code stringlengths 3 6.57k |
|---|
return(total_letters) |
print(solve_problem() |
TypesrcValidator(_plotly_utils.basevalidators.SrcValidator) |
super(TypesrcValidator, self) |
kwargs.pop("edit_type", "none") |
kwargs.pop("role", "info") |
TypeValidator(_plotly_utils.basevalidators.EnumeratedValidator) |
super(TypeValidator, self) |
kwargs.pop("array_ok", True) |
kwargs.pop("edit_type", "calc") |
kwargs.pop("role", "style") |
kwargs.pop("values", ["radial", "horizontal", "vertical", "none"]) |
ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator) |
super(ColorsrcValidator, self) |
kwargs.pop("edit_type", "none") |
kwargs.pop("role", "info") |
ColorValidator(_plotly_utils.basevalidators.ColorValidator) |
super(ColorValidator, self) |
kwargs.pop("array_ok", True) |
kwargs.pop("edit_type", "calc") |
kwargs.pop("role", "style") |
AwsInstance(Instance) |
field(default="co.yellowdog.platform.model.AwsInstance", init=False) |
field(default=None, init=False) |
Copyright (c) |
Exponential(BasePDF) |
__init__(self, lam=None, obs: ztyping.ObsTypeInput = None, name: str = "Exponential", lambda_=None) |
exp(lambda * x) |
BreakingAPIChangeError("The 'lambda' parameter has been renamed from 'lambda_' to 'lam'.") |
super() |
__init__(obs, name=name, params=params) |
z.constant(0.) |
self._set_numerics_data_shift(self.space) |
_unnormalized_pdf(self, x) |
x.unstack_x() |
znp.exp(lambda_ * (self._shift_x(x) |
data (and norm_range, if explicitly set differently) |
_shift_x(self, x) |
self._calc_numerics_data_shift() |
_set_numerics_data_shift(self, limits) |
calc_numerics_data_shift() |
lower.append(z.convert_to_tensor(low[:, 0]) |
upper.append(z.convert_to_tensor(up[:, 0]) |
z.convert_to_tensor(lower) |
z.convert_to_tensor(upper) |
znp.min(lower, axis=0) |
znp.max(upper, axis=0) |
return (upper_val + lower_val) |
_single_hook_integrate(self, limits, norm_range, x) |
self._set_numerics_data_shift(norm_range) |
super() |
_single_hook_integrate(limits, norm_range, x=x) |
_single_hook_analytic_integrate(self, limits, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_analytic_integrate(limits, norm_range) |
_single_hook_numeric_integrate(self, limits, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_numeric_integrate(limits, norm_range) |
_single_hook_partial_integrate(self, x, limits, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_partial_integrate(x, limits, norm_range) |
_single_hook_partial_analytic_integrate(self, x, limits, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_partial_analytic_integrate(x, limits, norm_range) |
_single_hook_partial_numeric_integrate(self, x, limits, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_partial_numeric_integrate(x, limits, norm_range) |
_single_hook_normalization(self, limits) |
self._set_numerics_data_shift(limits=limits) |
super() |
_single_hook_normalization(limits) |
_single_hook_unnormalized_pdf(self, x, name) |
self._set_numerics_data_shift(limits=component_norm_range) |
super() |
_single_hook_unnormalized_pdf(x, name) |
super() |
_single_hook_unnormalized_pdf(x, name) |
_single_hook_pdf(self, x, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_pdf(x, norm_range) |
_single_hook_log_pdf(self, x, norm_range) |
self._set_numerics_data_shift(limits=norm_range) |
super() |
_single_hook_log_pdf(x, norm_range) |
_single_hook_sample(self, n, limits, x=None) |
self._set_numerics_data_shift(limits=limits) |
super() |
_single_hook_sample(n, limits, x) |
_exp_integral_from_any_to_any(limits, params, model) |
any(np.isinf([lower, upper]) |
_exp_integral_func_shifting(lambd=lambda_, lower=lower, upper=upper, model=model) |
_exp_integral_func_shifting(lambd, lower, upper, model) |
raw_integral(x) |
z.exp(lambd * (model._shift_x(x) |
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