resistics.time.data module¶
-
class
resistics.time.data.TimeData(sampleFreq: float, startTime: Union[datetime.datetime, str], stopTime: Union[datetime.datetime, str], data, comments: Union[str, List[str]] = [])[source]¶ Bases:
resistics.common.base.ResisticsBaseClass for holding time data
- Attributes
- numSamplesint
The number of samples in the data
- sampleFreqfloat
The sampling frequency
- startTimedatetime.datetime
The time of the first sample
- stopTimedatetime.datetime
The time of the last sample
- chansList[str]
The channels in the data
- numChansint
The number of channels
- dataDict
The time data with channels as keys and arrays as values
- commentsList[str]
Information about the time data as a list of strings
Methods
__init__(kwargs)
Initialise the time data
setData(windowSize, dataSize, sampleFreq, startTime, stopTime, data)
Set data with parameters
getDateArray()
(np.ndarray) A datetime array of the sample times
getComments()
Get a deepcopy of the comments
addComment(comment)
Add a comment to the dataset
copy()
Get a copy of the timeseries data
view(kwargs)
View the time data
printList()
Class status returned as list of strings
-
copy(self)[source]¶ Get a copy of the time data object
- Returns
- TimeData
A copy of the time data object
-
getComments(self) → List[str][source]¶ Get a deepcopy of the comments
- Returns
- List[str]
Dataset comments as a list of strings
-
getDateArray(self) → numpy.ndarray[source]¶ Get the date array
- Returns
- np.ndarray
The date array of the time samples
-
printList(self) → List[str][source]¶ Class information as a list of strings
- Returns
- outList[str]
List of strings with information
-
setData(self, sampleFreq: float, startTime: Union[datetime.datetime, str], stopTime: Union[datetime.datetime, str], data)[source]¶ Set the object parameters
- Parameters
- sampleFreqfloat
The sampling frequency in Hz
- startTimedatetime, str
The startTime of the window
- stopTimedatetime, str
The stopTime of the window
- dataDict
The data dictionary with keys as channels and values as spectra data
-
view(self, **kwargs) → matplotlib.figure.Figure[source]¶ View timeseries data as a line plot
- Parameters
- sampleStartint, optional
Sample to start plotting from
- sampleStopint, optional
Sample to plot to
- figmatplotlib.pyplot.figure, optional
A figure object
- plotfontsDict, optional
A dictionary of plot fonts
- chansList[str]
Channels to plot
- labelstr, optional
Label for the plots
- xlimList, optional
Limits for the x axis
- legenedbool
Boolean flag for adding a legend
- Returns
- plt.figure
Matplotlib figure object