def __init__(self):
        # An array of accessible functions
        self.functions = {
        # Logarithms
            'ln': ln,
            'log': lambda a, b=10: dmath.log(a, b),
        # Trigonometric Functions
            'sin': lambda x: handle_type(sin(x)),
            'cos': lambda x: handle_type(cos(x)),
            'tan': lambda x: handle_type(tan(x)),
            'arcsin': lambda x: handle_type(dmath.asin(x)),
            'arccos': lambda x: handle_type(dmath.acos(x)),
            'arctan': lambda x: handle_type(dmath.atan(x)),
            'sinh': lambda x: handle_type(dmath.sinh(x)),
            'cosh': lambda x: handle_type(dmath.cosh(x)),
            'tanh': lambda x: handle_type(dmath.tanh(x)),
            'arcsinh': lambda z: handle_type(log(z + (Integer(1)
                + z**Integer(2))**Real('0.5'))),
            'arccosh': lambda z: ht(log(z + (z + Integer(1))**Real('0.5')
                * (z - Integer(1))**Real('0.5'))),
            'arctanh': lambda z: handle_type(log(Integer(1) + z)
                - log(Integer(1) - z))/Integer(2),
            'degrees': lambda x: handle_type(degrees(x)),
        # Statistics
            'nCr': nCr,
            'nPr': nPr,
            'binomialpdf': binomialpdf,
            'binomialcdf': binomialcdf,
            'poissonpdf': poissonpdf,
            'poissoncdf': poissoncdf,
            'normalcdf': normalcdf,
            'mean': lambda a: a.mean(),
            'median': lambda a: a.median(),
            'mode': lambda a: a.mode(),
            'variance': lambda a: a.variance(),
            'stdev': lambda a: a.stdev(),
            'sxx': lambda a: a.Sxx(),
        # Manipulation of functions
            'expand': expand,
            'differentiate': lambda a, b=Symbol('x'):\
                partial_differential(a, b),
            'integrate': lambda y, a=None, b=None, x=Symbol('x'):\
                partial_integral(y, x) if a == None or b == None \
                else partial_integral(y, x).limit(a, b, variable=x),
            'romberg': lambda f, a, b, *n: f.romberg_integral(a, b, *n),
            'trapeziumrule': lambda f, a, b, *n:\
                f.trapezoidal_integral(a, b, *n),
            'simpsonrule': lambda f, a, b, *n: f.simpson_integral(a, b, *n),
            'simpsonthreeeightrule': lambda f, a, b, *n: f.simpson38_integral(a, b, *n),
            'roots': lambda a, n=1000: List(*list(a.roots(n))),
            'maxima': lambda a, n=100: List(*a.maxima(n)),
            'minima': lambda a, n=100: List(*a.minima(n)),
        # Vectors
            'norm': lambda a: a.norm(),
        # Matrices
            'transpose': lambda a: a.transpose(),
            'order': lambda a: '{}×{}'.format(*a.order()),
            'eval': lambda a, b, c=None: a(b, variable=c),
            'identity': identity_matrix,
            'diag': diagonal_matrix,
            'inv': lambda a: a.inverse(),
            'invert': lambda a: a.inverse(),
            'decompose': lambda a: List(*a.LU_decomposition()),
            'trace': lambda a: a.trace(),
            'poly': lambda a: a.characteristic_polynomial(),
            'adj': lambda a: a.adjgate(),
            'zero': Matrix,
            'minor': lambda a, b, c: a.minor(b, c),
            'det': lambda a: a.determinant(),
            'eigenvalues': lambda a: List(*a.eigenvalues()),
            'rank': lambda a: a.rank(),
        # Complex Numbers
            're': lambda a: a.real,
            'im': lambda a: a.imag,
            'arg': lambda a: a.argument(),
            'conj': lambda a: a.conjugate(),
        # Misc
            'yum': pi,
            'plot': lambda f, a=-10, b=10: StrWithHtml('testing...',
                '''<canvas id="{0}" onclick="new CartesianPlot('{0}').simplePlot('{1}',{2},{3})" width="600" height="600">{4}</canvas>'''.format('graph-'
                    + str(random.randint(1, 1000)), f, a, b, gnuplot(f, a, b).html)),
            'polarplot': lambda f, a=-pi(), b=pi(): StrWithHtml('testing...',
                '''<canvas id="{0}" onclick="new PolarPlot('{0}').simplePlot('{1}',{2},{3})" width="600" height="600"></canvas>'''.format('graph-'
                    + str(random.randint(1, 1000)), f, a, b)),
            'testcanvas': lambda: StrWithHtml('testing...',
                '''<canvas id="testcanvas" width="600" height="600"></canvas>'''),
            'evalbetween': evalute_between,
            'factorial': factorial,
            'factors': lambda a: a.factors(),
            'decimal': lambda a: Decimal(a) if not isinstance(a, List)\
               else List(*list(map(Decimal, a))),
            'complex': lambda a: complex(a) if not isinstance(a, List)\
               else List(*list(map(complex, a))),
            'round': lambda a: handle_type(round),
            'list': lambda a: str(list(a)),
            'gnuplot': gnuplot,
            'type': lambda a: str(type(a)),
            'typelist': lambda b: ', '.join(map(lambda a: str(type(a)), b)),
            'typematrix': lambda c: '; '.join(map(lambda b:
                ', '.join(map(lambda a: str(type(a)), b)), c)),
            'setprec': self.set_precision,
            'setexact': self.set_exact,
            'about': lambda:\
                StrWithHtml('Copyright Tom Wright <*****@*****.**>',
                '''<img src="./images/about.png" />
                <br>This program was written by Tom Wright
                 <*****@*****.**>'''),
            'help': help.help,
            'quit': exit,
        }

        # An array of accessible post functions
        self.post_functions = {
            '!': factorial,
            'degs': radians
        }

        # An array of standard constants
        self.consts = {
            'pi': pi(),
            'g': Real('9.81'),
            'h': Real('6.62606896e-34'),
        }

        # An array of miscellaneous internal variables such as ans
        # which stores the previous result
        self.objects = {'ans': Integer(0)}
示例#2
0
Circle = namedtuple("Circle", "x y r")

def circle_cross((x0, y0, r0), (x1, y1, r1)):
    d = vdist(Vec(x0, y0), Vec(x1, y1))
    if d >= r0 + r1 or d <= abs(r0 - r1):
        return []

    s = (r0 + r1 + d) / D2
    a = sqrt(s * (s - d) * (s - r0) * (s - r1))
    h = D2 * a / d
    dr = Vec(x1 - x0, y1 - y0)
    dx = vscale(sqrt(r0 ** 2 - h ** 2), vnorm(dr))
    ang = vangle(dr) if \
          r0 ** 2 + d ** 2 > r1 ** 2 \
          else pi + vangle(dr)
    da = asin(h / r0)
    return map(anorm, [ang - da, ang + da])

# Angles of the start and end points of the circle arc.
Angle2 = namedtuple("Angle2", "a1 a2")

Arc = namedtuple("Arc", "c aa")

arcPoint = lambda (x, y, r), a: \
    vadd(Vec(x, y), Vec(r * cos(a), r * sin(a)))

arc_start  = lambda (c, (a0, a1)):  arcPoint(c, a0)
arc_mid    = lambda (c, (a0, a1)):  arcPoint(c, (a0 + a1) / D2)
arc_end    = lambda (c, (a0, a1)):  arcPoint(c, a1)
arc_center = lambda ((x, y, r), _): Vec(x, y)
示例#3
0
def test_asin():

    for x in range(-1, 1):
        assert dmath.asin(x) == math.asin(x)
        assert grad(dmath.asin)(x) == approx(1 / math.sqrt(1 - x**2))