clean up tests and folders
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This commit is contained in:
2026-03-20 16:47:53 +01:00
parent c8192ecbb0
commit 5e37c1baa3
12 changed files with 35 additions and 29 deletions
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# 1. disable any possible re-launch
GIO_USE_VFS=local # stop gvfs daemonising
GSETTINGS_BACKEND=memory # dont spawn dconf-service
# 2. ask glib to abort on the first warning so nothing can “eat” it
G_DEBUG=fatal-warnings # or =fatal-criticals
# 3. turn on *all* debug domains
G_MESSAGES_DEBUG=all
# 4. run inside gdb so we can see the exact line that fails
gdb -ex run --args python3 src/gui/DamarisGUI.py
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import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gtk
print("GTK imported successfully")
win = Gtk.Window()
win.connect("destroy", Gtk.main_quit)
win.show_all()
Gtk.main()
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HDF5 "testaccu.hdf5" {
DATASET "/name/accu_data" {
DATATYPE H5T_IEEE_F32LE
DATASPACE SIMPLE { ( 2, 4 ) / ( 2, 4 ) }
DATA {
(0,0): 10, 0, 15, 0,
(1,0): 20, 0, 25, 0
}
ATTRIBUTE "CLASS" {
DATATYPE H5T_STRING {
STRSIZE 6;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
}
DATASPACE SCALAR
DATA {
(0): "CARRAY"
}
}
ATTRIBUTE "TITLE" {
DATATYPE H5T_STRING {
STRSIZE 9;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
}
DATASPACE SCALAR
DATA {
(0): "accu data"
}
}
ATTRIBUTE "VERSION" {
DATATYPE H5T_STRING {
STRSIZE 3;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
}
DATASPACE SCALAR
DATA {
(0): "1.1"
}
}
}
}
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HDF5 "test.hdf5" {
DATASET "/name/adc_data" {
DATATYPE H5T_STD_I16LE
DATASPACE SIMPLE { ( 2, 2 ) / ( 2, 2 ) }
DATA {
(0,0): 10, 15,
(1,0): 20, 25
}
ATTRIBUTE "CLASS" {
DATATYPE H5T_STRING {
STRSIZE 6;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
}
DATASPACE SCALAR
DATA {
(0): "CARRAY"
}
}
ATTRIBUTE "TITLE" {
DATATYPE H5T_STRING {
STRSIZE 8;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
}
DATASPACE SCALAR
DATA {
(0): "adc data"
}
}
ATTRIBUTE "VERSION" {
DATATYPE H5T_STRING {
STRSIZE 3;
STRPAD H5T_STR_NULLTERM;
CSET H5T_CSET_ASCII;
CTYPE H5T_C_S1;
}
DATASPACE SCALAR
DATA {
(0): "1.1"
}
}
}
}
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#!/usr/bin/env python3
import os
import sys
# 1) force GTK3 backend *before* pyplot is imported
os.environ['MPLBACKEND'] = 'GTK3Agg' # or GTK3Cairo
# 2) turn on every debug message GLib/GTK will give us
os.environ['G_MESSAGES_DEBUG'] = 'all'
os.environ['GTK_DEBUG'] = 'interactive' # also enables Ctrl-Shift-I inspector
import matplotlib
matplotlib.use('GTK3Agg') # belt-and-braces: make sure
import matplotlib.pyplot as plt
print('GTK3Agg backend loaded, creating figure…')
fig, ax = plt.subplots()
ax.plot([0, 1], [0, 1])
ax.set_title('GTK3-Matplotlib window close it to finish')
print('Showing figure…')
plt.show()
print('plt.show() returned script ends')
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import os
import subprocess
import unittest
from datetime import datetime
import numpy as np
from src.data.ADC_Result import ADC_Result
class TestADCResult(unittest.TestCase):
@staticmethod
def create_adc_result():
x = np.array([0.0, 1.0, 2.0])
y = [np.array([10, 20, 30]), np.array([15, 25, 35])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id = 11
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
adc.set_nChannels(2)
return adc
def test_constructor_with_no_arguments(self):
"""Test initializer with no arguments."""
adc = ADC_Result()
self.assertFalse(adc.contains_data())
self.assertEqual(adc.sampling_rate, 0)
self.assertEqual(len(adc.index), 0)
self.assertEqual(len(adc.x), 0)
self.assertEqual(len(adc.y), 0)
def test_constructor_with_arguments(self):
"""Test initializer with all arguments."""
x = np.array([0.0, 1.0, 2.0])
y = [np.array([10, 20, 30]), np.array([15, 25, 35])]
index = [(0, 2)]
sampl_freq = 1000.0
desc = {"key1": "value1"}
job_id = 1
job_date = datetime(2023, 1, 1)
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
self.assertTrue(adc.contains_data())
self.assertEqual(adc.sampling_rate, sampl_freq)
self.assertEqual(adc.x.all(), x.all())
self.assertEqual(adc.y[0].all(), y[0].all())
self.assertEqual(adc.description, desc)
self.assertEqual(adc.job_id, job_id)
self.assertEqual(adc.job_date, job_date)
self.assertTrue(np.array_equal(adc.x, np.array(x, dtype="float32")))
self.assertTrue(np.array_equal(adc.y[0], np.array(y[0], dtype="int16")))
self.assertTrue(np.array_equal(adc.y[1], np.array(y[1], dtype="int16")))
def test_create_data_space(self):
"""Test creating a new data space."""
adc = ADC_Result()
adc.create_data_space(channels=2, samples=3)
self.assertTrue(adc.contains_data())
self.assertEqual(len(adc.y), 2)
self.assertEqual(len(adc.x), 3)
self.assertTrue(np.array_equal(adc.x, np.zeros(3, dtype="float32")))
self.assertTrue(np.array_equal(adc.y[0], np.zeros(3, dtype="int16")))
self.assertEqual(adc.index, [(0, 2)])
def test_add_sample_space(self):
"""Test adding sample space."""
adc = ADC_Result()
adc.create_data_space(channels=1, samples=3)
adc.add_sample_space(2)
self.assertEqual(len(adc.x), 5)
self.assertEqual(len(adc.y[0]), 5)
self.assertEqual(adc.index[-1], (3, 4))
def test_get_result_by_index(self):
"""Test retrieving data by index."""
adc = self.create_adc_result()
adc.index = [(0, 1), (1, 2)]
adc.job_id = 42
sub_result = adc.get_result_by_index(1)
self.assertEqual(sub_result.sampling_rate, 1000.0)
self.assertTrue(np.array_equal(sub_result.x, np.array([1.0, 2.0])))
self.assertTrue(np.array_equal(sub_result.y[0], np.array([20, 30])))
self.assertTrue(np.array_equal(sub_result.y[1], np.array([25, 35])))
self.assertEqual(sub_result.index, [(0, 1)])
self.assertEqual(sub_result.description, {"key": "value"})
self.assertEqual(sub_result.job_id, 42)
def test_set_sampling_rate(self):
"""Test updating the sampling rate."""
adc = ADC_Result()
adc.set_sampling_rate(5000.0)
self.assertEqual(adc.get_sampling_rate(), 5000.0)
def test_set_nChannels(self):
"""Test setting the number of channels."""
adc = ADC_Result()
adc.set_nChannels(5)
self.assertEqual(adc.get_nChannels(), 5)
def test_write_to_csv(self):
"""Test the functionality of writing to CSV."""
from io import StringIO
x = np.array([0.0, 1.0])
y = [np.array([10, 20]), np.array([15, 25])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id=9
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
output = StringIO()
adc.write_to_csv(output, delimiter=",")
content = output.getvalue()
expected = (
"# adc_result\n"
"# t y0 y1 ...\n"
"0.000000e+00,1.000000e+01,1.500000e+01\n"
"1.000000e+00,2.000000e+01,2.500000e+01\n"
)
self.assertEqual(content, expected)
def test_write_to_hdf(self):
"""Test the functionality of writing to HDF."""
import tables
# do not change the values here, or you need to recreate the h5dump with new values
x = np.array([0.0, 1.0])
y = [np.array([10, 20]), np.array([15, 25])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id = 10
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
# write out data
hdffile = tables.open_file("test.hdf5", mode="w")
adc.write_to_hdf(hdffile, where="/", name="name", title="title", complib="zlib", complevel=3)
hdffile.close()
# read back data with h5dump utility (apt-get -y install hdf5-tools)
h5dump = subprocess.run(["h5dump", "-d", "/name/adc_data", "test.hdf5"], capture_output=True)
content = h5dump.stdout.decode("utf-8")
test_dir = os.path.dirname(__file__)
with open(os.path.join(test_dir, "h5dump1_adc_data.ascii"), "r") as f:
expected = f.read()
self.assertEqual(content, expected)
os.unlink("test.hdf5")
def test_operator_len(self):
"""Test the functionality of __len__"""
adc = self.create_adc_result()
self.assertEqual(len(adc), 3)
def test_operator_add_scalar(self):
"""
Test the functionality of __add__ and __radd__
"""
adc = self.create_adc_result()
y = adc.y
# test integer addition
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i]+10, y[i] + 10, strict=True)
adc += 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] + 10, strict=True)
# test float addition
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i] + 10., y[i] + 10., strict=True)
adc += 10.
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] + 10 + 10., strict=True)
def test_operator_sub_scalar(self):
"""
Test the functionality of __sub__ and __rsub__
"""
adc = self.create_adc_result()
y = adc.y
# test integer subtraction
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i] - 10, y[i] - 10, strict=True)
adc -= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] - 10, strict=True)
# test float subtraction
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i] - 10., y[i] - 10., strict=True)
adc -= 10.
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] - 10 - 10., strict=True)
def test_operator_mul_scalar(self):
"""
Test the functionality of __mul and __rmul__
"""
adc = self.create_adc_result()
y = adc.y
# test integer multiplication
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i] * 10, y[i] * 10, strict=True)
adc *= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] * 10, strict=True)
# test float multiplication
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i] * 10.0, y[i] * 10.0, strict=True)
adc *= 10.0
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] * 10 * 10.0, strict=True)
def test_operator_truediv_scalar(self):
"""
Test the functionality of __div__ and __rdiv__
"""
adc = self.create_adc_result()
y = adc.y
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i]/10, y[i] / 10, strict=True)
adc /= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] / 10, strict=True)
def test_operator_floordiv_scalar(self):
"""
Test the functionality of __div__ and __rdiv__
"""
adc = self.create_adc_result()
y = adc.y
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i]//10, y[i] // 10, strict=True)
adc //= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] // 10, strict=True)
self.assertRaises(ValueError, adc.__floordiv__, 1.0)
self.assertRaises(ValueError, adc.__rfloordiv__, 1.0)
def test_operator_overload_adc_result_exception(self):
"""
Test the ValueError raised when ADC_Result is used as an operand in an arithmetic operation
"""
adc1 = self.create_adc_result()
adc2 = self.create_adc_result()
self.assertRaises(ValueError, adc1.__add__, adc2)
self.assertRaises(ValueError, adc1.__radd__, adc2)
self.assertRaises(ValueError, adc1.__sub__, adc2)
self.assertRaises(ValueError, adc1.__rsub__, adc2)
self.assertRaises(ValueError, adc1.__mul__, adc2)
self.assertRaises(ValueError, adc1.__rmul__, adc2)
self.assertRaises(ValueError, adc1.__truediv__, adc2)
self.assertRaises(ValueError, adc1.__rtruediv__, adc2)
self.assertRaises(ValueError, adc1.__floordiv__, adc2)
self.assertRaises(ValueError, adc1.__rfloordiv__, adc2)
self.assertRaises(ValueError, adc1.__pow__, adc2)
if __name__ == "__main__":
unittest.main()
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import os
import subprocess
import unittest
from datetime import datetime
import numpy as np
from src.data.ADC_Result import ADC_Result
from src.data.Accumulation import Accumulation
class TestAccumulation(unittest.TestCase):
@staticmethod
def create_adc_result():
x = np.array([0.0, 1.0, 2.0])
y = [np.array([10, 20, 30]), np.array([15, 25, 35])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id = 11
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
adc.set_nChannels(2)
return adc
def test_constructor_with_no_arguments(self):
"""Test initializer with no arguments."""
accu = Accumulation()
self.assertFalse(accu.contains_data())
self.assertEqual(accu.sampling_rate, 0)
self.assertEqual(len(accu.index), 0)
self.assertEqual(len(accu.x), 0)
self.assertEqual(len(accu.y), 0)
def test_constructor_with_arguments(self):
"""Test initializer with all arguments."""
x = np.array([0.0, 1.0, 2.0])
y = [np.array([10, 20, 30]), np.array([15, 25, 35])]
n = 1
index = [(0, 2)]
sampl_freq = 1000.0
accu = Accumulation(x=x,
y=y,
y_2=None,
index=index,
sampl_freq=sampl_freq,
n=n)
self.assertTrue(accu.contains_data())
self.assertEqual(accu.sampling_rate, sampl_freq)
self.assertEqual(accu.x.all(), x.all())
self.assertEqual(accu.y[0].all(), y[0].all())
# TODO make testing strict with array types!
np.testing.assert_array_equal(accu.x, np.array(x, dtype="float32"), strict=False)
np.testing.assert_array_equal(accu.y[0], np.array(y[0], dtype="int16"), strict=False)
np.testing.assert_array_equal(accu.y[1], np.array(y[1], dtype="int16"), strict=False)
def test_add_adc_result(self):
"""Test adding sample space."""
adc = self.create_adc_result()
accu = Accumulation()
accu += adc
self.assertEqual(len(adc.x), len(accu.x))
self.assertEqual(len(adc.y[0]), len(accu.y[0]))
self.assertEqual(adc.index[-1], accu.index[-1])
np.testing.assert_array_equal(accu.x, adc.x)
np.testing.assert_array_equal(accu.y[0], adc.y[0])
def test_add_accumulation(self):
"""Test adding sample space."""
adc1 = self.create_adc_result()
adc1.set_description("common", "somerandomtext")
adc1.set_description("same_variable", "somerandomtext_variable1")
adc1.set_description("variable1", "somerandomtext_variable1_1")
adc2 = self.create_adc_result()
adc2.set_description("common", "somerandomtext")
adc2.set_description("same_variable", "somerandomtext_variable2")
adc2.set_description("variable2", "somerandomtext_variable2_2")
accu1 = Accumulation()
accu1 += adc1
print(accu1.common_descriptions)
accu2 = Accumulation()
accu2 += adc2
accu2 += accu1
self.assertEqual(len(accu1.x), len(accu2.x))
self.assertEqual(len(accu1.y[0]), len(accu2.y[0]))
self.assertEqual(accu1.index[-1], accu2.index[-1])
self.assertEqual(accu1.common_descriptions["same_variable"], "somerandomtext_variable1")
self.assertEqual(accu2.common_descriptions["common"], "somerandomtext")
np.testing.assert_array_equal(accu2.x, accu1.x)
np.testing.assert_array_equal(accu2.y[0], accu1.y[0]*2)
def test_get_accu_by_index(self):
"""Test retrieving data by index."""
accu = Accumulation()
adc = self.create_adc_result()
adc.index = [(0, 1), (1, 2)]
adc.job_id = 42
accu += adc
sub_result = accu.get_accu_by_index(1)
self.assertEqual(sub_result.sampling_rate, 1000.0)
self.assertTrue(np.array_equal(sub_result.x, np.array([1.0, 2.0])))
self.assertTrue(np.array_equal(sub_result.y[0], np.array([20, 30])))
self.assertTrue(np.array_equal(sub_result.y[1], np.array([25, 35])))
self.assertEqual(sub_result.index, [(0, 1)])
# TODO Fix #13: self.assertEqual(sub_result.common_descriptions, {"key": "value"})
def test_write_to_csv_without_error(self):
"""Test the functionality of writing to CSV."""
from io import StringIO
x = np.array([0.0, 1.0])
y = [np.array([10, 20]), np.array([15, 25])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id=9
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
accu = Accumulation()
accu += adc
output = StringIO()
accu.write_to_csv(output, delimiter=",")
content = output.getvalue()
expected = (
"# accumulation 1\n"
"# key : value\n"
"# t ch0_mean ch1_mean\n"
"0.000000e+00,1.000000e+01,1.500000e+01\n"
"1.000000e+00,2.000000e+01,2.500000e+01\n"
)
self.assertEqual(content, expected)
def test_write_to_csv_with_error(self):
"""Test the functionality of writing to CSV."""
from io import StringIO
x = np.array([0.0, 1.0])
y = [np.array([10, 20]), np.array([15, 25])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id=9
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
accu = Accumulation(error=True)
accu += adc
output = StringIO()
accu.write_to_csv(output, delimiter=",")
content = output.getvalue()
expected = (
"# accumulation 1\n"
"# key : value\n"
"# t ch0_mean ch0_err ch1_mean ch1_err\n"
"0.000000e+00,1.000000e+01,0.000000e+00,1.500000e+01,0.000000e+00\n"
"1.000000e+00,2.000000e+01,0.000000e+00,2.500000e+01,0.000000e+00\n"
)
self.assertEqual(content, expected)
def test_write_to_hdf(self):
"""Test the functionality of writing to HDF."""
import tables
# do not change the values here, or you need to recreate the h5dump with new values
x = np.array([0.0, 1.0])
y = [np.array([10, 20]), np.array([15, 25])]
index = [(0, 1)]
job_date = datetime(2023, 1, 1)
desc = {"key": "value"}
sampl_freq = 1000.0
job_id = 10
adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
accu = Accumulation()
accu += adc
# write out data
hdffile = tables.open_file("testaccu.hdf5", mode="w")
accu.write_to_hdf(hdffile, where="/", name="name", title="title", complib="zlib", complevel=3)
hdffile.close()
# read back data with h5dump utility (apt-get -y install hdf5-tools)
h5dump = subprocess.run(["h5dump", "-d", "/name/accu_data", "testaccu.hdf5"], capture_output=True)
content = h5dump.stdout.decode("utf-8")
# Use path relative to project root
test_dir = os.path.dirname(__file__)
with open(os.path.join(test_dir, "h5dump1_accu.ascii"), "r") as f:
expected = f.read()
self.assertEqual(content, expected)
os.unlink("testaccu.hdf5")
def test_operator_len(self):
"""Test the functionality of __len__"""
adc = self.create_adc_result()
accu = Accumulation()
accu += adc
self.assertEqual(len(accu), 3)
def test_operator_add_scalar(self):
"""
Test the functionality of __add__ and __radd__
"""
adc = self.create_adc_result()
accu = Accumulation()
accu += adc
y = adc.y
# test integer addition
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i]+10, y[i] + 10)
accu += 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i], y[i] + 10)
# test float addition
accu += 10.
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i], y[i] + 10 + 10.)
def test_operator_sub_scalar(self):
"""
Test the functionality of __sub__ and __rsub__
"""
adc = self.create_adc_result()
y = adc.y
accu = Accumulation()
accu += adc
# test integer subtraction
accu -= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i], y[i] - 10)
# test float subtraction
adc -= 10.
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i], y[i] - 10 - 10.)
@unittest.skip("Not implmented")
def test_operator_mul_scalar(self):
"""
Test the functionality of __mul and __rmul__
"""
adc = self.create_adc_result()
y = adc.y
accu = Accumulation()
accu += adc
# test integer multiplication
accu *= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i], y[i] * 10)
# test float multiplication
accu *= 10.0
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(accu.y[i], y[i] * 10 * 10.0)
@unittest.skip("Not implmented")
def test_operator_truediv_scalar(self):
"""
Test the functionality of __div__ and __rdiv__
"""
adc = self.create_adc_result()
y = adc.y
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i]/10, y[i] / 10, strict=True)
adc /= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] / 10, strict=True)
@unittest.skip("Not implmented")
def test_operator_floordiv_scalar(self):
"""
Test the functionality of __div__ and __rdiv__
"""
adc = self.create_adc_result()
y = adc.y
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i]//10, y[i] // 10, strict=True)
adc //= 10
for i in range(adc.get_nChannels()):
np.testing.assert_array_equal(adc.y[i], y[i] // 10, strict=True)
self.assertRaises(ValueError, adc.__floordiv__, 1.0)
self.assertRaises(ValueError, adc.__rfloordiv__, 1.0)
if __name__ == "__main__":
unittest.main()