def test_colorize():
coords = [np.array([0, 1]), np.array([2, 5])]
cat_agg = xr.DataArray(np.array([[(0, 12, 0), (3, 0, 3)],
[(12, 12, 12), (24, 0, 0)]]),
coords=(coords + [['a', 'b', 'c']]),
dims=(dims + ['cats']))
colors = [(255, 0, 0), '#0000FF', 'orange']
img = tf.colorize(cat_agg, colors, how='log')
sol = np.array([[3137273856, 2449494783],
[4266997674, 3841982719]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
colors = dict(zip('abc', colors))
img = tf.colorize(cat_agg, colors, how='cbrt')
sol = np.array([[3070164992, 2499826431],
[4283774890, 3774873855]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors, how='linear')
sol = np.array([[1660878848, 989876991],
[4283774890, 2952790271]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors, how=lambda x: x ** 2)
sol = np.array([[788463616, 436228863],
[4283774890, 2080375039]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
def test_colorize():
coords = [np.array([0, 1]), np.array([2, 5])]
cat_agg = xr.DataArray(np.array([[(0, 12, 0), (3, 0, 3)],
[(12, 12, 12), (24, 0, 0)]]),
coords=(coords + [['a', 'b', 'c']]),
dims=(dims + ['cats']))
colors = [(255, 0, 0), '#0000FF', 'orange']
img = tf.colorize(cat_agg, colors, how='log')
sol = np.array([[2583625728, 335565567], [4283774890, 3707764991]],
dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
colors = dict(zip('abc', colors))
img = tf.colorize(cat_agg, colors, how='cbrt')
sol = np.array([[2650734592, 335565567], [4283774890, 3657433343]],
dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors, how='linear')
sol = np.array([[1140785152, 335565567], [4283774890, 2701132031]],
dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg,
colors,
how=lambda x, m: np.where(m, np.nan, x)**2)
sol = np.array([[503250944, 335565567], [4283774890, 1744830719]],
dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
def test_colorize():
coords = [np.array([0, 1]), np.array([2, 5])]
cat_agg = xr.DataArray(np.array([[(0, 12, 0), (3, 0, 3)],
[(12, 12, 12), (24, 0, 0)]]),
coords=(coords + [['a', 'b', 'c']]),
dims=(dims + ['cats']))
colors = [(255, 0, 0), '#0000FF', 'orange']
img = tf.colorize(cat_agg, colors, how='log')
sol = np.array([[3137273856, 2449494783], [4266997674, 3841982719]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
colors = dict(zip('abc', colors))
img = tf.colorize(cat_agg, colors, how='cbrt')
sol = np.array([[3070164992, 2499826431], [4283774890, 3774873855]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors, how='linear')
sol = np.array([[1660878848, 989876991], [4283774890, 2952790271]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors, how=lambda x: x**2)
sol = np.array([[788463616, 436228863], [4283774890, 2080375039]])
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
def test_colorize():
coords = [np.array([0, 1]), np.array([2, 5])]
cat_agg = xr.DataArray(np.array([[(0, 12, 0), (3, 0, 3)],
[(12, 12, 12), (24, 0, 0)]]),
coords=(coords + [['a', 'b', 'c']]),
dims=(dims + ['cats']))
colors = [(255, 0, 0), '#0000FF', 'orange']
img = tf.colorize(cat_agg, colors, how='log', min_alpha=20)
sol = np.array([[2583625728, 335565567],
[4283774890, 3707764991]], dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
colors = dict(zip('abc', colors))
img = tf.colorize(cat_agg, colors, how='cbrt', min_alpha=20)
sol = np.array([[2650734592, 335565567],
[4283774890, 3657433343]], dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors, how='linear', min_alpha=20)
sol = np.array([[1140785152, 335565567],
[4283774890, 2701132031]], dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
img = tf.colorize(cat_agg, colors,
how=lambda x, m: np.where(m, np.nan, x) ** 2,
min_alpha=20)
sol = np.array([[503250944, 335565567],
[4283774890, 1744830719]], dtype='u4')
sol = tf.Image(sol, coords=coords, dims=dims)
assert img.equals(sol)
def create_image3(x_range, y_range, w=plot_width, h=plot_height):
cvs = dshader.Canvas(plot_width=w,
plot_height=h,
x_range=x_range,
y_range=y_range)
agg = cvs.points(df, 'dens', 'temp', dshader.count_cat('phase'))
img = tf.colorize(agg, phase_color_key, how='eq_hist')
return img
def create_image(x_range, y_range, w=plot_width, h=plot_height):
cvs = dshader.Canvas(plot_width=w,
plot_height=h,
x_range=x_range,
y_range=y_range)
agg = cvs.points(df, 'x', 'z', dshader.count_cat('phase'))
img = tf.colorize(agg, phase_color_key, how='eq_hist')
return tf.dynspread(img, threshold=0.3, max_px=4)
def test_colorize():
colors = [(255, 0, 0), '#0000FF', 'orange']
img = tf.colorize(cat_agg, colors, how='log').img
sol = np.array([[3137273856, 2449494783],
[4266997674, 3841982719]])
assert (img == sol).all()
img = cat_agg.colorize(colors, how='log').img
assert (img == sol).all()
colors = dict(zip('abc', colors))
img = tf.colorize(cat_agg, colors, how='cbrt').img
sol = np.array([[3070164992, 2499826431],
[4283774890, 3774873855]])
assert (img == sol).all()
img = tf.colorize(cat_agg, colors, how='linear').img
sol = np.array([[1660878848, 989876991],
[4283774890, 2952790271]])
assert (img == sol).all()
img = tf.colorize(cat_agg, colors, how=lambda x: x ** 2).img
sol = np.array([[788463616, 436228863],
[4283774890, 2080375039]])
assert (img == sol).all()
def render_image(self):
# handle categorical field
if self.field in self.categorical_fields:
pix = tf.colorize(self.agg, self.colormap, how=self.transfer_function)
# handle ordinal field
elif self.field in self.ordinal_fields:
pix = tf.interpolate(self.agg, cmap=self.color_ramp, how=self.transfer_function)
# handle no field
else:
pix = tf.interpolate(self.agg, cmap=self.color_ramp, how=self.transfer_function)
if self.spread_size > 0:
pix = tf.spread(pix, px=self.spread_size)
return pix
def render_image(self):
# handle categorical field
if self.field in self.categorical_fields:
pix = tf.colorize(self.agg,
self.colormap,
how=self.transfer_function)
# handle ordinal field
elif self.field in self.ordinal_fields:
pix = tf.interpolate(self.agg,
cmap=self.color_ramp,
how=self.transfer_function)
# handle no field
else:
pix = tf.interpolate(self.agg,
cmap=self.color_ramp,
how=self.transfer_function)
if self.spread_size > 0:
pix = tf.spread(pix, px=self.spread_size)
return pix
for i in range(len(tdb)):
events = list(tdb.trail(i, event_filter=query))
if events:
yield events[0].time, events
def get_dataframe():
tdb = TrailDB('pydata-tutorial.tdb')
base = tdb.min_timestamp()
types = []
xs = []
ys = []
# try this:
# for y, (first_ts, events) in enumerate(sorted(get_events(tdb), reverse=True)):
for y, (first_ts, events) in enumerate(get_events(tdb)):
for event in events:
xs.append(old_div(int(event.time - base), (24 * 3600)))
ys.append(y)
types.append('user' if event.user else 'anon')
data = pd.DataFrame({'x': xs, 'y': ys})
data['type'] = pd.Series(types, dtype='category')
return data
cnv = ds.Canvas(400, 300)
agg = cnv.points(get_dataframe(), 'x', 'y', ds.count_cat('type'))
colors = {'anon': 'red', 'user': '******'}
img = tf.set_background(tf.colorize(agg, colors, how='eq_hist'), 'white')
with open('prince.png', 'w') as f:
f.write(img.to_bytesio().getvalue())
def get_events(tdb):
query = [('title', 'Prince (musician)')]
for i in range(len(tdb)):
events = list(tdb.trail(i, event_filter=query))
if events:
yield events[0].time, events
def get_dataframe():
tdb = TrailDB('pydata-tutorial.tdb')
base = tdb.min_timestamp()
types = []
xs = []
ys = []
#try this:
#for y, (first_ts, events) in enumerate(sorted(get_events(tdb), reverse=True)):
for y, (first_ts, events) in enumerate(get_events(tdb)):
for event in events:
xs.append(int(event.time - base) / (24 * 3600))
ys.append(y)
types.append('user' if event.user else 'anon')
data = pd.DataFrame({'x': xs, 'y': ys})
data['type'] = pd.Series(types, dtype='category')
return data
cnv = ds.Canvas(400, 300)
agg = cnv.points(get_dataframe(), 'x', 'y', ds.count_cat('type'))
colors = {'anon': 'red', 'user': '******'}
img=tf.set_background(tf.colorize(agg, colors, how='eq_hist'), 'white')
with open('prince.png', 'w') as f:
f.write(img.to_bytesio().getvalue())
