MMTEB: Massive Multilingual Text Embedding Benchmark
Paper • 2502.13595 • Published • 49
Datasets:
title stringclasses 1
value | text stringlengths 46 1.11M | id stringlengths 27 30 |
|---|---|---|
sympy/utilities/lambdify.py/_EvaluatorPrinter/_preprocess
class _EvaluatorPrinter: def _preprocess(self, args, expr):
"""Preprocess args, expr to replace arguments that do not map
to valid Python identifiers.
Returns string form of args, and updated expr.
"""
from sympy impor... | apositive_train_query0_00000 | |
examples/all.py/__import__
def __import__(name, globals=None, locals=None, fromlist=None):
"""An alternative to the import function so that we can import
modules defined as strings.
This code was taken from: http://docs.python.org/lib/examples-imp.html
"""
# Fast path: see if the module has already... | negative_train_query0_00000 | |
examples/all.py/load_example_module
def load_example_module(example):
"""Loads modules based upon the given package name"""
mod = __import__(example)
return mod | negative_train_query0_00001 | |
examples/all.py/run_examples
def run_examples(windowed=False, quiet=False, summary=True):
"""Run all examples in the list of modules.
Returns a boolean value indicating whether all the examples were
successful.
"""
successes = []
failures = []
examples = TERMINAL_EXAMPLES
if windowed:
... | negative_train_query0_00002 | |
examples/all.py/run_example
def run_example(example, reporter=None):
"""Run a specific example.
Returns a boolean value indicating whether the example was successful.
"""
if reporter:
reporter.write(example)
else:
print("=" * 79)
print("Running: ", example)
try:
... | negative_train_query0_00003 | |
examples/all.py/suppress_output
def suppress_output(fn):
"""Suppresses the output of fn on sys.stdout."""
save_stdout = sys.stdout
try:
sys.stdout = DummyFile()
fn()
finally:
sys.stdout = save_stdout | negative_train_query0_00004 | |
examples/all.py/show_summary
def show_summary(successes, failures, reporter=None):
"""Shows a summary detailing which examples were successful and which failed."""
if reporter:
reporter.write("-" * reporter.terminal_width)
if failures:
reporter.write("FAILED:\n", "Red")
f... | negative_train_query0_00005 | |
examples/all.py/main
def main(*args, **kws):
"""Main script runner"""
parser = optparse.OptionParser()
parser.add_option('-w', '--windowed', action="store_true", dest="windowed",
help="also run examples requiring windowed environment")
parser.add_option('-q', '--quiet', action="store_true", dest... | negative_train_query0_00006 | |
examples/all.py/DummyFile/write
class DummyFile: def write(self, x):
pass | negative_train_query0_00007 | |
examples/intermediate/vandermonde.py/symbol_gen
def symbol_gen(sym_str):
"""Symbol generator
Generates sym_str_n where n is the number of times the generator
has been called.
"""
n = 0
while True:
yield Symbol("%s_%d" % (sym_str, n))
n += 1 | negative_train_query0_00008 | |
examples/intermediate/vandermonde.py/comb_w_rep
def comb_w_rep(n, k):
"""Combinations with repetition
Returns the list of k combinations with repetition from n objects.
"""
if k == 0:
return [[]]
combs = [[i] for i in range(n)]
for i in range(k - 1):
curr = []
for p in c... | negative_train_query0_00009 | |
examples/intermediate/vandermonde.py/vandermonde
def vandermonde(order, dim=1, syms='a b c d'):
"""Computes a Vandermonde matrix of given order and dimension.
Define syms to give beginning strings for temporary variables.
Returns the Matrix, the temporary variables, and the terms for the
polynomials.
... | negative_train_query0_00010 | |
examples/intermediate/vandermonde.py/gen_poly
def gen_poly(points, order, syms):
"""Generates a polynomial using a Vandermonde system"""
num_pts = len(points)
if num_pts == 0:
raise ValueError("Must provide points")
dim = len(points[0]) - 1
if dim > len(syms):
raise ValueError("Must ... | negative_train_query0_00011 | |
examples/intermediate/vandermonde.py/main
def main():
order = 2
V, tmp_syms, _ = vandermonde(order)
print("Vandermonde matrix of order 2 in 1 dimension")
pprint(V)
print('-'*79)
print("Computing the determinant and comparing to \sum_{0<i<j<=3}(a_j - a_i)")
det_sum = 1
for j in range(or... | negative_train_query0_00012 | |
examples/intermediate/infinite_1d_box.py/X_n
def X_n(n, a, x):
"""
Returns the wavefunction X_{n} for an infinite 1D box
``n``
the "principal" quantum number. Corresponds to the number of nodes in
the wavefunction. n >= 0
``a``
width of the well. a > 0
``x``
x coord... | negative_train_query0_00013 | |
examples/intermediate/infinite_1d_box.py/E_n
def E_n(n, a, mass):
"""
Returns the Energy psi_{n} for a 1d potential hole with infinity borders
``n``
the "principal" quantum number. Corresponds to the number of nodes in
the wavefunction. n >= 0
``a``
width of the well. a > 0
... | negative_train_query0_00014 | |
examples/intermediate/infinite_1d_box.py/energy_corrections
def energy_corrections(perturbation, n, a=10, mass=0.5):
"""
Calculating first two order corrections due to perturbation theory and
returns tuple where zero element is unperturbated energy, and two second
is corrections
``n``
the "... | negative_train_query0_00015 | |
examples/intermediate/infinite_1d_box.py/main
def main():
print()
print("Applying perturbation theory to calculate the ground state energy")
print("of the infinite 1D box of width ``a`` with a perturbation")
print("which is linear in ``x``, up to second order in perturbation.")
print()
x, _a = ... | negative_train_query0_00016 | |
examples/intermediate/trees.py/T
def T(x):
return x + x**2 + 2*x**3 + 4*x**4 + 9*x**5 + 20*x**6 + 48 * x**7 + \
115*x**8 + 286*x**9 + 719*x**10 | negative_train_query0_00017 | |
examples/intermediate/trees.py/A
def A(x):
return 1 + T(x) - T(x)**2/2 + T(x**2)/2 | negative_train_query0_00018 | |
examples/intermediate/trees.py/main
def main():
x = Symbol("x")
s = Poly(A(x), x)
num = list(reversed(s.coeffs()))[:11]
print(s.as_expr())
print(num) | negative_train_query0_00019 | |
examples/intermediate/differential_equations.py/main
def main():
x = Symbol("x")
f = Function("f")
eq = Eq(f(x).diff(x), f(x))
print("Solution for ", eq, " : ", dsolve(eq, f(x)))
eq = Eq(f(x).diff(x, 2), -f(x))
print("Solution for ", eq, " : ", dsolve(eq, f(x)))
eq = Eq(x**2*f(x).diff(x),... | negative_train_query0_00020 | |
examples/intermediate/print_gtk.py/main
def main():
x = Symbol('x')
example_limit = Limit(sin(x)/x, x, 0)
print_gtk(example_limit)
example_integral = Integral(x, (x, 0, 1))
print_gtk(example_integral) | negative_train_query0_00021 | |
examples/intermediate/coupled_cluster.py/get_CC_operators
def get_CC_operators():
"""
Returns a tuple (T1,T2) of unique operators.
"""
i = symbols('i', below_fermi=True, cls=Dummy)
a = symbols('a', above_fermi=True, cls=Dummy)
t_ai = AntiSymmetricTensor('t', (a,), (i,))
ai = NO(Fd(a)*F(i))
... | negative_train_query0_00022 | |
examples/intermediate/coupled_cluster.py/main
def main():
print()
print("Calculates the Coupled-Cluster energy- and amplitude equations")
print("See 'An Introduction to Coupled Cluster Theory' by")
print("T. Daniel Crawford and Henry F. Schaefer III")
print("Reference to a Lecture Series: http://ver... | negative_train_query0_00023 | |
examples/intermediate/partial_differential_eqs.py/main
def main():
r, phi, theta = symbols("r,phi,theta")
Xi = Function('Xi')
R, Phi, Theta, u = map(Function, ['R', 'Phi', 'Theta', 'u'])
C1, C2 = symbols('C1,C2')
pprint("Separation of variables in Laplace equation in spherical coordinates")
ppr... | negative_train_query0_00024 | |
examples/intermediate/sample.py/sample2d
def sample2d(f, x_args):
"""
Samples a 2d function f over specified intervals and returns two
arrays (X, Y) suitable for plotting with matlab (matplotlib)
syntax. See examples\mplot2d.py.
f is a function of one variable, such as x**2.
x_args is an interv... | negative_train_query0_00025 | |
examples/intermediate/sample.py/sample3d
def sample3d(f, x_args, y_args):
"""
Samples a 3d function f over specified intervals and returns three
2d arrays (X, Y, Z) suitable for plotting with matlab (matplotlib)
syntax. See examples\mplot3d.py.
f is a function of two variables, such as x**2 + y**2.... | negative_train_query0_00026 | |
examples/intermediate/sample.py/sample
def sample(f, *var_args):
"""
Samples a 2d or 3d function over specified intervals and returns
a dataset suitable for plotting with matlab (matplotlib) syntax.
Wrapper for sample2d and sample3d.
f is a function of one or two variables, such as x**2.
var_ar... | negative_train_query0_00027 | |
examples/intermediate/sample.py/meshgrid
def meshgrid(x, y):
"""
Taken from matplotlib.mlab.meshgrid.
"""
x = np.array(x)
y = np.array(y)
numRows, numCols = len(y), len(x)
x.shape = 1, numCols
X = np.repeat(x, numRows, 0)
y.shape = numRows, 1
... | negative_train_query0_00028 | |
examples/intermediate/mplot3d.py/mplot3d
def mplot3d(f, var1, var2, show=True):
"""
Plot a 3d function using matplotlib/Tk.
"""
import warnings
warnings.filterwarnings("ignore", "Could not match \S")
p = import_module('pylab')
# Try newer version first
p3 = import_module('mpl_toolkits.... | negative_train_query0_00029 | |
examples/intermediate/mplot3d.py/main
def main():
x = Symbol('x')
y = Symbol('y')
mplot3d(x**2 - y**2, (x, -10.0, 10.0, 20), (y, -10.0, 10.0, 20)) | negative_train_query0_00030 | |
examples/intermediate/mplot2d.py/mplot2d
def mplot2d(f, var, show=True):
"""
Plot a 2d function using matplotlib/Tk.
"""
import warnings
warnings.filterwarnings("ignore", "Could not match \S")
p = import_module('pylab')
if not p:
sys.exit("Matplotlib is required to use mplot2d.")
... | negative_train_query0_00031 | |
examples/intermediate/mplot2d.py/main
def main():
x = Symbol('x')
# mplot2d(log(x), (x, 0, 2, 100))
# mplot2d([sin(x), -sin(x)], (x, float(-2*pi), float(2*pi), 50))
mplot2d([sqrt(x), -sqrt(x), sqrt(-x), -sqrt(-x)], (x, -40.0, 40.0, 80)) | negative_train_query0_00032 | |
examples/beginner/limits_examples.py/sqrt3
def sqrt3(x):
return x**Rational(1, 3) | negative_train_query0_00033 | |
examples/beginner/limits_examples.py/show
def show(computed, correct):
print("computed:", computed, "correct:", correct) | negative_train_query0_00034 | |
examples/beginner/limits_examples.py/main
def main():
x = Symbol("x")
show( limit(sqrt(x**2 - 5*x + 6) - x, x, oo), -Rational(5)/2 )
show( limit(x*(sqrt(x**2 + 1) - x), x, oo), Rational(1)/2 )
show( limit(x - sqrt(x**3 - 1), x, oo), Rational(0) )
show( limit(log(1 + exp(x))/x, x, -oo), Rational(... | negative_train_query0_00035 | |
examples/beginner/series.py/main
def main():
x = Symbol('x')
e = 1/cos(x)
print('')
print("Series for sec(x):")
print('')
pprint(e.series(x, 0, 10))
print("\n")
e = 1/sin(x)
print("Series for csc(x):")
print('')
pprint(e.series(x, 0, 4))
print('') | negative_train_query0_00036 | |
examples/beginner/precision.py/main
def main():
x = Pow(2, 50, evaluate=False)
y = Pow(10, -50, evaluate=False)
# A large, unevaluated expression
m = Mul(x, y, evaluate=False)
# Evaluating the expression
e = S(2)**50/S(10)**50
print("%s == %s" % (m, e)) | negative_train_query0_00037 | |
examples/beginner/plotting_nice_plot.py/main
def main():
fun1 = cos(x)*sin(y)
fun2 = sin(x)*sin(y)
fun3 = cos(y) + log(tan(y/2)) + 0.2*x
PygletPlot(fun1, fun2, fun3, [x, -0.00, 12.4, 40], [y, 0.1, 2, 40]) | negative_train_query0_00038 | |
examples/beginner/print_pretty.py/main
def main():
x = Symbol("x")
y = Symbol("y")
pprint( x**x )
print('\n') # separate with two blank likes
pprint(x**2 + y + x)
print('\n')
pprint(sin(x)**x)
print('\n')
pprint( sin(x)**cos(x) )
print('\n')
pprint( sin(x)/(cos(x)**2 * ... | negative_train_query0_00039 | |
examples/beginner/expansion.py/main
def main():
a = Symbol('a')
b = Symbol('b')
e = (a + b)**5
print("\nExpression:")
pprint(e)
print('\nExpansion of the above expression:')
pprint(e.expand())
print() | negative_train_query0_00040 | |
examples/beginner/differentiation.py/main
def main():
a = Symbol('a')
b = Symbol('b')
e = (a + 2*b)**5
print("\nExpression : ")
print()
pprint(e)
print("\n\nDifferentiating w.r.t. a:")
print()
pprint(e.diff(a))
print("\n\nDifferentiating w.r.t. b:")
print()
pprint(e.diff... | negative_train_query0_00041 | |
examples/beginner/functions.py/main
def main():
a = Symbol('a')
b = Symbol('b')
e = log((a + b)**5)
print()
pprint(e)
print('\n')
e = exp(e)
pprint(e)
print('\n')
e = log(exp((a + b)**5))
pprint(e)
print | negative_train_query0_00042 | |
examples/beginner/substitution.py/main
def main():
x = sympy.Symbol('x')
y = sympy.Symbol('y')
e = 1/sympy.cos(x)
print()
pprint(e)
print('\n')
pprint(e.subs(sympy.cos(x), y))
print('\n')
pprint(e.subs(sympy.cos(x), y).subs(y, x**2))
e = 1/sympy.log(x)
e = e.subs(x, sympy.F... | negative_train_query0_00043 | |
examples/beginner/basic.py/main
def main():
a = Symbol('a')
b = Symbol('b')
c = Symbol('c')
e = ( a*b*b + 2*b*a*b )**c
print('')
pprint(e)
print('') | negative_train_query0_00044 | |
examples/advanced/grover_example.py/demo_vgate_app
def demo_vgate_app(v):
for i in range(2**v.nqubits):
print('qapply(v*IntQubit(%i, %r))' % (i, v.nqubits))
pprint(qapply(v*IntQubit(i, v.nqubits)))
qapply(v*IntQubit(i, v.nqubits)) | negative_train_query0_00045 | |
examples/advanced/grover_example.py/black_box
def black_box(qubits):
return True if qubits == IntQubit(1, qubits.nqubits) else False | negative_train_query0_00046 | |
examples/advanced/grover_example.py/main
def main():
print()
print('Demonstration of Grover\'s Algorithm')
print('The OracleGate or V Gate carries the unknown function f(x)')
print('> V|x> = ((-1)^f(x))|x> where f(x) = 1 when x = a (True in our case)')
print('> and 0 (False in our case) otherwise')
... | negative_train_query0_00047 | |
examples/advanced/autowrap_integrators.py/main
def main():
print(__doc__)
# arrays are represented with IndexedBase, indices with Idx
m = Symbol('m', integer=True)
i = Idx('i', m)
A = IndexedBase('A')
B = IndexedBase('B')
x = Symbol('x')
print("Compiling ufuncs for radial harmonic osc... | negative_train_query0_00048 | |
examples/advanced/fem.py/bernstein_space
def bernstein_space(order, nsd):
if nsd > 3:
raise RuntimeError("Bernstein only implemented in 1D, 2D, and 3D")
sum = 0
basis = []
coeff = []
if nsd == 1:
b1, b2 = x, 1 - x
for o1 in range(0, order + 1):
for o2 in range(0,... | negative_train_query0_00049 | |
examples/advanced/fem.py/create_point_set
def create_point_set(order, nsd):
h = Rational(1, order)
set = []
if nsd == 1:
for i in range(0, order + 1):
x = i*h
if x <= 1:
set.append((x, y))
if nsd == 2:
for i in range(0, order + 1):
x ... | negative_train_query0_00050 | |
examples/advanced/fem.py/create_matrix
def create_matrix(equations, coeffs):
A = zeros(len(equations))
i = 0
j = 0
for j in range(0, len(coeffs)):
c = coeffs[j]
for i in range(0, len(equations)):
e = equations[i]
d, _ = reduced(e, [c])
A[i, j] = d[0]
... | negative_train_query0_00051 | |
examples/advanced/fem.py/main
def main():
t = ReferenceSimplex(2)
fe = Lagrange(2, 2)
u = 0
# compute u = sum_i u_i N_i
us = []
for i in range(0, fe.nbf()):
ui = Symbol("u_%d" % i)
us.append(ui)
u += ui*fe.N[i]
J = zeros(fe.nbf())
for i in range(0, fe.nbf()):
... | negative_train_query0_00052 | |
examples/advanced/fem.py/ReferenceSimplex/__init__
class ReferenceSimplex: def __init__(self, nsd):
self.nsd = nsd
if nsd <= 3:
coords = symbols('x,y,z')[:nsd]
else:
coords = [Symbol("x_%d" % d) for d in range(nsd)]
self.coords = coords | negative_train_query0_00053 | |
examples/advanced/fem.py/ReferenceSimplex/integrate
class ReferenceSimplex: def integrate(self, f):
coords = self.coords
nsd = self.nsd
limit = 1
for p in coords:
limit -= p
intf = f
for d in range(0, nsd):
p = coords[d]
limit += p... | negative_train_query0_00054 | |
examples/advanced/fem.py/Lagrange/__init__
class Lagrange: def __init__(self, nsd, order):
self.nsd = nsd
self.order = order
self.compute_basis() | negative_train_query0_00055 | |
examples/advanced/fem.py/Lagrange/nbf
class Lagrange: def nbf(self):
return len(self.N) | negative_train_query0_00056 | |
examples/advanced/fem.py/Lagrange/compute_basis
class Lagrange: def compute_basis(self):
order = self.order
nsd = self.nsd
N = []
pol, coeffs, basis = bernstein_space(order, nsd)
points = create_point_set(order, nsd)
equations = []
for p in points:
... | negative_train_query0_00057 | |
examples/advanced/autowrap_ufuncify.py/main
def main():
print(__doc__)
x = symbols('x')
# a numpy array we can apply the ufuncs to
grid = np.linspace(-1, 1, 1000)
# set mpmath precision to 20 significant numbers for verification
mpmath.mp.dps = 20
print("Compiling legendre ufuncs and ch... | negative_train_query0_00058 | |
examples/advanced/dense_coding_example.py/main
def main():
psi = superposition_basis(2)
psi
# Dense coding demo:
# Assume Alice has the left QBit in psi
print("An even superposition of 2 qubits. Assume Alice has the left QBit.")
pprint(psi)
# The corresponding gates applied to Alice's QB... | negative_train_query0_00059 | |
examples/advanced/qft.py/u
def u(p, r):
""" p = (p1, p2, p3); r = 0,1 """
if r not in [1, 2]:
raise ValueError("Value of r should lie between 1 and 2")
p1, p2, p3 = p
if r == 1:
ksi = Matrix([[1], [0]])
else:
ksi = Matrix([[0], [1]])
a = (sigma1*p1 + sigma2*p2 + sigma3*p3... | negative_train_query0_00060 | |
examples/advanced/qft.py/v
def v(p, r):
""" p = (p1, p2, p3); r = 0,1 """
if r not in [1, 2]:
raise ValueError("Value of r should lie between 1 and 2")
p1, p2, p3 = p
if r == 1:
ksi = Matrix([[1], [0]])
else:
ksi = -Matrix([[0], [1]])
a = (sigma1*p1 + sigma2*p2 + sigma3*p... | negative_train_query0_00061 | |
examples/advanced/qft.py/pslash
def pslash(p):
p1, p2, p3 = p
p0 = sqrt(m**2 + p1**2 + p2**2 + p3**2)
return gamma0*p0 - gamma1*p1 - gamma2*p2 - gamma3*p3 | negative_train_query0_00062 | |
examples/advanced/qft.py/Tr
def Tr(M):
return M.trace() | negative_train_query0_00063 | |
examples/advanced/qft.py/xprint
def xprint(lhs, rhs):
pprint(Eq(sympify(lhs), rhs)) | negative_train_query0_00064 | |
examples/advanced/qft.py/main
def main():
a = Symbol("a", real=True)
b = Symbol("b", real=True)
c = Symbol("c", real=True)
p = (a, b, c)
assert u(p, 1).D*u(p, 2) == Matrix(1, 1, [0])
assert u(p, 2).D*u(p, 1) == Matrix(1, 1, [0])
p1, p2, p3 = [Symbol(x, real=True) for x in ["p1", "p2", "p3... | negative_train_query0_00065 | |
examples/advanced/pidigits.py/display_fraction
def display_fraction(digits, skip=0, colwidth=10, columns=5):
"""Pretty printer for first n digits of a fraction"""
perline = colwidth * columns
printed = 0
for linecount in range((len(digits) - skip) // (colwidth * columns)):
line = digits[skip + l... | negative_train_query0_00066 | |
examples/advanced/pidigits.py/calculateit
def calculateit(func, base, n, tofile):
"""Writes first n base-digits of a mpmath function to file"""
prec = 100
intpart = libmp.numeral(3, base)
if intpart == 0:
skip = 0
else:
skip = len(intpart)
print("Step 1 of 2: calculating binary v... | negative_train_query0_00067 | |
examples/advanced/pidigits.py/interactive
def interactive():
"""Simple function to interact with user"""
print("Compute digits of pi with SymPy\n")
base = input("Which base? (2-36, 10 for decimal) \n> ")
digits = input("How many digits? (enter a big number, say, 10000)\n> ")
tofile = raw_input("Outp... | negative_train_query0_00068 | |
examples/advanced/pidigits.py/main
def main():
"""A non-interactive runner"""
base = 16
digits = 500
tofile = None
calculateit(pi, base, digits, tofile) | negative_train_query0_00069 | |
examples/advanced/pyglet_plotting.py/main
def main():
x, y, z = symbols('x,y,z')
# toggle axes visibility with F5, colors with F6
axes_options = 'visible=false; colored=true; label_ticks=true; label_axes=true; overlay=true; stride=0.5'
# axes_options = 'colored=false; overlay=false; stride=(1.0, 0.5, 0... | negative_train_query0_00070 | |
examples/advanced/pyglet_plotting.py/example_wrapper
def example_wrapper(f):
examples.append(f)
return f | negative_train_query0_00071 | |
examples/advanced/pyglet_plotting.py/mirrored_saddles
def mirrored_saddles():
p[5] = x**2 - y**2, [20], [20]
p[6] = y**2 - x**2, [20], [20] | negative_train_query0_00072 | |
examples/advanced/pyglet_plotting.py/mirrored_saddles_saveimage
def mirrored_saddles_saveimage():
p[5] = x**2 - y**2, [20], [20]
p[6] = y**2 - x**2, [20], [20]
p.wait_for_calculations()
# although the calculation is complete,
# we still need to wait for it to be
# ren... | negative_train_query0_00073 | |
examples/advanced/pyglet_plotting.py/mirrored_ellipsoids
def mirrored_ellipsoids():
p[2] = x**2 + y**2, [40], [40], 'color=zfade'
p[3] = -x**2 - y**2, [40], [40], 'color=zfade' | negative_train_query0_00074 | |
examples/advanced/pyglet_plotting.py/saddle_colored_by_derivative
def saddle_colored_by_derivative():
f = x**2 - y**2
p[1] = f, 'style=solid'
p[1].color = abs(f.diff(x)), abs(f.diff(x) + f.diff(y)), abs(f.diff(y)) | negative_train_query0_00075 | |
examples/advanced/pyglet_plotting.py/ding_dong_surface
def ding_dong_surface():
f = sqrt(1.0 - y)*y
p[1] = f, [x, 0, 2*pi,
40], [y, -
1, 4, 100], 'mode=cylindrical; style=solid; color=zfade4' | negative_train_query0_00076 | |
examples/advanced/pyglet_plotting.py/polar_circle
def polar_circle():
p[7] = 1, 'mode=polar' | negative_train_query0_00077 | |
examples/advanced/pyglet_plotting.py/polar_flower
def polar_flower():
p[8] = 1.5*sin(4*x), [160], 'mode=polar'
p[8].color = z, x, y, (0.5, 0.5, 0.5), (
0.8, 0.8, 0.8), (x, y, None, z) # z is used for t | negative_train_query0_00078 | |
examples/advanced/pyglet_plotting.py/simple_cylinder
def simple_cylinder():
p[9] = 1, 'mode=cylindrical' | negative_train_query0_00079 | |
examples/advanced/pyglet_plotting.py/cylindrical_hyperbola
def cylindrical_hyperbola():
# (note that polar is an alias for cylindrical)
p[10] = 1/y, 'mode=polar', [x], [y, -2, 2, 20] | negative_train_query0_00080 | |
examples/advanced/pyglet_plotting.py/extruded_hyperbolas
def extruded_hyperbolas():
p[11] = 1/x, [x, -10, 10, 100], [1], 'style=solid'
p[12] = -1/x, [x, -10, 10, 100], [1], 'style=solid' | negative_train_query0_00081 | |
examples/advanced/pyglet_plotting.py/torus
def torus():
a, b = 1, 0.5 # radius, thickness
p[13] = (a + b*cos(x))*cos(y), (a + b*cos(x)) *\
sin(y), b*sin(x), [x, 0, pi*2, 40], [y, 0, pi*2, 40] | negative_train_query0_00082 | |
examples/advanced/pyglet_plotting.py/warped_torus
def warped_torus():
a, b = 2, 1 # radius, thickness
p[13] = (a + b*cos(x))*cos(y), (a + b*cos(x))*sin(y), b *\
sin(x) + 0.5*sin(4*y), [x, 0, pi*2, 40], [y, 0, pi*2, 40] | negative_train_query0_00083 | |
examples/advanced/pyglet_plotting.py/parametric_spiral
def parametric_spiral():
p[14] = cos(y), sin(y), y / 10.0, [y, -4*pi, 4*pi, 100]
p[14].color = x, (0.1, 0.9), y, (0.1, 0.9), z, (0.1, 0.9) | negative_train_query0_00084 | |
examples/advanced/pyglet_plotting.py/multistep_gradient
def multistep_gradient():
p[1] = 1, 'mode=spherical', 'style=both'
# p[1] = exp(-x**2-y**2+(x*y)/4), [-1.7,1.7,100], [-1.7,1.7,100], 'style=solid'
# p[1] = 5*x*y*exp(-x**2-y**2), [-2,2,100], [-2,2,100]
gradient = [0.0, (0.3, 0.3... | negative_train_query0_00085 | |
examples/advanced/pyglet_plotting.py/lambda_vs_sympy_evaluation
def lambda_vs_sympy_evaluation():
start = clock()
p[4] = x**2 + y**2, [100], [100], 'style=solid'
p.wait_for_calculations()
print("lambda-based calculation took %s seconds." % (clock() - start))
start = clock()
... | negative_train_query0_00086 | |
examples/advanced/pyglet_plotting.py/gradient_vectors
def gradient_vectors():
def gradient_vectors_inner(f, i):
from sympy import lambdify
from sympy.plotting.plot_interval import PlotInterval
from pyglet.gl import glBegin, glColor3f
from pyglet.gl import glVe... | negative_train_query0_00087 | |
examples/advanced/pyglet_plotting.py/help_str
def help_str():
s = ("\nPlot p has been created. Useful commands: \n"
" help(p), p[1] = x**2, print p, p.clear() \n\n"
"Available examples (see source in plotting.py):\n\n")
for i in range(len(examples)):
s += "(%... | negative_train_query0_00088 | |
examples/advanced/pyglet_plotting.py/example
def example(i):
if callable(i):
p.clear()
i()
elif i >= 0 and i < len(examples):
p.clear()
examples[i]()
else:
print("Not a valid example.\n")
print(p) | negative_train_query0_00089 | |
examples/advanced/pyglet_plotting.py/gradient_vectors_inner
def gradient_vectors_inner(f, i):
from sympy import lambdify
from sympy.plotting.plot_interval import PlotInterval
from pyglet.gl import glBegin, glColor3f
from pyglet.gl import glVertex3f, glEnd, GL_LINE... | negative_train_query0_00090 | |
examples/advanced/pyglet_plotting.py/draw_gradient_vectors
def draw_gradient_vectors(f, iu, iv):
"""
Create a function which draws vectors
representing the gradient of f.
"""
dx, dy, dz = f.diff(x), f.diff(y), 0
... | negative_train_query0_00091 | |
examples/advanced/pyglet_plotting.py/draw_arrow
def draw_arrow(p1, p2):
"""
Draw a single vector.
"""
glColor3f(0.4, 0.4, 0.9)
glVertex3f(*p1)
glColor3f(0.9, 0.4, 0.4)
... | negative_train_query0_00092 | |
examples/advanced/pyglet_plotting.py/draw
def draw():
"""
Iterate through the calculated
vectors and draw them.
"""
glBegin(GL_LINES)
for u in Gvl:
for v in u:
... | negative_train_query0_00093 | |
examples/advanced/relativity.py/grad
def grad(f, X):
a = []
for x in X:
a.append(f.diff(x))
return a | negative_train_query0_00094 | |
examples/advanced/relativity.py/d
def d(m, x):
return grad(m[0, 0], x) | negative_train_query0_00095 | |
examples/advanced/relativity.py/curvature
def curvature(Rmn):
return Rmn.ud(0, 0) + Rmn.ud(1, 1) + Rmn.ud(2, 2) + Rmn.ud(3, 3) | negative_train_query0_00096 | |
examples/advanced/relativity.py/pprint_Gamma_udd
def pprint_Gamma_udd(i, k, l):
pprint(Eq(Symbol('Gamma^%i_%i%i' % (i, k, l)), Gamma.udd(i, k, l))) | negative_train_query0_00097 | |
examples/advanced/relativity.py/pprint_Rmn_dd
def pprint_Rmn_dd(i, j):
pprint(Eq(Symbol('R_%i%i' % (i, j)), Rmn.dd(i, j))) | negative_train_query0_00098 |
End of preview. Expand in Data Studio
Software Issue Localization.
| Task category | t2t |
| Domains | Programming, Written |
| Reference | https://www.swebench.com/ |
Source datasets:
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("SWEbenchLiteRR")
evaluator = mteb.MTEB([task])
model = mteb.get_model(YOUR_MODEL)
evaluator.run(model)
To learn more about how to run models on mteb task check out the GitHub repository.
Citation
If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a part of the MMTEB Contribution.
@misc{jimenez2024swebenchlanguagemodelsresolve,
archiveprefix = {arXiv},
author = {Carlos E. Jimenez and John Yang and Alexander Wettig and Shunyu Yao and Kexin Pei and Ofir Press and Karthik Narasimhan},
eprint = {2310.06770},
primaryclass = {cs.CL},
title = {SWE-bench: Can Language Models Resolve Real-World GitHub Issues?},
url = {https://arxiv.org/abs/2310.06770},
year = {2024},
}
@article{enevoldsen2025mmtebmassivemultilingualtext,
title={MMTEB: Massive Multilingual Text Embedding Benchmark},
author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
publisher = {arXiv},
journal={arXiv preprint arXiv:2502.13595},
year={2025},
url={https://arxiv.org/abs/2502.13595},
doi = {10.48550/arXiv.2502.13595},
}
@article{muennighoff2022mteb,
author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Loïc and Reimers, Nils},
title = {MTEB: Massive Text Embedding Benchmark},
publisher = {arXiv},
journal={arXiv preprint arXiv:2210.07316},
year = {2022}
url = {https://arxiv.org/abs/2210.07316},
doi = {10.48550/ARXIV.2210.07316},
}
Dataset Statistics
Dataset Statistics
The following code contains the descriptive statistics from the task. These can also be obtained using:
import mteb
task = mteb.get_task("SWEbenchLiteRR")
desc_stats = task.metadata.descriptive_stats
{}
This dataset card was automatically generated using MTEB
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