a6a37c7bd9
Drop NaN targets.
This mirrors INNER join in merge_features_and_targets_for_individual_model.py:
data = pd.concat([sensor_features, targets[["target"]]], axis=1, join="inner")
2 months ago
9f5edf1c2b
Revert "Add a rule for model baselines."
The example was for a classification rather than regression problem.
This reverts commit 9ab0c8f289
2 months ago
4ad261fae5
Rename baseline features AGAIN.
Correct other mistakes.
2 months ago
9ab0c8f289
Add a rule for model baselines.
Add baselines and helper functions to main models dir.
2 months ago
f5688f6154
Add a rule to merge sensor and baseline features.
And select target as before.
3 months ago
b1f356c3f7
Extract a function to be used elsewhere.
3 months ago
7ff3dcf5fc
Move and rename target variable.
3 months ago
50c0defca7
Select target columns (no parsing necessary).
3 months ago
ac86221662
[WIP] Add a rule to parse targets.
Does nothing for now.
3 months ago
d326a1b09d
Include the constant directly in main.py.
3 months ago
2e545e81f0
Include feature calculations for different scales.
3 months ago
cbc8ae4e03
Add necessary checks for empty data frames.
3 months ago
751b04f3f4
Pass scale names to Snakemake correctly.
3 months ago
99245afca3
Try a different approach for preprocessing ESMs.
It is important that this follows generic RAPIDS pattern.
In the subsequent step of calculating features,
there is an expected file and folder structure of data/interim.
See rules/common.smk/find_features_files()
3 months ago
ed298a9479
Implement the basic feature extraction steps.
3 months ago
3af8de6235
Create feature provider script.
3 months ago
9478dc94f2
Add an else.
This is to make sure that in case the reversing fails, we do not get any output items.
Snakemake will inform us of an error in this event.
3 months ago
b18dba366e
Add an else.
This is to make sure that in case the reversing fails, we do not get any output items.
Snakemake will inform us of an error in this event.
3 months ago
c6144f8403
Reverse JCQ items.
3 months ago
23f0aaba3a
Get the name of the questionnaire from Snakefile.
3 months ago
679f00dc19
Enable selecting any questionnaire as target.
3 months ago
1374eda171
Flatten questionnaire ID dict.
3 months ago
19b9da0ba3
Separate function definitions from main.
3 months ago
ef57103bac
Add questionnaire ID key.
3 months ago
5f293211a7
Reformat.
3 months ago
d470eef27e
Add a rule to preprocess and clean ESM.
4 months ago
d4a4bbbff0
Remove unused columns.
4 months ago
085a6d144b
Add files to compute and create an empty script.
4 months ago
42d62f16d0
Add RAPIDS mandatory columns for ESM.
4 months ago
2bef86b1da
Add a format for ESM and add to config.
4 months ago
d8e9a309f7
Rename features and write baseline_interim.
4 months ago
a3a4f04ffe
Setting with : produces NaNs.
4 months ago
aedb8b6785
Write questionnaire data to data/interim.
4 months ago
d3ebfeeabd
Write questionnaire data to data/interim.
4 months ago
f13a91044d
Write questionnaire data to data/interim.
4 months ago
b5a6317f4b
Calculate JCQ control and demand control ratio.
Include norms and corresponding quartile.
4 months ago
2fed962644
Calculate JCQ demand score.
Hardcode question IDs to be reversed.
4 months ago
30ac8b1cd5
Start calculating demand control features.
4 months ago
9a74e74d08
Add the baseline features rule to snakefile.
Correct age calculation for a single value instead of dataframe.
4 months ago
07da6be398
Add age, gender, and language as features.
Move calculation of age from merge_baseline_data.py to baseline_features.py.
4 months ago
176367631b
Prepare baseline feature rule.
4 months ago
bf9c764c97
Split baseline data to participants.
And some csv I/O settings.
5 months ago
16e608db74
First merge baseline datasets.
5 months ago
204f6f50b0
Read the relevant files.
5 months ago
685ed6a546
Set up demographic data download.
5 months ago
463ac0a2aa
Fix bug#169 ( #174 )
5 months ago
10e896ca1d
Add data stream for AWARE Micro server ( #173 )
* Add data stream for AWARE Micro server
* Fix one documentation typo and one ommission
5 months ago
afa3b8546f
Mutate data in an R script.
The Python script did not read the timestamp correctly for some reason. All timestamps were 0.
5 months ago
e5dbbfce44
Avoid NA problem in barnett location evaluation ( #172 )
* Avoid occasional issue where does_not_span evaluates to NA, which breaks the if()
* Restored original warning
5 months ago
8ae26fb845
Fixes issue where 'duration' in the 'ios_calls' dataframe is seen as a character type. ( #171 )
5 months ago
junos
Meng Li
Sam