removing notices

This commit is contained in:
Andy Eschbacher
2016-09-02 17:58:19 -04:00
parent feab6f177e
commit 6d6d7ef2ba

View File

@@ -30,17 +30,13 @@ def moran(subquery, attr_name,
query = pu.construct_neighbor_query(w_type, qvals)
plpy.notice('** Query: %s' % query)
try:
result = plpy.execute(query)
# if there are no neighbors, exit
if len(result) == 0:
return pu.empty_zipped_array(2)
plpy.notice('** Query returned with %d rows' % len(result))
except plpy.SPIError, e:
plpy.error('Analysis failed: %s' % e)
plpy.notice('** Query failed: "%s"' % query)
return pu.empty_zipped_array(2)
## collect attributes
@@ -80,7 +76,6 @@ def moran_local(subquery, attr,
return pu.empty_zipped_array(5)
except plpy.SPIError, e:
plpy.error('Analysis failed: %s' % e)
plpy.notice('** Query failed: "%s"' % query)
return pu.empty_zipped_array(5)
attr_vals = pu.get_attributes(result)
@@ -110,17 +105,13 @@ def moran_rate(subquery, numerator, denominator,
query = pu.construct_neighbor_query(w_type, qvals)
plpy.notice('** Query: %s' % query)
try:
result = plpy.execute(query)
# if there are no neighbors, exit
if len(result) == 0:
return pu.empty_zipped_array(2)
plpy.notice('** Query returned with %d rows' % len(result))
except plpy.SPIError, e:
plpy.error('Analysis failed: %s' % e)
plpy.notice('** Query failed: "%s"' % query)
return pu.empty_zipped_array(2)
## collect attributes
@@ -160,7 +151,6 @@ def moran_local_rate(subquery, numerator, denominator,
return pu.empty_zipped_array(5)
except plpy.SPIError, e:
plpy.error('Analysis failed: %s' % e)
plpy.notice('** Query failed: "%s"' % query)
return pu.empty_zipped_array(5)
## collect attributes
@@ -183,7 +173,6 @@ def moran_local_bv(subquery, attr1, attr2,
"""
Moran's I (local) Bivariate (untested)
"""
plpy.notice('** Constructing query')
qvals = OrderedDict([("id_col", id_col),
("attr1", attr1),
@@ -202,7 +191,6 @@ def moran_local_bv(subquery, attr1, attr2,
except plpy.SPIError:
plpy.error("Error: areas of interest query failed, " \
"check input parameters")
plpy.notice('** Query failed: "%s"' % query)
return pu.empty_zipped_array(4)
## collect attributes
@@ -216,13 +204,9 @@ def moran_local_bv(subquery, attr1, attr2,
lisa = ps.esda.moran.Moran_Local_BV(attr1_vals, attr2_vals, weight,
permutations=permutations)
plpy.notice("len of Is: %d" % len(lisa.Is))
# find clustering of significance
lisa_sig = quad_position(lisa.q)
plpy.notice('** Finished calculations')
return zip(lisa.Is, lisa_sig, lisa.p_sim, weight.id_order)
# Low level functions ----------------------------------------