def test_coverage_recovery(self):
# Create the coverage
dp_id, stream_id, route, stream_def_id, dataset_id = self.load_data_product()
self.populate_dataset(dataset_id, 36)
dset = self.dataset_management.read_dataset(dataset_id)
dprod = self.dpsc_cli.read_data_product(dp_id)
cov = DatasetManagementService._get_simplex_coverage(dataset_id)
cov_pth = cov.persistence_dir
cov.close()
# Analyze the valid coverage
dr = CoverageDoctor(cov_pth, dprod, dset)
dr_result = dr.analyze()
# Get original values (mock)
orig_cov = AbstractCoverage.load(cov_pth)
time_vals_orig = orig_cov.get_time_values()
# TODO: Destroy the metadata files
# TODO: RE-analyze coverage
# TODO: Should be corrupt, take action to repair if so
# Repair the metadata files
dr.repair_metadata()
# TODO: Re-analyze fixed coverage
fixed_cov = AbstractCoverage.load(cov_pth)
self.assertIsInstance(fixed_cov, AbstractCoverage)
time_vals_fixed = fixed_cov.get_time_values()
self.assertTrue(np.array_equiv(time_vals_orig, time_vals_fixed))
def test_coverage_recovery(self):
# Create the coverage
dp_id, stream_id, route, stream_def_id, dataset_id = self.load_data_product()
self.populate_dataset(dataset_id, 36)
dset = self.dataset_management.read_dataset(dataset_id)
dprod = self.dpsc_cli.read_data_product(dp_id)
cov = DatasetManagementService._get_simplex_coverage(dataset_id)
cov_pth = cov.persistence_dir
cov.close()
# Analyze the valid coverage
dr = CoverageDoctor(cov_pth, dprod, dset)
dr_result = dr.analyze()
# TODO: Turn these into meaningful Asserts
self.assertEqual(len(dr_result.get_brick_corruptions()), 0)
self.assertEqual(len(dr_result.get_brick_size_ratios()), 8)
self.assertEqual(len(dr_result.get_corruptions()), 0)
self.assertEqual(len(dr_result.get_master_corruption()), 0)
self.assertEqual(len(dr_result.get_param_corruptions()), 0)
self.assertEqual(len(dr_result.get_param_size_ratios()), 64)
self.assertEqual(len(dr_result.get_master_size_ratio()), 1)
self.assertEqual(len(dr_result.get_size_ratios()), 73)
self.assertEqual(dr_result.master_status[1], 'NORMAL')
self.assertFalse(dr_result.is_corrupt)
self.assertEqual(dr_result.param_file_count, 64)
self.assertEqual(dr_result.brick_file_count, 8)
self.assertEqual(dr_result.total_file_count, 73)
# Get original values (mock)
orig_cov = AbstractCoverage.load(cov_pth)
time_vals_orig = orig_cov.get_time_values()
orig_cov.close()
# Corrupt the Master File
fo = open(cov._persistence_layer.master_manager.file_path, "wb")
fo.write('Junk')
fo.close()
# Corrupt the lon Parameter file
fo = open(cov._persistence_layer.parameter_metadata['lon'].file_path, "wb")
fo.write('Junk')
fo.close()
corrupt_res = dr.analyze(reanalyze=True)
self.assertTrue(corrupt_res.is_corrupt)
# Repair the metadata files
dr.repair(reanalyze=True)
fixed_res = dr.analyze(reanalyze=True)
self.assertFalse(fixed_res.is_corrupt)
fixed_cov = AbstractCoverage.load(cov_pth)
self.assertIsInstance(fixed_cov, AbstractCoverage)
time_vals_fixed = fixed_cov.get_time_values()
fixed_cov.close()
self.assertTrue(np.array_equiv(time_vals_orig, time_vals_fixed))
def _splice_coverage(cls, dataset_id, scov):
file_root = FileSystem.get_url(FS.CACHE,'datasets')
vcov = cls._get_coverage(dataset_id,mode='a')
scov_pth = scov.persistence_dir
if isinstance(vcov.reference_coverage, SimplexCoverage):
ccov = ComplexCoverage(file_root, uuid4().hex, 'Complex coverage for %s' % dataset_id,
reference_coverage_locs=[vcov.head_coverage_path,],
parameter_dictionary=ParameterDictionary(),
complex_type=ComplexCoverageType.TEMPORAL_AGGREGATION)
log.info('Creating Complex Coverage: %s', ccov.persistence_dir)
ccov.append_reference_coverage(scov_pth)
ccov_pth = ccov.persistence_dir
ccov.close()
vcov.replace_reference_coverage(ccov_pth)
elif isinstance(vcov.reference_coverage, ComplexCoverage):
log.info('Appending simplex coverage to complex coverage')
#vcov.reference_coverage.append_reference_coverage(scov_pth)
dir_path = vcov.reference_coverage.persistence_dir
vcov.close()
ccov = AbstractCoverage.load(dir_path, mode='a')
ccov.append_reference_coverage(scov_pth)
ccov.refresh()
ccov.close()
vcov.refresh()
vcov.close()
def _splice_coverage(cls, dataset_id, scov):
file_root = FileSystem.get_url(FS.CACHE, 'datasets')
vcov = cls._get_coverage(dataset_id, mode='a')
scov_pth = scov.persistence_dir
if isinstance(vcov.reference_coverage, SimplexCoverage):
ccov = ComplexCoverage(
file_root,
uuid4().hex,
'Complex coverage for %s' % dataset_id,
reference_coverage_locs=[
vcov.head_coverage_path,
],
parameter_dictionary=ParameterDictionary(),
complex_type=ComplexCoverageType.TEMPORAL_AGGREGATION)
log.info('Creating Complex Coverage: %s', ccov.persistence_dir)
ccov.append_reference_coverage(scov_pth)
ccov_pth = ccov.persistence_dir
ccov.close()
vcov.replace_reference_coverage(ccov_pth)
elif isinstance(vcov.reference_coverage, ComplexCoverage):
log.info('Appending simplex coverage to complex coverage')
#vcov.reference_coverage.append_reference_coverage(scov_pth)
dir_path = vcov.reference_coverage.persistence_dir
vcov.close()
ccov = AbstractCoverage.load(dir_path, mode='a')
ccov.append_reference_coverage(scov_pth)
ccov.refresh()
ccov.close()
vcov.refresh()
vcov.close()
def _get_nonview_coverage(cls, dataset_id, mode='r'):
cov = cls._get_coverage(dataset_id, mode)
if isinstance(cov, ViewCoverage):
rcov = cov.reference_coverage
pdir = rcov.persistence_dir
rcov = None
cov.close()
cov = AbstractCoverage.load(pdir, mode=mode)
return cov
def _get_nonview_coverage(cls, dataset_id, mode='r'):
cov = cls._get_coverage(dataset_id, mode)
if isinstance(cov, ViewCoverage):
rcov = cov.reference_coverage
pdir = rcov.persistence_dir
rcov = None
cov.close()
cov = AbstractCoverage.load(pdir, mode=mode)
return cov
def fill_temporal_gap(self, dataset_id, gap_coverage_path=None, gap_coverage_id=None):
if gap_coverage_path is None and gap_coverage_id is None:
raise ValueError('Must specify either \'gap_coverage_path\' or \'gap_coverage_id\'')
if gap_coverage_path is None:
gap_coverage_path = self.get_coverage_path(gap_coverage_id)
from coverage_model import AbstractCoverage
gap_cov = AbstractCoverage.load(gap_coverage_path)
self.pause_ingestion(self.get_stream_id(dataset_id))
DatasetManagementService._splice_coverage(dataset_id, gap_cov)
def _get_coverage(cls, dataset_id, mode='w'):
file_root = FileSystem.get_url(FS.CACHE, 'datasets')
coverage = AbstractCoverage.load(file_root, dataset_id, mode=mode)
return coverage
def get_dataset_xml(self,
coverage_path,
product_id,
product_name='',
available_fields=None):
#http://coastwatch.pfeg.noaa.gov/erddap/download/setupDatasetsXml.html
result = ''
paths = os.path.split(coverage_path)
cov = AbstractCoverage.load(coverage_path)
doc = xml.dom.minidom.Document()
#erd_type_map = {'d':'double', 'f':"float", 'h':'short', 'i':'int', 'l':'int', 'q':'int', 'b':'byte', 'b':'char', 'S':'String'}
#Get lists of variables with unique sets of dimensions.
#Datasets can only have variables with the same sets of dimensions
if not cov.list_parameters():
raise BadRequest(
'Attempting to register an empty dataset. The coverage (%s) has no definition.\n%s'
% (coverage_path, cov))
datasets = {}
for key in cov.list_parameters():
pc = cov.get_parameter_context(key)
#if getattr(pc, 'visible', None):
# continue
if available_fields and pc.name not in available_fields:
continue
#if not isinstance(pc.param_type, QuantityType):
# continue
param = cov.get_parameter(key)
dims = (cov.temporal_parameter_name, )
if len(param.shape) == 2:
dims = (cov.temporal_parameter_name,
cov.spatial_domain.shape.name)
if not dims in datasets.keys():
datasets[dims] = []
datasets[dims].append(key)
index = 0
if not datasets:
raise BadRequest(
'Attempting to register a dimensionless dataset. The coverage (%s) has no dimension(s).\n%s'
% (coverage_path, cov))
for dims, vars in datasets.iteritems():
erd_name_map = self.get_errdap_name_map(vars)
if len(vars) == 1:
raise BadRequest(
'A dataset needs a proper range, not just the temporal dimension. %s\n%s'
% (coverage_path, cov))
dataset_element = doc.createElement('dataset')
#dataset_element.setAttribute('type', 'EDDGridFromDap')
dataset_element.setAttribute('type', 'EDDTableFromDapSequence')
dataset_element.setAttribute('datasetID', 'data' + product_id)
dataset_element.setAttribute('active', 'True')
source_element = doc.createElement('sourceUrl')
text_node = doc.createTextNode(self.pydap_url + paths[1])
source_element.appendChild(text_node)
dataset_element.appendChild(source_element)
reload_element = doc.createElement('reloadEveryNMinutes')
if self.CFG.get_safe('server.erddap.dataset_caching', True):
text_node = doc.createTextNode('1440')
else:
text_node = doc.createTextNode('5')
reload_element.appendChild(text_node)
dataset_element.appendChild(reload_element)
outer_element = doc.createElement('outerSequenceName')
text_node = doc.createTextNode('data')
outer_element.appendChild(text_node)
dataset_element.appendChild(outer_element)
default_element = doc.createElement('defaultDataQuery')
text_node = doc.createTextNode('&time>=1970-01-01')
default_element.appendChild(text_node)
dataset_element.appendChild(default_element)
# No longer applicable
#if self.CFG.get_safe('server.erddap.dataset_caching',True):
#refresh_interval = self.CFG.get_safe('server.erddap.refresh_interval', 30000)
#update_element = doc.createElement('updateEveryNMillis')
#text_node = doc.createTextNode(str(refresh_interval))
#update_element.appendChild(text_node)
#dataset_element.appendChild(update_element)
add_attributes_element = doc.createElement('addAttributes')
atts = {}
atts['title'] = product_name or urllib.unquote(cov.name)
atts['infoUrl'] = self.ux_url + 'DataProduct/face/' + product_id
atts['institution'] = 'OOI'
atts[
'Conventions'] = "COARDS, CF-1.6, Unidata Dataset Discovery v1.0"
atts[
'license'] = '''These data were collected by the Ocean Observatory Initiative (OOI) project purely for internal system development purposes during the construction phase of the project and are offered for release to the public with no assurance of data quality, consistency, temporal continuity or additional support. The OOI Program assumes no liability resulting from the use of these data for other than the intended purpose. No data quality assurance steps have been implemented on this data to date.'''
atts['summary'] = cov.name
atts['cdm_data_type'] = 'Other'
atts['standard_name_vocabulary'] = 'CF-12'
for key, val in atts.iteritems():
self.xml_attr(doc, add_attributes_element, key, val)
if len(add_attributes_element.childNodes) > 0:
dataset_element.appendChild(add_attributes_element)
for var_name in vars:
var = cov.get_parameter_context(var_name)
if re.match(r'.*_[a-z0-9]{32}', var.name):
continue # Let's not do this
#if len(param.shape) >=1 and not param.is_coordinate: #dataVariable
data_element = doc.createElement('dataVariable')
source_name_element = doc.createElement('sourceName')
text_node = doc.createTextNode(var.name)
source_name_element.appendChild(text_node)
data_element.appendChild(source_name_element)
destination_name_element = doc.createElement('destinationName')
text_node = doc.createTextNode(erd_name_map[var.name])
destination_name_element.appendChild(text_node)
data_element.appendChild(destination_name_element)
add_attributes_element = doc.createElement('addAttributes')
units = "unknown"
if hasattr(var, 'uom') and var.uom:
units = var.uom
self.xml_attr(doc, add_attributes_element, 'units', units)
#if var.ATTRS is not None:
#for key in var.ATTRS:
#if not hasattr(var,key):
#continue
#val = getattr(var,key)
#if not val:
#val = ''
#att_element = doc.createElement('att')
#att_element.setAttribute('name', key)
#text_node = doc.createTextNode(val)
#att_element.appendChild(text_node)
#add_attributes_element.appendChild(att_element)
ioos_cat = self.get_ioos_category(var.name, units)
self.xml_attr(doc, add_attributes_element, 'ioos_category',
ioos_cat)
if hasattr(var,
'display_name') and var.display_name is not None:
self.xml_attr(doc, add_attributes_element, 'long_name',
var.display_name)
if hasattr(var,
'standard_name') and var.standard_name is not None:
self.xml_attr(doc, add_attributes_element, 'standard_name',
var.standard_name)
if 'seconds' in units and 'since' in units:
self.xml_attr(doc, add_attributes_element,
'time_precision', '1970-01-01T00:00:00.000Z')
if hasattr(var, 'ooi_short_name') and var.ooi_short_name:
sname = var.ooi_short_name
sname = re.sub('[\t\n ]+', ' ', sname)
self.xml_attr(doc, add_attributes_element,
'ooi_short_name', sname)
m = re.match(r'[A-Z0-9]{7}', sname)
if m:
reference_url = 'https://confluence.oceanobservatories.org/display/instruments/' + m.group(
)
self.xml_attr(doc, add_attributes_element,
'references', reference_url)
if 'L2' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'L2')
self.xml_attr(doc, add_attributes_element, 'source',
'level 2 calibrated sensor observation')
elif 'L1' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'L1')
self.xml_attr(doc, add_attributes_element, 'source',
'level 1 calibrated sensor observation')
elif 'L0' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'L0')
self.xml_attr(doc, add_attributes_element, 'source',
'sensor observation')
elif 'QC' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'QC')
elif not isinstance(var.param_type, ParameterFunctionType):
self.xml_attr(doc, add_attributes_element,
'ooi_short_name', var.name)
if units == 'counts':
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'L0')
self.xml_attr(doc, add_attributes_element, 'source',
'sensor observation')
elif 'seconds' in units and 'since' in units:
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'axis')
else:
self.xml_attr(doc, add_attributes_element,
'data_product_level', 'unknown')
if hasattr(var, 'reference_urls') and var.reference_urls:
if isinstance(var.reference_urls, list):
references = ','.join(var.reference_urls)
else:
references = var.reference_urls
self.xml_attr(doc, add_attributes_element,
'instrument_type', references)
if isinstance(var.param_type, ParameterFunctionType):
if isinstance(var.function, PythonFunction):
self.xml_attr(doc, add_attributes_element,
'function_module', var.function.owner
or '')
self.xml_attr(doc, add_attributes_element,
'function_name', var.function.func_name
or '')
if var.function.owner.startswith('ion_functions'):
s = var.function.owner
url = s.replace('.', '/') + '.py'
url = 'https://github.com/ooici/ion-functions/blob/master/' + url
self.xml_attr(doc, add_attributes_element,
'function_url', url)
elif var.function.egg_uri:
self.xml_attr(doc, add_attributes_element,
'function_url', var.function.egg_uri
or '')
elif isinstance(var.function, NumexprFunction):
self.xml_attr(doc, add_attributes_element,
'function_name', var.function.name or '')
data_element.appendChild(add_attributes_element)
dataset_element.appendChild(data_element)
index += 1
#bug with prettyxml
#http://ronrothman.com/public/leftbraned/xml-dom-minidom-toprettyxml-and-silly-whitespace/
result += dataset_element.toprettyxml() + '\n'
#result += dataset_element.toxml() + '\n'
cov.close()
if not result:
log.error(
"Attempted to register empty dataset\nDims: %s\nDatasets: %s",
dims, datasets)
return result
def _get_coverage(cls,dataset_id,mode='r'):
file_root = FileSystem.get_url(FS.CACHE,'datasets')
coverage = AbstractCoverage.load(file_root, dataset_id, mode=mode)
return coverage
def get_dataset_xml(self, coverage_path, product_id, product_name='', available_fields=None):
#http://coastwatch.pfeg.noaa.gov/erddap/download/setupDatasetsXml.html
result = ''
paths = os.path.split(coverage_path)
cov = AbstractCoverage.load(coverage_path)
doc = xml.dom.minidom.Document()
#erd_type_map = {'d':'double', 'f':"float", 'h':'short', 'i':'int', 'l':'int', 'q':'int', 'b':'byte', 'b':'char', 'S':'String'}
#Get lists of variables with unique sets of dimensions.
#Datasets can only have variables with the same sets of dimensions
if not cov.list_parameters():
raise BadRequest('Attempting to register an empty dataset. The coverage (%s) has no definition.\n%s' %(coverage_path, cov))
datasets = {}
for key in cov.list_parameters():
pc = cov.get_parameter_context(key)
#if getattr(pc, 'visible', None):
# continue
if available_fields and pc.name not in available_fields:
continue
#if not isinstance(pc.param_type, QuantityType):
# continue
param = cov.get_parameter(key)
dims = (cov.temporal_parameter_name,)
if len(param.shape) == 2:
dims = (cov.temporal_parameter_name, cov.spatial_domain.shape.name)
if not dims in datasets.keys():
datasets[dims] = []
datasets[dims].append(key)
index = 0
if not datasets:
raise BadRequest('Attempting to register a dimensionless dataset. The coverage (%s) has no dimension(s).\n%s' %( coverage_path, cov))
for dims, vars in datasets.iteritems():
erd_name_map = self.get_errdap_name_map(vars)
if len(vars)==1:
raise BadRequest('A dataset needs a proper range, not just the temporal dimension. %s\n%s' %( coverage_path, cov))
dataset_element = doc.createElement('dataset')
#dataset_element.setAttribute('type', 'EDDGridFromDap')
dataset_element.setAttribute('type', 'EDDTableFromDapSequence')
dataset_element.setAttribute('datasetID', 'data' + product_id)
dataset_element.setAttribute('active', 'True')
source_element = doc.createElement('sourceUrl')
text_node = doc.createTextNode(self.pydap_url + paths[1])
source_element.appendChild(text_node)
dataset_element.appendChild(source_element)
reload_element = doc.createElement('reloadEveryNMinutes')
if self.CFG.get_safe('server.erddap.dataset_caching',True):
text_node = doc.createTextNode('1440')
else:
text_node = doc.createTextNode('5')
reload_element.appendChild(text_node)
dataset_element.appendChild(reload_element)
outer_element = doc.createElement('outerSequenceName')
text_node = doc.createTextNode('data')
outer_element.appendChild(text_node)
dataset_element.appendChild(outer_element)
default_element = doc.createElement('defaultDataQuery')
text_node = doc.createTextNode('&time>=1970-01-01')
default_element.appendChild(text_node)
dataset_element.appendChild(default_element)
# No longer applicable
#if self.CFG.get_safe('server.erddap.dataset_caching',True):
#refresh_interval = self.CFG.get_safe('server.erddap.refresh_interval', 30000)
#update_element = doc.createElement('updateEveryNMillis')
#text_node = doc.createTextNode(str(refresh_interval))
#update_element.appendChild(text_node)
#dataset_element.appendChild(update_element)
add_attributes_element = doc.createElement('addAttributes')
atts = {}
atts['title'] = product_name or urllib.unquote(cov.name)
atts['infoUrl'] = self.ux_url + 'DataProduct/face/' + product_id
atts['institution'] = 'OOI'
atts['Conventions'] = "COARDS, CF-1.6, Unidata Dataset Discovery v1.0"
atts['license'] = '''These data were collected by the Ocean Observatory Initiative (OOI) project purely for internal system development purposes during the construction phase of the project and are offered for release to the public with no assurance of data quality, consistency, temporal continuity or additional support. The OOI Program assumes no liability resulting from the use of these data for other than the intended purpose. No data quality assurance steps have been implemented on this data to date.'''
atts['summary'] = cov.name
atts['cdm_data_type'] = 'Other'
atts['standard_name_vocabulary'] = 'CF-12'
for key, val in atts.iteritems():
self.xml_attr(doc, add_attributes_element, key, val)
if len(add_attributes_element.childNodes) > 0:
dataset_element.appendChild(add_attributes_element)
for var_name in vars:
var = cov.get_parameter_context(var_name)
if re.match(r'.*_[a-z0-9]{32}', var.name):
continue # Let's not do this
#if len(param.shape) >=1 and not param.is_coordinate: #dataVariable
data_element = doc.createElement('dataVariable')
source_name_element = doc.createElement('sourceName')
text_node = doc.createTextNode(var.name)
source_name_element.appendChild(text_node)
data_element.appendChild(source_name_element)
destination_name_element = doc.createElement('destinationName')
text_node = doc.createTextNode(erd_name_map[var.name])
destination_name_element.appendChild(text_node)
data_element.appendChild(destination_name_element)
add_attributes_element = doc.createElement('addAttributes')
units = "unknown"
if hasattr(var,'uom') and var.uom:
units = var.uom
self.xml_attr(doc, add_attributes_element, 'units', units)
#if var.ATTRS is not None:
#for key in var.ATTRS:
#if not hasattr(var,key):
#continue
#val = getattr(var,key)
#if not val:
#val = ''
#att_element = doc.createElement('att')
#att_element.setAttribute('name', key)
#text_node = doc.createTextNode(val)
#att_element.appendChild(text_node)
#add_attributes_element.appendChild(att_element)
ioos_cat = self.get_ioos_category(var.name, units)
self.xml_attr(doc, add_attributes_element, 'ioos_category', ioos_cat)
if hasattr(var,'display_name') and var.display_name is not None:
self.xml_attr(doc, add_attributes_element, 'long_name', var.display_name)
if hasattr(var,'standard_name') and var.standard_name is not None:
self.xml_attr(doc, add_attributes_element, 'standard_name', var.standard_name)
if 'seconds' in units and 'since' in units:
self.xml_attr(doc, add_attributes_element, 'time_precision', '1970-01-01T00:00:00.000Z')
if hasattr(var, 'ooi_short_name') and var.ooi_short_name:
sname = var.ooi_short_name
sname = re.sub('[\t\n ]+', ' ', sname)
self.xml_attr(doc, add_attributes_element, 'ooi_short_name', sname)
m = re.match(r'[A-Z0-9]{7}', sname)
if m:
reference_url = 'https://confluence.oceanobservatories.org/display/instruments/' + m.group()
self.xml_attr(doc, add_attributes_element, 'references', reference_url)
if 'L2' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'L2')
self.xml_attr(doc, add_attributes_element, 'source', 'level 2 calibrated sensor observation')
elif 'L1' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'L1')
self.xml_attr(doc, add_attributes_element, 'source', 'level 1 calibrated sensor observation')
elif 'L0' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'L0')
self.xml_attr(doc, add_attributes_element, 'source', 'sensor observation')
elif 'QC' in var.ooi_short_name:
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'QC')
elif not isinstance(var.param_type, ParameterFunctionType):
self.xml_attr(doc, add_attributes_element, 'ooi_short_name', var.name)
if units == 'counts':
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'L0')
self.xml_attr(doc, add_attributes_element, 'source', 'sensor observation')
elif 'seconds' in units and 'since' in units:
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'axis')
else:
self.xml_attr(doc, add_attributes_element, 'data_product_level', 'unknown')
if hasattr(var, 'reference_urls') and var.reference_urls:
if isinstance(var.reference_urls, list):
references = ','.join(var.reference_urls)
else:
references = var.reference_urls
self.xml_attr(doc, add_attributes_element, 'instrument_type', references)
if isinstance(var.param_type, ParameterFunctionType):
if isinstance(var.function, PythonFunction):
self.xml_attr(doc, add_attributes_element, 'function_module', var.function.owner or '')
self.xml_attr(doc, add_attributes_element, 'function_name', var.function.func_name or '')
if var.function.owner.startswith('ion_functions'):
s = var.function.owner
url = s.replace('.','/') + '.py'
url = 'https://github.com/ooici/ion-functions/blob/master/' + url
self.xml_attr(doc, add_attributes_element, 'function_url', url)
elif var.function.egg_uri:
self.xml_attr(doc, add_attributes_element, 'function_url', var.function.egg_uri or '')
elif isinstance(var.function, NumexprFunction):
self.xml_attr(doc, add_attributes_element, 'function_name', var.function.name or '')
data_element.appendChild(add_attributes_element)
dataset_element.appendChild(data_element)
index += 1
#bug with prettyxml
#http://ronrothman.com/public/leftbraned/xml-dom-minidom-toprettyxml-and-silly-whitespace/
result += dataset_element.toprettyxml() + '\n'
#result += dataset_element.toxml() + '\n'
cov.close()
if not result:
log.error("Attempted to register empty dataset\nDims: %s\nDatasets: %s", dims, datasets)
return result
def repair(
self,
backup=True,
copy_over=True,
keep_temp=False,
reanalyze=False,
analyze_bricks=False,
detailed_analysis=False,
):
"""
Heavy repair tool that recreates a blank persisted Coverage from the broken coverage's
original construction parameters, then reconstructs the Master and Parameter metadata
files by inspection of the ION objects and "valid" brick files.
@return:
"""
if self._ar is None or reanalyze:
self._ar = self._do_analysis(analyze_bricks=analyze_bricks, detailed_analysis=detailed_analysis)
if self._ar.is_corrupt:
if len(self._ar.get_brick_corruptions()) > 0:
raise NotImplementedError("Brick corruption. Cannot repair at this time!!!")
else:
# Repair the Master and Parameter metadata files
# Need the ParameterDictionary, TemporalDomain and SpatialDomain
pdict = ParameterDictionary.load(self._dso.parameter_dictionary)
tdom = GridDomain.load(self._dso.temporal_domain)
sdom = GridDomain.load(self._dso.spatial_domain)
# Set up the working directory for the recovered coverage
tempcov_dir = tempfile.mkdtemp("covs")
# Create the temporary Coverage
tempcov = SimplexCoverage(
root_dir=tempcov_dir,
persistence_guid=self._guid,
name=self._guid,
parameter_dictionary=pdict,
spatial_domain=sdom,
temporal_domain=tdom,
)
# Handle to persistence layer for tempcov
pl = tempcov._persistence_layer
# Set up the original and temporary coverage path strings
orig_dir = os.path.join(self.cov_pth, self._guid)
temp_dir = os.path.join(tempcov.persistence_dir, tempcov.persistence_guid)
# Insert same number of timesteps into temporary coverage as in broken coverage
brick_domains_new, new_brick_list, brick_list_spans, tD, bD, min_data_bound, max_data_bound = self.inspect_bricks(
self.cov_pth, self._guid, "time"
)
empty_cov = (
brick_list_spans is None
) # If None, there are no brick files --> no timesteps, empty coverage!
if not empty_cov: # If None, there are no brick files --> no timesteps, empty coverage!
bls = [s.value for s in brick_list_spans]
maxes = [sum(b[3]) for b in new_brick_list.values()]
# Replace metadata is the Master file
pl.master_manager.brick_domains = brick_domains_new
pl.master_manager.brick_list = new_brick_list
# Repair ExternalLinks to brick files
with HDFLockingFile(pl.master_manager.file_path, "r+") as f:
for param_name in pdict.keys():
del f[param_name]
f.create_group(param_name)
for param_name in pdict.keys():
for brick in bls:
link_path = "/{0}/{1}".format(param_name, brick[0])
brick_file_name = "{0}.hdf5".format(brick[0])
brick_rel_path = os.path.join(
pl.parameter_metadata[param_name].root_dir.replace(tempcov.persistence_dir, "."),
brick_file_name,
)
log.debug("link_path: %s", link_path)
log.debug("brick_rel_path: %s", brick_rel_path)
pl.master_manager.add_external_link(link_path, brick_rel_path, brick[0])
pl.flush_values()
pl.flush()
tempcov.close()
# Remove 'rtree' dataset from Master file if it already exists (post domain expansion)
# to make way for reconstruction
with HDFLockingFile(pl.master_manager.file_path, "r+") as f:
if "rtree" in f.keys():
del f["rtree"]
# Reconstruct 'rtree' dataset
# Open temporary Coverage and PersistenceLayer objects
fixed_cov = AbstractCoverage.load(tempcov.persistence_dir, mode="r+")
pl_fixed = fixed_cov._persistence_layer
# Call update_rtree for each brick using PersistenceLayer builtin
brick_count = 0
if not empty_cov:
for brick in bls:
rtree_extents, brick_extents, brick_active_size = pl_fixed.calculate_extents(
brick[1][1], bD, tD
)
pl_fixed.master_manager.update_rtree(brick_count, rtree_extents, obj=brick[0])
brick_count += 1
# Update parameter_bounds property based on each parameter's brick data using deep inspection
valid_bounds_types = ["BooleanType", "ConstantType", "QuantityType", "ConstantRangeType"]
if not empty_cov:
for param in pdict.keys():
if pdict.get_context(param).param_type.__class__.__name__ in valid_bounds_types:
brick_domains_new, new_brick_list, brick_list_spans, tD, bD, min_data_bound, max_data_bound = self.inspect_bricks(
self.cov_pth, self._guid, param
)
# Update the metadata
pl_fixed.update_parameter_bounds(param, [min_data_bound, max_data_bound])
pl_fixed.flush()
fixed_cov.close()
# Create backup copy of original Master and Parameter files
if backup:
import datetime
orig_master_file = os.path.join(self.cov_pth, "{0}_master.hdf5".format(self._guid))
# Generate the timestamp
tstamp_format = "%Y%m%d%H%M%S"
tstamp = datetime.datetime.now().strftime(tstamp_format)
backup_master_file = os.path.join(self.cov_pth, "{0}_master.{1}.hdf5".format(self._guid, tstamp))
shutil.copy2(orig_master_file, backup_master_file)
for param in pdict.keys():
param_orig = os.path.join(orig_dir, param, "{0}.hdf5".format(param))
param_backup = os.path.join(orig_dir, param, "{0}.{1}.hdf5".format(param, tstamp))
shutil.copy2(param_orig, param_backup)
# Copy Master and Parameter metadata files back to original/broken coverage (cov_pth) location
if copy_over == True:
shutil.copy2(
os.path.join(tempcov.persistence_dir, "{0}_master.hdf5".format(self._guid)),
os.path.join(self.cov_pth, "{0}_master.hdf5".format(self._guid)),
)
for param in pdict.keys():
shutil.copy2(
os.path.join(temp_dir, param, "{0}.hdf5".format(param)),
os.path.join(orig_dir, param, "{0}.hdf5".format(param)),
)
# Reanalyze the repaired coverage
self._ar = self._do_analysis(analyze_bricks=True)
# Verify repair worked, clean up if not
if self._ar.is_corrupt:
# If the files were backed up then revert
if backup:
# Remove backed up files and clean up the repair attempt
log.info("Repair attempt failed. Reverting to pre-repair state.")
# Use backup copy to replace post-repair file.
shutil.copy2(backup_master_file, orig_master_file)
# Delete the backup
os.remove(backup_master_file)
# Iterate over parameters and revert to pre-repair state
for param in pdict.keys():
param_orig = os.path.join(orig_dir, param, "{0}.hdf5".format(param))
param_backup = os.path.join(orig_dir, param, "{0}.{1}.hdf5".format(param, tstamp))
# Use backup copy to replace post-repair file.
shutil.copy2(param_backup, param_orig)
# Delete the backup
os.remove(param_backup)
raise ValueError("Coverage repair failed! Revert to stored backup version, if possible.")
# Remove temporary coverage
if keep_temp == False:
shutil.rmtree(tempcov_dir)
else:
return tempcov_dir
else:
log.info("Coverage is not corrupt, nothing to repair!")
def repair(self,
backup=True,
copy_over=True,
keep_temp=False,
reanalyze=False,
analyze_bricks=False,
detailed_analysis=False):
"""
Heavy repair tool that recreates a blank persisted Coverage from the broken coverage's
original construction parameters, then reconstructs the Master and Parameter metadata
files by inspection of the ION objects and "valid" brick files.
@return:
"""
if self._ar is None or reanalyze:
self._ar = self._do_analysis(analyze_bricks=analyze_bricks,
detailed_analysis=detailed_analysis)
if self._ar.is_corrupt:
if len(self._ar.get_brick_corruptions()) > 0:
raise NotImplementedError(
'Brick corruption. Cannot repair at this time!!!')
else:
# Repair the Master and Parameter metadata files
# Need the ParameterDictionary, TemporalDomain and SpatialDomain
pdict = ParameterDictionary.load(
self._dso.parameter_dictionary)
tdom = GridDomain.load(self._dso.temporal_domain)
sdom = GridDomain.load(self._dso.spatial_domain)
# Set up the working directory for the recovered coverage
tempcov_dir = tempfile.mkdtemp('covs')
# Create the temporary Coverage
tempcov = SimplexCoverage(root_dir=tempcov_dir,
persistence_guid=self._guid,
name=self._guid,
parameter_dictionary=pdict,
spatial_domain=sdom,
temporal_domain=tdom)
# Handle to persistence layer for tempcov
pl = tempcov._persistence_layer
# Set up the original and temporary coverage path strings
orig_dir = os.path.join(self.cov_pth, self._guid)
temp_dir = os.path.join(tempcov.persistence_dir,
tempcov.persistence_guid)
# Insert same number of timesteps into temporary coverage as in broken coverage
brick_domains_new, new_brick_list, brick_list_spans, tD, bD, min_data_bound, max_data_bound = self.inspect_bricks(
self.cov_pth, self._guid, 'time')
empty_cov = brick_list_spans is None # If None, there are no brick files --> no timesteps, empty coverage!
if not empty_cov: # If None, there are no brick files --> no timesteps, empty coverage!
bls = [s.value for s in brick_list_spans]
maxes = [sum(b[3]) for b in new_brick_list.values()]
tempcov.insert_timesteps(sum(maxes))
# Replace metadata is the Master file
pl.master_manager.brick_domains = brick_domains_new
pl.master_manager.brick_list = new_brick_list
# Repair ExternalLinks to brick files
f = h5py.File(pl.master_manager.file_path, 'a')
for param_name in pdict.keys():
del f[param_name]
f.create_group(param_name)
for brick in bls:
link_path = '/{0}/{1}'.format(param_name, brick[0])
brick_file_name = '{0}.hdf5'.format(brick[0])
brick_rel_path = os.path.join(
pl.parameter_metadata[param_name].root_dir.
replace(tempcov.persistence_dir,
'.'), brick_file_name)
log.debug('link_path: %s', link_path)
log.debug('brick_rel_path: %s', brick_rel_path)
pl.master_manager.add_external_link(
link_path, brick_rel_path, brick[0])
pl.flush_values()
pl.flush()
tempcov.close()
# Remove 'rtree' dataset from Master file if it already exists (post domain expansion)
# to make way for reconstruction
f = h5py.File(pl.master_manager.file_path, 'a')
if 'rtree' in f.keys():
del f['rtree']
f.close()
# Reconstruct 'rtree' dataset
# Open temporary Coverage and PersistenceLayer objects
fixed_cov = AbstractCoverage.load(tempcov.persistence_dir,
mode='a')
pl_fixed = fixed_cov._persistence_layer
# Call update_rtree for each brick using PersistenceLayer builtin
brick_count = 0
if not empty_cov:
for brick in bls:
rtree_extents, brick_extents, brick_active_size = pl_fixed.calculate_extents(
brick[1][1], bD, tD)
pl_fixed.master_manager.update_rtree(brick_count,
rtree_extents,
obj=brick[0])
brick_count += 1
# Update parameter_bounds property based on each parameter's brick data using deep inspection
valid_bounds_types = [
'BooleanType', 'ConstantType', 'QuantityType',
'ConstantRangeType'
]
if not empty_cov:
for param in pdict.keys():
if pdict.get_context(
param
).param_type.__class__.__name__ in valid_bounds_types:
brick_domains_new, new_brick_list, brick_list_spans, tD, bD, min_data_bound, max_data_bound = self.inspect_bricks(
self.cov_pth, self._guid, param)
# Update the metadata
pl_fixed.update_parameter_bounds(
param, [min_data_bound, max_data_bound])
pl_fixed.flush()
fixed_cov.close()
# Create backup copy of original Master and Parameter files
if backup:
import datetime
orig_master_file = os.path.join(
self.cov_pth, '{0}_master.hdf5'.format(self._guid))
# Generate the timestamp
tstamp_format = '%Y%m%d%H%M%S'
tstamp = datetime.datetime.now().strftime(tstamp_format)
backup_master_file = os.path.join(
self.cov_pth,
'{0}_master.{1}.hdf5'.format(self._guid, tstamp))
shutil.copy2(orig_master_file, backup_master_file)
for param in pdict.keys():
param_orig = os.path.join(orig_dir, param,
'{0}.hdf5'.format(param))
param_backup = os.path.join(
orig_dir, param,
'{0}.{1}.hdf5'.format(param, tstamp))
shutil.copy2(param_orig, param_backup)
# Copy Master and Parameter metadata files back to original/broken coverage (cov_pth) location
if copy_over == True:
shutil.copy2(
os.path.join(tempcov.persistence_dir,
'{0}_master.hdf5'.format(self._guid)),
os.path.join(self.cov_pth,
'{0}_master.hdf5'.format(self._guid)))
for param in pdict.keys():
shutil.copy2(
os.path.join(temp_dir, param,
'{0}.hdf5'.format(param)),
os.path.join(orig_dir, param,
'{0}.hdf5'.format(param)))
# Reanalyze the repaired coverage
self._ar = self._do_analysis(analyze_bricks=True)
# Verify repair worked, clean up if not
if self._ar.is_corrupt:
# If the files were backed up then revert
if backup:
# Remove backed up files and clean up the repair attempt
log.info(
'Repair attempt failed. Reverting to pre-repair state.'
)
# Use backup copy to replace post-repair file.
shutil.copy2(backup_master_file, orig_master_file)
# Delete the backup
os.remove(backup_master_file)
# Iterate over parameters and revert to pre-repair state
for param in pdict.keys():
param_orig = os.path.join(orig_dir, param,
'{0}.hdf5'.format(param))
param_backup = os.path.join(
orig_dir, param,
'{0}.{1}.hdf5'.format(param, tstamp))
# Use backup copy to replace post-repair file.
shutil.copy2(param_backup, param_orig)
# Delete the backup
os.remove(param_backup)
raise ValueError(
'Coverage repair failed! Revert to stored backup version, if possible.'
)
# Remove temporary coverage
if keep_temp == False:
shutil.rmtree(tempcov_dir)
else:
return tempcov_dir
else:
log.info('Coverage is not corrupt, nothing to repair!')
def test_coverage_recovery(self):
# Create the coverage
dp_id, stream_id, route, stream_def_id, dataset_id = self.load_data_product(
)
self.populate_dataset(dataset_id, 36)
dset = self.dataset_management.read_dataset(dataset_id)
dprod = self.dpsc_cli.read_data_product(dp_id)
cov = DatasetManagementService._get_simplex_coverage(dataset_id)
cov_pth = cov.persistence_dir
cov.close()
num_params = len(cov.list_parameters())
num_bricks = 8
total = num_params + num_bricks + 1
# Analyze the valid coverage
dr = CoverageDoctor(cov_pth, dprod, dset)
dr_result = dr.analyze()
# TODO: Turn these into meaningful Asserts
self.assertEqual(len(dr_result.get_brick_corruptions()), 0)
self.assertEqual(len(dr_result.get_brick_size_ratios()), num_bricks)
self.assertEqual(len(dr_result.get_corruptions()), 0)
self.assertEqual(len(dr_result.get_master_corruption()), 0)
self.assertEqual(len(dr_result.get_param_corruptions()), 0)
self.assertEqual(len(dr_result.get_param_size_ratios()), num_params)
self.assertEqual(len(dr_result.get_master_size_ratio()), 1)
self.assertEqual(len(dr_result.get_size_ratios()), total)
self.assertEqual(dr_result.master_status[1], 'NORMAL')
self.assertFalse(dr_result.is_corrupt)
self.assertEqual(dr_result.param_file_count, num_params)
self.assertEqual(dr_result.brick_file_count, num_bricks)
self.assertEqual(dr_result.total_file_count, total)
# Get original values (mock)
orig_cov = AbstractCoverage.load(cov_pth)
time_vals_orig = orig_cov.get_time_values()
orig_cov.close()
# Corrupt the Master File
fo = open(cov._persistence_layer.master_manager.file_path, "wb")
fo.write('Junk')
fo.close()
# Corrupt the lon Parameter file
fo = open(cov._persistence_layer.parameter_metadata['lon'].file_path,
"wb")
fo.write('Junk')
fo.close()
corrupt_res = dr.analyze(reanalyze=True)
self.assertTrue(corrupt_res.is_corrupt)
# Repair the metadata files
dr.repair(reanalyze=True)
fixed_res = dr.analyze(reanalyze=True)
self.assertFalse(fixed_res.is_corrupt)
fixed_cov = AbstractCoverage.load(cov_pth)
self.assertIsInstance(fixed_cov, AbstractCoverage)
time_vals_fixed = fixed_cov.get_time_values()
fixed_cov.close()
self.assertTrue(np.array_equiv(time_vals_orig, time_vals_fixed))
def get_dataset_xml(self, coverage_path, product_id, product_name='', available_fields=None):
#http://coastwatch.pfeg.noaa.gov/erddap/download/setupDatasetsXml.html
result = ''
paths = os.path.split(coverage_path)
cov = AbstractCoverage.load(coverage_path)
doc = xml.dom.minidom.Document()
#erd_type_map = {'d':'double', 'f':"float", 'h':'short', 'i':'int', 'l':'int', 'q':'int', 'b':'byte', 'b':'char', 'S':'String'}
#Get lists of variables with unique sets of dimensions.
#Datasets can only have variables with the same sets of dimensions
if not cov.list_parameters():
raise BadRequest('Attempting to register an empty dataset. The coverage (%s) has no definition.\n%s' %(coverage_path, cov))
datasets = {}
for key in cov.list_parameters():
pc = cov.get_parameter_context(key)
#if getattr(pc, 'visible', None):
# continue
if available_fields and pc.name not in available_fields:
continue
#if not isinstance(pc.param_type, QuantityType):
# continue
param = cov.get_parameter(key)
dims = (cov.temporal_parameter_name,)
if len(param.shape) == 2:
dims = (cov.temporal_parameter_name, cov.spatial_domain.shape.name)
if not dims in datasets.keys():
datasets[dims] = []
datasets[dims].append(key)
index = 0
if not datasets:
raise BadRequest('Attempting to register a dimensionless dataset. The coverage (%s) has no dimension(s).\n%s' %( coverage_path, cov))
for dims, vars in datasets.iteritems():
erd_name_map = self.get_errdap_name_map(vars)
if len(vars)==1:
raise BadRequest('A dataset needs a proper range, not just the temporal dimension. %s\n%s' %( coverage_path, cov))
if not (len(dims) == 1 and dims[0] == vars[0]):
dataset_element = doc.createElement('dataset')
dataset_element.setAttribute('type', 'EDDGridFromDap')
dataset_element.setAttribute('datasetID', product_id)
dataset_element.setAttribute('active', 'True')
source_element = doc.createElement('sourceUrl')
text_node = doc.createTextNode(self.pydap_url + paths[1])
source_element.appendChild(text_node)
dataset_element.appendChild(source_element)
reload_element = doc.createElement('reloadEveryNMinutes')
if self.CFG.get_safe('server.erddap.dataset_caching',True):
text_node = doc.createTextNode('1440')
else:
text_node = doc.createTextNode('5')
reload_element.appendChild(text_node)
dataset_element.appendChild(reload_element)
if self.CFG.get_safe('server.erddap.dataset_caching',True):
refresh_interval = self.CFG.get_safe('server.erddap.refresh_interval', 30000)
update_element = doc.createElement('updateEveryNMillis')
text_node = doc.createTextNode(str(refresh_interval))
update_element.appendChild(text_node)
dataset_element.appendChild(update_element)
add_attributes_element = doc.createElement('addAttributes')
atts = {}
atts['title'] = product_name or urllib.unquote(cov.name)
atts['infoUrl'] = self.pydap_url + paths[1]
atts['institution'] = 'OOI'
atts['Conventions'] = "COARDS, CF-1.6, Unidata Dataset Discovery v1.0"
atts['license'] = '[standard]'
atts['summary'] = cov.name
atts['cdm_data_type'] = 'Grid'
atts['standard_name_vocabulary'] = 'CF-12'
for key, val in atts.iteritems():
att_element = doc.createElement('att')
att_element.setAttribute('name', key)
text_node = doc.createTextNode(val)
att_element.appendChild(text_node)
add_attributes_element.appendChild(att_element)
if len(add_attributes_element.childNodes) > 0:
dataset_element.appendChild(add_attributes_element)
for var_name in vars:
var = cov.get_parameter_context(var_name)
units = "unknown"
if hasattr(var,'uom') and var.uom:
units = var.uom
#if len(param.shape) >=1 and not param.is_coordinate: #dataVariable
data_element = doc.createElement('dataVariable')
source_name_element = doc.createElement('sourceName')
text_node = doc.createTextNode(var.name)
source_name_element.appendChild(text_node)
data_element.appendChild(source_name_element)
destination_name_element = doc.createElement('destinationName')
text_node = doc.createTextNode(erd_name_map[var.name])
destination_name_element.appendChild(text_node)
data_element.appendChild(destination_name_element)
add_attributes_element = doc.createElement('addAttributes')
if var.ATTRS is not None:
for key in var.ATTRS:
if not hasattr(var,key):
continue
val = getattr(var,key)
if not val:
val = ''
att_element = doc.createElement('att')
att_element.setAttribute('name', key)
text_node = doc.createTextNode(val)
att_element.appendChild(text_node)
add_attributes_element.appendChild(att_element)
att_element = doc.createElement('att')
att_element.setAttribute('name', 'ioos_category')
text_node = doc.createTextNode(self.get_ioos_category(var.name, units))
att_element.appendChild(text_node)
add_attributes_element.appendChild(att_element)
att_element = doc.createElement('att')
att_element.setAttribute('name', 'long_name')
long_name = ""
if hasattr(var,'display_name') and var.display_name is not None:
long_name = var.display_name
text_node = doc.createTextNode(long_name)
att_element.appendChild(text_node)
add_attributes_element.appendChild(att_element)
att_element = doc.createElement('att')
standard_name = ""
if hasattr(var,'standard_name') and var.standard_name is not None:
standard_name = var.standard_name
att_element.setAttribute('name', 'standard_name')
text_node = doc.createTextNode(standard_name)
att_element.appendChild(text_node)
add_attributes_element.appendChild(att_element)
att_element = doc.createElement('att')
att_element.setAttribute('name', 'units')
text_node = doc.createTextNode(units)
att_element.appendChild(text_node)
add_attributes_element.appendChild(att_element)
data_element.appendChild(add_attributes_element)
dataset_element.appendChild(data_element)
index += 1
#bug with prettyxml
#http://ronrothman.com/public/leftbraned/xml-dom-minidom-toprettyxml-and-silly-whitespace/
#result += dataset_element.toprettyxml() + '\n'
result += dataset_element.toxml() + '\n'
cov.close()
return result
