Sleep analysis

Find lengths of bouts of sleep

# break down a specimens sleep into bout duration and type

bout_df = df.sleep_bout_analysis()

output:
                               duration  asleep         t
id
2019-08-02_14-21-23_021d6b|01      60.0    True   86400.0
2019-08-02_14-21-23_021d6b|01     900.0   False   86460.0
...                                 ...     ...       ...
2020-08-07_12-23-10_172d50|05     240.0    True  430980.0
2020-08-07_12-23-10_172d50|05     120.0   False  431760.0
2020-08-07_12-23-10_172d50|05      60.0    True  431880.0

# have the data returned in a format ready to be made into a histogram
hist_df = df.sleep_bout_analysis(as_hist = True, max_bins = 30, bin_size = 1, time_immobile = 5, asleep = True)

output:
                               bins  count      prob
id
2019-08-02_14-21-23_021d6b|01    60      0  0.000000
2019-08-02_14-21-23_021d6b|01   120    179  0.400447
2019-08-02_14-21-23_021d6b|01   180     92  0.205817
...                             ...    ...       ...
2020-08-07_12-23-10_172d50|05  1620      1  0.002427
2020-08-07_12-23-10_172d50|05  1680      0  0.000000
2020-08-07_12-23-10_172d50|05  1740      0  0.000000

# max bins is the largest bout you want to include
# bin_size is the what length runs together, i.e. 5 would find all bouts between factors of 5 minutes
# time_immobile is the time in minutes sleep was defined as prior. This removes anything that is small than this as produced by error previously.
# if alseep is True (the default) the return data frame will be for asleep bouts, change to False for one for awake bouts

Plotting a histogram of sleep_bout_analysis

# You can take the output from above and create your own histograms, or you can use this handy method to plot a historgram with error bars from across your specimens
# Like all functions you can facet by your metadata
# Here we'll compare two of the species and group the bouts into periods of 5 minutes, with up to 12 of them (1 hour)

df.plot_sleep_bouts(
sleep_column = 'asleep',
facet_col = 'species',
facet_arg = ['D.vir', 'D.ere'],
facet_labels = ['D.virilis', 'D.erecta'],
bin_size = 5, 
max_bins = 12
)

Bouts of slep in a histogram

Find bouts of sleep

# If you haven't already analysed the dataset to find periods of sleep, but you do have a column containing the movement as True/False. Call this method to find contiguous bouts of sleep according to a minimum length

new_df = df.sleep_contiguous(time_window_length = 60, min_time_immobile = 300)   

Sleep download functions as methods

# some of the download functions mentioned previously can be called as methods if the data wasn't previously analysed
# dont't call this method if your data was already analysed! If it's already analysed it will be missing columns needed for this metho
   
new_df = df.motion_detector(time_window_length = 60)