.913772e-01
+577 Pilot03 2 elastic ... -0.806993 -0.139394 1.213925e-05
+
+[578 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi10.0-12.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 3.877603e-02 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 7.009716e-02 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 4.702307e-02 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 1.689162e-02 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 1.187485e-01 5.380273e-03
+.. ... ... ... ... ... ... ...
+575 Pilot03 2 elastic ... -1.926497 -1.864318e-01 4.243797e-09
+576 Pilot02 3 elastic ... -2.947342 -7.501254e-03 7.913772e-01
+577 Pilot03 2 elastic ... -0.806993 -1.393941e-01 1.213925e-05
+578 Pilot02 3 elastic ... -2.285661 6.344185e-07 9.999821e-01
+579 Pilot03 2 elastic ... -0.123614 1.726530e-02 5.896886e-01
+
+[580 rows x 18 columns]
+Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='elastic', overwrite=0, subject=3, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
diff --git a/logs/singularity_2810990.out b/logs/singularity_2810990.out
index 179501a..28f11f2 100644
--- a/logs/singularity_2810990.out
+++ b/logs/singularity_2810990.out
@@ -4,4 +4,460 @@ Using TensorFlow backend
Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='linreg', overwrite=1, subject=3, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
Using pre-set data id: 2
Dependency not available for matrix_profile, this feature will be disabled!
-
Feature Extraction: 0%| | 0/65 [00:00<?, ?it/s]
\ No newline at end of file
+
Feature Extraction: 0%| | 0/65 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/65 [05:32<5:54:39, 332.48s/it]
Feature Extraction: 3%|â–Ž | 2/65 [05:34<2:25:10, 138.27s/it]
Feature Extraction: 5%|â– | 3/65 [05:36<1:18:40, 76.14s/it]
Feature Extraction: 6%|▌ | 4/65 [05:38<47:35, 46.82s/it]
Feature Extraction: 8%|â–Š | 5/65 [05:40<30:41, 30.69s/it]
Feature Extraction: 9%|â–‰ | 6/65 [05:42<20:18, 20.65s/it]
Feature Extraction: 11%|â–ˆ | 7/65 [05:43<13:49, 14.30s/it]
Feature Extraction: 12%|█■| 8/65 [05:44<09:34, 10.08s/it]
Feature Extraction: 14%|█■| 9/65 [05:48<07:31, 8.07s/it]
Feature Extraction: 15%|█▌ | 10/65 [05:48<05:15, 5.73s/it]
Feature Extraction: 17%|█▋ | 11/65 [05:49<03:49, 4.24s/it]
Feature Extraction: 18%|█▊ | 12/65 [05:50<02:47, 3.17s/it]
Feature Extraction: 20%|██ | 13/65 [05:51<02:12, 2.55s/it]
Feature Extraction: 22%|██■| 14/65 [11:02<1:21:18, 95.65s/it]
Feature Extraction: 23%|██▎ | 15/65 [11:09<57:27, 68.94s/it]
Feature Extraction: 25%|██■| 16/65 [11:12<40:05, 49.08s/it]
Feature Extraction: 26%|██▌ | 17/65 [11:13<27:49, 34.78s/it]
Feature Extraction: 28%|██▊ | 18/65 [11:13<19:05, 24.36s/it]
Feature Extraction: 29%|██▉ | 19/65 [11:14<13:10, 17.18s/it]
Feature Extraction: 31%|███ | 20/65 [11:19<10:16, 13.70s/it]
Feature Extraction: 32%|███■| 21/65 [11:19<07:05, 9.68s/it]
Feature Extraction: 34%|███■| 22/65 [11:21<05:09, 7.19s/it]
Feature Extraction: 35%|███▌ | 23/65 [11:21<03:35, 5.14s/it]
Feature Extraction: 37%|███▋ | 24/65 [11:22<02:36, 3.81s/it]
Feature Extraction: 38%|███▊ | 25/65 [11:25<02:18, 3.46s/it]
Feature Extraction: 40%|████ | 26/65 [11:27<02:08, 3.29s/it]
Feature Extraction: 42%|████■| 27/65 [16:36<1:00:02, 94.79s/it]
Feature Extraction: 43%|████▎ | 28/65 [16:38<41:21, 67.06s/it]
Feature Extraction: 45%|████■| 29/65 [16:39<28:21, 47.25s/it]
Feature Extraction: 46%|████▌ | 30/65 [16:41<19:31, 33.48s/it]
Feature Extraction: 48%|████▊ | 31/65 [16:48<14:28, 25.54s/it]
Feature Extraction: 49%|████▉ | 32/65 [16:48<09:51, 17.92s/it]
Feature Extraction: 51%|█████ | 33/65 [16:48<06:42, 12.58s/it]
Feature Extraction: 52%|█████■| 34/65 [16:50<04:50, 9.37s/it]
Feature Extraction: 54%|█████■| 35/65 [16:53<03:44, 7.49s/it]
Feature Extraction: 55%|█████▌ | 36/65 [16:56<02:58, 6.14s/it]
Feature Extraction: 57%|█████▋ | 37/65 [16:57<02:13, 4.75s/it]
Feature Extraction: 58%|█████▊ | 38/65 [16:59<01:40, 3.73s/it]
Feature Extraction: 60%|██████ | 39/65 [17:01<01:25, 3.30s/it]
Feature Extraction: 62%|██████■| 40/65 [22:06<39:02, 93.69s/it]
Feature Extraction: 63%|██████▎ | 41/65 [22:10<26:42, 66.78s/it]
Feature Extraction: 65%|██████■| 42/65 [22:10<17:56, 46.80s/it]
Feature Extraction: 66%|██████▌ | 43/65 [22:11<12:07, 33.05s/it]
Feature Extraction: 68%|██████▊ | 44/65 [22:16<08:39, 24.73s/it]
Feature Extraction: 69%|██████▉ | 45/65 [22:18<06:00, 18.01s/it]
Feature Extraction: 71%|███████ | 46/65 [22:19<04:03, 12.83s/it]
Feature Extraction: 72%|███████■| 47/65 [22:21<02:50, 9.44s/it]
Feature Extraction: 74%|███████■| 48/65 [22:24<02:07, 7.50s/it]
Feature Extraction: 75%|███████▌ | 49/65 [22:24<01:25, 5.33s/it]
Feature Extraction: 77%|███████▋ | 50/65 [22:28<01:12, 4.86s/it]
Feature Extraction: 78%|███████▊ | 51/65 [22:28<00:48, 3.49s/it]
Feature Extraction: 80%|████████ | 52/65 [22:29<00:34, 2.69s/it]
Feature Extraction: 82%|████████■| 53/65 [25:40<11:52, 59.34s/it]
Feature Extraction: 83%|████████▎ | 54/65 [27:29<13:36, 74.23s/it]
Feature Extraction: 85%|████████■| 55/65 [27:30<08:42, 52.22s/it]
Feature Extraction: 86%|████████▌ | 56/65 [27:31<05:30, 36.70s/it]
Feature Extraction: 88%|████████▊ | 57/65 [27:36<03:38, 27.26s/it]
Feature Extraction: 89%|████████▉ | 58/65 [27:39<02:19, 19.91s/it]
Feature Extraction: 91%|█████████ | 59/65 [27:41<01:27, 14.56s/it]
Feature Extraction: 92%|█████████â–| 60/65 [27:42<00:53, 10.72s/it]
Feature Extraction: 94%|█████████â–| 61/65 [27:43<00:31, 7.80s/it]
Feature Extraction: 95%|█████████▌| 62/65 [27:44<00:16, 5.63s/it]
Feature Extraction: 97%|█████████▋| 63/65 [27:47<00:09, 4.86s/it]
Feature Extraction: 98%|█████████▊| 64/65 [27:49<00:04, 4.10s/it]
Feature Extraction: 100%|██████████| 65/65 [27:50<00:00, 3.17s/it]
Feature Extraction: 100%|██████████| 65/65 [27:50<00:00, 25.70s/it]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/47 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/47 [00:08<06:53, 9.00s/it]
Feature Extraction: 4%|â– | 2/47 [00:09<02:50, 3.79s/it]
Feature Extraction: 9%|â–Š | 4/47 [00:09<01:04, 1.50s/it]
Feature Extraction: 15%|█■| 7/47 [00:09<00:28, 1.38it/s]
Feature Extraction: 17%|█▋ | 8/47 [00:09<00:23, 1.68it/s]
Feature Extraction: 19%|█▉ | 9/47 [00:10<00:19, 1.99it/s]
Feature Extraction: 26%|██▌ | 12/47 [00:10<00:09, 3.55it/s]
Feature Extraction: 28%|██▊ | 13/47 [00:10<00:11, 3.08it/s]
Feature Extraction: 30%|██▉ | 14/47 [00:19<01:07, 2.03s/it]
Feature Extraction: 32%|███■| 15/47 [00:19<00:50, 1.59s/it]
Feature Extraction: 36%|███▌ | 17/47 [00:19<00:29, 1.01it/s]
Feature Extraction: 40%|████ | 19/47 [00:19<00:20, 1.38it/s]
Feature Extraction: 43%|████▎ | 20/47 [00:20<00:17, 1.58it/s]
Feature Extraction: 47%|████▋ | 22/47 [00:20<00:10, 2.32it/s]
Feature Extraction: 51%|█████ | 24/47 [00:20<00:08, 2.65it/s]
Feature Extraction: 55%|█████▌ | 26/47 [00:21<00:07, 2.78it/s]
Feature Extraction: 57%|█████▋ | 27/47 [00:28<00:31, 1.55s/it]
Feature Extraction: 60%|█████▉ | 28/47 [00:28<00:25, 1.34s/it]
Feature Extraction: 62%|██████■| 29/47 [00:28<00:19, 1.06s/it]
Feature Extraction: 64%|██████■| 30/47 [00:29<00:14, 1.20it/s]
Feature Extraction: 66%|██████▌ | 31/47 [00:29<00:11, 1.44it/s]
Feature Extraction: 70%|███████ | 33/47 [00:29<00:05, 2.34it/s]
Feature Extraction: 72%|███████■| 34/47 [00:29<00:04, 2.80it/s]
Feature Extraction: 74%|███████■| 35/47 [00:30<00:05, 2.39it/s]
Feature Extraction: 77%|███████▋ | 36/47 [00:30<00:04, 2.35it/s]
Feature Extraction: 83%|████████▎ | 39/47 [00:31<00:02, 3.04it/s]
Feature Extraction: 85%|████████▌ | 40/47 [00:34<00:06, 1.03it/s]
Feature Extraction: 87%|████████▋ | 41/47 [00:35<00:05, 1.13it/s]
Feature Extraction: 89%|████████▉ | 42/47 [00:36<00:04, 1.09it/s]
Feature Extraction: 94%|█████████▎| 44/47 [00:37<00:01, 1.58it/s]
Feature Extraction: 96%|█████████▌| 45/47 [00:37<00:01, 1.86it/s]
Feature Extraction: 98%|█████████▊| 46/47 [00:37<00:00, 2.22it/s]
Feature Extraction: 100%|██████████| 47/47 [00:37<00:00, 1.26it/s]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/47 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/47 [00:08<06:43, 8.78s/it]
Feature Extraction: 4%|â– | 2/47 [00:09<02:50, 3.79s/it]
Feature Extraction: 6%|â–‹ | 3/47 [00:09<01:33, 2.12s/it]
Feature Extraction: 15%|█■| 7/47 [00:09<00:24, 1.63it/s]
Feature Extraction: 19%|█▉ | 9/47 [00:09<00:16, 2.34it/s]
Feature Extraction: 23%|██▎ | 11/47 [00:09<00:12, 2.82it/s]
Feature Extraction: 28%|██▊ | 13/47 [00:10<00:10, 3.30it/s]
Feature Extraction: 30%|██▉ | 14/47 [00:18<00:57, 1.74s/it]
Feature Extraction: 32%|███■| 15/47 [00:18<00:46, 1.45s/it]
Feature Extraction: 34%|███■| 16/47 [00:18<00:35, 1.15s/it]
Feature Extraction: 36%|███▌ | 17/47 [00:18<00:26, 1.11it/s]
Feature Extraction: 40%|████ | 19/47 [00:19<00:16, 1.74it/s]
Feature Extraction: 45%|████■| 21/47 [00:19<00:11, 2.28it/s]
Feature Extraction: 49%|████▉ | 23/47 [00:19<00:07, 3.07it/s]
Feature Extraction: 51%|█████ | 24/47 [00:19<00:06, 3.55it/s]
Feature Extraction: 53%|█████▎ | 25/47 [00:20<00:06, 3.42it/s]
Feature Extraction: 55%|█████▌ | 26/47 [00:20<00:05, 3.68it/s]
Feature Extraction: 57%|█████▋ | 27/47 [00:27<00:41, 2.09s/it]
Feature Extraction: 60%|█████▉ | 28/47 [00:28<00:29, 1.57s/it]
Feature Extraction: 62%|██████■| 29/47 [00:28<00:21, 1.21s/it]
Feature Extraction: 64%|██████■| 30/47 [00:28<00:16, 1.04it/s]
Feature Extraction: 66%|██████▌ | 31/47 [00:28<00:11, 1.36it/s]
Feature Extraction: 68%|██████▊ | 32/47 [00:29<00:08, 1.69it/s]
Feature Extraction: 72%|███████■| 34/47 [00:29<00:04, 2.67it/s]
Feature Extraction: 74%|███████■| 35/47 [00:29<00:03, 3.01it/s]
Feature Extraction: 79%|███████▊ | 37/47 [00:29<00:02, 3.67it/s]
Feature Extraction: 83%|████████▎ | 39/47 [00:30<00:02, 3.86it/s]
Feature Extraction: 85%|████████▌ | 40/47 [00:34<00:07, 1.02s/it]
Feature Extraction: 87%|████████▋ | 41/47 [00:35<00:06, 1.13s/it]
Feature Extraction: 89%|████████▉ | 42/47 [00:35<00:04, 1.11it/s]
Feature Extraction: 91%|█████████â–| 43/47 [00:36<00:02, 1.35it/s]
Feature Extraction: 94%|█████████▎| 44/47 [00:36<00:01, 1.68it/s]
Feature Extraction: 96%|█████████▌| 45/47 [00:36<00:01, 1.94it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00, 3.06it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00, 1.27it/s]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/47 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/47 [00:08<06:23, 8.35s/it]
Feature Extraction: 4%|â– | 2/47 [00:08<02:38, 3.53s/it]
Feature Extraction: 6%|â–‹ | 3/47 [00:08<01:28, 2.02s/it]
Feature Extraction: 11%|â–ˆ | 5/47 [00:08<00:39, 1.07it/s]
Feature Extraction: 13%|█▎ | 6/47 [00:09<00:28, 1.42it/s]
Feature Extraction: 15%|█■| 7/47 [00:09<00:22, 1.74it/s]
Feature Extraction: 21%|██■| 10/47 [00:09<00:10, 3.48it/s]
Feature Extraction: 23%|██▎ | 11/47 [00:09<00:10, 3.38it/s]
Feature Extraction: 28%|██▊ | 13/47 [00:10<00:08, 3.96it/s]
Feature Extraction: 30%|██▉ | 14/47 [00:16<00:47, 1.44s/it]
Feature Extraction: 32%|███■| 15/47 [00:18<00:50, 1.56s/it]
Feature Extraction: 34%|███■| 16/47 [00:18<00:37, 1.22s/it]
Feature Extraction: 36%|███▌ | 17/47 [00:18<00:29, 1.01it/s]
Feature Extraction: 38%|███▊ | 18/47 [00:18<00:22, 1.30it/s]
Feature Extraction: 43%|████▎ | 20/47 [00:19<00:13, 1.99it/s]
Feature Extraction: 47%|████▋ | 22/47 [00:19<00:09, 2.60it/s]
Feature Extraction: 49%|████▉ | 23/47 [00:19<00:08, 2.85it/s]
Feature Extraction: 53%|█████▎ | 25/47 [00:20<00:06, 3.42it/s]
Feature Extraction: 55%|█████▌ | 26/47 [00:20<00:05, 3.68it/s]
Feature Extraction: 57%|█████▋ | 27/47 [00:25<00:27, 1.38s/it]
Feature Extraction: 60%|█████▉ | 28/47 [00:27<00:31, 1.63s/it]
Feature Extraction: 62%|██████■| 29/47 [00:27<00:22, 1.25s/it]
Feature Extraction: 64%|██████■| 30/47 [00:28<00:17, 1.03s/it]
Feature Extraction: 66%|██████▌ | 31/47 [00:28<00:13, 1.19it/s]
Feature Extraction: 68%|██████▊ | 32/47 [00:28<00:09, 1.58it/s]
Feature Extraction: 70%|███████ | 33/47 [00:28<00:07, 1.96it/s]
Feature Extraction: 72%|███████■| 34/47 [00:29<00:05, 2.19it/s]
Feature Extraction: 77%|███████▋ | 36/47 [00:29<00:03, 3.22it/s]
Feature Extraction: 79%|███████▊ | 37/47 [00:29<00:03, 3.25it/s]
Feature Extraction: 81%|████████ | 38/47 [00:30<00:02, 3.36it/s]
Feature Extraction: 83%|████████▎ | 39/47 [00:30<00:02, 3.43it/s]
Feature Extraction: 85%|████████▌ | 40/47 [00:34<00:09, 1.34s/it]
Feature Extraction: 89%|████████▉ | 42/47 [00:35<00:04, 1.07it/s]
Feature Extraction: 91%|█████████â–| 43/47 [00:35<00:03, 1.29it/s]
Feature Extraction: 94%|█████████▎| 44/47 [00:36<00:02, 1.27it/s]
Feature Extraction: 98%|█████████▊| 46/47 [00:36<00:00, 1.88it/s]
Feature Extraction: 100%|██████████| 47/47 [00:37<00:00, 2.03it/s]
Feature Extraction: 100%|██████████| 47/47 [00:37<00:00, 1.27it/s]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/47 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/47 [00:08<06:50, 8.92s/it]
Feature Extraction: 4%|â– | 2/47 [00:09<02:54, 3.87s/it]
Feature Extraction: 13%|█▎ | 6/47 [00:09<00:37, 1.10it/s]
Feature Extraction: 19%|█▉ | 9/47 [00:09<00:19, 1.94it/s]
Feature Extraction: 26%|██▌ | 12/47 [00:09<00:12, 2.86it/s]
Feature Extraction: 30%|██▉ | 14/47 [00:18<00:47, 1.43s/it]
Feature Extraction: 38%|███▊ | 18/47 [00:18<00:24, 1.20it/s]
Feature Extraction: 43%|████▎ | 20/47 [00:18<00:17, 1.52it/s]
Feature Extraction: 47%|████▋ | 22/47 [00:19<00:13, 1.90it/s]
Feature Extraction: 51%|█████ | 24/47 [00:19<00:09, 2.35it/s]
Feature Extraction: 53%|█████▎ | 25/47 [00:19<00:08, 2.49it/s]
Feature Extraction: 55%|█████▌ | 26/47 [00:20<00:08, 2.56it/s]
Feature Extraction: 57%|█████▋ | 27/47 [00:27<00:38, 1.94s/it]
Feature Extraction: 60%|█████▉ | 28/47 [00:28<00:30, 1.60s/it]
Feature Extraction: 64%|██████■| 30/47 [00:28<00:16, 1.00it/s]
Feature Extraction: 66%|██████▌ | 31/47 [00:28<00:12, 1.24it/s]
Feature Extraction: 68%|██████▊ | 32/47 [00:28<00:09, 1.51it/s]
Feature Extraction: 77%|███████▋ | 36/47 [00:28<00:03, 3.33it/s]
Feature Extraction: 81%|████████ | 38/47 [00:29<00:02, 3.76it/s]
Feature Extraction: 85%|████████▌ | 40/47 [00:34<00:06, 1.05it/s]
Feature Extraction: 87%|████████▋ | 41/47 [00:35<00:05, 1.10it/s]
Feature Extraction: 89%|████████▉ | 42/47 [00:35<00:04, 1.22it/s]
Feature Extraction: 91%|█████████â–| 43/47 [00:35<00:02, 1.52it/s]
Feature Extraction: 94%|█████████▎| 44/47 [00:36<00:01, 1.75it/s]
Feature Extraction: 96%|█████████▌| 45/47 [00:36<00:00, 2.21it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00, 3.12it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00, 1.29it/s]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/49 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/49 [00:08<06:58, 8.72s/it]
Feature Extraction: 6%|▌ | 3/49 [00:08<01:46, 2.31s/it]
Feature Extraction: 8%|â–Š | 4/49 [00:09<01:13, 1.62s/it]
Feature Extraction: 14%|█■| 7/49 [00:09<00:28, 1.46it/s]
Feature Extraction: 18%|█▊ | 9/49 [00:09<00:20, 1.92it/s]
Feature Extraction: 24%|██■| 12/49 [00:10<00:12, 3.00it/s]
Feature Extraction: 27%|██▋ | 13/49 [00:10<00:11, 3.10it/s]
Feature Extraction: 29%|██▊ | 14/49 [00:18<01:02, 1.77s/it]
Feature Extraction: 31%|███ | 15/49 [00:18<00:48, 1.43s/it]
Feature Extraction: 33%|███▎ | 16/49 [00:18<00:36, 1.12s/it]
Feature Extraction: 35%|███■| 17/49 [00:18<00:28, 1.11it/s]
Feature Extraction: 39%|███▉ | 19/49 [00:18<00:17, 1.69it/s]
Feature Extraction: 41%|████ | 20/49 [00:19<00:15, 1.84it/s]
Feature Extraction: 43%|████▎ | 21/49 [00:19<00:12, 2.26it/s]
Feature Extraction: 47%|████▋ | 23/49 [00:19<00:09, 2.81it/s]
Feature Extraction: 53%|█████▎ | 26/49 [00:20<00:07, 2.96it/s]
Feature Extraction: 55%|█████▌ | 27/49 [00:26<00:29, 1.35s/it]
Feature Extraction: 57%|█████▋ | 28/49 [00:27<00:26, 1.28s/it]
Feature Extraction: 59%|█████▉ | 29/49 [00:27<00:20, 1.03s/it]
Feature Extraction: 61%|██████ | 30/49 [00:28<00:15, 1.20it/s]
Feature Extraction: 63%|██████▎ | 31/49 [00:28<00:11, 1.51it/s]
Feature Extraction: 65%|██████▌ | 32/49 [00:29<00:11, 1.49it/s]
Feature Extraction: 67%|██████▋ | 33/49 [00:29<00:08, 1.95it/s]
Feature Extraction: 69%|██████▉ | 34/49 [00:29<00:05, 2.53it/s]
Feature Extraction: 71%|███████■| 35/49 [00:29<00:04, 3.12it/s]
Feature Extraction: 73%|███████▎ | 36/49 [00:29<00:04, 3.19it/s]
Feature Extraction: 78%|███████▊ | 38/49 [00:29<00:02, 4.39it/s]
Feature Extraction: 80%|███████▉ | 39/49 [00:30<00:04, 2.46it/s]
Feature Extraction: 82%|████████■| 40/49 [00:35<00:13, 1.52s/it]
Feature Extraction: 84%|████████▎ | 41/49 [00:35<00:09, 1.16s/it]
Feature Extraction: 86%|████████▌ | 42/49 [00:35<00:06, 1.15it/s]
Feature Extraction: 88%|████████▊ | 43/49 [00:36<00:04, 1.27it/s]
Feature Extraction: 90%|████████▉ | 44/49 [00:36<00:03, 1.45it/s]
Feature Extraction: 92%|█████████â–| 45/49 [00:37<00:02, 1.75it/s]
Feature Extraction: 96%|█████████▌| 47/49 [00:37<00:00, 2.14it/s]
Feature Extraction: 98%|█████████▊| 48/49 [00:38<00:00, 2.64it/s]
Feature Extraction: 100%|██████████| 49/49 [00:38<00:00, 1.29it/s]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/47 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/47 [00:08<06:31, 8.51s/it]
Feature Extraction: 4%|â– | 2/47 [00:08<02:50, 3.79s/it]
Feature Extraction: 13%|█▎ | 6/47 [00:09<00:36, 1.12it/s]
Feature Extraction: 17%|█▋ | 8/47 [00:09<00:23, 1.65it/s]
Feature Extraction: 23%|██▎ | 11/47 [00:09<00:13, 2.71it/s]
Feature Extraction: 28%|██▊ | 13/47 [00:09<00:10, 3.31it/s]
Feature Extraction: 32%|███■| 15/47 [00:18<00:46, 1.46s/it]
Feature Extraction: 36%|███▌ | 17/47 [00:18<00:31, 1.05s/it]
Feature Extraction: 40%|████ | 19/47 [00:18<00:21, 1.29it/s]
Feature Extraction: 45%|████■| 21/47 [00:19<00:15, 1.66it/s]
Feature Extraction: 51%|█████ | 24/47 [00:19<00:11, 2.03it/s]
Feature Extraction: 55%|█████▌ | 26/47 [00:20<00:08, 2.39it/s]
Feature Extraction: 57%|█████▋ | 27/47 [00:26<00:28, 1.40s/it]
Feature Extraction: 60%|█████▉ | 28/47 [00:27<00:25, 1.34s/it]
Feature Extraction: 64%|██████■| 30/47 [00:28<00:15, 1.08it/s]
Feature Extraction: 68%|██████▊ | 32/47 [00:28<00:09, 1.52it/s]
Feature Extraction: 72%|███████■| 34/47 [00:28<00:06, 2.13it/s]
Feature Extraction: 77%|███████▋ | 36/47 [00:28<00:04, 2.72it/s]
Feature Extraction: 79%|███████▊ | 37/47 [00:29<00:04, 2.34it/s]
Feature Extraction: 81%|████████ | 38/47 [00:30<00:03, 2.35it/s]
Feature Extraction: 83%|████████▎ | 39/47 [00:30<00:03, 2.29it/s]
Feature Extraction: 85%|████████▌ | 40/47 [00:34<00:08, 1.27s/it]
Feature Extraction: 87%|████████▋ | 41/47 [00:34<00:06, 1.01s/it]
Feature Extraction: 89%|████████▉ | 42/47 [00:35<00:05, 1.03s/it]
Feature Extraction: 91%|█████████â–| 43/47 [00:36<00:03, 1.15it/s]
Feature Extraction: 96%|█████████▌| 45/47 [00:36<00:01, 1.91it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00, 2.25it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00, 1.27it/s]
+Dependency not available for matrix_profile, this feature will be disabled!
+
Feature Extraction: 0%| | 0/49 [00:00<?, ?it/s]
Feature Extraction: 2%|â– | 1/49 [00:08<06:54, 8.63s/it]
Feature Extraction: 4%|â– | 2/49 [00:09<02:59, 3.81s/it]
Feature Extraction: 8%|â–Š | 4/49 [00:09<01:07, 1.50s/it]
Feature Extraction: 12%|█■| 6/49 [00:09<00:38, 1.13it/s]
Feature Extraction: 18%|█▊ | 9/49 [00:09<00:18, 2.17it/s]
Feature Extraction: 22%|██■| 11/49 [00:10<00:13, 2.87it/s]
Feature Extraction: 27%|██▋ | 13/49 [00:10<00:09, 3.78it/s]
Feature Extraction: 31%|███ | 15/49 [00:17<00:47, 1.38s/it]
Feature Extraction: 33%|███▎ | 16/49 [00:18<00:41, 1.26s/it]
Feature Extraction: 39%|███▉ | 19/49 [00:18<00:22, 1.35it/s]
Feature Extraction: 41%|████ | 20/49 [00:18<00:18, 1.58it/s]
Feature Extraction: 43%|████▎ | 21/49 [00:19<00:15, 1.81it/s]
Feature Extraction: 49%|████▉ | 24/49 [00:19<00:10, 2.43it/s]
Feature Extraction: 51%|█████ | 25/49 [00:20<00:10, 2.37it/s]
Feature Extraction: 53%|█████▎ | 26/49 [00:21<00:11, 2.08it/s]
Feature Extraction: 55%|█████▌ | 27/49 [00:26<00:34, 1.56s/it]
Feature Extraction: 57%|█████▋ | 28/49 [00:27<00:29, 1.39s/it]
Feature Extraction: 59%|█████▉ | 29/49 [00:27<00:22, 1.12s/it]
Feature Extraction: 61%|██████ | 30/49 [00:27<00:16, 1.13it/s]
Feature Extraction: 63%|██████▎ | 31/49 [00:27<00:12, 1.49it/s]
Feature Extraction: 65%|██████▌ | 32/49 [00:28<00:10, 1.63it/s]
Feature Extraction: 67%|██████▋ | 33/49 [00:29<00:09, 1.63it/s]
Feature Extraction: 69%|██████▉ | 34/49 [00:29<00:07, 2.06it/s]
Feature Extraction: 71%|███████■| 35/49 [00:29<00:06, 2.14it/s]
Feature Extraction: 76%|███████▌ | 37/49 [00:29<00:03, 3.55it/s]
Feature Extraction: 78%|███████▊ | 38/49 [00:30<00:03, 3.45it/s]
Feature Extraction: 80%|███████▉ | 39/49 [00:31<00:06, 1.54it/s]
Feature Extraction: 82%|████████■| 40/49 [00:34<00:11, 1.27s/it]
Feature Extraction: 84%|████████▎ | 41/49 [00:35<00:08, 1.10s/it]
Feature Extraction: 86%|████████▌ | 42/49 [00:36<00:07, 1.06s/it]
Feature Extraction: 88%|████████▊ | 43/49 [00:36<00:04, 1.26it/s]
Feature Extraction: 92%|█████████â–| 45/49 [00:37<00:02, 1.50it/s]
Feature Extraction: 98%|█████████▊| 48/49 [00:37<00:00, 2.68it/s]
Feature Extraction: 100%|██████████| 49/49 [00:37<00:00, 3.02it/s]
Feature Extraction: 100%|██████████| 49/49 [00:37<00:00, 1.29it/s]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-15.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+512 Pilot02 3 linreg ... -6.796172 0.051448 0.069456
+513 Pilot02 3 linreg ... -9.129009 0.001051 0.970434
+514 Pilot02 3 linreg ... -5.420812 -0.014440 0.610586
+515 Pilot02 3 linreg ... -25.639528 -0.037107 0.190544
+516 Pilot03 2 linreg ... -1.298246 -0.065345 0.041042
+
+[517 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-17.0
+train
+(100, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+513 Pilot02 3 linreg ... -9.129009 0.001051 0.970434
+514 Pilot02 3 linreg ... -5.420812 -0.014440 0.610586
+515 Pilot02 3 linreg ... -25.639528 -0.037107 0.190544
+516 Pilot03 2 linreg ... -1.298246 -0.065345 0.041042
+517 Pilot03 2 linreg ... -1.320072 -0.068867 0.031281
+
+[518 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+514 Pilot02 3 linreg ... -5.420812 -0.014440 0.610586
+515 Pilot02 3 linreg ... -25.639528 -0.037107 0.190544
+516 Pilot03 2 linreg ... -1.298246 -0.065345 0.041042
+517 Pilot03 2 linreg ... -1.320072 -0.068867 0.031281
+518 Pilot03 2 linreg ... -1.719100 -0.014930 0.640971
+
+[519 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+515 Pilot02 3 linreg ... -25.639528 -0.037107 0.190544
+516 Pilot03 2 linreg ... -1.298246 -0.065345 0.041042
+517 Pilot03 2 linreg ... -1.320072 -0.068867 0.031281
+518 Pilot03 2 linreg ... -1.719100 -0.014930 0.640971
+519 Pilot03 2 linreg ... -1.205096 -0.094689 0.003036
+
+[520 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+516 Pilot03 2 linreg ... -1.298246 -0.065345 0.041042
+517 Pilot03 2 linreg ... -1.320072 -0.068867 0.031281
+518 Pilot03 2 linreg ... -1.719100 -0.014930 0.640971
+519 Pilot03 2 linreg ... -1.205096 -0.094689 0.003036
+520 Pilot03 2 linreg ... -1.369422 -0.058643 0.066776
+
+[521 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+517 Pilot03 2 linreg ... -1.320072 -0.068867 0.031281
+518 Pilot03 2 linreg ... -1.719100 -0.014930 0.640971
+519 Pilot03 2 linreg ... -1.205096 -0.094689 0.003036
+520 Pilot03 2 linreg ... -1.369422 -0.058643 0.066776
+521 Pilot03 2 linreg ... -1.410067 -0.043944 0.169702
+
+[522 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+518 Pilot03 2 linreg ... -1.719100 -0.014930 0.640971
+519 Pilot03 2 linreg ... -1.205096 -0.094689 0.003036
+520 Pilot03 2 linreg ... -1.369422 -0.058643 0.066776
+521 Pilot03 2 linreg ... -1.410067 -0.043944 0.169702
+522 Pilot03 2 linreg ... -1.209088 -0.069918 0.028784
+
+[523 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+519 Pilot03 2 linreg ... -1.205096 -0.094689 0.003036
+520 Pilot03 2 linreg ... -1.369422 -0.058643 0.066776
+521 Pilot03 2 linreg ... -1.410067 -0.043944 0.169702
+522 Pilot03 2 linreg ... -1.209088 -0.069918 0.028784
+523 Pilot03 2 linreg ... -1.500180 -0.038757 0.225913
+
+[524 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+520 Pilot03 2 linreg ... -1.369422 -0.058643 0.066776
+521 Pilot03 2 linreg ... -1.410067 -0.043944 0.169702
+522 Pilot03 2 linreg ... -1.209088 -0.069918 0.028784
+523 Pilot03 2 linreg ... -1.500180 -0.038757 0.225913
+524 Pilot03 2 linreg ... -1.486533 -0.028625 0.371199
+
+[525 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-7.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+521 Pilot03 2 linreg ... -1.410067 -0.043944 0.169702
+522 Pilot03 2 linreg ... -1.209088 -0.069918 0.028784
+523 Pilot03 2 linreg ... -1.500180 -0.038757 0.225913
+524 Pilot03 2 linreg ... -1.486533 -0.028625 0.371199
+525 Pilot03 2 linreg ... -1.234225 -0.050201 0.116671
+
+[526 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+522 Pilot03 2 linreg ... -1.209088 -0.069918 0.028784
+523 Pilot03 2 linreg ... -1.500180 -0.038757 0.225913
+524 Pilot03 2 linreg ... -1.486533 -0.028625 0.371199
+525 Pilot03 2 linreg ... -1.234225 -0.050201 0.116671
+526 Pilot03 2 linreg ... -0.895766 -0.081948 0.010353
+
+[527 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+523 Pilot03 2 linreg ... -1.500180 -0.038757 0.225913
+524 Pilot03 2 linreg ... -1.486533 -0.028625 0.371199
+525 Pilot03 2 linreg ... -1.234225 -0.050201 0.116671
+526 Pilot03 2 linreg ... -0.895766 -0.081948 0.010353
+527 Pilot03 2 linreg ... -1.147796 -0.053428 0.094935
+
+[528 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+524 Pilot03 2 linreg ... -1.486533 -0.028625 0.371199
+525 Pilot03 2 linreg ... -1.234225 -0.050201 0.116671
+526 Pilot03 2 linreg ... -0.895766 -0.081948 0.010353
+527 Pilot03 2 linreg ... -1.147796 -0.053428 0.094935
+528 Pilot03 2 linreg ... -1.169716 -0.041156 0.198449
+
+[529 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-10.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+525 Pilot03 2 linreg ... -1.234225 -0.050201 0.116671
+526 Pilot03 2 linreg ... -0.895766 -0.081948 0.010353
+527 Pilot03 2 linreg ... -1.147796 -0.053428 0.094935
+528 Pilot03 2 linreg ... -1.169716 -0.041156 0.198449
+529 Pilot03 2 linreg ... -0.941939 -0.074300 0.020135
+
+[530 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi5.0-12.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+526 Pilot03 2 linreg ... -0.895766 -0.081948 0.010353
+527 Pilot03 2 linreg ... -1.147796 -0.053428 0.094935
+528 Pilot03 2 linreg ... -1.169716 -0.041156 0.198449
+529 Pilot03 2 linreg ... -0.941939 -0.074300 0.020135
+530 Pilot03 2 linreg ... -0.999938 -0.044756 0.161942
+
+[531 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-15.0-17.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+527 Pilot03 2 linreg ... -1.147796 -0.053428 0.094935
+528 Pilot03 2 linreg ... -1.169716 -0.041156 0.198449
+529 Pilot03 2 linreg ... -0.941939 -0.074300 0.020135
+530 Pilot03 2 linreg ... -0.999938 -0.044756 0.161942
+531 Pilot03 2 linreg ... -0.445521 -0.103372 0.001207
+
+[532 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-15.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+528 Pilot03 2 linreg ... -1.169716 -0.041156 0.198449
+529 Pilot03 2 linreg ... -0.941939 -0.074300 0.020135
+530 Pilot03 2 linreg ... -0.999938 -0.044756 0.161942
+531 Pilot03 2 linreg ... -0.445521 -0.103372 0.001207
+532 Pilot03 2 linreg ... -0.629643 -0.066178 0.038526
+
+[533 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-17.0-20.0
+train
+(101, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+529 Pilot03 2 linreg ... -0.941939 -0.074300 0.020135
+530 Pilot03 2 linreg ... -0.999938 -0.044756 0.161942
+531 Pilot03 2 linreg ... -0.445521 -0.103372 0.001207
+532 Pilot03 2 linreg ... -0.629643 -0.066178 0.038526
+533 Pilot03 2 linreg ... -0.683093 -0.060810 0.057299
+
+[534 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-10.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+530 Pilot03 2 linreg ... -0.999938 -0.044756 0.161942
+531 Pilot03 2 linreg ... -0.445521 -0.103372 0.001207
+532 Pilot03 2 linreg ... -0.629643 -0.066178 0.038526
+533 Pilot03 2 linreg ... -0.683093 -0.060810 0.057299
+534 Pilot03 2 linreg ... -0.579251 -0.067470 0.034885
+
+[535 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi7.0-12.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+531 Pilot03 2 linreg ... -0.445521 -0.103372 0.001207
+532 Pilot03 2 linreg ... -0.629643 -0.066178 0.038526
+533 Pilot03 2 linreg ... -0.683093 -0.060810 0.057299
+534 Pilot03 2 linreg ... -0.579251 -0.067470 0.034885
+535 Pilot03 2 linreg ... -0.584314 -0.068252 0.032827
+
+[536 rows x 18 columns]
+imu-bvp_rr_Pilot03_id2_combi10.0-12.0-15.0-17.0-20.0
+train
+(102, 5485)
+test
+(978, 5484)
+---LinearRegression---
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+532 Pilot03 2 linreg ... -0.629643 -0.066178 0.038526
+533 Pilot03 2 linreg ... -0.683093 -0.060810 0.057299
+534 Pilot03 2 linreg ... -0.579251 -0.067470 0.034885
+535 Pilot03 2 linreg ... -0.584314 -0.068252 0.032827
+536 Pilot03 2 linreg ... -0.325231 -0.063084 0.048580
+
+[537 rows x 18 columns]
+Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='linreg', overwrite=1, subject=3, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
diff --git a/logs/singularity_4027803.out b/logs/singularity_4027803.out
new file mode 100644
index 0000000..b676352
--- /dev/null
+++ b/logs/singularity_4027803.out
@@ -0,0 +1,495 @@
+2023-11-26 23:59:27.557260: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Using TensorFlow backend
+Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='elastic', overwrite=0, subject=2, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
+Using pre-set data id: 3
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-10.0-12.0-15.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+546 Pilot02 3 linreg ... -16.926541 -0.011023 0.697489
+547 Pilot02 3 linreg ... -0.948799 -0.007771 0.784065
+548 Pilot03 2 elastic ... -1.758438 -0.126951 0.000069
+549 Pilot03 2 elastic ... -1.925223 -0.070755 0.026920
+550 Pilot02 3 elastic ... -5.596573 0.107220 0.000150
+
+[551 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-10.0-12.0-17.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+549 Pilot03 2 elastic ... -1.925223 -0.070755 0.026920
+550 Pilot02 3 elastic ... -5.596573 0.107220 0.000150
+551 Pilot03 2 elastic ... -2.161178 -0.052695 0.099562
+552 Pilot03 2 elastic ... -1.996716 -0.129399 0.000049
+553 Pilot02 3 elastic ... -7.182356 0.069423 0.014245
+
+[554 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-10.0-12.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+/usr/local/lib/python3.8/dist-packages/scipy/stats/_stats_py.py:4424: ConstantInputWarning: An input array is constant; the correlation coefficient is not defined.
+ warnings.warn(stats.ConstantInputWarning(msg))
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+552 Pilot03 2 elastic ... -1.996716 -0.129399 0.000049
+553 Pilot02 3 elastic ... -7.182356 0.069423 0.014245
+554 Pilot03 2 elastic ... -2.473361 -0.103564 0.001181
+555 Pilot03 2 elastic ... -2.166505 -0.051172 0.109753
+556 Pilot02 3 elastic ... -3.104293 NaN NaN
+
+[557 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-10.0-15.0-17.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+554 Pilot03 2 elastic ... -2.473361 -0.103564 0.001181
+555 Pilot03 2 elastic ... -2.166505 -0.051172 0.109753
+556 Pilot02 3 elastic ... -3.104293 NaN NaN
+557 Pilot03 2 elastic ... -1.913436 -0.117161 0.000241
+558 Pilot02 3 elastic ... -5.419605 0.029585 0.296716
+
+[559 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-10.0-15.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+558 Pilot02 3 elastic ... -5.419605 0.029585 0.296716
+559 Pilot03 2 elastic ... -2.370444 -0.110486 0.000537
+560 Pilot03 2 elastic ... -2.268817 -0.092573 0.003761
+561 Pilot03 2 elastic ... -1.844984 -0.102995 0.001258
+562 Pilot02 3 elastic ... -1.737720 0.018534 0.513349
+
+[563 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-10.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+561 Pilot03 2 elastic ... -1.844984 -0.102995 0.001258
+562 Pilot02 3 elastic ... -1.737720 0.018534 0.513349
+563 Pilot03 2 elastic ... -2.074848 -0.111489 0.000478
+564 Pilot03 2 elastic ... -2.468988 -0.096367 0.002554
+565 Pilot02 3 elastic ... -1.610216 -0.007174 0.800294
+
+[566 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-12.0-15.0-17.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+564 Pilot03 2 elastic ... -2.468988 -0.096367 0.002554
+565 Pilot02 3 elastic ... -1.610216 -0.007174 0.800294
+566 Pilot03 2 elastic ... -2.274461 -0.073805 0.020982
+567 Pilot03 2 elastic ... -1.732794 -0.102280 0.001360
+568 Pilot02 3 elastic ... -3.323004 0.042106 0.137421
+
+[569 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-12.0-15.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+567 Pilot03 2 elastic ... -1.732794 -0.102280 1.360380e-03
+568 Pilot02 3 elastic ... -3.323004 0.042106 1.374214e-01
+569 Pilot03 2 elastic ... -1.298003 -0.060662 5.790618e-02
+570 Pilot03 2 elastic ... -1.030237 -0.161102 4.088040e-07
+571 Pilot02 3 elastic ... -2.548343 0.009285 7.433378e-01
+
+[572 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-12.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+569 Pilot03 2 elastic ... -1.298003 -0.060662 5.790618e-02
+570 Pilot03 2 elastic ... -1.030237 -0.161102 4.088040e-07
+571 Pilot02 3 elastic ... -2.548343 0.009285 7.433378e-01
+572 Pilot03 2 elastic ... -1.815615 -0.193334 1.087464e-09
+573 Pilot02 3 elastic ... -1.880238 -0.040916 1.488975e-01
+
+[574 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-7.0-15.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 0.070097 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 0.047023 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 0.016892 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 0.118749 5.380273e-03
+.. ... ... ... ... ... ... ...
+572 Pilot03 2 elastic ... -1.815615 -0.193334 1.087464e-09
+573 Pilot02 3 elastic ... -1.880238 -0.040916 1.488975e-01
+574 Pilot03 2 elastic ... -1.328308 -0.136510 1.838231e-05
+575 Pilot03 2 elastic ... -1.926497 -0.186432 4.243797e-09
+576 Pilot02 3 elastic ... -2.947342 -0.007501 7.913772e-01
+
+[577 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-10.0-12.0-15.0-17.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+/usr/local/lib/python3.8/dist-packages/scipy/stats/_stats_py.py:4461: NearConstantInputWarning: An input array is nearly constant; the computed correlation coefficient may be inaccurate.
+ warnings.warn(stats.NearConstantInputWarning(msg))
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 3.877603e-02 3.649402e-01
+1 Pilot02 0 linreg ... -11.875765 7.009716e-02 1.011711e-01
+2 Pilot02 0 linreg ... -11.069278 4.702307e-02 2.718220e-01
+3 Pilot02 0 linreg ... -25.345517 1.689162e-02 6.931765e-01
+4 Pilot02 0 linreg ... -15.299470 1.187485e-01 5.380273e-03
+.. ... ... ... ... ... ... ...
+574 Pilot03 2 elastic ... -1.328308 -1.365100e-01 1.838231e-05
+575 Pilot03 2 elastic ... -1.926497 -1.864318e-01 4.243797e-09
+576 Pilot02 3 elastic ... -2.947342 -7.501254e-03 7.913772e-01
+577 Pilot03 2 elastic ... -0.806993 -1.393941e-01 1.213925e-05
+578 Pilot02 3 elastic ... -2.285661 6.344185e-07 9.999821e-01
+
+[579 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-10.0-12.0-15.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 3.877603e-02 0.364940
+1 Pilot02 0 linreg ... -11.875765 7.009716e-02 0.101171
+2 Pilot02 0 linreg ... -11.069278 4.702307e-02 0.271822
+3 Pilot02 0 linreg ... -25.345517 1.689162e-02 0.693177
+4 Pilot02 0 linreg ... -15.299470 1.187485e-01 0.005380
+.. ... ... ... ... ... ... ...
+576 Pilot02 3 elastic ... -2.947342 -7.501254e-03 0.791377
+577 Pilot03 2 elastic ... -0.806993 -1.393941e-01 0.000012
+578 Pilot02 3 elastic ... -2.285661 6.344185e-07 0.999982
+579 Pilot03 2 elastic ... -0.123614 1.726530e-02 0.589689
+580 Pilot02 3 elastic ... -1.856123 -3.904010e-02 0.168448
+
+[581 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-10.0-12.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 3.877603e-02 0.364940
+1 Pilot02 0 linreg ... -11.875765 7.009716e-02 0.101171
+2 Pilot02 0 linreg ... -11.069278 4.702307e-02 0.271822
+3 Pilot02 0 linreg ... -25.345517 1.689162e-02 0.693177
+4 Pilot02 0 linreg ... -15.299470 1.187485e-01 0.005380
+.. ... ... ... ... ... ... ...
+577 Pilot03 2 elastic ... -0.806993 -1.393941e-01 0.000012
+578 Pilot02 3 elastic ... -2.285661 6.344185e-07 0.999982
+579 Pilot03 2 elastic ... -0.123614 1.726530e-02 0.589689
+580 Pilot02 3 elastic ... -1.856123 -3.904010e-02 0.168448
+581 Pilot02 3 elastic ... -1.560151 -4.462040e-02 0.115431
+
+[582 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-10.0-15.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 3.877603e-02 0.364940
+1 Pilot02 0 linreg ... -11.875765 7.009716e-02 0.101171
+2 Pilot02 0 linreg ... -11.069278 4.702307e-02 0.271822
+3 Pilot02 0 linreg ... -25.345517 1.689162e-02 0.693177
+4 Pilot02 0 linreg ... -15.299470 1.187485e-01 0.005380
+.. ... ... ... ... ... ... ...
+578 Pilot02 3 elastic ... -2.285661 6.344185e-07 0.999982
+579 Pilot03 2 elastic ... -0.123614 1.726530e-02 0.589689
+580 Pilot02 3 elastic ... -1.856123 -3.904010e-02 0.168448
+581 Pilot02 3 elastic ... -1.560151 -4.462040e-02 0.115431
+582 Pilot02 3 elastic ... -1.242345 -4.401314e-02 0.120471
+
+[583 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi5.0-12.0-15.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+/usr/local/lib/python3.8/dist-packages/scipy/stats/_stats_py.py:4424: ConstantInputWarning: An input array is constant; the correlation coefficient is not defined.
+ warnings.warn(stats.ConstantInputWarning(msg))
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+579 Pilot03 2 elastic ... -0.123614 0.017265 0.589689
+580 Pilot02 3 elastic ... -1.856123 -0.039040 0.168448
+581 Pilot02 3 elastic ... -1.560151 -0.044620 0.115431
+582 Pilot02 3 elastic ... -1.242345 -0.044013 0.120471
+583 Pilot02 3 elastic ... -1.023577 NaN NaN
+
+[584 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi7.0-10.0-12.0-15.0-17.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+580 Pilot02 3 elastic ... -1.856123 -0.039040 0.168448
+581 Pilot02 3 elastic ... -1.560151 -0.044620 0.115431
+582 Pilot02 3 elastic ... -1.242345 -0.044013 0.120471
+583 Pilot02 3 elastic ... -1.023577 NaN NaN
+584 Pilot02 3 elastic ... -1.205065 -0.004848 0.864262
+
+[585 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi7.0-10.0-12.0-15.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+581 Pilot02 3 elastic ... -1.560151 -0.044620 0.115431
+582 Pilot02 3 elastic ... -1.242345 -0.044013 0.120471
+583 Pilot02 3 elastic ... -1.023577 NaN NaN
+584 Pilot02 3 elastic ... -1.205065 -0.004848 0.864262
+585 Pilot02 3 elastic ... -0.963534 0.021076 0.457296
+
+[586 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi7.0-10.0-12.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+582 Pilot02 3 elastic ... -1.242345 -0.044013 0.120471
+583 Pilot02 3 elastic ... -1.023577 NaN NaN
+584 Pilot02 3 elastic ... -1.205065 -0.004848 0.864262
+585 Pilot02 3 elastic ... -0.963534 0.021076 0.457296
+586 Pilot02 3 elastic ... -0.832011 0.014414 0.611245
+
+[587 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi7.0-10.0-15.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+583 Pilot02 3 elastic ... -1.023577 NaN NaN
+584 Pilot02 3 elastic ... -1.205065 -0.004848 0.864262
+585 Pilot02 3 elastic ... -0.963534 0.021076 0.457296
+586 Pilot02 3 elastic ... -0.832011 0.014414 0.611245
+587 Pilot02 3 elastic ... -0.777954 0.006047 0.831128
+
+[588 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi7.0-12.0-15.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+584 Pilot02 3 elastic ... -1.205065 -0.004848 0.864262
+585 Pilot02 3 elastic ... -0.963534 0.021076 0.457296
+586 Pilot02 3 elastic ... -0.832011 0.014414 0.611245
+587 Pilot02 3 elastic ... -0.777954 0.006047 0.831128
+588 Pilot02 3 elastic ... -4.740700 0.001226 0.965517
+
+[589 rows x 18 columns]
+imu-bvp_rr_Pilot02_id3_combi10.0-12.0-15.0-17.0-20.0
+train
+(100, 5485)
+test
+(1246, 5484)
+---ElasticNet---
+/usr/local/lib/python3.8/dist-packages/sklearn/linear_model/_coordinate_descent.py:1563: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
+ y = column_or_1d(y, warn=True)
+adding new entry
+ subject config_id mdl_str ... r2 pearsonr_coeff pearsonr_pval
+0 Pilot02 0 linreg ... -9.864563 0.038776 0.364940
+1 Pilot02 0 linreg ... -11.875765 0.070097 0.101171
+2 Pilot02 0 linreg ... -11.069278 0.047023 0.271822
+3 Pilot02 0 linreg ... -25.345517 0.016892 0.693177
+4 Pilot02 0 linreg ... -15.299470 0.118749 0.005380
+.. ... ... ... ... ... ... ...
+585 Pilot02 3 elastic ... -0.963534 0.021076 0.457296
+586 Pilot02 3 elastic ... -0.832011 0.014414 0.611245
+587 Pilot02 3 elastic ... -0.777954 0.006047 0.831128
+588 Pilot02 3 elastic ... -4.740700 0.001226 0.965517
+589 Pilot02 3 elastic ... -0.478754 -0.043455 0.125258
+
+[590 rows x 18 columns]
+Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='elastic', overwrite=0, subject=2, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
diff --git a/modules/digitalsignalprocessing.py b/modules/digitalsignalprocessing.py
index c4f4f41..d03d9b5 100644
--- a/modules/digitalsignalprocessing.py
+++ b/modules/digitalsignalprocessing.py
@@ -77,8 +77,8 @@ def run_fft(data, fs):
xf = fftfreq(N,T)[:N//2]
return xf, yf
-def do_pad_fft(sig, fs=IMU_FS):
- pad_len = npads_frequency_resolution(len(sig), fs=fs)
+def do_pad_fft(sig, fs=IMU_FS, fr=0.02):
+ pad_len = npads_frequency_resolution(len(sig), fs=fs, fr=fr)
data_pad = np.pad(sig.squeeze(), (0, pad_len), 'constant', constant_values=0)
data_xf, data_yf = run_fft(data_pad, fs)
return data_xf, data_yf
diff --git a/regress_rr.py b/regress_rr.py
index c420b0c..cc0024d 100644
--- a/regress_rr.py
+++ b/regress_rr.py
@@ -367,47 +367,29 @@ def sync_to_ref(df0, df1):
return dsync0.sync_df(df0), dsync1.sync_df(df1)
-# Multiprocessing task for windowing dataframe
-def imu_df_win_task(w_inds, df, i, cols):
- time = df['sec'].values
- if w_inds[-1] == 0: return
- w_df = df.iloc[w_inds]
- t0, t1 = time[w_inds][0], time[w_inds][-1]
- diff = time[w_inds[1:]] - time[w_inds[0:-1]]
- mask = np.abs(diff)>20
- diff_chk = np.any(mask)
- if diff_chk:
- return
-
- if cols is None:
- cols = IMU_COLS
-
- data = w_df[cols].values
-
- # DSP
- sd_data = (data - np.mean(data, axis=0))/np.std(data, axis=0)
- # ys = cubic_interp(sd_data, BR_FS, FS_RESAMPLE)
- filt_data = imu_signal_processing(sd_data, IMU_FS)
- x_out = pd.DataFrame(filt_data,
- columns=IMU_COLS)
-
- sm_out = w_df['BR'].values
- ps_out = w_df['PSS'].values
-
- x_vec_time = np.median(time[w_inds])
-
- fs = 1/np.mean(diff)
- ps_freq = int(get_max_frequency(ps_out, fs=fs))
-
- y_tmp = np.array([x_vec_time, np.nanmedian(sm_out), ps_freq])
-
- x_out['sec'] = x_vec_time
- x_out['id'] = i
- y_out = pd.DataFrame([y_tmp], columns=['sec', 'br', 'pss'])
+# Task for windowing dataframe
+def df_win_task(w_inds, df, i, cols):
+ """
+ Performs signal processing on IMU. If BVP values exist in the column
+ namespace, BVP signal processing is performed. Extract median BR from the
+ summary bioharness file and max frequency of the PSS wave.
+ Add index value for each window for tsfresh processing.
- return x_out, y_out
+ Attributes
+ ----------
+ w_inds : numpy.ndarray
+ specifies the window indexes for the df
+ df : pandas.DataFrame
+ DataFrame to extract window from
+ i : int
+ window index
+ cols : list
+ columns to perform data processing functions across
-def df_win_task(w_inds, df, i, cols):
+ Returns
+ -------
+ pandas.DataFrame, pandas.DataFrame
+ """
time = df['sec'].values
if w_inds[-1] == 0: return
w_df = df.iloc[w_inds]
@@ -417,6 +399,8 @@ def df_win_task(w_inds, df, i, cols):
fs_est = 1/np.mean(diff)
if fs_est > 70 and 'acc_x' in cols: fs = IMU_FS
elif fs_est < 70 and 'bvp' in cols: fs = PPG_FS
+
+ # Reject window if there is a time difference between rows greater than 20s
mask = np.abs(diff)>20
diff_chk = np.any(mask)
if diff_chk:
@@ -445,6 +429,7 @@ def df_win_task(w_inds, df, i, cols):
x_vec_time = np.median(time[w_inds])
fs = 1/np.mean(diff)
+ ps_out = pressure_signal_processing(ps_out, fs=fs)
ps_freq = int(get_max_frequency(ps_out, fs=fs))
y_tmp = np.array([x_vec_time, np.nanmedian(sm_out), ps_freq])
@@ -458,18 +443,40 @@ def df_win_task(w_inds, df, i, cols):
if 'bvp' in cols:
xf, yf = do_pad_fft(bvp_filt, fs=fs)
bv_freq = int(xf[yf.argmax()]*60)
- # y_out['bvp_est'] = bv_freq
+ # Uncomment if you wish to extract BVP estimated HR.
+ # y_out['hr_est'] = bv_freq
return x_out, y_out
-def get_max_frequency(data, fs=IMU_FS):
- data = pressure_signal_processing(data, fs=fs)
+def get_max_frequency(data, fs=IMU_FS, fr=0.02):
+ """
+ Returns the maximum frequency after padded fft
+
+ Attributes
+ ----------
+ data : numpy.ndarray
+ signal to extract max frequency
+ fs : int
+ signal sampling frequency (default = IMU_FS)
+ fr : float
+ frequency resolution to set pad length (default = 0.02)
- xf, yf = do_pad_fft(data, fs=fs)
+ Returns
+ -------
+ float
+ """
+ xf, yf = do_pad_fft(data, fs=fs, fr=fr)
max_freq = xf[yf.argmax()]*60
return max_freq
def convert_to_float(df):
+ """
+ Converts 'sec', 'pss', 'br', and 'subject' columns to float
+
+ Attributes
+ ----------
+ df : pandas.DataFrame
+ """
cols = df.columns.values
if 'sec' in cols:
df['sec'] = df['sec'].astype(float)
@@ -481,6 +488,22 @@ def convert_to_float(df):
df['subject'] = df['subject'].astype(float)
def load_and_sync_xsens(subject, sens_list:list=['imu', 'bvp']):
+ """
+ Loads requested sensors from the subject folder and synchronises each to
+ the beginning and end timestamps. Linearly interpolates the data and
+ timestamps to match the higher frequency data.
+
+ Arguments
+ ---------
+ subject : str
+ subject to extract data from (i.e. 'Pilot02', 'S02')
+ sens_list : list
+ a list that contains either or both 'imu' and 'bvp'
+
+ Returns
+ -------
+ pd.DataFrame
+ """
assert 'imu' in sens_list or 'bvp' in sens_list, \
f"{sens_list} is not supported, must contain"\
"'imu', 'bvp' or 'imu, bvp'"
@@ -610,10 +633,6 @@ def load_tsfresh(xsens_df, home_dir,
"""
assert data_cols is not None, "invalid selection for data columns"
- assert 'acc_x' in xsens_df.columns.tolist() and \
- 'gyro_x' in xsens_df.columns.tolist() and \
- 'bvp' in xsens_df.columns.tolist(), \
- "Does not include the full required dataset. Must have both IMU and BVP"
# raise NotImplementedError("To be implemented")
@@ -629,6 +648,12 @@ def load_tsfresh(xsens_df, home_dir,
if exists(pkl_file) and not overwrite:
return pd.read_pickle(pkl_file)
+
+ assert 'acc_x' in xsens_df.columns.tolist() and \
+ 'gyro_x' in xsens_df.columns.tolist() and \
+ 'bvp' in xsens_df.columns.tolist(), \
+ "First instance must include the full required dataset. Must have both "\
+ "IMU and BVP"
x_df, y_df = get_df_windows(xsens_df,
df_win_task,
window_size=window_size,
@@ -847,6 +872,8 @@ def dsp_win_func(w_inds, df, i, cols):
x_vec_time = np.median(time[w_inds])
fs = 1/np.mean(diff)
+ ps_out = pressure_signal_processing(ps_out, fs=fs)
+
ps_freq = int(get_max_frequency(ps_out, fs=IMU_FS))
y_tmp = np.array([x_vec_time, np.nanmedian(sm_out), ps_freq])
@@ -1226,8 +1253,8 @@ def sens_rr_model(subject,
x_test = make_windows_from_id(x_test_df, data_cols)
y_test = y_test_df[lbl_str].values.reshape(-1, 1)
- # x_train = y_train_df['bvp_est'].values.reshape(-1, 1)
- # x_test = y_test_df['bvp_est'].values.reshape(-1, 1)
+ # x_train = y_train_df['hr_est'].values.reshape(-1, 1)
+ # x_test = y_test_df['hr_est'].values.reshape(-1, 1)
print("minirocket transforming...")
x_train = np.swapaxes(x_train, 1, 2)
x_test = np.swapaxes(x_test, 1, 2)
--
GitLab