def __init__(self):
self.new_tool = Tools()
self.matrix_play = []
self.row = 0
self.column = 0
self.value = 0
self.new_menu = Menus()
self.return_game = ""
self.boards = integrator.integrator()
def some_func(bot, update):
pass
if not update.effective_message.photo:
update.effective_message.reply_text(
text="This bot is only capable of Computer Vision Tasks!")
else:
msg = update.effective_message
file_id = msg.photo[-1].file_id
photo = bot.get_file(file_id)
download_image(photo["file_path"], 'wassup')
update.effective_message.reply_text(
text=i.beautify(i.integrator('wassup.jpeg')))
def __init__(self):
"""
Constructs the SIS response function class
"""
self.Igap = 1.0
self.Vgap = 1.0
self.Rn = 1.0
self.yIntercept = 0.0
self.noPoints = 201
self.__bias__ = 0.0 # used in calculating the KK transform
self.__ikk__ = range(self.noPoints)
self.__idc__ = range(self.noPoints)
self.__vdc__ = range(self.noPoints)
self.__Int__ = integrator.integrator()
self.__Int__.__jMax__ = 12
self.__KK_vMax__ = 10.0
self.separator = "\t" # data value separator in idc and ikk files
def test_failsdifferenttend(self):
int_c = integrator(self.int_coarse.tstart, 1e-10+self.int_coarse.tend, self.int_coarse.nsteps)
with self.assertRaises(AssertionError):
ts = timeslice(self.int_fine, int_c, 1e-10, 5)
generate_x_vs_t = False
generate_x_vs_h = False
generate_x_vs_a = False
generate_x_vs_x0 = False
generate_ibar = False
generate_xyz_vs_t = False
# Get a simulator, an integrator, and a analytic
simulator = sim.Simulator(n=n,
x0=x0,
El=El,
Eh=Eh,
a=a,
alpha=alpha,
num_groups=num_groups)
integrator = integ.integrator(n=n, x0=x0, Eh=Eh, El=El, a=a, alpha=alpha, h=h)
analytic = an.analytic(n=n, x0=x0, Eh=Eh, El=El, a=a, alpha=alpha, h=h)
simulator_cont = sim_cont.Simulator(n=n,
x0=x0,
min_effort=El,
max_effort=Eh,
a=a,
alpha=alpha,
num_groups=num_groups)
simulator_tri = sim_tri.Simulator(n=n,
x0=x0,
y0=y0,
El=El,
Em=Em,
Eh=Eh,
a=a,
import sys
sys.setrecursionlimit(10000)
a = 0
b = 1
nevals = 0
def f1(x):
global nevals
nevals += 1
return np.sqrt(x)
integral1 = integrator(f1)
Q = integral1.adaptive_trapz(a, b)
print('Function:\t\t f(x) = sqrt(x)')
print('Absolute accuracy:\t', 1e-4)
print('Relative accuracy:\t', 1e-4)
print('Integral bounds:\t', a, 4)
print('Integrand evaluations: \t', nevals)
print('Numeric integral:\t', Q)
print('Analytic integral: \t', 2 / 3)
print('')
nevals = 0
def f2(x):
global nevals
def test_integrate_x_squared(self):
f = lambda x: x ** 2
integrated = integrator(f, 0, 1, n_steps=10 ** 5)
npt.assert_allclose(integrated, 1 / 3, rtol=1e-4)
def test_integrate_planck(self):
T = 300
integrated = integrator(B_nu, 1e6, 1e16, T, n_steps=10 ** 5)
analytic = B(T)
npt.assert_allclose(integrated, analytic, rtol=1e-4)
def test_integrate_planck(self):
T = 300
integrated = integrator(B_nu, 1e6, 1e16, T, n_steps=10**5)
analytic = B(T)
npt.assert_allclose(integrated, analytic, rtol=1e-4)
def test_failgenericrun(self):
integ = integrator(self.t[0], self.t[1], self.nsteps)
sol = solution(np.array([-1]))
with self.assertRaises(NotImplementedError):
integ.run(sol)
def test_nstepfloatfail(self):
with self.assertRaises(AssertionError):
integ = integrator(0.0, 1.0, 1.15)
def test_nstepnegativefail(self):
with self.assertRaises(AssertionError):
integ = integrator(0.0, 1.0, -10)
def test_wrongboundsfail(self):
with self.assertRaises(AssertionError):
integ = integrator(0.0, -1.0, 10)
def test_caninstantiate(self): integ = integrator(self.t[0], self.t[1], self.nsteps)
def test_integrate_x_squared(self):
f = lambda x: x**2
integrated = integrator(f, 0, 1, n_steps=10**5)
npt.assert_allclose(integrated, 1 / 3, rtol=1e-4)
def test_failwrongu0(self):
integ = integrator(self.t[0], self.t[1], self.nsteps)
with self.assertRaises(AssertionError):
integ.run(-1)
import integrator
from MAV import MAV
import state_viewer
import matplotlib.pyplot as plt
my_mav = MAV('hw1_1')
my_mav.state0
my_mav.FMeq
[t, s] = integrator.integrator(my_mav)
state_viewer.open_GUI(t, s)
