def query(nidm_file_list, query_file, output_file, get_participants,get_instruments,get_instrument_vars):
#query result list
results = []
if get_participants:
df = GetParticipantIDs(nidm_file_list.split(','),output_file=output_file)
elif get_instruments:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count=1
for project in project_list:
if count == 1:
df = GetProjectInstruments(nidm_file_list.split(','),project_id=project)
count+=1
else:
df = df.append(GetProjectInstruments(nidm_file_list.split(','),project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
#with open(output_file,'w') as myfile:
# wr=csv.writer(myfile,quoting=csv.QUOTE_ALL)
# wr.writerow(df)
#pd.DataFrame.from_records(df,columns=["Instruments"]).to_csv(output_file)
else:
print(df)
elif get_instrument_vars:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count=1
for project in project_list:
if count == 1:
df = GetInstrumentVariables(nidm_file_list.split(','),project_id=project)
count+=1
else:
df = df.append(GetInstrumentVariables(nidm_file_list.split(','),project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
else:
print(df)
else:
#read query from text fiile
with open(query_file, 'r') as fp:
query = fp.read()
df = sparql_query_nidm(nidm_file_list.split(','),query,output_file)
return df
def query(nidm_file_list, cde_file_list, query_file, output_file,
get_participants, get_instruments, get_instrument_vars,
get_dataelements, get_brainvols, get_dataelements_brainvols,
get_fields, uri, blaze, j, verbosity):
"""
This function provides query support for NIDM graphs.
"""
#query result list
results = []
# if there is a CDE file list, seed the CDE cache
if cde_file_list:
getCDEs(cde_file_list.split(","))
if blaze:
os.environ["BLAZEGRAPH_URL"] = blaze
print("setting BLAZEGRAPH_URL to {}".format(blaze))
if get_participants:
df = GetParticipantIDs(nidm_file_list.split(','),
output_file=output_file)
if ((output_file) is None):
print(df.to_string())
return df
elif get_instruments:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count = 1
for project in project_list:
if count == 1:
df = GetProjectInstruments(nidm_file_list.split(','),
project_id=project)
count += 1
else:
df = df.append(
GetProjectInstruments(nidm_file_list.split(','),
project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
#with open(output_file,'w') as myfile:
# wr=csv.writer(myfile,quoting=csv.QUOTE_ALL)
# wr.writerow(df)
#pd.DataFrame.from_records(df,columns=["Instruments"]).to_csv(output_file)
else:
print(df.to_string())
elif get_instrument_vars:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count = 1
for project in project_list:
if count == 1:
df = GetInstrumentVariables(nidm_file_list.split(','),
project_id=project)
count += 1
else:
df = df.append(
GetInstrumentVariables(nidm_file_list.split(','),
project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
else:
print(df.to_string())
elif get_dataelements:
datael = GetDataElements(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
datael.to_csv(output_file)
else:
print(datael.to_string())
elif get_fields:
# fields only query. We'll do it with the rest api
restParser = RestParser(verbosity_level=int(verbosity))
if (output_file is not None):
restParser.setOutputFormat(RestParser.OBJECT_FORMAT)
df_list = []
else:
restParser.setOutputFormat(RestParser.CLI_FORMAT)
# set up uri to do fields query for each nidm file
for nidm_file in nidm_file_list.split(","):
# get project UUID
project = GetProjectsUUID([nidm_file])
uri = "/projects/" + project[0].toPython().split(
"/")[-1] + "?fields=" + get_fields
# get fields output from each file and concatenate
if (output_file is None):
# just print results
print(restParser.run([nidm_file], uri))
else:
df_list.append(pd.DataFrame(restParser.run([nidm_file], uri)))
if (output_file is not None):
# concatenate data frames
df = pd.concat(df_list)
# output to csv file
df.to_csv(output_file)
elif uri:
restParser = RestParser(verbosity_level=int(verbosity))
if j:
restParser.setOutputFormat(RestParser.JSON_FORMAT)
elif (output_file is not None):
restParser.setOutputFormat(RestParser.OBJECT_FORMAT)
else:
restParser.setOutputFormat(RestParser.CLI_FORMAT)
df = restParser.run(nidm_file_list.split(','), uri)
if (output_file is not None):
if j:
with open(output_file, "w+") as f:
f.write(dumps(df))
else:
# convert object df to dataframe and output
pd.DataFrame(df).to_csv(output_file)
else:
print(df)
elif get_dataelements_brainvols:
brainvol = GetBrainVolumeDataElements(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
brainvol.to_csv(output_file)
else:
print(brainvol.to_string())
elif get_brainvols:
brainvol = GetBrainVolumes(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
brainvol.to_csv(output_file)
else:
print(brainvol.to_string())
elif query_file:
df = sparql_query_nidm(nidm_file_list.split(','), query_file,
output_file)
if ((output_file) is None):
print(df.to_string())
return df
else:
print("ERROR: No query parameter provided. See help:")
print()
os.system("pynidm query --help")
exit(1)
def query(nidm_file_list, cde_file_list, query_file, output_file,
get_participants, get_instruments, get_instrument_vars,
get_dataelements, get_brainvols, get_dataelements_brainvols, uri, j,
verbosity):
#query result list
results = []
# if there is a CDE file list, seed the CDE cache
if cde_file_list:
getCDEs(cde_file_list.split(","))
if get_participants:
df = GetParticipantIDs(nidm_file_list.split(','),
output_file=output_file)
if ((output_file) is None):
print(df.to_string())
return df
elif get_instruments:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count = 1
for project in project_list:
if count == 1:
df = GetProjectInstruments(nidm_file_list.split(','),
project_id=project)
count += 1
else:
df = df.append(
GetProjectInstruments(nidm_file_list.split(','),
project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
#with open(output_file,'w') as myfile:
# wr=csv.writer(myfile,quoting=csv.QUOTE_ALL)
# wr.writerow(df)
#pd.DataFrame.from_records(df,columns=["Instruments"]).to_csv(output_file)
else:
print(df.to_string())
elif get_instrument_vars:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count = 1
for project in project_list:
if count == 1:
df = GetInstrumentVariables(nidm_file_list.split(','),
project_id=project)
count += 1
else:
df = df.append(
GetInstrumentVariables(nidm_file_list.split(','),
project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
else:
print(df.to_string())
elif get_dataelements:
datael = GetDataElements(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
datael.to_csv(output_file)
else:
print(datael.to_string())
elif uri:
df = restParser(nidm_file_list.split(','), uri, int(verbosity))
if j:
print(dumps(df, indent=2))
else:
if type(df) == list:
for x in df:
print(x)
elif type(df) == dict:
for k in df.keys():
print(str(k) + ' ' + str(df[k]))
else:
print(df.to_string())
elif get_dataelements_brainvols:
brainvol = GetBrainVolumeDataElements(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
brainvol.to_csv(output_file)
else:
print(brainvol.to_string())
elif get_brainvols:
brainvol = GetBrainVolumes(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
brainvol.to_csv(output_file)
else:
print(brainvol.to_string())
else:
#read query from text fiile
with open(query_file, 'r') as fp:
query = fp.read()
df = sparql_query_nidm(nidm_file_list.split(','), query, output_file)
if ((output_file) is None):
print(df.to_string())
return df
def query(nidm_file_list, cde_file_list, query_file, output_file, get_participants, get_instruments, get_instrument_vars, get_dataelements, get_brainvols,get_dataelements_brainvols, uri, j, verbosity):
"""
This function provides query support for NIDM graphs.
"""
#query result list
results = []
# if there is a CDE file list, seed the CDE cache
if cde_file_list:
getCDEs(cde_file_list.split(","))
if get_participants:
df = GetParticipantIDs(nidm_file_list.split(','),output_file=output_file)
if ((output_file) is None):
print(df.to_string())
return df
elif get_instruments:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count=1
for project in project_list:
if count == 1:
df = GetProjectInstruments(nidm_file_list.split(','),project_id=project)
count+=1
else:
df = df.append(GetProjectInstruments(nidm_file_list.split(','),project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
#with open(output_file,'w') as myfile:
# wr=csv.writer(myfile,quoting=csv.QUOTE_ALL)
# wr.writerow(df)
#pd.DataFrame.from_records(df,columns=["Instruments"]).to_csv(output_file)
else:
print(df.to_string())
elif get_instrument_vars:
#first get all project UUIDs then iterate and get instruments adding to output dataframe
project_list = GetProjectsUUID(nidm_file_list.split(','))
count=1
for project in project_list:
if count == 1:
df = GetInstrumentVariables(nidm_file_list.split(','),project_id=project)
count+=1
else:
df = df.append(GetInstrumentVariables(nidm_file_list.split(','),project_id=project))
#write dataframe
#if output file parameter specified
if (output_file is not None):
df.to_csv(output_file)
else:
print(df.to_string())
elif get_dataelements:
datael = GetDataElements(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
datael.to_csv(output_file)
else:
print(datael.to_string())
elif uri:
restParser = RestParser(verbosity_level = int(verbosity))
if j:
restParser.setOutputFormat(RestParser.JSON_FORMAT)
else:
restParser.setOutputFormat(RestParser.CLI_FORMAT)
df = restParser.run(nidm_file_list.split(','), uri)
print (df)
elif get_dataelements_brainvols:
brainvol = GetBrainVolumeDataElements(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
brainvol.to_csv(output_file)
else:
print(brainvol.to_string())
elif get_brainvols:
brainvol = GetBrainVolumes(nidm_file_list=nidm_file_list)
#if output file parameter specified
if (output_file is not None):
brainvol.to_csv(output_file)
else:
print(brainvol.to_string())
elif query_file:
df = sparql_query_nidm(nidm_file_list.split(','),query_file,output_file)
if ((output_file) is None):
print(df.to_string())
return df
else:
print("ERROR: No query parameter provided. See help:")
print()
os.system("pynidm query --help")
exit(1)