def setMarkerObject(self, markerobject):
self.markerobj = markerobject
tmpobj = vcs.createmarker(source=self.markerobj)
tmpobj.x = [.5, .5]
tmpobj.y = [.5, .5]
self.clear()
self.plot(tmpobj)
def test_preview():
prev = MarkerPreview.MarkerPreviewWidget()
marker = vcs.createmarker("test")
prev.setMarkerObject(marker)
assert prev.markerobj == marker
marker.type = "cross"
prev.update()
assert prev.markerobj.type == ["cross"]
def testVCSreset1only(self):
for gtype in vcs.listelements():
b0 = vcs.listelements(gtype)
if gtype == 'colormap':
b = vcs.createcolormap()
xtra = vcs.createisofill()
untouched = vcs.listelements("isofill")
elif gtype == "template":
b = vcs.createtemplate()
elif gtype == "textcombined":
b = vcs.createtextcombined()
elif gtype == "textorientation":
b = vcs.createtextorientation()
elif gtype == "texttable":
b = vcs.createtexttable()
elif gtype == "fillarea":
b = vcs.createfillarea()
elif gtype == "projection":
b = vcs.createprojection()
elif gtype == "marker":
b = vcs.createmarker()
elif gtype == "line":
b = vcs.createline()
elif gtype in ["display", "font", "fontNumber", "list", "format"]:
vcs.manageElements.reset()
continue
else:
b = vcs.creategraphicsmethod(gtype)
if gtype != "colormap":
xtra = vcs.createcolormap()
untouched = vcs.listelements("colormap")
b1 = vcs.listelements(gtype)
self.assertNotEqual(b0, b1)
vcs.manageElements.reset(gtype)
b2 = vcs.listelements(gtype)
self.assertEqual(b0, b2)
if gtype == "colormap":
self.assertEqual(untouched, vcs.listelements("isofill"))
else:
self.assertEqual(untouched, vcs.listelements("colormap"))
vcs.manageElements.reset()
if gtype == "colormap":
self.assertNotEqual(untouched, vcs.listelements("isofill"))
else:
self.assertNotEqual(untouched, vcs.listelements("colormap"))
# case for 1d weirdness
sc = vcs.createscatter()
vcs.manageElements.reset()
src=sys.argv[1]
if os.path.exists("test_vcs_dump_json.json"):
os.remove("test_vcs_dump_json.json")
b = vcs.createboxfill("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createisofill("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createisoline("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createmeshfill("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createoneD("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createfillarea("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createtext("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createline("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createmarker("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createtemplate("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
b = vcs.createprojection("Charles.Doutriaux")
b.script("test_vcs_dump_json","a")
assert(filecmp.cmp("test_vcs_dump_json.json",src))
def plot(self, var, theta=None, template=None, bg=0, x=None):
"""
Plots a polar plot of your data.
If var is an ndarray with the second dimension being 2, it will use the first value
as magnitude and the second as theta.
Otherwise, if theta is provided, it uses var as magnitude and the theta given.
"""
if x is None:
if self.x is None:
self.x = vcs.init()
x = self.x
if template is None:
template = self.template
if self.markercolorsource.lower() not in ("group", "magnitude",
"theta"):
raise ValueError(
"polar.markercolorsource must be one of: 'group', 'magnitude', 'theta'"
)
magnitudes, thetas, names = convert_arrays(var, theta)
if not self.negative_magnitude: # negative amplitude means 180 degree shift
neg = numpy.ma.less(magnitudes, 0.0)
magnitudes = numpy.ma.abs(magnitudes)
thetas = numpy.ma.where(neg, theta + numpy.pi, theta)
if self.group_names:
names = self.group_names
while len(names) < len(magnitudes):
names.append(None)
flat_magnitude = numpy.ravel(magnitudes)
canvas = x
# Determine aspect ratio for plotting the circle
canvas_info = canvas.canvasinfo()
# Calculate aspect ratio of window
window_aspect = canvas_info["width"] / float(canvas_info["height"])
if window_aspect > 1:
ymul = window_aspect
xmul = 1
else:
ymul = 1
xmul = window_aspect
# Use window_aspect to adjust size of template.data
x0, x1 = template.data.x1, template.data.x2
y0, y1 = template.data.y1, template.data.y2
xdiff = abs(x1 - x0)
ydiff = abs(y1 - y0)
center = x0 + xdiff / 2., y0 + ydiff / 2.
diameter = min(xdiff, ydiff)
radius = diameter / 2.
plot_kwargs = {"render": False, "bg": bg, "donotstoredisplay": True}
# Outer line
if template.box1.priority > 0:
outer = vcs.createline(source=template.box1.line)
x, y = circle_points(center, radius, ratio=window_aspect)
outer.x = x
outer.y = y
canvas.plot(outer, **plot_kwargs)
del vcs.elements["line"][outer.name]
if numpy.allclose((self.datawc_y1, self.datawc_y2), 1e20):
if self.magnitude_ticks == "*":
m_scale = vcs.mkscale(*vcs.minmax(flat_magnitude))
else:
if isinstance(self.magnitude_ticks, str):
ticks = vcs.elements["list"][self.magnitude_ticks]
else:
ticks = self.magnitude_ticks
m_scale = ticks
else:
m_scale = vcs.mkscale(self.datawc_y1, self.datawc_y2)
if template.ytic1.priority > 0:
m_ticks = vcs.createline(source=template.ytic1.line)
m_ticks.x = []
m_ticks.y = []
if template.ylabel1.priority > 0:
to = self.text_orientation_for_angle(
self.magnitude_tick_angle + self.theta_offset,
source=template.ylabel1.textorientation)
m_labels = self.create_text(template.ylabel1.texttable, to)
m_labels.x = []
m_labels.y = []
m_labels.string = []
if self.yticlabels1 == "*":
mag_labels = vcs.mklabels(m_scale)
else:
mag_labels = self.yticlabels1
else:
m_labels = None
for lev in m_scale:
lev_radius = radius * self.magnitude_from_value(lev, m_scale)
x, y = circle_points(center, lev_radius, ratio=window_aspect)
if m_labels is not None:
if lev in mag_labels:
m_labels.string.append(mag_labels[lev])
m_labels.x.append(xmul * lev_radius *
numpy.cos(self.magnitude_tick_angle +
self.theta_offset) +
center[0])
m_labels.y.append(ymul * lev_radius *
numpy.sin(self.magnitude_tick_angle +
self.theta_offset) +
center[1])
m_ticks.x.append(x)
m_ticks.y.append(y)
canvas.plot(m_ticks, **plot_kwargs)
del vcs.elements["line"][m_ticks.name]
if m_labels is not None:
canvas.plot(m_labels, **plot_kwargs)
del vcs.elements["textcombined"][m_labels.name]
if template.ymintic1.priority > 0 and self.magnitude_mintics is not None:
mag_mintics = vcs.createline(source=template.ymintic1.line)
mag_mintics.x = []
mag_mintics.y = []
mintics = self.magnitude_mintics
if isinstance(mintics, str):
mintics = vcs.elements["list"][mintics]
for mag in mintics:
mintic_radius = radius * \
self.magnitude_from_value(mag, m_scale)
x, y = circle_points(center,
mintic_radius,
ratio=window_aspect)
mag_mintics.x.append(x)
mag_mintics.y.append(y)
canvas.plot(mag_mintics, **plot_kwargs)
del vcs.elements["line"][mag_mintics.name]
if self.xticlabels1 == "*":
if numpy.allclose((self.datawc_x1, self.datawc_x2), 1e20):
tick_thetas = list(numpy.arange(0, numpy.pi * 2, numpy.pi / 4))
tick_labels = {t: str(t) for t in tick_thetas}
else:
d_theta = (self.datawc_x2 - self.datawc_x1) / \
float(self.theta_tick_count)
tick_thetas = numpy.arange(self.datawc_x1,
self.datawc_x2 + .0001, d_theta)
tick_labels = vcs.mklabels(tick_thetas)
else:
tick_thetas = sorted(list(self.xticlabels1.keys()))
tick_labels = self.xticlabels1
if template.xtic1.priority > 0:
t_ticks = vcs.createline(source=template.xtic1.line)
t_ticks.x = []
t_ticks.y = []
if template.xlabel1.priority > 0:
t_labels = []
theta_labels = tick_labels
else:
t_labels = None
for t in tick_thetas:
angle = self.theta_from_value(t)
x0 = center[0] + (xmul * radius * numpy.cos(angle))
x1 = center[0]
y0 = center[1] + (ymul * radius * numpy.sin(angle))
y1 = center[1]
if t_labels is not None:
label = self.create_text(
template.xlabel1.texttable,
self.text_orientation_for_angle(
angle, source=template.xlabel1.textorientation))
label.string = [theta_labels[t]]
label.x = [x0]
label.y = [y0]
t_labels.append(label)
t_ticks.x.append([x0, x1])
t_ticks.y.append([y0, y1])
canvas.plot(t_ticks, **plot_kwargs)
del vcs.elements["line"][t_ticks.name]
if t_labels is not None:
for l in t_labels:
canvas.plot(l, **plot_kwargs)
del vcs.elements["textcombined"][l.name]
values = vcs.createmarker()
values.type = self.markertypes
values.size = self.markersizes
values.color = self.markercolors
values.colormap = self.colormap
values.priority = self.markerpriority
values.x = []
values.y = []
if template.legend.priority > 0:
# Only labels that are set will show up in the legend
label_count = len(names) - len([i for i in names if i is None])
labels = self.create_text(template.legend.texttable,
template.legend.textorientation)
labels.x = []
labels.y = []
labels.string = []
if self.linepriority > 0:
line = vcs.createline()
line.x = []
line.y = []
line.type = self.linetypes
line.color = self.linecolors if self.linecolors is not None else self.markercolors
line.width = self.linewidths
line.priority = self.linepriority
# This is up here because when it's part of the main loop, we can
# lose "order" of points when we flatten them.
for mag, theta in zip(magnitudes, thetas):
x = []
y = []
for m, t in zip(mag, theta):
t = self.theta_from_value(t)
r = self.magnitude_from_value(m, m_scale) * radius
if r == numpy.nan:
continue
x.append(xmul * numpy.cos(t) * r + center[0])
y.append(ymul * numpy.sin(t) * r + center[1])
if self.connect_groups:
line.x.extend(x)
line.y.extend(y)
else:
line.x.append(x)
line.y.append(y)
if self.markercolorsource.lower() in ('magnitude', "theta"):
# Regroup the values using the appropriate metric
mag_flat = numpy.array(magnitudes).flatten()
theta_flat = numpy.array(thetas).flatten()
if self.markercolorsource.lower() == "magnitude":
scale = m_scale
vals = mag_flat
else:
scale = tick_thetas
vals = theta_flat
indices = [
numpy.where(
numpy.logical_and(vals >= scale[i], vals <= scale[i + 1]))
for i in range(len(scale) - 1)
]
magnitudes = [mag_flat[inds] for inds in indices]
thetas = [theta_flat[inds] for inds in indices]
names = vcs.mklabels(scale, output="list")
names = [
names[i] + " - " + names[i + 1] for i in range(len(names) - 1)
]
label_count = len(names)
for mag, theta, name in zip(magnitudes, thetas, names):
x = []
y = []
for m, t in zip(mag, theta):
t = self.theta_from_value(t)
r = self.magnitude_from_value(m, m_scale) * radius
x.append(xmul * numpy.cos(t) * r + center[0])
y.append(ymul * numpy.sin(t) * r + center[1])
if template.legend.priority > 0 and name is not None:
y_offset = len(labels.x) / float(label_count) * \
(template.legend.y2 - template.legend.y1)
lx, ly = template.legend.x1, template.legend.y1 + y_offset
x.append(lx)
y.append(ly)
labels.x.append(lx + .01)
labels.y.append(ly)
labels.string.append(str(name))
values.x.append(x)
values.y.append(y)
if template.legend.priority > 0:
canvas.plot(labels, **plot_kwargs)
del vcs.elements["textcombined"][labels.name]
if self.linepriority > 0:
canvas.plot(line, **plot_kwargs)
del vcs.elements["line"][line.name]
for el in self.to_cleanup:
if vcs.istexttable(el):
if el.name in vcs.elements["texttable"]:
del vcs.elements["texttable"][el.name]
else:
if el.name in vcs.elements["textorientation"]:
del vcs.elements["textorientation"][el.name]
self.to_cleanup = []
# Prune unneeded levels from values
to_prune = []
for ind, (x, y) in enumerate(zip(values.x, values.y)):
if x and y:
continue
else:
to_prune.append(ind)
for prune_ind in to_prune[::-1]:
del values.x[prune_ind]
del values.y[prune_ind]
if len(values.color) > prune_ind and len(values.color) > 1:
del values.color[prune_ind]
if len(values.size) > prune_ind and len(values.size) > 1:
del values.size[prune_ind]
if len(values.type) > prune_ind and len(values.type) > 1:
del values.type[prune_ind]
canvas.plot(values, bg=bg, donotstoredisplay=True)
del vcs.elements["marker"][values.name]
return canvas
def editor():
editor = MarkerEditor.MarkerEditorWidget()
marker = vcs.createmarker()
editor.setMarkerObject(marker)
return editor
os.remove("test_vcs_dump_json.json")
b = vcs.createboxfill("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createisofill("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createisoline("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createmeshfill("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.create1d("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createfillarea("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createvector("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createtext("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createline("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createmarker("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createtemplate("vcs_instance")
b.script("test_vcs_dump_json", "a")
b = vcs.createprojection("vcs_instance")
b.script("test_vcs_dump_json", "a")
print "Comparing:", os.path.realpath("test_vcs_dump_json.json"), src
assert (filecmp.cmp("test_vcs_dump_json.json", src))
os.remove("test_vcs_dump_json.json")
# Component time is a more useful format, that has the date/time in human-readable attributes print "Time:", relative_time.tocomponent() print "Lat:", lataxis[lat_index] print "Lon:", lonaxis[lon_index] # Now we can plot clt at the specified time, and stick a marker at the lat/lon x = vcs.init() template = x.createtemplate() template.scale(.66, "x") template.blank() template.data.priority = 1 x.plot(clt(time=time_index), template) marker = vcs.createmarker() marker.type = "cross" # data describes where the actual plot is placed on the canvas data = template.data # Viewport represents the area in which markers are drawn marker.viewport = (data.x1, data.x2, data.y1, data.y2) # Worldcoordinate represents the scale that x/y are given in marker.worldcoordinate = (min(lonaxis), max(lonaxis), min(lataxis), max(lataxis)) marker.x = [lonaxis[lon_index]] marker.y = [lataxis[lat_index]] marker.size = 10 x.plot(marker) murica = clt(time=time_index, latitude=(12, 80), longitude=(-150, -40))
import vcs, os, filecmp
import vcs, numpy, os, sys
src = sys.argv[1]
if os.path.exists("test_vcs_dump_json.json"):
os.remove("test_vcs_dump_json.json")
b = vcs.createboxfill("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createisofill("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createisoline("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createmeshfill("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createoneD("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createfillarea("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createtext("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createline("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createmarker("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createtemplate("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
b = vcs.createprojection("Charles.Doutriaux")
b.script("test_vcs_dump_json", "a")
assert (filecmp.cmp("test_vcs_dump_json.json", src))
cdutil.setTimeBoundsMonthly(tas)
var = cdutil.averager(tas(squeeze=1), axis="xy")
var = cdutil.ANNUALCYCLE.climatology(var)
var.id = saved_id
variables.append(var)
# Customize the lines used to draw the plots
line = vcs.createline()
line.width = 2
line.color = [
"red", "blue", "salmon", "medium aquamarine", "orange", "chartreuse"
]
line.type = ["dot", "dash", "dash-dot", "long-dash", "solid", "dash"]
# Customize the markers drawn
marker = vcs.createmarker()
marker.size = 6
# You can just use the same colors as the lines
marker.color = line.color
marker.type = [
"triangle_up", "plus", "diamond", "circle", "cross", "triangle_down"
]
# Middle of the month (from the time axis)
months = {
15.5: "Jan",
45.0: "Feb",
74.5: "March",
105.0: "April",
135.5: "May",
166.0: "June",
os.remove("test_vcs_dump_json.json")
b = vcs.createboxfill("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createisofill("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createisoline("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createmeshfill("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.create1d("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createfillarea("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createvector("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createtext("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createline("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createmarker("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createtemplate("vcs_instance")
b.script("test_vcs_dump_json","a")
b = vcs.createprojection("vcs_instance")
b.script("test_vcs_dump_json","a")
assert(filecmp.cmp("test_vcs_dump_json.json", src))
# Component time is a more useful format, that has the date/time in human-readable attributes print "Time:", relative_time.tocomponent() print "Lat:", lataxis[lat_index] print "Lon:", lonaxis[lon_index] # Now we can plot clt at the specified time, and stick a marker at the lat/lon x = vcs.init() template = x.createtemplate() template.scale(0.66, "x") template.blank() template.data.priority = 1 x.plot(clt(time=time_index), template) marker = vcs.createmarker() marker.type = "cross" # data describes where the actual plot is placed on the canvas data = template.data # Viewport represents the area in which markers are drawn marker.viewport = (data.x1, data.x2, data.y1, data.y2) # Worldcoordinate represents the scale that x/y are given in marker.worldcoordinate = (min(lonaxis), max(lonaxis), min(lataxis), max(lataxis)) marker.x = [lonaxis[lon_index]] marker.y = [lataxis[lat_index]] marker.size = 10 x.plot(marker) murica = clt(time=time_index, latitude=(12, 80), longitude=(-150, -40))
def editor():
editor = MarkerEditorWidget()
marker = vcs.createmarker()
editor.setMarkerObject(marker)
return editor
def plot(self, var, theta=None, template=None, bg=0, x=None):
"""
Plots a polar plot of your data.
If var is an ndarray with the second dimension being 2, it will use the first value
as magnitude and the second as theta.
Otherwise, if theta is provided, it uses var as magnitude and the theta given.
"""
if x is None:
if self.x is None:
self.x = vcs.init()
x = self.x
if template is None:
template = self.template
if self.markercolorsource.lower() not in ("group", "magnitude", "theta"):
raise ValueError("polar.markercolorsource must be one of: 'group', 'magnitude', 'theta'")
magnitudes, thetas, names = convert_arrays(var, theta)
if self.group_names:
names = self.group_names
while len(names) < len(magnitudes):
names.append(None)
flat_magnitude = []
for i in magnitudes:
flat_magnitude.extend(i)
flat_theta = []
for i in thetas:
flat_theta.extend(i)
canvas = x
# Determine aspect ratio for plotting the circle
canvas_info = canvas.canvasinfo()
# Calculate aspect ratio of window
window_aspect = canvas_info["width"] / float(canvas_info["height"])
if window_aspect > 1:
ymul = window_aspect
xmul = 1
else:
ymul = 1
xmul = window_aspect
# Use window_aspect to adjust size of template.data
x0, x1 = template.data.x1, template.data.x2
y0, y1 = template.data.y1, template.data.y2
xdiff = abs(x1 - x0)
ydiff = abs(y1 - y0)
center = x0 + xdiff / 2., y0 + ydiff / 2.
diameter = min(xdiff, ydiff)
radius = diameter / 2.
plot_kwargs = {"render": False, "bg": bg, "donotstoredisplay": True}
# Outer line
if template.box1.priority > 0:
outer = vcs.createline(source=template.box1.line)
x, y = circle_points(center, radius, ratio=window_aspect)
outer.x = x
outer.y = y
canvas.plot(outer, **plot_kwargs)
del vcs.elements["line"][outer.name]
if numpy.allclose((self.datawc_y1, self.datawc_y2), 1e20):
if self.magnitude_ticks == "*":
m_scale = vcs.mkscale(*vcs.minmax(flat_magnitude))
else:
if isinstance(self.magnitude_ticks, (str, unicode)):
ticks = vcs.elements["list"][self.magnitude_ticks]
else:
ticks = self.magnitude_ticks
m_scale = ticks
else:
m_scale = vcs.mkscale(self.datawc_y1, self.datawc_y2)
if template.ytic1.priority > 0:
m_ticks = vcs.createline(source=template.ytic1.line)
m_ticks.x = []
m_ticks.y = []
if template.ylabel1.priority > 0:
to = self.text_orientation_for_angle(self.magnitude_tick_angle,
source=template.ylabel1.textorientation)
m_labels = self.create_text(template.ylabel1.texttable, to)
m_labels.x = []
m_labels.y = []
m_labels.string = []
if self.yticlabels1 == "*":
mag_labels = vcs.mklabels(m_scale)
else:
mag_labels = self.yticlabels1
else:
m_labels = None
for lev in m_scale:
lev_radius = radius * self.magnitude_from_value(lev, (m_scale[0], m_scale[-1]))
x, y = circle_points(center, lev_radius, ratio=window_aspect)
if m_labels is not None:
if lev in mag_labels:
m_labels.string.append(mag_labels[lev])
m_labels.x.append(xmul * lev_radius * numpy.cos(self.magnitude_tick_angle) + center[0])
m_labels.y.append(ymul * lev_radius * numpy.sin(self.magnitude_tick_angle) + center[1])
m_ticks.x.append(x)
m_ticks.y.append(y)
canvas.plot(m_ticks, **plot_kwargs)
del vcs.elements["line"][m_ticks.name]
if m_labels is not None:
canvas.plot(m_labels, **plot_kwargs)
del vcs.elements["textcombined"][m_labels.name]
if template.ymintic1.priority > 0 and self.magnitude_mintics is not None:
mag_mintics = vcs.createline(source=template.ymintic1.line)
mag_mintics.x = []
mag_mintics.y = []
mintics = self.magnitude_mintics
if isinstance(mintics, (str, unicode)):
mintics = vcs.elements["list"][mintics]
for mag in mintics:
mintic_radius = radius * self.magnitude_from_value(mag, (m_scale[0], m_scale[-1]))
x, y = circle_points(center, mintic_radius, ratio=window_aspect)
mag_mintics.x.append(x)
mag_mintics.y.append(y)
canvas.plot(mag_mintics, **plot_kwargs)
del vcs.elements["line"][mag_mintics.name]
if self.xticlabels1 == "*":
if numpy.allclose((self.datawc_x1, self.datawc_x2), 1e20):
tick_thetas = list(numpy.arange(0, numpy.pi * 2, numpy.pi / 4))
tick_labels = {t: str(t) for t in tick_thetas}
else:
d_theta = (self.datawc_x2 - self.datawc_x1) / float(self.theta_tick_count)
tick_thetas = numpy.arange(self.datawc_x1, self.datawc_x2 + .0001, d_theta)
tick_labels = vcs.mklabels(tick_thetas)
else:
tick_thetas = self.xticlabels1.keys()
tick_labels = self.xticlabels1
if template.xtic1.priority > 0:
t_ticks = vcs.createline(source=template.xtic1.line)
t_ticks.x = []
t_ticks.y = []
if template.xlabel1.priority > 0:
t_labels = []
theta_labels = tick_labels
else:
t_labels = None
for t in tick_thetas:
angle = self.theta_from_value(t)
x0 = center[0] + (xmul * radius * numpy.cos(angle))
x1 = center[0]
y0 = center[1] + (ymul * radius * numpy.sin(angle))
y1 = center[1]
if t_labels is not None:
label = self.create_text(template.xlabel1.texttable,
self.text_orientation_for_angle(angle,
source=template.xlabel1.textorientation))
label.string = [theta_labels[t]]
label.x = [x0]
label.y = [y0]
t_labels.append(label)
t_ticks.x.append([x0, x1])
t_ticks.y.append([y0, y1])
canvas.plot(t_ticks, **plot_kwargs)
del vcs.elements["line"][t_ticks.name]
if t_labels is not None:
for l in t_labels:
canvas.plot(l, **plot_kwargs)
del vcs.elements["textcombined"][l.name]
values = vcs.createmarker()
values.type = self.markers
values.size = self.markersizes
values.color = self.markercolors
values.colormap = self.colormap
values.priority = self.markerpriority
values.x = []
values.y = []
if template.legend.priority > 0:
# Only labels that are set will show up in the legend
label_count = len(names) - len([i for i in names if i is None])
labels = self.create_text(template.legend.texttable, template.legend.textorientation)
labels.x = []
labels.y = []
labels.string = []
if self.draw_lines:
line = vcs.createline()
line.x = []
line.y = []
line.type = self.lines
line.color = self.linecolors if self.linecolors is not None else self.markercolors
line.width = self.linewidths
line.priority = self.linepriority
# This is up here because when it's part of the main loop, we can lose "order" of points when we flatten them.
for mag, theta in zip(magnitudes, thetas):
x = []
y = []
for m, t in zip(mag, theta):
t = self.theta_from_value(t)
r = self.magnitude_from_value(m, (m_scale[0], m_scale[-1])) * radius
x.append(xmul * numpy.cos(t) * r + center[0])
y.append(ymul * numpy.sin(t) * r + center[1])
if self.connect_groups:
line.x.extend(x)
line.y.extend(y)
else:
line.x.append(x)
line.y.append(y)
if self.markercolorsource.lower() in ('magnitude', "theta"):
# Regroup the values using the appropriate metric
mag_flat = numpy.array(magnitudes).flatten()
theta_flat = numpy.array(thetas).flatten()
if self.markercolorsource.lower() == "magnitude":
scale = m_scale
vals = mag_flat
else:
scale = theta_ticks
vals = theta_flat
indices = [numpy.where(numpy.logical_and(vals >= scale[i], vals <= scale[i + 1]))
for i in range(len(scale) - 1)]
magnitudes = [mag_flat[inds] for inds in indices]
thetas = [theta_flat[inds] for inds in indices]
names = vcs.mklabels(scale, output="list")
names = [names[i] + " - " + names[i + 1] for i in range(len(names) - 1)]
label_count = len(names)
for mag, theta, name in zip(magnitudes, thetas, names):
x = []
y = []
for m, t in zip(mag, theta):
t = self.theta_from_value(t)
r = self.magnitude_from_value(m, (m_scale[0], m_scale[-1])) * radius
x.append(xmul * numpy.cos(t) * r + center[0])
y.append(ymul * numpy.sin(t) * r + center[1])
if template.legend.priority > 0 and name is not None:
y_offset = len(labels.x) / float(label_count) * (template.legend.y2 - template.legend.y1)
lx, ly = template.legend.x1, template.legend.y1 + y_offset
x.append(lx)
y.append(ly)
labels.x.append(lx + .01)
labels.y.append(ly)
labels.string.append(str(name))
values.x.append(x)
values.y.append(y)
if template.legend.priority > 0:
canvas.plot(labels, **plot_kwargs)
del vcs.elements["textcombined"][labels.name]
if self.draw_lines:
canvas.plot(line, **plot_kwargs)
del vcs.elements["line"][line.name]
for el in self.to_cleanup:
if vcs.istexttable(el):
if el.name in vcs.elements["texttable"]:
del vcs.elements["texttable"][el.name]
else:
if el.name in vcs.elements["textorientation"]:
del vcs.elements["textorientation"][el.name]
self.to_cleanup = []
# Prune unneeded levels from values
to_prune = []
for ind, (x, y) in enumerate(zip(values.x, values.y)):
if x and y:
continue
else:
to_prune.append(ind)
for prune_ind in to_prune[::-1]:
del values.x[prune_ind]
del values.y[prune_ind]
if len(values.color) > prune_ind and len(values.color) > 1:
del values.color[prune_ind]
if len(values.size) > prune_ind and len(values.size) > 1:
del values.size[prune_ind]
if len(values.type) > prune_ind and len(values.type) > 1:
del values.type[prune_ind]
canvas.plot(values, bg=bg, donotstoredisplay=True)
del vcs.elements["marker"][values.name]
return canvas
saved_id = tas.id
# Make sure the data is bounded before averaging
cdutil.setTimeBoundsMonthly(tas)
var = cdutil.averager(tas(squeeze=1), axis="xy")
var = cdutil.ANNUALCYCLE.climatology(var)
var.id = saved_id
variables.append(var)
# Customize the lines used to draw the plots
line = vcs.createline()
line.width = 2
line.color = ["red", "blue", "salmon", "medium aquamarine", "orange", "chartreuse"]
line.type = ["dot", "dash", "dash-dot", "long-dash", "solid", "dash"]
# Customize the markers drawn
marker = vcs.createmarker()
marker.size = 6
# You can just use the same colors as the lines
marker.color = line.color
marker.type = ["triangle_up", "plus", "diamond", "circle", "cross", "triangle_down"]
# Middle of the month (from the time axis)
months = {
15.5: "Jan",
45.0: "Feb",
74.5: "March",
105.0: "April",
135.5: "May",
166.0: "June",
196.5: "July",
227.5: "Aug",
import numpy
with open("data/geolocate_activity.json") as f:
geo_data = json.load(f)
template = vcs.createtemplate()
template.blank()
template.data.priority = 1
template.box1.priority = 1
template.xtic1.priority = 1
template.ytic1.priority = 1
template.xlabel1.priority = 1
template.ylabel1.priority = 1
base_marker = vcs.createmarker()
base_marker.worldcoordinate = [-180, 180, -90, 90]
base_marker.viewport = [template.data.x1, template.data.x2, template.data.y1, template.data.y2]
max_count = 0
for p in geo_data:
max_count = max(p["count"], max_count)
markers = {
}
zeroes = cdms2.MV2.ones((180, 360))
lon = cdms2.createAxis(numpy.arange(-180, 180, 1), id="lon")
lat = cdms2.createAxis(numpy.arange(-90, 90, 1), id="lat")
zeroes.setAxis(1, lon)
zeroes.setAxis(0, lat)
