def test_check_dataset_attrs_car_attrs_good(capsys, nc_dataset):
"""check_dataset_attrs prints nothing when reqd var attrs present w/ values
"""
dataset_attrs = (
('Conventions', 'CF-1.6'),
('title', 'Test Dataset'),
('institution', 'Unit Tests'),
('source', 'foo'),
('references', 'bar'),
('history', 'was'),
('comment', ''),
)
for attr, value in dataset_attrs:
nc_dataset.setncattr(attr, value)
nc_dataset.createDimension('x', 42)
foo = nc_dataset.createVariable('foo', float, ('x', ))
reqd_attrs = (
('units', 'foo'),
('long_name', 'bar'),
)
for attr, value in reqd_attrs:
foo.setncattr(attr, value)
nc_tools.check_dataset_attrs(nc_dataset)
out, err = capsys.readouterr()
assert out == ''
def test_check_dataset_attrs_reqd_var_attr_values(capsys, nc_dataset):
"""check_dataset_attrs warns of missing reqd variable attr values
"""
dataset_attrs = (
('Conventions', 'CF-1.6'),
('title', 'Test Dataset'),
('institution', 'Unit Tests'),
('source', 'foo'),
('references', 'bar'),
('history', 'was'),
('comment', ''),
)
for attr, value in dataset_attrs:
nc_dataset.setncattr(attr, value)
nc_dataset.createDimension('x', 42)
foo = nc_dataset.createVariable('foo', float, ('x', ))
reqd_attrs = (
'units',
'long_name',
)
for attr in reqd_attrs:
foo.setncattr(attr, '')
nc_tools.check_dataset_attrs(nc_dataset)
out, err = capsys.readouterr()
for line, expected in enumerate(reqd_attrs):
assert out.splitlines()[line] == (
'Missing value for variable attribute for foo: {}'.format(expected)
)
def test_check_dataset_attrs_good(capsys, nc_dataset):
"""check_dataset_attrs prints nothing when all reqd attts present w/ value
"""
dataset_attrs = (
('Conventions', 'CF-1.6'),
('title', 'Test Dataset'),
('institution', 'Unit Tests'),
('source', 'foo'),
('references', 'bar'),
('history', 'was'),
('comment', ''),
)
for attr, value in dataset_attrs:
nc_dataset.setncattr(attr, value)
nc_tools.check_dataset_attrs(nc_dataset)
out, err = capsys.readouterr()
assert out == ''
def test_check_dataset_attrs_reqd_dataset_attrs(capsys, nc_dataset):
"""check_dataset_attrs warns of missing required dataset attributes
"""
nc_tools.check_dataset_attrs(nc_dataset)
out, err = capsys.readouterr()
reqd_attrs = (
'Conventions',
'title',
'institution',
'source',
'references',
'history',
'comment',
)
for line, expected in enumerate(reqd_attrs):
assert out.splitlines()[line] == (
'Missing required dataset attribute: {}'.format(expected))
def test_check_dataset_attrs_reqd_dataset_attr_values(capsys, nc_dataset):
"""check_dataset_attrs warns of missing reqd dataset attr values
"""
reqd_attrs = (
'Conventions',
'title',
'institution',
'source',
'references',
'history',
)
for attr in reqd_attrs:
nc_dataset.setncattr(attr, '')
nc_tools.check_dataset_attrs(nc_dataset)
out, err = capsys.readouterr()
for line, attr in enumerate(reqd_attrs):
assert out.splitlines()[line] == (
'Missing value for dataset attribute: {}'.format(attr))
def test_check_dataset_attrs_url_reqd(capsys, nc_dataset):
"""check_dataset_attrs warns of source or references set to REQUIRED
"""
empty_reqd_attrs = (
'Conventions',
'title',
'institution',
'references',
)
for attr in empty_reqd_attrs:
nc_dataset.setncattr(attr, 'foo')
REQUIRED_reqd_attrs = (
'source',
'references',
)
for attr in REQUIRED_reqd_attrs:
nc_dataset.setncattr(attr, 'REQUIRED')
nc_tools.check_dataset_attrs(nc_dataset)
out, err = capsys.readouterr()
for line, attr in enumerate(REQUIRED_reqd_attrs):
assert out.splitlines()[line] == (
'Missing value for dataset attribute: {}'.format(attr))
def create_northern_tides_contd(Z1,
Z2,
tidevar,
constituent,
code,
name='SalishSea2'):
import netCDF4 as NC
import numpy as np
from salishsea_tools import nc_tools
nemo = NC.Dataset(name + '_' + code + '_North_tide_' + constituent +
'_grid_' + tidevar + '.nc',
'w',
zlib=True)
#start and end points
starti = 32
endi = 62
lengthi = endi - starti
# dataset attributes
nc_tools.init_dataset_attrs(
nemo,
title='Tidal Boundary Conditions for Northern Boundary',
notebook_name='johnstone_tides_contd',
nc_filepath=
'../../../NEMO-forcing/open_boundaries/north/tides/SalishSea2_North_tide_'
+ constituent + '_grid_' + tidevar + '.nc',
comment=
'Tidal current and amplitude data scaled based on differences between K1/M2 and North observations and webtide.'
)
# dimensions (only need x and y, don't need depth or time_counter)
nemo.createDimension('xb', lengthi)
nemo.createDimension('yb', 1)
# variables
# nbidta, ndjdta, ndrdta
nbidta = nemo.createVariable('nbidta', 'int32', ('yb', 'xb'))
nbidta.long_name = 'i grid position'
nbidta.units = 1
nbjdta = nemo.createVariable('nbjdta', 'int32', ('yb', 'xb'))
nbjdta.long_name = 'j grid position'
nbjdta.units = 1
nbrdta = nemo.createVariable('nbrdta', 'int32', ('yb', 'xb'))
nbrdta.long_name = 'position from boundary'
nbrdta.units = 1
print(nbidta.shape)
# add in the counter around the boundary (taken from Susan's code in Prepare Tide Files)
xb = nemo.createVariable('xb', 'int32', ('xb', ), zlib=True)
xb.units = 'non dim'
xb.long_name = 'counter around boundary'
yb = nemo.createVariable('yb', 'int32', ('yb', ), zlib=True)
yb.units = 'non dim'
yb.long_name = 'counter along boundary'
yb[0] = 897
xb[:] = np.arange(starti, endi)
# values
# nbidta, nbjdta
nbidta[:] = np.arange(starti, endi)
nbjdta[:] = 897
nbrdta[:] = 1
if tidevar == 'T':
z1 = nemo.createVariable('z1', 'float32', ('yb', 'xb'), zlib=True)
z1.units = 'm'
z1.long_name = 'tidal elevation: cosine'
z2 = nemo.createVariable('z2', 'float32', ('yb', 'xb'), zlib=True)
z2.units = 'm'
z2.long_name = 'tidal elevation: sine'
z1[0, :] = np.array([Z1] * lengthi)
z2[0, :] = np.array([Z2] * lengthi)
if tidevar == 'U':
u1 = nemo.createVariable('u1', 'float32', ('yb', 'xb'), zlib=True)
u1.units = 'm'
u1.long_name = 'tidal x-velocity: cosine'
u2 = nemo.createVariable('u2', 'float32', ('yb', 'xb'), zlib=True)
u2.units = 'm'
u2.long_name = 'tidal x-velocity: sine'
u1[0, 0:lengthi] = Z1[:, 0]
u2[0, 0:lengthi] = Z2[:, 0]
if tidevar == 'V':
v1 = nemo.createVariable('v1', 'float32', ('yb', 'xb'), zlib=True)
v1.units = 'm'
v1.long_name = 'tidal y-velocity: cosine'
v2 = nemo.createVariable('v2', 'float32', ('yb', 'xb'), zlib=True)
v2.units = 'm'
v2.long_name = 'tidal y-velocity: sine'
v1[0, 0:lengthi] = Z1[:, 0]
v2[0, 0:lengthi] = Z2[:, 0]
nc_tools.check_dataset_attrs(nemo)
nemo.close()
