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Dev #55

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Dev #55

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6ba56d6
Updates
jr3cermak Apr 13, 2024
0d109a3
Fixes
jr3cermak May 1, 2024
ec50124
Updates
jr3cermak May 1, 2024
8f615c3
run pre-commit on new changes only
ocefpaf May 23, 2024
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62 changes: 44 additions & 18 deletions cc_plugin_glider/glider_dac.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,9 @@ class GliderCheck(BaseNCCheck):
_cc_display_headers = {3: "Required", 2: "Recommended", 1: "Suggested"}
acceptable_platform_types = {"Seaglider", "Spray Glider", "Slocum Glider"}

def __init__(self):
def __init__(self, options=None):
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@jr3cermak do you want a generic options kw or should we name this skip_variables? I may not be understanding what you want to do but it seems that it is the latter, right?

# Pass through testing options for gliderdac
self.options = options
# try to get the sea names table
ncei_base_table_url = "https://gliders.ioos.us/ncei_authority_tables/"
# might refactor if the authority tables names change
Expand Down Expand Up @@ -201,7 +203,11 @@ def check_lat_lon_attributes(self, dataset):

check_vars = ["lat", "lon"]
for var in check_vars:
stat, num_checks, msgs = util._check_variable_attrs(dataset, var)
stat, num_checks, msgs = util._check_variable_attrs(
dataset,
var,
options=self.options,
)
score += int(stat)
out_of += num_checks
messages.extend(msgs)
Expand Down Expand Up @@ -236,7 +242,11 @@ def check_pressure_depth_attributes(self, dataset):

check_vars = ["pressure", "depth"]
for var in check_vars:
stat, num_checks, msgs = util._check_variable_attrs(dataset, var)
stat, num_checks, msgs = util._check_variable_attrs(
dataset,
var,
options=self.options,
)
score += int(stat)
out_of += num_checks
messages.extend(msgs)
Expand All @@ -261,7 +271,11 @@ def check_ctd_variable_attributes(self, dataset):

check_vars = ["temperature", "conductivity", "salinity", "density"]
for var in check_vars:
stat, num_checks, msgs = util._check_variable_attrs(dataset, var)
stat, num_checks, msgs = util._check_variable_attrs(
dataset,
var,
options=self.options,
)
score += int(stat)
out_of += num_checks
messages.extend(msgs)
Expand Down Expand Up @@ -289,7 +303,11 @@ def check_profile_variable_attributes_and_types(self, dataset):
"v",
]
for var in check_vars:
stat, num_checks, msgs = util._check_variable_attrs(dataset, var)
stat, num_checks, msgs = util._check_variable_attrs(
dataset,
var,
options=self.options,
)
score += int(stat)
out_of += num_checks
messages.extend(msgs)
Expand Down Expand Up @@ -596,7 +614,11 @@ def check_container_variables(self, dataset):
"instrument_ctd",
]
for var in check_vars:
stat, num_checks, msgs = util._check_variable_attrs(dataset, var)
stat, num_checks, msgs = util._check_variable_attrs(
dataset,
var,
options=self.options,
)
score += int(stat)
out_of += num_checks
messages.extend(msgs)
Expand Down Expand Up @@ -653,8 +675,7 @@ def check_qartod(self, dataset):
dtype = flag_values.dtype
test_ctx.assert_true(
util.compare_dtype(dtype, np.dtype("|i1")),
f"attribute {qartod_var}:flag_values has an illegal data-type, must "
"be byte",
f"attribute {qartod_var}:flag_values has an illegal data-type, must be byte",
)

valid_min_dtype = getattr(valid_min, "dtype", None)
Expand Down Expand Up @@ -692,10 +713,7 @@ def check_ancillary_variables(self, dataset):
test = acv in dataset.variables
score += int(test)
if not test:
msg = (
f"Invalid ancillary_variables attribute for {var}, "
f"{acv} is not a variable"
)
msg = f"Invalid ancillary_variables attribute for {var}, {acv} is not a variable"
messages.append(msg)

return self.make_result(level, score, out_of, "Ancillary Variables", messages)
Expand Down Expand Up @@ -746,8 +764,7 @@ def check_valid_min_dtype(self, dataset):
if valid_min is not None:
test_ctx.assert_true(
util.compare_dtype(np.dtype(valid_min_dtype), ncvar.dtype),
f"{var_name}:valid_min has a different data type, {valid_min_dtype}, than variable {var_name}, "
f"{str(ncvar.dtype)}",
f"{var_name}:valid_min has a different data type, {valid_min_dtype}, than variable {var_name}, {ncvar.dtype}",
)

return test_ctx.to_result()
Expand All @@ -774,8 +791,7 @@ def check_valid_max_dtype(self, dataset):
if valid_max is not None:
test_ctx.assert_true(
util.compare_dtype(np.dtype(valid_max_dtype), ncvar.dtype),
f"{var_name}:valid_max has a different data type, {valid_max_dtype}, than variable {str(ncvar.dtype)} "
f"{var_name}",
f"{var_name}:valid_max has a different data type, {valid_max_dtype}, than variable {ncvar.dtype} {var_name}",
)

return test_ctx.to_result()
Expand Down Expand Up @@ -814,8 +830,18 @@ def check_valid_lon(self, dataset):
return

longitude = dataset.variables["lon"]
valid_min = longitude.valid_min
valid_max = longitude.valid_max
valid_min = getattr(longitude, "valid_min", None)
if valid_min is None:
test_ctx.assert_true(
False,
"valid_min attribute for longitude should be defined",
)
valid_max = getattr(longitude, "valid_max", None)
if valid_min is None:
test_ctx.assert_true(
False,
"valid_max attribute for longitude should be defined",
)
test_ctx.assert_true(
not (valid_min == -90 and valid_max == 90),
"Longitude's valid_min and valid_max are [-90, 90], it's likely this was a mistake",
Expand Down
7 changes: 5 additions & 2 deletions cc_plugin_glider/util.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ def _check_dtype(dataset, var_name):
if not compare_dtype(var.dtype, np.dtype(expected_dtype)):
messages.append(
f"Variable {var_name} is expected to have a dtype of "
f"{var.dtype}, instead has a dtype of {expected_dtype}"
f"{expected_dtype}, instead has a dtype of {var.dtype}"
"",
)
score -= 1
Expand All @@ -58,7 +58,7 @@ def _check_dtype(dataset, var_name):
return (score, out_of, messages)


def _check_variable_attrs(dataset, var_name, required_attributes=None):
def _check_variable_attrs(dataset, var_name, required_attributes=None, options=None):
"""
Convenience method to check a variable attributes based on the
expected_vars dict
Expand All @@ -74,6 +74,9 @@ def _check_variable_attrs(dataset, var_name, required_attributes=None):

# Get the expected attrs to check
check_attrs = required_attributes or required_var_attrs.get(var_name, {})
if not options is None:
if "ancillary_variables" in check_attrs and "no_ancillary_variables" in options:
del check_attrs["ancillary_variables"]
var_attrs = set(var.ncattrs())
for attr in check_attrs:
if attr == "dtype":
Expand Down
9 changes: 9 additions & 0 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,15 @@ tag_regex = "^(?P<prefix>v)?(?P<version>[^\\+]+)(?P<suffix>.*)?$"
target-version = "py38"
line-length = 79

lint.select = [
"A", # flake8-builtins
"B", # flake8-bugbear
"C4", # flake8-comprehensions
"F", # flakes
"I", # import sorting
"T20", # flake8-print
"UP", # upgrade
]
select = [
"A", # flake8-builtins
"B", # flake8-bugbear
Expand Down
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