def datasource():
"""Use pepdata to fetch and search IEDB epitopes"""
print request.vars
db = request.vars.database
epitope = request.vars.epitope
from pepdata import iedb, hpv, imma2, hiv_frahm, tcga, tantigen
if db == 'iedb':
df = iedb.mhc.load_dataframe(mhc_class=2,human=False)
df.columns = df.columns.get_level_values(1)
df = df[df.columns[5:18]]
#df = iedb.tcell.load_dataframe()
#if epitope != '':
# df = df[df['Description'].str.contains(epitope)]
#print df
elif db == 'hpv':
df = hpv.load_mhc()
#df = hpv.load_tcell()
elif db == 'IMMA2':
df, non = imma2.load_classes()
elif db == 'hiv_frahm':
df = hiv_frahm.load_dataframe()
elif db == 'tcga':
df = tcga.load_dataframe(cancer_type='paad')
df = df[:50]
elif db == 'tantigen':
df = tantigen.load_mhc()
#df = tantigen.load_tcell()
if len(df) > 5000:
df = df[:5000]
print df
return dict(results=df)
def test_same_size():
peptides = hiv_frahm.load_set()
df = hiv_frahm.load_dataframe()
assert len(peptides) == len(df)
def test_load_dataframe():
df = hiv_frahm.load_dataframe()
assert df is not None
assert len(df) > 0
def test_same_size():
peptides = hiv_frahm.load_set()
df = hiv_frahm.load_dataframe()
assert len(peptides) == len(df)
def test_load_dataframe():
df = hiv_frahm.load_dataframe()
assert df is not None
assert len(df) > 0
