def test_peak_fitter_beam_key(self, monkeypatch):
def mockreturn(img):
return 0, 1, 2, 3, 4, 5, 6, 7
monkeypatch.setattr(utils, 'get_peak_parameters', mockreturn)
data = Data(datetime(2018, 8, 28), {
"frame": np.random.randn(600, 800),
"quality": 0
},
metadata={"id": 1234})
pf = PeakFitter("frame")
proc_data = pf(data)
assert proc_data.timestamp == data.timestamp
assert proc_data.value["quality"] == 0
assert proc_data.value["beam_on"] is True
assert proc_data.value["mu_x"] == 2
assert proc_data.value["mu_y"] == 3
assert proc_data.value["sigma_x"] == 4
assert proc_data.value["sigma_y"] == 5
assert proc_data.value["rotation"] == 6
assert proc_data.value["z_offset"] == 0
assert proc_data.value["amplitude"] == 1
assert proc_data.value["cutoff"] == 7
assert proc_data.metadata["id"] == 1234
def test_format_number(self, influx_sink):
time = datetime(2018, 8, 15, 17, 37, 39, 660510)
data = Data(time, 1, metadata={"attribute": "postition"})
res = influx_sink._format(data)
assert res["measurement"] == influx_sink.measurement
assert res["time"] == time
assert res["tags"]["id"] == 1234
assert res["tags"]["attribute"] == "postition"
assert res["fields"]["value"] == 1
def test_peak_fitter_no_beam(self):
data = Data(datetime(2018, 8, 28),
np.random.randn(600, 800),
metadata={"id": 1234})
pf = PeakFitter()
proc_data = pf(data)
assert proc_data.timestamp == data.timestamp
assert proc_data.value["beam_on"] is False
assert proc_data.metadata["id"] == 1234
def test_format_error(self, influx_sink):
time = datetime(2018, 8, 15, 17, 37, 39, 660510)
data = Data(time, None, failure=Exception("msg"),
metadata={"attribute": "postition"})
res = influx_sink._format(data)
assert res["measurement"] == influx_sink.measurement
assert res["time"] == time
assert res["tags"]["id"] == 1234
assert res["tags"]["attribute"] == "postition"
assert res["fields"]["error"] == "msg"
def test_format_dict(self, influx_sink):
time = datetime(2018, 8, 15, 17, 37, 39, 660510)
data = Data(time, {"value1": 1, "value2": 2, "value": None},
metadata={"attribute": "postition"})
res = influx_sink._format(data)
assert res["measurement"] == influx_sink.measurement
assert res["time"] == time
assert res["tags"]["id"] == 1234
assert res["tags"]["attribute"] == "postition"
assert res["fields"]["value1"] == 1
assert res["fields"]["value2"] == 2
assert "value3" not in res["fields"]
def test_write_failure(self, influx_client, influx_sink):
time = datetime(2018, 8, 15, 17, 37, 39, 524288)
data = Data(time, None, failure=Exception("msg"),
metadata={"attribute": "postition"})
success = influx_sink.write(data)
assert not success
res = influx_client.query("SELECT * FROM " +
influx_sink.measurement)
rows = list(res.get_points())
assert len(rows) == 1
assert rows[0]["time"] == '2018-08-15T17:37:39.524288Z'
assert rows[0]["error"] == "msg"
def test_to_string_failure(self):
ex = Exception("An error occured")
data = Data(datetime(2018, 8, 28),
None,
failure=ex,
metadata={"id": 1234})
to_string = ToString()
proc_data = to_string(data)
assert proc_data.timestamp == data.timestamp
assert proc_data.value is None
assert proc_data.failure is ex
assert proc_data.metadata["id"] == 1234
def test_to_string_mapping(self):
data = Data(datetime(2018, 8, 28), {
"a": 1,
"b": "foo"
},
metadata={"id": 1234})
to_string = ToString()
proc_data = to_string(data)
assert type(proc_data.value["a"]) is str
assert type(proc_data.value["b"]) is str
assert proc_data.value["a"] == "1"
assert proc_data.value["b"] == "foo"
def test_peak_fitter_failure(self):
ex = Exception("An error occured")
data = Data(datetime(2018, 8, 28),
None,
failure=ex,
metadata={"id": 1234})
pf = PeakFitter()
proc_data = pf(data)
assert proc_data.timestamp == data.timestamp
assert proc_data.value is None
assert proc_data.failure is ex
assert proc_data.metadata["id"] == 1234
def test_write_none(self, influx_client, influx_sink, value):
time = datetime(2018, 8, 15, 17, 37, 39, 524288)
data = Data(time, value, metadata={"attribute": "postition"})
success = influx_sink.write(data)
assert not success
res = influx_client.query("SELECT * FROM " +
influx_sink.measurement)
rows = list(res.get_points())
assert len(rows) == 1
assert len(rows[0]) == 4
assert rows[0]["time"] == '2018-08-15T17:37:39.524288Z'
assert rows[0]["NoValue"]
assert rows[0]["id"] == "1234"
assert rows[0]["attribute"] == "postition"
def test_write(self, influx_client, influx_sink):
time = datetime(2018, 8, 15, 17, 37, 39, 524288)
time = timezone("Europe/Berlin").localize(time)
data = Data(time, 1, metadata={"attribute": "postition"})
success = influx_sink.write(data)
assert success
res = influx_client.query("SELECT * FROM " +
influx_sink.measurement)
rows = list(res.get_points())
assert len(rows) == 1
assert rows[0]["time"] == '2018-08-15T15:37:39.524288Z'
assert rows[0]["value"] == 1
assert rows[0]["id"] == "1234"
assert rows[0]["attribute"] == "postition"
def test_peak_fitter_convert_float(self, monkeypatch):
dtype = None
def mockreturn(img):
nonlocal dtype
dtype = img.dtype
return 0, 1, 2, 3, 4, 5, 6, 7
monkeypatch.setattr(utils, 'get_peak_parameters', mockreturn)
data = Data(datetime(2018, 8, 28), {
"frame": np.random.randint(0, 255, (600, 800)),
"quality": 0
},
metadata={"id": 1234})
pf = PeakFitter("frame")
pf(data)
assert dtype == np.float64
def test_peak_fitter_log(self, monkeypatch, do_log, tmpdir):
mocksave = Mock()
mockplot = Mock()
mocksavefig = Mock()
monkeypatch.setattr(procs.np, 'save', mocksave)
monkeypatch.setattr(procs.utils, 'plot_gauss', mockplot)
monkeypatch.setattr(procs.plt, 'savefig', mocksavefig)
params = 0, 1, 2, 3, 4, 5, 6, 7
def mockreturn(img):
return params
monkeypatch.setattr(utils, 'get_peak_parameters', mockreturn)
img1 = np.random.randn(60, 80)
data1 = Data(datetime(2018, 8, 28), {
"frame": img1,
"quality": 0
},
metadata={"id": 1234})
if do_log:
pf = PeakFitter("frame", log_dir=str(tmpdir))
else:
pf = PeakFitter("frame")
pf(data1)
if do_log:
h, a, x0, y0, sx, sy, theta, cutoff = params
assert pf.last_h == h
assert pf.last_a == a
assert pf.last_x0 == x0
assert pf.last_y0 == y0
assert pf.last_sx == sx
assert pf.last_sy == sy
assert pf.last_theta == theta
assert pf.last_cutoff == cutoff
params = 10, 11, 12, 13, 14, 15, 16, 17
params2 = params
img2 = np.random.randn(60, 80)
time2 = datetime(2018, 8, 29)
data2 = Data(time2, {
"frame": img2,
"quality": 0
},
metadata={"id": 1234})
pf(data2)
if do_log:
h, a, x0, y0, sx, sy, theta, cutoff = params
assert pf.last_h == h
assert pf.last_a == a
assert pf.last_x0 == x0
assert pf.last_y0 == y0
assert pf.last_sx == sx
assert pf.last_sy == sy
assert pf.last_theta == theta
assert pf.last_cutoff == cutoff
params = 10.1, 11.1, 12.1, 13.1, 14.1, 15.1, 16.1, 17.1
img3 = np.random.randn(60, 80)
time3 = datetime(2018, 8, 30)
data3 = Data(time3, {
"frame": img3,
"quality": 0
},
metadata={"id": 1234})
pf(data3)
if do_log:
h, a, x0, y0, sx, sy, theta, cutoff = params
assert pf.last_h == h
assert pf.last_a == a
assert pf.last_x0 == x0
assert pf.last_y0 == y0
assert pf.last_sx == sx
assert pf.last_sy == sy
assert pf.last_theta == theta
assert pf.last_cutoff == cutoff
basename = os.path.join(str(tmpdir), "img_" + time2.isoformat())
assert mocksave.call_count == 1
assert mockplot.call_count == 2
assert mocksavefig.call_count == 2
(fname, array), kwargs = mocksave.call_args
assert fname == basename
assert (array == img2).all()
assert not kwargs
(array, p_fit), kwargs = mockplot.call_args_list[0]
assert (array == img2).all()
assert p_fit == params2
assert not kwargs
(array, p_fit), kwargs = mockplot.call_args_list[1]
assert (array == img2).all()
assert p_fit == params2
assert kwargs == {"zoom": True}
(fname, ), kwargs = mocksavefig.call_args_list[0]
assert fname == basename + ".png"
assert not kwargs
(fname, ), kwargs = mocksavefig.call_args_list[1]
assert fname == basename + "_zoomed.png"
assert not kwargs
else:
assert mocksave.call_count == 0
assert mockplot.call_count == 0
assert mocksavefig.call_count == 0
def test_to_string(self):
data = Data(datetime(2018, 8, 28), 1, metadata={"id": 1234})
to_string = ToString()
proc_data = to_string(data)
assert type(proc_data.value) is str
assert proc_data.value == "1"