pip install esploco-
Download a demo dataset from https://drive.google.com/drive/folders/1v-0Y_xNaec4OhzOqzwE8L2Wng8Cn-\_vq?usp=share_link
-
Import libraries
# from esploco import esploco
# from espresso import espressoHint: to see the function signature of any function or method, type function?
# esploco.esploco?# esplocoPath='D:\\xusy\mb113'
# e = espresso(esplocoPath, expt_duration_minutes=120)
# ele = esploco.esploco(esplocoPath, 0, 120, companionEspObj = e)C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\pandas\core\arrays\categorical.py:2631: FutureWarning: The `inplace` parameter in pandas.Categorical.remove_unused_categories is deprecated and will be removed in a future version.
res = method(*args, **kwargs)
countLog files found:
['CountLog_2019-07-09_15-19-37.csv' 'CountLog_2020-03-09_11-49-38.csv'
'CountLog_2020-03-17_14-35-58.csv' 'CountLog_2020-06-26_13-13-58.csv'
'CountLog_2021-06-25_17-56-21.csv' 'CountLog_2021-07-13_16-18-05.csv'
'CountLog_2021-07-15_15-12-44.csv' 'CountLog_2021-07-16_15-18-24.csv']
metaData files found:
['MetaData_2019-07-09_15-19-37.csv' 'MetaData_2019-07-09_15-19-39.csv'
'MetaData_2020-03-09_11-49-38.csv' 'MetaData_2020-03-09_11-49-41.csv'
'MetaData_2020-03-17_14-35-58.csv' 'MetaData_2020-03-17_14-36-00.csv'
'MetaData_2020-06-26_13-13-58.csv' 'MetaData_2020-06-26_13-14-00.csv'
'MetaData_2021-06-25_17-56-21.csv' 'MetaData_2021-06-25_17-56-24.csv'
'MetaData_2021-07-13_16-18-05.csv' 'MetaData_2021-07-13_16-18-08.csv'
'MetaData_2021-07-15_15-12-44.csv' 'MetaData_2021-07-15_15-12-46.csv'
'MetaData_2021-07-16_15-18-24.csv' 'MetaData_2021-07-16_15-18-26.csv']
portLocations files found:
['PortLocations_2019-07-09_15-19-39.csv'
'PortLocations_2020-03-09_11-49-41.csv'
'PortLocations_2020-03-17_14-36-00.csv'
'PortLocations_2020-06-26_13-14-00.csv'
'PortLocations_2021-06-25_17-56-24.csv'
'PortLocations_2021-07-13_16-18-08.csv'
'PortLocations_2021-07-15_15-12-46.csv'
'PortLocations_2021-07-16_15-18-26.csv']
feedLog files found:
['FeedLog_2019-07-09_15-19-39.csv' 'FeedLog_2020-03-09_11-49-41.csv'
'FeedLog_2020-03-17_14-36-00.csv' 'FeedLog_2020-06-26_13-14-00.csv'
'FeedLog_2021-06-25_17-56-24.csv' 'FeedLog_2021-07-13_16-18-08.csv'
'FeedLog_2021-07-15_15-12-46.csv' 'FeedLog_2021-07-16_15-18-26.csv']
CountLog_2019-07-09_15-19-37.csv
MetaData_2019-07-09_15-19-37.csv
CountLog_2020-03-09_11-49-38.csv
MetaData_2020-03-09_11-49-38.csv
CountLog_2020-03-17_14-35-58.csv
MetaData_2020-03-17_14-35-58.csv
CountLog_2020-06-26_13-13-58.csv
MetaData_2020-06-26_13-13-58.csv
CountLog_2021-06-25_17-56-21.csv
MetaData_2021-06-25_17-56-21.csv
CountLog_2021-07-13_16-18-05.csv
MetaData_2021-07-13_16-18-05.csv
MetaData is missing IDs [16 26]
CountLog_2021-07-15_15-12-44.csv
MetaData_2021-07-15_15-12-44.csv
MetaData is missing IDs [22 27]
CountLog_2021-07-16_15-18-24.csv
MetaData_2021-07-16_15-18-24.csv
# ele.calculatePeriFeedSpeed(e, monitorWindow=120)recalculating feed duration for feeds...
[----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------]
C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\esploco\esploco.py:361: FutureWarning: Dropping invalid columns in DataFrameGroupBy.mean is deprecated. In a future version, a TypeError will be raised. Before calling .mean, select only columns which should be valid for the function.
self.feedsRevisedDf, self.countLogDf, self.meanPeriSpeed, self.maxSpeed= locoDataMunger.calculatePeriFeedLoco(
C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\esploco\locoDataMunger.py:361: FutureWarning: Dropping invalid columns in DataFrameGroupBy.add is deprecated. In a future version, a TypeError will be raised. Before calling .add, select only columns which should be valid for the function.
total_df = grouped_df.sum(numeric_only=False)
putting feeds back into countlog...
[----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------]
plotting PeriFeedDiagonal
plotting pairedSpeedPlots
dabest version = 0.3.9999
C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\dabest\_classes.py:1855: UserWarning: The lower limit of the interval was in the bottom 10 values. The result should be considered unstable.
warnings.warn(err_temp.substitute(lim_type="lower",
# ele.calculateFallEvents()Detecting Fall Events...
[--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------]
Done
# ele.resultsDf.columnsIndex(['ChamberID', 'Starved hrs', 'MealSizePerFly_µL',
'AverageFeedSpeedPerFly_µl/s', 'startMonitorIdx', 'startFeedIdx',
'startFeedIdxRevised', 'endFeedIdx', 'endFeedIdxRevised',
'endMonitorIdx', 'MeanSpeed120sBeforeFeed_mm/s',
'MeanSpeedDuringFeed_mm/s', 'MeanSpeed120sAfterFeed_mm/s',
'MeanMealDurationPerFly_s', 'AviFile', 'ExperimentState', 'Tube1',
'AverageFeedVolumePerFly_µl', 'AverageFeedCountPerFly',
'AverageFeedDurationPerFly_min', 'FeedVol_pl', 'Latency_min',
'duringBeforeSpeedRatio', 'afterBeforeSpeedRatio', 'ID', 'Status',
'Genotype', 'Sex', 'MinimumAge', 'MaximumAge', 'Food1', 'Food2',
'Temperature', '#Flies', 'Starvedhrs', 'Date', 'averageSpeed_mm/s',
'xPosition_mm', 'yPosition_mm', 'inLeftPort', 'inRightPort',
'countLogDate', 'feedLogDate', 'falls'],
dtype='object')
# Fstacked, feeds_sorted, colorBy = ele.plotStacked(endMin = 120,
# colorBy = ['Status', 'Temperature'],
# metricsToStack = ['Volume', 'Speed'],
# figsize = None,
# plotNonFeeders=False,
# showRasterYticks=True,
# ylimPresets = None)
#consult the function signature for different configurations of input argumentsC:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\esploco\esploco.py:541: UserWarning: FixedFormatter should only be used together with FixedLocator
axbig.set_yticklabels(s, fontsize = 5)
# ele.plotChamberSmallMultiples()Espresso Runs found:
['2019-07-09_15-19-37' '2020-03-09_11-49-38' '2020-03-17_14-35-58'
'2020-06-26_13-13-58' '2021-06-25_17-56-21' '2021-07-13_16-18-05'
'2021-07-15_15-12-44' '2021-07-16_15-18-24']
plotting 2019-07-09_15-19-37...
plotting 2020-03-09_11-49-38...
plotting 2020-03-17_14-35-58...
plotting 2020-06-26_13-13-58...
plotting 2021-06-25_17-56-21...
plotting 2021-07-13_16-18-05...
plotting 2021-07-15_15-12-44...
plotting 2021-07-16_15-18-24...
(array([<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>], dtype=object),
array([<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>,
<Figure size 720x144 with 30 Axes>], dtype=object))
# ele.plotMeanHeatMaps(row = 'Genotype', col = 'Temperature')<Figure size 360x2764.8 with 0 Axes>
# ele.plotBoundedLines(col = 'Temperature', colorBy = 'Status')(<Figure size 432x216 with 2 Axes>,
array([[<AxesSubplot:title={'center':' Red Light Off'}, ylabel='Average Speed (mm/s)'>,
<AxesSubplot:title={'center':' Red Light On'}>]], dtype=object),
[<matplotlib.lines.Line2D>,
<matplotlib.lines.Line2D>,
<matplotlib.lines.Line2D>,
<matplotlib.lines.Line2D>],
[<matplotlib.collections.PolyCollection>,
<matplotlib.collections.PolyCollection>,
<matplotlib.collections.PolyCollection>,
<matplotlib.collections.PolyCollection>])
‘ChamberID’, ‘Starved hrs’, ‘MealSizePerFly_µL’, ‘AverageFeedSpeedPerFly_µl/s’, ‘startMonitorIdx’, ‘startFeedIdx’, ‘startFeedIdxRevised’, ‘endFeedIdx’, ‘endFeedIdxRevised’, ‘endMonitorIdx’, ‘MeanSpeed120sBeforeFeed_mm/s’, ‘MeanSpeedDuringFeed_mm/s’, ‘MeanSpeed120sAfterFeed_mm/s’, ‘MeanMealDurationPerFly_s’, ‘AviFile’, ‘ExperimentState’, ‘Tube1’, ‘AverageFeedVolumePerFly_µl’, ‘AverageFeedCountPerFly’, ‘AverageFeedDuration_min’, ‘FeedVol_pl’, ‘Latency_min’, ‘duringBeforeSpeedRatio’, ‘afterBeforeSpeedRatio’, ‘ID’, ‘Status’, ‘Genotype’, ‘Sex’, ‘MinimumAge’, ‘MaximumAge’, ‘Food1’, ‘Food2’, ‘Temperature’, ‘#Flies’, ‘Starvedhrs’, ‘Date’, ‘averageSpeed_mm/s’, ‘xPosition_mm’, ‘yPosition_mm’, ‘inLeftPort’, ‘inRightPort’, ‘countLogDate’, ‘feedLogDate’
# import dabest
# print(dabest.__version__)
# contrast = dabest.load(data = ele.resultsDf,
# x = ['Temperature', 'Genotype'],
# y = 'MealSizePerFly_µL',
# experiment = 'Status', x1_level=['Red Light Off', 'Red Light On'] , delta2 = True)
# f = contrast.mean_diff.plot()
# f.axes[0].set_xticklabels(['Ctrl Off', 'Ctrl On', 'Test Off', 'Test On'])
# f.axes[1].set_xticklabels(['', 'Ctrl Δ', '', 'Test Δ', '', 'ΔΔ'])0.3.9999
C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\seaborn\categorical.py:1296: UserWarning: 22.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
warnings.warn(msg, UserWarning)
C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\seaborn\categorical.py:1296: UserWarning: 30.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
warnings.warn(msg, UserWarning)
[Text(0, 0, ''),
Text(1, 0, 'Ctrl Δ'),
Text(2, 0, ''),
Text(3, 0, 'Test Δ'),
Text(4, 0, ''),
Text(5, 0, 'ΔΔ')]
C:\Users\xusy\.conda\envs\nbdevdabestdev\lib\site-packages\IPython\core\pylabtools.py:151: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
fig.canvas.print_figure(bytes_io, **kw)
# ele.resultsDf.columnsIndex(['ChamberID', 'Starved hrs', 'MealSizePerFly_µL',
'AverageFeedSpeedPerFly_µl/s', 'startMonitorIdx', 'startFeedIdx',
'startFeedIdxRevised', 'endFeedIdx', 'endFeedIdxRevised',
'endMonitorIdx', 'MeanSpeed120sBeforeFeed_mm/s',
'MeanSpeedDuringFeed_mm/s', 'MeanSpeed120sAfterFeed_mm/s',
'MeanMealDurationPerFly_s', 'AviFile', 'ExperimentState', 'Tube1',
'AverageFeedVolumePerFly_µl', 'AverageFeedCountPerFly',
'AverageFeedDurationPerFly_min', 'FeedVol_pl', 'Latency_min',
'duringBeforeSpeedRatio', 'afterBeforeSpeedRatio', 'ID', 'Status',
'Genotype', 'Sex', 'MinimumAge', 'MaximumAge', 'Food1', 'Food2',
'Temperature', '#Flies', 'Starvedhrs', 'Date', 'averageSpeed_mm/s',
'xPosition_mm', 'yPosition_mm', 'inLeftPort', 'inRightPort',
'countLogDate', 'feedLogDate', 'falls'],
dtype='object')