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7 Commits

Author SHA1 Message Date
junos e5cc02501f Set the timezone.csv path in config.
Take into account that TZCODES_FILE can be created with a rule.
2021-12-15 18:09:30 +01:00
junos 352598f3da Use absolute path to avoid RuleException. 2021-12-15 17:27:13 +01:00
junos 15653b6e70 Add forgotten line for hashed app names in config. 2021-12-15 17:26:54 +01:00
junos a66a7d0cc3 Keep track of warning messages.
These are not runtime errors, but might still indicate a problem.
2021-12-15 16:19:29 +01:00
junos 70cada8bb8 Consider a subset of columns when dropping. 2021-12-15 16:14:33 +01:00
junos d2ed73dccf Debug ValueError for index.
See exploration/debug_heatmap.py for illustration.
2021-12-15 16:03:04 +01:00
junos 6f451e05ac Bring back application_name.
This column still needs to be in the data, so add it in app_add_name.py.
Later, join categories by package hash.
2021-12-15 12:58:27 +01:00
11 changed files with 73 additions and 7 deletions

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@ -31,6 +31,7 @@ TIMEZONE:
SINGLE: SINGLE:
TZCODE: Europe/Ljubljana TZCODE: Europe/Ljubljana
MULTIPLE: MULTIPLE:
TZ_FILE: data/external/timezone.csv
TZCODES_FILE: data/external/multiple_timezones.csv TZCODES_FILE: data/external/multiple_timezones.csv
IF_MISSING_TZCODE: USE_DEFAULT IF_MISSING_TZCODE: USE_DEFAULT
DEFAULT_TZCODE: Europe/Ljubljana DEFAULT_TZCODE: Europe/Ljubljana
@ -110,6 +111,7 @@ PHONE_APPLICATIONS_FOREGROUND:
APPLICATION_CATEGORIES: APPLICATION_CATEGORIES:
CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store) CATALOGUE_SOURCE: FILE # FILE (genres are read from CATALOGUE_FILE) or GOOGLE (genres are scrapped from the Play Store)
CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv" CATALOGUE_FILE: "data/external/stachl_application_genre_catalogue.csv"
PACKAGE_NAMES_HASHED: True
UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE UPDATE_CATALOGUE_FILE: False # if CATALOGUE_SOURCE is equal to FILE, whether or not to update CATALOGUE_FILE, if CATALOGUE_SOURCE is equal to GOOGLE all scraped genres will be saved to CATALOGUE_FILE
SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway SCRAPE_MISSING_CATEGORIES: False # whether or not to scrape missing genres, only effective if CATALOGUE_SOURCE is equal to FILE. If CATALOGUE_SOURCE is equal to GOOGLE, all genres are scraped anyway
PROVIDERS: PROVIDERS:

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@ -0,0 +1,33 @@
Warning: 1241 parsing failures.
row col expected actual file
1 is_system_app an integer TRUE 'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
2 is_system_app an integer FALSE 'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
3 is_system_app an integer TRUE 'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
4 is_system_app an integer TRUE 'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
5 is_system_app an integer TRUE 'data/raw/p011/phone_applications_foreground_with_datetime_with_categories.csv'
... ............. .......... ...... ...............................................................................
See problems(...) for more details.
Warning message:
The following named parsers don't match the column names: application_name
Error: Problem with `filter()` input `..1`.
✖ object 'application_name' not found
Input `..1` is `!is.na(application_name)`.
Backtrace:
1. ├─`%>%`(...)
2. ├─dplyr::mutate(...)
3. ├─utils::head(., -1)
4. ├─dplyr::select(., -c("timestamp"))
5. ├─dplyr::filter(., !is.na(application_name))
6. ├─dplyr:::filter.data.frame(., !is.na(application_name))
7. │ └─dplyr:::filter_rows(.data, ...)
8. │ ├─base::withCallingHandlers(...)
9. │ └─mask$eval_all_filter(dots, env_filter)
10. └─base::.handleSimpleError(...)
11. └─dplyr:::h(simpleError(msg, call))
Execution halted
[Mon Dec 13 17:19:06 2021]
Error in rule app_episodes:
jobid: 54
output: data/interim/p011/phone_app_episodes.csv

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@ -0,0 +1,5 @@
Warning message:
In barnett_daily_features(snakemake) :
Barnett's location features cannot be computed for data or time segments that do not span one or more entire days (00:00:00 to 23:59:59). Values below point to the problem:
Location data rows within a daily time segment: 0
Location data time span in days: 398.6

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@ -114,7 +114,16 @@ def input_tzcodes_file(wilcards):
if not config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"].lower().endswith(".csv"): if not config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"].lower().endswith(".csv"):
raise ValueError("[TIMEZONE][MULTIPLE][TZCODES_FILE] should point to a CSV file, instead you typed: " + config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]) raise ValueError("[TIMEZONE][MULTIPLE][TZCODES_FILE] should point to a CSV file, instead you typed: " + config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"])
if not Path(config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]).exists(): if not Path(config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]).exists():
raise ValueError("[TIMEZONE][MULTIPLE][TZCODES_FILE] should point to a CSV file, the file in the path you typed does not exist: " + config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]) try:
config["TIMEZONE"]["MULTIPLE"]["TZ_FILE"]
except KeyError:
raise ValueError("To create TZCODES_FILE, a list of timezones should be created " +
"with the rule preprocessing.smk/prepare_tzcodes_file " +
"which will create a file specified as config['TIMEZONE']['MULTIPLE']['TZ_FILE']." +
"\n An alternative is to provide the file manually:" +
"[TIMEZONE][MULTIPLE][TZCODES_FILE] should point to a CSV file," +
"but the file in the path you typed does not exist: " +
config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"])
return [config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]] return [config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]]
return [] return []

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@ -9,13 +9,13 @@ rule query_usernames_device_empatica_ids:
baseline_folder = "/mnt/e/STRAWbaseline/" baseline_folder = "/mnt/e/STRAWbaseline/"
output: output:
usernames_file = config["CREATE_PARTICIPANT_FILES"]["USERNAMES_CSV"], usernames_file = config["CREATE_PARTICIPANT_FILES"]["USERNAMES_CSV"],
timezone_file = "data/external/timezone.csv" timezone_file = config["TIMEZONE"]["MULTIPLE"]["TZ_FILE"]
script: script:
"../../participants/prepare_usernames_file.py" "../../participants/prepare_usernames_file.py"
rule prepare_tzcodes_file: rule prepare_tzcodes_file:
input: input:
timezone_file = "data/external/timezone.csv" timezone_file = config["TIMEZONE"]["MULTIPLE"]["TZ_FILE"]
output: output:
tzcodes_file = config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"] tzcodes_file = config["TIMEZONE"]["MULTIPLE"]["TZCODES_FILE"]
script: script:

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@ -29,6 +29,7 @@ get_genre <- function(apps){
apps <- read.csv(snakemake@input[[1]], stringsAsFactors = F) apps <- read.csv(snakemake@input[[1]], stringsAsFactors = F)
genre_catalogue <- data.frame() genre_catalogue <- data.frame()
catalogue_source <- snakemake@params[["catalogue_source"]] catalogue_source <- snakemake@params[["catalogue_source"]]
package_names_hashed <- snakemake@params[["package_names_hashed"]]
update_catalogue_file <- snakemake@params[["update_catalogue_file"]] update_catalogue_file <- snakemake@params[["update_catalogue_file"]]
scrape_missing_genres <- snakemake@params[["scrape_missing_genres"]] scrape_missing_genres <- snakemake@params[["scrape_missing_genres"]]
apps_with_genre <- data.frame(matrix(ncol=length(colnames(apps)) + 1,nrow=0, dimnames=list(NULL, c(colnames(apps), "genre")))) apps_with_genre <- data.frame(matrix(ncol=length(colnames(apps)) + 1,nrow=0, dimnames=list(NULL, c(colnames(apps), "genre"))))
@ -38,7 +39,11 @@ if(nrow(apps) > 0){
apps_with_genre <- apps %>% mutate(genre = NA_character_) apps_with_genre <- apps %>% mutate(genre = NA_character_)
} else if(catalogue_source == "FILE"){ } else if(catalogue_source == "FILE"){
genre_catalogue <- read.csv(snakemake@params[["catalogue_file"]], colClasses = c("character", "character")) genre_catalogue <- read.csv(snakemake@params[["catalogue_file"]], colClasses = c("character", "character"))
apps_with_genre <- left_join(apps, genre_catalogue, by = "package_name") if (package_names_hashed) {
apps_with_genre <- left_join(apps, genre_catalogue, by = "package_hash")
} else {
apps_with_genre <- left_join(apps, genre_catalogue, by = "package_name")
}
} }
if(catalogue_source == "GOOGLE" || (catalogue_source == "FILE" && scrape_missing_genres)){ if(catalogue_source == "GOOGLE" || (catalogue_source == "FILE" && scrape_missing_genres)){

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@ -67,10 +67,12 @@ PHONE_APPLICATIONS_FOREGROUND:
TIMESTAMP: timestamp TIMESTAMP: timestamp
DEVICE_ID: device_id DEVICE_ID: device_id
PACKAGE_NAME: package_hash PACKAGE_NAME: package_hash
APPLICATION_NAME: FLAG_TO_MUTATE
IS_SYSTEM_APP: is_system_app IS_SYSTEM_APP: is_system_app
MUTATION: MUTATION:
COLUMN_MAPPINGS: COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data SCRIPTS:
- src/data/streams/mutations/phone/straw/app_add_name.py
PHONE_APPLICATIONS_NOTIFICATIONS: PHONE_APPLICATIONS_NOTIFICATIONS:
ANDROID: ANDROID:
@ -78,11 +80,13 @@ PHONE_APPLICATIONS_NOTIFICATIONS:
TIMESTAMP: timestamp TIMESTAMP: timestamp
DEVICE_ID: device_id DEVICE_ID: device_id
PACKAGE_NAME: package_hash PACKAGE_NAME: package_hash
APPLICATION_NAME: FLAG_TO_MUTATE
SOUND: sound SOUND: sound
VIBRATE: vibrate VIBRATE: vibrate
MUTATION: MUTATION:
COLUMN_MAPPINGS: COLUMN_MAPPINGS:
SCRIPTS: # List any python or r scripts that mutate your raw data SCRIPTS:
- src/data/streams/mutations/phone/straw/app_add_name.py
PHONE_BATTERY: PHONE_BATTERY:
ANDROID: ANDROID:

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@ -0,0 +1,5 @@
import pandas as pd
def main(data, stream_parameters):
data["application_name"] = "hashed"
return(data)

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@ -27,12 +27,14 @@ PHONE_APPLICATIONS_FOREGROUND:
- TIMESTAMP - TIMESTAMP
- DEVICE_ID - DEVICE_ID
- PACKAGE_NAME - PACKAGE_NAME
- APPLICATION_NAME
- IS_SYSTEM_APP - IS_SYSTEM_APP
PHONE_APPLICATIONS_NOTIFICATIONS: PHONE_APPLICATIONS_NOTIFICATIONS:
- TIMESTAMP - TIMESTAMP
- DEVICE_ID - DEVICE_ID
- PACKAGE_NAME - PACKAGE_NAME
- APPLICATION_NAME
- SOUND - SOUND
- VIBRATE - VIBRATE

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@ -38,6 +38,7 @@ def getDataForPlot(phone_data_yield_per_segment):
for columns in columns_for_full_index: for columns in columns_for_full_index:
full_index = full_index + columns full_index = full_index + columns
full_index = pd.MultiIndex.from_tuples(full_index, names=("local_segment_start_datetimes", "minutes_after_segment_start")) full_index = pd.MultiIndex.from_tuples(full_index, names=("local_segment_start_datetimes", "minutes_after_segment_start"))
phone_data_yield_per_segment = phone_data_yield_per_segment.drop_duplicates(subset=["local_segment_start_datetimes", "minutes_after_segment_start"], keep="first")
phone_data_yield_per_segment = phone_data_yield_per_segment.set_index(["local_segment_start_datetimes", "minutes_after_segment_start"]).reindex(full_index).reset_index().fillna(0) phone_data_yield_per_segment = phone_data_yield_per_segment.set_index(["local_segment_start_datetimes", "minutes_after_segment_start"]).reindex(full_index).reset_index().fillna(0)
# transpose the dataframe per local start datetime of the segment and discard the useless index layer # transpose the dataframe per local start datetime of the segment and discard the useless index layer

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@ -22,7 +22,7 @@ output:
</style> </style>
```{r include=FALSE} ```{r include=FALSE}
source("renv/activate.R") source("/mnt/c/Users/junos/Documents/FWO-ARRS/Analysis/straw2analysis/rapids/renv/activate.R")
``` ```