def open_databases( conf ):
"""
A helper function that returns handles to the hdf and sql databases
"""
db = hdf.hdf_open( conf.HDF_DATABASE, mode='r' )
session = sql.get_session( conf.SQL_URI )
return db, session
def search(self, trans, word='', dataset_id=None, submit=''):
"""
Default search page
"""
data = trans.app.model.HistoryDatasetAssociation.get( dataset_id )
if not data:
raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( dataset_id ) )
# the main configuration file
conf = BaseConf(
TITLE = "<i>%s</i>: %s" % (data.metadata.dbkey, data.metadata.label),
HDF_DATABASE = os.path.join( data.extra_files_path, data.metadata.hdf ),
SQL_URI = "sqlite:///%s" % os.path.join( data.extra_files_path, data.metadata.sqlite ),
LABEL = data.metadata.label,
FIT_LABEL = "%s-SIGMA-%d" % (data.metadata.label, 20),
PRED_LABEL = "PRED-%s-SIGMA-%d" % (data.metadata.label, 20),
)
param = atlas.Param( word=word )
# search for a given
try:
session = sql.get_session( conf.SQL_URI )
except:
return trans.fill_template_mako('genetrack/invalid.html', dataset_id=dataset_id)
if param.word:
def search_query( word, text ):
query = session.query(sql.Feature).filter( "name LIKE :word or freetext LIKE :text" ).params(word=word, text=text)
query = list(query[:20])
return query
# a little heuristics to match most likely target
targets = [
(param.word+'%', 'No match'), # match beginning
('%'+param.word+'%', 'No match'), # match name anywhere
('%'+param.word+'%', '%'+param.word+'%'), # match json anywhere
]
for word, text in targets:
query = search_query( word=word, text=text)
if query:
break
else:
query = []
return trans.fill_template_mako('genetrack/search.html', param=param, query=query, dataset_id=dataset_id)
def index(self, trans, dataset_id=None, **kwds):
"""
Main request handler
"""
color = cycle( [LIGHT, WHITE] )
data = trans.app.model.HistoryDatasetAssociation.get( dataset_id )
if not data:
raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( dataset_id ) )
# the main configuration file
conf = BaseConf(
TITLE = "<i>%s</i>: %s" % (data.metadata.dbkey, data.metadata.label),
HDF_DATABASE = os.path.join( data.extra_files_path, data.metadata.hdf ),
SQL_URI = "sqlite:///%s" % os.path.join( data.extra_files_path, data.metadata.sqlite ),
LABEL = data.metadata.label,
FIT_LABEL = "%s-SIGMA-%d" % (data.metadata.label, 20),
PRED_LABEL = "PRED-%s-SIGMA-%d" % (data.metadata.label, 20),
)
try:
session = sql.get_session( conf.SQL_URI )
except:
return trans.fill_template_mako('genetrack/invalid.html', dataset_id=dataset_id)
if os.path.exists( conf.HDF_DATABASE ):
db = hdf.hdf_open( conf.HDF_DATABASE, mode='r' )
conf.CHROM_FIELDS = [(x,x) for x in hdf.GroupData(db=db, name=conf.LABEL).labels]
db.close()
else:
query = session.execute(sql.select([sql.feature_table.c.chrom]).distinct())
conf.CHROM_FIELDS = [(x.chrom,x.chrom) for x in query]
# generate a new form based on the configuration
form = formlib.main_form( conf )
# clear the tempdir every once in a while
atlas_utils.clear_tempdir( dir=conf.IMAGE_DIR, days=1, chance=10)
incoming = form.defaults()
incoming.update( kwds )
# manage the zoom and pan requests
incoming = formlib.zoom_change( kdict=incoming, levels=conf.LEVELS)
incoming = formlib.pan_view( kdict=incoming )
# process the form
param = atlas.Param( **incoming )
form.process( incoming )
if kwds and form.isSuccessful():
# adds the sucessfull parameters
param.update( form.values() )
# if it was a search word not a number go to search page
try:
center = int( param.feature )
except ValueError:
# go and search for these
return trans.response.send_redirect( web.url_for( controller='genetrack', action='search', word=param.feature, dataset_id=dataset_id ) )
param.width = min( [2000, int(param.img_size)] )
param.xscale = [ param.start, param.end ]
param.show_labels = ( param.end - param.start ) <= SHOW_LABEL_LIMIT
# get the template and the function used to generate the tracks
tmpl_name, track_maker = conf.PLOT_MAPPER[param.plot]
# check against a hash, display an image that already exists if it was previously created.
hash = sha.new()
hash.update(str(dataset_id))
for key in sorted(kwds.keys()):
hash.update(str(kwds[key]))
fname = "%s.png" % hash.hexdigest()
fpath = os.path.join(conf.IMAGE_DIR, fname)
charts = []
param.fname = fname
# The SHA1 hash should uniquely identify the qs that created the plot...
if os.path.exists(fpath):
os.utime(fpath, (time.time(), time.time()))
return trans.fill_template_mako(tmpl_name, conf=conf, form=form, param=param, dataset_id=dataset_id)
# If the hashed filename doesn't exist, create it.
if track_maker is not None and os.path.exists( conf.HDF_DATABASE ):
# generate the fit track
charts = track_maker( param=param, conf=conf )
for label in list_labels( session ):
charts.extend( feature_chart(param=param, session=session, label=label.name, label_dict={label.name:label.id}, color=color))
track_chart = consolidate_charts( charts, param )
track_chart.save(fname=fpath)
return trans.fill_template_mako(tmpl_name, conf=conf, form=form, param=param, dataset_id=dataset_id)
