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Project: demo
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%var x y z g = golden_ratio; r = 4.77 p = 2 - (cos(x + g*y) + cos(x - g*y) + cos(y + g*z) + cos(y - g*z) + cos(z - g*x) + cos(z + g*x)) show(implicit_plot3d(p, (x, -r, r), (y, -r, r), (z, -r, r), plot_points=30, color='orange', mesh=1, opacity=.7), spin=1)
3D rendering not yet implemented
time??
File: /projects/sage/sage-7.5/local/lib/python2.7/site-packages/smc_sagews/sage_salvus.py Source: class Time: """ Time execution of code exactly once in Salvus by: - putting %time at the top of a cell to time execution of the entire cell - put %time at the beginning of line to time execution of just that line - write time('some code') to executation of the contents of the string. If you want to time repeated execution of code for benchmarking purposes, use the timeit command instead. """ def __init__(self, start=False): if start: from sage.all import walltime, cputime self._start_walltime = walltime() self._start_cputime = cputime() def before(self, code): return Time(start=True) def after(self, code): from sage.all import walltime, cputime print("CPU time: %.2f s, Wall time: %.2f s" % (cputime(self._start_cputime), walltime(self._start_walltime))) self._start_cputime = self._start_walltime = None def __call__(self, code): from sage.all import walltime, cputime not_as_decorator = self._start_cputime is None if not_as_decorator: self.before(code) salvus.execute(code) if not_as_decorator: self.after(code)
numerical_integral(1 + x + x^2, 0, 3)[0] # [1] gives error bound
16.500000000000004
v = [(0,0,0)] for i in range(1000): v.append([a+random()-.5 for a in v[-1]]) line3d(v, color='red', thickness=3, spin=3)
3D rendering not yet implemented
%time stats.TimeSeries(1000000).randomize('normal').sums().plot()
CPU time: 0.34 s, Wall time: 0.35 s
@interact def g(n=[1..10]): print n^3
Interact: please open in CoCalc
def f(n): return factor(n+2)
f(10)
2^2 * 3
for i in range(10): print i sleep(1)
0 1 2 3 4 5 6 7 8 9
next_prime(2017)
2027
%var x, y plot3d(x^3 + y^3, (x,0,2), (y,0,2))
3D rendering not yet implemented
g = graphs.RandomGNM(15, 20) # 15 vertices and 20 edges show(g) g.incidence_matrix()
d3-based renderer not yet implemented
[1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0] [0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0] [0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0] [0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 1 0 0 0] [0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0] [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1] [0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0] [0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1]
# what is next year like? factor(2018)
2 * 1009
Example x3x^3

Example x3x^3

2 + 3
5
stats.TimeSeries(1000).randomize('normal').sums().plot()
points = [(2,0,0), (0,2,0), (0,0,2), (-1,0,0), (0,-1,0), (0,0,-1)] show(LatticePolytope(points).plot3d(), spin=5)
3D rendering not yet implemented
g
Graph on 15 vertices
show(g)
d3-based renderer not yet implemented