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Software for evaluating quality of ACTRIS-Cloudnet data products.
$ pip3 install cloudnetpy-qc
import json
from cloudnetpy_qc import quality
site_meta = {"latitude": 61.844, "longitude": 24.287, "altitude": 150}
report = quality.run_tests('cloudnet-file.nc', site_meta)
json_object = json.dumps(report.to_dict(), indent=2)
print(json_object)
timestamp
: UTC timestamp of the testqcVersion
: cloudnetpy-qc
versiontests
: Test[]
data_coverage
: floatTest
testId
: Unique name of the testexceptions
: Exception[]
Exception
message
: Free-form message about the exceptionresult
: "info"
, "error"
or "warning"
{
"timestamp": "2022-10-13T07:00:26.906815Z",
"qcVersion": "1.1.2",
"tests": [
{
"testId": "TestUnits",
"exceptions": []
},
{
"testId": "TestInstrumentPid",
"exceptions": [
{
"message": "Instrument PID is missing.",
"result": "warning"
}
]
},
{
"testId": "TestTimeVector",
"exceptions": []
},
{
"testId": "TestVariableNames",
"exceptions": []
},
{
"testId": "TestCFConvention",
"exceptions": []
}
]
}
Test | Description |
---|---|
FindAttributeOutliers | Find suspicious values in global attributes. |
FindFolding | Test for radar folding. |
FindVariableOutliers | Find suspicious data values. |
TestBrightnessTemperature | Test that brightness temperature data are valid. |
TestCFConvention | Test compliance with the CF metadata conventions. |
TestComment | Check that variables have expected comments. |
TestCoordinateVariables | Test dimensions of coordinate variables are correct. |
TestCoordinates | Check that file coordinates match site coordinates. |
TestDataCoverage | Test that file contains enough data. |
TestDataModel | Test netCDF data model. |
TestDataTypes | Check that variables have expected data types. |
TestFillValue | Test that fill value is explicitly set for variables with missing data. |
TestFloatingPointValues | Test for special floating-point values which may indicate problems with the processing. |
TestGlobalAttributes | Check that file contains required global attributes. |
TestIfRangeCorrected | Test that beta is range corrected. |
TestInstrumentPid | Test that valid instrument PID exists. |
TestLDR | Test that LDR values are proper. |
TestLidarBeta | Test that one beta variable exists. |
TestLongNames | Check that variables have expected long names. |
TestMWRMultiTemperature | Test that temperature data are valid. |
TestMWRSingleLWP | Test that LWP data are valid. |
TestMask | Test that data are not completely masked. |
TestMedianLwp | Test that LWP data are valid. |
TestModelData | Test that model data are valid. |
TestRainfallConsistency | Test that precipitation rate and amount are consistent. |
TestStandardNames | Check that variable have expected standard names. |
TestTimeVector | Test that time vector is continuous. |
TestUnexpectedMask | Test if data contain unexpected masked values. |
TestUnits | Check that variables have expected units. |
TestVariableNames | Check that file contains required variables. |
TestVariableNamesDefined | Check that variables have expected names. |
TestZenithAngle | Test lidar zenith angle. |
MIT
FAQs
Quality control routines for CloudnetPy products
We found that cloudnetpy-qc demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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