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test_basiccsv.py
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test_basiccsv.py
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import pytest
from tests.utils import (
datagram_from_input,
standard_datagram_test,
pars_datagram_test,
)
@pytest.mark.parametrize(
"input, ts",
[
(
{ # ts0 - units on 2nd line, correct number of rows, correct value, sigma from d.p.
"case": "case_uts_units.csv"
},
{
"nsteps": 1,
"step": 0,
"nrows": 6,
"point": 0,
"pars": {"flow": {"sigma": 0.1, "value": 15.0, "unit": "ml/min"}},
},
),
(
{ # ts1 - timestamp from uts and index
"case": "case_uts_units.csv",
"parameters": {"timestamp": {"uts": {"index": 0}}},
},
{
"nsteps": 1,
"step": 0,
"nrows": 6,
"point": 2,
"pars": {"uts": {"value": 1631626610.0}},
},
),
(
{ # ts2 - semicolon separator, sigmas from decimal places
"case": "case_timestamp.ssv",
"parameters": {
"sep": ";",
"units": {"flow": "ml/min", "T": "K", "p": "atm"},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 3,
"point": 0,
"pars": {
"flow": {"sigma": 0.1, "value": 15.0, "unit": "ml/min"},
"T": {"sigma": 0.1, "value": 23.1, "unit": "K"},
"p": {"sigma": 0.0001, "value": 1.0001, "unit": "atm"},
},
},
),
(
{ # ts3 - semicolon separator, timestamp from timestamp and index
"case": "case_timestamp.ssv",
"parameters": {
"sep": ";",
"units": {"flow": "ml/min", "T": "K", "p": "atm"},
"timestamp": {"timestamp": {"index": 0}},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 3,
"point": 1,
"pars": {"uts": {"value": 1631284345.0}},
},
),
(
{ # ts4 - tab separator
"case": "case_custom_ts.tsv",
"parameters": {
"sep": "\t",
"timestamp": {
"timestamp": {"index": 1, "format": "%d.%m.%Y %I:%M:%S%p"}
},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 5,
"point": 3,
"pars": {"T": {"value": 351.2, "sigma": 0.1, "unit": "K"}},
},
),
(
{ # ts5 - tab separator, timestamp from timestamp, format, index
"case": "case_custom_ts.tsv",
"parameters": {
"sep": "\t",
"timestamp": {
"timestamp": {"index": 1, "format": "%d.%m.%Y %I:%M:%S%p"}
},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 5,
"point": 4,
"pars": {"uts": {"value": 1631280585.0}},
},
),
(
{ # ts6 - tab separator, timestamp from timestamp, format, index
"case": "case_custom_ts.tsv",
"parameters": {
"sep": "\t",
"timestamp": {
"timestamp": {"index": 1, "format": "%d.%m.%Y %I:%M:%S%p"}
},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 5,
"point": 2,
"pars": {"uts": {"value": 1631276985.0}},
},
),
(
{ # ts7 - tab separator, timestamp from timestamp, format, index
"case": "case_custom_ts.tsv",
"parameters": {
"sep": "\t",
"timestamp": {
"timestamp": {"index": 1, "format": "%d.%m.%Y %I:%M:%S%p"}
},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 5,
"point": 0,
"pars": {"uts": {"value": 1631273385.0}},
},
),
(
{ # ts8 - tab separator, timestamp from iso date and iso time
"case": "case_date_time_iso.csv",
"parameters": {
"timestamp": {"date": {"index": 0}, "time": {"index": 1}}
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 4,
"point": 1,
"pars": {"uts": {"value": 1610659800.0}},
},
),
(
{ # ts9 - timestamp from time with external date only
"case": "case_time_custom.csv",
"parameters": {
"timestamp": {"time": {"index": 0, "format": "%I.%M%p"}}
},
"externaldate": {"from": {"isostring": "2021-01-01"}},
},
{
"nsteps": 1,
"step": 0,
"nrows": 3,
"point": 0,
"pars": {"uts": {"value": 1609502340.0}},
},
),
(
{ # ts10 - timestamp from time with custom format only
"case": "case_time_custom.csv",
"parameters": {
"timestamp": {"time": {"index": 0, "format": "%I.%M%p"}}
},
"externaldate": {"from": {"utsoffset": 0.0}},
},
{
"nsteps": 1,
"step": 0,
"nrows": 3,
"point": 1,
"pars": {"uts": {"value": 43200}},
},
),
(
{ # ts11 - convert functionality test
"case": "case_timestamp.ssv",
"parameters": {
"sep": ";",
"units": {"flow": "ml/min", "T": "K", "p": "atm"},
"convert": {
"flow": {
"flow": {
"calib": {"linear": {"slope": 1e-6 / 60}, "atol": 1e-8}
},
"unit": "m^3/s",
}
},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 3,
"point": 0,
"pars": {
"flow": {
"sigma": 1e-8,
"value": 2.5e-7,
"unit": "m^3/s",
"raw": False,
},
},
},
),
(
{ # ts12 - convert functionality with intercept only and both global and calib sigma
"case": "case_uts_units.csv",
"parameters": {
"convert": {
"T": {
"T": {
"calib": {"linear": {"intercept": 273.15}, "atol": 0.5}
},
"unit": "K",
}
},
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 6,
"point": 0,
"pars": {
"T": {"sigma": 0.5, "value": 296.25, "unit": "K", "raw": False},
},
},
),
(
{ # ts13 - calfile functionality
"case": "case_uts_units.csv",
"parameters": {"calfile": "calibrations/test_calib.json"},
},
{
"nsteps": 1,
"step": 0,
"nrows": 6,
"point": 0,
"pars": {
"T": {"sigma": 0.1, "value": 296.25, "unit": "K", "raw": False}
},
},
),
(
{ # ts14 - calfile functionality with fractions and total
"case": "data_3.1.0/00-experiment/measurement.csv",
"parameters": {
"sep": ";",
"timestamp": {
"timestamp": {"index": 0, "format": "%Y-%m-%d-%H-%M-%S"}
},
"calfile": "calibrations/fhi_tfcal.json",
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 1662,
"point": 0,
"pars": {
"C3H8": {
"sigma": 0.002,
"value": 0.000,
"unit": "ml/min",
"raw": False,
},
"N2": {
"sigma": 0.01351715237,
"value": 30.36065211976,
"unit": "ml/min",
"raw": False,
},
"O2": {
"sigma": 0.01092061507,
"value": 1.57860743175,
"unit": "ml/min",
"raw": False,
},
"Total": {
"sigma": 0.0323269088,
"value": 31.9392595515,
"unit": "ml/min",
"raw": False,
},
},
},
),
(
{ # ts15 - calfile functionality with fractions and total
"case": "data_3.1.0/00-experiment/measurement.csv",
"parameters": {
"sep": ";",
"timestamp": {
"timestamp": {"index": 0, "format": "%Y-%m-%d-%H-%M-%S"}
},
"calfile": "calibrations/fhi_tfcal.json",
},
},
{
"nsteps": 1,
"step": 0,
"nrows": 1662,
"point": 100,
"pars": {
"C3H8": {
"sigma": 0.00157299296,
"value": 1.20450873872,
"unit": "ml/min",
"raw": False,
},
"N2": {
"sigma": 0.01258182490,
"value": 35.1460003698,
"unit": "ml/min",
"raw": False,
},
"O2": {
"sigma": 0.01092061507,
"value": 3.57707998956,
"unit": "ml/min",
"raw": False,
},
"Total": {
"sigma": 0.03683714813,
"value": 39.9275890981,
"unit": "ml/min",
"raw": False,
},
},
},
),
],
)
def test_datagram_from_basiccsv(input, ts, datadir):
ret = datagram_from_input(input, "basiccsv", datadir)
standard_datagram_test(ret, ts)
pars_datagram_test(ret, ts)