Пример #1
0
def main(argv):
    

    heat_d, h2o_d = get_climate_data()
    irrigation_d = get_irrigation_data()    

    the_db.query(queries.starch_query)    
    data = the_db.store_result().fetch_row(how=1, maxrows=0)

    data = [DO.StarchData(d.keys(), d.values()) for d in data]

    golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
                             'sub_id')
    dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
                              'sub_id')
    field_data = [d for d in data if d.location_id in FIELD_TRIALS]

    jki_gh_data = CD1.group_by([d for d in data if d.location_id == 6019],
                               'sub_id')
    jki_sh_data = CD1.group_by([d for d in data if d.location_id == 6020],
                               'sub_id')
    

    jki_gh_results = CD1.compute_starch_rel_ctrl(jki_gh_data, 6019,
                                                 [CD1.DROUGHT_ID])
    jki_sh_results = CD1.compute_starch_rel_ctrl(jki_sh_data, 6020,
                                                 [CD1.DROUGHT_ID])

    golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537, 
                                               [CD1.DROUGHT_ID])
    dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
                                                CD1.DETHLINGEN_DROUGHT_IDS)
    field_results = CD1.compute_starch_rel_field(field_data,
                                                 FIELD_TRIALS, CD1.DROUGHT_ID)


    all_results = [(jki_gh_results, 'JKI_CGW'),
                   (jki_sh_results, 'JKI_SHE'),
                   (golm_results, 'MPI_FIELD'),
                   (dethl_results, 'DET_FIELD'),
                   (field_results, 'ALL_FIELD')]

    """
    compiled = {}
    # compiled.update(golm_results)
    compiled.update(dethl_results)
    # compiled.update(field_results)
    # compiled.update(jki_sh_results)
    # compiled.update(jki_gh_results)
    """
    
    for data, name in all_results:
        print name
        annotate_compiled_data(data, heat_d, h2o_d, irrigation_d)
        WT.write_table(data, WT.FIELDS, 
                       out=open('STARCH_REL_%s.csv' % name, 'w'))

    return None
    
    """
Пример #2
0
def main(argv):
    
    """ 
    Climate data
    """
    
    the_db.query(queries.climate_query)
    climate_data = the_db.store_result().fetch_row(how=1, maxrows=0)
    climate_data = [DO.ClimateData(d.keys(), d.values()) 
                    for d in climate_data]
    heat_d, h2o_d = CD1.compute_climate_data(climate_data)
    # print heat_d
    

    
    # return None
    the_db.query(queries.starch_query)
    data = the_db.store_result().fetch_row(how=1, maxrows=9999999)

    data = [DO.StarchData(d.keys(), d.values()) for d in data]

    golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
                             'sub_id')
    dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
                              'sub_id')
    field_data = [d for d in data if d.location_id in FIELD_TRIALS]
    
    golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537, 
                                               [CD1.DROUGHT_ID])
    dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
                                                CD1.DETHLINGEN_DROUGHT_IDS)
    field_results = CD1.compute_starch_rel_field(field_data,
                                                 FIELD_TRIALS, CD1.DROUGHT_ID)
    # print field_results


    compiled = {}
    # compiled.update(golm_results)
    # compiled.update(dethl_results)
    compiled.update(field_results)
    for k, v in sorted(compiled.items()):
        if isinstance(k, str): continue
        # print k
        compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
        compiled[k].limsloc = k[0]
        compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]
        # print v
    # print heat_d
    
    WT.write_table(compiled, WT.FIELDS)

    return None
    
    """
Пример #3
0
def main(argv):

    heat_d, h2o_d = get_climate_data()
    irrigation_d = get_irrigation_data()

    the_db.query(queries.starch_query)
    data = the_db.store_result().fetch_row(how=1, maxrows=0)

    data = [DO.StarchData(d.keys(), d.values()) for d in data]

    golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
                             'sub_id')
    dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
                              'sub_id')
    field_data = [d for d in data if d.location_id in FIELD_TRIALS]

    jki_gh_data = CD1.group_by([d for d in data if d.location_id == 6019],
                               'sub_id')
    jki_sh_data = CD1.group_by([d for d in data if d.location_id == 6020],
                               'sub_id')

    jki_gh_results = CD1.compute_starch_rel_ctrl(jki_gh_data, 6019,
                                                 [CD1.DROUGHT_ID])
    jki_sh_results = CD1.compute_starch_rel_ctrl(jki_sh_data, 6020,
                                                 [CD1.DROUGHT_ID])

    golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537,
                                               [CD1.DROUGHT_ID])
    dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
                                                CD1.DETHLINGEN_DROUGHT_IDS)
    field_results = CD1.compute_starch_rel_field(field_data, FIELD_TRIALS,
                                                 CD1.DROUGHT_ID)

    all_results = [(jki_gh_results, 'JKI_CGW'), (jki_sh_results, 'JKI_SHE'),
                   (golm_results, 'MPI_FIELD'), (dethl_results, 'DET_FIELD'),
                   (field_results, 'ALL_FIELD')]
    """
    compiled = {}
    # compiled.update(golm_results)
    compiled.update(dethl_results)
    # compiled.update(field_results)
    # compiled.update(jki_sh_results)
    # compiled.update(jki_gh_results)
    """

    for data, name in all_results:
        print name
        annotate_compiled_data(data, heat_d, h2o_d, irrigation_d)
        WT.write_table(data,
                       WT.FIELDS,
                       out=open('STARCH_REL_%s.csv' % name, 'w'))

    return None
    """
Пример #4
0
def main(argv):
    """ 
    Climate data
    """

    the_db.query(queries.climate_query)
    climate_data = the_db.store_result().fetch_row(how=1, maxrows=0)
    climate_data = [DO.ClimateData(d.keys(), d.values()) for d in climate_data]
    heat_d, h2o_d = CD1.compute_climate_data(climate_data)
    # print heat_d

    # return None
    the_db.query(queries.starch_query)
    data = the_db.store_result().fetch_row(how=1, maxrows=9999999)

    data = [DO.StarchData(d.keys(), d.values()) for d in data]

    golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
                             'sub_id')
    dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
                              'sub_id')
    field_data = [d for d in data if d.location_id in FIELD_TRIALS]

    golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537,
                                               [CD1.DROUGHT_ID])
    dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
                                                CD1.DETHLINGEN_DROUGHT_IDS)
    field_results = CD1.compute_starch_rel_field(field_data, FIELD_TRIALS,
                                                 CD1.DROUGHT_ID)
    # print field_results

    compiled = {}
    # compiled.update(golm_results)
    # compiled.update(dethl_results)
    compiled.update(field_results)
    for k, v in sorted(compiled.items()):
        if isinstance(k, str): continue
        # print k
        compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
        compiled[k].limsloc = k[0]
        compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]
        # print v
    # print heat_d

    WT.write_table(compiled, WT.FIELDS)

    return None
    """
Пример #5
0
def main(argv):

    heat_d, h2o_d = CD2.get_climate_data()
    the_db.query(daisy_query)
    data = the_db.store_result().fetch_row(how=1, maxrows=0)
    data = [DO.StarchData(d.keys(), d.values()) for d in data]
    field_data = [d for d in data if d.location_id in CD2.FIELD_TRIALS]
    # print field_data
    field_results = CD1.compute_starch_rel_field(field_data,
                                                 CD2.FIELD_TRIALS, CD1.DROUGHT_ID)
    compiled = {}
    compiled.update(field_results)
    
    for k, v in sorted(compiled.items()):
        if isinstance(k, str): continue
        compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
        compiled[k].limsloc = k[0]
        compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]

    WT.write_table(compiled, WT.FIELDS)
    return None
Пример #6
0
def main(argv):

    heat_d, h2o_d = CD2.get_climate_data()
    the_db.query(daisy_query)
    data = the_db.store_result().fetch_row(how=1, maxrows=0)
    data = [DO.StarchData(d.keys(), d.values()) for d in data]
    field_data = [d for d in data if d.location_id in CD2.FIELD_TRIALS]
    # print field_data
    field_results = CD1.compute_starch_rel_field(field_data, CD2.FIELD_TRIALS,
                                                 CD1.DROUGHT_ID)
    compiled = {}
    compiled.update(field_results)

    for k, v in sorted(compiled.items()):
        if isinstance(k, str): continue
        compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
        compiled[k].limsloc = k[0]
        compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]

    WT.write_table(compiled, WT.FIELDS)
    return None