#!/usr/bin/env python2
# -*- coding: utf-8 -*-
############################################################################
#
# MODULE:       t.rast.aggregate
# AUTHOR(S):    Soeren Gebbert
#
# PURPOSE:      Temporally aggregates the maps of a space time raster dataset by a user defined granularity.
# COPYRIGHT:    (C) 2011-2014 by the GRASS Development Team
#
#               This program is free software under the GNU General Public
#               License (version 2). Read the file COPYING that comes with GRASS
#               for details.
#
#############################################################################

#%module
#% description: Aggregates temporally the maps of a space time raster dataset by a user defined granularity.
#% keyword: temporal
#% keyword: aggregation
#% keyword: raster
#% keyword: time
#%end

#%option G_OPT_STRDS_INPUT
#%end

#%option G_OPT_STRDS_OUTPUT
#%end

#%option
#% key: basename
#% type: string
#% label: Basename of the new generated output maps
#% description: Either a numerical suffix or the start time (s-flag) separated by an underscore will be attached to create a unique identifier
#% required: yes
#% multiple: no
#% gisprompt:
#%end

#%option
#% key: suffix
#% type: string
#% description: Suffix to add at basename: set 'gran' for granularity, 'time' for the full time format, 'num' for numerical suffix with a specific number of digits (default %05)
#% answer: gran
#% required: no
#% multiple: no
#%end

#%option
#% key: granularity
#% type: string
#% description: Aggregation granularity, format absolute time "x years, x months, x weeks, x days, x hours, x minutes, x seconds" or an integer value for relative time
#% required: yes
#% multiple: no
#%end

#%option
#% key: method
#% type: string
#% description: Aggregate operation to be performed on the raster maps
#% required: yes
#% multiple: no
#% options: average,count,median,mode,minimum,min_raster,maximum,max_raster,stddev,range,sum,variance,diversity,slope,offset,detcoeff,quart1,quart3,perc90,quantile,skewness,kurtosis
#% answer: average
#%end

#%option
#% key: offset
#% type: integer
#% description: Offset that is used to create the output map ids, output map id is generated as: basename_ (count + offset)
#% required: no
#% multiple: no
#% answer: 0
#%end

#%option
#% key: nprocs
#% type: integer
#% description: Number of r.series processes to run in parallel
#% required: no
#% multiple: no
#% answer: 1
#%end

#%option
#% key: file_limit
#% type: integer
#% description: The maximum number of open files allowed for each r.series process
#% required: no
#% multiple: no
#% answer: 1000
#%end

#%option G_OPT_T_SAMPLE
#% options: equal,overlaps,overlapped,starts,started,finishes,finished,during,contains
#% answer: contains
#%end

#%option G_OPT_T_WHERE
#%end

#%flag
#% key: n
#% description: Register Null maps
#%end

import grass.script as gcore
import grass.temporal as tgis

############################################################################

def main():

    # Get the options
    input = options["input"]
    output = options["output"]
    where = options["where"]
    gran = options["granularity"]
    base = options["basename"]
    register_null = flags["n"]
    method = options["method"]
    sampling = options["sampling"]
    offset = options["offset"]
    nprocs = options["nprocs"]
    file_limit = options["file_limit"]
    time_suffix = options["suffix"]

    topo_list = sampling.split(",")

    tgis.init()

    dbif = tgis.SQLDatabaseInterfaceConnection()
    dbif.connect()

    sp = tgis.open_old_stds(input, "strds", dbif)

    map_list = sp.get_registered_maps_as_objects(where=where, order="start_time", dbif=dbif)

    if not map_list:
        dbif.close()
        gcore.fatal(_("Space time raster dataset <%s> is empty") % input)

    # We will create the strds later, but need to check here
    tgis.check_new_stds(output, "strds",   dbif,  gcore.overwrite())

    start_time = map_list[0].temporal_extent.get_start_time()

    if sp.is_time_absolute():
        start_time = tgis.adjust_datetime_to_granularity(start_time,  gran)

    # We use the end time first
    end_time = map_list[-1].temporal_extent.get_end_time()
    has_end_time = True

    # In case no end time is available, then we use the start time of the last map layer
    if end_time is None:
        end_time = map_list[- 1].temporal_extent.get_start_time()
        has_end_time = False

    granularity_list = []

    # Build the granularity list
    while True:
        if has_end_time is True:
            if start_time >= end_time:
                break
        else:
            if start_time > end_time:
                break

        granule = tgis.RasterDataset(None)
        start = start_time
        if sp.is_time_absolute():
            end = tgis.increment_datetime_by_string(start_time, gran)
            granule.set_absolute_time(start, end)
        else:
            end = start_time + int(gran)
            granule.set_relative_time(start, end,  sp.get_relative_time_unit())
        start_time = end

        granularity_list.append(granule)

    output_list = tgis.aggregate_by_topology(granularity_list=granularity_list,  granularity=gran,
                                                                       map_list=map_list,
                                                                       topo_list=topo_list,  basename=base, time_suffix=time_suffix,
                                                                       offset=offset,  method=method,  nprocs=nprocs,  spatial=None,
                                                                       overwrite=gcore.overwrite(), file_limit=file_limit)

    if output_list:
        temporal_type, semantic_type, title, description = sp.get_initial_values()
        output_strds = tgis.open_new_stds(output, "strds", temporal_type,
                                                                 title, description, semantic_type,
                                                                 dbif, gcore.overwrite())
        if register_null:
            register_null=False
        else:
            register_null=True

        tgis.register_map_object_list("rast", output_list,  output_strds, register_null,
                                                       sp.get_relative_time_unit(),  dbif)

        # Update the raster metadata table entries with aggregation type
        output_strds.set_aggregation_type(method)
        output_strds.metadata.update(dbif)

    dbif.close()

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