Unit 25 - Spatio-temporal parallelization

This unit is focused on improving script created in Unit 24 - Spatio-temporal scripting by processing Sentinel scenes in parallel. The paralelization is done by ParallelModuleQueue, see line 217 similarly to Unit 17 - DTM script parallelization.

New feature of PyGRASS library is introduced on line 146. By MultiModule you can define list of modules which will work as isolated units not influenced by other processes running parallel. By setting set_temp_region the computation region settings will be not influenced by other processes running in parallel.

New script option ncproc on line 43 enables controlling number of processes running in parallel.

#!/usr/bin/env python
#
##############################################################################
#
# MODULE:       ndvi-tgrass-v2
#
# AUTHOR(S):    martin
#
# PURPOSE:      NDVI TGRASS version 2
#
# DATE:         Sat Feb  3 15:45:35 2018
#
##############################################################################

#%module
#% description: NDVI TGRASS script version 2
#%end                
#%option G_OPT_STRDS_INPUT
#% key: b4
#% description: Name of the input 4th band space time raster dataset
#%end
#%option G_OPT_STRDS_INPUT
#% key: b8
#% description: Name of the input 4th band space time raster dataset
#%end
#%option G_OPT_STRDS_INPUT
#% key: mask
#% description: Name of the input mask space time raster dataset
#%end
#%option G_OPT_F_OUTPUT
#%end
#%option
#% key: basename
#% description: Basename for output raster maps
#% required: yes
#%end
#%option
#% key: threshold
#% description: Threshold for removing small areas
#% answer: 1600
#%end
#%option
#% key: nprocs
#% description: Number of processes
#% answer: 1
#% type: integer
#%end

import sys
import os
import atexit

from grass.pygrass.modules import Module, MultiModule, ParallelModuleQueue
from grass.script import parser
from grass.script.vector import vector_db_select
    
def cleanup(idx):
    Module('g.remove', flags='f', name='mask' + idx, type='raster')
    Module('g.remove', flags='f', name='ndvi' + idx, type='raster')
    Module('g.remove', flags='f', name='ndvi_class' + idx, type='raster')
    Module('g.remove', flags='f', name='ndvi_class' + idx, type='vector')

def compute(b4, b8, msk, output, idx):

    modules = []
    modules.append(
        Module("g.region",
               overwrite = True,
               vector = msk,
               align = b4,
               run_ = False)
    )
    modules.append(
        Module("v.to.rast",
               overwrite = True,
               input = msk,
               output = 'mask' + idx,
               type = 'area',
               use = 'val',
               value='1',
               run_ = False)
    )
    modules.append(
        Module("r.mapcalc",
               overwrite = True,
               expression = "ndvi{idx} = if(isnull({clouds}), null(), float({b8} - {b4}) / ({b8} + {b4}))".format(
                   idx=idx, clouds=msk, b8=b8, b4=b4),
               run_ = False)
    )
                
    recode_str="""-1:0.1:1
0.1:0.5:2
0.5:1:3"""

    modules.append(
        Module("r.recode",
               overwrite = True,
               input = "ndvi" + idx,
               output = "ndvi_class" + idx,
               rules = "-",
               stdin_ = recode_str,
               run_ = False)
    )
    
    colors_str="""1 grey
2 255 255 0
3 green"""
    modules.append(
        Module("r.colors",
               map = "ndvi_class" + idx,
               rules = "-",
               stdin_ = colors_str,
               run_ = False)
    )

    modules.append(
        Module("r.to.vect",
               flags = 'sv',
               overwrite = True,
               input = "ndvi_class" + idx,
               output = "ndvi_class" + idx,
               type = "area",
               run_ = False)
    )

    modules.append(
        Module("v.clean",
               overwrite = True,
               input = "ndvi_class" + idx,
               output = output,
               tool = "rmarea",
               threshold = options['threshold'],
               run_ = False)
    )

    modules.append(
        Module('v.rast.stats',
               flags='c',
               map=output,
               raster='ndvi'+idx,
               column_prefix='ndvi',
               method=['minimum','maximum','average'],
               run_ = False)
    )

    queue.put(MultiModule(modules, sync=False, set_temp_region=True))

def stats(output, date, fd):
    fd.write('-' * 80)
    fd.write(os.linesep)
    fd.write('NDVI class statistics ({0}: {1})'.format(output, date))
    fd.write(os.linesep)
    fd.write('-' * 80)
    fd.write(os.linesep)
    from subprocess import PIPE
    ret = Module('v.report', map=output, option='area',
                 stdout_=PIPE)
    for line in ret.outputs.stdout.splitlines()[1:]: # skip first line (cat|label|area)
        # parse line (eg. 1||2712850)
        data = line.split('|')
        cat = data[0]
        area = float(data[-1])
        fd.write('NDVI class {0}: {1:.1f} ha'.format(cat, area/1e4))
        fd.write(os.linesep)

    data = vector_db_select(output)
    for vals in data['values'].itervalues():
        # unfortunately we need to cast values by float
        fd.write('NDVI class {0}: {1:.4f} (min) {2:.4f} (max) {3:.4f} (mean)'.format(
            vals[0], float(vals[2]), float(vals[3]), float(vals[4])))
        fd.write(os.linesep)
        
def main():
    import grass.temporal as tgis

    tgis.init()

    sp4 = tgis.open_old_stds(options['b4'], 'raster')
    sp8 = tgis.open_old_stds(options['b8'], 'raster')
    msk = tgis.open_old_stds(options['mask'], 'raster')

    idx = 1
    data = []
    for item in sp4.get_registered_maps(columns='name,start_time'):
        b4 = item[0]
        date=item[1]
        b8 = sp8.get_registered_maps(columns='name',
                                     where="start_time = '{}'".format(date))[0][0]
        ms = msk.get_registered_maps(columns='name',
                                     where="start_time = '{}'".format(date))[0][0]
        output = '{}_{}'.format(options['basename'], idx)
        compute(b4, b8, ms, output, str(idx))

        data.append(
            (output, date)
        )
            
        idx += 1

    queue.wait()

    idx = 1
    fd = open(options['output'], 'w')
    for output, date in data:
        stats(output, date, fd)
        cleanup(str(idx))
        idx += 1

    fd.close()
    
    return 0

if __name__ == "__main__":
    options, flags = parser()

    # queue for parallel jobs
    queue = ParallelModuleQueue(int(options['nprocs']))

    sys.exit(main())

Sample script to download: ndvi-tgrass-v2.py