Unit 23 - ST script tuning

Let’s improve script created in Unit 22 - ST scripting by processing Sentinel scenes in parallel. The paralelization is done by ParallelModuleQueue, see line 237 similarly to Unit 19 - Lidar scripting.

New feature of PyGRASS library is introduced on line 166. By MultiModule you can define list of modules which will work as separated units not influenced by other processes running parallel. By set_temp_region we ensure that computation region settings will not influenced by other processes running in parallel.

New script option ncproc on line 48 enables controlling number of processes running in parallel.

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#!/usr/bin/env python
#
##############################################################################
#
# MODULE:       ndvi-tgrass-v1
#
# 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_V_INPUT
#% key: region
#% description: Name of input vector region map 
#% answer: jena_boundary@PERMANENT
#%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: clouds
#% description: Name of the input clouds 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='region_mask' + idx, type='vector')
    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, cl, output, idx):

    modules = []
    if cl:
        region_mask = "region_mask" + idx
        modules.append(
            Module("v.overlay",
                   overwrite = True,
                   ainput = options["region"],
                   binput = cl,
                   operator = "not",
                   output = region_mask,
                   run_ = False)
        )
    else:
        region_mask = options["region"]

    modules.append(
        Module("g.region",
               overwrite = True,
               vector = region_mask,
               align = b4,
               run_ = False)
    )
    modules.append(
        Module("v.to.rast",
               overwrite = True,
               input = region_mask,
               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=cl, 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')
    spc = tgis.open_old_stds(options['clouds'], '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]
        cl = spc.get_registered_maps(columns='name',
                                     where="start_time = '{}'".format(date))[0][0]
        output = '{}_{}'.format(options['basename'], idx)
        compute(b4, b8, cl, 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