def conceptPatientCount(self, top: pd.DataFrame, c_fullname: str, lc: LoggedConnection,
# Moderate degree to support work on several tables in parallel.
parallel_degree: int=8) -> int:
counts = read_sql_step(
'''
select /*+ parallel({degree}) */
c_fullname, c_hlevel, c_visualattributes, c_name
, case
when upper(meta.c_visualattributes) like 'C%'
then :sentinel * 1
when lower(meta.c_tablename) <> 'concept_dimension'
or lower(meta.c_operator) <> 'like'
or lower(meta.c_facttablecolumn) <> 'concept_cd'
then :sentinel * 2
else coalesce((
select count(distinct obs.patient_num)
from (
select concept_cd
from {i2b2star}.concept_dimension
where concept_path like (meta.c_dimcode || '%')
) cd
join {i2b2star}.observation_fact obs
on obs.concept_cd = cd.concept_cd), :sentinel * 3)
end c_totalnum
from {i2b2meta}.{table_name} meta
where c_synonym_cd = 'N'
and meta.c_fullname = :c_fullname
'''.strip().format(i2b2star=self.i2b2star,
i2b2meta=self.i2b2meta,
degree=parallel_degree,
table_name=top.c_table_name),
lc=lc, params=dict(c_fullname=c_fullname,
sentinel=self.sentinel)).set_index('c_fullname')
[count] = counts.c_totalnum.values
return int(count)
def topFolders(i2b2meta: str, lc: LoggedConnection) -> pd.DataFrame:
folders = read_sql_step('''
select c_table_cd, c_hlevel, c_visualattributes, c_name, upper(c_table_name) c_table_name, c_fullname
from {i2b2meta}.table_access ta
where upper(ta.c_visualattributes) like '_A%'
order by ta.c_name
'''.format(i2b2meta=i2b2meta).strip(), lc, {}).set_index('c_table_cd')
return folders
def cohorts(self, lc: et.LoggedConnection) -> pd.DataFrame:
cohorts = rif_etl.read_sql_step(
'''
select site_schema, result_instance_id, start_date, task_id, count(distinct patient_num)
from site_cohorts
group by site_schema, result_instance_id, start_date, task_id
order by start_date desc
''', lc)
cohorts = cohorts.append(
rif_etl.read_sql_step(
'''
select count(distinct site_schema) site_schema
, max(result_instance_id) result_instance_id
, max(start_date) start_date
, 'Total' task_id
, count(distinct patient_num)
from site_cohorts''', lc)).set_index('task_id')
return cohorts
def top(self, lc: LoggedConnection) -> pd.Series:
return read_sql_step('''
select c_table_cd, c_hlevel, c_visualattributes, c_name
, upper(c_table_name) c_table_name, c_fullname
from {i2b2meta}.table_access ta
where upper(ta.c_visualattributes) like '_A%'
and ta.c_table_cd = :c_table_cd
'''.format(i2b2meta=self.i2b2meta).strip(),
lc, dict(c_table_cd=self.c_table_cd)).set_index('c_table_cd').iloc[0]
def uploads(self, lc: et.LoggedConnection) -> pd.DataFrame:
return rif_etl.read_sql_step(
'''
select *
from upload_status up
where load_status like 'OK%' and ((
loaded_record > 0
and substr(transform_name, -11) in (
select distinct task_id from site_cohorts
)
) or (
upload_label like 'migrate obs%'
) or (
message like 'UP#%' and upload_label like '% #1 of 1%'
))
order by load_date desc
''', lc).set_index('upload_id')
def activeDescendants(self, lc: LoggedConnection) -> pd.DataFrame:
top = self.top(lc)
desc = read_sql_step(
'''
select c_fullname, c_hlevel, c_visualattributes, c_totalnum, c_name, c_tooltip
from {i2b2meta}.{meta_table} meta
where meta.c_hlevel > :c_hlevel
and meta.c_fullname like (:c_fullname || '%')
and upper(meta.c_visualattributes) like '_A%'
and c_synonym_cd = 'N'
and m_applied_path = '@'
order by meta.c_hlevel, upper(meta.c_name)
'''.format(i2b2meta=self.i2b2meta,
meta_table=top.c_table_name).strip(),
lc=lc,
params=dict(c_fullname=top.c_fullname, c_hlevel=int(top.c_hlevel))).set_index('c_fullname')
return desc
def inclusion_criteria(self, lc: et.LoggedConnection) -> pd.DataFrame:
# ISSUE: sync with build_cohort.sql?
# ISSUE: left out 'NAACCR|400:C509'
return rif_etl.read_sql_step(
'''
select concept_cd, min(name_char) name_char
from blueherondata_kumc_calamus.concept_dimension
where concept_cd in (
'SEER_SITE:26000',
'NAACCR|400:C500',
'NAACCR|400:C501',
'NAACCR|400:C502',
'NAACCR|400:C503',
'NAACCR|400:C504',
'NAACCR|400:C505',
'NAACCR|400:C506',
'NAACCR|400:C507',
'NAACCR|400:C508',
'NAACCR|400:C509'
)
group by concept_cd
order by concept_cd
''', lc).set_index('concept_cd')
