Exemplo n.º 1
0
def test_queries():
    doi = "10.1016/j.neurobiolaging.2012.11.002"

    # A DOI is associated with a collection. Download it.
    collection = collections_from_dois(doi)
    assert_equal(collection.shape[0],1)
    collections = collections_from_dois([doi,doi])
    assert_equal(collections.shape[0],2)
Exemplo n.º 2
0
def test_queries():
    doi = "10.1016/j.neurobiolaging.2012.11.002"

    # A DOI is associated with a collection. Download it.
    collection = collections_from_dois(doi)
    assert_equal(collection.shape[0], 1)
    collections = collections_from_dois([doi, doi])
    assert_equal(collections.shape[0], 2)
Exemplo n.º 3
0
def test_NeuroVault_metadata():
    from pyneurovault import api

    # Test for all images
    print "Checking metadata extraction for images..."
    images = api.get_images()
    check_df(df=images,size_min=7000,columns=["url","name","map_type"])

    # Test for subset of images
    images = api.get_images(pks=images.image_id[0:10].tolist())
    check_df(df=images,size_min=10,columns=["url","name","map_type"])

    # Test for collections
    print "Checking metadata extraction for collections..."
    collections = api.get_collections()
    check_df(df=collections,size_min=300,columns=["used_smoothing","url","collection_id"])

    # Test metadata from specific DOIs
    dois = collections.DOI[collections.DOI.isnull()==False].tolist()[0:15]
    results = api.collections_from_dois(dois)
    check_df(df=results,size_min=len(dois),columns=["used_smoothing","url","collection_id"])

    # Test get_images_and_collections
    combined_df = api.get_images_with_collections(collection_pks=[877,437])
    check_df(df=combined_df,size_min=50,columns=["url_image","collection_id","name_image","map_type","image_id"])

    # Test metadata for subset of collections
    collections = api.get_collections(pks=[877,437])
    check_df(df=collections,size_min=1,columns=["used_smoothing","url","collection_id"])
    
    # Test metadata of images from specific collections
    images = api.get_images(collection_pks=[877,437])
    check_df(df=images,size_min=50,columns=["url","name","map_type"])
Exemplo n.º 4
0
#!/usr/bin/env python2

# This script will use the pyneurovault module to perform single REST queries from NeuroVault.

from pyneurovault.api import collections_from_dois, images_from_collections, get_images_with_collections
from pyneurovault import pubmed as pm

# 1) SINGLE REST QUERY EXAMPLE
# Here is a doi that we are interested in
doi = "10.1016/j.neurobiolaging.2012.11.002"

# A DOI is associated with a collection. Download it.
collection = collections_from_dois(doi)

# Here is the identifier
# collection[0]["id"]
# 77

# Get the images
images = images_from_collections(collection[0]["id"])[0]

# Here are the file URLs for the images, as well as contrasts
# and cognitive atlas contrasts IDs. (we can use this later to tag to CA)
for image in images:
    print "<file:%s><contrast:%s><ca-contrast:%s>" % (
        image["file"], image["contrast_definition"],
        image["contrast_definition_cogatlas"])

# We now want to use the doi to look up the pmid
pubmed = pm.Pubmed(email="*****@*****.**")
article = pubmed.get_single_article(doi)
Exemplo n.º 5
0
#!/usr/bin/env python2

# This script will use the pyneurovault module to perform single REST queries from NeuroVault. This strategy is intended for smaller/single queries that use the REST api. For larger analysis to download all of NeuroVault meta at once, see download_example.py.

from pyneurovault import api, pubmed as pm

# 1) SINGLE REST QUERY EXAMPLE
# Here is a doi that we are interested in
doi = "10.1016/j.neurobiolaging.2012.11.002"

# A DOI is associated with a collection. Download it.
collection = api.collections_from_dois(doi)

# Get the images
images = api.images_from_collections(collection)

# Here are the file URLs for the images, as well as contrasts 
# and cognitive atlas contrasts IDs. (we can use this later to tag to CA)
for image in images:
  print "<file:%s><contrast:%s><ca-contrast:%s>" %(image["file"],image["contrast_definition"],image["contrast_definition_cogatlas"])
 
# We now want to use the doi to look up the pmid
pubmed = pm.Pubmed(email="*****@*****.**")
article = pubmed.get_single_article(doi)
pmid = article.get_pmid()


# 2) SEARCH FIELD ACROSS ALL COLLECTIONS OR DATA
nv = api.NeuroVault()
df = nv.get_images_with_collections_df()
result = nv.search(df=df,column_name="description_collection",search_string="OpenfMRI")
Exemplo n.º 6
0
#!/usr/bin/env python2

# This script will use the pyneurovault module to perform single REST queries from NeuroVault. 

from pyneurovault.api import collections_from_dois, images_from_collections, get_images_with_collections
from pyneurovault import pubmed as pm

# 1) SINGLE REST QUERY EXAMPLE
# Here is a doi that we are interested in
doi = "10.1016/j.neurobiolaging.2012.11.002"

# A DOI is associated with a collection. Download it.
collection = collections_from_dois(doi)

# Here is the identifier
# collection[0]["id"]
# 77

# Get the images
images = images_from_collections(collection[0]["id"])[0]

# Here are the file URLs for the images, as well as contrasts 
# and cognitive atlas contrasts IDs. (we can use this later to tag to CA)
for image in images:
  print "<file:%s><contrast:%s><ca-contrast:%s>" %(image["file"],image["contrast_definition"],image["contrast_definition_cogatlas"])
 
# We now want to use the doi to look up the pmid
pubmed = pm.Pubmed(email="*****@*****.**")
article = pubmed.get_single_article(doi)
pmid = article.get_pmid()