ts_conv

satiopst.ts_convR.ts_stackR(imglist,replace_nodata=True)

Stack multi-time image list to stacked NumPy array.

Parameters

imglist : list of image files. image file paths with directory and name.
replace_nodata : True/False, optional convert nodata value to nan if present in the image metadata. The default is True.

Returns

ilist : stacked numpy array of images. Where 3rd dim represent different time.
meta : Updated metadata with new bands.

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satiopst.ts_convR.ts_frameR(imgarray,startD=None,endD=None,freq="D")

Convert time series image array to time series frame. Where band represents Day, Month or Year.

Parameters

imgarray : image as numpy ndarray.
startD : Stating data of the image. In format of 'YYYY-MM-DD','YYYY' or 'DD'. The default is None.
endD : End data of the image. In format of 'YYYY-MM-DD','YYYY' or 'DD'. The default is None.
freq : time frequency. same as pandas timedate, Visit https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases. The default is "D".

Returns

iframe : Dataframe where index represent time and column represent pixels.

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satiopst.ts_convR.ts_arrayR(imgframe,width=None,height=None)

Convert time series image frame to image array

Parameters

imgframe : Stuctured image data. Time series image frame.
width : Width of the image array.
height : Height of the image array.

Returns

imgr : Image as numpy array. bands represent time.