def sample_metadata(v_sample):
"""MetaData for a given sample.
Args: Sample in the format: `BB_940`
Returns a json dictionary of sample metadata in the format
{
AGE: 24,
BBTYPE: "I",
ETHNICITY: "Caucasian",
GENDER: "F",
LOCATION: "Beaufort/NC",
SAMPLEID: 940
}
"""
list1 = sess.query(
c_samples_metadata.AGE,
c_samples_metadata.BBTYPE,
c_samples_metadata.ETHNICITY,
c_samples_metadata.GENDER,
c_samples_metadata.LOCATION, c_samples_metadata.SAMPLEID). \
filter(c_samples_metadata.SAMPLEID == func.replace(v_sample, 'BB_', ''))
d1 = {
'AGE': list1[0][0],
'BBTYPE': list1[0][1],
'ETHNICITY': list1[0][2],
'GENDER': list1[0][3],
'LOCATION': list1[0][4],
'SAMPLEID': list1[0][5]
}
return jsonify(d1)
def wfreq(v_sample):
"""Weekly Washing Frequency as a number.
Args: Sample in the format: `BB_940`
Returns an integer value for the weekly washing frequency `WFREQ`
"""
r1 = sess.query(c_samples_metadata.WFREQ). \
filter(c_samples_metadata.SAMPLEID == func.replace(v_sample, 'BB_', ''))
r2 = str(r1[0][0])
return r2
def otu():
"""List of OTU descriptions.
Returns a list of OTU descriptions in the following format
[
"Archaea;Euryarchaeota;Halobacteria;Halobacteriales;Halobacteriaceae;Halococcus",
"Archaea;Euryarchaeota;Halobacteria;Halobacteriales;Halobacteriaceae;Halococcus",
"Bacteria",
"Bacteria",
"Bacteria",
...
]
"""
list1 = sess.query(c_otu.lowest_taxonomic_unit_found). \
order_by(c_otu.lowest_taxonomic_unit_found). \
all()
r1 = [x[0] for x in list1]
return jsonify(r1)
def sample(v_sample):
"""OTU IDs and Sample Values for a given sample.
Sort your Pandas DataFrame (OTU ID and Sample Value)
in Descending Order by Sample Value
Return a list of dictionaries containing sorted lists for `otu_ids`
and `sample_values`
[
{
otu_ids: [
1166,
2858,
481,
...
],
sample_values: [
163,
126,
113,
...
]
}
]
"""
list_2d_statement = sess.query(
c_otu.lowest_taxonomic_unit_found, c_samples.otu_id, 'samples.' +
v_sample).filter(c_otu.otu_id == c_samples.otu_id).statement
df = pd.read_sql_query(list_2d_statement,
sess.bind).sort_values(['samples.' + v_sample],
ascending=False).head(10)
#otu_id samples.BB_943
l_otu_ids = [int(r['otu_id']) for i, r in df.iterrows()]
l_sample_values = [int(r['samples.' + v_sample]) for i, r in df.iterrows()]
l_otu_desc = [r['lowest_taxonomic_unit_found'] for i, r in df.iterrows()]
d1 = {
"otu_ids": l_otu_ids,
"sample_values": l_sample_values,
"otu_desc": l_otu_desc
}
print(d1)
return jsonify(d1)
def name():
"""List of sample names.
Returns a list of sample names in the format
[
"BB_940",
"BB_941",
"BB_943",
"BB_944",
"BB_945",
"BB_946",
"BB_947",
...
]
"""
list1 = sess.query( c_samples_metadata.SAMPLEID). \
order_by(c_samples_metadata.SAMPLEID). \
all()
r1 = ['BB_' + str(x[0]) for x in list1]
return jsonify(r1)