Add scripts to download and prepare ldopa data (#13)

.gitignore

@@ -10,6 +10,8 @@ tramp
 .\#*
 runs/
 
+# data files
+data/*
 
 # intermediate files
 *.log
@@ -69,3 +71,6 @@ multirun
 
 # tmp files
 tmp
+
+# env file
+.env

data_parsing/README.md

@@ -1,22 +1,24 @@
 ## Baseline pre-processing
-All the data are processed to have a unit of G. They will also be clipped to have values between +- 3g. 
+All the data are processed to have a unit of G. They will also be clipped to have values between ±3g. 
 The range and sampling frequencies of different datasets are 
 different. The clipping of values should only be done at the modeling stage. When doing pre-processing, we should 
 only extract the raw data. Not sure if this matters:
 
 We have included links to the processed datasets that are publicly available. One would however make a request to access
-data from the [UK-Biobank](https://www.ukbiobank.ac.uk) and the [Rowlands](https://pubmed.ncbi.nlm.nih.gov/21088628/) dataset.
+data from the [UK-Biobank](https://www.ukbiobank.ac.uk), the [Rowlands](https://pubmed.ncbi.nlm.nih.gov/21088628/) dataset and the [MJFF-LR](https://www.synapse.org/#!Synapse:syn20681023/wiki/594678) dataset.
 
-| Dataset  | n |Output_size |  Range  | Sample rate  |  Validation method |
+| Dataset  | n |Output_size |  Range  | Sample rate (Hz)  |  Validation method |
 |---|---|---|---|---|---|
-| PAMAP2   | 8 | 8  |+- 16g |  100Hz | Held-one-subject-out cross-validation, using one in test and one in val. This is because  not all the activities are performed by all subjects.  We will use only activities 1, 2, 3, 4, 12, 13, 16, 17 and remove subject 109. This ensures that every subject will have all eight activities. |
-|  OPPO    |4 | 4  | -     | 30Hz     | Held-one-subject-out cross-validation. Four locomotion labels. Every subject will have all the activities. Weighted-cross-entropy.| 
-|  Clemson | 30 |1  | +- 2g | 15Hz      | Five-fold cross-validation. All subjects have roughly about 300-600 samples.| 
-|  Rowlands | 55 |13  | - | 80Hz      | - | 
-|  Capture-24 | 152 |6  | - | 100      | Five-fold | 
-|  Real-world | 14 |8  | - | 30      | Five-fold, subject 2 removed  | 
-|  WISDM | 46 |18  | - | 30      | Five-fold, subject 1616, 1618, 1637, 1639, 1642 removed  | 
-|  ADL | 7 |5  | - | 30      | Held-one-subject out | 
+| Capture-24 | 152 | 6 | - | 100 | Five-fold |
+| Rowlands | 55 | 13 | - | 80 | - |
+| WISDM | 46 | 18 | - | 30 | Five-fold, subject 1616, 1618, 1637, 1639, 1642 removed |
+| MJFF-LR | 28 | 12 | - | 50 | Five-fold, days 2 and 3 and activities finger-to-nose and repeated-arm-movement removed |
+| REALWORLD | 14 | 8 | - | 30 | Five-fold, subject 2 removed |
+| Opportunity | 4 | 4 | - | 30 | Held-one-subject-out cross-validation. Four locomotion labels. Every subject will have all the activities. Weighted-cross-entropy.|
+| PAMAP2 | 8 | 8 | ±16g | 100 | Held-one-subject-out cross-validation, using one in test and one in val. This is because  not all the activities are performed by all subjects.  We will use only activities 1, 2, 3, 4, 12, 13, 16, 17 and remove subject 109. This ensures that every subject will have all eight activities. |
+| Clemson | 30 | 1  | ±2g | 15 | Five-fold cross-validation. All subjects have roughly about 300-600 samples. | 
+| ADL | 7 | 5 | - | 30 | Held-one-subject out | 
+
 
 70/10/20 ratio for five-fold cross-validation.
 
@@ -25,4 +27,4 @@ References:
 * [WISDM Smartphone and Smartwatch Activity and Biometrics Dataset Data Set 
 ](https://archive.ics.uci.edu/ml/datasets/WISDM+Smartphone+and+Smartwatch+Activity+and+Biometrics+Dataset+)
 * [Dataset for ADL Recognition with Wrist-worn Accelerometer Data Set](https://archive.ics.uci.edu/ml/datasets/Dataset+for+ADL+Recognition+with+Wrist-worn+Accelerometer?ref=datanews.io)
-* [RealWorld](https://sensor.informatik.uni-mannheim.de/#dataset_realworld)  
+* [RealWorld](https://sensor.informatik.uni-mannheim.de/#dataset_realworld)