def test_2(self):
data1 = np.random.rand(100)
data2 = np.random.rand(100)
hh = h2(data1, data2, 120)
hha = h2(data1, data2, 60)
hhb = hh.merge_bins(2, inplace=False)
assert hha == hhb
def test_add_cross_2d(self):
d1 = np.asarray([1, 21, 3])
d2 = np.asarray([10, 12, 20])
h = h2(d1, d2, "fixed_width", 10, adaptive=True)
hb = h2(d1, d2 + 10, "fixed_width", 10, adaptive=True)
hc = h + hb
assert np.array_equal(hc.numpy_bins[1], [10, 20, 30, 40])
def test_dropna(self):
vals2 = np.array(vals)
vals2[0, 1] = np.nan
with pytest.raises(RuntimeError):
hist = physt.h2(vals2[:,0], vals2[:,1], dropna=False)
hist = physt.h2(vals2[:, 0], vals2[:, 1])
assert hist.frequencies.sum() == 6
def test_add_cross_2d(self):
d1 = np.asarray([1, 21, 3])
d2 = np.asarray([10, 12, 20])
h = h2(d1, d2, "fixed_width", 10, adaptive=True)
hb = h2(d1, d2 +10, "fixed_width", 10, adaptive=True)
hc = h + hb
assert np.array_equal(hc.numpy_bins[1], [10, 20, 30, 40])
def test_addition_with_adaptive(self):
ha = h2([1], [11], "fixed_width", 10, adaptive=True)
hb = h2([10], [5], "fixed_width", 10, adaptive=True)
hha = ha + hb
assert hha == hb + ha
assert hha.shape == (2, 2)
assert hha.total == 2
assert np.array_equal(hha.frequencies, [[0, 1], [1, 0]])
def test_divide_by_constant(self):
xx = np.array([0.5, 1.5, 2.5, 2.2, 3.3, 4.2])
yy = np.array([1.5, 1.5, 1.5, 2.2, 1.3, 1.2])
h = physt.h2(xx, yy, "fixed_width", 1)
i = h / 2
assert np.array_equal(i.frequencies, freqs / 2)
assert np.array_equal(i.errors2, freqs / 4)
def vignette_histogram(path,
width=1920,
height=1280,
grid=32,
jitter=1,
**kwargs):
histogram = h2(None,
None,
"fixed_width",
grid,
range=((0, width), (0, height)))
xs = [0, width, width, 0, width / 2]
ys = [0, 0, height, height, height / 2]
count = int((height / grid)**2 / jitter)
counts = [count] * 4 + [count / 4]
radii = [height / 4] * 5
for xs, ys in multicenter_data(xs, ys, counts, radii):
fill_data = np.concatenate([xs[:, np.newaxis], ys[:, np.newaxis]],
axis=1)
histogram.fill_n(fill_data)
dpi = 100
fig, ax = plt.subplots(figsize=(width / dpi, height / dpi))
histogram.plot("image",
ax=ax,
show_colorbar=False,
cmap="Greens",
cmap_max=histogram.frequencies.max(),
cmap_min=-0.2 * histogram.frequencies.max(),
**kwargs)
ax.set_axis_off()
save_only_axis(ax, path, dpi=dpi)
def test_subtraction_with_another(self):
xx = np.array([0.5, 1.5, 2.5, 2.2, 3.3, 4.2])
yy = np.array([1.5, 1.5, 1.5, 2.2, 1.3, 1.2])
h = physt.h2(xx, yy, "fixed_width", 1)
i = h * 2 - h
assert np.array_equal(i.frequencies, freqs)
assert np.array_equal(i.errors2, 5 * freqs)
def test_fill_nonempty(self):
d1 = [1, 21, 3]
d2 = [10, 12, 20]
h = h2(d1, d2, "fixed_width", 10, adaptive=True)
h.fill([4, 60])
assert h.total == 4
assert h.shape == (3, 6)
def test_fill_nonempty(self):
d1 = [1, 21, 3]
d2 = [10, 12, 20]
h = h2(d1, d2, "fixed_width", 10, adaptive=True)
h.fill([4, 60])
assert h.total == 4
assert h.shape == (3, 6)
def test_simple_random(self):
x = np.random.normal(100, 1, 1000)
y = np.random.normal(10, 10, 1000)
h2 = physt.h2(x, y, [8, 4], name="Some histogram", axis_names=["x", "y"])
assert h2.frequencies.sum() == 1000
assert h2.shape == (8, 4)
assert h2.name == "Some histogram"
assert h2.axis_names == ("x", "y")
def create_h2(cursor, *args, **kwargs):
axis_names = _get_axis_names(cursor)
if len(axis_names) != 2:
raise RuntimeError(
"Invalid number of columns: {0}".format(len(axis_names)))
kwargs["axis_names"] = kwargs.get("axis_names", axis_names)
if kwargs.get("adaptive", False):
h = h2(None, None, *args, **kwargs)
for row in cursor:
h << row
return h
else:
raise NotImplementedError()
def test_multiply_by_constant(self):
xx = np.array([0.5, 1.5, 2.5, 2.2, 3.3, 4.2])
yy = np.array([1.5, 1.5, 1.5, 2.2, 1.3, 1.2])
h = physt.h2(xx, yy, "fixed_width", 1)
assert np.array_equal(h.frequencies, freqs)
i = h * 2
assert np.array_equal(i.frequencies, freqs * 2)
assert np.array_equal(i.errors2, freqs * 4)
i = h * 0.5
assert np.array_equal(i.frequencies, freqs * 0.5)
assert np.array_equal(i.errors2, freqs * 0.25)
def vignette_histogram(path, width=1920, height=1280, grid=32, jitter=1, **kwargs):
histogram = h2(None, None, "fixed_width", grid, range=((0, width), (0, height)))
xs = [0, width, width, 0, width / 2]
ys = [0, 0, height, height, height / 2]
count = int((height / grid) ** 2 / jitter)
counts = [count] * 4 + [count / 4]
radii = [height / 4] * 5
for xs, ys in multicenter_data(xs, ys, counts, radii):
fill_data = np.concatenate([xs[:, np.newaxis], ys[:, np.newaxis]], axis=1)
histogram.fill_n(fill_data)
dpi = 100
fig, ax = plt.subplots(figsize=(width / dpi, height / dpi))
histogram.plot("image", ax=ax, show_colorbar=False, cmap="Greens", cmap_max=histogram.frequencies.max(), cmap_min=-0.2 * histogram.frequencies.max(), **kwargs)
ax.set_axis_off()
save_only_axis(ax, path, dpi=dpi)
def test_create_empty(self):
h = h2(None, None, "fixed_width", 10, adaptive=True)
for b in h._binnings:
assert b.is_adaptive()
assert h.ndim == 2
def test_multiply_by_other(self):
xx = np.array([0.5, 1.5, 2.5, 2.2, 3.3, 4.2])
yy = np.array([1.5, 1.5, 1.5, 2.2, 1.3, 1.2])
h = physt.h2(xx, yy, "fixed_width", 1)
with pytest.raises(RuntimeError):
h * h
def test_fill_empty(self):
h = h2(None, None, "fixed_width", 10, adaptive=True)
h.fill([4, 14])
assert h.total == 1
assert np.array_equal(h.numpy_bins, [[0, 10], [10, 20]])
def test_create_nonempty(self):
d1 = [1, 21, 3]
d2 = [11, 12, 13]
h = h2(d1, d2, "fixed_width", 10, adaptive=True)
assert h.shape == (3, 1)
def test_create_empty(self):
h = h2(None, None, "fixed_width", 10, adaptive=True)
for b in h._binnings:
assert b.is_adaptive()
assert h.ndim == 2
def test_subtraction_by_constant(self):
xx = np.array([0.5, 1.5, 2.5, 2.2, 3.3, 4.2])
yy = np.array([1.5, 1.5, 1.5, 2.2, 1.3, 1.2])
h = physt.h2(xx, yy, "fixed_width", 1)
with pytest.raises(RuntimeError):
h - 4
def test_create_nonempty(self):
d1 = [1, 21, 3]
d2 = [11, 12, 13]
h = h2(d1, d2, "fixed_width", 10, adaptive=True)
assert h.shape == (3, 1)
def test_fill_empty(self):
h = h2(None, None, "fixed_width", 10, adaptive=True)
h.fill([4, 14])
assert h.total == 1
assert np.array_equal(h.numpy_bins, [[0, 10], [10, 20]])
def test_create_empty_h2(self):
h2(None, None, "integer", adaptive=True)
def test_simple(self):
h = physt.h2(None, None, "integer", adaptive=True)
h << (0, 1)
json = h.to_json()
read = io.parse_json(json)
assert h == read
def test_json_write_2d(self):
from physt import h2
values = np.random.rand(500, 2)
h = h2(values[:, 0], values[:, 1], 3)
def test_simple(self):
h = physt.h2(None, None, "integer", adaptive=True)
h << (0, 1)
json = h.to_json()
read = io.parse_json(json)
assert h == read
def test_json_write_2d(self):
from physt import h2
values = np.random.rand(500, 2)
h = h2(values[:,0], values[:,1], 3)
