def __init__(self, obj, figsize=4, name=None):
r"""
Which is the specialized widget class name for viewing this object (if any)
TESTS::
sage: from sage_explorer._widgets import PlotWidget
sage: w = PlotWidget(sin)
sage: w.name
'sin'
sage: len(w.children)
1
sage: w = PlotWidget(list(cremona_curves(srange(35)))[0])
sage: w.name
'Elliptic Curve defined by y^2 + y = x^3 - x^2 - 10*x - 20 over Rational Field'
sage: x, y = var('x y')
sage: g(x,y) = x**2 + y**2
sage: w = PlotWidget(g)
sage: w.name
'(x, y) |--> x^2 + y^2'
"""
super(PlotWidget, self).__init__()
self.value = obj
if not name:
name = repr(obj)
self.name = name
svgfilename = path_join(SAGE_TMP, '%s.svg' % name)
pngfilename = path_join('.', '%s.png' % name)
if hasattr(obj,
'number_of_arguments') and obj.number_of_arguments() == 2:
if type(figsize) == type(()):
if len(figsize) == 2:
urange, vrange = figsize
elif len(figsize) == 1:
urange, vrange = figsize, figsize
elif str(figsize).isnumeric():
urange = vrange = (-float(figsize) / 2, float(figsize) / 2)
self.plot = plot3d(obj, urange, vrange)
else:
try:
self.plot = plot(obj, figsize=figsize)
except:
try:
self.plot = obj.plot()
except:
self.plot = plot(obj)
try:
self.plot.save(svgfilename)
self.children = [HTML(open(svgfilename, 'rb').read())]
except:
self.plot.save(pngfilename)
self.children = [
HTML('<img title="' + self.name + ' Plot" src="' +
pngfilename + '">')
]
def EC_nf_plot(E,base_field_gen_name):
K = E.base_field()
n1 = K.signature()[0]
if n1 == 0:
return plot([])
prec = 53
maxprec = 10**6
while prec < maxprec: # Try to base change to R. May fail if resulting curve is almost singular, so increase precision.
try:
SR = K.embeddings(RealField(prec))
X = [E.base_extend(s) for s in SR]
break
except ArithmeticError:
prec *= 2
if prec >= maxprec:
return text("Unable to plot",(1,1),fontsize="xx-large")
X = [e.plot() for e in X]
xmin = min([x.xmin() for x in X])
xmax = max([x.xmax() for x in X])
ymin = min([x.ymin() for x in X])
ymax = max([x.ymax() for x in X])
cols = ["blue","red","green","orange","brown"] # Preset colours, because rainbow tends to return too pale ones
if n1 > len(cols):
cols = rainbow(n1)
return sum([EC_R_plot([SR[i](a) for a in E.ainvs()],xmin,xmax,ymin,ymax,cols[i],"$"+base_field_gen_name+" \mapsto$ "+str(SR[i].im_gens()[0].n(20))) for i in range(n1)])
def EC_nf_plot(K, ainvs, base_field_gen_name):
try:
n1 = K.signature()[0]
if n1 == 0:
return plot([])
R=[]
S=K.embeddings(RDF)
for s in S:
A=[s(c) for c in ainvs]
R.append(EC_R_plot_zone(Rx([A[4],A[3],A[1],1]),Rx([A[2],A[0]])))
xmin = min([r[0] for r in R])
xmax = max([r[1] for r in R])
ymin = min([r[2] for r in R])
ymax = max([r[3] for r in R])
cols = rainbow(n1) # Default choice of n colours
# However, these tend to be too pale, so we preset them for small values of n
if n1==1:
cols=["blue"]
elif n1==2:
cols=["red","blue"]
elif n1==3:
cols=["red","limegreen","blue"]
elif n1==4:
cols = ["red", "orange", "forestgreen", "blue"]
elif n1==5:
cols = ["red", "orange", "forestgreen", "blue", "darkviolet"]
elif n1==6:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet"]
elif n1==7:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet", "fuchsia"]
return sum([EC_R_plot([S[i](c) for c in ainvs], xmin, xmax, ymin, ymax, cols[i], "$" + base_field_gen_name + " \mapsto$ " + str(S[i].im_gens()[0].n(20))+"$\dots$") for i in range(n1)])
except:
return text("Unable to plot", (1, 1), fontsize=36)
def EC_nf_plot(K, ainvs, base_field_gen_name):
try:
n1 = K.signature()[0]
if n1 == 0:
return plot([])
R=[]
S=K.embeddings(RDF)
for s in S:
A=[s(c) for c in ainvs]
R.append(EC_R_plot_zone(Rx([A[4],A[3],A[1],1]),Rx([A[2],A[0]])))
xmin = min([r[0] for r in R])
xmax = max([r[1] for r in R])
ymin = min([r[2] for r in R])
ymax = max([r[3] for r in R])
cols = rainbow(n1) # Default choice of n colours
# However, these tend to be too pale, so we preset them for small values of n
if n1==1:
cols=["blue"]
elif n1==2:
cols=["red","blue"]
elif n1==3:
cols=["red","limegreen","blue"]
elif n1==4:
cols = ["red", "orange", "forestgreen", "blue"]
elif n1==5:
cols = ["red", "orange", "forestgreen", "blue", "darkviolet"]
elif n1==6:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet"]
elif n1==7:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet", "fuchsia"]
return sum([EC_R_plot([S[i](c) for c in ainvs], xmin, xmax, ymin, ymax, cols[i], "$" + base_field_gen_name + " \mapsto$ " + str(S[i].im_gens()[0].n(20))+"$\dots$") for i in range(n1)])
except:
return text("Unable to plot", (1, 1), fontsize=36)
def EC_nf_plot(E, base_field_gen_name):
K = E.base_field()
n1 = K.signature()[0]
if n1 == 0:
return plot([])
prec = 53
maxprec = 10 ** 6
while prec < maxprec: # Try to base change to R. May fail if resulting curve is almost singular, so increase precision.
try:
SR = K.embeddings(RealField(prec))
X = [E.base_extend(s) for s in SR]
break
except ArithmeticError:
prec *= 2
if prec >= maxprec:
return text("Unable to plot", (1, 1), fontsize="xx-large")
X = [e.plot() for e in X]
xmin = min([x.xmin() for x in X])
xmax = max([x.xmax() for x in X])
ymin = min([x.ymin() for x in X])
ymax = max([x.ymax() for x in X])
cols = ["blue", "red", "green", "orange", "brown"] # Preset colours, because rainbow tends to return too pale ones
if n1 > len(cols):
cols = rainbow(n1)
return sum([EC_R_plot([SR[i](a) for a in E.ainvs()], xmin, xmax, ymin, ymax, cols[i], "$" + base_field_gen_name + " \mapsto$ " + str(SR[i].im_gens()[0].n(20))) for i in range(n1)])
def guess_plot(obj, figsize=4):
r"""
Find the corresponding graphics object, if there is one.
TESTS::
sage: from sage_explorer import guess_plot
sage: guess_plot(sin)
Graphics object consisting of 1 graphics primitive
sage: guess_plot(list(cremona_curves(srange(35)))[0])
Graphics object consisting of 1 graphics primitive
sage: x, y = var('x y')
sage: g(x,y) = x**2 + y**2
sage: guess_plot(g)
Graphics3d Object
sage: type(guess_plot(Partition([4,3])))
...
<class 'NoneType'>
"""
plt = None
if hasattr(obj, 'number_of_arguments') and obj.number_of_arguments() == 2:
if type(figsize) == type(()):
if len(figsize) == 2:
urange, vrange = figsize
elif len(figsize) == 1:
urange, vrange = figsize, figsize
elif str(figsize).isnumeric():
urange = vrange = (-float(figsize) / 2, float(figsize) / 2)
try:
plt = plot3d(obj, urange, vrange)
except:
pass
return plt
try:
plt = plot(obj, figsize=figsize)
except:
try:
plt = obj.plot()
except:
try:
plt = plot(obj)
except:
pass
if plt is not None and plt._objects:
return plt
else:
return None
def plotit(k):
k = int(k[0])
# FIXME there could be a filename collission
fn = tempfile.mktemp(suffix=".png")
x = var('x')
p = plot(sin(k * x))
p.save(filename=fn)
data = file(fn).read()
os.remove(fn)
return data
def __init__(self, obj, figsize=4, name=None):
super(PlotWidget, self).__init__()
self.value = obj
if not name:
name = repr(obj)
svgfilename = path_join(SAGE_TMP, '%s.svg' % name)
self.plot = plot(obj, figsize=figsize)
self.plot.save(svgfilename)
self.name = name
self.children = [HTML(open(svgfilename, 'rb').read())]
def judgeFlight(self, flight, dbg=False):
"""Old version of flight fitness function."""
#times, result = self._scene.evaluateCrafts([flight])
# TODO define elsewhere
bat_Wh_cap = 15.5 * 650
times = pd.date_range(start='2020-11-28T08',
end='2020-11-30T08',
freq='120S',
tz='America/Detroit').to_series()
poses = flight.toPoses(times)
throughput = self._scene.posesToThroughput(flight, poses)
solar = flight._craft.calcSolarPower(poses, 36, -84)
battery = flight._craft.calcBatteryCharge(poses,
solar,
15.5 * 650,
constant_draw=109)
#print('up to', poses.z.max())
mSocStart = pd.to_datetime(times[0]) + pd.offsets.Hour(6)
mSoc = battery[mSocStart:].min() / bat_Wh_cap * 100
if dbg:
# The ridiculous size is needed for Sage 9.0
positions = (flight._trajectory.render() +
self._scene.render(size=20000)) #.scale(0.001)
else:
positions = None
# # Mean flight power in watts
meanFlightPower = flight.cycleEnergy / flight.cycleTime
# # Minimum throughput of any user in kbps
# thru = np.mean(result) / 1e3
# # Roughly Mb/J
# score = (thru / meanFlightPower).n()
#meanFlightPower = poses.power.mean()
thru = throughput.mean()[0]
#score = thru / meanFlightPower / 1e3
#score = thru * mSoc / 1e6
score = mSoc
if dbg:
from sage.all import plot, var
thruPlot = self._scene.plotResults(times, result) + plot(
[thru], (var('x'), min(times), max(times)), ymin=0)
else:
thruPlot = None
return score, thru, mSoc, flight.cycleTime, positions, thruPlot
def EC_nf_plot(E,base_field_gen_name):
K = E.base_field()
SR = K.embeddings(RR)
n1 = len(SR)
if n1 == 0:
return plot([])
X = [E.base_extend(s).plot() for s in SR]
xmin = min([x.xmin() for x in X])
xmax = max([x.xmax() for x in X])
ymin = min([x.ymin() for x in X])
ymax = max([x.ymax() for x in X])
cols = rainbow(n1)
return sum([EC_R_plot([SR[i](a) for a in E.ainvs()],xmin,xmax,ymin,ymax,cols[i],"$"+base_field_gen_name+" \mapsto$ "+str(SR[i].im_gens()[0].n(20))) for i in range(n1)])
def render_plotLfunction_from_db(db, dbTable, condition):
data_location = os.path.expanduser(
"~/data/lfunction_plots/{0}.db".format(db))
if not os.path.exists(data_location):
# We want to raise some exception so that the calling
# function can catch it and fall back to normal plotting
# when the database does not exist or doesn't have the
# plot. This seems like a reasonable exception to raise.
raise KeyError
try:
db = sqlite3.connect(data_location)
with db:
cur = db.cursor()
query = "SELECT start,end,points FROM {0} WHERE {1} LIMIT 1".format(dbTable,
condition)
cur.execute(query)
row = cur.fetchone()
db.close()
start,end,values = row
values = numpy.frombuffer(values)
step = (end - start)/values.size
pairs = [ (start + x * step, values[x] )
for x in range(0, values.size, 1)]
p = plot(spline(pairs), -30, 30, thickness = 0.4)
styleLfunctionPlot(p, 8)
except (sqlite3.OperationalError, TypeError):
# An OperationalError will happen when the database exists for some reason
# but it doesn't have the table. A TypeError will happen when there are no
# results returned, in which case row will be None and unpacking the tuple
# will fail. We turn both of these in KeyErrors, which can be caught by
# the calling function to fallback to normal plotting.
raise KeyError
fn = tempfile.mktemp(suffix=".png")
p.save(filename=fn, dpi = 100)
data = file(fn).read()
os.remove(fn)
response = make_response(data)
response.headers['Content-type'] = 'image/png'
return response
def EC_nf_plot(E, base_field_gen_name):
K = E.base_field()
SR = K.embeddings(RR)
n1 = len(SR)
if n1 == 0:
return plot([])
X = [E.base_extend(s).plot() for s in SR]
xmin = min([x.xmin() for x in X])
xmax = max([x.xmax() for x in X])
ymin = min([x.ymin() for x in X])
ymax = max([x.ymax() for x in X])
cols = rainbow(n1)
return sum([
EC_R_plot([SR[i](a) for a in E.ainvs()], xmin, xmax, ymin, ymax,
cols[i], "$" + base_field_gen_name + " \mapsto$ " +
str(SR[i].im_gens()[0].n(20))) for i in range(n1)
])
def EC_nf_plot(E, base_field_gen_name):
K = E.base_field()
n1 = K.signature()[0]
if n1 == 0:
return plot([])
prec = 53
maxprec = 10 ** 6
while prec < maxprec: # Try to base change to RR. May fail if resulting curve is almost singular, so increase precision.
try:
SR = K.embeddings(RealField(prec))
X = [E.base_extend(s) for s in SR]
break
except ArithmeticError:
prec *= 2
if prec >= maxprec:
return text("Unable to plot", (1, 1), fontsize=36)
try:
X = [e.plot() for e in X]
except:
return text("Unable to plot", (1, 1), fontsize=36)
xmin = min([x.xmin() for x in X])
xmax = max([x.xmax() for x in X])
ymin = min([x.ymin() for x in X])
ymax = max([x.ymax() for x in X])
cols = rainbow(n1) # Default choice of n colours
# Howver, these tend to be too pale, so we preset them for small values of n
if n1==1:
cols=["blue"]
elif n1==2:
cols=["red","blue"]
elif n1==3:
cols=["red","limegreen","blue"]
elif n1==4:
cols = ["red", "orange", "forestgreen", "blue"]
elif n1==5:
cols = ["red", "orange", "forestgreen", "blue", "darkviolet"]
elif n1==6:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet"]
elif n1==7:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet", "fuchsia"]
return sum([EC_R_plot([SR[i](a) for a in E.ainvs()], xmin, xmax, ymin, ymax, cols[i], "$" + base_field_gen_name + " \mapsto$ " + str(SR[i].im_gens()[0].n(20))+"$\dots$") for i in range(n1)])
def EC_R_plot(ainvs, xmin, xmax, ymin, ymax, colour, legend):
x = var('x')
y = var('y')
c = (xmin + xmax) / 2
d = (xmax - xmin)
return implicit_plot(
y**2 + ainvs[0] * x * y + ainvs[2] * y - x**3 - ainvs[1] * x**2 -
ainvs[3] * x - ainvs[4], (x, xmin, xmax), (y, ymin, ymax),
plot_points=500,
aspect_ratio="automatic",
color=colour
) + plot(
0,
xmin=c - 1e-5 * d,
xmax=c + 1e-5 * d,
ymin=ymin,
ymax=ymax,
aspect_ratio="automatic",
color=colour,
legend_label=legend
) # Add an extra plot outside the visible frame because implicit plots are buggy: their legend does not show (http://trac.sagemath.org/ticket/15903)
def EC_R_plot(ainvs, xmin, xmax, ymin, ymax, colour, legend):
x = var("x")
y = var("y")
c = (xmin + xmax) / 2
d = xmax - xmin
return implicit_plot(
y ** 2 + ainvs[0] * x * y + ainvs[2] * y - x ** 3 - ainvs[1] * x ** 2 - ainvs[3] * x - ainvs[4],
(x, xmin, xmax),
(y, ymin, ymax),
plot_points=1000,
aspect_ratio="automatic",
color=colour,
) + plot(
0,
xmin=c - 1e-5 * d,
xmax=c + 1e-5 * d,
ymin=ymin,
ymax=ymax,
aspect_ratio="automatic",
color=colour,
legend_label=legend,
) # Add an extra plot outside the visible frame because implicit plots are buggy: their legend does not show (http://trac.sagemath.org/ticket/15903)
def EC_nf_plot(E, base_field_gen_name):
K = E.base_field()
n1 = K.signature()[0]
if n1 == 0:
return plot([])
prec = 53
maxprec = 10 ** 6
while prec < maxprec: # Try to base change to RR. May fail if resulting curve is almost singular, so increase precision.
try:
SR = K.embeddings(RealField(prec))
X = [E.base_extend(s) for s in SR]
break
except ArithmeticError:
prec *= 2
if prec >= maxprec:
return text("Unable to plot", (1, 1), fontsize="xx-large")
X = [e.plot() for e in X]
xmin = min([x.xmin() for x in X])
xmax = max([x.xmax() for x in X])
ymin = min([x.ymin() for x in X])
ymax = max([x.ymax() for x in X])
cols = rainbow(n1) # Default choice of n colours
# Howver, these tend to be too pale, so we preset them for small values of n
if n1==1:
cols=["blue"]
elif n1==2:
cols=["red","blue"]
elif n1==3:
cols=["red","limegreen","blue"]
elif n1==4:
cols = ["red", "orange", "forestgreen", "blue"]
elif n1==5:
cols = ["red", "orange", "forestgreen", "blue", "darkviolet"]
elif n1==6:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet"]
elif n1==7:
cols = ["red", "darkorange", "gold", "forestgreen", "blue", "darkviolet", "fuchsia"]
return sum([EC_R_plot([SR[i](a) for a in E.ainvs()], xmin, xmax, ymin, ymax, cols[i], "$" + base_field_gen_name + " \mapsto$ " + str(SR[i].im_gens()[0].n(20))+"$\dots$") for i in range(n1)])
