Updated WIFI testing, bugfix and docs
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Manage virtual environments
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====================
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=============================
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**Add new packages**
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@ -7,7 +7,7 @@ Along with the continued development and the addition of new sensors and feature
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List of Sensor with Tests
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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The following is a list of the sesors that testing is currently available.
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The following is a list of the sensors that testing is currently available.
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Messages (SMS)
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@ -50,43 +50,45 @@ Battery
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Due to the difference in the format of the raw battery data for iOS and Android as well as versions of iOS (see the **Assumptions/Observations** section of :ref:`Battery<battery-sensor-doc>`) the following is the expected results the ``battery_deltas.csv``. This would give a better idea of the use cases being tested since the ``battery_deltas.csv`` would make both the iOS and Android data comparable. These files are used to calculate the features for the battery sensor.
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- The battery delta data file contains data for 1 day.
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- The battery delta data contains 1 record each for a ``charging`` and ``discharging`` episode that falls within an ``epoch`` for every ``epoch``. Thus for the ``daily`` epoch there would be multiple ``charging`` and ``discharging`` episodes
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- Since either a ``charging`` episode or a ``discharging`` episode and not both can occur across epochs, in order to test epsiodes that occur across epochs alternating episodes of ``charging`` and ``discharging`` episodes that fall across ``night`` to ``morning``, ``morning`` to ``afternoon`` and finally ``afternoon`` to ``night`` are present in the battery delta data. This starts with a ``discharging`` episode that begins in ``night`` and end in ``morning``.
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- The battery delta data contains 1 record each for a ``charging`` and ``discharging`` episode that falls within an ``epoch`` for every ``epoch``. Thus, for the ``daily`` epoch there would be multiple ``charging`` and ``discharging`` episodes
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- Since either a ``charging`` episode or a ``discharging`` episode and not both can occur across epochs, in order to test episodes that occur across epochs alternating episodes of ``charging`` and ``discharging`` episodes that fall across ``night`` to ``morning``, ``morning`` to ``afternoon`` and finally ``afternoon`` to ``night`` are present in the battery delta data. This starts with a ``discharging`` episode that begins in ``night`` and end in ``morning``.
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- There is one battery data file each, for testing both iOS and Android data formats.
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- There is also an additional empty data file for both android and iOS for testing empty data files
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Bluetooth
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""""""""""
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- The raw bluetooth data file contains data for 1 day.
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- The raw bluetooth data contains at least 2 records for each ``epoch``. Each ``epoch`` has a record with a ``timestamp`` for the beginning boundary for that ``epoch`` and a record with a ``timestamp`` for the ending boundary for that ``epoch``. (e.g. For the ``morning`` epoch there is a record with a ``timestamp`` for ``6:00AM`` and another record with a ``timestamp`` for ``11:59:59AM``. These are to test edge cases)
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- An option of 5 bluetooth devices are randomly distributed throughout the data records.
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- There is one raw bluetooth data file each, for testing both iOS and Android data formats.
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- The raw Bluetooth data file contains data for 1 day.
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- The raw Bluetooth data contains at least 2 records for each ``epoch``. Each ``epoch`` has a record with a ``timestamp`` for the beginning boundary for that ``epoch`` and a record with a ``timestamp`` for the ending boundary for that ``epoch``. (e.g. For the ``morning`` epoch there is a record with a ``timestamp`` for ``6:00AM`` and another record with a ``timestamp`` for ``11:59:59AM``. These are to test edge cases)
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- An option of 5 Bluetooth devices are randomly distributed throughout the data records.
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- There is one raw Bluetooth data file each, for testing both iOS and Android data formats.
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- There is also an additional empty data file for both android and iOS for testing empty data files.
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WIFI
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"""""
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- The raw WIFI data file contains data for 1 day.
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- The raw WIFI data contains at least 2 records for each ``epoch``. Each ``epoch`` has a record with a ``timestamp`` for the beginning boundary for that ``epoch`` and a record with a ``timestamp`` for the ending boundary for that ``epoch``. (e.g. For the ``morning`` epoch there is a record with a ``timestamp`` for ``6:00AM`` and another record with a ``timestamp`` for ``11:59:59AM``. These are to test edge cases)
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- An option of 5 access point devices is randomly distributed throughout the data records.
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- There is one raw WIFI data file each, for testing both iOS and Android data formats.
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- There is also an additional empty data file for both android and iOS for testing empty data files.
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- There are 2 data files (``wifi_raw.csv`` and ``sensor_wifi_raw.csv``) for each fake participant for each phone platform. (see the **Assumptions/Observations** section of :ref:`WIFI<wifi-sensor-doc>`)
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- The raw WIFI data files contain data for 1 day.
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- The ``sensor_wifi_raw.csv`` data contains at least 2 records for each ``epoch``. Each ``epoch`` has a record with a ``timestamp`` for the beginning boundary for that ``epoch`` and a record with a ``timestamp`` for the ending boundary for that ``epoch``. (e.g. For the ``morning`` epoch there is a record with a ``timestamp`` for ``6:00AM`` and another record with a ``timestamp`` for ``11:59:59AM``. These are to test edge cases)
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- The ``wifi_raw.csv`` data contains 3 records with random timestamps for each ``epoch`` to represent visible broadcasting WIFI network. This file is empty for the iOS phone testing data.
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- An option of 10 access point devices is randomly distributed throughout the data records. 5 each for ``sensor_wifi_raw.csv`` and ``wifi_raw.csv``.
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- There data files for testing both iOS and Android data formats.
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- There are also additional empty data files for both android and iOS for testing empty data files.
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Light
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"""""""
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- The raw light data file contains data for 1 day.
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- The raw light data contains 3 or 4 rows of data for each ``epoch`` except ``night``. The single row of data for ``night`` is for testing features for single values inputs. (Example testing the standard deviation of one input value)
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- Since light is only available for Android there is only one file that constains data for Android. All other files (i.e. for iPhone) are empty data files.
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- Since light is only available for Android there is only one file that contains data for Android. All other files (i.e. for iPhone) are empty data files.
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Application Foreground
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"""""""""""""""""""""""
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- The raw application foreground data file contains data for 1 day.
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- The raw application foreground data contains 7 - 9 rows of data for each ``epoch``. The records for each ``epoch`` contains apps that are randomly selected from a list of apps that are from the ``MULTIPLE_CATEGORIES`` and ``SINGLE_CATEGORIES`` (See `test_config.yaml`_). There are also records in each epoch that have apps randomly selected from a list of apps that are from the ``EXCLUDED_CATEGORIES`` and ``EXCLUDED_APPS``. This is to test that these apps are actually being excluded from the calculations of features. There are also records to test ``SINGLE_APPS`` calculations.
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- Since application foreground is only available for Android there is only one file that constains data for Android. All other files (i.e. for iPhone) are empty data files.
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- The raw application foreground data contains 7 - 9 rows of data for each ``epoch``. The records for each ``epoch`` contains apps that are randomly selected from a list of apps that are from the ``MULTIPLE_CATEGORIES`` and ``SINGLE_CATEGORIES`` (See `testing_config.yaml`_). There are also records in each epoch that have apps randomly selected from a list of apps that are from the ``EXCLUDED_CATEGORIES`` and ``EXCLUDED_APPS``. This is to test that these apps are actually being excluded from the calculations of features. There are also records to test ``SINGLE_APPS`` calculations.
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- Since application foreground is only available for Android there is only one file that contains data for Android. All other files (i.e. for iPhone) are empty data files.
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.. _`test_config.yaml`: TBD
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.. _`testing_config.yaml`: https://github.com/carissalow/rapids/blob/c498b8d2dfd7cc29d1e4d53e978d30cff6cdf3f2/tests/settings/testing_config.yaml#L70
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@ -287,7 +287,8 @@ uniquedevices devices Number of unique access point during
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countscansmostuniquedevice scans Number of scans of the most scanned access point during a ``day_segment`` across the whole monitoring period
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=========================== ========= =============
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**Assumptions/Observations:** N/A
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**Assumptions/Observations:**
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Both phone platforms record the wifi networks a phone is connected to in ``sensor_wifi`` and those networks that are being broadcasted around a phone in ``wifi``. However, iOS cannot record any broadcasting network due to API restrictions, therefore iOS wifi data only exists in ``sensor_wifi``.
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.. _accelerometer-sensor-doc:
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@ -655,7 +656,7 @@ See `Location (Doryab's) Config Code`_
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- Rule ``rules/preprocessing.snakefile/resample_fused_location`` (only relevant if setting ``location_to_use`` to ````RESAMPLE_FUSED``.
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- Rule ``rules/features.snakefile/location_doryab_features``
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.. _location-parameters:
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.. _location-doryab-parameters:
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**Location Rule Parameters (location_doryab_features):**
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@ -672,7 +673,7 @@ maximum_gap_allowed The maximum gap (in seconds) allowed between any two cons
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minutes_data_used This is NOT a feature. This is just a quality control check, and if set to TRUE, a new column is added to the output file with the number of minutes containing location data that were used to compute all features. The more data minutes exist for a period, the more reliable its features should be. For fused location, a single minute can contain more than one coordinate pair if the participant is moving fast enough.
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=================== ===================
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.. _location-available-features:
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.. _location-doryab-available-features:
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**Available Location Features**
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@ -682,7 +683,7 @@ Name Units Description
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locationvariance :math:`meters^2` The sum of the variances of the latitude and longitude columns.
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loglocationvariance Log of the sum of the variances of the latitude and longitude columns.
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totaldistance meters Total distance travelled in a ``day_segment`` using the haversine formula.
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averagespeed km/hr Average speed in a ``day_segment` considering only the instances labeled as Moving.
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averagespeed km/hr Average speed in a ``day_segment`` considering only the instances labeled as Moving.
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varspeed km/hr Speed variance in a ``day_segment`` considering only the instances labeled as Moving.
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circadianmovement "It encodes the extent to which a person’s location patterns follow a 24-hour circadian cycle." (Doryab et. al. 2019)
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numberofsignificantplaces places Number of significant locations visited. It is calculated using the DBSCAN clustering algorithm which takes in EPS and MIN_SAMPLES as paramters to identify clusters. Each cluster is a significant place.
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@ -10,6 +10,7 @@ if(!is.null(snakemake@input[["visible_access_points"]]) && is.null(snakemake@inp
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wifi_data <- wifi_data %>% mutate(connected = 1)
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} else if(!is.null(snakemake@input[["visible_access_points"]]) && !is.null(snakemake@input[["connected_access_points"]])){
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visible_access_points <- read.csv(snakemake@input[["visible_access_points"]], stringsAsFactors = FALSE)
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visible_access_points <- visible_access_points %>% mutate(connected = 0)
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connected_access_points <- read.csv(snakemake@input[["connected_access_points"]], stringsAsFactors = FALSE)
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connected_access_points <- connected_access_points %>% mutate(connected = 1)
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wifi_data <- bind_rows(visible_access_points, connected_access_points) %>% arrange(timestamp)
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@ -23,10 +23,13 @@ if config["CALLS"]["COMPUTE"]:
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files_to_compute.extend(expand("data/processed/{pid}/calls_{call_type}_{segment}.csv", pid=config["PIDS"], call_type=config["CALLS"]["TYPES"], segment = config["CALLS"]["DAY_SEGMENTS"]))
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if config["SCREEN"]["COMPUTE"]:
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if config["SCREEN"]["DB_TABLE"] not in config["PHONE_VALID_SENSED_BINS"]["TABLES"]:
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if config["SCREEN"]["DB_TABLE"] in config["PHONE_VALID_SENSED_BINS"]["TABLES"]:
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files_to_compute.extend(expand("data/interim/{pid}/phone_sensed_bins.csv", pid=config["PIDS"]))
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else:
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raise ValueError("Error: Add your screen table (and as many sensor tables as you have) to [PHONE_VALID_SENSED_BINS][TABLES] in config.yaml. This is necessary to compute phone_sensed_bins (bins of time when the smartphone was sensing data)")
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["SCREEN"]["DB_TABLE"]))
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["SCREEN"]["DB_TABLE"]))
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime_unified.csv", pid=config["PIDS"], sensor=config["SCREEN"]["DB_TABLE"]))
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files_to_compute.extend(expand("data/processed/{pid}/screen_deltas.csv", pid=config["PIDS"]))
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files_to_compute.extend(expand("data/processed/{pid}/screen_{day_segment}.csv", pid = config["PIDS"], day_segment = config["SCREEN"]["DAY_SEGMENTS"]))
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@ -43,8 +46,14 @@ if config["BLUETOOTH"]["COMPUTE"]:
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files_to_compute.extend(expand("data/processed/{pid}/bluetooth_{segment}.csv", pid=config["PIDS"], segment = config["BLUETOOTH"]["DAY_SEGMENTS"]))
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if config["WIFI"]["COMPUTE"]:
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["WIFI"]["DB_TABLE"]))
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["WIFI"]["DB_TABLE"]))
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if len(config["WIFI"]["DB_TABLE"]["VISIBLE_ACCESS_POINTS"]) > 0:
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["WIFI"]["DB_TABLE"]["VISIBLE_ACCESS_POINTS"]))
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["WIFI"]["DB_TABLE"]["VISIBLE_ACCESS_POINTS"]))
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files_to_compute.extend(expand("data/processed/{pid}/wifi_{day_segment}.csv", pid = config["PIDS"], day_segment = config["WIFI"]["DAY_SEGMENTS"]))
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if len(config["WIFI"]["DB_TABLE"]["CONNECTED_ACCESS_POINTS"]) > 0:
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["WIFI"]["DB_TABLE"]["CONNECTED_ACCESS_POINTS"]))
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files_to_compute.extend(expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["WIFI"]["DB_TABLE"]["CONNECTED_ACCESS_POINTS"]))
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files_to_compute.extend(expand("data/processed/{pid}/wifi_{day_segment}.csv", pid = config["PIDS"], day_segment = config["WIFI"]["DAY_SEGMENTS"]))
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if config["LIGHT"]["COMPUTE"]:
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@ -1,2 +1,2 @@
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"local_date","wifi_afternoon_countscans","wifi_afternoon_uniquedevices","wifi_afternoon_countscansmostuniquedevice"
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"2020-07-03",2,2,1
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"2020-07-03",4,4,1
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@ -1,2 +1,2 @@
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"local_date","wifi_daily_countscans","wifi_daily_uniquedevices","wifi_daily_countscansmostuniquedevice"
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"2020-07-03",14,5,6
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"2020-07-03",26,10,6
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@ -1,2 +1,2 @@
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"local_date","wifi_evening_countscans","wifi_evening_uniquedevices","wifi_evening_countscansmostuniquedevice"
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"2020-07-03",3,3,1
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"2020-07-03",7,6,2
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@ -1,2 +1,2 @@
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"local_date","wifi_morning_countscans","wifi_morning_uniquedevices","wifi_morning_countscansmostuniquedevice"
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"2020-07-03",4,3,2
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"2020-07-03",7,5,2
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@ -1,2 +1,2 @@
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"local_date","wifi_night_countscans","wifi_night_uniquedevices","wifi_night_countscansmostuniquedevice"
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"2020-07-03",5,4,2
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"2020-07-03",8,6,2
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@ -0,0 +1,13 @@
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timestamp,device_id,mac_address,ssid,bssid
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1593771645547,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,HOME-1234,E0:A9:8A:1E:48:1B
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1593791393289,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,HOME-1234,E0:A9:8A:1E:48:1B
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1593779101251,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,Stewart Family,0D:FB:75:AA:43:0A
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1593813989898,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,NETGEAR07,EF:E7:56:4A:F4:1D
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1593799538019,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,Fios-H4S9a,48:6B:8C:51:08:F2
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1593797221589,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,HOME-1234,E0:A9:8A:1E:48:1B
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1593820668588,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,Stewart Family,0D:FB:75:AA:43:0A
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1593831618372,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,Fios-H4S9a,48:6B:8C:51:08:F2
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1593821661830,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,NETGEAR07,EF:E7:56:4A:F4:1D
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1593768441273,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,NETGEAR07,EF:E7:56:4A:F4:1D
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1593764562099,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,Galactica,E6:4C:9A:3F:D0:1B
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1593765323772,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,NETGEAR07,EF:E7:56:4A:F4:1D
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@ -0,0 +1,15 @@
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timestamp,device_id,mac_address,ssid,bssid
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1593770400547,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,xfinity,E6:06:DA:AF:F9:91
|
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1593791999289,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,xfinity,E6:06:DA:AF:F9:91
|
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1593774038251,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,CMU-SECURE,D0:B8:2F:EB:0E:F8
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1593792000898,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,,3D:12:EC:DE:96:E1
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1593813599019,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,eduroam,24:2B:A2:55:8A:E0
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1593813600589,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,xfinity,E6:06:DA:AF:F9:91
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1593835199588,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,CMU-SECURE,D0:B8:2F:EB:0E:F8
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1593825019372,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,eduroam,24:2B:A2:55:8A:E0
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1593833925830,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,,3D:12:EC:DE:96:E1
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1593819918273,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,,3D:12:EC:DE:96:E1
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1593748800099,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,WIRELESS-PITTNET,86:90:7B:8A:3E:43
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1593770399772,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,,3D:12:EC:DE:96:E1
|
||||
1593761699709,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,eduroam,24:2B:A2:55:8A:E0
|
||||
1593751744305,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,af:13:50:8b:5f:ab,CMU-SECURE,D0:B8:2F:EB:0E:F8
|
||||
|
|
|
@ -1,15 +1 @@
|
|||
timestamp,device_id,bssid,ssid,security,frequency,rssi,label
|
||||
1593770400547,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,E6:06:DA:AF:F9:91,xfinity,,0,0,
|
||||
1593791999289,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,E6:06:DA:AF:F9:91,xfinity,,0,0,
|
||||
1593774038251,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,D0:B8:2F:EB:0E:F8,CMU-SECURE,,0,0,
|
||||
1593792000898,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,3D:12:EC:DE:96:E1,,,0,0,
|
||||
1593813599019,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,24:2B:A2:55:8A:E0,eduroam,,0,0,
|
||||
1593813600589,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,E6:06:DA:AF:F9:91,xfinity,,0,0,
|
||||
1593835199588,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,D0:B8:2F:EB:0E:F8,CMU-SECURE,,0,0,
|
||||
1593825019372,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,24:2B:A2:55:8A:E0,eduroam,,0,0,
|
||||
1593833925830,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,3D:12:EC:DE:96:E1,,,0,0,
|
||||
1593819918273,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,3D:12:EC:DE:96:E1,,,0,0,
|
||||
1593748800099,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,86:90:7B:8A:3E:43,WIRELESS-PITTNET,,0,0,
|
||||
1593770399772,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,3D:12:EC:DE:96:E1,,,0,0,
|
||||
1593761699709,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,24:2B:A2:55:8A:E0,eduroam,,0,0,
|
||||
1593751744305,7yKzcQm4-xKTC-0bhC-PZXC-3jAbRIXOsf5w,D0:B8:2F:EB:0E:F8,CMU-SECURE,,0,0,
|
||||
|
|
|
@ -0,0 +1 @@
|
|||
timestamp,device_id,mac_address,ssid,bssid
|
||||
|
|
|
@ -0,0 +1 @@
|
|||
timestamp,device_id,mac_address,ssid,bssid
|
||||
|
|
|
@ -100,23 +100,23 @@ def generate_sensor_file_lists(config):
|
|||
if 'TYPES' in config[sensor]:
|
||||
for each in config[sensor]['TYPES']:
|
||||
sensor_type.append(each+'_')
|
||||
|
||||
lower_sensor = sensor.lower()
|
||||
if sensor_type:
|
||||
act_file_list = expand(act_str, pid=config["PIDS"],
|
||||
sensor = config[sensor]["DB_TABLE"],
|
||||
sensor = lower_sensor,
|
||||
sensor_type = sensor_type,
|
||||
day_segment = config[sensor]["DAY_SEGMENTS"])
|
||||
exp_file_list = expand(exp_str, pid=config["PIDS"],
|
||||
sensor = config[sensor]["DB_TABLE"],
|
||||
sensor = lower_sensor,
|
||||
sensor_type = sensor_type,
|
||||
day_segment = config[sensor]["DAY_SEGMENTS"])
|
||||
else:
|
||||
act_file_list = expand(act_str, pid=config["PIDS"],
|
||||
sensor = config[sensor]["DB_TABLE"],
|
||||
sensor = lower_sensor,
|
||||
sensor_type = '',
|
||||
day_segment = config[sensor]["DAY_SEGMENTS"])
|
||||
exp_file_list = expand(exp_str, pid=config["PIDS"],
|
||||
sensor = config[sensor]["DB_TABLE"],
|
||||
sensor = lower_sensor,
|
||||
sensor_type = '',
|
||||
day_segment = config[sensor]["DAY_SEGMENTS"])
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue