How to use hydrafloods - 10 common examples

def load(self,files,gcsBucket='',eeAsset=''):
        if gcsBucket[-1] != '/':
            gcsBucket += '/'
        if eeAsset[-1] != '/':
            eeAsset += '/'

        for f in files:
            fName = os.path.basename(f)
            utils.push_to_gcs(f,gcsBucket)
            bso = gcsBucket + fName
            tstr = fName.split('.')[3]
            t = '{0}-{1}-{2}:{3}:00'.format(tstr[:4],tstr[4:6],tstr[6:11],tstr[11:])
            utils.push_to_gee(bso,eeAsset,properties={'time_start':t})

        return

def load(self, files, gcsBucket='', eeAsset=''):
        if gcsBucket[-1] != '/':
            gcsBucket += '/'
        if eeAsset[-1] != '/':
            eeAsset += '/'

        for f in files:
            fName = os.path.basename(f)
            utils.push_to_gcs(f, gcsBucket)
            bso = gcsBucket + fName
            tstr = fName.split('.')[3]
            t = '{0}-{1}-{2}:{3}:00'.format(tstr[:4],
                                            tstr[4:6], tstr[6:11], tstr[11:])
            utils.push_to_gee(bso, eeAsset, properties={'time_start': t})

        return

def load(self, files, gcsBucket='', eeAsset=''):
        if gcsBucket[-1] != '/':
            gcsBucket += '/'
        if eeAsset[-1] != '/':
            eeAsset += '/'

        for f in files:
            fName = os.path.basename(f)
            utils.push_to_gcs(f, gcsBucket)
            bso = gcsBucket + fName
            tstr = fName.split('.')[3]
            t = '{0}-{1}-{2}:{3}:00'.format(tstr[:4],
                                            tstr[4:6], tstr[6:11], tstr[11:])
            utils.push_to_gee(bso, eeAsset, properties={'time_start': t})

        return

def load(self,files,gcsBucket='',eeAsset=''):
        if gcsBucket[-1] != '/':
            gcsBucket += '/'
        if eeAsset[-1] != '/':
            eeAsset += '/'

        for f in files:
            fName = os.path.basename(f)
            utils.push_to_gcs(f,gcsBucket)
            bso = gcsBucket + fName
            tstr = fName.split('.')[3]
            t = '{0}-{1}-{2}:{3}:00'.format(tstr[:4],tstr[4:6],tstr[6:11],tstr[11:])
            utils.push_to_gee(bso,eeAsset,properties={'time_start':t})

        return

def applyFilter(img):
        img = geeutils.dbToPower(img)

        # MMSE estimator
        mmseMask = img.gte(a1).Or(img.lte(a2))
        mmseIn = img.updateMask(mmseMask)
        oneImg = ee.Image(1)
        z = mmseIn.reduceNeighborhood(ee.Reducer.mean(), kernel, None, True)
        varz = mmseIn.reduceNeighborhood(ee.Reducer.variance(), kernel)
        varx = (varz.subtract(z.abs().pow(2).multiply(eta))).divide(oneImg.add(eta))
        b = varx.divide(varz)
        mmse = oneImg.subtract(b).multiply(z.abs()).add(b.multiply(mmseIn))

        # workflow
        z99 = ee.Dictionary(img.reduceRegion(
            reducer= ee.Reducer.percentile([99], None, 255, 0.001, 1e6),
            geometry= img.geometry(),
            scale= 10,

i = ee.Number(iteration)
            sim = geeutils.globalOtsu(self.downscaled,target_date,self.region,seed=i,**kwargs)
            return sim.And(hand.lt(30))

        tDate = ee.Date(target_date)

        if probablistic:
            iters = ee.List.sequence(0,nIters-1)

            sims = ee.ImageCollection(iters.map(_threholdWrapper))
            probs = sims.sum().divide(nIters).rename(['probability'])
            water = probs.select(['probability']).gt(probTreshold).rename('water')
            mapResult = water.addBands(probs.multiply(10000).uint16())

        else:
            mapResult = geeutils.globalOtsu(self.downscaled,target_date,self.region,**kwargs)\
                .And(hand.lt(30))

        return mapResult

def _threholdWrapper(iteration):
            i = ee.Number(iteration)
            sim = geeutils.globalOtsu(
                self.downscaled, target_date, self.region, seed=i, **kwargs)
            return sim.And(hand.lt(30))

def __init__(self, *args, assetid='MODIS/006/MOD09GA', **kwargs):
        super(Modis, self).__init__(*args, assetid=assetid, **kwargs)

        if self.useQa:
            self.collection = self.collection.map(self._qa)

        self.collection = self.collection\
            .select(BANDREMAP.get('modis'), BANDREMAP.get('new'))\
            .map(geeutils.addIndices)

        self.clipToRegion(inplace=True)

        return

mmse = oneImg.subtract(b).multiply(z.abs()).add(b.multiply(mmseIn))

        # workflow
        z99 = ee.Dictionary(img.reduceRegion(
            reducer= ee.Reducer.percentile([99], None, 255, 0.001, 1e6),
            geometry= img.geometry(),
            scale= 10,
            bestEffort= True
        )).toImage()

        overThresh = img.gte(z99)

        K = overThresh.reduceNeighborhood(ee.Reducer.sum(), targetKernel, None, True)

        retainPixel = K.gte(Tk)
        xHat = geeutils.powerToDb(img.updateMask(retainPixel).unmask(mmse))

        return ee.Image(xHat).rename(bandNames)

def __init__(self,*args,**kwargs):
        super(Modis, self).__init__(*args,**kwargs)

        self.collection = self.collection.map(self._qaMask)\
            .select(BANDREMAP.get('modis'),BANDREMAP.get('new'))\
            .map(self.clip)\
            .map(geeutils.addIndices)

        return