def test_calculate_bins(self):
kwargs = {
"comp_x": 10,
"comp_y": 20
}
self.assertEqual(((10, 5), None), mf.calculate_bin_counts(
self.unsorted_data, **kwargs
))
self.assert_all_equal(
lambda data: mf.calculate_bin_counts(data, **kwargs),
self.all_data
)
def test_bad_inputs(self):
self.assertRaises(
ValueError,
lambda: mf.calculate_bin_counts(self.unsorted_data, 0, 0))
self.assertRaises(
ValueError,
lambda: mf.calculate_bin_counts(self.unsorted_data, 10, -1))
self.assertRaises(
ValueError,
lambda: mf.calculate_bin_counts(self.unsorted_data, 1, 1,
min_count=20, max_count=10))
def test_max_count(self):
kwargs = {
"comp_x": 5,
"comp_y": 10,
"max_count": 15
}
self.assertEqual(
((15, 10), "Bin count exceeded maximum value of 15. Adjustment "
"made."),
mf.calculate_bin_counts(self.unsorted_data, **kwargs))
self.assert_all_equal(
lambda data: mf.calculate_bin_counts(data, **kwargs),
self.all_data
)
def test_sorted_count(self):
kwargs = {
"comp_x": 10,
"comp_y": 10,
"data_sorted": True
}
expected_x = int(math.fabs(self.unsorted_data[0][0] -
self.unsorted_data[0][-1]) / 10)
expected_y = int(math.fabs(self.unsorted_data[1][0] -
self.unsorted_data[1][-1]) / 10)
if not expected_x:
expected_x = 1
if not expected_y:
expected_y = 1
self.assertEqual(((expected_x, expected_y), None),
mf.calculate_bin_counts(self.unsorted_data, **kwargs))
self.assert_all_equal(
lambda data: mf.calculate_bin_counts(data, **kwargs),
[self.asc_sorted_data, self.desc_sorted_data]
)
def test_return_type(self):
# bin counts should always be integers
n = 10
for _ in range(n):
kwargs = {
"data": [
[random.random() for _ in range(20)],
[random.random() for _ in range(20)]
],
"comp_x": random.random(),
"comp_y": random.random(),
"min_count": random.uniform(5.5, 15.5),
"max_count": random.uniform(25.5, 35.5),
"data_sorted": random.random() > 0.5
}
(x_bins, y_bins), _ = mf.calculate_bin_counts(**kwargs)
self.assertIsInstance(x_bins, int)
self.assertIsInstance(y_bins, int)
def on_draw(self):
"""Draw method for matplotlib.
"""
# Values for zoom
x_min, x_max = self.axes.get_xlim()
y_min, y_max = self.axes.get_ylim()
x_data = self.__x_data
y_data = self.__y_data
# Transpose
if self.transpose_axes:
x_data, y_data = y_data, x_data # Always transpose data if checked.
if not self.__transposed:
self.__transposed = True
self.measurement.selector.transpose(True)
# Switch axes names
self.name_x_axis, self.name_y_axis = (self.name_y_axis,
self.name_x_axis)
# Switch min & max values
x_min, x_max, y_min, y_max = y_min, y_max, x_min, x_max
# Switch inverts
self.invert_X, self.invert_Y = self.invert_Y, self.invert_X
if not self.transpose_axes and self.__transposed:
self.__transposed = False
self.measurement.selector.transpose(False)
# Switch axes names
self.name_x_axis, self.name_y_axis \
= self.name_y_axis, self.name_x_axis
# Switch min & max values
x_min, x_max, y_min, y_max = y_min, y_max, x_min, x_max
# Switch inverts
self.invert_X, self.invert_Y = self.invert_Y, self.invert_X
# Clear old stuff
self.axes.clear()
# Check bin counts and axes ranges
# If bin count too high -> it will crash the program, use 3500
# If 10 000, tofe_65 example can have compression as 1, but REALLY
# slow. Usually, bin count around 8000
if self.axes_range_mode == 1:
# Manual axe range mode
bin_counts, msg = mf.calculate_bin_counts(
self.axes_range,
self.compression_x,
self.compression_y,
max_count=MatplotlibHistogramWidget.MAX_BIN_COUNT)
axes_range = self.axes_range
else:
# Automatic mode
bin_counts, msg = mf.calculate_bin_counts(
[x_data, y_data],
self.compression_x,
self.compression_y,
max_count=MatplotlibHistogramWidget.MAX_BIN_COUNT)
axes_range = None
if msg is not None:
# Message is displayed when bin count was too high and had to be
# lowered
QtWidgets.QMessageBox.warning(self.parent, "Warning", msg,
QtWidgets.QMessageBox.Ok,
QtWidgets.QMessageBox.Ok)
colormap = cm.get_cmap(self.color_scheme.value)
self.axes.hist2d(x_data,
y_data,
bins=bin_counts,
norm=LogNorm(),
range=axes_range,
cmap=colormap)
self.__on_draw_legend()
if 0.09 < x_max < 1.01: # This works..
x_min, x_max = self.axes.get_xlim()
if 0.09 < y_max < 1.01: # or self.axes_range_mode
y_min, y_max = self.axes.get_ylim()
# Change zoom limits if compression factor was changed (or new graph).
if not self.__range_mode_automated and self.axes_range_mode == 0 \
or self.axes_range_mode == 1:
# self.__range_mode_automated and self.axes_range_mode == 1
tx_min, tx_max = self.axes.get_xlim()
ty_min, ty_max = self.axes.get_ylim()
# If user has zoomed the graph, change the home position to new max.
# Else reset the graph to new ranges and clear zoom levels.
if self.mpl_toolbar._views:
self.mpl_toolbar._views[0][0] = (tx_min, tx_max, ty_min,
ty_max)
else:
x_min, x_max = tx_min, tx_max
y_min, y_max = ty_min, ty_max
self.mpl_toolbar.update()
self.__range_mode_automated = self.axes_range_mode == 0
# print(self.axes.get_xlim())
# Set limits accordingly
self.axes.set_ylim([y_min, y_max])
self.axes.set_xlim([x_min, x_max])
self.measurement.draw_selection()
# Invert axis
if self.invert_Y and not self.__inverted_Y:
self.axes.set_ylim(self.axes.get_ylim()[::-1])
self.__inverted_Y = True
elif not self.invert_Y and self.__inverted_Y:
self.axes.set_ylim(self.axes.get_ylim()[::-1])
self.__inverted_Y = False
if self.invert_X and not self.__inverted_X:
self.axes.set_xlim(self.axes.get_xlim()[::-1])
self.__inverted_X = True
elif not self.invert_X and self.__inverted_X:
self.axes.set_xlim(self.axes.get_xlim()[::-1])
self.__inverted_X = False
# [::-1] is elegant reverse. Slice sequence with step of -1.
# http://stackoverflow.com/questions/3705670/
# best-way-to-create-a-reversed-list-in-python
# self.axes.set_title('ToF Histogram\n\n')
self.axes.set_ylabel(self.name_y_axis.title())
self.axes.set_xlabel(self.name_x_axis.title())
# Remove axis ticks and draw
self.remove_axes_ticks()
self.canvas.draw()
def test_empty_list(self):
self.assertEqual(((1, 1), None),
mf.calculate_bin_counts([[1], []], 1, 1))