def _handler(self, request, response):
init_process_logger('log.txt')
response.outputs['output_log'].file = 'log.txt'
#
#
# init_process_logger('log.txt')
# self.output_log.setValue('log.txt')
#
response.update_status('Start process', 0)
from flyingpigeon import sdm
try:
LOGGER.info('reading the arguments')
taxon_name = request.inputs['taxon_name'][0].data
bbox = [-180, -90, 180, 90]
# bbox_obj = self.BBox.getValue()
# bbox = [bbox_obj.coords[0][0],
# bbox_obj.coords[0][1],
# bbox_obj.coords[1][0],
# bbox_obj.coords[1][1]]
LOGGER.info("bbox={0}".format(bbox))
LOGGER.info("Taxon Name = %s", taxon_name)
except:
msg = 'failed to read in the arguments.'
LOGGER.exception(msg)
raise Exception(msg)
try:
response.update_status('Fetching GBIF Data', 10)
gbifdic = sdm.get_gbif(taxon_name, bbox=bbox)
except:
msg = 'failed to search gbif.'
LOGGER.exception(msg)
raise Exception(msg)
try:
response.update_status('write csv file', 70)
gbifcsv = sdm.gbifdic2csv(gbifdic)
except:
msg = 'failed to write csv file.'
LOGGER.exception(msg)
raise Exception(msg)
try:
response.update_status('plot map', 80)
from flyingpigeon.visualisation import map_gbifoccurrences
latlon = sdm.latlon_gbifdic(gbifdic)
occurence_map = map_gbifoccurrences(latlon)
except:
msg = 'failed to plot occurence map.'
LOGGER.exception(msg)
raise Exception(msg)
response.outputs['output_map'].file = occurence_map
response.outputs['output_csv'].file = gbifcsv
response.update_status('done', 100)
return response
def _handler(self, request, response):
init_process_logger('log.txt')
response.outputs['output_log'].file = 'log.txt'
response.update_status('Start process', 0)
try:
LOGGER.info('reading the arguments')
resources = archiveextract(
resource=rename_complexinputs(request.inputs['resource']))
taxon_name = request.inputs['taxon_name'][0].data
bbox = [-180, -90, 180, 90]
# bbox_obj = self.BBox.getValue()
# bbox = [bbox_obj.coords[0][0],
# bbox_obj.coords[0][1],
# bbox_obj.coords[1][0],
# bbox_obj.coords[1][1]]
period = request.inputs['period']
period = period[0].data
indices = [inpt.data for inpt in request.inputs['indices']]
archive_format = request.inputs['archive_format'][0].data
LOGGER.exception("indices = %s for %s ", indices, taxon_name)
LOGGER.info("bbox={0}".format(bbox))
except:
LOGGER.exception('failed to read in the arguments')
LOGGER.info('indices %s ' % indices)
try:
response.update_status('Fetching GBIF Data', 10)
gbifdic = sdm.get_gbif(taxon_name, bbox=bbox)
LOGGER.info('Fetched GBIF data')
except:
msg = 'failed to search gbif.'
LOGGER.exception(msg)
raise Exception(msg)
try:
response.update_status('write csv file', 70)
gbifcsv = sdm.gbifdic2csv(gbifdic)
LOGGER.info('GBIF data written to file')
except:
msg = 'failed to write csv file.'
LOGGER.exception(msg)
raise Exception(msg)
try:
response.update_status('plot map', 80)
latlon = sdm.latlon_gbifdic(gbifdic)
occurence_map = map_gbifoccurrences(latlon)
except:
msg = 'failed to plot occurence map.'
LOGGER.exception(msg)
raise Exception(msg)
#################################
# calculate the climate indices
#################################
# get the indices
ncs_indices = None
try:
response.update_status(
'start calculation of climate indices for %s' % indices, 30)
ncs_indices = sdm.get_indices(resource=resources, indices=indices)
LOGGER.info('indice calculation done')
except:
msg = 'failed to calculate indices'
LOGGER.exception(msg)
raise Exception(msg)
try:
# sort indices
indices_dic = sdm.sort_indices(ncs_indices)
LOGGER.info('indice files sorted in dictionary')
except:
msg = 'failed to sort indices'
LOGGER.exception(msg)
indices_dic = {'dummy': []}
ncs_references = []
species_files = []
stat_infos = []
PAmask_pngs = []
response.update_status('Start processing for %s Datasets' %
len(indices_dic.keys()))
for count, key in enumerate(indices_dic.keys()):
try:
staus_nr = 40 + count * 10
response.update_status('Start processing of %s' % key,
staus_nr)
ncs = indices_dic[key]
LOGGER.info('with %s files' % len(ncs))
try:
response.update_status('generating the PA mask', 20)
PAmask = sdm.get_PAmask(coordinates=latlon, nc=ncs[0])
LOGGER.info('PA mask sucessfully generated')
except:
LOGGER.exception('failed to generate the PA mask')
try:
response.update_status('Ploting PA mask', 25)
PAmask_pngs.extend([map_PAmask(PAmask)])
except:
LOGGER.exception('failed to plot the PA mask')
try:
ncs_reference = sdm.get_reference(ncs_indices=ncs,
period=period)
ncs_references.extend(ncs_reference)
LOGGER.info('reference indice calculated %s ' %
ncs_references)
except:
msg = 'failed to calculate the reference'
LOGGER.exception(msg)
try:
gam_model, predict_gam, gam_info = sdm.get_gam(
ncs_reference, PAmask)
stat_infos.append(gam_info)
response.update_status('GAM sucessfully trained',
staus_nr + 5)
except:
msg = 'failed to train GAM for %s' % (key)
LOGGER.exception(msg)
try:
prediction = sdm.get_prediction(gam_model, ncs)
response.update_status('prediction done', staus_nr + 7)
except:
msg = 'failed to predict tree occurence'
LOGGER.exception(msg)
# raise Exception(msg)
# try:
# response.update_status('land sea mask for predicted data', staus_nr + 8)
# from numpy import invert, isnan, nan, broadcast_arrays # , array, zeros, linspace, meshgrid
# mask = invert(isnan(PAmask))
# mask = broadcast_arrays(prediction, mask)[1]
# prediction[mask is False] = nan
# except:
# LOGGER.exception('failed to mask predicted data')
try:
species_files.append(sdm.write_to_file(ncs[0], prediction))
LOGGER.info('Favourabillity written to file')
except:
msg = 'failed to write species file'
LOGGER.exception(msg)
# raise Exception(msg)
except:
msg = 'failed to calculate reference indices'
LOGGER.exception(msg)
raise Exception(msg)
try:
archive_indices = archive(ncs_indices, format=archive_format)
LOGGER.info('indices added to archive')
except:
msg = 'failed adding indices to archive'
LOGGER.exception(msg)
archive_indices = tempfile.mkstemp(suffix='.tar',
prefix='foobar-',
dir='.')
try:
archive_references = archive(ncs_references, format=archive_format)
LOGGER.info('indices reference added to archive')
except:
msg = 'failed adding reference indices to archive'
LOGGER.exception(msg)
archive_references = tempfile.mkstemp(suffix='.tar',
prefix='foobar-',
dir='.')
try:
archive_prediction = archive(species_files, format=archive_format)
LOGGER.info('species_files added to archive')
except:
msg = 'failed adding species_files indices to archive'
LOGGER.exception(msg)
raise Exception(msg)
try:
stat_infosconcat = pdfmerge(stat_infos)
LOGGER.debug('pngs %s' % PAmask_pngs)
PAmask_png = concat_images(PAmask_pngs, orientation='h')
LOGGER.info('stat infos pdfs and mask pngs merged')
except:
LOGGER.exception('failed to concat images')
_, stat_infosconcat = tempfile.mkstemp(suffix='.pdf',
prefix='foobar-',
dir='.')
_, PAmask_png = tempfile.mkstemp(suffix='.png',
prefix='foobar-',
dir='.')
response.outputs['output_gbif'].file = occurence_map
response.outputs['output_PA'].file = PAmask_png
response.outputs['output_indices'].file = archive_indices
response.outputs['output_reference'].file = archive_references
response.outputs['output_prediction'].file = archive_prediction
response.outputs['output_info'].file = stat_infosconcat
response.outputs['output_csv'].file = gbifcsv
response.update_status('done', 100)
return response
def execute(self):
init_process_logger('log.txt')
self.output_log.setValue('log.txt')
from os.path import basename
from flyingpigeon import sdm
from flyingpigeon.utils import archive, archiveextract
self.status.set('Start process', 0)
try:
logger.info('reading the arguments')
resources = archiveextract(
self.getInputValues(identifier='resources'))
taxon_name = self.getInputValues(identifier='taxon_name')[0]
bbox_obj = self.BBox.getValue()
bbox = [
bbox_obj.coords[0][0], bbox_obj.coords[0][1],
bbox_obj.coords[1][0], bbox_obj.coords[1][1]
]
period = self.getInputValues(identifier='period')
period = period[0]
indices = self.getInputValues(identifier='input_indices')
archive_format = self.archive_format.getValue()
logger.debug("indices = %s for %s ", indices, taxon_name)
logger.info("bbox={0}".format(bbox))
except Exception as e:
logger.error('failed to read in the arguments %s ' % e)
logger.info('indices %s ' % indices)
try:
self.status.set('Fetching GBIF Data', 10)
gbifdic = sdm.get_gbif(taxon_name, bbox=bbox)
except Exception as e:
msg = 'failed to search gbif.'
logger.exception(msg)
raise Exception(msg)
try:
self.status.set('write csv file', 70)
gbifcsv = sdm.gbifdic2csv(gbifdic)
except Exception as e:
msg = 'failed to write csv file.'
logger.exception(msg)
raise Exception(msg)
try:
self.status.set('plot map', 80)
from flyingpigeon.visualisation import map_gbifoccurrences
latlon = sdm.latlon_gbifdic(gbifdic)
occurence_map = map_gbifoccurrences(latlon)
except Exception as e:
msg = 'failed to plot occurence map.'
logger.exception(msg)
raise Exception(msg)
#################################
# calculate the climate indices
#################################
# get the indices
ncs_indices = None
try:
self.status.set(
'start calculation of climate indices for %s' % indices, 30)
ncs_indices = sdm.get_indices(resources=resources, indices=indices)
logger.info('indice calculation done')
except:
msg = 'failed to calculate indices'
logger.exception(msg)
raise Exception(msg)
try:
self.status.set('get domain', 30)
domains = set()
for resource in ncs_indices:
# get_domain works only if metadata are set in a correct way
domains = domains.union([basename(resource).split('_')[1]])
if len(domains) == 1:
domain = list(domains)[0]
logger.debug('Domain %s found in indices files' % domain)
else:
logger.error('Not a single domain in indices files %s' %
domains)
except Exception as e:
logger.exception('failed to get domains %s' % e)
try:
self.status.set('generating the PA mask', 20)
PAmask = sdm.get_PAmask(coordinates=latlon, domain=domain)
logger.info('PA mask sucessfully generated')
except Exception as e:
logger.exception('failed to generate the PA mask: %s' % e)
try:
self.status.set('Ploting PA mask', 25)
from flyingpigeon.visualisation import map_PAmask
PAmask_png = map_PAmask(PAmask)
except Exception as e:
logger.exception('failed to plot the PA mask: %s' % e)
try:
# sort indices
indices_dic = None
indices_dic = sdm.sort_indices(ncs_indices)
logger.info('indice files sorted for %s Datasets' %
len(indices_dic.keys()))
except:
msg = 'failed to sort indices'
logger.exception(msg)
raise Exception(msg)
ncs_references = []
species_files = []
stat_infos = []
for count, key in enumerate(indices_dic.keys()):
try:
staus_nr = 40 + count * 10
self.status.set('Start processing of %s' % key, staus_nr)
ncs = indices_dic[key]
logger.info('with %s files' % len(ncs))
try:
ncs_reference = sdm.get_reference(ncs_indices=ncs,
period=period)
ncs_references.extend(ncs_reference)
logger.info('reference indice calculated %s ' %
ncs_references)
except:
msg = 'failed to calculate the reference'
logger.exception(msg)
raise Exception(msg)
try:
gam_model, predict_gam, gam_info = sdm.get_gam(
ncs_reference, PAmask)
stat_infos.append(gam_info)
self.status.set('GAM sucessfully trained', staus_nr + 5)
except Exception as e:
msg = 'failed to train GAM for %s : %s' % (key, e)
logger.debug(msg)
try:
prediction = sdm.get_prediction(gam_model, ncs)
self.status.set('prediction done', staus_nr + 7)
except Exception as e:
msg = 'failed to predict tree occurence %s' % e
logger.exception(msg)
# raise Exception(msg)
try:
self.status.set('land sea mask for predicted data',
staus_nr + 8)
from numpy import invert, isnan, nan, broadcast_arrays # , array, zeros, linspace, meshgrid
mask = invert(isnan(PAmask))
mask = broadcast_arrays(prediction, mask)[1]
prediction[mask is False] = nan
except Exception as e:
logger.debug('failed to mask predicted data: %s' % e)
try:
species_files.append(sdm.write_to_file(ncs[0], prediction))
logger.info('Favourabillity written to file')
except Exception as e:
msg = 'failed to write species file %s' % e
logger.debug(msg)
# raise Exception(msg)
except Exception as e:
msg = 'failed to calculate reference indices. %s ' % e
logger.exception(msg)
raise Exception(msg)
try:
archive_indices = None
archive_indices = archive(ncs_indices, format=archive_format)
logger.info('indices added to archive')
except:
msg = 'failed adding indices to archive'
logger.exception(msg)
raise Exception(msg)
archive_references = None
try:
archive_references = archive(ncs_references, format=archive_format)
logger.info('indices reference added to archive')
except:
msg = 'failed adding reference indices to archive'
logger.exception(msg)
raise Exception(msg)
archive_predicion = None
try:
archive_predicion = archive(species_files, format=archive_format)
logger.info('species_files added to archive')
except:
msg = 'failed adding species_files indices to archive'
logger.exception(msg)
raise Exception(msg)
try:
from flyingpigeon.visualisation import pdfmerge
stat_infosconcat = pdfmerge(stat_infos)
logger.info('stat infos pdfs merged')
except:
logger.exception('failed to concat images')
_, stat_infosconcat = tempfile.mkstemp(suffix='.pdf',
prefix='foobar-',
dir='.')
self.output_csv.setValue(gbifcsv)
self.output_gbif.setValue(occurence_map)
self.output_PA.setValue(PAmask_png)
self.output_indices.setValue(archive_indices)
self.output_reference.setValue(archive_references)
self.output_prediction.setValue(archive_predicion)
self.output_info.setValue(stat_infosconcat)
self.status.set('done', 100)
def execute(self):
init_process_logger('log.txt')
self.output_log.setValue('log.txt')
self.status.set('Start process', 0)
from flyingpigeon import sdm
try:
logger.info('reading the arguments')
taxon_name = self.getInputValues(identifier='taxon_name')[0]
bbox_obj = self.BBox.getValue()
bbox = [
bbox_obj.coords[0][0], bbox_obj.coords[0][1],
bbox_obj.coords[1][0], bbox_obj.coords[1][1]
]
logger.info("bbox={0}".format(bbox))
logger.info("Taxon Name = %s", taxon_name)
except Exception as e:
msg = 'failed to read in the arguments.'
logger.exception(msg)
raise Exception(msg)
try:
self.status.set('Fetching GBIF Data', 10)
gbifdic = sdm.get_gbif(taxon_name, bbox=bbox)
except Exception as e:
msg = 'failed to search gbif.'
logger.exception(msg)
raise Exception(msg)
try:
self.status.set('write csv file', 70)
gbifcsv = sdm.gbifdic2csv(gbifdic)
except Exception as e:
msg = 'failed to write csv file.'
logger.exception(msg)
raise Exception(msg)
try:
self.status.set('plot map', 80)
from flyingpigeon.visualisation import map_gbifoccurrences
latlon = sdm.latlon_gbifdic(gbifdic)
occurence_map = map_gbifoccurrences(latlon)
except Exception as e:
msg = 'failed to plot occurence map.'
logger.exception(msg)
raise Exception(msg)
self.output_map.setValue(occurence_map)
self.output_csv.setValue(gbifcsv)
# write folder statistics:
import shlex
import subprocess
import os
import socket
logger.debug('HOSTNAME: %s ' % socket.gethostname())
cmd = 'stat %s/' % os.path.abspath(os.curdir)
args = shlex.split(cmd)
output, error = subprocess.Popen(args,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE).communicate()
logger.debug('temp folder statistics: %s ERRORS: %s' %
(output, error))
self.status.set('done', 100)