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Add minimal tests to to_* methods of dataset and cache for 2D case
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@astafan8 @jenshnielsen
astafan8 authored and jenshnielsen committed Feb 15, 2023
1 parent 73c352f commit 3d4c0f2
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186 changes: 186 additions & 0 deletions qcodes/tests/dataset/test_data_set_cache.py
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Expand Up @@ -4,7 +4,9 @@

import hypothesis.strategies as hst
import numpy as np
import pandas
import pytest
import xarray
from hypothesis import HealthCheck, given, settings

from qcodes.dataset.descriptions.detect_shapes import detect_shape_of_measurement
Expand Down Expand Up @@ -790,6 +792,171 @@ def test_cache_2d_shape(experiment,
clip=cache_size == "too_large")


@pytest.mark.parametrize("bg_writing", [True, False])
@pytest.mark.parametrize("in_memory_cache", [True, False])
@settings(deadline=None, max_examples=5,
suppress_health_check=(HealthCheck.function_scoped_fixture,))
@given(n_points_outer=hst.integers(min_value=1, max_value=11),
n_points_inner=hst.integers(min_value=1, max_value=11))
def test_cache_2d_to_dataframe_dict_and_dataframe(
experiment, DAC, DMM, n_points_outer, n_points_inner, bg_writing,
channel_array_instrument, in_memory_cache
):
meas = Measurement()

meas.register_parameter(DAC.ch1)
meas.register_parameter(DAC.ch2)

meas_parameters = (DMM.v1,
channel_array_instrument.A.dummy_multi_parameter,
channel_array_instrument.A.dummy_scalar_multi_parameter,
channel_array_instrument.A.dummy_2d_multi_parameter,
channel_array_instrument.A.dummy_2d_multi_parameter_2,
channel_array_instrument.A.dummy_array_parameter,
channel_array_instrument.A.dummy_complex_array_parameter,
channel_array_instrument.A.dummy_complex,
channel_array_instrument.A.dummy_parameter_with_setpoints,
channel_array_instrument.A.dummy_parameter_with_setpoints_complex,
)
channel_array_instrument.A.dummy_start(0)
channel_array_instrument.A.dummy_stop(10)
channel_array_instrument.A.dummy_n_points(10)
for param in meas_parameters:
meas.register_parameter(param, setpoints=(DAC.ch1, DAC.ch2))
n_rows_written = 0
with meas.run(
write_in_background=bg_writing,
in_memory_cache=in_memory_cache) as datasaver:
dataset = datasaver.dataset

_assert_dataframe_dicts_are_identical(
dataset.to_pandas_dataframe_dict(),
dataset.cache.to_pandas_dataframe_dict()
)

pandas.testing.assert_frame_equal(
dataset.to_pandas_dataframe(),
dataset.cache.to_pandas_dataframe()
)

for v1 in np.linspace(-1, 1, n_points_outer):
for v2 in np.linspace(-1, 1, n_points_inner):
DAC.ch1.set(v1)
DAC.ch2.set(v2)
meas_vals = [(param, param.get()) for param in meas_parameters[:-2]]
meas_vals += expand_setpoints_helper(meas_parameters[-2])
meas_vals += expand_setpoints_helper(meas_parameters[-1])

datasaver.add_result((DAC.ch1, v1),
(DAC.ch2, v2),
*meas_vals)
datasaver.flush_data_to_database(block=True)
n_rows_written += 1

_assert_dataframe_dicts_are_identical(
dataset.to_pandas_dataframe_dict(),
dataset.cache.to_pandas_dataframe_dict()
)

pandas.testing.assert_frame_equal(
dataset.to_pandas_dataframe(),
dataset.cache.to_pandas_dataframe()
)

_assert_dataframe_dicts_are_identical(
dataset.to_pandas_dataframe_dict(),
dataset.cache.to_pandas_dataframe_dict()
)

pandas.testing.assert_frame_equal(
dataset.to_pandas_dataframe(),
dataset.cache.to_pandas_dataframe()
)


@pytest.mark.parametrize("bg_writing", [True, False])
@pytest.mark.parametrize("in_memory_cache", [True, False])
@settings(deadline=None, max_examples=5,
suppress_health_check=(HealthCheck.function_scoped_fixture,))
@given(n_points_outer=hst.integers(min_value=1, max_value=11),
n_points_inner=hst.integers(min_value=1, max_value=11))
def test_cache_2d_to_xarray_dataarray_dict_and_xarray_dataset(
experiment, DAC, DMM, n_points_outer, n_points_inner, bg_writing,
channel_array_instrument, in_memory_cache
):
meas = Measurement()

meas.register_parameter(DAC.ch1)
meas.register_parameter(DAC.ch2)

meas_parameters = (DMM.v1,
channel_array_instrument.A.dummy_multi_parameter,
channel_array_instrument.A.dummy_scalar_multi_parameter,
channel_array_instrument.A.dummy_2d_multi_parameter,
channel_array_instrument.A.dummy_2d_multi_parameter_2,
channel_array_instrument.A.dummy_array_parameter,
channel_array_instrument.A.dummy_complex_array_parameter,
channel_array_instrument.A.dummy_complex,
channel_array_instrument.A.dummy_parameter_with_setpoints,
channel_array_instrument.A.dummy_parameter_with_setpoints_complex,
)
channel_array_instrument.A.dummy_start(0)
channel_array_instrument.A.dummy_stop(10)
channel_array_instrument.A.dummy_n_points(10)
for param in meas_parameters:
meas.register_parameter(param, setpoints=(DAC.ch1, DAC.ch2))
n_rows_written = 0
with meas.run(
write_in_background=bg_writing,
in_memory_cache=in_memory_cache) as datasaver:
dataset = datasaver.dataset

_assert_xarray_dataarray_dicts_are_identical(
dataset.to_xarray_dataarray_dict(),
dataset.cache.to_xarray_dataarray_dict()
)

xarray.testing.assert_identical(
dataset.to_xarray_dataset(),
dataset.cache.to_xarray_dataset()
)

for v1 in np.linspace(-1, 1, n_points_outer):
for v2 in np.linspace(-1, 1, n_points_inner):
DAC.ch1.set(v1)
DAC.ch2.set(v2)
meas_vals = [(param, param.get()) for param in
meas_parameters[:-2]]
meas_vals += expand_setpoints_helper(meas_parameters[-2])
meas_vals += expand_setpoints_helper(meas_parameters[-1])

datasaver.add_result((DAC.ch1, v1),
(DAC.ch2, v2),
*meas_vals)
datasaver.flush_data_to_database(block=True)
n_rows_written += 1

_assert_xarray_dataarray_dicts_are_identical(
dataset.to_xarray_dataarray_dict(),
dataset.cache.to_xarray_dataarray_dict()
)

xarray.testing.assert_identical(
dataset.to_xarray_dataset(),
dataset.cache.to_xarray_dataset()
)

_assert_xarray_dataarray_dicts_are_identical(
dataset.to_xarray_dataarray_dict(),
dataset.cache.to_xarray_dataarray_dict()
)

xarray.testing.assert_identical(
dataset.to_xarray_dataset(),
dataset.cache.to_xarray_dataset()
)


def _assert_completed_cache_is_as_expected(
cache_data_trees,
param_data_trees,
Expand Down Expand Up @@ -915,6 +1082,25 @@ def _assert_parameter_data_is_identical(
)


def _assert_dataframe_dicts_are_identical(df_dict_left, df_dict_right) -> None:
for param_name, param_df_from_left in df_dict_left.items():
assert param_name in df_dict_right
param_df_from_right = df_dict_right[param_name]
pandas.testing.assert_frame_equal(
param_df_from_left, param_df_from_right
)


def _assert_xarray_dataarray_dicts_are_identical(xr_dict_left, xr_dict_right
) -> None:
for param_name, param_dataarray_from_left in xr_dict_left.items():
assert param_name in xr_dict_right
param_dataarray_from_right = xr_dict_right[param_name]
xarray.testing.assert_identical(
param_dataarray_from_left, param_dataarray_from_right
)


def _array_param_used_in_tree(measurement: Measurement) -> bool:
found_array = False
for paramspecbase in measurement.parameters.values():
Expand Down

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