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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3590304f68bf81464b47f08ad59507651c81a081 | 24,012 | py | Python | edward/inferences/klqp.py | bfredl/edward | 6d49374b13096b26c81139ba6ba2f2c3bffdb8b2 | [
"Apache-2.0"
] | null | null | null | edward/inferences/klqp.py | bfredl/edward | 6d49374b13096b26c81139ba6ba2f2c3bffdb8b2 | [
"Apache-2.0"
] | null | null | null | edward/inferences/klqp.py | bfredl/edward | 6d49374b13096b26c81139ba6ba2f2c3bffdb8b2 | [
"Apache-2.0"
] | 1 | 2021-06-13T06:58:00.000Z | 2021-06-13T06:58:00.000Z | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import six
import tensorflow as tf
from edward.inferences.variational_inference import VariationalInference
from edward.models import RandomVariable
from edward.util import copy
from tensorflow.contrib import distributions as ds
try:
from edward.models import Normal
except Exception as e:
raise ImportError("{0}. Your TensorFlow version is not supported.".format(e))
class KLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective by automatically selecting from a
variety of black box inference techniques.
Notes
-----
``KLqp`` also optimizes any model parameters :math:`p(z \mid x;
\\theta)`. It does this by variational EM, minimizing
.. math::
\mathbb{E}_{q(z; \lambda)} [ \log p(x, z; \\theta) ]
with respect to :math:`\\theta`.
In conditional inference, we infer :math:`z` in :math:`p(z, \\beta
\mid x)` while fixing inference over :math:`\\beta` using another
distribution :math:`q(\\beta)`. During gradient calculation, instead
of using the model's density
.. math::
\log p(x, z^{(s)}), z^{(s)} \sim q(z; \lambda),
for each sample :math:`s=1,\ldots,S`, ``KLqp`` uses
.. math::
\log p(x, z^{(s)}, \\beta^{(s)}),
where :math:`z^{(s)} \sim q(z; \lambda)` and :math:`\\beta^{(s)}
\sim q(\\beta)`.
"""
def __init__(self, *args, **kwargs):
super(KLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, kl_scaling=None, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
kl_scaling : dict of RandomVariable to float, optional
Provides option to scale terms when using ELBO with KL divergence.
If the KL divergence terms are
.. math::
\\alpha_p \mathbb{E}_{q(z\mid x, \lambda)} [
\log q(z\mid x, \lambda) - \log p(z)],
then pass {:math:`p(z)`: :math:`\\alpha_p`} as ``kl_scaling``,
where :math:`\\alpha_p` is a float that specifies how much to
scale the KL term.
"""
if kl_scaling is None:
kl_scaling = {}
self.n_samples = n_samples
self.kl_scaling = kl_scaling
return super(KLqp, self).initialize(*args, **kwargs)
def build_loss_and_gradients(self, var_list):
"""Wrapper for the ``KLqp`` loss function.
.. math::
-\\text{ELBO} =
-\mathbb{E}_{q(z; \lambda)} [ \log p(x, z) - \log q(z; \lambda) ]
KLqp supports
1. score function gradients (Paisley et al., 2012)
2. reparameterization gradients (Kingma and Welling, 2014)
of the loss function.
If the KL divergence between the variational model and the prior
is tractable, then the loss function can be written as
.. math::
-\mathbb{E}_{q(z; \lambda)}[\log p(x \mid z)] +
\\text{KL}( q(z; \lambda) \| p(z) ),
where the KL term is computed analytically (Kingma and Welling,
2014). We compute this automatically when :math:`p(z)` and
:math:`q(z; \lambda)` are Normal.
"""
is_reparameterizable = all([
rv.reparameterization_type ==
tf.contrib.distributions.FULLY_REPARAMETERIZED
for rv in six.itervalues(self.latent_vars)])
is_analytic_kl = all([isinstance(z, Normal) and isinstance(qz, Normal)
for z, qz in six.iteritems(self.latent_vars)])
if not is_analytic_kl and self.kl_scaling:
raise TypeError("kl_scaling must be None when using non-analytic KL term")
if is_reparameterizable:
if is_analytic_kl:
return build_reparam_kl_loss_and_gradients(self, var_list)
# elif is_analytic_entropy:
# return build_reparam_entropy_loss_and_gradients(self, var_list)
else:
return build_reparam_loss_and_gradients(self, var_list)
else:
if is_analytic_kl:
return build_score_kl_loss_and_gradients(self, var_list)
# Analytic entropies may lead to problems around
# convergence; for now it is deactivated.
# elif is_analytic_entropy:
# return build_score_entropy_loss_and_gradients(self, var_list)
else:
return build_score_loss_and_gradients(self, var_list)
class ReparameterizationKLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective using the reparameterization
gradient.
"""
def __init__(self, *args, **kwargs):
super(ReparameterizationKLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
"""
self.n_samples = n_samples
return super(ReparameterizationKLqp, self).initialize(*args, **kwargs)
def build_loss_and_gradients(self, var_list):
return build_reparam_loss_and_gradients(self, var_list)
class ReparameterizationKLKLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective using the reparameterization
gradient and an analytic KL term.
"""
def __init__(self, *args, **kwargs):
super(ReparameterizationKLKLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, kl_scaling=None, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
kl_scaling : dict of RandomVariable to float, optional
Provides option to scale terms when using ELBO with KL divergence.
If the KL divergence terms are
.. math::
\\alpha_p \mathbb{E}_{q(z\mid x, \lambda)} [
\log q(z\mid x, \lambda) - \log p(z)],
then pass {:math:`p(z)`: :math:`\\alpha_p`} as ``kl_scaling``,
where :math:`\\alpha_p` is a float that specifies how much to
scale the KL term.
"""
if kl_scaling is None:
kl_scaling = {}
self.n_samples = n_samples
self.kl_scaling = kl_scaling
return super(ReparameterizationKLKLqp, self).initialize(*args, **kwargs)
def build_loss_and_gradients(self, var_list):
return build_reparam_kl_loss_and_gradients(self, var_list)
class ReparameterizationEntropyKLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective using the reparameterization
gradient and an analytic entropy term.
"""
def __init__(self, *args, **kwargs):
super(ReparameterizationEntropyKLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
"""
self.n_samples = n_samples
return super(ReparameterizationEntropyKLqp, self).initialize(
*args, **kwargs)
def build_loss_and_gradients(self, var_list):
return build_reparam_entropy_loss_and_gradients(self, var_list)
class ScoreKLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective using the score function
gradient.
"""
def __init__(self, *args, **kwargs):
super(ScoreKLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
"""
self.n_samples = n_samples
return super(ScoreKLqp, self).initialize(*args, **kwargs)
def build_loss_and_gradients(self, var_list):
return build_score_loss_and_gradients(self, var_list)
class ScoreKLKLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective using the score function gradient
and an analytic KL term.
"""
def __init__(self, *args, **kwargs):
super(ScoreKLKLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, kl_scaling=None, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
kl_scaling : dict of RandomVariable to float, optional
Provides option to scale terms when using ELBO with KL divergence.
If the KL divergence terms are
.. math::
\\alpha_p \mathbb{E}_{q(z\mid x, \lambda)} [
\log q(z\mid x, \lambda) - \log p(z)],
then pass {:math:`p(z)`: :math:`\\alpha_p`} as ``kl_scaling``,
where :math:`\\alpha_p` is a float that specifies how much to
scale the KL term.
"""
if kl_scaling is None:
kl_scaling = {}
self.n_samples = n_samples
self.kl_scaling = kl_scaling
return super(ScoreKLKLqp, self).initialize(*args, **kwargs)
def build_loss_and_gradients(self, var_list):
return build_score_kl_loss_and_gradients(self, var_list)
class ScoreEntropyKLqp(VariationalInference):
"""Variational inference with the KL divergence
.. math::
\\text{KL}( q(z; \lambda) \| p(z \mid x) ).
This class minimizes the objective using the score function gradient
and an analytic entropy term.
"""
def __init__(self, *args, **kwargs):
super(ScoreEntropyKLqp, self).__init__(*args, **kwargs)
def initialize(self, n_samples=1, *args, **kwargs):
"""Initialization.
Parameters
----------
n_samples : int, optional
Number of samples from variational model for calculating
stochastic gradients.
"""
self.n_samples = n_samples
return super(ScoreEntropyKLqp, self).initialize(*args, **kwargs)
def build_loss_and_gradients(self, var_list):
return build_score_entropy_loss_and_gradients(self, var_list)
def build_reparam_loss_and_gradients(inference, var_list):
"""Build loss function. Its automatic differentiation
is a stochastic gradient of
.. math::
-\\text{ELBO} =
-\mathbb{E}_{q(z; \lambda)} [ \log p(x, z) - \log q(z; \lambda) ]
based on the reparameterization trick (Kingma and Welling, 2014).
Computed by sampling from :math:`q(z;\lambda)` and evaluating the
expectation using Monte Carlo sampling.
"""
p_log_prob = [0.0] * inference.n_samples
q_log_prob = [0.0] * inference.n_samples
for s in range(inference.n_samples):
# Form dictionary in order to replace conditioning on prior or
# observed variable with conditioning on a specific value.
scope = 'inference_' + str(id(inference)) + '/' + str(s)
dict_swap = {}
for x, qx in six.iteritems(inference.data):
if isinstance(x, RandomVariable):
if isinstance(qx, RandomVariable):
qx_copy = copy(qx, scope=scope)
dict_swap[x] = qx_copy.value()
else:
dict_swap[x] = qx
for z, qz in six.iteritems(inference.latent_vars):
# Copy q(z) to obtain new set of posterior samples.
qz_copy = copy(qz, scope=scope)
dict_swap[z] = qz_copy.value()
q_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) * qz_copy.log_prob(dict_swap[z]))
for z in six.iterkeys(inference.latent_vars):
z_copy = copy(z, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) * z_copy.log_prob(dict_swap[z]))
for x in six.iterkeys(inference.data):
if isinstance(x, RandomVariable):
x_copy = copy(x, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(x, 1.0) * x_copy.log_prob(dict_swap[x]))
p_log_prob = tf.reduce_mean(p_log_prob)
q_log_prob = tf.reduce_mean(q_log_prob)
if inference.logging:
summary_key = 'summaries_' + str(id(inference))
tf.summary.scalar("loss/p_log_prob", p_log_prob, collections=[summary_key])
tf.summary.scalar("loss/q_log_prob", q_log_prob, collections=[summary_key])
loss = -(p_log_prob - q_log_prob)
grads = tf.gradients(loss, var_list)
grads_and_vars = list(zip(grads, var_list))
return loss, grads_and_vars
def build_reparam_kl_loss_and_gradients(inference, var_list):
"""Build loss function. Its automatic differentiation
is a stochastic gradient of
.. math::
-\\text{ELBO} = - ( \mathbb{E}_{q(z; \lambda)} [ \log p(x \mid z) ]
+ \\text{KL}(q(z; \lambda) \| p(z)) )
based on the reparameterization trick (Kingma and Welling, 2014).
It assumes the KL is analytic.
Computed by sampling from :math:`q(z;\lambda)` and evaluating the
expectation using Monte Carlo sampling.
"""
p_log_lik = [0.0] * inference.n_samples
for s in range(inference.n_samples):
# Form dictionary in order to replace conditioning on prior or
# observed variable with conditioning on a specific value.
scope = 'inference_' + str(id(inference)) + '/' + str(s)
dict_swap = {}
for x, qx in six.iteritems(inference.data):
if isinstance(x, RandomVariable):
if isinstance(qx, RandomVariable):
qx_copy = copy(qx, scope=scope)
dict_swap[x] = qx_copy.value()
else:
dict_swap[x] = qx
for z, qz in six.iteritems(inference.latent_vars):
# Copy q(z) to obtain new set of posterior samples.
qz_copy = copy(qz, scope=scope)
dict_swap[z] = qz_copy.value()
for x in six.iterkeys(inference.data):
if isinstance(x, RandomVariable):
x_copy = copy(x, dict_swap, scope=scope)
p_log_lik[s] += tf.reduce_sum(
inference.scale.get(x, 1.0) * x_copy.log_prob(dict_swap[x]))
p_log_lik = tf.reduce_mean(p_log_lik)
kl_penalty = tf.reduce_sum([
inference.kl_scaling.get(z, 1.0) * tf.reduce_sum(ds.kl(qz, z))
for z, qz in six.iteritems(inference.latent_vars)])
if inference.logging:
summary_key = 'summaries_' + str(id(inference))
tf.summary.scalar("loss/p_log_lik", p_log_lik, collections=[summary_key])
tf.summary.scalar("loss/kl_penalty", kl_penalty, collections=[summary_key])
loss = -(p_log_lik - kl_penalty)
grads = tf.gradients(loss, var_list)
grads_and_vars = list(zip(grads, var_list))
return loss, grads_and_vars
def build_reparam_entropy_loss_and_gradients(inference, var_list):
"""Build loss function. Its automatic differentiation
is a stochastic gradient of
.. math::
-\\text{ELBO} = -( \mathbb{E}_{q(z; \lambda)} [ \log p(x , z) ]
+ \mathbb{H}(q(z; \lambda)) )
based on the reparameterization trick (Kingma and Welling, 2014).
It assumes the entropy is analytic.
Computed by sampling from :math:`q(z;\lambda)` and evaluating the
expectation using Monte Carlo sampling.
"""
p_log_prob = [0.0] * inference.n_samples
for s in range(inference.n_samples):
# Form dictionary in order to replace conditioning on prior or
# observed variable with conditioning on a specific value.
scope = 'inference_' + str(id(inference)) + '/' + str(s)
dict_swap = {}
for x, qx in six.iteritems(inference.data):
if isinstance(x, RandomVariable):
if isinstance(qx, RandomVariable):
qx_copy = copy(qx, scope=scope)
dict_swap[x] = qx_copy.value()
else:
dict_swap[x] = qx
for z, qz in six.iteritems(inference.latent_vars):
# Copy q(z) to obtain new set of posterior samples.
qz_copy = copy(qz, scope=scope)
dict_swap[z] = qz_copy.value()
for z in six.iterkeys(inference.latent_vars):
z_copy = copy(z, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) * z_copy.log_prob(dict_swap[z]))
for x in six.iterkeys(inference.data):
if isinstance(x, RandomVariable):
x_copy = copy(x, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(x, 1.0) * x_copy.log_prob(dict_swap[x]))
p_log_prob = tf.reduce_mean(p_log_prob)
q_entropy = tf.reduce_sum([
qz.entropy() for z, qz in six.iteritems(inference.latent_vars)])
if inference.logging:
summary_key = 'summaries_' + str(id(inference))
tf.summary.scalar("loss/p_log_prob", p_log_prob, collections=[summary_key])
tf.summary.scalar("loss/q_entropy", q_entropy, collections=[summary_key])
loss = -(p_log_prob + q_entropy)
grads = tf.gradients(loss, var_list)
grads_and_vars = list(zip(grads, var_list))
return loss, grads_and_vars
def build_score_loss_and_gradients(inference, var_list):
"""Build loss function and gradients based on the score function
estimator (Paisley et al., 2012).
Computed by sampling from :math:`q(z;\lambda)` and evaluating the
expectation using Monte Carlo sampling.
"""
p_log_prob = [0.0] * inference.n_samples
q_log_prob = [0.0] * inference.n_samples
for s in range(inference.n_samples):
# Form dictionary in order to replace conditioning on prior or
# observed variable with conditioning on a specific value.
scope = 'inference_' + str(id(inference)) + '/' + str(s)
dict_swap = {}
for x, qx in six.iteritems(inference.data):
if isinstance(x, RandomVariable):
if isinstance(qx, RandomVariable):
qx_copy = copy(qx, scope=scope)
dict_swap[x] = qx_copy.value()
else:
dict_swap[x] = qx
for z, qz in six.iteritems(inference.latent_vars):
# Copy q(z) to obtain new set of posterior samples.
qz_copy = copy(qz, scope=scope)
dict_swap[z] = qz_copy.value()
q_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) *
qz_copy.log_prob(tf.stop_gradient(dict_swap[z])))
for z in six.iterkeys(inference.latent_vars):
z_copy = copy(z, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) * z_copy.log_prob(dict_swap[z]))
for x in six.iterkeys(inference.data):
if isinstance(x, RandomVariable):
x_copy = copy(x, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(x, 1.0) * x_copy.log_prob(dict_swap[x]))
p_log_prob = tf.stack(p_log_prob)
q_log_prob = tf.stack(q_log_prob)
if inference.logging:
summary_key = 'summaries_' + str(id(inference))
tf.summary.scalar("loss/p_log_prob", tf.reduce_mean(p_log_prob),
collections=[summary_key])
tf.summary.scalar("loss/q_log_prob", tf.reduce_mean(q_log_prob),
collections=[summary_key])
losses = p_log_prob - q_log_prob
loss = -tf.reduce_mean(losses)
grads = tf.gradients(
-tf.reduce_mean(q_log_prob * tf.stop_gradient(losses)),
var_list)
grads_and_vars = list(zip(grads, var_list))
return loss, grads_and_vars
def build_score_kl_loss_and_gradients(inference, var_list):
"""Build loss function and gradients based on the score function
estimator (Paisley et al., 2012).
It assumes the KL is analytic.
Computed by sampling from :math:`q(z;\lambda)` and evaluating the
expectation using Monte Carlo sampling.
"""
p_log_lik = [0.0] * inference.n_samples
q_log_prob = [0.0] * inference.n_samples
for s in range(inference.n_samples):
# Form dictionary in order to replace conditioning on prior or
# observed variable with conditioning on a specific value.
scope = 'inference_' + str(id(inference)) + '/' + str(s)
dict_swap = {}
for x, qx in six.iteritems(inference.data):
if isinstance(x, RandomVariable):
if isinstance(qx, RandomVariable):
qx_copy = copy(qx, scope=scope)
dict_swap[x] = qx_copy.value()
else:
dict_swap[x] = qx
for z, qz in six.iteritems(inference.latent_vars):
# Copy q(z) to obtain new set of posterior samples.
qz_copy = copy(qz, scope=scope)
dict_swap[z] = qz_copy.value()
q_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) *
qz_copy.log_prob(tf.stop_gradient(dict_swap[z])))
for x in six.iterkeys(inference.data):
if isinstance(x, RandomVariable):
x_copy = copy(x, dict_swap, scope=scope)
p_log_lik[s] += tf.reduce_sum(
inference.scale.get(x, 1.0) * x_copy.log_prob(dict_swap[x]))
p_log_lik = tf.stack(p_log_lik)
q_log_prob = tf.stack(q_log_prob)
kl_penalty = tf.reduce_sum([
inference.kl_scaling.get(z, 1.0) * tf.reduce_sum(ds.kl(qz, z))
for z, qz in six.iteritems(inference.latent_vars)])
if inference.logging:
summary_key = 'summaries_' + str(id(inference))
tf.summary.scalar("loss/p_log_lik", tf.reduce_mean(p_log_lik),
collections=[summary_key])
tf.summary.scalar("loss/kl_penalty", kl_penalty, collections=[summary_key])
loss = -(tf.reduce_mean(p_log_lik) - kl_penalty)
grads = tf.gradients(
-(tf.reduce_mean(q_log_prob * tf.stop_gradient(p_log_lik)) - kl_penalty),
var_list)
grads_and_vars = list(zip(grads, var_list))
return loss, grads_and_vars
def build_score_entropy_loss_and_gradients(inference, var_list):
"""Build loss function and gradients based on the score function
estimator (Paisley et al., 2012).
It assumes the entropy is analytic.
Computed by sampling from :math:`q(z;\lambda)` and evaluating the
expectation using Monte Carlo sampling.
"""
p_log_prob = [0.0] * inference.n_samples
q_log_prob = [0.0] * inference.n_samples
for s in range(inference.n_samples):
# Form dictionary in order to replace conditioning on prior or
# observed variable with conditioning on a specific value.
scope = 'inference_' + str(id(inference)) + '/' + str(s)
dict_swap = {}
for x, qx in six.iteritems(inference.data):
if isinstance(x, RandomVariable):
if isinstance(qx, RandomVariable):
qx_copy = copy(qx, scope=scope)
dict_swap[x] = qx_copy.value()
else:
dict_swap[x] = qx
for z, qz in six.iteritems(inference.latent_vars):
# Copy q(z) to obtain new set of posterior samples.
qz_copy = copy(qz, scope=scope)
dict_swap[z] = qz_copy.value()
q_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) *
qz_copy.log_prob(tf.stop_gradient(dict_swap[z])))
for z in six.iterkeys(inference.latent_vars):
z_copy = copy(z, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(z, 1.0) * z_copy.log_prob(dict_swap[z]))
for x in six.iterkeys(inference.data):
if isinstance(x, RandomVariable):
x_copy = copy(x, dict_swap, scope=scope)
p_log_prob[s] += tf.reduce_sum(
inference.scale.get(x, 1.0) * x_copy.log_prob(dict_swap[x]))
p_log_prob = tf.stack(p_log_prob)
q_log_prob = tf.stack(q_log_prob)
q_entropy = tf.reduce_sum([
qz.entropy() for z, qz in six.iteritems(inference.latent_vars)])
if inference.logging:
summary_key = 'summaries_' + str(id(inference))
tf.summary.scalar("loss/p_log_prob", tf.reduce_mean(p_log_prob),
collections=[summary_key])
tf.summary.scalar("loss/q_log_prob", tf.reduce_mean(q_log_prob),
collections=[summary_key])
tf.summary.scalar("loss/q_entropy", q_entropy, collections=[summary_key])
loss = -(tf.reduce_mean(p_log_prob) + q_entropy)
grads = tf.gradients(
-(tf.reduce_mean(q_log_prob * tf.stop_gradient(p_log_prob)) +
q_entropy),
var_list)
grads_and_vars = list(zip(grads, var_list))
return loss, grads_and_vars
| 33.630252 | 80 | 0.66954 | 3,442 | 24,012 | 4.465718 | 0.074085 | 0.0337 | 0.017175 | 0.024722 | 0.873333 | 0.870991 | 0.858305 | 0.854011 | 0.846009 | 0.834949 | 0 | 0.005212 | 0.208896 | 24,012 | 713 | 81 | 33.677419 | 0.803959 | 0.339247 | 0 | 0.787234 | 0 | 0 | 0.027574 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.082067 | false | 0 | 0.033435 | 0.018237 | 0.206687 | 0.00304 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
35ab2ba6c0b462e0c935542007eef7c40d014609 | 28,484 | py | Python | tests/resources/test_field_goal.py | bahalbach/pbpstats | 6a9f602764edb7a3ee0e880fffbb5aa34990d6e9 | [
"MIT"
] | 54 | 2019-10-16T00:10:51.000Z | 2022-03-19T21:21:05.000Z | tests/resources/test_field_goal.py | bahalbach/pbpstats | 6a9f602764edb7a3ee0e880fffbb5aa34990d6e9 | [
"MIT"
] | 15 | 2019-11-19T01:20:52.000Z | 2022-02-04T13:38:37.000Z | tests/resources/test_field_goal.py | bahalbach/pbpstats | 6a9f602764edb7a3ee0e880fffbb5aa34990d6e9 | [
"MIT"
] | 15 | 2019-11-19T11:54:51.000Z | 2022-03-21T05:08:53.000Z | import pbpstats
from pbpstats.resources.enhanced_pbp.data_nba.field_goal import DataFieldGoal
from pbpstats.resources.enhanced_pbp.stats_nba.field_goal import StatsFieldGoal
from pbpstats.resources.enhanced_pbp.stats_nba.foul import StatsFoul
from pbpstats.resources.enhanced_pbp.stats_nba.free_throw import StatsFreeThrow
from pbpstats.resources.enhanced_pbp.stats_nba.rebound import StatsRebound
from pbpstats.resources.enhanced_pbp.stats_nba.turnover import StatsTurnover
from pbpstats.resources.enhanced_pbp.stats_nba.violation import StatsViolation
def test_data_field_goal_3_shot_value_is_3():
item = {
"evt": 20,
"cl": "09:57",
"de": "[NYK 5-2] Rose 3pt Shot: Made (5 PTS) Assist: Anthony (1 AST)",
"locX": -230,
"locY": 28,
"mtype": 1,
"etype": 1,
"opid": "",
"tid": 1610612752,
"pid": 201565,
"hs": 5,
"vs": 2,
"epid": "2546",
"oftid": 1610612752,
}
period = 1
game_id = "0021900001"
fg = DataFieldGoal(item, period, game_id)
assert fg.shot_value == 3
def test_data_field_goal_2_shot_value_is_2():
item = {
"evt": 14,
"cl": "10:34",
"de": "[BKN] Bogdanovic Layup Shot: Missed",
"locX": 4,
"locY": 16,
"mtype": 5,
"etype": 2,
"opid": "",
"tid": 1610612751,
"pid": 202711,
"hs": 2,
"vs": 2,
"epid": "",
"oftid": 1610612751,
}
period = 1
game_id = "0021900001"
fg = DataFieldGoal(item, period, game_id)
assert fg.shot_value == 2
def test_stats_field_goal_3_shot_value_is_3():
item = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": "2546",
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg = StatsFieldGoal(item, order)
assert fg.shot_value == 3
def test_stats_field_goal_2_shot_value_is_2():
item = {
"EVENTNUM": 14,
"PCTIMESTRING": "10:34",
"VISITORDESCRIPTION": "MISS Bogdanovic 2' Layup",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 202711,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg = StatsFieldGoal(item, order)
assert fg.shot_value == 2
def test_made_true():
event = {
"EVENTNUM": 21,
"PCTIMESTRING": "09:31",
"VISITORDESCRIPTION": "Bogdanovic 2' Driving Layup (2 PTS)",
"EVENTMSGACTIONTYPE": 42,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 202711,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_made is True
def test_made_false():
event = {
"EVENTNUM": 14,
"PCTIMESTRING": "10:34",
"VISITORDESCRIPTION": "MISS Bogdanovic 2' Layup",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 202711,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_made is False
def test_blocked_true():
event = {
"EVENTNUM": 59,
"PCTIMESTRING": "05:27",
"HOMEDESCRIPTION": "MISS Porzingis 3' Layup",
"VISITORDESCRIPTION": "Lopez BLOCK (1 BLK)",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 204001,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": 201572,
"PLAYER3_TEAM_ID": 1610612751,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_blocked is True
def test_blocked_false():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson 1' Layup",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_blocked is False
def test_assisted_true():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": 2546,
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_assisted is True
def test_assisted_false():
event = {
"EVENTNUM": 21,
"PCTIMESTRING": "09:31",
"VISITORDESCRIPTION": "Bogdanovic 2' Driving Layup (2 PTS)",
"EVENTMSGACTIONTYPE": 42,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 202711,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_assisted is False
def test_rebound_event_on_miss():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson 1' Layup",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
rebound = {
"EVENTNUM": 62,
"PCTIMESTRING": "05:20",
"HOMEDESCRIPTION": "Thomas Rebound (Off:0 Def:1)",
"EVENTMSGACTIONTYPE": 0,
"EVENTMSGTYPE": 4,
"PLAYER1_ID": 202498,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 2
rebound_event = StatsRebound(rebound, order)
fg_event.next_event = rebound_event
rebound_event.previous_event = fg_event
rebound_event.next_event = None
assert fg_event.rebound == rebound_event
def test_placeholder_rebound_event_on_miss_returns_none():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson 1' Layup",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
rebound = {
"EVENTNUM": 62,
"PCTIMESTRING": "05:20",
"HOMEDESCRIPTION": "Knicks Rebound",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 4,
"PLAYER1_ID": 0,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 2
rebound_event = StatsRebound(rebound, order)
fg_event.next_event = rebound_event
rebound_event.previous_event = fg_event
rebound_event.next_event = None
assert fg_event.rebound is None
def test_heave_true():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "00:01",
"HOMEDESCRIPTION": "Rose 45' 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": 2546,
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_heave is True
def test_heave_false():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 25' 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": 2546,
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_heave is False
def test_corner3_true():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": "2546",
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
fg_event.locX = -230
fg_event.locY = 28
assert fg_event.is_corner_3 is True
def test_corner3_false():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": "2546",
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
fg_event.locX = -230
fg_event.locY = 100
assert fg_event.is_corner_3 is False
def test_corner3_no_coords_is_false():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": "2546",
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_corner_3 is False
def test_corner3_2pt_is_false():
event = {
"EVENTNUM": 21,
"PCTIMESTRING": "09:31",
"VISITORDESCRIPTION": "Bogdanovic 2' Driving Layup (2 PTS)",
"EVENTMSGACTIONTYPE": 42,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 202711,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_corner_3 is False
def test_distance_with_coords():
event = {
"EVENTNUM": 115,
"PCTIMESTRING": "00:46",
"HOMEDESCRIPTION": "MISS Anthony Jump Shot",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 2546,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
fg_event.locX = -100
fg_event.locY = 150
assert fg_event.distance == 18
def test_distance_without_coords_from_description():
event = {
"EVENTNUM": 115,
"PCTIMESTRING": "00:46",
"HOMEDESCRIPTION": "MISS Anthony 16' Jump Shot",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 2546,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.distance == 16
def test_distance_no_coords_or_description_returns_none():
event = {
"EVENTNUM": 115,
"PCTIMESTRING": "00:46",
"HOMEDESCRIPTION": "MISS Anthony Jump Shot",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 2546,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.distance is None
def test_shot_type_corner3():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": "2546",
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
fg_event.locX = -230
fg_event.locY = 28
assert fg_event.shot_type == pbpstats.CORNER_3_STRING
def test_shot_type_arc3():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": "2546",
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
fg_event.locX = -230
fg_event.locY = 100
assert fg_event.shot_type == pbpstats.ARC_3_STRING
def test_shot_type_at_rim():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson 1' Layup",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.shot_type == pbpstats.AT_RIM_STRING
def test_shot_type_short_mid_range():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson 12' Jump Shot",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.shot_type == pbpstats.SHORT_MID_RANGE_STRING
def test_shot_type_long_mid_range():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson 19' Jump Shot",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.shot_type == pbpstats.LONG_MID_RANGE_STRING
def test_shot_type_unknown():
event = {
"EVENTNUM": 61,
"PCTIMESTRING": "05:21",
"VISITORDESCRIPTION": "MISS Hollis-Jefferson Jump Shot",
"EVENTMSGACTIONTYPE": 5,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1626178,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.shot_type == pbpstats.UNKNOWN_SHOT_DISTANCE_STRING
def test_putback_true():
miss = {
"EVENTMSGTYPE": 2,
"PCTIMESTRING": "1:06",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
miss_event = StatsFieldGoal(miss, order)
rebound = {
"EVENTMSGTYPE": 4,
"EVENTMSGACTIONTYPE": 0,
"PCTIMESTRING": "1:03",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
rebound_event = StatsRebound(rebound, order)
make = {
"EVENTMSGTYPE": 1,
"PCTIMESTRING": "1:02",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
make_event = StatsFieldGoal(make, order)
miss_event.previous_event = None
miss_event.next_event = rebound_event
rebound_event.previous_event = miss_event
rebound_event.next_event = make_event
make_event.previous_event = rebound_event
make_event.next_event = None
assert make_event.is_putback is True
def test_putback_outside_time_cutoff_false():
miss = {
"EVENTMSGTYPE": 2,
"PCTIMESTRING": "1:06",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
miss_event = StatsFieldGoal(miss, order)
rebound = {
"EVENTMSGTYPE": 4,
"EVENTMSGACTIONTYPE": 0,
"PCTIMESTRING": "1:05",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
rebound_event = StatsRebound(rebound, order)
make = {
"EVENTMSGTYPE": 1,
"PCTIMESTRING": "1:02",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
make_event = StatsFieldGoal(make, order)
miss_event.previous_event = None
miss_event.next_event = rebound_event
rebound_event.previous_event = miss_event
rebound_event.next_event = make_event
make_event.previous_event = rebound_event
make_event.next_event = None
assert make_event.is_putback is False
def test_putback_reb_by_different_player_false():
miss = {
"EVENTMSGTYPE": 2,
"PCTIMESTRING": "1:06",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
miss_event = StatsFieldGoal(miss, order)
rebound = {
"EVENTMSGTYPE": 4,
"EVENTMSGACTIONTYPE": 0,
"PCTIMESTRING": "1:03",
"PLAYER1_ID": 13,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
rebound_event = StatsRebound(rebound, order)
make = {
"EVENTMSGTYPE": 1,
"PCTIMESTRING": "1:02",
"PLAYER1_ID": 12,
"PLAYER1_TEAM_ID": 1,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
make_event = StatsFieldGoal(make, order)
miss_event.previous_event = None
miss_event.next_event = rebound_event
rebound_event.previous_event = miss_event
rebound_event.next_event = make_event
make_event.previous_event = rebound_event
make_event.next_event = None
assert make_event.is_putback is False
def test_putback_goaltend_true():
miss = {
"EVENTNUM": 781,
"PCTIMESTRING": "01:14",
"VISITORDESCRIPTION": "MISS Shamet 7' Driving Floating Jump Shot",
"EVENTMSGACTIONTYPE": 101,
"EVENTMSGTYPE": 2,
"PLAYER1_ID": 1629013,
"PLAYER1_TEAM_ID": 1610612755,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
miss_event = StatsFieldGoal(miss, order)
rebound = {
"EVENTNUM": 783,
"PCTIMESTRING": "01:13",
"VISITORDESCRIPTION": "Muscala REBOUND (Off:1 Def:3)",
"EVENTMSGACTIONTYPE": 0,
"EVENTMSGTYPE": 4,
"PLAYER1_ID": 203488,
"PLAYER1_TEAM_ID": 1610612755,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
rebound_event = StatsRebound(rebound, order)
goaltend = {
"EVENTNUM": 785,
"PCTIMESTRING": "01:12",
"HOMEDESCRIPTION": "DiVincenzo Violation:Defensive Goaltending (N.Buchert)",
"EVENTMSGACTIONTYPE": 2,
"EVENTMSGTYPE": 7,
"PLAYER1_ID": 1628978,
"PLAYER1_TEAM_ID": 1610612749,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
goaltend_event = StatsViolation(goaltend, order)
make = {
"EVENTNUM": 784,
"PCTIMESTRING": "01:12",
"VISITORDESCRIPTION": "Muscala 1' Tip Layup Shot (8 PTS)",
"EVENTMSGACTIONTYPE": 97,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 203488,
"PLAYER1_TEAM_ID": 1610612755,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
make_event = StatsFieldGoal(make, order)
miss_event.previous_event = None
miss_event.next_event = rebound_event
rebound_event.previous_event = miss_event
rebound_event.next_event = goaltend_event
goaltend_event.previous_event = rebound_event
goaltend_event.next_event = make_event
make_event.previous_event = goaltend_event
make_event.next_event = None
assert make_event.is_putback is True
def test_putback_3pt_false():
event = {
"EVENTNUM": 20,
"PCTIMESTRING": "09:57",
"HOMEDESCRIPTION": "Rose 3PT Jump Shot (5 PTS) (Anthony 1 AST)",
"EVENTMSGACTIONTYPE": 1,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 201565,
"PLAYER1_TEAM_ID": 1610612752,
"PLAYER2_ID": 2546,
"PLAYER2_TEAM_ID": 1610612752,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
assert fg_event.is_putback is False
def test_putback_no_prev_event_false():
event = {
"EVENTNUM": 21,
"PCTIMESTRING": "09:31",
"VISITORDESCRIPTION": "Bogdanovic 2' Driving Layup (2 PTS)",
"EVENTMSGACTIONTYPE": 42,
"EVENTMSGTYPE": 1,
"PLAYER1_ID": 202711,
"PLAYER1_TEAM_ID": 1610612751,
"PLAYER2_ID": None,
"PLAYER2_TEAM_ID": None,
"PLAYER3_ID": None,
"PLAYER3_TEAM_ID": None,
}
order = 1
fg_event = StatsFieldGoal(event, order)
fg_event.previous_event = None
assert fg_event.is_putback is False
def test_is_make_that_does_not_end_possession_shot_at_time_of_and1_ft_is_false():
make = {
"EVENTMSGTYPE": 1,
"EVENTMSGACTIONTYPE": 10,
"PLAYER1_ID": 15,
"PLAYER1_TEAM_ID": 1,
"HOMEDESCRIPTION": "Made Shot",
"PCTIMESTRING": "0:45",
"EVENTNUM": 1,
}
order = 1
make_event = StatsFieldGoal(make, order)
foul = {
"EVENTMSGTYPE": 6,
"EVENTMSGACTIONTYPE": 2,
"VISITORDESCRIPTION": "Shooting Foul",
"PCTIMESTRING": "0:45",
"PLAYER1_TEAM_ID": 2,
"PLAYER1_ID": 12,
"PLAYER2_ID": 15,
"EVENTNUM": 2,
}
order = 1
foul_event = StatsFoul(foul, order)
ft = {
"EVENTMSGTYPE": 3,
"EVENTMSGACTIONTYPE": 10,
"HOMEDESCRIPTION": "Free Throw 1 of 1",
"PCTIMESTRING": "0:45",
"PLAYER1_TEAM_ID": 1,
"PLAYER1_ID": 15,
"EVENTNUM": 3,
}
order = 1
ft_event = StatsFreeThrow(ft, order)
rebound = {
"EVENTMSGTYPE": 4,
"EVENTMSGACTIONTYPE": 0,
"PLAYER1_ID": 17,
"PLAYER1_TEAM_ID": 1,
"HOMEDESCRIPTION": "Rebound",
"PCTIMESTRING": "0:45",
"EVENTNUM": 4,
}
order = 2
rebound_event = StatsRebound(rebound, order)
tip = {
"EVENTMSGTYPE": 1,
"EVENTMSGACTIONTYPE": 10,
"PLAYER1_ID": 17,
"PLAYER1_TEAM_ID": 1,
"HOMEDESCRIPTION": "Made Shot",
"PCTIMESTRING": "0:45",
"EVENTNUM": 5,
}
order = 1
tip_event = StatsFieldGoal(tip, order)
make_event.previous_event = None
make_event.next_event = foul_event
foul_event.previous_event = make_event
foul_event.next_event = ft_event
ft_event.previous_event = foul_event
ft_event.next_event = rebound_event
rebound_event.previous_event = ft_event
rebound_event.next_event = tip_event
tip_event.previous_event = rebound_event
tip_event.next_event = None
assert make_event.is_make_that_does_not_end_possession is True
assert tip_event.is_make_that_does_not_end_possession is False
def test_is_make_that_does_not_end_possession_with_foul_out_of_order_true():
make = {
"EVENTMSGTYPE": 1,
"EVENTMSGACTIONTYPE": 10,
"PLAYER1_ID": 15,
"PLAYER1_TEAM_ID": 1,
"HOMEDESCRIPTION": "Made Shot",
"PCTIMESTRING": "0:45",
"EVENTNUM": 1,
}
order = 1
make_event = StatsFieldGoal(make, order)
ft = {
"EVENTMSGTYPE": 3,
"EVENTMSGACTIONTYPE": 10,
"HOMEDESCRIPTION": "Free Throw 1 of 1",
"PCTIMESTRING": "0:45",
"PLAYER1_TEAM_ID": 1,
"PLAYER1_ID": 15,
"EVENTNUM": 2,
}
order = 1
ft_event = StatsFreeThrow(ft, order)
foul = {
"EVENTMSGTYPE": 6,
"EVENTMSGACTIONTYPE": 2,
"VISITORDESCRIPTION": "Shooting Foul",
"PCTIMESTRING": "0:45",
"PLAYER1_TEAM_ID": 2,
"PLAYER1_ID": 12,
"PLAYER2_ID": 15,
"EVENTNUM": 3,
}
order = 1
foul_event = StatsFoul(foul, order)
make_event.previous_event = None
make_event.next_event = ft_event
ft_event.previous_event = make_event
ft_event.next_event = foul_event
foul_event.previous_event = ft_event
foul_event.next_event = None
assert make_event.is_make_that_does_not_end_possession is True
def test_is_make_that_does_not_end_possession_with_lane_violation_true():
make = {
"EVENTMSGTYPE": 1,
"EVENTMSGACTIONTYPE": 10,
"PLAYER1_ID": 15,
"PLAYER1_TEAM_ID": 1,
"HOMEDESCRIPTION": "Made Shot",
"PCTIMESTRING": "0:45",
"EVENTNUM": 1,
}
order = 1
make_event = StatsFieldGoal(make, order)
foul = {
"EVENTMSGTYPE": 6,
"EVENTMSGACTIONTYPE": 2,
"VISITORDESCRIPTION": "Shooting Foul",
"PCTIMESTRING": "0:45",
"PLAYER1_TEAM_ID": 2,
"PLAYER1_ID": 12,
"PLAYER2_ID": 15,
"EVENTNUM": 2,
}
order = 1
foul_event = StatsFoul(foul, order)
lane_violation = {
"EVENTMSGTYPE": 5,
"EVENTMSGACTIONTYPE": 17,
"HOMEDESCRIPTION": "Lane Violation Turnover",
"PCTIMESTRING": "0:45",
"PLAYER1_TEAM_ID": 1,
"PLAYER1_ID": 15,
"PLAYER2_ID": None,
"EVENTNUM": 3,
}
order = 1
lane_violation_event = StatsTurnover(lane_violation, order)
make_event.previous_event = None
make_event.next_event = foul_event
foul_event.previous_event = make_event
foul_event.next_event = lane_violation_event
lane_violation_event.previous_event = foul_event
lane_violation_event.next_event = None
assert make_event.is_make_that_does_not_end_possession is True
| 28.684794 | 84 | 0.596967 | 3,186 | 28,484 | 5.045512 | 0.066541 | 0.054868 | 0.059036 | 0.051011 | 0.862457 | 0.844728 | 0.828243 | 0.798756 | 0.788678 | 0.764666 | 0 | 0.083771 | 0.285037 | 28,484 | 992 | 85 | 28.71371 | 0.705573 | 0 | 0 | 0.766376 | 0 | 0.001092 | 0.297009 | 0 | 0 | 0 | 0 | 0 | 0.040393 | 1 | 0.039301 | false | 0 | 0.008734 | 0 | 0.048035 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
ea4843853f9afb0b8697bc0ded19d272108b3e89 | 147 | bzl | Python | third_party/chromium/device/device.bzl | chokobole/felicia | 3b5eeb5f93c59c5364d3932bc407e054977aa1ec | [
"BSD-3-Clause"
] | 17 | 2018-10-28T13:58:01.000Z | 2022-03-22T07:54:12.000Z | third_party/chromium/device/device.bzl | chokobole/felicia | 3b5eeb5f93c59c5364d3932bc407e054977aa1ec | [
"BSD-3-Clause"
] | 2 | 2018-11-09T04:15:58.000Z | 2018-11-09T06:42:57.000Z | third_party/chromium/device/device.bzl | chokobole/felicia | 3b5eeb5f93c59c5364d3932bc407e054977aa1ec | [
"BSD-3-Clause"
] | 5 | 2019-10-31T06:50:05.000Z | 2022-03-22T07:54:30.000Z | def device_copts():
return []
def device_defines():
return []
def device_includes():
return []
def device_linkopts():
return []
| 12.25 | 22 | 0.62585 | 16 | 147 | 5.5 | 0.4375 | 0.409091 | 0.511364 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.238095 | 147 | 11 | 23 | 13.363636 | 0.785714 | 0 | 0 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0 | 0.5 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
ea8678a55b501026fc75b2adaf819808220d4efe | 205 | py | Python | tests/test_load_repository_url.py | LucaCappelletti94/setup_python_package | 61b5f3cff1ed3181f932293c63c4fcb71cbe0062 | [
"MIT"
] | 5 | 2019-09-17T14:46:35.000Z | 2020-06-06T08:17:02.000Z | tests/test_load_repository_url.py | LucaCappelletti94/setup_python_package | 61b5f3cff1ed3181f932293c63c4fcb71cbe0062 | [
"MIT"
] | 2 | 2020-12-18T01:47:55.000Z | 2020-12-25T10:08:30.000Z | tests/test_load_repository_url.py | LucaCappelletti94/setup_python_package | 61b5f3cff1ed3181f932293c63c4fcb71cbe0062 | [
"MIT"
] | null | null | null | from setup_python_package.utils.load_repository import load_repository_url
def test_load_repository_url():
assert load_repository_url() == "https://github.com/LucaCappelletti94/setup_python_package"
| 34.166667 | 95 | 0.839024 | 27 | 205 | 5.925926 | 0.592593 | 0.35 | 0.31875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010582 | 0.078049 | 205 | 5 | 96 | 41 | 0.835979 | 0 | 0 | 0 | 0 | 0 | 0.278049 | 0 | 0 | 0 | 0 | 0 | 0.333333 | 1 | 0.333333 | true | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
ea95fffe5a1b8bb6183981bc17b33c5c10d3412e | 102 | py | Python | tests/docs/test_joined_dependant.py | Kludex/di | dc8b3ad3f6b0004a439a17208872ddbd24b62fbf | [
"MIT"
] | 5 | 2021-07-30T10:10:16.000Z | 2021-09-23T11:23:15.000Z | tests/docs/test_joined_dependant.py | Kludex/di | dc8b3ad3f6b0004a439a17208872ddbd24b62fbf | [
"MIT"
] | 3 | 2021-07-26T06:22:09.000Z | 2021-09-24T16:11:08.000Z | tests/docs/test_joined_dependant.py | Kludex/di | dc8b3ad3f6b0004a439a17208872ddbd24b62fbf | [
"MIT"
] | 1 | 2021-09-17T07:22:23.000Z | 2021-09-17T07:22:23.000Z | from docs.src import joined_dependant
def test_bind_as_a_dep() -> None:
joined_dependant.main()
| 17 | 37 | 0.764706 | 16 | 102 | 4.5 | 0.875 | 0.416667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.147059 | 102 | 5 | 38 | 20.4 | 0.827586 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | true | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
578566530d0d03ce6c6873aa034cce53cafd7ecf | 379 | py | Python | python/alg/lcd.py | Zeyu-Li/quick_algorithm | 5fcbb18f94b49ff164c61f412cf9e13cb7d53e6e | [
"MIT"
] | 6 | 2020-12-31T14:11:45.000Z | 2021-12-07T17:44:13.000Z | python/alg/lcd.py | Zeyu-Li/quick_algorithm | 5fcbb18f94b49ff164c61f412cf9e13cb7d53e6e | [
"MIT"
] | null | null | null | python/alg/lcd.py | Zeyu-Li/quick_algorithm | 5fcbb18f94b49ff164c61f412cf9e13cb7d53e6e | [
"MIT"
] | 1 | 2021-01-03T00:55:11.000Z | 2021-01-03T00:55:11.000Z | """" LCD (lowest common denominator) """
def lcd(gcd, int1, int2):
return int((int1*int2)/gcd)
def lcd_no_gcd(int1, int2):
from gcd import gcd
return int((int1*int2)/gcd(int1,int2))
# different name, same thing
def lcm(gcd, int1, int2):
return int((int1*int2)/gcd)
def lcm_no_gcd(int1, int2):
from gcd import gcd
return int((int1*int2)/gcd(int1,int2)) | 23.6875 | 42 | 0.664908 | 62 | 379 | 4 | 0.290323 | 0.322581 | 0.266129 | 0.274194 | 0.733871 | 0.733871 | 0.733871 | 0.733871 | 0.733871 | 0.459677 | 0 | 0.064309 | 0.17942 | 379 | 16 | 43 | 23.6875 | 0.733119 | 0.163588 | 0 | 0.6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.4 | false | 0 | 0.2 | 0.2 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 9 |
5789924b33855cffe1abfc12d116972fb0351478 | 302,742 | py | Python | pybullet_tools/pr2_never_collisions.py | shrirangsp/pybullet-planning | 2ea8692221e5bbb93ccad4c800a3590d264c5bd6 | [
"MIT"
] | null | null | null | pybullet_tools/pr2_never_collisions.py | shrirangsp/pybullet-planning | 2ea8692221e5bbb93ccad4c800a3590d264c5bd6 | [
"MIT"
] | null | null | null | pybullet_tools/pr2_never_collisions.py | shrirangsp/pybullet-planning | 2ea8692221e5bbb93ccad4c800a3590d264c5bd6 | [
"MIT"
] | null | null | null | # TODO: maybe some OpenRAVE links are disabled
# http://openrave.org/docs/0.8.2/collada_robot_extensions/
# < extra
# type = "collision" >
# < technique
# profile = "OpenRAVE"
# ignore_link_pair
NEVER_COLLISIONS_TIAGO = [('base_link','base_antenna_left_link'), ('base_link','base_antenna_right_link'), ('base_link','wheel_right_link'), ('base_link','wheel_left_link'), ('base_link','ignore_caster_front_right_2_link'), ('base_link','ignore_caster_front_left_2_link'), ('base_link','ignore_caster_back_right_2_link'), ('base_link','ignore_caster_back_left_2_link'), ('base_link','torso_fixed_link'), ('base_link','torso_lift_link'), ('base_link','head_1_link'), ('base_link','head_2_link'), ('base_link','arm_left_1_link'), ('base_link','arm_left_2_link'), ('base_link','arm_left_3_link'), ('base_link','arm_left_4_link'), ('base_link','arm_left_5_link'), ('base_link','arm_left_6_link'), ('base_link','arm_left_7_link'), ('base_link','arm_left_tool_link'), ('base_link','wrist_left_ft_link'), ('base_link','wrist_left_ft_tool_link'), ('base_link','gripper_left_link'), ('base_link','gripper_left_right_finger_link'), ('base_link','gripper_left_left_finger_link'), ('base_link','arm_right_1_link'), ('base_link','arm_right_2_link'), ('base_link','arm_right_3_link'), ('base_link','arm_right_4_link'), ('base_link','arm_right_5_link'), ('base_link','arm_right_6_link'), ('base_link','arm_right_7_link'), ('base_link','arm_right_tool_link'), ('base_link','wrist_right_ft_link'), ('base_link','wrist_right_ft_tool_link'), ('base_link','hand_right_palm_link'), ('base_link','hand_right_thumb_link'), ('base_link','hand_right_index_link'), ('base_link','hand_right_mrl_link'), ('base_link','hand_right_thumb_abd_link'), ('base_link','hand_right_thumb_virtual_1_link'), ('base_link','hand_right_thumb_flex_1_link'), ('base_link','hand_right_thumb_virtual_2_link'), ('base_link','hand_right_thumb_flex_2_link'), ('base_link','hand_right_index_abd_link'), ('base_link','hand_right_index_virtual_1_link'), ('base_link','hand_right_index_flex_1_link'), ('base_link','hand_right_index_virtual_2_link'), ('base_link','hand_right_index_flex_2_link'), ('base_link','hand_right_index_virtual_3_link'), ('base_link','hand_right_index_flex_3_link'), ('base_link','hand_right_middle_abd_link'), ('base_link','hand_right_middle_virtual_1_link'), ('base_link','hand_right_middle_flex_1_link'), ('base_link','hand_right_middle_virtual_2_link'), ('base_link','hand_right_middle_flex_2_link'), ('base_link','hand_right_middle_virtual_3_link'), ('base_link','hand_right_middle_flex_3_link'), ('base_link','hand_right_ring_abd_link'), ('base_link','hand_right_ring_virtual_1_link'), ('base_link','hand_right_ring_flex_1_link'), ('base_link','hand_right_ring_virtual_2_link'), ('base_link','hand_right_ring_flex_2_link'), ('base_link','hand_right_ring_virtual_3_link'), ('base_link','hand_right_ring_flex_3_link'), ('base_link','hand_right_little_abd_link'), ('base_link','hand_right_little_virtual_1_link'), ('base_link','hand_right_little_flex_1_link'), ('base_link','hand_right_little_virtual_2_link'), ('base_link','hand_right_little_flex_2_link'), ('base_link','hand_right_little_virtual_3_link'), ('base_link','hand_right_little_flex_3_link'), ('base_link','torso_fixed_column_link '), ('base_antenna_left_link','base_link'), ('base_antenna_left_link','base_antenna_right_link'), ('base_antenna_left_link','wheel_right_link'), ('base_antenna_left_link','wheel_left_link'), ('base_antenna_left_link','ignore_caster_front_right_2_link'), ('base_antenna_left_link','ignore_caster_front_left_2_link'), ('base_antenna_left_link','ignore_caster_back_right_2_link'), ('base_antenna_left_link','ignore_caster_back_left_2_link'), ('base_antenna_left_link','torso_fixed_link'), ('base_antenna_left_link','torso_lift_link'), ('base_antenna_left_link','head_1_link'), ('base_antenna_left_link','head_2_link'), ('base_antenna_left_link','arm_left_1_link'), ('base_antenna_left_link','arm_left_2_link'), ('base_antenna_left_link','arm_left_3_link'), ('base_antenna_left_link','arm_left_4_link'), ('base_antenna_left_link','arm_left_5_link'), ('base_antenna_left_link','arm_left_6_link'), ('base_antenna_left_link','arm_left_7_link'), ('base_antenna_left_link','arm_left_tool_link'), ('base_antenna_left_link','wrist_left_ft_link'), ('base_antenna_left_link','wrist_left_ft_tool_link'), ('base_antenna_left_link','gripper_left_link'), ('base_antenna_left_link','gripper_left_right_finger_link'), ('base_antenna_left_link','gripper_left_left_finger_link'), ('base_antenna_left_link','arm_right_1_link'), ('base_antenna_left_link','arm_right_2_link'), ('base_antenna_left_link','arm_right_3_link'), ('base_antenna_left_link','arm_right_4_link'), ('base_antenna_left_link','arm_right_5_link'), ('base_antenna_left_link','arm_right_6_link'), ('base_antenna_left_link','arm_right_7_link'), ('base_antenna_left_link','arm_right_tool_link'), ('base_antenna_left_link','wrist_right_ft_link'), ('base_antenna_left_link','wrist_right_ft_tool_link'), ('base_antenna_left_link','hand_right_palm_link'), ('base_antenna_left_link','hand_right_thumb_link'), ('base_antenna_left_link','hand_right_index_link'), ('base_antenna_left_link','hand_right_mrl_link'), ('base_antenna_left_link','hand_right_thumb_abd_link'), ('base_antenna_left_link','hand_right_thumb_virtual_1_link'), ('base_antenna_left_link','hand_right_thumb_flex_1_link'), ('base_antenna_left_link','hand_right_thumb_virtual_2_link'), ('base_antenna_left_link','hand_right_thumb_flex_2_link'), ('base_antenna_left_link','hand_right_index_abd_link'), ('base_antenna_left_link','hand_right_index_virtual_1_link'), ('base_antenna_left_link','hand_right_index_flex_1_link'), ('base_antenna_left_link','hand_right_index_virtual_2_link'), ('base_antenna_left_link','hand_right_index_flex_2_link'), ('base_antenna_left_link','hand_right_index_virtual_3_link'), ('base_antenna_left_link','hand_right_index_flex_3_link'), ('base_antenna_left_link','hand_right_middle_abd_link'), ('base_antenna_left_link','hand_right_middle_virtual_1_link'), ('base_antenna_left_link','hand_right_middle_flex_1_link'), ('base_antenna_left_link','hand_right_middle_virtual_2_link'), ('base_antenna_left_link','hand_right_middle_flex_2_link'), ('base_antenna_left_link','hand_right_middle_virtual_3_link'), ('base_antenna_left_link','hand_right_middle_flex_3_link'), ('base_antenna_left_link','hand_right_ring_abd_link'), ('base_antenna_left_link','hand_right_ring_virtual_1_link'), ('base_antenna_left_link','hand_right_ring_flex_1_link'), ('base_antenna_left_link','hand_right_ring_virtual_2_link'), ('base_antenna_left_link','hand_right_ring_flex_2_link'), ('base_antenna_left_link','hand_right_ring_virtual_3_link'), ('base_antenna_left_link','hand_right_ring_flex_3_link'), ('base_antenna_left_link','hand_right_little_abd_link'), ('base_antenna_left_link','hand_right_little_virtual_1_link'), ('base_antenna_left_link','hand_right_little_flex_1_link'), ('base_antenna_left_link','hand_right_little_virtual_2_link'), ('base_antenna_left_link','hand_right_little_flex_2_link'), ('base_antenna_left_link','hand_right_little_virtual_3_link'), ('base_antenna_left_link','hand_right_little_flex_3_link'), ('base_antenna_left_link','torso_fixed_column_link '), ('base_antenna_right_link','base_link'), ('base_antenna_right_link','base_antenna_left_link'), ('base_antenna_right_link','wheel_right_link'), ('base_antenna_right_link','wheel_left_link'), ('base_antenna_right_link','ignore_caster_front_right_2_link'), ('base_antenna_right_link','ignore_caster_front_left_2_link'), ('base_antenna_right_link','ignore_caster_back_right_2_link'), ('base_antenna_right_link','ignore_caster_back_left_2_link'), ('base_antenna_right_link','torso_fixed_link'), ('base_antenna_right_link','torso_lift_link'), ('base_antenna_right_link','head_1_link'), ('base_antenna_right_link','head_2_link'), ('base_antenna_right_link','arm_left_1_link'), ('base_antenna_right_link','arm_left_2_link'), ('base_antenna_right_link','arm_left_3_link'), ('base_antenna_right_link','arm_left_4_link'), ('base_antenna_right_link','arm_left_5_link'), ('base_antenna_right_link','arm_left_6_link'), ('base_antenna_right_link','arm_left_7_link'), ('base_antenna_right_link','arm_left_tool_link'), ('base_antenna_right_link','wrist_left_ft_link'), ('base_antenna_right_link','wrist_left_ft_tool_link'), ('base_antenna_right_link','gripper_left_link'), ('base_antenna_right_link','gripper_left_right_finger_link'), ('base_antenna_right_link','gripper_left_left_finger_link'), ('base_antenna_right_link','arm_right_1_link'), ('base_antenna_right_link','arm_right_2_link'), ('base_antenna_right_link','arm_right_3_link'), ('base_antenna_right_link','arm_right_4_link'), ('base_antenna_right_link','arm_right_5_link'), ('base_antenna_right_link','arm_right_6_link'), ('base_antenna_right_link','arm_right_7_link'), ('base_antenna_right_link','arm_right_tool_link'), ('base_antenna_right_link','wrist_right_ft_link'), ('base_antenna_right_link','wrist_right_ft_tool_link'), ('base_antenna_right_link','hand_right_palm_link'), ('base_antenna_right_link','hand_right_thumb_link'), ('base_antenna_right_link','hand_right_index_link'), ('base_antenna_right_link','hand_right_mrl_link'), ('base_antenna_right_link','hand_right_thumb_abd_link'), ('base_antenna_right_link','hand_right_thumb_virtual_1_link'), ('base_antenna_right_link','hand_right_thumb_flex_1_link'), ('base_antenna_right_link','hand_right_thumb_virtual_2_link'), ('base_antenna_right_link','hand_right_thumb_flex_2_link'), ('base_antenna_right_link','hand_right_index_abd_link'), ('base_antenna_right_link','hand_right_index_virtual_1_link'), ('base_antenna_right_link','hand_right_index_flex_1_link'), ('base_antenna_right_link','hand_right_index_virtual_2_link'), ('base_antenna_right_link','hand_right_index_flex_2_link'), ('base_antenna_right_link','hand_right_index_virtual_3_link'), ('base_antenna_right_link','hand_right_index_flex_3_link'), ('base_antenna_right_link','hand_right_middle_abd_link'), ('base_antenna_right_link','hand_right_middle_virtual_1_link'), ('base_antenna_right_link','hand_right_middle_flex_1_link'), ('base_antenna_right_link','hand_right_middle_virtual_2_link'), ('base_antenna_right_link','hand_right_middle_flex_2_link'), ('base_antenna_right_link','hand_right_middle_virtual_3_link'), ('base_antenna_right_link','hand_right_middle_flex_3_link'), ('base_antenna_right_link','hand_right_ring_abd_link'), ('base_antenna_right_link','hand_right_ring_virtual_1_link'), ('base_antenna_right_link','hand_right_ring_flex_1_link'), ('base_antenna_right_link','hand_right_ring_virtual_2_link'), ('base_antenna_right_link','hand_right_ring_flex_2_link'), ('base_antenna_right_link','hand_right_ring_virtual_3_link'), ('base_antenna_right_link','hand_right_ring_flex_3_link'), ('base_antenna_right_link','hand_right_little_abd_link'), ('base_antenna_right_link','hand_right_little_virtual_1_link'), ('base_antenna_right_link','hand_right_little_flex_1_link'), ('base_antenna_right_link','hand_right_little_virtual_2_link'), ('base_antenna_right_link','hand_right_little_flex_2_link'), ('base_antenna_right_link','hand_right_little_virtual_3_link'), ('base_antenna_right_link','hand_right_little_flex_3_link'), ('base_antenna_right_link','torso_fixed_column_link '), ('wheel_right_link','base_link'), ('wheel_right_link','base_antenna_left_link'), ('wheel_right_link','base_antenna_right_link'), ('wheel_right_link','wheel_left_link'), ('wheel_right_link','ignore_caster_front_right_2_link'), ('wheel_right_link','ignore_caster_front_left_2_link'), ('wheel_right_link','ignore_caster_back_right_2_link'), ('wheel_right_link','ignore_caster_back_left_2_link'), ('wheel_right_link','torso_fixed_link'), ('wheel_right_link','torso_lift_link'), ('wheel_right_link','head_1_link'), ('wheel_right_link','head_2_link'), ('wheel_right_link','arm_left_1_link'), ('wheel_right_link','arm_left_2_link'), ('wheel_right_link','arm_left_3_link'), ('wheel_right_link','arm_left_4_link'), ('wheel_right_link','arm_left_5_link'), ('wheel_right_link','arm_left_6_link'), ('wheel_right_link','arm_left_7_link'), ('wheel_right_link','arm_left_tool_link'), ('wheel_right_link','wrist_left_ft_link'), ('wheel_right_link','wrist_left_ft_tool_link'), ('wheel_right_link','gripper_left_link'), ('wheel_right_link','gripper_left_right_finger_link'), ('wheel_right_link','gripper_left_left_finger_link'), ('wheel_right_link','arm_right_1_link'), ('wheel_right_link','arm_right_2_link'), ('wheel_right_link','arm_right_3_link'), ('wheel_right_link','arm_right_4_link'), ('wheel_right_link','arm_right_5_link'), ('wheel_right_link','arm_right_6_link'), ('wheel_right_link','arm_right_7_link'), ('wheel_right_link','arm_right_tool_link'), ('wheel_right_link','wrist_right_ft_link'), ('wheel_right_link','wrist_right_ft_tool_link'), ('wheel_right_link','hand_right_palm_link'), ('wheel_right_link','hand_right_thumb_link'), ('wheel_right_link','hand_right_index_link'), ('wheel_right_link','hand_right_mrl_link'), ('wheel_right_link','hand_right_thumb_abd_link'), ('wheel_right_link','hand_right_thumb_virtual_1_link'), ('wheel_right_link','hand_right_thumb_flex_1_link'), ('wheel_right_link','hand_right_thumb_virtual_2_link'), ('wheel_right_link','hand_right_thumb_flex_2_link'), ('wheel_right_link','hand_right_index_abd_link'), ('wheel_right_link','hand_right_index_virtual_1_link'), ('wheel_right_link','hand_right_index_flex_1_link'), ('wheel_right_link','hand_right_index_virtual_2_link'), ('wheel_right_link','hand_right_index_flex_2_link'), ('wheel_right_link','hand_right_index_virtual_3_link'), ('wheel_right_link','hand_right_index_flex_3_link'), ('wheel_right_link','hand_right_middle_abd_link'), ('wheel_right_link','hand_right_middle_virtual_1_link'), ('wheel_right_link','hand_right_middle_flex_1_link'), ('wheel_right_link','hand_right_middle_virtual_2_link'), ('wheel_right_link','hand_right_middle_flex_2_link'), ('wheel_right_link','hand_right_middle_virtual_3_link'), ('wheel_right_link','hand_right_middle_flex_3_link'), ('wheel_right_link','hand_right_ring_abd_link'), ('wheel_right_link','hand_right_ring_virtual_1_link'), ('wheel_right_link','hand_right_ring_flex_1_link'), ('wheel_right_link','hand_right_ring_virtual_2_link'), ('wheel_right_link','hand_right_ring_flex_2_link'), ('wheel_right_link','hand_right_ring_virtual_3_link'), ('wheel_right_link','hand_right_ring_flex_3_link'), ('wheel_right_link','hand_right_little_abd_link'), ('wheel_right_link','hand_right_little_virtual_1_link'), ('wheel_right_link','hand_right_little_flex_1_link'), ('wheel_right_link','hand_right_little_virtual_2_link'), ('wheel_right_link','hand_right_little_flex_2_link'), ('wheel_right_link','hand_right_little_virtual_3_link'), ('wheel_right_link','hand_right_little_flex_3_link'), ('wheel_right_link','torso_fixed_column_link '), ('wheel_left_link','base_link'), ('wheel_left_link','base_antenna_left_link'), ('wheel_left_link','base_antenna_right_link'), ('wheel_left_link','wheel_right_link'), ('wheel_left_link','ignore_caster_front_right_2_link'), ('wheel_left_link','ignore_caster_front_left_2_link'), ('wheel_left_link','ignore_caster_back_right_2_link'), ('wheel_left_link','ignore_caster_back_left_2_link'), ('wheel_left_link','torso_fixed_link'), ('wheel_left_link','torso_lift_link'), ('wheel_left_link','head_1_link'), ('wheel_left_link','head_2_link'), ('wheel_left_link','arm_left_1_link'), ('wheel_left_link','arm_left_2_link'), ('wheel_left_link','arm_left_3_link'), ('wheel_left_link','arm_left_4_link'), ('wheel_left_link','arm_left_5_link'), ('wheel_left_link','arm_left_6_link'), ('wheel_left_link','arm_left_7_link'), ('wheel_left_link','arm_left_tool_link'), ('wheel_left_link','wrist_left_ft_link'), ('wheel_left_link','wrist_left_ft_tool_link'), ('wheel_left_link','gripper_left_link'), ('wheel_left_link','gripper_left_right_finger_link'), ('wheel_left_link','gripper_left_left_finger_link'), ('wheel_left_link','arm_right_1_link'), ('wheel_left_link','arm_right_2_link'), ('wheel_left_link','arm_right_3_link'), ('wheel_left_link','arm_right_4_link'), ('wheel_left_link','arm_right_5_link'), ('wheel_left_link','arm_right_6_link'), ('wheel_left_link','arm_right_7_link'), ('wheel_left_link','arm_right_tool_link'), ('wheel_left_link','wrist_right_ft_link'), ('wheel_left_link','wrist_right_ft_tool_link'), ('wheel_left_link','hand_right_palm_link'), ('wheel_left_link','hand_right_thumb_link'), ('wheel_left_link','hand_right_index_link'), ('wheel_left_link','hand_right_mrl_link'), ('wheel_left_link','hand_right_thumb_abd_link'), ('wheel_left_link','hand_right_thumb_virtual_1_link'), ('wheel_left_link','hand_right_thumb_flex_1_link'), ('wheel_left_link','hand_right_thumb_virtual_2_link'), ('wheel_left_link','hand_right_thumb_flex_2_link'), ('wheel_left_link','hand_right_index_abd_link'), ('wheel_left_link','hand_right_index_virtual_1_link'), ('wheel_left_link','hand_right_index_flex_1_link'), ('wheel_left_link','hand_right_index_virtual_2_link'), ('wheel_left_link','hand_right_index_flex_2_link'), ('wheel_left_link','hand_right_index_virtual_3_link'), ('wheel_left_link','hand_right_index_flex_3_link'), ('wheel_left_link','hand_right_middle_abd_link'), ('wheel_left_link','hand_right_middle_virtual_1_link'), ('wheel_left_link','hand_right_middle_flex_1_link'), ('wheel_left_link','hand_right_middle_virtual_2_link'), ('wheel_left_link','hand_right_middle_flex_2_link'), ('wheel_left_link','hand_right_middle_virtual_3_link'), ('wheel_left_link','hand_right_middle_flex_3_link'), ('wheel_left_link','hand_right_ring_abd_link'), ('wheel_left_link','hand_right_ring_virtual_1_link'), ('wheel_left_link','hand_right_ring_flex_1_link'), ('wheel_left_link','hand_right_ring_virtual_2_link'), ('wheel_left_link','hand_right_ring_flex_2_link'), ('wheel_left_link','hand_right_ring_virtual_3_link'), ('wheel_left_link','hand_right_ring_flex_3_link'), ('wheel_left_link','hand_right_little_abd_link'), ('wheel_left_link','hand_right_little_virtual_1_link'), ('wheel_left_link','hand_right_little_flex_1_link'), ('wheel_left_link','hand_right_little_virtual_2_link'), ('wheel_left_link','hand_right_little_flex_2_link'), ('wheel_left_link','hand_right_little_virtual_3_link'), ('wheel_left_link','hand_right_little_flex_3_link'), ('wheel_left_link','torso_fixed_column_link '), ('ignore_caster_front_right_2_link','base_link'), ('ignore_caster_front_right_2_link','base_antenna_left_link'), ('ignore_caster_front_right_2_link','base_antenna_right_link'), ('ignore_caster_front_right_2_link','wheel_right_link'), ('ignore_caster_front_right_2_link','wheel_left_link'), ('ignore_caster_front_right_2_link','ignore_caster_front_left_2_link'), ('ignore_caster_front_right_2_link','ignore_caster_back_right_2_link'), ('ignore_caster_front_right_2_link','ignore_caster_back_left_2_link'), ('ignore_caster_front_right_2_link','torso_fixed_link'), ('ignore_caster_front_right_2_link','torso_lift_link'), ('ignore_caster_front_right_2_link','head_1_link'), ('ignore_caster_front_right_2_link','head_2_link'), ('ignore_caster_front_right_2_link','arm_left_1_link'), ('ignore_caster_front_right_2_link','arm_left_2_link'), ('ignore_caster_front_right_2_link','arm_left_3_link'), ('ignore_caster_front_right_2_link','arm_left_4_link'), ('ignore_caster_front_right_2_link','arm_left_5_link'), ('ignore_caster_front_right_2_link','arm_left_6_link'), ('ignore_caster_front_right_2_link','arm_left_7_link'), ('ignore_caster_front_right_2_link','arm_left_tool_link'), ('ignore_caster_front_right_2_link','wrist_left_ft_link'), ('ignore_caster_front_right_2_link','wrist_left_ft_tool_link'), ('ignore_caster_front_right_2_link','gripper_left_link'), ('ignore_caster_front_right_2_link','gripper_left_right_finger_link'), ('ignore_caster_front_right_2_link','gripper_left_left_finger_link'), ('ignore_caster_front_right_2_link','arm_right_1_link'), ('ignore_caster_front_right_2_link','arm_right_2_link'), ('ignore_caster_front_right_2_link','arm_right_3_link'), ('ignore_caster_front_right_2_link','arm_right_4_link'), ('ignore_caster_front_right_2_link','arm_right_5_link'), ('ignore_caster_front_right_2_link','arm_right_6_link'), ('ignore_caster_front_right_2_link','arm_right_7_link'), ('ignore_caster_front_right_2_link','arm_right_tool_link'), ('ignore_caster_front_right_2_link','wrist_right_ft_link'), ('ignore_caster_front_right_2_link','wrist_right_ft_tool_link'), ('ignore_caster_front_right_2_link','hand_right_palm_link'), ('ignore_caster_front_right_2_link','hand_right_thumb_link'), ('ignore_caster_front_right_2_link','hand_right_index_link'), ('ignore_caster_front_right_2_link','hand_right_mrl_link'), ('ignore_caster_front_right_2_link','hand_right_thumb_abd_link'), 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('hand_right_little_virtual_3_link','hand_right_palm_link'), ('hand_right_little_virtual_3_link','hand_right_thumb_link'), ('hand_right_little_virtual_3_link','hand_right_index_link'), ('hand_right_little_virtual_3_link','hand_right_mrl_link'), ('hand_right_little_virtual_3_link','hand_right_thumb_abd_link'), ('hand_right_little_virtual_3_link','hand_right_thumb_virtual_1_link'), ('hand_right_little_virtual_3_link','hand_right_thumb_flex_1_link'), ('hand_right_little_virtual_3_link','hand_right_thumb_virtual_2_link'), ('hand_right_little_virtual_3_link','hand_right_thumb_flex_2_link'), ('hand_right_little_virtual_3_link','hand_right_index_abd_link'), ('hand_right_little_virtual_3_link','hand_right_index_virtual_1_link'), ('hand_right_little_virtual_3_link','hand_right_index_flex_1_link'), ('hand_right_little_virtual_3_link','hand_right_index_virtual_2_link'), ('hand_right_little_virtual_3_link','hand_right_index_flex_2_link'), ('hand_right_little_virtual_3_link','hand_right_index_virtual_3_link'), ('hand_right_little_virtual_3_link','hand_right_index_flex_3_link'), ('hand_right_little_virtual_3_link','hand_right_middle_abd_link'), ('hand_right_little_virtual_3_link','hand_right_middle_virtual_1_link'), ('hand_right_little_virtual_3_link','hand_right_middle_flex_1_link'), ('hand_right_little_virtual_3_link','hand_right_middle_virtual_2_link'), ('hand_right_little_virtual_3_link','hand_right_middle_flex_2_link'), ('hand_right_little_virtual_3_link','hand_right_middle_virtual_3_link'), ('hand_right_little_virtual_3_link','hand_right_middle_flex_3_link'), ('hand_right_little_virtual_3_link','hand_right_ring_abd_link'), ('hand_right_little_virtual_3_link','hand_right_ring_virtual_1_link'), ('hand_right_little_virtual_3_link','hand_right_ring_flex_1_link'), ('hand_right_little_virtual_3_link','hand_right_ring_virtual_2_link'), ('hand_right_little_virtual_3_link','hand_right_ring_flex_2_link'), ('hand_right_little_virtual_3_link','hand_right_ring_virtual_3_link'), ('hand_right_little_virtual_3_link','hand_right_ring_flex_3_link'), ('hand_right_little_virtual_3_link','hand_right_little_abd_link'), ('hand_right_little_virtual_3_link','hand_right_little_virtual_1_link'), ('hand_right_little_virtual_3_link','hand_right_little_flex_1_link'), ('hand_right_little_virtual_3_link','hand_right_little_virtual_2_link'), ('hand_right_little_virtual_3_link','hand_right_little_flex_2_link'), ('hand_right_little_virtual_3_link','hand_right_little_flex_3_link'), ('hand_right_little_virtual_3_link','torso_fixed_column_link '), ('hand_right_little_flex_3_link','base_link'), ('hand_right_little_flex_3_link','base_antenna_left_link'), ('hand_right_little_flex_3_link','base_antenna_right_link'), ('hand_right_little_flex_3_link','wheel_right_link'), ('hand_right_little_flex_3_link','wheel_left_link'), ('hand_right_little_flex_3_link','ignore_caster_front_right_2_link'), ('hand_right_little_flex_3_link','ignore_caster_front_left_2_link'), ('hand_right_little_flex_3_link','ignore_caster_back_right_2_link'), ('hand_right_little_flex_3_link','ignore_caster_back_left_2_link'), ('hand_right_little_flex_3_link','torso_fixed_link'), ('hand_right_little_flex_3_link','torso_lift_link'),('hand_right_little_flex_3_link','head_1_link'), ('hand_right_little_flex_3_link','head_2_link'), ('hand_right_little_flex_3_link','arm_left_1_link'), ('hand_right_little_flex_3_link','arm_left_2_link'), ('hand_right_little_flex_3_link','arm_left_3_link'), ('hand_right_little_flex_3_link','arm_left_4_link'), ('hand_right_little_flex_3_link','arm_left_5_link'), ('hand_right_little_flex_3_link','arm_left_6_link'), ('hand_right_little_flex_3_link','arm_left_7_link'), ('hand_right_little_flex_3_link','arm_left_tool_link'), ('hand_right_little_flex_3_link','wrist_left_ft_link'), ('hand_right_little_flex_3_link','wrist_left_ft_tool_link'), ('hand_right_little_flex_3_link','gripper_left_link'), ('hand_right_little_flex_3_link','gripper_left_right_finger_link'), ('hand_right_little_flex_3_link','gripper_left_left_finger_link'), ('hand_right_little_flex_3_link','arm_right_1_link'), ('hand_right_little_flex_3_link','arm_right_2_link'), ('hand_right_little_flex_3_link','arm_right_3_link'), ('hand_right_little_flex_3_link','arm_right_4_link'), ('hand_right_little_flex_3_link','arm_right_5_link'), ('hand_right_little_flex_3_link','arm_right_6_link'), ('hand_right_little_flex_3_link','arm_right_7_link'), ('hand_right_little_flex_3_link','arm_right_tool_link'), ('hand_right_little_flex_3_link','wrist_right_ft_link'), ('hand_right_little_flex_3_link','wrist_right_ft_tool_link'), ('hand_right_little_flex_3_link','hand_right_palm_link'), ('hand_right_little_flex_3_link','hand_right_thumb_link'), ('hand_right_little_flex_3_link','hand_right_index_link'), ('hand_right_little_flex_3_link','hand_right_mrl_link'), ('hand_right_little_flex_3_link','hand_right_thumb_abd_link'), ('hand_right_little_flex_3_link','hand_right_thumb_virtual_1_link'), ('hand_right_little_flex_3_link','hand_right_thumb_flex_1_link'), ('hand_right_little_flex_3_link','hand_right_thumb_virtual_2_link'), ('hand_right_little_flex_3_link','hand_right_thumb_flex_2_link'), ('hand_right_little_flex_3_link','hand_right_index_abd_link'), ('hand_right_little_flex_3_link','hand_right_index_virtual_1_link'), ('hand_right_little_flex_3_link','hand_right_index_flex_1_link'), ('hand_right_little_flex_3_link','hand_right_index_virtual_2_link'), ('hand_right_little_flex_3_link','hand_right_index_flex_2_link'), ('hand_right_little_flex_3_link','hand_right_index_virtual_3_link'), ('hand_right_little_flex_3_link','hand_right_index_flex_3_link'), ('hand_right_little_flex_3_link','hand_right_middle_abd_link'), ('hand_right_little_flex_3_link','hand_right_middle_virtual_1_link'), ('hand_right_little_flex_3_link','hand_right_middle_flex_1_link'), ('hand_right_little_flex_3_link','hand_right_middle_virtual_2_link'), ('hand_right_little_flex_3_link','hand_right_middle_flex_2_link'), ('hand_right_little_flex_3_link','hand_right_middle_virtual_3_link'), ('hand_right_little_flex_3_link','hand_right_middle_flex_3_link'), ('hand_right_little_flex_3_link','hand_right_ring_abd_link'), ('hand_right_little_flex_3_link','hand_right_ring_virtual_1_link'), ('hand_right_little_flex_3_link','hand_right_ring_flex_1_link'), ('hand_right_little_flex_3_link','hand_right_ring_virtual_2_link'), ('hand_right_little_flex_3_link','hand_right_ring_flex_2_link'), ('hand_right_little_flex_3_link','hand_right_ring_virtual_3_link'), ('hand_right_little_flex_3_link','hand_right_ring_flex_3_link'), ('hand_right_little_flex_3_link','hand_right_little_abd_link'), ('hand_right_little_flex_3_link','hand_right_little_virtual_1_link'), ('hand_right_little_flex_3_link','hand_right_little_flex_1_link'), ('hand_right_little_flex_3_link','hand_right_little_virtual_2_link'), ('hand_right_little_flex_3_link','hand_right_little_flex_2_link'), ('hand_right_little_flex_3_link','hand_right_little_virtual_3_link'), ('hand_right_little_flex_3_link','torso_fixed_column_link '), ('torso_fixed_column_link ','base_link'), ('torso_fixed_column_link ','base_antenna_left_link'), ('torso_fixed_column_link ','base_antenna_right_link'), ('torso_fixed_column_link ','wheel_right_link'), ('torso_fixed_column_link ','wheel_left_link'), ('torso_fixed_column_link ','ignore_caster_front_right_2_link'), ('torso_fixed_column_link ','ignore_caster_front_left_2_link'), ('torso_fixed_column_link ','ignore_caster_back_right_2_link'), ('torso_fixed_column_link ','ignore_caster_back_left_2_link'), ('torso_fixed_column_link ','torso_fixed_link'), ('torso_fixed_column_link ','torso_lift_link'), ('torso_fixed_column_link ','head_1_link'), ('torso_fixed_column_link ','head_2_link'), ('torso_fixed_column_link ','arm_left_1_link'), ('torso_fixed_column_link ','arm_left_2_link'), ('torso_fixed_column_link ','arm_left_3_link'), ('torso_fixed_column_link ','arm_left_4_link'), ('torso_fixed_column_link ','arm_left_5_link'), ('torso_fixed_column_link ','arm_left_6_link'), ('torso_fixed_column_link ','arm_left_7_link'), ('torso_fixed_column_link ','arm_left_tool_link'), ('torso_fixed_column_link ','wrist_left_ft_link'), ('torso_fixed_column_link ','wrist_left_ft_tool_link'), ('torso_fixed_column_link ','gripper_left_link'), ('torso_fixed_column_link ','gripper_left_right_finger_link'), ('torso_fixed_column_link ','gripper_left_left_finger_link'), ('torso_fixed_column_link ','arm_right_1_link'), ('torso_fixed_column_link ','arm_right_2_link'), ('torso_fixed_column_link ','arm_right_3_link'), ('torso_fixed_column_link ','arm_right_4_link'), ('torso_fixed_column_link ','arm_right_5_link'), ('torso_fixed_column_link ','arm_right_6_link'), ('torso_fixed_column_link ','arm_right_7_link'), ('torso_fixed_column_link ','arm_right_tool_link'), ('torso_fixed_column_link ','wrist_right_ft_link'), ('torso_fixed_column_link ','wrist_right_ft_tool_link'), ('torso_fixed_column_link ','hand_right_palm_link'), ('torso_fixed_column_link ','hand_right_thumb_link'), ('torso_fixed_column_link ','hand_right_index_link'), ('torso_fixed_column_link ','hand_right_mrl_link'), ('torso_fixed_column_link ','hand_right_thumb_abd_link'), ('torso_fixed_column_link ','hand_right_thumb_virtual_1_link'), ('torso_fixed_column_link ','hand_right_thumb_flex_1_link'), ('torso_fixed_column_link ','hand_right_thumb_virtual_2_link'), ('torso_fixed_column_link ','hand_right_thumb_flex_2_link'), ('torso_fixed_column_link ','hand_right_index_abd_link'), ('torso_fixed_column_link ','hand_right_index_virtual_1_link'), ('torso_fixed_column_link ','hand_right_index_flex_1_link'), ('torso_fixed_column_link ','hand_right_index_virtual_2_link'), ('torso_fixed_column_link ','hand_right_index_flex_2_link'), ('torso_fixed_column_link ','hand_right_index_virtual_3_link'), ('torso_fixed_column_link ','hand_right_index_flex_3_link'), ('torso_fixed_column_link ','hand_right_middle_abd_link'), ('torso_fixed_column_link ','hand_right_middle_virtual_1_link'), ('torso_fixed_column_link ','hand_right_middle_flex_1_link'), ('torso_fixed_column_link ','hand_right_middle_virtual_2_link'), ('torso_fixed_column_link ','hand_right_middle_flex_2_link'), ('torso_fixed_column_link ','hand_right_middle_virtual_3_link'), ('torso_fixed_column_link ','hand_right_middle_flex_3_link'), ('torso_fixed_column_link ','hand_right_ring_abd_link'), ('torso_fixed_column_link ','hand_right_ring_virtual_1_link'), ('torso_fixed_column_link ','hand_right_ring_flex_1_link'), ('torso_fixed_column_link ','hand_right_ring_virtual_2_link'), ('torso_fixed_column_link ','hand_right_ring_flex_2_link'), ('torso_fixed_column_link ','hand_right_ring_virtual_3_link'), ('torso_fixed_column_link ','hand_right_ring_flex_3_link'), ('torso_fixed_column_link ','hand_right_little_abd_link'), ('torso_fixed_column_link ','hand_right_little_virtual_1_link'), ('torso_fixed_column_link ','hand_right_little_flex_1_link'), ('torso_fixed_column_link ','hand_right_little_virtual_2_link'), ('torso_fixed_column_link ','hand_right_little_flex_2_link'), ('torso_fixed_column_link ','hand_right_little_virtual_3_link'), ('torso_fixed_column_link ','hand_right_little_flex_3_link')]
| 16,819 | 302,537 | 0.838708 | 52,589 | 302,742 | 4.034114 | 0.001217 | 0.229168 | 0.330959 | 0.081697 | 0.999236 | 0.999236 | 0.999208 | 0.998209 | 0.994735 | 0.985397 | 0 | 0.023594 | 0.018448 | 302,742 | 17 | 302,538 | 17,808.352941 | 0.690339 | 0.000595 | 0 | 0 | 0 | 0 | 0.839186 | 0.626371 | 0 | 0 | 0 | 0.058824 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 13 |
17ac1cecace772d4aa43b7a2af785acd6fbd6f99 | 133 | py | Python | task1.3.py | ExplosiveGreen/end_project | f20c0a233ea3356c008bb7b422562f3ab89e238d | [
"MIT"
] | null | null | null | task1.3.py | ExplosiveGreen/end_project | f20c0a233ea3356c008bb7b422562f3ab89e238d | [
"MIT"
] | null | null | null | task1.3.py | ExplosiveGreen/end_project | f20c0a233ea3356c008bb7b422562f3ab89e238d | [
"MIT"
] | null | null | null | #!/usr/bin/python3
from scapy.all import *
send(IP(dst='216.58.213.14',ttl=14)/ICMP())
send(IP(dst='216.58.213.14',ttl=13)/ICMP()) | 33.25 | 44 | 0.654135 | 27 | 133 | 3.222222 | 0.62963 | 0.137931 | 0.206897 | 0.275862 | 0.505747 | 0.505747 | 0.505747 | 0.505747 | 0 | 0 | 0 | 0.201613 | 0.067669 | 133 | 4 | 45 | 33.25 | 0.5 | 0.12782 | 0 | 0 | 0 | 0 | 0.230089 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
17ad6b868a86ddc3e5c1b87cc2f6c4267c1181eb | 13,885 | py | Python | test/pytest/test_polynomial.py | leannejdong/NumCpp | 2ecc1312f5f4fd8aeba298f917228c120f98d155 | [
"MIT"
] | null | null | null | test/pytest/test_polynomial.py | leannejdong/NumCpp | 2ecc1312f5f4fd8aeba298f917228c120f98d155 | [
"MIT"
] | null | null | null | test/pytest/test_polynomial.py | leannejdong/NumCpp | 2ecc1312f5f4fd8aeba298f917228c120f98d155 | [
"MIT"
] | 1 | 2020-08-29T14:56:50.000Z | 2020-08-29T14:56:50.000Z | import numpy as np
from numpy.polynomial.polynomial import Polynomial
import scipy.special as sp
import os
import sys
sys.path.append(os.path.abspath(r'../lib'))
import NumCpp # noqa E402
####################################################################################
ORDER_MAX = 5
DECIMALS_ROUND = 7
####################################################################################
def test_seed():
np.random.seed(666)
####################################################################################
def test_poly1D_coefficents_constructor():
numCoefficients = np.random.randint(3, 10, [1, ]).item()
coefficients = np.random.randint(-20, 20, [numCoefficients, ])
coefficientsC = NumCpp.NdArray(1, numCoefficients)
coefficientsC.setArray(coefficients)
polyC = NumCpp.Poly1d(coefficientsC, False)
assert np.array_equal(polyC.coefficients().getNumpyArray().flatten(), coefficients)
####################################################################################
def test_poly1D_roots_constructor():
numRoots = np.random.randint(3, 10, [1, ]).item()
roots = np.random.randint(-20, 20, [numRoots, ])
rootsC = NumCpp.NdArray(1, numRoots)
rootsC.setArray(roots)
poly = np.poly1d(roots, True)
polyC = NumCpp.Poly1d(rootsC, True)
assert np.array_equal(np.fliplr(polyC.coefficients().getNumpyArray()).flatten().astype(np.int), poly.coefficients)
####################################################################################
def test_poly1D_integ_deriv_area_order():
numRoots = np.random.randint(3, 10, [1, ]).item()
roots = np.random.randint(-20, 20, [numRoots, ])
rootsC = NumCpp.NdArray(1, numRoots)
rootsC.setArray(roots)
poly = np.poly1d(roots, True)
polyC = NumCpp.Poly1d(rootsC, True)
bounds = np.random.rand(2) * 100 - 50
bounds = np.sort(bounds)
polyIntegral = poly.integ()
assert np.round(polyC.area(*bounds), 3) == np.round(polyIntegral(bounds[1]) - polyIntegral(bounds[0]), 3)
assert np.array_equal(polyC.deriv().coefficients().getNumpyArray().flatten(), np.flipud(poly.deriv().coefficients))
assert np.array_equal(polyC.integ().coefficients().getNumpyArray().flatten(), np.flipud(poly.integ().coefficients))
assert polyC.order() == roots.size
value = np.random.randint(-20, 20, [1, ]).item()
assert polyC[value] == poly(value)
####################################################################################
def test_poly1D_fit():
polyOrder = np.random.randint(2, 5)
numMeasurements = np.random.randint(50, 100)
xValues = np.random.rand(numMeasurements) * 100 - 50
coefficients = np.random.rand(polyOrder + 1) * 5 - 10
yValues = []
for x in xValues:
y = 0
for order in range(polyOrder + 1):
y += coefficients[order] * x ** order
yValues.append(y + np.random.randn(1).item())
yValues = np.array(yValues)
yValues = yValues.reshape(yValues.size, 1)
cX = NumCpp.NdArray(1, xValues.size)
cY = NumCpp.NdArray(yValues.size, 1)
cX.setArray(xValues)
cY.setArray(yValues)
poly = Polynomial.fit(xValues, yValues.flatten(), polyOrder).convert().coef
polyC = NumCpp.Poly1d.fit(cX, cY, polyOrder).coefficients().getNumpyArray().flatten()
assert np.array_equal(np.round(poly, 5), np.round(polyC, 5))
####################################################################################
def test_poly1D_fit_weighted():
polyOrder = np.random.randint(2, 5)
numMeasurements = np.random.randint(50, 100)
xValues = np.random.rand(numMeasurements) * 100 - 50
coefficients = np.random.rand(polyOrder + 1) * 5 - 10
yValues = []
for x in xValues:
y = 0
for order in range(polyOrder + 1):
y += coefficients[order] * x ** order
yValues.append(y + np.random.randn(1).item())
yValues = np.array(yValues)
yValues = yValues.reshape(yValues.size, 1)
weights = np.random.rand(numMeasurements)
cX = NumCpp.NdArray(1, xValues.size)
cY = NumCpp.NdArray(yValues.size, 1)
cWeights = NumCpp.NdArray(1, xValues.size)
cX.setArray(xValues)
cY.setArray(yValues)
cWeights.setArray(weights)
poly = Polynomial.fit(xValues, yValues.flatten(), polyOrder, w=weights).convert().coef
polyC = NumCpp.Poly1d.fitWeighted(cX, cY, cWeights, polyOrder).coefficients().getNumpyArray().flatten()
assert np.array_equal(np.round(poly, 1), np.round(polyC, 1))
####################################################################################
def test_poly1D_operators():
numRoots = np.random.randint(3, 10, [1, ]).item()
roots = np.random.randint(-20, 20, [numRoots, ])
rootsC = NumCpp.NdArray(1, numRoots)
rootsC.setArray(roots)
poly = np.poly1d(roots, True)
polyC = NumCpp.Poly1d(rootsC, True)
numCoefficients = np.random.randint(3, 10, [1, ]).item()
coefficients = np.random.randint(-20, 20, [numCoefficients, ])
coefficientsC = NumCpp.NdArray(1, numCoefficients)
coefficientsC.setArray(coefficients)
polyC2 = NumCpp.Poly1d(coefficientsC, False)
poly2 = np.poly1d(np.flip(coefficients))
assert np.array_equal(np.fliplr((polyC + polyC2).coefficients().getNumpyArray()).flatten(),
(poly + poly2).coefficients)
assert np.array_equal(np.fliplr((polyC - polyC2).coefficients().getNumpyArray()).flatten(),
(poly - poly2).coefficients)
assert np.array_equal(np.fliplr((polyC * polyC2).coefficients().getNumpyArray()).flatten(),
(poly * poly2).coefficients)
exponent = np.random.randint(0, 5, [1, ]).item()
assert np.array_equal(np.fliplr((polyC2 ** exponent).coefficients().getNumpyArray()).flatten(),
(poly2 ** exponent).coefficients)
polyC.print()
####################################################################################
def test_chebyshev():
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
valuePy = sp.eval_chebyt(order, x)
valueCpp = NumCpp.chebyshev_t_Scaler(order, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
shapeInput = np.random.randint(10, 100, [2, ], dtype=np.uint32)
shape = NumCpp.Shape(*shapeInput)
cArray = NumCpp.NdArray(shape)
x = np.random.rand(*shapeInput)
cArray.setArray(x)
valuePy = sp.eval_chebyt(order, x)
valueCpp = NumCpp.chebyshev_t_Array(order, cArray)
if not np.array_equal(np.round(valuePy, DECIMALS_ROUND), np.round(valueCpp, DECIMALS_ROUND)):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
valuePy = sp.eval_chebyu(order, x)
valueCpp = NumCpp.chebyshev_u_Scaler(order, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
shapeInput = np.random.randint(10, 100, [2, ], dtype=np.uint32)
shape = NumCpp.Shape(*shapeInput)
cArray = NumCpp.NdArray(shape)
x = np.random.rand(*shapeInput)
cArray.setArray(x)
valuePy = sp.eval_chebyu(order, x)
valueCpp = NumCpp.chebyshev_u_Array(order, cArray)
if not np.array_equal(np.round(valuePy, DECIMALS_ROUND), np.round(valueCpp, DECIMALS_ROUND)):
allTrue = False
assert allTrue
####################################################################################
def test_hermite():
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
valuePy = sp.eval_hermite(order, x)
valueCpp = NumCpp.hermite_Scaler(order, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
shapeInput = np.random.randint(10, 100, [2, ], dtype=np.uint32)
shape = NumCpp.Shape(*shapeInput)
cArray = NumCpp.NdArray(shape)
x = np.random.rand(*shapeInput)
cArray.setArray(x)
valuePy = sp.eval_hermite(order, x)
valueCpp = NumCpp.hermite_Array(order, cArray)
if not np.array_equal(np.round(valuePy, DECIMALS_ROUND), np.round(valueCpp, DECIMALS_ROUND)):
allTrue = False
assert allTrue
####################################################################################
def test_laguerre():
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
valuePy = sp.eval_laguerre(order, x)
valueCpp = NumCpp.laguerre_Scaler1(order, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
shapeInput = np.random.randint(10, 100, [2, ], dtype=np.uint32)
shape = NumCpp.Shape(*shapeInput)
cArray = NumCpp.NdArray(shape)
x = np.random.rand(*shapeInput)
cArray.setArray(x)
valuePy = sp.eval_laguerre(order, x)
valueCpp = NumCpp.laguerre_Array1(order, cArray)
if not np.array_equal(np.round(valuePy, DECIMALS_ROUND), np.round(valueCpp, DECIMALS_ROUND)):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
degree = np.random.randint(0, 10, [1, ]).item()
x = np.random.rand(1).item()
valuePy = sp.eval_genlaguerre(degree, order, x)
valueCpp = NumCpp.laguerre_Scaler2(order, degree, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
degree = np.random.randint(0, 10, [1, ]).item()
shapeInput = np.random.randint(10, 100, [2, ], dtype=np.uint32)
shape = NumCpp.Shape(*shapeInput)
cArray = NumCpp.NdArray(shape)
x = np.random.rand(*shapeInput)
cArray.setArray(x)
valuePy = sp.eval_genlaguerre(degree, order, x)
valueCpp = NumCpp.laguerre_Array2(order, degree, cArray)
if not np.array_equal(np.round(valuePy, DECIMALS_ROUND), np.round(valueCpp, DECIMALS_ROUND)):
allTrue = False
assert allTrue
####################################################################################
def test_legendre():
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
valuePy = sp.eval_legendre(order, x)
valueCpp = NumCpp.legendre_p_Scaler1(order, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
shapeInput = np.random.randint(10, 100, [2, ], dtype=np.uint32)
shape = NumCpp.Shape(*shapeInput)
cArray = NumCpp.NdArray(shape)
x = np.random.rand(*shapeInput)
cArray.setArray(x)
valuePy = sp.eval_legendre(order, x)
valueCpp = NumCpp.legendre_p_Array1(order, cArray)
if not np.array_equal(np.round(valuePy, DECIMALS_ROUND), np.round(valueCpp, DECIMALS_ROUND)):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
degree = np.random.randint(order, ORDER_MAX)
valuePy = sp.lpmn(order, degree, x)[0][order, degree]
valueCpp = NumCpp.legendre_p_Scaler2(order, degree, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
x = np.random.rand(1).item()
valuePy = sp.lqn(order, x)[0][order]
valueCpp = NumCpp.legendre_q_Scaler(order, x)
if np.round(valuePy, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
####################################################################################
def test_spherical_harmonic():
allTrue = True
for order in range(ORDER_MAX):
degree = np.random.randint(order, ORDER_MAX)
theta = np.random.rand(1).item() * np.pi * 2
phi = np.random.rand(1).item() * np.pi
valuePy = sp.sph_harm(order, degree, theta, phi)
valueCpp = NumCpp.spherical_harmonic(order, degree, theta, phi)
if (np.round(valuePy.real, DECIMALS_ROUND) != np.round(valueCpp[0], DECIMALS_ROUND) or
np.round(valuePy.imag, DECIMALS_ROUND) != np.round(valueCpp[1], DECIMALS_ROUND)):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
degree = np.random.randint(order, ORDER_MAX)
theta = np.random.rand(1).item() * np.pi * 2
phi = np.random.rand(1).item() * np.pi
valuePy = sp.sph_harm(order, degree, theta, phi)
valueCpp = NumCpp.spherical_harmonic_r(order, degree, theta, phi)
if np.round(valuePy.real, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
allTrue = True
for order in range(ORDER_MAX):
degree = np.random.randint(order, ORDER_MAX)
theta = np.random.rand(1).item() * np.pi * 2
phi = np.random.rand(1).item() * np.pi
valuePy = sp.sph_harm(order, degree, theta, phi)
valueCpp = NumCpp.spherical_harmonic_i(order, degree, theta, phi)
if np.round(valuePy.imag, DECIMALS_ROUND) != np.round(valueCpp, DECIMALS_ROUND):
allTrue = False
assert allTrue
| 38.041096 | 119 | 0.594166 | 1,624 | 13,885 | 4.992611 | 0.086823 | 0.056241 | 0.051801 | 0.03515 | 0.850641 | 0.828318 | 0.805871 | 0.78626 | 0.78367 | 0.75629 | 0 | 0.021021 | 0.20857 | 13,885 | 364 | 120 | 38.145604 | 0.716808 | 0.000648 | 0 | 0.724382 | 0 | 0 | 0.000469 | 0 | 0 | 0 | 0 | 0 | 0.106007 | 1 | 0.042403 | false | 0 | 0.021201 | 0 | 0.063604 | 0.003534 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
17f957c33dc59abf0c7ed37db76efd65c5f7a74b | 4,135 | py | Python | Code/Functions/choiceModels.py | jeroenvanbaar/ReciprocityMotives | 9a6708f723a15e3cc614be9f438be42c6cc1a715 | [
"MIT"
] | 1 | 2021-01-19T23:50:13.000Z | 2021-01-19T23:50:13.000Z | Code/Functions/choiceModels.py | jeroenvanbaar/ReciprocityMotives | 9a6708f723a15e3cc614be9f438be42c6cc1a715 | [
"MIT"
] | null | null | null | Code/Functions/choiceModels.py | jeroenvanbaar/ReciprocityMotives | 9a6708f723a15e3cc614be9f438be42c6cc1a715 | [
"MIT"
] | 1 | 2021-01-19T23:50:39.000Z | 2021-01-19T23:50:39.000Z | import os
import numpy as np
import pandas as pd
def MP_model(inv, mult, baseMult, exp, theta, phi):
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(exp); theta = float(theta); phi = float(phi);
# exp = .5*(10 - inv + inv*baseMult)-(10-inv);
totalAmt = inv*mult
choiceOpt = np.arange(0,totalAmt+1) # Only integers in strategy space (but not further discretized)
own = totalAmt-choiceOpt
other = 10 - inv + choiceOpt
ownShare = own/totalAmt # Should be totalAmt
guilt = np.square(np.maximum((exp-choiceOpt)/(inv*baseMult),0))
inequity = np.square(own/(own+other) - .5)
utility = theta*ownShare - (1-theta)*np.minimum(guilt+phi, inequity-phi)
return choiceOpt[np.where(utility == np.max(utility))[0][0]]
def MP_model_ppSOE(inv, mult, baseMult, exp, theta, phi):
# 'pre-programmed Second-Order Expectations'
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(0.5*baseMult*inv); theta = float(theta); phi = float(phi);
totalAmt = inv*mult
choiceOpt = np.arange(0,totalAmt+1) # Only integers in strategy space (but not further discretized)
own = totalAmt-choiceOpt
other = 10 - inv + choiceOpt
ownShare = own/totalAmt # Should be totalAmt
guilt = np.square(np.maximum((exp-choiceOpt)/(inv*baseMult),0))
inequity = np.square(own/(own+other) - .5)
utility = theta*ownShare - (1-theta)*np.minimum(guilt+phi, inequity-phi)
return choiceOpt[np.where(utility == np.max(utility))[0][0]]
def IA_model(inv, mult, baseMult, exp, theta, phi):
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(exp); theta = float(theta); phi = float(phi);
totalAmt = inv*mult
choiceOpt = np.arange(0,totalAmt+1)
own = totalAmt-choiceOpt
other = 10 - inv + choiceOpt
inequity = np.square(own/(own+other) - .5)
utility = own - theta*inequity
return choiceOpt[np.where(utility == np.max(utility))[0][0]]
def GA_model(inv, mult, baseMult, exp, theta, phi):
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(exp); theta = float(theta); phi = float(phi);
# exp = .5*(10 - inv + inv*baseMult)-(10-inv);
totalAmt = inv*mult
choiceOpt = np.arange(0,totalAmt+1)
guilt = np.square(np.maximum((exp-choiceOpt)/(inv*baseMult),0))
own = totalAmt-choiceOpt
utility = own - theta*guilt
return choiceOpt[np.where(utility == np.max(utility))[0][0]]
def GA_model_ppSOE(inv, mult, baseMult, exp, theta, phi):
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(0.5*baseMult*inv); theta = float(theta); phi = float(phi);
totalAmt = inv*mult
choiceOpt = np.arange(0,totalAmt+1)
guilt = np.square(np.maximum((exp-choiceOpt)/(inv*baseMult),0))
own = totalAmt-choiceOpt
utility = own - theta*guilt
return choiceOpt[np.where(utility == np.max(utility))[0][0]]
def GR_model(inv, mult, baseMult, exp, theta, phi):
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(exp); theta = float(theta); phi = float(phi);
return 0
def hybrid_model(inv,mult,baseMult,exp,theta,phi):
inv = float(inv); mult = float(mult); baseMult = float(baseMult);
exp = float(exp); theta = float(theta); phi = float(phi);
totalAmt = inv*mult
choiceOpt = np.arange(0,totalAmt+1)
own = totalAmt-choiceOpt
ownShare = own/totalAmt
other = 10 - inv + choiceOpt
inequity = np.square(np.maximum(own/(own+other) - .5,0))
guilt = np.square(np.maximum((exp-choiceOpt)/(inv*baseMult),0))
comparison = ((guilt+phi)-(inequity-phi))>=0 # Indexes where inequity is smallest
socPref = np.zeros([1,len(choiceOpt)])[0]
socPref[comparison==True] = inequity[comparison==True]
socPref[comparison==False] = guilt[comparison==False]
exponent = .3
thetaTrans = theta**exponent/((.2**exponent)/.2)
utility = own - (.2-thetaTrans)*3000*socPref
choice = choiceOpt[np.where(utility == np.max(utility))[0][0]]
return choice
| 34.173554 | 103 | 0.648126 | 572 | 4,135 | 4.66958 | 0.125874 | 0.052415 | 0.039311 | 0.047173 | 0.841258 | 0.841258 | 0.841258 | 0.821041 | 0.792587 | 0.778735 | 0 | 0.021002 | 0.193954 | 4,135 | 120 | 104 | 34.458333 | 0.780378 | 0.079565 | 0 | 0.717949 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.089744 | false | 0 | 0.038462 | 0 | 0.217949 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
17fb7a0d7804fb7d4b63e721b0629dee96670549 | 20,155 | py | Python | examples/data/expressions.py | iwob/pysv | 6fdfb93d66cce84cceacabd3806f3f51f0cbbe17 | [
"MIT"
] | 2 | 2017-06-21T04:00:11.000Z | 2018-06-11T17:28:55.000Z | examples/data/expressions.py | iwob/pysv | 6fdfb93d66cce84cceacabd3806f3f51f0cbbe17 | [
"MIT"
] | null | null | null | examples/data/expressions.py | iwob/pysv | 6fdfb93d66cce84cceacabd3806f3f51f0cbbe17 | [
"MIT"
] | 1 | 2018-06-11T17:28:56.000Z | 2018-06-11T17:28:56.000Z | expressions = ['(a+b)/(a+b+c)-b/(b+d)/(a+b+c)*(a+b+c+d)',
'(a+b)/(a+b+c+d)*a/(a+c)-(a+b)/(a+b+c+d)*b/(b+d)',
'(a+b)/(a+b+c+d)-b/(a+b+c+d)/d*(c+d)',
'(a+b)/(a+b+c+d)-b/(b+d)',
'(a+b)/(a+b+c+d)/b*(b+d)-(a+c)/(a+b+c+d)/a*(a+b)',
'(a+b)/(a+b+c+d)/b*(b+d)-1',
'(a+b)/(a+b+c+d)/b*(b+d)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'(a+b)/(a+b+c+d)/b*(b+d)-b/(a+b)/(b+d)*(a+b+c+d)',
'(a+b)/(a+b+c+d)/b*(b+d)-b/(a+b)/d*(c+d)',
'(a+b)/(a+b+c+d)/b*(b+d)-b/(b+d)/a*(a+c)',
'(a+b)/(a+b+c+d)/b*(b+d)-c/(a+c)/(c+d)*(a+b+c+d)',
'(a+b)/(a+b+c+d)/b*(b+d)-c/(a+c)/d*(b+d)',
'(a+b)/(a+b+c+d)/b*(b+d)-c/(c+d)/a*(a+b)',
'(a+b)/(a+b+c+d)/c*(a+c)-(a+b)/(a+b+c+d)/d*(b+d)',
'(a+b)/(a+b+c+d)/c*(a+c)-(a+b)/(c+d)',
'(a+b)/(a+b+c+d)/c*(a+c)-b/(b+d)/(c+d)*(a+b+c+d)',
'(a+b)/(a+b+c+d)/c*(a+c)-b/(b+d)/c*(a+c)',
'(a+b)/(a+b+c+d)/c*(a+c)-b/d',
'(a+b)/(a+b+c+d)/c*(c+d)-1/(a+c)*(a+b)',
'(a+b)/(a+b+c+d)/c*(c+d)-b/(b+d)/(a+c)*(a+b+c+d)',
'(a+b)/(a+b+c+d)/c*(c+d)-b/(b+d)/a*(a+b)',
'(a+b)/(a+b+c+d)/c*(c+d)-b/(b+d)/c*(c+d)',
'(a+b)/(a+b+c+d)/d*(b+d)-b/d',
'(a+b)/(a+b+c+d)/d*(c+d)-b/(b+d)/d*(c+d)',
'(a+b)/(a+b+d)-b/(b+d)/(a+b+d)*(a+b+c+d)',
'(a+b)/(a+c+d)-b/(b+d)/(a+c+d)*(a+b+c+d)',
'(a+b)/(b+c+d)-b/(b+d)/(b+c+d)*(a+b+c+d)',
'(a+b)/(c+d)-(a+b)/(a+b+c+d)/d*(b+d)',
'(a+b)/(c+d)-b/(b+d)/(c+d)*(a+b+c+d)',
'(a+b)/(c+d)-b/d',
'(a+b)/a-b/(b+d)/a*(a+b+c+d)',
'(a+b)/b-(c+d)/d',
'(a+b)/b-1/(b+d)*(a+b+c+d)',
'(a+b)/b-c/(a+c)/d*(a+b+c+d)',
'(a+b)/c-b/(b+d)/c*(a+b+c+d)',
'(a+b)/d-b/(b+d)/d*(a+b+c+d)',
'(a+b+c)/(a+b)-(a+b+c)/(a+b+c+d)/a*(a+c)',
'(a+b+c)/(a+b+c+d)*a/(a+b)-(a+b+c)/(a+b+c+d)*c/(c+d)',
'(a+b+c)/(a+b+c+d)*d/(c+d)-(a+b+c)/(a+b+c+d)*b/(a+b)',
'(a+b+c)/(a+b+c+d)/b*(a+b)-(a+b+c)/(a+b+c+d)/d*(c+d)',
'(a+b+c)/(a+b+c+d)/b*(a+b)-(a+b+c)/(b+d)',
'(a+b+c)/(a+b+c+d)/b*(b+d)-(a+b+c)/(a+b)',
'(a+b+c)/(a+b+c+d)/b*(b+d)-(a+b+c)/(a+b+c+d)/a*(a+c)',
'(a+b+c)/(a+b+c+d)/c*(a+c)-(a+b+c)/(a+b+c+d)/d*(b+d)',
'(a+b+c)/(a+b+c+d)/c*(a+c)-(a+b+c)/(c+d)',
'(a+b+c)/(a+b+c+d)/c*(c+d)-(a+b+c)/(a+b+c+d)/a*(a+b)',
'(a+b+c)/(a+b+c+d)/c*(c+d)-(a+b+c)/(a+c)',
'(a+b+c)/(a+c)-(a+b+c)/(a+b+c+d)/a*(a+b)',
'(a+b+c)/(b+d)-(a+b+c)/(a+b+c+d)/d*(c+d)',
'(a+b+c)/(c+d)-(a+b+c)/(a+b+c+d)/d*(b+d)',
'(a+b+d)/(a+b)-(a+b+d)/(a+b+c+d)/a*(a+c)',
'(a+b+d)/(a+b+c+d)*a/(a+b)-(a+b+d)/(a+b+c+d)*c/(c+d)',
'(a+b+d)/(a+b+c+d)*a/(a+c)-(a+b+d)/(a+b+c+d)*b/(b+d)',
'(a+b+d)/(a+b+c+d)*d/(c+d)-(a+b+d)/(a+b+c+d)*b/(a+b)',
'(a+b+d)/(a+b+c+d)/b*(a+b)-(a+b+d)/(a+b+c+d)/d*(c+d)',
'(a+b+d)/(a+b+c+d)/b*(a+b)-(a+b+d)/(b+d)',
'(a+b+d)/(a+b+c+d)/b*(b+d)-(a+b+d)/(a+b)',
'(a+b+d)/(a+b+c+d)/b*(b+d)-(a+b+d)/(a+b+c+d)/a*(a+c)',
'(a+b+d)/(a+b+c+d)/c*(a+c)-(a+b+d)/(a+b+c+d)/d*(b+d)',
'(a+b+d)/(a+b+c+d)/c*(a+c)-(a+b+d)/(c+d)',
'(a+b+d)/(a+b+c+d)/c*(c+d)-(a+b+d)/(a+b+c+d)/a*(a+b)',
'(a+b+d)/(a+b+c+d)/c*(c+d)-(a+b+d)/(a+c)',
'(a+b+d)/(a+c)-(a+b+d)/(a+b+c+d)/a*(a+b)',
'(a+b+d)/(b+d)-(a+b+d)/(a+b+c+d)/d*(c+d)',
'(a+b+d)/(c+d)-(a+b+d)/(a+b+c+d)/d*(b+d)',
'(a+c)/(a+b)-c/(c+d)/(a+b)*(a+b+c+d)',
'(a+c)/(a+b)-c/(c+d)/a*(a+c)',
'(a+c)/(a+b+c)-c/(c+d)/(a+b+c)*(a+b+c+d)',
'(a+c)/(a+b+c+d)*a/(a+b)-(a+c)/(a+b+c+d)*c/(c+d)',
'(a+c)/(a+b+c+d)*d/(b+d)-c/(a+b+c+d)',
'(a+c)/(a+b+c+d)*d/(c+d)-(a+c)/(a+b+c+d)*b/(a+b)',
'(a+c)/(a+b+c+d)*d/(c+d)-(b+d)/(a+b+c+d)*c/(c+d)',
'(a+c)/(a+b+c+d)*d/(c+d)-c/(c+d)*b/(a+b)',
'(a+c)/(a+b+c+d)-c/(a+b+c+d)/d*(b+d)',
'(a+c)/(a+b+c+d)-c/(c+d)',
'(a+c)/(a+b+c+d)/a*(a+b)-b/(b+d)/a*(a+c)',
'(a+c)/(a+b+c+d)/a*(a+b)-c/(c+d)/a*(a+b)',
'(a+c)/(a+b+c+d)/b*(a+b)-(a+c)/(a+b+c+d)/d*(c+d)',
'(a+c)/(a+b+c+d)/b*(a+b)-(a+c)/(b+d)',
'(a+c)/(a+b+c+d)/b*(a+b)-c/(c+d)/(b+d)*(a+b+c+d)',
'(a+c)/(a+b+c+d)/b*(a+b)-c/(c+d)/b*(a+b)',
'(a+c)/(a+b+c+d)/b*(a+b)-c/d',
'(a+c)/(a+b+c+d)/b*(b+d)-(a+c)/(a+b)',
'(a+c)/(a+b+c+d)/b*(b+d)-c/(c+d)/(a+b)*(a+b+c+d)',
'(a+c)/(a+b+c+d)/b*(b+d)-c/(c+d)/a*(a+c)',
'(a+c)/(a+b+c+d)/b*(b+d)-c/(c+d)/b*(b+d)',
'(a+c)/(a+b+c+d)/c*(c+d)-(a+c)/(a+b+c+d)/a*(a+b)',
'(a+c)/(a+b+c+d)/c*(c+d)-1',
'(a+c)/(a+b+c+d)/c*(c+d)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'(a+c)/(a+b+c+d)/c*(c+d)-b/(a+b)/(b+d)*(a+b+c+d)',
'(a+c)/(a+b+c+d)/c*(c+d)-b/(a+b)/d*(c+d)',
'(a+c)/(a+b+c+d)/c*(c+d)-b/(b+d)/a*(a+c)',
'(a+c)/(a+b+c+d)/c*(c+d)-c/(a+c)/(c+d)*(a+b+c+d)',
'(a+c)/(a+b+c+d)/c*(c+d)-c/(a+c)/d*(b+d)',
'(a+c)/(a+b+c+d)/c*(c+d)-c/(c+d)/a*(a+b)',
'(a+c)/(a+b+c+d)/d*(b+d)-c/(c+d)/d*(b+d)',
'(a+c)/(a+b+c+d)/d*(c+d)-c/d',
'(a+c)/(a+b+d)-c/(c+d)/(a+b+d)*(a+b+c+d)',
'(a+c)/(a+c+d)-c/(c+d)/(a+c+d)*(a+b+c+d)',
'(a+c)/(b+c+d)-c/(c+d)/(b+c+d)*(a+b+c+d)',
'(a+c)/(b+d)-(a+c)/(a+b+c+d)/d*(c+d)',
'(a+c)/(b+d)-c/(c+d)/(b+d)*(a+b+c+d)',
'(a+c)/(b+d)-c/d',
'(a+c)/a-c/(c+d)/a*(a+b+c+d)',
'(a+c)/b-c/(c+d)/b*(a+b+c+d)',
'(a+c)/c-(b+d)/d',
'(a+c)/c-1/(c+d)*(a+b+c+d)',
'(a+c)/c-b/(a+b)/d*(a+b+c+d)',
'(a+c)/d-c/(c+d)/d*(a+b+c+d)',
'(a+c+d)/(a+b)-(a+c+d)/(a+b+c+d)/a*(a+c)',
'(a+c+d)/(a+b+c+d)*a/(a+b)-(a+c+d)/(a+b+c+d)*c/(c+d)',
'(a+c+d)/(a+b+c+d)*d/(b+d)-(a+c+d)/(a+b+c+d)*c/(a+c)',
'(a+c+d)/(a+b+c+d)*d/(c+d)-(a+c+d)/(a+b+c+d)*b/(a+b)',
'(a+c+d)/(a+b+c+d)/b*(a+b)-(a+c+d)/(a+b+c+d)/d*(c+d)',
'(a+c+d)/(a+b+c+d)/b*(a+b)-(a+c+d)/(b+d)',
'(a+c+d)/(a+b+c+d)/b*(b+d)-(a+c+d)/(a+b)',
'(a+c+d)/(a+b+c+d)/b*(b+d)-(a+c+d)/(a+b+c+d)/a*(a+c)',
'(a+c+d)/(a+b+c+d)/c*(a+c)-(a+c+d)/(a+b+c+d)/d*(b+d)',
'(a+c+d)/(a+b+c+d)/c*(a+c)-(a+c+d)/(c+d)',
'(a+c+d)/(a+b+c+d)/c*(c+d)-(a+c+d)/(a+b+c+d)/a*(a+b)',
'(a+c+d)/(a+b+c+d)/c*(c+d)-(a+c+d)/(a+c)',
'(a+c+d)/(a+c)-(a+c+d)/(a+b+c+d)/a*(a+b)',
'(a+c+d)/(b+d)-(a+c+d)/(a+b+c+d)/d*(c+d)',
'(a+c+d)/(c+d)-(a+c+d)/(a+b+c+d)/d*(b+d)',
'(b+c+d)/(a+b)-(b+c+d)/(a+b+c+d)/a*(a+c)',
'(b+c+d)/(a+b+c+d)*a/(a+b)-(b+c+d)/(a+b+c+d)*c/(c+d)',
'(b+c+d)/(a+b+c+d)*d/(b+d)-(b+c+d)/(a+b+c+d)*c/(a+c)',
'(b+c+d)/(a+b+c+d)*d/(c+d)-(b+c+d)/(a+b+c+d)*b/(a+b)',
'(b+c+d)/(a+b+c+d)/b*(a+b)-(b+c+d)/(a+b+c+d)/d*(c+d)',
'(b+c+d)/(a+b+c+d)/b*(a+b)-(b+c+d)/(b+d)',
'(b+c+d)/(a+b+c+d)/b*(b+d)-(b+c+d)/(a+b)',
'(b+c+d)/(a+b+c+d)/b*(b+d)-(b+c+d)/(a+b+c+d)/a*(a+c)',
'(b+c+d)/(a+b+c+d)/c*(a+c)-(b+c+d)/(a+b+c+d)/d*(b+d)',
'(b+c+d)/(a+b+c+d)/c*(a+c)-(b+c+d)/(c+d)',
'(b+c+d)/(a+b+c+d)/c*(c+d)-(b+c+d)/(a+b+c+d)/a*(a+b)',
'(b+c+d)/(a+b+c+d)/c*(c+d)-(b+c+d)/(a+c)',
'(b+c+d)/(a+c)-(b+c+d)/(a+b+c+d)/a*(a+b)',
'(b+c+d)/(b+d)-(b+c+d)/(a+b+c+d)/d*(c+d)',
'(b+c+d)/(c+d)-(b+c+d)/(a+b+c+d)/d*(b+d)',
'(b+d)/(a+b+c)-b/(a+b)/(a+b+c)*(a+b+c+d)',
'(b+d)/(a+b+c+d)*a/(a+b)-(a+c)/(a+b+c+d)*b/(a+b)',
'(b+d)/(a+b+c+d)*a/(a+b)-(b+d)/(a+b+c+d)*c/(c+d)',
'(b+d)/(a+b+c+d)*a/(a+b)-c/(c+d)*b/(a+b)',
'(b+d)/(a+b+c+d)*d/(c+d)-(b+d)/(a+b+c+d)*b/(a+b)',
'(b+d)/(a+b+c+d)-b/(a+b)',
'(b+d)/(a+b+c+d)-b/(a+b+c+d)/a*(a+c)',
'(b+d)/(a+b+c+d)/a*(a+b)-b/a',
'(b+d)/(a+b+c+d)/a*(a+c)-b/(a+b)/a*(a+c)',
'(b+d)/(a+b+c+d)/c*(a+c)-1/(c+d)*(b+d)',
'(b+d)/(a+b+c+d)/c*(a+c)-b/(a+b)/(c+d)*(a+b+c+d)',
'(b+d)/(a+b+c+d)/c*(a+c)-b/(a+b)/c*(a+c)',
'(b+d)/(a+b+c+d)/c*(a+c)-b/(a+b)/d*(b+d)',
'(b+d)/(a+b+c+d)/c*(c+d)-(b+d)/(a+b+c+d)/a*(a+b)',
'(b+d)/(a+b+c+d)/c*(c+d)-(b+d)/(a+c)',
'(b+d)/(a+b+c+d)/c*(c+d)-b/(a+b)/(a+c)*(a+b+c+d)',
'(b+d)/(a+b+c+d)/c*(c+d)-b/(a+b)/c*(c+d)',
'(b+d)/(a+b+c+d)/c*(c+d)-b/a',
'(b+d)/(a+b+d)-b/(a+b)/(a+b+d)*(a+b+c+d)',
'(b+d)/(a+c)-(b+d)/(a+b+c+d)/a*(a+b)',
'(b+d)/(a+c)-b/(a+b)/(a+c)*(a+b+c+d)',
'(b+d)/(a+c)-b/a',
'(b+d)/(a+c+d)-b/(a+b)/(a+c+d)*(a+b+c+d)',
'(b+d)/(b+c+d)-b/(a+b)/(b+c+d)*(a+b+c+d)',
'(b+d)/a-b/(a+b)/a*(a+b+c+d)',
'(b+d)/b-(a+c)/a',
'(b+d)/b-1/(a+b)*(a+b+c+d)',
'(b+d)/b-c/(c+d)/a*(a+b+c+d)',
'(b+d)/c-b/(a+b)/c*(a+b+c+d)',
'(b+d)/d-b/(a+b)/d*(a+b+c+d)',
'(c+d)/(a+b)-(c+d)/(a+b+c+d)/a*(a+c)',
'(c+d)/(a+b)-c/(a+c)/(a+b)*(a+b+c+d)',
'(c+d)/(a+b)-c/a',
'(c+d)/(a+b+c)-c/(a+c)/(a+b+c)*(a+b+c+d)',
'(c+d)/(a+b+c+d)*a/(a+b)-c/(a+b+c+d)',
'(c+d)/(a+b+c+d)*a/(a+c)-(a+b)/(a+b+c+d)*c/(a+c)',
'(c+d)/(a+b+c+d)*a/(a+c)-(c+d)/(a+b+c+d)*b/(b+d)',
'(c+d)/(a+b+c+d)*a/(a+c)-b/(b+d)*c/(a+c)',
'(c+d)/(a+b+c+d)-c/(a+b+c+d)/a*(a+b)',
'(c+d)/(a+b+c+d)-c/(a+c)',
'(c+d)/(a+b+c+d)/a*(a+b)-c/(a+c)/a*(a+b)',
'(c+d)/(a+b+c+d)/a*(a+c)-c/a',
'(c+d)/(a+b+c+d)/b*(a+b)-1/(b+d)*(c+d)',
'(c+d)/(a+b+c+d)/b*(a+b)-c/(a+c)/(b+d)*(a+b+c+d)',
'(c+d)/(a+b+c+d)/b*(a+b)-c/(a+c)/b*(a+b)',
'(c+d)/(a+b+c+d)/b*(a+b)-c/(a+c)/d*(c+d)',
'(c+d)/(a+b+c+d)/b*(b+d)-(c+d)/(a+b)',
'(c+d)/(a+b+c+d)/b*(b+d)-(c+d)/(a+b+c+d)/a*(a+c)',
'(c+d)/(a+b+c+d)/b*(b+d)-c/(a+c)/(a+b)*(a+b+c+d)',
'(c+d)/(a+b+c+d)/b*(b+d)-c/(a+c)/b*(b+d)',
'(c+d)/(a+b+c+d)/b*(b+d)-c/a',
'(c+d)/(a+b+d)-c/(a+c)/(a+b+d)*(a+b+c+d)',
'(c+d)/(a+c+d)-c/(a+c)/(a+c+d)*(a+b+c+d)',
'(c+d)/(b+c+d)-c/(a+c)/(b+c+d)*(a+b+c+d)',
'(c+d)/a-c/(a+c)/a*(a+b+c+d)',
'(c+d)/b-c/(a+c)/b*(a+b+c+d)',
'(c+d)/c-(a+b)/a',
'(c+d)/c-1/(a+c)*(a+b+c+d)',
'(c+d)/c-b/(b+d)/a*(a+b+c+d)',
'(c+d)/d-c/(a+c)/d*(a+b+c+d)',
'1-(a+c)/(a+b+c+d)/a*(a+b)',
'1-1/(a+b+c+d)*(b+d)/d*(c+d)',
'1-b/(a+b)/(b+d)*(a+b+c+d)',
'1-b/(a+b)/d*(c+d)',
'1-b/(b+d)/a*(a+c)',
'1-c/(a+c)/(c+d)*(a+b+c+d)',
'1-c/(a+c)/d*(b+d)',
'1-c/(c+d)/a*(a+b)',
'1/(a+b)*(a+b+c+d)-(a+c)/a',
'1/(a+b)*(a+b+c+d)-c/(c+d)/a*(a+b+c+d)',
'1/(a+b)*(b+d)-(b+d)/(a+b+c+d)/a*(a+c)',
'1/(a+b)*(b+d)-b/(a+b)/a*(a+c)',
'1/(a+b+c+d)*(b+d)/d*(c+d)-b/(a+b)/d*(c+d)',
'1/(a+b+c+d)*(b+d)/d*(c+d)-c/(a+c)/d*(b+d)',
'1/(a+c)*(a+b)-b/(b+d)/(a+c)*(a+b+c+d)',
'1/(a+c)*(a+b)-b/(b+d)/a*(a+b)',
'1/(a+c)*(a+b+c+d)-(a+b)/a',
'1/(a+c)*(a+b+c+d)-b/(b+d)/a*(a+b+c+d)',
'1/(a+c)*(c+d)-(c+d)/(a+b+c+d)/a*(a+b)',
'1/(a+c)*(c+d)-c/(a+c)/a*(a+b)',
'1/(b+d)*(a+b)-(a+b)/(a+b+c+d)/d*(c+d)',
'1/(b+d)*(a+b)-b/(b+d)/d*(c+d)',
'1/(b+d)*(a+b+c+d)-(c+d)/d',
'1/(b+d)*(a+b+c+d)-c/(a+c)/d*(a+b+c+d)',
'1/(b+d)*(c+d)-c/(a+c)/(b+d)*(a+b+c+d)',
'1/(b+d)*(c+d)-c/(a+c)/d*(c+d)',
'1/(c+d)*(a+b+c+d)-(b+d)/d',
'1/(c+d)*(a+b+c+d)-b/(a+b)/d*(a+b+c+d)',
'1/(c+d)*(a+c)-(a+c)/(a+b+c+d)/d*(b+d)',
'1/(c+d)*(a+c)-c/(c+d)/d*(b+d)',
'1/(c+d)*(b+d)-b/(a+b)/(c+d)*(a+b+c+d)',
'1/(c+d)*(b+d)-b/(a+b)/d*(b+d)',
'a/(a+b)*d/(a+b+c+d)-b/(a+b)*c/(a+b+c+d)',
'a/(a+b)*d/(c+d)-(a+c)/(a+b+c+d)*b/(a+b)',
'a/(a+b)*d/(c+d)-(b+d)/(a+b+c+d)*c/(c+d)',
'a/(a+b)*d/(c+d)-c/(c+d)*b/(a+b)',
'a/(a+b)-(a+c)/(a+b+c+d)',
'a/(a+b)-c/(a+b+c+d)/d*(b+d)',
'a/(a+b)-c/(c+d)',
'a/(a+b)/(a+b+c)*(a+b+c+d)-(a+c)/(a+b+c)',
'a/(a+b)/(a+b+c)*(a+b+c+d)-c/(c+d)/(a+b+c)*(a+b+c+d)',
'a/(a+b)/(a+b+d)*(a+b+c+d)-(a+c)/(a+b+d)',
'a/(a+b)/(a+b+d)*(a+b+c+d)-c/(c+d)/(a+b+d)*(a+b+c+d)',
'a/(a+b)/(a+c+d)*(a+b+c+d)-(a+c)/(a+c+d)',
'a/(a+b)/(a+c+d)*(a+b+c+d)-c/(c+d)/(a+c+d)*(a+b+c+d)',
'a/(a+b)/(b+c+d)*(a+b+c+d)-(a+c)/(b+c+d)',
'a/(a+b)/(b+c+d)*(a+b+c+d)-c/(c+d)/(b+c+d)*(a+b+c+d)',
'a/(a+b)/(b+d)*(a+b+c+d)-(a+c)/(a+b+c+d)/d*(c+d)',
'a/(a+b)/(b+d)*(a+b+c+d)-(a+c)/(b+d)',
'a/(a+b)/(b+d)*(a+b+c+d)-c/(c+d)/(b+d)*(a+b+c+d)',
'a/(a+b)/(b+d)*(a+b+c+d)-c/d',
'a/(a+b)/(c+d)*(a+b+c+d)-(a+c)/(a+b+c+d)/d*(b+d)',
'a/(a+b)/(c+d)*(a+b+c+d)-1/(c+d)*(a+c)',
'a/(a+b)/(c+d)*(a+b+c+d)-c/(c+d)/d*(b+d)',
'a/(a+b)/b*(a+b+c+d)-(a+c)/b',
'a/(a+b)/b*(a+b+c+d)-c/(c+d)/b*(a+b+c+d)',
'a/(a+b)/b*(b+d)-(a+c)/(a+b)',
'a/(a+b)/b*(b+d)-(a+c)/(a+b+c+d)/b*(b+d)',
'a/(a+b)/b*(b+d)-c/(c+d)/(a+b)*(a+b+c+d)',
'a/(a+b)/b*(b+d)-c/(c+d)/a*(a+c)',
'a/(a+b)/b*(b+d)-c/(c+d)/b*(b+d)',
'a/(a+b)/c*(a+b+c+d)-(a+c)/c',
'a/(a+b)/c*(a+b+c+d)-(b+d)/d',
'a/(a+b)/c*(a+b+c+d)-1/(c+d)*(a+b+c+d)',
'a/(a+b)/c*(a+b+c+d)-b/(a+b)/d*(a+b+c+d)',
'a/(a+b)/c*(a+c)-(a+c)/(a+b+c+d)/d*(b+d)',
'a/(a+b)/c*(a+c)-1/(c+d)*(a+c)',
'a/(a+b)/c*(a+c)-c/(c+d)/d*(b+d)',
'a/(a+b)/c*(c+d)-(a+c)/(a+b+c+d)/a*(a+b)',
'a/(a+b)/c*(c+d)-(a+c)/(a+b+c+d)/c*(c+d)',
'a/(a+b)/c*(c+d)-1',
'a/(a+b)/c*(c+d)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'a/(a+b)/c*(c+d)-b/(a+b)/(b+d)*(a+b+c+d)',
'a/(a+b)/c*(c+d)-b/(a+b)/d*(c+d)',
'a/(a+b)/c*(c+d)-b/(b+d)/a*(a+c)',
'a/(a+b)/c*(c+d)-c/(a+c)/(c+d)*(a+b+c+d)',
'a/(a+b)/c*(c+d)-c/(a+c)/d*(b+d)',
'a/(a+b)/c*(c+d)-c/(c+d)/a*(a+b)',
'a/(a+b)/d*(a+b+c+d)-(a+c)/d',
'a/(a+b)/d*(a+b+c+d)-c/(c+d)/d*(a+b+c+d)',
'a/(a+b)/d*(b+d)-(a+c)/(a+b+c+d)/d*(b+d)',
'a/(a+b)/d*(b+d)-c/(c+d)/d*(b+d)',
'a/(a+b)/d*(c+d)-(a+c)/(a+b+c+d)/d*(c+d)',
'a/(a+b)/d*(c+d)-c/d',
'a/(a+b+c+d)*d/(c+d)-b/(a+b+c+d)*c/(c+d)',
'a/(a+b+c+d)-(a+b)/(a+b+c+d)*c/(c+d)',
'a/(a+b+c+d)-(a+c)/(a+b+c+d)*b/(b+d)',
'a/(a+b+c+d)-b/(b+d)*c/(c+d)',
'a/(a+b+c+d)/b*(b+d)-(a+c)/(a+b+c+d)',
'a/(a+b+c+d)/b*(b+d)-c/(a+b+c+d)/d*(b+d)',
'a/(a+b+c+d)/b*(b+d)-c/(c+d)',
'a/(a+b+c+d)/c*(c+d)-(a+b)/(a+b+c+d)',
'a/(a+b+c+d)/c*(c+d)-b/(a+b+c+d)/d*(c+d)',
'a/(a+b+c+d)/c*(c+d)-b/(b+d)',
'a/(a+c)*(a+b+c)/(a+b+c+d)-(a+b+c)/(a+b+c+d)*b/(b+d)',
'a/(a+c)*(a+c+d)/(a+b+c+d)-(a+c+d)/(a+b+c+d)*b/(b+d)',
'a/(a+c)*(b+c+d)/(a+b+c+d)-(b+c+d)/(a+b+c+d)*b/(b+d)',
'a/(a+c)*(b+d)/(a+b+c+d)-b/(a+b+c+d)',
'a/(a+c)*d/(a+b+c+d)-c/(a+c)*b/(a+b+c+d)',
'a/(a+c)*d/(b+d)-(a+b)/(a+b+c+d)*c/(a+c)',
'a/(a+c)*d/(b+d)-(c+d)/(a+b+c+d)*b/(b+d)',
'a/(a+c)*d/(b+d)-b/(b+d)*c/(a+c)',
'a/(a+c)-(a+b)/(a+b+c+d)',
'a/(a+c)-b/(a+b+c+d)/d*(c+d)',
'a/(a+c)-b/(b+d)',
'a/(a+c)/(a+b)*(a+b+c+d)-(a+c)/(a+b+c+d)/a*(a+b)',
'a/(a+c)/(a+b)*(a+b+c+d)-1',
'a/(a+c)/(a+b)*(a+b+c+d)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'a/(a+c)/(a+b)*(a+b+c+d)-b/(a+b)/(b+d)*(a+b+c+d)',
'a/(a+c)/(a+b)*(a+b+c+d)-b/(a+b)/d*(c+d)',
'a/(a+c)/(a+b)*(a+b+c+d)-b/(b+d)/a*(a+c)',
'a/(a+c)/(a+b)*(a+b+c+d)-c/(a+c)/(c+d)*(a+b+c+d)',
'a/(a+c)/(a+b)*(a+b+c+d)-c/(a+c)/d*(b+d)',
'a/(a+c)/(a+b)*(a+b+c+d)-c/(c+d)/a*(a+b)',
'a/(a+c)/(a+b+c)*(a+b+c+d)-(a+b)/(a+b+c)',
'a/(a+c)/(a+b+c)*(a+b+c+d)-b/(b+d)/(a+b+c)*(a+b+c+d)',
'a/(a+c)/(a+b+d)*(a+b+c+d)-(a+b)/(a+b+d)',
'a/(a+c)/(a+b+d)*(a+b+c+d)-b/(b+d)/(a+b+d)*(a+b+c+d)',
'a/(a+c)/(a+c+d)*(a+b+c+d)-(a+b)/(a+c+d)',
'a/(a+c)/(a+c+d)*(a+b+c+d)-b/(b+d)/(a+c+d)*(a+b+c+d)',
'a/(a+c)/(b+c+d)*(a+b+c+d)-(a+b)/(b+c+d)',
'a/(a+c)/(b+c+d)*(a+b+c+d)-b/(b+d)/(b+c+d)*(a+b+c+d)',
'a/(a+c)/(b+d)*(a+b+c+d)-(a+b)/(a+b+c+d)/d*(c+d)',
'a/(a+c)/(b+d)*(a+b+c+d)-1/(b+d)*(a+b)',
'a/(a+c)/(b+d)*(a+b+c+d)-b/(b+d)/d*(c+d)',
'a/(a+c)/(c+d)*(a+b+c+d)-(a+b)/(a+b+c+d)/d*(b+d)',
'a/(a+c)/(c+d)*(a+b+c+d)-(a+b)/(c+d)',
'a/(a+c)/(c+d)*(a+b+c+d)-b/(b+d)/(c+d)*(a+b+c+d)',
'a/(a+c)/(c+d)*(a+b+c+d)-b/d',
'a/(a+c)/b*(a+b)-(a+b)/(a+b+c+d)/d*(c+d)',
'a/(a+c)/b*(a+b)-1/(b+d)*(a+b)',
'a/(a+c)/b*(a+b)-b/(b+d)/d*(c+d)',
'a/(a+c)/b*(a+b+c+d)-(a+b)/b',
'a/(a+c)/b*(a+b+c+d)-(c+d)/d',
'a/(a+c)/b*(a+b+c+d)-1/(b+d)*(a+b+c+d)',
'a/(a+c)/b*(a+b+c+d)-c/(a+c)/d*(a+b+c+d)',
'a/(a+c)/b*(b+d)-(a+b)/(a+b+c+d)/b*(b+d)',
'a/(a+c)/b*(b+d)-(a+c)/(a+b+c+d)/a*(a+b)',
'a/(a+c)/b*(b+d)-1',
'a/(a+c)/b*(b+d)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'a/(a+c)/b*(b+d)-b/(a+b)/(b+d)*(a+b+c+d)',
'a/(a+c)/b*(b+d)-b/(a+b)/d*(c+d)',
'a/(a+c)/b*(b+d)-b/(b+d)/a*(a+c)',
'a/(a+c)/b*(b+d)-c/(a+c)/(c+d)*(a+b+c+d)',
'a/(a+c)/b*(b+d)-c/(a+c)/d*(b+d)',
'a/(a+c)/b*(b+d)-c/(c+d)/a*(a+b)',
'a/(a+c)/c*(a+b+c+d)-(a+b)/c',
'a/(a+c)/c*(a+b+c+d)-b/(b+d)/c*(a+b+c+d)',
'a/(a+c)/c*(c+d)-(a+b)/(a+b+c+d)/c*(c+d)',
'a/(a+c)/c*(c+d)-1/(a+c)*(a+b)',
'a/(a+c)/c*(c+d)-b/(b+d)/(a+c)*(a+b+c+d)',
'a/(a+c)/c*(c+d)-b/(b+d)/a*(a+b)',
'a/(a+c)/c*(c+d)-b/(b+d)/c*(c+d)',
'a/(a+c)/d*(a+b+c+d)-(a+b)/d',
'a/(a+c)/d*(a+b+c+d)-b/(b+d)/d*(a+b+c+d)',
'a/(a+c)/d*(b+d)-(a+b)/(a+b+c+d)/d*(b+d)',
'a/(a+c)/d*(b+d)-b/d',
'a/(a+c)/d*(c+d)-(a+b)/(a+b+c+d)/d*(c+d)',
'a/(a+c)/d*(c+d)-b/(b+d)/d*(c+d)',
'a/b-(a+c)/(a+b+c+d)/b*(a+b)',
'a/b-(a+c)/(a+b+c+d)/d*(c+d)',
'a/b-(a+c)/(b+d)',
'a/b-c/(c+d)/(b+d)*(a+b+c+d)',
'a/b-c/(c+d)/b*(a+b)',
'a/b-c/d',
'a/c-(a+b)/(a+b+c+d)/c*(a+c)',
'a/c-(a+b)/(a+b+c+d)/d*(b+d)',
'a/c-(a+b)/(c+d)',
'a/c-b/(b+d)/(c+d)*(a+b+c+d)',
'a/c-b/(b+d)/c*(a+c)',
'a/c-b/d',
'd/(a+b+c+d)-(b+d)/(a+b+c+d)*c/(a+c)',
'd/(a+b+c+d)-(c+d)/(a+b+c+d)*b/(a+b)',
'd/(a+b+c+d)-b/(a+b)*c/(a+c)',
'd/(a+b+c+d)/b*(a+b)-(c+d)/(a+b+c+d)',
'd/(a+b+c+d)/b*(a+b)-c/(a+b+c+d)/a*(a+b)',
'd/(a+b+c+d)/b*(a+b)-c/(a+c)',
'd/(a+b+c+d)/c*(a+c)-(b+d)/(a+b+c+d)',
'd/(a+b+c+d)/c*(a+c)-b/(a+b)',
'd/(a+b+c+d)/c*(a+c)-b/(a+b+c+d)/a*(a+c)',
'd/(b+d)*(a+b)/(a+b+c+d)-(a+b)/(a+b+c+d)*c/(a+c)',
'd/(b+d)*(a+b)/(a+b+c+d)-(c+d)/(a+b+c+d)*b/(b+d)',
'd/(b+d)*(a+b)/(a+b+c+d)-b/(b+d)*c/(a+c)',
'd/(b+d)*(a+b+c)/(a+b+c+d)-(a+b+c)/(a+b+c+d)*c/(a+c)',
'd/(b+d)*(a+b+d)/(a+b+c+d)-(a+b+d)/(a+b+c+d)*c/(a+c)',
'd/(b+d)*(c+d)/(a+b+c+d)-(c+d)/(a+b+c+d)*c/(a+c)',
'd/(b+d)*a/(a+b)-c/(a+b+c+d)',
'd/(b+d)*a/(a+b+c+d)-b/(b+d)*c/(a+b+c+d)',
'd/(b+d)-(c+d)/(a+b+c+d)',
'd/(b+d)-c/(a+b+c+d)/a*(a+b)',
'd/(b+d)-c/(a+c)',
'd/(b+d)/(a+b)*(a+b+c+d)-(c+d)/(a+b)',
'd/(b+d)/(a+b)*(a+b+c+d)-(c+d)/(a+b+c+d)/a*(a+c)',
'd/(b+d)/(a+b)*(a+b+c+d)-c/(a+c)/(a+b)*(a+b+c+d)',
'd/(b+d)/(a+b)*(a+b+c+d)-c/a',
'd/(b+d)/(a+b+c)*(a+b+c+d)-(c+d)/(a+b+c)',
'd/(b+d)/(a+b+c)*(a+b+c+d)-c/(a+c)/(a+b+c)*(a+b+c+d)',
'd/(b+d)/(a+b+d)*(a+b+c+d)-(c+d)/(a+b+d)',
'd/(b+d)/(a+b+d)*(a+b+c+d)-c/(a+c)/(a+b+d)*(a+b+c+d)',
'd/(b+d)/(a+c)*(a+b+c+d)-(c+d)/(a+b+c+d)/a*(a+b)',
'd/(b+d)/(a+c)*(a+b+c+d)-1/(a+c)*(c+d)',
'd/(b+d)/(a+c)*(a+b+c+d)-c/(a+c)/a*(a+b)',
'd/(b+d)/(a+c+d)*(a+b+c+d)-(c+d)/(a+c+d)',
'd/(b+d)/(a+c+d)*(a+b+c+d)-c/(a+c)/(a+c+d)*(a+b+c+d)',
'd/(b+d)/(b+c+d)*(a+b+c+d)-(c+d)/(b+c+d)',
'd/(b+d)/(b+c+d)*(a+b+c+d)-c/(a+c)/(b+c+d)*(a+b+c+d)',
'd/(b+d)/a*(a+b)-(c+d)/(a+b+c+d)/a*(a+b)',
'd/(b+d)/a*(a+b)-c/(a+c)/a*(a+b)',
'd/(b+d)/a*(a+b+c+d)-(c+d)/a',
'd/(b+d)/a*(a+b+c+d)-c/(a+c)/a*(a+b+c+d)',
'd/(b+d)/a*(a+c)-(c+d)/(a+b+c+d)/a*(a+c)',
'd/(b+d)/a*(a+c)-c/a',
'd/(b+d)/b*(a+b)-(c+d)/(a+b+c+d)/b*(a+b)',
'd/(b+d)/b*(a+b)-1/(b+d)*(c+d)',
'd/(b+d)/b*(a+b)-c/(a+c)/(b+d)*(a+b+c+d)',
'd/(b+d)/b*(a+b)-c/(a+c)/b*(a+b)',
'd/(b+d)/b*(a+b)-c/(a+c)/d*(c+d)',
'd/(b+d)/b*(a+b+c+d)-(c+d)/b',
'd/(b+d)/b*(a+b+c+d)-c/(a+c)/b*(a+b+c+d)',
'd/(b+d)/c*(a+b+c+d)-(a+b)/a',
'd/(b+d)/c*(a+b+c+d)-(c+d)/c',
'd/(b+d)/c*(a+b+c+d)-1/(a+c)*(a+b+c+d)',
'd/(b+d)/c*(a+b+c+d)-b/(b+d)/a*(a+b+c+d)',
'd/(b+d)/c*(a+c)-(a+c)/(a+b+c+d)/a*(a+b)',
'd/(b+d)/c*(a+c)-(a+c)/(a+b+c+d)/c*(c+d)',
'd/(b+d)/c*(a+c)-1',
'd/(b+d)/c*(a+c)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'd/(b+d)/c*(a+c)-b/(a+b)/(b+d)*(a+b+c+d)',
'd/(b+d)/c*(a+c)-b/(a+b)/d*(c+d)',
'd/(b+d)/c*(a+c)-b/(b+d)/a*(a+c)',
'd/(b+d)/c*(a+c)-c/(a+c)/(c+d)*(a+b+c+d)',
'd/(b+d)/c*(a+c)-c/(a+c)/d*(b+d)',
'd/(b+d)/c*(a+c)-c/(c+d)/a*(a+b)',
'd/(b+d)/c*(c+d)-(c+d)/(a+b+c+d)/a*(a+b)',
'd/(b+d)/c*(c+d)-1/(a+c)*(c+d)',
'd/(b+d)/c*(c+d)-c/(a+c)/a*(a+b)',
'd/(c+d)*(a+b)/(a+b+c+d)-b/(a+b+c+d)',
'd/(c+d)*a/(a+c)-b/(a+b+c+d)',
'd/(c+d)-(b+d)/(a+b+c+d)',
'd/(c+d)-b/(a+b)',
'd/(c+d)-b/(a+b+c+d)/a*(a+c)',
'd/(c+d)/(a+b)*(a+b+c+d)-(b+d)/(a+b+c+d)/a*(a+c)',
'd/(c+d)/(a+b)*(a+b+c+d)-1/(a+b)*(b+d)',
'd/(c+d)/(a+b)*(a+b+c+d)-b/(a+b)/a*(a+c)',
'd/(c+d)/(a+b+c)*(a+b+c+d)-(b+d)/(a+b+c)',
'd/(c+d)/(a+b+c)*(a+b+c+d)-b/(a+b)/(a+b+c)*(a+b+c+d)',
'd/(c+d)/(a+b+d)*(a+b+c+d)-(b+d)/(a+b+d)',
'd/(c+d)/(a+b+d)*(a+b+c+d)-b/(a+b)/(a+b+d)*(a+b+c+d)',
'd/(c+d)/(a+c)*(a+b+c+d)-(b+d)/(a+b+c+d)/a*(a+b)',
'd/(c+d)/(a+c)*(a+b+c+d)-(b+d)/(a+c)',
'd/(c+d)/(a+c)*(a+b+c+d)-b/(a+b)/(a+c)*(a+b+c+d)',
'd/(c+d)/(a+c)*(a+b+c+d)-b/a',
'd/(c+d)/(a+c+d)*(a+b+c+d)-(b+d)/(a+c+d)',
'd/(c+d)/(a+c+d)*(a+b+c+d)-b/(a+b)/(a+c+d)*(a+b+c+d)',
'd/(c+d)/(b+c+d)*(a+b+c+d)-(b+d)/(b+c+d)',
'd/(c+d)/(b+c+d)*(a+b+c+d)-b/(a+b)/(b+c+d)*(a+b+c+d)',
'd/(c+d)/(b+d)*(a+b+c+d)-(a+c)/(a+b+c+d)/a*(a+b)',
'd/(c+d)/(b+d)*(a+b+c+d)-1',
'd/(c+d)/(b+d)*(a+b+c+d)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'd/(c+d)/(b+d)*(a+b+c+d)-b/(a+b)/(b+d)*(a+b+c+d)',
'd/(c+d)/(b+d)*(a+b+c+d)-b/(a+b)/d*(c+d)',
'd/(c+d)/(b+d)*(a+b+c+d)-b/(b+d)/a*(a+c)',
'd/(c+d)/(b+d)*(a+b+c+d)-c/(a+c)/(c+d)*(a+b+c+d)',
'd/(c+d)/(b+d)*(a+b+c+d)-c/(a+c)/d*(b+d)',
'd/(c+d)/(b+d)*(a+b+c+d)-c/(c+d)/a*(a+b)',
'd/(c+d)/a*(a+b)-(b+d)/(a+b+c+d)/a*(a+b)',
'd/(c+d)/a*(a+b)-b/a',
'd/(c+d)/a*(a+b+c+d)-(b+d)/a',
'd/(c+d)/a*(a+b+c+d)-b/(a+b)/a*(a+b+c+d)',
'd/(c+d)/a*(a+c)-(b+d)/(a+b+c+d)/a*(a+c)',
'd/(c+d)/a*(a+c)-b/(a+b)/a*(a+c)',
'd/(c+d)/b*(a+b)-(a+b)/(a+b+c+d)/b*(b+d)',
'd/(c+d)/b*(a+b)-(a+c)/(a+b+c+d)/a*(a+b)',
'd/(c+d)/b*(a+b)-1',
'd/(c+d)/b*(a+b)-1/(a+b+c+d)*(b+d)/d*(c+d)',
'd/(c+d)/b*(a+b)-b/(a+b)/(b+d)*(a+b+c+d)',
'd/(c+d)/b*(a+b)-b/(a+b)/d*(c+d)',
'd/(c+d)/b*(a+b)-b/(b+d)/a*(a+c)',
'd/(c+d)/b*(a+b)-c/(a+c)/(c+d)*(a+b+c+d)',
'd/(c+d)/b*(a+b)-c/(a+c)/d*(b+d)',
'd/(c+d)/b*(a+b)-c/(c+d)/a*(a+b)',
'd/(c+d)/b*(a+b+c+d)-(a+c)/a',
'd/(c+d)/b*(a+b+c+d)-(b+d)/b',
'd/(c+d)/b*(a+b+c+d)-1/(a+b)*(a+b+c+d)',
'd/(c+d)/b*(a+b+c+d)-c/(c+d)/a*(a+b+c+d)',
'd/(c+d)/b*(b+d)-(b+d)/(a+b+c+d)/a*(a+c)',
'd/(c+d)/b*(b+d)-1/(a+b)*(b+d)',
'd/(c+d)/b*(b+d)-b/(a+b)/a*(a+c)',
'd/(c+d)/c*(a+b+c+d)-(b+d)/c',
'd/(c+d)/c*(a+b+c+d)-b/(a+b)/c*(a+b+c+d)',
'd/(c+d)/c*(a+c)-(b+d)/(a+b+c+d)/c*(a+c)',
'd/(c+d)/c*(a+c)-1/(c+d)*(b+d)',
'd/(c+d)/c*(a+c)-b/(a+b)/(c+d)*(a+b+c+d)',
'd/(c+d)/c*(a+c)-b/(a+b)/c*(a+c)',
'd/(c+d)/c*(a+c)-b/(a+b)/d*(b+d)',
'd/b-(c+d)/(a+b)',
'd/b-(c+d)/(a+b+c+d)/a*(a+c)',
'd/b-(c+d)/(a+b+c+d)/b*(b+d)',
'd/b-c/(a+c)/(a+b)*(a+b+c+d)',
'd/b-c/(a+c)/b*(b+d)',
'd/b-c/a',
'd/c-(b+d)/(a+b+c+d)/a*(a+b)',
'd/c-(b+d)/(a+b+c+d)/c*(c+d)',
'd/c-(b+d)/(a+c)',
'd/c-b/(a+b)/(a+c)*(a+b+c+d)',
'd/c-b/(a+b)/c*(c+d)',
'd/c-b/a']
| 39.753452 | 57 | 0.351575 | 7,076 | 20,155 | 1.001413 | 0.000848 | 0.3116 | 0.294666 | 0.331922 | 0.998165 | 0.996472 | 0.990827 | 0.979537 | 0.956393 | 0.904601 | 0 | 0.003614 | 0.025205 | 20,155 | 506 | 58 | 39.832016 | 0.357052 | 0 | 0 | 0 | 0 | 0.889328 | 0.898834 | 0.871248 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 |
353c3a55293e93ebb7e16ec5c46e01f6265f6a04 | 32 | py | Python | albert0/demo2.py | laohur/albert_pytorch | fd463014335717596a72888bad4bc653496c6a12 | [
"Apache-2.0"
] | null | null | null | albert0/demo2.py | laohur/albert_pytorch | fd463014335717596a72888bad4bc653496c6a12 | [
"Apache-2.0"
] | null | null | null | albert0/demo2.py | laohur/albert_pytorch | fd463014335717596a72888bad4bc653496c6a12 | [
"Apache-2.0"
] | null | null | null | def test():
return 5
test() | 8 | 12 | 0.5625 | 5 | 32 | 3.6 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.043478 | 0.28125 | 32 | 4 | 13 | 8 | 0.73913 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | true | 0 | 0 | 0.333333 | 0.666667 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
353fb33eb1fabe7a7e34a550fa6fea3c40f79c6f | 3,790 | py | Python | Assignment1/solution.py | khushhallchandra/EE677-VLSI-CAD | c40fbe3bd0c07cd1f3b18d477917c85702607e51 | [
"MIT"
] | 4 | 2016-12-05T12:43:58.000Z | 2020-02-21T00:29:42.000Z | Assignment1/solution.py | khushhallchandra/EE677-VLSI-CAD | c40fbe3bd0c07cd1f3b18d477917c85702607e51 | [
"MIT"
] | null | null | null | Assignment1/solution.py | khushhallchandra/EE677-VLSI-CAD | c40fbe3bd0c07cd1f3b18d477917c85702607e51 | [
"MIT"
] | null | null | null | def apply_AND_robdds_rec ( level, robdd_f_root_index, robdd_g_root_index ) :
if(robdd_f_root_index==0 or robdd_g_root_index==0):
return 0
if ( level == NumVars ) :
return 1 if (robdd_f_root_index==1 and robdd_g_root_index==1) else 0
if ( 'x'+str(level) != robdd_store[ robdd_f_root_index ][0] ) :
robdd_f_E_index = robdd_f_root_index
robdd_f_T_index = robdd_f_root_index
else :
robdd_f_E_index = robdd_store[ robdd_f_root_index ][1]
robdd_f_T_index = robdd_store[ robdd_f_root_index ][2]
if ( 'x'+str(level) != robdd_store[ robdd_g_root_index ][0] ) :
robdd_g_E_index = robdd_g_root_index
robdd_g_T_index = robdd_g_root_index
else :
robdd_g_E_index = robdd_store[ robdd_g_root_index ][1]
robdd_g_T_index = robdd_store[ robdd_g_root_index ][2]
E_tuple_index = apply_AND_robdds_rec ( level+1, robdd_f_E_index, robdd_g_E_index )
T_tuple_index = apply_AND_robdds_rec ( level+1, robdd_f_T_index, robdd_g_T_index )
if ( E_tuple_index == T_tuple_index ) :
return E_tuple_index
if ( not ( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) in robdd_store ) ) :
robdd_store.append( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) )
return len(robdd_store) - 1
else :
return robdd_store.index( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) )
def apply_NAND_robdds_rec ( level, robdd_f_root_index, robdd_g_root_index ) :
if(robdd_f_root_index==0 or robdd_g_root_index==0):
return 1
if ( level == NumVars ) :
return 0 if (robdd_f_root_index==1 and robdd_g_root_index==1) else 1
if ( 'x'+str(level) != robdd_store[ robdd_f_root_index ][0] ) :
robdd_f_E_index = robdd_f_root_index
robdd_f_T_index = robdd_f_root_index
else :
robdd_f_E_index = robdd_store[ robdd_f_root_index ][1]
robdd_f_T_index = robdd_store[ robdd_f_root_index ][2]
if ( 'x'+str(level) != robdd_store[ robdd_g_root_index ][0] ) :
robdd_g_E_index = robdd_g_root_index
robdd_g_T_index = robdd_g_root_index
else :
robdd_g_E_index = robdd_store[ robdd_g_root_index ][1]
robdd_g_T_index = robdd_store[ robdd_g_root_index ][2]
E_tuple_index = apply_NAND_robdds_rec ( level+1, robdd_f_E_index, robdd_g_E_index )
T_tuple_index = apply_NAND_robdds_rec ( level+1, robdd_f_T_index, robdd_g_T_index )
if ( E_tuple_index == T_tuple_index ) :
return E_tuple_index
if ( not ( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) in robdd_store ) ) :
robdd_store.append( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) )
return len(robdd_store) - 1
else :
return robdd_store.index( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) )
def apply_NOT_robdds_rec ( level, robdd_f_root_index ) :
if ( level == NumVars ) :
return 0 if (robdd_f_root_index==1 ) else 1
if ( 'x'+str(level) != robdd_store[ robdd_f_root_index ][0] ) :
robdd_f_E_index = robdd_f_root_index
robdd_f_T_index = robdd_f_root_index
else :
robdd_f_E_index = robdd_store[ robdd_f_root_index ][1]
robdd_f_T_index = robdd_store[ robdd_f_root_index ][2]
E_tuple_index = apply_NOT_robdds_rec ( level+1, robdd_f_E_index )
T_tuple_index = apply_NOT_robdds_rec ( level+1, robdd_f_T_index )
if ( E_tuple_index == T_tuple_index ) :
return E_tuple_index
if ( not ( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) in robdd_store ) ) :
robdd_store.append( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) )
return len(robdd_store) - 1
else :
return robdd_store.index( ( 'x'+str(level) , E_tuple_index, T_tuple_index ) ) | 41.195652 | 94 | 0.673087 | 629 | 3,790 | 3.535771 | 0.047695 | 0.110612 | 0.103417 | 0.155126 | 0.98786 | 0.981115 | 0.980665 | 0.967176 | 0.964478 | 0.964478 | 0 | 0.014041 | 0.229551 | 3,790 | 92 | 94 | 41.195652 | 0.747603 | 0 | 0 | 0.8 | 0 | 0 | 0.003693 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
1039d162b576cafc021c2abe9a4e5bd494df5eeb | 177 | py | Python | loafang/__init__.py | Adwaith-Rajesh/loafang | 2ccea64ddbc19b7a4ba5219ec2bb5185919146be | [
"MIT"
] | 3 | 2021-11-17T13:32:21.000Z | 2021-11-27T04:20:48.000Z | loafang/__init__.py | Adwaith-Rajesh/loafang | 2ccea64ddbc19b7a4ba5219ec2bb5185919146be | [
"MIT"
] | null | null | null | loafang/__init__.py | Adwaith-Rajesh/loafang | 2ccea64ddbc19b7a4ba5219ec2bb5185919146be | [
"MIT"
] | null | null | null | from .methods import Methods # noqa: F401
from .methods import MethodsError # noqa: F401
from .parser import parse # noqa: F401
from .query import QueryBuilder # noqa: F401
| 35.4 | 47 | 0.751412 | 24 | 177 | 5.541667 | 0.416667 | 0.240602 | 0.270677 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.082759 | 0.180791 | 177 | 4 | 48 | 44.25 | 0.834483 | 0.242938 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
10416c46deb2a7e61b929f1a7cbbcfd37851604e | 4,951 | py | Python | tests/test_tefy.py | 03b8/TEfy | 7dd4f6c9a0ba32ce521f7c1745a733412f25dfc9 | [
"MIT"
] | 2 | 2019-10-20T22:32:57.000Z | 2021-12-05T12:01:09.000Z | tests/test_tefy.py | 03b8/tefy | 7dd4f6c9a0ba32ce521f7c1745a733412f25dfc9 | [
"MIT"
] | 1 | 2018-08-27T11:26:38.000Z | 2018-08-27T11:47:15.000Z | tests/test_tefy.py | ghineaion/TEfy | 7dd4f6c9a0ba32ce521f7c1745a733412f25dfc9 | [
"MIT"
] | null | null | null | from tefy import OxGaWrap, __version__
def test_version():
assert __version__ == '0.1.3'
def get_tag_list(frmt):
"""
Gets a list of tags from the XML conversion output of a specific document.
:param frmt: format/extension of the input document (document must be present in the tests/in folder)
:return: list of element tags
"""
oxobj = OxGaWrap(f'tests/in/test.{frmt}')
tree = oxobj.tei_xml
elems = [el.tag for el in tree.xpath('//*')]
return elems
# Test TEI XML output for each format by comparing a list of all element tags in document with a list of expected tags
def test_doc_output():
elems = get_tag_list('doc')
expected_elems = ['{http://www.tei-c.org/ns/1.0}TEI', '{http://www.tei-c.org/ns/1.0}teiHeader',
'{http://www.tei-c.org/ns/1.0}fileDesc', '{http://www.tei-c.org/ns/1.0}titleStmt',
'{http://www.tei-c.org/ns/1.0}title', '{http://www.tei-c.org/ns/1.0}author',
'{http://www.tei-c.org/ns/1.0}editionStmt', '{http://www.tei-c.org/ns/1.0}edition',
'{http://www.tei-c.org/ns/1.0}date', '{http://www.tei-c.org/ns/1.0}publicationStmt',
'{http://www.tei-c.org/ns/1.0}p', '{http://www.tei-c.org/ns/1.0}sourceDesc',
'{http://www.tei-c.org/ns/1.0}p', '{http://www.tei-c.org/ns/1.0}revisionDesc',
'{http://www.tei-c.org/ns/1.0}listChange', '{http://www.tei-c.org/ns/1.0}change',
'{http://www.tei-c.org/ns/1.0}name', '{http://www.tei-c.org/ns/1.0}date',
'{http://www.tei-c.org/ns/1.0}text', '{http://www.tei-c.org/ns/1.0}body',
'{http://www.tei-c.org/ns/1.0}div', '{http://www.tei-c.org/ns/1.0}head',
'{http://www.tei-c.org/ns/1.0}p']
assert elems == expected_elems
def test_docx_output():
elems = get_tag_list('docx')
expected_elems = ['{http://www.tei-c.org/ns/1.0}TEI', '{http://www.tei-c.org/ns/1.0}teiHeader',
'{http://www.tei-c.org/ns/1.0}fileDesc', '{http://www.tei-c.org/ns/1.0}titleStmt',
'{http://www.tei-c.org/ns/1.0}title', '{http://www.tei-c.org/ns/1.0}author',
'{http://www.tei-c.org/ns/1.0}editionStmt', '{http://www.tei-c.org/ns/1.0}edition',
'{http://www.tei-c.org/ns/1.0}date', '{http://www.tei-c.org/ns/1.0}publicationStmt',
'{http://www.tei-c.org/ns/1.0}p', '{http://www.tei-c.org/ns/1.0}sourceDesc',
'{http://www.tei-c.org/ns/1.0}p', '{http://www.tei-c.org/ns/1.0}encodingDesc',
'{http://www.tei-c.org/ns/1.0}appInfo', '{http://www.tei-c.org/ns/1.0}application',
'{http://www.tei-c.org/ns/1.0}label', '{http://www.tei-c.org/ns/1.0}revisionDesc',
'{http://www.tei-c.org/ns/1.0}listChange', '{http://www.tei-c.org/ns/1.0}change',
'{http://www.tei-c.org/ns/1.0}date', '{http://www.tei-c.org/ns/1.0}name',
'{http://www.tei-c.org/ns/1.0}text', '{http://www.tei-c.org/ns/1.0}body',
'{http://www.tei-c.org/ns/1.0}div', '{http://www.tei-c.org/ns/1.0}head',
'{http://www.tei-c.org/ns/1.0}p']
assert elems == expected_elems
def test_odt_output():
elems = get_tag_list('odt')
expected_elems = ['{http://www.tei-c.org/ns/1.0}TEI', '{http://www.tei-c.org/ns/1.0}teiHeader',
'{http://www.tei-c.org/ns/1.0}fileDesc', '{http://www.tei-c.org/ns/1.0}titleStmt',
'{http://www.tei-c.org/ns/1.0}title', '{http://www.tei-c.org/ns/1.0}author',
'{http://www.tei-c.org/ns/1.0}editionStmt', '{http://www.tei-c.org/ns/1.0}edition',
'{http://www.tei-c.org/ns/1.0}date', '{http://www.tei-c.org/ns/1.0}publicationStmt',
'{http://www.tei-c.org/ns/1.0}p', '{http://www.tei-c.org/ns/1.0}sourceDesc',
'{http://www.tei-c.org/ns/1.0}p', '{http://www.tei-c.org/ns/1.0}profileDesc',
'{http://www.tei-c.org/ns/1.0}langUsage', '{http://www.tei-c.org/ns/1.0}language',
'{http://www.tei-c.org/ns/1.0}revisionDesc', '{http://www.tei-c.org/ns/1.0}listChange',
'{http://www.tei-c.org/ns/1.0}change', '{http://www.tei-c.org/ns/1.0}name',
'{http://www.tei-c.org/ns/1.0}date', '{http://www.tei-c.org/ns/1.0}text',
'{http://www.tei-c.org/ns/1.0}body', '{http://www.tei-c.org/ns/1.0}p',
'{http://www.tei-c.org/ns/1.0}p']
assert elems == expected_elems
| 64.298701 | 118 | 0.502929 | 818 | 4,951 | 3.007335 | 0.103912 | 0.213415 | 0.304878 | 0.335366 | 0.794715 | 0.769106 | 0.769106 | 0.769106 | 0.73252 | 0.73252 | 0 | 0.04216 | 0.267017 | 4,951 | 76 | 119 | 65.144737 | 0.635712 | 0.065441 | 0 | 0.535714 | 0 | 0 | 0.585053 | 0 | 0 | 0 | 0 | 0 | 0.071429 | 1 | 0.089286 | false | 0 | 0.017857 | 0 | 0.125 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
10b4a6a04008f830e9543971b8b731ea40b3f80c | 211 | py | Python | mfplugin/__init__.py | albator75/mfplugin | eab633a8d95d8bc08f77709b9118b6af94d8a862 | [
"BSD-3-Clause"
] | null | null | null | mfplugin/__init__.py | albator75/mfplugin | eab633a8d95d8bc08f77709b9118b6af94d8a862 | [
"BSD-3-Clause"
] | 5 | 2020-05-28T07:32:40.000Z | 2021-08-17T10:37:40.000Z | mfplugin/__init__.py | albator75/mfplugin | eab633a8d95d8bc08f77709b9118b6af94d8a862 | [
"BSD-3-Clause"
] | 2 | 2021-08-17T09:41:55.000Z | 2021-08-17T10:25:16.000Z | import lazy_import
lazy_import.lazy_module("configupdater")
lazy_import.lazy_module("cerberus")
lazy_import.lazy_module("mfutil")
opinionated_configparser = lazy_import.lazy_module("opinionated_configparser")
| 26.375 | 78 | 0.853081 | 26 | 211 | 6.5 | 0.307692 | 0.35503 | 0.414201 | 0.473373 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.047393 | 211 | 7 | 79 | 30.142857 | 0.840796 | 0 | 0 | 0 | 0 | 0 | 0.241706 | 0.113744 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
10bc14cb356f76afacc1af22b3f67a178fbe5538 | 53 | py | Python | ckanext/os/celery_import.py | datagovuk/ckanext-os | 49eefdd5a9e8a5b950c161860307b6e1fdd071ca | [
"BSD-3-Clause"
] | 2 | 2015-07-06T00:16:07.000Z | 2015-07-06T00:20:58.000Z | ckanext/os/celery_import.py | datagovuk/ckanext-os | 49eefdd5a9e8a5b950c161860307b6e1fdd071ca | [
"BSD-3-Clause"
] | 1 | 2016-12-28T09:21:41.000Z | 2016-12-28T09:21:41.000Z | ckanext/os/celery_import.py | datagovuk/ckanext-os | 49eefdd5a9e8a5b950c161860307b6e1fdd071ca | [
"BSD-3-Clause"
] | 2 | 2019-05-01T13:14:15.000Z | 2021-04-10T21:22:20.000Z |
def task_imports():
return ['ckanext.os.tasks']
| 13.25 | 31 | 0.660377 | 7 | 53 | 4.857143 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.169811 | 53 | 3 | 32 | 17.666667 | 0.772727 | 0 | 0 | 0 | 0 | 0 | 0.307692 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0.5 | 0.5 | 1.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 7 |
52a0a2739495f3d5e8f707a51abb0ad1e0ccc15d | 101,907 | py | Python | gisele/MILP_models.py | Energy4Growing/gisele_v02 | 5845772423ef8afe382854bc35819c4f3b698841 | [
"Apache-2.0"
] | null | null | null | gisele/MILP_models.py | Energy4Growing/gisele_v02 | 5845772423ef8afe382854bc35819c4f3b698841 | [
"Apache-2.0"
] | null | null | null | gisele/MILP_models.py | Energy4Growing/gisele_v02 | 5845772423ef8afe382854bc35819c4f3b698841 | [
"Apache-2.0"
] | null | null | null | ''' ALL DIFFERENT MILP MODELS IN ONE FILE
1. MILP WITHOUT MG -> Doesn't consider the Microgrid option and works with only 1 type of cable. However, it considers reliability.
2. MILP2 -> Consider
3. MILP3
4. MILP4
5. MILP5
'''
from __future__ import division
from pyomo.opt import SolverFactory
from pyomo.core import AbstractModel
from pyomo.dataportal.DataPortal import DataPortal
from pyomo.environ import *
import pandas as pd
from datetime import datetime
import os
def MILP_without_MG(gisele_folder,case_study,n_clusters,coe,voltage,resistance,reactance,Pmax,line_cost):
############ Create abstract model ###########
model = AbstractModel()
data = DataPortal()
MILP_input_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_input'
MILP_output_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_output'
os.chdir(MILP_input_folder)
# Define some basic parameter for the per unit conversion and voltage limitation
Abase = 1
Vmin = 0.9
####################Define sets#####################
model.N = Set()
data.load(filename='nodes.csv', set=model.N) # first row is not read
model.N_clusters = Set()
data.load(filename='nodes_clusters.csv', set=model.N_clusters)
model.N_PS = Set()
data.load(filename='nodes_PS.csv', set=model.N_PS)
# Node corresponding to primary substation
# Allowed connections
model.links = Set(dimen=2) # in the csv the values must be delimited by commas
data.load(filename='links_all.csv', set=model.links)
model.links_clusters = Set(dimen=2)
data.load(filename='links_clusters.csv', set=model.links_clusters)
model.links_decision = Set(dimen=2)
data.load(filename='links_decision.csv', set=model.links_decision)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
#####################Define parameters#####################
# Electric power in the nodes (injected (-) or absorbed (+))
model.Psub = Param(model.N_clusters)
data.load(filename='power_nodes.csv', param=model.Psub)
model.ps_cost = Param(model.N_PS)
data.load(filename='PS_costs.csv', param=model.ps_cost)
model.PSmax = Param(model.N_PS)
data.load(filename='PS_power_max.csv', param=model.PSmax)
model.PS_voltage = Param(model.N_PS)
data.load(filename='PS_voltage.csv', param=model.PS_voltage)
model.PS_distance = Param(model.N_PS)
data.load(filename='PS_distance.csv', param=model.PS_distance)
# Connection distance of all the edges
model.dist = Param(model.links)
data.load(filename='distances.csv', param=model.dist)
model.weights = Param(model.links_decision)
data.load(filename='weights_decision_lines.csv', param=model.weights)
# Electrical parameters of all the cables
model.V_ref = Param(initialize=voltage)
model.A_ref = Param(initialize=Abase)
model.E_min = Param(initialize=Vmin)
model.R_ref = Param(initialize=resistance)
model.X_ref = Param(initialize=reactance)
model.P_max = Param(initialize=Pmax)
model.cf = Param(initialize=line_cost)
model.Z = Param(initialize=model.R_ref + model.X_ref * 0.5)
model.Z_ref = Param(initialize=model.V_ref ** 2 / Abase)
model.n_clusters = Param(initialize=n_clusters)
model.coe = Param(initialize=coe)
#####################Define variables#####################
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise
model.x = Var(model.links_decision, within=Binary)
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links)
# positive variables E(i) is p.u. voltage at each node
model.E = Var(model.N, within=NonNegativeReals)
# binary variable k[i]: 1 if node i is a primary substation, 0 otherwise
model.k = Var(model.N_PS, within=Binary)
# Power output of Primary substation
model.PPS = Var(model.N_PS, within=NonNegativeReals)
model.positive_p = Var(model.links_clusters, within=Binary)
model.Distance = Var(model.N, within=Reals)
model.cable_type = Var(model.links)
#####################Define constraints###############################
# Radiality constraint
def Radiality_rule(model):
return summation(model.x) == model.n_clusters
model.Radiality = Constraint(rule=Radiality_rule)
# Power flow constraints
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == model.Psub[node]
model.Power_flow_conservation = Constraint(model.N_clusters, rule=Power_flow_conservation_rule)
def Power_flow_conservation_rule3(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.PPS[node]
model.Power_flow_conservation3 = Constraint(model.N_PS, rule=Power_flow_conservation_rule3)
def Power_upper_decision(model, i, j):
return model.P[i, j] <= model.P_max * model.x[i, j]
model.Power_upper_decision = Constraint(model.links_decision, rule=Power_upper_decision)
def Power_lower_decision(model, i, j):
return model.P[i, j] >= 0 # -model.P_max*model.x[i,j]
model.Power_lower_decision = Constraint(model.links_decision, rule=Power_lower_decision)
def Power_upper_clusters(model, i, j):
return model.P[i, j] <= model.P_max * model.positive_p[i, j]
model.Power_upper_clusters = Constraint(model.links_clusters, rule=Power_upper_clusters)
def Power_lower_clusters(model, i, j):
return model.P[i, j] >= 0 # -model.P_max*model.x[i,j]
model.Power_lower_clusters = Constraint(model.links_clusters, rule=Power_lower_clusters)
# Voltage constraints
def Voltage_balance_rule(model, i, j):
return (model.E[i] - model.E[j]) + model.x[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule = Constraint(model.links_decision, rule=Voltage_balance_rule)
def Voltage_balance_rule2(model, i, j):
return (model.E[i] - model.E[j]) - model.x[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule2 = Constraint(model.links_decision, rule=Voltage_balance_rule2)
def Voltage_balance_rule3(model, i, j):
return (model.E[i] - model.E[j]) + model.positive_p[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule3 = Constraint(model.links_clusters, rule=Voltage_balance_rule3)
def Voltage_balance_rule4(model, i, j):
return (model.E[i] - model.E[j]) - model.positive_p[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule4 = Constraint(model.links_clusters, rule=Voltage_balance_rule4)
def Voltage_limit(model, i):
return model.E[i] >= model.k[i] * (model.PS_voltage[i] - model.E_min) + model.E_min
model.Voltage_limit = Constraint(model.N_PS, rule=Voltage_limit)
def Voltage_PS2(model, i):
return model.E[i] <= model.PS_voltage[i]
model.Voltage_PS2 = Constraint(model.N_PS, rule=Voltage_PS2)
def Voltage_limit_clusters2(model, i):
return model.E[i] >= model.E_min
model.Voltage_limit_clusters2 = Constraint(model.N_clusters, rule=Voltage_limit_clusters2)
def PS_power_rule_upper(model, i):
return model.PPS[i] <= model.PSmax[i] * model.k[i]
model.PS_power_upper = Constraint(model.N_PS, rule=PS_power_rule_upper)
def distance_from_PS(model, i):
return model.Distance[i] <= -model.PS_distance[i]
model.distance_from_PS = Constraint(model.N_PS, rule=distance_from_PS)
def distance_from_PS2(model, i):
return model.Distance[i] >= (model.k[i] - 1) * 200 - model.PS_distance[i] * model.k[i]
model.distance_from_PS2 = Constraint(model.N_PS, rule=distance_from_PS2)
def distance_balance_decision(model, i, j):
return model.Distance[i] - model.Distance[j] + 1000 * (model.x[i, j] - 1) <= model.dist[i, j] / 1000
model.distance_balance_decision = Constraint(model.links_decision, rule=distance_balance_decision)
def distance_balance_decision2(model, i, j):
return (model.Distance[i] - model.Distance[j]) - 1000 * (model.x[i, j] - 1) >= model.dist[i, j] / 1000
model.distance_balance_decision2 = Constraint(model.links_decision, rule=distance_balance_decision2)
def distance_balance_clusters(model, i, j):
return model.Distance[i] - model.Distance[j] + 1000 * (model.positive_p[i, j] - 1) <= model.dist[i, j] / 1000
model.distance_balance_clusters = Constraint(model.links_clusters, rule=distance_balance_clusters)
def distance_balance_clusters2(model, i, j):
return (model.Distance[i] - model.Distance[j]) - 1000 * (model.positive_p[i, j] - 1) >= model.dist[i, j] / 1000
model.distance_balance_clusters2 = Constraint(model.links_clusters, rule=distance_balance_clusters2)
def Balance_rule(model):
return (sum(model.PPS[i] for i in model.N_PS) - sum(model.Psub[i] for i in model.N_clusters)) == 0
model.Balance = Constraint(rule=Balance_rule)
def anti_paralel(model, i, j):
return model.x[i, j] + model.x[j, i] <= 1
model.anti_paralel = Constraint(model.links_decision, rule=anti_paralel)
def anti_paralel_clusters(model, i, j):
return model.positive_p[i, j] + model.positive_p[j, i] == 1
model.anti_paralel_clusters = Constraint(model.links_clusters, rule=anti_paralel_clusters)
####################Define objective function##########################
####################Define objective function##########################
reliability_index = 1000
def ObjectiveFunction(model):
return summation(model.weights, model.x) * model.cf / 1000 + summation(model.ps_cost, model.k)
# return summation(model.weights, model.x) * model.cf / 1000 + summation(model.ps_cost,model.k) - sum(model.Psub[i]*model.Distance[i] for i in model.N_clusters)*reliability_index
model.Obj = Objective(rule=ObjectiveFunction, sense=minimize)
#############Solve model##################
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\Gisele_MILP\cbc')
opt = SolverFactory('gurobi')
opt.options['TimeLimit'] = 300
# opt.options['numericfocus']=0
# opt.options['mipgap'] = 0.0002
# opt.options['presolve']=2
# opt.options['mipfocus']=2
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\New folder\cbc')
print('Starting optimization process')
time_i = datetime.now()
opt.solve(instance, tee=True, symbolic_solver_labels=True)
time_f = datetime.now()
print('Time required for optimization is', time_f - time_i)
links = instance.x
power = instance.P
subs = instance.k
voltage = instance.E
PS = instance.PPS
DISTANCE = instance.Distance
links_clusters = instance.links_clusters
# voltage_drop=instance.z
connections_output = pd.DataFrame(columns=[['id1', 'id2', 'power']])
PrSubstation = pd.DataFrame(columns=[['index', 'power']])
all_lines = pd.DataFrame(columns=[['id1', 'id2', 'power']])
Voltages = pd.DataFrame(columns=[['index', 'voltage [p.u]']])
Links_Clusters = pd.DataFrame(columns=[['id1', 'id2', 'power']])
distance = pd.DataFrame(columns=[['index', 'length[km]']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in subs:
if int(round(value(subs[index]))) == 1:
PrSubstation.loc[k, 'index'] = index
PrSubstation.loc[k, 'power'] = value(PS[index])
print(((value(PS[index]))))
k = k + 1
k = 0
for v in voltage:
Voltages.loc[k, 'index'] = v
Voltages.loc[k, 'voltage [p.u]'] = value(voltage[v])
k = k + 1
k = 0
for index in power:
all_lines.loc[k, 'id1'] = index[0]
all_lines.loc[k, 'id2'] = index[1]
all_lines.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in links_clusters:
Links_Clusters.loc[k, 'id1'] = index[0]
Links_Clusters.loc[k, 'id2'] = index[1]
Links_Clusters.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for dist in DISTANCE:
distance.loc[k, 'index'] = dist
distance.loc[k, 'length[m]'] = value(DISTANCE[dist])
k = k + 1
Links_Clusters.to_csv(MILP_output_folder + '/links_clusters.csv', index=False)
connections_output.to_csv(MILP_output_folder + '/connections_output.csv', index=False)
PrSubstation.to_csv(MILP_output_folder + '/PrimarySubstations.csv', index=False)
Voltages.to_csv(MILP_output_folder + '/Voltages.csv', index=False)
all_lines.to_csv(MILP_output_folder + '/all_lines.csv', index=False)
distance.to_csv(MILP_output_folder + '/Distances.csv', index=False)
def MILP_MG_reliability(gisele_folder,case_study,n_clusters,coe,voltage,resistance,reactance,Pmax,line_cost):
model = AbstractModel()
data = DataPortal()
MILP_input_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_input'
MILP_output_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_output'
os.chdir(MILP_input_folder)
# Define some basic parameter for the per unit conversion and voltage limitation
Abase = 1
Vmin = 0.9
# ####################Define sets#####################
# Name of all the nodes (primary and secondary substations)
model.N = Set()
data.load(filename='nodes.csv', set=model.N) # first row is not read
model.N_clusters = Set()
data.load(filename='nodes_clusters.csv', set=model.N_clusters)
model.N_MG = Set()
data.load(filename='microgrids_nodes.csv', set=model.N_MG)
model.N_PS = Set()
data.load(filename='nodes_PS.csv', set=model.N_PS)
# Node corresponding to primary substation
# Allowed connections
model.links = Set(dimen=2) # in the csv the values must be delimited by commas
data.load(filename='links_all.csv', set=model.links)
model.links_clusters = Set(dimen=2)
data.load(filename='links_clusters.csv', set=model.links_clusters)
model.links_decision = Set(dimen=2)
data.load(filename='links_decision.csv', set=model.links_decision)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
#####################Define parameters#####################
# Electric power in the nodes (injected (-) or absorbed (+))
model.Psub = Param(model.N_clusters)
data.load(filename='power_nodes.csv', param=model.Psub)
# model.PS=Param(model.N)
# data.load(filename='PS.csv',param=model.PS)
model.microgrid_power = Param(model.N_MG)
data.load(filename='microgrids_powers.csv', param=model.microgrid_power)
model.energy = Param(model.N_MG)
data.load(filename='energy.csv', param=model.energy)
model.mg_cost = Param(model.N_MG)
data.load(filename='microgrids_costs.csv', param=model.mg_cost)
model.ps_cost = Param(model.N_PS)
data.load(filename='PS_costs.csv', param=model.ps_cost)
model.PSmax = Param(model.N_PS)
data.load(filename='PS_power_max.csv', param=model.PSmax)
# Power of the primary substation as sum of all the other powers
# def PPS_init(model):
# return sum(model.Psub[i] for i in model.N)
# model.PPS=Param(model.PS,initialize=PPS_init)
# Connection distance of all the edges
model.dist = Param(model.links)
data.load(filename='distances.csv', param=model.dist)
model.weights = Param(model.links_decision)
data.load(filename='weights_decision_lines.csv', param=model.weights)
# Electrical parameters of all the cables
model.V_ref = Param()
model.A_ref = Param()
model.R_ref = Param()
model.X_ref = Param()
model.P_max = Param()
model.cf = Param()
model.cPS = Param()
model.E_min = Param()
model.PPS_max = Param()
model.PPS_min = Param()
model.Z = Param()
model.Z_ref = Param()
model.n_clusters = Param()
model.coe = Param()
data.load(filename='data2.dat')
#####################Define variables#####################
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise
model.x = Var(model.links_decision, within=Binary)
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links)
# positive variables E(i) is p.u. voltage at each node
model.E = Var(model.N, within=NonNegativeReals)
# microgrid
model.z = Var(model.N_MG, within=Binary)
# binary variable k[i]: 1 if node i is a primary substation, 0 otherwise
model.k = Var(model.N_PS, within=Binary)
# Power output of Primary substation
model.PPS = Var(model.N_PS, within=NonNegativeReals)
model.MG_output = Var(model.N_MG)
model.positive_p = Var(model.links_clusters, within=Binary)
model.Distance = Var(model.N, within=Reals)
#####################Define constraints###############################
# def Make_problem_easy(model,i,j):
# return model.x[i,j]+model.weights[i,j]>=1
# model.easy = Constraint(model.links, rule=Make_problem_easy)
def Radiality_rule(model):
# return summation(model.x)==len(model.N)-summation(model.k)
return summation(model.x) == model.n_clusters
model.Radiality = Constraint(rule=Radiality_rule)
def Radiality_rule(model):
return summation(model.k) + summation(model.z) <= model.n_clusters
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == model.Psub[node]
model.Power_flow_conservation = Constraint(model.N_clusters, rule=Power_flow_conservation_rule)
def Power_flow_conservation_rule2(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.MG_output[node]
model.Power_flow_conservation2 = Constraint(model.N_MG, rule=Power_flow_conservation_rule2)
def Power_flow_conservation_rule3(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.PPS[node]
model.Power_flow_conservation3 = Constraint(model.N_PS, rule=Power_flow_conservation_rule3)
def Power_upper_decision(model, i, j):
return model.P[i, j] <= model.P_max * model.x[i, j]
model.Power_upper_decision = Constraint(model.links_decision, rule=Power_upper_decision)
def Power_lower_decision(model, i, j):
return model.P[i, j] >= 0 # -model.P_max*model.x[i,j]
model.Power_lower_decision = Constraint(model.links_decision, rule=Power_lower_decision)
def Power_upper_clusters(model, i, j):
return model.P[i, j] <= model.P_max * model.positive_p[i, j]
model.Power_upper_clusters = Constraint(model.links_clusters, rule=Power_upper_clusters)
def Power_lower_clusters(model, i, j):
return model.P[i, j] >= 0 # -model.P_max*model.x[i,j]
model.Power_lower_clusters = Constraint(model.links_clusters, rule=Power_lower_clusters)
# Voltage constraints
def Voltage_balance_rule(model, i, j):
return (model.E[i] - model.E[j]) + model.x[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule = Constraint(model.links_decision, rule=Voltage_balance_rule)
def Voltage_balance_rule2(model, i, j):
return (model.E[i] - model.E[j]) - model.x[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule2 = Constraint(model.links_decision, rule=Voltage_balance_rule2)
def Voltage_balance_rule3(model, i, j):
return (model.E[i] - model.E[j]) + model.positive_p[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule3 = Constraint(model.links_clusters, rule=Voltage_balance_rule3)
def Voltage_balance_rule4(model, i, j):
return (model.E[i] - model.E[j]) - model.positive_p[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule4 = Constraint(model.links_clusters, rule=Voltage_balance_rule4)
def Voltage_limit(model, i):
return model.E[i] >= model.k[i] * (1 - model.E_min) + model.E_min
model.Voltage_limit = Constraint(model.N_PS, rule=Voltage_limit)
def Voltage_PS2(model, i):
return model.E[i] <= 1
model.Voltage_PS2 = Constraint(model.N_PS, rule=Voltage_PS2)
def Voltage_limit_MG(model, i):
return model.E[i] <= 1
model.Voltage_limit_MG = Constraint(model.N_MG, rule=Voltage_limit_MG)
def Voltage_limit_MG2(model, i):
return model.E[i] >= model.z[i] * (1 - model.E_min) + model.E_min
model.Voltage_limit_MG2 = Constraint(model.N_MG, rule=Voltage_limit_MG2)
def Voltage_limit_clusters2(model, i):
return model.E[i] >= model.E_min
model.Voltage_limit_clusters2 = Constraint(model.N_clusters, rule=Voltage_limit_clusters2)
def PS_power_rule_upper(model, i):
return model.PPS[i] <= model.PSmax[i] * model.k[i]
model.PS_power_upper = Constraint(model.N_PS, rule=PS_power_rule_upper)
def distance_from_PS(model, i):
return model.Distance[i] <= 0
model.distance_from_PS = Constraint(model.N_PS, rule=distance_from_PS)
def distance_from_PS2(model, i):
return model.Distance[i] >= (model.k[i] - 1) * 100
model.distance_from_PS2 = Constraint(model.N_PS, rule=distance_from_PS2)
def distance_from_MG(model, i):
return model.Distance[i] <= 0
model.distance_from_MG = Constraint(model.N_MG, rule=distance_from_MG)
def distance_from_MG2(model, i):
return model.Distance[i] >= (model.z[i] - 1) * 100 # length must be <100km in this case
model.distance_from_MG2 = Constraint(model.N_MG, rule=distance_from_MG2)
def distance_balance_decision(model, i, j):
return model.Distance[i] - model.Distance[j] + 1000 * (model.x[i, j] - 1) <= model.dist[i, j] / 1000
model.distance_balance_decision = Constraint(model.links_decision, rule=distance_balance_decision)
def distance_balance_decision2(model, i, j):
return (model.Distance[i] - model.Distance[j]) - 1000 * (model.x[i, j] - 1) >= model.dist[i, j] / 1000
model.distance_balance_decision2 = Constraint(model.links_decision, rule=distance_balance_decision2)
def distance_balance_clusters(model, i, j):
return model.Distance[i] - model.Distance[j] + 1000 * (model.positive_p[i, j] - 1) <= model.dist[i, j] / 1000
model.distance_balance_clusters = Constraint(model.links_clusters, rule=distance_balance_clusters)
def distance_balance_clusters2(model, i, j):
return (model.Distance[i] - model.Distance[j]) - 1000 * (model.positive_p[i, j] - 1) >= model.dist[i, j] / 1000
model.distance_balance_clusters2 = Constraint(model.links_clusters, rule=distance_balance_clusters2)
def Balance_rule(model):
return (sum(model.PPS[i] for i in model.N_PS) + sum(model.MG_output[i] for i in model.N_MG) - sum(
model.Psub[i] for i in model.N_clusters)) == 0
model.Balance = Constraint(rule=Balance_rule)
def MG_power_limit(model, i):
return model.MG_output[i] == model.z[i] * model.microgrid_power[i]
model.MG_power_limit = Constraint(model.N_MG, rule=MG_power_limit)
def anti_paralel(model, i, j):
return model.x[i, j] + model.x[j, i] <= 1
model.anti_paralel = Constraint(model.links_decision, rule=anti_paralel)
def anti_paralel_clusters(model, i, j):
return model.positive_p[i, j] + model.positive_p[j, i] == 1
model.anti_paralel_clusters = Constraint(model.links_clusters, rule=anti_paralel_clusters)
####################Define objective function##########################
def ObjectiveFunction(model):
# return summation(model.weights, model.x) * model.cf / 1000
return summation(model.weights, model.x) * model.cf / 1000 + summation(model.mg_cost, model.z) * 1000 + sum(
model.energy[i] * (1 - model.z[i]) for i in model.N_MG) * model.coe
# + summation(model.ps_cost,model.k)
# +sum((model.P[i]/model.A_ref)**2*0.5*1.25*model.R_ref/model.Z_ref*model.dist[i]/1000*24*365*20 for i in model.links)
# return summation(model.dist,model.x)*model.cf/1000 + summation(model.k) *model.cPS
model.Obj = Objective(rule=ObjectiveFunction, sense=minimize)
#############Solve model##################
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\Gisele_MILP\cbc')
opt = SolverFactory('gurobi')
# opt.options['numericfocus']=0
# opt.options['mipgap'] = 0.0002
# opt.options['presolve']=2
# opt.options['mipfocus']=2
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\New folder\cbc')
print('Starting optimization process')
time_i = datetime.now()
opt.solve(instance, tee=True, symbolic_solver_labels=True)
time_f = datetime.now()
print('Time required for optimization is', time_f - time_i)
links = instance.x
power = instance.P
subs = instance.k
voltage = instance.E
PS = instance.PPS
mg_output = instance.MG_output
microGrid = instance.z
DISTANCE = instance.Distance
links_clusters = instance.links_clusters
# voltage_drop=instance.z
connections_output = pd.DataFrame(columns=[['id1', 'id2', 'power']])
PrSubstation = pd.DataFrame(columns=[['index', 'power']])
all_lines = pd.DataFrame(columns=[['id1', 'id2', 'power']])
Voltages = pd.DataFrame(columns=[['index', 'voltage [p.u]']])
Microgrid = pd.DataFrame(columns=[['index', 'microgrid', 'power']])
distance = pd.DataFrame(columns=[['index', 'length[km]']])
Links_Clusters = pd.DataFrame(columns=[['id1', 'id2', 'power']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in subs:
if int(round(value(subs[index]))) == 1:
PrSubstation.loc[k, 'index'] = index
PrSubstation.loc[k, 'power'] = value(PS[index])
print(((value(PS[index]))))
k = k + 1
k = 0
for v in voltage:
Voltages.loc[k, 'index'] = v
Voltages.loc[k, 'voltage [p.u]'] = value(voltage[v])
k = k + 1
k = 0
for index in power:
all_lines.loc[k, 'id1'] = index[0]
all_lines.loc[k, 'id2'] = index[1]
all_lines.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in mg_output:
Microgrid.loc[k, 'index'] = index
Microgrid.loc[k, 'microgrid'] = value(microGrid[index])
Microgrid.loc[k, 'power'] = value(mg_output[index])
k = k + 1
k = 0
for dist in DISTANCE:
distance.loc[k, 'index'] = dist
distance.loc[k, 'length[m]'] = value(DISTANCE[dist])
k = k + 1
k = 0
for index in links_clusters:
Links_Clusters.loc[k, 'id1'] = index[0]
Links_Clusters.loc[k, 'id2'] = index[1]
Links_Clusters.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for dist in DISTANCE:
distance.loc[k, 'index'] = dist
distance.loc[k, 'length[m]'] = value(DISTANCE[dist])
k = k + 1
Links_Clusters.to_csv(MILP_output_folder + '/links_clusters.csv', index=False)
connections_output.to_csv(MILP_output_folder + '/connections_output.csv', index=False)
PrSubstation.to_csv(MILP_output_folder + '/PrimarySubstations.csv', index=False)
Voltages.to_csv(MILP_output_folder + '/Voltages.csv', index=False)
all_lines.to_csv(MILP_output_folder + '/all_lines.csv', index=False)
Microgrid.to_csv(MILP_output_folder + '/Microgrid.csv', index=False)
distance.to_csv(MILP_output_folder + '/Distances.csv', index=False)
def MILP_multiobjective(p_max_lines, coe, nation_emis, nation_rel, line_rel,input_michele):
# useful parameters from michele
proj_lifetime = input_michele['num_years']
nren = 3
# Initialize model
model = AbstractModel()
data = DataPortal()
# Define sets
model.of = Set(initialize=['cost', 'emis', 'rel']) # Set of objective functions
model.N = Set() # Set of all nodes, clusters and substations
data.load(filename=r'Output/LCOE/set.csv', set=model.N)
model.clusters = Set() # Set of clusters
data.load(filename='Output/LCOE/clusters.csv', set=model.clusters)
model.renfr = RangeSet(0, nren - 1,1) # set of microgrids with different ren fractions
model.mg = Set(dimen=2, within=model.clusters * model.renfr)
model.substations = Set() # Set of substations
data.load(filename='Output/LCOE/subs.csv', set=model.substations)
model.links = Set(dimen=2,within=model.N * model.N) # in the csv the values must be delimited by commas
data.load(filename='Output/LCOE/possible_links_complete.csv',set=model.links)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
def NodesOutSub_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOutSub = Set(model.substations, initialize=NodesOutSub_init)
def NodesInSub_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesInSub = Set(model.substations, initialize=NodesInSub_init)
#####################Define parameters#####################
# Direction of optimization for each objective function: -1 to minimize, +1 to maximize
model.dir = Param(model.of)
# Weight of objective functions in multi-objective optimization, range 0-1, sum over model.of has to be 1
model.weight = Param(model.of)
data.load(filename='Output/LCOE/data_MO.dat')
# Parameters identifying the range of variation of each objective function (needed for normalization)
model.min_obj = Param(model.of, initialize=0, mutable=True)
model.max_obj = Param(model.of, initialize=1, mutable=True)
# Electric power in the nodes (injected (-) or absorbed (+))
model.p_clusters = Param(model.clusters)
data.load(filename='Output/LCOE/c_power.csv', param=model.p_clusters)
# Maximum power supplied by substations
model.p_max_substations = Param(model.substations)
data.load(filename='Output/LCOE/sub_power.csv',
param=model.p_max_substations)
# Total net present cost of microgrid to supply each cluster
model.c_microgrids = Param(model.mg)
# data.load(filename='Output/LCOE/c_npc.csv', param=model.c_microgrids)
# Total net present cost of substations
model.c_substations = Param(model.substations)
data.load(filename='Output/LCOE/sub_npc.csv',
param=model.c_substations)
# Connection cost of the possible links
model.c_links = Param(model.links)
data.load(filename='Output/LCOE/cost_links_complete.csv',
param=model.c_links)
# Energy consumed by each cluster in microgrid lifetime
model.energy = Param(model.mg)
# data.load(filename='Output/LCOE/energy.csv', param=model.energy)
# CO2 emission produced by each cluster in microgrid lifetime
model.emission = Param(model.mg)
# data.load(filename='Output/LCOE/emissions.csv', param=model.emission)
# CO2 emission related to construction of power infrastructure
model.em_links = Param(model.links)
data.load(filename='Output/LCOE/em_links.csv', param=model.em_links)
# lol due to microgrid components_failure
model.rel_mg = Param(model.mg)
# data.load(filename='Output/LCOE/mg_rel.csv', param=model.rel_mg)
# Connection length associated to the nodes
# todo->put the real length
model.d_nodes = Param(model.N)
data.load(filename='Output/LCOE/len_nodes.csv', param=model.d_nodes)
# Connection length of the possible links
model.d_links = Param(model.links)
data.load(filename='Output/LCOE/len_links_complete.csv',
param=model.d_links)
# poximum power flowing on lines
# model.p_max_lines = Param() # max power flowing on MV lines
# data.load(filename='Input/data_procedure2.dat')
# M_max and M_min, values required to linearize the problem
model.M_max = Param(initialize=10000)
model.M_min = Param(initialize=-10000)
data.load(filename='Output/Microgrids/microgrids.csv',
select=(
'Cluster', 'Renewable fraction index', 'Total Cost [kEUR]',
'Energy Demand [MWh]', 'CO2 [kg]', 'Unavailability [MWh/y]'),
param=(model.c_microgrids, model.energy, model.emission,
model.rel_mg), index=model.mg)
#####################Define variables#####################
# objective function variables
model.obj = Var(model.of, within=NonNegativeReals)
# auxiliary variables for normalization step
model.aux = Var(model.of)
# normalized objective functions
model.norm_obj = Var(model.of, within=NonNegativeReals)
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise,initialize=x_rule
model.x = Var(model.links, within=Binary)
# binary variable y[i]: 1 if a substation is installed in node i, 0 otherwise,initialize=y_rule
model.y = Var(model.substations, within=Binary)
# binary variable z[i]: 1 if a microgrid is installed in node i, 0 otherwise,initialize=z_rule
model.z = Var(model.mg, within=Binary)
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links, within=NonNegativeReals)
# power[i] is the power provided by substation i
model.p_substations = Var(model.substations, within=NonNegativeReals)
# # variables k(i,j) is the variable necessary to linearize
model.k = Var(model.links)
# distance of cluster from substation
model.dist = Var(model.N, within=NonNegativeReals)
# lol due to MV lines
model.lol_line = Var(model.clusters, within=NonNegativeReals)
#####################Define constraints###############################
def Radiality_rule(model):
return summation(model.x) == len(model.clusters) - summation(
model.z)
model.Radiality = Constraint(
rule=Radiality_rule) # all the clusters are either connected to the MV grid or powered by microgrid
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j]
for j in model.NodesOut[node])) == +model.p_clusters[node] * (
1 - sum(model.z[node, j] for j in model.renfr))
model.Power_flow_conservation = Constraint(model.clusters,
rule=Power_flow_conservation_rule) # when the node is powered by SHS all the power is transferred to the outgoing link
def PS_Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j]
for j in model.NodesOut[node])) == -model.p_substations[node]
model.PS_Power_flow_conservation = Constraint(model.substations,
rule=PS_Power_flow_conservation_rule) # outgoing power from PS to connected links
def Power_upper_bounds_rule(model, i, j):
return model.P[i, j] <= p_max_lines * model.x[i, j]
model.upper_Power_limits = Constraint(model.links,
rule=Power_upper_bounds_rule) # limit to power flowing on MV lines
def Power_lower_bounds_rule(model, i, j):
return model.P[i, j] >= -p_max_lines * model.x[i, j]
model.lower_Power_limits = Constraint(model.links,
rule=Power_lower_bounds_rule)
def Primary_substation_upper_bound_rule(model, i):
return model.p_substations[i] <= model.p_max_substations[i] * \
model.y[i]
model.Primary_substation_upper_bound = Constraint(model.substations,
rule=Primary_substation_upper_bound_rule) # limit to power of PS
def Number_substations_rule(model, node):
return model.y[node] <= sum(
model.x[j, node] for j in model.NodesInSub[node]) + \
sum(model.x[node, j] for j in model.NodesOutSub[node])
model.Number_substation = Constraint(model.substations,
rule=Number_substations_rule)
def Limit_mg_rule(model, i):
return sum(model.z[i, j] for j in model.renfr) <= 1
model.Limit_mg = Constraint(model.clusters, rule=Limit_mg_rule)
#### Distance constraints #####
def distance_balance_rule(model, i, j):
return model.k[i, j] == (-model.d_links[i, j] - model.d_nodes[i]) * \
model.x[i, j]
model.distance_balance_rule = Constraint(model.links,
rule=distance_balance_rule)
def distance_linearization_rule_1(model, i, j):
return model.k[i, j] <= model.M_max * model.x[i, j]
model.distance_linearization_rule_1 = Constraint(model.links,
rule=distance_linearization_rule_1)
#
def distance_linearization_rule_2(model, i, j):
return model.k[i, j] >= model.M_min * model.x[i, j]
model.distance_linearization_rule_2 = Constraint(model.links,
rule=distance_linearization_rule_2)
#
def distance_linearization_rule_3(model, i, j):
return model.dist[i] - model.dist[j] - (
1 - model.x[i, j]) * model.M_max <= \
model.k[i, j]
model.distance_linearization_rule_3 = Constraint(model.links,
rule=distance_linearization_rule_3)
def distance_linearization_rule_4(model, i, j):
return model.dist[i] - model.dist[j] - (
1 - model.x[i, j]) * model.M_min >= \
model.k[i, j]
model.distance_linearization_rule_4 = Constraint(model.links,
rule=distance_linearization_rule_4)
def distance_linearization_rule_5(model, i, j):
return model.dist[i] - model.dist[j] + (
1 - model.x[i, j]) * model.M_max >= \
model.k[i, j]
model.distance_linearization_rule_5 = Constraint(model.links,
rule=distance_linearization_rule_5)
# if a cluster is electrified with a microgrid, its distance is 0,
# otherwise it must be less than a max treshold
def distance_upper_bound_rule(model, i, j):
return 100 * (1 - model.z[i, j]) >= model.dist[i]
model.distance_upper_bound = Constraint(model.clusters, model.renfr,
rule=distance_upper_bound_rule)
def distance_primary_substation_rule(model, i):
return model.dist[i] == 0
model.distance_primary_substation = Constraint(model.substations,
rule=distance_primary_substation_rule)
# define loss of load dependent on distance from connection point
def lol_calculation_rule(model, i):
return model.lol_line[i] == model.dist[i] * line_rel * \
model.energy[i, 1] / 8760 / proj_lifetime
model.lol_calculation = Constraint(model.clusters,
rule=lol_calculation_rule)
####################Define objective function##########################
# total npc over microgrid lifetime
def ObjectiveFunctionCost(model):
return model.obj['cost'] == summation(model.c_microgrids, model.z) \
+ summation(model.c_substations, model.y) + summation(
model.c_links, model.x) \
+ sum(model.energy[i, 1] * (
1 - sum(model.z[i, j] for j in model.renfr)) for i in
model.clusters) * coe
model.Obj1 = Constraint(rule=ObjectiveFunctionCost)
# total direct emissions over microgrid lifetime
def ObjectiveFunctionEmis(model):
return model.obj['emis'] == summation(model.emission, model.z) + \
summation(model.em_links, model.x) + \
sum(model.energy[i, 1] * (
1 - sum(model.z[i, j] for j in model.renfr)) for
i in model.clusters) * nation_emis
model.Obj2 = Constraint(rule=ObjectiveFunctionEmis)
# minimization of total energy not supplied [MWh]
def ObjectiveFunctionRel(model):
return model.obj['rel'] == \
sum(model.rel_mg[i] * (model.z[i]) for i in model.mg) + \
summation(model.lol_line) + \
sum(model.energy[i, 1] / 8760 / proj_lifetime * (
1 - sum(model.z[i, j] for j in model.renfr)) for
i in model.clusters) * nation_rel
model.Obj3 = Constraint(rule=ObjectiveFunctionRel)
# auxiliary variable to allow the activation and deactivation of OF in the for loop
def AuxiliaryNorm(model, of):
return model.aux[of] == model.dir[of] * model.obj[of]
model.AuxNorm = Constraint(model.of, rule=AuxiliaryNorm)
# aux is null for the OF not optimized in the loop
def NullAuxiliary(model, of):
return model.aux[of] == 0
model.NullAux = Constraint(model.of, rule=NullAuxiliary)
# objective function for identification of ranges of objective functions (needed for normalization)
def ObjectiveFunctionNorm(model):
return sum(model.aux[of] for of in model.of)
model.ObjNorm = Objective(rule=ObjectiveFunctionNorm, sense=maximize)
# normalized objective functions
def DefineNormalizedObj(model, of):
if model.dir[of] == 1:
return model.norm_obj[of] == (
model.obj[of] - model.min_obj[of]) / (
model.max_obj[of] - model.min_obj[of])
else:
return model.norm_obj[of] == (
model.max_obj[of] - model.obj[of]) / (
model.max_obj[of] - model.min_obj[of])
model.DefNormObj = Constraint(model.of, rule=DefineNormalizedObj)
# multi-objective optimization through weighted sum approach
def MultiObjective(model):
return summation(model.weight, model.norm_obj)
model.MultiObj = Objective(rule=MultiObjective, sense=maximize)
#############Solve model##################
# opt = SolverFactory('cplex',executable=r'C:\Users\silvi\IBM\ILOG\CPLEX_Studio1210\cplex\bin\x64_win64\cplex')
# opt = SolverFactory('glpk')
opt = SolverFactory('gurobi')
opt.options['mipgap'] = 0.01
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
obj_list = list(instance.of) # list of the objective functions
print(obj_list)
num_of = len(obj_list) # number of objective functions
# payoff_table = np.empty((num_of,num_of)) # table of the ranges of variations of objective functions
payoff_table = pd.DataFrame(index=obj_list, columns=obj_list)
payoff_table.index.name = 'optimization'
# for the first step, ObjNorm is the OF to be used
instance.MultiObj.deactivate()
instance.ObjNorm.activate()
instance.DefNormObj.deactivate()
print(
'1) Optimizing one objective function at a time to identify ranges of variations')
time_i = datetime.now()
for of in obj_list:
# for of in instance.of:
print('Optimize ' + of)
instance.NullAux.activate()
instance.NullAux[of].deactivate()
instance.AuxNorm.deactivate()
instance.AuxNorm[of].activate()
opt.solve(instance, tee=True)
payoff_of = []
for i in obj_list:
p_of = float(instance.obj.get_values()[i])
payoff_of.append(p_of)
payoff_table.loc[of, :] = payoff_of
print(payoff_table)
multi_obj = True
k = 0
print('Find ranges of variation of each objective function:')
for of in obj_list:
instance.min_obj[of] = min(payoff_table[of])
instance.max_obj[of] = max(payoff_table[of])
print('min' + str(of) + '=' + str(min(payoff_table[of])))
print('max' + str(of) + '=' + str(max(payoff_table[of])))
# do not make multiobjective optimization if there is a unique solution
# that means if all objective functions do not change
if instance.min_obj[of] == instance.max_obj[of]:
k = k + 1
if k == num_of:
multi_obj = False
print('Multi-obj not needed')
# for the second step, MultiObj is the OF to be used
instance.NullAux.deactivate()
instance.AuxNorm.deactivate()
instance.ObjNorm.deactivate()
instance.MultiObj.activate()
instance.DefNormObj.activate()
if multi_obj:
print('2) Multi-objective optimization: Weighted sum approach')
opt.solve(instance, tee=True)
for of in obj_list:
print(str(of) + '=' + str(instance.obj.get_values()[of]))
time_f = datetime.now()
print('Time required for the two steps is', time_f - time_i)
###################Process results#######################
links = instance.x
power = instance.P
microgrids = instance.z
distance = instance.dist
lol_line = instance.lol_line
connections_output = pd.DataFrame(columns=[['id1', 'id2']])
microgrids_output = pd.DataFrame(
columns=['Cluster', 'Renewable fraction'])
power_output = pd.DataFrame(columns=[['id1', 'id2', 'P']])
dist_output = pd.DataFrame(columns=[['ID', 'dist', 'lol']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
k = k + 1
k = 0
for index in microgrids:
if int(round(value(microgrids[index]))) == 1:
microgrids_output.loc[k, 'Cluster'] = index[0]
microgrids_output.loc[k, 'Renewable fraction'] = index[1]
k = k + 1
k = 0
for index in power:
if value(power[index]) != 0:
power_output.loc[k, 'id1'] = index[0]
power_output.loc[k, 'id2'] = index[1]
power_output.loc[k, 'P'] = value(power[index])
k = k + 1
k = 0
for index in distance:
if value(distance[index]) != 0:
dist_output.loc[k, 'ID'] = index
dist_output.loc[k, 'dist'] = value(distance[index])
dist_output.loc[k, 'lol'] = value(lol_line[index])
k = k + 1
connections_output.to_csv('Output/LCOE/MV_connections_output.csv',
index=False)
microgrids_output.to_csv('Output/LCOE/MV_SHS_output.csv', index=False)
power_output.to_csv('Output/LCOE/MV_power_output.csv', index=False)
dist_output.to_csv('Output/LCOE/MV_dist_output.csv', index=False)
return microgrids_output, connections_output
def MILP_MG_noRel(gisele_folder,case_study,n_clusters,coe,voltage,resistance,reactance,Pmax,line_cost):
model = AbstractModel()
data = DataPortal()
MILP_input_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_input'
MILP_output_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_output'
os.chdir(MILP_input_folder)
# ####################Define sets#####################
# Define some basic parameter for the per unit conversion and voltage limitation
Abase = 1
Vmin = 0.9
# Name of all the nodes (primary and secondary substations)
model.N = Set()
data.load(filename='nodes.csv', set=model.N) # first row is not read
model.N_clusters = Set()
data.load(filename='nodes_clusters.csv', set=model.N_clusters)
model.N_MG = Set()
data.load(filename='microgrids_nodes.csv', set=model.N_MG)
model.N_PS = Set()
data.load(filename='nodes_PS.csv', set=model.N_PS)
# Node corresponding to primary substation
# Allowed connections
model.links = Set(dimen=2) # in the csv the values must be delimited by commas
data.load(filename='links_all.csv', set=model.links)
model.links_clusters = Set(dimen=2)
data.load(filename='links_clusters.csv', set=model.links_clusters)
model.links_decision = Set(dimen=2)
data.load(filename='links_decision.csv', set=model.links_decision)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
#####################Define parameters#####################
# Electric power in the nodes (injected (-) or absorbed (+))
model.Psub = Param(model.N_clusters)
data.load(filename='power_nodes.csv', param=model.Psub)
# model.PS=Param(model.N)
# data.load(filename='PS.csv',param=model.PS)
model.microgrid_power = Param(model.N_MG)
data.load(filename='microgrids_powers.csv', param=model.microgrid_power)
model.energy = Param(model.N_MG)
data.load(filename='energy.csv', param=model.energy)
# TODO also calculate npv
model.mg_cost = Param(model.N_MG)
data.load(filename='microgrids_costs.csv', param=model.mg_cost)
# TODO also calculate npv
model.ps_cost = Param(model.N_PS)
data.load(filename='PS_costs.csv', param=model.ps_cost)
model.PSmax = Param(model.N_PS)
data.load(filename='PS_power_max.csv', param=model.PSmax)
model.PS_voltage = Param(model.N_PS)
data.load(filename='PS_voltage.csv', param=model.PS_voltage)
# Power of the primary substation as sum of all the other powers
# def PPS_init(model):
# return sum(model.Psub[i] for i in model.N)
# model.PPS=Param(model.PS,initialize=PPS_init)
# Connection distance of all the edges
model.dist = Param(model.links)
data.load(filename='distances.csv', param=model.dist)
#TODO use the npv cost of the lines
model.weights = Param(model.links_decision)
data.load(filename='weights_decision_lines.csv', param=model.weights)
#data.load(filename='weights_decision_lines_npv.csv', param=model.weights)
# Electrical parameters of all the cables
model.V_ref = Param(initialize=voltage)
model.A_ref = Param(initialize=Abase)
model.E_min = Param(initialize=Vmin)
model.R_ref = Param(initialize=resistance)
model.X_ref = Param(initialize=reactance)
model.P_max = Param(initialize=Pmax)
model.cf = Param(initialize=line_cost)
model.Z = Param(initialize=model.R_ref + model.X_ref * 0.5)
model.Z_ref = Param(initialize=model.V_ref ** 2 / Abase)
model.n_clusters = Param(initialize=n_clusters)
model.coe = Param(initialize=coe)
#####################Define variables#####################
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise
model.x = Var(model.links_decision, within=Binary)
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links)
# positive variables E(i) is p.u. voltage at each node
model.E = Var(model.N, within=NonNegativeReals)
# microgrid
model.z = Var(model.N_MG, within=Binary)
# binary variable k[i]: 1 if node i is a primary substation, 0 otherwise
model.k = Var(model.N_PS, within=Binary)
# Power output of Primary substation
model.PPS = Var(model.N_PS, within=NonNegativeReals)
model.MG_output = Var(model.N_MG)
#####################Define constraints###############################
# def Make_problem_easy(model,i,j):
# return model.x[i,j]+model.weights[i,j]>=1
# model.easy = Constraint(model.links, rule=Make_problem_easy)
def Radiality_rule(model):
# return summation(model.x)==len(model.N)-summation(model.k)
return summation(model.x) == model.n_clusters
model.Radiality = Constraint(rule=Radiality_rule)
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == model.Psub[node]
model.Power_flow_conservation = Constraint(model.N_clusters, rule=Power_flow_conservation_rule)
def Power_flow_conservation_rule2(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.MG_output[node]
model.Power_flow_conservation2 = Constraint(model.N_MG, rule=Power_flow_conservation_rule2)
def Power_flow_conservation_rule3(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.PPS[node]
model.Power_flow_conservation3 = Constraint(model.N_PS, rule=Power_flow_conservation_rule3)
def Power_upper_decision(model, i, j):
return model.P[i, j] <= model.P_max * model.x[i, j]
model.Power_upper_decision = Constraint(model.links_decision, rule=Power_upper_decision)
def Power_lower_decision(model, i, j):
return model.P[i, j] >= -model.P_max * model.x[i, j]
model.Power_lower_decision = Constraint(model.links_decision, rule=Power_lower_decision)
def Power_upper_clusters(model, i, j):
return model.P[i, j] <= model.P_max
model.Power_upper_clusters = Constraint(model.links_clusters, rule=Power_upper_clusters)
def Power_lower_clusters(model, i, j):
return model.P[i, j] >= -model.P_max
model.Power_lower_clusters = Constraint(model.links_clusters, rule=Power_lower_clusters)
# Voltage constraints
def Voltage_balance_rule(model, i, j):
return (model.E[i] - model.E[j]) + model.x[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule = Constraint(model.links_decision, rule=Voltage_balance_rule)
def Voltage_balance_rule2(model, i, j):
return (model.E[i] - model.E[j]) - model.x[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule2 = Constraint(model.links_decision, rule=Voltage_balance_rule2)
def Voltage_balance_rule3(model, i, j):
return (model.E[i] - model.E[j]) <= model.dist[i, j] / 1000 * model.P[i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule3 = Constraint(model.links_clusters, rule=Voltage_balance_rule3)
def Voltage_balance_rule4(model, i, j):
return (model.E[i] - model.E[j]) >= model.dist[i, j] / 1000 * model.P[i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule4 = Constraint(model.links_clusters, rule=Voltage_balance_rule4)
def Voltage_limit(model, i):
return model.E[i] >= model.k[i] * (model.PS_voltage[i] - model.E_min) + model.E_min
model.Voltage_limit = Constraint(model.N_PS, rule=Voltage_limit)
def Voltage_PS2(model, i):
return model.E[i] <= model.PS_voltage[i]
model.Voltage_PS2 = Constraint(model.N_PS, rule=Voltage_PS2)
def Voltage_limit_MG(model, i):
return model.E[i] <= 1
model.Voltage_limit_MG = Constraint(model.N_MG, rule=Voltage_limit_MG)
def Voltage_limit_MG2(model, i):
return model.E[i] >= model.z[i] * (1 - model.E_min) + model.E_min
model.Voltage_limit_MG2 = Constraint(model.N_MG, rule=Voltage_limit_MG2)
def Voltage_limit_clusters2(model, i):
return model.E[i] >= model.E_min
model.Voltage_limit_clusters2 = Constraint(model.N_clusters, rule=Voltage_limit_clusters2)
def PS_power_rule_upper(model, i):
return model.PPS[i] <= model.PSmax[i] * model.k[i]
model.PS_power_upper = Constraint(model.N_PS, rule=PS_power_rule_upper)
def Balance_rule(model):
return (sum(model.PPS[i] for i in model.N_PS) + sum(model.MG_output[i] for i in model.N_MG) - sum(
model.Psub[i] for i in model.N_clusters)) == 0
model.Balance = Constraint(rule=Balance_rule)
def MG_power_limit(model, i):
return model.MG_output[i] == model.z[i] * model.microgrid_power[i]
model.MG_power_limit = Constraint(model.N_MG, rule=MG_power_limit)
####################Define objective function##########################
print(coe)
def ObjectiveFunction(model):
# model.weights is in euro, model.coe is euro/MWh,
return summation(model.weights, model.x) + summation(model.mg_cost, model.z) * 1000 + \
sum(model.energy[i] * (1 - model.z[i]) for i in model.N_MG) * model.coe + summation(model.ps_cost,
model.k)
# +sum((model.P[i]/model.A_ref)**2*0.5*1.25*model.R_ref/model.Z_ref*model.dist[i]/1000*24*365*20 for i in model.links)
# return summation(model.dist,model.x)*model.cf/1000 + summation(model.k) *model.cPS
model.Obj = Objective(rule=ObjectiveFunction, sense=minimize)
#############Solve model##################
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\Gisele_MILP\cbc')
opt = SolverFactory('gurobi')
# opt.options['numericfocus']=0
opt.options['mipgap'] = 0.02
opt.options['presolve']=2
# opt.options['mipfocus'] = 3
print('Starting optimization process')
time_i = datetime.now()
opt.solve(instance, tee=True, symbolic_solver_labels=True)
time_f = datetime.now()
print('Time required for optimization is', time_f - time_i)
links = instance.x
power = instance.P
subs = instance.k
voltage = instance.E
PS = instance.PPS
mg_output = instance.MG_output
microGrid = instance.z
links_clusters = instance.links_clusters
# voltage_drop=instance.z
connections_output = pd.DataFrame(columns=[['id1', 'id2', 'power']])
PrSubstation = pd.DataFrame(columns=[['index', 'power']])
all_lines = pd.DataFrame(columns=[['id1', 'id2', 'power']])
Voltages = pd.DataFrame(columns=[['index', 'voltage [p.u]']])
Microgrid = pd.DataFrame(columns=[['index', 'microgrid', 'power']])
Links_Clusters = pd.DataFrame(columns=[['id1', 'id2', 'power']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in subs:
if int(round(value(subs[index]))) == 1:
PrSubstation.loc[k, 'index'] = index
PrSubstation.loc[k, 'power'] = value(PS[index])
print(((value(PS[index]))))
k = k + 1
k = 0
for v in voltage:
Voltages.loc[k, 'index'] = v
Voltages.loc[k, 'voltage [p.u]'] = value(voltage[v])
k = k + 1
k = 0
for index in power:
all_lines.loc[k, 'id1'] = index[0]
all_lines.loc[k, 'id2'] = index[1]
all_lines.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in mg_output:
Microgrid.loc[k, 'index'] = index
Microgrid.loc[k, 'microgrid'] = value(microGrid[index])
Microgrid.loc[k, 'power'] = value(mg_output[index])
k = k + 1
k = 0
for index in links_clusters:
Links_Clusters.loc[k, 'id1'] = index[0]
Links_Clusters.loc[k, 'id2'] = index[1]
Links_Clusters.loc[k, 'power'] = value(power[index])
k = k + 1
Links_Clusters.to_csv(MILP_output_folder + '/links_clusters.csv', index=False)
connections_output.to_csv(MILP_output_folder + '/connections_output.csv', index=False)
PrSubstation.to_csv(MILP_output_folder + '/PrimarySubstations.csv', index=False)
Voltages.to_csv(MILP_output_folder + '/Voltages.csv', index=False)
all_lines.to_csv(MILP_output_folder + '/all_lines.csv', index=False)
Microgrid.to_csv(MILP_output_folder + '/Microgrid.csv', index=False)
# k=0
# for index in links:
# if int(round(value(links[index])))==1:
# Voltage_drop.loc[k,'id1']=index[0]
# Voltage_drop.loc[k,'id2']=index[1]
# Voltage_drop.loc[k,'v_drop']=value(voltage_drop[index])
# k=k+1
# Voltage_drop.to_csv('MILP_results/solution_new/Voltage_drops.csv',index=False)
def MILP_MG_2cables(gisele_folder,case_study,n_clusters,coe,voltage,resistance,reactance,Pmax,line_cost,
resistance2,reactance2,Pmax2,line_cost2):
############ Create abstract model ###########
model = AbstractModel()
data = DataPortal()
MILP_input_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_input'
MILP_output_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_output'
os.chdir(MILP_input_folder)
# ####################Define sets#####################
# Define some basic parameter for the per unit conversion and voltage limitation
Abase = 1
Vmin = 0.9
# Name of all the nodes (primary and secondary substations)
model.N = Set()
data.load(filename='nodes.csv', set=model.N) # first row is not read
model.N_clusters = Set()
data.load(filename='nodes_clusters.csv', set=model.N_clusters)
model.N_MG = Set()
data.load(filename='microgrids_nodes.csv', set=model.N_MG)
model.N_PS = Set()
data.load(filename='nodes_PS.csv', set=model.N_PS)
# Node corresponding to primary substation
# Allowed connections
model.links = Set(dimen=2) # in the csv the values must be delimited by commas
data.load(filename='links_all.csv', set=model.links)
model.links_clusters = Set(dimen=2)
data.load(filename='links_clusters.csv', set=model.links_clusters)
model.links_decision = Set(dimen=2)
data.load(filename='links_decision.csv', set=model.links_decision)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
#####################Define parameters#####################
# Electric power in the nodes (injected (-) or absorbed (+))
model.Psub = Param(model.N_clusters)
data.load(filename='power_nodes.csv', param=model.Psub)
# model.PS=Param(model.N)
# data.load(filename='PS.csv',param=model.PS)
model.microgrid_power = Param(model.N_MG)
data.load(filename='microgrids_powers.csv', param=model.microgrid_power)
model.energy = Param(model.N_MG)
data.load(filename='energy.csv', param=model.energy)
model.mg_cost = Param(model.N_MG)
data.load(filename='microgrids_costs.csv', param=model.mg_cost)
model.ps_cost = Param(model.N_PS)
data.load(filename='PS_costs.csv', param=model.ps_cost)
model.PSmax = Param(model.N_PS)
data.load(filename='PS_power_max.csv', param=model.PSmax)
model.PS_voltage = Param(model.N_PS)
data.load(filename='PS_voltage.csv', param=model.PS_voltage)
# Power of the primary substation as sum of all the other powers
# def PPS_init(model):
# return sum(model.Psub[i] for i in model.N)
# model.PPS=Param(model.PS,initialize=PPS_init)
# Connection distance of all the edges
model.dist = Param(model.links)
data.load(filename='distances.csv', param=model.dist)
model.weights = Param(model.links_decision)
data.load(filename='weights_decision_lines.csv', param=model.weights)
# Electrical parameters of all the cables
model.V_ref = Param(initialize=voltage)
model.A_ref = Param(initialize=Abase)
model.E_min = Param(initialize=Vmin)
model.R_ref = Param(initialize=resistance)
model.R_ref2 = Param(initialize=resistance2)
model.X_ref = Param(initialize=reactance)
model.X_ref2 = Param(initialize = reactance2)
model.P_max = Param(initialize=Pmax)
model.P_max2 = Param(initialize = Pmax2)
model.cf = Param(initialize=line_cost)
model.cf2 = Param(initialize = line_cost2)
model.Z = Param(initialize=model.R_ref + model.X_ref * 0.5)
model.Z2 = Param(initialize = model.Ref2+model.X_ref2 * 0.5)
model.Z_ref = Param(initialize=model.V_ref ** 2 / Abase)
model.n_clusters = Param(initialize=n_clusters)
model.coe = Param(initialize=coe)
#####################Define variables#####################
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise
model.x = Var(model.links_decision, within=Binary)
model.x1 = Var(model.links_decision, within=Binary)
model.y = Var(model.links_clusters, within=Binary)
# x is if decision link is of cable type 1, x1 if it is of cable type 2. On the other hand, y is simply 1 decision variable
# since we know that it is chosen, we just want to know if it's the better cable or not. So, we consider that the base cable is the smaller one,
# and we just add the additional power availability, voltage drop and cost.
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links)
# positive variables E(i) is p.u. voltage at each node
model.E = Var(model.N, within=NonNegativeReals)
# microgrid
model.z = Var(model.N_MG, within=Binary)
# binary variable k[i]: 1 if node i is a primary substation, 0 otherwise
model.k = Var(model.N_PS, within=Binary)
# Power output of Primary substation
model.PPS = Var(model.N_PS, within=NonNegativeReals)
model.MG_output = Var(model.N_MG)
model.delta_Pmax = model.P_max - model.P_max2
model.delta_Z = model.Z - model.Z2
model.delta_cf = model.cf - model.cf2
#####################Define constraints###############################
# def Make_problem_easy(model,i,j):
# return model.x[i,j]+model.weights[i,j]>=1
# model.easy = Constraint(model.links, rule=Make_problem_easy)
def Radiality_rule(model):
# return summation(model.x)==len(model.N)-summation(model.k)
return summation(model.x) + summation(model.x1) == model.n_clusters
model.Radiality = Constraint(rule=Radiality_rule)
def Radiality_rule(model):
return summation(model.k) + summation(model.z) <= model.n_clusters
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == model.Psub[node]
model.Power_flow_conservation = Constraint(model.N_clusters, rule=Power_flow_conservation_rule)
def Power_flow_conservation_rule2(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.MG_output[node]
model.Power_flow_conservation2 = Constraint(model.N_MG, rule=Power_flow_conservation_rule2)
def Power_flow_conservation_rule3(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.PPS[node]
model.Power_flow_conservation3 = Constraint(model.N_PS, rule=Power_flow_conservation_rule3)
def Power_upper_decision(model, i, j):
return model.P[i, j] <= model.P_max * model.x[i, j] + model.P_max2 * model.x1[i, j]
model.Power_upper_decision = Constraint(model.links_decision, rule=Power_upper_decision)
def Power_lower_decision(model, i, j):
return model.P[i, j] >= -model.P_max * model.x[i, j] - model.P_max2 * model.x1[i, j]
model.Power_lower_decision = Constraint(model.links_decision, rule=Power_lower_decision)
def Power_upper_clusters(model, i, j):
return model.P[i, j] <= model.P_max2 + model.y[i, j] * model.delta_Pmax
model.Power_upper_clusters = Constraint(model.links_clusters, rule=Power_upper_clusters)
def Power_lower_clusters(model, i, j):
return model.P[i, j] >= -model.P_max2 - model.y[i, j] * model.delta_Pmax
model.Power_lower_clusters = Constraint(model.links_clusters, rule=Power_lower_clusters)
# Voltage constraints
def Voltage_balance_rule(model, i, j):
return (model.E[i] - model.E[j]) + model.x[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule = Constraint(model.links_decision, rule=Voltage_balance_rule)
def Voltage_balance_rule11(model, i, j):
return (model.E[i] - model.E[j]) + model.x1[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z2 / model.Z_ref
model.Voltage_balance_rule11 = Constraint(model.links_decision, rule=Voltage_balance_rule11)
def Voltage_balance_rule2(model, i, j):
return (model.E[i] - model.E[j]) - model.x[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule2 = Constraint(model.links_decision, rule=Voltage_balance_rule2)
def Voltage_balance_rule22(model, i, j):
return (model.E[i] - model.E[j]) - model.x1[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z2 / model.Z_ref
model.Voltage_balance_rule22 = Constraint(model.links_decision, rule=Voltage_balance_rule22)
def Voltage_balance_rule3(model, i, j):
return (model.E[i] - model.E[j]) + model.y[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule3 = Constraint(model.links_clusters, rule=Voltage_balance_rule3)
def Voltage_balance_rule33(model, i, j):
return (model.E[i] - model.E[j]) - model.y[i, j] <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z2 / model.Z_ref
model.Voltage_balance_rule33 = Constraint(model.links_clusters, rule=Voltage_balance_rule33)
def Voltage_balance_rule4(model, i, j):
return (model.E[i] - model.E[j]) - model.y[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule4 = Constraint(model.links_clusters, rule=Voltage_balance_rule4)
def Voltage_balance_rule44(model, i, j):
return (model.E[i] - model.E[j]) + model.y[i, j] >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z2 / model.Z_ref
model.Voltage_balance_rule44 = Constraint(model.links_clusters, rule=Voltage_balance_rule44)
def Voltage_limit(model, i):
return model.E[i] >= model.k[i] * (model.PS_voltage[i] - model.E_min) + model.E_min
model.Voltage_limit = Constraint(model.N_PS, rule=Voltage_limit)
def Voltage_PS2(model, i):
return model.E[i] <= model.PS_voltage[i]
model.Voltage_PS2 = Constraint(model.N_PS, rule=Voltage_PS2)
def Voltage_limit_MG(model, i):
return model.E[i] <= 1
model.Voltage_limit_MG = Constraint(model.N_MG, rule=Voltage_limit_MG)
def Voltage_limit_MG2(model, i):
return model.E[i] >= model.z[i] * (1 - model.E_min) + model.E_min
model.Voltage_limit_MG2 = Constraint(model.N_MG, rule=Voltage_limit_MG2)
def Voltage_limit_clusters2(model, i):
return model.E[i] >= model.E_min
model.Voltage_limit_clusters2 = Constraint(model.N_clusters, rule=Voltage_limit_clusters2)
def PS_power_rule_upper(model, i):
return model.PPS[i] <= model.PSmax[i] * model.k[i]
model.PS_power_upper = Constraint(model.N_PS, rule=PS_power_rule_upper)
def Balance_rule(model):
return (sum(model.PPS[i] for i in model.N_PS) + sum(model.MG_output[i] for i in model.N_MG) - sum(
model.Psub[i] for i in model.N_clusters)) == 0
model.Balance = Constraint(rule=Balance_rule)
def anti_paralel(model, i, j):
return model.x[i, j] + model.x1[i, j] <= 1
model.anti_paralel = Constraint(model.links_decision, rule=anti_paralel)
def MG_power_limit(model, i):
return model.MG_output[i] == model.z[i] * model.microgrid_power[i]
model.MG_power_limit = Constraint(model.N_MG, rule=MG_power_limit)
####################Define objective function##########################
def ObjectiveFunction(model):
# return summation(model.weights, model.x) * model.cf / 1000 + summation(model.weights, model.x1) * model.cf2 / 10000
return summation(model.weights, model.x) * model.cf / 10000 + summation(model.mg_cost, model.z) * 1000 + sum(
model.energy[i] * (1 - model.z[i]) for i in model.N_MG) * model.coe \
+ summation(model.ps_cost, model.k) + summation(model.weights, model.x1) * model.cf2 / 10000 + sum(
model.y[i] for i in model.links_clusters) * model.delta_cf
model.Obj = Objective(rule=ObjectiveFunction, sense=minimize)
#############Solve model##################
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\Gisele_MILP\cbc')
opt = SolverFactory('gurobi')
# opt.options['numericfocus']=0
opt.options['mipgap'] = 0.01
opt.options['presolve'] = 2
# opt.options['mipfocus']=2
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\New folder\cbc')
print('Starting optimization process')
time_i = datetime.now()
opt.solve(instance, tee=True, symbolic_solver_labels=True)
time_f = datetime.now()
print('Time required for optimization is', time_f - time_i)
links = instance.x
links_small = instance.x1
power = instance.P
subs = instance.k
voltage = instance.E
PS = instance.PPS
mg_output = instance.MG_output
microGrid = instance.z
links_clusters_type = instance.y
links_clusters = instance.links_clusters
# voltage_drop=instance.z
connections_output = pd.DataFrame(columns=[['id1', 'id2', 'power', 'Type']])
PrSubstation = pd.DataFrame(columns=[['index', 'power']])
all_lines = pd.DataFrame(columns=[['id1', 'id2', 'power']])
Voltages = pd.DataFrame(columns=[['index', 'voltage [p.u]']])
Microgrid = pd.DataFrame(columns=[['index', 'microgrid', 'power']])
Links_Clusters = pd.DataFrame(columns=[['id1', 'id2', 'power', 'Type']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
connections_output.loc[k, 'Type'] = 'Large'
k = k + 1
elif int(round(value(links_small[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
connections_output.loc[k, 'Type'] = 'Small'
k = k + 1
k = 0
for index in subs:
if int(round(value(subs[index]))) == 1:
PrSubstation.loc[k, 'index'] = index
PrSubstation.loc[k, 'power'] = value(PS[index])
print(((value(PS[index]))))
k = k + 1
k = 0
for v in voltage:
Voltages.loc[k, 'index'] = v
Voltages.loc[k, 'voltage [p.u]'] = value(voltage[v])
k = k + 1
k = 0
for index in power:
all_lines.loc[k, 'id1'] = index[0]
all_lines.loc[k, 'id2'] = index[1]
all_lines.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in mg_output:
Microgrid.loc[k, 'index'] = index
Microgrid.loc[k, 'microgrid'] = value(microGrid[index])
Microgrid.loc[k, 'power'] = value(mg_output[index])
k = k + 1
k = 0
for index in links_clusters:
print(index)
Links_Clusters.loc[k, 'id1'] = index[0]
Links_Clusters.loc[k, 'id2'] = index[1]
Links_Clusters.loc[k, 'power'] = value(power[index])
if int(round(value(links_clusters_type[index]))) == 1:
Links_Clusters.loc[k, 'Type'] = 'Large'
else:
Links_Clusters.loc[k, 'Type'] = 'Small'
k = k + 1
Links_Clusters.to_csv(MILP_output_folder + '/links_clusters.csv', index=False)
connections_output.to_csv(MILP_output_folder + '/connections_output.csv', index=False)
PrSubstation.to_csv(MILP_output_folder + '/PrimarySubstations.csv', index=False)
Voltages.to_csv(MILP_output_folder + '/Voltages.csv', index=False)
all_lines.to_csv(MILP_output_folder + '/all_lines.csv', index=False)
Microgrid.to_csv(MILP_output_folder + '/Microgrid.csv', index=False)
# k=0
# for index in links:
# if int(round(value(links[index])))==1:
# Voltage_drop.loc[k,'id1']=index[0]
# Voltage_drop.loc[k,'id2']=index[1]
# Voltage_drop.loc[k,'v_drop']=value(voltage_drop[index])
# k=k+1
# Voltage_drop.to_csv('MILP_results/solution_new/Voltage_drops.csv',index=False)
def MILP_base_no_voltage(gisele_folder,case_study,n_clusters,coe,voltage,resistance,reactance,Pmax,line_cost):
############ Create abstract model ###########
model = AbstractModel()
data = DataPortal()
MILP_input_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_input'
MILP_output_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_output'
os.chdir(MILP_input_folder)
# Define some basic parameter for the per unit conversion and voltage limitation
Abase = 1
Vmin = 0.9
####################Define sets#####################
model.N = Set()
data.load(filename='nodes.csv', set=model.N) # first row is not read
model.N_clusters = Set()
data.load(filename='nodes_clusters.csv', set=model.N_clusters)
model.N_PS = Set()
data.load(filename='nodes_PS.csv', set=model.N_PS)
# Node corresponding to primary substation
# Allowed connections
model.links = Set(dimen=2) # in the csv the values must be delimited by commas
data.load(filename='links_all.csv', set=model.links)
model.links_clusters = Set(dimen=2)
data.load(filename='links_clusters.csv', set=model.links_clusters)
model.links_decision = Set(dimen=2)
data.load(filename='links_decision.csv', set=model.links_decision)
# Connection distance of all the edges
model.dist = Param(model.links)
data.load(filename='distances.csv', param=model.dist)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
#####################Define parameters#####################
# Electric power in the nodes (injected (-) or absorbed (+))
model.Psub = Param(model.N_clusters)
data.load(filename='power_nodes.csv', param=model.Psub)
model.ps_cost = Param(model.N_PS)
data.load(filename='PS_costs.csv', param=model.ps_cost)
model.PSmax = Param(model.N_PS)
data.load(filename='PS_power_max.csv', param=model.PSmax)
model.weights = Param(model.links_decision)
data.load(filename='weights_decision_lines.csv', param=model.weights)
# Electrical parameters of all the cables
model.V_ref = Param(initialize=voltage)
model.A_ref = Param(initialize=Abase)
model.E_min = Param(initialize=Vmin)
model.R_ref = Param(initialize=resistance)
model.X_ref = Param(initialize=reactance)
model.P_max = Param(initialize=Pmax)
model.cf = Param(initialize=line_cost)
model.Z = Param(initialize=model.R_ref + model.X_ref * 0.5)
model.Z_ref = Param(initialize=model.V_ref ** 2 / Abase)
model.n_clusters = Param(initialize=n_clusters)
model.coe = Param(initialize=coe)
#####################Define variables#####################
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise
model.x = Var(model.links_decision, within=Binary)
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links)
# binary variable k[i]: 1 if node i is a primary substation, 0 otherwise
model.k = Var(model.N_PS, within=Binary)
# Power output of Primary substation
model.PPS = Var(model.N_PS, within=NonNegativeReals)
model.cable_type = Var(model.links)
#####################Define constraints###############################
# Radiality constraint
def Radiality_rule(model):
return summation(model.x) == model.n_clusters
model.Radiality = Constraint(rule=Radiality_rule)
# Power flow constraints
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == model.Psub[node]
model.Power_flow_conservation = Constraint(model.N_clusters, rule=Power_flow_conservation_rule)
def Power_flow_conservation_rule3(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.PPS[node]
model.Power_flow_conservation3 = Constraint(model.N_PS, rule=Power_flow_conservation_rule3)
def Power_upper_decision(model, i, j):
return model.P[i, j] <= model.P_max * model.x[i, j]
model.Power_upper_decision = Constraint(model.links_decision, rule=Power_upper_decision)
def Power_lower_decision(model, i, j):
return model.P[i, j] >= -model.P_max * model.x[i, j]
model.Power_lower_decision = Constraint(model.links_decision, rule=Power_lower_decision)
def Power_upper_cluster(model, i, j):
return model.P[i, j] <= model.P_max
model.Power_upper_cluster = Constraint(model.links_clusters, rule=Power_upper_cluster)
def Power_lower_cluster(model, i, j):
return model.P[i, j] >= -model.P_max
model.Power_lower_cluster= Constraint(model.links_clusters, rule=Power_lower_cluster)
def PS_power_rule_upper(model, i):
return model.PPS[i] <= model.PSmax[i] * model.k[i]
model.PS_power_upper = Constraint(model.N_PS, rule=PS_power_rule_upper)
def Balance_rule(model):
return (sum(model.PPS[i] for i in model.N_PS) - sum(model.Psub[i] for i in model.N_clusters)) == 0
model.Balance = Constraint(rule=Balance_rule)
####################Define objective function##########################
####################Define objective function##########################
reliability_index = 1000
def ObjectiveFunction(model):
return summation(model.weights, model.x) * model.cf / 1000 + summation(model.ps_cost, model.k)
# return summation(model.weights, model.x) * model.cf / 1000 + summation(model.ps_cost,model.k) - sum(model.Psub[i]*model.Distance[i] for i in model.N_clusters)*reliability_index
model.Obj = Objective(rule=ObjectiveFunction, sense=minimize)
#############Solve model##################
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\Gisele_MILP\cbc')
opt = SolverFactory('gurobi')
opt.options['TimeLimit'] = 300
# opt.options['numericfocus']=0
# opt.options['mipgap'] = 0.0002
# opt.options['presolve']=2
# opt.options['mipfocus']=2
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\New folder\cbc')
print('Starting optimization process')
time_i = datetime.now()
opt.solve(instance, tee=True, symbolic_solver_labels=True)
time_f = datetime.now()
print('Time required for optimization is', time_f - time_i)
links = instance.x
power = instance.P
subs = instance.k
PS = instance.PPS
links_clusters = instance.links_clusters
# voltage_drop=instance.z
connections_output = pd.DataFrame(columns=[['id1', 'id2', 'power']])
PrSubstation = pd.DataFrame(columns=[['index', 'power']])
all_lines = pd.DataFrame(columns=[['id1', 'id2', 'power']])
Links_Clusters = pd.DataFrame(columns=[['id1', 'id2', 'power']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in subs:
if int(round(value(subs[index]))) == 1:
PrSubstation.loc[k, 'index'] = index
PrSubstation.loc[k, 'power'] = value(PS[index])
print(((value(PS[index]))))
k = k + 1
for index in power:
all_lines.loc[k, 'id1'] = index[0]
all_lines.loc[k, 'id2'] = index[1]
all_lines.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in links_clusters:
Links_Clusters.loc[k, 'id1'] = index[0]
Links_Clusters.loc[k, 'id2'] = index[1]
Links_Clusters.loc[k, 'power'] = value(power[index])
k = k + 1
Links_Clusters.to_csv(MILP_output_folder + '/links_clusters.csv', index=False)
connections_output.to_csv(MILP_output_folder + '/connections_output.csv', index=False)
PrSubstation.to_csv(MILP_output_folder + '/PrimarySubstations.csv', index=False)
all_lines.to_csv(MILP_output_folder + '/all_lines.csv', index=False)
def MILP_base(gisele_folder,case_study,n_clusters,coe,voltage,resistance,reactance,Pmax,line_cost):
############ Create abstract model ###########
model = AbstractModel()
data = DataPortal()
MILP_input_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_input'
MILP_output_folder = gisele_folder + '/Case studies/' + case_study + '/Intermediate/Optimization/MILP_output'
os.chdir(MILP_input_folder)
# Define some basic parameter for the per unit conversion and voltage limitation
Abase = 1
Vmin = 0.9
####################Define sets#####################
model.N = Set()
data.load(filename='nodes.csv', set=model.N) # first row is not read
model.N_clusters = Set()
data.load(filename='nodes_clusters.csv', set=model.N_clusters)
model.N_PS = Set()
data.load(filename='nodes_PS.csv', set=model.N_PS)
# Node corresponding to primary substation
# Allowed connections
model.links = Set(dimen=2) # in the csv the values must be delimited by commas
data.load(filename='links_all.csv', set=model.links)
model.links_clusters = Set(dimen=2)
data.load(filename='links_clusters.csv', set=model.links_clusters)
model.links_decision = Set(dimen=2)
data.load(filename='links_decision.csv', set=model.links_decision)
# Connection distance of all the edges
model.dist = Param(model.links)
data.load(filename='distances.csv', param=model.dist)
# Nodes are divided into two sets, as suggested in https://pyomo.readthedocs.io/en/stable/pyomo_modeling_components/Sets.html:
# NodesOut[nodes] gives for each node all nodes that are connected to it via outgoing links
# NodesIn[nodes] gives for each node all nodes that are connected to it via ingoing links
def NodesOut_init(model, node):
retval = []
for (i, j) in model.links:
if i == node:
retval.append(j)
return retval
model.NodesOut = Set(model.N, initialize=NodesOut_init)
def NodesIn_init(model, node):
retval = []
for (i, j) in model.links:
if j == node:
retval.append(i)
return retval
model.NodesIn = Set(model.N, initialize=NodesIn_init)
#####################Define parameters#####################
# Electric power in the nodes (injected (-) or absorbed (+))
model.Psub = Param(model.N_clusters)
data.load(filename='power_nodes.csv', param=model.Psub)
model.ps_cost = Param(model.N_PS)
data.load(filename='PS_costs.csv', param=model.ps_cost)
model.PSmax = Param(model.N_PS)
data.load(filename='PS_power_max.csv', param=model.PSmax)
model.PS_voltage = Param(model.N_PS)
data.load(filename='PS_voltage.csv', param=model.PS_voltage)
model.weights = Param(model.links_decision)
data.load(filename='weights_decision_lines.csv', param=model.weights)
# Electrical parameters of all the cables
model.V_ref = Param(initialize=voltage)
model.A_ref = Param(initialize=Abase)
model.E_min = Param(initialize=Vmin)
model.R_ref = Param(initialize=resistance)
model.X_ref = Param(initialize=reactance)
model.P_max = Param(initialize=Pmax)
model.cf = Param(initialize=line_cost)
model.Z = Param(initialize=model.R_ref + model.X_ref * 0.5)
model.Z_ref = Param(initialize=model.V_ref ** 2 / Abase)
model.n_clusters = Param(initialize=n_clusters)
model.coe = Param(initialize=coe)
#####################Define variables#####################
# binary variable x[i,j]: 1 if the connection i,j is present, 0 otherwise
model.x = Var(model.links_decision, within=Binary)
# power[i,j] is the power flow of connection i-j
model.P = Var(model.links)
# positive variables E(i) is p.u. voltage at each node
model.E = Var(model.N, within=NonNegativeReals)
# binary variable k[i]: 1 if node i is a primary substation, 0 otherwise
model.k = Var(model.N_PS, within=Binary)
# Power output of Primary substation
model.PPS = Var(model.N_PS, within=NonNegativeReals)
model.cable_type = Var(model.links)
#####################Define constraints###############################
# Radiality constraint
def Radiality_rule(model):
return summation(model.x) == model.n_clusters
model.Radiality = Constraint(rule=Radiality_rule)
# Power flow constraints
def Power_flow_conservation_rule(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == model.Psub[node]
model.Power_flow_conservation = Constraint(model.N_clusters, rule=Power_flow_conservation_rule)
def Power_flow_conservation_rule3(model, node):
return (sum(model.P[j, node] for j in model.NodesIn[node]) - sum(
model.P[node, j] for j in model.NodesOut[node])) == - model.PPS[node]
model.Power_flow_conservation3 = Constraint(model.N_PS, rule=Power_flow_conservation_rule3)
def Power_upper_decision(model, i, j):
return model.P[i, j] <= model.P_max * model.x[i, j]
model.Power_upper_decision = Constraint(model.links_decision, rule=Power_upper_decision)
def Power_lower_decision(model, i, j):
return model.P[i, j] >= -model.P_max * model.x[i, j]
model.Power_lower_decision = Constraint(model.links_decision, rule=Power_lower_decision)
def Power_upper_cluster(model, i, j):
return model.P[i, j] <= model.P_max
model.Power_upper_cluster = Constraint(model.links_clusters, rule=Power_upper_cluster)
def Power_lower_cluster(model, i, j):
return model.P[i, j] >= -model.P_max
model.Power_lower_cluster= Constraint(model.links_clusters, rule=Power_lower_cluster)
# Voltage constraints
def Voltage_balance_rule(model, i, j):
return (model.E[i] - model.E[j]) + model.x[i, j] - 1 <= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule = Constraint(model.links_decision, rule=Voltage_balance_rule)
def Voltage_balance_rule2(model, i, j):
return (model.E[i] - model.E[j]) - model.x[i, j] + 1 >= model.dist[i, j] / 1000 * model.P[
i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule2 = Constraint(model.links_decision, rule=Voltage_balance_rule2)
def Voltage_balance_rule3(model, i, j):
return (model.E[i] - model.E[j]) <= model.dist[i, j] / 1000 * model.P[i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule3 = Constraint(model.links_clusters, rule=Voltage_balance_rule3)
def Voltage_balance_rule4(model, i, j):
return (model.E[i] - model.E[j]) >= model.dist[i, j] / 1000 * model.P[i, j] * model.Z / model.Z_ref
model.Voltage_balance_rule4 = Constraint(model.links_clusters, rule=Voltage_balance_rule4)
def Voltage_limit(model, i):
return model.E[i] >= model.k[i] * (model.PS_voltage[i] - model.E_min) + model.E_min
model.Voltage_limit = Constraint(model.N_PS, rule=Voltage_limit)
def Voltage_PS2(model, i):
return model.E[i] <= model.PS_voltage[i]
model.Voltage_PS2 = Constraint(model.N_PS, rule=Voltage_PS2)
def Voltage_limit_clusters2(model, i):
return model.E[i] >= model.E_min
model.Voltage_limit_clusters2 = Constraint(model.N_clusters, rule=Voltage_limit_clusters2)
def PS_power_rule_upper(model, i):
return model.PPS[i] <= model.PSmax[i] * model.k[i]
model.PS_power_upper = Constraint(model.N_PS, rule=PS_power_rule_upper)
def Balance_rule(model):
return (sum(model.PPS[i] for i in model.N_PS) - sum(model.Psub[i] for i in model.N_clusters)) == 0
model.Balance = Constraint(rule=Balance_rule)
####################Define objective function##########################
####################Define objective function##########################
reliability_index = 1000
def ObjectiveFunction(model):
return summation(model.weights, model.x) * model.cf / 1000 + summation(model.ps_cost, model.k)
# return summation(model.weights, model.x) * model.cf / 1000 + summation(model.ps_cost,model.k) - sum(model.Psub[i]*model.Distance[i] for i in model.N_clusters)*reliability_index
model.Obj = Objective(rule=ObjectiveFunction, sense=minimize)
#############Solve model##################
instance = model.create_instance(data)
print('Instance is constructed:', instance.is_constructed())
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\Gisele_MILP\cbc')
opt = SolverFactory('gurobi')
opt.options['TimeLimit'] = 600
# opt.options['numericfocus']=0
# opt.options['mipgap'] = 0.0002
# opt.options['presolve']=2
# opt.options['mipfocus']=2
# opt = SolverFactory('cbc',executable=r'C:\Users\Asus\Desktop\POLIMI\Thesis\GISELE\New folder\cbc')
print('Starting optimization process')
time_i = datetime.now()
opt.solve(instance, tee=True, symbolic_solver_labels=True)
time_f = datetime.now()
print('Time required for optimization is', time_f - time_i)
links = instance.x
power = instance.P
subs = instance.k
voltage = instance.E
PS = instance.PPS
links_clusters = instance.links_clusters
# voltage_drop=instance.z
connections_output = pd.DataFrame(columns=[['id1', 'id2', 'power']])
PrSubstation = pd.DataFrame(columns=[['index', 'power']])
all_lines = pd.DataFrame(columns=[['id1', 'id2', 'power']])
Voltages = pd.DataFrame(columns=[['index', 'voltage [p.u]']])
Links_Clusters = pd.DataFrame(columns=[['id1', 'id2', 'power']])
distance = pd.DataFrame(columns=[['index', 'length[km]']])
k = 0
for index in links:
if int(round(value(links[index]))) == 1:
connections_output.loc[k, 'id1'] = index[0]
connections_output.loc[k, 'id2'] = index[1]
connections_output.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in subs:
if int(round(value(subs[index]))) == 1:
PrSubstation.loc[k, 'index'] = index
PrSubstation.loc[k, 'power'] = value(PS[index])
print(((value(PS[index]))))
k = k + 1
k = 0
for v in voltage:
Voltages.loc[k, 'index'] = v
Voltages.loc[k, 'voltage [p.u]'] = value(voltage[v])
k = k + 1
k = 0
for index in power:
all_lines.loc[k, 'id1'] = index[0]
all_lines.loc[k, 'id2'] = index[1]
all_lines.loc[k, 'power'] = value(power[index])
k = k + 1
k = 0
for index in links_clusters:
Links_Clusters.loc[k, 'id1'] = index[0]
Links_Clusters.loc[k, 'id2'] = index[1]
Links_Clusters.loc[k, 'power'] = value(power[index])
k = k + 1
Links_Clusters.to_csv(MILP_output_folder + '/links_clusters.csv', index=False)
connections_output.to_csv(MILP_output_folder + '/connections_output.csv', index=False)
PrSubstation.to_csv(MILP_output_folder + '/PrimarySubstations.csv', index=False)
Voltages.to_csv(MILP_output_folder + '/Voltages.csv', index=False)
all_lines.to_csv(MILP_output_folder + '/all_lines.csv', index=False) | 41.241198 | 187 | 0.650731 | 14,241 | 101,907 | 4.507338 | 0.035672 | 0.008724 | 0.026422 | 0.014784 | 0.868809 | 0.846983 | 0.83251 | 0.815093 | 0.806431 | 0.803066 | 0 | 0.012615 | 0.207316 | 101,907 | 2,471 | 188 | 41.241198 | 0.782001 | 0.162226 | 0 | 0.789107 | 0 | 0 | 0.061395 | 0.016604 | 0 | 0 | 0 | 0.000405 | 0 | 1 | 0.113996 | false | 0 | 0.005067 | 0.098797 | 0.229892 | 0.024066 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
52bc711fdace85d5bc553bea493b581e378b84d7 | 2,753 | py | Python | meross_iot/controller/known/strips.py | mjrinker/MerossIot | 69deebfc6326e82d35e74ed945230c1933291471 | [
"MIT"
] | null | null | null | meross_iot/controller/known/strips.py | mjrinker/MerossIot | 69deebfc6326e82d35e74ed945230c1933291471 | [
"MIT"
] | null | null | null | meross_iot/controller/known/strips.py | mjrinker/MerossIot | 69deebfc6326e82d35e74ed945230c1933291471 | [
"MIT"
] | null | null | null | from meross_iot.controller.device import BaseDevice
from meross_iot.controller.mixins.toggle import ToggleXMixin
class MSS420F(ToggleXMixin, BaseDevice):
"""
MSS420F power strip
"""
def __init__(self, device_uuid: str, manager, **kwargs):
if 'channels' not in kwargs:
kwargs['channels'] = [
{}, # Master channel
{}, # First switch
{}, # Second switch
{}, # Third switch
{}, # Fourth switch
]
super().__init__(device_uuid=device_uuid,
manager=manager,
**kwargs)
class MSS425E(ToggleXMixin, BaseDevice):
"""
MSS425E power strip
"""
def __init__(self, device_uuid: str, manager, **kwargs):
if 'channels' not in kwargs:
kwargs['channels'] = [
{}, # Master channel
{}, # First switch
{}, # Second switch
{}, # Third switch
{
'type': 'USB'
} # USB switch
]
super().__init__(device_uuid=device_uuid,
manager=manager,
**kwargs)
class MSS425F(ToggleXMixin, BaseDevice):
"""
MSS425F power strip
"""
def __init__(self, device_uuid: str, manager, **kwargs):
if 'channels' not in kwargs:
kwargs['channels'] = [
{}, # Master channel
{}, # First switch
{}, # Second switch
{}, # Third switch
{}, # Fourth switch
{
'type': 'USB'
} # USB switch
]
super().__init__(device_uuid=device_uuid,
manager=manager,
**kwargs)
class MSS530(ToggleXMixin, BaseDevice):
"""
MSS530 Multiple light control switches
"""
def __init__(self, device_uuid: str, manager, **kwargs):
if 'channels' not in kwargs:
kwargs['channels'] = [
{}, # Master channel
{}, # First switch
{}, # Second switch
{}, # Third switch
]
super().__init__(device_uuid=device_uuid,
manager=manager,
**kwargs)
| 34.848101 | 60 | 0.396658 | 185 | 2,753 | 5.654054 | 0.227027 | 0.114723 | 0.042065 | 0.06501 | 0.739006 | 0.739006 | 0.739006 | 0.739006 | 0.739006 | 0.739006 | 0 | 0.017844 | 0.511442 | 2,753 | 78 | 61 | 35.294872 | 0.759851 | 0.134036 | 0 | 0.758621 | 0 | 0 | 0.033854 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.068966 | false | 0 | 0.034483 | 0 | 0.172414 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
5e22310ee80600ec2cb8908500ecfb2f82f93de2 | 73 | py | Python | spts/scripts/spts_gui.py | Toonggg/spts | f67e75e15644cc1c7825c3be6b772d9e2686a249 | [
"BSD-2-Clause"
] | null | null | null | spts/scripts/spts_gui.py | Toonggg/spts | f67e75e15644cc1c7825c3be6b772d9e2686a249 | [
"BSD-2-Clause"
] | 5 | 2021-03-26T11:37:40.000Z | 2021-03-31T09:20:40.000Z | spts/scripts/spts_gui.py | mhantke/spts | eb446f9019946110368cd9eefd78aaa4f8d42b56 | [
"BSD-2-Clause"
] | 2 | 2020-01-06T17:20:15.000Z | 2020-11-04T09:27:35.000Z | #!/usr/bin/env python
import spts.gui.spts_gui
spts.gui.spts_gui.main()
| 14.6 | 24 | 0.753425 | 14 | 73 | 3.785714 | 0.571429 | 0.528302 | 0.622642 | 0.792453 | 0.528302 | 0.528302 | 0 | 0 | 0 | 0 | 0 | 0 | 0.082192 | 73 | 4 | 25 | 18.25 | 0.791045 | 0.273973 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
eab0212290a6224151514e08b7aeece882d39716 | 9,068 | py | Python | utils/proto_train.py | zhangmin4215/PoseNorm_Fewshot | 3b20ddc33ee14d7747cc536524000cc23343cbb5 | [
"MIT"
] | 43 | 2020-04-03T02:07:05.000Z | 2021-12-24T22:44:38.000Z | utils/proto_train.py | zhangmin4215/PoseNorm_Fewshot | 3b20ddc33ee14d7747cc536524000cc23343cbb5 | [
"MIT"
] | 2 | 2020-07-01T09:06:30.000Z | 2021-05-27T21:00:56.000Z | utils/proto_train.py | zhangmin4215/PoseNorm_Fewshot | 3b20ddc33ee14d7747cc536524000cc23343cbb5 | [
"MIT"
] | 9 | 2020-04-20T04:39:47.000Z | 2021-03-03T14:36:56.000Z | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from tensorboardX import SummaryWriter
from torchvision.utils import make_grid
from torch.nn import NLLLoss,BCEWithLogitsLoss,BCELoss
from . import util
def default_train(train_loader,model,
optimizer,writer,iter_counter):
way = model.way
test_shot = model.shots[-1]
target = torch.LongTensor([i//test_shot for i in range(test_shot*way)]).cuda()
criterion = NLLLoss().cuda()
lr = optimizer.param_groups[0]['lr']
writer.add_scalar('lr',lr,iter_counter)
avg_loss = 0
avg_acc = 0
for i, (inp,_) in enumerate(train_loader):
iter_counter += 1
if isinstance(inp,list):
(image_inp,mask) = inp
image_inp = image_inp.cuda()
mask = mask.cuda()
log_prediction = model(image_inp,mask)
elif isinstance(inp,torch.Tensor):
inp = inp.cuda()
log_prediction = model(inp)
loss = criterion(log_prediction,target)
optimizer.zero_grad()
loss.backward()
optimizer.step()
loss_value = loss.item()
_,max_index = torch.max(log_prediction,1)
acc = 100*torch.sum(torch.eq(max_index,target)).item()/test_shot/way
avg_acc += acc
avg_loss += loss_value
avg_acc = avg_acc/(i+1)
avg_loss = avg_loss/(i+1)
writer.add_scalar('proto_loss',avg_loss,iter_counter)
writer.add_scalar('train_acc',avg_acc,iter_counter)
return iter_counter,avg_acc
def PN_train(train_loader,model,
optimizer,writer,iter_counter,alpha):
test_shot = model.shots[-1]
way = model.way
target = torch.LongTensor([i//test_shot for i in range(test_shot*way)]).cuda()
criterion = NLLLoss().cuda()
criterion_part = BCEWithLogitsLoss().cuda()
lr = optimizer.param_groups[0]['lr']
writer.add_scalar('lr',lr,iter_counter)
avg_proto_loss = 0
avg_heatmap_loss = 0
avg_total_loss = 0
avg_acc = 0
for i, ((inp,mask),_) in enumerate(train_loader):
iter_counter += 1
inp = inp.cuda()
mask = mask.cuda()
if iter_counter%1000==0:
model.eval()
util.visualize(model,writer,iter_counter,inp[:9],mask[:9])
model.train()
log_prediction,heatmap_logits = model(inp,mask)
loss_heatmap = criterion_part(heatmap_logits,mask)
loss_proto = criterion(log_prediction,target)
loss = alpha*loss_heatmap+loss_proto
optimizer.zero_grad()
loss.backward()
optimizer.step()
_,max_index = torch.max(log_prediction,1)
acc = 100*torch.sum(torch.eq(max_index,target)).item()/test_shot/way
avg_acc += acc
avg_total_loss += loss.item()
avg_proto_loss += loss_proto.item()
avg_heatmap_loss += loss_heatmap.item()
avg_total_loss = avg_total_loss/(i+1)
avg_proto_loss = avg_proto_loss/(i+1)
avg_heatmap_loss = avg_heatmap_loss/(i+1)
avg_acc = avg_acc/(i+1)
writer.add_scalar('total_loss',avg_total_loss,iter_counter)
writer.add_scalar('proto_loss',avg_proto_loss,iter_counter)
writer.add_scalar('heatmap_loss',avg_heatmap_loss,iter_counter)
writer.add_scalar('train_acc',avg_acc,iter_counter)
return iter_counter,avg_acc
def PN_train_less_annot(train_loader,model,
optimizer,writer,iter_counter,alpha,batch_size):
test_shot = model.shots[-1]
way = model.way
target = torch.LongTensor([i//test_shot for i in range(test_shot*way)]).cuda()
criterion = NLLLoss().cuda()
criterion_part = BCEWithLogitsLoss().cuda()
lr = optimizer.param_groups[0]['lr']
writer.add_scalar('lr',lr,iter_counter)
avg_proto_loss = 0
avg_heatmap_loss = 0
avg_total_loss = 0
avg_acc = 0
for i, ((inp,mask),_) in enumerate(train_loader):
iter_counter += 1
mask = mask[:way*batch_size]
optimizer.zero_grad()
log_prediction = model.forward_class(inp[way*batch_size:].cuda())
loss_proto = criterion(log_prediction,target)
loss_proto.backward()
heatmap_logits = model.forward_part(inp[:batch_size*way].cuda())
loss_heatmap = alpha*criterion_part(heatmap_logits,mask.cuda())
loss_heatmap.backward()
optimizer.step()
_,max_index = torch.max(log_prediction,1)
loss = loss_proto+loss_heatmap
acc = 100*torch.sum(torch.eq(max_index,target)).item()/test_shot/way
avg_acc += acc
avg_total_loss += loss.item()
avg_proto_loss += loss_proto.item()
avg_heatmap_loss += (loss_heatmap/alpha).item()
if iter_counter%1000==0:
model.eval()
util.visualize(model,writer,iter_counter,inp[:9].cuda(),mask[:9])
model.train()
avg_total_loss = avg_total_loss/(i+1)
avg_proto_loss = avg_proto_loss/(i+1)
avg_heatmap_loss = avg_heatmap_loss/(i+1)
avg_acc = avg_acc/(i+1)
writer.add_scalar('total_loss',avg_total_loss,iter_counter)
writer.add_scalar('proto_loss',avg_proto_loss,iter_counter)
writer.add_scalar('heatmap_loss',avg_heatmap_loss,iter_counter)
writer.add_scalar('train_acc',avg_acc,iter_counter)
return iter_counter,avg_acc
def bbN_train(train_loader,model,
optimizer,writer,iter_counter,alpha):
test_shot = model.shots[-1]
way = model.way
target = torch.LongTensor([i//test_shot for i in range(test_shot*way)]).cuda()
criterion = NLLLoss().cuda()
criterion_local = BCELoss().cuda()
lr = optimizer.param_groups[0]['lr']
writer.add_scalar('lr',lr,iter_counter)
avg_proto_loss = 0
avg_heatmap_loss = 0
avg_total_loss = 0
avg_acc = 0
for i, ((inp,mask),_) in enumerate(train_loader):
iter_counter += 1
inp = inp.cuda()
mask = mask.cuda()
mask = torch.cat((mask,1.0-mask),1)
if iter_counter%1000==0:
model.eval()
util.visualize(model,writer,iter_counter,inp[:9],mask[:9])
model.train()
log_prediction,heatmap = model(inp,mask)
loss_heatmap = criterion_local(heatmap,mask)
loss_proto = criterion(log_prediction,target)
loss = alpha*loss_heatmap+loss_proto
optimizer.zero_grad()
loss.backward()
optimizer.step()
_,max_index = torch.max(log_prediction,1)
acc = 100*torch.sum(torch.eq(max_index,target)).item()/test_shot/way
avg_acc += acc
avg_total_loss += loss.item()
avg_proto_loss += loss_proto.item()
avg_heatmap_loss += loss_heatmap.item()
avg_total_loss = avg_total_loss/(i+1)
avg_proto_loss = avg_proto_loss/(i+1)
avg_heatmap_loss = avg_heatmap_loss/(i+1)
avg_acc = avg_acc/(i+1)
writer.add_scalar('total_loss',avg_total_loss,iter_counter)
writer.add_scalar('proto_loss',avg_proto_loss,iter_counter)
writer.add_scalar('heatmap_loss',avg_heatmap_loss,iter_counter)
writer.add_scalar('train_acc',avg_acc,iter_counter)
return iter_counter,avg_acc
def fgvc_PN_train(train_loader,oid_loader,model,
optimizer,writer,iter_counter,alpha):
way = model.way
shots = model.shots
test_shot = shots[-1]
target = torch.LongTensor([i//test_shot for i in range(test_shot*way)]).cuda()
criterion = NLLLoss().cuda()
criterion_part = BCEWithLogitsLoss().cuda()
lr = optimizer.param_groups[0]['lr']
writer.add_scalar('lr',lr,iter_counter)
avg_proto_loss = 0
avg_heatmap_loss = 0
avg_total_loss = 0
avg_acc = 0
for i, ((inp,_),(oid_img,mask)) in enumerate(zip(train_loader,oid_loader)):
iter_counter += 1
optimizer.zero_grad()
log_prediction = model.forward_class(inp.cuda())
loss_proto = criterion(log_prediction,target)
loss_proto.backward()
heatmap_logits = model.forward_part(oid_img.cuda())
loss_heatmap = alpha*criterion_part(heatmap_logits,mask.cuda())
loss_heatmap.backward()
optimizer.step()
_,max_index = torch.max(log_prediction,1)
loss = loss_proto+loss_heatmap
acc = 100*torch.sum(torch.eq(max_index,target)).item()/test_shot/way
avg_acc += acc
avg_total_loss += loss.item()
avg_proto_loss += loss_proto.item()
avg_heatmap_loss += (loss_heatmap/alpha).item()
if iter_counter%1000==0:
model.eval()
util.visualize(model,writer,iter_counter,oid_img[:9].cuda(),mask[:9])
model.train()
avg_total_loss = avg_total_loss/(i+1)
avg_proto_loss = avg_proto_loss/(i+1)
avg_heatmap_loss = avg_heatmap_loss/(i+1)
avg_acc = avg_acc/(i+1)
writer.add_scalar('total_loss',avg_total_loss,iter_counter)
writer.add_scalar('proto_loss',avg_proto_loss,iter_counter)
writer.add_scalar('heatmap_loss',avg_heatmap_loss,iter_counter)
writer.add_scalar('train_acc',avg_acc,iter_counter)
return iter_counter,avg_acc
| 28.878981 | 82 | 0.658249 | 1,266 | 9,068 | 4.408373 | 0.076619 | 0.090665 | 0.061817 | 0.048916 | 0.877979 | 0.868841 | 0.850027 | 0.828884 | 0.808636 | 0.790719 | 0 | 0.01447 | 0.222651 | 9,068 | 313 | 83 | 28.971246 | 0.777273 | 0 | 0 | 0.797235 | 0 | 0 | 0.022386 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.023041 | false | 0 | 0.036866 | 0 | 0.082949 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
d80cd3939fbdf28a90a517833b4c9ef519867ee1 | 36,271 | py | Python | sdk/python/pulumi_oci/database/pluggable_database.py | EladGabay/pulumi-oci | 6841e27d4a1a7e15c672306b769912efbfd3ba99 | [
"ECL-2.0",
"Apache-2.0"
] | 5 | 2021-08-17T11:14:46.000Z | 2021-12-31T02:07:03.000Z | sdk/python/pulumi_oci/database/pluggable_database.py | pulumi-oci/pulumi-oci | 6841e27d4a1a7e15c672306b769912efbfd3ba99 | [
"ECL-2.0",
"Apache-2.0"
] | 1 | 2021-09-06T11:21:29.000Z | 2021-09-06T11:21:29.000Z | sdk/python/pulumi_oci/database/pluggable_database.py | pulumi-oci/pulumi-oci | 6841e27d4a1a7e15c672306b769912efbfd3ba99 | [
"ECL-2.0",
"Apache-2.0"
] | 2 | 2021-08-24T23:31:30.000Z | 2022-01-02T19:26:54.000Z | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['PluggableDatabaseArgs', 'PluggableDatabase']
@pulumi.input_type
class PluggableDatabaseArgs:
def __init__(__self__, *,
container_database_id: pulumi.Input[str],
pdb_admin_password: pulumi.Input[str],
pdb_name: pulumi.Input[str],
tde_wallet_password: pulumi.Input[str],
defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None):
"""
The set of arguments for constructing a PluggableDatabase resource.
:param pulumi.Input[str] container_database_id: The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
:param pulumi.Input[str] pdb_admin_password: A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
:param pulumi.Input[str] pdb_name: The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
:param pulumi.Input[str] tde_wallet_password: The existing TDE wallet password of the CDB.
:param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
:param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
"""
pulumi.set(__self__, "container_database_id", container_database_id)
pulumi.set(__self__, "pdb_admin_password", pdb_admin_password)
pulumi.set(__self__, "pdb_name", pdb_name)
pulumi.set(__self__, "tde_wallet_password", tde_wallet_password)
if defined_tags is not None:
pulumi.set(__self__, "defined_tags", defined_tags)
if freeform_tags is not None:
pulumi.set(__self__, "freeform_tags", freeform_tags)
@property
@pulumi.getter(name="containerDatabaseId")
def container_database_id(self) -> pulumi.Input[str]:
"""
The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
"""
return pulumi.get(self, "container_database_id")
@container_database_id.setter
def container_database_id(self, value: pulumi.Input[str]):
pulumi.set(self, "container_database_id", value)
@property
@pulumi.getter(name="pdbAdminPassword")
def pdb_admin_password(self) -> pulumi.Input[str]:
"""
A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
"""
return pulumi.get(self, "pdb_admin_password")
@pdb_admin_password.setter
def pdb_admin_password(self, value: pulumi.Input[str]):
pulumi.set(self, "pdb_admin_password", value)
@property
@pulumi.getter(name="pdbName")
def pdb_name(self) -> pulumi.Input[str]:
"""
The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
"""
return pulumi.get(self, "pdb_name")
@pdb_name.setter
def pdb_name(self, value: pulumi.Input[str]):
pulumi.set(self, "pdb_name", value)
@property
@pulumi.getter(name="tdeWalletPassword")
def tde_wallet_password(self) -> pulumi.Input[str]:
"""
The existing TDE wallet password of the CDB.
"""
return pulumi.get(self, "tde_wallet_password")
@tde_wallet_password.setter
def tde_wallet_password(self, value: pulumi.Input[str]):
pulumi.set(self, "tde_wallet_password", value)
@property
@pulumi.getter(name="definedTags")
def defined_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
"""
return pulumi.get(self, "defined_tags")
@defined_tags.setter
def defined_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "defined_tags", value)
@property
@pulumi.getter(name="freeformTags")
def freeform_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
(Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
"""
return pulumi.get(self, "freeform_tags")
@freeform_tags.setter
def freeform_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "freeform_tags", value)
@pulumi.input_type
class _PluggableDatabaseState:
def __init__(__self__, *,
compartment_id: Optional[pulumi.Input[str]] = None,
connection_strings: Optional[pulumi.Input['PluggableDatabaseConnectionStringsArgs']] = None,
container_database_id: Optional[pulumi.Input[str]] = None,
defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
is_restricted: Optional[pulumi.Input[bool]] = None,
lifecycle_details: Optional[pulumi.Input[str]] = None,
open_mode: Optional[pulumi.Input[str]] = None,
pdb_admin_password: Optional[pulumi.Input[str]] = None,
pdb_name: Optional[pulumi.Input[str]] = None,
state: Optional[pulumi.Input[str]] = None,
tde_wallet_password: Optional[pulumi.Input[str]] = None,
time_created: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering PluggableDatabase resources.
:param pulumi.Input[str] compartment_id: The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the compartment.
:param pulumi.Input['PluggableDatabaseConnectionStringsArgs'] connection_strings: Connection strings to connect to an Oracle Pluggable Database.
:param pulumi.Input[str] container_database_id: The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
:param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
:param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
:param pulumi.Input[bool] is_restricted: The restricted mode of the pluggable database. If a pluggable database is opened in restricted mode, the user needs both create a session and have restricted session privileges to connect to it.
:param pulumi.Input[str] lifecycle_details: Detailed message for the lifecycle state.
:param pulumi.Input[str] open_mode: The mode that pluggable database is in. Open mode can only be changed to READ_ONLY or MIGRATE directly from the backend (within the Oracle Database software).
:param pulumi.Input[str] pdb_admin_password: A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
:param pulumi.Input[str] pdb_name: The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
:param pulumi.Input[str] state: The current state of the pluggable database.
:param pulumi.Input[str] tde_wallet_password: The existing TDE wallet password of the CDB.
:param pulumi.Input[str] time_created: The date and time the pluggable database was created.
"""
if compartment_id is not None:
pulumi.set(__self__, "compartment_id", compartment_id)
if connection_strings is not None:
pulumi.set(__self__, "connection_strings", connection_strings)
if container_database_id is not None:
pulumi.set(__self__, "container_database_id", container_database_id)
if defined_tags is not None:
pulumi.set(__self__, "defined_tags", defined_tags)
if freeform_tags is not None:
pulumi.set(__self__, "freeform_tags", freeform_tags)
if is_restricted is not None:
pulumi.set(__self__, "is_restricted", is_restricted)
if lifecycle_details is not None:
pulumi.set(__self__, "lifecycle_details", lifecycle_details)
if open_mode is not None:
pulumi.set(__self__, "open_mode", open_mode)
if pdb_admin_password is not None:
pulumi.set(__self__, "pdb_admin_password", pdb_admin_password)
if pdb_name is not None:
pulumi.set(__self__, "pdb_name", pdb_name)
if state is not None:
pulumi.set(__self__, "state", state)
if tde_wallet_password is not None:
pulumi.set(__self__, "tde_wallet_password", tde_wallet_password)
if time_created is not None:
pulumi.set(__self__, "time_created", time_created)
@property
@pulumi.getter(name="compartmentId")
def compartment_id(self) -> Optional[pulumi.Input[str]]:
"""
The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the compartment.
"""
return pulumi.get(self, "compartment_id")
@compartment_id.setter
def compartment_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "compartment_id", value)
@property
@pulumi.getter(name="connectionStrings")
def connection_strings(self) -> Optional[pulumi.Input['PluggableDatabaseConnectionStringsArgs']]:
"""
Connection strings to connect to an Oracle Pluggable Database.
"""
return pulumi.get(self, "connection_strings")
@connection_strings.setter
def connection_strings(self, value: Optional[pulumi.Input['PluggableDatabaseConnectionStringsArgs']]):
pulumi.set(self, "connection_strings", value)
@property
@pulumi.getter(name="containerDatabaseId")
def container_database_id(self) -> Optional[pulumi.Input[str]]:
"""
The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
"""
return pulumi.get(self, "container_database_id")
@container_database_id.setter
def container_database_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "container_database_id", value)
@property
@pulumi.getter(name="definedTags")
def defined_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
"""
return pulumi.get(self, "defined_tags")
@defined_tags.setter
def defined_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "defined_tags", value)
@property
@pulumi.getter(name="freeformTags")
def freeform_tags(self) -> Optional[pulumi.Input[Mapping[str, Any]]]:
"""
(Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
"""
return pulumi.get(self, "freeform_tags")
@freeform_tags.setter
def freeform_tags(self, value: Optional[pulumi.Input[Mapping[str, Any]]]):
pulumi.set(self, "freeform_tags", value)
@property
@pulumi.getter(name="isRestricted")
def is_restricted(self) -> Optional[pulumi.Input[bool]]:
"""
The restricted mode of the pluggable database. If a pluggable database is opened in restricted mode, the user needs both create a session and have restricted session privileges to connect to it.
"""
return pulumi.get(self, "is_restricted")
@is_restricted.setter
def is_restricted(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "is_restricted", value)
@property
@pulumi.getter(name="lifecycleDetails")
def lifecycle_details(self) -> Optional[pulumi.Input[str]]:
"""
Detailed message for the lifecycle state.
"""
return pulumi.get(self, "lifecycle_details")
@lifecycle_details.setter
def lifecycle_details(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "lifecycle_details", value)
@property
@pulumi.getter(name="openMode")
def open_mode(self) -> Optional[pulumi.Input[str]]:
"""
The mode that pluggable database is in. Open mode can only be changed to READ_ONLY or MIGRATE directly from the backend (within the Oracle Database software).
"""
return pulumi.get(self, "open_mode")
@open_mode.setter
def open_mode(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "open_mode", value)
@property
@pulumi.getter(name="pdbAdminPassword")
def pdb_admin_password(self) -> Optional[pulumi.Input[str]]:
"""
A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
"""
return pulumi.get(self, "pdb_admin_password")
@pdb_admin_password.setter
def pdb_admin_password(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "pdb_admin_password", value)
@property
@pulumi.getter(name="pdbName")
def pdb_name(self) -> Optional[pulumi.Input[str]]:
"""
The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
"""
return pulumi.get(self, "pdb_name")
@pdb_name.setter
def pdb_name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "pdb_name", value)
@property
@pulumi.getter
def state(self) -> Optional[pulumi.Input[str]]:
"""
The current state of the pluggable database.
"""
return pulumi.get(self, "state")
@state.setter
def state(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "state", value)
@property
@pulumi.getter(name="tdeWalletPassword")
def tde_wallet_password(self) -> Optional[pulumi.Input[str]]:
"""
The existing TDE wallet password of the CDB.
"""
return pulumi.get(self, "tde_wallet_password")
@tde_wallet_password.setter
def tde_wallet_password(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "tde_wallet_password", value)
@property
@pulumi.getter(name="timeCreated")
def time_created(self) -> Optional[pulumi.Input[str]]:
"""
The date and time the pluggable database was created.
"""
return pulumi.get(self, "time_created")
@time_created.setter
def time_created(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "time_created", value)
class PluggableDatabase(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
container_database_id: Optional[pulumi.Input[str]] = None,
defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
pdb_admin_password: Optional[pulumi.Input[str]] = None,
pdb_name: Optional[pulumi.Input[str]] = None,
tde_wallet_password: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
This resource provides the Pluggable Database resource in Oracle Cloud Infrastructure Database service.
Creates and starts a pluggable database in the specified container database.
Use the [StartPluggableDatabase](#/en/database/latest/PluggableDatabase/StartPluggableDatabase] and [StopPluggableDatabase](#/en/database/latest/PluggableDatabase/StopPluggableDatabase] APIs to start and stop the pluggable database.
## Example Usage
```python
import pulumi
import pulumi_oci as oci
test_pluggable_database = oci.database.PluggableDatabase("testPluggableDatabase",
container_database_id=oci_database_database["test_database"]["id"],
pdb_admin_password=var["pluggable_database_pdb_admin_password"],
pdb_name=var["pluggable_database_pdb_name"],
tde_wallet_password=var["pluggable_database_tde_wallet_password"],
defined_tags=var["pluggable_database_defined_tags"],
freeform_tags={
"Department": "Finance",
})
```
## Import
PluggableDatabases can be imported using the `id`, e.g.
```sh
$ pulumi import oci:database/pluggableDatabase:PluggableDatabase test_pluggable_database "id"
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] container_database_id: The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
:param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
:param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
:param pulumi.Input[str] pdb_admin_password: A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
:param pulumi.Input[str] pdb_name: The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
:param pulumi.Input[str] tde_wallet_password: The existing TDE wallet password of the CDB.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: PluggableDatabaseArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
This resource provides the Pluggable Database resource in Oracle Cloud Infrastructure Database service.
Creates and starts a pluggable database in the specified container database.
Use the [StartPluggableDatabase](#/en/database/latest/PluggableDatabase/StartPluggableDatabase] and [StopPluggableDatabase](#/en/database/latest/PluggableDatabase/StopPluggableDatabase] APIs to start and stop the pluggable database.
## Example Usage
```python
import pulumi
import pulumi_oci as oci
test_pluggable_database = oci.database.PluggableDatabase("testPluggableDatabase",
container_database_id=oci_database_database["test_database"]["id"],
pdb_admin_password=var["pluggable_database_pdb_admin_password"],
pdb_name=var["pluggable_database_pdb_name"],
tde_wallet_password=var["pluggable_database_tde_wallet_password"],
defined_tags=var["pluggable_database_defined_tags"],
freeform_tags={
"Department": "Finance",
})
```
## Import
PluggableDatabases can be imported using the `id`, e.g.
```sh
$ pulumi import oci:database/pluggableDatabase:PluggableDatabase test_pluggable_database "id"
```
:param str resource_name: The name of the resource.
:param PluggableDatabaseArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(PluggableDatabaseArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
container_database_id: Optional[pulumi.Input[str]] = None,
defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
pdb_admin_password: Optional[pulumi.Input[str]] = None,
pdb_name: Optional[pulumi.Input[str]] = None,
tde_wallet_password: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = PluggableDatabaseArgs.__new__(PluggableDatabaseArgs)
if container_database_id is None and not opts.urn:
raise TypeError("Missing required property 'container_database_id'")
__props__.__dict__["container_database_id"] = container_database_id
__props__.__dict__["defined_tags"] = defined_tags
__props__.__dict__["freeform_tags"] = freeform_tags
if pdb_admin_password is None and not opts.urn:
raise TypeError("Missing required property 'pdb_admin_password'")
__props__.__dict__["pdb_admin_password"] = pdb_admin_password
if pdb_name is None and not opts.urn:
raise TypeError("Missing required property 'pdb_name'")
__props__.__dict__["pdb_name"] = pdb_name
if tde_wallet_password is None and not opts.urn:
raise TypeError("Missing required property 'tde_wallet_password'")
__props__.__dict__["tde_wallet_password"] = tde_wallet_password
__props__.__dict__["compartment_id"] = None
__props__.__dict__["connection_strings"] = None
__props__.__dict__["is_restricted"] = None
__props__.__dict__["lifecycle_details"] = None
__props__.__dict__["open_mode"] = None
__props__.__dict__["state"] = None
__props__.__dict__["time_created"] = None
super(PluggableDatabase, __self__).__init__(
'oci:database/pluggableDatabase:PluggableDatabase',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
compartment_id: Optional[pulumi.Input[str]] = None,
connection_strings: Optional[pulumi.Input[pulumi.InputType['PluggableDatabaseConnectionStringsArgs']]] = None,
container_database_id: Optional[pulumi.Input[str]] = None,
defined_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
freeform_tags: Optional[pulumi.Input[Mapping[str, Any]]] = None,
is_restricted: Optional[pulumi.Input[bool]] = None,
lifecycle_details: Optional[pulumi.Input[str]] = None,
open_mode: Optional[pulumi.Input[str]] = None,
pdb_admin_password: Optional[pulumi.Input[str]] = None,
pdb_name: Optional[pulumi.Input[str]] = None,
state: Optional[pulumi.Input[str]] = None,
tde_wallet_password: Optional[pulumi.Input[str]] = None,
time_created: Optional[pulumi.Input[str]] = None) -> 'PluggableDatabase':
"""
Get an existing PluggableDatabase resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] compartment_id: The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the compartment.
:param pulumi.Input[pulumi.InputType['PluggableDatabaseConnectionStringsArgs']] connection_strings: Connection strings to connect to an Oracle Pluggable Database.
:param pulumi.Input[str] container_database_id: The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
:param pulumi.Input[Mapping[str, Any]] defined_tags: (Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
:param pulumi.Input[Mapping[str, Any]] freeform_tags: (Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
:param pulumi.Input[bool] is_restricted: The restricted mode of the pluggable database. If a pluggable database is opened in restricted mode, the user needs both create a session and have restricted session privileges to connect to it.
:param pulumi.Input[str] lifecycle_details: Detailed message for the lifecycle state.
:param pulumi.Input[str] open_mode: The mode that pluggable database is in. Open mode can only be changed to READ_ONLY or MIGRATE directly from the backend (within the Oracle Database software).
:param pulumi.Input[str] pdb_admin_password: A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
:param pulumi.Input[str] pdb_name: The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
:param pulumi.Input[str] state: The current state of the pluggable database.
:param pulumi.Input[str] tde_wallet_password: The existing TDE wallet password of the CDB.
:param pulumi.Input[str] time_created: The date and time the pluggable database was created.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _PluggableDatabaseState.__new__(_PluggableDatabaseState)
__props__.__dict__["compartment_id"] = compartment_id
__props__.__dict__["connection_strings"] = connection_strings
__props__.__dict__["container_database_id"] = container_database_id
__props__.__dict__["defined_tags"] = defined_tags
__props__.__dict__["freeform_tags"] = freeform_tags
__props__.__dict__["is_restricted"] = is_restricted
__props__.__dict__["lifecycle_details"] = lifecycle_details
__props__.__dict__["open_mode"] = open_mode
__props__.__dict__["pdb_admin_password"] = pdb_admin_password
__props__.__dict__["pdb_name"] = pdb_name
__props__.__dict__["state"] = state
__props__.__dict__["tde_wallet_password"] = tde_wallet_password
__props__.__dict__["time_created"] = time_created
return PluggableDatabase(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="compartmentId")
def compartment_id(self) -> pulumi.Output[str]:
"""
The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the compartment.
"""
return pulumi.get(self, "compartment_id")
@property
@pulumi.getter(name="connectionStrings")
def connection_strings(self) -> pulumi.Output['outputs.PluggableDatabaseConnectionStrings']:
"""
Connection strings to connect to an Oracle Pluggable Database.
"""
return pulumi.get(self, "connection_strings")
@property
@pulumi.getter(name="containerDatabaseId")
def container_database_id(self) -> pulumi.Output[str]:
"""
The [OCID](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm) of the CDB
"""
return pulumi.get(self, "container_database_id")
@property
@pulumi.getter(name="definedTags")
def defined_tags(self) -> pulumi.Output[Mapping[str, Any]]:
"""
(Updatable) Defined tags for this resource. Each key is predefined and scoped to a namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm).
"""
return pulumi.get(self, "defined_tags")
@property
@pulumi.getter(name="freeformTags")
def freeform_tags(self) -> pulumi.Output[Mapping[str, Any]]:
"""
(Updatable) Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. For more information, see [Resource Tags](https://docs.cloud.oracle.com/iaas/Content/General/Concepts/resourcetags.htm). Example: `{"Department": "Finance"}`
"""
return pulumi.get(self, "freeform_tags")
@property
@pulumi.getter(name="isRestricted")
def is_restricted(self) -> pulumi.Output[bool]:
"""
The restricted mode of the pluggable database. If a pluggable database is opened in restricted mode, the user needs both create a session and have restricted session privileges to connect to it.
"""
return pulumi.get(self, "is_restricted")
@property
@pulumi.getter(name="lifecycleDetails")
def lifecycle_details(self) -> pulumi.Output[str]:
"""
Detailed message for the lifecycle state.
"""
return pulumi.get(self, "lifecycle_details")
@property
@pulumi.getter(name="openMode")
def open_mode(self) -> pulumi.Output[str]:
"""
The mode that pluggable database is in. Open mode can only be changed to READ_ONLY or MIGRATE directly from the backend (within the Oracle Database software).
"""
return pulumi.get(self, "open_mode")
@property
@pulumi.getter(name="pdbAdminPassword")
def pdb_admin_password(self) -> pulumi.Output[str]:
"""
A strong password for PDB Admin. The password must be at least nine characters and contain at least two uppercase, two lowercase, two numbers, and two special characters. The special characters must be _, \#, or -.
"""
return pulumi.get(self, "pdb_admin_password")
@property
@pulumi.getter(name="pdbName")
def pdb_name(self) -> pulumi.Output[str]:
"""
The name for the pluggable database (PDB). The name is unique in the context of a [container database](https://docs.cloud.oracle.com/iaas/api/#/en/database/latest/Database/). The name must begin with an alphabetic character and can contain a maximum of thirty alphanumeric characters. Special characters are not permitted. The pluggable database name should not be same as the container database name.
"""
return pulumi.get(self, "pdb_name")
@property
@pulumi.getter
def state(self) -> pulumi.Output[str]:
"""
The current state of the pluggable database.
"""
return pulumi.get(self, "state")
@property
@pulumi.getter(name="tdeWalletPassword")
def tde_wallet_password(self) -> pulumi.Output[str]:
"""
The existing TDE wallet password of the CDB.
"""
return pulumi.get(self, "tde_wallet_password")
@property
@pulumi.getter(name="timeCreated")
def time_created(self) -> pulumi.Output[str]:
"""
The date and time the pluggable database was created.
"""
return pulumi.get(self, "time_created")
| 56.585023 | 444 | 0.690662 | 4,485 | 36,271 | 5.386845 | 0.059309 | 0.056457 | 0.048676 | 0.040066 | 0.895075 | 0.86043 | 0.842881 | 0.83423 | 0.829056 | 0.784023 | 0 | 0.000035 | 0.208955 | 36,271 | 640 | 445 | 56.673438 | 0.842012 | 0.455212 | 0 | 0.587079 | 1 | 0 | 0.130765 | 0.027263 | 0 | 0 | 0 | 0 | 0 | 1 | 0.162921 | false | 0.154494 | 0.019663 | 0 | 0.283708 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 8 |
dc1ce1b18fee71cd82a81a9b37c1c60a235b67f6 | 7,804 | py | Python | expt/setupExperiments.py | rahulk90/vae_sparse | 102b3cf72abae8d66718b945df365edd4a23a62d | [
"MIT"
] | 11 | 2017-11-16T13:01:47.000Z | 2021-12-26T20:07:24.000Z | expt/setupExperiments.py | rahulk90/inference_introspection | 102b3cf72abae8d66718b945df365edd4a23a62d | [
"MIT"
] | null | null | null | expt/setupExperiments.py | rahulk90/inference_introspection | 102b3cf72abae8d66718b945df365edd4a23a62d | [
"MIT"
] | null | null | null | """ Commands to reproduce experimental results """
from collections import OrderedDict
import sys
expt_type = 'rcv2_tfidf'
valid_expts= set(['20newsgroups_norm','20newsgroups_tfidf','rcv2_norm','rcv2_tfidf','rcv2_q_vary','rcv2_p_fixed','rcv2_p_fixed_random',
'wikicorp','wikicorp_sparsity','wikicorp-large','wikicorp_evaluate','wikicorp_evaluate','wikicorp_mixed_training'])
print 'Valid Expts: ',','.join(list(valid_expts))
print 'Default: ',expt_type
if len(sys.argv)>=2:
expt_type = sys.argv[-1].strip()
if expt_type not in valid_expts:
raise ValueError,(expt_type+' not a valid experiment')
print 'Selected: ',expt_type,'\n'
expt_runs = OrderedDict()
gpu_0_half = 'THEANO_FLAGS="compiledir_format=gpu0,lib.cnmem=0.45,scan.allow_gc=False"'
gpu_0_full = 'THEANO_FLAGS="compiledir_format=gpu0,lib.cnmem=0.95,scan.allow_gc=False"'
gpu_1_half = 'THEANO_FLAGS="compiledir_format=gpu1,lib.cnmem=0.45,scan.allow_gc=False"'
gpu_1_full = 'THEANO_FLAGS="compiledir_format=gpu1,lib.cnmem=0.95,scan.allow_gc=False"'
gpu_2_half = 'THEANO_FLAGS="compiledir_format=gpu2,lib.cnmem=0.45,scan.allow_gc=False"'
gpu_2_full = 'THEANO_FLAGS="compiledir_format=gpu2,lib.cnmem=0.95,scan.allow_gc=False"'
gpu_3_half = 'THEANO_FLAGS="compiledir_format=gpu3,lib.cnmem=0.45,scan.allow_gc=False"'
gpu_3_full = 'THEANO_FLAGS="compiledir_format=gpu3,lib.cnmem=0.95,scan.allow_gc=False"'
"""
Experiments on 20newsgroups
June 11- Rerun
"""
expt_runs['20newsgroups_norm'] = OrderedDict()
expt_runs['20newsgroups_norm']['2_none'] = gpu_0_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -nl relu -otype none -pl 2 -ns 100 -ep 200'
expt_runs['20newsgroups_norm']['2_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -nl relu -otype finopt -pl 2 -ns 100 -ep 200'
expt_runs['20newsgroups_norm']['0_none'] = gpu_0_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -nl relu -otype none -pl 0 -ns 100 -ep 200'
expt_runs['20newsgroups_norm']['0_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -nl relu -otype finopt -pl 0 -ns 100 -ep 200'
expt_runs['20newsgroups_tfidf'] = OrderedDict()
expt_runs['20newsgroups_tfidf']['2_none'] = gpu_0_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 200'
expt_runs['20newsgroups_tfidf']['2_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -itype tfidf -nl relu -otype finopt -pl 2 -ns 100 -ep 200'
expt_runs['20newsgroups_tfidf']['0_none'] = gpu_0_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -itype tfidf -nl relu -otype none -pl 0 -ns 100 -ep 200'
expt_runs['20newsgroups_tfidf']['0_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset 20newsgroups -ds 100 -itype tfidf -nl relu -otype finopt -pl 0 -ns 100 -ep 200'
"""
Experiments on RCV2
"""
expt_runs['rcv2_norm'] = OrderedDict()
expt_runs['rcv2_norm']['2_none'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -nl relu -otype none -pl 2 -ns 100 -ep 200'
expt_runs['rcv2_norm']['2_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -nl relu -otype finopt -pl 2 -ns 100 -ep 200'
expt_runs['rcv2_norm']['0_none'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -nl relu -otype none -pl 0 -ns 100 -ep 200'
expt_runs['rcv2_norm']['0_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -nl relu -otype finopt -pl 0 -ns 100 -ep 200'
expt_runs['rcv2_tfidf'] = OrderedDict()
expt_runs['rcv2_tfidf']['2_none'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 200'
expt_runs['rcv2_tfidf']['2_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype finopt -pl 2 -ns 100 -ep 200'
expt_runs['rcv2_tfidf']['0_none'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 0 -ns 100 -ep 200'
expt_runs['rcv2_tfidf']['0_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype finopt -pl 0 -ns 100 -ep 200'
expt_runs['rcv2_tfidf']['2-ar10k'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 200 -ar 10000'
expt_runs['rcv2_tfidf']['0-ar10k'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 0 -ns 100 -ep 200 -ar 10000'
expt_runs['rcv2_tfidf']['2-ar50k'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 200 -ar 50000'
expt_runs['rcv2_tfidf']['0-ar50k'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 0 -ns 100 -ep 200 -ar 50000'
expt_runs['rcv2_tfidf']['2-ar100k'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 200 -ar 100000'
expt_runs['rcv2_tfidf']['0-ar100k'] = gpu_0_full+' '+'python2.7 train.py -dset rcv2 -ds 100 -itype tfidf -nl relu -otype none -pl 0 -ns 100 -ep 200 -ar 100000'
"""
Experiments on the WikiCorpus Dataset
"""
#chronos
expt_runs['wikicorp'] = OrderedDict()
expt_runs['wikicorp']['2-none'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp']['2-finopt'] = gpu_1_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype finopt -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp']['0-none'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype none -pl 0 -ns 100 -ep 52'
expt_runs['wikicorp']['0-finopt'] = gpu_1_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype finopt -pl 0 -ns 100 -ep 52'
expt_runs['wikicorp']['2-ar10k'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52 -ar 10000'
expt_runs['wikicorp']['2-ar50k'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52 -ar 50000'
expt_runs['wikicorp']['2-ar100k'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52 -ar 100000'
#r730
expt_runs['wikicorp_sparsity'] = OrderedDict()
expt_runs['wikicorp_sparsity']['1000-2-finopt'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp_1000 -ds 100 -itype tfidf -nl relu -otype finopt -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp_sparsity']['5000-2-finopt'] = gpu_1_full+' '+'python2.7 train.py -dset wikicorp_5000 -ds 100 -itype tfidf -nl relu -otype finopt -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp_sparsity']['10000-2-finopt'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp_10000 -ds 100 -itype tfidf -nl relu -otype finopt -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp_sparsity']['1000-2-none'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp_1000 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp_sparsity']['5000-2-none'] = gpu_1_full+' '+'python2.7 train.py -dset wikicorp_5000 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp_sparsity']['10000-2-none'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp_10000 -ds 100 -itype tfidf -nl relu -otype none -pl 2 -ns 100 -ep 52'
#k80
expt_runs['wikicorp_mixed_training'] = OrderedDict()
expt_runs['wikicorp_mixed_training']['none_finopt'] = gpu_1_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype none_finopt -pl 2 -ns 100 -ep 52'
expt_runs['wikicorp_mixed_training']['finopt_none'] = gpu_0_full+' '+'python2.7 train.py -dset wikicorp -ds 100 -itype tfidf -nl relu -otype finopt_none -pl 2 -ns 100 -ep 52'
for expt in expt_runs[expt_type]:
print 'screen -S '+expt
print expt_runs[expt_type][expt]
| 80.453608 | 174 | 0.711814 | 1,374 | 7,804 | 3.858079 | 0.080786 | 0.07093 | 0.083758 | 0.118657 | 0.83305 | 0.797774 | 0.788342 | 0.785324 | 0.733447 | 0.68704 | 0 | 0.110278 | 0.128524 | 7,804 | 96 | 175 | 81.291667 | 0.669166 | 0.001794 | 0 | 0 | 0 | 0.544118 | 0.706238 | 0.087722 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.029412 | null | null | 0.073529 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
dc904045ae6481e3c1db53440c4e7e69c5f44bb0 | 26,109 | py | Python | tests/test_conceptmap.py | glichtner/fhir.resources | 94896d8f8a0b7dd69253762aab968f4fd6eb69a0 | [
"BSD-3-Clause"
] | null | null | null | tests/test_conceptmap.py | glichtner/fhir.resources | 94896d8f8a0b7dd69253762aab968f4fd6eb69a0 | [
"BSD-3-Clause"
] | null | null | null | tests/test_conceptmap.py | glichtner/fhir.resources | 94896d8f8a0b7dd69253762aab968f4fd6eb69a0 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Profile: http://hl7.org/fhir/StructureDefinition/ConceptMap
Release: R5
Version: 4.5.0
Build ID: 0d95498
Last updated: 2021-04-03T00:34:11.075+00:00
"""
from pydantic.validators import bytes_validator # noqa: F401
from fhir.resources import fhirtypes # noqa: F401
from fhir.resources import conceptmap
def impl_conceptmap_1(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.contact[0].telecom[1].system == "email"
assert inst.contact[0].telecom[1].value == "fhir@lists.hl7.org"
assert inst.date == fhirtypes.DateTime.validate("2020-12-28T05:55:11+00:00")
assert inst.description == (
'Canonical Mapping for "The verification status to support '
"or decline the clinical status of the condition or "
'diagnosis."'
)
assert inst.group[0].element[0].code == "entered-in-error"
assert inst.group[0].element[0].target[0].code == "error"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "unconfirmed, provisional"
assert inst.group[0].element[1].target[0].code == "unconfirmed"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "confirmed"
assert inst.group[0].element[2].target[0].code == "confirmed"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].element[3].code == "refuted"
assert inst.group[0].element[3].target[0].code == "refuted"
assert inst.group[0].element[3].target[0].relationship == "equivalent"
assert inst.group[0].element[4].code == "differential"
assert inst.group[0].element[4].target[0].code == "differential"
assert inst.group[0].element[4].target[0].relationship == "equivalent"
assert (
inst.group[0].source
== "http://terminology.hl7.org/CodeSystem/condition-ver-status"
)
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-condition-ver-status"
assert inst.name == "ConditionVerificationStatusCanonicalMap"
assert inst.publisher == "HL7 (FHIR Project)"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/condition-ver-status"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "ConditionVerificationStatus"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-condition-ver-status"
assert inst.version == "4.5.0"
def test_conceptmap_1(base_settings):
"""No. 1 tests collection for ConceptMap.
Test File: sc-valueset-condition-ver-status.json
"""
filename = (
base_settings["unittest_data_dir"] / "sc-valueset-condition-ver-status.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_1(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_1(inst2)
def impl_conceptmap_2(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.contact[0].telecom[1].system == "email"
assert inst.contact[0].telecom[1].value == "fhir@lists.hl7.org"
assert inst.date == fhirtypes.DateTime.validate("2020-12-28T05:55:11+00:00")
assert inst.description == (
'Canonical Mapping for "Indicates the state of the ' 'consent."'
)
assert inst.group[0].element[0].code == "entered-in-error"
assert inst.group[0].element[0].target[0].code == "error"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "draft"
assert inst.group[0].element[1].target[0].code == "draft"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "active"
assert inst.group[0].element[2].target[0].code == "active"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].element[3].code == "inactive"
assert inst.group[0].element[3].target[0].code == "inactive"
assert inst.group[0].element[3].target[0].relationship == "equivalent"
assert inst.group[0].element[4].code == "unknown"
assert inst.group[0].element[4].target[0].code == "unknown"
assert inst.group[0].element[4].target[0].relationship == "equivalent"
assert inst.group[0].source == "http://hl7.org/fhir/consent-state-codes"
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-consent-state-codes"
assert inst.name == "ConsentStateCanonicalMap"
assert inst.publisher == "HL7 (FHIR Project)"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/consent-state-codes"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "ConsentState"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-consent-state-codes"
assert inst.version == "4.5.0"
def test_conceptmap_2(base_settings):
"""No. 2 tests collection for ConceptMap.
Test File: sc-valueset-consent-state-codes.json
"""
filename = (
base_settings["unittest_data_dir"] / "sc-valueset-consent-state-codes.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_2(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_2(inst2)
def impl_conceptmap_3(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.contact[0].telecom[1].system == "email"
assert inst.contact[0].telecom[1].value == "fhir@lists.hl7.org"
assert inst.date == fhirtypes.DateTime.validate("2020-12-28T05:55:11+00:00")
assert inst.description == (
'Canonical Mapping for "The Participation status of an ' 'appointment."'
)
assert inst.group[0].element[0].code == "tentative"
assert inst.group[0].element[0].target[0].code == "draft"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "declined"
assert inst.group[0].element[1].target[0].code == "declined"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "accepted"
assert inst.group[0].element[2].target[0].code == "accepted"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].element[3].code == "needs-action"
assert inst.group[0].element[3].target[0].code == "failed"
assert inst.group[0].element[3].target[0].relationship == "equivalent"
assert inst.group[0].source == "http://hl7.org/fhir/participationstatus"
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-participationstatus"
assert inst.name == "ParticipationStatusCanonicalMap"
assert inst.publisher == "HL7 (FHIR Project)"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/participationstatus"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "ParticipationStatus"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-participationstatus"
assert inst.version == "4.5.0"
def test_conceptmap_3(base_settings):
"""No. 3 tests collection for ConceptMap.
Test File: sc-valueset-participationstatus.json
"""
filename = (
base_settings["unittest_data_dir"] / "sc-valueset-participationstatus.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_3(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_3(inst2)
def impl_conceptmap_4(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.group[0].element[0].code == "entered-in-error"
assert inst.group[0].element[0].target[0].code == "error"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "completed"
assert inst.group[0].element[1].target[0].code == "complete"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "not-done"
assert inst.group[0].element[2].target[0].code == "abandoned"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].source == "http://hl7.org/fhir/event-status"
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-immunization-status"
assert inst.name == "ImmunizationStatusCodesCanonicalMap"
assert inst.publisher == "FHIR Project team"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/immunization-status"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "Immunization Status Codes"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-immunization-status"
assert inst.version == "4.5.0"
def test_conceptmap_4(base_settings):
"""No. 4 tests collection for ConceptMap.
Test File: sc-valueset-immunization-status.json
"""
filename = (
base_settings["unittest_data_dir"] / "sc-valueset-immunization-status.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_4(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_4(inst2)
def impl_conceptmap_5(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.description == (
'Canonical Mapping for "Preferred value set for Condition ' 'Clinical Status."'
)
assert inst.group[0].element[0].code == "active,recurrence,relapse"
assert inst.group[0].element[0].target[0].code == "active"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "inactive,remission"
assert inst.group[0].element[1].target[0].code == "suspended"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "resolved"
assert inst.group[0].element[2].target[0].code == "failed"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert (
inst.group[0].source
== "http://terminology.hl7.org/CodeSystem/condition-clinical"
)
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-condition-clinical"
assert inst.name == "ConditionClinicalStatusCodesCanonicalMap"
assert inst.publisher == "FHIR Project team"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/condition-clinical"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "Condition Clinical Status Codes"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-condition-clinical"
assert inst.version == "4.5.0"
def test_conceptmap_5(base_settings):
"""No. 5 tests collection for ConceptMap.
Test File: sc-valueset-condition-clinical.json
"""
filename = (
base_settings["unittest_data_dir"] / "sc-valueset-condition-clinical.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_5(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_5(inst2)
def impl_conceptmap_6(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.contact[0].telecom[1].system == "email"
assert inst.contact[0].telecom[1].value == "fhir@lists.hl7.org"
assert inst.date == fhirtypes.DateTime.validate("2020-12-28T05:55:11+00:00")
assert inst.description == 'Canonical Mapping for "The status of the location."'
assert inst.group[0].element[0].code == "planned"
assert inst.group[0].element[0].target[0].code == "planned"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "reserved"
assert inst.group[0].element[1].target[0].code == "accepted"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "active"
assert inst.group[0].element[2].target[0].code == "active"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].element[3].code == "completed"
assert inst.group[0].element[3].target[0].code == "complete"
assert inst.group[0].element[3].target[0].relationship == "equivalent"
assert inst.group[0].source == "http://hl7.org/fhir/encounter-location-status"
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-encounter-location-status"
assert inst.name == "EncounterLocationStatusCanonicalMap"
assert inst.publisher == "HL7 (FHIR Project)"
assert (
inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/encounter-location-status"
)
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "EncounterLocationStatus"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-encounter-location-status"
assert inst.version == "4.5.0"
def test_conceptmap_6(base_settings):
"""No. 6 tests collection for ConceptMap.
Test File: sc-valueset-encounter-location-status.json
"""
filename = (
base_settings["unittest_data_dir"]
/ "sc-valueset-encounter-location-status.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_6(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_6(inst2)
def impl_conceptmap_7(inst):
assert inst.contact[0].telecom[0].system == "url"
assert (
inst.contact[0].telecom[0].value
== "http://www.hl7.org/Special/committees/patientcare/"
)
assert inst.description == (
'Canonical Mapping for "Describes the progression, or lack '
'thereof, towards the goal against the target."'
)
assert (
inst.group[0].element[0].code
== "in-progress, sustaining, improving, worsening, no-change"
)
assert inst.group[0].element[0].target[0].code == "active"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "achieved"
assert inst.group[0].element[1].target[0].code == "complete"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "not-attainable"
assert inst.group[0].element[2].target[0].code == "abandoned"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].element[3].code == "no-progress, not-achieved"
assert inst.group[0].element[3].target[0].code == "not-done"
assert inst.group[0].element[3].target[0].relationship == "equivalent"
assert (
inst.group[0].source == "http://terminology.hl7.org/CodeSystem/goal-achievement"
)
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-goal-achievement"
assert inst.name == "GoalAchievementStatusCanonicalMap"
assert inst.publisher == "HL7 International - Patient Care WG"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/goal-achievement"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "GoalAchievementStatus"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-goal-achievement"
assert inst.version == "4.5.0"
def test_conceptmap_7(base_settings):
"""No. 7 tests collection for ConceptMap.
Test File: sc-valueset-goal-achievement.json
"""
filename = base_settings["unittest_data_dir"] / "sc-valueset-goal-achievement.json"
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_7(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_7(inst2)
def impl_conceptmap_8(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.contact[0].telecom[1].system == "email"
assert inst.contact[0].telecom[1].value == "fhir@lists.hl7.org"
assert inst.date == fhirtypes.DateTime.validate("2020-12-28T05:55:11+00:00")
assert inst.description == (
'Canonical Mapping for "Indicates the status of the care ' 'team."'
)
assert inst.group[0].element[0].code == "entered-in-error"
assert inst.group[0].element[0].target[0].code == "error"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "proposed"
assert inst.group[0].element[1].target[0].code == "proposed"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "active"
assert inst.group[0].element[2].target[0].code == "active"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].element[3].code == "suspended"
assert inst.group[0].element[3].target[0].code == "suspended"
assert inst.group[0].element[3].target[0].relationship == "equivalent"
assert inst.group[0].element[4].code == "inactive"
assert inst.group[0].element[4].target[0].code == "inactive"
assert inst.group[0].element[4].target[0].relationship == "equivalent"
assert inst.group[0].source == "http://hl7.org/fhir/care-team-status"
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-care-team-status"
assert inst.name == "CareTeamStatusCanonicalMap"
assert inst.publisher == "HL7 (FHIR Project)"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/care-team-status"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "CareTeamStatus"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-care-team-status"
assert inst.version == "4.5.0"
def test_conceptmap_8(base_settings):
"""No. 8 tests collection for ConceptMap.
Test File: sc-valueset-care-team-status.json
"""
filename = base_settings["unittest_data_dir"] / "sc-valueset-care-team-status.json"
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_8(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_8(inst2)
def impl_conceptmap_9(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.contact[0].telecom[1].system == "email"
assert inst.contact[0].telecom[1].value == "fhir@lists.hl7.org"
assert inst.date == fhirtypes.DateTime.validate("2020-12-28T05:55:11+00:00")
assert inst.description == (
'Canonical Mapping for "Indicates whether this flag is '
"active and needs to be displayed to a user, or whether it is"
' no longer needed or was entered in error."'
)
assert inst.group[0].element[0].code == "entered-in-error"
assert inst.group[0].element[0].target[0].code == "error"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "active"
assert inst.group[0].element[1].target[0].code == "active"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert inst.group[0].element[2].code == "inactive"
assert inst.group[0].element[2].target[0].code == "inactive"
assert inst.group[0].element[2].target[0].relationship == "equivalent"
assert inst.group[0].source == "http://hl7.org/fhir/flag-status"
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-flag-status"
assert inst.name == "FlagStatusCanonicalMap"
assert inst.publisher == "HL7 (FHIR Project)"
assert inst.sourceCanonical == "http://hl7.org/fhir/ValueSet/flag-status"
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == 'Canonical Mapping for "FlagStatus"'
assert inst.url == "http://hl7.org/fhir/ConceptMap/sc-flag-status"
assert inst.version == "4.5.0"
def test_conceptmap_9(base_settings):
"""No. 9 tests collection for ConceptMap.
Test File: sc-valueset-flag-status.json
"""
filename = base_settings["unittest_data_dir"] / "sc-valueset-flag-status.json"
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_9(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_9(inst2)
def impl_conceptmap_10(inst):
assert inst.contact[0].telecom[0].system == "url"
assert inst.contact[0].telecom[0].value == "http://hl7.org/fhir"
assert inst.group[0].element[0].code == "entered-in-error"
assert inst.group[0].element[0].target[0].code == "error"
assert inst.group[0].element[0].target[0].relationship == "equivalent"
assert inst.group[0].element[1].code == "completed"
assert inst.group[0].element[1].target[0].code == "complete"
assert inst.group[0].element[1].target[0].relationship == "equivalent"
assert (
inst.group[0].source == "http://hl7.org/fhir/CodeSystem/medication-admin-status"
)
assert inst.group[0].target == "http://hl7.org/fhir/resource-status"
assert inst.id == "sc-immunization-evaluation-status"
assert inst.name == "ImmunizationEvaluationStatusCodesCanonicalMap"
assert inst.publisher == "FHIR Project team"
assert (
inst.sourceCanonical
== "http://hl7.org/fhir/ValueSet/immunization-evaluation-status"
)
assert inst.status == "draft"
assert inst.targetCanonical == "http://hl7.org/fhir/ValueSet/resource-status"
assert inst.text.status == "extensions"
assert inst.title == (
'Canonical Mapping for "Immunization Evaluation Status ' 'Codes"'
)
assert inst.url == (
"http://hl7.org/fhir/ConceptMap/sc-immunization-evaluation-" "status"
)
assert inst.version == "4.5.0"
def test_conceptmap_10(base_settings):
"""No. 10 tests collection for ConceptMap.
Test File: sc-valueset-immunization-evaluation-status.json
"""
filename = (
base_settings["unittest_data_dir"]
/ "sc-valueset-immunization-evaluation-status.json"
)
inst = conceptmap.ConceptMap.parse_file(
filename, content_type="application/json", encoding="utf-8"
)
assert "ConceptMap" == inst.resource_type
impl_conceptmap_10(inst)
# testing reverse by generating data from itself and create again.
data = inst.dict()
assert "ConceptMap" == data["resourceType"]
inst2 = conceptmap.ConceptMap(**data)
impl_conceptmap_10(inst2)
| 44.860825 | 88 | 0.685741 | 3,427 | 26,109 | 5.180333 | 0.066239 | 0.15772 | 0.11322 | 0.120768 | 0.890216 | 0.875232 | 0.850335 | 0.843801 | 0.824987 | 0.762519 | 0 | 0.032834 | 0.156613 | 26,109 | 581 | 89 | 44.938038 | 0.773388 | 0.065763 | 0 | 0.533477 | 0 | 0 | 0.291763 | 0.046921 | 0 | 0 | 0 | 0 | 0.647948 | 1 | 0.043197 | false | 0 | 0.006479 | 0 | 0.049676 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
dc9530a4b7f63a513dbe627d25b8f8f468996d84 | 612 | py | Python | plot.py | YashIITM/Numerical-Quadrature | 628d72f3397c104a1309dc30444a629a49945573 | [
"MIT"
] | null | null | null | plot.py | YashIITM/Numerical-Quadrature | 628d72f3397c104a1309dc30444a629a49945573 | [
"MIT"
] | null | null | null | plot.py | YashIITM/Numerical-Quadrature | 628d72f3397c104a1309dc30444a629a49945573 | [
"MIT"
] | null | null | null | import matplotlib.pyplot as plt
def plot(h,abs_err,color,name):
plt.scatter(h,abs_err,color = color,label = name)
plt.title("|E| vs x ")
plt.xlabel('h')
plt.ylabel('|E|')
#plt.show()
def SLplot(h,abs_err,color,name):
plt.scatter(np.log(h),abs_err,color = color,label = name)
plt.title("log(|E|) vs x ")
plt.xlabel('h')
plt.ylabel('|E|')
#plt.show()
def LLplot(h,abs_err,color,name):
plt.scatter(np.log(h),np.log(abs_err),color = color,label = name)
plt.title("log(|E|) vs log(x)")
plt.xlabel('h')
plt.ylabel('|E|')
#plt.show()
| 29.142857 | 70 | 0.580065 | 101 | 612 | 3.455446 | 0.247525 | 0.103152 | 0.189112 | 0.17192 | 0.845272 | 0.845272 | 0.845272 | 0.770774 | 0.770774 | 0.593123 | 0 | 0 | 0.212418 | 612 | 20 | 71 | 30.6 | 0.724066 | 0.04902 | 0 | 0.375 | 0 | 0 | 0.094812 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1875 | false | 0 | 0.0625 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
dcade14ec8210bf4c11989042c16df9fa779cd4d | 145 | py | Python | use.py | Kemixd3/kryp | 3df98e329cb21566b0874a5bc378d825ca054af7 | [
"Apache-2.0"
] | null | null | null | use.py | Kemixd3/kryp | 3df98e329cb21566b0874a5bc378d825ca054af7 | [
"Apache-2.0"
] | null | null | null | use.py | Kemixd3/kryp | 3df98e329cb21566b0874a5bc378d825ca054af7 | [
"Apache-2.0"
] | null | null | null | import os
#os.system("pyarmor obfuscate --restrict=0 use.py")
os.system("pyarmor obfuscate --recursive --output dist.2 dist/__init__.py")
| 24.166667 | 76 | 0.717241 | 21 | 145 | 4.761905 | 0.666667 | 0.16 | 0.3 | 0.48 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015873 | 0.131034 | 145 | 5 | 77 | 29 | 0.777778 | 0.344828 | 0 | 0 | 0 | 0 | 0.704545 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
dcb7fe226c90829c3188ad6223188b57f01f9c6b | 432,369 | py | Python | clarifai_grpc/grpc/api/resources_pb2.py | olga-clarifai/clarifai-python-grpc | c1d45ea965f781de5ccf682b142049c7628d0480 | [
"Apache-2.0"
] | null | null | null | clarifai_grpc/grpc/api/resources_pb2.py | olga-clarifai/clarifai-python-grpc | c1d45ea965f781de5ccf682b142049c7628d0480 | [
"Apache-2.0"
] | null | null | null | clarifai_grpc/grpc/api/resources_pb2.py | olga-clarifai/clarifai-python-grpc | c1d45ea965f781de5ccf682b142049c7628d0480 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: proto/clarifai/api/resources.proto
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from clarifai_grpc.grpc.api.status import status_pb2 as proto_dot_clarifai_dot_api_dot_status_dot_status__pb2
from clarifai_grpc.grpc.api.utils import extensions_pb2 as proto_dot_clarifai_dot_api_dot_utils_dot_extensions__pb2
from clarifai_grpc.grpc.auth.util import extension_pb2 as proto_dot_clarifai_dot_auth_dot_util_dot_extension__pb2
from google.protobuf import struct_pb2 as google_dot_protobuf_dot_struct__pb2
from google.protobuf import timestamp_pb2 as google_dot_protobuf_dot_timestamp__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='proto/clarifai/api/resources.proto',
package='clarifai.api',
syntax='proto3',
serialized_options=b'\n\025com.clarifai.grpc.apiP\001Zsgithub.com/Clarifai/clarifai-go-grpc/proto/clarifai/api/github.com/Clarifai/clarifai-go-grpc/proto/clarifai/api/api\242\002\004CAIP',
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,
dependencies=[proto_dot_clarifai_dot_api_dot_status_dot_status__pb2.DESCRIPTOR,proto_dot_clarifai_dot_api_dot_utils_dot_extensions__pb2.DESCRIPTOR,proto_dot_clarifai_dot_auth_dot_util_dot_extension__pb2.DESCRIPTOR,google_dot_protobuf_dot_struct__pb2.DESCRIPTOR,google_dot_protobuf_dot_timestamp__pb2.DESCRIPTOR,])
_EXPIRATIONACTION = _descriptor.EnumDescriptor(
name='ExpirationAction',
full_name='clarifai.api.ExpirationAction',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='EXPIRATION_ACTION_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='DELAY', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='EXPIRY', index=2, number=2,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23444,
serialized_end=23516,
)
_sym_db.RegisterEnumDescriptor(_EXPIRATIONACTION)
ExpirationAction = enum_type_wrapper.EnumTypeWrapper(_EXPIRATIONACTION)
_LICENSESCOPE = _descriptor.EnumDescriptor(
name='LicenseScope',
full_name='clarifai.api.LicenseScope',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='LICENSE_SCOPE_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='PREDICT', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='TRAIN', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='SEARCH', index=3, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23518,
serialized_end=23595,
)
_sym_db.RegisterEnumDescriptor(_LICENSESCOPE)
LicenseScope = enum_type_wrapper.EnumTypeWrapper(_LICENSESCOPE)
_VALUECOMPARATOR = _descriptor.EnumDescriptor(
name='ValueComparator',
full_name='clarifai.api.ValueComparator',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='CONCEPT_THRESHOLD_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='GREATER_THAN', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='GREATER_THAN_OR_EQUAL', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='LESS_THAN', index=3, number=3,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='LESS_THAN_OR_EQUAL', index=4, number=4,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='EQUAL', index=5, number=5,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23598,
serialized_end=23741,
)
_sym_db.RegisterEnumDescriptor(_VALUECOMPARATOR)
ValueComparator = enum_type_wrapper.EnumTypeWrapper(_VALUECOMPARATOR)
_EVALUATIONTYPE = _descriptor.EnumDescriptor(
name='EvaluationType',
full_name='clarifai.api.EvaluationType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='Classification', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='Detection', index=1, number=1,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23743,
serialized_end=23794,
)
_sym_db.RegisterEnumDescriptor(_EVALUATIONTYPE)
EvaluationType = enum_type_wrapper.EnumTypeWrapper(_EVALUATIONTYPE)
_APIEVENTTYPE = _descriptor.EnumDescriptor(
name='APIEventType',
full_name='clarifai.api.APIEventType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='API_EVENT_TYPE_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ON_PREM_PREDICT', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ON_PREM_TRAIN', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ON_PREM_SEARCH', index=3, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23796,
serialized_end=23898,
)
_sym_db.RegisterEnumDescriptor(_APIEVENTTYPE)
APIEventType = enum_type_wrapper.EnumTypeWrapper(_APIEVENTTYPE)
_USAGEINTERVALTYPE = _descriptor.EnumDescriptor(
name='UsageIntervalType',
full_name='clarifai.api.UsageIntervalType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='undef', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='day', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='month', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='year', index=3, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23900,
serialized_end=23960,
)
_sym_db.RegisterEnumDescriptor(_USAGEINTERVALTYPE)
UsageIntervalType = enum_type_wrapper.EnumTypeWrapper(_USAGEINTERVALTYPE)
_ROLETYPE = _descriptor.EnumDescriptor(
name='RoleType',
full_name='clarifai.api.RoleType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='TEAM', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ORG', index=1, number=1,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23962,
serialized_end=23991,
)
_sym_db.RegisterEnumDescriptor(_ROLETYPE)
RoleType = enum_type_wrapper.EnumTypeWrapper(_ROLETYPE)
_STATVALUEAGGTYPE = _descriptor.EnumDescriptor(
name='StatValueAggType',
full_name='clarifai.api.StatValueAggType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='SUM', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='AVG', index=1, number=1,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23993,
serialized_end=24029,
)
_sym_db.RegisterEnumDescriptor(_STATVALUEAGGTYPE)
StatValueAggType = enum_type_wrapper.EnumTypeWrapper(_STATVALUEAGGTYPE)
_STATTIMEAGGTYPE = _descriptor.EnumDescriptor(
name='StatTimeAggType',
full_name='clarifai.api.StatTimeAggType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='NO_TIME_AGG', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='YEAR', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='MONTH', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='WEEK', index=3, number=3,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='DAY', index=4, number=4,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='HOUR', index=5, number=5,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='MINUTE', index=6, number=6,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=24031,
serialized_end=24127,
)
_sym_db.RegisterEnumDescriptor(_STATTIMEAGGTYPE)
StatTimeAggType = enum_type_wrapper.EnumTypeWrapper(_STATTIMEAGGTYPE)
_VALIDATIONERRORTYPE = _descriptor.EnumDescriptor(
name='ValidationErrorType',
full_name='clarifai.api.ValidationErrorType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='VALIDATION_ERROR_TYPE_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESTRICTED', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='DATABASE', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='FORMAT', index=3, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=24129,
serialized_end=24227,
)
_sym_db.RegisterEnumDescriptor(_VALIDATIONERRORTYPE)
ValidationErrorType = enum_type_wrapper.EnumTypeWrapper(_VALIDATIONERRORTYPE)
EXPIRATION_ACTION_NOT_SET = 0
DELAY = 1
EXPIRY = 2
LICENSE_SCOPE_NOT_SET = 0
PREDICT = 1
TRAIN = 2
SEARCH = 3
CONCEPT_THRESHOLD_NOT_SET = 0
GREATER_THAN = 1
GREATER_THAN_OR_EQUAL = 2
LESS_THAN = 3
LESS_THAN_OR_EQUAL = 4
EQUAL = 5
Classification = 0
Detection = 1
API_EVENT_TYPE_NOT_SET = 0
ON_PREM_PREDICT = 1
ON_PREM_TRAIN = 2
ON_PREM_SEARCH = 3
undef = 0
day = 1
month = 2
year = 3
TEAM = 0
ORG = 1
SUM = 0
AVG = 1
NO_TIME_AGG = 0
YEAR = 1
MONTH = 2
WEEK = 3
DAY = 4
HOUR = 5
MINUTE = 6
VALIDATION_ERROR_TYPE_NOT_SET = 0
RESTRICTED = 1
DATABASE = 2
FORMAT = 3
_MODELTYPEFIELD_MODELTYPEFIELDTYPE = _descriptor.EnumDescriptor(
name='ModelTypeFieldType',
full_name='clarifai.api.ModelTypeField.ModelTypeFieldType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='INVALID_MODEL_TYPE_FIELD_TYPE', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='BOOLEAN', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='STRING', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='NUMBER', index=3, number=3,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ARRAY_OF_CONCEPTS', index=4, number=4,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ARRAY_OF_CONCEPTS_WITH_THRESHOLD', index=5, number=5,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RANGE', index=6, number=7,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ENUM', index=7, number=8,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='COLLABORATORS', index=8, number=9,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='JSON', index=9, number=10,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ARRAY_OF_NUMBERS', index=10, number=11,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='WORKFLOW_EMBED_MODELS', index=11, number=12,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ARRAY_OF_STRINGS', index=12, number=13,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RECURSIVE_ENUM', index=13, number=14,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=10164,
serialized_end=10464,
)
_sym_db.RegisterEnumDescriptor(_MODELTYPEFIELD_MODELTYPEFIELDTYPE)
_TASK_TASKTYPE = _descriptor.EnumDescriptor(
name='TaskType',
full_name='clarifai.api.Task.TaskType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='TYPE_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='CONCEPTS_CLASSIFICATION', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='BOUNDING_BOX_DETECTION', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='POLYGON_DETECTION', index=3, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=20162,
serialized_end=20270,
)
_sym_db.RegisterEnumDescriptor(_TASK_TASKTYPE)
_TASKWORKER_TASKWORKERSTRATEGY = _descriptor.EnumDescriptor(
name='TaskWorkerStrategy',
full_name='clarifai.api.TaskWorker.TaskWorkerStrategy',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='WORKER_STRATEGY_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='PARTITIONED', index=1, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='FULL', index=2, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=20552,
serialized_end=20634,
)
_sym_db.RegisterEnumDescriptor(_TASKWORKER_TASKWORKERSTRATEGY)
_TASKWORKERPARTITIONEDSTRATEGYINFO_TASKWORKERPARTITIONEDSTRATEGY = _descriptor.EnumDescriptor(
name='TaskWorkerPartitionedStrategy',
full_name='clarifai.api.TaskWorkerPartitionedStrategyInfo.TaskWorkerPartitionedStrategy',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='PARTITIONED_WORKER_STRATEGY_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='EVENLY', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='WEIGHTED', index=2, number=2,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=20853,
serialized_end=20951,
)
_sym_db.RegisterEnumDescriptor(_TASKWORKERPARTITIONEDSTRATEGYINFO_TASKWORKERPARTITIONEDSTRATEGY)
_TASKINPUTSOURCE_TASKINPUTSOURCETYPE = _descriptor.EnumDescriptor(
name='TaskInputSourceType',
full_name='clarifai.api.TaskInputSource.TaskInputSourceType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='INPUT_SOURCE_TYPE_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ALL_INPUTS', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='SAVED_SEARCH', index=2, number=2,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=21050,
serialized_end=21136,
)
_sym_db.RegisterEnumDescriptor(_TASKINPUTSOURCE_TASKINPUTSOURCETYPE)
_TASKREVIEW_TASKREVIEWSTRATEGY = _descriptor.EnumDescriptor(
name='TaskReviewStrategy',
full_name='clarifai.api.TaskReview.TaskReviewStrategy',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='TASK_REVIEW_STRATEGY_NOT_SET', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='NONE', index=1, number=1,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='MANUAL', index=2, number=2,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='CONSENSUS', index=3, number=3,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=21392,
serialized_end=21483,
)
_sym_db.RegisterEnumDescriptor(_TASKREVIEW_TASKREVIEWSTRATEGY)
_VISIBILITY_GETTABLE = _descriptor.EnumDescriptor(
name='Gettable',
full_name='clarifai.api.Visibility.Gettable',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='UNKNOWN_VISIBILITY', index=0, number=0,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='PRIVATE', index=1, number=10,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='ORG', index=2, number=30,
serialized_options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='PUBLIC', index=3, number=50,
serialized_options=None,
type=None),
],
containing_type=None,
serialized_options=None,
serialized_start=23110,
serialized_end=23178,
)
_sym_db.RegisterEnumDescriptor(_VISIBILITY_GETTABLE)
_ANNOTATION = _descriptor.Descriptor(
name='Annotation',
full_name='clarifai.api.Annotation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Annotation.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input_id', full_name='clarifai.api.Annotation.input_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.Annotation.data', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='annotation_info', full_name='clarifai.api.Annotation.annotation_info', index=3,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.Annotation.user_id', index=4,
number=15, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_version_id', full_name='clarifai.api.Annotation.model_version_id', index=5,
number=16, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='embed_model_version_id', full_name='clarifai.api.Annotation.embed_model_version_id', index=6,
number=14, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.Annotation.status', index=7,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Annotation.created_at', index=8,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Annotation.modified_at', index=9,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='trusted', full_name='clarifai.api.Annotation.trusted', index=10,
number=10, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input_level', full_name='clarifai.api.Annotation.input_level', index=11,
number=17, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='consensus_info', full_name='clarifai.api.Annotation.consensus_info', index=12,
number=18, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='task_id', full_name='clarifai.api.Annotation.task_id', index=13,
number=19, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=241,
serialized_end=726,
)
_APP = _descriptor.Descriptor(
name='App',
full_name='clarifai.api.App',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.App.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.App.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='default_language', full_name='clarifai.api.App.default_language', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='default_workflow_id', full_name='clarifai.api.App.default_workflow_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.App.user_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.App.created_at', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.App.modified_at', index=6,
number=17, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='legal_consent_status', full_name='clarifai.api.App.legal_consent_status', index=7,
number=7, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.App.metadata', index=8,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.App.description', index=9,
number=14, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sample_ms', full_name='clarifai.api.App.sample_ms', index=10,
number=15, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.App.visibility', index=11,
number=16, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data_tier_id', full_name='clarifai.api.App.data_tier_id', index=12,
number=18, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='is_starred', full_name='clarifai.api.App.is_starred', index=13,
number=19, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='star_count', full_name='clarifai.api.App.star_count', index=14,
number=20, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=729,
serialized_end=1168,
)
_APPQUERY = _descriptor.Descriptor(
name='AppQuery',
full_name='clarifai.api.AppQuery',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.AppQuery.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1170,
serialized_end=1194,
)
_COLLABORATOR = _descriptor.Descriptor(
name='Collaborator',
full_name='clarifai.api.Collaborator',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Collaborator.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app', full_name='clarifai.api.Collaborator.app', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user', full_name='clarifai.api.Collaborator.user', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='scopes', full_name='clarifai.api.Collaborator.scopes', index=3,
number=4, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='endpoints', full_name='clarifai.api.Collaborator.endpoints', index=4,
number=5, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Collaborator.created_at', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Collaborator.modified_at', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='deleted_at', full_name='clarifai.api.Collaborator.deleted_at', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1197,
serialized_end=1469,
)
_COLLABORATION = _descriptor.Descriptor(
name='Collaboration',
full_name='clarifai.api.Collaboration',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='app', full_name='clarifai.api.Collaboration.app', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_owner', full_name='clarifai.api.Collaboration.app_owner', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='scopes', full_name='clarifai.api.Collaboration.scopes', index=2,
number=3, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='endpoints', full_name='clarifai.api.Collaboration.endpoints', index=3,
number=4, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Collaboration.created_at', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1472,
serialized_end=1641,
)
_AUDIO = _descriptor.Descriptor(
name='Audio',
full_name='clarifai.api.Audio',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='url', full_name='clarifai.api.Audio.url', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='base64', full_name='clarifai.api.Audio.base64', index=1,
number=2, type=12, cpp_type=9, label=1,
has_default_value=False, default_value=b"",
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='allow_duplicate_url', full_name='clarifai.api.Audio.allow_duplicate_url', index=2,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hosted', full_name='clarifai.api.Audio.hosted', index=3,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='audio_info', full_name='clarifai.api.Audio.audio_info', index=4,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1644,
serialized_end=1795,
)
_AUDIOINFO = _descriptor.Descriptor(
name='AudioInfo',
full_name='clarifai.api.AudioInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='audio_format', full_name='clarifai.api.AudioInfo.audio_format', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sample_rate', full_name='clarifai.api.AudioInfo.sample_rate', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='duration_seconds', full_name='clarifai.api.AudioInfo.duration_seconds', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='bit_rate', full_name='clarifai.api.AudioInfo.bit_rate', index=3,
number=4, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1797,
serialized_end=1895,
)
_TRACK = _descriptor.Descriptor(
name='Track',
full_name='clarifai.api.Track',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Track.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.Track.data', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='time_info', full_name='clarifai.api.Track.time_info', index=2,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='quality', full_name='clarifai.api.Track.quality', index=3,
number=5, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1897,
serialized_end=2016,
)
_CLUSTER = _descriptor.Descriptor(
name='Cluster',
full_name='clarifai.api.Cluster',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Cluster.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='count', full_name='clarifai.api.Cluster.count', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='score', full_name='clarifai.api.Cluster.score', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hits', full_name='clarifai.api.Cluster.hits', index=3,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='projection', full_name='clarifai.api.Cluster.projection', index=4,
number=5, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2018,
serialized_end=2122,
)
_COLOR = _descriptor.Descriptor(
name='Color',
full_name='clarifai.api.Color',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='raw_hex', full_name='clarifai.api.Color.raw_hex', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='w3c', full_name='clarifai.api.Color.w3c', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.Color.value', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2124,
serialized_end=2201,
)
_W3C = _descriptor.Descriptor(
name='W3C',
full_name='clarifai.api.W3C',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='hex', full_name='clarifai.api.W3C.hex', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.W3C.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2203,
serialized_end=2235,
)
_USERAPPIDSET = _descriptor.Descriptor(
name='UserAppIDSet',
full_name='clarifai.api.UserAppIDSet',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.UserAppIDSet.user_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.UserAppIDSet.app_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2237,
serialized_end=2284,
)
_PATCHACTION = _descriptor.Descriptor(
name='PatchAction',
full_name='clarifai.api.PatchAction',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='op', full_name='clarifai.api.PatchAction.op', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='merge_conflict_resolution', full_name='clarifai.api.PatchAction.merge_conflict_resolution', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='path', full_name='clarifai.api.PatchAction.path', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2286,
serialized_end=2360,
)
_CONCEPT = _descriptor.Descriptor(
name='Concept',
full_name='clarifai.api.Concept',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Concept.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.Concept.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.Concept.value', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\325\265\030\000\000\200?\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Concept.created_at', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='language', full_name='clarifai.api.Concept.language', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.Concept.app_id', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='definition', full_name='clarifai.api.Concept.definition', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='vocab_id', full_name='clarifai.api.Concept.vocab_id', index=7,
number=8, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.Concept.visibility', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.Concept.user_id', index=9,
number=10, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2363,
serialized_end=2609,
)
_CONCEPTCOUNT = _descriptor.Descriptor(
name='ConceptCount',
full_name='clarifai.api.ConceptCount',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ConceptCount.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.ConceptCount.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept_type_count', full_name='clarifai.api.ConceptCount.concept_type_count', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='detail_concept_count', full_name='clarifai.api.ConceptCount.detail_concept_count', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2612,
serialized_end=2776,
)
_CONCEPTTYPECOUNT = _descriptor.Descriptor(
name='ConceptTypeCount',
full_name='clarifai.api.ConceptTypeCount',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='positive', full_name='clarifai.api.ConceptTypeCount.positive', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='negative', full_name='clarifai.api.ConceptTypeCount.negative', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2778,
serialized_end=2844,
)
_DETAILCONCEPTCOUNT = _descriptor.Descriptor(
name='DetailConceptCount',
full_name='clarifai.api.DetailConceptCount',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='processed', full_name='clarifai.api.DetailConceptCount.processed', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to_process', full_name='clarifai.api.DetailConceptCount.to_process', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='errors', full_name='clarifai.api.DetailConceptCount.errors', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='processing', full_name='clarifai.api.DetailConceptCount.processing', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=2847,
serialized_end=3070,
)
_CONCEPTQUERY = _descriptor.Descriptor(
name='ConceptQuery',
full_name='clarifai.api.ConceptQuery',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.ConceptQuery.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='language', full_name='clarifai.api.ConceptQuery.language', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='workflow_id', full_name='clarifai.api.ConceptQuery.workflow_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3072,
serialized_end=3139,
)
_CONCEPTRELATION = _descriptor.Descriptor(
name='ConceptRelation',
full_name='clarifai.api.ConceptRelation',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ConceptRelation.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='subject_concept', full_name='clarifai.api.ConceptRelation.subject_concept', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='object_concept', full_name='clarifai.api.ConceptRelation.object_concept', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='predicate', full_name='clarifai.api.ConceptRelation.predicate', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='knowledge_graph_id', full_name='clarifai.api.ConceptRelation.knowledge_graph_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.ConceptRelation.visibility', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3142,
serialized_end=3359,
)
_KNOWLEDGEGRAPH = _descriptor.Descriptor(
name='KnowledgeGraph',
full_name='clarifai.api.KnowledgeGraph',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.KnowledgeGraph.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.KnowledgeGraph.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.KnowledgeGraph.description', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='examples_app_id', full_name='clarifai.api.KnowledgeGraph.examples_app_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sampled_examples_app_id', full_name='clarifai.api.KnowledgeGraph.sampled_examples_app_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3361,
serialized_end=3482,
)
_CONCEPTMAPPINGJOB = _descriptor.Descriptor(
name='ConceptMappingJob',
full_name='clarifai.api.ConceptMappingJob',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='knowledge_graph_id', full_name='clarifai.api.ConceptMappingJob.knowledge_graph_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept_ids', full_name='clarifai.api.ConceptMappingJob.concept_ids', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3484,
serialized_end=3552,
)
_CONCEPTLANGUAGE = _descriptor.Descriptor(
name='ConceptLanguage',
full_name='clarifai.api.ConceptLanguage',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ConceptLanguage.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.ConceptLanguage.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='definition', full_name='clarifai.api.ConceptLanguage.definition', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3554,
serialized_end=3617,
)
_DATA = _descriptor.Descriptor(
name='Data',
full_name='clarifai.api.Data',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='image', full_name='clarifai.api.Data.image', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='video', full_name='clarifai.api.Data.video', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concepts', full_name='clarifai.api.Data.concepts', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.Data.metadata', index=3,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='geo', full_name='clarifai.api.Data.geo', index=4,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='colors', full_name='clarifai.api.Data.colors', index=5,
number=7, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='clusters', full_name='clarifai.api.Data.clusters', index=6,
number=8, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='embeddings', full_name='clarifai.api.Data.embeddings', index=7,
number=9, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='regions', full_name='clarifai.api.Data.regions', index=8,
number=11, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='frames', full_name='clarifai.api.Data.frames', index=9,
number=12, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='text', full_name='clarifai.api.Data.text', index=10,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='audio', full_name='clarifai.api.Data.audio', index=11,
number=14, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tracks', full_name='clarifai.api.Data.tracks', index=12,
number=15, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='time_segments', full_name='clarifai.api.Data.time_segments', index=13,
number=16, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=3620,
serialized_end=4182,
)
_REGION = _descriptor.Descriptor(
name='Region',
full_name='clarifai.api.Region',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Region.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='region_info', full_name='clarifai.api.Region.region_info', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.Region.data', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.Region.value', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='track_id', full_name='clarifai.api.Region.track_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4185,
serialized_end=4319,
)
_REGIONINFO = _descriptor.Descriptor(
name='RegionInfo',
full_name='clarifai.api.RegionInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='bounding_box', full_name='clarifai.api.RegionInfo.bounding_box', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='mask', full_name='clarifai.api.RegionInfo.mask', index=1,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='polygon', full_name='clarifai.api.RegionInfo.polygon', index=2,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='point', full_name='clarifai.api.RegionInfo.point', index=3,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4322,
serialized_end=4505,
)
_BOUNDINGBOX = _descriptor.Descriptor(
name='BoundingBox',
full_name='clarifai.api.BoundingBox',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='top_row', full_name='clarifai.api.BoundingBox.top_row', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='left_col', full_name='clarifai.api.BoundingBox.left_col', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='bottom_row', full_name='clarifai.api.BoundingBox.bottom_row', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='right_col', full_name='clarifai.api.BoundingBox.right_col', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4507,
serialized_end=4618,
)
_FRAMEINFO = _descriptor.Descriptor(
name='FrameInfo',
full_name='clarifai.api.FrameInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='index', full_name='clarifai.api.FrameInfo.index', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='time', full_name='clarifai.api.FrameInfo.time', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4620,
serialized_end=4672,
)
_FRAME = _descriptor.Descriptor(
name='Frame',
full_name='clarifai.api.Frame',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='frame_info', full_name='clarifai.api.Frame.frame_info', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.Frame.data', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Frame.id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4674,
serialized_end=4772,
)
_MASK = _descriptor.Descriptor(
name='Mask',
full_name='clarifai.api.Mask',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='image', full_name='clarifai.api.Mask.image', index=0,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4774,
serialized_end=4822,
)
_POLYGON = _descriptor.Descriptor(
name='Polygon',
full_name='clarifai.api.Polygon',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='points', full_name='clarifai.api.Polygon.points', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4824,
serialized_end=4870,
)
_POINT = _descriptor.Descriptor(
name='Point',
full_name='clarifai.api.Point',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='row', full_name='clarifai.api.Point.row', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='col', full_name='clarifai.api.Point.col', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='z', full_name='clarifai.api.Point.z', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4872,
serialized_end=4928,
)
_EMBEDDING = _descriptor.Descriptor(
name='Embedding',
full_name='clarifai.api.Embedding',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='vector', full_name='clarifai.api.Embedding.vector', index=0,
number=1, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\020\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='num_dimensions', full_name='clarifai.api.Embedding.num_dimensions', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4930,
serialized_end=4985,
)
_GEOPOINT = _descriptor.Descriptor(
name='GeoPoint',
full_name='clarifai.api.GeoPoint',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='longitude', full_name='clarifai.api.GeoPoint.longitude', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='latitude', full_name='clarifai.api.GeoPoint.latitude', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=4987,
serialized_end=5046,
)
_GEOLIMIT = _descriptor.Descriptor(
name='GeoLimit',
full_name='clarifai.api.GeoLimit',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.GeoLimit.type', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.GeoLimit.value', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5048,
serialized_end=5093,
)
_GEOBOXEDPOINT = _descriptor.Descriptor(
name='GeoBoxedPoint',
full_name='clarifai.api.GeoBoxedPoint',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='geo_point', full_name='clarifai.api.GeoBoxedPoint.geo_point', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5095,
serialized_end=5153,
)
_GEO = _descriptor.Descriptor(
name='Geo',
full_name='clarifai.api.Geo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='geo_point', full_name='clarifai.api.Geo.geo_point', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='geo_limit', full_name='clarifai.api.Geo.geo_limit', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='geo_box', full_name='clarifai.api.Geo.geo_box', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5156,
serialized_end=5293,
)
_IMAGE = _descriptor.Descriptor(
name='Image',
full_name='clarifai.api.Image',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='url', full_name='clarifai.api.Image.url', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='base64', full_name='clarifai.api.Image.base64', index=1,
number=2, type=12, cpp_type=9, label=1,
has_default_value=False, default_value=b"",
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='allow_duplicate_url', full_name='clarifai.api.Image.allow_duplicate_url', index=2,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hosted', full_name='clarifai.api.Image.hosted', index=3,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='image_info', full_name='clarifai.api.Image.image_info', index=4,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5296,
serialized_end=5453,
)
_IMAGEINFO = _descriptor.Descriptor(
name='ImageInfo',
full_name='clarifai.api.ImageInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='width', full_name='clarifai.api.ImageInfo.width', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='height', full_name='clarifai.api.ImageInfo.height', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='format', full_name='clarifai.api.ImageInfo.format', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='color_mode', full_name='clarifai.api.ImageInfo.color_mode', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5455,
serialized_end=5533,
)
_HOSTEDURL = _descriptor.Descriptor(
name='HostedURL',
full_name='clarifai.api.HostedURL',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='prefix', full_name='clarifai.api.HostedURL.prefix', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='suffix', full_name='clarifai.api.HostedURL.suffix', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sizes', full_name='clarifai.api.HostedURL.sizes', index=2,
number=3, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='crossorigin', full_name='clarifai.api.HostedURL.crossorigin', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5535,
serialized_end=5614,
)
_INPUT = _descriptor.Descriptor(
name='Input',
full_name='clarifai.api.Input',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Input.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.Input.data', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Input.created_at', index=2,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Input.modified_at', index=3,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.Input.status', index=4,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='dataset_ids', full_name='clarifai.api.Input.dataset_ids', index=5,
number=7, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5617,
serialized_end=5839,
)
_INPUTCOUNT = _descriptor.Descriptor(
name='InputCount',
full_name='clarifai.api.InputCount',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='processed', full_name='clarifai.api.InputCount.processed', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to_process', full_name='clarifai.api.InputCount.to_process', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='errors', full_name='clarifai.api.InputCount.errors', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='processing', full_name='clarifai.api.InputCount.processing', index=3,
number=4, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='reindexed', full_name='clarifai.api.InputCount.reindexed', index=4,
number=5, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='to_reindex', full_name='clarifai.api.InputCount.to_reindex', index=5,
number=6, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='reindex_errors', full_name='clarifai.api.InputCount.reindex_errors', index=6,
number=7, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='reindexing', full_name='clarifai.api.InputCount.reindexing', index=7,
number=8, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=5842,
serialized_end=6060,
)
_DATASETFILTER = _descriptor.Descriptor(
name='DatasetFilter',
full_name='clarifai.api.DatasetFilter',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.DatasetFilter.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.DatasetFilter.created_at', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.DatasetFilter.modified_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.DatasetFilter.user_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.DatasetFilter.app_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='dataset_id', full_name='clarifai.api.DatasetFilter.dataset_id', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='saved_search', full_name='clarifai.api.DatasetFilter.saved_search', index=6,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=6063,
serialized_end=6290,
)
_DATASETVERSION = _descriptor.Descriptor(
name='DatasetVersion',
full_name='clarifai.api.DatasetVersion',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.DatasetVersion.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.DatasetVersion.created_at', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.DatasetVersion.modified_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.DatasetVersion.app_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.DatasetVersion.user_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='dataset_id', full_name='clarifai.api.DatasetVersion.dataset_id', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='dataset_filter_config', full_name='clarifai.api.DatasetVersion.dataset_filter_config', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.DatasetVersion.status', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.DatasetVersion.description', index=8,
number=10, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='summary', full_name='clarifai.api.DatasetVersion.summary', index=9,
number=11, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.DatasetVersion.metadata', index=10,
number=12, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.DatasetVersion.visibility', index=11,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='embed_model_version_ids', full_name='clarifai.api.DatasetVersion.embed_model_version_ids', index=12,
number=14, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='data_config', full_name='clarifai.api.DatasetVersion.data_config',
index=0, containing_type=None, fields=[]),
],
serialized_start=6293,
serialized_end=6816,
)
_DATASETVERSIONDATASETFILTERCONFIG = _descriptor.Descriptor(
name='DatasetVersionDatasetFilterConfig',
full_name='clarifai.api.DatasetVersionDatasetFilterConfig',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='dataset_filter', full_name='clarifai.api.DatasetVersionDatasetFilterConfig.dataset_filter', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=6818,
serialized_end=6906,
)
_DATASETVERSIONSUMMARY_INPUTCOUNTSENTRY = _descriptor.Descriptor(
name='InputCountsEntry',
full_name='clarifai.api.DatasetVersionSummary.InputCountsEntry',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='key', full_name='clarifai.api.DatasetVersionSummary.InputCountsEntry.key', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.DatasetVersionSummary.InputCountsEntry.value', index=1,
number=2, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=b'8\001',
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=7010,
serialized_end=7060,
)
_DATASETVERSIONSUMMARY = _descriptor.Descriptor(
name='DatasetVersionSummary',
full_name='clarifai.api.DatasetVersionSummary',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='input_counts', full_name='clarifai.api.DatasetVersionSummary.input_counts', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[_DATASETVERSIONSUMMARY_INPUTCOUNTSENTRY, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=6909,
serialized_end=7060,
)
_WORKFLOWRESULTSSIMILARITY = _descriptor.Descriptor(
name='WorkflowResultsSimilarity',
full_name='clarifai.api.WorkflowResultsSimilarity',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='probe_input', full_name='clarifai.api.WorkflowResultsSimilarity.probe_input', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='pool_results', full_name='clarifai.api.WorkflowResultsSimilarity.pool_results', index=1,
number=2, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=7062,
serialized_end=7172,
)
_KEY = _descriptor.Descriptor(
name='Key',
full_name='clarifai.api.Key',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Key.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.Key.type', index=1,
number=8, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.Key.description', index=2,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='scopes', full_name='clarifai.api.Key.scopes', index=3,
number=3, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='endpoints', full_name='clarifai.api.Key.endpoints', index=4,
number=7, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='apps', full_name='clarifai.api.Key.apps', index=5,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Key.created_at', index=6,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='expires_at', full_name='clarifai.api.Key.expires_at', index=7,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='authorized_idp_ids', full_name='clarifai.api.Key.authorized_idp_ids', index=8,
number=9, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=7175,
serialized_end=7419,
)
_MODEL = _descriptor.Descriptor(
name='Model',
full_name='clarifai.api.Model',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Model.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.Model.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Model.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Model.modified_at', index=3,
number=19, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.Model.app_id', index=4,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='output_info', full_name='clarifai.api.Model.output_info', index=5,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_version', full_name='clarifai.api.Model.model_version', index=6,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='display_name', full_name='clarifai.api.Model.display_name', index=7,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.Model.user_id', index=8,
number=9, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input_info', full_name='clarifai.api.Model.input_info', index=9,
number=12, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='train_info', full_name='clarifai.api.Model.train_info', index=10,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_type_id', full_name='clarifai.api.Model.model_type_id', index=11,
number=14, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.Model.visibility', index=12,
number=15, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.Model.description', index=13,
number=16, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.Model.metadata', index=14,
number=17, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='notes', full_name='clarifai.api.Model.notes', index=15,
number=18, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='toolkits', full_name='clarifai.api.Model.toolkits', index=16,
number=20, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='use_cases', full_name='clarifai.api.Model.use_cases', index=17,
number=21, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='languages', full_name='clarifai.api.Model.languages', index=18,
number=25, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='is_starred', full_name='clarifai.api.Model.is_starred', index=19,
number=22, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='star_count', full_name='clarifai.api.Model.star_count', index=20,
number=23, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='import_info', full_name='clarifai.api.Model.import_info', index=21,
number=24, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=7422,
serialized_end=8128,
)
_MODELREFERENCE = _descriptor.Descriptor(
name='ModelReference',
full_name='clarifai.api.ModelReference',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ModelReference.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_id', full_name='clarifai.api.ModelReference.model_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='url', full_name='clarifai.api.ModelReference.url', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.ModelReference.name', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.ModelReference.metadata', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8130,
serialized_end=8246,
)
_MODELVERSIONINPUTEXAMPLE = _descriptor.Descriptor(
name='ModelVersionInputExample',
full_name='clarifai.api.ModelVersionInputExample',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ModelVersionInputExample.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_id', full_name='clarifai.api.ModelVersionInputExample.model_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_version_id', full_name='clarifai.api.ModelVersionInputExample.model_version_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.ModelVersionInputExample.data', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.ModelVersionInputExample.name', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.ModelVersionInputExample.description', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8249,
serialized_end=8400,
)
_OUTPUTINFO = _descriptor.Descriptor(
name='OutputInfo',
full_name='clarifai.api.OutputInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.OutputInfo.data', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='output_config', full_name='clarifai.api.OutputInfo.output_config', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='message', full_name='clarifai.api.OutputInfo.message', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.OutputInfo.type', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='type_ext', full_name='clarifai.api.OutputInfo.type_ext', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='fields_map', full_name='clarifai.api.OutputInfo.fields_map', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='params', full_name='clarifai.api.OutputInfo.params', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8403,
serialized_end=8635,
)
_INPUTINFO = _descriptor.Descriptor(
name='InputInfo',
full_name='clarifai.api.InputInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='fields_map', full_name='clarifai.api.InputInfo.fields_map', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='params', full_name='clarifai.api.InputInfo.params', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8637,
serialized_end=8734,
)
_TRAININFO = _descriptor.Descriptor(
name='TrainInfo',
full_name='clarifai.api.TrainInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='params', full_name='clarifai.api.TrainInfo.params', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8736,
serialized_end=8788,
)
_IMPORTINFO = _descriptor.Descriptor(
name='ImportInfo',
full_name='clarifai.api.ImportInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='params', full_name='clarifai.api.ImportInfo.params', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8790,
serialized_end=8843,
)
_OUTPUTCONFIG = _descriptor.Descriptor(
name='OutputConfig',
full_name='clarifai.api.OutputConfig',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='concepts_mutually_exclusive', full_name='clarifai.api.OutputConfig.concepts_mutually_exclusive', index=0,
number=1, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='closed_environment', full_name='clarifai.api.OutputConfig.closed_environment', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='existing_model_id', full_name='clarifai.api.OutputConfig.existing_model_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='language', full_name='clarifai.api.OutputConfig.language', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hyper_parameters', full_name='clarifai.api.OutputConfig.hyper_parameters', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='max_concepts', full_name='clarifai.api.OutputConfig.max_concepts', index=5,
number=6, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='min_value', full_name='clarifai.api.OutputConfig.min_value', index=6,
number=7, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='select_concepts', full_name='clarifai.api.OutputConfig.select_concepts', index=7,
number=8, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='training_timeout', full_name='clarifai.api.OutputConfig.training_timeout', index=8,
number=9, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sample_ms', full_name='clarifai.api.OutputConfig.sample_ms', index=9,
number=10, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hyper_params', full_name='clarifai.api.OutputConfig.hyper_params', index=10,
number=13, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='embed_model_version_id', full_name='clarifai.api.OutputConfig.embed_model_version_id', index=11,
number=14, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='fail_on_missing_positive_examples', full_name='clarifai.api.OutputConfig.fail_on_missing_positive_examples', index=12,
number=15, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_metadata', full_name='clarifai.api.OutputConfig.model_metadata', index=13,
number=17, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=8846,
serialized_end=9361,
)
_MODELTYPE = _descriptor.Descriptor(
name='ModelType',
full_name='clarifai.api.ModelType',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ModelType.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='title', full_name='clarifai.api.ModelType.title', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.ModelType.description', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.ModelType.type', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input_fields', full_name='clarifai.api.ModelType.input_fields', index=4,
number=5, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='output_fields', full_name='clarifai.api.ModelType.output_fields', index=5,
number=6, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='trainable', full_name='clarifai.api.ModelType.trainable', index=6,
number=8, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='creatable', full_name='clarifai.api.ModelType.creatable', index=7,
number=9, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='internal_only', full_name='clarifai.api.ModelType.internal_only', index=8,
number=10, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_type_fields', full_name='clarifai.api.ModelType.model_type_fields', index=9,
number=11, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='requires_sequential_frames', full_name='clarifai.api.ModelType.requires_sequential_frames', index=10,
number=12, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='evaluable', full_name='clarifai.api.ModelType.evaluable', index=11,
number=13, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='expected_pretrained_input_fields', full_name='clarifai.api.ModelType.expected_pretrained_input_fields', index=12,
number=14, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='expected_pretrained_output_fields', full_name='clarifai.api.ModelType.expected_pretrained_output_fields', index=13,
number=15, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=9364,
serialized_end=9796,
)
_MODELTYPEFIELD = _descriptor.Descriptor(
name='ModelTypeField',
full_name='clarifai.api.ModelTypeField',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='path', full_name='clarifai.api.ModelTypeField.path', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='field_type', full_name='clarifai.api.ModelTypeField.field_type', index=1,
number=2, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='default_value', full_name='clarifai.api.ModelTypeField.default_value', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.ModelTypeField.description', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='placeholder', full_name='clarifai.api.ModelTypeField.placeholder', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_type_enum_options', full_name='clarifai.api.ModelTypeField.model_type_enum_options', index=5,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='internal_only', full_name='clarifai.api.ModelTypeField.internal_only', index=6,
number=7, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='required', full_name='clarifai.api.ModelTypeField.required', index=7,
number=8, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_type_range_info', full_name='clarifai.api.ModelTypeField.model_type_range_info', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_MODELTYPEFIELD_MODELTYPEFIELDTYPE,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=9799,
serialized_end=10464,
)
_MODELTYPERANGEINFO = _descriptor.Descriptor(
name='ModelTypeRangeInfo',
full_name='clarifai.api.ModelTypeRangeInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='min', full_name='clarifai.api.ModelTypeRangeInfo.min', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='max', full_name='clarifai.api.ModelTypeRangeInfo.max', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='step', full_name='clarifai.api.ModelTypeRangeInfo.step', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=10466,
serialized_end=10526,
)
_MODELTYPEENUMOPTION = _descriptor.Descriptor(
name='ModelTypeEnumOption',
full_name='clarifai.api.ModelTypeEnumOption',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ModelTypeEnumOption.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.ModelTypeEnumOption.description', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_type_fields', full_name='clarifai.api.ModelTypeEnumOption.model_type_fields', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='internal_only', full_name='clarifai.api.ModelTypeEnumOption.internal_only', index=3,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=10529,
serialized_end=10663,
)
_MODELQUERY = _descriptor.Descriptor(
name='ModelQuery',
full_name='clarifai.api.ModelQuery',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.ModelQuery.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.ModelQuery.type', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_type_id', full_name='clarifai.api.ModelQuery.model_type_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=10665,
serialized_end=10732,
)
_MODELVERSION = _descriptor.Descriptor(
name='ModelVersion',
full_name='clarifai.api.ModelVersion',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.ModelVersion.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.ModelVersion.created_at', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.ModelVersion.status', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='active_concept_count', full_name='clarifai.api.ModelVersion.active_concept_count', index=3,
number=4, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metrics', full_name='clarifai.api.ModelVersion.metrics', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='total_input_count', full_name='clarifai.api.ModelVersion.total_input_count', index=5,
number=6, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='completed_at', full_name='clarifai.api.ModelVersion.completed_at', index=6,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.ModelVersion.description', index=7,
number=11, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.ModelVersion.visibility', index=8,
number=12, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.ModelVersion.app_id', index=9,
number=13, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.ModelVersion.user_id', index=10,
number=14, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.ModelVersion.modified_at', index=11,
number=15, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.ModelVersion.metadata', index=12,
number=16, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='license', full_name='clarifai.api.ModelVersion.license', index=13,
number=17, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=10735,
serialized_end=11220,
)
_LABELCOUNT = _descriptor.Descriptor(
name='LabelCount',
full_name='clarifai.api.LabelCount',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='concept_name', full_name='clarifai.api.LabelCount.concept_name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='count', full_name='clarifai.api.LabelCount.count', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11222,
serialized_end=11271,
)
_LABELDISTRIBUTION = _descriptor.Descriptor(
name='LabelDistribution',
full_name='clarifai.api.LabelDistribution',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='positive_label_counts', full_name='clarifai.api.LabelDistribution.positive_label_counts', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11273,
serialized_end=11349,
)
_COOCCURRENCEMATRIXENTRY = _descriptor.Descriptor(
name='CooccurrenceMatrixEntry',
full_name='clarifai.api.CooccurrenceMatrixEntry',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='row', full_name='clarifai.api.CooccurrenceMatrixEntry.row', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='col', full_name='clarifai.api.CooccurrenceMatrixEntry.col', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='count', full_name='clarifai.api.CooccurrenceMatrixEntry.count', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11351,
serialized_end=11417,
)
_COOCCURRENCEMATRIX = _descriptor.Descriptor(
name='CooccurrenceMatrix',
full_name='clarifai.api.CooccurrenceMatrix',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='matrix', full_name='clarifai.api.CooccurrenceMatrix.matrix', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept_ids', full_name='clarifai.api.CooccurrenceMatrix.concept_ids', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11419,
serialized_end=11515,
)
_CONFUSIONMATRIXENTRY = _descriptor.Descriptor(
name='ConfusionMatrixEntry',
full_name='clarifai.api.ConfusionMatrixEntry',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='predicted', full_name='clarifai.api.ConfusionMatrixEntry.predicted', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='actual', full_name='clarifai.api.ConfusionMatrixEntry.actual', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.ConfusionMatrixEntry.value', index=2,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11517,
serialized_end=11595,
)
_CONFUSIONMATRIX = _descriptor.Descriptor(
name='ConfusionMatrix',
full_name='clarifai.api.ConfusionMatrix',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='matrix', full_name='clarifai.api.ConfusionMatrix.matrix', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept_ids', full_name='clarifai.api.ConfusionMatrix.concept_ids', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11597,
serialized_end=11687,
)
_ROC = _descriptor.Descriptor(
name='ROC',
full_name='clarifai.api.ROC',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='fpr', full_name='clarifai.api.ROC.fpr', index=0,
number=1, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tpr', full_name='clarifai.api.ROC.tpr', index=1,
number=2, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='thresholds', full_name='clarifai.api.ROC.thresholds', index=2,
number=3, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='fpr_per_image', full_name='clarifai.api.ROC.fpr_per_image', index=3,
number=4, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='fpr_per_object', full_name='clarifai.api.ROC.fpr_per_object', index=4,
number=5, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11689,
serialized_end=11805,
)
_PRECISIONRECALLCURVE = _descriptor.Descriptor(
name='PrecisionRecallCurve',
full_name='clarifai.api.PrecisionRecallCurve',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='recall', full_name='clarifai.api.PrecisionRecallCurve.recall', index=0,
number=1, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='precision', full_name='clarifai.api.PrecisionRecallCurve.precision', index=1,
number=2, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='thresholds', full_name='clarifai.api.PrecisionRecallCurve.thresholds', index=2,
number=3, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11807,
serialized_end=11902,
)
_BINARYMETRICS = _descriptor.Descriptor(
name='BinaryMetrics',
full_name='clarifai.api.BinaryMetrics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='num_pos', full_name='clarifai.api.BinaryMetrics.num_pos', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='num_neg', full_name='clarifai.api.BinaryMetrics.num_neg', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='num_tot', full_name='clarifai.api.BinaryMetrics.num_tot', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='roc_auc', full_name='clarifai.api.BinaryMetrics.roc_auc', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='f1', full_name='clarifai.api.BinaryMetrics.f1', index=4,
number=5, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept', full_name='clarifai.api.BinaryMetrics.concept', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='roc_curve', full_name='clarifai.api.BinaryMetrics.roc_curve', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='precision_recall_curve', full_name='clarifai.api.BinaryMetrics.precision_recall_curve', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='avg_precision', full_name='clarifai.api.BinaryMetrics.avg_precision', index=8,
number=9, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='area_name', full_name='clarifai.api.BinaryMetrics.area_name', index=9,
number=10, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='area_min', full_name='clarifai.api.BinaryMetrics.area_min', index=10,
number=11, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='area_max', full_name='clarifai.api.BinaryMetrics.area_max', index=11,
number=12, type=1, cpp_type=5, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='iou', full_name='clarifai.api.BinaryMetrics.iou', index=12,
number=13, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=11905,
serialized_end=12267,
)
_TRACKERMETRICS = _descriptor.Descriptor(
name='TrackerMetrics',
full_name='clarifai.api.TrackerMetrics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='mot_mota', full_name='clarifai.api.TrackerMetrics.mot_mota', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='mot_num_switches', full_name='clarifai.api.TrackerMetrics.mot_num_switches', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='morse_frag', full_name='clarifai.api.TrackerMetrics.morse_frag', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='avg_precision', full_name='clarifai.api.TrackerMetrics.avg_precision', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='aiid', full_name='clarifai.api.TrackerMetrics.aiid', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='unique_switch_rate', full_name='clarifai.api.TrackerMetrics.unique_switch_rate', index=5,
number=6, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=12270,
serialized_end=12415,
)
_EVALTESTSETENTRY = _descriptor.Descriptor(
name='EvalTestSetEntry',
full_name='clarifai.api.EvalTestSetEntry',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.EvalTestSetEntry.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='url', full_name='clarifai.api.EvalTestSetEntry.url', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input', full_name='clarifai.api.EvalTestSetEntry.input', index=2,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='predicted_concepts', full_name='clarifai.api.EvalTestSetEntry.predicted_concepts', index=3,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='ground_truth_concepts', full_name='clarifai.api.EvalTestSetEntry.ground_truth_concepts', index=4,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='annotation', full_name='clarifai.api.EvalTestSetEntry.annotation', index=5,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=12418,
serialized_end=12656,
)
_LOPQEVALRESULT = _descriptor.Descriptor(
name='LOPQEvalResult',
full_name='clarifai.api.LOPQEvalResult',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='k', full_name='clarifai.api.LOPQEvalResult.k', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='recall_vs_brute_force', full_name='clarifai.api.LOPQEvalResult.recall_vs_brute_force', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='kendall_tau_vs_brute_force', full_name='clarifai.api.LOPQEvalResult.kendall_tau_vs_brute_force', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='most_frequent_code_percent', full_name='clarifai.api.LOPQEvalResult.most_frequent_code_percent', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='lopq_ndcg', full_name='clarifai.api.LOPQEvalResult.lopq_ndcg', index=4,
number=5, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='brute_force_ndcg', full_name='clarifai.api.LOPQEvalResult.brute_force_ndcg', index=5,
number=6, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=12659,
serialized_end=12864,
)
_METRICSSUMMARY = _descriptor.Descriptor(
name='MetricsSummary',
full_name='clarifai.api.MetricsSummary',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='top1_accuracy', full_name='clarifai.api.MetricsSummary.top1_accuracy', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='top5_accuracy', full_name='clarifai.api.MetricsSummary.top5_accuracy', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='macro_avg_roc_auc', full_name='clarifai.api.MetricsSummary.macro_avg_roc_auc', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='macro_std_roc_auc', full_name='clarifai.api.MetricsSummary.macro_std_roc_auc', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='macro_avg_f1_score', full_name='clarifai.api.MetricsSummary.macro_avg_f1_score', index=4,
number=5, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='macro_std_f1_score', full_name='clarifai.api.MetricsSummary.macro_std_f1_score', index=5,
number=6, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='macro_avg_precision', full_name='clarifai.api.MetricsSummary.macro_avg_precision', index=6,
number=7, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='macro_avg_recall', full_name='clarifai.api.MetricsSummary.macro_avg_recall', index=7,
number=8, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='mean_avg_precision_iou_50', full_name='clarifai.api.MetricsSummary.mean_avg_precision_iou_50', index=8,
number=10, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='mean_avg_precision_iou_range', full_name='clarifai.api.MetricsSummary.mean_avg_precision_iou_range', index=9,
number=11, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='lopq_metrics', full_name='clarifai.api.MetricsSummary.lopq_metrics', index=10,
number=9, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=12867,
serialized_end=13263,
)
_EVALMETRICS = _descriptor.Descriptor(
name='EvalMetrics',
full_name='clarifai.api.EvalMetrics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.EvalMetrics.status', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.EvalMetrics.id', index=1,
number=10, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='summary', full_name='clarifai.api.EvalMetrics.summary', index=2,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='confusion_matrix', full_name='clarifai.api.EvalMetrics.confusion_matrix', index=3,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='cooccurrence_matrix', full_name='clarifai.api.EvalMetrics.cooccurrence_matrix', index=4,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='label_counts', full_name='clarifai.api.EvalMetrics.label_counts', index=5,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='binary_metrics', full_name='clarifai.api.EvalMetrics.binary_metrics', index=6,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='test_set', full_name='clarifai.api.EvalMetrics.test_set', index=7,
number=7, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metrics_by_area', full_name='clarifai.api.EvalMetrics.metrics_by_area', index=8,
number=8, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metrics_by_class', full_name='clarifai.api.EvalMetrics.metrics_by_class', index=9,
number=9, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tracker_metrics', full_name='clarifai.api.EvalMetrics.tracker_metrics', index=10,
number=11, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=13266,
serialized_end=13825,
)
_FIELDSVALUE = _descriptor.Descriptor(
name='FieldsValue',
full_name='clarifai.api.FieldsValue',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='confusion_matrix', full_name='clarifai.api.FieldsValue.confusion_matrix', index=0,
number=1, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='cooccurrence_matrix', full_name='clarifai.api.FieldsValue.cooccurrence_matrix', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='label_counts', full_name='clarifai.api.FieldsValue.label_counts', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='binary_metrics', full_name='clarifai.api.FieldsValue.binary_metrics', index=3,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='test_set', full_name='clarifai.api.FieldsValue.test_set', index=4,
number=5, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metrics_by_area', full_name='clarifai.api.FieldsValue.metrics_by_area', index=5,
number=6, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metrics_by_class', full_name='clarifai.api.FieldsValue.metrics_by_class', index=6,
number=7, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=13828,
serialized_end=14011,
)
_OUTPUT = _descriptor.Descriptor(
name='Output',
full_name='clarifai.api.Output',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Output.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.Output.status', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Output.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model', full_name='clarifai.api.Output.model', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input', full_name='clarifai.api.Output.input', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.Output.data', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14014,
serialized_end=14233,
)
_SCOPEDEPS = _descriptor.Descriptor(
name='ScopeDeps',
full_name='clarifai.api.ScopeDeps',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='scope', full_name='clarifai.api.ScopeDeps.scope', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='depending_scopes', full_name='clarifai.api.ScopeDeps.depending_scopes', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14235,
serialized_end=14287,
)
_ENDPOINTDEPS = _descriptor.Descriptor(
name='EndpointDeps',
full_name='clarifai.api.EndpointDeps',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='endpoint', full_name='clarifai.api.EndpointDeps.endpoint', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='depending_scopes', full_name='clarifai.api.EndpointDeps.depending_scopes', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14289,
serialized_end=14347,
)
_HIT = _descriptor.Descriptor(
name='Hit',
full_name='clarifai.api.Hit',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='score', full_name='clarifai.api.Hit.score', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input', full_name='clarifai.api.Hit.input', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='annotation', full_name='clarifai.api.Hit.annotation', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14349,
serialized_end=14457,
)
_AND = _descriptor.Descriptor(
name='And',
full_name='clarifai.api.And',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='input', full_name='clarifai.api.And.input', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='output', full_name='clarifai.api.And.output', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='negate', full_name='clarifai.api.And.negate', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='annotation', full_name='clarifai.api.And.annotation', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14460,
serialized_end=14601,
)
_QUERY = _descriptor.Descriptor(
name='Query',
full_name='clarifai.api.Query',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='ands', full_name='clarifai.api.Query.ands', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='language', full_name='clarifai.api.Query.language', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='filters', full_name='clarifai.api.Query.filters', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='ranks', full_name='clarifai.api.Query.ranks', index=3,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14604,
serialized_end=14736,
)
_SEARCH = _descriptor.Descriptor(
name='Search',
full_name='clarifai.api.Search',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='query', full_name='clarifai.api.Search.query', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Search.id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='application_id', full_name='clarifai.api.Search.application_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.Search.name', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='as_of', full_name='clarifai.api.Search.as_of', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='git_hash', full_name='clarifai.api.Search.git_hash', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Search.created_at', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Search.modified_at', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='algorithm', full_name='clarifai.api.Search.algorithm', index=8,
number=9, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='save', full_name='clarifai.api.Search.save', index=9,
number=10, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='min_value', full_name='clarifai.api.Search.min_value', index=10,
number=11, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.Search.visibility', index=11,
number=12, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=14739,
serialized_end=15089,
)
_FILTER = _descriptor.Descriptor(
name='Filter',
full_name='clarifai.api.Filter',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='negate', full_name='clarifai.api.Filter.negate', index=0,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='annotation', full_name='clarifai.api.Filter.annotation', index=1,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input', full_name='clarifai.api.Filter.input', index=2,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='last_updated_time_range', full_name='clarifai.api.Filter.last_updated_time_range', index=3,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15092,
serialized_end=15256,
)
_TIMERANGE = _descriptor.Descriptor(
name='TimeRange',
full_name='clarifai.api.TimeRange',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='start_time', full_name='clarifai.api.TimeRange.start_time', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='end_time', full_name='clarifai.api.TimeRange.end_time', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15258,
serialized_end=15363,
)
_RANK = _descriptor.Descriptor(
name='Rank',
full_name='clarifai.api.Rank',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='negate', full_name='clarifai.api.Rank.negate', index=0,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='annotation', full_name='clarifai.api.Rank.annotation', index=1,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15365,
serialized_end=15433,
)
_ANNOTATIONSEARCHMETRICS = _descriptor.Descriptor(
name='AnnotationSearchMetrics',
full_name='clarifai.api.AnnotationSearchMetrics',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='ground_truth', full_name='clarifai.api.AnnotationSearchMetrics.ground_truth', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='search_to_eval', full_name='clarifai.api.AnnotationSearchMetrics.search_to_eval', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metrics', full_name='clarifai.api.AnnotationSearchMetrics.metrics', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.AnnotationSearchMetrics.data', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='active_concept_count', full_name='clarifai.api.AnnotationSearchMetrics.active_concept_count', index=4,
number=5, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.AnnotationSearchMetrics.visibility', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15436,
serialized_end=15705,
)
_TEXT = _descriptor.Descriptor(
name='Text',
full_name='clarifai.api.Text',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='raw', full_name='clarifai.api.Text.raw', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='url', full_name='clarifai.api.Text.url', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='allow_duplicate_url', full_name='clarifai.api.Text.allow_duplicate_url', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hosted', full_name='clarifai.api.Text.hosted', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='text_info', full_name='clarifai.api.Text.text_info', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15708,
serialized_end=15853,
)
_TEXTINFO = _descriptor.Descriptor(
name='TextInfo',
full_name='clarifai.api.TextInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='char_count', full_name='clarifai.api.TextInfo.char_count', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='encoding', full_name='clarifai.api.TextInfo.encoding', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15855,
serialized_end=15903,
)
_USER = _descriptor.Descriptor(
name='User',
full_name='clarifai.api.User',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.User.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='primary_email', full_name='clarifai.api.User.primary_email', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='first_name', full_name='clarifai.api.User.first_name', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='last_name', full_name='clarifai.api.User.last_name', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='company_name', full_name='clarifai.api.User.company_name', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='job_title', full_name='clarifai.api.User.job_title', index=5,
number=19, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='job_role', full_name='clarifai.api.User.job_role', index=6,
number=20, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='bill_type', full_name='clarifai.api.User.bill_type', index=7,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.User.created_at', index=8,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='date_gdpr_consent', full_name='clarifai.api.User.date_gdpr_consent', index=9,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='date_tos_consent', full_name='clarifai.api.User.date_tos_consent', index=10,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='date_marketing_consent', full_name='clarifai.api.User.date_marketing_consent', index=11,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.User.metadata', index=12,
number=11, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='email_addresses', full_name='clarifai.api.User.email_addresses', index=13,
number=12, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='is_org_admin', full_name='clarifai.api.User.is_org_admin', index=14,
number=14, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='two_factor_auth_enabled', full_name='clarifai.api.User.two_factor_auth_enabled', index=15,
number=15, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='teams_count', full_name='clarifai.api.User.teams_count', index=16,
number=16, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='is_starred', full_name='clarifai.api.User.is_starred', index=17,
number=21, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='star_count', full_name='clarifai.api.User.star_count', index=18,
number=22, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.User.visibility', index=19,
number=17, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_detail', full_name='clarifai.api.User.user_detail', index=20,
number=18, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=15906,
serialized_end=16632,
)
_USERDETAIL = _descriptor.Descriptor(
name='UserDetail',
full_name='clarifai.api.UserDetail',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='primary_email', full_name='clarifai.api.UserDetail.primary_email', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='bill_type', full_name='clarifai.api.UserDetail.bill_type', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='date_gdpr_consent', full_name='clarifai.api.UserDetail.date_gdpr_consent', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='date_tos_consent', full_name='clarifai.api.UserDetail.date_tos_consent', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='date_marketing_consent', full_name='clarifai.api.UserDetail.date_marketing_consent', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.UserDetail.metadata', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='email_addresses', full_name='clarifai.api.UserDetail.email_addresses', index=6,
number=7, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='is_org_admin', full_name='clarifai.api.UserDetail.is_org_admin', index=7,
number=8, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='two_factor_auth_enabled', full_name='clarifai.api.UserDetail.two_factor_auth_enabled', index=8,
number=9, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='teams_count', full_name='clarifai.api.UserDetail.teams_count', index=9,
number=10, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='country', full_name='clarifai.api.UserDetail.country', index=10,
number=11, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='state', full_name='clarifai.api.UserDetail.state', index=11,
number=12, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=16635,
serialized_end=17062,
)
_EMAILADDRESS = _descriptor.Descriptor(
name='EmailAddress',
full_name='clarifai.api.EmailAddress',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='email', full_name='clarifai.api.EmailAddress.email', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='primary', full_name='clarifai.api.EmailAddress.primary', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='verified', full_name='clarifai.api.EmailAddress.verified', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=17064,
serialized_end=17146,
)
_PASSWORD = _descriptor.Descriptor(
name='Password',
full_name='clarifai.api.Password',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='plaintext', full_name='clarifai.api.Password.plaintext', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=17148,
serialized_end=17177,
)
_PASSWORDVIOLATIONS = _descriptor.Descriptor(
name='PasswordViolations',
full_name='clarifai.api.PasswordViolations',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='minimum_length', full_name='clarifai.api.PasswordViolations.minimum_length', index=0,
number=1, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='maximum_length', full_name='clarifai.api.PasswordViolations.maximum_length', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='upper_case_needed', full_name='clarifai.api.PasswordViolations.upper_case_needed', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='lower_case_needed', full_name='clarifai.api.PasswordViolations.lower_case_needed', index=3,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='numeric_needed', full_name='clarifai.api.PasswordViolations.numeric_needed', index=4,
number=5, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='non_alphanumeric_needed', full_name='clarifai.api.PasswordViolations.non_alphanumeric_needed', index=5,
number=6, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='password_reuse', full_name='clarifai.api.PasswordViolations.password_reuse', index=6,
number=7, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='exclude_names', full_name='clarifai.api.PasswordViolations.exclude_names', index=7,
number=8, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='exclude_email', full_name='clarifai.api.PasswordViolations.exclude_email', index=8,
number=9, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='no_confusing_letters', full_name='clarifai.api.PasswordViolations.no_confusing_letters', index=9,
number=10, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='no_simple_passwords', full_name='clarifai.api.PasswordViolations.no_simple_passwords', index=10,
number=11, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='no_common_vocabs', full_name='clarifai.api.PasswordViolations.no_common_vocabs', index=11,
number=12, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='no_overlap_with_old', full_name='clarifai.api.PasswordViolations.no_overlap_with_old', index=12,
number=13, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='password_lifespan', full_name='clarifai.api.PasswordViolations.password_lifespan', index=13,
number=14, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=17180,
serialized_end=17570,
)
_VIDEO = _descriptor.Descriptor(
name='Video',
full_name='clarifai.api.Video',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='url', full_name='clarifai.api.Video.url', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='base64', full_name='clarifai.api.Video.base64', index=1,
number=2, type=12, cpp_type=9, label=1,
has_default_value=False, default_value=b"",
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='allow_duplicate_url', full_name='clarifai.api.Video.allow_duplicate_url', index=2,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='thumbnail_url', full_name='clarifai.api.Video.thumbnail_url', index=3,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='hosted', full_name='clarifai.api.Video.hosted', index=4,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='video_info', full_name='clarifai.api.Video.video_info', index=5,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=17573,
serialized_end=17747,
)
_VIDEOINFO = _descriptor.Descriptor(
name='VideoInfo',
full_name='clarifai.api.VideoInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='width', full_name='clarifai.api.VideoInfo.width', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='height', full_name='clarifai.api.VideoInfo.height', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='fps', full_name='clarifai.api.VideoInfo.fps', index=2,
number=3, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='video_format', full_name='clarifai.api.VideoInfo.video_format', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='bit_rate', full_name='clarifai.api.VideoInfo.bit_rate', index=4,
number=5, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='frame_count', full_name='clarifai.api.VideoInfo.frame_count', index=5,
number=6, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='duration_seconds', full_name='clarifai.api.VideoInfo.duration_seconds', index=6,
number=7, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=17750,
serialized_end=17892,
)
_WORKFLOW = _descriptor.Descriptor(
name='Workflow',
full_name='clarifai.api.Workflow',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Workflow.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.Workflow.app_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Workflow.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='nodes', full_name='clarifai.api.Workflow.nodes', index=3,
number=4, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.Workflow.metadata', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.Workflow.visibility', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.Workflow.user_id', index=6,
number=7, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Workflow.modified_at', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='version', full_name='clarifai.api.Workflow.version', index=8,
number=9, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='is_starred', full_name='clarifai.api.Workflow.is_starred', index=9,
number=10, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='star_count', full_name='clarifai.api.Workflow.star_count', index=10,
number=11, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.Workflow.description', index=11,
number=12, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='notes', full_name='clarifai.api.Workflow.notes', index=12,
number=13, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='use_cases', full_name='clarifai.api.Workflow.use_cases', index=13,
number=14, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=17895,
serialized_end=18328,
)
_WORKFLOWVERSION = _descriptor.Descriptor(
name='WorkflowVersion',
full_name='clarifai.api.WorkflowVersion',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.WorkflowVersion.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='workflow_id', full_name='clarifai.api.WorkflowVersion.workflow_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.WorkflowVersion.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.WorkflowVersion.modified_at', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.WorkflowVersion.visibility', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='nodes', full_name='clarifai.api.WorkflowVersion.nodes', index=5,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='metadata', full_name='clarifai.api.WorkflowVersion.metadata', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.WorkflowVersion.app_id', index=7,
number=8, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.WorkflowVersion.user_id', index=8,
number=9, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.WorkflowVersion.description', index=9,
number=10, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='license', full_name='clarifai.api.WorkflowVersion.license', index=10,
number=11, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=18331,
serialized_end=18681,
)
_WORKFLOWNODE = _descriptor.Descriptor(
name='WorkflowNode',
full_name='clarifai.api.WorkflowNode',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.WorkflowNode.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model', full_name='clarifai.api.WorkflowNode.model', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='node_inputs', full_name='clarifai.api.WorkflowNode.node_inputs', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='suppress_output', full_name='clarifai.api.WorkflowNode.suppress_output', index=3,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=18684,
serialized_end=18817,
)
_NODEINPUT = _descriptor.Descriptor(
name='NodeInput',
full_name='clarifai.api.NodeInput',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='node_id', full_name='clarifai.api.NodeInput.node_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=18819,
serialized_end=18847,
)
_WORKFLOWRESULT = _descriptor.Descriptor(
name='WorkflowResult',
full_name='clarifai.api.WorkflowResult',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.WorkflowResult.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.WorkflowResult.status', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.WorkflowResult.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model', full_name='clarifai.api.WorkflowResult.model', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input', full_name='clarifai.api.WorkflowResult.input', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='outputs', full_name='clarifai.api.WorkflowResult.outputs', index=5,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='suppress_output', full_name='clarifai.api.WorkflowResult.suppress_output', index=6,
number=7, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=18850,
serialized_end=19107,
)
_WORKFLOWSTATE = _descriptor.Descriptor(
name='WorkflowState',
full_name='clarifai.api.WorkflowState',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.WorkflowState.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=19109,
serialized_end=19136,
)
_APPDUPLICATION = _descriptor.Descriptor(
name='AppDuplication',
full_name='clarifai.api.AppDuplication',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.AppDuplication.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='new_app_id', full_name='clarifai.api.AppDuplication.new_app_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='new_app_name', full_name='clarifai.api.AppDuplication.new_app_name', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.AppDuplication.status', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.AppDuplication.created_at', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='last_modified_at', full_name='clarifai.api.AppDuplication.last_modified_at', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='filter', full_name='clarifai.api.AppDuplication.filter', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=19139,
serialized_end=19409,
)
_APPDUPLICATIONFILTERS = _descriptor.Descriptor(
name='AppDuplicationFilters',
full_name='clarifai.api.AppDuplicationFilters',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='copy_inputs', full_name='clarifai.api.AppDuplicationFilters.copy_inputs', index=0,
number=1, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='copy_concepts', full_name='clarifai.api.AppDuplicationFilters.copy_concepts', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='copy_annotations', full_name='clarifai.api.AppDuplicationFilters.copy_annotations', index=2,
number=3, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='copy_models', full_name='clarifai.api.AppDuplicationFilters.copy_models', index=3,
number=4, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='copy_workflows', full_name='clarifai.api.AppDuplicationFilters.copy_workflows', index=4,
number=5, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=19412,
serialized_end=19550,
)
_TASK = _descriptor.Descriptor(
name='Task',
full_name='clarifai.api.Task',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Task.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Task.created_at', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='modified_at', full_name='clarifai.api.Task.modified_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.Task.type', index=3,
number=4, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.Task.description', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='worker', full_name='clarifai.api.Task.worker', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept_ids', full_name='clarifai.api.Task.concept_ids', index=6,
number=7, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='input_source', full_name='clarifai.api.Task.input_source', index=7,
number=8, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='sample_ms', full_name='clarifai.api.Task.sample_ms', index=8,
number=9, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='ai_assistant', full_name='clarifai.api.Task.ai_assistant', index=9,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='review', full_name='clarifai.api.Task.review', index=10,
number=11, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.Task.status', index=11,
number=12, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='name', full_name='clarifai.api.Task.name', index=12,
number=13, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='ai_assist_params', full_name='clarifai.api.Task.ai_assist_params', index=13,
number=14, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='visibility', full_name='clarifai.api.Task.visibility', index=14,
number=15, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.Task.app_id', index=15,
number=16, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.Task.user_id', index=16,
number=17, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_TASK_TASKTYPE,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=19553,
serialized_end=20270,
)
_AIASSISTPARAMETERS = _descriptor.Descriptor(
name='AiAssistParameters',
full_name='clarifai.api.AiAssistParameters',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='min_threshold', full_name='clarifai.api.AiAssistParameters.min_threshold', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='max_threshold', full_name='clarifai.api.AiAssistParameters.max_threshold', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='concept_relation_ids', full_name='clarifai.api.AiAssistParameters.concept_relation_ids', index=2,
number=3, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=20272,
serialized_end=20368,
)
_TASKWORKER = _descriptor.Descriptor(
name='TaskWorker',
full_name='clarifai.api.TaskWorker',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='strategy', full_name='clarifai.api.TaskWorker.strategy', index=0,
number=1, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_ids', full_name='clarifai.api.TaskWorker.user_ids', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='partitioned_strategy_info', full_name='clarifai.api.TaskWorker.partitioned_strategy_info', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_TASKWORKER_TASKWORKERSTRATEGY,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='strategy_info', full_name='clarifai.api.TaskWorker.strategy_info',
index=0, containing_type=None, fields=[]),
],
serialized_start=20371,
serialized_end=20651,
)
_TASKWORKERPARTITIONEDSTRATEGYINFO = _descriptor.Descriptor(
name='TaskWorkerPartitionedStrategyInfo',
full_name='clarifai.api.TaskWorkerPartitionedStrategyInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.TaskWorkerPartitionedStrategyInfo.type', index=0,
number=1, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='workers_per_input', full_name='clarifai.api.TaskWorkerPartitionedStrategyInfo.workers_per_input', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='weights', full_name='clarifai.api.TaskWorkerPartitionedStrategyInfo.weights', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_TASKWORKERPARTITIONEDSTRATEGYINFO_TASKWORKERPARTITIONEDSTRATEGY,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=20654,
serialized_end=20951,
)
_TASKINPUTSOURCE = _descriptor.Descriptor(
name='TaskInputSource',
full_name='clarifai.api.TaskInputSource',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='type', full_name='clarifai.api.TaskInputSource.type', index=0,
number=1, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.TaskInputSource.id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_TASKINPUTSOURCE_TASKINPUTSOURCETYPE,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=20954,
serialized_end=21136,
)
_TASKREVIEW = _descriptor.Descriptor(
name='TaskReview',
full_name='clarifai.api.TaskReview',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='strategy', full_name='clarifai.api.TaskReview.strategy', index=0,
number=1, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='user_ids', full_name='clarifai.api.TaskReview.user_ids', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='manual_strategy_info', full_name='clarifai.api.TaskReview.manual_strategy_info', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='consensus_strategy_info', full_name='clarifai.api.TaskReview.consensus_strategy_info', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_TASKREVIEW_TASKREVIEWSTRATEGY,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='strategy_info', full_name='clarifai.api.TaskReview.strategy_info',
index=0, containing_type=None, fields=[]),
],
serialized_start=21139,
serialized_end=21500,
)
_TASKREVIEWMANUALSTRATEGYINFO = _descriptor.Descriptor(
name='TaskReviewManualStrategyInfo',
full_name='clarifai.api.TaskReviewManualStrategyInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='sample_percentage', full_name='clarifai.api.TaskReviewManualStrategyInfo.sample_percentage', index=0,
number=1, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=21502,
serialized_end=21559,
)
_TASKREVIEWCONSENSUSSTRATEGYINFO = _descriptor.Descriptor(
name='TaskReviewConsensusStrategyInfo',
full_name='clarifai.api.TaskReviewConsensusStrategyInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='approval_threshold', full_name='clarifai.api.TaskReviewConsensusStrategyInfo.approval_threshold', index=0,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=21561,
serialized_end=21628,
)
_TASKAIASSISTANT = _descriptor.Descriptor(
name='TaskAIAssistant',
full_name='clarifai.api.TaskAIAssistant',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='workflow_id', full_name='clarifai.api.TaskAIAssistant.workflow_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=21630,
serialized_end=21668,
)
_TASKSTATUSCOUNTPERUSER = _descriptor.Descriptor(
name='TaskStatusCountPerUser',
full_name='clarifai.api.TaskStatusCountPerUser',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.TaskStatusCountPerUser.user_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='pending', full_name='clarifai.api.TaskStatusCountPerUser.pending', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='awaiting_review', full_name='clarifai.api.TaskStatusCountPerUser.awaiting_review', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='success', full_name='clarifai.api.TaskStatusCountPerUser.success', index=3,
number=4, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='review_denied', full_name='clarifai.api.TaskStatusCountPerUser.review_denied', index=4,
number=5, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='awaiting_consensus_review', full_name='clarifai.api.TaskStatusCountPerUser.awaiting_consensus_review', index=5,
number=6, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=b'\200\265\030\001', file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=21671,
serialized_end=21859,
)
_COLLECTOR = _descriptor.Descriptor(
name='Collector',
full_name='clarifai.api.Collector',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.Collector.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='clarifai.api.Collector.description', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='created_at', full_name='clarifai.api.Collector.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='pre_queue_workflow_id', full_name='clarifai.api.Collector.pre_queue_workflow_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='post_queue_workflow_id', full_name='clarifai.api.Collector.post_queue_workflow_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='collector_source', full_name='clarifai.api.Collector.collector_source', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='status', full_name='clarifai.api.Collector.status', index=6,
number=7, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=21862,
serialized_end=22119,
)
_COLLECTORSOURCE = _descriptor.Descriptor(
name='CollectorSource',
full_name='clarifai.api.CollectorSource',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='api_post_model_outputs_collector_source', full_name='clarifai.api.CollectorSource.api_post_model_outputs_collector_source', index=0,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=22121,
serialized_end=22237,
)
_APIPOSTMODELOUTPUTSCOLLECTORSOURCE = _descriptor.Descriptor(
name='APIPostModelOutputsCollectorSource',
full_name='clarifai.api.APIPostModelOutputsCollectorSource',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='model_user_id', full_name='clarifai.api.APIPostModelOutputsCollectorSource.model_user_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_app_id', full_name='clarifai.api.APIPostModelOutputsCollectorSource.model_app_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_id', full_name='clarifai.api.APIPostModelOutputsCollectorSource.model_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='model_version_id', full_name='clarifai.api.APIPostModelOutputsCollectorSource.model_version_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='post_inputs_key_id', full_name='clarifai.api.APIPostModelOutputsCollectorSource.post_inputs_key_id', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=22240,
serialized_end=22393,
)
_STATVALUE = _descriptor.Descriptor(
name='StatValue',
full_name='clarifai.api.StatValue',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='time', full_name='clarifai.api.StatValue.time', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='clarifai.api.StatValue.value', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tags', full_name='clarifai.api.StatValue.tags', index=2,
number=3, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=22395,
serialized_end=22477,
)
_STATVALUEAGGREGATERESULT = _descriptor.Descriptor(
name='StatValueAggregateResult',
full_name='clarifai.api.StatValueAggregateResult',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='stat_value_aggregates', full_name='clarifai.api.StatValueAggregateResult.stat_value_aggregates', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='stat_value_aggregate_query', full_name='clarifai.api.StatValueAggregateResult.stat_value_aggregate_query', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=22480,
serialized_end=22646,
)
_STATVALUEAGGREGATE = _descriptor.Descriptor(
name='StatValueAggregate',
full_name='clarifai.api.StatValueAggregate',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='time', full_name='clarifai.api.StatValueAggregate.time', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='aggregate_value', full_name='clarifai.api.StatValueAggregate.aggregate_value', index=1,
number=2, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='count', full_name='clarifai.api.StatValueAggregate.count', index=2,
number=3, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tags', full_name='clarifai.api.StatValueAggregate.tags', index=3,
number=4, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=22648,
serialized_end=22764,
)
_STATVALUEAGGREGATEQUERY = _descriptor.Descriptor(
name='StatValueAggregateQuery',
full_name='clarifai.api.StatValueAggregateQuery',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='tags', full_name='clarifai.api.StatValueAggregateQuery.tags', index=0,
number=1, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tag_groups', full_name='clarifai.api.StatValueAggregateQuery.tag_groups', index=1,
number=2, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='stat_value_agg_type', full_name='clarifai.api.StatValueAggregateQuery.stat_value_agg_type', index=2,
number=3, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='stat_time_agg_type', full_name='clarifai.api.StatValueAggregateQuery.stat_time_agg_type', index=3,
number=4, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='start_time', full_name='clarifai.api.StatValueAggregateQuery.start_time', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='end_time', full_name='clarifai.api.StatValueAggregateQuery.end_time', index=5,
number=6, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=22767,
serialized_end=23040,
)
_VISIBILITY = _descriptor.Descriptor(
name='Visibility',
full_name='clarifai.api.Visibility',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='gettable', full_name='clarifai.api.Visibility.gettable', index=0,
number=1, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
_VISIBILITY_GETTABLE,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=23043,
serialized_end=23178,
)
_TRENDINGMETRIC = _descriptor.Descriptor(
name='TrendingMetric',
full_name='clarifai.api.TrendingMetric',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='user_id', full_name='clarifai.api.TrendingMetric.user_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='app_id', full_name='clarifai.api.TrendingMetric.app_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='object_id', full_name='clarifai.api.TrendingMetric.object_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='view_count', full_name='clarifai.api.TrendingMetric.view_count', index=3,
number=4, type=4, cpp_type=4, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=23180,
serialized_end=23268,
)
_TIMESEGMENT = _descriptor.Descriptor(
name='TimeSegment',
full_name='clarifai.api.TimeSegment',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='clarifai.api.TimeSegment.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='clarifai.api.TimeSegment.data', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='time_info', full_name='clarifai.api.TimeSegment.time_info', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=23270,
serialized_end=23372,
)
_TIMEINFO = _descriptor.Descriptor(
name='TimeInfo',
full_name='clarifai.api.TimeInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='num_frames', full_name='clarifai.api.TimeInfo.num_frames', index=0,
number=1, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='begin_time', full_name='clarifai.api.TimeInfo.begin_time', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='end_time', full_name='clarifai.api.TimeInfo.end_time', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=23374,
serialized_end=23442,
)
_ANNOTATION.fields_by_name['data'].message_type = _DATA
_ANNOTATION.fields_by_name['annotation_info'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_ANNOTATION.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_ANNOTATION.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_ANNOTATION.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_ANNOTATION.fields_by_name['consensus_info'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_APP.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_APP.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_APP.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_APP.fields_by_name['visibility'].message_type = _VISIBILITY
_COLLABORATOR.fields_by_name['app'].message_type = _APP
_COLLABORATOR.fields_by_name['user'].message_type = _USER
_COLLABORATOR.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_COLLABORATOR.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_COLLABORATOR.fields_by_name['deleted_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_COLLABORATION.fields_by_name['app'].message_type = _APP
_COLLABORATION.fields_by_name['app_owner'].message_type = _USER
_COLLABORATION.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_AUDIO.fields_by_name['hosted'].message_type = _HOSTEDURL
_AUDIO.fields_by_name['audio_info'].message_type = _AUDIOINFO
_TRACK.fields_by_name['data'].message_type = _DATA
_TRACK.fields_by_name['time_info'].message_type = _TIMEINFO
_CLUSTER.fields_by_name['hits'].message_type = _HIT
_COLOR.fields_by_name['w3c'].message_type = _W3C
_CONCEPT.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_CONCEPT.fields_by_name['visibility'].message_type = _VISIBILITY
_CONCEPTCOUNT.fields_by_name['concept_type_count'].message_type = _CONCEPTTYPECOUNT
_CONCEPTCOUNT.fields_by_name['detail_concept_count'].message_type = _DETAILCONCEPTCOUNT
_DETAILCONCEPTCOUNT.fields_by_name['processed'].message_type = _CONCEPTTYPECOUNT
_DETAILCONCEPTCOUNT.fields_by_name['to_process'].message_type = _CONCEPTTYPECOUNT
_DETAILCONCEPTCOUNT.fields_by_name['errors'].message_type = _CONCEPTTYPECOUNT
_DETAILCONCEPTCOUNT.fields_by_name['processing'].message_type = _CONCEPTTYPECOUNT
_CONCEPTRELATION.fields_by_name['subject_concept'].message_type = _CONCEPT
_CONCEPTRELATION.fields_by_name['object_concept'].message_type = _CONCEPT
_CONCEPTRELATION.fields_by_name['visibility'].message_type = _VISIBILITY
_DATA.fields_by_name['image'].message_type = _IMAGE
_DATA.fields_by_name['video'].message_type = _VIDEO
_DATA.fields_by_name['concepts'].message_type = _CONCEPT
_DATA.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_DATA.fields_by_name['geo'].message_type = _GEO
_DATA.fields_by_name['colors'].message_type = _COLOR
_DATA.fields_by_name['clusters'].message_type = _CLUSTER
_DATA.fields_by_name['embeddings'].message_type = _EMBEDDING
_DATA.fields_by_name['regions'].message_type = _REGION
_DATA.fields_by_name['frames'].message_type = _FRAME
_DATA.fields_by_name['text'].message_type = _TEXT
_DATA.fields_by_name['audio'].message_type = _AUDIO
_DATA.fields_by_name['tracks'].message_type = _TRACK
_DATA.fields_by_name['time_segments'].message_type = _TIMESEGMENT
_REGION.fields_by_name['region_info'].message_type = _REGIONINFO
_REGION.fields_by_name['data'].message_type = _DATA
_REGIONINFO.fields_by_name['bounding_box'].message_type = _BOUNDINGBOX
_REGIONINFO.fields_by_name['mask'].message_type = _MASK
_REGIONINFO.fields_by_name['polygon'].message_type = _POLYGON
_REGIONINFO.fields_by_name['point'].message_type = _POINT
_FRAME.fields_by_name['frame_info'].message_type = _FRAMEINFO
_FRAME.fields_by_name['data'].message_type = _DATA
_MASK.fields_by_name['image'].message_type = _IMAGE
_POLYGON.fields_by_name['points'].message_type = _POINT
_GEOBOXEDPOINT.fields_by_name['geo_point'].message_type = _GEOPOINT
_GEO.fields_by_name['geo_point'].message_type = _GEOPOINT
_GEO.fields_by_name['geo_limit'].message_type = _GEOLIMIT
_GEO.fields_by_name['geo_box'].message_type = _GEOBOXEDPOINT
_IMAGE.fields_by_name['hosted'].message_type = _HOSTEDURL
_IMAGE.fields_by_name['image_info'].message_type = _IMAGEINFO
_INPUT.fields_by_name['data'].message_type = _DATA
_INPUT.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_INPUT.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_INPUT.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_DATASETFILTER.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_DATASETFILTER.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_DATASETFILTER.fields_by_name['saved_search'].message_type = _SEARCH
_DATASETVERSION.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_DATASETVERSION.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_DATASETVERSION.fields_by_name['dataset_filter_config'].message_type = _DATASETVERSIONDATASETFILTERCONFIG
_DATASETVERSION.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_DATASETVERSION.fields_by_name['summary'].message_type = _DATASETVERSIONSUMMARY
_DATASETVERSION.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_DATASETVERSION.fields_by_name['visibility'].message_type = _VISIBILITY
_DATASETVERSION.oneofs_by_name['data_config'].fields.append(
_DATASETVERSION.fields_by_name['dataset_filter_config'])
_DATASETVERSION.fields_by_name['dataset_filter_config'].containing_oneof = _DATASETVERSION.oneofs_by_name['data_config']
_DATASETVERSIONDATASETFILTERCONFIG.fields_by_name['dataset_filter'].message_type = _DATASETFILTER
_DATASETVERSIONSUMMARY_INPUTCOUNTSENTRY.containing_type = _DATASETVERSIONSUMMARY
_DATASETVERSIONSUMMARY.fields_by_name['input_counts'].message_type = _DATASETVERSIONSUMMARY_INPUTCOUNTSENTRY
_WORKFLOWRESULTSSIMILARITY.fields_by_name['probe_input'].message_type = _INPUT
_WORKFLOWRESULTSSIMILARITY.fields_by_name['pool_results'].message_type = _HIT
_KEY.fields_by_name['apps'].message_type = _APP
_KEY.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_KEY.fields_by_name['expires_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODEL.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODEL.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODEL.fields_by_name['output_info'].message_type = _OUTPUTINFO
_MODEL.fields_by_name['model_version'].message_type = _MODELVERSION
_MODEL.fields_by_name['input_info'].message_type = _INPUTINFO
_MODEL.fields_by_name['train_info'].message_type = _TRAININFO
_MODEL.fields_by_name['visibility'].message_type = _VISIBILITY
_MODEL.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_MODEL.fields_by_name['import_info'].message_type = _IMPORTINFO
_MODELREFERENCE.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_MODELVERSIONINPUTEXAMPLE.fields_by_name['data'].message_type = _DATA
_OUTPUTINFO.fields_by_name['data'].message_type = _DATA
_OUTPUTINFO.fields_by_name['output_config'].message_type = _OUTPUTCONFIG
_OUTPUTINFO.fields_by_name['fields_map'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_OUTPUTINFO.fields_by_name['params'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_INPUTINFO.fields_by_name['fields_map'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_INPUTINFO.fields_by_name['params'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_TRAININFO.fields_by_name['params'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_IMPORTINFO.fields_by_name['params'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_OUTPUTCONFIG.fields_by_name['select_concepts'].message_type = _CONCEPT
_OUTPUTCONFIG.fields_by_name['hyper_params'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_OUTPUTCONFIG.fields_by_name['model_metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_MODELTYPE.fields_by_name['model_type_fields'].message_type = _MODELTYPEFIELD
_MODELTYPE.fields_by_name['expected_pretrained_input_fields'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_MODELTYPE.fields_by_name['expected_pretrained_output_fields'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_MODELTYPEFIELD.fields_by_name['field_type'].enum_type = _MODELTYPEFIELD_MODELTYPEFIELDTYPE
_MODELTYPEFIELD.fields_by_name['default_value'].message_type = google_dot_protobuf_dot_struct__pb2._VALUE
_MODELTYPEFIELD.fields_by_name['model_type_enum_options'].message_type = _MODELTYPEENUMOPTION
_MODELTYPEFIELD.fields_by_name['model_type_range_info'].message_type = _MODELTYPERANGEINFO
_MODELTYPEFIELD_MODELTYPEFIELDTYPE.containing_type = _MODELTYPEFIELD
_MODELTYPEENUMOPTION.fields_by_name['model_type_fields'].message_type = _MODELTYPEFIELD
_MODELVERSION.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODELVERSION.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_MODELVERSION.fields_by_name['metrics'].message_type = _EVALMETRICS
_MODELVERSION.fields_by_name['completed_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODELVERSION.fields_by_name['visibility'].message_type = _VISIBILITY
_MODELVERSION.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODELVERSION.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_LABELDISTRIBUTION.fields_by_name['positive_label_counts'].message_type = _LABELCOUNT
_COOCCURRENCEMATRIX.fields_by_name['matrix'].message_type = _COOCCURRENCEMATRIXENTRY
_CONFUSIONMATRIX.fields_by_name['matrix'].message_type = _CONFUSIONMATRIXENTRY
_BINARYMETRICS.fields_by_name['concept'].message_type = _CONCEPT
_BINARYMETRICS.fields_by_name['roc_curve'].message_type = _ROC
_BINARYMETRICS.fields_by_name['precision_recall_curve'].message_type = _PRECISIONRECALLCURVE
_EVALTESTSETENTRY.fields_by_name['input'].message_type = _INPUT
_EVALTESTSETENTRY.fields_by_name['predicted_concepts'].message_type = _CONCEPT
_EVALTESTSETENTRY.fields_by_name['ground_truth_concepts'].message_type = _CONCEPT
_EVALTESTSETENTRY.fields_by_name['annotation'].message_type = _ANNOTATION
_METRICSSUMMARY.fields_by_name['lopq_metrics'].message_type = _LOPQEVALRESULT
_EVALMETRICS.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_EVALMETRICS.fields_by_name['summary'].message_type = _METRICSSUMMARY
_EVALMETRICS.fields_by_name['confusion_matrix'].message_type = _CONFUSIONMATRIX
_EVALMETRICS.fields_by_name['cooccurrence_matrix'].message_type = _COOCCURRENCEMATRIX
_EVALMETRICS.fields_by_name['label_counts'].message_type = _LABELDISTRIBUTION
_EVALMETRICS.fields_by_name['binary_metrics'].message_type = _BINARYMETRICS
_EVALMETRICS.fields_by_name['test_set'].message_type = _EVALTESTSETENTRY
_EVALMETRICS.fields_by_name['metrics_by_area'].message_type = _BINARYMETRICS
_EVALMETRICS.fields_by_name['metrics_by_class'].message_type = _BINARYMETRICS
_EVALMETRICS.fields_by_name['tracker_metrics'].message_type = _TRACKERMETRICS
_OUTPUT.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_OUTPUT.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_OUTPUT.fields_by_name['model'].message_type = _MODEL
_OUTPUT.fields_by_name['input'].message_type = _INPUT
_OUTPUT.fields_by_name['data'].message_type = _DATA
_HIT.fields_by_name['input'].message_type = _INPUT
_HIT.fields_by_name['annotation'].message_type = _ANNOTATION
_AND.fields_by_name['input'].message_type = _INPUT
_AND.fields_by_name['output'].message_type = _OUTPUT
_AND.fields_by_name['annotation'].message_type = _ANNOTATION
_QUERY.fields_by_name['ands'].message_type = _AND
_QUERY.fields_by_name['filters'].message_type = _FILTER
_QUERY.fields_by_name['ranks'].message_type = _RANK
_SEARCH.fields_by_name['query'].message_type = _QUERY
_SEARCH.fields_by_name['as_of'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_SEARCH.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_SEARCH.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_SEARCH.fields_by_name['visibility'].message_type = _VISIBILITY
_FILTER.fields_by_name['annotation'].message_type = _ANNOTATION
_FILTER.fields_by_name['input'].message_type = _INPUT
_FILTER.fields_by_name['last_updated_time_range'].message_type = _TIMERANGE
_TIMERANGE.fields_by_name['start_time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_TIMERANGE.fields_by_name['end_time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_RANK.fields_by_name['annotation'].message_type = _ANNOTATION
_ANNOTATIONSEARCHMETRICS.fields_by_name['ground_truth'].message_type = _SEARCH
_ANNOTATIONSEARCHMETRICS.fields_by_name['search_to_eval'].message_type = _SEARCH
_ANNOTATIONSEARCHMETRICS.fields_by_name['metrics'].message_type = _EVALMETRICS
_ANNOTATIONSEARCHMETRICS.fields_by_name['data'].message_type = _DATA
_ANNOTATIONSEARCHMETRICS.fields_by_name['visibility'].message_type = _VISIBILITY
_TEXT.fields_by_name['hosted'].message_type = _HOSTEDURL
_TEXT.fields_by_name['text_info'].message_type = _TEXTINFO
_USER.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USER.fields_by_name['date_gdpr_consent'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USER.fields_by_name['date_tos_consent'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USER.fields_by_name['date_marketing_consent'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USER.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_USER.fields_by_name['email_addresses'].message_type = _EMAILADDRESS
_USER.fields_by_name['visibility'].message_type = _VISIBILITY
_USER.fields_by_name['user_detail'].message_type = _USERDETAIL
_USERDETAIL.fields_by_name['date_gdpr_consent'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USERDETAIL.fields_by_name['date_tos_consent'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USERDETAIL.fields_by_name['date_marketing_consent'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_USERDETAIL.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_USERDETAIL.fields_by_name['email_addresses'].message_type = _EMAILADDRESS
_VIDEO.fields_by_name['hosted'].message_type = _HOSTEDURL
_VIDEO.fields_by_name['video_info'].message_type = _VIDEOINFO
_WORKFLOW.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_WORKFLOW.fields_by_name['nodes'].message_type = _WORKFLOWNODE
_WORKFLOW.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_WORKFLOW.fields_by_name['visibility'].message_type = _VISIBILITY
_WORKFLOW.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_WORKFLOW.fields_by_name['version'].message_type = _WORKFLOWVERSION
_WORKFLOWVERSION.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_WORKFLOWVERSION.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_WORKFLOWVERSION.fields_by_name['visibility'].message_type = _VISIBILITY
_WORKFLOWVERSION.fields_by_name['nodes'].message_type = _WORKFLOWNODE
_WORKFLOWVERSION.fields_by_name['metadata'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_WORKFLOWNODE.fields_by_name['model'].message_type = _MODEL
_WORKFLOWNODE.fields_by_name['node_inputs'].message_type = _NODEINPUT
_WORKFLOWRESULT.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_WORKFLOWRESULT.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_WORKFLOWRESULT.fields_by_name['model'].message_type = _MODEL
_WORKFLOWRESULT.fields_by_name['input'].message_type = _INPUT
_WORKFLOWRESULT.fields_by_name['outputs'].message_type = _OUTPUT
_APPDUPLICATION.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_APPDUPLICATION.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_APPDUPLICATION.fields_by_name['last_modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_APPDUPLICATION.fields_by_name['filter'].message_type = _APPDUPLICATIONFILTERS
_TASK.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_TASK.fields_by_name['modified_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_TASK.fields_by_name['type'].enum_type = _TASK_TASKTYPE
_TASK.fields_by_name['worker'].message_type = _TASKWORKER
_TASK.fields_by_name['input_source'].message_type = _TASKINPUTSOURCE
_TASK.fields_by_name['ai_assistant'].message_type = _TASKAIASSISTANT
_TASK.fields_by_name['review'].message_type = _TASKREVIEW
_TASK.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_TASK.fields_by_name['ai_assist_params'].message_type = _AIASSISTPARAMETERS
_TASK.fields_by_name['visibility'].message_type = _VISIBILITY
_TASK_TASKTYPE.containing_type = _TASK
_TASKWORKER.fields_by_name['strategy'].enum_type = _TASKWORKER_TASKWORKERSTRATEGY
_TASKWORKER.fields_by_name['partitioned_strategy_info'].message_type = _TASKWORKERPARTITIONEDSTRATEGYINFO
_TASKWORKER_TASKWORKERSTRATEGY.containing_type = _TASKWORKER
_TASKWORKER.oneofs_by_name['strategy_info'].fields.append(
_TASKWORKER.fields_by_name['partitioned_strategy_info'])
_TASKWORKER.fields_by_name['partitioned_strategy_info'].containing_oneof = _TASKWORKER.oneofs_by_name['strategy_info']
_TASKWORKERPARTITIONEDSTRATEGYINFO.fields_by_name['type'].enum_type = _TASKWORKERPARTITIONEDSTRATEGYINFO_TASKWORKERPARTITIONEDSTRATEGY
_TASKWORKERPARTITIONEDSTRATEGYINFO.fields_by_name['weights'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_TASKWORKERPARTITIONEDSTRATEGYINFO_TASKWORKERPARTITIONEDSTRATEGY.containing_type = _TASKWORKERPARTITIONEDSTRATEGYINFO
_TASKINPUTSOURCE.fields_by_name['type'].enum_type = _TASKINPUTSOURCE_TASKINPUTSOURCETYPE
_TASKINPUTSOURCE_TASKINPUTSOURCETYPE.containing_type = _TASKINPUTSOURCE
_TASKREVIEW.fields_by_name['strategy'].enum_type = _TASKREVIEW_TASKREVIEWSTRATEGY
_TASKREVIEW.fields_by_name['manual_strategy_info'].message_type = _TASKREVIEWMANUALSTRATEGYINFO
_TASKREVIEW.fields_by_name['consensus_strategy_info'].message_type = _TASKREVIEWCONSENSUSSTRATEGYINFO
_TASKREVIEW_TASKREVIEWSTRATEGY.containing_type = _TASKREVIEW
_TASKREVIEW.oneofs_by_name['strategy_info'].fields.append(
_TASKREVIEW.fields_by_name['manual_strategy_info'])
_TASKREVIEW.fields_by_name['manual_strategy_info'].containing_oneof = _TASKREVIEW.oneofs_by_name['strategy_info']
_TASKREVIEW.oneofs_by_name['strategy_info'].fields.append(
_TASKREVIEW.fields_by_name['consensus_strategy_info'])
_TASKREVIEW.fields_by_name['consensus_strategy_info'].containing_oneof = _TASKREVIEW.oneofs_by_name['strategy_info']
_COLLECTOR.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_COLLECTOR.fields_by_name['collector_source'].message_type = _COLLECTORSOURCE
_COLLECTOR.fields_by_name['status'].message_type = proto_dot_clarifai_dot_api_dot_status_dot_status__pb2._STATUS
_COLLECTORSOURCE.fields_by_name['api_post_model_outputs_collector_source'].message_type = _APIPOSTMODELOUTPUTSCOLLECTORSOURCE
_STATVALUE.fields_by_name['time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_STATVALUEAGGREGATERESULT.fields_by_name['stat_value_aggregates'].message_type = _STATVALUEAGGREGATE
_STATVALUEAGGREGATERESULT.fields_by_name['stat_value_aggregate_query'].message_type = _STATVALUEAGGREGATEQUERY
_STATVALUEAGGREGATE.fields_by_name['time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_STATVALUEAGGREGATEQUERY.fields_by_name['stat_value_agg_type'].enum_type = _STATVALUEAGGTYPE
_STATVALUEAGGREGATEQUERY.fields_by_name['stat_time_agg_type'].enum_type = _STATTIMEAGGTYPE
_STATVALUEAGGREGATEQUERY.fields_by_name['start_time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_STATVALUEAGGREGATEQUERY.fields_by_name['end_time'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_VISIBILITY.fields_by_name['gettable'].enum_type = _VISIBILITY_GETTABLE
_VISIBILITY_GETTABLE.containing_type = _VISIBILITY
_TIMESEGMENT.fields_by_name['data'].message_type = _DATA
_TIMESEGMENT.fields_by_name['time_info'].message_type = _TIMEINFO
DESCRIPTOR.message_types_by_name['Annotation'] = _ANNOTATION
DESCRIPTOR.message_types_by_name['App'] = _APP
DESCRIPTOR.message_types_by_name['AppQuery'] = _APPQUERY
DESCRIPTOR.message_types_by_name['Collaborator'] = _COLLABORATOR
DESCRIPTOR.message_types_by_name['Collaboration'] = _COLLABORATION
DESCRIPTOR.message_types_by_name['Audio'] = _AUDIO
DESCRIPTOR.message_types_by_name['AudioInfo'] = _AUDIOINFO
DESCRIPTOR.message_types_by_name['Track'] = _TRACK
DESCRIPTOR.message_types_by_name['Cluster'] = _CLUSTER
DESCRIPTOR.message_types_by_name['Color'] = _COLOR
DESCRIPTOR.message_types_by_name['W3C'] = _W3C
DESCRIPTOR.message_types_by_name['UserAppIDSet'] = _USERAPPIDSET
DESCRIPTOR.message_types_by_name['PatchAction'] = _PATCHACTION
DESCRIPTOR.message_types_by_name['Concept'] = _CONCEPT
DESCRIPTOR.message_types_by_name['ConceptCount'] = _CONCEPTCOUNT
DESCRIPTOR.message_types_by_name['ConceptTypeCount'] = _CONCEPTTYPECOUNT
DESCRIPTOR.message_types_by_name['DetailConceptCount'] = _DETAILCONCEPTCOUNT
DESCRIPTOR.message_types_by_name['ConceptQuery'] = _CONCEPTQUERY
DESCRIPTOR.message_types_by_name['ConceptRelation'] = _CONCEPTRELATION
DESCRIPTOR.message_types_by_name['KnowledgeGraph'] = _KNOWLEDGEGRAPH
DESCRIPTOR.message_types_by_name['ConceptMappingJob'] = _CONCEPTMAPPINGJOB
DESCRIPTOR.message_types_by_name['ConceptLanguage'] = _CONCEPTLANGUAGE
DESCRIPTOR.message_types_by_name['Data'] = _DATA
DESCRIPTOR.message_types_by_name['Region'] = _REGION
DESCRIPTOR.message_types_by_name['RegionInfo'] = _REGIONINFO
DESCRIPTOR.message_types_by_name['BoundingBox'] = _BOUNDINGBOX
DESCRIPTOR.message_types_by_name['FrameInfo'] = _FRAMEINFO
DESCRIPTOR.message_types_by_name['Frame'] = _FRAME
DESCRIPTOR.message_types_by_name['Mask'] = _MASK
DESCRIPTOR.message_types_by_name['Polygon'] = _POLYGON
DESCRIPTOR.message_types_by_name['Point'] = _POINT
DESCRIPTOR.message_types_by_name['Embedding'] = _EMBEDDING
DESCRIPTOR.message_types_by_name['GeoPoint'] = _GEOPOINT
DESCRIPTOR.message_types_by_name['GeoLimit'] = _GEOLIMIT
DESCRIPTOR.message_types_by_name['GeoBoxedPoint'] = _GEOBOXEDPOINT
DESCRIPTOR.message_types_by_name['Geo'] = _GEO
DESCRIPTOR.message_types_by_name['Image'] = _IMAGE
DESCRIPTOR.message_types_by_name['ImageInfo'] = _IMAGEINFO
DESCRIPTOR.message_types_by_name['HostedURL'] = _HOSTEDURL
DESCRIPTOR.message_types_by_name['Input'] = _INPUT
DESCRIPTOR.message_types_by_name['InputCount'] = _INPUTCOUNT
DESCRIPTOR.message_types_by_name['DatasetFilter'] = _DATASETFILTER
DESCRIPTOR.message_types_by_name['DatasetVersion'] = _DATASETVERSION
DESCRIPTOR.message_types_by_name['DatasetVersionDatasetFilterConfig'] = _DATASETVERSIONDATASETFILTERCONFIG
DESCRIPTOR.message_types_by_name['DatasetVersionSummary'] = _DATASETVERSIONSUMMARY
DESCRIPTOR.message_types_by_name['WorkflowResultsSimilarity'] = _WORKFLOWRESULTSSIMILARITY
DESCRIPTOR.message_types_by_name['Key'] = _KEY
DESCRIPTOR.message_types_by_name['Model'] = _MODEL
DESCRIPTOR.message_types_by_name['ModelReference'] = _MODELREFERENCE
DESCRIPTOR.message_types_by_name['ModelVersionInputExample'] = _MODELVERSIONINPUTEXAMPLE
DESCRIPTOR.message_types_by_name['OutputInfo'] = _OUTPUTINFO
DESCRIPTOR.message_types_by_name['InputInfo'] = _INPUTINFO
DESCRIPTOR.message_types_by_name['TrainInfo'] = _TRAININFO
DESCRIPTOR.message_types_by_name['ImportInfo'] = _IMPORTINFO
DESCRIPTOR.message_types_by_name['OutputConfig'] = _OUTPUTCONFIG
DESCRIPTOR.message_types_by_name['ModelType'] = _MODELTYPE
DESCRIPTOR.message_types_by_name['ModelTypeField'] = _MODELTYPEFIELD
DESCRIPTOR.message_types_by_name['ModelTypeRangeInfo'] = _MODELTYPERANGEINFO
DESCRIPTOR.message_types_by_name['ModelTypeEnumOption'] = _MODELTYPEENUMOPTION
DESCRIPTOR.message_types_by_name['ModelQuery'] = _MODELQUERY
DESCRIPTOR.message_types_by_name['ModelVersion'] = _MODELVERSION
DESCRIPTOR.message_types_by_name['LabelCount'] = _LABELCOUNT
DESCRIPTOR.message_types_by_name['LabelDistribution'] = _LABELDISTRIBUTION
DESCRIPTOR.message_types_by_name['CooccurrenceMatrixEntry'] = _COOCCURRENCEMATRIXENTRY
DESCRIPTOR.message_types_by_name['CooccurrenceMatrix'] = _COOCCURRENCEMATRIX
DESCRIPTOR.message_types_by_name['ConfusionMatrixEntry'] = _CONFUSIONMATRIXENTRY
DESCRIPTOR.message_types_by_name['ConfusionMatrix'] = _CONFUSIONMATRIX
DESCRIPTOR.message_types_by_name['ROC'] = _ROC
DESCRIPTOR.message_types_by_name['PrecisionRecallCurve'] = _PRECISIONRECALLCURVE
DESCRIPTOR.message_types_by_name['BinaryMetrics'] = _BINARYMETRICS
DESCRIPTOR.message_types_by_name['TrackerMetrics'] = _TRACKERMETRICS
DESCRIPTOR.message_types_by_name['EvalTestSetEntry'] = _EVALTESTSETENTRY
DESCRIPTOR.message_types_by_name['LOPQEvalResult'] = _LOPQEVALRESULT
DESCRIPTOR.message_types_by_name['MetricsSummary'] = _METRICSSUMMARY
DESCRIPTOR.message_types_by_name['EvalMetrics'] = _EVALMETRICS
DESCRIPTOR.message_types_by_name['FieldsValue'] = _FIELDSVALUE
DESCRIPTOR.message_types_by_name['Output'] = _OUTPUT
DESCRIPTOR.message_types_by_name['ScopeDeps'] = _SCOPEDEPS
DESCRIPTOR.message_types_by_name['EndpointDeps'] = _ENDPOINTDEPS
DESCRIPTOR.message_types_by_name['Hit'] = _HIT
DESCRIPTOR.message_types_by_name['And'] = _AND
DESCRIPTOR.message_types_by_name['Query'] = _QUERY
DESCRIPTOR.message_types_by_name['Search'] = _SEARCH
DESCRIPTOR.message_types_by_name['Filter'] = _FILTER
DESCRIPTOR.message_types_by_name['TimeRange'] = _TIMERANGE
DESCRIPTOR.message_types_by_name['Rank'] = _RANK
DESCRIPTOR.message_types_by_name['AnnotationSearchMetrics'] = _ANNOTATIONSEARCHMETRICS
DESCRIPTOR.message_types_by_name['Text'] = _TEXT
DESCRIPTOR.message_types_by_name['TextInfo'] = _TEXTINFO
DESCRIPTOR.message_types_by_name['User'] = _USER
DESCRIPTOR.message_types_by_name['UserDetail'] = _USERDETAIL
DESCRIPTOR.message_types_by_name['EmailAddress'] = _EMAILADDRESS
DESCRIPTOR.message_types_by_name['Password'] = _PASSWORD
DESCRIPTOR.message_types_by_name['PasswordViolations'] = _PASSWORDVIOLATIONS
DESCRIPTOR.message_types_by_name['Video'] = _VIDEO
DESCRIPTOR.message_types_by_name['VideoInfo'] = _VIDEOINFO
DESCRIPTOR.message_types_by_name['Workflow'] = _WORKFLOW
DESCRIPTOR.message_types_by_name['WorkflowVersion'] = _WORKFLOWVERSION
DESCRIPTOR.message_types_by_name['WorkflowNode'] = _WORKFLOWNODE
DESCRIPTOR.message_types_by_name['NodeInput'] = _NODEINPUT
DESCRIPTOR.message_types_by_name['WorkflowResult'] = _WORKFLOWRESULT
DESCRIPTOR.message_types_by_name['WorkflowState'] = _WORKFLOWSTATE
DESCRIPTOR.message_types_by_name['AppDuplication'] = _APPDUPLICATION
DESCRIPTOR.message_types_by_name['AppDuplicationFilters'] = _APPDUPLICATIONFILTERS
DESCRIPTOR.message_types_by_name['Task'] = _TASK
DESCRIPTOR.message_types_by_name['AiAssistParameters'] = _AIASSISTPARAMETERS
DESCRIPTOR.message_types_by_name['TaskWorker'] = _TASKWORKER
DESCRIPTOR.message_types_by_name['TaskWorkerPartitionedStrategyInfo'] = _TASKWORKERPARTITIONEDSTRATEGYINFO
DESCRIPTOR.message_types_by_name['TaskInputSource'] = _TASKINPUTSOURCE
DESCRIPTOR.message_types_by_name['TaskReview'] = _TASKREVIEW
DESCRIPTOR.message_types_by_name['TaskReviewManualStrategyInfo'] = _TASKREVIEWMANUALSTRATEGYINFO
DESCRIPTOR.message_types_by_name['TaskReviewConsensusStrategyInfo'] = _TASKREVIEWCONSENSUSSTRATEGYINFO
DESCRIPTOR.message_types_by_name['TaskAIAssistant'] = _TASKAIASSISTANT
DESCRIPTOR.message_types_by_name['TaskStatusCountPerUser'] = _TASKSTATUSCOUNTPERUSER
DESCRIPTOR.message_types_by_name['Collector'] = _COLLECTOR
DESCRIPTOR.message_types_by_name['CollectorSource'] = _COLLECTORSOURCE
DESCRIPTOR.message_types_by_name['APIPostModelOutputsCollectorSource'] = _APIPOSTMODELOUTPUTSCOLLECTORSOURCE
DESCRIPTOR.message_types_by_name['StatValue'] = _STATVALUE
DESCRIPTOR.message_types_by_name['StatValueAggregateResult'] = _STATVALUEAGGREGATERESULT
DESCRIPTOR.message_types_by_name['StatValueAggregate'] = _STATVALUEAGGREGATE
DESCRIPTOR.message_types_by_name['StatValueAggregateQuery'] = _STATVALUEAGGREGATEQUERY
DESCRIPTOR.message_types_by_name['Visibility'] = _VISIBILITY
DESCRIPTOR.message_types_by_name['TrendingMetric'] = _TRENDINGMETRIC
DESCRIPTOR.message_types_by_name['TimeSegment'] = _TIMESEGMENT
DESCRIPTOR.message_types_by_name['TimeInfo'] = _TIMEINFO
DESCRIPTOR.enum_types_by_name['ExpirationAction'] = _EXPIRATIONACTION
DESCRIPTOR.enum_types_by_name['LicenseScope'] = _LICENSESCOPE
DESCRIPTOR.enum_types_by_name['ValueComparator'] = _VALUECOMPARATOR
DESCRIPTOR.enum_types_by_name['EvaluationType'] = _EVALUATIONTYPE
DESCRIPTOR.enum_types_by_name['APIEventType'] = _APIEVENTTYPE
DESCRIPTOR.enum_types_by_name['UsageIntervalType'] = _USAGEINTERVALTYPE
DESCRIPTOR.enum_types_by_name['RoleType'] = _ROLETYPE
DESCRIPTOR.enum_types_by_name['StatValueAggType'] = _STATVALUEAGGTYPE
DESCRIPTOR.enum_types_by_name['StatTimeAggType'] = _STATTIMEAGGTYPE
DESCRIPTOR.enum_types_by_name['ValidationErrorType'] = _VALIDATIONERRORTYPE
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
Annotation = _reflection.GeneratedProtocolMessageType('Annotation', (_message.Message,), {
'DESCRIPTOR' : _ANNOTATION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Annotation)
})
_sym_db.RegisterMessage(Annotation)
App = _reflection.GeneratedProtocolMessageType('App', (_message.Message,), {
'DESCRIPTOR' : _APP,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.App)
})
_sym_db.RegisterMessage(App)
AppQuery = _reflection.GeneratedProtocolMessageType('AppQuery', (_message.Message,), {
'DESCRIPTOR' : _APPQUERY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.AppQuery)
})
_sym_db.RegisterMessage(AppQuery)
Collaborator = _reflection.GeneratedProtocolMessageType('Collaborator', (_message.Message,), {
'DESCRIPTOR' : _COLLABORATOR,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Collaborator)
})
_sym_db.RegisterMessage(Collaborator)
Collaboration = _reflection.GeneratedProtocolMessageType('Collaboration', (_message.Message,), {
'DESCRIPTOR' : _COLLABORATION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Collaboration)
})
_sym_db.RegisterMessage(Collaboration)
Audio = _reflection.GeneratedProtocolMessageType('Audio', (_message.Message,), {
'DESCRIPTOR' : _AUDIO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Audio)
})
_sym_db.RegisterMessage(Audio)
AudioInfo = _reflection.GeneratedProtocolMessageType('AudioInfo', (_message.Message,), {
'DESCRIPTOR' : _AUDIOINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.AudioInfo)
})
_sym_db.RegisterMessage(AudioInfo)
Track = _reflection.GeneratedProtocolMessageType('Track', (_message.Message,), {
'DESCRIPTOR' : _TRACK,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Track)
})
_sym_db.RegisterMessage(Track)
Cluster = _reflection.GeneratedProtocolMessageType('Cluster', (_message.Message,), {
'DESCRIPTOR' : _CLUSTER,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Cluster)
})
_sym_db.RegisterMessage(Cluster)
Color = _reflection.GeneratedProtocolMessageType('Color', (_message.Message,), {
'DESCRIPTOR' : _COLOR,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Color)
})
_sym_db.RegisterMessage(Color)
W3C = _reflection.GeneratedProtocolMessageType('W3C', (_message.Message,), {
'DESCRIPTOR' : _W3C,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.W3C)
})
_sym_db.RegisterMessage(W3C)
UserAppIDSet = _reflection.GeneratedProtocolMessageType('UserAppIDSet', (_message.Message,), {
'DESCRIPTOR' : _USERAPPIDSET,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.UserAppIDSet)
})
_sym_db.RegisterMessage(UserAppIDSet)
PatchAction = _reflection.GeneratedProtocolMessageType('PatchAction', (_message.Message,), {
'DESCRIPTOR' : _PATCHACTION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.PatchAction)
})
_sym_db.RegisterMessage(PatchAction)
Concept = _reflection.GeneratedProtocolMessageType('Concept', (_message.Message,), {
'DESCRIPTOR' : _CONCEPT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Concept)
})
_sym_db.RegisterMessage(Concept)
ConceptCount = _reflection.GeneratedProtocolMessageType('ConceptCount', (_message.Message,), {
'DESCRIPTOR' : _CONCEPTCOUNT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConceptCount)
})
_sym_db.RegisterMessage(ConceptCount)
ConceptTypeCount = _reflection.GeneratedProtocolMessageType('ConceptTypeCount', (_message.Message,), {
'DESCRIPTOR' : _CONCEPTTYPECOUNT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConceptTypeCount)
})
_sym_db.RegisterMessage(ConceptTypeCount)
DetailConceptCount = _reflection.GeneratedProtocolMessageType('DetailConceptCount', (_message.Message,), {
'DESCRIPTOR' : _DETAILCONCEPTCOUNT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.DetailConceptCount)
})
_sym_db.RegisterMessage(DetailConceptCount)
ConceptQuery = _reflection.GeneratedProtocolMessageType('ConceptQuery', (_message.Message,), {
'DESCRIPTOR' : _CONCEPTQUERY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConceptQuery)
})
_sym_db.RegisterMessage(ConceptQuery)
ConceptRelation = _reflection.GeneratedProtocolMessageType('ConceptRelation', (_message.Message,), {
'DESCRIPTOR' : _CONCEPTRELATION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConceptRelation)
})
_sym_db.RegisterMessage(ConceptRelation)
KnowledgeGraph = _reflection.GeneratedProtocolMessageType('KnowledgeGraph', (_message.Message,), {
'DESCRIPTOR' : _KNOWLEDGEGRAPH,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.KnowledgeGraph)
})
_sym_db.RegisterMessage(KnowledgeGraph)
ConceptMappingJob = _reflection.GeneratedProtocolMessageType('ConceptMappingJob', (_message.Message,), {
'DESCRIPTOR' : _CONCEPTMAPPINGJOB,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConceptMappingJob)
})
_sym_db.RegisterMessage(ConceptMappingJob)
ConceptLanguage = _reflection.GeneratedProtocolMessageType('ConceptLanguage', (_message.Message,), {
'DESCRIPTOR' : _CONCEPTLANGUAGE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConceptLanguage)
})
_sym_db.RegisterMessage(ConceptLanguage)
Data = _reflection.GeneratedProtocolMessageType('Data', (_message.Message,), {
'DESCRIPTOR' : _DATA,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Data)
})
_sym_db.RegisterMessage(Data)
Region = _reflection.GeneratedProtocolMessageType('Region', (_message.Message,), {
'DESCRIPTOR' : _REGION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Region)
})
_sym_db.RegisterMessage(Region)
RegionInfo = _reflection.GeneratedProtocolMessageType('RegionInfo', (_message.Message,), {
'DESCRIPTOR' : _REGIONINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.RegionInfo)
})
_sym_db.RegisterMessage(RegionInfo)
BoundingBox = _reflection.GeneratedProtocolMessageType('BoundingBox', (_message.Message,), {
'DESCRIPTOR' : _BOUNDINGBOX,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.BoundingBox)
})
_sym_db.RegisterMessage(BoundingBox)
FrameInfo = _reflection.GeneratedProtocolMessageType('FrameInfo', (_message.Message,), {
'DESCRIPTOR' : _FRAMEINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.FrameInfo)
})
_sym_db.RegisterMessage(FrameInfo)
Frame = _reflection.GeneratedProtocolMessageType('Frame', (_message.Message,), {
'DESCRIPTOR' : _FRAME,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Frame)
})
_sym_db.RegisterMessage(Frame)
Mask = _reflection.GeneratedProtocolMessageType('Mask', (_message.Message,), {
'DESCRIPTOR' : _MASK,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Mask)
})
_sym_db.RegisterMessage(Mask)
Polygon = _reflection.GeneratedProtocolMessageType('Polygon', (_message.Message,), {
'DESCRIPTOR' : _POLYGON,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Polygon)
})
_sym_db.RegisterMessage(Polygon)
Point = _reflection.GeneratedProtocolMessageType('Point', (_message.Message,), {
'DESCRIPTOR' : _POINT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Point)
})
_sym_db.RegisterMessage(Point)
Embedding = _reflection.GeneratedProtocolMessageType('Embedding', (_message.Message,), {
'DESCRIPTOR' : _EMBEDDING,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Embedding)
})
_sym_db.RegisterMessage(Embedding)
GeoPoint = _reflection.GeneratedProtocolMessageType('GeoPoint', (_message.Message,), {
'DESCRIPTOR' : _GEOPOINT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.GeoPoint)
})
_sym_db.RegisterMessage(GeoPoint)
GeoLimit = _reflection.GeneratedProtocolMessageType('GeoLimit', (_message.Message,), {
'DESCRIPTOR' : _GEOLIMIT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.GeoLimit)
})
_sym_db.RegisterMessage(GeoLimit)
GeoBoxedPoint = _reflection.GeneratedProtocolMessageType('GeoBoxedPoint', (_message.Message,), {
'DESCRIPTOR' : _GEOBOXEDPOINT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.GeoBoxedPoint)
})
_sym_db.RegisterMessage(GeoBoxedPoint)
Geo = _reflection.GeneratedProtocolMessageType('Geo', (_message.Message,), {
'DESCRIPTOR' : _GEO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Geo)
})
_sym_db.RegisterMessage(Geo)
Image = _reflection.GeneratedProtocolMessageType('Image', (_message.Message,), {
'DESCRIPTOR' : _IMAGE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Image)
})
_sym_db.RegisterMessage(Image)
ImageInfo = _reflection.GeneratedProtocolMessageType('ImageInfo', (_message.Message,), {
'DESCRIPTOR' : _IMAGEINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ImageInfo)
})
_sym_db.RegisterMessage(ImageInfo)
HostedURL = _reflection.GeneratedProtocolMessageType('HostedURL', (_message.Message,), {
'DESCRIPTOR' : _HOSTEDURL,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.HostedURL)
})
_sym_db.RegisterMessage(HostedURL)
Input = _reflection.GeneratedProtocolMessageType('Input', (_message.Message,), {
'DESCRIPTOR' : _INPUT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Input)
})
_sym_db.RegisterMessage(Input)
InputCount = _reflection.GeneratedProtocolMessageType('InputCount', (_message.Message,), {
'DESCRIPTOR' : _INPUTCOUNT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.InputCount)
})
_sym_db.RegisterMessage(InputCount)
DatasetFilter = _reflection.GeneratedProtocolMessageType('DatasetFilter', (_message.Message,), {
'DESCRIPTOR' : _DATASETFILTER,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.DatasetFilter)
})
_sym_db.RegisterMessage(DatasetFilter)
DatasetVersion = _reflection.GeneratedProtocolMessageType('DatasetVersion', (_message.Message,), {
'DESCRIPTOR' : _DATASETVERSION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.DatasetVersion)
})
_sym_db.RegisterMessage(DatasetVersion)
DatasetVersionDatasetFilterConfig = _reflection.GeneratedProtocolMessageType('DatasetVersionDatasetFilterConfig', (_message.Message,), {
'DESCRIPTOR' : _DATASETVERSIONDATASETFILTERCONFIG,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.DatasetVersionDatasetFilterConfig)
})
_sym_db.RegisterMessage(DatasetVersionDatasetFilterConfig)
DatasetVersionSummary = _reflection.GeneratedProtocolMessageType('DatasetVersionSummary', (_message.Message,), {
'InputCountsEntry' : _reflection.GeneratedProtocolMessageType('InputCountsEntry', (_message.Message,), {
'DESCRIPTOR' : _DATASETVERSIONSUMMARY_INPUTCOUNTSENTRY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.DatasetVersionSummary.InputCountsEntry)
})
,
'DESCRIPTOR' : _DATASETVERSIONSUMMARY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.DatasetVersionSummary)
})
_sym_db.RegisterMessage(DatasetVersionSummary)
_sym_db.RegisterMessage(DatasetVersionSummary.InputCountsEntry)
WorkflowResultsSimilarity = _reflection.GeneratedProtocolMessageType('WorkflowResultsSimilarity', (_message.Message,), {
'DESCRIPTOR' : _WORKFLOWRESULTSSIMILARITY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.WorkflowResultsSimilarity)
})
_sym_db.RegisterMessage(WorkflowResultsSimilarity)
Key = _reflection.GeneratedProtocolMessageType('Key', (_message.Message,), {
'DESCRIPTOR' : _KEY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Key)
})
_sym_db.RegisterMessage(Key)
Model = _reflection.GeneratedProtocolMessageType('Model', (_message.Message,), {
'DESCRIPTOR' : _MODEL,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Model)
})
_sym_db.RegisterMessage(Model)
ModelReference = _reflection.GeneratedProtocolMessageType('ModelReference', (_message.Message,), {
'DESCRIPTOR' : _MODELREFERENCE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelReference)
})
_sym_db.RegisterMessage(ModelReference)
ModelVersionInputExample = _reflection.GeneratedProtocolMessageType('ModelVersionInputExample', (_message.Message,), {
'DESCRIPTOR' : _MODELVERSIONINPUTEXAMPLE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelVersionInputExample)
})
_sym_db.RegisterMessage(ModelVersionInputExample)
OutputInfo = _reflection.GeneratedProtocolMessageType('OutputInfo', (_message.Message,), {
'DESCRIPTOR' : _OUTPUTINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.OutputInfo)
})
_sym_db.RegisterMessage(OutputInfo)
InputInfo = _reflection.GeneratedProtocolMessageType('InputInfo', (_message.Message,), {
'DESCRIPTOR' : _INPUTINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.InputInfo)
})
_sym_db.RegisterMessage(InputInfo)
TrainInfo = _reflection.GeneratedProtocolMessageType('TrainInfo', (_message.Message,), {
'DESCRIPTOR' : _TRAININFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TrainInfo)
})
_sym_db.RegisterMessage(TrainInfo)
ImportInfo = _reflection.GeneratedProtocolMessageType('ImportInfo', (_message.Message,), {
'DESCRIPTOR' : _IMPORTINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ImportInfo)
})
_sym_db.RegisterMessage(ImportInfo)
OutputConfig = _reflection.GeneratedProtocolMessageType('OutputConfig', (_message.Message,), {
'DESCRIPTOR' : _OUTPUTCONFIG,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.OutputConfig)
})
_sym_db.RegisterMessage(OutputConfig)
ModelType = _reflection.GeneratedProtocolMessageType('ModelType', (_message.Message,), {
'DESCRIPTOR' : _MODELTYPE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelType)
})
_sym_db.RegisterMessage(ModelType)
ModelTypeField = _reflection.GeneratedProtocolMessageType('ModelTypeField', (_message.Message,), {
'DESCRIPTOR' : _MODELTYPEFIELD,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelTypeField)
})
_sym_db.RegisterMessage(ModelTypeField)
ModelTypeRangeInfo = _reflection.GeneratedProtocolMessageType('ModelTypeRangeInfo', (_message.Message,), {
'DESCRIPTOR' : _MODELTYPERANGEINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelTypeRangeInfo)
})
_sym_db.RegisterMessage(ModelTypeRangeInfo)
ModelTypeEnumOption = _reflection.GeneratedProtocolMessageType('ModelTypeEnumOption', (_message.Message,), {
'DESCRIPTOR' : _MODELTYPEENUMOPTION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelTypeEnumOption)
})
_sym_db.RegisterMessage(ModelTypeEnumOption)
ModelQuery = _reflection.GeneratedProtocolMessageType('ModelQuery', (_message.Message,), {
'DESCRIPTOR' : _MODELQUERY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelQuery)
})
_sym_db.RegisterMessage(ModelQuery)
ModelVersion = _reflection.GeneratedProtocolMessageType('ModelVersion', (_message.Message,), {
'DESCRIPTOR' : _MODELVERSION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ModelVersion)
})
_sym_db.RegisterMessage(ModelVersion)
LabelCount = _reflection.GeneratedProtocolMessageType('LabelCount', (_message.Message,), {
'DESCRIPTOR' : _LABELCOUNT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.LabelCount)
})
_sym_db.RegisterMessage(LabelCount)
LabelDistribution = _reflection.GeneratedProtocolMessageType('LabelDistribution', (_message.Message,), {
'DESCRIPTOR' : _LABELDISTRIBUTION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.LabelDistribution)
})
_sym_db.RegisterMessage(LabelDistribution)
CooccurrenceMatrixEntry = _reflection.GeneratedProtocolMessageType('CooccurrenceMatrixEntry', (_message.Message,), {
'DESCRIPTOR' : _COOCCURRENCEMATRIXENTRY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.CooccurrenceMatrixEntry)
})
_sym_db.RegisterMessage(CooccurrenceMatrixEntry)
CooccurrenceMatrix = _reflection.GeneratedProtocolMessageType('CooccurrenceMatrix', (_message.Message,), {
'DESCRIPTOR' : _COOCCURRENCEMATRIX,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.CooccurrenceMatrix)
})
_sym_db.RegisterMessage(CooccurrenceMatrix)
ConfusionMatrixEntry = _reflection.GeneratedProtocolMessageType('ConfusionMatrixEntry', (_message.Message,), {
'DESCRIPTOR' : _CONFUSIONMATRIXENTRY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConfusionMatrixEntry)
})
_sym_db.RegisterMessage(ConfusionMatrixEntry)
ConfusionMatrix = _reflection.GeneratedProtocolMessageType('ConfusionMatrix', (_message.Message,), {
'DESCRIPTOR' : _CONFUSIONMATRIX,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ConfusionMatrix)
})
_sym_db.RegisterMessage(ConfusionMatrix)
ROC = _reflection.GeneratedProtocolMessageType('ROC', (_message.Message,), {
'DESCRIPTOR' : _ROC,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ROC)
})
_sym_db.RegisterMessage(ROC)
PrecisionRecallCurve = _reflection.GeneratedProtocolMessageType('PrecisionRecallCurve', (_message.Message,), {
'DESCRIPTOR' : _PRECISIONRECALLCURVE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.PrecisionRecallCurve)
})
_sym_db.RegisterMessage(PrecisionRecallCurve)
BinaryMetrics = _reflection.GeneratedProtocolMessageType('BinaryMetrics', (_message.Message,), {
'DESCRIPTOR' : _BINARYMETRICS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.BinaryMetrics)
})
_sym_db.RegisterMessage(BinaryMetrics)
TrackerMetrics = _reflection.GeneratedProtocolMessageType('TrackerMetrics', (_message.Message,), {
'DESCRIPTOR' : _TRACKERMETRICS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TrackerMetrics)
})
_sym_db.RegisterMessage(TrackerMetrics)
EvalTestSetEntry = _reflection.GeneratedProtocolMessageType('EvalTestSetEntry', (_message.Message,), {
'DESCRIPTOR' : _EVALTESTSETENTRY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.EvalTestSetEntry)
})
_sym_db.RegisterMessage(EvalTestSetEntry)
LOPQEvalResult = _reflection.GeneratedProtocolMessageType('LOPQEvalResult', (_message.Message,), {
'DESCRIPTOR' : _LOPQEVALRESULT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.LOPQEvalResult)
})
_sym_db.RegisterMessage(LOPQEvalResult)
MetricsSummary = _reflection.GeneratedProtocolMessageType('MetricsSummary', (_message.Message,), {
'DESCRIPTOR' : _METRICSSUMMARY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.MetricsSummary)
})
_sym_db.RegisterMessage(MetricsSummary)
EvalMetrics = _reflection.GeneratedProtocolMessageType('EvalMetrics', (_message.Message,), {
'DESCRIPTOR' : _EVALMETRICS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.EvalMetrics)
})
_sym_db.RegisterMessage(EvalMetrics)
FieldsValue = _reflection.GeneratedProtocolMessageType('FieldsValue', (_message.Message,), {
'DESCRIPTOR' : _FIELDSVALUE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.FieldsValue)
})
_sym_db.RegisterMessage(FieldsValue)
Output = _reflection.GeneratedProtocolMessageType('Output', (_message.Message,), {
'DESCRIPTOR' : _OUTPUT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Output)
})
_sym_db.RegisterMessage(Output)
ScopeDeps = _reflection.GeneratedProtocolMessageType('ScopeDeps', (_message.Message,), {
'DESCRIPTOR' : _SCOPEDEPS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.ScopeDeps)
})
_sym_db.RegisterMessage(ScopeDeps)
EndpointDeps = _reflection.GeneratedProtocolMessageType('EndpointDeps', (_message.Message,), {
'DESCRIPTOR' : _ENDPOINTDEPS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.EndpointDeps)
})
_sym_db.RegisterMessage(EndpointDeps)
Hit = _reflection.GeneratedProtocolMessageType('Hit', (_message.Message,), {
'DESCRIPTOR' : _HIT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Hit)
})
_sym_db.RegisterMessage(Hit)
And = _reflection.GeneratedProtocolMessageType('And', (_message.Message,), {
'DESCRIPTOR' : _AND,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.And)
})
_sym_db.RegisterMessage(And)
Query = _reflection.GeneratedProtocolMessageType('Query', (_message.Message,), {
'DESCRIPTOR' : _QUERY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Query)
})
_sym_db.RegisterMessage(Query)
Search = _reflection.GeneratedProtocolMessageType('Search', (_message.Message,), {
'DESCRIPTOR' : _SEARCH,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Search)
})
_sym_db.RegisterMessage(Search)
Filter = _reflection.GeneratedProtocolMessageType('Filter', (_message.Message,), {
'DESCRIPTOR' : _FILTER,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Filter)
})
_sym_db.RegisterMessage(Filter)
TimeRange = _reflection.GeneratedProtocolMessageType('TimeRange', (_message.Message,), {
'DESCRIPTOR' : _TIMERANGE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TimeRange)
})
_sym_db.RegisterMessage(TimeRange)
Rank = _reflection.GeneratedProtocolMessageType('Rank', (_message.Message,), {
'DESCRIPTOR' : _RANK,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Rank)
})
_sym_db.RegisterMessage(Rank)
AnnotationSearchMetrics = _reflection.GeneratedProtocolMessageType('AnnotationSearchMetrics', (_message.Message,), {
'DESCRIPTOR' : _ANNOTATIONSEARCHMETRICS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.AnnotationSearchMetrics)
})
_sym_db.RegisterMessage(AnnotationSearchMetrics)
Text = _reflection.GeneratedProtocolMessageType('Text', (_message.Message,), {
'DESCRIPTOR' : _TEXT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Text)
})
_sym_db.RegisterMessage(Text)
TextInfo = _reflection.GeneratedProtocolMessageType('TextInfo', (_message.Message,), {
'DESCRIPTOR' : _TEXTINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TextInfo)
})
_sym_db.RegisterMessage(TextInfo)
User = _reflection.GeneratedProtocolMessageType('User', (_message.Message,), {
'DESCRIPTOR' : _USER,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.User)
})
_sym_db.RegisterMessage(User)
UserDetail = _reflection.GeneratedProtocolMessageType('UserDetail', (_message.Message,), {
'DESCRIPTOR' : _USERDETAIL,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.UserDetail)
})
_sym_db.RegisterMessage(UserDetail)
EmailAddress = _reflection.GeneratedProtocolMessageType('EmailAddress', (_message.Message,), {
'DESCRIPTOR' : _EMAILADDRESS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.EmailAddress)
})
_sym_db.RegisterMessage(EmailAddress)
Password = _reflection.GeneratedProtocolMessageType('Password', (_message.Message,), {
'DESCRIPTOR' : _PASSWORD,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Password)
})
_sym_db.RegisterMessage(Password)
PasswordViolations = _reflection.GeneratedProtocolMessageType('PasswordViolations', (_message.Message,), {
'DESCRIPTOR' : _PASSWORDVIOLATIONS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.PasswordViolations)
})
_sym_db.RegisterMessage(PasswordViolations)
Video = _reflection.GeneratedProtocolMessageType('Video', (_message.Message,), {
'DESCRIPTOR' : _VIDEO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Video)
})
_sym_db.RegisterMessage(Video)
VideoInfo = _reflection.GeneratedProtocolMessageType('VideoInfo', (_message.Message,), {
'DESCRIPTOR' : _VIDEOINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.VideoInfo)
})
_sym_db.RegisterMessage(VideoInfo)
Workflow = _reflection.GeneratedProtocolMessageType('Workflow', (_message.Message,), {
'DESCRIPTOR' : _WORKFLOW,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Workflow)
})
_sym_db.RegisterMessage(Workflow)
WorkflowVersion = _reflection.GeneratedProtocolMessageType('WorkflowVersion', (_message.Message,), {
'DESCRIPTOR' : _WORKFLOWVERSION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.WorkflowVersion)
})
_sym_db.RegisterMessage(WorkflowVersion)
WorkflowNode = _reflection.GeneratedProtocolMessageType('WorkflowNode', (_message.Message,), {
'DESCRIPTOR' : _WORKFLOWNODE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.WorkflowNode)
})
_sym_db.RegisterMessage(WorkflowNode)
NodeInput = _reflection.GeneratedProtocolMessageType('NodeInput', (_message.Message,), {
'DESCRIPTOR' : _NODEINPUT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.NodeInput)
})
_sym_db.RegisterMessage(NodeInput)
WorkflowResult = _reflection.GeneratedProtocolMessageType('WorkflowResult', (_message.Message,), {
'DESCRIPTOR' : _WORKFLOWRESULT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.WorkflowResult)
})
_sym_db.RegisterMessage(WorkflowResult)
WorkflowState = _reflection.GeneratedProtocolMessageType('WorkflowState', (_message.Message,), {
'DESCRIPTOR' : _WORKFLOWSTATE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.WorkflowState)
})
_sym_db.RegisterMessage(WorkflowState)
AppDuplication = _reflection.GeneratedProtocolMessageType('AppDuplication', (_message.Message,), {
'DESCRIPTOR' : _APPDUPLICATION,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.AppDuplication)
})
_sym_db.RegisterMessage(AppDuplication)
AppDuplicationFilters = _reflection.GeneratedProtocolMessageType('AppDuplicationFilters', (_message.Message,), {
'DESCRIPTOR' : _APPDUPLICATIONFILTERS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.AppDuplicationFilters)
})
_sym_db.RegisterMessage(AppDuplicationFilters)
Task = _reflection.GeneratedProtocolMessageType('Task', (_message.Message,), {
'DESCRIPTOR' : _TASK,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Task)
})
_sym_db.RegisterMessage(Task)
AiAssistParameters = _reflection.GeneratedProtocolMessageType('AiAssistParameters', (_message.Message,), {
'DESCRIPTOR' : _AIASSISTPARAMETERS,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.AiAssistParameters)
})
_sym_db.RegisterMessage(AiAssistParameters)
TaskWorker = _reflection.GeneratedProtocolMessageType('TaskWorker', (_message.Message,), {
'DESCRIPTOR' : _TASKWORKER,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskWorker)
})
_sym_db.RegisterMessage(TaskWorker)
TaskWorkerPartitionedStrategyInfo = _reflection.GeneratedProtocolMessageType('TaskWorkerPartitionedStrategyInfo', (_message.Message,), {
'DESCRIPTOR' : _TASKWORKERPARTITIONEDSTRATEGYINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskWorkerPartitionedStrategyInfo)
})
_sym_db.RegisterMessage(TaskWorkerPartitionedStrategyInfo)
TaskInputSource = _reflection.GeneratedProtocolMessageType('TaskInputSource', (_message.Message,), {
'DESCRIPTOR' : _TASKINPUTSOURCE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskInputSource)
})
_sym_db.RegisterMessage(TaskInputSource)
TaskReview = _reflection.GeneratedProtocolMessageType('TaskReview', (_message.Message,), {
'DESCRIPTOR' : _TASKREVIEW,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskReview)
})
_sym_db.RegisterMessage(TaskReview)
TaskReviewManualStrategyInfo = _reflection.GeneratedProtocolMessageType('TaskReviewManualStrategyInfo', (_message.Message,), {
'DESCRIPTOR' : _TASKREVIEWMANUALSTRATEGYINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskReviewManualStrategyInfo)
})
_sym_db.RegisterMessage(TaskReviewManualStrategyInfo)
TaskReviewConsensusStrategyInfo = _reflection.GeneratedProtocolMessageType('TaskReviewConsensusStrategyInfo', (_message.Message,), {
'DESCRIPTOR' : _TASKREVIEWCONSENSUSSTRATEGYINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskReviewConsensusStrategyInfo)
})
_sym_db.RegisterMessage(TaskReviewConsensusStrategyInfo)
TaskAIAssistant = _reflection.GeneratedProtocolMessageType('TaskAIAssistant', (_message.Message,), {
'DESCRIPTOR' : _TASKAIASSISTANT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskAIAssistant)
})
_sym_db.RegisterMessage(TaskAIAssistant)
TaskStatusCountPerUser = _reflection.GeneratedProtocolMessageType('TaskStatusCountPerUser', (_message.Message,), {
'DESCRIPTOR' : _TASKSTATUSCOUNTPERUSER,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TaskStatusCountPerUser)
})
_sym_db.RegisterMessage(TaskStatusCountPerUser)
Collector = _reflection.GeneratedProtocolMessageType('Collector', (_message.Message,), {
'DESCRIPTOR' : _COLLECTOR,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Collector)
})
_sym_db.RegisterMessage(Collector)
CollectorSource = _reflection.GeneratedProtocolMessageType('CollectorSource', (_message.Message,), {
'DESCRIPTOR' : _COLLECTORSOURCE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.CollectorSource)
})
_sym_db.RegisterMessage(CollectorSource)
APIPostModelOutputsCollectorSource = _reflection.GeneratedProtocolMessageType('APIPostModelOutputsCollectorSource', (_message.Message,), {
'DESCRIPTOR' : _APIPOSTMODELOUTPUTSCOLLECTORSOURCE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.APIPostModelOutputsCollectorSource)
})
_sym_db.RegisterMessage(APIPostModelOutputsCollectorSource)
StatValue = _reflection.GeneratedProtocolMessageType('StatValue', (_message.Message,), {
'DESCRIPTOR' : _STATVALUE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.StatValue)
})
_sym_db.RegisterMessage(StatValue)
StatValueAggregateResult = _reflection.GeneratedProtocolMessageType('StatValueAggregateResult', (_message.Message,), {
'DESCRIPTOR' : _STATVALUEAGGREGATERESULT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.StatValueAggregateResult)
})
_sym_db.RegisterMessage(StatValueAggregateResult)
StatValueAggregate = _reflection.GeneratedProtocolMessageType('StatValueAggregate', (_message.Message,), {
'DESCRIPTOR' : _STATVALUEAGGREGATE,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.StatValueAggregate)
})
_sym_db.RegisterMessage(StatValueAggregate)
StatValueAggregateQuery = _reflection.GeneratedProtocolMessageType('StatValueAggregateQuery', (_message.Message,), {
'DESCRIPTOR' : _STATVALUEAGGREGATEQUERY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.StatValueAggregateQuery)
})
_sym_db.RegisterMessage(StatValueAggregateQuery)
Visibility = _reflection.GeneratedProtocolMessageType('Visibility', (_message.Message,), {
'DESCRIPTOR' : _VISIBILITY,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.Visibility)
})
_sym_db.RegisterMessage(Visibility)
TrendingMetric = _reflection.GeneratedProtocolMessageType('TrendingMetric', (_message.Message,), {
'DESCRIPTOR' : _TRENDINGMETRIC,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TrendingMetric)
})
_sym_db.RegisterMessage(TrendingMetric)
TimeSegment = _reflection.GeneratedProtocolMessageType('TimeSegment', (_message.Message,), {
'DESCRIPTOR' : _TIMESEGMENT,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TimeSegment)
})
_sym_db.RegisterMessage(TimeSegment)
TimeInfo = _reflection.GeneratedProtocolMessageType('TimeInfo', (_message.Message,), {
'DESCRIPTOR' : _TIMEINFO,
'__module__' : 'proto.clarifai.api.resources_pb2'
# @@protoc_insertion_point(class_scope:clarifai.api.TimeInfo)
})
_sym_db.RegisterMessage(TimeInfo)
DESCRIPTOR._options = None
_ANNOTATION.fields_by_name['embed_model_version_id']._options = None
_ANNOTATION.fields_by_name['trusted']._options = None
_COLOR.fields_by_name['value']._options = None
_CONCEPT.fields_by_name['value']._options = None
_CONCEPTTYPECOUNT.fields_by_name['positive']._options = None
_CONCEPTTYPECOUNT.fields_by_name['negative']._options = None
_BOUNDINGBOX.fields_by_name['top_row']._options = None
_BOUNDINGBOX.fields_by_name['left_col']._options = None
_BOUNDINGBOX.fields_by_name['bottom_row']._options = None
_BOUNDINGBOX.fields_by_name['right_col']._options = None
_FRAMEINFO.fields_by_name['index']._options = None
_FRAMEINFO.fields_by_name['time']._options = None
_POINT.fields_by_name['row']._options = None
_POINT.fields_by_name['col']._options = None
_EMBEDDING.fields_by_name['vector']._options = None
_GEOPOINT.fields_by_name['longitude']._options = None
_GEOPOINT.fields_by_name['latitude']._options = None
_GEOLIMIT.fields_by_name['value']._options = None
_INPUTCOUNT.fields_by_name['processed']._options = None
_INPUTCOUNT.fields_by_name['to_process']._options = None
_INPUTCOUNT.fields_by_name['errors']._options = None
_INPUTCOUNT.fields_by_name['processing']._options = None
_INPUTCOUNT.fields_by_name['reindexed']._options = None
_INPUTCOUNT.fields_by_name['to_reindex']._options = None
_INPUTCOUNT.fields_by_name['reindex_errors']._options = None
_INPUTCOUNT.fields_by_name['reindexing']._options = None
_DATASETVERSIONSUMMARY_INPUTCOUNTSENTRY._options = None
_MODEL.fields_by_name['app_id']._options = None
_MODEL.fields_by_name['toolkits']._options = None
_MODEL.fields_by_name['use_cases']._options = None
_MODEL.fields_by_name['languages']._options = None
_OUTPUTCONFIG.fields_by_name['concepts_mutually_exclusive']._options = None
_OUTPUTCONFIG.fields_by_name['closed_environment']._options = None
_OUTPUTCONFIG.fields_by_name['existing_model_id']._options = None
_OUTPUTCONFIG.fields_by_name['hyper_parameters']._options = None
_OUTPUTCONFIG.fields_by_name['max_concepts']._options = None
_OUTPUTCONFIG.fields_by_name['min_value']._options = None
_OUTPUTCONFIG.fields_by_name['model_metadata']._options = None
_MODELQUERY.fields_by_name['type']._options = None
_CONFUSIONMATRIXENTRY.fields_by_name['value']._options = None
_ROC.fields_by_name['fpr']._options = None
_ROC.fields_by_name['tpr']._options = None
_ROC.fields_by_name['thresholds']._options = None
_PRECISIONRECALLCURVE.fields_by_name['recall']._options = None
_PRECISIONRECALLCURVE.fields_by_name['precision']._options = None
_PRECISIONRECALLCURVE.fields_by_name['thresholds']._options = None
_BINARYMETRICS.fields_by_name['num_pos']._options = None
_BINARYMETRICS.fields_by_name['num_neg']._options = None
_BINARYMETRICS.fields_by_name['num_tot']._options = None
_BINARYMETRICS.fields_by_name['roc_auc']._options = None
_BINARYMETRICS.fields_by_name['f1']._options = None
_EVALTESTSETENTRY.fields_by_name['id']._options = None
_EVALTESTSETENTRY.fields_by_name['url']._options = None
_LOPQEVALRESULT.fields_by_name['recall_vs_brute_force']._options = None
_LOPQEVALRESULT.fields_by_name['kendall_tau_vs_brute_force']._options = None
_LOPQEVALRESULT.fields_by_name['most_frequent_code_percent']._options = None
_LOPQEVALRESULT.fields_by_name['lopq_ndcg']._options = None
_LOPQEVALRESULT.fields_by_name['brute_force_ndcg']._options = None
_METRICSSUMMARY.fields_by_name['top1_accuracy']._options = None
_METRICSSUMMARY.fields_by_name['top5_accuracy']._options = None
_METRICSSUMMARY.fields_by_name['macro_avg_roc_auc']._options = None
_METRICSSUMMARY.fields_by_name['macro_std_roc_auc']._options = None
_METRICSSUMMARY.fields_by_name['macro_avg_f1_score']._options = None
_METRICSSUMMARY.fields_by_name['macro_std_f1_score']._options = None
_METRICSSUMMARY.fields_by_name['macro_avg_precision']._options = None
_METRICSSUMMARY.fields_by_name['macro_avg_recall']._options = None
_HIT.fields_by_name['score']._options = None
_USER.fields_by_name['primary_email']._options = None
_USER.fields_by_name['bill_type']._options = None
_USER.fields_by_name['date_gdpr_consent']._options = None
_USER.fields_by_name['date_tos_consent']._options = None
_USER.fields_by_name['date_marketing_consent']._options = None
_USER.fields_by_name['metadata']._options = None
_USER.fields_by_name['email_addresses']._options = None
_USER.fields_by_name['is_org_admin']._options = None
_USER.fields_by_name['two_factor_auth_enabled']._options = None
_USER.fields_by_name['teams_count']._options = None
_EMAILADDRESS.fields_by_name['email']._options = None
_EMAILADDRESS.fields_by_name['primary']._options = None
_EMAILADDRESS.fields_by_name['verified']._options = None
_WORKFLOW.fields_by_name['use_cases']._options = None
_TASKSTATUSCOUNTPERUSER.fields_by_name['pending']._options = None
_TASKSTATUSCOUNTPERUSER.fields_by_name['awaiting_review']._options = None
_TASKSTATUSCOUNTPERUSER.fields_by_name['success']._options = None
_TASKSTATUSCOUNTPERUSER.fields_by_name['review_denied']._options = None
_TASKSTATUSCOUNTPERUSER.fields_by_name['awaiting_consensus_review']._options = None
# @@protoc_insertion_point(module_scope)
| 45.061907 | 43,340 | 0.746353 | 56,670 | 432,369 | 5.411964 | 0.028022 | 0.056812 | 0.041683 | 0.049499 | 0.809385 | 0.746172 | 0.711248 | 0.68998 | 0.673279 | 0.664785 | 0 | 0.04711 | 0.12426 | 432,369 | 9,594 | 43,341 | 45.066604 | 0.762877 | 0.019167 | 0 | 0.715831 | 1 | 0.006734 | 0.18656 | 0.139627 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.003312 | 0.002429 | 0 | 0.002429 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
f4c64a7a54b7978071d99d5cdc4a84cf994c7184 | 182 | py | Python | config.py | cclauss/Exchange2domain | d4765cac7f18800b00e82cce02c27bf22b4f9fdd | [
"MIT"
] | null | null | null | config.py | cclauss/Exchange2domain | d4765cac7f18800b00e82cce02c27bf22b4f9fdd | [
"MIT"
] | null | null | null | config.py | cclauss/Exchange2domain | d4765cac7f18800b00e82cce02c27bf22b4f9fdd | [
"MIT"
] | 1 | 2019-04-19T08:21:15.000Z | 2019-04-19T08:21:15.000Z | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
class global_var:
success = False
def set_suc(status):
global_var.success = status
def get_suc():
return global_var.success
| 20.222222 | 31 | 0.681319 | 27 | 182 | 4.407407 | 0.666667 | 0.226891 | 0.403361 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006711 | 0.181319 | 182 | 8 | 32 | 22.75 | 0.791946 | 0.230769 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0 | 0.166667 | 0.833333 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
f4fabdbef731c8fe0641e0e395956d9370f3d23a | 6,069 | py | Python | tests/test_lists.py | milokmet/trakt.py | 94fac17931a2f16e4719ff71cd35cf70e5be3e7b | [
"MIT"
] | 147 | 2015-01-07T11:27:26.000Z | 2022-02-21T19:57:44.000Z | tests/test_lists.py | milokmet/trakt.py | 94fac17931a2f16e4719ff71cd35cf70e5be3e7b | [
"MIT"
] | 90 | 2015-01-11T14:38:22.000Z | 2021-10-03T12:18:13.000Z | tests/test_lists.py | milokmet/trakt.py | 94fac17931a2f16e4719ff71cd35cf70e5be3e7b | [
"MIT"
] | 61 | 2015-01-09T12:32:09.000Z | 2022-02-03T00:50:36.000Z | # flake8: noqa: F403, F405
from __future__ import absolute_import, division, print_function
from tests.core import mock
from trakt import Trakt
from trakt.objects import PublicList, User
from hamcrest import *
from httmock import HTTMock
def test_popular():
with HTTMock(mock.fixtures, mock.unknown):
items = Trakt['lists'].popular()
assert_that(items, all_of(
has_length(2),
contains(
all_of(
instance_of(PublicList),
has_properties({
'pk': ('trakt', '1338'),
'name': 'Top Chihuahua Movies',
'description': 'So cute.',
'privacy': 'public',
'allow_comments': True,
'display_numbers': True,
'sort_by': 'rank',
'sort_how': 'asc',
'comment_count': 20,
'comment_total': 20,
'like_count': 109,
'like_total': 109,
'item_count': 50,
# Keys
'keys': [
('trakt', '1338'),
('slug', 'top-chihuahua-movies')
],
# User
'user': all_of(
instance_of(User),
has_properties({
'pk': ('slug', 'justin'),
'username': 'justin',
'private': False,
'name': 'Justin Nemeth',
'vip': True,
'vip_ep': False
})
)
})
),
all_of(
instance_of(PublicList),
has_properties({
'pk': ('trakt', '1337'),
'name': 'Incredible Thoughts',
'description': 'How could my brain conceive them?',
'privacy': 'public',
'allow_comments': True,
'display_numbers': True,
'sort_by': 'rank',
'sort_how': 'asc',
'comment_count': 10,
'comment_total': 10,
'like_count': 99,
'like_total': 99,
'item_count': 50,
# Keys
'keys': [
('trakt', '1337'),
('slug', 'incredible-thoughts')
],
# User
'user': all_of(
instance_of(User),
has_properties({
'pk': ('slug', 'justin'),
'username': 'justin',
'private': False,
'name': 'Justin Nemeth',
'vip': True,
'vip_ep': False
})
)
})
)
)
))
def test_trending():
with HTTMock(mock.fixtures, mock.unknown):
items = Trakt['lists'].trending()
assert_that(items, all_of(
has_length(2),
contains(
all_of(
instance_of(PublicList),
has_properties({
'pk': ('trakt', '1337'),
'name': 'Incredible Thoughts',
'description': 'How could my brain conceive them?',
'privacy': 'public',
'allow_comments': True,
'display_numbers': True,
'sort_by': 'rank',
'sort_how': 'asc',
'comment_count': 5,
'comment_total': 10,
'like_count': 5,
'like_total': 99,
'item_count': 50,
# Keys
'keys': [
('trakt', '1337'),
('slug', 'incredible-thoughts')
],
# User
'user': all_of(
instance_of(User),
has_properties({
'pk': ('slug', 'justin'),
'username': 'justin',
'private': False,
'name': 'Justin Nemeth',
'vip': True,
'vip_ep': False
})
)
})
),
all_of(
instance_of(PublicList),
has_properties({
'pk': ('trakt', '1338'),
'name': 'Top Chihuahua Movies',
'description': 'So cute.',
'privacy': 'public',
'allow_comments': True,
'display_numbers': True,
'sort_by': 'rank',
'sort_how': 'asc',
'comment_count': 4,
'comment_total': 20,
'like_count': 4,
'like_total': 109,
'item_count': 50,
# Keys
'keys': [
('trakt', '1338'),
('slug', 'top-chihuahua-movies')
],
# User
'user': all_of(
instance_of(User),
has_properties({
'pk': ('slug', 'justin'),
'username': 'justin',
'private': False,
'name': 'Justin Nemeth',
'vip': True,
'vip_ep': False
})
)
})
)
)
))
| 30.964286 | 71 | 0.32872 | 394 | 6,069 | 4.865482 | 0.225888 | 0.026082 | 0.054251 | 0.062598 | 0.871153 | 0.823161 | 0.823161 | 0.823161 | 0.823161 | 0.77204 | 0 | 0.030087 | 0.561872 | 6,069 | 195 | 72 | 31.123077 | 0.690861 | 0.010545 | 0 | 0.831169 | 0 | 0 | 0.19216 | 0 | 0 | 0 | 0 | 0 | 0.012987 | 1 | 0.012987 | false | 0 | 0.038961 | 0 | 0.051948 | 0.006494 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
522c8ef4fb7576aa13834a5f872f572ec9ffdec9 | 1,760 | py | Python | tests.py | kangfend/timespans | 0d33d079eed1468de3d164605b20e1d738f9091d | [
"MIT"
] | 1 | 2018-10-25T12:47:33.000Z | 2018-10-25T12:47:33.000Z | tests.py | kangfend/timespans | 0d33d079eed1468de3d164605b20e1d738f9091d | [
"MIT"
] | null | null | null | tests.py | kangfend/timespans | 0d33d079eed1468de3d164605b20e1d738f9091d | [
"MIT"
] | 1 | 2018-10-25T08:08:33.000Z | 2018-10-25T08:08:33.000Z | from timespans import TimeSpanSet, TimeSpan
from datetime import datetime
from unittest import TestCase
class SpanSetCase(TestCase):
def test_converge(self):
span_set = TimeSpanSet([TimeSpan(datetime(2015, 5, 1, 0), datetime(2015, 5, 1, 4)),
TimeSpan(datetime(2015, 5, 1, 0), datetime(2015, 5, 1, 5)),
TimeSpan(datetime(2015, 5, 1, 5,30), datetime(2015, 5, 1, 6))])
self.assertEqual(span_set, TimeSpanSet([TimeSpan(datetime(2015, 5, 1), datetime(2015, 5, 1, 5)),
TimeSpan(datetime(2015, 5, 1, 5, 30), datetime(2015, 5, 1, 6))]))
def test_add(self):
span_set = TimeSpanSet([TimeSpan(datetime(2015, 5, 1, 0), datetime(2015, 5, 1, 4)),
TimeSpan(datetime(2015, 5, 1, 0), datetime(2015, 5, 1, 5)),
TimeSpan(datetime(2015, 5, 1, 5, 30), datetime(2015, 5, 1, 6))])
span_set2 = TimeSpanSet(TimeSpan(start=datetime(2015, 5, 1, 5), end=datetime(2015, 5, 1, 7)))
self.assertEqual(span_set + span_set2,
TimeSpanSet([TimeSpan(datetime(2015, 5, 1), datetime(2015, 5, 1, 7))]))
def test_sub(self):
span_set = TimeSpanSet([TimeSpan(datetime(2015, 5, 1, 0), datetime(2015, 5, 1, 4)),
TimeSpan(datetime(2015, 5, 1, 0), datetime(2015, 5, 1, 5)),
TimeSpan(datetime(2015, 5, 1, 5, 30), datetime(2015, 5, 1, 6))])
span_set2 = TimeSpanSet(TimeSpan(start=datetime(2015, 5, 1, 5), end=datetime(2015, 5, 1, 7)))
self.assertEqual(span_set - span_set2,
TimeSpanSet([TimeSpan(datetime(2015, 5, 1), datetime(2015, 5, 1, 5))]))
| 51.764706 | 104 | 0.552273 | 232 | 1,760 | 4.133621 | 0.12931 | 0.375391 | 0.406674 | 0.437956 | 0.828989 | 0.827946 | 0.827946 | 0.827946 | 0.820647 | 0.820647 | 0 | 0.176755 | 0.296023 | 1,760 | 33 | 105 | 53.333333 | 0.597256 | 0 | 0 | 0.458333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 1 | 0.125 | false | 0 | 0.125 | 0 | 0.291667 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
524ef5c9f7ea1ee1a26da86b37c611856d263189 | 40,970 | py | Python | BlenderDataGeneration/sceneSetup.py | C3Imaging/SyntheticHeadPose | b139aeda41ace2a07138705a4997d2ea65cb11a6 | [
"MIT"
] | 1 | 2021-02-03T09:49:50.000Z | 2021-02-03T09:49:50.000Z | BlenderDataGeneration/sceneSetup.py | C3Imaging/SyntheticHeadPose | b139aeda41ace2a07138705a4997d2ea65cb11a6 | [
"MIT"
] | 1 | 2022-03-25T07:30:38.000Z | 2022-03-25T07:33:48.000Z | BlenderDataGeneration/sceneSetup.py | C3Imaging/SyntheticHeadPose | b139aeda41ace2a07138705a4997d2ea65cb11a6 | [
"MIT"
] | null | null | null | import bpy
import numpy as np
from itertools import repeat
import random
import bmesh
from math import radians, degrees
from mathutils import Matrix, Euler
from sympy.geometry import Point
"""
This code do the following -
Blender scene setup after importing the fbx model
Add camera
Set rendering parameters
Set continuous rotations (Yaw, Pitch, Roll) to the headbone
"""
def map_tuple_gen(func, tup):
"""
Applies func to each element of tup and returns a new tuple.
>>> a = (1, 2, 3, 4)
>>> func = lambda x: x * x
>>> map_tuple(func, a)
(1, 4, 9, 16)
Based on : https://codereview.stackexchange.com/questions/86753/map-a-function-to-all-elements-of-a-tuple/86756
"""
return tuple(func(itup) for itup in tup)
# Class camera
# setup camera attributes and properties
class Camera:
def __init__(self):
self.camera = bpy.data.cameras.new('Camera')
self.camera.name = 'Camera'
# Import camera object
self.scene_camera = bpy.data.objects.new('Camera', self.camera)
self.location = self.scene_camera.location
bpy.context.collection.objects.link(self.scene_camera)
bpy.context.scene.camera = self.scene_camera
def set_perspective(self, focal_length=35, sensor=32):
self.scene_camera.data.type = "PERSP"
self.scene_camera.data.lens = focal_length
self.scene_camera.data.sensor_width = sensor
def set_orthographic(self, ortho_scale):
self.scene_camera.data.type = "ORTHO"
self.scene_camera.data.ortho_scale = ortho_scale
def set_far_clipping_plane(self, clip):
self.scene_camera.data.clip_end = clip
def rotate_around_3D_point(self, point, context_override, angle_degrees, axis):
# Place the 3D cursor at the point
bpy.context.scene.cursor_location = point
# Set the pivot point to the 3D cursor
for area in bpy.context.screen.areas:
if area.type == 'VIEW_3D':
area.spaces[0].pivot_point = 'CURSOR'
break
bpy.ops.object.select_all(action='DESELECT') # Deselect all
blender_scene = bpy.context.scene
blender_scene.objects.active = self.scene_camera
print("CAMERA: {}. Rotation {}".format(self.scene_camera, angle_degrees))
self.scene_camera.select = True # Ensure only the camera is rotated
# Override the context of the operator or else it will only rotate around the object's median point
bpy.ops.transform.rotate(context_override, value=Util.degrees_to_Radians(angle_degrees), axis=axis)
def set_rotation(self,
rotation): # TODO modify set_rotation so that it takes angles in degrees and converts them to radians
self.scene_camera.rotation_euler = rotation
def set_location(self, location):
self.scene_camera.location = location
def get_location(self):
return self.scene_camera.location
def get_roatation(self):
return self.scene_camera.rotation_euler.copy()
def get_roatation_degrees(self):
rotation_radians = self.get_roatation()
rotation_degrees = []
for i in range(0, 3):
rotation_degrees.append(Util.radians_to_degrees(rotation_radians[i]))
return rotation_degrees
# Align initial head with respect to head bone
arma = bpy.data.objects['Armature']
bpy.context.view_layer.objects.active = arma
bpy.ops.object.mode_set(mode='POSE')
boneHead = arma.pose.bones['Head'] # Head G6Beta_Head
boneNeck = arma.pose.bones['NeckTwist01'] # NeckTwist01 G6Beta_Neck
boneHead.rotation_mode = 'XYZ'
boneNeck.rotation_mode = 'XYZ'
bpy.context.view_layer.update()
boneHeadPose = tuple(map(round, np.degrees(np.array(boneHead.matrix.to_euler('XYZ')[0:3])), repeat(4)))
boneNeck.rotation_euler.rotate_axis('X', radians(90 - boneHeadPose[0])) # pitch
bpy.context.view_layer.update()
boneHeadPose = tuple(map(round, np.degrees(np.array(boneHead.matrix.to_euler('XYZ')[0:3])), repeat(4)))
boneNeck.rotation_euler.rotate_axis('Z', radians(boneHeadPose[1])) # roll
bpy.context.view_layer.update()
boneHeadPose = tuple(map(round, np.degrees(np.array(boneHead.matrix.to_euler('XYZ')[0:3])), repeat(4)))
boneNeck.rotation_euler.rotate_axis('Y', radians(-boneHeadPose[2])) # yaw
#############################################################
# region Render
# The render resolution of the final texture and depth images:
final_image_resolution_x = 640
final_image_resolution_y = 480
render_resolution_percent = 100
render_focal_length = 20 # 35 is the default Blender uses - using 20 to match Synaptics data when camera is 500mm away
render_sensor_size = 32
default_camera_position = 0.3 # Default distance from the origin on the z-axis (assume millimetres)
bpy.context.scene.unit_settings.system = 'METRIC'
bpy.context.scene.unit_settings.length_unit = 'METERS'
# ------- setup scene render parameters -------- #
bpy.context.scene.render.engine = 'CYCLES'
bpy.context.scene.cycles.device = 'GPU'
# ------- setup screen resolution ------- #
bpy.context.scene.render.resolution_x = final_image_resolution_x
bpy.context.scene.render.resolution_y = final_image_resolution_y
bpy.context.view_layer.update()
_objects = bpy.context.scene.objects
bpy.ops.object.mode_set(mode='EDIT')
# --- Get the Mid Point of eye ball ---- #
emptyList = []
for _obj in _objects:
# print(_obj.type)
if _obj.type == 'MESH':
# print(_obj_name)
if 'Eye' in _obj.name:
# print(_obj.name)
for name in _obj.vertex_groups.keys():
# print(name)
# bpy.ops.object.empty_add(location=(0, 0, 0))
mt = bpy.data.objects.new("empty", None)
bpy.context.scene.collection.objects.link(mt)
# mt = context.object
mt.name = f"{_obj.name}_{name}"
emptyList.append(mt.name)
cl = mt.constraints.new('COPY_LOCATION')
cl.target = _obj
cl.subtarget = name
cr = mt.constraints.new('COPY_ROTATION')
cr.target = _obj
cr.subtarget = name
# print(mt.matrix_world)
bpy.ops.object.mode_set(mode='OBJECT')
l_eye = bpy.data.objects[emptyList[1]]
r_eye = bpy.data.objects[emptyList[0]]
l_eye_pos = Point(l_eye.matrix_world.translation)
r_eye_pos = Point(r_eye.matrix_world.translation)
global_location = map_tuple_gen(float, l_eye_pos.midpoint(r_eye_pos))
scn = bpy.context.scene
# --- Set Scene camera ---- #
camera = Camera()
camera.set_perspective(focal_length=render_focal_length, sensor=render_sensor_size)
bpy.data.scenes["Scene"].render.resolution_x = final_image_resolution_x
bpy.data.scenes["Scene"].render.resolution_y = final_image_resolution_y
bpy.data.scenes["Scene"].render.resolution_percentage = render_resolution_percent
# Offset the camera by the default camera position along the z-axis
camera_location = [global_location[0], -(-global_location[1] + default_camera_position), global_location[2]]
camera.set_location(camera_location)
camera.set_rotation((radians(90), 0, 0))
# Set the far clipping plane of the camera
camera.set_far_clipping_plane(default_camera_position * 10)
# Deselect all and delete the eye empty
bpy.ops.object.select_all(action='DESELECT')
l_eye.select_set(True)
bpy.ops.object.delete()
bpy.ops.object.select_all(action='DESELECT')
r_eye.select_set(True)
bpy.ops.object.delete()
# -----------------------------------
empty1 = bpy.data.objects.new("empty", None)
empty1.location = global_location
scn.collection.objects.link(empty1)
bpy.ops.object.mode_set(mode='OBJECT')
bpy.ops.object.select_all(action='DESELECT')
ob = bpy.data.objects['empty']
arma = bpy.data.objects['Armature']
bpy.ops.object.select_all(action='DESELECT')
arma.select_set(True)
bpy.context.view_layer.objects.active = arma
bpy.ops.object.mode_set(mode='EDIT')
parent_bone = 'Head' # choose the bone name which you want to be the parent # G6Beta_Head Head
arma.data.edit_bones.active = arma.data.edit_bones[parent_bone]
bpy.ops.object.mode_set(mode='OBJECT')
bpy.ops.object.select_all(action='DESELECT') # deselect all objects
ob.select_set(True)
arma.select_set(True)
bpy.context.view_layer.objects.active = arma # the active object will be the parent of all selected object
bpy.ops.object.parent_set(type='BONE', keep_transform=True)
context = bpy.context
for ob in context.selected_objects:
ob.animation_data_clear()
arma = bpy.data.objects['Armature']
# bpy.context.scene.objects.active = ob
bpy.context.view_layer.objects.active = arma
bpy.ops.object.mode_set(mode='POSE')
pbone = arma.pose.bones['NeckTwist01'] # G6Beta_Neck NeckTwist01
# Set rotation mode to Euler XYZ, easier to understand
# than default quaternions
pbone.rotation_mode = 'XYZ'
init_headpose = tuple(pbone.rotation_euler)
# Put manual rotations on the headbone/neckbone
if False:
pbone.keyframe_insert(data_path="rotation_euler", frame=0)
print("-------------------------------------------")
print(map_tuple_gen(degrees, pbone.rotation_euler))
# ------ Yaw (-80, +80) Pitch 0, Roll (-8.0, 8.0) ------ #
for i in range(1, 21):
pbone.rotation_euler = init_headpose # Pitch 0
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-8.0, 8.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-4 * (i - 0 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(21, 41):
pbone.rotation_euler = init_headpose # Pitch 0
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-8.0, 8.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(4 * (i - 20 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# ------ Yaw (-60, +60) Pitch 10, Roll (-10.0, 10.0) ------ #
for i in range(41, 61):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-10)) # Pitch 10
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-10.0, 10.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-3 * (i - 40 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(61, 81):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-10)) # Pitch 10
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-10.0, 10.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(3 * (i - 60 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(81, 101):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(10)) # Pitch -10
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-10.0, 10.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-3 * (i - 80 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(101, 121):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(10)) # Pitch -10
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-10.0, 10.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(3 * (i - 100 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# ------ Yaw (-75, +75) Pitch 20, Roll (-20.0, 20.0) ------ #
for i in range(121, 151):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(20)) # Pitch -20
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-20.0, 20.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-2.5 * (i - 120 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(151, 181):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(20)) # Pitch -20
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-20.0, 20.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(2.5 * (i - 150 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(181, 211):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-20)) # Pitch 20
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-20.0, 20.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-2.5 * (i - 180 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(211, 241):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-20)) # Pitch 20
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-20.0, 20.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(2.5 * (i - 210 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# ------ Yaw (-75, +75) Pitch 35, Roll (-30.0, 30.0) ------ #
for i in range(241, 261):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(35)) # Pitch -35
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-30.0, 30.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(3 * (i - 240 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(261, 281):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(35)) # Pitch -35
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-30.0, 30.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-3 * (i - 260 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(281, 301):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-35)) # Pitch 35
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-30.0, 30.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(3 * (i - 280 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(301, 321):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-35)) # Pitch 35
pbone.rotation_euler.rotate_axis('Z', radians(random.uniform(-30.0, 30.0))) # Roll
pbone.rotation_euler.rotate_axis('Y', radians(-3 * (i - 300 + 1))) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# ------ Yaw (-80, +80) Pitch 0 ------ #
pbone.rotation_euler = init_headpose # Pitch 0
for i in range(321, 361):
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.rotation_euler = init_headpose # Pitch 0
for i in range(361, 421):
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
# ------ Yaw (-70, +70) Pitch Up to 62.5 ------ #
# Pitch 2.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-2.5)) # Pitch 2.5
for i in range(421, 456):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-2.5)) # Pitch 2.5
for i in range(456, 491):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-5)) # Pitch 5
for i in range(491, 526):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-5)) # Pitch 5
for i in range(526, 561):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 7.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-7.5)) # Pitch 7.5
for i in range(561, 596):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-7.5)) # Pitch 7.5
for i in range(596, 631):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 10
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-10)) # Pitch 10
for i in range(631, 666):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-10)) # Pitch 10
for i in range(666, 701):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 12.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-12.5)) # Pitch 12.5
for i in range(701, 736):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-12.5)) # Pitch 12.5
for i in range(736, 771):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 15
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-15)) # Pitch 15
for i in range(771, 806):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-15)) # Pitch 15
for i in range(806, 841):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 17.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-17.5)) # Pitch 17.5
for i in range(841, 876):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-17.5)) # Pitch 17.5
for i in range(876, 911):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 20
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-20)) # Pitch 20
for i in range(911, 946):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-20)) # Pitch 20
for i in range(946, 981):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 22.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-22.5)) # Pitch 22.5
for i in range(981, 1016):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-22.5)) # Pitch 22.5
for i in range(1016, 1051):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 25
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-25)) # Pitch 25
for i in range(1051, 1086):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-25)) # Pitch 25
for i in range(1086, 1121):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 27.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-27.5)) # Pitch 27.5
for i in range(1121, 1156):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-27.5)) # Pitch 27.5
for i in range(1156, 1191):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 30
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-30)) # Pitch 30
for i in range(1191, 1226):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-30)) # Pitch 30
for i in range(1226, 1261):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 32.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-32.5)) # Pitch 32.5
for i in range(1261, 1296):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-32.5)) # Pitch 32.5
for i in range(1296, 1331):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 35
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-35)) # Pitch 35
for i in range(1331, 1366):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-35)) # Pitch 35
for i in range(1366, 1401):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 37.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-37.5)) # Pitch 37.5
for i in range(1401, 1436):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-37.5)) # Pitch 37.5
for i in range(1436, 1471):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 40
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-40)) # Pitch 40
for i in range(1471, 1506):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-40)) # Pitch 40
for i in range(1506, 1541):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 42.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-42.5)) # Pitch 42.5
for i in range(1541, 1576):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-42.5)) # Pitch 42.5
for i in range(1576, 1611):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 45
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-45)) # Pitch 45
for i in range(1611, 1646):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-45)) # Pitch 45
for i in range(1646, 1681):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 47.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-47.5)) # Pitch 47.5
for i in range(1681, 1716):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-47.5)) # Pitch 47.5
for i in range(1716, 1751):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 50
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-50)) # Pitch 50
for i in range(1751, 1786):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-50)) # Pitch 50
for i in range(1786, 1821):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 52.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-52.5)) # Pitch 52.5
for i in range(1821, 1856):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-52.5)) # Pitch 52.5
for i in range(1856, 1891):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 55
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-55)) # Pitch 55
for i in range(1891, 1926):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-55)) # Pitch 55
for i in range(1926, 1961):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 57.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-57.5)) # Pitch 57.5
for i in range(1961, 1996):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-57.5)) # Pitch 57.5
for i in range(1996, 2031):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 60
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-60)) # Pitch 60
for i in range(2031, 2066):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-60)) # Pitch 60
for i in range(2066, 2101):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 62.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-62.5)) # Pitch 62.5
for i in range(2101, 2136):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(-62.5)) # Pitch 62.5
for i in range(2136, 2171):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# ------ Yaw (-70, +70) Pitch Down to 47.5 ------ #
# Pitch -2.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(2.5)) # Pitch -2.5
for i in range(2171, 2206):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(2.5)) # Pitch -2.5
for i in range(2206, 2241):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(5)) # Pitch -5
for i in range(2241, 2276):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(5)) # Pitch -5
for i in range(2276, 2311):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -7.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(7.5)) # Pitch -7.5
for i in range(2311, 2346):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(7.5)) # Pitch 7.5
for i in range(2346, 2381):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -10
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(10)) # Pitch -10
for i in range(2381, 2416):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(10)) # Pitch -10
for i in range(2416, 2451):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -12.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(12.5)) # Pitch -12.5
for i in range(2451, 2486):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(12.5)) # Pitch -12.5
for i in range(2486, 2521):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -15
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(15)) # Pitch -15
for i in range(2521, 2556):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(15)) # Pitch -15
for i in range(2556, 2591):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -17.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(17.5)) # Pitch -17.5
for i in range(2591, 2626):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(17.5)) # Pitch -17.5
for i in range(2626, 2661):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -20
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(20)) # Pitch -20
for i in range(2661, 2696):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(20)) # Pitch -20
for i in range(2696, 2731):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -22.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(22.5)) # Pitch -22.5
for i in range(2731, 2766):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(22.5)) # Pitch -22.5
for i in range(2766, 2801):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -25
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(25)) # Pitch -25
for i in range(2801, 2836):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(25)) # Pitch -25
for i in range(2836, 2871):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -27.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(27.5)) # Pitch -27.5
for i in range(2871, 2906):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(27.5)) # Pitch -27.5
for i in range(2906, 2941):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -30
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(30)) # Pitch -30
for i in range(2941, 2976):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(30)) # Pitch -30
for i in range(2976, 3011):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -32.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(32.5)) # Pitch -32.5
for i in range(3011, 3046):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(32.5)) # Pitch -32.5
for i in range(3046, 3081):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -35
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(35)) # Pitch -35
for i in range(3081, 3116):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(35)) # Pitch -35
for i in range(3116, 3151):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -37.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(37.5)) # Pitch -37.5
for i in range(3151, 3186):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(37.5)) # Pitch -37.5
for i in range(3186, 3221):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 40
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(40)) # Pitch -40
for i in range(3221, 3246):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(40)) # Pitch -40
for i in range(3246, 3271):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 42.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(42.5)) # Pitch -42.5
for i in range(3271, 3296):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(42.5)) # Pitch -42.5
for i in range(3296, 3321):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch 45
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(45)) # Pitch -45
for i in range(3321, 3346):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(45)) # Pitch -45
for i in range(3346, 3371):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# Pitch -47.5
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(47.5)) # Pitch -47.5
for i in range(3371, 3396):
pbone.rotation_euler.rotate_axis('Y', radians(-2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('X', radians(47.5)) # Pitch -47.5
for i in range(3396, 3421):
pbone.rotation_euler.rotate_axis('Y', radians(2)) # Yaw
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# ------ Roll (-45, +45) ------ #
for i in range(3421, 3445):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('Z', radians(-2 * (i - 3421 + 1))) # roll
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
for i in range(3445, 3469):
pbone.rotation_euler = init_headpose
pbone.rotation_euler.rotate_axis('Z', radians(2 * (i - 3445 + 1))) # roll
pbone.keyframe_insert(data_path="rotation_euler", frame=i)
# -----------------------------------
bpy.ops.object.mode_set(mode='OBJECT')
bpy.ops.object.select_all(action='DESELECT')
bpy.ops.wm.save_mainfile()
| 41.678535 | 123 | 0.675397 | 5,897 | 40,970 | 4.489741 | 0.073597 | 0.216045 | 0.222994 | 0.193723 | 0.801367 | 0.787543 | 0.779007 | 0.770434 | 0.766166 | 0.757063 | 0 | 0.053013 | 0.18782 | 40,970 | 982 | 124 | 41.720978 | 0.74266 | 0.103539 | 0 | 0.646043 | 0 | 0 | 0.058258 | 0.001192 | 0 | 0 | 0 | 0.001018 | 0 | 1 | 0.015827 | false | 0 | 0.011511 | 0.002878 | 0.034532 | 0.004317 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
52644b8a5f45585eb13dcdbb9d12f69382df4aea | 2,629 | py | Python | tests/integer_util.py | seiren87/yangsutil | 045fc958bee57be905c2f48240b10abece58e55b | [
"MIT"
] | null | null | null | tests/integer_util.py | seiren87/yangsutil | 045fc958bee57be905c2f48240b10abece58e55b | [
"MIT"
] | null | null | null | tests/integer_util.py | seiren87/yangsutil | 045fc958bee57be905c2f48240b10abece58e55b | [
"MIT"
] | null | null | null | import unittest
from yangsutil import IntegerUtil
class IntegerUtilTestCase(unittest.TestCase):
def test_1_is_check(self):
self.assertTrue(
IntegerUtil.is_check(0),
msg='normal, 0 test'
)
self.assertTrue(
IntegerUtil.is_check(-1),
msg='normal, -1 test'
)
self.assertTrue(
IntegerUtil.is_check(1),
msg='normal, 1 test'
)
self.assertTrue(
IntegerUtil.is_check('0'),
msg='normal, string 0 test'
)
self.assertTrue(
IntegerUtil.is_check('1'),
msg='normal, string 1 test'
)
self.assertTrue(
IntegerUtil.is_check('-1'),
msg='normal, string -1 test'
)
self.assertFalse(
IntegerUtil.is_check('aaa'),
msg='normal, string test'
)
self.assertTrue(
IntegerUtil.is_check(0, IntegerUtil.POSITIVE),
msg='POSITIVE, 0 test'
)
self.assertTrue(
IntegerUtil.is_check(1, IntegerUtil.POSITIVE),
msg='POSITIVE, 1 test'
)
self.assertFalse(
IntegerUtil.is_check(-1, IntegerUtil.POSITIVE),
msg='POSITIVE, -1 test'
)
self.assertTrue(
IntegerUtil.is_check(0, IntegerUtil.NEGATIVE),
msg='NEGATIVE, 0 test'
)
self.assertFalse(
IntegerUtil.is_check(1, IntegerUtil.NEGATIVE),
msg='NEGATIVE, 1 test'
)
self.assertTrue(
IntegerUtil.is_check(-1, IntegerUtil.NEGATIVE),
msg='NEGATIVE, -1 test'
)
self.assertFalse(
IntegerUtil.is_check(0, IntegerUtil.POSITIVE_WITHOUT_ZERO),
msg='POSITIVE_WITHOUT_ZERO, 0 test'
)
self.assertTrue(
IntegerUtil.is_check(1, IntegerUtil.POSITIVE_WITHOUT_ZERO),
msg='POSITIVE_WITHOUT_ZERO, 1 test'
)
self.assertFalse(
IntegerUtil.is_check(-1, IntegerUtil.POSITIVE_WITHOUT_ZERO),
msg='POSITIVE_WITHOUT_ZERO, -1 test'
)
self.assertFalse(
IntegerUtil.is_check(0, IntegerUtil.NEGATIVE_WITHOUT_ZERO),
msg='NEGATIVE_WITHOUT_ZERO, 0 test'
)
self.assertFalse(
IntegerUtil.is_check(1, IntegerUtil.NEGATIVE_WITHOUT_ZERO),
msg='NEGATIVE_WITHOUT_ZERO, 1 test'
)
self.assertTrue(
IntegerUtil.is_check(-1, IntegerUtil.NEGATIVE_WITHOUT_ZERO),
msg='NEGATIVE_WITHOUT_ZERO, -1 test'
)
| 29.539326 | 72 | 0.554583 | 257 | 2,629 | 5.494163 | 0.097276 | 0.09915 | 0.24221 | 0.229462 | 0.894476 | 0.894476 | 0.883144 | 0.862606 | 0.705382 | 0.667847 | 0 | 0.021537 | 0.34652 | 2,629 | 88 | 73 | 29.875 | 0.800349 | 0 | 0 | 0.2375 | 0 | 0 | 0.154812 | 0.050209 | 0 | 0 | 0 | 0 | 0.2375 | 1 | 0.0125 | false | 0 | 0.025 | 0 | 0.05 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
52647cef38ad591791b04610141e885f4d7e6a59 | 4,443 | py | Python | tests/test_config.py | spikoc/stateless-password-manager | 4d1100f6c1c80d39d1855b5a5cf3061a4040afb1 | [
"MIT"
] | null | null | null | tests/test_config.py | spikoc/stateless-password-manager | 4d1100f6c1c80d39d1855b5a5cf3061a4040afb1 | [
"MIT"
] | null | null | null | tests/test_config.py | spikoc/stateless-password-manager | 4d1100f6c1c80d39d1855b5a5cf3061a4040afb1 | [
"MIT"
] | null | null | null | """
Test the configuration parameters for the different environments (development, testing and
production).
"""
import os
from flask_testing import TestCase
from project import create_app
class DevelopmentConfigTest(TestCase):
"""Test the development environment settings."""
def create_app(self):
return create_app(settings='project.config.DevelopmentConfig')
def test_app_name(self):
"""test the application name is correct"""
self.assertEqual(os.getenv('APP_NAME', 'stateless-password-manager'),
self.app.config.get('APP_NAME'))
def test_debug_enabled(self):
"""test debug mode is enabled"""
self.assertTrue(self.app.config.get('DEBUG'))
def test_debug_toolbar_enabled(self):
"""test debug toolbar is enabled"""
self.assertTrue(self.app.config.get('DEBUG_TB_ENABLED'))
def test_debug_toolbar_intercept_redirects(self):
"""test intercept does not redirect"""
self.assertFalse(self.app.config.get('DEBUG_TB_INTERCEPT_REDIRECTS'))
def test_env(self):
"""test what environment the app is running in"""
self.assertEqual('development', self.app.config.get('ENV'))
def test_secret_key(self):
"""test the secret key value is valid"""
self.assertEqual(os.getenv('SECRET_KEY', '77c84dc23ad11ebd1e78e80acf73ce8a'),
self.app.config.get('SECRET_KEY'))
def test_testing_disabled(self):
"""test testing mode is disabled"""
self.assertFalse(self.app.config.get('TESTING'))
def test_wtf_csrf_disabled(self):
"""test CSRF protection is disabled"""
self.assertFalse(self.app.config.get('WTF_CSRF_ENABLED'))
class TestingConfigTest(TestCase):
"""Test the testing environment settings."""
def create_app(self):
return create_app(settings='project.config.TestingConfig')
def test_app_name(self):
"""test the application name is correct"""
self.assertEqual(os.getenv('APP_NAME', 'stateless-password-manager'),
self.app.config.get('APP_NAME'))
def test_debug_disabled(self):
"""test debug mode is disabled"""
self.assertFalse(self.app.config.get('DEBUG'))
def test_debug_toolbar_disabled(self):
"""test debug toolbar is disabled"""
self.assertFalse(self.app.config.get('DEBUG_TB_ENABLED'))
def test_env(self):
"""test what environment the app is running in"""
self.assertEqual('production', self.app.config.get('ENV'))
def test_secret_key(self):
"""test the secret key value is valid"""
self.assertEqual(os.getenv('SECRET_KEY', '77c84dc23ad11ebd1e78e80acf73ce8a'),
self.app.config.get('SECRET_KEY'))
def test_testing_enabled(self):
"""test testing mode is enabled"""
self.assertTrue(self.app.config.get('TESTING'))
def test_wtf_csrf_disabled(self):
"""test CSRF protection is disabled"""
self.assertFalse(self.app.config.get('WTF_CSRF_ENABLED'))
class ProductionConfigTest(TestCase):
"""Test the production environment settings."""
def create_app(self):
return create_app(settings='project.config.ProductionConfig')
def test_app_name(self):
"""test the application name is correct"""
self.assertEqual(os.getenv('APP_NAME', 'stateless-password-manager'),
self.app.config.get('APP_NAME'))
def test_debug_disabled(self):
"""test debug mode is disabled"""
self.assertFalse(self.app.config.get('DEBUG'))
def test_debug_toolbar_disabled(self):
"""test debug toolbar is disabled"""
self.assertFalse(self.app.config.get('DEBUG_TB_ENABLED'))
def test_env(self):
"""test what environment the app is running in"""
self.assertEqual('production', self.app.config.get('ENV'))
def test_secret_key(self):
"""test the secret key value is valid"""
self.assertEqual(os.getenv('SECRET_KEY', '77c84dc23ad11ebd1e78e80acf73ce8a'),
self.app.config.get('SECRET_KEY'))
def test_testing_disabled(self):
"""test testing mode is disabled"""
self.assertFalse(self.app.config.get('TESTING'))
def test_wtf_csrf_enabled(self):
"""test CSRF protection is enabled"""
self.assertTrue(self.app.config.get('WTF_CSRF_ENABLED'))
| 35.544 | 94 | 0.66284 | 538 | 4,443 | 5.317844 | 0.124535 | 0.053827 | 0.099965 | 0.123034 | 0.841664 | 0.817197 | 0.817197 | 0.812303 | 0.78539 | 0.731562 | 0 | 0.013706 | 0.211794 | 4,443 | 124 | 95 | 35.830645 | 0.803255 | 0.219221 | 0 | 0.677419 | 0 | 0 | 0.171763 | 0.08783 | 0 | 0 | 0 | 0 | 0.354839 | 1 | 0.403226 | false | 0.048387 | 0.048387 | 0.048387 | 0.548387 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 8 |
875b9f8d28fad459528d47c3d3fd1a463303a1a3 | 167 | py | Python | src/cirrus/plugins/publishers/__init__.py | Maxsparrow/cirrus | ae9639daba4f2d8d9285e98d5b11a89eac573f96 | [
"Apache-2.0"
] | 12 | 2016-04-30T16:13:55.000Z | 2021-01-20T23:42:31.000Z | src/cirrus/plugins/publishers/__init__.py | Maxsparrow/cirrus | ae9639daba4f2d8d9285e98d5b11a89eac573f96 | [
"Apache-2.0"
] | 153 | 2015-02-12T15:25:42.000Z | 2020-03-09T07:16:15.000Z | src/cirrus/plugins/publishers/__init__.py | Maxsparrow/cirrus | ae9639daba4f2d8d9285e98d5b11a89eac573f96 | [
"Apache-2.0"
] | 7 | 2015-06-15T21:30:38.000Z | 2020-02-17T02:13:00.000Z | #!/usr/bin/env python
"""
_publishers_
Documentation publisher plugins
"""
import cirrus.plugins.publishers.doc_file_server
import cirrus.plugins.publishers.jenkins
| 16.7 | 48 | 0.814371 | 20 | 167 | 6.6 | 0.7 | 0.181818 | 0.287879 | 0.439394 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083832 | 167 | 9 | 49 | 18.555556 | 0.862745 | 0.39521 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
5e440a737d874706f673aab20a91cfc2e73c9466 | 10,979 | py | Python | cogs/linkingcommands.py | CDESamBotDev/VCRoles | 764fff6be5dc44194ee3979dbfa72340cd66a172 | [
"Apache-2.0"
] | 3 | 2022-02-18T11:41:07.000Z | 2022-02-22T17:33:09.000Z | cogs/linkingcommands.py | CDESamBotDev/VCRoles | 764fff6be5dc44194ee3979dbfa72340cd66a172 | [
"Apache-2.0"
] | 15 | 2022-01-22T20:15:10.000Z | 2022-03-29T16:10:40.000Z | cogs/linkingcommands.py | CDESamBotDev/VCRoles | 764fff6be5dc44194ee3979dbfa72340cd66a172 | [
"Apache-2.0"
] | null | null | null | from typing import Union
import discord
from discord import app_commands
from discord.ext import commands
from bot import MyClient
from checks import check_any, command_available, is_owner
from utils import handle_data_deletion
class Linking(commands.Cog):
def __init__(self, client: MyClient):
self.client = client
suffix_commands = app_commands.Group(
name="suffix", description="Suffix to add to the end of usernames"
)
reverse_commands = app_commands.Group(name="reverse", description="Reverse roles")
@app_commands.command()
@app_commands.describe(
channel="Select a channel to link", role="Select a role to link"
)
@check_any(command_available, is_owner)
@app_commands.checks.has_permissions(administrator=True)
async def link(
self,
interaction: discord.Interaction,
channel: Union[
discord.CategoryChannel, discord.VoiceChannel, discord.StageChannel
],
role: discord.Role,
):
"""Use to link a channel with a role"""
if isinstance(channel, discord.CategoryChannel):
channel_type = "category"
elif isinstance(channel, discord.VoiceChannel):
channel_type = "voice"
elif isinstance(channel, discord.StageChannel):
channel_type = "stage"
data = self.client.redis.get_linked(channel_type, interaction.guild_id)
try:
data[str(channel.id)]
except:
data[str(channel.id)] = {"roles": [], "suffix": "", "reverse_roles": []}
if str(role.id) not in data[str(channel.id)]["roles"]:
data[str(channel.id)]["roles"].append(str(role.id))
self.client.redis.update_linked(channel_type, interaction.guild_id, data)
await interaction.response.send_message(
f"Linked {channel.mention} with role: `@{role.name}`"
)
member = interaction.guild.get_member(self.client.user.id)
if member.top_role.position < role.position:
await interaction.followup.send(
f"Please ensure my highest role is above `@{role.name}`"
)
else:
await interaction.response.send_message(
f"The channel and role are already linked."
)
return self.client.incr_counter("link")
@app_commands.command()
@app_commands.describe(
channel="Select a channel to unlink", role="Select a role to unlink"
)
@check_any(command_available, is_owner)
@app_commands.checks.has_permissions(administrator=True)
async def unlink(
self,
interaction: discord.Interaction,
channel: Union[
discord.CategoryChannel, discord.VoiceChannel, discord.StageChannel
],
role: discord.Role,
):
"""Use to unlink a channel from a role"""
if isinstance(channel, discord.CategoryChannel):
channel_type = "category"
elif isinstance(channel, discord.VoiceChannel):
channel_type = "voice"
elif isinstance(channel, discord.StageChannel):
channel_type = "stage"
data = self.client.redis.get_linked(channel_type, interaction.guild_id)
try:
data[str(channel.id)]
except:
return await interaction.response.send_message(
f"The channel and role are not linked."
)
if str(role.id) in data[str(channel.id)]["roles"]:
try:
data[str(channel.id)]["roles"].remove(str(role.id))
data = handle_data_deletion(data, str(channel.id))
self.client.redis.update_linked(
channel_type, interaction.guild_id, data
)
await interaction.response.send_message(
f"Unlinked {channel.mention} and role: `@{role.name}`"
)
except:
return await interaction.response.send_message(
f"There was an error unlinking the channel and role."
)
else:
await interaction.response.send_message(
f"The channel and role are not linked."
)
return self.client.incr_counter("unlink")
@suffix_commands.command()
@app_commands.describe(
channel="Select a channel to link",
suffix="Add a suffix to the end of usernames",
)
@check_any(command_available, is_owner)
@app_commands.checks.has_permissions(administrator=True)
async def add(
self,
interaction: discord.Interaction,
channel: Union[
discord.CategoryChannel, discord.VoiceChannel, discord.StageChannel
],
suffix: str,
):
"""Use to set a suffix for a channel"""
if isinstance(channel, discord.CategoryChannel):
channel_type = "category"
elif isinstance(channel, discord.VoiceChannel):
channel_type = "voice"
elif isinstance(channel, discord.StageChannel):
channel_type = "stage"
data = self.client.redis.get_linked(channel_type, interaction.guild_id)
try:
data[str(channel.id)]
except:
data[str(channel.id)] = {"roles": [], "suffix": "", "reverse_roles": []}
data[str(channel.id)]["suffix"] = suffix
self.client.redis.update_linked(channel_type, interaction.guild_id, data)
await interaction.response.send_message(
f"Set the suffix for {channel.mention} to `{suffix}`"
)
return self.client.incr_counter("add_suffix")
@suffix_commands.command()
@app_commands.describe(channel="Select a channel to link")
@check_any(command_available, is_owner)
@app_commands.checks.has_permissions(administrator=True)
async def remove(
self,
interaction: discord.Interaction,
channel: Union[
discord.CategoryChannel, discord.VoiceChannel, discord.StageChannel
],
):
"""Use to remove a suffix for a channel"""
if isinstance(channel, discord.CategoryChannel):
channel_type = "category"
elif isinstance(channel, discord.VoiceChannel):
channel_type = "voice"
elif isinstance(channel, discord.StageChannel):
channel_type = "stage"
data = self.client.redis.get_linked(channel_type, interaction.guild_id)
try:
data[str(channel.id)]
except:
return await interaction.response.send_message(
f"The channel has no associated rules."
)
data[str(channel.id)]["suffix"] = ""
data = handle_data_deletion(data, str(channel.id))
self.client.redis.update_linked(channel_type, interaction.guild_id, data)
await interaction.response.send_message(
f"Removed the suffix for {channel.mention}"
)
return self.client.incr_counter("remove_suffix")
@reverse_commands.command(name="link")
@app_commands.describe(
channel="Select a channel to link", role="Select a role to link"
)
@check_any(command_available, is_owner)
@app_commands.checks.has_permissions(administrator=True)
async def reverse_link(
self,
interaction: discord.Interaction,
channel: Union[
discord.CategoryChannel, discord.VoiceChannel, discord.StageChannel
],
role: discord.Role,
):
"""Use to add a reverse role link"""
if isinstance(channel, discord.CategoryChannel):
channel_type = "category"
elif isinstance(channel, discord.VoiceChannel):
channel_type = "voice"
elif isinstance(channel, discord.StageChannel):
channel_type = "stage"
data = self.client.redis.get_linked(channel_type, interaction.guild_id)
try:
data[str(channel.id)]
except:
data[str(channel.id)] = {"roles": [], "suffix": "", "reverse_roles": []}
if str(role.id) not in data[str(channel.id)]["reverse_roles"]:
data[str(channel.id)]["reverse_roles"].append(str(role.id))
self.client.redis.update_linked(channel_type, interaction.guild_id, data)
await interaction.response.send_message(
f"Linked {channel.mention} with role: `@{role.name}`"
)
member = interaction.guild.get_member(self.client.user.id)
if member.top_role.position < role.position:
await interaction.channel.send(
f"Please ensure my highest role is above `@{role.name}`"
)
else:
await interaction.response.send_message(
f"The channel and role are already linked."
)
return self.client.incr_counter("reverse_link")
@reverse_commands.command(name="unlink")
@app_commands.describe(
channel="Select a channel to link", role="Select a role to link"
)
@check_any(command_available, is_owner)
@app_commands.checks.has_permissions(administrator=True)
async def reverse_unlink(
self,
interaction: discord.Interaction,
channel: Union[
discord.CategoryChannel, discord.VoiceChannel, discord.StageChannel
],
role: discord.Role,
):
"""Use to remove a reverse role link"""
if isinstance(channel, discord.CategoryChannel):
channel_type = "category"
elif isinstance(channel, discord.VoiceChannel):
channel_type = "voice"
elif isinstance(channel, discord.StageChannel):
channel_type = "stage"
data = self.client.redis.get_linked(channel_type, interaction.guild_id)
try:
data[str(channel.id)]
except:
return await interaction.response.send_message(
f"The channel has no associated rules."
)
if str(role.id) in data[str(channel.id)]["reverse_roles"]:
try:
data[str(channel.id)]["reverse_roles"].remove(str(role.id))
data = handle_data_deletion(data, str(channel.id))
self.client.redis.update_linked(
channel_type, interaction.guild_id, data
)
await interaction.response.send_message(
f"Unlinked {channel.mention} and role: `@{role.name}`"
)
except:
return await interaction.response.send_message(
f"There was an error unlinking the channel and role."
)
else:
await interaction.response.send_message(
f"The channel and role are not linked."
)
return self.client.incr_counter("reverse_unlink")
async def setup(client: MyClient):
await client.add_cog(Linking(client))
| 34.096273 | 86 | 0.609163 | 1,186 | 10,979 | 5.508432 | 0.096121 | 0.050513 | 0.047145 | 0.05388 | 0.907852 | 0.867901 | 0.848768 | 0.842951 | 0.842951 | 0.834073 | 0 | 0 | 0.290737 | 10,979 | 321 | 87 | 34.202492 | 0.838962 | 0 | 0 | 0.711462 | 0 | 0 | 0.132365 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.003953 | false | 0 | 0.027668 | 0 | 0.086957 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
5ea77c3a47cfa618a5f03b392eff7604b6303afe | 1,468 | py | Python | simulator/scripts/bug-display.py | LEGO-Robotics/SPIKE-Prime | 90673d1b650877df9b4df5c18fbcb609ddf35402 | [
"MIT"
] | 1 | 2021-11-28T06:44:30.000Z | 2021-11-28T06:44:30.000Z | simulator/scripts/bug-display.py | LEGO-Robotics/SPIKE-Prime | 90673d1b650877df9b4df5c18fbcb609ddf35402 | [
"MIT"
] | null | null | null | simulator/scripts/bug-display.py | LEGO-Robotics/SPIKE-Prime | 90673d1b650877df9b4df5c18fbcb609ddf35402 | [
"MIT"
] | null | null | null | from hub import display
from utime import sleep
display.clear()
sleep(1)
display.pixel(0,0,100)
sleep(1)
display.rotation(90)
sleep(1)
display.pixel(0,0,100)
sleep(1)
display.rotation(-90)
sleep(1)
display.pixel(0,0,0)
# Expected output if the display.pixel(...) command works on the rotated display.
# clear set00 rot+90 set00 rot-90 set00
# 00000 #0000 0000# 0000# #0000 00000
# 00000 00000 00000 00000 00000 00000
# 00000 -> 00000 -> 00000 -> 00000 -> 00000 -> 00000
# 00000 00000 00000 00000 00000 00000
# 00000 00000 00000 00000 00000 00000
# Expected output if the display.pixel(...) command works on the NOT rotated display.
# clear set00 rot+90 set00 rot-90 set00
# 00000 #0000 0000# #000# #0000 00000
# 00000 00000 00000 00000 00000 00000
# 00000 -> 00000 -> 00000 -> 00000 -> 00000 -> 00000
# 00000 00000 00000 00000 00000 00000
# 00000 00000 00000 00000 #0000 #0000
# Recorded output.
# clear set00 rot+90 set00 rot-90 set00
# 00000 #0000 0000# 0000# #000# 00000
# 00000 00000 00000 00000 00000 00000
# 00000 -> 00000 -> 00000 -> 00000 -> 00000 -> 00000
# 00000 00000 00000 00000 00000 00000
# 00000 00000 00000 0000# 00000 #0000
#
# It seems that the display.pixel(...) command opperates on the display rotated by twice the amount?
| 34.952381 | 100 | 0.616485 | 198 | 1,468 | 4.570707 | 0.176768 | 0.740331 | 1.060773 | 1.348066 | 0.816575 | 0.816575 | 0.816575 | 0.816575 | 0.816575 | 0.816575 | 0 | 0.465833 | 0.292234 | 1,468 | 41 | 101 | 35.804878 | 0.405197 | 0.803134 | 0 | 0.538462 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.153846 | 0 | 0.153846 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 13 |
5eb3160557b005cfb8090bda3bd97c9376840035 | 896 | py | Python | expense_tracker/expense_app/models.py | cs-fullstack-fall-2018/project3-django-myiahm | 59039cccd482ea0d69a14e23a9ac165e4730c993 | [
"Apache-2.0"
] | null | null | null | expense_tracker/expense_app/models.py | cs-fullstack-fall-2018/project3-django-myiahm | 59039cccd482ea0d69a14e23a9ac165e4730c993 | [
"Apache-2.0"
] | null | null | null | expense_tracker/expense_app/models.py | cs-fullstack-fall-2018/project3-django-myiahm | 59039cccd482ea0d69a14e23a9ac165e4730c993 | [
"Apache-2.0"
] | null | null | null | from django.db import models
from datetime import datetime
from django.contrib.auth.models import User
class User(models.Model):
name = models.CharField(max_length=200)
currentBal = models.DecimalField(max_digits=15, decimal_places=2)
emergency = models.DecimalField(max_digits=15,decimal_places=2)
date = models.DateField(default=datetime.now)
def __str__(self):
return self.name
class Withdaraw(models.Model):
name = models.CharField(max_length=200)
amount = models.DecimalField(max_digits=4, decimal_places=2)
date = models.DateField(default=datetime.now)
def __str__(self):
return self.name
class Deposit(models.Model):
name = models.CharField(max_length=200)
amount = models.DecimalField(max_digits=15, decimal_places=2)
date = models.DateField(default=datetime.now)
def __str__(self):
return self.name
| 25.6 | 69 | 0.732143 | 118 | 896 | 5.364407 | 0.305085 | 0.113744 | 0.132701 | 0.170616 | 0.791469 | 0.791469 | 0.791469 | 0.791469 | 0.657188 | 0.657188 | 0 | 0.026846 | 0.168527 | 896 | 34 | 70 | 26.352941 | 0.822819 | 0 | 0 | 0.545455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.136364 | false | 0 | 0.136364 | 0.136364 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
0d756fd5fe560350f8331847fac5048b501a7490 | 156 | py | Python | Titanic/model/__init__.py | xHeliotrope/KaggleCompetitions | c50bf9ac85a6540f9f1ab611f84ebe2517e64da4 | [
"MIT"
] | null | null | null | Titanic/model/__init__.py | xHeliotrope/KaggleCompetitions | c50bf9ac85a6540f9f1ab611f84ebe2517e64da4 | [
"MIT"
] | null | null | null | Titanic/model/__init__.py | xHeliotrope/KaggleCompetitions | c50bf9ac85a6540f9f1ab611f84ebe2517e64da4 | [
"MIT"
] | null | null | null | def get_training_data():
"""get training data from train.csv
"""
with open('../data/train.csv') as train_file:
return train_file.read()
| 26 | 49 | 0.634615 | 22 | 156 | 4.318182 | 0.590909 | 0.231579 | 0.315789 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.217949 | 156 | 5 | 50 | 31.2 | 0.778689 | 0.205128 | 0 | 0 | 0 | 0 | 0.150442 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | true | 0 | 0 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 7 |
0d786df8cd1d6b6402cf1aa55926be5a3bd762a7 | 153 | py | Python | 05_functions/python/functions.py | pjuangph/python2rust | cc99abe8738e5d1d7d9a34debb2892186ff77965 | [
"CC0-1.0"
] | 24 | 2021-07-09T13:56:45.000Z | 2022-03-26T19:44:00.000Z | 05_functions/python/functions.py | pjuangph/python2rust | cc99abe8738e5d1d7d9a34debb2892186ff77965 | [
"CC0-1.0"
] | null | null | null | 05_functions/python/functions.py | pjuangph/python2rust | cc99abe8738e5d1d7d9a34debb2892186ff77965 | [
"CC0-1.0"
] | 3 | 2021-07-09T17:16:31.000Z | 2022-03-24T15:44:44.000Z | def do_something(x):
def do_some_other(x):
return x * 3
return do_some_other(x)
if __name__ == '__main__':
print(do_something(3))
| 15.3 | 27 | 0.633987 | 24 | 153 | 3.458333 | 0.5 | 0.120482 | 0.26506 | 0.289157 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017391 | 0.248366 | 153 | 9 | 28 | 17 | 0.704348 | 0 | 0 | 0 | 0 | 0 | 0.052288 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0 | 0.166667 | 0.666667 | 0.166667 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
0d8c0e5b221a8f1373207eb780d08ea2bbd7a115 | 177 | py | Python | tests/dataset/test_get_attribute.py | lparolari/weakvtg | e5d5f738ff0d916da8b31e967aa21f01fb74a906 | [
"RSA-MD",
"Info-ZIP"
] | null | null | null | tests/dataset/test_get_attribute.py | lparolari/weakvtg | e5d5f738ff0d916da8b31e967aa21f01fb74a906 | [
"RSA-MD",
"Info-ZIP"
] | null | null | null | tests/dataset/test_get_attribute.py | lparolari/weakvtg | e5d5f738ff0d916da8b31e967aa21f01fb74a906 | [
"RSA-MD",
"Info-ZIP"
] | null | null | null | import torch
from weakvtg.dataset import get_attribute
def test_get_attribute():
x = torch.rand((2, 3))
assert torch.equal(get_attribute(x), torch.argmax(x, dim=-1))
| 19.666667 | 65 | 0.717514 | 28 | 177 | 4.392857 | 0.642857 | 0.292683 | 0.211382 | 0.292683 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02 | 0.152542 | 177 | 8 | 66 | 22.125 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 1 | 0.2 | false | 0 | 0.4 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
0db1d6dbcf13842db54f1d8700ba52d1b5eb11c2 | 131 | py | Python | summarize/modules/rnns/__init__.py | danieldeutsch/summarize | f36a86d58f381ff1f607f356dad3d6ef7b0e0224 | [
"Apache-2.0"
] | 15 | 2019-11-01T11:49:44.000Z | 2021-01-19T06:59:32.000Z | summarize/modules/rnns/__init__.py | CogComp/summary-cloze | b38e3e8c7755903477fd92a4cff27125cbf5553d | [
"Apache-2.0"
] | 2 | 2020-03-30T07:54:01.000Z | 2021-11-15T16:27:42.000Z | summarize/modules/rnns/__init__.py | CogComp/summary-cloze | b38e3e8c7755903477fd92a4cff27125cbf5553d | [
"Apache-2.0"
] | 3 | 2019-12-06T05:57:51.000Z | 2019-12-11T11:34:21.000Z | from summarize.modules.rnns.rnn import RNN
from summarize.modules.rnns.lstm import LSTM
from summarize.modules.rnns.gru import GRU
| 32.75 | 44 | 0.839695 | 21 | 131 | 5.238095 | 0.380952 | 0.354545 | 0.545455 | 0.654545 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.091603 | 131 | 3 | 45 | 43.666667 | 0.92437 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
216e2a00116c7826dc1246de665e226619864859 | 7,598 | py | Python | tests/end_to_end/scenarios/join_history_limit.py | norayr/biboumi | 805671032d25ee6ce09ed75e8a385c04e9563cdd | [
"Zlib"
] | 68 | 2015-01-29T21:07:37.000Z | 2022-03-20T14:48:07.000Z | tests/end_to_end/scenarios/join_history_limit.py | norayr/biboumi | 805671032d25ee6ce09ed75e8a385c04e9563cdd | [
"Zlib"
] | 5 | 2016-10-24T18:34:30.000Z | 2021-08-31T13:30:37.000Z | tests/end_to_end/scenarios/join_history_limit.py | norayr/biboumi | 805671032d25ee6ce09ed75e8a385c04e9563cdd | [
"Zlib"
] | 13 | 2015-12-11T15:19:05.000Z | 2021-08-31T13:24:35.000Z | from scenarios import *
scenario = (
# Disable the throttling because the test is based on timings
send_stanza("<iq type='set' id='id1' from='{jid_one}/{resource_one}' to='{irc_server_one}'><command xmlns='http://jabber.org/protocol/commands' node='configure' action='execute' /></iq>"),
expect_stanza("/iq[@type='result']",
after = save_value("sessionid", extract_attribute("/iq[@type='result']/commands:command[@node='configure']", "sessionid"))),
send_stanza("<iq type='set' id='id2' from='{jid_one}/{resource_one}' to='{irc_server_one}'>"
"<command xmlns='http://jabber.org/protocol/commands' node='configure' sessionid='{sessionid}' action='next'>"
"<x xmlns='jabber:x:data' type='submit'>"
"<field var='ports'><value>6667</value></field>"
"<field var='tls_ports'><value>6697</value><value>6670</value></field>"
"<field var='throttle_limit'><value>9999</value></field>"
"</x></command></iq>"),
expect_stanza("/iq[@type='result']/commands:command[@node='configure'][@status='completed']/commands:note[@type='info'][text()='Configuration successfully applied.']"),
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}/{nick_one}' ><x xmlns='http://jabber.org/protocol/muc'/></presence>"),
sequences.connection("irc.localhost", '{jid_one}/{resource_one}'),
expect_stanza("/presence[@to='{jid_one}/{resource_one}'][@from='#foo%{irc_server_one}/{nick_one}']/muc_user:x/muc_user:item[@affiliation='admin'][@role='moderator']",
"/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message[@from='#foo%{irc_server_one}'][@type='groupchat']/subject[not(text())]"),
# Send two channel messages
send_stanza("<message from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='groupchat'><body>coucou</body></message>"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@to='{jid_one}/{resource_one}'][@type='groupchat']/body[text()='coucou']",
"/message/stable_id:stanza-id[@by='#foo%{irc_server_one}'][@id]"),
send_stanza("<message from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='groupchat'><body>coucou 2</body></message>"),
# Record the current time
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@to='{jid_one}/{resource_one}'][@type='groupchat']/body[text()='coucou 2']",
after = save_current_timestamp_plus_delta("first_timestamp", datetime.timedelta(seconds=1))),
# Wait two seconds before sending two new messages
sleep_for(2),
send_stanza("<message from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='groupchat'><body>coucou 3</body></message>"),
send_stanza("<message from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='groupchat'><body>coucou 4</body></message>"),
expect_stanza("/message[@type='groupchat']/body[text()='coucou 3']"),
expect_stanza("/message[@type='groupchat']/body[text()='coucou 4']",
after = save_current_timestamp_plus_delta("second_timestamp", datetime.timedelta(seconds=1))),
# join some other channel, to stay connected to the server even after leaving #foo
send_stanza("<presence from='{jid_one}/{resource_one}' to='#DUMMY%{irc_server_one}/{nick_one}' ><x xmlns='http://jabber.org/protocol/muc'/></presence>"),
expect_stanza("/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message/subject"),
# Leave #foo
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='unavailable' />"),
expect_stanza("/presence[@type='unavailable']"),
sleep_for(0.2),
# Rejoin #foo, with some history limit
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}/{nick_one}'><x xmlns='http://jabber.org/protocol/muc'><history maxchars='0'/></x></presence>"),
expect_stanza("/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message/subject"),
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='unavailable' />"),
expect_stanza("/presence[@type='unavailable']"),
sleep_for(0.2),
# Rejoin #foo, with some history limit
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}/{nick_one}'><x xmlns='http://jabber.org/protocol/muc'><history maxstanzas='3'/></x></presence>"),
expect_stanza("/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 2']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 3']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 4']"),
expect_stanza("/message/subject"),
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='unavailable' />"),
expect_stanza("/presence[@type='unavailable']"),
# Rejoin #foo, with some history limit
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}/{nick_one}'><x xmlns='http://jabber.org/protocol/muc'><history since='{first_timestamp}'/></x></presence>"),
expect_stanza("/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 3']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 4']"),
expect_stanza("/message/subject"),
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='unavailable' />"),
expect_stanza("/presence[@type='unavailable']"),
# Rejoin #foo, with some history limit
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}/{nick_one}'><x xmlns='http://jabber.org/protocol/muc'><history seconds='1'/></x></presence>"),
expect_stanza("/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 3']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 4']"),
expect_stanza("/message/subject"),
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='unavailable' />"),
expect_stanza("/presence[@type='unavailable']"),
# Rejoin #foo, with some history limit
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}/{nick_one}'><x xmlns='http://jabber.org/protocol/muc'><history seconds='5'/></x></presence>"),
expect_stanza("/presence/muc_user:x/muc_user:status[@code='110']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou']"), expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 2']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 3']"),
expect_stanza("/message[@from='#foo%{irc_server_one}/{nick_one}'][@type='groupchat']/body[text()='coucou 4']"),
expect_stanza("/message/subject"),
send_stanza("<presence from='{jid_one}/{resource_one}' to='#foo%{irc_server_one}' type='unavailable' />"),
expect_stanza("/presence[@type='unavailable']"),
)
| 74.490196 | 245 | 0.667281 | 1,013 | 7,598 | 4.779862 | 0.131293 | 0.091698 | 0.086741 | 0.099133 | 0.835399 | 0.809789 | 0.775919 | 0.753821 | 0.744321 | 0.734614 | 0 | 0.009679 | 0.102527 | 7,598 | 101 | 246 | 75.227723 | 0.700396 | 0.056331 | 0 | 0.465753 | 0 | 0.383562 | 0.735981 | 0.559083 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.013699 | 0 | 0.013699 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
219c21ba34da445a69d1cdec278ad448e8aa7bfd | 20,521 | py | Python | experiments/project_generators/histogram_per_query_generate_500_dbpedia_cleaned_queries_first_round.py | pjotrscholtze/trident | 865da68fff21d31490acc24db2f4b6bde0b80796 | [
"Apache-2.0"
] | null | null | null | experiments/project_generators/histogram_per_query_generate_500_dbpedia_cleaned_queries_first_round.py | pjotrscholtze/trident | 865da68fff21d31490acc24db2f4b6bde0b80796 | [
"Apache-2.0"
] | null | null | null | experiments/project_generators/histogram_per_query_generate_500_dbpedia_cleaned_queries_first_round.py | pjotrscholtze/trident | 865da68fff21d31490acc24db2f4b6bde0b80796 | [
"Apache-2.0"
] | null | null | null | import json
base_raw = """
{
"name": "histogram-generate-per-query-%d-500-dbpedia-cleaned-queries-first-round",
"description": "Generate histogram/counters for index and table usage, repetition will be 5 times (generate the stats per query), using dbpedia database, removed some queries that crashed or made the experiment take toolong",
"github_url": "https://github.com/pjotrscholtze/trident.git",
"github_checkout": "master",
"script": [
"#!/bin/bash -e",
"#SBATCH -t 15:00 -N 1 -n 8 --mem=16000M",
"#SBATCH -p longq",
"#SBATCH --output=$PROJECT_PATH/slurm_%j.out",
"du -h -d0 $DATABASE_PATH/dbpedia",
"__REPLACED_BELOW__"
]
}
"""
updating_queries = ['/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_331.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_203.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_108.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_819.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_64.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_634.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_537.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_520.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_172.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_166.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_842.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_603.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_312.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_526.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_124.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_7.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_821.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_606.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_801.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_141.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_439.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_421.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_820.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_252.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_749.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_577.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_174.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_121.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_19.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_400.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_671.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_666.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_392.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_890.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_131.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_367.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_517.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_676.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_83.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_748.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_407.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_516.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_192.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_431.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_21.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_297.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_16.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_267.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_36.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_783.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_852.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_257.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_195.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_419.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_774.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_683.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_418.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_652.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_868.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_328.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_305.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_447.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_243.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_844.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_78.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_409.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_622.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_238.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_672.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_746.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_685.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_646.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_515.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_77.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_449.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_3.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_874.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_253.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_240.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_274.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_894.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_489.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_454.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_106.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_771.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_362.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_299.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_790.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_67.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_307.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_13.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_695.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_196.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_66.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_144.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_663.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_910.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_709.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_224.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_731.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_519.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_690.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_295.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_473.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_471.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_125.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_105.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_254.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_892.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_679.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_539.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_416.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_777.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_726.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_465.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_178.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_609.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_370.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_714.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_45.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_725.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_490.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_584.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_463.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_430.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_384.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_154.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_319.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_762.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_287.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_656.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_272.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_34.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_232.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_276.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_626.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_369.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_110.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_487.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_420.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_2.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_311.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_544.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_300.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_130.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_470.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_581.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_858.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_807.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_851.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_651.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_488.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_383.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_119.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_814.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_712.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_889.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_63.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_6.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_836.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_766.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_301.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_345.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_754.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_674.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_265.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_264.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_82.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_304.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_68.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_686.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_65.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_256.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_406.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_402.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_882.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_589.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_28.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_511.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_352.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_388.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_809.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_59.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_135.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_863.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_263.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_151.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_602.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_289.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_76.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_429.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_824.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_472.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_729.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_357.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_58.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_351.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_793.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_617.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_508.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_697.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_480.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_859.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_653.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_164.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_359.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_33.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_707.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_883.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_514.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_308.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_733.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_564.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_25.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_356.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_554.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_887.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_100.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_38.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_27.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_818.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_769.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_205.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_512.sparql', '/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_199.sparql']
# print([int(p[len("/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_"):-len(".sparql")])for p in updating_queries])
res = []
for i in [int(p[len("/storage/wdps/trident/experiments/queries/queries_cleaned/query_chunk_"):-len(".sparql")])for p in updating_queries]:
data = json.loads(base_raw)
data["name"] = data["name"] % i
data["script"][5] = "$BUILD_CACHE_PATH/trident/trident benchmark -i $DATABASE_PATH/dbpedia --query_type query_native --query_file $BUILD_CACHE_PATH/trident/experiments/queries_cleaned_first_round/queries-500/query_chunk_%d.sparql --results_file $PROJECT_PATH/res.json.lines --histogram_mode generate --histogram_file $PROJECT_PATH/temp.json --repetitions 5" % i
res.append(data)
# print(len(updating_queries))
with open("projects/histogram-generate-per-query-500-dbpedia-cleaned-queries-first-round.json", "w") as f:
f.writelines([json.dumps(res, indent=2)]) | 641.28125 | 18,886 | 0.845183 | 2,706 | 20,521 | 6.145233 | 0.124169 | 0.246798 | 0.342775 | 0.395875 | 0.908413 | 0.908413 | 0.904324 | 0.904324 | 0.904324 | 0.900716 | 0 | 0.033222 | 0.021636 | 20,521 | 32 | 18,887 | 641.28125 | 0.795039 | 0.007992 | 0 | 0 | 1 | 0.153846 | 0.940899 | 0.906853 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.038462 | 0 | 0.038462 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 |
21a43a0e047133d44a76fdbfc7f720c7f7e16bb2 | 151 | py | Python | Python_Advanced_Softuni/Modules_Lab/venv/triangle/print_triangle.py | borisboychev/SoftUni | 22062312f08e29a1d85377a6d41ef74966d37e99 | [
"MIT"
] | 1 | 2020-12-14T23:25:19.000Z | 2020-12-14T23:25:19.000Z | Python_Advanced_Softuni/Modules_Lab/venv/triangle/print_triangle.py | borisboychev/SoftUni | 22062312f08e29a1d85377a6d41ef74966d37e99 | [
"MIT"
] | null | null | null | Python_Advanced_Softuni/Modules_Lab/venv/triangle/print_triangle.py | borisboychev/SoftUni | 22062312f08e29a1d85377a6d41ef74966d37e99 | [
"MIT"
] | null | null | null | from triangle.print_line import *
def print_triangle(n):
[print_line(1, x) for x in range(n)]
[print_line(1, x) for x in range(n , 0 , -1)]
| 18.875 | 49 | 0.635762 | 29 | 151 | 3.172414 | 0.448276 | 0.293478 | 0.217391 | 0.23913 | 0.51087 | 0.51087 | 0.51087 | 0.51087 | 0.51087 | 0.51087 | 0 | 0.033898 | 0.218543 | 151 | 7 | 50 | 21.571429 | 0.745763 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.5 | 1 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 7 |
21b05623e4192215fe6ed349aaa10b1005b53181 | 71,907 | py | Python | vitrage/tests/functional/evaluator/test_scenario_evaluator.py | HoonMinJeongUm/Hunmin-vitrage | 37d43d6b78e8b76fa6a2e83e5c739e9e4917a7b6 | [
"Apache-2.0"
] | null | null | null | vitrage/tests/functional/evaluator/test_scenario_evaluator.py | HoonMinJeongUm/Hunmin-vitrage | 37d43d6b78e8b76fa6a2e83e5c739e9e4917a7b6 | [
"Apache-2.0"
] | null | null | null | vitrage/tests/functional/evaluator/test_scenario_evaluator.py | HoonMinJeongUm/Hunmin-vitrage | 37d43d6b78e8b76fa6a2e83e5c739e9e4917a7b6 | [
"Apache-2.0"
] | null | null | null | # Copyright 2016 - Nokia
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from oslo_log import log
from testtools import matchers
from vitrage.tests.functional.test_configuration import TestConfiguration
LOG = log.getLogger(__name__)
from six.moves import queue
from oslo_config import cfg
from vitrage.common.constants import DatasourceAction
from vitrage.common.constants import DatasourceProperties as DSProps
from vitrage.common.constants import EdgeLabel
from vitrage.common.constants import EdgeProperties as EProps
from vitrage.common.constants import EntityCategory
from vitrage.common.constants import VertexProperties as VProps
from vitrage.datasources.cinder.volume.transformer import \
CINDER_VOLUME_DATASOURCE
from vitrage.datasources.nagios import NAGIOS_DATASOURCE
from vitrage.datasources.nagios.properties import NagiosProperties
from vitrage.datasources.nagios.properties import NagiosTestStatus
from vitrage.datasources.neutron.network import NEUTRON_NETWORK_DATASOURCE
from vitrage.datasources.neutron.port import NEUTRON_PORT_DATASOURCE
from vitrage.datasources.nova.host import NOVA_HOST_DATASOURCE
from vitrage.datasources.nova.instance import NOVA_INSTANCE_DATASOURCE
from vitrage.datasources.nova.zone import NOVA_ZONE_DATASOURCE
from vitrage.entity_graph.mappings.operational_resource_state import \
OperationalResourceState
from vitrage.evaluator.actions.evaluator_event_transformer \
import VITRAGE_DATASOURCE
from vitrage.evaluator.scenario_evaluator import ScenarioEvaluator
from vitrage.evaluator.scenario_repository import ScenarioRepository
from vitrage.graph import create_edge
from vitrage.tests.base import IsEmpty
from vitrage.tests.functional.base import \
TestFunctionalBase
import vitrage.tests.mocks.mock_driver as mock_driver
from vitrage.tests.mocks import utils
from vitrage.utils.datetime import utcnow
_TARGET_HOST = 'host-2'
_TARGET_ZONE = 'zone-1'
_NAGIOS_TEST_INFO = {NagiosProperties.RESOURCE_NAME: _TARGET_HOST,
'resource_id': _TARGET_HOST,
DSProps.DATASOURCE_ACTION: DatasourceAction.SNAPSHOT}
class TestScenarioEvaluator(TestFunctionalBase, TestConfiguration):
EVALUATOR_OPTS = [
cfg.StrOpt('templates_dir',
default=utils.get_resources_dir() +
'/templates/evaluator',
),
cfg.StrOpt('notifier_topic',
default='vitrage.evaluator',
),
]
# noinspection PyPep8Naming
@classmethod
def setUpClass(cls):
super(TestScenarioEvaluator, cls).setUpClass()
cls.conf = cfg.ConfigOpts()
cls.conf.register_opts(cls.PROCESSOR_OPTS, group='entity_graph')
cls.conf.register_opts(cls.EVALUATOR_OPTS, group='evaluator')
cls.conf.register_opts(cls.DATASOURCES_OPTS, group='datasources')
cls.add_db(cls.conf)
cls.add_templates(cls.conf.evaluator.templates_dir)
TestScenarioEvaluator.load_datasources(cls.conf)
cls.scenario_repository = ScenarioRepository(cls.conf)
def test_deduced_state(self):
event_queue, processor, evaluator = self._init_system()
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
_TARGET_HOST,
_TARGET_HOST,
processor.entity_graph)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when starting')
# generate nagios alarm to trigger template scenario
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'cause_suboptimal_state'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
warning_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.SUBOPTIMAL,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be SUBOPTIMAL with warning alarm')
# next disable the alarm
warning_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when alarm disabled')
def test_overlapping_deduced_state_1(self):
event_queue, processor, evaluator = self._init_system()
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
_TARGET_HOST,
_TARGET_HOST,
processor.entity_graph)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when starting')
# generate nagios alarm to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'cause_suboptimal_state'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
warning_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.SUBOPTIMAL,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be SUBOPTIMAL with warning alarm')
# generate CRITICAL nagios alarm to trigger
test_vals = \
{NagiosProperties.STATUS: NagiosTestStatus.CRITICAL,
NagiosProperties.SERVICE: 'cause_error_state'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
critical_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.ERROR,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be ERROR with critical alarm')
# next disable the critical alarm
critical_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.SUBOPTIMAL,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be SUBOPTIMAL with only warning alarm')
# next disable the alarm
warning_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE after alarm disabled')
def test_overlapping_deduced_state_2(self):
event_queue, processor, evaluator = self._init_system()
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
_TARGET_HOST,
_TARGET_HOST,
processor.entity_graph)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when starting')
# generate CRITICAL nagios alarm to trigger
test_vals = \
{NagiosProperties.STATUS: NagiosTestStatus.CRITICAL,
NagiosProperties.SERVICE: 'cause_error_state'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
critical_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.ERROR,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be ERROR with critical alarm')
# generate WARNING nagios alarm to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'cause_suboptimal_state'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
warning_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.ERROR,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be ERROR with critical alarm')
# next disable the critical alarm
critical_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
self.assertEqual(OperationalResourceState.SUBOPTIMAL,
host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be SUBOPTIMAL with only warning alarm')
def test_deduced_alarm(self):
event_queue, processor, evaluator = self._init_system()
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
_TARGET_HOST,
_TARGET_HOST,
processor.entity_graph)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when starting')
# generate CRITICAL nagios alarm to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'cause_warning_deduced_alarm'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
warning_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.WARNING,
alarms[0][VProps.SEVERITY])
causes = self._get_alarm_causes(alarms[0], processor.entity_graph)
self.assertThat(causes, matchers.HasLength(1))
# next disable the alarm
warning_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, IsEmpty())
# recreate the nagios alarm
warning_test[NagiosProperties.STATUS] = NagiosTestStatus.WARNING
warning_test[DSProps.SAMPLE_DATE] = str(utcnow())
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.WARNING,
alarms[0][VProps.SEVERITY])
causes = self._get_alarm_causes(alarms[0], processor.entity_graph)
self.assertThat(causes, matchers.HasLength(1))
# next disable the alarm
warning_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, IsEmpty())
def test_overlapping_deduced_alarm_1(self):
event_queue, processor, evaluator = self._init_system()
# generate WARNING nagios alarm
vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'cause_warning_deduced_alarm'}
vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, vals)
warning_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.WARNING,
alarms[0][VProps.SEVERITY])
causes = self._get_alarm_causes(alarms[0], processor.entity_graph)
self.assertThat(causes, matchers.HasLength(1))
# generate CRITICAL nagios alarm to trigger
vals = {NagiosProperties.STATUS: NagiosTestStatus.CRITICAL,
NagiosProperties.SERVICE: 'cause_critical_deduced_alarm'}
vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, vals)
critical_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.CRITICAL,
alarms[0][VProps.SEVERITY])
causes = self._get_alarm_causes(alarms[0], processor.entity_graph)
self.assertThat(causes, matchers.HasLength(2))
# remove WARNING nagios alarm, leaving only CRITICAL one
warning_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.CRITICAL, alarms[0][VProps.SEVERITY])
causes = self._get_alarm_causes(alarms[0], processor.entity_graph)
self.assertThat(causes, matchers.HasLength(1))
# next disable the alarm
critical_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, IsEmpty())
def test_overlapping_deduced_alarm_2(self):
event_queue, processor, evaluator = self._init_system()
# generate CRITICAL nagios alarm to trigger
test_vals = \
{NagiosProperties.STATUS: NagiosTestStatus.CRITICAL,
NagiosProperties.SERVICE: 'cause_critical_deduced_alarm'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
critical_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.CRITICAL,
alarms[0][VProps.SEVERITY])
# generate WARNING nagios alarm to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'cause_warning_deduced_alarm'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
warning_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, warning_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.CRITICAL,
alarms[0][VProps.SEVERITY])
# remove CRITICAL nagios alarm, leaving only WARNING one
critical_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, critical_test,
processor, _TARGET_HOST)
alarms = \
self._get_deduced_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(NagiosTestStatus.WARNING,
alarms[0][VProps.SEVERITY])
def test_simple_not_operator_deduced_alarm(self):
"""Handles a simple not operator use case
We have created the following template: if there is a neutron.port that
doesn't have a nagios alarm of vitrage_type PORT_PROBLEM on it, then
raise a deduced alarm on the port called simple_port_deduced_alarm.
The test has 5 steps in it:
1. create neutron.network and neutron.port and check that the
simple_port_deduced_alarm is raised on the neutron.port because it
doesn't have a nagios alarm on it.
2. create a nagios alarm called PORT_PROBLEM on the port and check
that the alarm simple_port_deduced_alarm doesn't appear on the
neutron.port.
3. delete the edge between nagios alarm called PORT_PROBLEM and the
neutron.port. check that the alarm simple_port_deduced_alarm appear
on the neutron.port.
4. create the edge between nagios alarm called PORT_PROBLEM and the
neutron.port.check that the alarm simple_port_deduced_alarm doesn't
appear on the neutron.port.
5. delete the nagios alarm called PORT_PROBLEM from the port, and
check that the alarm alarm simple_port_deduced_alarm appear on the
neutron.port.
"""
event_queue, processor, evaluator = self._init_system()
entity_graph = processor.entity_graph
# constants
num_orig_vertices = entity_graph.num_vertices()
num_orig_edges = entity_graph.num_edges()
num_added_vertices = 2
num_added_edges = 2
num_deduced_vertices = 1
num_deduced_edges = 1
num_nagios_alarm_vertices = 1
num_nagios_alarm_edges = 1
# find instances
query = {
VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: NOVA_INSTANCE_DATASOURCE
}
instance_ver = entity_graph.get_vertices(vertex_attr_filter=query)[0]
# update network
network_event = {
'tenant_id': 'admin',
'name': 'net-0',
'updated_at': '2015-12-01T12:46:41Z',
'status': 'active',
'id': '12345',
DSProps.ENTITY_TYPE: NEUTRON_NETWORK_DATASOURCE,
DSProps.DATASOURCE_ACTION: DatasourceAction.SNAPSHOT,
DSProps.SAMPLE_DATE: '2015-12-01T12:46:41Z',
}
# update port
port_event = {
'tenant_id': 'admin',
'name': 'port-0',
'updated_at': '2015-12-01T12:46:41Z',
'status': 'active',
'id': '54321',
DSProps.ENTITY_TYPE: NEUTRON_PORT_DATASOURCE,
DSProps.DATASOURCE_ACTION: DatasourceAction.SNAPSHOT,
DSProps.SAMPLE_DATE: '2015-12-01T12:46:41Z',
'network_id': '12345',
'device_id': instance_ver.get(VProps.ID),
'device_owner': 'compute:nova',
'fixed_ips': {}
}
processor.process_event(network_event)
processor.process_event(port_event)
port_vertex = entity_graph.get_vertices(
vertex_attr_filter={VProps.VITRAGE_TYPE:
NEUTRON_PORT_DATASOURCE})[0]
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM}
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices, entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges,
entity_graph.num_edges())
self.assertThat(port_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
port_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
port_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('simple_port_deduced_alarm',
port_neighbors[0][VProps.NAME])
# Add PORT_PROBLEM alarm
test_vals = {'status': NagiosTestStatus.WARNING,
'service': 'PORT_PROBLEM',
'name': 'PORT_PROBLEM',
DSProps.DATASOURCE_ACTION: DatasourceAction.SNAPSHOT,
VProps.RESOURCE_ID: port_vertex.get(VProps.ID),
NagiosProperties.RESOURCE_NAME:
port_vertex.get(VProps.ID),
NagiosProperties.RESOURCE_TYPE: NEUTRON_PORT_DATASOURCE}
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
nagios_event = mock_driver.generate_random_events_list(generator)[0]
processor.process_event(nagios_event)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices + num_nagios_alarm_vertices,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges +
num_nagios_alarm_edges, entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE}
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(port_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
port_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
port_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('simple_port_deduced_alarm',
port_neighbors[0][VProps.NAME])
self.assertTrue(port_neighbors[0][VProps.VITRAGE_IS_DELETED])
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: NAGIOS_DATASOURCE}
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertEqual(EntityCategory.ALARM,
port_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(NAGIOS_DATASOURCE,
port_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('PORT_PROBLEM', port_neighbors[0][VProps.NAME])
self.assertFalse(port_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(port_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# ################### STEP 3 ###################
# disable connection between port and alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: NAGIOS_DATASOURCE}
nagios_vertex = \
processor.entity_graph.get_vertices(vertex_attr_filter=query)[0]
nagios_edge = [e for e in processor.entity_graph.get_edges(
nagios_vertex.vertex_id)][0]
nagios_edge[EProps.VITRAGE_IS_DELETED] = True
processor.entity_graph.update_edge(nagios_edge)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices + num_nagios_alarm_vertices +
# a new uuid is created for every new vertex,
# even if it existed before with another uuid.
# new alarm doesn't override old one
1,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges +
num_nagios_alarm_edges + 1, entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: True}
vitrage_is_deleted = True
for counter in range(0, 1):
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(port_neighbors, matchers.HasLength(1))
self.assertEqual(port_neighbors[0][VProps.VITRAGE_CATEGORY],
EntityCategory.ALARM)
self.assertEqual(port_neighbors[0][VProps.VITRAGE_TYPE],
VITRAGE_DATASOURCE)
self.assertEqual(port_neighbors[0][VProps.NAME],
'simple_port_deduced_alarm')
self.assertEqual(port_neighbors[0][VProps.VITRAGE_IS_DELETED],
vitrage_is_deleted)
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: False}
vitrage_is_deleted = False
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: NAGIOS_DATASOURCE}
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertEqual(EntityCategory.ALARM,
port_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(NAGIOS_DATASOURCE,
port_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('PORT_PROBLEM', port_neighbors[0][VProps.NAME])
self.assertFalse(port_neighbors[0][VProps.VITRAGE_IS_DELETED])
# ################### STEP 4 ###################
# enable connection between port and alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: NAGIOS_DATASOURCE}
nagios_vertex = \
processor.entity_graph.get_vertices(vertex_attr_filter=query)[0]
nagios_edge = [e for e in processor.entity_graph.get_edges(
nagios_vertex.vertex_id)][0]
nagios_edge[EProps.VITRAGE_IS_DELETED] = False
processor.entity_graph.update_edge(nagios_edge)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices + num_nagios_alarm_vertices +
# a new uuid is created for every new vertex,
# even if it existed before with another uuid.
# new alarm doesn't override old one
1,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges +
num_nagios_alarm_edges + 1, entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: True}
vitrage_is_deleted = True
for counter in range(0, 1):
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(port_neighbors, matchers.HasLength(2))
for in_counter in range(0, 1):
self.assertEqual(
EntityCategory.ALARM,
port_neighbors[in_counter][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
port_neighbors[in_counter]
[VProps.VITRAGE_TYPE])
self.assertEqual('simple_port_deduced_alarm',
port_neighbors[in_counter][VProps.NAME])
self.assertEqual(
vitrage_is_deleted,
port_neighbors[in_counter][VProps.VITRAGE_IS_DELETED])
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: False}
vitrage_is_deleted = False
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: NAGIOS_DATASOURCE}
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertEqual(EntityCategory.ALARM,
port_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(NAGIOS_DATASOURCE,
port_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('PORT_PROBLEM', port_neighbors[0][VProps.NAME])
self.assertFalse(port_neighbors[0][VProps.VITRAGE_IS_DELETED])
# ################### STEP 5 ###################
# disable PORT_PROBLEM alarm
nagios_event[NagiosProperties.STATUS] = NagiosTestStatus.OK
processor.process_event(nagios_event)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices + num_nagios_alarm_vertices +
# a new uuid is created for every new vertex,
# even if it existed before with another uuid.
# new alarm doesn't override old one
2,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges +
num_nagios_alarm_edges + 2, entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: True}
vitrage_is_deleted = True
for counter in range(0, 1):
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(port_neighbors, matchers.HasLength(2))
for in_counter in range(0, 1):
self.assertEqual(
EntityCategory.ALARM,
port_neighbors[in_counter][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
port_neighbors[in_counter]
[VProps.VITRAGE_TYPE])
self.assertEqual('simple_port_deduced_alarm',
port_neighbors[in_counter][VProps.NAME])
self.assertEqual(
vitrage_is_deleted,
port_neighbors[in_counter][VProps.VITRAGE_IS_DELETED])
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: False}
vitrage_is_deleted = False
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: NAGIOS_DATASOURCE}
port_neighbors = entity_graph.neighbors(port_vertex.vertex_id,
vertex_attr_filter=query)
self.assertEqual(EntityCategory.ALARM,
port_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(NAGIOS_DATASOURCE,
port_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('PORT_PROBLEM', port_neighbors[0][VProps.NAME])
self.assertTrue(port_neighbors[0][VProps.VITRAGE_IS_DELETED])
def test_complex_not_operator_deduced_alarm(self):
"""Handles a complex not operator use case
We have created the following template: if there is an
openstack.cluster that has a nova.zone which is connected to a
neutron.network and also there is no nagios alarm of vitrage_type
CLUSTER_PROBLEM on the cluster and no nagios alarm of vitrage_type
NETWORK_PROBLEM on the neutron.network, then raise a deduced alarm
on the nova.zone called complex_zone_deduced_alarm.
The test has 3 steps in it:
1. create a neutron.network and connect it to a zone, and check that
the complex_zone_deduced_alarm is raised on the nova.zone because it
doesn't have nagios alarms the openstack.cluster and on the
neutron.network.
2. create a nagios alarm called NETWORK_PROBLEM on the network and
check that the alarm complex_zone_deduced_alarm doesn't appear on
the nova.zone.
3. delete the nagios alarm called NETWORK_PROBLEM from the port, and
check that the alarm alarm complex_zone_deduced_alarm appear on the
nova.zone.
"""
event_queue, processor, evaluator = self._init_system()
entity_graph = processor.entity_graph
# constants
num_orig_vertices = entity_graph.num_vertices()
num_orig_edges = entity_graph.num_edges()
num_added_vertices = 2
num_added_edges = 3
num_deduced_vertices = 1
num_deduced_edges = 1
num_network_alarm_vertices = 1
num_network_alarm_edges = 1
# ################### STEP 1 ###################
# update zone
generator = mock_driver.simple_zone_generators(1, 1, snapshot_events=1)
zone_event = mock_driver.generate_random_events_list(generator)[0]
zone_event['zoneName'] = 'zone-7'
# update network
network_event = {
'tenant_id': 'admin',
'name': 'net-0',
'updated_at': '2015-12-01T12:46:41Z',
'status': 'active',
'id': '12345',
DSProps.ENTITY_TYPE: NEUTRON_NETWORK_DATASOURCE,
DSProps.DATASOURCE_ACTION: DatasourceAction.SNAPSHOT,
DSProps.SAMPLE_DATE: '2015-12-01T12:46:41Z',
}
# process events
processor.process_event(zone_event)
query = {VProps.VITRAGE_TYPE: NOVA_ZONE_DATASOURCE,
VProps.ID: 'zone-7'}
zone_vertex = entity_graph.get_vertices(vertex_attr_filter=query)[0]
processor.process_event(network_event)
query = {VProps.VITRAGE_TYPE: NEUTRON_NETWORK_DATASOURCE}
network_vertex = entity_graph.get_vertices(vertex_attr_filter=query)[0]
# add edge between network and zone
edge = create_edge(network_vertex.vertex_id, zone_vertex.vertex_id,
EdgeLabel.ATTACHED)
entity_graph.add_edge(edge)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM}
zone_neighbors = entity_graph.neighbors(zone_vertex.vertex_id,
vertex_attr_filter=query)
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices, entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges,
entity_graph.num_edges())
self.assertThat(zone_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
zone_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
zone_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('complex_zone_deduced_alarm',
zone_neighbors[0][VProps.NAME])
# ################### STEP 2 ###################
# Add NETWORK_PROBLEM alarm
test_vals = {'status': NagiosTestStatus.WARNING,
'service': 'NETWORK_PROBLEM',
'name': 'NETWORK_PROBLEM',
DSProps.DATASOURCE_ACTION: DatasourceAction.SNAPSHOT,
VProps.RESOURCE_ID: network_vertex[VProps.ID],
NagiosProperties.RESOURCE_NAME: network_vertex[VProps.ID],
NagiosProperties.RESOURCE_TYPE:
NEUTRON_NETWORK_DATASOURCE}
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
nagios_event = mock_driver.generate_random_events_list(generator)[0]
processor.process_event(nagios_event)
while not event_queue.empty():
processor.process_event(event_queue.get())
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices + num_network_alarm_vertices,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges +
num_network_alarm_edges, entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM}
network_neighbors = entity_graph.neighbors(network_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(network_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
network_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(NAGIOS_DATASOURCE,
network_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('NETWORK_PROBLEM', network_neighbors[0][VProps.NAME])
self.assertFalse(network_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(network_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
zone_neighbors = entity_graph.neighbors(zone_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(zone_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
zone_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
zone_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('complex_zone_deduced_alarm',
zone_neighbors[0][VProps.NAME])
self.assertTrue(zone_neighbors[0][VProps.VITRAGE_IS_DELETED])
# ################### STEP 3 ###################
# delete NETWORK_PROBLEM alarm
nagios_event[NagiosProperties.STATUS] = NagiosTestStatus.OK
processor.process_event(nagios_event)
while not event_queue.empty():
processor.process_event(event_queue.get())
self.assertEqual(num_orig_vertices + num_added_vertices +
num_deduced_vertices + num_network_alarm_vertices +
# a new uuid is created for every new vertex,
# even if it existed before with another uuid.
# new alarm doesn't override old one
1,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_added_edges + num_deduced_edges +
num_network_alarm_edges + 1, entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM}
network_neighbors = entity_graph.neighbors(network_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(network_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
network_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(NAGIOS_DATASOURCE,
network_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('NETWORK_PROBLEM', network_neighbors[0][VProps.NAME])
self.assertTrue(network_neighbors[0][VProps.VITRAGE_IS_DELETED])
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_IS_DELETED: True}
vitrage_is_deleted = True
# Alarm History is saved. We are testing the deleted alarm and
# then we are testing the live alarm
for counter in range(0, 1):
zone_neighbors = entity_graph.neighbors(zone_vertex.vertex_id,
vertex_attr_filter=query)
self.assertThat(zone_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
zone_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
zone_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('complex_zone_deduced_alarm',
zone_neighbors[0][VProps.NAME])
self.assertEqual(vitrage_is_deleted,
zone_neighbors[0][VProps.VITRAGE_IS_DELETED])
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_IS_DELETED: False}
vitrage_is_deleted = False
def test_ha(self):
event_queue, processor, evaluator = self._init_system()
entity_graph = processor.entity_graph
# find host
query = {
VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: NOVA_HOST_DATASOURCE
}
hosts = entity_graph.get_vertices(vertex_attr_filter=query)
# find instances on host
query = {
VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: NOVA_INSTANCE_DATASOURCE
}
instances = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
entity_graph.remove_vertex(instances[2])
entity_graph.remove_vertex(instances[3])
# constants
num_orig_vertices = entity_graph.num_vertices()
num_orig_edges = entity_graph.num_edges()
# ################### STEP 1 ###################
# Add cinder volume 1
generator = mock_driver.simple_volume_generators(volume_num=1,
instance_num=1,
snapshot_events=1)
volume_event1 = mock_driver.generate_random_events_list(generator)[0]
volume_event1['display_name'] = 'volume-1'
volume_event1[VProps.ID] = 'volume-1'
volume_event1['attachments'][0]['server_id'] = instances[0][VProps.ID]
processor.process_event(volume_event1)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
num_volumes = 1
num_deduced_alarms = 1
self.assertEqual(num_orig_vertices + num_volumes + num_deduced_alarms,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_volumes + num_deduced_alarms,
entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: CINDER_VOLUME_DATASOURCE}
instance_neighbors = entity_graph.neighbors(instances[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(instance_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.RESOURCE,
instance_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(CINDER_VOLUME_DATASOURCE,
instance_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('volume-1', instance_neighbors[0][VProps.NAME])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_warning_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# ################### STEP 2 ###################
# Add cinder volume 2
generator = mock_driver.simple_volume_generators(volume_num=1,
instance_num=1,
snapshot_events=1)
volume_event2 = mock_driver.generate_random_events_list(generator)[0]
volume_event2['display_name'] = 'volume-2'
volume_event2[VProps.ID] = 'volume-2'
volume_event2['attachments'][0]['server_id'] = instances[1][VProps.ID]
processor.process_event(volume_event2)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
num_volumes = 2
num_deduced_alarms = 2
self.assertEqual(num_orig_vertices + num_volumes + num_deduced_alarms,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_volumes + num_deduced_alarms,
entity_graph.num_edges())
# check instance neighbors
query = {VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: CINDER_VOLUME_DATASOURCE}
instance_neighbors = entity_graph.neighbors(instances[1].vertex_id,
vertex_attr_filter=query)
self.assertThat(instance_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.RESOURCE,
instance_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(CINDER_VOLUME_DATASOURCE,
instance_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('volume-2', instance_neighbors[0][VProps.NAME])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check ha_error_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_error_deduced_alarm'}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_error_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check ha_warning_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_warning_deduced_alarm'}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_warning_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertTrue(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# ################### STEP 3 ###################
# Remove Cinder Volume 2
volume_event2[DSProps.DATASOURCE_ACTION] = DatasourceAction.UPDATE
volume_event2[DSProps.EVENT_TYPE] = 'volume.detach.start'
volume_event2['volume_id'] = volume_event2['id']
volume_event2['volume_attachment'] = volume_event2['attachments']
volume_event2['volume_attachment'][0]['instance_uuid'] = \
volume_event2['attachments'][0]['server_id']
processor.process_event(volume_event2)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
self.assertEqual(num_orig_vertices + num_volumes + num_deduced_alarms +
# a new uuid is created for every new vertex,
# even if it existed before with another uuid.
# new alarm doesn't override old one
1,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_volumes + num_deduced_alarms + 1,
entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: CINDER_VOLUME_DATASOURCE}
instance_neighbors = entity_graph.neighbors(instances[1].vertex_id,
vertex_attr_filter=query)
self.assertThat(instance_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.RESOURCE,
instance_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(CINDER_VOLUME_DATASOURCE,
instance_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('volume-2', instance_neighbors[0][VProps.NAME])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check ha_error_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_error_deduced_alarm'}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_error_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertTrue(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check new ha_warning_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_warning_deduced_alarm',
VProps.VITRAGE_IS_DELETED: False}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_warning_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check old deleted ha_warning_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_warning_deduced_alarm',
VProps.VITRAGE_IS_DELETED: True}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_warning_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertTrue(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# ################### STEP 4 ###################
# Remove Cinder Volume 1
volume_event1[DSProps.DATASOURCE_ACTION] = DatasourceAction.UPDATE
volume_event1[DSProps.EVENT_TYPE] = 'volume.detach.start'
volume_event1['volume_id'] = volume_event1['id']
volume_event1['volume_attachment'] = volume_event1['attachments']
volume_event1['volume_attachment'][0]['instance_uuid'] = \
volume_event1['attachments'][0]['server_id']
processor.process_event(volume_event1)
while not event_queue.empty():
processor.process_event(event_queue.get())
# test asserts
self.assertEqual(num_orig_vertices + num_volumes + num_deduced_alarms +
# a new uuid is created for every new vertex,
# even if it existed before with another uuid.
# new alarm doesn't override old one
1,
entity_graph.num_vertices())
self.assertEqual(num_orig_edges + num_volumes + num_deduced_alarms + 1,
entity_graph.num_edges())
query = {VProps.VITRAGE_CATEGORY: EntityCategory.RESOURCE,
VProps.VITRAGE_TYPE: CINDER_VOLUME_DATASOURCE}
instance_neighbors = entity_graph.neighbors(instances[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(instance_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.RESOURCE,
instance_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(CINDER_VOLUME_DATASOURCE,
instance_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('volume-1', instance_neighbors[0][VProps.NAME])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(instance_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check ha_error_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_error_deduced_alarm'}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(1))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_error_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertTrue(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
# check old ha_warning_deduced_alarm
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.NAME: 'ha_warning_deduced_alarm'}
host_neighbors = entity_graph.neighbors(hosts[0].vertex_id,
vertex_attr_filter=query)
self.assertThat(host_neighbors, matchers.HasLength(2))
self.assertEqual(EntityCategory.ALARM,
host_neighbors[0][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[0][VProps.VITRAGE_TYPE])
self.assertEqual('ha_warning_deduced_alarm',
host_neighbors[0][VProps.NAME])
self.assertTrue(host_neighbors[0][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[0][VProps.VITRAGE_IS_PLACEHOLDER])
self.assertEqual(EntityCategory.ALARM,
host_neighbors[1][VProps.VITRAGE_CATEGORY])
self.assertEqual(VITRAGE_DATASOURCE,
host_neighbors[1][VProps.VITRAGE_TYPE])
self.assertEqual('ha_warning_deduced_alarm',
host_neighbors[1][VProps.NAME])
self.assertTrue(host_neighbors[1][VProps.VITRAGE_IS_DELETED])
self.assertFalse(host_neighbors[1][VProps.VITRAGE_IS_PLACEHOLDER])
def test_simple_or_operator_deduced_alarm(self):
"""Handles a simple not operator use case
We have created the following template:
alarm1 or alarm2 cause alarm3
"""
event_queue, processor, evaluator = self._init_system()
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
_TARGET_HOST,
_TARGET_HOST,
processor.entity_graph)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when starting')
# generate nagios alarm1 to trigger, raise alarm3
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'alarm1'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm1_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm1_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(2))
# generate nagios alarm2 to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'alarm2'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm2_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm2_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(3))
# disable alarm1, alarm3 is not deleted
alarm1_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
host_v = self.get_host_after_event(event_queue, alarm1_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, matchers.HasLength(2))
# disable alarm2, alarm3 is deleted
alarm2_test[NagiosProperties.STATUS] = NagiosTestStatus.OK
alarm2_test[DSProps.SAMPLE_DATE] = str(utcnow())
host_v = self.get_host_after_event(event_queue, alarm2_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, processor.entity_graph)
self.assertThat(alarms, IsEmpty())
def test_both_and_or_operator_for_tracker(self):
"""(alarm_a or alarm_b) and alarm_c use case
We have created the following template:
(alarm_a or alarm_b) and alarm_c cause alarm_d
1. alarm_a is reported
2. alarm_b is reported
3. alarm_c is reported --> alarm_d is raised
4. alarm_b is removed --> alarm_d should not be removed
5. alarm_a is removed --> alarm_d should be removed
"""
event_queue, processor, evaluator = self._init_system()
entity_graph = processor.entity_graph
# constants
num_orig_vertices = entity_graph.num_vertices()
num_orig_edges = entity_graph.num_edges()
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
_TARGET_HOST,
_TARGET_HOST,
entity_graph)
self.assertEqual('AVAILABLE', host_v[VProps.VITRAGE_AGGREGATED_STATE],
'host should be AVAILABLE when starting')
# generate nagios alarm_a to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'alarm_a'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm_a_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm_a_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
self.assertEqual(num_orig_vertices + 1, entity_graph.num_vertices())
self.assertEqual(num_orig_edges + 1, entity_graph.num_edges())
# generate nagios alarm_b to trigger
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'alarm_b'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm_b_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm_b_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, entity_graph)
self.assertThat(alarms, matchers.HasLength(2))
self.assertEqual(num_orig_vertices + 2, entity_graph.num_vertices())
self.assertEqual(num_orig_edges + 2, entity_graph.num_edges())
# generate nagios alarm_c to trigger, alarm_d is raised
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.WARNING,
NagiosProperties.SERVICE: 'alarm_c'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm_c_test = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm_c_test,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, entity_graph)
self.assertThat(alarms, matchers.HasLength(4))
self.assertEqual(num_orig_vertices + 4, entity_graph.num_vertices())
self.assertEqual(num_orig_edges + 4, entity_graph.num_edges())
# remove nagios alarm_b, alarm_d should not be removed
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.OK,
NagiosProperties.SERVICE: 'alarm_b'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm_b_ok = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm_b_ok,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, entity_graph)
self.assertThat(alarms, matchers.HasLength(3))
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_IS_DELETED: True}
deleted_alarms = entity_graph.neighbors(host_v.vertex_id,
vertex_attr_filter=query)
self.assertEqual(num_orig_vertices + len(deleted_alarms) + 3,
entity_graph.num_vertices())
query = {VProps.VITRAGE_IS_DELETED: True}
deleted_edges = entity_graph.neighbors(host_v.vertex_id,
edge_attr_filter=query)
self.assertEqual(num_orig_edges + len(deleted_edges) + 3,
entity_graph.num_edges())
# remove nagios alarm_a, alarm_d should be removed
test_vals = {NagiosProperties.STATUS: NagiosTestStatus.OK,
NagiosProperties.SERVICE: 'alarm_a'}
test_vals.update(_NAGIOS_TEST_INFO)
generator = mock_driver.simple_nagios_alarm_generators(1, 1, test_vals)
alarm_a_ok = mock_driver.generate_random_events_list(generator)[0]
host_v = self.get_host_after_event(event_queue, alarm_a_ok,
processor, _TARGET_HOST)
alarms = self._get_alarms_on_host(host_v, entity_graph)
self.assertThat(alarms, matchers.HasLength(1))
query = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_IS_DELETED: True}
deleted_alarms = entity_graph.neighbors(host_v.vertex_id,
vertex_attr_filter=query)
self.assertEqual(num_orig_vertices + len(deleted_alarms) + 1,
entity_graph.num_vertices())
query = {VProps.VITRAGE_IS_DELETED: True}
deleted_edges = entity_graph.neighbors(host_v.vertex_id,
edge_attr_filter=query)
self.assertEqual(num_orig_edges + len(deleted_edges) + 1,
entity_graph.num_edges())
def get_host_after_event(self, event_queue, nagios_event,
processor, target_host):
processor.process_event(nagios_event)
while not event_queue.empty():
processor.process_event(event_queue.get())
host_v = self._get_entity_from_graph(NOVA_HOST_DATASOURCE,
target_host,
target_host,
processor.entity_graph)
return host_v
def _init_system(self):
processor = self._create_processor_with_graph(self.conf)
event_queue = queue.Queue()
def actions_callback(event_type, data):
"""Mock notify method
Mocks vitrage.messaging.VitrageNotifier.notify(event_type, data)
:param event_type: is currently always the same and is ignored
:param data:
"""
event_queue.put(data)
evaluator = ScenarioEvaluator(self.conf,
processor.entity_graph,
self.scenario_repository,
actions_callback,
enabled=True)
return event_queue, processor, evaluator
@staticmethod
def _get_entity_from_graph(entity_type, entity_name,
entity_id,
entity_graph):
vertex_attrs = {VProps.VITRAGE_TYPE: entity_type,
VProps.ID: entity_id,
VProps.NAME: entity_name}
vertices = entity_graph.get_vertices(vertex_attr_filter=vertex_attrs)
return vertices[0]
@staticmethod
def _get_deduced_alarms_on_host(host_v, entity_graph):
v_id = host_v.vertex_id
vertex_attrs = {VProps.NAME: 'deduced_alarm',
VProps.VITRAGE_TYPE: VITRAGE_DATASOURCE,
VProps.VITRAGE_IS_DELETED: False, }
return entity_graph.neighbors(v_id=v_id,
vertex_attr_filter=vertex_attrs)
@staticmethod
def _get_alarms_on_host(host_v, entity_graph):
v_id = host_v.vertex_id
vertex_attrs = {VProps.VITRAGE_CATEGORY: EntityCategory.ALARM,
VProps.VITRAGE_IS_DELETED: False, }
return entity_graph.neighbors(v_id=v_id,
vertex_attr_filter=vertex_attrs)
@staticmethod
def _get_alarm_causes(alarm_v, entity_graph):
v_id = alarm_v.vertex_id
edge_attrs = {EProps.RELATIONSHIP_TYPE: EdgeLabel.CAUSES,
EProps.VITRAGE_IS_DELETED: False, }
return entity_graph.neighbors(v_id=v_id, edge_attr_filter=edge_attrs)
| 50.745942 | 79 | 0.627324 | 7,576 | 71,907 | 5.62632 | 0.046859 | 0.059472 | 0.04054 | 0.045326 | 0.876293 | 0.847296 | 0.822381 | 0.806076 | 0.789513 | 0.771918 | 0 | 0.010431 | 0.294742 | 71,907 | 1,416 | 80 | 50.78178 | 0.830083 | 0.085624 | 0 | 0.768441 | 0 | 0 | 0.039362 | 0.012009 | 0 | 0 | 0 | 0 | 0.20915 | 1 | 0.01774 | false | 0 | 0.028011 | 0 | 0.053221 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
1d04e0a25c514ff09ecaf581cd9f6526135cd6f7 | 9,026 | py | Python | test/test_environmentpreparation.py | SvenMarcus/ssh-slurm-runner | 91ea1a052a0362b5b8676b6e429aa3c890359e73 | [
"MIT"
] | 2 | 2021-04-16T15:53:38.000Z | 2021-04-16T20:36:05.000Z | test/test_environmentpreparation.py | SvenMarcus/ssh-slurm-runner | 91ea1a052a0362b5b8676b6e429aa3c890359e73 | [
"MIT"
] | 18 | 2021-04-16T15:53:55.000Z | 2021-09-13T17:38:44.000Z | test/test_environmentpreparation.py | SvenMarcus/ssh-slurm-runner | 91ea1a052a0362b5b8676b6e429aa3c890359e73 | [
"MIT"
] | null | null | null | from unittest.mock import MagicMock, call
import pytest
from hpcrocket.core.environmentpreparation import (CopyInstruction,
EnvironmentPreparation)
from hpcrocket.core.filesystem import Filesystem
def new_mock_filesystem() -> Filesystem:
return MagicMock(
spec="hpcrocket.filesystem.Filesystem").return_value
def test__given_files_to_copy__but_not_preparing__should_not_do_anything():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_copy([
CopyInstruction("file1.txt", "file2.txt")
])
source_fs_spy.copy.assert_not_called()
def test__given_files_to_copy__when_preparing__should_copy_files():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_copy([
CopyInstruction("file.txt", "filecopy.txt"),
CopyInstruction("funny.gif", "evenfunnier.gif", overwrite=True)
])
sut.prepare()
source_fs_spy.copy.assert_has_calls([
call("file.txt", "filecopy.txt", False, filesystem=target_fs),
call("funny.gif", "evenfunnier.gif", True, filesystem=target_fs)
])
def test__given_files_to_copy_with_non_existing_file__when_preparing_then_rollback__should_remove_copied_files_from_target_fs():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
source_fs_spy.copy.side_effect = raise_file_not_found_on_given_call(2)
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_copy([
CopyInstruction("file.txt", "filecopy.txt"),
CopyInstruction("funny.gif", "evenfunnier.gif")
])
with pytest.raises(FileNotFoundError):
sut.prepare()
sut.rollback()
target_fs.delete.assert_called_with("filecopy.txt")
def test__given_copied_file_not_on_target_fs__when_rolling_back__should_remove_remaining_copied_files_from_target_fs():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.delete.side_effect = raise_file_not_found_on_given_call(1)
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_copy([
CopyInstruction("file.txt", "filecopy.txt"),
CopyInstruction("funny.gif", "evenfunnier.gif")
])
sut.prepare()
sut.rollback()
target_fs.delete.assert_has_calls([
call("evenfunnier.gif")
])
def test__given_rollback_done__when_rolling_back_again__should_not_do_anything():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_copy([
CopyInstruction("file.txt", "filecopy.txt"),
CopyInstruction("funny.gif", "evenfunnier.gif")
])
sut.prepare()
sut.rollback()
target_fs.reset_mock()
sut.rollback()
target_fs.delete.assert_not_called()
def test__given_rollback_done_with_file_not_found__when_rolling_back_again__should_try_to_delete_remaining_files():
source_fs_spy = new_mock_filesystem()
target_fs_spy = new_mock_filesystem()
target_fs_spy.delete.side_effect = raise_file_not_found_on_given_call(1)
sut = EnvironmentPreparation(source_fs_spy, target_fs_spy)
sut.files_to_copy([
CopyInstruction("file.txt", "filecopy.txt"),
CopyInstruction("funny.gif", "evenfunnier.gif")
])
sut.prepare()
sut.rollback()
target_fs_spy.reset_mock()
sut.rollback()
target_fs_spy.delete.assert_has_calls([
call("filecopy.txt")
])
def test__given_files_to_clean__but_not_cleaning__should_not_do_anything():
source_fs = new_mock_filesystem()
target_fs_spy = new_mock_filesystem()
sut = EnvironmentPreparation(source_fs, target_fs_spy)
sut.files_to_clean(["file1.txt"])
target_fs_spy.delete.assert_not_called()
def test__given_files_to_clean__when_cleaning__should_delete_files():
source_fs = new_mock_filesystem()
target_fs_spy = new_mock_filesystem()
sut = EnvironmentPreparation(source_fs, target_fs_spy)
sut.files_to_clean([
"file.txt",
"funny.gif",
])
sut.clean()
target_fs_spy.delete.assert_has_calls([
call("file.txt"),
call("funny.gif")
])
def test__given_files_to_clean_with_non_existing_files__when_cleaning__should_still_clean_remaining_files():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.delete.side_effect = raise_file_not_found_on_given_call(1)
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_clean([
"file.txt",
"funny.gif",
])
sut.clean()
target_fs.delete.assert_called_with("funny.gif")
def test__given_files_to_clean_with_non_existing_files__when_cleaning__should_log_error_to_ui():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.delete.side_effect = raise_file_not_found_on_given_call(1)
ui_spy = MagicMock()
sut = EnvironmentPreparation(source_fs_spy, target_fs, ui_spy)
sut.files_to_clean([
"file.txt",
"funny.gif",
])
sut.clean()
ui_spy.error.assert_called_with(
"FileNotFoundError: Cannot delete file 'file.txt'")
def test__given_files_to_collect__when_collect__should_copy_to_source_fs():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_collect([
CopyInstruction("file.txt", "copy_file.txt", True),
CopyInstruction("funny.gif", "copy_funny.gif", False),
])
sut.collect()
target_fs.copy.assert_has_calls([
call("file.txt", "copy_file.txt", True, filesystem=source_fs_spy),
call("funny.gif", "copy_funny.gif", False, filesystem=source_fs_spy)
])
def test__given_files_to_collect_with_non_existing_file__when_collecting__should_collect_remaining_files():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.copy.side_effect = raise_file_not_found_on_given_call(1)
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_collect([
CopyInstruction("file.txt", "copy_file.txt"),
CopyInstruction("funny.gif", "copy_funny.gif"),
])
sut.collect()
target_fs.copy.assert_has_calls([
call("funny.gif", "copy_funny.gif", False, filesystem=source_fs_spy),
])
def test__given_files_to_collect_with_non_existing_file__when_collecting__should_log_error_to_ui():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.copy.side_effect = raise_file_not_found_on_given_call(1)
ui_spy = MagicMock()
sut = EnvironmentPreparation(source_fs_spy, target_fs, ui_spy)
sut.files_to_collect([
CopyInstruction("file.txt", "copy_file.txt", True),
CopyInstruction("funny.gif", "copy_funny.gif", False),
])
sut.collect()
ui_spy.error.assert_called_with(
"FileNotFoundError: Cannot copy file 'file.txt'")
def test__given_files_to_collect_with_file_already_existing_on_source_fs__when_collecting__should_still_collect_remaining_files():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.copy.side_effect = raise_file_exists_on_given_call(1)
sut = EnvironmentPreparation(source_fs_spy, target_fs)
sut.files_to_collect([
CopyInstruction("file.txt", "copy_file.txt", False),
CopyInstruction("funny.gif", "copy_funny.gif", False),
])
sut.collect()
target_fs.copy.assert_has_calls([
call("funny.gif", "copy_funny.gif", False, filesystem=source_fs_spy),
])
def test__given_files_to_collect_with_file_already_existing_on_source_fs__when_collecting__should_log_error_to_ui():
source_fs_spy = new_mock_filesystem()
target_fs = new_mock_filesystem()
target_fs.copy.side_effect = raise_file_exists_on_given_call(1)
ui_spy = MagicMock()
sut = EnvironmentPreparation(source_fs_spy, target_fs, ui_spy)
sut.files_to_collect([
CopyInstruction("file.txt", "copy_file.txt", False),
CopyInstruction("funny.gif", "copy_funny.gif", False),
])
sut.collect()
ui_spy.error.assert_called_with(
"FileExistsError: Cannot copy file 'file.txt'")
def raise_file_not_found_on_given_call(call: int = 1):
call_count = 0
def raise_file_not_found(*args, **kwargs):
nonlocal call_count
call_count += 1
if call_count == call:
raise FileNotFoundError(*args)
return raise_file_not_found
def raise_file_exists_on_given_call(call: int = 1):
call_count = 0
def raise_file_exists(*args, **kwargs):
nonlocal call_count
call_count += 1
if call_count == call:
raise FileExistsError(*args)
return raise_file_exists
| 29.593443 | 130 | 0.727897 | 1,195 | 9,026 | 4.973222 | 0.077824 | 0.074037 | 0.06108 | 0.089012 | 0.860003 | 0.827023 | 0.779236 | 0.763756 | 0.718997 | 0.707555 | 0 | 0.002412 | 0.173056 | 9,026 | 304 | 131 | 29.690789 | 0.79381 | 0 | 0 | 0.712919 | 0 | 0 | 0.098161 | 0.003435 | 0 | 0 | 0 | 0 | 0.07177 | 1 | 0.095694 | false | 0 | 0.019139 | 0.004785 | 0.129187 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
df0fc1ece8ee4d1914232084127100b4895fe32d | 65,117 | py | Python | cnn_lstm/src/graphs_draw.py | lancopku/LexicalAT | cafd53224834f844833f8b92be1fc727e7b3412d | [
"Apache-2.0"
] | 15 | 2019-08-28T17:40:58.000Z | 2021-09-10T08:15:09.000Z | cnn_lstm/src/graphs_draw.py | lancopku/LexicalAT | cafd53224834f844833f8b92be1fc727e7b3412d | [
"Apache-2.0"
] | null | null | null | cnn_lstm/src/graphs_draw.py | lancopku/LexicalAT | cafd53224834f844833f8b92be1fc727e7b3412d | [
"Apache-2.0"
] | 3 | 2019-12-05T07:26:41.000Z | 2020-12-12T07:33:16.000Z |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import os
# Dependency imports
import tensorflow as tf
import layers as layers_lib
import adversarial_losses as adv_lib
from get_data import get_msr_dataset,get_rt_dataset,get_sst_dataset
flags = tf.app.flags
FLAGS = flags.FLAGS
# Flags governing adversarial training are defined in adversarial_losses.py.
# Classifier
flags.DEFINE_integer('num_classes', 2, 'Number of classes for classification')
# Data path
flags.DEFINE_string('data_dir','','Directory path to preprocessed text dataset.')
flags.DEFINE_string('vocab_freq_path', '',
'Path to pre-calculated vocab frequency data. If '
'None, use FLAGS.data_dir/vocab_freq.txt.')
flags.DEFINE_integer('batch_size', 64, 'Size of the batch.')
flags.DEFINE_integer('num_timesteps', 120, 'Number of timesteps for BPTT')
# Model architechture
flags.DEFINE_bool('bidir_lstm', False, 'Whether to build a bidirectional LSTM.')
flags.DEFINE_bool('single_label', True, 'Whether the sequence has a single '
'label, for optimization.')
flags.DEFINE_integer('rnn_num_layers', 1, 'Number of LSTM layers.')
flags.DEFINE_integer('rnn_cell_size', 2,
'Number of hidden units in the LSTM.')
# flags.DEFINE_integer('cl_num_layers', 1,
# 'Number of hidden layers of classification model.')
# flags.DEFINE_integer('cl_hidden_size', 30,
# 'Number of hidden units in classification layer.')
# flags.DEFINE_integer('num_candidate_samples', -1,
# 'Num samples used in the sampled output layer.')
# Vocabulary and embeddings
flags.DEFINE_integer('embedding_dims', 256, 'Dimensions of embedded vector.')
flags.DEFINE_bool('normalize_embeddings', False,
'Normalize word embeddings by vocab frequency')
flags.DEFINE_integer('action_type', 4, """ zero denotes not change , one denotes change""" # ANCHOR before is five we test when use four action what will change
'action type 0/no action 1/synets 2/upper 3/blew 4/upperdown')
# Optimization
# flags.DEFINE_float('learning_rate_generator', 0, 'lr for generator')
flags.DEFINE_float('learning_rate', 0.001, 'Learning rate while fine-tuning.')
flags.DEFINE_float('learning_rate_decay_factor', 1.0,
'Learning rate decay factor')
flags.DEFINE_boolean('sync_replicas', False, 'sync_replica or not')
flags.DEFINE_integer('replicas_to_aggregate', 1,
'The number of replicas to aggregate')
# Regularization
flags.DEFINE_float('max_grad_norm', 1.0,
'Clip the global gradient norm to this value.')
flags.DEFINE_float('keep_prob_emb', 0.6, 'keep probability on embedding layer. '
'0.5 is optimal on IMDB with virtual adversarial training.')
flags.DEFINE_float('keep_prob_lstm_out', 0.9,
'keep probability on lstm output.')
flags.DEFINE_float('keep_prob_cl_hidden', 0.9,
'keep probability on classification hidden layer')
flags.DEFINE_float('keep_prob_dense',0.9,'keep probability on dense layers')
flags.DEFINE_float('generator_learning_rate',0.001,'the learning rate of generator')
class vatRnnModel(object):
def __init__(self,cl_logits_input_dim=None):
self.layers = {}
self.initialize_vocab()
self.layers['embedding'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb)
self.layers['embedding_1'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb,name='embedding_1')
self.layers['lstm'] = layers_lib.LSTM(
FLAGS.rnn_cell_size, FLAGS.rnn_num_layers)
# self.layers['lstm_1'] = layers_lib.BiLSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers,name="Bilstm")
# self.layers['action_select'] = layers_lib.Actionselect(FLAGS.action_type,FLAGS.keep_prob_dense,name='action_output')
self.layers['cl_logits'] = layers_lib.Project_layer(FLAGS.num_classes,FLAGS.keep_prob_dense,name='project_layer')
def build_train_graph(self,global_step):
self.initialize_train_dataset()
self.global_step = global_step
embedded_one = self.layers['embedding'](self.train_sentence)
_, one_next_state = self.layers['lstm'](embedded_one, None,self.train_sentence_len)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.train_label,logits=logits)
loss = tf.reduce_mean(loss)
embedding_adv = self.adversarial_embedding(embedded_one,loss)
_, one_next_state = self.layers['lstm'](embedding_adv, None,self.train_sentence_len)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
adv_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.train_label,logits=logits)
adv_loss = tf.reduce_mean(adv_loss)
adv_loss = (adv_loss * tf.constant(FLAGS.adv_reg_coeff, name='adv_reg_coeff'))
loss += adv_loss
tf.summary.scalar('loss',loss)
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.train_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
train_op = adam_optimize(loss, self.global_step)
tf.summary.scalar('train_accuracy', accuracy)
return loss, train_op, accuracy
def initialize_vocab(self):
_,self.vocab = get_sst_dataset('train')
self.vocab_freqs = self.vocab.get_freq()
self.vocab_size = self.vocab.size
def from_embedding_get_logit(self,embedding):
_, one_next_state = self.layers['lstm'](embedding, None,self.train_sentence_len)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
return logits
def initialize_train_dataset(self):
train_dataset,_ = get_sst_dataset('train',self.vocab)
train_dataset = train_dataset.shuffle(buffer_size = 1000 , seed=321)
train_dataset = train_dataset.padded_batch(FLAGS.batch_size,
padded_shapes=([FLAGS.num_timesteps],(),()),drop_remainder=True).repeat().prefetch(15*FLAGS.batch_size)
train_dataset = train_dataset.make_one_shot_iterator()
self.train_sentence,self.train_sentence_len,self.train_label = train_dataset.get_next()
def initialize_test_dataset(self):
test_dataset,_ = get_sst_dataset('test',self.vocab)
test_dataset = test_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size)
test_iterator = test_dataset.make_one_shot_iterator()
self.test_init_op = test_iterator.make_initializer(test_dataset,name='test_init')
self.test_sentence,self.test_sentence_len,self.test_label = test_iterator.get_next()
def initialize_dev_dataset(self):
dev_dataset,_ = get_sst_dataset('dev',self.vocab)
dev_dataset = dev_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size*3)
dev_iterator = dev_dataset.make_one_shot_iterator()
self.dev_init_op = dev_iterator.make_initializer(dev_dataset,name='dev_init')
self.dev_sentence,self.dev_sentence_len,self.dev_label = dev_iterator.get_next()
def build_dev_graph(self):
self.initialize_dev_dataset()
embedded_one = self.layers['embedding'](self.dev_sentence,False)
batch_number = tf.shape(embedded_one)[0]
_, one_next_state = self.layers['lstm'](embedded_one, None,self.dev_sentence_len,False)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h,False))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.dev_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
tf.summary.scalar('dev_accuracy', accuracy)
return accuracy,batch_number,self.dev_init_op
def build_test_graph(self):
self.initialize_test_dataset()
embedded_one = self.layers['embedding'](self.test_sentence,False)
batch_number = tf.shape(embedded_one)[0]
_, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h,False))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.test_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
tf.summary.scalar('test_accuracy', accuracy)
return accuracy,batch_number,self.test_init_op
def adversarial_embedding(self,embedding_one,loss_one):
embedding_adv = adv_lib.adversarial_loss(embedding_one,loss_one) # get embedding need to calculate loss
return embedding_adv
@property
def pretrained_variables(self):
# return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights + self.layers['action_select'].trainable_weights
return self.layers['embedding'].trainable_weights
class vatCnnModel(object):
def __init__(self,cl_logits_input_dim=None):
self.layers = {}
self.initialize_vocab()
self.layers['embedding'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb)
self.layers['embedding_1'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb,name='embedding_1')
# self.layers['lstm'] = layers_lib.LSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers)
self.layers['cnn'] = layers_lib.CNN( # in https://github.com/pfnet-research/contextual_augmentation the cnn ouput keep prob uses the same value as embedding keep prob
FLAGS.embedding_dims, FLAGS.keep_prob_emb)
self.layers['lstm_1'] = layers_lib.BiLSTM(
FLAGS.rnn_cell_size, FLAGS.rnn_num_layers,name="Bilstm")
self.layers['action_select'] = layers_lib.Actionselect(FLAGS.action_type,FLAGS.keep_prob_dense,name='action_output')
self.layers['cl_logits'] = layers_lib.Project_layer(FLAGS.num_classes,FLAGS.keep_prob_dense,name='project_layer')
# cl_logits_input_dim = cl_logits_input_dim or FLAGS.rnn_cell_size
# self.layers['cl_logits'] = layers_lib.cl_logits_subgraph( # get the last state for classification
# [FLAGS.cl_hidden_size] * FLAGS.cl_num_layers, cl_logits_input_dim,
# FLAGS.num_classes, FLAGS.keep_prob_cl_hidden, name='cl_logits')
def build_train_graph(self,global_step):
self.initialize_train_dataset()
self.global_step = global_step
embedded_one = self.layers['embedding'](self.train_sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.train_sentence_len)
one_next_state = self.layers['cnn'](embedded_one)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# print(one_next_state)
# raise ValueError('ddd')
logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.train_label,logits=logits)
loss = tf.reduce_mean(loss)
embedding_adv = self.adversarial_embedding(embedded_one,loss)
one_next_state = self.layers['cnn'](embedding_adv)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
adv_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.train_label,logits=logits)
adv_loss = tf.reduce_mean(adv_loss)
adv_loss = (adv_loss * tf.constant(FLAGS.adv_reg_coeff, name='adv_reg_coeff'))
loss += adv_loss
tf.summary.scalar('loss',loss)
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.train_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
train_op = adam_optimize(loss, self.global_step)
tf.summary.scalar('train_accuracy', accuracy)
return loss, train_op, accuracy
def initialize_vocab(self):
_,self.vocab = get_sst_dataset('train')
self.vocab_freqs = self.vocab.get_freq()
self.vocab_size = self.vocab.size
def initialize_train_dataset(self):
train_dataset,_ = get_sst_dataset('train',self.vocab)
train_dataset = train_dataset.shuffle(buffer_size = 1000 , seed=321)
train_dataset = train_dataset.padded_batch(FLAGS.batch_size,
padded_shapes=([FLAGS.num_timesteps],(),()),drop_remainder=True).repeat().prefetch(15*FLAGS.batch_size)
train_dataset = train_dataset.make_one_shot_iterator()
self.train_sentence,self.train_sentence_len,self.train_label = train_dataset.get_next()
def initialize_test_dataset(self):
test_dataset,_ = get_sst_dataset('test',self.vocab)
test_dataset = test_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size)
test_iterator = test_dataset.make_one_shot_iterator()
self.test_init_op = test_iterator.make_initializer(test_dataset,name='test_init')
self.test_sentence,self.test_sentence_len,self.test_label = test_iterator.get_next()
def initialize_dev_dataset(self):
dev_dataset,_ = get_sst_dataset('dev',self.vocab)
dev_dataset = dev_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size*3)
dev_iterator = dev_dataset.make_one_shot_iterator()
self.dev_init_op = dev_iterator.make_initializer(dev_dataset,name='dev_init')
self.dev_sentence,self.dev_sentence_len,self.dev_label = dev_iterator.get_next()
def build_dev_graph(self):
self.initialize_dev_dataset()
embedded_one = self.layers['embedding'](self.dev_sentence,False)
batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.dev_sentence_len,False)
one_next_state = self.layers['cnn'](embedded_one,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
logits = tf.squeeze(self.layers['cl_logits'](one_next_state,False))
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.dev_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
tf.summary.scalar('dev_accuracy', accuracy)
return accuracy,batch_number,self.dev_init_op
def build_test_graph(self):
self.initialize_test_dataset()
embedded_one = self.layers['embedding'](self.test_sentence,False)
batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
one_next_state = self.layers['cnn'](embedded_one,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
logits = tf.squeeze(self.layers['cl_logits'](one_next_state,False))
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.test_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
tf.summary.scalar('test_accuracy', accuracy)
return accuracy,batch_number,self.test_init_op
def adversarial_embedding(self,embedding_one,loss_one):
embedding_adv = adv_lib.adversarial_loss(embedding_one,loss_one) # get embedding need to calculate loss
return embedding_adv
@property
def pretrained_variables(self):
# return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights + self.layers['action_select'].trainable_weights
return self.layers['embedding'].trainable_weights
# def adversarial_loss(self,embedding_one,loss_one):
# """Compute adversarial loss based on FLAGS.adv_training_method."""
# def virtual_adversarial_loss():
# def logits_from_embedding(embedded, return_next_state=False):
# _, next_state, logits, _ = self.cl_loss_from_embedding(
# embedded, inputs=self.lm_inputs, return_intermediates=True)
# if return_next_state:
# return next_state, logits
# else:
# return logits
# next_state, lm_cl_logits = logits_from_embedding(
# self.tensors['lm_embedded'], return_next_state=True)
# va_loss = adv_lib.virtual_adversarial_loss(
# lm_cl_logits, self.tensors['lm_embedded'], self.lm_inputs,
# logits_from_embedding)
# with tf.control_dependencies([self.lm_inputs.save_state(next_state)]):
# va_loss = tf.identity(va_loss)
# return va_loss
# def combo_loss():
# return adversarial_loss() + virtual_adversarial_loss()
# adv_training_methods = {
# # Random perturbation
# 'rp': random_perturbation_loss,
# # Adversarial training
# 'at': adversarial_loss,
# # Virtual adversarial training
# 'vat': virtual_adversarial_loss,
# # Both at and vat
# 'atvat': combo_loss,
# '': lambda: tf.constant(0.),
# None: lambda: tf.constant(0.),
# }
# with tf.name_scope('adversarial_loss'):
# return adv_training_methods[FLAGS.adv_training_method]()
class cnnModel(object):
def __init__(self,cl_logits_input_dim=None):
self.layers = {}
self.initialize_vocab()
self.layers['embedding'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb)
self.layers['embedding_1'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb,name='embedding_1')
# self.layers['lstm'] = layers_lib.LSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers)
self.layers['cnn'] = layers_lib.CNN( # in https://github.com/pfnet-research/contextual_augmentation the cnn ouput keep prob uses the same value as embedding keep prob
FLAGS.embedding_dims, FLAGS.keep_prob_emb)
self.layers['lstm_1'] = layers_lib.BiLSTM(
FLAGS.rnn_cell_size, FLAGS.rnn_num_layers,name="Bilstm")
self.layers['action_select'] = layers_lib.Actionselect(FLAGS.action_type,FLAGS.keep_prob_dense,name='action_output')
self.layers['cl_logits'] = layers_lib.Project_layer(FLAGS.num_classes,FLAGS.keep_prob_dense,name='project_layer')
# cl_logits_input_dim = cl_logits_input_dim or FLAGS.rnn_cell_size
# self.layers['cl_logits'] = layers_lib.cl_logits_subgraph( # get the last state for classification
# [FLAGS.cl_hidden_size] * FLAGS.cl_num_layers, cl_logits_input_dim,
# FLAGS.num_classes, FLAGS.keep_prob_cl_hidden, name='cl_logits')
def build_train_graph(self,global_step):
self.initialize_train_dataset()
self.global_step = global_step
embedded_one = self.layers['embedding'](self.train_sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.train_sentence_len)
one_next_state = self.layers['cnn'](embedded_one)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# print(one_next_state)
# raise ValueError('ddd')
logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.train_label,logits=logits)
loss = tf.reduce_mean(loss)
tf.summary.scalar('loss',loss)
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.train_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
train_op = adam_optimize(loss, self.global_step)
tf.summary.scalar('train_accuracy', accuracy)
return loss, train_op, accuracy
def initialize_vocab(self):
_,self.vocab = get_sst_dataset('train')
self.vocab_freqs = self.vocab.get_freq()
self.vocab_size = self.vocab.size
def initialize_train_dataset(self):
train_dataset,_ = get_sst_dataset('train',self.vocab)
train_dataset = train_dataset.shuffle(buffer_size = 1000 , seed=321)
train_dataset = train_dataset.padded_batch(FLAGS.batch_size,
padded_shapes=([FLAGS.num_timesteps],(),()),drop_remainder=True).repeat().prefetch(15*FLAGS.batch_size)
train_dataset = train_dataset.make_one_shot_iterator()
self.train_sentence,self.train_sentence_len,self.train_label = train_dataset.get_next()
def initialize_test_dataset(self):
test_dataset,_ = get_sst_dataset('test',self.vocab)
test_dataset = test_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size)
test_iterator = test_dataset.make_one_shot_iterator()
self.test_init_op = test_iterator.make_initializer(test_dataset,name='test_init')
self.test_sentence,self.test_sentence_len,self.test_label = test_iterator.get_next()
def initialize_dev_dataset(self):
dev_dataset,_ = get_sst_dataset('dev',self.vocab)
dev_dataset = dev_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size*3)
dev_iterator = dev_dataset.make_one_shot_iterator()
self.dev_init_op = dev_iterator.make_initializer(dev_dataset,name='dev_init')
self.dev_sentence,self.dev_sentence_len,self.dev_label = dev_iterator.get_next()
def build_dev_graph(self):
self.initialize_dev_dataset()
embedded_one = self.layers['embedding'](self.dev_sentence,False)
batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.dev_sentence_len,False)
one_next_state = self.layers['cnn'](embedded_one,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
logits = tf.squeeze(self.layers['cl_logits'](one_next_state,False))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.dev_label,logits=logits)
loss = tf.reduce_mean(loss)
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.dev_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
return loss,accuracy,batch_number,self.dev_init_op
def build_test_graph(self):
self.initialize_test_dataset()
embedded_one = self.layers['embedding'](self.test_sentence,False)
batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
one_next_state = self.layers['cnn'](embedded_one,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
logits = tf.squeeze(self.layers['cl_logits'](one_next_state,False))
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.test_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
tf.summary.scalar('test_accuracy', accuracy)
return accuracy,batch_number,self.test_init_op
# def build_adv_test_graph(self): # done
# self.initialize_test_dataset()
# embedded_one = self.layers['embedding'](self.test_sentence,False)
# batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h)) # four real_0 real_1 fake_0 fake_1
# this_logits = tf.concat([tf.expand_dims(logits[:,0],-1)+tf.expand_dims(logits[:,2],-1),tf.expand_dims(logits[:,1],-1)+tf.expand_dims(logits[:,3],-1)],-1)
# prediction = tf.equal(tf.cast(tf.argmax(this_logits,-1), tf.int32),self.test_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# tf.summary.scalar('test_accuracy', accuracy)
# return accuracy,batch_number,self.test_init_op
@property
def pretrained_variables(self):
# return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights + self.layers['action_select'].trainable_weights
return self.layers['embedding'].trainable_weights
# return self.layers['lstm'].trainable_weights
@property
def dis_pretrained_variables(self):
return self.layers['embedding'].trainable_weights + self.layers['cnn'].trainable_weights + self.layers['cl_logits'].trainable_weights
# @property
# def my_pretrained_variables(self):
# return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights
def train_generator(self,global_step):
with tf.name_scope(name='generator'):
self.initialize_train_dataset()
self.global_step = global_step
train_sentence = tf.placeholder(dtype=tf.int32,shape=[FLAGS.batch_size,FLAGS.num_timesteps],name='train_sentence')
train_sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='train_sentence_len')
reward_score = tf.placeholder(dtype=tf.float32, shape=[None],name="reward_score")
# action_idx = tf.placeholder(dtype=tf.int32,shape=[None,FLAGS.num_timesteps,3],name='action_idx') # if the choiced action is [[1,2,4,1],[2,4,3,1]] then action idx is [[[0,0,1][0,1,2],[0,2,4][0,3,1]],[[1,0,2],[1,1,4],[1,2,3],[1,3,1]]]
action_idx = tf.placeholder(dtype=tf.int32,shape=[None,FLAGS.num_timesteps],name='action_idx') #the action of each position in sentence
embedded = self.layers['embedding_1'](train_sentence)
lstm_out_all, _, = self.layers['lstm_1'](embedded,None,train_sentence_len)
lstm_out = tf.concat([lstm_out_all[0],lstm_out_all[1]],-1) # concat forward and backward lstm_out doing predict
action_logits = self.layers['action_select'](lstm_out)
prob = tf.nn.softmax(action_logits,axis=-1)
# ori_loss = tf.gather_nd(tf.log(prob),action_idx)
# ori_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=tf.argmax(self.action_logits,2),logits=self.action_logits)
ori_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels= action_idx,logits=action_logits)
reward_score = tf.nn.relu(reward_score) # we don't use negative reward for training
gene_loss = tf.reduce_mean(reward_score * tf.reduce_sum(ori_loss,-1))
# train_gene_op = adam_optimize(gene_loss,self.global_step)
train_gene_op = gene_adam_optimize(gene_loss,self.global_step)
return prob,gene_loss,train_gene_op
def get_generator_data(self):
return self.train_sentence,self.train_sentence_len,self.train_label
def get_original_prob(self):
sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence_original")
sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len_original')
sentence_label = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_label_original')
embedded_one = self.layers['embedding'](sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
one_next_state = self.layers['cnn'](embedded_one)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
prob = tf.nn.softmax(logits)
return tf.gather_nd(prob, tf.stack((tf.range(tf.shape(prob)[0],dtype=tf.int32),sentence_label),axis=1))
def train_discriminator(self):
with tf.name_scope(name='discriminator') as scope:
sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence")
sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len')
train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
original_prob = tf.placeholder(dtype=tf.float32,shape=[None],name='original_prob')
embedded_one = self.layers['embedding'](sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
one_next_state = self.layers['cnn'](embedded_one)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=train_label,logits=logits)
dis_loss = tf.reduce_mean(loss)
train_dis_op = adam_optimize(dis_loss, self.global_step)
tf.summary.scalar('dis_loss', dis_loss)
softmax_prob = tf.nn.softmax(logits)
prob = tf.gather_nd(softmax_prob, tf.stack((tf.range(tf.shape(softmax_prob)[0],dtype=tf.int32),train_label),axis=1))
# train_label=tf.cast(train_label,tf.float32)
# reward = prob*train_label+(1-prob)*(1-train_label)
# reward = tf.abs(original_prob-prob)
reward = original_prob - prob
return dis_loss,train_dis_op,reward
# def train_discriminator(self):
# with tf.name_scope(name='discriminator') as scope:
# sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence")
# sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len')
# train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
# embedded_one = self.layers['embedding'](sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
# logits = tf.squeeze(self.layers['cl_logits_1'](one_next_state[0].h))
# loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=train_label,logits=logits)
# dis_loss = tf.reduce_mean(loss)
# train_dis_op = adam_optimize(dis_loss, self.global_step)
# tf.summary.scalar('dis_loss', dis_loss)
# this_logits = tf.nn.softmax(logits)
# prob = this_logits[:,1]+this_logits[:,3] # the probability of 1 label
# train_label=tf.cast(train_label,tf.float32)
# reward = prob*train_label+(1-prob)*(1-train_label)
# return dis_loss,train_dis_op,reward
class rnnModel(object):
def __init__(self,cl_logits_input_dim=None):
self.layers = {}
self.initialize_vocab()
self.layers['embedding'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb)
self.layers['embedding_1'] = layers_lib.Embedding(
self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
self.vocab_freqs, FLAGS.keep_prob_emb,name='embedding_1')
self.layers['lstm'] = layers_lib.LSTM(
FLAGS.rnn_cell_size, FLAGS.rnn_num_layers)
self.layers['lstm_1'] = layers_lib.BiLSTM(
FLAGS.rnn_cell_size, FLAGS.rnn_num_layers,name="Bilstm")
self.layers['action_select'] = layers_lib.Actionselect(FLAGS.action_type,FLAGS.keep_prob_dense,name='action_output')
self.layers['cl_logits'] = layers_lib.Project_layer(FLAGS.num_classes,FLAGS.keep_prob_dense,name='project_layer')
# cl_logits_input_dim = cl_logits_input_dim or FLAGS.rnn_cell_size
# self.layers['cl_logits'] = layers_lib.cl_logits_subgraph( # get the last state for classification
# [FLAGS.cl_hidden_size] * FLAGS.cl_num_layers, cl_logits_input_dim,
# FLAGS.num_classes, FLAGS.keep_prob_cl_hidden, name='cl_logits')
def build_train_graph(self,global_step):
self.initialize_train_dataset()
self.global_step = global_step
embedded_one = self.layers['embedding'](self.train_sentence)
_, one_next_state = self.layers['lstm'](embedded_one, None,self.train_sentence_len)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.train_label,logits=logits)
loss = tf.reduce_mean(loss)
tf.summary.scalar('loss',loss)
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.train_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
train_op = adam_optimize(loss, self.global_step)
tf.summary.scalar('train_accuracy', accuracy)
return loss, train_op, accuracy
def initialize_vocab(self):
_,self.vocab = get_sst_dataset('train')
self.vocab_freqs = self.vocab.get_freq()
self.vocab_size = self.vocab.size
def initialize_train_dataset(self):
train_dataset,_ = get_sst_dataset('train',self.vocab)
train_dataset = train_dataset.shuffle(buffer_size = 1000 , seed=321)
train_dataset = train_dataset.padded_batch(FLAGS.batch_size,
padded_shapes=([FLAGS.num_timesteps],(),()),drop_remainder=True).repeat().prefetch(15*FLAGS.batch_size)
train_dataset = train_dataset.make_one_shot_iterator()
self.train_sentence,self.train_sentence_len,self.train_label = train_dataset.get_next()
def initialize_test_dataset(self):
test_dataset,_ = get_sst_dataset('test',self.vocab)
test_dataset = test_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size)
test_iterator = test_dataset.make_one_shot_iterator()
self.test_init_op = test_iterator.make_initializer(test_dataset,name='test_init')
self.test_sentence,self.test_sentence_len,self.test_label = test_iterator.get_next()
def initialize_dev_dataset(self):
dev_dataset,_ = get_sst_dataset('dev',self.vocab)
dev_dataset = dev_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size*3)
dev_iterator = dev_dataset.make_one_shot_iterator()
self.dev_init_op = dev_iterator.make_initializer(dev_dataset,name='dev_init')
self.dev_sentence,self.dev_sentence_len,self.dev_label = dev_iterator.get_next()
def build_dev_graph(self):
self.initialize_dev_dataset()
embedded_one = self.layers['embedding'](self.dev_sentence,False)
batch_number = tf.shape(embedded_one)[0]
_, one_next_state = self.layers['lstm'](embedded_one, None,self.dev_sentence_len,False)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h,False))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.dev_label,logits=logits)
loss = tf.reduce_mean(loss)
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.dev_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
return loss,accuracy,batch_number,self.dev_init_op
def build_test_graph(self):
self.initialize_test_dataset()
embedded_one = self.layers['embedding'](self.test_sentence,False)
batch_number = tf.shape(embedded_one)[0]
_, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h,False))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
prediction = tf.equal(tf.cast(tf.argmax(logits,-1), tf.int32),self.test_label)
accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
tf.summary.scalar('test_accuracy', accuracy)
return accuracy,batch_number,self.test_init_op
# def build_adv_test_graph(self): # done
# self.initialize_test_dataset()
# embedded_one = self.layers['embedding'](self.test_sentence,False)
# batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h)) # four real_0 real_1 fake_0 fake_1
# this_logits = tf.concat([tf.expand_dims(logits[:,0],-1)+tf.expand_dims(logits[:,2],-1),tf.expand_dims(logits[:,1],-1)+tf.expand_dims(logits[:,3],-1)],-1)
# prediction = tf.equal(tf.cast(tf.argmax(this_logits,-1), tf.int32),self.test_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# tf.summary.scalar('test_accuracy', accuracy)
# return accuracy,batch_number,self.test_init_op
@property
def pretrained_variables(self):
# return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights + self.layers['action_select'].trainable_weights
return self.layers['embedding'].trainable_weights
# return self.layers['lstm'].trainable_weights
# @property
# def my_pretrained_variables(self):
# return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights
@property
def dis_pretrained_variables(self):
return self.layers['embedding'].trainable_weights + self.layers['lstm'].trainable_weights + self.layers['cl_logits'].trainable_weights
def train_generator(self,global_step):
with tf.name_scope(name='generator'):
self.initialize_train_dataset()
self.global_step = global_step
train_sentence = tf.placeholder(dtype=tf.int32,shape=[FLAGS.batch_size,FLAGS.num_timesteps],name='train_sentence')
train_sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='train_sentence_len')
reward_score = tf.placeholder(dtype=tf.float32, shape=[None],name="reward_score")
action_idx = tf.placeholder(dtype=tf.int32,shape=[None,FLAGS.num_timesteps],name='action_idx') #the action of each position in sentence
embedded = self.layers['embedding_1'](train_sentence)
lstm_out_all, _, = self.layers['lstm_1'](embedded,None,train_sentence_len)
lstm_out = tf.concat([lstm_out_all[0],lstm_out_all[1]],-1)
action_logits= self.layers['action_select'](lstm_out)
# ori_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=tf.argmax(self.action_logits,2),logits=self.action_logits)
# gene_loss = tf.reduce_mean(reward_score * tf.reduce_mean(ori_loss,1))
# train_gene_op = adam_optimize(gene_loss,self.global_step)
# return self.action_logits,gene_loss,train_gene_op
prob = tf.nn.softmax(action_logits,axis=-1)
# ori_loss = tf.gather_nd(tf.log(prob),action_idx)
# ori_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=tf.argmax(self.action_logits,2),logits=self.action_logits)
ori_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels= action_idx,logits=action_logits)
reward_score = tf.nn.relu(reward_score) #
gene_loss = tf.reduce_mean(reward_score * tf.reduce_sum(ori_loss,-1))
train_gene_op = gene_adam_optimize(gene_loss,self.global_step)
return prob,gene_loss,train_gene_op
def get_generator_data(self):
return self.train_sentence,self.train_sentence_len,self.train_label
def get_original_prob(self):
sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence_original")
sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len_original')
sentence_label = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_label_original')
embedded_one = self.layers['embedding'](sentence)
_, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
prob = tf.nn.softmax(logits)
return tf.gather_nd(prob, tf.stack((tf.range(tf.shape(prob)[0],dtype=tf.int32),sentence_label),axis=1))
def train_discriminator(self):
with tf.name_scope(name='discriminator') as scope:
sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence")
sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len')
train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
original_prob = tf.placeholder(dtype=tf.float32,shape=[None],name='original_prob')
embedded_one = self.layers['embedding'](sentence)
_, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state))
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=train_label,logits=logits)
dis_loss = tf.reduce_mean(loss)
train_dis_op = adam_optimize(dis_loss, self.global_step)
tf.summary.scalar('dis_loss', dis_loss)
softmax_prob = tf.nn.softmax(logits)
prob = tf.gather_nd(softmax_prob, tf.stack((tf.range(tf.shape(softmax_prob)[0],dtype=tf.int32),train_label),axis=1))
# train_label=tf.cast(train_label,tf.float32)
# reward = prob*train_label+(1-prob)*(1-train_label)
reward = original_prob-prob
return dis_loss,train_dis_op,reward
# def train_discriminator(self):
# with tf.name_scope(name='discriminator') as scope:
# sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence")
# sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len')
# train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
# embedded_one = self.layers['embedding'](sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
# logits = tf.squeeze(self.layers['cl_logits_1'](one_next_state[0].h))
# loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=train_label,logits=logits)
# dis_loss = tf.reduce_mean(loss)
# train_dis_op = adam_optimize(dis_loss, self.global_step)
# tf.summary.scalar('dis_loss', dis_loss)
# this_logits = tf.nn.softmax(logits)
# prob = this_logits[:,1]+this_logits[:,3] # the probability of 1 label
# train_label=tf.cast(train_label,tf.float32)
# reward = prob*train_label+(1-prob)*(1-train_label)
# return dis_loss,train_dis_op,reward
# class rtModel(object):
# def __init__(self,cl_logits_input_dim=None):
# self.layers = {}
# self.initialize_vocab()
# self.layers['embedding'] = layers_lib.Embedding( # generator
# self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
# self.vocab_freqs, 1)
# self.layers['embedding_1'] = layers_lib.Embedding( # discriminator
# self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
# self.vocab_freqs, FLAGS.keep_prob_emb)
# self.layers['lstm'] = layers_lib.LSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers, FLAGS.keep_prob_lstm_out)
# self.layers['lstm_1'] = layers_lib.LSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers, FLAGS.keep_prob_lstm_out,
# name="lstm_1")
# self.layers['action_select'] = layers_lib.Actionselect(
# FLAGS.action_type,
# name='action_output')
# cl_logits_input_dim = cl_logits_input_dim or FLAGS.rnn_cell_size
# self.layers['cl_logits'] = layers_lib.cl_logits_subgraph(
# [FLAGS.cl_hidden_size] * FLAGS.cl_num_layers, cl_logits_input_dim,
# FLAGS.num_classes, FLAGS.keep_prob_cl_hidden, name='cl_logits')
# # cl_logits_input_dim = cl_logits_input_dim or FLAGS.rnn_cell_size
# # self.layers['cl_logits_1'] = layers_lib.cl_logits_subgraph(
# # [FLAGS.cl_hidden_size] * FLAGS.cl_num_layers, cl_logits_input_dim,
# # FLAGS.num_classes, FLAGS.keep_prob_cl_hidden, name='cl_logits_1')
# def build_train_graph(self,global_step):
# self.initialize_train_dataset()
# self.global_step = global_step
# embedded_one = self.layers['embedding'](self.train_sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.train_sentence_len)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.cast(self.train_label,tf.float32),logits=logits)
# loss = tf.reduce_mean(loss)
# tf.summary.scalar('loss',loss)
# prediction = tf.equal(tf.cast(tf.greater(logits, 0.), tf.int32),self.train_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# train_op = optimize(loss, self.global_step)
# tf.summary.scalar('train_accuracy', accuracy)
# return loss, train_op, accuracy
# def initialize_vocab(self):
# _,self.vocab = get_rt_dataset('train')
# self.vocab_freqs = self.vocab.get_freq()
# self.vocab_size = self.vocab.size
# def initialize_train_dataset(self):
# train_dataset,_ = get_rt_dataset('train',self.vocab)
# train_dataset = train_dataset.shuffle(buffer_size = 10000 , seed=321)
# train_dataset = train_dataset.padded_batch(FLAGS.batch_size,
# padded_shapes=([FLAGS.num_timesteps],(),()),drop_remainder=True).repeat(1000).prefetch(5*FLAGS.batch_size)
# train_dataset = train_dataset.make_one_shot_iterator()
# self.train_sentence,self.train_sentence_len,self.train_label = train_dataset.get_next()
# def initialize_test_dataset(self):
# test_dataset,_ = get_rt_dataset('test',self.vocab)
# test_dataset = test_dataset.padded_batch(FLAGS.batch_size, # because default padding_value and pad_idx are 0
# padded_shapes=([FLAGS.num_timesteps],(),())).prefetch(FLAGS.batch_size)
# test_iterator = test_dataset.make_one_shot_iterator()
# self.test_init_op = test_iterator.make_initializer(test_dataset,name='test_init')
# self.test_sentence,self.test_sentence_len,self.test_label = test_iterator.get_next()
# def build_test_graph(self):
# self.initialize_test_dataset()
# embedded_one = self.layers['embedding'](self.test_sentence,False)
# batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# prediction = tf.equal(tf.cast(tf.greater(logits, 0.), tf.int32),self.test_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# tf.summary.scalar('test_accuracy', accuracy)
# return accuracy,batch_number,self.test_init_op
# def build_adv_test_graph(self): # done
# self.initialize_test_dataset()
# embedded_one = self.layers['embedding'](self.test_sentence,False)
# batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_len,False)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h)) # four real_0 real_1 fake_0 fake_1
# this_logits = tf.concat([tf.expand_dims(logits[:,0],-1)+tf.expand_dims(logits[:,2],-1),tf.expand_dims(logits[:,1],-1)+tf.expand_dims(logits[:,3],-1)],-1)
# prediction = tf.equal(tf.cast(tf.argmax(this_logits,-1), tf.int32),self.test_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# tf.summary.scalar('test_accuracy', accuracy)
# return accuracy,batch_number,self.test_init_op
# @property
# def pretrained_variables(self):
# return self.layers['embedding'].trainable_weights + self.layers['lstm'].trainable_weights
# # return self.layers['embedding'].trainable_weights
# # return self.layers['lstm'].trainable_weights
# # @property
# # def my_pretrained_variables(self):
# # return self.layers['embedding_1'].trainable_weights + self.layers['lstm_1'].trainable_weights
# def train_generator(self,global_step):
# with tf.name_scope(name='generator'):
# self.initialize_train_dataset()
# self.global_step = global_step
# train_sentence = tf.placeholder(dtype=tf.int32,shape=[FLAGS.batch_size,FLAGS.num_timesteps],name='train_sentence')
# train_sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='train_sentence_len')
# reward_score = tf.placeholder(dtype=tf.float32, shape=[None],name="reward_score")
# embedded = self.layers['embedding_1'](train_sentence)
# lstm_out, _, = self.layers['lstm_1'](embedded,None,train_sentence_len)
# self.action_logits= self.layers['action_select'](lstm_out)
# ori_loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=tf.argmax(self.action_logits,2),logits=self.action_logits)
# gene_loss = tf.reduce_mean(reward_score * tf.reduce_mean(ori_loss,1))
# train_gene_op = optimize(gene_loss)
# return self.action_logits,gene_loss,train_gene_op
# def get_generator_data(self):
# return self.train_sentence,self.train_sentence_len,self.train_label
# def get_original_prob(self):
# sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence_original")
# sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len_original')
# embedded_one = self.layers['embedding'](sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# prob = tf.sigmoid(logits)
# return prob
# def train_discriminator(self):
# with tf.name_scope(name='discriminator') as scope:
# sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence")
# sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len')
# train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
# original_prob = tf.placeholder(dtype=tf.float32,shape=[None],name='original_prob')
# embedded_one = self.layers['embedding'](sentence)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
# logits = tf.squeeze(self.layers['cl_logits'](one_next_state[0].h))
# loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.cast(train_label,tf.float32),logits=logits)
# dis_loss = tf.reduce_mean(loss)
# train_dis_op = optimize(dis_loss, self.global_step)
# tf.summary.scalar('dis_loss', dis_loss)
# prob = tf.sigmoid(logits)
# train_label=tf.cast(train_label,tf.float32)
# # reward = prob*train_label+(1-prob)*(1-train_label)
# reward = tf.abs(original_prob-prob)
# return dis_loss,train_dis_op,reward
# # def train_discriminator(self):
# # with tf.name_scope(name='discriminator') as scope:
# # sentence = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence")
# # sentence_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_len')
# # train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
# # embedded_one = self.layers['embedding'](sentence)
# # _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_len)
# # logits = tf.squeeze(self.layers['cl_logits_1'](one_next_state[0].h))
# # loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=train_label,logits=logits)
# # dis_loss = tf.reduce_mean(loss)
# # train_dis_op = optimize(dis_loss, self.global_step)
# # tf.summary.scalar('dis_loss', dis_loss)
# # this_logits = tf.nn.softmax(logits)
# # prob = this_logits[:,1]+this_logits[:,3] # the probability of 1 label
# # train_label=tf.cast(train_label,tf.float32)
# # reward = prob*train_label+(1-prob)*(1-train_label)
# # return dis_loss,train_dis_op,reward
# class paraphraseModel(object):
# def __init__(self):
# self.layers = {}
# self.initialize_vocab()
# self.layers['embedding'] = layers_lib.Embedding( # generator
# self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
# self.vocab_freqs, 1)
# self.layers['embedding_1'] = layers_lib.Embedding( # discriminator
# self.vocab_size, FLAGS.embedding_dims, FLAGS.normalize_embeddings,
# self.vocab_freqs, FLAGS.keep_prob_emb)
# self.layers['lstm'] = layers_lib.LSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers, FLAGS.keep_prob_lstm_out)
# self.layers['lstm_1'] = layers_lib.LSTM(
# FLAGS.rnn_cell_size, FLAGS.rnn_num_layers, FLAGS.keep_prob_lstm_out,
# name="lstm_1")
# self.layers['action_select'] = layers_lib.Actionselect(
# FLAGS.action_type,
# name='action_output')
# cl_logits_input_dim = 2*FLAGS.rnn_cell_size
# self.layers['cl_logits'] = layers_lib.cl_logits_subgraph(
# [FLAGS.cl_hidden_size] * FLAGS.cl_num_layers, cl_logits_input_dim,
# FLAGS.num_classes, FLAGS.keep_prob_cl_hidden, name='cl_logits')
# def build_train_graph(self,global_step):
# with tf.name_scope(name='train_graph') as scope:
# self.initialize_train_dataset()
# self.global_step = global_step
# embedded_one = self.layers['embedding'](self.train_sentence_one)
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.train_sentence_one_len)
# embedded_two = self.layers['embedding'](self.train_sentence_two)
# _, two_next_state = self.layers['lstm'](embedded_two, None,self.train_sentence_two_len)
# lstm_out = tf.concat([one_next_state[0].h,two_next_state[0].h],1)
# logits = tf.squeeze(self.layers['cl_logits'](lstm_out))
# loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.cast(self.train_label,tf.float32),logits=logits)
# loss = tf.reduce_mean(loss)
# tf.summary.scalar('loss',loss)
# prediction = tf.equal(tf.cast(tf.greater(logits, 0.), tf.int32),self.train_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# train_op = optimize(loss, self.global_step)
# tf.summary.scalar('train_accuracy', accuracy)
# return loss, train_op, accuracy
# def initialize_vocab(self):
# _,self.vocab = get_msr_dataset('train')
# self.vocab_freqs = self.vocab.get_freq()
# self.vocab_size = self.vocab.size
# def initialize_train_dataset(self):
# train_dataset,_ = get_msr_dataset('train')
# train_dataset = train_dataset.shuffle(buffer_size = 10000,seed=321)
# train_dataset = train_dataset.padded_batch(FLAGS.batch_size,
# padded_shapes=([FLAGS.num_timesteps],(),[FLAGS.num_timesteps],(),())).repeat(1000).prefetch(5*FLAGS.batch_size)
# train_dataset = train_dataset.make_one_shot_iterator()
# self.train_sentence_one,self.train_sentence_one_len,self.train_sentence_two,\
# self.train_sentence_two_len,self.train_label = train_dataset.get_next()
# def initialize_test_dataset(self):
# test_dataset,_ = get_msr_dataset('test')
# test_dataset = test_dataset.padded_batch(FLAGS.batch_size,
# padded_shapes=([FLAGS.num_timesteps],(),[FLAGS.num_timesteps],(),()),padding_values=(0,0,0,0,0)).prefetch(1)
# test_iterator = test_dataset.make_one_shot_iterator()
# self.test_init_op = test_iterator.make_initializer(test_dataset,name='test_init')
# self.test_sentence_one,self.test_sentence_one_len,self.test_sentence_two,\
# self.test_sentence_two_len,self.test_label = test_iterator.get_next()
# def build_test_graph(self):
# with tf.name_scope('test') as scope:
# self.initialize_test_dataset()
# embedded_one = self.layers['embedding'](self.test_sentence_one,False)
# batch_number = tf.shape(embedded_one)[0]
# _, one_next_state = self.layers['lstm'](embedded_one, None,self.test_sentence_one_len,False)
# embedded_two = self.layers['embedding'](self.test_sentence_two,False)
# _, two_next_state = self.layers['lstm'](embedded_two, None,self.test_sentence_two_len,False)
# lstm_out = tf.concat([one_next_state[0].h,two_next_state[0].h],1)
# logits = tf.squeeze(self.layers['cl_logits'](lstm_out))
# prediction = tf.equal(tf.cast(tf.greater(logits, 0.), tf.int32),self.test_label)
# accuracy = tf.reduce_mean(tf.cast(prediction, tf.float32))
# tf.summary.scalar('test_accuracy', accuracy)
# return accuracy,batch_number,self.test_init_op
# @property
# def pretrained_variables(self):
# return (self.layers['embedding'].trainable_weights +
# self.layers['lstm'].trainable_weights)
# def train_generator(self,global_step):
# with tf.name_scope(name='generator'):
# self.initialize_train_dataset()
# self.global_step = global_step
# train_sentence_one = tf.placeholder(dtype=tf.int32,shape=[None,FLAGS.num_timesteps],name='train_sentence_one')
# train_sentence_one_len = tf.placeholder(dtype=tf.int32,shape=[None],name='train_sentence_one_len')
# train_sentence_two = tf.placeholder(dtype=tf.int32,shape=[None,FLAGS.num_timesteps],name='train_sentence_two')
# train_sentence_two_len = tf.placeholder(dtype=tf.int32,shape=[None],name='train_sentence_two_len')
# mode = tf.placeholder(shape=None,dtype=tf.int32,name='mode')
# reward_score = tf.placeholder(dtype=tf.float32, shape=[None],name="reward_score")
# embedded = self.layers['embedding_1'](train_sentence_one)
# lstm_out, _, = self.layers['lstm_1'](embedded,None,train_sentence_one_len)
# self.action_logits_one = self.layers['action_select'](lstm_out)
# embedded = self.layers['embedding_1'](train_sentence_two)
# lstm_out, _, = self.layers['lstm_1'](embedded,None,train_sentence_two_len)
# self.action_logits_two = self.layers['action_select'](lstm_out)
# ori_loss = tf.cond(
# tf.equal(mode,1),
# lambda:tf.nn.sparse_softmax_cross_entropy_with_logits(labels=tf.argmax(self.action_logits_one,2),logits=self.action_logits_one),
# lambda:tf.nn.sparse_softmax_cross_entropy_with_logits(labels=tf.argmax(self.action_logits_two,2),logits=self.action_logits_two),
# )
# gene_loss = tf.reduce_mean(reward_score * tf.reduce_mean(ori_loss,1))
# train_gene_op = optimize(gene_loss)
# return self.action_logits_one,self.action_logits_two,gene_loss,train_gene_op
# def get_generator_data(self):
# return self.train_sentence_one,self.train_sentence_one_len,\
# self.train_sentence_two,self.train_sentence_two_len,self.train_label
# def train_discriminator(self):
# with tf.name_scope(name='discriminator') as scope:
# sentence_one = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence_one")
# sentence_two = tf.placeholder(dtype=tf.int32, shape=(None, FLAGS.num_timesteps), name="sentence_two")
# sentence_one_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_one_len')
# sentence_two_len = tf.placeholder(dtype=tf.int32,shape=[None],name='sentence_two_len')
# train_label = tf.placeholder(dtype=tf.int32,shape=[None],name='train_label')
# embedded_one = self.layers['embedding'](sentence_one)
# _, one_next_state = self.layers['lstm'](embedded_one, None,sentence_one_len)
# embedded_two = self.layers['embedding'](sentence_two)
# _, two_next_state = self.layers['lstm'](embedded_two, None,sentence_two_len)
# # print("sadfasdfasfd: ",type(one_next_state)," ",(type(two_next_state)))
# lstm_out = tf.concat([one_next_state[0].h,two_next_state[0].h],1)
# logits = tf.squeeze(self.layers['cl_logits'](lstm_out))
# loss = tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.cast(train_label,tf.float32),logits=logits)
# dis_loss = tf.reduce_mean(loss)
# train_dis_op = optimize(dis_loss, self.global_step)
# tf.summary.scalar('dis_loss', dis_loss)
# prob = tf.sigmoid(logits)
# train_label=tf.cast(train_label,tf.float32)
# reward = prob*train_label+(1-prob)*(1-train_label)
# return dis_loss,train_dis_op,reward,one_next_state[0].h,two_next_state[0].h
def make_restore_average_vars_dict():
"""Returns dict mapping moving average names to variables."""
var_restore_dict = {}
variable_averages = tf.train.ExponentialMovingAverage(0.999)
for v in tf.global_variables():
if v in tf.trainable_variables():
name = variable_averages.average_name(v)
else:
name = v.op.name
var_restore_dict[name] = v
return var_restore_dict
def adam_optimize(loss,global_step=None):
return layers_lib.adam_optimize(loss,global_step,FLAGS.learning_rate,FLAGS.max_grad_norm)
def gene_adam_optimize(loss,global_step=None):
return layers_lib.adam_optimize(loss,global_step,FLAGS.generator_learning_rate,FLAGS.max_grad_norm)
def optimize(loss, global_step=None):
return layers_lib.optimize(
loss, global_step, FLAGS.max_grad_norm, FLAGS.learning_rate,
FLAGS.learning_rate_decay_factor)
def optimize_for_generator(loss, global_step=None):
return layers_lib.optimize(
loss, global_step, FLAGS.max_grad_norm, FLAGS.learning_rate_generator,
FLAGS.learning_rate_decay_factor)
if __name__=='__main__':
model = paraphraseModel()
FLAGS.batch_size = 3
FLAGS.input_dir = 'D:\\ChromeDownload\\msrp_data.tar\\msrp_data\\msr'
FLAGS.num_timesteps = 100
model.initialize_test_dataset()
with tf.Session() as sess:
print(sess.run([model.test_sentence_one,model.test_sentence_one_len,model.test_sentence_two,model.test_label]))
| 59.576395 | 246 | 0.679654 | 8,657 | 65,117 | 4.79531 | 0.042162 | 0.053959 | 0.027172 | 0.026883 | 0.901814 | 0.888276 | 0.885169 | 0.881531 | 0.876906 | 0.874569 | 0 | 0.011302 | 0.198289 | 65,117 | 1,092 | 247 | 59.630952 | 0.78389 | 0.471336 | 0 | 0.838583 | 0 | 0 | 0.08458 | 0.006992 | 0 | 0 | 0 | 0 | 0 | 1 | 0.106299 | false | 0 | 0.017717 | 0.023622 | 0.198819 | 0.003937 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
df7b865acf668b6d37018be0029661f7c248bba3 | 38,828 | py | Python | alibabacloud/clients/qualitycheck_20190115.py | wallisyan/alibabacloud-python-sdk-v2 | 6e024c97cded2403025a7dd8fea8261e41872156 | [
"Apache-2.0"
] | 21 | 2018-12-20T07:34:13.000Z | 2020-03-05T14:32:08.000Z | alibabacloud/clients/qualitycheck_20190115.py | wallisyan/alibabacloud-python-sdk-v2 | 6e024c97cded2403025a7dd8fea8261e41872156 | [
"Apache-2.0"
] | 22 | 2018-12-21T13:22:33.000Z | 2020-06-29T08:37:09.000Z | alibabacloud/clients/qualitycheck_20190115.py | wallisyan/alibabacloud-python-sdk-v2 | 6e024c97cded2403025a7dd8fea8261e41872156 | [
"Apache-2.0"
] | 12 | 2018-12-29T05:45:55.000Z | 2022-01-05T09:59:30.000Z | # Copyright 2019 Alibaba Cloud Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from alibabacloud.client import AlibabaCloudClient
from alibabacloud.request import APIRequest
from alibabacloud.utils.parameter_validation import verify_params
class QualitycheckClient(AlibabaCloudClient):
def __init__(self, client_config, credentials_provider=None, retry_policy=None,
endpoint_resolver=None):
AlibabaCloudClient.__init__(self, client_config,
credentials_provider=credentials_provider,
retry_policy=retry_policy,
endpoint_resolver=endpoint_resolver)
self.product_code = 'Qualitycheck'
self.api_version = '2019-01-15'
self.location_service_code = None
self.location_endpoint_type = 'openAPI'
def get_user_config(self, resource_owner_id=None):
api_request = APIRequest('GetUserConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id}
return self._handle_request(api_request).result
def update_user_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateUserConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_user(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteUser', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_task_assign_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteTaskAssignRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def create_user(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CreateUser', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def create_task_assign_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CreateTaskAssignRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def assign_reviewer(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('AssignReviewer', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def handle_complaint(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('HandleComplaint', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def submit_complaint(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitComplaint', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_task_assign_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateTaskAssignRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_user(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateUser', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_users(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListUsers', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_roles(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListRoles', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_task_assign_rules(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListTaskAssignRules', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def create_skill_group_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CreateSkillGroupConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def create_warning_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CreateWarningConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_precision_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeletePrecisionTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_skill_group_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteSkillGroupConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_warning_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteWarningConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_skill_group_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetSkillGroupConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_skill_group_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListSkillGroupConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_warning_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListWarningConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_skill_group_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateSkillGroupConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_warning_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateWarningConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_next_result_to_verify(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetNextResultToVerify', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_precision_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetPrecisionTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_precision_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListPrecisionTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def submit_precision_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitPrecisionTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def verify_file(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('VerifyFile', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def verify_sentence(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('VerifySentence', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_asr_vocab(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListAsrVocab', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_user_info(self, resource_owner_id=None):
api_request = APIRequest('GetUserInfo', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id}
return self._handle_request(api_request).result
def restart_asr_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('RestartAsrTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def open_service(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('OpenService', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_result_to_review(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetResultToReview', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def create_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CreateRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_next_result_to_review(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetNextResultToReview', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def close_service(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CloseService', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def save_review_result(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SaveReviewResult', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_audio_data(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadAudioData', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_audio_data4_pre(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadAudioData4Pre', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def generate_customization_model_id(self, resource_owner_id=None):
api_request = APIRequest('GenerateCustomizationModelId', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id}
return self._handle_request(api_request).result
def add_thesaurus_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('AddThesaurusForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def remove_and_get_task_rules(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('RemoveAndGetTaskRules', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def submit_review_info(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitReviewInfo', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_audio_data_status(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetAudioDataStatus', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def review_single_result_by_id(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ReviewSingleResultById', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_data_sync(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadDataSync', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def save_config_data_set(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SaveConfigDataSet', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_sub_score_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateSubScoreForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def config_data_set(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ConfigDataSet', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def insert_score_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('InsertScoreForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def insert_sub_score_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('InsertSubScoreForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def submit_model_test_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitModelTestTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def del_rule_category(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DelRuleCategory', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_acc_asr_result(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetAccAsrResult', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def test_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('TestRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def exchange_audio(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ExchangeAudio', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_poc_test_report(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetPocTestReport', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_rule_detail(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetRuleDetail', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_asr_vocab(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateAsrVocab', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_rule_for_ant(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateRuleForAnt', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_oss_header(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetOssHeader', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_recognize_result(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetRecognizeResult', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_business_category_list(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetBusinessCategoryList', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def invalid_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('InvalidRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_sub_score_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteSubScoreForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_on_purchase_success(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateOnPurchaseSuccess', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_thesaurus_by_synonym_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetThesaurusBySynonymForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def create_asr_vocab(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('CreateAsrVocab', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def list_data_set_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ListDataSetTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def submit_audio_label(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitAudioLabel', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def del_thesaurus_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DelThesaurusForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_asr_vocab(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteAsrVocab', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_audio_url(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetAudioUrl', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def add_rule_category(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('AddRuleCategory', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_rule_dimension(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetRuleDimension', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def add_upload_data_set(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('AddUploadDataSet', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_result_count(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetResultCount', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_customization_config_list(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetCustomizationConfigList', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def edit_thesaurus_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('EditThesaurusForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def execute_asr_transform(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ExecuteAsrTransform', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_score_info(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetScoreInfo', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_data(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadData', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def add_business_category(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('AddBusinessCategory', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_asr_vocab(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetAsrVocab', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def do_logical_delete_resource(
self,
country=None,
resource_owner_id=None,
hid=None,
success=None,
interrupt=None,
gmt_wakeup=None,
pk=None,
bid=None,
message=None,
task_extra_data=None,
task_identifier=None):
api_request = APIRequest('DoLogicalDeleteResource', 'GET', 'http', 'RPC', 'query')
api_request._params = {
"Country": country,
"ResourceOwnerId": resource_owner_id,
"Hid": hid,
"Success": success,
"Interrupt": interrupt,
"GmtWakeup": gmt_wakeup,
"Pk": pk,
"Bid": bid,
"Message": message,
"TaskExtraData": task_extra_data,
"TaskIdentifier": task_identifier}
return self._handle_request(api_request).result
def upload_audio_data_with_rules(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadAudioDataWithRules', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_review_info(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetReviewInfo', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_result(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetResult', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def submit_quality_check_task(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitQualityCheckTask', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_rule_category(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetRuleCategory', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_data_set_list(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetDataSetList', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_rule_for_ant(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadRuleForAnt', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_user_group(self, resource_owner_id=None):
api_request = APIRequest('GetUserGroup', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id}
return self._handle_request(api_request).result
def submit_customization_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('SubmitCustomizationConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_task_file_result_list(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetTaskFileResultList', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def do_physical_delete_resource(
self,
country=None,
resource_owner_id=None,
hid=None,
success=None,
interrupt=None,
gmt_wakeup=None,
pk=None,
bid=None,
task_extra_data=None,
task_identifier=None):
api_request = APIRequest('DoPhysicalDeleteResource', 'GET', 'http', 'RPC', 'query')
api_request._params = {
"Country": country,
"ResourceOwnerId": resource_owner_id,
"Hid": hid,
"Success": success,
"Interrupt": interrupt,
"GmtWakeup": gmt_wakeup,
"Pk": pk,
"Bid": bid,
"TaskExtraData": task_extra_data,
"TaskIdentifier": task_identifier}
return self._handle_request(api_request).result
def delete_data_set(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteDataSet', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_score_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateScoreForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_data_with_rules(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadDataWithRules', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_customization_config(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteCustomizationConfig', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def validate_role_set(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('ValidateRoleSet', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def do_check_resource(
self,
country=None,
resource_owner_id=None,
hid=None,
level=None,
message=None,
success=None,
interrupt=None,
gmt_wakeup=None,
pk=None,
bid=None,
prompt=None,
task_extra_data=None,
task_identifier=None):
api_request = APIRequest('DoCheckResource', 'GET', 'http', 'RPC', 'query')
api_request._params = {
"Country": country,
"ResourceOwnerId": resource_owner_id,
"Hid": hid,
"Level": level,
"Message": message,
"Success": success,
"Interrupt": interrupt,
"GmtWakeup": gmt_wakeup,
"Pk": pk,
"Bid": bid,
"Prompt": prompt,
"TaskExtraData": task_extra_data,
"TaskIdentifier": task_identifier}
return self._handle_request(api_request).result
def register_notice(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('RegisterNotice', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_business_category(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteBusinessCategory', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_data_set_oss_header(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetDataSetOssHeader', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_task_rule_list(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetTaskRuleList', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_audio_content_info(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetAudioContentInfo', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def upload_audio_data_with_rules4_pre(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UploadAudioDataWithRules4Pre', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_file_dimension(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetFileDimension', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def get_result_review_list(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('GetResultReviewList', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def update_rule(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('UpdateRule', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def delete_score_for_api(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('DeleteScoreForApi', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
def test_network(self, resource_owner_id=None, json_str=None):
api_request = APIRequest('TestNetwork', 'GET', 'http', 'RPC', 'query')
api_request._params = {"ResourceOwnerId": resource_owner_id, "JsonStr": json_str}
return self._handle_request(api_request).result
| 56.436047 | 95 | 0.700036 | 4,642 | 38,828 | 5.485782 | 0.070875 | 0.137836 | 0.137836 | 0.087296 | 0.867779 | 0.867779 | 0.864402 | 0.864009 | 0.857255 | 0.856666 | 0 | 0.000626 | 0.176625 | 38,828 | 687 | 96 | 56.518195 | 0.795902 | 0.014809 | 0 | 0.544304 | 0 | 0 | 0.169173 | 0.012866 | 0 | 0 | 0 | 0 | 0 | 1 | 0.213382 | false | 0 | 0.005425 | 0 | 0.432188 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
10d6b9689688f362634e554af734447828da1dd5 | 16,066 | py | Python | dfirtrack_main/tests/domain/test_domain_views.py | cclauss/dfirtrack | 2a307c5fe82e927b3c229a20a02bc0c7a5d66d9a | [
"Apache-2.0"
] | null | null | null | dfirtrack_main/tests/domain/test_domain_views.py | cclauss/dfirtrack | 2a307c5fe82e927b3c229a20a02bc0c7a5d66d9a | [
"Apache-2.0"
] | null | null | null | dfirtrack_main/tests/domain/test_domain_views.py | cclauss/dfirtrack | 2a307c5fe82e927b3c229a20a02bc0c7a5d66d9a | [
"Apache-2.0"
] | null | null | null | import urllib.parse
from django.contrib.auth.models import User
from django.test import TestCase
from dfirtrack_main.models import Domain
class DomainViewTestCase(TestCase):
""" domain view tests """
@classmethod
def setUpTestData(cls):
# create object
Domain.objects.create(domain_name='domain_1')
# create user
User.objects.create_user(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
def test_domain_list_not_logged_in(self):
""" test list view """
# create url
destination = '/login/?next=' + urllib.parse.quote('/domain/', safe='')
# get response
response = self.client.get('/domain/', follow=True)
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_list_logged_in(self):
""" test list view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/')
# compare
self.assertEqual(response.status_code, 200)
def test_domain_list_template(self):
""" test list view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/')
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/domain/domain_list.html')
def test_domain_list_get_user_context(self):
""" test list view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/')
# compare
self.assertEqual(str(response.context['user']), 'testuser_domain')
def test_domain_list_redirect(self):
""" test list view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create url
destination = urllib.parse.quote('/domain/', safe='/')
# get response
response = self.client.get('/domain', follow=True)
# compare
self.assertRedirects(response, destination, status_code=301, target_status_code=200)
def test_domain_detail_not_logged_in(self):
""" test detail view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# create url
destination = '/login/?next=' + urllib.parse.quote('/domain/' + str(domain_1.domain_id) + '/', safe='')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/', follow=True)
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_detail_logged_in(self):
""" test detail view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/')
# compare
self.assertEqual(response.status_code, 200)
def test_domain_detail_template(self):
""" test detail view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/')
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/domain/domain_detail.html')
def test_domain_detail_get_user_context(self):
""" test detail view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/')
# compare
self.assertEqual(str(response.context['user']), 'testuser_domain')
def test_domain_detail_redirect(self):
""" test detail view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create url
destination = urllib.parse.quote('/domain/' + str(domain_1.domain_id) + '/', safe='/')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id), follow=True)
# compare
self.assertRedirects(response, destination, status_code=301, target_status_code=200)
def test_domain_add_not_logged_in(self):
""" test add view """
# create url
destination = '/login/?next=' + urllib.parse.quote('/domain/add/', safe='')
# get response
response = self.client.get('/domain/add/', follow=True)
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_add_logged_in(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/add/')
# compare
self.assertEqual(response.status_code, 200)
def test_domain_add_template(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/add/')
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/generic_form.html')
def test_domain_add_get_user_context(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/add/')
# compare
self.assertEqual(str(response.context['user']), 'testuser_domain')
def test_domain_add_redirect(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create url
destination = urllib.parse.quote('/domain/add/', safe='/')
# get response
response = self.client.get('/domain/add', follow=True)
# compare
self.assertRedirects(response, destination, status_code=301, target_status_code=200)
def test_domain_add_post_redirect(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create post data
data_dict = {
'domain_name': 'domain_add_post_test',
}
# get response
response = self.client.post('/domain/add/', data_dict)
# get object
domain_id = Domain.objects.get(domain_name = 'domain_add_post_test').domain_id
# create url
destination = urllib.parse.quote('/domain/' + str(domain_id) + '/', safe='/')
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_add_post_invalid_reload(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create post data
data_dict = {}
# get response
response = self.client.post('/domain/add/', data_dict)
# compare
self.assertEqual(response.status_code, 200)
def test_domain_add_post_invalid_template(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create post data
data_dict = {}
# get response
response = self.client.post('/domain/add/', data_dict)
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/generic_form.html')
def test_domain_add_popup_not_logged_in(self):
""" test add view """
# create url
destination = '/login/?next=' + urllib.parse.quote('/domain/add_popup/', safe='')
# get response
response = self.client.get('/domain/add_popup/', follow=True)
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_add_popup_logged_in(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/add_popup/')
# compare
self.assertEqual(response.status_code, 200)
def test_domain_add_popup_template(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/add_popup/')
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/generic_form_popup.html')
def test_domain_add_popup_get_user_context(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/add_popup/')
# compare
self.assertEqual(str(response.context['user']), 'testuser_domain')
def test_domain_add_popup_redirect(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create url
destination = urllib.parse.quote('/domain/add_popup/', safe='/')
# get response
response = self.client.get('/domain/add_popup', follow=True)
# compare
self.assertRedirects(response, destination, status_code=301, target_status_code=200)
def test_domain_add_popup_post_redirect(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create post data
data_dict = {
'domain_name': 'domain_add_popup_post_test',
}
# get response
response = self.client.post('/domain/add_popup/', data_dict)
# compare
self.assertEqual(response.status_code, 200)
def test_domain_add_popup_post_invalid_reload(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create post data
data_dict = {}
# get response
response = self.client.post('/domain/add_popup/', data_dict)
# compare
self.assertEqual(response.status_code, 200)
def test_domain_add_popup_post_invalid_template(self):
""" test add view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create post data
data_dict = {}
# get response
response = self.client.post('/domain/add_popup/', data_dict)
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/generic_form_popup.html')
def test_domain_edit_not_logged_in(self):
""" test edit view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# create url
destination = '/login/?next=' + urllib.parse.quote('/domain/' + str(domain_1.domain_id) + '/edit/', safe='')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/edit/', follow=True)
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_edit_logged_in(self):
""" test edit view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/edit/')
# compare
self.assertEqual(response.status_code, 200)
def test_domain_edit_template(self):
""" test edit view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/edit/')
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/generic_form.html')
def test_domain_edit_get_user_context(self):
""" test edit view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/edit/')
# compare
self.assertEqual(str(response.context['user']), 'testuser_domain')
def test_domain_edit_redirect(self):
""" test edit view """
# get object
domain_1 = Domain.objects.get(domain_name='domain_1')
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create url
destination = urllib.parse.quote('/domain/' + str(domain_1.domain_id) + '/edit/', safe='/')
# get response
response = self.client.get('/domain/' + str(domain_1.domain_id) + '/edit', follow=True)
# compare
self.assertRedirects(response, destination, status_code=301, target_status_code=200)
def test_domain_edit_post_redirect(self):
""" test edit view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# create object
domain_1 = Domain.objects.create(domain_name='domain_edit_post_test_1')
# create post data
data_dict = {
'domain_name': 'domain_edit_post_test_2',
}
# get response
response = self.client.post('/domain/' + str(domain_1.domain_id) + '/edit/', data_dict)
# get object
domain_2 = Domain.objects.get(domain_name='domain_edit_post_test_2')
# create url
destination = urllib.parse.quote('/domain/' + str(domain_2.domain_id) + '/', safe='/')
# compare
self.assertRedirects(response, destination, status_code=302, target_status_code=200)
def test_domain_edit_post_invalid_reload(self):
""" test edit view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get object
domain_id = Domain.objects.get(domain_name='domain_1').domain_id
# create post data
data_dict = {}
# get response
response = self.client.post('/domain/' + str(domain_id) + '/edit/', data_dict)
# compare
self.assertEqual(response.status_code, 200)
def test_domain_edit_post_invalid_template(self):
""" test edit view """
# login testuser
self.client.login(username='testuser_domain', password='vOKJXW7ZsJ7TZ3dsu43w')
# get object
domain_id = Domain.objects.get(domain_name='domain_1').domain_id
# create post data
data_dict = {}
# get response
response = self.client.post('/domain/' + str(domain_id) + '/edit/', data_dict)
# compare
self.assertTemplateUsed(response, 'dfirtrack_main/generic_form.html')
| 37.625293 | 116 | 0.639861 | 1,778 | 16,066 | 5.565242 | 0.042182 | 0.063669 | 0.044669 | 0.07903 | 0.963315 | 0.943608 | 0.928449 | 0.921475 | 0.906114 | 0.887519 | 0 | 0.023975 | 0.239325 | 16,066 | 426 | 117 | 37.713615 | 0.785697 | 0.136001 | 0 | 0.576923 | 0 | 0 | 0.173094 | 0.027852 | 0 | 0 | 0 | 0 | 0.186813 | 1 | 0.192308 | false | 0.164835 | 0.021978 | 0 | 0.21978 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 7 |
8030701ea1837ccf8cbea1514cbb3d9115babde9 | 56 | py | Python | pylogic/__init__.py | moriire/pyLogic | 54dc3c0fb2b0d736dc7ebbd0a4af90c8add34c86 | [
"MIT"
] | 1 | 2021-12-19T05:38:39.000Z | 2021-12-19T05:38:39.000Z | pylogic/__init__.py | moriire/pyLogic | 54dc3c0fb2b0d736dc7ebbd0a4af90c8add34c86 | [
"MIT"
] | null | null | null | pylogic/__init__.py | moriire/pyLogic | 54dc3c0fb2b0d736dc7ebbd0a4af90c8add34c86 | [
"MIT"
] | null | null | null | from .pyLogic import Truth
from .pyLogic import Logic
| 18.666667 | 27 | 0.785714 | 8 | 56 | 5.5 | 0.625 | 0.5 | 0.772727 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.178571 | 56 | 2 | 28 | 28 | 0.956522 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
33c7a536d237a1f91cee014deef191bb1d824b0b | 2,922 | py | Python | joplin/pages/news_page/tests.py | cityofaustin/joplin | 01424e46993e9b1c8e57391d6b7d9448f31d596b | [
"MIT"
] | 15 | 2018-09-27T07:36:30.000Z | 2021-08-03T16:01:21.000Z | joplin/pages/news_page/tests.py | cityofaustin/joplin | 01424e46993e9b1c8e57391d6b7d9448f31d596b | [
"MIT"
] | 183 | 2017-11-16T23:30:47.000Z | 2020-12-18T21:43:36.000Z | joplin/pages/news_page/tests.py | cityofaustin/joplin | 01424e46993e9b1c8e57391d6b7d9448f31d596b | [
"MIT"
] | 12 | 2017-12-12T22:48:05.000Z | 2021-03-01T18:01:24.000Z | import pytest
from pages.news_page.models import NewsPage
import pages.news_page.fixtures as fixtures
# For news pages, we need to make sure our urls and our byline departments are set correctly
# example:
# "From Austin Public Health, written by Communications and Public Information Office"
@pytest.mark.django_db
def test_written_by_APH():
# APH makes a page for APH, doesn’t assign a different department:
page = fixtures.written_by_APH()
# Make sure we made a news page
assert isinstance(page, NewsPage)
# Make sure we only have one instance
assert len(page.janis_instances()) == 1
janis_instance = page.janis_instances()[0]
# Make sure we only have one URL
assert len(page.janis_urls()) == 1
janis_url = page.janis_urls()[0]
# Make sure the URL is APH
assert janis_instance['url'] == '/mvp-news-aph/mvp-news-by-aph/'
assert janis_url == '/mvp-news-aph/mvp-news-by-aph/'
# Make sure "From" is APH
assert janis_instance['from_department'].title == 'Austin Public Health'
# Make sure written by is not shown
assert not janis_instance['by_department']
@pytest.mark.django_db
def test_written_by_APH_written_for_APH():
# APH makes a page for APH, doesn’t assign a different department:
page = fixtures.written_by_APH_written_for_APH()
# Make sure we made a news page
assert isinstance(page, NewsPage)
# Make sure we only have one instance
assert len(page.janis_instances()) == 1
janis_instance = page.janis_instances()[0]
# Make sure we only have one URL
assert len(page.janis_urls()) == 1
janis_url = page.janis_urls()[0]
# Make sure the URL is APH
assert janis_instance['url'] == '/mvp-news-aph/mvp-news/'
assert janis_url == '/mvp-news-aph/mvp-news/'
# Make sure "From" is APH
assert janis_instance['from_department'].title == 'Austin Public Health'
# Make sure written by is not shown
assert not janis_instance['by_department']
@pytest.mark.django_db
def test_written_by_CPIO_written_for_APH():
# APH makes a page for APH, doesn’t assign a different department:
page = fixtures.written_by_CPIO_written_for_APH()
# Make sure we made a news page
assert isinstance(page, NewsPage)
# Make sure we only have one instance
assert len(page.janis_instances()) == 1
janis_instance = page.janis_instances()[0]
# Make sure we only have one URL
assert len(page.janis_urls()) == 1
janis_url = page.janis_urls()[0]
# Make sure the URL is APH
assert janis_instance['url'] == '/mvp-news-aph/mvp-news-by-cpio-for-aph/'
assert janis_url == '/mvp-news-aph/mvp-news-by-cpio-for-aph/'
# Make sure "From" is APH
assert janis_instance['from_department'].title == 'Austin Public Health'
# Make sure written by is CPIO
assert janis_instance['by_department'].title == 'Communications and Public Information Office'
| 32.831461 | 98 | 0.706023 | 448 | 2,922 | 4.453125 | 0.147321 | 0.07619 | 0.045113 | 0.042105 | 0.881203 | 0.841103 | 0.837093 | 0.837093 | 0.821554 | 0.803008 | 0 | 0.005093 | 0.193703 | 2,922 | 88 | 99 | 33.204545 | 0.841681 | 0.312799 | 0 | 0.589744 | 0 | 0 | 0.192133 | 0.092789 | 0 | 0 | 0 | 0 | 0.538462 | 1 | 0.076923 | false | 0 | 0.076923 | 0 | 0.153846 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
d50da3439e8b80cdba7c5f6a2e43040278c6365e | 12,414 | py | Python | python/neptune/source/nutil/math.py | b-io/io.barras | 87b103baeb2c14c8d91360bc27b9c0468a2d4e71 | [
"MIT"
] | 5 | 2018-08-12T19:48:54.000Z | 2021-03-16T12:46:10.000Z | python/neptune/source/nutil/math.py | b-io/io.barras | 87b103baeb2c14c8d91360bc27b9c0468a2d4e71 | [
"MIT"
] | 2 | 2021-06-12T08:09:24.000Z | 2021-12-21T23:08:41.000Z | python/neptune/source/nutil/math.py | b-io/io.barras | 87b103baeb2c14c8d91360bc27b9c0468a2d4e71 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
####################################################################################################
# NAME
# <NAME> - contain mathematical utility functions
#
# SYNOPSIS
# <NAME>
#
# AUTHOR
# Written by Florian Barras (florian@barras.io).
#
# COPYRIGHT
# Copyright © 2013-2021 Florian Barras <https://barras.io>.
# The MIT License (MIT) <https://opensource.org/licenses/MIT>.
####################################################################################################
from nutil.common import *
####################################################################################################
# MATH CONSTANTS
####################################################################################################
__MATH_CONSTANTS__________________________________ = ''
E = np.e
PI = np.pi
#########################
DEG_TO_RAD = PI / 180
RAD_TO_DEG = 180 / PI
####################################################################################################
# MATH FUNCTIONS
####################################################################################################
__MATH____________________________________________ = ''
def is_negative(x):
return x < 0
def is_non_negative(x):
return x >= 0
def is_positive(x):
return x > 0
def is_non_positive(x):
return x <= 0
##################################################
def abs(x):
return np.abs(x)
def exp(x):
return np.exp(x)
def log(x):
return np.log(x)
def sqrt(x):
return np.sqrt(x)
#########################
def scale(x, base=10):
if is_collection(x):
return apply(scale, x, axis=1, base=base)
return x / base ** floor(log(maximum(abs(x)) + EPS) / log(base))
# • MATH ARITHMETIC ################################################################################
__MATH_ARITHMETIC_________________________________ = ''
def add_all(*args, numeric_default=None, object_default=None, rename=False):
return reduce(add, *args, numeric_default=numeric_default, object_default=object_default,
rename=rename)
def add(c1, c2, numeric_default=None, object_default=None, rename=False):
"""Returns the addition of the specified collections."""
if is_list(c1):
return [add(c, c2, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c1]
elif is_list(c2):
return [add(c1, c, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c2]
elif is_table(c1) and is_table(c2):
if is_frame(c1) and not is_frame(c2):
return concat_cols(
[add(set_names(c1[k], k), c2, numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c1)])
elif not is_frame(c1) and is_frame(c2):
return concat_cols(
[add(c1, set_names(c2[k], k), numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c2)])
if rename:
names = get_names(c2)
rename_all(c1, c2, names=get_names(c1))
result = fill_null_all(c1, c2, numeric_default=numeric_default, object_default=object_default) + \
fill_null_all(c2, c1, numeric_default=numeric_default, object_default=object_default)
if rename:
set_names(c2, names)
return result
elif (is_table(c1) or is_number(c1)) and (is_table(c2) or is_number(c2)) or \
(is_array(c1) or is_number(c1)) and (is_array(c2) or is_number(c2)):
return c1 + c2
elif is_array(c1):
return [collection_to_type(a, c2) for a in np.vstack(c1) + get_values(c2)]
elif is_array(c2):
return [collection_to_type(a, c1) for a in get_values(c1) + np.vstack(c2)]
elif is_table(c1):
return sum_cols(join(c1, get_values(c2)))
elif is_table(c2):
return sum_cols(join(c2, get_values(c1)))
v1 = fill_null(get_values(c1), numeric_default=numeric_default, object_default=object_default)
v2 = fill_null(get_values(c2), numeric_default=numeric_default, object_default=object_default)
return collection_to_type(np.add(v1, v2), c1)
def subtract_all(*args, numeric_default=None, object_default=None, rename=False):
return reduce(subtract, *args, numeric_default=numeric_default, object_default=object_default,
rename=rename)
def subtract(c1, c2, numeric_default=None, object_default=None, rename=False):
"""Returns the subtraction of the specified collections."""
if is_list(c1):
return [subtract(c, c2, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c1]
elif is_list(c2):
return [subtract(c1, c, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c2]
elif is_table(c1) and is_table(c2):
if is_frame(c1) and not is_frame(c2):
return concat_cols(
[subtract(set_names(c1[k], k), c2, numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c1)])
elif not is_frame(c1) and is_frame(c2):
return concat_cols(
[subtract(c1, set_names(c2[k], k), numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c2)])
if rename:
names = get_names(c2)
rename_all(c1, c2, names=get_names(c1))
result = fill_null_all(c1, c2, numeric_default=numeric_default, object_default=object_default) - \
fill_null_all(c2, c1, numeric_default=numeric_default, object_default=object_default)
if rename:
set_names(c2, names)
return result
elif (is_table(c1) or is_number(c1)) and (is_table(c2) or is_number(c2)) or \
(is_array(c1) or is_number(c1)) and (is_array(c2) or is_number(c2)):
return c1 - c2
elif is_array(c1):
return [collection_to_type(a, c2) for a in np.vstack(c1) - get_values(c2)]
elif is_array(c2):
return [collection_to_type(a, c1) for a in get_values(c1) - np.vstack(c2)]
elif is_table(c1):
return sum_cols(join(c1, -get_values(c2)))
elif is_table(c2):
return sum_cols(join(-c2, get_values(c1)))
v1 = fill_null(get_values(c1), numeric_default=numeric_default, object_default=object_default)
v2 = fill_null(get_values(c2), numeric_default=numeric_default, object_default=object_default)
return collection_to_type(np.subtract(v1, v2), c1)
def multiply_all(*args, numeric_default=None, object_default=None, rename=False):
return reduce(multiply, *args, numeric_default=numeric_default, object_default=object_default,
rename=rename)
def multiply(c1, c2, numeric_default=None, object_default=None, rename=False):
"""Returns the multiplication of the specified collections."""
if is_list(c1):
return [multiply(c, c2, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c1]
elif is_list(c2):
return [multiply(c1, c, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c2]
elif is_table(c1) and is_table(c2):
if is_frame(c1) and not is_frame(c2):
return concat_cols(
[multiply(set_names(c1[k], k), c2, numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c1)])
elif not is_frame(c1) and is_frame(c2):
return concat_cols(
[multiply(c1, set_names(c2[k], k), numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c2)])
if rename:
names = get_names(c2)
rename_all(c1, c2, names=get_names(c1))
result = fill_null_all(c1, c2, numeric_default=numeric_default, object_default=object_default) * \
fill_null_all(c2, c1, numeric_default=numeric_default, object_default=object_default)
if rename:
set_names(c2, names)
return result
elif (is_table(c1) or is_number(c1)) and (is_table(c2) or is_number(c2)) or \
(is_array(c1) or is_number(c1)) and (is_array(c2) or is_number(c2)):
return c1 * c2
elif is_array(c1):
return [collection_to_type(a, c2) for a in np.vstack(c1) * get_values(c2)]
elif is_array(c2):
return [collection_to_type(a, c1) for a in get_values(c1) * np.vstack(c2)]
elif is_table(c1):
return product_cols(join(c1, get_values(c2)))
elif is_table(c2):
return product_cols(join(c2, get_values(c1)))
v1 = fill_null(get_values(c1), numeric_default=numeric_default, object_default=object_default)
v2 = fill_null(get_values(c2), numeric_default=numeric_default, object_default=object_default)
return collection_to_type(np.multiply(v1, v2), c1)
def divide_all(*args, numeric_default=None, object_default=None, rename=False):
return reduce(divide, *args, numeric_default=numeric_default, object_default=object_default,
rename=rename)
def divide(c1, c2, numeric_default=None, object_default=None, rename=False):
"""Returns the division of the specified collections."""
if is_list(c1):
return [divide(c, c2, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c1]
elif is_list(c2):
return [divide(c1, c, numeric_default=numeric_default, object_default=object_default,
rename=rename) for c in c2]
elif is_table(c1) and is_table(c2):
if is_frame(c1) and not is_frame(c2):
return concat_cols(
[divide(set_names(c1[k], k), c2, numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c1)])
elif not is_frame(c1) and is_frame(c2):
return concat_cols(
[divide(c1, set_names(c2[k], k), numeric_default=numeric_default,
object_default=object_default, rename=rename) for k in get_keys(c2)])
if rename:
names = get_names(c2)
rename_all(c1, c2, names=get_names(c1))
result = fill_null_all(c1, c2, numeric_default=numeric_default, object_default=object_default) / \
fill_null_all(c2, c1, numeric_default=numeric_default, object_default=object_default)
if rename:
set_names(c2, names)
return result
elif (is_table(c1) or is_number(c1)) and (is_table(c2) or is_number(c2)) or \
(is_array(c1) or is_number(c1)) and (is_array(c2) or is_number(c2)):
return c1 / c2
elif is_array(c1):
return [collection_to_type(a, c2) for a in np.vstack(c1) / get_values(c2)]
elif is_array(c2):
return [collection_to_type(a, c1) for a in get_values(c1) / np.vstack(c2)]
elif is_table(c1):
return product_cols(join(c1, 1 / get_values(c2)))
elif is_table(c2):
return product_cols(join(1 / c2, get_values(c1)))
v1 = fill_null(get_values(c1), numeric_default=numeric_default, object_default=object_default)
v2 = fill_null(get_values(c2), numeric_default=numeric_default, object_default=object_default)
return collection_to_type(np.divide(v1, v2), c1)
#########################
def nearest_inferior(c, value):
if not is_series(c) and not is_array(c):
c = to_list(c)
return nearest(add(filter_with(subtract(c, value), is_non_positive), value), value)
def nearest_superior(c, value):
if not is_series(c) and not is_array(c):
c = to_list(c)
return nearest(add(filter_with(subtract(c, value), is_non_negative), value), value)
def farthest_inferior(c, value):
if not is_series(c) and not is_array(c):
c = to_list(c)
return farthest(add(filter_with(subtract(c, value), is_non_positive), value), value)
def farthest_superior(c, value):
if not is_series(c) and not is_array(c):
c = to_list(c)
return farthest(add(filter_with(subtract(c, value), is_non_negative), value), value)
# • MATH GEOMETRY ##################################################################################
__MATH_GEOMETRY___________________________________ = ''
def create_ellipse(center, a, b, angle=0, precision=100):
X = []
Y = []
cx, cy = center
for theta in create_sequence(0, 2 * PI, include=True, n=precision):
# Calculate the coordinates of the ellipse point at the angle theta
px = a * cos(theta)
py = b * sin(theta)
# Rotate the ellipse point by the angle and translate it to the center
x, y = rotate(px, py, angle)
x += cx
y += cy
X.append(x)
Y.append(y)
return X, Y
##################################################
def cos(x):
return np.cos(x)
def acos(x):
return np.arccos(x)
def sin(x):
return np.sin(x)
def asin(x):
return np.arcsin(x)
def tan(x):
return np.tan(x)
def atan(x):
return np.arctan(x)
def atan2(y, x):
return np.arctan2(y, x)
#########################
def rotate(x, y, angle=0):
return cos(angle) * x - sin(angle) * y, \
sin(angle) * x + cos(angle) * y
| 34.870787 | 100 | 0.663283 | 1,840 | 12,414 | 4.171196 | 0.089674 | 0.145928 | 0.187622 | 0.131336 | 0.829967 | 0.829967 | 0.826319 | 0.811466 | 0.811466 | 0.790098 | 0 | 0.025733 | 0.148542 | 12,414 | 355 | 101 | 34.969014 | 0.700095 | 0.056469 | 0 | 0.485356 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.125523 | false | 0 | 0.004184 | 0.083682 | 0.426778 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
1d1ec8f324a01dc2b9dd235901252d6a3f5e9889 | 62,495 | py | Python | metashare/repository/seltests/test_filter.py | zeehio/META-SHARE | b796769629734353a63d98db72c84617f725e544 | [
"BSD-3-Clause"
] | 11 | 2015-07-13T13:36:44.000Z | 2021-11-15T08:07:25.000Z | metashare/repository/seltests/test_filter.py | zeehio/META-SHARE | b796769629734353a63d98db72c84617f725e544 | [
"BSD-3-Clause"
] | 13 | 2015-03-21T14:08:31.000Z | 2021-05-18T18:47:58.000Z | metashare/repository/seltests/test_filter.py | zeehio/META-SHARE | b796769629734353a63d98db72c84617f725e544 | [
"BSD-3-Clause"
] | 12 | 2015-01-07T02:16:50.000Z | 2021-05-18T08:25:31.000Z | from metashare import settings, test_utils
from metashare.repository.seltests.test_utils import setup_screenshots_folder, \
import_dir, click_and_wait, MetashareSeleniumTestCase
from metashare.settings import DJANGO_URL, DJANGO_BASE, ROOT_PATH
import time
from django.core.management import call_command
from selenium.webdriver.support.select import Select
TESTFIXTURE_XML = '{}/repository/test_fixtures/test_fixtures_for_filtering/'.format(ROOT_PATH)
class FilterTest(MetashareSeleniumTestCase):
def setUp(self):
# make sure the index does not contain any stale entries
call_command('rebuild_index', interactive=False, using=settings.TEST_MODE_NAME)
# load test fixture; status will be set 'published'
test_utils.setup_test_storage()
import_dir(TESTFIXTURE_XML)
super(FilterTest, self).setUp()
self.base_url = '{0}/{1}'.format(DJANGO_URL, DJANGO_BASE)
def tearDown(self):
test_utils.clean_resources_db()
test_utils.clean_storage()
super(FilterTest, self).tearDown()
def test_filter(self):
ss_path = setup_screenshots_folder(
"PNG-metashare.repository.seltests.test_editor.FilterTest",
"test_filter")
driver = self.driver
driver.implicitly_wait(60) # seconds
driver.get(self.base_url)
# TODO remove this workaround when Selenium starts working again as intended
driver.set_window_size(3250, 2600)
# click 'browse'
driver.find_element_by_xpath("//div[@id='header']/ul/li[1]/a").click()
driver.get_screenshot_as_file('{0}/{1}.png'.format(ss_path, time.time()))
self.assertEqual("40 Language Resources (Page 1 of 2)", driver.find_element_by_css_selector("h3").text)
# make sure all filters are available
self.assertEqual("Language", driver.find_element_by_link_text("Language").text)
self.assertEqual("Resource Type", driver.find_element_by_link_text("Resource Type").text)
self.assertEqual("Media Type", driver.find_element_by_link_text("Media Type").text)
self.assertEqual("Availability", driver.find_element_by_link_text("Availability").text)
self.assertEqual("Licence", driver.find_element_by_link_text("Licence").text)
self.assertEqual("Restrictions of Use", driver.find_element_by_link_text("Restrictions of Use").text)
self.assertEqual("Validated", driver.find_element_by_link_text("Validated").text)
self.assertEqual("Foreseen Use", driver.find_element_by_link_text("Foreseen Use").text)
self.assertEqual("Use Is NLP Specific", driver.find_element_by_link_text("Use Is NLP Specific").text)
self.assertEqual("Linguality Type", driver.find_element_by_link_text("Linguality Type").text)
self.assertEqual("Multilinguality Type", driver.find_element_by_link_text("Multilinguality Type").text)
self.assertEqual("Modality Type", driver.find_element_by_link_text("Modality Type").text)
self.assertEqual("MIME Type", driver.find_element_by_link_text("MIME Type").text)
self.assertEqual("Conformance to Standards/Best Practices", driver \
.find_element_by_link_text("Conformance to Standards/Best Practices").text)
self.assertEqual("Domain", driver.find_element_by_link_text("Domain").text)
self.assertEqual("Geographic Coverage", driver.find_element_by_link_text("Geographic Coverage").text)
self.assertEqual("Time Coverage", driver.find_element_by_link_text("Time Coverage").text)
self.assertEqual("Subject", driver.find_element_by_link_text("Subject").text)
self.assertEqual("Language Variety", driver.find_element_by_link_text("Language Variety").text)
# check Language filter
click_and_wait(driver.find_element_by_link_text("Language"))
self.assertEqual("English (15)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[1]").text)
self.assertEqual("Spanish (7)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[2]").text)
self.assertEqual("Modern Greek (1453-) (5)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[3]").text)
self.assertEqual("Italian (4)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[4]").text)
self.assertEqual("French (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[5]").text)
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[19]").text)
# check Language filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Bulgarian (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[6]").text)
self.assertEqual("German (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[7]").text)
self.assertEqual("Polish (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[8]").text)
self.assertEqual("Portuguese (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[9]").text)
self.assertEqual("Aleut (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[10]").text)
self.assertEqual("Arabic (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[11]").text)
self.assertEqual("Asturian; Bable; Leonese; Asturleonese (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[12]").text)
self.assertEqual("Basque (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[13]").text)
self.assertEqual("Chinese (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[14]").text)
self.assertEqual("Estonian (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[15]").text)
self.assertEqual("Greek, Modern (1453-) (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[16]").text)
self.assertEqual("Thai (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[17]").text)
self.assertEqual("Turkish (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[18]").text)
self.assertEqual("less", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[19]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[2]/div[19]").text)
click_and_wait(driver.find_element_by_link_text("Language"))
# check Resource Type filter
click_and_wait(driver.find_element_by_link_text("Resource Type"))
self.assertEqual("Corpus (23)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[4]/div[1]").text)
self.assertEqual("Lexical Conceptual Resource (11)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[4]/div[2]").text)
self.assertEqual("Language Description (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[4]/div[3]").text)
self.assertEqual("Tool Service (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[4]/div[4]").text)
click_and_wait(driver.find_element_by_link_text("Resource Type"))
# check Media Type filter
click_and_wait(driver.find_element_by_link_text("Media Type"))
self.assertEqual("Text (29)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[1]").text)
self.assertEqual("Audio (8)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[2]").text)
self.assertEqual("Image (6)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[3]").text)
self.assertEqual("Textngram (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[4]").text)
self.assertEqual("Textnumerical (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[5]").text)
# check Media Type filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Video (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[6]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[6]/div[7]").text)
click_and_wait(driver.find_element_by_link_text("Media Type"))
# check Availability filter
click_and_wait(driver.find_element_by_link_text("Availability"))
self.assertEqual("Available - Restricted Use (31)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[8]/div[1]").text)
self.assertEqual("Available - Unrestricted Use (9)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[8]/div[2]").text)
click_and_wait(driver.find_element_by_link_text("Availability"))
# check Licence filter
click_and_wait(driver.find_element_by_link_text("Licence"))
self.assertEqual("ELRA_VAR (15)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[1]").text)
self.assertEqual("ELRA_END_USER (13)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[2]").text)
self.assertEqual("Proprietary (6)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[3]").text)
self.assertEqual("ELRA_EVALUATION (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[4]").text)
self.assertEqual("LGPL (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[5]").text)
# check Licence filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("BSD - Style (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[6]").text)
self.assertEqual("CC - BY (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[7]").text)
self.assertEqual("CC - BY - NC - ND (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[8]").text)
self.assertEqual("CC - BY - NC - SA (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[9]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[10]/div[10]").text)
click_and_wait(driver.find_element_by_link_text("Licence"))
# check Restrictions of Use filter
click_and_wait(driver.find_element_by_link_text("Restrictions of Use"))
self.assertEqual("Academic - Non Commercial Use (18)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[12]/div[1]").text)
self.assertEqual("Commercial Use (15)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[12]/div[2]").text)
self.assertEqual("Evaluation Use (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[12]/div[3]").text)
self.assertEqual("Attribution (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[12]/div[4]").text)
self.assertEqual("Share Alike (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[12]/div[5]").text)
click_and_wait(driver.find_element_by_link_text("Restrictions of Use"))
# check Validated filter
click_and_wait(driver.find_element_by_link_text("Validated"))
self.assertEqual("True (6)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[14]/div[1]").text)
click_and_wait(driver.find_element_by_link_text("Validated"))
# check Foreseen Use filter
click_and_wait(driver.find_element_by_link_text("Foreseen Use"))
self.assertEqual("Nlp Applications (8)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[16]/div[1]").text)
self.assertEqual("Human Use (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[16]/div[2]").text)
click_and_wait(driver.find_element_by_link_text("Foreseen Use"))
# check Use Is NLP Specific filter
click_and_wait(driver.find_element_by_link_text("Use Is NLP Specific"))
self.assertEqual("Other (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[1]").text)
self.assertEqual("Contradiction Detection (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[2]").text)
self.assertEqual("Emotion Recognition (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[3]").text)
self.assertEqual("Expression Recognition (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[4]").text)
self.assertEqual("Face Recognition (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[5]").text)
# check Use Is NLP Specific filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Linguistic Research (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[6]").text)
self.assertEqual("Pos Tagging (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[7]").text)
self.assertEqual("Semantic Role Labelling (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[8]").text)
self.assertEqual("Speech Synthesis (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[9]").text)
self.assertEqual("Spoken Dialogue Systems (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[10]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[18]/div[11]").text)
click_and_wait(driver.find_element_by_link_text("Use Is NLP Specific"))
# check Linguality Type filter
click_and_wait(driver.find_element_by_link_text("Linguality Type"))
self.assertEqual("Monolingual (31)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[20]/div[1]").text)
self.assertEqual("Bilingual (4)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[20]/div[2]").text)
click_and_wait(driver.find_element_by_link_text("Linguality Type"))
# check Multilinguality Type filter
click_and_wait(driver.find_element_by_link_text("Multilinguality Type"))
self.assertEqual("Comparable (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[22]/div[1]").text)
self.assertEqual("Other (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[22]/div[2]").text)
self.assertEqual("Parallel (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[22]/div[3]").text)
click_and_wait(driver.find_element_by_link_text("Multilinguality Type"))
# check Modality Type filter
click_and_wait(driver.find_element_by_link_text("Modality Type"))
self.assertEqual("Written Language (8)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[1]").text)
self.assertEqual("Facial Expression (5)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[2]").text)
self.assertEqual("Combination Of Modalities (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[3]").text)
self.assertEqual("Spoken Language (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[4]").text)
self.assertEqual("Voice (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[5]").text)
# check Modality Type filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Body Gesture (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[6]").text)
self.assertEqual("Other (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[7]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[24]/div[8]").text)
click_and_wait(driver.find_element_by_link_text("Modality Type"))
# check MIME Type filter
click_and_wait(driver.find_element_by_link_text("MIME Type"))
self.assertEqual("Plain text (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[1]").text)
self.assertEqual("Audio/ PCMA (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[2]").text)
self.assertEqual("Text/plain (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[3]").text)
self.assertEqual("Text/txt (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[4]").text)
self.assertEqual("Text/xml (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[5]").text)
# check MIME Type filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Txt/plain (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[6]").text)
self.assertEqual("Txt/xml (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[7]").text)
self.assertEqual("Video/mpeg (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[8]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[26]/div[9]").text)
click_and_wait(driver.find_element_by_link_text("MIME Type"))
# check Conformance to Standards/Best Practices filter
click_and_wait(driver.find_element_by_link_text("Conformance to Standards/Best Practices"))
self.assertEqual("Other (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[1]").text)
self.assertEqual("EAGLES (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[2]").text)
self.assertEqual("TEI (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[3]").text)
self.assertEqual("XCES (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[4]").text)
self.assertEqual("BLM (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[5]").text)
# check Conformance to Standards/Best Practices filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("EML (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[6]").text)
self.assertEqual("MUMIN (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[7]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[28]/div[8]").text)
click_and_wait(driver.find_element_by_link_text("Conformance to Standards/Best Practices"))
# check Domain filter
click_and_wait(driver.find_element_by_link_text("Domain"))
self.assertEqual("General (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[1]").text)
self.assertEqual("Science (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[2]").text)
self.assertEqual("EU parliamentary sessions (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[3]").text)
self.assertEqual("Business (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[4]").text)
self.assertEqual("Fiction (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[5]").text)
# check Domain filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Geography (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[6]").text)
self.assertEqual("Health (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[7]").text)
self.assertEqual("History (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[8]").text)
self.assertEqual("Humanities (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[9]").text)
self.assertEqual("Law_politics (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[10]").text)
self.assertEqual("Leisure (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[11]").text)
self.assertEqual("Society (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[12]").text)
self.assertEqual("Travel (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[13]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[30]/div[14]").text)
click_and_wait(driver.find_element_by_link_text("Domain"))
# check Geographic Coverage filter
click_and_wait(driver.find_element_by_link_text("Geographic Coverage"))
self.assertEqual("European Union (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[32]/div[1]").text)
self.assertEqual("Thrace (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[32]/div[2]").text)
click_and_wait(driver.find_element_by_link_text("Geographic Coverage"))
# check Time Coverage filter
click_and_wait(driver.find_element_by_link_text("Time Coverage"))
self.assertEqual("1958-2006 (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[34]/div[1]").text)
self.assertEqual("2003-2011 (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[34]/div[2]").text)
self.assertEqual("2004-2011 (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[34]/div[3]").text)
self.assertEqual("After 1990 (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[34]/div[4]").text)
click_and_wait(driver.find_element_by_link_text("Time Coverage"))
# check Subject filter
click_and_wait(driver.find_element_by_link_text("Subject"))
self.assertEqual("News (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[36]/div[1]").text)
click_and_wait(driver.find_element_by_link_text("Subject"))
# check Language Variety filter
click_and_wait(driver.find_element_by_link_text("Language Variety"))
self.assertEqual("Castilian (7)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[38]/div[1]").text)
click_and_wait(driver.find_element_by_link_text("Language Variety"))
# test sorting:
# default sorting is by resource name, ascending
self.assertEqual("Resource Name A-Z", driver.find_element_by_xpath(
# first option is selected by default
"//select[@name='ordering']/option[1]").text)
self.assertEqual("AURORA-5", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/a[1]").text)
# now sort by Resource name descending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Resource Name Z-A")
self.assertEqual("VERBA Polytechnic and Plurilingual Terminological Database - S-AA Anatomy", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/a[1]").text)
# now sort by resource type ascending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Resource Type A-Z")
self.assertEqual("Corpus", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/img[1]").get_attribute("title"))
# now sort by resource type descending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Resource Type Z-A")
self.assertEqual("Tool/Service", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/img[1]").get_attribute("title"))
# now sort by media type ascending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Media Type A-Z")
self.assertEqual("audio", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/img[2]").get_attribute("title"))
# now sort by media type descending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Media Type Z-A")
self.assertEqual("text", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/img[2]").get_attribute("title"))
# now sort by language ascending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Language Name A-Z")
self.assertEqual("Aleut", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/ul/li[1]").text)
# now sort by language descending
Select(driver.find_element_by_name("ordering")).select_by_visible_text("Language Name Z-A")
self.assertEqual("Turkish", driver.find_element_by_xpath(
"//div[@class='results']/div[1]/ul/li[1]").text)
driver.get_screenshot_as_file('{0}/{1}.png'.format(ss_path, time.time()))
# test filter application:
# filter by language English
driver.find_element_by_link_text("Language").click()
driver.find_element_by_link_text("English").click()
self.assertEqual("15 Language Resources", driver.find_element_by_css_selector("h3").text)
# additionally filter by license
driver.find_element_by_link_text("Licence").click()
driver.find_element_by_link_text("ELRA_VAR").click()
self.assertEqual("6 Language Resources", driver.find_element_by_css_selector("h3").text)
# additionally filter by media type
driver.find_element_by_link_text("Media Type").click()
driver.find_element_by_link_text("Text").click()
self.assertEqual("5 Language Resources", driver.find_element_by_css_selector("h3").text)
# additionally filter by restriction of use
driver.find_element_by_link_text("Restrictions of Use").click()
driver.find_element_by_link_text("Commercial Use").click()
self.assertEqual("5 Language Resources", driver.find_element_by_css_selector("h3").text)
driver.get_screenshot_as_file('{0}/{1}.png'.format(ss_path, time.time()))
# remove language filter
driver.find_element_by_link_text("English").click()
self.assertEqual("10 Language Resources", driver.find_element_by_css_selector("h3").text)
# remove license filter
driver.find_element_by_link_text("ELRA_VAR").click()
self.assertEqual("10 Language Resources", driver.find_element_by_css_selector("h3").text)
# remove media type filter
driver.find_element_by_link_text("Text").click()
self.assertEqual("15 Language Resources", driver.find_element_by_css_selector("h3").text)
# remove restiriction of use filter
driver.find_element_by_link_text("Commercial Use").click()
self.assertEqual("40 Language Resources (Page 1 of 2)", driver.find_element_by_css_selector("h3").text)
driver.get_screenshot_as_file('{0}/{1}.png'.format(ss_path, time.time()))
# Test sub filters
# Test all sub filter of Resource Type / Corpus are available
click_and_wait(driver.find_element_by_link_text("Resource Type"))
click_and_wait(driver.find_element_by_link_text("Corpus"))
self.assertEqual("Annotation Type", driver.find_element_by_link_text("Annotation Type").text)
self.assertEqual("Annotation Format", driver.find_element_by_link_text("Annotation Format").text)
# check content of Annotation Type filter
click_and_wait(driver.find_element_by_link_text("Annotation Type"))
self.assertEqual("Segmentation (4)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Lemmatization (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Modality Annotation - Body Movements (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
self.assertEqual("Morphosyntactic Annotation - B Pos Tagging (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[4]").text)
self.assertEqual("Morphosyntactic Annotation - Pos Tagging (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[5]").text)
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[16]").text)
# check Corpus filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Other (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[6]").text)
self.assertEqual("Semantic Annotation - Named Entities (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[7]").text)
self.assertEqual("Structural Annotation (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[8]").text)
self.assertEqual("Alignment (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[9]").text)
self.assertEqual("Modality Annotation - Facial Expressions (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[10]").text)
self.assertEqual("Modality Annotation - Hand Arm Gestures (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[11]").text)
self.assertEqual("Speech Annotation (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[12]").text)
self.assertEqual("Speech Annotation - Orthographic Transcription (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[13]").text)
self.assertEqual("Speech Annotation - Phonetic Transcription (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[14]").text)
self.assertEqual("Syntactic Annotation - Shallow Parsing (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[15]").text)
self.assertEqual("less", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[16]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[16]").text)
# Close Annotation Type filter
click_and_wait(driver.find_element_by_link_text("Annotation Type"))
# check content of Annotation Format filter
click_and_wait(driver.find_element_by_link_text("Annotation Format"))
self.assertEqual("Text/xml (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("TIPSTER (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
self.assertEqual("XML (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[3]").text)
self.assertEqual("Eaf (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[4]").text)
self.assertEqual("Trs (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[5]").text)
# Close Annotation Type filter
click_and_wait(driver.find_element_by_link_text("Annotation Format"))
# remove Resource Type filter
click_and_wait(driver.find_element_by_link_text("Corpus"))
# Test all sub filter of Resource Type / Lexical Conceptual Resource are available
click_and_wait(driver.find_element_by_link_text("Resource Type"))
click_and_wait(driver.find_element_by_link_text("Lexical Conceptual Resource"))
self.assertEqual("Lexical/Conceptual Resource Type", driver.find_element_by_link_text("Lexical/Conceptual Resource Type").text)
self.assertEqual("Encoding Level", driver.find_element_by_link_text("Encoding Level").text)
self.assertEqual("Linguistic Information", driver.find_element_by_link_text("Linguistic Information").text)
# check content of Lexical/Conceptual Resource Type filter
click_and_wait(driver.find_element_by_link_text("Lexical/Conceptual Resource Type"))
self.assertEqual("Lexicon (6)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Terminological Resource (4)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Computational Lexicon (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
# Close Lexical/Conceptual Resource Type filter
click_and_wait(driver.find_element_by_link_text("Lexical/Conceptual Resource Type"))
# check content of Encoding Level filter
click_and_wait(driver.find_element_by_link_text("Encoding Level"))
self.assertEqual("Morphology (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("Semantics (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
self.assertEqual("Syntax (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[3]").text)
# Close Encoding Level filter
click_and_wait(driver.find_element_by_link_text("Encoding Level"))
# check content of Linguistic Information filter
click_and_wait(driver.find_element_by_link_text("Linguistic Information"))
self.assertEqual("Definition/gloss (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[1]").text)
self.assertEqual("Part Of Speech (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[2]").text)
self.assertEqual("Semantics - Event Type (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[3]").text)
self.assertEqual("Semantics - Semantic Roles (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[4]").text)
# Close Linguistic Information filter
click_and_wait(driver.find_element_by_link_text("Linguistic Information"))
# remove Resource Type filter
click_and_wait(driver.find_element_by_link_text("Lexical Conceptual Resource"))
# Test all sub filter of Resource Type / Language Description are available
click_and_wait(driver.find_element_by_link_text("Resource Type"))
click_and_wait(driver.find_element_by_link_text("Language Description"))
self.assertEqual("Language Description Type", driver.find_element_by_link_text("Language Description Type").text)
self.assertEqual("Encoding Level", driver.find_element_by_link_text("Encoding Level").text)
self.assertEqual("Grammatical Phenomena Coverage", driver.find_element_by_link_text("Grammatical Phenomena Coverage").text)
# check content of Language Description Type filter
click_and_wait(driver.find_element_by_link_text("Language Description Type"))
self.assertEqual("Grammar (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Other (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
# Close Language Description Type filter
click_and_wait(driver.find_element_by_link_text("Language Description Type"))
# check content of Encoding Level filter
click_and_wait(driver.find_element_by_link_text("Encoding Level"))
self.assertEqual("Phonetics (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("Syntax (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
self.assertEqual("Morphology (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[3]").text)
self.assertEqual("Other (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[4]").text)
self.assertEqual("Semantics (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[5]").text)
# Close Encoding Level filter
click_and_wait(driver.find_element_by_link_text("Encoding Level"))
# check content of Grammatical Phenomena Coverage filter
click_and_wait(driver.find_element_by_link_text("Grammatical Phenomena Coverage"))
self.assertEqual("Clause Structure (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[1]").text)
self.assertEqual("Coordination (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[2]").text)
self.assertEqual("Anaphora (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[3]").text)
# Close Grammatical Phenomena Coverage filter
click_and_wait(driver.find_element_by_link_text("Grammatical Phenomena Coverage"))
# remove Resource Type filter
click_and_wait(driver.find_element_by_link_text("Language Description"))
# Test all sub filter of Resource Type / Tool Service are available
click_and_wait(driver.find_element_by_link_text("Resource Type"))
click_and_wait(driver.find_element_by_link_text("Tool Service"))
self.assertEqual("Tool/Service Type", driver.find_element_by_link_text("Tool/Service Type").text)
self.assertEqual("Tool/Service Subtype", driver.find_element_by_link_text("Tool/Service Subtype").text)
self.assertEqual("Language Dependent", driver.find_element_by_link_text("Language Dependent").text)
self.assertEqual("InputInfo/OutputInfo Resource Type", driver.find_element_by_link_text("InputInfo/OutputInfo Resource Type").text)
self.assertEqual("InputInfo/OutputInfo Media Type", driver.find_element_by_link_text("InputInfo/OutputInfo Media Type").text)
self.assertEqual("Annotation Type", driver.find_element_by_link_text("Annotation Type").text)
self.assertEqual("Annotation Format", driver.find_element_by_link_text("Annotation Format").text)
self.assertEqual("Evaluated", driver.find_element_by_link_text("Evaluated").text)
# check content of Tool/Service Type filter
click_and_wait(driver.find_element_by_link_text("Tool/Service Type"))
self.assertEqual("Platform (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Service (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Tool (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
# Close Tool/Service Type filter
click_and_wait(driver.find_element_by_link_text("Tool/Service Type"))
# check content of Tool/Service Subtype filter
click_and_wait(driver.find_element_by_link_text("Tool/Service Subtype"))
self.assertEqual("Text- To- Speech server (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("Soap-service (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
# Close Tool/Service Subtype filter
click_and_wait(driver.find_element_by_link_text("Tool/Service Subtype"))
# check content of Language Dependent filter
click_and_wait(driver.find_element_by_link_text("Language Dependent"))
self.assertEqual("No (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[1]").text)
self.assertEqual("Yes (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[2]").text)
# Close Language Dependent filter
click_and_wait(driver.find_element_by_link_text("Language Dependent"))
# check content of InputInfo/OutputInfo Resource Type filter
click_and_wait(driver.find_element_by_link_text("InputInfo/OutputInfo Resource Type"))
self.assertEqual("Corpus (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[9]/div[1]").text)
self.assertEqual("Language Description (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[9]/div[2]").text)
self.assertEqual("Lexical Conceptual Resource (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[9]/div[3]").text)
# Close InputInfo/OutputInfo Resource Type filter
click_and_wait(driver.find_element_by_link_text("InputInfo/OutputInfo Resource Type"))
# check content of InputInfo/OutputInfo Media Type filter
click_and_wait(driver.find_element_by_link_text("InputInfo/OutputInfo Media Type"))
self.assertEqual("Text (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[11]/div[1]").text)
self.assertEqual("Audio (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[11]/div[2]").text)
# Close InputInfo/OutputInfo Media Type filter
click_and_wait(driver.find_element_by_link_text("InputInfo/OutputInfo Media Type"))
# check content of Annotation Type filter
click_and_wait(driver.find_element_by_link_text("Annotation Type"))
self.assertEqual("Morphosyntactic Annotation - Pos Tagging (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[13]/div[1]").text)
# Close Annotation Type filter
click_and_wait(driver.find_element_by_link_text("Annotation Type"))
# check content of Annotation Format filter
click_and_wait(driver.find_element_by_link_text("Annotation Format"))
self.assertEqual("Plain text (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[15]/div[1]").text)
self.assertEqual("Tab separated (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[15]/div[2]").text)
# Close Annotation Format filter
click_and_wait(driver.find_element_by_link_text("Annotation Format"))
# check content of Evaluated filter
click_and_wait(driver.find_element_by_link_text("Evaluated"))
self.assertEqual("Yes (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[17]/div[1]").text)
# Close Evaluated filter
click_and_wait(driver.find_element_by_link_text("Evaluated"))
# remove Resource Type filter
click_and_wait(driver.find_element_by_link_text("Tool Service"))
# Test all sub filter of Media Type / Text are available
click_and_wait(driver.find_element_by_link_text("Media Type"))
click_and_wait(driver.find_element_by_link_text("Text"))
self.assertEqual("Text Genre", driver.find_element_by_link_text("Text Genre").text)
self.assertEqual("Text Type", driver.find_element_by_link_text("Text Type").text)
self.assertEqual("Register", driver.find_element_by_link_text("Register").text)
self.assertEqual("Type of Text Numerical Content", driver.find_element_by_link_text("Type of Text Numerical Content").text)
# check content of Text Genre filter
click_and_wait(driver.find_element_by_link_text("Text Genre"))
self.assertEqual("Advertising (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Discussion (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Feature (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
self.assertEqual("Fiction (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[4]").text)
self.assertEqual("Information (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[5]").text)
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[10]").text)
# check Text Genre filter more/less
click_and_wait(driver.find_element_by_link_text("more"))
self.assertEqual("Interviews (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[6]").text)
self.assertEqual("Non-fiction (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[7]").text)
self.assertEqual("Official (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[8]").text)
self.assertEqual("Private (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[9]").text)
self.assertEqual("less", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[10]").text)
click_and_wait(driver.find_element_by_link_text("less"))
self.assertEqual("more", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[10]").text)
# Close Text Genre filter
click_and_wait(driver.find_element_by_link_text("Text Genre"))
# check content of Text Type filter
click_and_wait(driver.find_element_by_link_text("Text Type"))
self.assertEqual("Fairy tales (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("Fiction (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
self.assertEqual("Poems (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[3]").text)
self.assertEqual("Quasi-spoken (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[4]").text)
# Close Text Type filter
click_and_wait(driver.find_element_by_link_text("Text Type"))
# check content of Register filter
# with xpath because Register send to the Account Registration
click_and_wait(driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[6]/a"))
self.assertEqual("Formal (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[1]").text)
# Close Register filter
click_and_wait(driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[6]/a"))
# check content of Type of Text Numerical Content filter
click_and_wait(driver.find_element_by_link_text("Type of Text Numerical Content"))
self.assertEqual("Coordinates (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[9]/div[1]").text)
# Close Type of Text Numerical Content filter
click_and_wait(driver.find_element_by_link_text("Type of Text Numerical Content"))
click_and_wait(driver.find_element_by_link_text("Text"))
# Test all sub filter of Media Type / Audio are available
click_and_wait(driver.find_element_by_link_text("Media Type"))
click_and_wait(driver.find_element_by_link_text("Audio"))
self.assertEqual("Audio Genre", driver.find_element_by_link_text("Audio Genre").text)
self.assertEqual("Speech Genre", driver.find_element_by_link_text("Speech Genre").text)
self.assertEqual("Speech Items", driver.find_element_by_link_text("Speech Items").text)
self.assertEqual("Naturality", driver.find_element_by_link_text("Naturality").text)
self.assertEqual("Conversational Type", driver.find_element_by_link_text("Conversational Type").text)
self.assertEqual("Scenario Type", driver.find_element_by_link_text("Scenario Type").text)
# check content of Audio Genre filter
click_and_wait(driver.find_element_by_link_text("Audio Genre"))
self.assertEqual("Speech (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
# Close Audio Genre filter
click_and_wait(driver.find_element_by_link_text("Audio Genre"))
# check content of Speech Genre filter
click_and_wait(driver.find_element_by_link_text("Speech Genre"))
self.assertEqual("Interview (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
# Close Speech Genre filter
click_and_wait(driver.find_element_by_link_text("Speech Genre"))
# check content of Speech Items filter
click_and_wait(driver.find_element_by_link_text("Speech Items"))
self.assertEqual("Free Speech (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[1]").text)
# Close Speech Items filter
click_and_wait(driver.find_element_by_link_text("Speech Items"))
# check content of Naturality filter
click_and_wait(driver.find_element_by_link_text("Naturality"))
self.assertEqual("Natural (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[9]/div[1]").text)
# Close Naturality filter
click_and_wait(driver.find_element_by_link_text("Naturality"))
# check content of Conversational Type filter
click_and_wait(driver.find_element_by_link_text("Conversational Type"))
self.assertEqual("Dialogue (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[11]/div[1]").text)
# Close Conversational Type filter
click_and_wait(driver.find_element_by_link_text("Conversational Type"))
# check content of Scenario Type filter
click_and_wait(driver.find_element_by_link_text("Scenario Type"))
self.assertEqual("Other (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[13]/div[1]").text)
# Close Scenario Type filter
click_and_wait(driver.find_element_by_link_text("Scenario Type"))
# remove Media Type filter
click_and_wait(driver.find_element_by_link_text("Audio"))
# Test all sub filter of Media Type / Image are available
click_and_wait(driver.find_element_by_link_text("Media Type"))
click_and_wait(driver.find_element_by_link_text("Image"))
self.assertEqual("Image Genre", driver.find_element_by_link_text("Image Genre").text)
self.assertEqual("Type of Image Content", driver.find_element_by_link_text("Type of Image Content").text)
# check content of Image Genre filter
click_and_wait(driver.find_element_by_link_text("Image Genre"))
self.assertEqual("Photos (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Paintings (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Testimage (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
# Close Image Genre filter
click_and_wait(driver.find_element_by_link_text("Image Genre"))
# check content of Type of Image Content filter
click_and_wait(driver.find_element_by_link_text("Type of Image Content"))
self.assertEqual("Nature (3)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("Cars (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
self.assertEqual("Cartoons (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[3]").text)
self.assertEqual("Face (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[4]").text)
# Close Type of Image Content filter
click_and_wait(driver.find_element_by_link_text("Type of Image Content"))
# remove Media Type filter
click_and_wait(driver.find_element_by_link_text("Image"))
# Test all sub filter of Media Type / Textngram are available
click_and_wait(driver.find_element_by_link_text("Media Type"))
click_and_wait(driver.find_element_by_link_text("Textngram"))
self.assertEqual("Base Item", driver.find_element_by_link_text("Base Item").text)
self.assertEqual("Order", driver.find_element_by_link_text("Order").text)
# check content of Base Item filter
click_and_wait(driver.find_element_by_link_text("Base Item"))
self.assertEqual("Letter (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Syllable, Letter (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Word (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
# Close Base Item filter
click_and_wait(driver.find_element_by_link_text("Base Item"))
# check content of Order filter
click_and_wait(driver.find_element_by_link_text("Order"))
self.assertEqual("1 (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
self.assertEqual("2 (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[2]").text)
# Close Order filter
click_and_wait(driver.find_element_by_link_text("Order"))
# remove Media Type filter
click_and_wait(driver.find_element_by_link_text("Textngram"))
# Test all sub filter of Media Type / Textnumerical are available
click_and_wait(driver.find_element_by_link_text("Media Type"))
click_and_wait(driver.find_element_by_link_text("Textnumerical"))
self.assertEqual("Type of Text Numerical Content", driver.find_element_by_link_text("Type of Text Numerical Content").text)
# check content of Type of Text Numerical Content filter
click_and_wait(driver.find_element_by_link_text("Type of Text Numerical Content"))
self.assertEqual("Coordinates (2)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
self.assertEqual("Temperature (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[2]").text)
self.assertEqual("Testcontent (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[3]").text)
# Close Type of Text Numerical Content filter
click_and_wait(driver.find_element_by_link_text("Type of Text Numerical Content"))
# remove Media Type filter
click_and_wait(driver.find_element_by_link_text("Textnumerical"))
# Test all sub filter of Media Type / Video are available
click_and_wait(driver.find_element_by_link_text("Media Type"))
click_and_wait(driver.find_element_by_link_text("more"))
click_and_wait(driver.find_element_by_link_text("Video"))
self.assertEqual("Video Genre", driver.find_element_by_link_text("Video Genre").text)
self.assertEqual("Type of Video Content", driver.find_element_by_link_text("Type of Video Content").text)
self.assertEqual("Naturality", driver.find_element_by_link_text("Naturality").text)
self.assertEqual("Conversational Type", driver.find_element_by_link_text("Conversational Type").text)
self.assertEqual("Scenario Type", driver.find_element_by_link_text("Scenario Type").text)
# check content of Video Genre filter
click_and_wait(driver.find_element_by_link_text("Video Genre"))
self.assertEqual("Interview (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[3]/div[1]").text)
# Close Video Genre filter
click_and_wait(driver.find_element_by_link_text("Video Genre"))
# check content of Type of Video Content filter
click_and_wait(driver.find_element_by_link_text("Type of Video Content"))
self.assertEqual("11 face to face TV interviews (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[5]/div[1]").text)
# Close Type of Video Content filter
click_and_wait(driver.find_element_by_link_text("Type of Video Content"))
# check content of Naturality filter
click_and_wait(driver.find_element_by_link_text("Naturality"))
self.assertEqual("Natural (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[7]/div[1]").text)
# Close Naturality filter
click_and_wait(driver.find_element_by_link_text("Naturality"))
# check content of Conversational Type filter
click_and_wait(driver.find_element_by_link_text("Conversational Type"))
self.assertEqual("Dialogue (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[9]/div[1]").text)
# Close Conversational Type filter
click_and_wait(driver.find_element_by_link_text("Conversational Type"))
# check content of Scenario Type filter
click_and_wait(driver.find_element_by_link_text("Scenario Type"))
self.assertEqual("Other (1)", driver.find_element_by_xpath(
"//div[@id='searchFilters']/div[@class='filter']/div[11]/div[1]").text)
# Close Scenario Type filter
click_and_wait(driver.find_element_by_link_text("Scenario Type"))
# remove Media Type filter
click_and_wait(driver.find_element_by_link_text("Video"))
| 67.708559 | 140 | 0.665909 | 8,182 | 62,495 | 4.833904 | 0.05341 | 0.11934 | 0.202877 | 0.226745 | 0.870345 | 0.811838 | 0.801598 | 0.779879 | 0.759602 | 0.754166 | 0 | 0.01715 | 0.17987 | 62,495 | 922 | 141 | 67.781996 | 0.754517 | 0.087015 | 0 | 0.461119 | 0 | 0.140518 | 0.348599 | 0.20703 | 0 | 0 | 0 | 0.001085 | 0.396999 | 1 | 0.004093 | false | 0 | 0.010914 | 0 | 0.016371 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
d523c9bdb70affc88ab5ac209a081bb55a104475 | 317,852 | py | Python | parser/team06/parsetab.py | gstavosanchez/tytus | 5a0e72053cc3a1917ab047b3d9fc39d8f800ea39 | [
"MIT"
] | null | null | null | parser/team06/parsetab.py | gstavosanchez/tytus | 5a0e72053cc3a1917ab047b3d9fc39d8f800ea39 | [
"MIT"
] | null | null | null | parser/team06/parsetab.py | gstavosanchez/tytus | 5a0e72053cc3a1917ab047b3d9fc39d8f800ea39 | [
"MIT"
] | null | null | null |
# parsetab.py
# This file is automatically generated. Do not edit.
# pylint: disable=W,C,R
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'leftTYPECASTrightUMINUSrightUNOTleftMASMENOSleftPOTENCIAleftPORDIVRESIDUOleftANDORSIMBOLOOR2SIMBOLOORSIMBOLOAND2leftDESPLAZAMIENTOIZQUIERDADESPLAZAMIENTODERECHAABS ACOS ACOSD ACOSH ADD ALL ALTER AND ANY AS ASC ASIN ASIND ASINH ATAN ATAN2 ATANH AUTO_INCREMENT AVG BEGIN BETWEEN BIGINT BOOLEAN BOTH BY CADENA CASE CBRT CEIL CEILING CHAR CHARACTER CHECK COLOCHO COLUMN COLUMNS COMA CONCAT CONSTRAINT CONT CONVERT CORCHETEDER CORCHETEIZQ COS COSD COSH COT COTD CREATE CURRENT_USER DATABASE DATABASES DATE DAY DECIMAL DECIMALTOKEN DECLARE DECODE DEFAULT DEGREES DELETE DESC DESPLAZAMIENTODERECHA DESPLAZAMIENTOIZQUIERDA DIFERENTE DISTINCT DIV DIV DOSPUNTOS DOUBLE DROP ELSE ENCODE END ENTERO ENUM ENUM ESCAPE ETIQUETA EXCEPT EXISTS EXP FACTORIAL FALSE FIRST FLOOR FOR FOREIGN FROM FULL FUNCTION GCD GET_BYTE GREATEST GROUP HAVING HOUR ID IF IGUAL IGUALIGUAL ILIKE IN INHERITS INNER INSERT INTEGER INTERSECT INTERVAL INTO IS ISNULL JOIN KEY LAST LCM LEADING LEAST LEFT LENGTH LIKE LIMIT LN LOG LOG10 MAS MAX MAYOR MAYORIGUAL MD5 MENOR MENORIGUAL MENOS MIN MINUTE MIN_SCALE MOD MODE MONEY MONTH NATURAL NOT NOTEQUAL NOTNULL NULL NULLS NUMERAL NUMERIC OF OFFSET ON ONLY OR ORDER OUTER OWNER PARENTESISDERECHA PARENTESISIZQUIERDA PI POR POTENCIA POWER PRECISION PRIMARY PUNTO PUNTOYCOMA RADIANS RANDOM REAL REFERENCES RENAME REPLACE RESIDUO RETURNING RETURNS RIGHT ROUND SCALE SECOND SELECT SESSION_USER SET SETSEED SET_BYTE SHA256 SHOW SIGN SIMBOLOAND SIMBOLOAND2 SIMBOLOOR SIMBOLOOR2 SIN SIND SINH SMALLINT SOME SQRT SUBSTR SUBSTRING SUM SYMMETRIC TABLE TABLES TAN TAND TANH TEXT THEN TIME TIMESTAMP TO TRAILING TRIM TRIM_SCALE TRUC TRUE TYPE TYPECAST UNION UNIQUE UNKNOWN UPDATE UPPER USING VALUES VARCHAR VARYING VIEW WHEN WHERE WIDTH_BUCKET YEARinicio : queriesqueries : queries queryqueries : queryquery : mostrarBD\n | crearBD\n | alterBD\n | dropBD\n | operacion\n | insertinBD\n | updateinBD\n | deleteinBD\n | createTable\n | inheritsBD\n | dropTable\n | alterTable\n | variantesAt\n | contAdd\n | contDrop\n | contAlter\n | listaid\n | tipoAlter\n \n | selectData\n crearBD : CREATE DATABASE ID PUNTOYCOMAcrearBD : CREATE OR REPLACE DATABASE ID PUNTOYCOMAcrearBD : CREATE OR REPLACE DATABASE ID parametrosCrearBD PUNTOYCOMAcrearBD : CREATE DATABASE ID parametrosCrearBD PUNTOYCOMAparametrosCrearBD : parametrosCrearBD parametroCrearBDparametrosCrearBD : parametroCrearBDparametroCrearBD : OWNER IGUAL final\n | MODE IGUAL final\n mostrarBD : SHOW DATABASES PUNTOYCOMAalterBD : ALTER DATABASE ID RENAME TO ID PUNTOYCOMAalterBD : ALTER DATABASE ID OWNER TO parametroAlterUser PUNTOYCOMAparametroAlterUser : CURRENT_USER\n | SESSION_USER\n | final\n dropTable : DROP TABLE ID PUNTOYCOMA\n alterTable : ALTER TABLE ID variantesAt PUNTOYCOMA\n\n \n variantesAt : ADD contAdd\n | ALTER listaContAlter\n | DROP contDrop\n \n listaContAlter : listaContAlter COMA contAlter \n \n listaContAlter : contAlter\n \n contAlter : COLUMN ID SET NOT NULL \n | COLUMN ID TYPE tipo\n \n contAdd : COLUMN ID tipo \n | CHECK PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | FOREIGN KEY PARENTESISIZQUIERDA ID PARENTESISDERECHA REFERENCES ID\n | CONSTRAINT ID UNIQUE PARENTESISIZQUIERDA listaid PARENTESISDERECHA\n \n contDrop : COLUMN ID \n | CONSTRAINT ID\n \n listaid : listaid COMA ID\n \n listaid : ID\n \n tipoAlter : ADD \n | DROP\n dropBD : DROP DATABASE ID PUNTOYCOMAdropBD : DROP DATABASE IF EXISTS ID PUNTOYCOMAoperacion : operacion MAS operacion\n | operacion MENOS operacion\n | operacion POR operacion\n | operacion DIV operacion\n | operacion RESIDUO operacion\n\n\n | operacion POTENCIA operacion\n | operacion AND operacion\n | operacion OR operacion\n | operacion SIMBOLOOR2 operacion\n | operacion SIMBOLOOR operacion\n\n\n | operacion SIMBOLOAND2 operacion\n | operacion DESPLAZAMIENTOIZQUIERDA operacion\n | operacion DESPLAZAMIENTODERECHA operacion\n | operacion IGUAL operacion\n | operacion IGUALIGUAL operacion\n\n\n | operacion NOTEQUAL operacion\n | operacion MAYORIGUAL operacion\n | operacion MENORIGUAL operacion\n | operacion MAYOR operacion\n | operacion MENOR operacion\n | operacion DIFERENTE operacion\n | PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n \n operacion : MENOS ENTERO %prec UMINUSoperacion : NOT operacion %prec UNOToperacion : funcionBasicaoperacion : finalfuncionBasica : ABS PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | CBRT PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | CEIL PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | CEILING PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | DEGREES PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | DIV PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | EXP PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | FACTORIAL PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | FLOOR PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | GCD PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | LCM PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | LN PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | LOG PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | LOG10 PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n \n\n\n | MIN_SCALE PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | MOD PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | POWER PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | RADIANS PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SCALE ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SIGN ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SQRT ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | TRIM_SCALE ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | TRUC ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | WIDTH_BUCKET PARENTESISIZQUIERDA operacion COMA operacion COMA operacion COMA operacion PARENTESISDERECHA\n | RANDOM PARENTESISIZQUIERDA PARENTESISDERECHA\n | SETSEED PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ACOS PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n\n\n\n | ACOSD PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ASIN PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ASIND PARENTESISIZQUIERDA operacion PARENTESISDERECHA \n | ATAN PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ATAN2 PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | COS PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n\t\t\t | COSD PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | COT PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | COTD PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SIN PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SIND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | TAN PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | TAND PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SINH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n\n\n\n | COSH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | TANH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ASINH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ACOSH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | ATANH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | LENGTH PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | TRIM PARENTESISIZQUIERDA opcionTrim operacion FROM operacion PARENTESISDERECHA\n | GET_BYTE PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | MD5 PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SET_BYTE PARENTESISIZQUIERDA operacion COMA operacion COMA operacion PARENTESISDERECHA\n | SHA256 PARENTESISIZQUIERDA operacion PARENTESISDERECHA \n | SUBSTR PARENTESISIZQUIERDA operacion COMA operacion COMA operacion PARENTESISDERECHA\n | CONVERT PARENTESISIZQUIERDA operacion COMA operacion COMA operacion PARENTESISDERECHA\n | ENCODE PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | DECODE PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA\n | AVG PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n | SUM PARENTESISIZQUIERDA operacion PARENTESISDERECHA\n funcionBasica : SUBSTRING PARENTESISIZQUIERDA operacion FROM operacion FOR operacion PARENTESISDERECHAfuncionBasica : SUBSTRING PARENTESISIZQUIERDA operacion FROM operacion PARENTESISDERECHAfuncionBasica : SUBSTRING PARENTESISIZQUIERDA operacion FOR operacion PARENTESISDERECHA opcionTrim : LEADING\n | TRAILING\n | BOTH\n final : DECIMAL\n | ENTEROfinal : IDfinal : ID PUNTO IDfinal : CADENAinsertinBD : INSERT INTO ID VALUES PARENTESISIZQUIERDA listaParam PARENTESISDERECHA PUNTOYCOMAinsertinBD : INSERT INTO ID PARENTESISIZQUIERDA listaParam PARENTESISDERECHA VALUES PARENTESISIZQUIERDA listaParam PARENTESISDERECHA PUNTOYCOMAlistaParam : listaParam COMA final\n listaParam : final\n updateinBD : UPDATE ID SET asignaciones WHERE asignaciones PUNTOYCOMAasignaciones : asignaciones COMA asigna\n asignaciones : asigna\n asigna : operaciondeleteinBD : DELETE FROM ID PUNTOYCOMAdeleteinBD : DELETE FROM ID WHERE operacion PUNTOYCOMAcreateTable : CREATE TABLE ID PARENTESISIZQUIERDA creaColumnas PARENTESISDERECHA PUNTOYCOMAinheritsBD : CREATE TABLE ID PARENTESISIZQUIERDA creaColumnas PARENTESISDERECHA INHERITS PARENTESISIZQUIERDA ID PARENTESISDERECHA PUNTOYCOMAcreaColumnas : creaColumnas COMA Columna \n creaColumnas : Columna \n Columna : ID tipo \n | ID tipo paramOpcional\n | constraintinColumn \n | checkinColumn\n | uniqueinColumn\n | primaryKey\n | foreignKey\n paramOpcional : paramOpcional paramopc\n paramOpcional : paramopc\n paramopc : DEFAULT final\n | NULL\n | NOT NULL\n | UNIQUE\n | constraintinColumn\n | checkinColumn\n | PRIMARY KEY\n constraintinColumn : CONSTRAINT ID checkinColumn\n | CONSTRAINT ID uniqueinColumn\n checkinColumn : CHECK PARENTESISIZQUIERDA operacion PARENTESISDERECHAuniqueinColumn : UNIQUE PARENTESISIZQUIERDA listaParam PARENTESISDERECHAprimaryKey : PRIMARY KEY PARENTESISIZQUIERDA listaParam PARENTESISDERECHAforeignKey : FOREIGN KEY PARENTESISIZQUIERDA listaParam PARENTESISDERECHA REFERENCES ID PARENTESISIZQUIERDA listaParam PARENTESISDERECHAtipo : SMALLINT\n | INTEGER\n | BIGINT\n | DECIMAL\n | NUMERIC\n | REAL\n | DOUBLE\n | PRECISION\n | MONEY\n | VARCHAR PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA\n | CHARACTER VARYING PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA\n | CHARACTER PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA\n | CHAR PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA\n | TEXT\n | BOOLEAN\n | TIMESTAMP\n | TIME\n | INTERVAL\n | DATE\n | YEAR\n | MONTH \n | DAY\n | HOUR \n | MINUTE\n | SECOND\n selectData : SELECT select_list FROM select_list WHERE search_condition opcionesSelect PUNTOYCOMA\n | SELECT POR FROM select_list WHERE search_condition opcionesSelect PUNTOYCOMA\n selectData : SELECT select_list FROM select_list WHERE search_condition PUNTOYCOMA\n | SELECT POR FROM select_list WHERE search_condition PUNTOYCOMA\n selectData : SELECT select_list FROM select_list PUNTOYCOMA\n | SELECT POR FROM select_list PUNTOYCOMA\n selectData : SELECT select_list PUNTOYCOMA\n opcionesSelect : opcionesSelect opcionSelect\n opcionesSelect : opcionSelect\n opcionSelect : LIMIT operacion\n | GROUP BY select_list\n | HAVING select_list\n | ORDER BY select_list \n opcionSelect : LIMIT operacion OFFSET operacion\n | ORDER BY select_list ordenamiento \n ordenamiento : ASC\n | DESC search_condition : search_condition AND search_condition\n | search_condition OR search_condition \n search_condition : NOT search_conditionsearch_condition : operacionsearch_condition : PARENTESISIZQUIERDA search_condition PARENTESISDERECHA select_list : select_list COMA operacionselect_list : operacion select_list : select_list condicion_select operacion COMA operacion select_list : condicion_select operacion select_list : select_list AS operacioncondicion_select : DISTINCT FROM \n condicion_select : IS DISTINCT FROM \n condicion_select : IS NOT DISTINCT FROMcondicion_select : DISTINCT condicion_select : IS DISTINCT \n condicion_select : IS NOT DISTINCT \n funcionBasica : operacion BETWEEN operacion AND operacionfuncionBasica : operacion LIKE CADENAfuncionBasica : operacion IN PARENTESISIZQUIERDA select_list PARENTESISDERECHA funcionBasica : operacion NOT BETWEEN operacion AND operacion funcionBasica : operacion BETWEEN SYMMETRIC operacion AND operacionfuncionBasica : operacion NOT BETWEEN SYMMETRIC operacion AND operacionfuncionBasica : operacion condicion_select operacion'
_lr_action_items = 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[293,],[414,]),'TO':([393,394,],[508,509,]),'CURRENT_USER':([509,],[567,]),'SESSION_USER':([509,],[568,]),'REFERENCES':([523,681,],[581,688,]),'INHERITS':([558,],[616,]),'BY':([638,640,],[669,671,]),}
_lr_action = {}
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = {}
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'inicio':([0,],[1,]),'queries':([0,],[2,]),'query':([0,2,],[3,105,]),'mostrarBD':([0,2,],[4,4,]),'crearBD':([0,2,],[5,5,]),'alterBD':([0,2,],[6,6,]),'dropBD':([0,2,],[7,7,]),'operacion':([0,2,30,32,43,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,131,151,162,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,192,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,217,218,219,220,221,222,223,224,225,226,227,250,252,253,276,310,312,313,314,315,335,336,337,338,339,364,379,383,410,433,434,439,440,448,472,474,476,477,478,479,482,483,485,487,515,516,526,528,529,541,552,561,584,586,593,596,597,598,601,634,635,637,639,669,671,674,683,],[8,8,152,154,167,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,254,273,307,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,340,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,368,369,370,371,372,373,374,375,376,377,378,380,167,382,408,167,421,422,423,167,443,444,445,446,447,471,484,488,517,531,532,533,534,540,542,543,544,545,546,547,548,549,550,551,408,408,585,587,585,594,604,620,642,644,647,649,650,651,652,585,585,668,167,167,167,686,690,]),'insertinBD':([0,2,],[9,9,]),'updateinBD':([0,2,],[10,10,]),'deleteinBD':([0,2,],[11,11,]),'createTable':([0,2,],[12,12,]),'inheritsBD':([0,2,],[13,13,]),'dropTable':([0,2,],[14,14,]),'alterTable':([0,2,],[15,15,]),'variantesAt':([0,2,265,],[16,16,396,]),'contAdd':([0,2,38,397,],[17,17,158,158,]),'contDrop':([0,2,27,398,],[18,18,147,147,]),'contAlter':([0,2,26,266,395,],[19,19,143,399,143,]),'listaid':([0,2,419,],[20,20,525,]),'tipoAlter':([0,2,],[21,21,]),'selectData':([0,2,],[22,22,]),'funcionBasica':([0,2,30,32,43,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,131,151,162,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,192,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,217,218,219,220,221,222,223,224,225,226,227,250,252,253,276,310,312,313,314,315,335,336,337,338,339,364,379,383,410,433,434,439,440,448,472,474,476,477,478,479,482,483,485,487,515,516,526,528,529,541,552,561,584,586,593,596,597,598,601,634,635,637,639,669,671,674,683,],[33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,]),'final':([0,2,30,32,43,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,131,151,162,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,192,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,217,218,219,220,221,222,223,224,225,226,227,250,252,253,276,310,312,313,314,315,335,336,337,338,339,364,379,383,405,410,433,434,439,440,448,472,474,476,477,478,479,482,483,485,487,492,493,509,512,515,516,526,528,529,541,552,561,562,573,584,586,593,596,597,598,601,608,622,623,634,635,637,639,663,669,671,674,683,698,],[34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,514,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,553,554,569,514,34,34,34,34,34,34,34,34,514,628,34,34,34,34,34,34,34,654,514,514,34,34,34,34,514,34,34,34,34,514,]),'condicion_select':([8,43,152,154,165,167,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,252,254,273,307,310,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,340,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,368,369,370,371,372,373,374,375,376,377,378,380,381,382,408,420,421,422,423,424,443,444,445,446,447,471,484,488,517,531,532,533,534,540,542,543,544,545,546,547,548,549,550,551,585,587,594,604,620,639,642,644,647,649,650,651,652,668,669,670,671,684,685,686,690,],[131,168,131,131,313,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,168,131,131,131,168,168,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,313,131,131,313,131,131,131,313,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,131,168,131,131,131,131,131,131,131,131,168,313,168,313,313,131,131,]),'listaContAlter':([26,395,],[142,142,]),'select_list':([43,252,310,315,639,669,671,],[165,381,420,424,670,684,685,]),'tipo':([161,278,282,495,],[280,280,412,557,]),'opcionTrim':([216,],[364,]),'parametrosCrearBD':([260,494,],[387,556,]),'parametroCrearBD':([260,387,494,556,],[388,491,388,491,]),'asignaciones':([276,515,],[406,574,]),'asigna':([276,515,516,],[407,407,575,]),'creaColumnas':([392,],[496,]),'Columna':([392,559,],[497,617,]),'constraintinColumn':([392,557,559,606,],[498,612,498,612,]),'checkinColumn':([392,557,559,560,606,],[499,613,499,618,613,]),'uniqueinColumn':([392,559,560,],[500,500,619,]),'primaryKey':([392,559,],[501,501,]),'foreignKey':([392,559,],[502,502,]),'listaParam':([405,512,562,622,623,663,698,],[513,571,621,660,661,682,699,]),'parametroAlterUser':([509,],[566,]),'search_condition':([526,529,584,586,634,635,],[583,588,641,643,666,667,]),'paramOpcional':([557,],[606,]),'paramopc':([557,606,],[607,653,]),'opcionesSelect':([583,588,],[632,645,]),'opcionSelect':([583,588,632,645,],[636,636,665,665,]),'ordenamiento':([685,],[691,]),}
_lr_goto = {}
for _k, _v in _lr_goto_items.items():
for _x, _y in zip(_v[0], _v[1]):
if not _x in _lr_goto: _lr_goto[_x] = {}
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> inicio","S'",1,None,None,None),
('inicio -> queries','inicio',1,'p_inicio_1','gramaticaAscendente.py',399),
('queries -> queries query','queries',2,'p_queries_1','gramaticaAscendente.py',406),
('queries -> query','queries',1,'p_queries_2','gramaticaAscendente.py',412),
('query -> mostrarBD','query',1,'p_query','gramaticaAscendente.py',419),
('query -> crearBD','query',1,'p_query','gramaticaAscendente.py',420),
('query -> alterBD','query',1,'p_query','gramaticaAscendente.py',421),
('query -> dropBD','query',1,'p_query','gramaticaAscendente.py',422),
('query -> operacion','query',1,'p_query','gramaticaAscendente.py',423),
('query -> insertinBD','query',1,'p_query','gramaticaAscendente.py',424),
('query -> updateinBD','query',1,'p_query','gramaticaAscendente.py',425),
('query -> deleteinBD','query',1,'p_query','gramaticaAscendente.py',426),
('query -> createTable','query',1,'p_query','gramaticaAscendente.py',427),
('query -> inheritsBD','query',1,'p_query','gramaticaAscendente.py',428),
('query -> dropTable','query',1,'p_query','gramaticaAscendente.py',429),
('query -> alterTable','query',1,'p_query','gramaticaAscendente.py',430),
('query -> variantesAt','query',1,'p_query','gramaticaAscendente.py',431),
('query -> contAdd','query',1,'p_query','gramaticaAscendente.py',432),
('query -> contDrop','query',1,'p_query','gramaticaAscendente.py',433),
('query -> contAlter','query',1,'p_query','gramaticaAscendente.py',434),
('query -> listaid','query',1,'p_query','gramaticaAscendente.py',435),
('query -> tipoAlter','query',1,'p_query','gramaticaAscendente.py',436),
('query -> selectData','query',1,'p_query','gramaticaAscendente.py',438),
('crearBD -> CREATE DATABASE ID PUNTOYCOMA','crearBD',4,'p_crearBaseDatos_1','gramaticaAscendente.py',453),
('crearBD -> CREATE OR REPLACE DATABASE ID PUNTOYCOMA','crearBD',6,'p_crearBaseDatos_2','gramaticaAscendente.py',458),
('crearBD -> CREATE OR REPLACE DATABASE ID parametrosCrearBD PUNTOYCOMA','crearBD',7,'p_crearBaseDatos_3','gramaticaAscendente.py',462),
('crearBD -> CREATE DATABASE ID parametrosCrearBD PUNTOYCOMA','crearBD',5,'p_crearBaseDatos_4','gramaticaAscendente.py',466),
('parametrosCrearBD -> parametrosCrearBD parametroCrearBD','parametrosCrearBD',2,'p_parametrosCrearBD_1','gramaticaAscendente.py',472),
('parametrosCrearBD -> parametroCrearBD','parametrosCrearBD',1,'p_parametrosCrearBD_2','gramaticaAscendente.py',476),
('parametroCrearBD -> OWNER IGUAL final','parametroCrearBD',3,'p_parametroCrearBD','gramaticaAscendente.py',480),
('parametroCrearBD -> MODE IGUAL final','parametroCrearBD',3,'p_parametroCrearBD','gramaticaAscendente.py',481),
('mostrarBD -> SHOW DATABASES PUNTOYCOMA','mostrarBD',3,'p_mostrarBD','gramaticaAscendente.py',487),
('alterBD -> ALTER DATABASE ID RENAME TO ID PUNTOYCOMA','alterBD',7,'p_alterBD_1','gramaticaAscendente.py',494),
('alterBD -> ALTER DATABASE ID OWNER TO parametroAlterUser PUNTOYCOMA','alterBD',7,'p_alterBD_2','gramaticaAscendente.py',498),
('parametroAlterUser -> CURRENT_USER','parametroAlterUser',1,'p_parametroAlterUser','gramaticaAscendente.py',502),
('parametroAlterUser -> SESSION_USER','parametroAlterUser',1,'p_parametroAlterUser','gramaticaAscendente.py',503),
('parametroAlterUser -> final','parametroAlterUser',1,'p_parametroAlterUser','gramaticaAscendente.py',504),
('dropTable -> DROP TABLE ID PUNTOYCOMA','dropTable',4,'p_dropTable','gramaticaAscendente.py',510),
('alterTable -> ALTER TABLE ID variantesAt PUNTOYCOMA','alterTable',5,'p_alterTable','gramaticaAscendente.py',515),
('variantesAt -> ADD contAdd','variantesAt',2,'p_variantesAt','gramaticaAscendente.py',523),
('variantesAt -> ALTER listaContAlter','variantesAt',2,'p_variantesAt','gramaticaAscendente.py',524),
('variantesAt -> DROP contDrop','variantesAt',2,'p_variantesAt','gramaticaAscendente.py',525),
('listaContAlter -> listaContAlter COMA contAlter','listaContAlter',3,'p_listaContAlter','gramaticaAscendente.py',537),
('listaContAlter -> contAlter','listaContAlter',1,'p_listaContAlter_2','gramaticaAscendente.py',543),
('contAlter -> COLUMN ID SET NOT NULL','contAlter',5,'p_contAlter','gramaticaAscendente.py',550),
('contAlter -> COLUMN ID TYPE tipo','contAlter',4,'p_contAlter','gramaticaAscendente.py',551),
('contAdd -> COLUMN ID tipo','contAdd',3,'p_contAdd','gramaticaAscendente.py',561),
('contAdd -> CHECK PARENTESISIZQUIERDA operacion PARENTESISDERECHA','contAdd',4,'p_contAdd','gramaticaAscendente.py',562),
('contAdd -> FOREIGN KEY PARENTESISIZQUIERDA ID PARENTESISDERECHA REFERENCES ID','contAdd',7,'p_contAdd','gramaticaAscendente.py',563),
('contAdd -> CONSTRAINT ID UNIQUE PARENTESISIZQUIERDA listaid PARENTESISDERECHA','contAdd',6,'p_contAdd','gramaticaAscendente.py',564),
('contDrop -> COLUMN ID','contDrop',2,'p_contDrop','gramaticaAscendente.py',579),
('contDrop -> CONSTRAINT ID','contDrop',2,'p_contDrop','gramaticaAscendente.py',580),
('listaid -> listaid COMA ID','listaid',3,'p_listaID','gramaticaAscendente.py',590),
('listaid -> ID','listaid',1,'p_listaID_2','gramaticaAscendente.py',596),
('tipoAlter -> ADD','tipoAlter',1,'p_tipoAlter','gramaticaAscendente.py',604),
('tipoAlter -> DROP','tipoAlter',1,'p_tipoAlter','gramaticaAscendente.py',605),
('dropBD -> DROP DATABASE ID PUNTOYCOMA','dropBD',4,'p_dropBD_1','gramaticaAscendente.py',611),
('dropBD -> DROP DATABASE IF EXISTS ID PUNTOYCOMA','dropBD',6,'p_dropBD_2','gramaticaAscendente.py',615),
('operacion -> operacion MAS operacion','operacion',3,'p_operacion','gramaticaAscendente.py',619),
('operacion -> operacion MENOS operacion','operacion',3,'p_operacion','gramaticaAscendente.py',620),
('operacion -> operacion POR operacion','operacion',3,'p_operacion','gramaticaAscendente.py',621),
('operacion -> operacion DIV operacion','operacion',3,'p_operacion','gramaticaAscendente.py',622),
('operacion -> operacion RESIDUO operacion','operacion',3,'p_operacion','gramaticaAscendente.py',623),
('operacion -> operacion POTENCIA operacion','operacion',3,'p_operacion','gramaticaAscendente.py',626),
('operacion -> operacion AND operacion','operacion',3,'p_operacion','gramaticaAscendente.py',627),
('operacion -> operacion OR operacion','operacion',3,'p_operacion','gramaticaAscendente.py',628),
('operacion -> operacion SIMBOLOOR2 operacion','operacion',3,'p_operacion','gramaticaAscendente.py',629),
('operacion -> operacion SIMBOLOOR operacion','operacion',3,'p_operacion','gramaticaAscendente.py',630),
('operacion -> operacion SIMBOLOAND2 operacion','operacion',3,'p_operacion','gramaticaAscendente.py',633),
('operacion -> operacion DESPLAZAMIENTOIZQUIERDA operacion','operacion',3,'p_operacion','gramaticaAscendente.py',634),
('operacion -> operacion DESPLAZAMIENTODERECHA operacion','operacion',3,'p_operacion','gramaticaAscendente.py',635),
('operacion -> operacion IGUAL operacion','operacion',3,'p_operacion','gramaticaAscendente.py',636),
('operacion -> operacion IGUALIGUAL operacion','operacion',3,'p_operacion','gramaticaAscendente.py',637),
('operacion -> operacion NOTEQUAL operacion','operacion',3,'p_operacion','gramaticaAscendente.py',640),
('operacion -> operacion MAYORIGUAL operacion','operacion',3,'p_operacion','gramaticaAscendente.py',641),
('operacion -> operacion MENORIGUAL operacion','operacion',3,'p_operacion','gramaticaAscendente.py',642),
('operacion -> operacion MAYOR operacion','operacion',3,'p_operacion','gramaticaAscendente.py',643),
('operacion -> operacion MENOR operacion','operacion',3,'p_operacion','gramaticaAscendente.py',644),
('operacion -> operacion DIFERENTE operacion','operacion',3,'p_operacion','gramaticaAscendente.py',645),
('operacion -> PARENTESISIZQUIERDA operacion PARENTESISDERECHA','operacion',3,'p_operacion','gramaticaAscendente.py',646),
('operacion -> MENOS ENTERO','operacion',2,'p_operacion_menos_unario','gramaticaAscendente.py',695),
('operacion -> NOT operacion','operacion',2,'p_operacion_not_unario','gramaticaAscendente.py',700),
('operacion -> funcionBasica','operacion',1,'p_operacion_funcion','gramaticaAscendente.py',704),
('operacion -> final','operacion',1,'p_operacion_final','gramaticaAscendente.py',709),
('funcionBasica -> ABS PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',721),
('funcionBasica -> CBRT PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',722),
('funcionBasica -> CEIL PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',723),
('funcionBasica -> CEILING PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',724),
('funcionBasica -> DEGREES PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',725),
('funcionBasica -> DIV PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',726),
('funcionBasica -> EXP PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',727),
('funcionBasica -> FACTORIAL PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',728),
('funcionBasica -> FLOOR PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',729),
('funcionBasica -> GCD PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',730),
('funcionBasica -> LCM PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',731),
('funcionBasica -> LN PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',732),
('funcionBasica -> LOG PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',733),
('funcionBasica -> LOG10 PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',734),
('funcionBasica -> MIN_SCALE PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',738),
('funcionBasica -> MOD PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',739),
('funcionBasica -> POWER PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',740),
('funcionBasica -> RADIANS PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',741),
('funcionBasica -> ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',742),
('funcionBasica -> SCALE ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',5,'p_funcion_basica','gramaticaAscendente.py',743),
('funcionBasica -> SIGN ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',5,'p_funcion_basica','gramaticaAscendente.py',744),
('funcionBasica -> SQRT ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',5,'p_funcion_basica','gramaticaAscendente.py',745),
('funcionBasica -> TRIM_SCALE ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',5,'p_funcion_basica','gramaticaAscendente.py',746),
('funcionBasica -> TRUC ROUND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',5,'p_funcion_basica','gramaticaAscendente.py',747),
('funcionBasica -> WIDTH_BUCKET PARENTESISIZQUIERDA operacion COMA operacion COMA operacion COMA operacion PARENTESISDERECHA','funcionBasica',10,'p_funcion_basica','gramaticaAscendente.py',748),
('funcionBasica -> RANDOM PARENTESISIZQUIERDA PARENTESISDERECHA','funcionBasica',3,'p_funcion_basica','gramaticaAscendente.py',749),
('funcionBasica -> SETSEED PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',750),
('funcionBasica -> ACOS PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',751),
('funcionBasica -> ACOSD PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',755),
('funcionBasica -> ASIN PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',756),
('funcionBasica -> ASIND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',757),
('funcionBasica -> ATAN PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',758),
('funcionBasica -> ATAN2 PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',759),
('funcionBasica -> COS PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',760),
('funcionBasica -> COSD PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',761),
('funcionBasica -> COT PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',762),
('funcionBasica -> COTD PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',763),
('funcionBasica -> SIN PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',764),
('funcionBasica -> SIND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',765),
('funcionBasica -> TAN PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',766),
('funcionBasica -> TAND PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',767),
('funcionBasica -> SINH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',768),
('funcionBasica -> COSH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',772),
('funcionBasica -> TANH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',773),
('funcionBasica -> ASINH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',774),
('funcionBasica -> ACOSH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',775),
('funcionBasica -> ATANH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',776),
('funcionBasica -> LENGTH PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',777),
('funcionBasica -> TRIM PARENTESISIZQUIERDA opcionTrim operacion FROM operacion PARENTESISDERECHA','funcionBasica',7,'p_funcion_basica','gramaticaAscendente.py',778),
('funcionBasica -> GET_BYTE PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',779),
('funcionBasica -> MD5 PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',780),
('funcionBasica -> SET_BYTE PARENTESISIZQUIERDA operacion COMA operacion COMA operacion PARENTESISDERECHA','funcionBasica',8,'p_funcion_basica','gramaticaAscendente.py',781),
('funcionBasica -> SHA256 PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',782),
('funcionBasica -> SUBSTR PARENTESISIZQUIERDA operacion COMA operacion COMA operacion PARENTESISDERECHA','funcionBasica',8,'p_funcion_basica','gramaticaAscendente.py',783),
('funcionBasica -> CONVERT PARENTESISIZQUIERDA operacion COMA operacion COMA operacion PARENTESISDERECHA','funcionBasica',8,'p_funcion_basica','gramaticaAscendente.py',784),
('funcionBasica -> ENCODE PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',785),
('funcionBasica -> DECODE PARENTESISIZQUIERDA operacion COMA operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica','gramaticaAscendente.py',786),
('funcionBasica -> AVG PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',787),
('funcionBasica -> SUM PARENTESISIZQUIERDA operacion PARENTESISDERECHA','funcionBasica',4,'p_funcion_basica','gramaticaAscendente.py',788),
('funcionBasica -> SUBSTRING PARENTESISIZQUIERDA operacion FROM operacion FOR operacion PARENTESISDERECHA','funcionBasica',8,'p_funcion_basica_1','gramaticaAscendente.py',915),
('funcionBasica -> SUBSTRING PARENTESISIZQUIERDA operacion FROM operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica_2','gramaticaAscendente.py',919),
('funcionBasica -> SUBSTRING PARENTESISIZQUIERDA operacion FOR operacion PARENTESISDERECHA','funcionBasica',6,'p_funcion_basica_3','gramaticaAscendente.py',923),
('opcionTrim -> LEADING','opcionTrim',1,'p_opcionTrim','gramaticaAscendente.py',928),
('opcionTrim -> TRAILING','opcionTrim',1,'p_opcionTrim','gramaticaAscendente.py',929),
('opcionTrim -> BOTH','opcionTrim',1,'p_opcionTrim','gramaticaAscendente.py',930),
('final -> DECIMAL','final',1,'p_final','gramaticaAscendente.py',937),
('final -> ENTERO','final',1,'p_final','gramaticaAscendente.py',938),
('final -> ID','final',1,'p_final_id','gramaticaAscendente.py',943),
('final -> ID PUNTO ID','final',3,'p_final_invocacion','gramaticaAscendente.py',947),
('final -> CADENA','final',1,'p_final_cadena','gramaticaAscendente.py',951),
('insertinBD -> INSERT INTO ID VALUES PARENTESISIZQUIERDA listaParam PARENTESISDERECHA PUNTOYCOMA','insertinBD',8,'p_insertBD_1','gramaticaAscendente.py',956),
('insertinBD -> INSERT INTO ID PARENTESISIZQUIERDA listaParam PARENTESISDERECHA VALUES PARENTESISIZQUIERDA listaParam PARENTESISDERECHA PUNTOYCOMA','insertinBD',11,'p_insertBD_2','gramaticaAscendente.py',960),
('listaParam -> listaParam COMA final','listaParam',3,'p_listaParam','gramaticaAscendente.py',965),
('listaParam -> final','listaParam',1,'p_listaParam_2','gramaticaAscendente.py',970),
('updateinBD -> UPDATE ID SET asignaciones WHERE asignaciones PUNTOYCOMA','updateinBD',7,'p_updateBD','gramaticaAscendente.py',977),
('asignaciones -> asignaciones COMA asigna','asignaciones',3,'p_asignaciones','gramaticaAscendente.py',983),
('asignaciones -> asigna','asignaciones',1,'p_asignaciones_2','gramaticaAscendente.py',988),
('asigna -> operacion','asigna',1,'p_asigna','gramaticaAscendente.py',993),
('deleteinBD -> DELETE FROM ID PUNTOYCOMA','deleteinBD',4,'p_deleteinBD_1','gramaticaAscendente.py',999),
('deleteinBD -> DELETE FROM ID WHERE operacion PUNTOYCOMA','deleteinBD',6,'p_deleteinBD_2','gramaticaAscendente.py',1003),
('createTable -> CREATE TABLE ID PARENTESISIZQUIERDA creaColumnas PARENTESISDERECHA PUNTOYCOMA','createTable',7,'p_createTable','gramaticaAscendente.py',1009),
('inheritsBD -> CREATE TABLE ID PARENTESISIZQUIERDA creaColumnas PARENTESISDERECHA INHERITS PARENTESISIZQUIERDA ID PARENTESISDERECHA PUNTOYCOMA','inheritsBD',11,'p_inheritsBD','gramaticaAscendente.py',1013),
('creaColumnas -> creaColumnas COMA Columna','creaColumnas',3,'p_creaColumna','gramaticaAscendente.py',1018),
('creaColumnas -> Columna','creaColumnas',1,'p_creaColumna_2','gramaticaAscendente.py',1023),
('Columna -> ID tipo','Columna',2,'p_columna_1','gramaticaAscendente.py',1029),
('Columna -> ID tipo paramOpcional','Columna',3,'p_columna_1','gramaticaAscendente.py',1030),
('Columna -> constraintinColumn','Columna',1,'p_columna_1','gramaticaAscendente.py',1031),
('Columna -> checkinColumn','Columna',1,'p_columna_1','gramaticaAscendente.py',1032),
('Columna -> uniqueinColumn','Columna',1,'p_columna_1','gramaticaAscendente.py',1033),
('Columna -> primaryKey','Columna',1,'p_columna_1','gramaticaAscendente.py',1034),
('Columna -> foreignKey','Columna',1,'p_columna_1','gramaticaAscendente.py',1035),
('paramOpcional -> paramOpcional paramopc','paramOpcional',2,'p_paramOpcional','gramaticaAscendente.py',1042),
('paramOpcional -> paramopc','paramOpcional',1,'p_paramOpcional_1','gramaticaAscendente.py',1048),
('paramopc -> DEFAULT final','paramopc',2,'p_paramopc','gramaticaAscendente.py',1053),
('paramopc -> NULL','paramopc',1,'p_paramopc','gramaticaAscendente.py',1054),
('paramopc -> NOT NULL','paramopc',2,'p_paramopc','gramaticaAscendente.py',1055),
('paramopc -> UNIQUE','paramopc',1,'p_paramopc','gramaticaAscendente.py',1056),
('paramopc -> constraintinColumn','paramopc',1,'p_paramopc','gramaticaAscendente.py',1057),
('paramopc -> checkinColumn','paramopc',1,'p_paramopc','gramaticaAscendente.py',1058),
('paramopc -> PRIMARY KEY','paramopc',2,'p_paramopc','gramaticaAscendente.py',1059),
('constraintinColumn -> CONSTRAINT ID checkinColumn','constraintinColumn',3,'p_constraintinColumn','gramaticaAscendente.py',1066),
('constraintinColumn -> CONSTRAINT ID uniqueinColumn','constraintinColumn',3,'p_constraintinColumn','gramaticaAscendente.py',1067),
('checkinColumn -> CHECK PARENTESISIZQUIERDA operacion PARENTESISDERECHA','checkinColumn',4,'p_checkinColumn','gramaticaAscendente.py',1072),
('uniqueinColumn -> UNIQUE PARENTESISIZQUIERDA listaParam PARENTESISDERECHA','uniqueinColumn',4,'p_uniqueinColumn','gramaticaAscendente.py',1077),
('primaryKey -> PRIMARY KEY PARENTESISIZQUIERDA listaParam PARENTESISDERECHA','primaryKey',5,'p_primaryKey','gramaticaAscendente.py',1082),
('foreignKey -> FOREIGN KEY PARENTESISIZQUIERDA listaParam PARENTESISDERECHA REFERENCES ID PARENTESISIZQUIERDA listaParam PARENTESISDERECHA','foreignKey',10,'p_foreingkey','gramaticaAscendente.py',1087),
('tipo -> SMALLINT','tipo',1,'p_tipo','gramaticaAscendente.py',1093),
('tipo -> INTEGER','tipo',1,'p_tipo','gramaticaAscendente.py',1094),
('tipo -> BIGINT','tipo',1,'p_tipo','gramaticaAscendente.py',1095),
('tipo -> DECIMAL','tipo',1,'p_tipo','gramaticaAscendente.py',1096),
('tipo -> NUMERIC','tipo',1,'p_tipo','gramaticaAscendente.py',1097),
('tipo -> REAL','tipo',1,'p_tipo','gramaticaAscendente.py',1098),
('tipo -> DOUBLE','tipo',1,'p_tipo','gramaticaAscendente.py',1099),
('tipo -> PRECISION','tipo',1,'p_tipo','gramaticaAscendente.py',1100),
('tipo -> MONEY','tipo',1,'p_tipo','gramaticaAscendente.py',1101),
('tipo -> VARCHAR PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA','tipo',4,'p_tipo','gramaticaAscendente.py',1102),
('tipo -> CHARACTER VARYING PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA','tipo',5,'p_tipo','gramaticaAscendente.py',1103),
('tipo -> CHARACTER PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA','tipo',4,'p_tipo','gramaticaAscendente.py',1104),
('tipo -> CHAR PARENTESISIZQUIERDA ENTERO PARENTESISDERECHA','tipo',4,'p_tipo','gramaticaAscendente.py',1105),
('tipo -> TEXT','tipo',1,'p_tipo','gramaticaAscendente.py',1106),
('tipo -> BOOLEAN','tipo',1,'p_tipo','gramaticaAscendente.py',1107),
('tipo -> TIMESTAMP','tipo',1,'p_tipo','gramaticaAscendente.py',1108),
('tipo -> TIME','tipo',1,'p_tipo','gramaticaAscendente.py',1109),
('tipo -> INTERVAL','tipo',1,'p_tipo','gramaticaAscendente.py',1110),
('tipo -> DATE','tipo',1,'p_tipo','gramaticaAscendente.py',1111),
('tipo -> YEAR','tipo',1,'p_tipo','gramaticaAscendente.py',1112),
('tipo -> MONTH','tipo',1,'p_tipo','gramaticaAscendente.py',1113),
('tipo -> DAY','tipo',1,'p_tipo','gramaticaAscendente.py',1114),
('tipo -> HOUR','tipo',1,'p_tipo','gramaticaAscendente.py',1115),
('tipo -> MINUTE','tipo',1,'p_tipo','gramaticaAscendente.py',1116),
('tipo -> SECOND','tipo',1,'p_tipo','gramaticaAscendente.py',1117),
('selectData -> SELECT select_list FROM select_list WHERE search_condition opcionesSelect PUNTOYCOMA','selectData',8,'p_select','gramaticaAscendente.py',1122),
('selectData -> SELECT POR FROM select_list WHERE search_condition opcionesSelect PUNTOYCOMA','selectData',8,'p_select','gramaticaAscendente.py',1123),
('selectData -> SELECT select_list FROM select_list WHERE search_condition PUNTOYCOMA','selectData',7,'p_select_1','gramaticaAscendente.py',1132),
('selectData -> SELECT POR FROM select_list WHERE search_condition PUNTOYCOMA','selectData',7,'p_select_1','gramaticaAscendente.py',1133),
('selectData -> SELECT select_list FROM select_list PUNTOYCOMA','selectData',5,'p_select_2','gramaticaAscendente.py',1141),
('selectData -> SELECT POR FROM select_list PUNTOYCOMA','selectData',5,'p_select_2','gramaticaAscendente.py',1142),
('selectData -> SELECT select_list PUNTOYCOMA','selectData',3,'p_select_3','gramaticaAscendente.py',1150),
('opcionesSelect -> opcionesSelect opcionSelect','opcionesSelect',2,'p_opcionesSelect_1','gramaticaAscendente.py',1155),
('opcionesSelect -> opcionSelect','opcionesSelect',1,'p_opcionesSelect_2','gramaticaAscendente.py',1160),
('opcionSelect -> LIMIT operacion','opcionSelect',2,'p_opcionesSelect_3','gramaticaAscendente.py',1166),
('opcionSelect -> GROUP BY select_list','opcionSelect',3,'p_opcionesSelect_3','gramaticaAscendente.py',1167),
('opcionSelect -> HAVING select_list','opcionSelect',2,'p_opcionesSelect_3','gramaticaAscendente.py',1168),
('opcionSelect -> ORDER BY select_list','opcionSelect',3,'p_opcionesSelect_3','gramaticaAscendente.py',1169),
('opcionSelect -> LIMIT operacion OFFSET operacion','opcionSelect',4,'p_opcionesSelect_4','gramaticaAscendente.py',1181),
('opcionSelect -> ORDER BY select_list ordenamiento','opcionSelect',4,'p_opcionesSelect_4','gramaticaAscendente.py',1182),
('ordenamiento -> ASC','ordenamiento',1,'p_ordenamiento','gramaticaAscendente.py',1192),
('ordenamiento -> DESC','ordenamiento',1,'p_ordenamiento','gramaticaAscendente.py',1193),
('search_condition -> search_condition AND search_condition','search_condition',3,'p_search_condition_1','gramaticaAscendente.py',1197),
('search_condition -> search_condition OR search_condition','search_condition',3,'p_search_condition_1','gramaticaAscendente.py',1198),
('search_condition -> NOT search_condition','search_condition',2,'p_search_condition_2','gramaticaAscendente.py',1203),
('search_condition -> operacion','search_condition',1,'p_search_condition_3','gramaticaAscendente.py',1207),
('search_condition -> PARENTESISIZQUIERDA search_condition PARENTESISDERECHA','search_condition',3,'p_search_condition_4','gramaticaAscendente.py',1211),
('select_list -> select_list COMA operacion','select_list',3,'p_select_list_1','gramaticaAscendente.py',1216),
('select_list -> operacion','select_list',1,'p_select_list_2','gramaticaAscendente.py',1222),
('select_list -> select_list condicion_select operacion COMA operacion','select_list',5,'p_select_list_3','gramaticaAscendente.py',1226),
('select_list -> condicion_select operacion','select_list',2,'p_select_list_4','gramaticaAscendente.py',1230),
('select_list -> select_list AS operacion','select_list',3,'p_select_list_5','gramaticaAscendente.py',1234),
('condicion_select -> DISTINCT FROM','condicion_select',2,'p_condicion_select','gramaticaAscendente.py',1238),
('condicion_select -> IS DISTINCT FROM','condicion_select',3,'p_condicion_select_2','gramaticaAscendente.py',1243),
('condicion_select -> IS NOT DISTINCT FROM','condicion_select',4,'p_condicion_select_3','gramaticaAscendente.py',1249),
('condicion_select -> DISTINCT','condicion_select',1,'p_condicion_select_4','gramaticaAscendente.py',1253),
('condicion_select -> IS DISTINCT','condicion_select',2,'p_condicion_select_5','gramaticaAscendente.py',1257),
('condicion_select -> IS NOT DISTINCT','condicion_select',3,'p_condicion_select_6','gramaticaAscendente.py',1262),
('funcionBasica -> operacion BETWEEN operacion AND operacion','funcionBasica',5,'p_funcion_basica_4','gramaticaAscendente.py',1267),
('funcionBasica -> operacion LIKE CADENA','funcionBasica',3,'p_funcion_basica_5','gramaticaAscendente.py',1271),
('funcionBasica -> operacion IN PARENTESISIZQUIERDA select_list PARENTESISDERECHA','funcionBasica',5,'p_funcion_basica_6','gramaticaAscendente.py',1275),
('funcionBasica -> operacion NOT BETWEEN operacion AND operacion','funcionBasica',6,'p_funcion_basica_7','gramaticaAscendente.py',1279),
('funcionBasica -> operacion BETWEEN SYMMETRIC operacion AND operacion','funcionBasica',6,'p_funcion_basica_8','gramaticaAscendente.py',1283),
('funcionBasica -> operacion NOT BETWEEN SYMMETRIC operacion AND operacion','funcionBasica',7,'p_funcion_basica_9','gramaticaAscendente.py',1287),
('funcionBasica -> operacion condicion_select operacion','funcionBasica',3,'p_funcion_basica_10','gramaticaAscendente.py',1292),
]
| 1,115.270175 | 265,219 | 0.67617 | 72,161 | 317,852 | 2.969776 | 0.017156 | 0.02489 | 0.008399 | 0.010583 | 0.809516 | 0.788485 | 0.751057 | 0.733414 | 0.723199 | 0.701104 | 0 | 0.584243 | 0.024269 | 317,852 | 284 | 265,220 | 1,119.197183 | 0.106746 | 0.000264 | 0 | 0.007299 | 1 | 0.00365 | 0.13066 | 0.020805 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 |
6342e6f40f1f277019f3c778673a49d87caa88d8 | 1,682 | gyp | Python | client/build/linux/system.gyp | zamorajavi/google-input-tools | fc9f11d80d957560f7accf85a5fc27dd23625f70 | [
"Apache-2.0"
] | 175 | 2015-01-01T12:40:33.000Z | 2019-05-24T22:33:59.000Z | client/build/linux/system.gyp | zamorajavi/google-input-tools | fc9f11d80d957560f7accf85a5fc27dd23625f70 | [
"Apache-2.0"
] | 11 | 2015-01-19T16:30:56.000Z | 2018-04-25T01:06:52.000Z | client/build/linux/system.gyp | zamorajavi/google-input-tools | fc9f11d80d957560f7accf85a5fc27dd23625f70 | [
"Apache-2.0"
] | 97 | 2015-01-19T15:35:29.000Z | 2019-05-15T05:48:02.000Z | {
'targets': [
{
'target_name': 'glib',
'type': '<(library)',
'conditions': [
['_toolset=="target"', {
'direct_dependent_settings': {
'cflags': [
'<!@(pkg-config --cflags glib-2.0)',
],
},
'link_settings': {
'ldflags': [
'<!@(pkg-config --libs-only-L --libs-only-other glib-2.0)',
],
'libraries': [
'<!@(pkg-config --libs-only-l glib-2.0)',
'-lpthread',
],
},
}]]
},
{
'target_name': 'gtk',
'type': '<(library)',
'conditions': [
['_toolset=="target"', {
'direct_dependent_settings': {
'cflags': [
'<!@(pkg-config --cflags gtk+-2.0)',
],
},
'link_settings': {
'ldflags': [
'<!@(pkg-config --libs-only-L --libs-only-other gtk+-2.0)',
],
'libraries': [
'<!@(pkg-config --libs-only-l gtk+-2.0)',
'-lpthread',
],
},
}]]
},
{
'target_name': 'm17n',
'type': '<(library)',
'conditions': [
['_toolset=="target"', {
'direct_dependent_settings': {
'cflags': [
'<!@(pkg-config --cflags m17n-shell)',
],
},
'link_settings': {
'ldflags': [
'<!@(pkg-config --libs-only-L --libs-only-other m17n-shell)',
],
'libraries': [
'<!@(pkg-config --libs-only-l m17n-shell)',
],
},
}]]
},
],
}
| 25.104478 | 75 | 0.359096 | 123 | 1,682 | 4.788618 | 0.219512 | 0.137521 | 0.132428 | 0.173175 | 0.870968 | 0.803056 | 0.757216 | 0.757216 | 0.658744 | 0.658744 | 0 | 0.020986 | 0.433413 | 1,682 | 66 | 76 | 25.484848 | 0.597062 | 0 | 0 | 0.590909 | 0 | 0.030303 | 0.453032 | 0.04459 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
899f56f5848579aee37154dce95b7267a22b7697 | 3,860 | py | Python | tests/test_databaseconnector.py | chgeuer/python_backup | d61af53490c791bac1226062af7744a69b335ce9 | [
"MIT"
] | 1 | 2018-08-08T12:55:26.000Z | 2018-08-08T12:55:26.000Z | tests/test_databaseconnector.py | chgeuer/python_backup | d61af53490c791bac1226062af7744a69b335ce9 | [
"MIT"
] | 4 | 2018-09-17T09:32:40.000Z | 2018-10-30T09:57:40.000Z | tests/test_databaseconnector.py | chgeuer/python_backup | d61af53490c791bac1226062af7744a69b335ce9 | [
"MIT"
] | 1 | 2021-09-29T11:34:36.000Z | 2021-09-29T11:34:36.000Z | # coding=utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# --------------------------------------------------------------------------
"""Unit tests for DatabaseConnector."""
import unittest
from asebackupcli.databaseconnector import DatabaseConnector
class TestDatabaseConnector(unittest.TestCase):
"""Unit tests for class DatabaseConnector."""
def test___sql_statement_create_backup_for_filenames(self):
"""Test for DatabaseConnector.sql_statement_create_backup_for_filenames"""
self.assertEqual(
DatabaseConnector.sql_statement_create_backup_for_filenames(
dbname="AZU",
is_full=True,
files=[
"/tmp/pipe0",
"/tmp/pipe1"
]),
'''use master
go
dump database AZU to '/tmp/pipe0'
stripe on '/tmp/pipe1'
with compression = '101'
if @@error = 0
begin
print 'ASE_AZURE_BACKUP_SUCCESS'
end
go
'''
)
def test___sql_statement_create_backup_1(self):
"""Test for DatabaseConnector.sql_statement_create_backup_for_filenames"""
self.assertEqual(
DatabaseConnector.sql_statement_create_backup(
output_dir="/tmp",
dbname="AZU",
is_full=True,
start_timestamp="20180629_124500",
stripe_count=1),
'''use master
go
dump database AZU to '/tmp/AZU_full_20180629_124500_S001-001.cdmp'
with compression = '101'
if @@error = 0
begin
print 'ASE_AZURE_BACKUP_SUCCESS'
end
go
'''
)
def test___sql_statement_create_backup_2(self):
"""Test for DatabaseConnector.sql_statement_create_backup_for_filenames"""
self.assertEqual(
DatabaseConnector.sql_statement_create_backup(
output_dir="/tmp",
dbname="AZU",
is_full=True,
start_timestamp="20180629_124500",
stripe_count=4),
'''use master
go
dump database AZU to '/tmp/AZU_full_20180629_124500_S001-004.cdmp'
stripe on '/tmp/AZU_full_20180629_124500_S002-004.cdmp'
stripe on '/tmp/AZU_full_20180629_124500_S003-004.cdmp'
stripe on '/tmp/AZU_full_20180629_124500_S004-004.cdmp'
with compression = '101'
if @@error = 0
begin
print 'ASE_AZURE_BACKUP_SUCCESS'
end
go
'''
)
def test___sql_statement_create_backup_3(self):
"""Test for DatabaseConnector.sql_statement_create_backup_for_filenames"""
self.assertEqual(
DatabaseConnector.sql_statement_create_backup(
output_dir="/tmp",
dbname="AZU",
is_full=False,
start_timestamp="20180629_124500",
stripe_count=1),
'''use master
go
dump transaction AZU to '/tmp/AZU_tran_20180629_124500_S001-001.cdmp'
with compression = '101'
if @@error = 0
begin
print 'ASE_AZURE_BACKUP_SUCCESS'
end
go
'''
)
def test___sql_statement_create_backup_4(self):
"""Test for DatabaseConnector.sql_statement_create_backup_for_filenames"""
self.assertEqual(
DatabaseConnector.sql_statement_create_backup(
output_dir="/tmp",
dbname="AZU",
is_full=False,
start_timestamp="20180629_124500",
stripe_count=4),
'''use master
go
dump transaction AZU to '/tmp/AZU_tran_20180629_124500_S001-004.cdmp'
stripe on '/tmp/AZU_tran_20180629_124500_S002-004.cdmp'
stripe on '/tmp/AZU_tran_20180629_124500_S003-004.cdmp'
stripe on '/tmp/AZU_tran_20180629_124500_S004-004.cdmp'
with compression = '101'
if @@error = 0
begin
print 'ASE_AZURE_BACKUP_SUCCESS'
end
go
'''
)
| 28.175182 | 82 | 0.621503 | 431 | 3,860 | 5.208817 | 0.197216 | 0.080178 | 0.120267 | 0.160356 | 0.864588 | 0.856125 | 0.853007 | 0.831626 | 0.817817 | 0.718931 | 0 | 0.100278 | 0.253368 | 3,860 | 136 | 83 | 28.382353 | 0.678695 | 0.173834 | 0 | 0.632653 | 0 | 0 | 0.058298 | 0 | 0 | 0 | 0 | 0 | 0.102041 | 1 | 0.102041 | false | 0 | 0.040816 | 0 | 0.163265 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
98a986eff09302e578ea8242be8b952e6647533d | 153 | py | Python | medimodule/Chest/__init__.py | cuchoco/MI2RLNet | 4ef84e641705df9b10e627c701eb0c9ed924a82a | [
"Apache-2.0"
] | 9 | 2021-02-25T23:10:17.000Z | 2022-02-14T11:48:11.000Z | medimodule/Chest/__init__.py | cuchoco/MI2RLNet | 4ef84e641705df9b10e627c701eb0c9ed924a82a | [
"Apache-2.0"
] | null | null | null | medimodule/Chest/__init__.py | cuchoco/MI2RLNet | 4ef84e641705df9b10e627c701eb0c9ed924a82a | [
"Apache-2.0"
] | 7 | 2021-02-22T12:20:24.000Z | 2022-03-07T04:56:53.000Z | from .module import LungSegmentation
from .module import ViewpointClassifier
from .module import EnhanceCTClassifier
from .module import LRmarkDetection
| 30.6 | 39 | 0.869281 | 16 | 153 | 8.3125 | 0.4375 | 0.300752 | 0.481203 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.104575 | 153 | 4 | 40 | 38.25 | 0.970803 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
7f62319eb5092d785ff85747a43be13454a6be01 | 544 | py | Python | running_modes/configurations/automated_curriculum_learning/__init__.py | lilleswing/Reinvent-1 | ac4e3e6fa6379c6f4af883478dfd1b3407933ada | [
"Apache-2.0"
] | 183 | 2020-04-04T02:01:15.000Z | 2022-03-30T21:56:56.000Z | running_modes/configurations/automated_curriculum_learning/__init__.py | lilleswing/Reinvent-1 | ac4e3e6fa6379c6f4af883478dfd1b3407933ada | [
"Apache-2.0"
] | 39 | 2020-04-05T15:19:56.000Z | 2022-03-09T12:58:21.000Z | running_modes/configurations/automated_curriculum_learning/__init__.py | lilleswing/Reinvent-1 | ac4e3e6fa6379c6f4af883478dfd1b3407933ada | [
"Apache-2.0"
] | 70 | 2020-04-05T19:25:43.000Z | 2022-02-22T12:04:39.000Z | from running_modes.configurations.automated_curriculum_learning.curriculum_strategy_configuration import \
CurriculumStrategyConfiguration
from running_modes.configurations.automated_curriculum_learning.inception_configuration import InceptionConfiguration
from running_modes.configurations.automated_curriculum_learning.automated_curriculum_learning_configuration import \
AutomatedCLConfiguration
from running_modes.configurations.automated_curriculum_learning.production_strategy_configuration import ProductionStrategyConfiguration
| 77.714286 | 136 | 0.926471 | 48 | 544 | 10.083333 | 0.333333 | 0.196281 | 0.278926 | 0.247934 | 0.471074 | 0.471074 | 0.471074 | 0 | 0 | 0 | 0 | 0 | 0.047794 | 544 | 6 | 137 | 90.666667 | 0.934363 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.666667 | 0 | 0.666667 | 0 | 0 | 0 | 1 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
7f94bdfde208152f1366a717e114390069ac074a | 7,983 | py | Python | datcore-sdk/python/datcore_sdk/api/security_api.py | mguidon/aiohttp-dsm | 612e4c7f6f73df7d6752269965c428fda0276191 | [
"MIT"
] | null | null | null | datcore-sdk/python/datcore_sdk/api/security_api.py | mguidon/aiohttp-dsm | 612e4c7f6f73df7d6752269965c428fda0276191 | [
"MIT"
] | null | null | null | datcore-sdk/python/datcore_sdk/api/security_api.py | mguidon/aiohttp-dsm | 612e4c7f6f73df7d6752269965c428fda0276191 | [
"MIT"
] | null | null | null | # coding: utf-8
"""
Blackfynn Swagger
Swagger documentation for the Blackfynn api # noqa: E501
OpenAPI spec version: 1.0.0
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from datcore_sdk.api_client import ApiClient
class SecurityApi(object):
"""NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def get_temporary_streaming_credentials(self, **kwargs): # noqa: E501
"""gets temporary credentials for allowing a user to write to a real time inbound stream # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_temporary_streaming_credentials(async_req=True)
>>> result = thread.get()
:param async_req bool
:return: TemporaryCredentialResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_temporary_streaming_credentials_with_http_info(**kwargs) # noqa: E501
else:
(data) = self.get_temporary_streaming_credentials_with_http_info(**kwargs) # noqa: E501
return data
def get_temporary_streaming_credentials_with_http_info(self, **kwargs): # noqa: E501
"""gets temporary credentials for allowing a user to write to a real time inbound stream # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_temporary_streaming_credentials_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool
:return: TemporaryCredentialResponse
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = [] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_temporary_streaming_credentials" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/security/user/credentials/streaming', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='TemporaryCredentialResponse', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
def get_temporary_upload_credentials(self, dataset, **kwargs): # noqa: E501
"""gets temporary credentials for a users folder in the s3 bucket # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_temporary_upload_credentials(dataset, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str dataset: (required)
:return: UploadCredentialsResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_temporary_upload_credentials_with_http_info(dataset, **kwargs) # noqa: E501
else:
(data) = self.get_temporary_upload_credentials_with_http_info(dataset, **kwargs) # noqa: E501
return data
def get_temporary_upload_credentials_with_http_info(self, dataset, **kwargs): # noqa: E501
"""gets temporary credentials for a users folder in the s3 bucket # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_temporary_upload_credentials_with_http_info(dataset, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str dataset: (required)
:return: UploadCredentialsResponse
If the method is called asynchronously,
returns the request thread.
"""
local_var_params = locals()
all_params = ['dataset'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
for key, val in six.iteritems(local_var_params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_temporary_upload_credentials" % key
)
local_var_params[key] = val
del local_var_params['kwargs']
# verify the required parameter 'dataset' is set
if ('dataset' not in local_var_params or
local_var_params['dataset'] is None):
raise ValueError("Missing the required parameter `dataset` when calling `get_temporary_upload_credentials`") # noqa: E501
collection_formats = {}
path_params = {}
if 'dataset' in local_var_params:
path_params['dataset'] = local_var_params['dataset'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# Authentication setting
auth_settings = ['api_key'] # noqa: E501
return self.api_client.call_api(
'/security/user/credentials/upload/{dataset}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='UploadCredentialsResponse', # noqa: E501
auth_settings=auth_settings,
async_req=local_var_params.get('async_req'),
_return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501
_preload_content=local_var_params.get('_preload_content', True),
_request_timeout=local_var_params.get('_request_timeout'),
collection_formats=collection_formats)
| 37.303738 | 134 | 0.63535 | 913 | 7,983 | 5.257393 | 0.16977 | 0.041667 | 0.058333 | 0.03 | 0.82 | 0.806042 | 0.803958 | 0.78875 | 0.7725 | 0.7725 | 0 | 0.015022 | 0.282851 | 7,983 | 213 | 135 | 37.478873 | 0.823406 | 0.326945 | 0 | 0.703704 | 1 | 0 | 0.161576 | 0.073151 | 0 | 0 | 0 | 0 | 0 | 1 | 0.046296 | false | 0 | 0.037037 | 0 | 0.148148 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
f6ec817bc9ad37e4fc11c44d0b1e1a54cde3e9eb | 3,038 | py | Python | tests/test_expressions.py | norecces/pymeera | 14cfff6797b0bda231980d9329b480b2c178c803 | [
"MIT"
] | null | null | null | tests/test_expressions.py | norecces/pymeera | 14cfff6797b0bda231980d9329b480b2c178c803 | [
"MIT"
] | null | null | null | tests/test_expressions.py | norecces/pymeera | 14cfff6797b0bda231980d9329b480b2c178c803 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals, division
import unittest
import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from pymeera.utils.exprparser import Expression
class TestExpressionParser(unittest.TestCase):
def test_simple(self):
expr = 'q1 by q2'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_simple_pads(self):
expr = 'q1 by (q2)'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_plus(self):
expr = 'q1 by q2 + q3'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2'], ['q3']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_simple_plus_pads(self):
expr = 'q1 by (q2 + q3)'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2'], ['q3']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_simple_cross(self):
expr = 'q1 by q2 > q3'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2', 'q3']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_simple_cross_pads(self):
expr = 'q1 by (q2 > q3)'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2', 'q3']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_simple_cross_plus_pads(self):
expr = 'q1 by (q2 + q3) > q4'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q2', 'q4'], ['q3', 'q4']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_stacked_cross_plus_pads(self):
expr = 'q1 by q5 + (q2 + q3) > q4'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual([['q5'], ['q2', 'q4'], ['q3', 'q4']], parsed['columns'])
self.assertIsNone(parsed['additional_axis'])
def test_multidim(self):
expr = 'q1 by q5 + (q2 + q3) > (q4 + q5) > q6 by q7'
parsed = Expression.parse(expression=expr)
self.assertEqual([['q1']], parsed['rows'])
self.assertEqual(
[['q5'], ['q2', 'q4', 'q6'], ['q2', 'q5', 'q6'], ['q3', 'q4', 'q6'], ['q3', 'q5', 'q6']],
parsed['columns']
)
self.assertEqual([['q7']], parsed['additional_axis'])
| 33.755556 | 101 | 0.591178 | 344 | 3,038 | 5.104651 | 0.15407 | 0.162301 | 0.051253 | 0.061503 | 0.806948 | 0.806948 | 0.80467 | 0.797267 | 0.764237 | 0.764237 | 0 | 0.032068 | 0.219882 | 3,038 | 89 | 102 | 34.134831 | 0.708861 | 0.006912 | 0 | 0.5 | 0 | 0 | 0.159867 | 0 | 0 | 0 | 0 | 0 | 0.421875 | 1 | 0.140625 | false | 0 | 0.078125 | 0 | 0.234375 | 0.015625 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
f6f7d9a802e4c285d5bbc82fa3aba9bca3ef060f | 188 | py | Python | addons/crm/tests/__init__.py | jjiege/odoo | fd5b8ad387c1881f349d125cbd56433f4d49398f | [
"MIT"
] | null | null | null | addons/crm/tests/__init__.py | jjiege/odoo | fd5b8ad387c1881f349d125cbd56433f4d49398f | [
"MIT"
] | null | null | null | addons/crm/tests/__init__.py | jjiege/odoo | fd5b8ad387c1881f349d125cbd56433f4d49398f | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from . import test_crm_lead
from . import test_new_lead_notification
from . import test_lead2opportunity
from . import test_crm_activity
from . import test_crm_ui
| 23.5 | 40 | 0.787234 | 28 | 188 | 4.928571 | 0.464286 | 0.362319 | 0.507246 | 0.369565 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012346 | 0.138298 | 188 | 7 | 41 | 26.857143 | 0.839506 | 0.111702 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
f6fdf850c2d6d510d98ff0d6acf076abc878a5cf | 4,140 | py | Python | tests/test_ws_get_account_trades.py | Mai-Te-Pora/tradehub-python | 8355b862f5cabeb9f5ee3d17682941116c95d08c | [
"MIT"
] | 7 | 2021-01-18T07:50:22.000Z | 2022-01-16T15:14:08.000Z | tests/test_ws_get_account_trades.py | Mai-Te-Pora/tradehub-python | 8355b862f5cabeb9f5ee3d17682941116c95d08c | [
"MIT"
] | 13 | 2021-01-22T12:26:56.000Z | 2021-03-07T09:24:49.000Z | tests/test_ws_get_account_trades.py | Mai-Te-Pora/tradehub-python | 8355b862f5cabeb9f5ee3d17682941116c95d08c | [
"MIT"
] | 1 | 2022-01-16T15:14:13.000Z | 2022-01-16T15:14:13.000Z | import asyncio
import concurrent
from typing import Optional
from tests import APITestCase, MAINNET_WS_URI, WEBSOCKET_TIMEOUT_GET_REQUEST, WALLET_DEVEL
from tradehub.websocket_client import DemexWebsocket
class TestWSGetAccountTrades(APITestCase):
def test_get_account_trades_structure(self):
"""
Check if response match expected dict structure.
:return:
"""
expect: dict = {
"id": str,
"result": [
{
"base_precision": int,
"quote_precision": int,
"fee_precision": int,
"order_id": str,
"market": str,
"side": str,
"quantity": str,
"price": str,
"fee_amount": str,
"fee_denom": str,
"address": str,
"block_height": str,
"block_created_at": str,
"id": int
}
]
}
# connect to websocket
client = DemexWebsocket(uri=MAINNET_WS_URI)
# little work around to save the response
self.response: Optional[dict] = None
async def on_connect():
await client.get_account_trades('account_trades', WALLET_DEVEL)
async def on_message(message: dict):
# save response into self
self.response = message
await client.disconnect()
try:
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(client.connect(on_connect_callback=on_connect,
on_receive_message_callback=on_message),
WEBSOCKET_TIMEOUT_GET_REQUEST))
except concurrent.futures._base.TimeoutError:
raise TimeoutError("Test did not complete in time.")
if not self.response:
raise RuntimeError("Did not receive a response.")
self.assertDictStructure(expect, self.response)
self.assertTrue(len(self.response["result"]) == 100, msg=f"Expected 100 recent trades, got {len(self.response['result'])}")
def test_get_account_trades_pagination(self):
"""
Check if response match expected dict structure.
:return:
"""
expect: dict = {
"id": str,
"result": [
{
"base_precision": int,
"quote_precision": int,
"fee_precision": int,
"order_id": str,
"market": str,
"side": str,
"quantity": str,
"price": str,
"fee_amount": str,
"fee_denom": str,
"address": str,
"block_height": str,
"block_created_at": str,
"id": int
}
]
}
# connect to websocket
client = DemexWebsocket(uri=MAINNET_WS_URI)
# little work around to save the response
self.response: Optional[dict] = None
async def on_connect():
await client.get_account_trades('account_trades', WALLET_DEVEL, page=1)
async def on_message(message: dict):
# save response into self
self.response = message
await client.disconnect()
try:
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(client.connect(on_connect_callback=on_connect,
on_receive_message_callback=on_message),
WEBSOCKET_TIMEOUT_GET_REQUEST))
except asyncio.TimeoutError:
raise TimeoutError("Test did not complete in time.")
if not self.response:
raise RuntimeError("Did not receive a response.")
self.assertDictStructure(expect, self.response)
| 34.5 | 131 | 0.511111 | 380 | 4,140 | 5.357895 | 0.265789 | 0.058939 | 0.031434 | 0.03831 | 0.82613 | 0.803536 | 0.803536 | 0.803536 | 0.803536 | 0.803536 | 0 | 0.002856 | 0.407971 | 4,140 | 119 | 132 | 34.789916 | 0.827825 | 0.069082 | 0 | 0.752941 | 0 | 0 | 0.127839 | 0.007924 | 0 | 0 | 0 | 0 | 0.035294 | 1 | 0.023529 | false | 0 | 0.058824 | 0 | 0.094118 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
101abf84af3721098f6c015c8aa0c2d1f6173a06 | 5,157 | py | Python | funcion_cruza.py | Mals12/Proyecto-AG | 24778c94cab421c29950732e1a23b17eb52e7cf0 | [
"MIT"
] | null | null | null | funcion_cruza.py | Mals12/Proyecto-AG | 24778c94cab421c29950732e1a23b17eb52e7cf0 | [
"MIT"
] | null | null | null | funcion_cruza.py | Mals12/Proyecto-AG | 24778c94cab421c29950732e1a23b17eb52e7cf0 | [
"MIT"
] | null | null | null | import random as rm
import collections
import numpy as np
def cruza_extre(pobla_padres):
pobla_hijos=[]
for i in range(0,25):
papa1=pobla_padres[2*i]
papa2=pobla_padres[2*i+1]
khijo=[]
khijo2=[]
e=[]
for i in range(0,8):
pos_en_papa2 = papa2.index(papa1[i])
if i <= 6:
if pos_en_papa2 != 7:
ex = [papa1[i - 1], papa1[i + 1], papa2[pos_en_papa2 - 1], papa2[pos_en_papa2 + 1]]
e.append(ex)
else:
ex = [papa1[i - 1], papa1[i + 1], papa2[pos_en_papa2 - 1], papa2[i - i]]
e.append(ex)
else:
if pos_en_papa2 != 7:
ex = [papa1[i - 1], papa1[i - i], papa2[pos_en_papa2 - 1], papa2[pos_en_papa2 + 1]]
e.append(ex)
else:
ex = [papa1[i - 1], papa1[i - i], papa2[pos_en_papa2 - 1], papa2[i - i]]
e.append(ex)
#print(e)
N=rm.randrange(0,8)
while len(khijo)<len(papa1):
khijo.append(N)
cokhijo=khijo.copy()
#print(khijo)
for m in range(0,2):
for i in range(len(e)):
if N in e[i]:
posN=e[i].index(N)
e[i].pop(posN)
inde=papa1.index(N)
lista_ext_N=e[inde]
if len(lista_ext_N)!=0:
ele_leN = lista_ext_N
elem_rep=[x for x,y in collections.Counter(ele_leN).items() if y>1]
if len(elem_rep)== 1 or len(elem_rep)==2:
N=elem_rep[0]
else:
jlon=[]
jpos=[]
for i in range(len(lista_ext_N)):
pos_leN=papa1.index(lista_ext_N[i])
jpos.append(pos_leN)
lisext_pos_leN=e[pos_leN]
jlon.append(len(lisext_pos_leN))
elerep_jlon=[x for x,y in collections.Counter(jlon).items() if y>1]
x=min(jlon)
if x in elerep_jlon:
g=[]
for i in range(0,8):
if i not in cokhijo:
g.append(i)
while len(cokhijo)<8:
Nn=rm.choice(g)
g.remove(Nn)
cokhijo.append(Nn)
N=Nn
else:
x_jlon=jlon.index(x)
x_jpos=jpos[x_jlon]
N=papa1[x_jpos]
else:
g=[]
for i in range(0,8):
if i not in cokhijo:
g.append(i)
while len(cokhijo)<8:
Nn=rm.choice(g)
g.remove(Nn)
cokhijo.append(Nn)
N=Nn
N=rm.randrange(0,8)
while len(khijo2)<len(papa1):
khijo2.append(N)
cokhijo2=khijo2.copy()
#print(khijo2)
for m in range(0,2):
for i in range(len(e)):
if N in e[i]:
posN=e[i].index(N)
e[i].pop(posN)
inde=papa1.index(N)
lista_ext_N=e[inde]
if len(lista_ext_N)!=0:
ele_leN = lista_ext_N
elem_rep=[x for x,y in collections.Counter(ele_leN).items() if y>1]
if len(elem_rep)== 1 or len(elem_rep)==2:
N=elem_rep[0]
else:
jlon=[]
jpos=[]
for i in range(len(lista_ext_N)):
pos_leN=papa1.index(lista_ext_N[i])
jpos.append(pos_leN)
lisext_pos_leN=e[pos_leN]
jlon.append(len(lisext_pos_leN))
elerep_jlon=[x for x,y in collections.Counter(jlon).items() if y>1]
x=min(jlon)
if x in elerep_jlon:
g=[]
for i in range(0,8):
if i not in cokhijo2:
g.append(i)
while len(cokhijo2)<8:
Nn=rm.choice(g)
g.remove(Nn)
cokhijo2.append(Nn)
N=Nn
else:
x_jlon=jlon.index(x)
x_jpos=jpos[x_jlon]
N=papa1[x_jpos]
else:
g=[]
for i in range(0,8):
if i not in cokhijo2:
g.append(i)
while len(cokhijo2)<8:
Nn=rm.choice(g)
g.remove(Nn)
cokhijo2.append(Nn)
N=Nn
pobla_hijos.append(khijo)
pobla_hijos.append(khijo2)
return pobla_hijos
| 38.2 | 103 | 0.38472 | 611 | 5,157 | 3.109656 | 0.11293 | 0.044211 | 0.031579 | 0.057895 | 0.821579 | 0.815263 | 0.808421 | 0.785263 | 0.785263 | 0.785263 | 0 | 0.04195 | 0.51464 | 5,157 | 134 | 104 | 38.485075 | 0.717139 | 0.006399 | 0 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.007692 | false | 0 | 0.023077 | 0 | 0.038462 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
d63193b20fc4e30d68bd0e335ccf124f79c3c31a | 6,483 | py | Python | buyer/tests.py | mrajeswarasai/CollegeMart | 34b4087e84fd753a4796ee1cdbd53d22f637f011 | [
"Apache-2.0"
] | null | null | null | buyer/tests.py | mrajeswarasai/CollegeMart | 34b4087e84fd753a4796ee1cdbd53d22f637f011 | [
"Apache-2.0"
] | 3 | 2021-06-08T22:29:18.000Z | 2022-03-12T00:48:30.000Z | buyer/tests.py | mrajeswarasai/CollegeMart | 34b4087e84fd753a4796ee1cdbd53d22f637f011 | [
"Apache-2.0"
] | null | null | null | # Create your tests here.
from django.contrib.auth.models import User
from django.utils import timezone
from django.test import TestCase, Client
from accounts.models import Profile
from seller.models import Products_Selling, Products_Leasing,Category
from .models import Orders_Buying, Orders_Leasing
class TestOB(TestCase):
def create_category(self, category):
return Category.objects.create(name=category)
def create_seller(self):
user = User.objects.create(username='Jagan', password='asdfghjkl', email='a@iiits.in')
return Profile.objects.create(user=user, fname="test", lname="tester", dob="2017-09-23", phone="+919110678098")
def create_buyer(self):
user = User.objects.create(username='Charan', password='qsefthuko', email='b@iiits.in')
return Profile.objects.create(user=user, fname="test", lname="tester", dob="2017-09-23", phone="+919910678098")
def create_SP(self, pname='Discrete Mathematics', description="yes, this is only a test",price="840.00",):
return Products_Selling.objects.create(pname=pname, description=description, price=price,
created_at=timezone.now(), category=self.create_category("Hostel"),
seller=self.create_seller())
def create_OB(self):
return Orders_Buying.objects.create(products_selling=self.create_SP(), buyer=self.create_buyer(),
created_at=timezone.now(), isConfirmed = "1")
def test_whatever_creation(self):
w = self.create_OB()
self.assertTrue(isinstance(w, Orders_Buying))
class TestOL(TestCase):
def create_category(self, category):
return Category.objects.create(name=category)
def create_seller(self):
user = User.objects.create(username='Jagan', password='asdfghjkl', email='a@iiits.in')
return Profile.objects.create(user=user,fname="test",lname="tester",dob="2017-09-23",phone="+919110678098")
def create_buyer(self):
user = User.objects.create(username='Charan', password='qsefthuko', email='b@iiits.in')
return Profile.objects.create(user=user, fname="test", lname="tester", dob="2017-09-23", phone="+919910678098")
def create_LP(self, pname='Discrete Mathematics', description="yes, this is only a test",price="840.00",):
return Products_Leasing.objects.create(pname1=pname, description1=description,price1=price,
updated_at=timezone.now(),category1=self.create_category("Hostel"),
leaser=self.create_seller(),leasing_period="9")
def create_OL(self):
return Orders_Leasing.objects.create(products_leasing=self.create_LP(),buyer=self.create_buyer(),
created_at=timezone.now(),isConfirmed = "1")
def test_whatever_creation(self):
w = self.create_OL()
self.assertTrue(isinstance(w, Orders_Leasing))
# URL Testing
class UrlTesting(TestCase):
def setUp(self):
self.createduser = User.objects.create_user(username="collegemart", email="collegemart@iiits.in",
password="collegemart123")
self.client = None
self.request_url = '/buyer/about/'
def test_feedback(self):
self.client=Client()
response=self.client.get(self.request_url)
self.assertEqual(response.status_code,200)
def test_register1(self):
self.client = Client()
self.client.force_login(self.createduser)
response = self.client.get(self.request_url)
self.assertEqual(response.status_code, 200)
class cartUrlTesting(TestCase):
def setUp(self):
self.createduser = User.objects.create_user(username="collegemart", email="collegemart@iiits.in",
password="collegemart123")
self.client = None
self.request_url = '/buyer/cart/'
def test_feedback(self):
self.client=Client()
response=self.client.get(self.request_url)
self.assertEqual(response.status_code,302)
def test_register1(self):
self.client = Client()
self.client.force_login(self.createduser)
response = self.client.get(self.request_url)
self.assertEqual(response.status_code, 200)
class paymentUrlTesting(TestCase):
def setUp(self):
self.createduser = User.objects.create_user(username="collegemart", email="collegemart@iiits.in",
password="collegemart123")
self.client = None
self.request_url = '/payment/payment'
def test_feedback(self):
self.client=Client()
response=self.client.get(self.request_url)
self.assertEqual(response.status_code,301)
class homeUrlTesting(TestCase):
def setUp(self):
self.createduser = User.objects.create_user(username="collegemart", email="collegemart@gmail.com",
password="collegemart123")
self.client = None
self.request_url = '/buyer/'
def test_feedback(self):
self.client=Client()
response=self.client.get(self.request_url)
self.assertEqual(response.status_code,200)
def test_register1(self):
self.client = Client()
self.client.force_login(self.createduser)
response = self.client.get(self.request_url)
self.assertEqual(response.status_code, 200)
class checkoutUrlTesting(TestCase):
def setUp(self):
self.createduser = User.objects.create_user(username="collegemart", email="collegemart@gmail.com",
password="collegemart123")
self.client = None
self.request_url = '/accounts/reset-password/complete/'
class shopUrlTesting(TestCase):
def setUp(self):
self.createduser = User.objects.create_user(username="collegemart", email="collegemart@gmail.com",
password="collegemart123")
self.client = None
self.request_url = '/accounts/reset-password/complete/'
def test_register1(self):
self.client = Client()
self.client.force_login(self.createduser)
response = self.client.get(self.request_url)
self.assertEqual(response.status_code, 200) | 43.22 | 119 | 0.640444 | 719 | 6,483 | 5.662031 | 0.16968 | 0.063866 | 0.048145 | 0.039302 | 0.785802 | 0.770572 | 0.770572 | 0.770572 | 0.770572 | 0.769344 | 0 | 0.02913 | 0.242789 | 6,483 | 150 | 120 | 43.22 | 0.800163 | 0.005399 | 0 | 0.689655 | 0 | 0 | 0.113869 | 0.020323 | 0 | 0 | 0 | 0 | 0.086207 | 1 | 0.224138 | false | 0.103448 | 0.051724 | 0.051724 | 0.431034 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 7 |
613baa67f287205f38d31e2e794630befcb33e32 | 37 | py | Python | UnitTesting/test_helper.py | aawadall/PyProjMan | 49b341b79db5fba45ae347a760d05dea7a49df40 | [
"MIT"
] | 5 | 2017-09-06T00:06:12.000Z | 2021-01-20T23:04:47.000Z | UnitTesting/test_helper.py | aawadall/PyProjMan | 49b341b79db5fba45ae347a760d05dea7a49df40 | [
"MIT"
] | 80 | 2017-09-03T18:06:40.000Z | 2017-09-21T17:50:26.000Z | UnitTesting/test_helper.py | aawadall/PyProjMan | 49b341b79db5fba45ae347a760d05dea7a49df40 | [
"MIT"
] | 3 | 2017-09-05T19:18:58.000Z | 2017-09-16T19:56:21.000Z | def prepare_type1():
return None
| 12.333333 | 20 | 0.702703 | 5 | 37 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.034483 | 0.216216 | 37 | 2 | 21 | 18.5 | 0.827586 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0 | 0.5 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
61a196dbe58cabe092217c5c726d208457727f4b | 7,310 | py | Python | src/test_extractor.py | nima3333/sram_puf_exp | f2b0d0163a44e928e8009a7d5cb58a8e4801a6c9 | [
"MIT"
] | null | null | null | src/test_extractor.py | nima3333/sram_puf_exp | f2b0d0163a44e928e8009a7d5cb58a8e4801a6c9 | [
"MIT"
] | null | null | null | src/test_extractor.py | nima3333/sram_puf_exp | f2b0d0163a44e928e8009a7d5cb58a8e4801a6c9 | [
"MIT"
] | 1 | 2022-02-08T13:47:52.000Z | 2022-02-08T13:47:52.000Z | import unittest
from extractor import *
class Test(unittest.TestCase):
def test_get_serial_matrix(self):
test = [b'BEGINNING\r\n', b'2047\r\n', b'0 0 0 0 6 1 66 0 93 0 53 1 C4 0 A2 0 \r\n', b'B6 0 D A 0 0 45 18 0 0 0 1C 0 0 0 4 \r\n', b'1 0 0 E8 3 0 0 0 0 0 0 C5 0 C4 0 C0 \r\n', b'0 C1 0 C2 0 C6 0 1 0 0 2D 2E 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 47 49 4E 4E \r\n', b'49 4E 47 D A 32 30 34 37 D A 30 20 30 20 30 \r\n', b'20 30 20 20 20 20 20 20 D A 20 20 20 20 D A \r\n', b'20 20 20 20 D A 20 20 20 20 20 D A D A D \r\n', b'A D A 20 20 20 20 D A 20 20 20 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 \r\n', b'0 0 0 FD 7B AF DA 33 1C 24 1F FC 26 BF D4 8B \r\n', b'38 9F 58 E2 46 F2 CD F7 E5 AF 53 CB F7 A7 F1 D5 \r\n', b'33 41 E3 55 BC 68 CE C1 B9 B0 3E E0 9F 3B 73 D3 \r\n', b'BC 31 8A 43 5B DB 21 A5 DF EC E2 3F 40 55 7B 1B \r\n', b'A7 FC 7E A3 51 3D 17 F7 BB E0 19 8B 9B 34 9 6C \r\n', b'46 3B D6 88 D3 A5 7A 79 DE 7F 79 B3 59 47 A9 9E \r\n', b'8A 89 78 F9 20 0 23 FE 3F 43 A5 A1 1E 83 DE CE \r\n', b'6B 87 A1 B3 91 36 72 26 F6 9A 48 CF F7 2D 74 D9 \r\n', b'87 3B 62 F7 D3 EE 1F 7B 94 22 B3 BC E ED 8B E6 \r\n', b'F BF EE 71 A6 C7 C B9 BF 3A DB 89 E6 29 FF 8E \r\n', b'7A 16 9D D6 9C 69 E5 68 F6 45 DF EF 33 43 EA E6 \r\n', b'F5 27 7B E3 52 4A 32 EF 5E CE 6D 79 DB 8F 79 FC \r\n', b'74 8B 11 A3 17 44 27 B8 39 AE 93 9B 75 95 F9 2F \r\n', b'4B 59 DB 92 EF FD E2 34 75 19 CF F8 F3 B7 91 9F \r\n', b'69 1 89 2E 76 A6 FB EB 92 7D AB 1F C3 71 5E 1 \r\n', b'E2 1E 8C 61 CD FB 31 73 5F A7 92 C3 BC 71 40 F1 \r\n', b'8E BD EB DF 83 7A 28 8D 93 3F 1C F5 74 5B 49 E2 \r\n', b'ED CE 1D 10 EF 85 91 DE 61 9B DA 58 51 BC CF 17 \r\n', b'DB CC 3 1F F2 36 D8 71 8B 22 7F E2 C7 94 1F 7E \r\n', b'A9 6C BC 23 A9 FA 1D 57 DF EF FA AE C8 4E 6E BC \r\n', b'F BE E2 F4 F1 FF CF 77 C9 FB 8D E9 A6 D7 4F 92 \r\n', b'C9 AD 85 5D 4F F1 D3 AE 82 DE C9 BA CB 2B 9F F3 \r\n', b'17 1A 7D D0 2C 12 30 8F CE 6E 70 1E D3 6D E7 64 \r\n', b'83 37 14 2A 42 9F 71 86 B8 34 AE FC D6 8E BE EC \r\n', b'1C 64 BF 39 37 C4 56 E4 BE 48 34 EC CE FA DF B0 \r\n', b'DF 19 34 CE 3F 41 7A 1F 9B 6F FD 94 31 66 E 6F \r\n', b'FA 37 A7 60 5B 45 E6 6D 35 73 C3 B8 B5 3C 6E 7E \r\n', b'BF 79 32 D0 EE 59 84 1D C 66 2B BB F7 BE 67 79 \r\n', b'F3 27 7B 7B 59 D3 FB 6E C 7E 1F 8B B6 4F A5 7B \r\n', b'DB 47 C1 7E 3F AA 7E 5E AF 85 E8 97 2D D4 60 77 \r\n', b'D AA 78 55 4F 7A DA 4C AE 3E ED 5 EF B5 E9 97 \r\n', b'9 CA EA 91 FF C3 E5 BE B5 58 CC BB 24 AD BF FC \r\n', b'77 63 7F C1 C5 37 71 54 86 F2 16 6F 8B 37 9B CE \r\n', b'35 57 AA 72 32 AA 3F 4 A3 2A 8B D5 74 DA 97 D4 \r\n', b'7D CB 6D 93 FE F2 BF AD 7E EC 1C 1A 27 5F 76 3F \r\n', b'9B A7 3F C6 3B 69 B3 F2 5F 7F 3A B9 F3 D1 D8 40 \r\n', b'8F 34 3E 9C AF E9 5 FD FD 6D 15 A8 95 41 AB 6D \r\n', b'5D 15 FA 8A F3 3D B4 E1 D CD B4 F6 D5 7C BC E3 \r\n', b'52 7D 41 EB 46 22 2A EF 7B A 9F E8 DA DF 4B 4B \r\n', b'DB BF F6 DA E8 FD 13 CB 9A A1 E3 F5 19 C0 BB CC \r\n', b'D1 77 D4 C2 15 98 3F DB 2F 5 C6 CE C2 57 BE 6B \r\n', b'7D DF 5B AE C5 2F F5 E7 23 71 1 DC EC 58 1F 6E \r\n', b'DF C3 7 D7 EE EA E6 DF 27 50 46 41 11 2F 1 37 \r\n', b'57 FC 1E A7 F2 97 E6 17 2D CB AA F5 DA FD 3C 8C \r\n', b'2D DF 17 65 1F 56 68 DB C3 A7 4D 57 93 B4 FB C7 \r\n', b'6A 72 A9 B5 AD FD CE 48 1E 83 BF 7B C3 DA ED E5 \r\n', b'BF F7 9B 7C CE 6B 7B E8 5F 60 92 5 BF 5E B8 9C \r\n', b'69 E6 CC 8B F6 E8 D4 7F 4A 71 A8 20 79 A5 E3 BB \r\n', b'DB CD 34 AD 3A C F0 3E 95 37 6A F5 AD 81 B2 0 \r\n', b'7A B 2 65 69 7F E2 59 B7 3E C3 F5 99 CC F1 1D \r\n', b'99 B9 F2 E5 76 AF 8E B7 9D 5F FB 8B CD E8 92 F8 \r\n', b'F7 BF 5B B6 4F 7B E2 78 C8 E4 C6 F9 D0 93 75 47 \r\n', b'49 FC B8 FB 8E B4 E2 FF A B 3D B9 3F FC A3 2D \r\n', b'65 1B 3C 4B FF FE B E9 7B 8A 64 B9 3C F0 8F A2 \r\n', b'BB E9 35 2B 9C 9 C7 E7 77 AE 58 6 B9 EC FD 15 \r\n', b'F7 86 5F CB DD FC F1 4F 4F FE 63 84 1A 3E FB BF \r\n', b'9B D7 E8 B0 F4 36 E4 DD 98 DD A7 3B C2 6A D7 83 \r\n', b'7F AD F3 5B B6 DF DB BF CA 34 7F 8D 9F 50 A0 F9 \r\n', b'67 3F A5 AD 28 42 1F B3 AF F5 FA BA FA 73 2D D9 \r\n', b'8B 5D AA FC F3 CC 5A DC A9 E9 4F FE DB 6C F5 B1 \r\n', b'E E1 EA EB 78 71 FA A7 B4 2D 3F FF A2 4 2D AA \r\n', b'D6 AC 63 3C 1A 6D 63 D1 43 9F C4 6 F9 F8 55 D7 \r\n', b'1B FF DD A8 5C D1 D3 DB 51 E4 F4 FF 2B 87 1E 59 \r\n', b'22 ED 68 FC CB C1 93 D2 C7 81 83 9E F5 50 64 7B \r\n', b'42 FA 99 52 CB F9 EB A0 BD D9 78 A1 F6 23 F4 DB \r\n', b'2A 9 3D CC 41 47 C6 DD 3F 7E 62 4 CD B2 36 19 \r\n', b'FD 7C 5B 16 CF E5 FA 72 F4 BB 6C 5F EB 77 7D 76 \r\n', b'AE 67 1B 3F 2A 47 8F 24 B7 E9 28 A7 CE AD 38 CD \r\n', b'3F EF F3 96 72 B9 6F E 55 99 35 6F F7 CE 9B 97 \r\n', b'71 93 E9 3A AF A1 83 C5 33 6E 1E F6 F 89 69 E3 \r\n', b'72 CF 1A CE 3A 24 DF 8F FF C1 21 6F D7 80 6C E7 \r\n', b'3B 73 B5 F7 47 44 A7 A9 15 33 14 1F C6 5E EF 86 \r\n', b'9B 31 6B DE AD FF F3 ED 68 74 19 DF FA A1 A7 99 \r\n', b'1B F9 58 EF FA 77 E 7A 3B 52 7F CA 13 D5 DA 5A \r\n', b'6B EA 75 9A B1 57 B9 77 3A 85 DC C7 B7 C6 FE 3A \r\n', b'2B B6 13 EE B0 E3 73 EF 7B D5 9E F7 4F C1 F2 FE \r\n', b'13 C8 88 B4 9B 3D BA E5 42 FF 42 F4 8A 71 73 36 \r\n', b'DF 7C FE 93 6E 69 3A AA EB 24 48 FA 37 DF 78 E5 \r\n', b'93 6F E0 5A CB 3D 91 9D FB 8F EE BB C3 5 EF 69 \r\n', b'D6 D5 EC EF 5F 75 5E 89 C5 9 CD B3 36 A7 B6 8A \r\n', b'76 C9 AF 29 9D F8 86 E7 B7 5D 23 7A E8 C6 F6 33 \r\n', b'D2 DD 2F E1 AE F3 1C CC 5F DA 3B 51 59 68 95 CC \r\n', b'83 20 43 63 9F D2 7C 35 12 B6 A5 34 F7 16 E5 DE \r\n', b'C5 E9 9C FA 7B 8D 4E 7F 6B C7 FF A1 EB D5 D7 34 \r\n', b'61 BE BD 55 6F FD 45 69 BD B8 96 7C F 9C 81 43 \r\n', b'AB 7B 7C FF F0 7C FE 74 FE 3A 4D FC 2A 7E 5B 2D \r\n', b'8F 9A E3 B6 E6 BE DE C7 CB 6F D3 36 FB 5F 4C B8 \r\n', b'20 D6 E5 E1 D5 AD AF 36 DF C3 BB C3 49 F7 DC 4E \r\n', b'D7 F6 E6 BD C B9 6C 9F 5D 9F A1 72 A3 97 FB C1 \r\n', b'DD DF D4 D4 6E 55 BC 48 BE 63 AF F2 E5 5E F 6D \r\n', b'10 F7 8C 76 F3 DE DD 14 9F BC 35 7F BC 3C 97 5D \r\n', b'9B 3B FD 36 F8 3B 9F 71 BA F2 D6 96 81 E6 E6 29 \r\n', b'99 89 63 77 53 E5 1B 73 DB 3E 8 66 6B 9C 3D 1B \r\n', b'FE 4A 8E F8 FF 96 9F B2 71 6A B9 F9 DD C9 8B 2A \r\n', b'AF E5 E8 62 2C 6E AB CD 8 83 B1 F3 FA 8F 54 A3 \r\n', b'43 F9 36 76 AF EC F1 3F BE 58 73 F6 18 BD BB 5B \r\n', b'DD F1 F4 3E FB A5 75 48 72 2B 69 30 6B AB AC 51 \r\n', b'57 AC 65 73 31 5 EB C1 7A 49 E7 A7 19 17 7B 32 \r\n', b'F9 DA F4 F6 DE BB 77 CF E1 77 77 35 37 AB D6 4A \r\n', b'5B C6 A5 BF F3 AC 9E FF 6D 8E E6 2F FD 7E 52 2F \r\n', b'9E 60 F6 FC AE D5 D3 1C B7 52 D5 8 59 B5 ED 5B \r\n', b'55 9F EF DC B1 57 B9 78 8F 8A BF BE F8 DB A1 9C \r\n', b'6 B1 D1 CF 25 B1 EA B9 E3 3C AE E1 B6 C5 DA F8 \r\n', b'F7 E8 E7 CC 1 20 B5 1 0 0 1 20 0 1 0 8 \r\n', b'F3 8 F3 8 F2 0 85 8 D2 8 F2 0 21 7F 48 0 \r\n', b'0 1 F8 C6 FC EE CE 75 EF F7 D6 5D 55 80 A0 1 \r\n', b'1 20 0 1 1 20 1 1F 0 2 1E 0 C1 0 0 8 \r\n', b'86 FC 8 0 11 B5 FF 35 80 0 1 87 3 54 0 \r\n', b'\x00']
assert(get_serial_matrix(test).shape == (2048,))
def test_get_mem_matrix(self):
assert(get_mem_matrix("./src/1").shape == (2048,))
if __name__ == '__main__':
unittest.main() | 562.307692 | 7,000 | 0.597674 | 2,483 | 7,310 | 1.752316 | 0.112364 | 0.092393 | 0.122041 | 0.145254 | 0.079062 | 0.071937 | 0.070558 | 0.067571 | 0.066651 | 0.062974 | 0 | 0.422569 | 0.306566 | 7,310 | 13 | 7,001 | 562.307692 | 0.435786 | 0 | 0 | 0 | 0 | 0 | 0.86787 | 0 | 0 | 1 | 0 | 0 | 0.2 | 1 | 0.2 | false | 0 | 0.2 | 0 | 0.5 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
61ab3b7e9986087ef6c79480dc9637b7d3f60727 | 771 | py | Python | day04/__init__.py | T-101/aoc17 | 23bd338c89c640c5a43e1b3a41e22aed12a9c796 | [
"MIT"
] | null | null | null | day04/__init__.py | T-101/aoc17 | 23bd338c89c640c5a43e1b3a41e22aed12a9c796 | [
"MIT"
] | null | null | null | day04/__init__.py | T-101/aoc17 | 23bd338c89c640c5a43e1b3a41e22aed12a9c796 | [
"MIT"
] | null | null | null | def day04_1(arr):
ret_arr = []
for row in arr:
fail = False
row_temp = row.split()
while len(row_temp):
test_val = row_temp.pop(0)
for item in row_temp:
if test_val == item:
fail = True
if not fail:
ret_arr.append(row)
return ret_arr
def day04_2(arr):
ret_arr = []
for row in arr:
fail = False
row_temp = row.split()
while len(row_temp):
sorted_word = ''.join(sorted([s for s in row_temp.pop(0)]))
for item in row_temp:
if sorted_word == ''.join(sorted([s for s in item])):
fail = True
if not fail:
ret_arr.append(row)
return ret_arr
| 24.09375 | 71 | 0.490272 | 106 | 771 | 3.377358 | 0.273585 | 0.156425 | 0.075419 | 0.067039 | 0.910615 | 0.910615 | 0.910615 | 0.910615 | 0.759777 | 0.759777 | 0 | 0.017699 | 0.413748 | 771 | 31 | 72 | 24.870968 | 0.774336 | 0 | 0 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.076923 | false | 0 | 0 | 0 | 0.153846 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
f65e903923ad1f3fe2405dfbf0ff9046ee4eaf9d | 185 | py | Python | canteen/templates/compiled/__init__.py | dbl0null/canteen | 3bef22a2059ef6ac5df178324fbc1dba45316e22 | [
"MIT"
] | 2 | 2016-08-24T18:42:41.000Z | 2017-12-08T00:41:02.000Z | canteen/templates/compiled/__init__.py | dbl0null/canteen | 3bef22a2059ef6ac5df178324fbc1dba45316e22 | [
"MIT"
] | null | null | null | canteen/templates/compiled/__init__.py | dbl0null/canteen | 3bef22a2059ef6ac5df178324fbc1dba45316e22 | [
"MIT"
] | 2 | 2015-09-22T05:36:27.000Z | 2017-12-08T00:41:21.000Z | # -*- coding: utf-8 -*-
"""
compiled templates: compiled
"""
# subtemplates
from canteen.templates.compiled.base import *
from canteen.templates.compiled.snippets.test import *
| 14.230769 | 54 | 0.708108 | 20 | 185 | 6.55 | 0.6 | 0.389313 | 0.305344 | 0.427481 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.006369 | 0.151351 | 185 | 12 | 55 | 15.416667 | 0.828025 | 0.345946 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
14745ca5f74bb93faef6409f82da8a194bf9b0b8 | 261 | py | Python | rime/plugins/rime_plus.py | matsu7874/rime | f6fd81a65dd4128d0385b0e1a11b7f7f03b342eb | [
"MIT"
] | 31 | 2017-02-20T05:04:06.000Z | 2022-01-21T09:05:17.000Z | rime/plugins/rime_plus.py | matsu7874/rime | f6fd81a65dd4128d0385b0e1a11b7f7f03b342eb | [
"MIT"
] | 62 | 2017-02-14T10:10:06.000Z | 2021-05-17T00:00:01.000Z | rime/plugins/rime_plus.py | matsu7874/rime | f6fd81a65dd4128d0385b0e1a11b7f7f03b342eb | [
"MIT"
] | 21 | 2017-02-13T16:41:42.000Z | 2021-08-19T00:34:49.000Z | #!/usr/bin/python
# import sub-modules
import rime.plugins.plus.basic_patch # NOQA
import rime.plugins.plus.commands # NOQA
import rime.plugins.plus.flexible_judge # NOQA
import rime.plugins.plus.merged_test # NOQA
import rime.plugins.plus.subtask # NOQA
| 29 | 47 | 0.781609 | 39 | 261 | 5.153846 | 0.461538 | 0.248756 | 0.422886 | 0.522388 | 0.497512 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.114943 | 261 | 8 | 48 | 32.625 | 0.87013 | 0.229885 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
14aa7b0d8012577bb67552dc6ba64bb613ae15b4 | 10,291 | py | Python | data_iterators.py | EliasVansteenkiste/bare_pytorch_project | 3d8536e203bdfa7f6b90db77ade116c8ce23e78c | [
"MIT"
] | 1 | 2017-10-10T18:02:01.000Z | 2017-10-10T18:02:01.000Z | data_iterators.py | EliasVansteenkiste/bare_pytorch_project | 3d8536e203bdfa7f6b90db77ade116c8ce23e78c | [
"MIT"
] | null | null | null | data_iterators.py | EliasVansteenkiste/bare_pytorch_project | 3d8536e203bdfa7f6b90db77ade116c8ce23e78c | [
"MIT"
] | null | null | null | import numpy as np
import itertools
import pathfinder
import utils
import app
import buffering
import os
class DataGenerator(object):
def __init__(self, dataset, batch_size, img_ids, p_transform, data_prep_fun, label_prep_fun, rng,
random, infinite, full_batch, override_patch_size=None, version=1, **kwargs):
self.dataset = dataset
self.img_ids = img_ids
self.nsamples = len(img_ids)
self.batch_size = batch_size
self.p_transform = p_transform
self.data_prep_fun = data_prep_fun
self.label_prep_fun = label_prep_fun
self.rng = rng
self.random = random
self.infinite = infinite
self.full_batch = full_batch
self.override_patch_size = override_patch_size
if override_patch_size:
self.patch_size = override_patch_size
else:
self.patch_size = self.p_transform['patch_size']
self.labels = app.get_labels_array(version=version)
def generate(self):
while True:
rand_idxs = np.arange(len(self.img_ids))
if self.random:
self.rng.shuffle(rand_idxs)
for pos in xrange(0, len(rand_idxs), self.batch_size):
idxs_batch = rand_idxs[pos:pos + self.batch_size]
nb = len(idxs_batch)
# allocate batches
if self.p_transform['channels']:
x_batch = np.zeros((nb,self.p_transform['channels'],) + self.patch_size, dtype='float32')
else:
x_batch = np.zeros((nb,) + self.patch_size, dtype='float32')
if self.p_transform['n_labels']>1:
y_batch = np.zeros((nb, self.p_transform['n_labels']), dtype='float32')
else:
y_batch = np.zeros((nb,), dtype='float32')
batch_ids = []
for i, idx in enumerate(idxs_batch):
img_id = self.img_ids[idx]
batch_ids.append(img_id)
try:
img = app.read_compressed_image(self.dataset, img_id)
except Exception:
print 'cannot open ', img_id
x_batch[i] = self.data_prep_fun(x=img)
if 'train' in self.dataset:
y_batch[i] = self.label_prep_fun(self.labels[img_id])
#print 'i', i, 'img_id', img_id, y_batch[i]
if self.full_batch:
if nb == self.batch_size:
yield x_batch, y_batch, batch_ids
else:
yield x_batch, y_batch, batch_ids
if not self.infinite:
break
class AutoEncoderDataGenerator(object):
def __init__(self, batch_size, img_paths, labeled_img_paths, p_transform, data_prep_fun, label_prep_fun, rng,
random, infinite, full_batch, **kwargs):
self.img_paths = img_paths
self.labeled_img_paths = labeled_img_paths
self.nsamples = len(img_paths)
self.batch_size = batch_size
self.p_transform = p_transform
self.data_prep_fun = data_prep_fun
self.label_prep_fun = label_prep_fun
self.rng = rng
self.random = random
self.infinite = infinite
self.full_batch = full_batch
self.labels = app.get_labels_array()
def generate(self):
while True:
rand_idxs = np.arange(len(self.img_paths))
if self.random:
self.rng.shuffle(rand_idxs)
for pos in xrange(0, len(rand_idxs), self.batch_size):
idxs_batch = rand_idxs[pos:pos + self.batch_size]
nb = len(idxs_batch)
# allocate batches
if self.p_transform['channels']:
x_batch = np.zeros((nb,self.p_transform['channels'],) + self.p_transform['patch_size'], dtype='float32')
else:
x_batch = np.zeros((nb,) + self.p_transform['patch_size'], dtype='float32')
if self.p_transform['n_labels']>1:
y_batch = np.zeros((nb, self.p_transform['n_labels']), dtype='float32')
else:
y_batch = np.zeros((nb,), dtype='float32')
z_batch = np.zeros((nb,), dtype='float32')
batch_ids = []
for i, idx in enumerate(idxs_batch):
img_path = self.img_paths[idx]
batch_ids.append(img_path)
try:
img = app.read_image_from_path(img_path)
except Exception:
print 'cannot open ', img_id
x_batch[i] = self.data_prep_fun(x=img)
if img_path in self.labeled_img_paths:
z_batch[i] = 1.
img_id = app.get_id_from_path(img_path)
y_batch[i] = self.label_prep_fun(self.labels[img_id])
#print 'i', i, 'img_id', img_id, y_batch[i]
if self.full_batch:
if nb == self.batch_size:
yield x_batch, y_batch, z_batch, batch_ids
else:
yield x_batch, y_batch, z_batch, batch_ids
if not self.infinite:
break
class SlimDataGenerator(object):
def __init__(self, dataset, batch_size, img_ids, p_transform, data_prep_fun, label_prep_fun, rng,
random, infinite, full_batch, **kwargs):
self.dataset = dataset
self.img_ids = img_ids
self.nsamples = len(img_ids)
self.batch_size = batch_size
self.p_transform = p_transform
self.data_prep_fun = data_prep_fun
self.label_prep_fun = label_prep_fun
self.rng = rng
self.random = random
self.infinite = infinite
self.full_batch = full_batch
self.labels = app.get_labels_array()
def generate(self):
while True:
rand_idxs = np.arange(len(self.img_ids))
if self.random:
self.rng.shuffle(rand_idxs)
for pos in xrange(0, len(rand_idxs), self.batch_size):
idxs_batch = rand_idxs[pos:pos + self.batch_size]
nb = len(idxs_batch)
# allocate batches
x_batch = []
y_batch = []
batch_ids = []
for i, idx in enumerate(idxs_batch):
img_id = self.img_ids[idx]
batch_ids.append(img_id)
try:
img = app.read_compressed_image(self.dataset, img_id)
except Exception:
print 'cannot open ', img_id
x_batch.append(self.data_prep_fun(x=img))
if 'train' in self.dataset:
y_batch.append(self.label_prep_fun(self.labels[img_id]))
if self.full_batch:
if nb == self.batch_size:
yield x_batch, y_batch, batch_ids
else:
yield x_batch, y_batch, batch_ids
if not self.infinite:
break
def _test_data_generator():
#testing data iterator
p_transform = {'patch_size': (256, 256),
'channels': 4,
'n_labels': 17}
rng = np.random.RandomState(42)
def data_prep_fun(x):
x = np.array(x)
x = np.swapaxes(x,0,2)
return x
def label_prep_fun(labels):
return labels
folds = app.make_stratified_split(no_folds=5)
all_ids = folds[0] + folds[1] + folds[2] + folds[3] +folds[4]
bad_ids = [18772, 28173, 5023]
img_ids = [x for x in all_ids if x not in bad_ids]
dg = DataGenerator(dataset='train-jpg',
batch_size=10,
img_ids = img_ids,
p_transform=p_transform,
data_prep_fun = data_prep_fun,
label_prep_fun = label_prep_fun,
rng=rng,
full_batch=True, random=False, infinite=False)
for (x_chunk, y_chunk, id_train) in buffering.buffered_gen_threaded(dg.generate()):
print x_chunk.shape, y_chunk.shape, id_train
def _test_simple_data_generator():
#testing data iterator
p_transform = {'patch_size': (256, 256),
'channels': 4,
'n_labels': 1}
label_id = 4
rng = np.random.RandomState(42)
def data_prep_fun(x):
return x
def label_prep_fun(labels):
print labels
return labels[label_id]
folds = app.make_stratified_split(no_folds=5)
all_ids = folds[0] + folds[1] + folds[2] + folds[3] +folds[4]
bad_ids = []
img_ids = [x for x in all_ids if x not in bad_ids]
dg = SlimDataGenerator(dataset='train-jpg',
batch_size=10,
label_id = label_id,
img_ids = all_ids,
p_transform=p_transform,
data_prep_fun = data_prep_fun,
label_prep_fun = label_prep_fun,
rng=rng,
full_batch=True,
random=False,
infinite=False)
print 'start'
avgs = []
stds = []
ch_avgs = [[],[],[],[]]
ch_stds = [[],[],[],[]]
for (x_chunk, y_chunk, id_train) in dg.generate():
x_chunk = np.stack(x_chunk)
#x_chunk = x_chunk/255.
avgs.append(np.mean(x_chunk))
stds.append(np.std(x_chunk))
for ch in range(4):
ch_avgs[ch].append(np.mean(x_chunk[:,ch]))
ch_stds[ch].append(np.std(x_chunk[:,ch]))
print 'avgs', np.mean(np.stack(avgs))
print 'stds', np.mean(np.stack(stds))
for ch in range(4):
print 'ch', str(ch)
print 'mean of avgs', np.mean(ch_avgs[ch])
print 'mean of stds', np.mean(ch_stds[ch])
if __name__ == "__main__":
_test_simple_data_generator()
| 35.732639 | 124 | 0.530075 | 1,264 | 10,291 | 4.024525 | 0.109177 | 0.049538 | 0.038923 | 0.031453 | 0.813053 | 0.766464 | 0.748575 | 0.735601 | 0.718105 | 0.702182 | 0 | 0.013054 | 0.374696 | 10,291 | 287 | 125 | 35.857143 | 0.777467 | 0.019434 | 0 | 0.660793 | 0 | 0 | 0.031743 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.030837 | null | null | 0.048458 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
1ad29a9385699fdcaff4549a27cda9752f4ba56d | 2,449 | py | Python | app/commands/account.py | godraadam/privy-cli | 1d809269e4d649b6f5f91402154873ba0ed20a87 | [
"MIT"
] | null | null | null | app/commands/account.py | godraadam/privy-cli | 1d809269e4d649b6f5f91402154873ba0ed20a87 | [
"MIT"
] | null | null | null | app/commands/account.py | godraadam/privy-cli | 1d809269e4d649b6f5f91402154873ba0ed20a87 | [
"MIT"
] | null | null | null | from typing import Optional
import typer
import requests
from store import router_url
app = typer.Typer(help="Manage accounts on this device")
@app.command()
def add(
username: Optional[str] = typer.Option(None, "--name", "-n", prompt=True),
password: Optional[str] = typer.Option(
None, "--password", "-p", prompt=True, hide_input=True
),
):
"""
Add an existing account on this device
"""
try:
response = requests.post(
f"{router_url}/api/account/add",
data={"username": username, "password": password},
)
if response.status_code == 409:
# TODO: separate username for pubkey gen from username alias
typer.echo("An account with given username already exists on this device!")
else:
typer.echo("Account addded successfully!")
except requests.exceptions.ConnectionError:
typer.echo("The privy router is not running! Please start it via privy init!")
@app.command()
def create(
username: Optional[str] = typer.Option(None, "--name", "-n", prompt=True),
password: Optional[str] = typer.Option(
None, "--password", "-p", prompt=True, hide_input=True
),
):
"""
Create a new account
"""
try:
response = requests.post(
f"{router_url}/api/account/add",
data={"username": username, "password": password},
)
if response.status_code == 409:
# TODO: separate username for pubkey gen from username alias
typer.echo("An account with given username already exists on this device!")
else:
typer.echo("Account created successfully!")
except requests.exceptions.ConnectionError:
typer.echo("The privy router is not running! Please start it via privy init!")
@app.command()
def remove(username: str = typer.Argument(...)):
"""
Remove an account from this device
"""
try:
response = requests.post(f"{router_url}/api/account/remove/{username}")
if response.status_code == 404:
# TODO: separate username for pubkey gen from username alias
typer.echo(f"No user by the name {username} was found, nothing was deleted.")
else:
typer.echo("Account removed successfully!")
except requests.exceptions.ConnectionError:
typer.echo("The privy router is not running! Please start it via privy init!")
| 34.985714 | 89 | 0.62842 | 294 | 2,449 | 5.204082 | 0.292517 | 0.052941 | 0.031373 | 0.057516 | 0.769935 | 0.769935 | 0.769935 | 0.769935 | 0.769935 | 0.769935 | 0 | 0.004929 | 0.25439 | 2,449 | 69 | 90 | 35.492754 | 0.832968 | 0.111066 | 0 | 0.686275 | 0 | 0 | 0.310944 | 0.046031 | 0 | 0 | 0 | 0.043478 | 0 | 1 | 0.058824 | false | 0.117647 | 0.078431 | 0 | 0.137255 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 7 |
dccdbf0dc2cf10a534d8bb4aa0e1247a8299eb9e | 1,495 | py | Python | application/migrations/0008_auto_20200403_1208.py | City-of-Helsinki/events-helsinki-cms | 64e4c1ce6cc058fb3783e417560dc244bd753d05 | [
"MIT"
] | 2 | 2020-04-20T05:37:28.000Z | 2021-02-19T10:33:45.000Z | application/migrations/0008_auto_20200403_1208.py | City-of-Helsinki/events-helsinki-cms | 64e4c1ce6cc058fb3783e417560dc244bd753d05 | [
"MIT"
] | 6 | 2020-02-12T12:55:37.000Z | 2021-03-30T12:56:28.000Z | application/migrations/0008_auto_20200403_1208.py | City-of-Helsinki/events-helsinki-cms | 64e4c1ce6cc058fb3783e417560dc244bd753d05 | [
"MIT"
] | 1 | 2021-02-18T12:11:18.000Z | 2021-02-18T12:11:18.000Z | # Generated by Django 2.2.9 on 2020-04-03 12:08
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('application', '0007_landingpage'),
]
operations = [
migrations.AlterField(
model_name='collections',
name='event_list_query',
field=models.URLField(max_length=500, null=True),
),
migrations.AlterField(
model_name='collections',
name='link_url_en',
field=models.URLField(blank=True, max_length=500, null=True),
),
migrations.AlterField(
model_name='collections',
name='link_url_fi',
field=models.URLField(blank=True, max_length=500, null=True),
),
migrations.AlterField(
model_name='collections',
name='link_url_sv',
field=models.URLField(blank=True, max_length=500, null=True),
),
migrations.AlterField(
model_name='landingpage',
name='button_url_en',
field=models.URLField(max_length=500, null=True),
),
migrations.AlterField(
model_name='landingpage',
name='button_url_fi',
field=models.URLField(max_length=500, null=True),
),
migrations.AlterField(
model_name='landingpage',
name='button_url_sv',
field=models.URLField(max_length=500, null=True),
),
]
| 30.510204 | 73 | 0.575251 | 152 | 1,495 | 5.467105 | 0.289474 | 0.168472 | 0.21059 | 0.244284 | 0.803851 | 0.78941 | 0.736462 | 0.736462 | 0.689531 | 0.689531 | 0 | 0.03876 | 0.309699 | 1,495 | 48 | 74 | 31.145833 | 0.766473 | 0.0301 | 0 | 0.666667 | 1 | 0 | 0.132597 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.02381 | 0 | 0.095238 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
dcf041609d85b521e716853655e94d6d945455e8 | 1,839 | py | Python | bsite.py | bnordgren/pylsce | 01d3a22bd721cbc438c8d6db28baa6061e86761a | [
"BSD-3-Clause"
] | 2 | 2018-06-25T12:31:51.000Z | 2019-12-18T12:56:10.000Z | bsite.py | bnordgren/pylsce | 01d3a22bd721cbc438c8d6db28baa6061e86761a | [
"BSD-3-Clause"
] | null | null | null | bsite.py | bnordgren/pylsce | 01d3a22bd721cbc438c8d6db28baa6061e86761a | [
"BSD-3-Clause"
] | 2 | 2018-05-26T07:06:10.000Z | 2019-12-18T12:56:15.000Z | '''
Define the site related information.
!!please note the sequence: CA-NS/CA-SF/US-Bn!!
NSlistburn=['CA-NS1 1850','CA-NS2 1930','CA-NS3 1964','CA-NS4 1964','CA-NS5 1981','CA-NS6 1989','CA-NS7 1998']
NSburn=[1850,1930,1964,1964,1981,1989,1998]
NSlist=['CA-NS1','CA-NS2','CA-NS3','CA-NS4','CA-NS5','CA-NS6','CA-NS7']
SFlistburn=['CA-SF1 1977','CA-SF2 1989','CA-SF3 1998']
SFburn=[1977,1989,1998]
SFlist=['CA-SF1','CA-SF2','CA-SF3']
Bnlistburn=['US-Bn1 1920','US-Bn2 1987','US-Bn3 1999']
Bnlist=['US-Bn1','US-Bn2','US-Bn3']
Bnburn=[1920,1987,1999]
'''
NSlistburn=['CA-NS1 1850','CA-NS2 1930','CA-NS3 1964','CA-NS4 1964','CA-NS5 1981','CA-NS6 1989','CA-NS7 1998']
NSburn=[1850,1930,1964,1964,1981,1989,1998]
NSlist=['CA-NS1','CA-NS2','CA-NS3','CA-NS4','CA-NS5','CA-NS6','CA-NS7']
SFlistburn=['CA-SF1 1977','CA-SF2 1989','CA-SF3 1998']
SFburn=[1977,1989,1998]
SFlist=['CA-SF1','CA-SF2','CA-SF3']
Bnlistburn=['US-Bn1 1920','US-Bn2 1987','US-Bn3 1999']
Bnlist=['US-Bn1','US-Bn2','US-Bn3']
Bnburn=[1920,1987,1999]
alllistburn=['CA-NS1 1850','CA-NS2 1930','CA-NS3 1964','CA-NS4 1964','CA-NS5 1981','CA-NS6 1989','CA-NS7 1998','CA-SF1 1977','CA-SF2 1989','CA-SF3 1998','US-Bn1 1920','US-Bn2 1987','US-Bn3 1999']
#alllistburndic={
# 'CA-NS1 1850',
# 'CA-NS2 1930',
# 'CA-NS3 1964',
# 'CA-NS4 1964',
# 'CA-NS5 1981',
# 'CA-NS6 1989',
# 'CA-NS7 1998',
# 'CA-SF1 1977',
# 'CA-SF2 1989',
# 'CA-SF3 1998',
# 'US-Bn1 1920',
# 'US-Bn2 1987',
# 'US-Bn3 1999'}
alllist=['CA-NS1','CA-NS2','CA-NS3','CA-NS4','CA-NS5','CA-NS6','CA-NS7','CA-SF1','CA-SF2','CA-SF3','US-Bn1','US-Bn2','US-Bn3']
allburn=[1850,1930,1964,1964,1981,1989,1998,1977,1989,1998,1920,1987,1999]
allosy=[2002,2001,2001,2002,2001,2001,2002,2003,2003,2003,2003,2003,2003]
alloey=[2005,2005,2005,2004,2005,2005,2005,2005,2005,2005,2003,2003,2003]
| 36.78 | 195 | 0.636215 | 338 | 1,839 | 3.461538 | 0.16568 | 0.041026 | 0.051282 | 0.037607 | 0.833333 | 0.792308 | 0.766667 | 0.742735 | 0.742735 | 0.742735 | 0 | 0.333135 | 0.087548 | 1,839 | 49 | 196 | 37.530612 | 0.364124 | 0.431756 | 0 | 0 | 0 | 0 | 0.432485 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
0d0cb373d97265d028318f3d30b7086c71ccd14b | 2,288 | py | Python | MidTemLabSol/AA2.py | knrastogi/PythonPrograms | b9eac94f6cfd4334a6b7f5715e93c71d6f6f716c | [
"Apache-2.0"
] | 1 | 2019-09-17T20:49:55.000Z | 2019-09-17T20:49:55.000Z | MidTemLabSol/AA2.py | knrastogi/PythonPrograms | b9eac94f6cfd4334a6b7f5715e93c71d6f6f716c | [
"Apache-2.0"
] | null | null | null | MidTemLabSol/AA2.py | knrastogi/PythonPrograms | b9eac94f6cfd4334a6b7f5715e93c71d6f6f716c | [
"Apache-2.0"
] | null | null | null | ##Q2. Write a program to swap two no.
##########################################################################
##Program Objective: to swap two no. ##
##Coded by: KNR ##
##Date: 17/09/2019 22:20 ##
##Lang: Python 3.7.4 ##
##Version: 1.0 ##
##########################################################################
### Method-1: Using multiple assignment
##print("--------------------------------------------------")
##num1 = int(input("Enter number #1:"))
##num2 = int(input("Enter number #2:"))
##print("Before swapping A: {0}, B: {1}".format(num1, num2))
##num1, num2 = num2, num1
##print("After swapping A: {0}, B: {1}".format(num1, num2))
##print("--------------------------------------------------")
### Method-2: Using a temporary variable
##print("--------------------------------------------------")
##num1 = int(input("Enter number #1:"))
##num2 = int(input("Enter number #2:"))
##print("Before swapping A: {0}, B: {1}".format(num1, num2))
##temp = num1
##num1 = num2
##num2 = temp
##print("After swapping A: {0}, B: {1}".format(num1, num2))
##print("--------------------------------------------------")
###Method-3: Without using a temporary variable v1
##print("--------------------------------------------------")
##num1 = int(input("Enter number #1:"))
##num2 = int(input("Enter number #2:"))
##print("Before swapping A: {0}, B: {1}".format(num1, num2))
##num1 = num1 + num2
##num2 = num1 - num2
##num1 = num1 - num2
##print("After swapping A: {0}, B: {1}".format(num1, num2))
##print("--------------------------------------------------")
# Method-4: Without using a temporary variable v2
print("--------------------------------------------------")
num1 = int(input("Enter number #1:"))
num2 = int(input("Enter number #2:"))
print("Before swapping A: {0}, B: {1}".format(num1, num2))
num1 = num1 * num2
num2 = num1 // num2
num1 = num1 // num2
print("After swapping A: {0}, B: {1}".format(num1, num2))
print("--------------------------------------------------")
| 40.857143 | 75 | 0.38243 | 222 | 2,288 | 3.941441 | 0.220721 | 0.146286 | 0.118857 | 0.173714 | 0.774857 | 0.706286 | 0.706286 | 0.706286 | 0.706286 | 0.706286 | 0 | 0.055336 | 0.225962 | 2,288 | 55 | 76 | 41.6 | 0.438735 | 0.690122 | 0 | 0.222222 | 0 | 0 | 0.456938 | 0.239234 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.444444 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 8 |
0d4ea9045049b9ed51bf815e4003429c0e655faf | 16,414 | py | Python | tests/ut/python/natural_robustness/test_natural_robustness.py | hboshnak/mindarmour | 0609a4eaea875a84667bed279add9305752880cc | [
"Apache-2.0"
] | null | null | null | tests/ut/python/natural_robustness/test_natural_robustness.py | hboshnak/mindarmour | 0609a4eaea875a84667bed279add9305752880cc | [
"Apache-2.0"
] | null | null | null | tests/ut/python/natural_robustness/test_natural_robustness.py | hboshnak/mindarmour | 0609a4eaea875a84667bed279add9305752880cc | [
"Apache-2.0"
] | null | null | null | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Example for natural robustness methods."""
import pytest
import numpy as np
from mindspore import context
from mindarmour.natural_robustness.transform.image import Translate, Curve, Perspective, Scale, Shear, Rotate, \
SaltAndPepperNoise, NaturalNoise, GaussianNoise, UniformNoise, MotionBlur, GaussianBlur, GradientBlur, Contrast,\
GradientLuminance
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_perspective():
"""
Feature: Test image perspective.
Description: Image will be transform for given perspective projection.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
ori_pos = [[0, 0], [0, 800], [800, 0], [800, 800]]
dst_pos = [[50, 0], [0, 800], [780, 0], [800, 800]]
trans = Perspective(ori_pos, dst_pos)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_uniform_noise():
"""
Feature: Test image uniform noise.
Description: Add uniform image in image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = UniformNoise(factor=0.1)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gaussian_noise():
"""
Feature: Test image gaussian noise.
Description: Add gaussian image in image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = GaussianNoise(factor=0.1)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_contrast():
"""
Feature: Test image contrast.
Description: Adjust image contrast.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = Contrast(alpha=0.3, beta=0)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gaussian_blur():
"""
Feature: Test image gaussian blur.
Description: Add gaussian blur to image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = GaussianBlur(ksize=5)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_salt_and_pepper_noise():
"""
Feature: Test image salt and pepper noise.
Description: Add salt and pepper to image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = SaltAndPepperNoise(factor=0.01)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_translate():
"""
Feature: Test image translate.
Description: Translate an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = Translate(x_bias=0.1, y_bias=0.1)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_scale():
"""
Feature: Test image scale.
Description: Scale an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = Scale(factor_x=0.7, factor_y=0.7)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_shear():
"""
Feature: Test image shear.
Description: Shear an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = Shear(factor=0.2)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_rotate():
"""
Feature: Test image rotate.
Description: Rotate an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = Rotate(angle=20)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_curve():
"""
Feature: Test image curve.
Description: Transform an image with curve.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = Curve(curves=1.5, depth=1.5, mode='horizontal')
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_natural_noise():
"""
Feature: Test natural noise.
Description: Add natural noise to an.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
trans = NaturalNoise(ratio=0.0001, k_x_range=(1, 30), k_y_range=(1, 10), auto_param=True)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gradient_luminance():
"""
Feature: Test gradient luminance.
Description: Adjust image luminance.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
height, width = image.shape[:2]
point = (height // 4, width // 2)
start = (255, 255, 255)
end = (0, 0, 0)
scope = 0.3
bright_rate = 0.4
trans = GradientLuminance(start, end, start_point=point, scope=scope, pattern='dark', bright_rate=bright_rate,
mode='horizontal')
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_motion_blur():
"""
Feature: Test motion blur.
Description: Add motion blur to an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
angle = -10.5
i = 3
trans = MotionBlur(degree=i, angle=angle)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gradient_blur():
"""
Feature: Test gradient blur.
Description: Add gradient blur to an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
image = np.random.random((32, 32, 3))
number = 10
h, w = image.shape[:2]
point = (int(h / 5), int(w / 5))
center = False
trans = GradientBlur(point, number, center)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_perspective_ascend():
"""
Feature: Test image perspective.
Description: Image will be transform for given perspective projection.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
ori_pos = [[0, 0], [0, 800], [800, 0], [800, 800]]
dst_pos = [[50, 0], [0, 800], [780, 0], [800, 800]]
trans = Perspective(ori_pos, dst_pos)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_uniform_noise_ascend():
"""
Feature: Test image uniform noise.
Description: Add uniform image in image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = UniformNoise(factor=0.1)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gaussian_noise_ascend():
"""
Feature: Test image gaussian noise.
Description: Add gaussian image in image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = GaussianNoise(factor=0.1)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_contrast_ascend():
"""
Feature: Test image contrast.
Description: Adjust image contrast.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = Contrast(alpha=0.3, beta=0)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gaussian_blur_ascend():
"""
Feature: Test image gaussian blur.
Description: Add gaussian blur to image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = GaussianBlur(ksize=5)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_salt_and_pepper_noise_ascend():
"""
Feature: Test image salt and pepper noise.
Description: Add salt and pepper to image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = SaltAndPepperNoise(factor=0.01)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_translate_ascend():
"""
Feature: Test image translate.
Description: Translate an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = Translate(x_bias=0.1, y_bias=0.1)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_ascend_mindarmour
def test_scale_ascend():
"""
Feature: Test image scale.
Description: Scale an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = Scale(factor_x=0.7, factor_y=0.7)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_shear_ascend():
"""
Feature: Test image shear.
Description: Shear an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = Shear(factor=0.2)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_rotate_ascend():
"""
Feature: Test image rotate.
Description: Rotate an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = Rotate(angle=20)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_curve_ascend():
"""
Feature: Test image curve.
Description: Transform an image with curve.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = Curve(curves=1.5, depth=1.5, mode='horizontal')
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_natural_noise_ascend():
"""
Feature: Test natural noise.
Description: Add natural noise to an.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
trans = NaturalNoise(ratio=0.0001, k_x_range=(1, 30), k_y_range=(1, 10), auto_param=True)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gradient_luminance_ascend():
"""
Feature: Test gradient luminance.
Description: Adjust image luminance.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
height, width = image.shape[:2]
point = (height // 4, width // 2)
start = (255, 255, 255)
end = (0, 0, 0)
scope = 0.3
bright_rate = 0.4
trans = GradientLuminance(start, end, start_point=point, scope=scope, pattern='dark', bright_rate=bright_rate,
mode='horizontal')
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_motion_blur_ascend():
"""
Feature: Test motion blur.
Description: Add motion blur to an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
angle = -10.5
i = 3
trans = MotionBlur(degree=i, angle=angle)
dst = trans(image)
print(dst)
@pytest.mark.level0
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_card
@pytest.mark.component_mindarmour
def test_gradient_blur_ascend():
"""
Feature: Test gradient blur.
Description: Add gradient blur to an image.
Expectation: success.
"""
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
image = np.random.random((32, 32, 3))
number = 10
h, w = image.shape[:2]
point = (int(h / 5), int(w / 5))
center = False
trans = GradientBlur(point, number, center)
dst = trans(image)
print(dst)
| 28.348877 | 117 | 0.707506 | 2,226 | 16,414 | 5.050314 | 0.084456 | 0.120085 | 0.072051 | 0.058708 | 0.924924 | 0.92279 | 0.92279 | 0.92279 | 0.92279 | 0.92279 | 0 | 0.032744 | 0.17016 | 16,414 | 578 | 118 | 28.397924 | 0.7926 | 0.207384 | 0 | 0.894587 | 0 | 0 | 0.014876 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.08547 | false | 0 | 0.011396 | 0 | 0.096866 | 0.08547 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
b4abc35617fbb7c127db62d6fe02b326da101525 | 2,433 | py | Python | export/model.py | FragLegs/mrnet | a05eb8902463cbcf88126c616911bd9f69d019df | [
"MIT"
] | 1 | 2021-06-18T08:16:01.000Z | 2021-06-18T08:16:01.000Z | export/model.py | FragLegs/mrnet | a05eb8902463cbcf88126c616911bd9f69d019df | [
"MIT"
] | null | null | null | export/model.py | FragLegs/mrnet | a05eb8902463cbcf88126c616911bd9f69d019df | [
"MIT"
] | null | null | null | import torch
import torch.nn as nn
from torchvision import models
class MRNet(nn.Module):
def __init__(self, pretrained=True):
super().__init__()
self.model = models.alexnet(pretrained=pretrained)
self.gap = nn.AdaptiveAvgPool2d(1)
self.classifier = nn.Linear(256, 1)
def forward(self, x):
x = torch.squeeze(x, dim=0) # only batch size 1 supported
x = self.model.features(x)
x = self.gap(x).view(x.size(0), -1)
x = torch.max(x, 0, keepdim=True)[0]
x = self.classifier(x)
return x
class MRNetSqueeze(nn.Module):
def __init__(self, pretrained=True):
super().__init__()
self.model = models.squeezenet1_0(pretrained=pretrained)
self.gap = nn.AdaptiveAvgPool2d(1)
self.classifier = nn.Linear(512, 1)
def forward(self, x):
x = torch.squeeze(x, dim=0) # only batch size 1 supported
x = self.model.features(x)
x = self.gap(x).view(x.size(0), -1)
x = torch.max(x, 0, keepdim=True)[0]
x = self.classifier(x)
return x
class MRNetAttention(nn.Module):
def __init__(self, pretrained=True):
super().__init__()
self.model = models.alexnet(pretrained=pretrained)
self.gap = nn.AdaptiveAvgPool2d(1)
self.attention = nn.Linear(256, 1)
self.classifier = nn.Linear(256, 1)
def forward(self, x):
x = torch.squeeze(x, dim=0) # only batch size 1 supported
x = self.model.features(x)
x = self.gap(x).view(x.size(0), -1) # (seq_len, n_feat)
a = torch.softmax(self.attention(x), dim=0) # (1, seq_len)
x = torch.sum(a.view(-1, 1) * x, dim=0, keepdim=True)
x = self.classifier(x)
return x
class MRNetSqueezeAttention(nn.Module):
def __init__(self, pretrained=True):
super().__init__()
self.model = models.squeezenet1_0(pretrained=pretrained)
self.gap = nn.AdaptiveAvgPool2d(1)
self.attention = nn.Linear(512, 1)
self.classifier = nn.Linear(512, 1)
def forward(self, x):
x = torch.squeeze(x, dim=0) # only batch size 1 supported
x = self.model.features(x)
x = self.gap(x).view(x.size(0), -1) # (seq_len, n_feat)
a = torch.softmax(self.attention(x), dim=0) # (1, seq_len)
x = torch.sum(a.view(-1, 1) * x, dim=0, keepdim=True)
x = self.classifier(x)
return x
| 33.328767 | 67 | 0.598027 | 347 | 2,433 | 4.07781 | 0.146974 | 0.042403 | 0.028269 | 0.042403 | 0.916608 | 0.916608 | 0.916608 | 0.913074 | 0.913074 | 0.913074 | 0 | 0.036667 | 0.260173 | 2,433 | 72 | 68 | 33.791667 | 0.749444 | 0.071106 | 0 | 0.847458 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.135593 | false | 0 | 0.050847 | 0 | 0.322034 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
b4ae5db3c844c08de3c1a6441b05a7e52cbf0b01 | 15,698 | py | Python | head_Force/loop_table_helix.py | pcmagic/stokes_flow | 464d512d3739eee77b33d1ebf2f27dae6cfa0423 | [
"MIT"
] | 1 | 2018-11-11T05:00:53.000Z | 2018-11-11T05:00:53.000Z | head_Force/loop_table_helix.py | pcmagic/stokes_flow | 464d512d3739eee77b33d1ebf2f27dae6cfa0423 | [
"MIT"
] | null | null | null | head_Force/loop_table_helix.py | pcmagic/stokes_flow | 464d512d3739eee77b33d1ebf2f27dae6cfa0423 | [
"MIT"
] | null | null | null | # coding=utf-8
import sys
import petsc4py
petsc4py.init(sys.argv)
import numpy as np
from time import time
from scipy.io import savemat
# from src.stokes_flow import problem_dic, obj_dic
from petsc4py import PETSc
from src import stokes_flow as sf
from src.myio import *
from src.objComposite import *
# from src.myvtk import save_singleEcoli_vtk
import codeStore.ecoli_common as ec
import pickle
# import import_my_lib
# Todo: rewrite input and print process.
def get_problem_kwargs(**main_kwargs):
OptDB = PETSc.Options()
fileHandle = OptDB.getString('f', 'loop_table_helix')
OptDB.setValue('f', fileHandle)
problem_kwargs = ec.get_problem_kwargs()
problem_kwargs['fileHandle'] = fileHandle
n_norm_theta = OptDB.getInt('n_norm_theta', 2)
n_norm_phi = OptDB.getInt('n_norm_phi', 2)
norm_psi = OptDB.getReal('norm_psi', 0)
problem_kwargs['n_norm_theta'] = n_norm_theta
problem_kwargs['n_norm_phi'] = n_norm_phi
problem_kwargs['norm_psi'] = norm_psi
kwargs_list = (get_shearFlow_kwargs(), main_kwargs,)
for t_kwargs in kwargs_list:
for key in t_kwargs:
problem_kwargs[key] = t_kwargs[key]
pickle_name = '%s_kwargs.pickle' % fileHandle
with open(pickle_name, 'wb') as handle:
pickle.dump(problem_kwargs, handle, protocol=4)
PETSc.Sys.Print('---->save kwargs to %s' % pickle_name)
return problem_kwargs
def print_case_info(**problem_kwargs):
caseIntro = '-->Passive helix in infinite shear flow case, make table. '
ec.print_case_info(caseIntro, **problem_kwargs)
n_norm_theta = problem_kwargs['n_norm_theta']
n_norm_phi = problem_kwargs['n_norm_phi']
norm_psi = problem_kwargs['norm_psi']
PETSc.Sys.Print('Loop parameter space: n_norm_theta %d, n_norm_phi %d. norm_psi %f' %
(n_norm_theta, n_norm_phi, norm_psi))
print_shearFlow_info(**problem_kwargs)
return True
def do_solve_once(problem_ff: sf.ShearFlowForceFreeProblem,
problem: sf.ShearFlowForceFreeIterateProblem,
ecoli_comp: sf.ForceFreeComposite,
fileHandle, norm_theta, norm_phi, norm_psi, planeShearRate, rank, idx, N,
iter_tor):
PETSc.Sys.Print()
PETSc.Sys.Print('%s %05d / %05d theta=%f, phi=%f, psi=%f %s' %
('#' * 25, idx, N, norm_theta, norm_phi, norm_psi, '#' * 25,))
# 1) ini guess
ref_U0 = ecoli_comp.get_ref_U()
problem_ff.create_matrix()
problem_ff.solve()
ref_U1 = ecoli_comp.get_ref_U()
PETSc.Sys.Print(' ini ref_U0 in shear flow %s' % str(ref_U0))
PETSc.Sys.Print(' ini ref_U1 in shear flow %s' % str(ref_U1))
# 2) optimize force and torque free
problem.create_matrix()
ref_U = problem.do_iterate3(ini_refU0=ref_U0, ini_refU1=ref_U1, rtol=iter_tor)
ecoli_comp.set_ref_U(ref_U)
PETSc.Sys.Print(' true ref_U in shear flow', ref_U)
tU = np.linalg.norm(ref_U[:3])
tW = np.linalg.norm(ref_U[3:])
terr = (ref_U1 - ref_U) / [tU, tU, tU, tW, tW, tW]
PETSc.Sys.Print(' error of direct method', terr)
if rank == 0:
mat_name = '%s_th%f_phi%f_psi_%f.mat' % (fileHandle, norm_theta, norm_phi, norm_psi)
savemat(mat_name, {
'norm_theta': norm_theta,
'norm_phi': norm_phi,
'norm_psi': norm_psi,
'planeShearRate': planeShearRate,
'ecoli_center': np.vstack(ecoli_comp.get_center()),
'ecoli_nodes': np.vstack([tobj.get_u_nodes() for tobj in ecoli_comp.get_obj_list()]),
'ecoli_f': np.hstack([np.zeros_like(tobj.get_force())
for tobj in ecoli_comp.get_obj_list()]).reshape(-1, 3),
'ecoli_u': np.hstack([np.zeros_like(tobj.get_re_velocity())
for tobj in ecoli_comp.get_obj_list()]).reshape(-1, 3),
'ecoli_norm': np.vstack(ecoli_comp.get_norm()),
'ecoli_U': np.vstack(ecoli_comp.get_ref_U()), }, oned_as='column', )
return True
def do_solve_once_noIter(problem_ff: sf.ShearFlowForceFreeProblem,
ecoli_comp: sf.ForceFreeComposite,
fileHandle, norm_theta, norm_phi, norm_psi, planeShearRate, rank, idx, N,
iter_tor):
PETSc.Sys.Print()
PETSc.Sys.Print('%s %05d / %05d theta=%f, phi=%f, psi=%f %s' %
('#' * 25, idx, N, norm_theta, norm_phi, norm_psi, '#' * 25,))
problem_ff.create_matrix()
problem_ff.solve()
ref_U = ecoli_comp.get_ref_U()
PETSc.Sys.Print(' ref_U in shear flow', ref_U)
if rank == 0:
mat_name = '%s_th%f_phi%f_psi_%f.mat' % (fileHandle, norm_theta, norm_phi, norm_psi)
savemat(mat_name, {
'norm_theta': norm_theta,
'norm_phi': norm_phi,
'norm_psi': norm_psi,
'planeShearRate': planeShearRate,
'ecoli_center': np.vstack(ecoli_comp.get_center()),
'ecoli_nodes': np.vstack([tobj.get_u_nodes() for tobj in ecoli_comp.get_obj_list()]),
'ecoli_f': np.hstack([np.zeros_like(tobj.get_force())
for tobj in ecoli_comp.get_obj_list()]).reshape(-1, 3),
'ecoli_u': np.hstack([np.zeros_like(tobj.get_re_velocity())
for tobj in ecoli_comp.get_obj_list()]).reshape(-1, 3),
'ecoli_norm': np.vstack(ecoli_comp.get_norm()),
'ecoli_U': np.vstack(ecoli_comp.get_ref_U()), }, oned_as='column', )
return True
def main_fun(**main_kwargs):
comm = PETSc.COMM_WORLD.tompi4py()
rank = comm.Get_rank()
problem_kwargs = get_problem_kwargs(**main_kwargs)
print_case_info(**problem_kwargs)
fileHandle = problem_kwargs['fileHandle']
n_norm_theta = problem_kwargs['n_norm_theta']
n_norm_phi = problem_kwargs['n_norm_phi']
norm_psi = problem_kwargs['norm_psi']
N = n_norm_phi * n_norm_theta
iter_tor = 1e-3
if not problem_kwargs['restart']:
# create helix
_, tail_obj_list = createEcoli_ellipse(name='ecoli0', **problem_kwargs)
tail_obj = sf.StokesFlowObj()
tail_obj.set_name('tail_obj')
tail_obj.combine(tail_obj_list)
tail_obj.move(-tail_obj.get_u_geo().get_center())
t_norm = tail_obj.get_u_geo().get_geo_norm()
helix_comp = sf.ForceFreeComposite(center=np.zeros(3), norm=t_norm, name='helix_0')
helix_comp.add_obj(obj=tail_obj, rel_U=np.zeros(6))
helix_comp.node_rotation(helix_comp.get_norm(), norm_psi)
problem_ff = sf.ShearFlowForceFreeProblem(**problem_kwargs)
problem_ff.add_obj(helix_comp)
problem_ff.print_info()
problem_ff.create_matrix()
problem = sf.ShearFlowForceFreeIterateProblem(**problem_kwargs)
problem.add_obj(helix_comp)
problem.set_iterate_comp(helix_comp)
planeShearRate = problem_ff.get_planeShearRate()
# 1). theta=0, ecoli_norm=(0, 0, 1)
norm_theta, norm_phi = 0, 0
t2 = time()
do_solve_once(problem_ff, problem, helix_comp, fileHandle, norm_theta, norm_phi, norm_psi,
planeShearRate, rank, 0, N, iter_tor)
ref_U000 = helix_comp.get_ref_U().copy()
t3 = time()
PETSc.Sys.Print(' Current process uses: %07.3fs' % (t3 - t2))
# 2). loop over parameter space
# using the new orientation definition method, {norm_theta, norm_phi = 0, 0} is not a singularity now.
for i0, norm_theta in enumerate(np.linspace(0, np.pi, n_norm_theta)):
helix_comp.set_ref_U(ref_U000)
helix_comp.node_rotation(np.array((0, 1, 0)), norm_theta)
for i1, norm_phi in enumerate(np.linspace(0, np.pi, n_norm_phi)):
t2 = time()
idx = i0 * n_norm_phi + i1 + 1
helix_comp.node_rotation(np.array((0, 0, 1)), norm_phi)
do_solve_once(problem_ff, problem, helix_comp, fileHandle, norm_theta, norm_phi,
norm_psi,
planeShearRate, rank, idx, N, iter_tor)
helix_comp.node_rotation(np.array((0, 0, 1)), -norm_phi) # rotate back
t3 = time()
PETSc.Sys.Print(' Current process uses: %07.3fs' % (t3 - t2))
helix_comp.node_rotation(np.array((0, 1, 0)), -norm_theta) # rotate back
else:
pass
return True
def main_fun_noIter(**main_kwargs):
comm = PETSc.COMM_WORLD.tompi4py()
rank = comm.Get_rank()
problem_kwargs = get_problem_kwargs(**main_kwargs)
print_case_info(**problem_kwargs)
fileHandle = problem_kwargs['fileHandle']
n_norm_theta = problem_kwargs['n_norm_theta']
n_norm_phi = problem_kwargs['n_norm_phi']
norm_psi = problem_kwargs['norm_psi']
N = n_norm_phi * n_norm_theta
iter_tor = 1e-3
if not problem_kwargs['restart']:
# create helix
_, tail_obj_list = createEcoli_ellipse(name='ecoli0', **problem_kwargs)
tail_obj = sf.StokesFlowObj()
tail_obj.set_name('tail_obj')
tail_obj.combine(tail_obj_list)
tail_obj.move(-tail_obj.get_u_geo().get_center())
t_norm = tail_obj.get_u_geo().get_geo_norm()
helix_comp = sf.ForceFreeComposite(center=np.zeros(3), norm=t_norm, name='helix_0')
helix_comp.add_obj(obj=tail_obj, rel_U=np.zeros(6))
helix_comp.node_rotation(helix_comp.get_norm(), norm_psi)
problem_ff = sf.ShearFlowForceFreeProblem(**problem_kwargs)
problem_ff.add_obj(helix_comp)
problem_ff.print_info()
problem_ff.create_matrix()
planeShearRate = problem_ff.get_planeShearRate()
# 2). loop over parameter space
# using the new orientation definition method, {norm_theta, norm_phi = 0, 0} is not a singularity now.
for i0, norm_theta in enumerate(np.linspace(0, np.pi, n_norm_theta)):
helix_comp.node_rotation(np.array((0, 1, 0)), norm_theta)
for i1, norm_phi in enumerate(np.linspace(0, np.pi, n_norm_phi)):
t2 = time()
idx = i0 * n_norm_phi + i1 + 1
helix_comp.node_rotation(np.array((0, 0, 1)), norm_phi)
do_solve_once_noIter(problem_ff, helix_comp, fileHandle, norm_theta, norm_phi,
norm_psi,
planeShearRate, rank, idx, N, iter_tor)
helix_comp.node_rotation(np.array((0, 0, 1)), -norm_phi) # rotate back
t3 = time()
PETSc.Sys.Print(' Current process uses: %07.3fs' % (t3 - t2))
helix_comp.node_rotation(np.array((0, 1, 0)), -norm_theta) # rotate back
else:
pass
return True
def test_location(**main_kwargs):
comm = PETSc.COMM_WORLD.tompi4py()
rank = comm.Get_rank()
problem_kwargs = get_problem_kwargs(**main_kwargs)
print_case_info(**problem_kwargs)
fileHandle = problem_kwargs['fileHandle']
norm_psi = problem_kwargs['norm_psi']
norm_theta = problem_kwargs['norm_theta']
norm_phi = problem_kwargs['norm_phi']
PETSc.Sys.Print('-->norm_theta=%f, norm_phi=%f' % (norm_theta, norm_phi))
iter_tor = 1e-3
if not problem_kwargs['restart']:
# create helix
_, tail_obj_list = createEcoli_ellipse(name='ecoli0', **problem_kwargs)
tail_obj = sf.StokesFlowObj()
tail_obj.set_name('tail_obj')
tail_obj.combine(tail_obj_list)
tail_obj.move(-tail_obj.get_u_geo().get_center())
t_norm = tail_obj.get_u_geo().get_geo_norm()
helix_comp = sf.ForceFreeComposite(center=np.zeros(3), norm=t_norm, name='helix_0')
helix_comp.add_obj(obj=tail_obj, rel_U=np.zeros(6))
helix_comp.node_rotation(helix_comp.get_norm(), norm_psi)
problem_ff = sf.ShearFlowForceFreeProblem(**problem_kwargs)
problem_ff.add_obj(helix_comp)
problem_ff.print_info()
problem_ff.create_matrix()
problem = sf.ShearFlowForceFreeIterateProblem(**problem_kwargs)
problem.add_obj(helix_comp)
problem.set_iterate_comp(helix_comp)
planeShearRate = problem_ff.get_planeShearRate()
helix_comp.node_rotation(np.array((0, 1, 0)), norm_theta)
helix_comp.node_rotation(np.array((0, 0, 1)), norm_phi)
do_solve_once(problem_ff, problem, helix_comp, fileHandle, norm_theta, norm_phi, norm_psi,
planeShearRate, rank, 0, 0, iter_tor)
ref_U = helix_comp.get_ref_U()
PETSc.Sys.Print(
'-->norm_theta=%f, norm_phi=%f, norm_psi=%f' % (norm_theta, norm_phi, norm_psi))
PETSc.Sys.Print('--> ref_U=%s' %
np.array2string(ref_U, separator=', ',
formatter={'float': lambda x: "%f" % x}))
else:
pass
return True
def test_location_noIter(**main_kwargs):
comm = PETSc.COMM_WORLD.tompi4py()
rank = comm.Get_rank()
problem_kwargs = get_problem_kwargs(**main_kwargs)
print_case_info(**problem_kwargs)
fileHandle = problem_kwargs['fileHandle']
norm_psi = problem_kwargs['norm_psi']
norm_theta = problem_kwargs['norm_theta']
norm_phi = problem_kwargs['norm_phi']
PETSc.Sys.Print('-->norm_theta=%f, norm_phi=%f' % (norm_theta, norm_phi))
iter_tor = 1e-3
if not problem_kwargs['restart']:
# create helix
_, tail_obj_list = createEcoli_ellipse(name='ecoli0', **problem_kwargs)
tail_obj = sf.StokesFlowObj()
tail_obj.set_name('tail_obj')
tail_obj.combine(tail_obj_list)
tail_obj.move(-tail_obj.get_u_geo().get_center())
t_norm = tail_obj.get_u_geo().get_geo_norm()
helix_comp = sf.ForceFreeComposite(center=np.zeros(3), norm=t_norm, name='helix_0')
helix_comp.add_obj(obj=tail_obj, rel_U=np.zeros(6))
helix_comp.node_rotation(helix_comp.get_norm(), norm_psi)
problem_ff = sf.ShearFlowForceFreeProblem(**problem_kwargs)
problem_ff.add_obj(helix_comp)
problem_ff.print_info()
problem_ff.create_matrix()
planeShearRate = problem_ff.get_planeShearRate()
helix_comp.node_rotation(np.array((0, 1, 0)), norm_theta)
helix_comp.node_rotation(np.array((0, 0, 1)), norm_phi)
do_solve_once_noIter(problem_ff, helix_comp, fileHandle, norm_theta, norm_phi, norm_psi,
planeShearRate, rank, 0, 0, iter_tor)
ref_U = helix_comp.get_ref_U()
PETSc.Sys.Print(
'-->norm_theta=%f, norm_phi=%f, norm_psi=%f' % (norm_theta, norm_phi, norm_psi))
PETSc.Sys.Print('--> ref_U=%s' %
np.array2string(ref_U, separator=', ',
formatter={'float': lambda x: "%f" % x}))
else:
pass
return True
if __name__ == '__main__':
OptDB = PETSc.Options()
if OptDB.getBool('main_fun_noIter', False):
OptDB.setValue('main_fun', False)
main_fun_noIter()
if OptDB.getBool('test_location', False):
OptDB.setValue('main_fun', False)
norm_theta = OptDB.getReal('norm_theta', 0)
norm_phi = OptDB.getReal('norm_phi', 0)
test_location(norm_theta=norm_theta, norm_phi=norm_phi)
if OptDB.getBool('test_location_noIter', False):
OptDB.setValue('main_fun', False)
norm_theta = OptDB.getReal('norm_theta', 0)
norm_phi = OptDB.getReal('norm_phi', 0)
test_location_noIter(norm_theta=norm_theta, norm_phi=norm_phi)
if OptDB.getBool('main_fun', True):
main_fun()
| 44.219718 | 110 | 0.632628 | 2,168 | 15,698 | 4.244465 | 0.097325 | 0.048685 | 0.039557 | 0.04173 | 0.849598 | 0.812867 | 0.795914 | 0.778744 | 0.764182 | 0.764182 | 0 | 0.015155 | 0.247611 | 15,698 | 354 | 111 | 44.344633 | 0.763949 | 0.038667 | 0 | 0.750831 | 0 | 0 | 0.094161 | 0.003185 | 0 | 0 | 0 | 0.002825 | 0 | 1 | 0.026578 | false | 0.016611 | 0.036545 | 0 | 0.089701 | 0.036545 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
b4c6e00840c6645c9f69a6e48fc640f67cf7153e | 3,850 | py | Python | tests/models/test_fccd.py | khlaifiabilel/torchgeo | 33efc2c0ca6ad7a5af9e29ddcedf67265fa8721f | [
"MIT"
] | 678 | 2021-09-03T18:22:56.000Z | 2022-03-31T08:34:35.000Z | tests/models/test_fccd.py | khlaifiabilel/torchgeo | 33efc2c0ca6ad7a5af9e29ddcedf67265fa8721f | [
"MIT"
] | 305 | 2021-09-03T00:34:23.000Z | 2022-03-31T18:18:35.000Z | tests/models/test_fccd.py | khlaifiabilel/torchgeo | 33efc2c0ca6ad7a5af9e29ddcedf67265fa8721f | [
"MIT"
] | 74 | 2021-09-04T16:13:13.000Z | 2022-03-31T08:35:27.000Z | # Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import itertools
import pytest
import torch
from torchgeo.models import FCEF, FCSiamConc, FCSiamDiff
BATCH_SIZE = [1, 2]
CHANNELS = [1, 3, 5]
CLASSES = [2, 3]
T = [2, 3]
class TestFCEF:
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, c", list(itertools.product(BATCH_SIZE, CHANNELS)))
def test_in_channels(self, b: int, c: int) -> None:
classes = 2
t, h, w = 2, 64, 64
model = FCEF(in_channels=c, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, classes", list(itertools.product(BATCH_SIZE, CLASSES)))
def test_classes(self, b: int, classes: int) -> None:
t, c, h, w = 2, 3, 64, 64
model = FCEF(in_channels=3, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, t", list(itertools.product(BATCH_SIZE, T)))
def test_t(self, b: int, t: int) -> None:
classes = 2
c, h, w = 3, 64, 64
model = FCEF(in_channels=3, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
class TestFCSiamConc:
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, c", list(itertools.product(BATCH_SIZE, CHANNELS)))
def test_in_channels(self, b: int, c: int) -> None:
classes = 2
t, h, w = 2, 64, 64
model = FCSiamConc(in_channels=c, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, classes", list(itertools.product(BATCH_SIZE, CLASSES)))
def test_classes(self, b: int, classes: int) -> None:
t, c, h, w = 2, 3, 64, 64
model = FCSiamConc(in_channels=3, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, t", list(itertools.product(BATCH_SIZE, T)))
def test_t(self, b: int, t: int) -> None:
classes = 2
c, h, w = 3, 64, 64
model = FCSiamConc(in_channels=3, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
class TestFCSiamDiff:
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, c", list(itertools.product(BATCH_SIZE, CHANNELS)))
def test_in_channels(self, b: int, c: int) -> None:
classes = 2
t, h, w = 2, 64, 64
model = FCSiamDiff(in_channels=c, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, classes", list(itertools.product(BATCH_SIZE, CLASSES)))
def test_classes(self, b: int, classes: int) -> None:
t, c, h, w = 2, 3, 64, 64
model = FCSiamDiff(in_channels=3, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
@torch.no_grad() # type: ignore[misc]
@pytest.mark.parametrize("b, t", list(itertools.product(BATCH_SIZE, T)))
def test_t(self, b: int, t: int) -> None:
classes = 2
c, h, w = 3, 64, 64
model = FCSiamDiff(in_channels=3, t=t, classes=classes)
x = torch.randn(b, t, c, h, w)
y = model(x)
assert y.shape == (b, classes, h, w)
| 35.648148 | 88 | 0.574805 | 597 | 3,850 | 3.639866 | 0.100503 | 0.02485 | 0.020709 | 0.022089 | 0.892315 | 0.892315 | 0.88127 | 0.88127 | 0.88127 | 0.88127 | 0 | 0.024373 | 0.264675 | 3,850 | 107 | 89 | 35.981308 | 0.7432 | 0.067532 | 0 | 0.842697 | 0 | 0 | 0.015092 | 0 | 0 | 0 | 0 | 0 | 0.101124 | 1 | 0.101124 | false | 0 | 0.044944 | 0 | 0.179775 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
b4e9e313c38ead0096a48962d964e6cd71942500 | 6,226 | py | Python | src/third_party/beaengine/tests/0f73.py | CrackerCat/rp | 5fe693c26d76b514efaedb4084f6e37d820db023 | [
"MIT"
] | 1 | 2022-01-17T17:40:29.000Z | 2022-01-17T17:40:29.000Z | src/third_party/beaengine/tests/0f73.py | CrackerCat/rp | 5fe693c26d76b514efaedb4084f6e37d820db023 | [
"MIT"
] | null | null | null | src/third_party/beaengine/tests/0f73.py | CrackerCat/rp | 5fe693c26d76b514efaedb4084f6e37d820db023 | [
"MIT"
] | null | null | null | #!/usr/bin/python
# -*- coding: utf-8 -*-
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
#
# @author : beaengine@gmail.com
from headers.BeaEnginePython import *
from nose.tools import *
class TestSuite:
def test(self):
# NP 0F 73 /6 ib
# psllq mm1, imm8
Buffer = bytes.fromhex('0f73f011')
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0xf73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'psllq')
assert_equal(myDisasm.repr(), 'psllq mm0, 11h')
# 66 0F 73 /6 ib
# psllq xmm1, imm8
Buffer = bytes.fromhex('660f73f011')
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0xf73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'psllq')
assert_equal(myDisasm.repr(), 'psllq xmm0, 11h')
# VEX.NDD.128.66.0F.WIG 73 /6 ib
# Vpsllq xmm1, xmm2, imm8
myVEX = VEX('VEX.NDD.128.66.0F.WIG')
myVEX.B = 1
myVEX.vvvv = 0b1111
Buffer = bytes.fromhex('{}73f011'.format(myVEX.c4()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpsllq')
assert_equal(myDisasm.repr(), 'vpsllq xmm0, xmm0, 11h')
# VEX.NDD.256.66.0F.WIG 73 /6 ib
# Vpsllq ymm1, ymm2, imm8
myVEX = VEX('VEX.NDD.256.66.0F.WIG')
Buffer = bytes.fromhex('{}73f011'.format(myVEX.c4()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpsllq')
assert_equal(myDisasm.repr(), 'vpsllq ymm15, ymm8, 11h')
# EVEX.NDD.128.66.0F.WIG 73 /6 ib
# Vpsllq xmm1 {k1}{z}, xmm2/m128, imm8
myEVEX = EVEX('EVEX.NDD.128.66.0F.WIG')
Buffer = bytes.fromhex('{}733211'.format(myEVEX.prefix()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpsllq')
assert_equal(myDisasm.repr(), 'vpsllq xmm31, xmmword ptr [r10], 11h')
# EVEX.NDD.256.66.0F.WIG 73 /6 ib
# Vpsllq ymm1 {k1}{z}, ymm2/m256, imm8
myEVEX = EVEX('EVEX.NDD.256.66.0F.WIG')
Buffer = bytes.fromhex('{}733211'.format(myEVEX.prefix()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpsllq')
assert_equal(myDisasm.repr(), 'vpsllq ymm31, ymmword ptr [r10], 11h')
# EVEX.NDD.512.66.0F.WIG 73 /6 ib
# Vpsllq zmm1 {k1}{z}, zmm2/m512, imm8
myEVEX = EVEX('EVEX.NDD.512.66.0F.WIG')
Buffer = bytes.fromhex('{}733211'.format(myEVEX.prefix()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpsllq')
assert_equal(myDisasm.repr(), 'vpsllq zmm31, zmmword ptr [r10], 11h')
# VEX.NDD.128.66.0F.WIG 73 /6 ib
# Vpslldq xmm1, xmm2, imm8
myVEX = VEX('VEX.NDD.128.66.0F.WIG')
myVEX.B = 1
myVEX.vvvv = 0b1111
Buffer = bytes.fromhex('{}73f811'.format(myVEX.c4()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpslldq')
assert_equal(myDisasm.repr(), 'vpslldq xmm0, xmm0, 11h')
# VEX.NDD.256.66.0F.WIG 73 /6 ib
# Vpslldq ymm1, ymm2, imm8
myVEX = VEX('VEX.NDD.256.66.0F.WIG')
Buffer = bytes.fromhex('{}73f811'.format(myVEX.c4()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpslldq')
assert_equal(myDisasm.repr(), 'vpslldq ymm15, ymm8, 11h')
# EVEX.NDD.128.66.0F.WIG 73 /6 ib
# Vpslldq xmm1 {k1}{z}, xmm2/m128, imm8
myEVEX = EVEX('EVEX.NDD.128.66.0F.WIG')
Buffer = bytes.fromhex('{}733a11'.format(myEVEX.prefix()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpslldq')
assert_equal(myDisasm.repr(), 'vpslldq xmm31, xmmword ptr [r10], 11h')
# EVEX.NDD.256.66.0F.WIG 73 /6 ib
# Vpslldq ymm1 {k1}{z}, ymm2/m256, imm8
myEVEX = EVEX('EVEX.NDD.256.66.0F.WIG')
Buffer = bytes.fromhex('{}733a11'.format(myEVEX.prefix()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpslldq')
assert_equal(myDisasm.repr(), 'vpslldq ymm31, ymmword ptr [r10], 11h')
# EVEX.NDD.512.66.0F.WIG 73 /6 ib
# Vpslldq zmm1 {k1}{z}, zmm2/m512, imm8
myEVEX = EVEX('EVEX.NDD.512.66.0F.WIG')
Buffer = bytes.fromhex('{}733a11'.format(myEVEX.prefix()))
myDisasm = Disasm(Buffer)
myDisasm.read()
assert_equal(myDisasm.infos.Instruction.Opcode, 0x73)
assert_equal(myDisasm.infos.Instruction.Mnemonic, b'vpslldq')
assert_equal(myDisasm.repr(), 'vpslldq zmm31, zmmword ptr [r10], 11h')
| 39.656051 | 78 | 0.634436 | 807 | 6,226 | 4.850062 | 0.195787 | 0.101175 | 0.174757 | 0.147164 | 0.84466 | 0.821921 | 0.807614 | 0.804292 | 0.804292 | 0.804292 | 0 | 0.083473 | 0.232252 | 6,226 | 156 | 79 | 39.910256 | 0.735356 | 0.226309 | 0 | 0.8 | 0 | 0 | 0.152606 | 0.045217 | 0 | 0 | 0.010467 | 0 | 0.4 | 1 | 0.011111 | false | 0 | 0.022222 | 0 | 0.044444 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
b4f9c3ff016a4aaa49f32bb66f53e64128b87b19 | 56,495 | py | Python | ctm/generic/rdm_kagome.py | slowlightx/peps-torch | 3f94e2ac32e79cbdadf572c89e57ae8e17d4e012 | [
"MIT"
] | null | null | null | ctm/generic/rdm_kagome.py | slowlightx/peps-torch | 3f94e2ac32e79cbdadf572c89e57ae8e17d4e012 | [
"MIT"
] | null | null | null | ctm/generic/rdm_kagome.py | slowlightx/peps-torch | 3f94e2ac32e79cbdadf572c89e57ae8e17d4e012 | [
"MIT"
] | null | null | null | import torch
#from ipeps.ipeps import IPEPS
from ctm.generic.env import ENV
from tn_interface import contract, einsum
from tn_interface import contiguous, view, permute
from tn_interface import conj
def _sym_pos_def_matrix(rdm, sym_pos_def=False, verbosity=0, who="unknown"):
rdm_asym= 0.5*(rdm-rdm.conj().t())
rdm= 0.5*(rdm+rdm.conj().t())
if verbosity>0:
log.info(f"{who} norm(rdm_sym) {rdm.norm()} norm(rdm_asym) {rdm_asym.norm()}")
if sym_pos_def:
with torch.no_grad():
D, U= torch.symeig(rdm, eigenvectors=True)
if D.min() < 0:
log.info(f"{who} max(diag(rdm)) {D.max()} min(diag(rdm)) {D.min()}")
D= torch.clamp(D, min=0)
rdm_posdef= U@torch.diag(D)@U.conj().t()
rdm.copy_(rdm_posdef)
rdm = rdm / rdm.diagonal().sum()
return rdm
def _sym_pos_def_rdm(rdm, sym_pos_def=False, verbosity=0, who=None):
assert len(rdm.size())%2==0, "invalid rank of RDM"
nsites= len(rdm.size())//2
orig_shape= rdm.size()
rdm= rdm.reshape(torch.prod(torch.as_tensor(rdm.size())[:nsites]),-1)
rdm= _sym_pos_def_matrix(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
rdm= rdm.reshape(orig_shape)
return rdm
def rdm1x1(coord, state, env, sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) for which reduced density matrix is constructed
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:type coord: tuple(int,int)
:type state: IPEPS
:type env: ENV
:type verbosity: int
:return: 1-site reduced density matrix with indices :math:`s;s'`
:rtype: torch.tensor
Computes 1-site reduced density matrix :math:`\rho_{1x1}` centered on vertex ``coord`` by
contracting the following tensor network::
C--T-----C
| | |
T--A^+A--T
| | |
C--T-----C
where the physical indices `s` and `s'` of on-site tensor :math:`A` at vertex ``coord``
and it's hermitian conjugate :math:`A^\dagger` are left uncontracted
"""
who= "rdm1x1"
# C(-1,-1)--1->0
# 0
# 0
# T(-1,0)--2
# 1
rdm = contract(env.C[(coord,(-1,-1))],env.T[(coord,(-1,0))],([0],[0]))
if verbosity>0:
print("rdm=CT "+str(rdm.size()))
# C(-1,-1)--0
# |
# T(-1,0)--2->1
# 1
# 0
# C(-1,1)--1->2
rdm = contract(rdm,env.C[(coord,(-1,1))],([1],[0]))
if verbosity>0:
print("rdm=CTC "+str(rdm.size()))
# C(-1,-1)--0
# |
# T(-1,0)--1
# | 0->2
# C(-1,1)--2 1--T(0,1)--2->3
rdm = contract(rdm,env.T[(coord,(0,1))],([2],[1]))
if verbosity>0:
print("rdm=CTCT "+str(rdm.size()))
# TODO - more efficent contraction with uncontracted-double-layer on-site tensor
# Possibly reshape indices 1,2 of rdm, which are to be contracted with
# on-site tensor and contract bra,ket in two steps instead of creating
# double layer tensor
# /
# --A--
# /|s
#
# s'|/
# --A--
# /
#
dimsA = state.site(coord).size()
a = contiguous(einsum('mefgh,nabcd->eafbgchdmn',state.site(coord),conj(state.site(coord))))
a = view(a, (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# C(-1,-1)--0
# |
# | 0->2
# T(-1,0)--1 1--a--3
# | 2\45(s,s')
# | 2
# C(-1,1)-------T(0,1)--3->1
rdm = contract(rdm,a,([1,2],[1,2]))
if verbosity>0:
print("rdm=CTCTa "+str(rdm.size()))
# C(-1,-1)--0 0--T(0,-1)--2->0
# | 1
# | 2
# T(-1,0)--------a--3->2
# | |\45->34(s,s')
# | |
# C(-1,1)--------T(0,1)--1
rdm = contract(env.T[(coord,(0,-1))],rdm,([0,1],[0,2]))
if verbosity>0:
print("rdm=CTCTaT "+str(rdm.size()))
# C(-1,-1)--T(0,-1)--0 0--C(1,-1)
# | | 1->0
# | |
# T(-1,0)---a--2
# | |\34(s,s')
# | |
# C(-1,1)---T(0,1)--0->1
rdm = contract(env.C[(coord,(1,-1))],rdm,([0],[0]))
if verbosity>0:
print("rdm=CTCTaTC "+str(rdm.size()))
# C(-1,-1)--T(0,-1)-----C(1,-1)
# | | 0
# | | 0
# T(-1,0)---a--2 1------T(1,0)
# | |\34->23(s,s') 2->0
# | |
# C(-1,1)---T(0,1)--1
rdm = contract(env.T[(coord,(1,0))],rdm,([0,1],[0,2]))
if verbosity>0:
print("rdm=CTCTaTCT "+str(rdm.size()))
# C(-1,-1)--T(0,-1)--------C(1,-1)
# | | |
# | | |
# T(-1,0)---a--------------T(1,0)
# | |\23->12(s,s') 0
# | | 0
# C(-1,1)---T(0,1)--1 1----C(1,1)
rdm = contract(rdm,env.C[(coord,(1,1))],([0,1],[0,1]))
if verbosity>0:
print("rdm=CTCTaTCTC "+str(rdm.size()))
# symmetrize and normalize
rdm= _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def build_reduced_density_matrix_kagome(coord, state, site_types=('A', 'B', 'C')):
r"""
:type coord: tuple(int,int)
:type state: IPEPS_KAGOME. State (rank-5 tensor) of the unit cell of kagome lattice
:param site_types: types of kagome sites needed
:rtype: torch.tensor
:return: reduced density matrix for the specified kagome sites
Build the two-layer reduced density matrix with specified physical degrees of freedom from
the unit cell tensor \'site_tensor\'.
"""
phys_dim = state.get_physical_dim()
dims_site = state.site(coord).size()
reduced_phys_dim = dims_site[0]
if phys_dim**3 != reduced_phys_dim:
raise Exception("Physical dimensions do not agree. 1 site: {}, 1 unit cell: {}".format(phys_dim, reduced_phys_dim))
tmp_site = state.site(coord)
idp = torch.eye(phys_dim, dtype=state.dtype)
if 'A' in site_types:
if 'B' in site_types:
if 'C' in site_types: # do nothing
rdm = torch.einsum('mefgh,nabcd->eafbgchdmn', tmp_site, conj(tmp_site))
else: # trace out C
reduced_phys_dim //= phys_dim
tmp_site = state.site(coord).view(phys_dim**2, phys_dim, *dims_site[1:])
rdm = einsum('miefgh,niabcd->eafbgchdmn', tmp_site, conj(tmp_site))
else:
reduced_phys_dim //= phys_dim
if 'C' in site_types: # trace out B
tmp_site = state.site(coord).view(phys_dim, phys_dim, phys_dim, *dims_site[1:])
rdm = torch.einsum('ijkefgh,lmnabcd,jm->eafbgchdikln', tmp_site, conj(tmp_site), idp).view(*dims_site[1:], *dims_site[1:], phys_dim**2, phys_dim**2)
else: # trace out B & C
reduced_phys_dim //= phys_dim
tmp_site = state.site(coord).view(phys_dim, phys_dim, phys_dim, *dims_site[1:])
rdm = einsum('mijefgh,nijabcd->eafbgchdmn', tmp_site, conj(tmp_site))
else:
reduced_phys_dim //= phys_dim
if 'B' in site_types:
if 'C' in site_types: # trace out A
tmp_site = state.site(coord).view(phys_dim, phys_dim**2, *dims_site[1:])
rdm = einsum('imefgh,inabcd->eafbgchdmn', tmp_site, conj(tmp_site))
else: # trace out A & C
reduced_phys_dim //= phys_dim
tmp_site = state.site(coord).view(phys_dim, phys_dim, phys_dim, *dims_site[1:])
rdm = einsum('imjefgh,injabcd->eafbgchdmn', tmp_site, conj(tmp_site))
else:
reduced_phys_dim //= phys_dim
if 'C' in site_types: # trace out A & B
tmp_site = state.site(coord).view(phys_dim, phys_dim, phys_dim, *dims_site[1:])
rdm = einsum('ijmefgh,ijnabcd->eafbgchdmn', tmp_site, conj(tmp_site))
else: # trace out A & B & C -> physical dimension = 0
reduced_phys_dim //= phys_dim
tmp_site = state.site(coord).view(phys_dim, phys_dim, phys_dim, *dims_site[1:])
rdm = einsum('ijkefgh,ijkabcd->eafbgchd', tmp_site, conj(tmp_site))
rdm = rdm.view(*rdm.size(), 1, 1)
return rdm, reduced_phys_dim
def rdm1x1_kagome(coord, state, env, sites_to_keep=('A', 'B', 'C'), sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) for which reduced density matrix is constructed
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:param sites_to_keep: physical degrees of freedom to be kept. Default: "ABC" - keep all the DOF
:type coord: tuple(int,int)
:type state: IPEPS_KAGOME
:type env: ENV
:type verbosity: int
:return: 1-site reduced density matrix with indices :math:`s;s'`
:rtype: torch.tensor
Compute 1-kagome-site reduced density matrix :math:`\rho{1x1}_{sites_to_keep}` centered on vertex ``coord``.
Inherited from the rdm1x1() method.
"""
who= "rdm1x1_kagome"
# C(-1,-1)--1->0
# 0
# 0
# T(-1,0)--2
# 1
rdm = contract(env.C[(coord,(-1,-1))],env.T[(coord,(-1,0))],([0],[0]))
if verbosity>0:
print("rdm=CT "+str(rdm.size()))
# C(-1,-1)--0
# |
# T(-1,0)--2->1
# 1
# 0
# C(-1,1)--1->2
rdm = contract(rdm,env.C[(coord,(-1,1))],([1],[0]))
if verbosity>0:
print("rdm=CTC "+str(rdm.size()))
# C(-1,-1)--0
# |
# T(-1,0)--1
# | 0->2
# C(-1,1)--2 1--T(0,1)--2->3
rdm = contract(rdm,env.T[(coord,(0,1))],([2],[1]))
if verbosity>0:
print("rdm=CTCT "+str(rdm.size()))
# TODO - more efficent contraction with uncontracted-double-layer on-site tensor
# Possibly reshape indices 1,2 of rdm, which are to be contracted with
# on-site tensor and contract bra,ket in two steps instead of creating
# double layer tensor
# /
# --A--
# /|s
#
# s'|/
# --A--
# /
#
dimsA = state.site(coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep)
a = view(contiguous(a), (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, rpd, rpd))
# C(-1,-1)--0
# |
# | 0->2
# T(-1,0)--1 1--a--3
# | 2\45(s,s')
# | 2
# C(-1,1)-------T(0,1)--3->1
rdm = contract(rdm,a,([1,2],[1,2]))
if verbosity>0:
print("rdm=CTCTa "+str(rdm.size()))
# C(-1,-1)--0 0--T(0,-1)--2->0
# | 1
# | 2
# T(-1,0)--------a--3->2
# | |\45->34(s,s')
# | |
# C(-1,1)--------T(0,1)--1
rdm = contract(env.T[(coord,(0,-1))],rdm,([0,1],[0,2]))
if verbosity>0:
print("rdm=CTCTaT "+str(rdm.size()))
# C(-1,-1)--T(0,-1)--0 0--C(1,-1)
# | | 1->0
# | |
# T(-1,0)---a--2
# | |\34(s,s')
# | |
# C(-1,1)---T(0,1)--0->1
rdm = contract(env.C[(coord,(1,-1))],rdm,([0],[0]))
if verbosity>0:
print("rdm=CTCTaTC "+str(rdm.size()))
# C(-1,-1)--T(0,-1)-----C(1,-1)
# | | 0
# | | 0
# T(-1,0)---a--2 1------T(1,0)
# | |\34->23(s,s') 2->0
# | |
# C(-1,1)---T(0,1)--1
rdm = contract(env.T[(coord,(1,0))],rdm,([0,1],[0,2]))
if verbosity>0:
print("rdm=CTCTaTCT "+str(rdm.size()))
# C(-1,-1)--T(0,-1)--------C(1,-1)
# | | |
# | | |
# T(-1,0)---a--------------T(1,0)
# | |\23->12(s,s') 0
# | | 0
# C(-1,1)---T(0,1)--1 1----C(1,1)
rdm = contract(rdm,env.C[(coord,(1,1))],([0,1],[0,1]))
if verbosity>0:
print("rdm=CTCTaTCTC "+str(rdm.size()))
# symmetrize and normalize
rdm= _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def trace1x1_dn_kagome(coord, state, env, op, verbosity=0):
r"""
:param coord: vertex (x,y) for which reduced density matrix is constructed
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:param op: operator to be contracted
:type coord: tuple(int,int)
:type state: IPEPS_KAGOME
:type env: ENV
:type verbosity: int
:return: trace of the given on-site observable
:rtype: torch.tensor
Compute 1-kagome-site trace :math:`Tr{\rho{1x1}_{ABC} O}` centered on vertex ``coord``.
Inherited from the rdm1x1() method.
"""
# C(-1,-1)--1->0
# 0
# 0
# T(-1,0)--2
# 1
trace = contract(env.C[(coord,(-1,-1))],env.T[(coord,(-1,0))],([0],[0]))
if verbosity>0:
print("rdm=CT "+str(trace.size()))
# C(-1,-1)--0
# |
# T(-1,0)--2->1
# 1
# 0
# C(-1,1)--1->2
trace = contract(trace,env.C[(coord,(-1,1))],([1],[0]))
if verbosity>0:
print("trace=CTC "+str(trace.size()))
# C(-1,-1)--0
# |
# T(-1,0)--1
# | 0->2
# C(-1,1)--2 1--T(0,1)--2->3
trace = contract(trace,env.T[(coord,(0,1))],([2],[1]))
if verbosity>0:
print("trace=CTCT "+str(trace.size()))
# TODO - more efficent contraction with uncontracted-double-layer on-site tensor
# Possibly reshape indices 1,2 of rdm, which are to be contracted with
# on-site tensor and contract bra,ket in two steps instead of creating
# double layer tensor
# /
# --A--
# /|
# op
# |/
# --A--
# /
#
dimsA = state.site(coord).size()
phys_dim = state.get_physical_dim()
tmp_site = state.site(coord).view(phys_dim, phys_dim, phys_dim, *dimsA[1:]).contiguous()
a = torch.einsum('ijkabcd,ijklmn->lmnabcd', tmp_site, op)
a = torch.einsum('lmnabcd,lmnefgh->aebfcgdh', a, conj(tmp_site))
a = view(contiguous(a), (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2))
# C(-1,-1)--0
# |
# | 0->2
# T(-1,0)--1 1--a_op--3
# | 2
# | 2
# C(-1,1)-------T(0,1)--3->1
trace = contract(trace,a,([1,2],[1,2]))
if verbosity>0:
print("trace=CTCTa "+str(trace.size()))
# C(-1,-1)--0 0--T(0,-1)--2->0
# | 1
# | 2
# T(-1,0)--------a_op--3->2
# | |
# | |
# C(-1,1)--------T(0,1)--1
trace = contract(env.T[(coord,(0,-1))],trace,([0,1],[0,2]))
if verbosity>0:
print("trace=CTCTaT "+str(trace.size()))
# C(-1,-1)--T(0,-1)--0 0--C(1,-1)
# | | 1->0
# | |
# T(-1,0)---a_op--2
# | |
# | |
# C(-1,1)---T(0,1)--0->1
trace = contract(env.C[(coord,(1,-1))],trace,([0],[0]))
if verbosity>0:
print("trace=CTCTaTC "+str(trace.size()))
# C(-1,-1)--T(0,-1)-----C(1,-1)
# | | 0
# | | 0
# T(-1,0)---a_op--2 1---T(1,0)
# | | 2->0
# | |
# C(-1,1)---T(0,1)--1
trace = contract(env.T[(coord,(1,0))],trace,([0,1],[0,2]))
if verbosity>0:
print("trace=CTCTaTCT "+str(trace.size()))
# C(-1,-1)--T(0,-1)--------C(1,-1)
# | | |
# | | |
# T(-1,0)---a_op-----------T(1,0)
# | | 0
# | | 0
# C(-1,1)---T(0,1)--1 1----C(1,1)
trace = contract(trace,env.C[(coord,(1,1))],([0,1],[0,1]))
if verbosity>0:
print("trace=CTCTaTCTC "+str(trace.size()))
return trace
def rdm2x1(coord, state, env, sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) specifies position of 2x1 subsystem
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:type coord: tuple(int,int)
:type state: IPEPS
:type env: ENV
:type verbosity: int
:return: 2-site reduced density matrix with indices :math:`s_0s_1;s'_0s'_1`
:rtype: torch.tensor
Computes 2-site reduced density matrix :math:`\rho_{2x1}` of a horizontal
2x1 subsystem using following strategy:
1. compute four individual corners
2. construct right and left half of the network
3. contract right and left halt to obtain final reduced density matrix
::
| | | | | |
T--A^+A(coord)--A^+A(coord+(1,0))--T C2x1_LD(coord)--C2x1(coord+(1,0))
| | | |
C--T------------T------------------C
The physical indices `s` and `s'` of on-sites tensors :math:`A` (and :math:`A^\dagger`)
at vertices ``coord``, ``coord+(1,0)`` are left uncontracted
"""
who="rdm2x1"
#----- building C2x2_LU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord),(-1,-1))]
T1 = env.T[(state.vertexToSite(coord),(0,-1))]
T2 = env.T[(state.vertexToSite(coord),(-1,0))]
dimsA = state.site(coord).size()
a = einsum('mefgh,nabcd->eafbgchdmn',state.site(coord),conj(state.site(coord)))
a = view(contiguous(a),\
(dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# C--10--T1--2
# 0 1
C2x2_LU =contract(C, T1, ([1],[0]))
# C------T1--2->1
# 0 1->0
# 0
# T2--2->3
# 1->2
C2x2_LU =contract(C2x2_LU, T2, ([0],[0]))
# C-------T1--1->0
# | 0
# | 0
# T2--3 1 a--3
# 2->1 2\45
C2x2_LU =contract(C2x2_LU, a, ([0,3],[0,1]))
# permute 012345->120345
# reshape (12)(03)45->0123
# C2x2--1
# |\23
# 0
C2x2_LU= permute(C2x2_LU, (1,2,0,3,4,5))
C2x2_LU= view(contiguous(C2x2_LU), \
(T2.size(1)*a.size(2),T1.size(2)*a.size(3),dimsA[0],dimsA[0]))
if verbosity>0:
print("C2X2 LU "+str(coord)+"->"+str(state.vertexToSite(coord))+" (-1,-1): "+str(C2x2_LU.size()))
#----- building C2x1_LD ----------------------------------------------------
C = env.C[(state.vertexToSite(coord),(-1,1))]
T2 = env.T[(state.vertexToSite(coord),(0,1))]
# 0 0->1
# C--1 1--T2--2
C2x1_LD=contract(C, T2, ([1],[1]))
# reshape (01)2->(0)1
# 0
# |
# C2x1--1
C2x1_LD= view(contiguous(C2x1_LD), (C.size(0)*T2.size(0),T2.size(2)))
if verbosity>0:
print("C2X1 LD "+str(coord)+"->"+str(state.vertexToSite(coord))+" (-1,1): "+str(C2x1_LD.size()))
#----- build left part C2x2_LU--C2x1_LD ------------------------------------
# C2x2_LU--1
# |\23
# 0
# 0
# C2x1_LD--1->0
# TODO is it worthy(performance-wise) to instead overwrite one of C2x2_LU,C2x2_RU ?
left_half= contract(C2x1_LD, C2x2_LU, ([0],[0]))
#----- building C2x2_RU ----------------------------------------------------
vec = (1,0)
shitf_coord = state.vertexToSite((coord[0]+vec[0],coord[1]+vec[1]))
C = env.C[(shitf_coord,(1,-1))]
T1 = env.T[(shitf_coord,(1,0))]
T2 = env.T[(shitf_coord,(0,-1))]
dimsA = state.site(shitf_coord).size()
a= einsum('mefgh,nabcd->eafbgchdmn',state.site(shitf_coord),conj(state.site(shitf_coord)))
a= view(contiguous(a), \
(dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# 0--C
# 1
# 0
# 1--T1
# 2
C2x2_RU =contract(C, T1, ([1],[0]))
# 2<-0--T2--2 0--C
# 3<-1 |
# 0<-1--T1
# 1<-2
C2x2_RU =contract(C2x2_RU, T2, ([0],[2]))
# 1<-2--T2------C
# 3 |
# 45\0 |
# 2<-1--a--3 0--T1
# 3<-2 0<-1
C2x2_RU =contract(C2x2_RU, a, ([0,3],[3,0]))
# permute 012334->120345
# reshape (12)(03)45->0123
# 0--C2x2
# 23/|
# 1
C2x2_RU= permute(C2x2_RU, (1,2,0,3,4,5))
C2x2_RU= view(contiguous(C2x2_RU), \
(T2.size(0)*a.size(1),T1.size(2)*a.size(2), dimsA[0], dimsA[0]))
if verbosity>0:
print("C2X2 RU "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (1,-1): "+str(C2x2_RU.size()))
#----- building C2x1_RD ----------------------------------------------------
C = env.C[(shitf_coord,(1,1))]
T1 = env.T[(shitf_coord,(0,1))]
# 1<-0 0
# 2<-1--T1--2 1--C
C2x1_RD =contract(C, T1, ([1],[2]))
# reshape (01)2->(0)1
C2x1_RD = view(contiguous(C2x1_RD), (C.size(0)*T1.size(0),T1.size(1)))
# 0
# |
# 1--C2x1
if verbosity>0:
print("C2X1 RD "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (1,1): "+str(C2x1_RD.size()))
#----- build right part C2x2_RU--C2x1_RD -----------------------------------
# 1<-0--C2x2_RU
# |\23
# 1
# 0
# 0<-1--C2x1_RD
right_half =contract(C2x1_RD, C2x2_RU, ([0],[1]))
# construct reduced density matrix by contracting left and right halfs
# C2x2_LU--1 1----C2x2_RU
# |\23->01 |\23
# | |
# C2x1_LD--0 0----C2x1_RD
rdm =contract(left_half,right_half,([0,1],[0,1]))
# permute into order of s0,s1;s0',s1' where primed indices
# represent "ket"
# 0123->0213
# symmetrize and normalize
rdm = contiguous(permute(rdm, (0,2,1,3)))
rdm= _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def rdm2x1_kagome(coord, state, env, sites_to_keep_00=('A', 'B', 'C'), sites_to_keep_10=('A', 'B', 'C'), sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) specifies position of 2x1 subsystem
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:param sites_to_keep_00: physical sites needed for the unit cell at coord + (0, 0)
:param sites_to_keep_10: physical sites needed for the unit cell at coord + (1, 0)
:type coord: tuple(int,int)
:type state: IPEPS_KAGOME
:type env: ENV
:type verbosity: int
:return: 2-site reduced density matrix with indices :math:`s_0s_1;s'_0s'_1`
:rtype: torch.tensor
Computes 2-site reduced density matrix :math:`\rho_{2x1}` of a horizontal
2x1 subsystem using following strategy:
1. compute four individual corners
2. construct right and left half of the network
3. contract right and left halt to obtain final reduced density matrix
::
C--T------------T------------------C = C2x2_LU(coord)--C2x2(coord+(1,0))
| | | | | |
T--A^+A(coord)--A^+A(coord+(1,0))--T C2x1_LD(coord)--C2x1(coord+(1,0))
| | | |
C--T------------T------------------C
The physical indices `s` and `s'` of on-sites tensors :math:`A` (and :math:`A^\dagger`)
at vertices ``coord``, ``coord+(1,0)`` are left uncontracted
"""
who = "rdm2x1_kagome"
# ----- building C2x2_LU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord), (-1, -1))]
T1 = env.T[(state.vertexToSite(coord), (0, -1))]
T2 = env.T[(state.vertexToSite(coord), (-1, 0))]
dimsA = state.site(coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_00)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# C--10--T1--2
# 0 1
C2x2_LU = contract(C, T1, ([1], [0]))
# C------T1--2->1
# 0 1->0
# 0
# T2--2->3
# 1->2
C2x2_LU = contract(C2x2_LU, T2, ([0], [0]))
# C-------T1--1->0
# | 0
# | 0
# T2--3 1 a--3
# 2->1 2\45
C2x2_LU = contract(C2x2_LU, a, ([0, 3], [0, 1]))
# permute 012345->120345
# reshape (12)(03)45->0123
# C2x2--1
# |\23
# 0
C2x2_LU = permute(C2x2_LU, (1, 2, 0, 3, 4, 5))
# dimsA[0] -> rpd. Modified by Yi. Similar for other functions
C2x2_LU = view(contiguous(C2x2_LU), (T2.size(1) * a.size(2), T1.size(2) * a.size(3), rpd, rpd))
if verbosity > 0:
print("C2X2 LU " + str(coord) + "->" + str(state.vertexToSite(coord)) + " (-1,-1): " + str(C2x2_LU.size()))
# ----- building C2x1_LD ----------------------------------------------------
C = env.C[(state.vertexToSite(coord), (-1, 1))]
T2 = env.T[(state.vertexToSite(coord), (0, 1))]
# 0 0->1
# C--1 1--T2--2
C2x1_LD = contract(C, T2, ([1], [1]))
# reshape (01)2->(0)1
# 0
# |
# C2x1--1
C2x1_LD = view(contiguous(C2x1_LD), (C.size(0) * T2.size(0), T2.size(2)))
if verbosity > 0:
print("C2X1 LD " + str(coord) + "->" + str(state.vertexToSite(coord)) + " (-1,1): " + str(C2x1_LD.size()))
# ----- build left part C2x2_LU--C2x1_LD ------------------------------------
# C2x2_LU--1
# |\23
# 0
# 0
# C2x1_LD--1->0
# TODO is it worthy(performance-wise) to instead overwrite one of C2x2_LU,C2x2_RU ?
left_half = contract(C2x1_LD, C2x2_LU, ([0], [0]))
# ----- building C2x2_RU ----------------------------------------------------
vec = (1, 0)
shitf_coord = state.vertexToSite((coord[0] + vec[0], coord[1] + vec[1]))
C = env.C[(shitf_coord, (1, -1))]
T1 = env.T[(shitf_coord, (1, 0))]
T2 = env.T[(shitf_coord, (0, -1))]
dimsA = state.site(shitf_coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_10)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# 0--C
# 1
# 0
# 1--T1
# 2
C2x2_RU = contract(C, T1, ([1], [0]))
# 2<-0--T2--2 0--C
# 3<-1 |
# 0<-1--T1
# 1<-2
C2x2_RU = contract(C2x2_RU, T2, ([0], [2]))
# 1<-2--T2------C
# 3 |
# 45\0 |
# 2<-1--a--3 0--T1
# 3<-2 0<-1
C2x2_RU = contract(C2x2_RU, a, ([0, 3], [3, 0]))
# permute 012334->120345
# reshape (12)(03)45->0123
# 0--C2x2
# 23/|
# 1
C2x2_RU = permute(C2x2_RU, (1, 2, 0, 3, 4, 5))
C2x2_RU = view(contiguous(C2x2_RU), \
(T2.size(0) * a.size(1), T1.size(2) * a.size(2), rpd, rpd))
if verbosity > 0:
print("C2X2 RU " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (1,-1): " + str(
C2x2_RU.size()))
# ----- building C2x1_RD ----------------------------------------------------
C = env.C[(shitf_coord, (1, 1))]
T1 = env.T[(shitf_coord, (0, 1))]
# 1<-0 0
# 2<-1--T1--2 1--C
C2x1_RD = contract(C, T1, ([1], [2]))
# reshape (01)2->(0)1
C2x1_RD = view(contiguous(C2x1_RD), (C.size(0) * T1.size(0), T1.size(1)))
# 0
# |
# 1--C2x1
if verbosity > 0:
print("C2X1 RD " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (1,1): " + str(
C2x1_RD.size()))
# ----- build right part C2x2_RU--C2x1_RD -----------------------------------
# 1<-0--C2x2_RU
# |\23
# 1
# 0
# 0<-1--C2x1_RD
right_half = contract(C2x1_RD, C2x2_RU, ([0], [1]))
# construct reduced density matrix by contracting left and right halfs
# C2x2_LU--1 1----C2x2_RU
# |\23->01 |\23
# | |
# C2x1_LD--0 0----C2x1_RD
rdm = contract(left_half, right_half, ([0, 1], [0, 1]))
# permute into order of s0,s1;s0',s1' where primed indices
# represent "ket"
# 0123->0213
# symmetrize and normalize
rdm = contiguous(permute(rdm, (0, 2, 1, 3)))
rdm = _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def rdm1x2(coord, state, env, sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) specifies position of 1x2 subsystem
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:type coord: tuple(int,int)
:type state: IPEPS
:type env: ENV
:type verbosity: int
:return: 2-site reduced density matrix with indices :math:`s_0s_1;s'_0s'_1`
:rtype: torch.tensor
Computes 2-site reduced density matrix :math:`\rho_{1x2}` of a vertical
1x2 subsystem using following strategy:
1. compute four individual corners
2. construct upper and lower half of the network
3. contract upper and lower halt to obtain final reduced density matrix
::
C--T------------------C = C2x2_LU(coord)--------C1x2(coord)
| | | | |
T--A^+A(coord)--------T C2x2_LD(coord+(0,1))--C1x2(coord+0,1))
| | |
T--A^+A(coord+(0,1))--T
| | |
C--T------------------C
The physical indices `s` and `s'` of on-sites tensors :math:`A` (and :math:`A^\dagger`)
at vertices ``coord``, ``coord+(0,1)`` are left uncontracted
"""
who="rdm1x2"
#----- building C2x2_LU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord),(-1,-1))]
T1 = env.T[(state.vertexToSite(coord),(0,-1))]
T2 = env.T[(state.vertexToSite(coord),(-1,0))]
dimsA = state.site(coord).size()
a= einsum('mefgh,nabcd->eafbgchdmn',state.site(coord), conj(state.site(coord)))
a= view(contiguous(a), \
(dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# C--10--T1--2
# 0 1
C2x2_LU =contract(C, T1, ([1],[0]))
# C------T1--2->1
# 0 1->0
# 0
# T2--2->3
# 1->2
C2x2_LU =contract(C2x2_LU, T2, ([0],[0]))
# C-------T1--1->0
# | 0
# | 0
# T2--3 1 a--3
# 2->1 2\45
C2x2_LU =contract(C2x2_LU, a, ([0,3],[0,1]))
# permute 012345->120345
# reshape (12)(03)45->0123
# C2x2--1
# |\23
# 0
C2x2_LU= permute(C2x2_LU, (1,2,0,3,4,5))
C2x2_LU= view(contiguous(C2x2_LU), \
(T2.size(1)*a.size(2),T1.size(2)*a.size(3),dimsA[0],dimsA[0]))
if verbosity>0:
print("C2X2 LU "+str(coord)+"->"+str(state.vertexToSite(coord))+" (-1,-1): "+str(C2x2_LU.size()))
#----- building C1x2_RU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord),(1,-1))]
T1 = env.T[(state.vertexToSite(coord),(1,0))]
# 0--C
# 1
# 0
# 1--T1
# 2
C1x2_RU =contract(C, T1, ([1],[0]))
# reshape (01)2->(0)1
# 0--C1x2
# 23/|
# 1
C1x2_RU= view(contiguous(C1x2_RU), (C.size(0)*T1.size(1),T1.size(2)))
if verbosity>0:
print("C1X2 RU "+str(coord)+"->"+str(state.vertexToSite(coord))+" (1,-1): "+str(C1x2_RU.size()))
#----- build upper part C2x2_LU--C1x2_RU -----------------------------------
# C2x2_LU--1 0--C1x2_RU
# |\23 |
# 0->1 1->0
upper_half =contract(C1x2_RU, C2x2_LU, ([0],[1]))
#----- building C2x2_LD ----------------------------------------------------
vec = (0,1)
shitf_coord = state.vertexToSite((coord[0]+vec[0],coord[1]+vec[1]))
C = env.C[(shitf_coord,(-1,1))]
T1 = env.T[(shitf_coord,(-1,0))]
T2 = env.T[(shitf_coord,(0,1))]
dimsA = state.site(shitf_coord).size()
a= einsum('mefgh,nabcd->eafbgchdmn',state.site(shitf_coord),conj(state.site(shitf_coord)))
a= view(contiguous(a), \
(dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# 0->1
# T1--2
# 1
# 0
# C--1->0
C2x2_LD =contract(C, T1, ([0],[1]))
# 1->0
# T1--2->1
# |
# | 0->2
# C--0 1--T2--2->3
C2x2_LD =contract(C2x2_LD, T2, ([0],[1]))
# 0 0->2
# T1--1 1--a--3
# | 2\45
# | 2
# C--------T2--3->1
C2x2_LD =contract(C2x2_LD, a, ([1,2],[1,2]))
# permute 012345->021345
# reshape (02)(13)45->0123
# 0
# |/23
# C2x2--1
C2x2_LD= permute(C2x2_LD, (0,2,1,3,4,5))
C2x2_LD= view(contiguous(C2x2_LD), \
(T1.size(0)*a.size(0),T2.size(2)*a.size(3), dimsA[0], dimsA[0]))
if verbosity>0:
print("C2X2 LD "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (-1,1): "+str(C2x2_LD.size()))
#----- building C2x2_RD ----------------------------------------------------
C = env.C[(shitf_coord,(1,1))]
T2 = env.T[(shitf_coord,(1,0))]
# 0
# 1--T2
# 2
# 0
# 2<-1--C
C1x2_RD =contract(T2, C, ([2],[0]))
# permute 012->021
# reshape 0(12)->0(1)
C1x2_RD = view(contiguous(permute(C1x2_RD,(0,2,1))), \
(T2.size()[0],C.size()[1]*T2.size()[1]))
# 0
# |
# 1--C1x2
if verbosity>0:
print("C1X2 RD "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (1,1): "+str(C1x2_RD.size()))
#----- build lower part C2x2_LD--C1x2_RD -----------------------------------
# 0->1 0
# |/23 |
# C2x2_LD--1 1--C1x2_RD
lower_half =contract(C1x2_RD, C2x2_LD, ([1],[1]))
# construct reduced density matrix by contracting lower and upper halfs
# C2x2_LU------C1x2_RU
# |\23->01 |
# 1 0
# 1 0
# |/23 |
# C2x2_LD------C1x2_RD
rdm =contract(upper_half,lower_half,([0,1],[0,1]))
# permute into order of s0,s1;s0',s1' where primed indices
# represent "ket"
# 0123->0213
# symmetrize and normalize
rdm = contiguous(permute(rdm, (0,2,1,3)))
rdm= _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def rdm1x2_kagome(coord, state, env, sites_to_keep_00=('A', 'B', 'C'), sites_to_keep_01=('A', 'B', 'C'), sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) specifies position of 1x2 subsystem
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:param sites_to_keep_00: physical sites needed for the unit cell at coord + (0, 0)
:param sites_to_keep_01: physical sites needed for the unit cell at coord + (0, 1)
:type coord: tuple(int,int)
:type state: IPEPS
:type env: ENV
:type verbosity: int
:return: 2-site reduced density matrix with indices :math:`s_0s_1;s'_0s'_1`
:rtype: torch.tensor
Computes 2-site reduced density matrix :math:`\rho_{1x2}` of a vertical
1x2 subsystem using following strategy:
"""
who = "rdm1x2_kagome"
# ----- building C2x2_LU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord), (-1, -1))]
T1 = env.T[(state.vertexToSite(coord), (0, -1))]
T2 = env.T[(state.vertexToSite(coord), (-1, 0))]
dimsA = state.site(coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_00)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# C--10--T1--2
# 0 1
C2x2_LU = contract(C, T1, ([1], [0]))
# C------T1--2->1
# 0 1->0
# 0
# T2--2->3
# 1->2
C2x2_LU = contract(C2x2_LU, T2, ([0], [0]))
# C-------T1--1->0
# | 0
# | 0
# T2--3 1 a--3
# 2->1 2\45
C2x2_LU = contract(C2x2_LU, a, ([0, 3], [0, 1]))
# permute 012345->120345
# reshape (12)(03)45->0123
# C2x2--1
# |\23
# 0
C2x2_LU = permute(C2x2_LU, (1, 2, 0, 3, 4, 5))
C2x2_LU = view(contiguous(C2x2_LU), (T2.size(1) * a.size(2), T1.size(2) * a.size(3), rpd, rpd))
if verbosity > 0:
print("C2X2 LU " + str(coord) + "->" + str(state.vertexToSite(coord)) + " (-1,-1): " + str(C2x2_LU.size()))
# ----- building C1x2_RU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord), (1, -1))]
T1 = env.T[(state.vertexToSite(coord), (1, 0))]
# 0--C
# 1
# 0
# 1--T1
# 2
C1x2_RU = contract(C, T1, ([1], [0]))
# reshape (01)2->(0)1
# 0--C1x2
# 23/|
# 1
C1x2_RU = view(contiguous(C1x2_RU), (C.size(0) * T1.size(1), T1.size(2)))
if verbosity > 0:
print("C1X2 RU " + str(coord) + "->" + str(state.vertexToSite(coord)) + " (1,-1): " + str(C1x2_RU.size()))
# ----- build upper part C2x2_LU--C1x2_RU -----------------------------------
# C2x2_LU--1 0--C1x2_RU
# |\23 |
# 0->1 1->0
upper_half = contract(C1x2_RU, C2x2_LU, ([0], [1]))
# ----- building C2x2_LD ----------------------------------------------------
vec = (0, 1)
shitf_coord = state.vertexToSite((coord[0] + vec[0], coord[1] + vec[1]))
C = env.C[(shitf_coord, (-1, 1))]
T1 = env.T[(shitf_coord, (-1, 0))]
T2 = env.T[(shitf_coord, (0, 1))]
dimsA = state.site(shitf_coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_01)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# 0->1
# T1--2
# 1
# 0
# C--1->0
C2x2_LD = contract(C, T1, ([0], [1]))
# 1->0
# T1--2->1
# |
# | 0->2
# C--0 1--T2--2->3
C2x2_LD = contract(C2x2_LD, T2, ([0], [1]))
# 0 0->2
# T1--1 1--a--3
# | 2\45
# | 2
# C--------T2--3->1
C2x2_LD = contract(C2x2_LD, a, ([1, 2], [1, 2]))
# permute 012345->021345
# reshape (02)(13)45->0123
# 0
# |/23
# C2x2--1
C2x2_LD = permute(C2x2_LD, (0, 2, 1, 3, 4, 5))
C2x2_LD = view(contiguous(C2x2_LD), (T1.size(0) * a.size(0), T2.size(2) * a.size(3), rpd, rpd))
if verbosity > 0:
print("C2X2 LD " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (-1,1): " + str(
C2x2_LD.size()))
# ----- building C2x2_RD ----------------------------------------------------
C = env.C[(shitf_coord, (1, 1))]
T2 = env.T[(shitf_coord, (1, 0))]
# 0
# 1--T2
# 2
# 0
# 2<-1--C
C1x2_RD = contract(T2, C, ([2], [0]))
# permute 012->021
# reshape 0(12)->0(1)
C1x2_RD = view(contiguous(permute(C1x2_RD, (0, 2, 1))), \
(T2.size()[0], C.size()[1] * T2.size()[1]))
# 0
# |
# 1--C1x2
if verbosity > 0:
print("C1X2 RD " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (1,1): " + str(
C1x2_RD.size()))
# ----- build lower part C2x2_LD--C1x2_RD -----------------------------------
# 0->1 0
# |/23 |
# C2x2_LD--1 1--C1x2_RD
lower_half = contract(C1x2_RD, C2x2_LD, ([1], [1]))
# construct reduced density matrix by contracting lower and upper halfs
# C2x2_LU------C1x2_RU
# |\23->01 |
# 1 0
# 1 0
# |/23 |
# C2x2_LD------C1x2_RD
rdm = contract(upper_half, lower_half, ([0, 1], [0, 1]))
# permute into order of s0,s1;s0',s1' where primed indices
# represent "ket"
# 0123->0213
# symmetrize and normalize
rdm = contiguous(permute(rdm, (0, 2, 1, 3)))
rdm = _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def rdm2x2(coord, state, env, sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) specifies upper left site of 2x2 subsystem
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:type coord: tuple(int,int)
:type state: IPEPS
:type env: ENV
:type verbosity: int
:return: 4-site reduced density matrix with indices :math:`s_0s_1s_2s_3;s'_0s'_1s'_2s'_3`
:rtype: torch.tensor
Computes 4-site reduced density matrix :math:`\rho_{2x2}` of 2x2 subsystem specified
by the vertex ``coord`` of its upper left corner using strategy:
1. compute four individual corners
2. construct upper and lower half of the network
3. contract upper and lower half to obtain final reduced density matrix
::
C--T------------------T------------------C = C2x2_LU(coord)--------C2x2(coord+(1,0))
| | | | | |
T--A^+A(coord)--------A^+A(coord+(1,0))--T C2x2_LD(coord+(0,1))--C2x2(coord+(1,1))
| | | |
T--A^+A(coord+(0,1))--A^+A(coord+(1,1))--T
| | | |
C--T------------------T------------------C
The physical indices `s` and `s'` of on-sites tensors :math:`A` (and :math:`A^\dagger`)
at vertices ``coord``, ``coord+(1,0)``, ``coord+(0,1)``, and ``coord+(1,1)`` are
left uncontracted and given in the same order::
s0 s1
s2 s3
"""
who= "rdm2x2"
#----- building C2x2_LU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord),(-1,-1))]
T1 = env.T[(state.vertexToSite(coord),(0,-1))]
T2 = env.T[(state.vertexToSite(coord),(-1,0))]
dimsA = state.site(coord).size()
a = contiguous(einsum('mefgh,nabcd->eafbgchdmn',state.site(coord),conj(state.site(coord))))
a = view(a, (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# C--10--T1--2
# 0 1
C2x2_LU = contract(C, T1, ([1],[0]))
# C------T1--2->1
# 0 1->0
# 0
# T2--2->3
# 1->2
C2x2_LU = contract(C2x2_LU, T2, ([0],[0]))
# C-------T1--1->0
# | 0
# | 0
# T2--3 1 a--3
# 2->1 2\45
C2x2_LU = contract(C2x2_LU, a, ([0,3],[0,1]))
# permute 012345->120345
# reshape (12)(03)45->0123
# C2x2--1
# |\23
# 0
C2x2_LU = contiguous(permute(C2x2_LU,(1,2,0,3,4,5)))
C2x2_LU = view(C2x2_LU, (T2.size(1)*a.size(2),T1.size(2)*a.size(3),dimsA[0],dimsA[0]))
if verbosity>0:
print("C2X2 LU "+str(coord)+"->"+str(state.vertexToSite(coord))+" (-1,-1): "+str(C2x2_LU.size()))
#----- building C2x2_RU ----------------------------------------------------
vec = (1,0)
shitf_coord = state.vertexToSite((coord[0]+vec[0],coord[1]+vec[1]))
C = env.C[(shitf_coord,(1,-1))]
T1 = env.T[(shitf_coord,(1,0))]
T2 = env.T[(shitf_coord,(0,-1))]
dimsA = state.site(shitf_coord).size()
a = contiguous(einsum('mefgh,nabcd->eafbgchdmn',state.site(shitf_coord),conj(state.site(shitf_coord))))
a = view(a, (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# 0--C
# 1
# 0
# 1--T1
# 2
C2x2_RU = contract(C, T1, ([1],[0]))
# 2<-0--T2--2 0--C
# 3<-1 |
# 0<-1--T1
# 1<-2
C2x2_RU = contract(C2x2_RU, T2, ([0],[2]))
# 1<-2--T2------C
# 3 |
# 45\0 |
# 2<-1--a--3 0--T1
# 3<-2 0<-1
C2x2_RU = contract(C2x2_RU, a, ([0,3],[3,0]))
# permute 012334->120345
# reshape (12)(03)45->0123
# 0--C2x2
# 23/|
# 1
C2x2_RU = contiguous(permute(C2x2_RU, (1,2,0,3,4,5)))
C2x2_RU = view(C2x2_RU, (T2.size(0)*a.size(1),T1.size(2)*a.size(2), dimsA[0], dimsA[0]))
if verbosity>0:
print("C2X2 RU "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (1,-1): "+str(C2x2_RU.size()))
#----- build upper part C2x2_LU--C2x2_RU -----------------------------------
# C2x2_LU--1 0--C2x2_RU C2x2_LU------C2x2_RU
# |\23->12 |\23->45 & permute |\12->23 |\45
# 0 1->3 0 3->1
# TODO is it worthy(performance-wise) to instead overwrite one of C2x2_LU,C2x2_RU ?
upper_half = contract(C2x2_LU, C2x2_RU, ([1],[0]))
upper_half = permute(upper_half, (0,3,1,2,4,5))
#----- building C2x2_RD ----------------------------------------------------
vec = (1,1)
shitf_coord = state.vertexToSite((coord[0]+vec[0],coord[1]+vec[1]))
C = env.C[(shitf_coord,(1,1))]
T1 = env.T[(shitf_coord,(0,1))]
T2 = env.T[(shitf_coord,(1,0))]
dimsA = state.site(shitf_coord).size()
a = contiguous(einsum('mefgh,nabcd->eafbgchdmn',state.site(shitf_coord),conj(state.site(shitf_coord))))
a = view(a, (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# 1<-0 0
# 2<-1--T1--2 1--C
C2x2_RD = contract(C, T1, ([1],[2]))
# 2<-0
# 3<-1--T2
# 2
# 0<-1 0
# 1<-2--T1---C
C2x2_RD = contract(C2x2_RD, T2, ([0],[2]))
# 2<-0 1<-2
# 3<-1--a--3 3--T2
# 2\45 |
# 0 |
# 0<-1--T1------C
C2x2_RD = contract(C2x2_RD, a, ([0,3],[2,3]))
# permute 012345->120345
# reshape (12)(03)45->0123
C2x2_RD = contiguous(permute(C2x2_RD, (1,2,0,3,4,5)))
C2x2_RD = view(C2x2_RD, (T2.size(0)*a.size(0),T1.size(1)*a.size(1), dimsA[0], dimsA[0]))
# 0
# |/23
# 1--C2x2
if verbosity>0:
print("C2X2 RD "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (1,1): "+str(C2x2_RD.size()))
#----- building C2x2_LD ----------------------------------------------------
vec = (0,1)
shitf_coord = state.vertexToSite((coord[0]+vec[0],coord[1]+vec[1]))
C = env.C[(shitf_coord,(-1,1))]
T1 = env.T[(shitf_coord,(-1,0))]
T2 = env.T[(shitf_coord,(0,1))]
dimsA = state.site(shitf_coord).size()
a = contiguous(einsum('mefgh,nabcd->eafbgchdmn',state.site(shitf_coord),conj(state.site(shitf_coord))))
a = view(a, (dimsA[1]**2, dimsA[2]**2, dimsA[3]**2, dimsA[4]**2, dimsA[0], dimsA[0]))
# 0->1
# T1--2
# 1
# 0
# C--1->0
C2x2_LD = contract(C, T1, ([0],[1]))
# 1->0
# T1--2->1
# |
# | 0->2
# C--0 1--T2--2->3
C2x2_LD = contract(C2x2_LD, T2, ([0],[1]))
# 0 0->2
# T1--1 1--a--3
# | 2\45
# | 2
# C--------T2--3->1
C2x2_LD = contract(C2x2_LD, a, ([1,2],[1,2]))
# permute 012345->021345
# reshape (02)(13)45->0123
# 0
# |/23
# C2x2--1
C2x2_LD = contiguous(permute(C2x2_LD, (0,2,1,3,4,5)))
C2x2_LD = view(C2x2_LD, (T1.size(0)*a.size(0),T2.size(2)*a.size(3), dimsA[0], dimsA[0]))
if verbosity>0:
print("C2X2 LD "+str((coord[0]+vec[0],coord[1]+vec[1]))+"->"+str(shitf_coord)+" (-1,1): "+str(C2x2_LD.size()))
#----- build lower part C2x2_LD--C2x2_RD -----------------------------------
# 0 0->3 0 3->1
# |/23->12 |/23->45 & permute |/12->23 |/45
# C2x2_LD--1 1--C2x2_RD C2x2_LD------C2x2_RD
# TODO is it worthy(performance-wise) to instead overwrite one of C2x2_LD,C2x2_RD ?
lower_half = contract(C2x2_LD, C2x2_RD, ([1],[1]))
lower_half = permute(lower_half, (0,3,1,2,4,5))
# construct reduced density matrix by contracting lower and upper halfs
# C2x2_LU------C2x2_RU
# |\23->01 |\45->23
# 0 1
# 0 1
# |/23->45 |/45->67
# C2x2_LD------C2x2_RD
rdm = contract(upper_half,lower_half,([0,1],[0,1]))
# permute into order of s0,s1,s2,s3;s0',s1',s2',s3' where primed indices
# represent "ket"
# 01234567->02461357
# symmetrize and normalize
rdm= contiguous(permute(rdm, (0,2,4,6,1,3,5,7)))
rdm= _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
def rdm2x2_kagome(coord, state, env, sites_to_keep_00=('A', 'B', 'C'), sites_to_keep_10=('A', 'B', 'C'), sites_to_keep_01=('A', 'B', 'C'), sites_to_keep_11=('A', 'B', 'C'), sym_pos_def=False, verbosity=0):
r"""
:param coord: vertex (x,y) specifies upper left site of 2x2 subsystem
:param state: underlying wavefunction
:param env: environment corresponding to ``state``
:param verbosity: logging verbosity
:param sites_to_keep_00: physical sites needed for the unit cell at coord + (0, 0)
:param sites_to_keep_10: physical sites needed for the unit cell at coord + (1, 0)
:param sites_to_keep_01: physical sites needed for the unit cell at coord + (0, 1)
:param sites_to_keep_11: physical sites needed for the unit cell at coord + (1, 1)
:type coord: tuple(int,int)
:type state: IPEPS_KAGOME
:type env: ENV
:type verbosity: int
:return: 4-site reduced density matrix with indices :math:`s_0s_1s_2s_3;s'_0s'_1s'_2s'_3`
:rtype: torch.tensor
Computes 4-site reduced density matrix :math:`\rho_{2x2}` of 2x2 subsystem specified
by the vertex ``coord`` of its upper left corner using strategy:
1. compute four individual corners
2. construct upper and lower half of the network
3. contract upper and lower half to obtain final reduced density matrix
::
C--T------------------T------------------C = C2x2_LU(coord)--------C2x2_RU(coord+(1,0))
| | | | | |
T--A^+A(coord)--------A^+A(coord+(1,0))--T C2x2_LD(coord+(0,1))--C2x2_RD(coord+(1,1))
| | | |
T--A^+A(coord+(0,1))--A^+A(coord+(1,1))--T
| | | |
C--T------------------T------------------C
The physical indices `s` and `s'` of on-sites tensors :math:`A` (and :math:`A^\dagger`)
at vertices ``coord``, ``coord+(1,0)``, ``coord+(0,1)``, and ``coord+(1,1)`` are
left uncontracted and given in the same order::
s0 s1
s2 s3
"""
who = "rdm2x2_kagome"
# ----- building C2x2_LU ----------------------------------------------------
C = env.C[(state.vertexToSite(coord), (-1, -1))]
T1 = env.T[(state.vertexToSite(coord), (0, -1))]
T2 = env.T[(state.vertexToSite(coord), (-1, 0))]
dimsA = state.site(coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_00)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# C--10--T1--2
# 0 1
C2x2_LU = contract(C, T1, ([1], [0]))
# C------T1--2->1
# 0 1->0
# 0
# T2--2->3
# 1->2
C2x2_LU = contract(C2x2_LU, T2, ([0], [0]))
# C-------T1--1->0
# | 0
# | 0
# T2--3 1 a--3
# 2->1 2\45
C2x2_LU = contract(C2x2_LU, a, ([0, 3], [0, 1]))
# permute 012345->120345
# reshape (12)(03)45->0123
# C2x2--1
# |\23
# 0
C2x2_LU = contiguous(permute(C2x2_LU, (1, 2, 0, 3, 4, 5)))
C2x2_LU = view(C2x2_LU, (T2.size(1) * a.size(2), T1.size(2) * a.size(3), rpd, rpd))
if verbosity > 0:
print("C2X2 LU " + str(coord) + "->" + str(state.vertexToSite(coord)) + " (-1,-1): " + str(C2x2_LU.size()))
# ----- building C2x2_RU ----------------------------------------------------
vec = (1, 0)
shitf_coord = state.vertexToSite((coord[0] + vec[0], coord[1] + vec[1]))
C = env.C[(shitf_coord, (1, -1))]
T1 = env.T[(shitf_coord, (1, 0))]
T2 = env.T[(shitf_coord, (0, -1))]
dimsA = state.site(shitf_coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_10)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# 0--C
# 1
# 0
# 1--T1
# 2
C2x2_RU = contract(C, T1, ([1], [0]))
# 2<-0--T2--2 0--C
# 3<-1 |
# 0<-1--T1
# 1<-2
C2x2_RU = contract(C2x2_RU, T2, ([0], [2]))
# 1<-2--T2------C
# 3 |
# 45\0 |
# 2<-1--a--3 0--T1
# 3<-2 0<-1
C2x2_RU = contract(C2x2_RU, a, ([0, 3], [3, 0]))
# permute 012334->120345
# reshape (12)(03)45->0123
# 0--C2x2
# 23/|
# 1
C2x2_RU = contiguous(permute(C2x2_RU, (1, 2, 0, 3, 4, 5)))
C2x2_RU = view(C2x2_RU, (T2.size(0) * a.size(1), T1.size(2) * a.size(2), rpd, rpd))
if verbosity > 0:
print("C2X2 RU " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (1,-1): " + str(
C2x2_RU.size()))
# ----- build upper part C2x2_LU--C2x2_RU -----------------------------------
# C2x2_LU--1 0--C2x2_RU C2x2_LU------C2x2_RU
# |\23->12 |\23->45 & permute |\12->23 |\45
# 0 1->3 0 3->1
# TODO is it worthy(performance-wise) to instead overwrite one of C2x2_LU,C2x2_RU ?
upper_half = contract(C2x2_LU, C2x2_RU, ([1], [0]))
upper_half = permute(upper_half, (0, 3, 1, 2, 4, 5))
# ----- building C2x2_RD ----------------------------------------------------
vec = (1, 1)
shitf_coord = state.vertexToSite((coord[0] + vec[0], coord[1] + vec[1]))
C = env.C[(shitf_coord, (1, 1))]
T1 = env.T[(shitf_coord, (0, 1))]
T2 = env.T[(shitf_coord, (1, 0))]
dimsA = state.site(shitf_coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_11)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# 1<-0 0
# 2<-1--T1--2 1--C
C2x2_RD = contract(C, T1, ([1], [2]))
# 2<-0
# 3<-1--T2
# 2
# 0<-1 0
# 1<-2--T1---C
C2x2_RD = contract(C2x2_RD, T2, ([0], [2]))
# 2<-0 1<-2
# 3<-1--a--3 3--T2
# 2\45 |
# 0 |
# 0<-1--T1------C
C2x2_RD = contract(C2x2_RD, a, ([0, 3], [2, 3]))
# permute 012345->120345
# reshape (12)(03)45->0123
C2x2_RD = contiguous(permute(C2x2_RD, (1, 2, 0, 3, 4, 5)))
C2x2_RD = view(C2x2_RD, (T2.size(0) * a.size(0), T1.size(1) * a.size(1), rpd, rpd))
# 0
# |/23
# 1--C2x2
if verbosity > 0:
print("C2X2 RD " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (1,1): " + str(
C2x2_RD.size()))
# ----- building C2x2_LD ----------------------------------------------------
vec = (0, 1)
shitf_coord = state.vertexToSite((coord[0] + vec[0], coord[1] + vec[1]))
C = env.C[(shitf_coord, (-1, 1))]
T1 = env.T[(shitf_coord, (-1, 0))]
T2 = env.T[(shitf_coord, (0, 1))]
dimsA = state.site(shitf_coord).size()
a, rpd = build_reduced_density_matrix_kagome(coord, state, site_types=sites_to_keep_01)
a = view(contiguous(a), (dimsA[1] ** 2, dimsA[2] ** 2, dimsA[3] ** 2, dimsA[4] ** 2, rpd, rpd))
# 0->1
# T1--2
# 1
# 0
# C--1->0
C2x2_LD = contract(C, T1, ([0], [1]))
# 1->0
# T1--2->1
# |
# | 0->2
# C--0 1--T2--2->3
C2x2_LD = contract(C2x2_LD, T2, ([0], [1]))
# 0 0->2
# T1--1 1--a--3
# | 2\45
# | 2
# C--------T2--3->1
C2x2_LD = contract(C2x2_LD, a, ([1, 2], [1, 2]))
# permute 012345->021345
# reshape (02)(13)45->0123
# 0
# |/23
# C2x2--1
C2x2_LD = contiguous(permute(C2x2_LD, (0, 2, 1, 3, 4, 5)))
C2x2_LD = view(C2x2_LD, (T1.size(0) * a.size(0), T2.size(2) * a.size(3), rpd, rpd))
if verbosity > 0:
print("C2X2 LD " + str((coord[0] + vec[0], coord[1] + vec[1])) + "->" + str(shitf_coord) + " (-1,1): " + str(
C2x2_LD.size()))
# ----- build lower part C2x2_LD--C2x2_RD -----------------------------------
# 0 0->3 0 3->1
# |/23->12 |/23->45 & permute |/12->23 |/45
# C2x2_LD--1 1--C2x2_RD C2x2_LD------C2x2_RD
# TODO is it worthy(performance-wise) to instead overwrite one of C2x2_LD,C2x2_RD ?
lower_half = contract(C2x2_LD, C2x2_RD, ([1], [1]))
lower_half = permute(lower_half, (0, 3, 1, 2, 4, 5))
# construct reduced density matrix by contracting lower and upper halfs
# C2x2_LU------C2x2_RU
# |\23->01 |\45->23
# 0 1
# 0 1
# |/23->45 |/45->67
# C2x2_LD------C2x2_RD
rdm = contract(upper_half, lower_half, ([0, 1], [0, 1]))
# permute into order of s0,s1,s2,s3;s0',s1',s2',s3' where primed indices
# represent "ket"
# 01234567->02461357
# symmetrize and normalize
rdm = contiguous(permute(rdm, (0, 2, 4, 6, 1, 3, 5, 7)))
rdm = torch.squeeze(rdm)
rdm = _sym_pos_def_rdm(rdm, sym_pos_def=sym_pos_def, verbosity=verbosity, who=who)
return rdm
| 34.659509 | 205 | 0.494044 | 8,417 | 56,495 | 3.212308 | 0.03683 | 0.016791 | 0.017346 | 0.03018 | 0.923811 | 0.918855 | 0.912494 | 0.904172 | 0.896331 | 0.884903 | 0 | 0.101568 | 0.272059 | 56,495 | 1,629 | 206 | 34.680786 | 0.555891 | 0.415187 | 0 | 0.775238 | 0 | 0.00381 | 0.048001 | 0.014833 | 0 | 0 | 0 | 0.004297 | 0.001905 | 1 | 0.022857 | false | 0 | 0.009524 | 0 | 0.055238 | 0.091429 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
25c27d2eb386e3b2e18f52aa76f31c236ffb9fdd | 46 | py | Python | cifar10/trainer/fid_score.py | rahhul/GANs | cec9e2f81528099407b8a9d3dce2f1cf85e449be | [
"MIT"
] | null | null | null | cifar10/trainer/fid_score.py | rahhul/GANs | cec9e2f81528099407b8a9d3dce2f1cf85e449be | [
"MIT"
] | null | null | null | cifar10/trainer/fid_score.py | rahhul/GANs | cec9e2f81528099407b8a9d3dce2f1cf85e449be | [
"MIT"
] | null | null | null | # python3
import tensorflow as tf
## TODO:
| 7.666667 | 23 | 0.673913 | 6 | 46 | 5.166667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.028571 | 0.23913 | 46 | 5 | 24 | 9.2 | 0.857143 | 0.282609 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
25df64ed52eb6b6bb0801936fc7e6f72990f56c2 | 1,726 | py | Python | {{cookiecutter.project_slug}}/tests/adapter/auth/test_01.py | mleist/d4 | d3f3d9b66d92db5fde474c4122a9188f4a9af776 | [
"BSD-3-Clause"
] | 5 | 2021-11-09T17:57:50.000Z | 2022-01-26T13:39:22.000Z | {{cookiecutter.project_slug}}/tests/adapter/auth/test_01.py | mleist/d4 | d3f3d9b66d92db5fde474c4122a9188f4a9af776 | [
"BSD-3-Clause"
] | null | null | null | {{cookiecutter.project_slug}}/tests/adapter/auth/test_01.py | mleist/d4 | d3f3d9b66d92db5fde474c4122a9188f4a9af776 | [
"BSD-3-Clause"
] | null | null | null | import requests
from lxml import html
def test_keycloak_alice01(docker_adapter):
status = 200
session = requests.Session()
url_1 = 'http://127.0.0.1:{{cookiecutter.d4service_adapter_port}}/finance/salary/alice'
resp_1 = session.get(url_1)
assert resp_1.status_code == status
tree = html.fromstring(resp_1.content)
url_2 = tree.xpath('//form[@id="kc-form-login"]')[0].attrib['action']
form_data = {'username': 'alice', 'password': 'alice', 'credentialId': ''}
resp_2 = session.post(url_2, data=form_data)
assert resp_2.json() == {"msg": "success", "name": "alice"}
def test_keycloak_bob01(docker_adapter):
status = 200
session = requests.Session()
url_1 = 'http://127.0.0.1:{{cookiecutter.d4service_adapter_port}}/finance/salary/bob'
resp_1 = session.get(url_1)
assert resp_1.status_code == status
tree = html.fromstring(resp_1.content)
url_2 = tree.xpath('//form[@id="kc-form-login"]')[0].attrib['action']
form_data = {'username': 'bob', 'password': 'bob', 'credentialId': ''}
resp_2 = session.post(url_2, data=form_data)
assert resp_2.json() == {"msg": "success", "name": "bob"}
def test_keycloak_bob02(docker_adapter):
status = 200
session = requests.Session()
url_1 = 'http://127.0.0.1:{{cookiecutter.d4service_adapter_port}}/finance/salary/alice'
resp_1 = session.get(url_1)
assert resp_1.status_code == status
tree = html.fromstring(resp_1.content)
url_2 = tree.xpath('//form[@id="kc-form-login"]')[0].attrib['action']
form_data = {'username': 'bob', 'password': 'bob', 'credentialId': ''}
resp_2 = session.post(url_2, data=form_data)
assert resp_2.json() == {"msg": "success", "name": "alice"}
| 41.095238 | 91 | 0.66628 | 243 | 1,726 | 4.522634 | 0.213992 | 0.040946 | 0.040946 | 0.060055 | 0.89263 | 0.89263 | 0.89263 | 0.89263 | 0.89263 | 0.89263 | 0 | 0.045051 | 0.151217 | 1,726 | 41 | 92 | 42.097561 | 0.705119 | 0 | 0 | 0.771429 | 0 | 0 | 0.283314 | 0.046929 | 0 | 0 | 0 | 0 | 0.171429 | 1 | 0.085714 | false | 0.085714 | 0.057143 | 0 | 0.142857 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 8 |
d335e087e7c26adb395be7be734e773f55c52c58 | 140 | py | Python | projects/TrainerCompose/joined_trainer.py | Bartolo1024/detectron2 | 29ead1f46c5054bc45906363aa5843b160650d18 | [
"Apache-2.0"
] | null | null | null | projects/TrainerCompose/joined_trainer.py | Bartolo1024/detectron2 | 29ead1f46c5054bc45906363aa5843b160650d18 | [
"Apache-2.0"
] | null | null | null | projects/TrainerCompose/joined_trainer.py | Bartolo1024/detectron2 | 29ead1f46c5054bc45906363aa5843b160650d18 | [
"Apache-2.0"
] | null | null | null | from . import apex_trainer, coco_eval_trainer
class TrainerCompose(coco_eval_trainer.COCOEvalTrainer, apex_trainer.ApexTrainer):
pass
| 23.333333 | 82 | 0.835714 | 17 | 140 | 6.529412 | 0.647059 | 0.198198 | 0.27027 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.107143 | 140 | 5 | 83 | 28 | 0.888 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.333333 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 7 |
d34ef83a353ca0d12a73767978a49964130ded96 | 117 | py | Python | learning_to_adapt/samplers/__init__.py | jeonggwanlee/varibad | 427bbfaa973710de50187d170452116ad1c2a742 | [
"MIT"
] | null | null | null | learning_to_adapt/samplers/__init__.py | jeonggwanlee/varibad | 427bbfaa973710de50187d170452116ad1c2a742 | [
"MIT"
] | 2 | 2021-01-13T14:58:50.000Z | 2021-01-13T14:59:40.000Z | learning_to_adapt/samplers/__init__.py | jeonggwanlee/varibad | 427bbfaa973710de50187d170452116ad1c2a742 | [
"MIT"
] | null | null | null | from learning_to_adapt.samplers.base import BaseSampler
from learning_to_adapt.samplers.base import SampleProcessor
| 29.25 | 59 | 0.888889 | 16 | 117 | 6.25 | 0.5625 | 0.24 | 0.28 | 0.38 | 0.74 | 0.74 | 0.74 | 0 | 0 | 0 | 0 | 0 | 0.076923 | 117 | 3 | 60 | 39 | 0.925926 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 10 |
d38135e5008ad2f729efcbab4cc4e3e1bf8cd1f1 | 2,339 | py | Python | dependencies.py | KittensAreDaBest/kittenpanel | e6e071458256967a376ecda98a167ec949ce0bc9 | [
"MIT"
] | 33 | 2021-08-30T08:28:29.000Z | 2022-03-06T12:04:41.000Z | dependencies.py | Shersha01/kittenpanel | e6e071458256967a376ecda98a167ec949ce0bc9 | [
"MIT"
] | 2 | 2021-09-12T06:58:24.000Z | 2021-09-21T15:55:43.000Z | dependencies.py | Shersha01/kittenpanel | e6e071458256967a376ecda98a167ec949ce0bc9 | [
"MIT"
] | 5 | 2021-08-30T08:29:18.000Z | 2022-01-23T05:41:11.000Z | from fastapi import Header, HTTPException, Request
from fastapi import Cookie
class AuthenticationException(Exception):
def __init__(self, name: str, disabled: bool):
self.name = name
self.disabled = disabled
class AdminException(Exception):
def __init__(self, name: str):
self.name = name
async def get_user(request: Request, kittenpanel_sessionid: str = Cookie(None)):
if kittenpanel_sessionid is None:
raise AuthenticationException(name="Not authenticated", disabled=False)
db = await request.app.database.get_db_client()
db = db[request.app.config['database']['database']]
session = await db.sessions.find_one({"_id": kittenpanel_sessionid})
if session is None:
raise AuthenticationException(name="Unauthorized", disabled=False)
else:
user = await db.users.find_one({"_id": session["user_id"]})
if user['disabled']:
raise AuthenticationException(name="Account Disabled", disabled=True)
return user
async def get_user_session(request: Request, kittenpanel_sessionid: str = Cookie(None)):
if kittenpanel_sessionid is None:
raise AuthenticationException(name="Not authenticated", disabled=False)
db = await request.app.database.get_db_client()
db = db[request.app.config['database']['database']]
session = await db.sessions.find_one({"_id": kittenpanel_sessionid})
if session is None:
raise AuthenticationException(name="Unauthorized", disabled=False)
else:
return session
async def get_admin_user(request: Request, kittenpanel_sessionid: str = Cookie(None)):
if kittenpanel_sessionid is None:
raise AuthenticationException(name="Not authenticated", disabled=False)
db = await request.app.database.get_db_client()
db = db[request.app.config['database']['database']]
session = await db.sessions.find_one({"_id": kittenpanel_sessionid})
if session is None:
raise AuthenticationException(name="Unauthorized", disabled=False)
else:
user = await db.users.find_one({"_id": session["user_id"]})
if user['disabled']:
raise AuthenticationException(name="Account Disabled", disabled=True)
if not user['pterodactyl']['admin']:
raise AdminException(name="Not an admin")
return user | 44.132075 | 88 | 0.700299 | 270 | 2,339 | 5.918519 | 0.185185 | 0.112641 | 0.1602 | 0.12766 | 0.806633 | 0.806633 | 0.772841 | 0.772841 | 0.772841 | 0.772841 | 0 | 0 | 0.189825 | 2,339 | 53 | 89 | 44.132075 | 0.843272 | 0 | 0 | 0.723404 | 0 | 0 | 0.102564 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.042553 | false | 0 | 0.042553 | 0 | 0.191489 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
9f1dbb1a456a581ed30e883af69a7b1e6d4b7ac3 | 976 | py | Python | tests/test_scrapbox.py | cl-tohoku/sb-unfurl | 8a333a5a4b68501859af0af5f959a22fe52d0f6a | [
"MIT"
] | null | null | null | tests/test_scrapbox.py | cl-tohoku/sb-unfurl | 8a333a5a4b68501859af0af5f959a22fe52d0f6a | [
"MIT"
] | null | null | null | tests/test_scrapbox.py | cl-tohoku/sb-unfurl | 8a333a5a4b68501859af0af5f959a22fe52d0f6a | [
"MIT"
] | null | null | null | from sb_unfurl.scrapbox import parse_url
def test_parse_url():
url = "https://scrapbox.io/tohoku-nlp/2019-01-31_Minutes_of_Research_Seminar_%23324"
team, title, line_id = parse_url(url)
assert team == "tohoku-nlp"
assert title == "2019-01-31_Minutes_of_Research_Seminar_%23324"
assert line_id == ""
url = "https://scrapbox.io/tohoku-nlp/2019-01-31_Minutes_of_Research_Seminar_%23324#5c5298c11309ba00005254b8"
team, title, line_id = parse_url(url)
assert team == "tohoku-nlp"
assert title == "2019-01-31_Minutes_of_Research_Seminar_%23324"
assert line_id == "5c5298c11309ba00005254b8"
url = "https://scrapbox.io/tohoku-nlp/2019-02-22;_%E5%A4%A7%E7%AB%B9,_%E4%BA%95%E4%B9%8B%E4%B8%8A,_%E6%A8%AA%E4%BA%95"
team, title, line_id = parse_url(url)
assert team == "tohoku-nlp"
assert (
title
== "2019-02-22;_%E5%A4%A7%E7%AB%B9,_%E4%BA%95%E4%B9%8B%E4%B8%8A,_%E6%A8%AA%E4%BA%95"
)
assert line_id == ""
| 39.04 | 122 | 0.685451 | 159 | 976 | 3.962264 | 0.27673 | 0.085714 | 0.069841 | 0.095238 | 0.826984 | 0.826984 | 0.826984 | 0.784127 | 0.784127 | 0.784127 | 0 | 0.174757 | 0.155738 | 976 | 24 | 123 | 40.666667 | 0.589806 | 0 | 0 | 0.5 | 0 | 0.1 | 0.522541 | 0.197746 | 0 | 0 | 0 | 0 | 0.45 | 1 | 0.05 | false | 0 | 0.05 | 0 | 0.1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
9f3041df0ac53320e68e428faefeac520d3cfb25 | 15,581 | py | Python | tests/snapshots/snap_test_holidata/test_holidata_produces_holidays_for_locale_and_year[es_ES-2011] 1.py | gour/holidata | 89c7323f9c5345a3ecbf5cd5a835b0e08cfebc13 | [
"MIT"
] | 32 | 2019-04-12T08:01:34.000Z | 2022-02-28T04:41:50.000Z | tests/snapshots/snap_test_holidata/test_holidata_produces_holidays_for_locale_and_year[es_ES-2011] 1.py | gour/holidata | 89c7323f9c5345a3ecbf5cd5a835b0e08cfebc13 | [
"MIT"
] | 74 | 2019-07-09T16:35:20.000Z | 2022-03-09T16:41:34.000Z | tests/snapshots/snap_test_holidata/test_holidata_produces_holidays_for_locale_and_year[es_ES-2011] 1.py | gour/holidata | 89c7323f9c5345a3ecbf5cd5a835b0e08cfebc13 | [
"MIT"
] | 20 | 2019-01-28T07:41:02.000Z | 2022-02-16T02:38:57.000Z | [
{
'date': '2011-01-01',
'description': 'Año Nuevo',
'locale': 'es-ES',
'notes': '',
'region': '',
'type': 'NF'
},
{
'date': '2011-01-06',
'description': 'Epifanía del Señor',
'locale': 'es-ES',
'notes': '',
'region': '',
'type': 'NRF'
},
{
'date': '2011-02-28',
'description': 'Día de Andalucía',
'locale': 'es-ES',
'notes': '',
'region': 'AN',
'type': 'F'
},
{
'date': '2011-03-01',
'description': 'Día de las Illes Balears',
'locale': 'es-ES',
'notes': '',
'region': 'IB',
'type': 'F'
},
{
'date': '2011-03-19',
'description': 'San José',
'locale': 'es-ES',
'notes': '',
'region': 'CM',
'type': 'RF'
},
{
'date': '2011-03-19',
'description': 'San José',
'locale': 'es-ES',
'notes': '',
'region': 'GA',
'type': 'RF'
},
{
'date': '2011-03-19',
'description': 'San José',
'locale': 'es-ES',
'notes': '',
'region': 'MC',
'type': 'RF'
},
{
'date': '2011-03-19',
'description': 'San José',
'locale': 'es-ES',
'notes': '',
'region': 'ML',
'type': 'RF'
},
{
'date': '2011-03-19',
'description': 'San José',
'locale': 'es-ES',
'notes': '',
'region': 'VC',
'type': 'RF'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'AN',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'AR',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'AS',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'CB',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'CE',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'CL',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'CM',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'CN',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'EX',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'GA',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'IB',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'MC',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'MD',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'ML',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'NC',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'PV',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'RI',
'type': 'RV'
},
{
'date': '2011-04-21',
'description': 'Jueves Santo',
'locale': 'es-ES',
'notes': '',
'region': 'VC',
'type': 'RV'
},
{
'date': '2011-04-22',
'description': 'Viernes Santo',
'locale': 'es-ES',
'notes': '',
'region': '',
'type': 'NRV'
},
{
'date': '2011-04-23',
'description': 'Fiesta de Castilla y León',
'locale': 'es-ES',
'notes': '',
'region': 'CL',
'type': 'F'
},
{
'date': '2011-04-23',
'description': 'San Jorge / Día de Aragón',
'locale': 'es-ES',
'notes': '',
'region': 'AR',
'type': 'RF'
},
{
'date': '2011-04-24',
'description': 'Pascua',
'locale': 'es-ES',
'notes': '',
'region': '',
'type': 'NRV'
},
{
'date': '2011-04-25',
'description': 'Lunes de Pascua',
'locale': 'es-ES',
'notes': '',
'region': 'CT',
'type': 'RV'
},
{
'date': '2011-04-25',
'description': 'Lunes de Pascua',
'locale': 'es-ES',
'notes': '',
'region': 'IB',
'type': 'RV'
},
{
'date': '2011-04-25',
'description': 'Lunes de Pascua',
'locale': 'es-ES',
'notes': '',
'region': 'NC',
'type': 'RV'
},
{
'date': '2011-04-25',
'description': 'Lunes de Pascua',
'locale': 'es-ES',
'notes': '',
'region': 'PV',
'type': 'RV'
},
{
'date': '2011-04-25',
'description': 'Lunes de Pascua',
'locale': 'es-ES',
'notes': '',
'region': 'RI',
'type': 'RV'
},
{
'date': '2011-04-25',
'description': 'Lunes de Pascua',
'locale': 'es-ES',
'notes': '',
'region': 'VC',
'type': 'RV'
},
{
'date': '2011-05-01',
'description': 'Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': '',
'type': 'NF'
},
{
'date': '2011-05-02',
'description': 'Fiesta de la Comunidad de Madrid',
'locale': 'es-ES',
'notes': '',
'region': 'MD',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'AN',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'AR',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'AS',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'CB',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'CE',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'EX',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'MC',
'type': 'F'
},
{
'date': '2011-05-02',
'description': 'Lunes siguiente a la Fiesta del Trabajo',
'locale': 'es-ES',
'notes': '',
'region': 'VC',
'type': 'F'
},
{
'date': '2011-05-17',
'description': 'Día de las Letras Gallegas',
'locale': 'es-ES',
'notes': '',
'region': 'GA',
'type': 'F'
},
{
'date': '2011-05-30',
'description': 'Día de Canarias',
'locale': 'es-ES',
'notes': '',
'region': 'CN',
'type': 'F'
},
{
'date': '2011-05-31',
'description': 'Día de Castilla-La Mancha',
'locale': 'es-ES',
'notes': '',
'region': 'CM',
'type': 'F'
},
{
'date': '2011-06-09',
'description': 'Día de la Región de Murcia',
'locale': 'es-ES',
'notes': '',
'region': 'MC',
'type': 'F'
},
{
'date': '2011-06-09',
'description': 'Día de La Rioja',
'locale': 'es-ES',
'notes': '',
'region': 'RI',
'type': 'F'
},
{
'date': '2011-06-13',
'description': 'Lunes de Pascua Granada',
'locale': 'es-ES',
'notes': '',
'region': 'CT',
'type': 'F'
},
{
'date': '2011-06-23',
'description': 'Corpus Christi',
'locale': 'es-ES',
'notes': '',
'region': 'CM',
'type': 'RV'
},
{
'date': '2011-06-23',
'description': 'Corpus Christi',
'locale': 'es-ES',
'notes': '',
'region': 'MD',
'type': 'RV'
},
{
'date': '2011-06-24',
'description': 'San Juan',
'locale': 'es-ES',
'notes': '',
'region': 'CT',
'type': 'RF'
},
{
'date': '2011-07-25',
'description': 'Santiago Apóstol',
'locale': 'es-ES',
'notes': '',
'region': 'CL',
'type': 'RF'
},
{
'date': '2011-07-25',
'description': 'Santiago Apóstol',
'locale': 'es-ES',
'notes': '',
'region': 'MD',
'type': 'RF'
},
{
'date': '2011-07-25',
'description': 'Santiago Apóstol',
'locale': 'es-ES',
'notes': '',
'region': 'NC',
'type': 'RF'
},
{
'date': '2011-07-25',
'description': 'Santiago Apóstol',
'locale': 'es-ES',
'notes': '',
'region': 'PV',
'type': 'RF'
},
{
'date': '2011-07-25',
'description': 'Santiago Apóstol',
'locale': 'es-ES',
'notes': '',
'region': 'RI',
'type': 'RF'
},
{
'date': '2011-07-25',
'description': 'Santiago Apóstol / Día Nacional de Galicia',
'locale': 'es-ES',
'notes': '',
'region': 'GA',
'type': 'RF'
},
{
'date': '2011-07-28',
'description': 'Día de las Instituciones de Cantabria',
'locale': 'es-ES',
'notes': '',
'region': 'CB',
'type': 'F'
},
{
'date': '2011-08-15',
'description': 'Asunción de la Virgen',
'locale': 'es-ES',
'notes': '',
'region': '',
'type': 'NRF'
},
{
'date': '2011-09-08',
'description': 'Día de Asturias',
'locale': 'es-ES',
'notes': '',
'region': 'AS',
'type': 'F'
},
{
'date': '2011-09-08',
'description': 'Día de Extremadura',
'locale': 'es-ES',
'notes': '',
'region': 'EX',
'type': 'F'
},
{
'date': '2011-09-15',
'description': 'La Bien Aparecida',
'locale': 'es-ES',
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'date': '2011-12-25',
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'date': '2011-12-26',
'description': 'San Esteban',
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'date': '2011-12-26',
'description': 'San Esteban',
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'date': '2011-12-26',
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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, 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, 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, 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, 0, 0, 0, 1, 3]] | 270,607 | 270,607 | 0.332608 | 90,001 | 270,607 | 1.000056 | 0.000056 | 1.970957 | 2.942571 | 3.905117 | 0.999933 | 0.999933 | 0.999933 | 0.999933 | 0.999933 | 0.999922 | 0 | 0.498317 | 0.332582 | 270,607 | 1 | 270,607 | 270,607 | 0.000033 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 |
9fa9bb7cbd55c991a365b06f1ffe65828b7442bc | 1,591 | py | Python | apol_dataviz/formatters.py | apolitical/apolitical-data-viz | 2ef27bf3354175a15c9f496729b29cae04ed3f82 | [
"MIT"
] | 2 | 2019-05-22T08:43:22.000Z | 2021-06-14T13:25:00.000Z | apol_dataviz/formatters.py | apolitical/apolitical-data-viz | 2ef27bf3354175a15c9f496729b29cae04ed3f82 | [
"MIT"
] | 4 | 2021-06-01T23:47:22.000Z | 2022-03-12T01:02:42.000Z | apol_dataviz/formatters.py | apolitical/apolitical-data-viz | 2ef27bf3354175a15c9f496729b29cae04ed3f82 | [
"MIT"
] | null | null | null | def get_ts_tick_labels(df):
"""
get_tick_labels
Function for producing cleanly-formatted tick labels for DataFrames
with a time-series index
INPUTS:
df - DataFrame with datetime Index from which to extract
tick labels for plotting
OUTPUTS:
tick_labs - array of tick labels (one per day, minimally complex)
"""
tick_labs = df.index.strftime("%d").values
is_first_week_of_month = df.index.day <= 7
is_first_week_of_year = df.index.dayofyear <= 7
tick_labs[is_first_week_of_month] = df.index[is_first_week_of_month].strftime(
"%d\n%b"
)
tick_labs[is_first_week_of_year] = df.index[is_first_week_of_year].strftime(
"%d\n%b\n%Y"
)
return tick_labs
def get_ts_tick_labels_monthly(df):
"""
get_ts_tick_labels_monthly
Function for producing cleanly-formatted tick labels for DataFrames
with a time-series index, one per week
INPUTS:
df - DataFrame with datetime Index from which to extract
tick labels for plotting
OUTPUTS:
tick_labs - array of tick labels (one per month, minimally complex)
"""
tick_labs = df.index.strftime("").values
is_first_week_of_month = df.index.day <= 7
is_first_week_of_year = df.index.dayofyear <= 7
tick_labs[is_first_week_of_month] = df.index[is_first_week_of_month].strftime("%b")
tick_labs[is_first_week_of_year] = df.index[is_first_week_of_year].strftime(
"%b\n%Y"
)
return tick_labs
| 25.253968 | 88 | 0.653677 | 231 | 1,591 | 4.194805 | 0.212121 | 0.086687 | 0.136223 | 0.160991 | 0.95872 | 0.891641 | 0.856553 | 0.776058 | 0.776058 | 0.776058 | 0 | 0.003419 | 0.264613 | 1,591 | 62 | 89 | 25.66129 | 0.824786 | 0.385921 | 0 | 0.4 | 0 | 0 | 0.031477 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0 | 0 | 0.2 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
9fc09673f96e69309677c45c0a8e2a7aa522c769 | 54,705 | py | Python | election/geocodio_ocdids.py | everyvoter/everyvoter | 65d9b8bdf9b5c64057135c279f6e03b6c207e0fa | [
"MIT"
] | 5 | 2019-07-01T17:50:44.000Z | 2022-02-20T02:44:42.000Z | election/geocodio_ocdids.py | everyvoter/everyvoter | 65d9b8bdf9b5c64057135c279f6e03b6c207e0fa | [
"MIT"
] | 3 | 2020-06-05T21:44:33.000Z | 2021-06-10T21:39:26.000Z | election/geocodio_ocdids.py | everyvoter/everyvoter | 65d9b8bdf9b5c64057135c279f6e03b6c207e0fa | [
"MIT"
] | 1 | 2021-12-09T06:32:40.000Z | 2021-12-09T06:32:40.000Z | """OCD ID(s) that map to individual Geocod.io Responses"""
# pylint: disable=line-too-long
GEOCODIO_OCDIDS_SENATE = {
'AK': {
'A': ['ocd-division/country:us/state:ak/sldu:a'],
'B': ['ocd-division/country:us/state:ak/sldu:b'],
'C': ['ocd-division/country:us/state:ak/sldu:c'],
'D': ['ocd-division/country:us/state:ak/sldu:d'],
'E': ['ocd-division/country:us/state:ak/sldu:e'],
'F': ['ocd-division/country:us/state:ak/sldu:f'],
'G': ['ocd-division/country:us/state:ak/sldu:g'],
'H': ['ocd-division/country:us/state:ak/sldu:h'],
'I': ['ocd-division/country:us/state:ak/sldu:i'],
'J': ['ocd-division/country:us/state:ak/sldu:j'],
'K': ['ocd-division/country:us/state:ak/sldu:k'],
'L': ['ocd-division/country:us/state:ak/sldu:l'],
'M': ['ocd-division/country:us/state:ak/sldu:m'],
'N': ['ocd-division/country:us/state:ak/sldu:n'],
'O': ['ocd-division/country:us/state:ak/sldu:o'],
'P': ['ocd-division/country:us/state:ak/sldu:p'],
'Q': ['ocd-division/country:us/state:ak/sldu:q'],
'R': ['ocd-division/country:us/state:ak/sldu:r'],
'S': ['ocd-division/country:us/state:ak/sldu:s'],
'T': ['ocd-division/country:us/state:ak/sldu:t']
},
'DC': {
'1': ['ocd-division/country:us/district:dc/ward:1'],
'2': ['ocd-division/country:us/district:dc/ward:2'],
'3': ['ocd-division/country:us/district:dc/ward:3'],
'4': ['ocd-division/country:us/district:dc/ward:4'],
'5': ['ocd-division/country:us/district:dc/ward:5'],
'6': ['ocd-division/country:us/district:dc/ward:6'],
'7': ['ocd-division/country:us/district:dc/ward:7'],
'8': ['ocd-division/country:us/district:dc/ward:8']
},
'MA': {
'1': ['ocd-division/country:us/state:ma/sldu:1st_suffolk'],
'2': ['ocd-division/country:us/state:ma/sldu:2nd_suffolk'],
'3': ['ocd-division/country:us/state:ma/sldu:hampden'],
'4': ['ocd-division/country:us/state:ma/sldu:berkshire_hampshire_franklin_and_hampden'],
'5': ['ocd-division/country:us/state:ma/sldu:2nd_hampden_and_hampshire'],
'6': ['ocd-division/country:us/state:ma/sldu:hampshire_franklin_and_worcester'],
'7': ['ocd-division/country:us/state:ma/sldu:1st_hampden_and_hampshire'],
'8': ['ocd-division/country:us/state:ma/sldu:worcester_hampden_hampshire_and_middlesex'],
'9': ['ocd-division/country:us/state:ma/sldu:worcester_and_middlesex'],
'10': ['ocd-division/country:us/state:ma/sldu:1st_worcester'],
'11': ['ocd-division/country:us/state:ma/sldu:2nd_worcester'],
'12': ['ocd-division/country:us/state:ma/sldu:worcester_and_norfolk'],
'13': ['ocd-division/country:us/state:ma/sldu:1st_middlesex'],
'14': ['ocd-division/country:us/state:ma/sldu:middlesex_and_worcester'],
'15': ['ocd-division/country:us/state:ma/sldu:2nd_middlesex_and_norfolk'],
'16': ['ocd-division/country:us/state:ma/sldu:3rd_middlesex'],
'17': ['ocd-division/country:us/state:ma/sldu:norfolk_bristol_and_middlesex'],
'18': ['ocd-division/country:us/state:ma/sldu:2nd_essex_and_middlesex'],
'19': ['ocd-division/country:us/state:ma/sldu:1st_essex'],
'20': ['ocd-division/country:us/state:ma/sldu:1st_essex_and_middlesex'],
'21': ['ocd-division/country:us/state:ma/sldu:2nd_essex'],
'22': ['ocd-division/country:us/state:ma/sldu:3rd_essex'],
'23': ['ocd-division/country:us/state:ma/sldu:5th_middlesex'],
'24': ['ocd-division/country:us/state:ma/sldu:4th_middlesex'],
'25': ['ocd-division/country:us/state:ma/sldu:2nd_middlesex'],
'26': ['ocd-division/country:us/state:ma/sldu:middlesex_and_suffolk'],
'27': ['ocd-division/country:us/state:ma/sldu:1st_suffolk_and_middlesex'],
'28': ['ocd-division/country:us/state:ma/sldu:2nd_suffolk_and_middlesex'],
'29': ['ocd-division/country:us/state:ma/sldu:1st_middlesex_and_norfolk'],
'30': ['ocd-division/country:us/state:ma/sldu:norfolk_and_suffolk'],
'31': ['ocd-division/country:us/state:ma/sldu:bristol_and_norfolk'],
'32': ['ocd-division/country:us/state:ma/sldu:norfolk_bristol_and_plymouth'],
'33': ['ocd-division/country:us/state:ma/sldu:norfolk_and_plymouth'],
'34': ['ocd-division/country:us/state:ma/sldu:plymouth_and_norfolk'],
'35': ['ocd-division/country:us/state:ma/sldu:2nd_plymouth_and_bristol'],
'36': ['ocd-division/country:us/state:ma/sldu:1st_plymouth_and_bristol'],
'37': ['ocd-division/country:us/state:ma/sldu:1st_bristol_and_plymouth'],
'38': ['ocd-division/country:us/state:ma/sldu:2nd_bristol_and_plymouth'],
'39': ['ocd-division/country:us/state:ma/sldu:plymouth_and_barnstable'],
'40': ['ocd-division/country:us/state:ma/sldu:cape_and_islands']
},
'VT': {
'ADD': ['ocd-division/country:us/state:vt/sldu:addison'],
'BEN': ['ocd-division/country:us/state:vt/sldu:bennington'],
'CAL': ['ocd-division/country:us/state:vt/sldu:caledonia'],
'CGI': ['ocd-division/country:us/state:vt/sldu:grand_isle-chittenden'],
'CHI': ['ocd-division/country:us/state:vt/sldu:chittenden'],
'E-O': ['ocd-division/country:us/state:vt/sldu:essex-orleans'],
'FRA': ['ocd-division/country:us/state:vt/sldu:franklin'],
'LAM': ['ocd-division/country:us/state:vt/sldu:lamoille'],
'ORA': ['ocd-division/country:us/state:vt/sldu:orange'],
'RUT': ['ocd-division/country:us/state:vt/sldu:rutland'],
'WAS': ['ocd-division/country:us/state:vt/sldu:washington'],
'WDM': ['ocd-division/country:us/state:vt/sldu:windham'],
'WSR': ['ocd-division/country:us/state:vt/sldu:windsor']
}
}
GEOCODIO_OCDIDS_HOUSE = {
'MA': {
'60': ['ocd-division/country:us/state:ma/sldl:1st_barnstable'],
'61': ['ocd-division/country:us/state:ma/sldl:2nd_barnstable'],
'62': ['ocd-division/country:us/state:ma/sldl:3rd_barnstable'],
'63': ['ocd-division/country:us/state:ma/sldl:4th_barnstable'],
'64': ['ocd-division/country:us/state:ma/sldl:barnstable_dukes_and_nantucket'],
'65': ['ocd-division/country:us/state:ma/sldl:1st_berkshire'],
'66': ['ocd-division/country:us/state:ma/sldl:2nd_berkshire'],
'67': ['ocd-division/country:us/state:ma/sldl:3rd_berkshire'],
'68': ['ocd-division/country:us/state:ma/sldl:4th_berkshire'],
'69': ['ocd-division/country:us/state:ma/sldl:1st_bristol'],
'70': ['ocd-division/country:us/state:ma/sldl:2nd_bristol'],
'71': ['ocd-division/country:us/state:ma/sldl:3rd_bristol'],
'72': ['ocd-division/country:us/state:ma/sldl:4th_bristol'],
'73': ['ocd-division/country:us/state:ma/sldl:5th_bristol'],
'74': ['ocd-division/country:us/state:ma/sldl:6th_bristol'],
'75': ['ocd-division/country:us/state:ma/sldl:7th_bristol'],
'76': ['ocd-division/country:us/state:ma/sldl:8th_bristol'],
'77': ['ocd-division/country:us/state:ma/sldl:9th_bristol'],
'78': ['ocd-division/country:us/state:ma/sldl:10th_bristol'],
'79': ['ocd-division/country:us/state:ma/sldl:11th_bristol'],
'80': ['ocd-division/country:us/state:ma/sldl:12th_bristol'],
'81': ['ocd-division/country:us/state:ma/sldl:13th_bristol'],
'82': ['ocd-division/country:us/state:ma/sldl:14th_bristol'],
'83': ['ocd-division/country:us/state:ma/sldl:1st_essex'],
'84': ['ocd-division/country:us/state:ma/sldl:2nd_essex'],
'85': ['ocd-division/country:us/state:ma/sldl:3rd_essex'],
'86': ['ocd-division/country:us/state:ma/sldl:4th_essex'],
'87': ['ocd-division/country:us/state:ma/sldl:5th_essex'],
'88': ['ocd-division/country:us/state:ma/sldl:6th_essex'],
'89': ['ocd-division/country:us/state:ma/sldl:7th_essex'],
'90': ['ocd-division/country:us/state:ma/sldl:8th_essex'],
'91': ['ocd-division/country:us/state:ma/sldl:9th_essex'],
'92': ['ocd-division/country:us/state:ma/sldl:10th_essex'],
'93': ['ocd-division/country:us/state:ma/sldl:11th_essex'],
'94': ['ocd-division/country:us/state:ma/sldl:12th_essex'],
'95': ['ocd-division/country:us/state:ma/sldl:13th_essex'],
'96': ['ocd-division/country:us/state:ma/sldl:14th_essex'],
'97': ['ocd-division/country:us/state:ma/sldl:15th_essex'],
'98': ['ocd-division/country:us/state:ma/sldl:16th_essex'],
'99': ['ocd-division/country:us/state:ma/sldl:17th_essex'],
'100': ['ocd-division/country:us/state:ma/sldl:1st_franklin'],
'101': ['ocd-division/country:us/state:ma/sldl:2nd_franklin'],
'102': ['ocd-division/country:us/state:ma/sldl:1st_hampden'],
'103': ['ocd-division/country:us/state:ma/sldl:2nd_hampden'],
'104': ['ocd-division/country:us/state:ma/sldl:3rd_hampden'],
'105': ['ocd-division/country:us/state:ma/sldl:4th_hampden'],
'106': ['ocd-division/country:us/state:ma/sldl:5th_hampden'],
'107': ['ocd-division/country:us/state:ma/sldl:6th_hampden'],
'108': ['ocd-division/country:us/state:ma/sldl:7th_hampden'],
'109': ['ocd-division/country:us/state:ma/sldl:8th_hampden'],
'110': ['ocd-division/country:us/state:ma/sldl:9th_hampden'],
'111': ['ocd-division/country:us/state:ma/sldl:10th_hampden'],
'112': ['ocd-division/country:us/state:ma/sldl:11th_hampden'],
'113': ['ocd-division/country:us/state:ma/sldl:12th_hampden'],
'114': ['ocd-division/country:us/state:ma/sldl:18th_essex'],
'115': ['ocd-division/country:us/state:ma/sldl:1st_hampshire'],
'116': ['ocd-division/country:us/state:ma/sldl:2nd_hampshire'],
'117': ['ocd-division/country:us/state:ma/sldl:3rd_hampshire'],
'118': ['ocd-division/country:us/state:ma/sldl:1st_middlesex'],
'119': ['ocd-division/country:us/state:ma/sldl:2nd_middlesex'],
'120': ['ocd-division/country:us/state:ma/sldl:3rd_middlesex'],
'121': ['ocd-division/country:us/state:ma/sldl:4th_middlesex'],
'122': ['ocd-division/country:us/state:ma/sldl:5th_middlesex'],
'123': ['ocd-division/country:us/state:ma/sldl:6th_middlesex'],
'124': ['ocd-division/country:us/state:ma/sldl:7th_middlesex'],
'125': ['ocd-division/country:us/state:ma/sldl:8th_middlesex'],
'126': ['ocd-division/country:us/state:ma/sldl:9th_middlesex'],
'127': ['ocd-division/country:us/state:ma/sldl:10th_middlesex'],
'128': ['ocd-division/country:us/state:ma/sldl:11th_middlesex'],
'129': ['ocd-division/country:us/state:ma/sldl:12th_middlesex'],
'130': ['ocd-division/country:us/state:ma/sldl:13th_middlesex'],
'131': ['ocd-division/country:us/state:ma/sldl:14th_middlesex'],
'132': ['ocd-division/country:us/state:ma/sldl:15th_middlesex'],
'133': ['ocd-division/country:us/state:ma/sldl:16th_middlesex'],
'134': ['ocd-division/country:us/state:ma/sldl:17th_middlesex'],
'135': ['ocd-division/country:us/state:ma/sldl:18th_middlesex'],
'136': ['ocd-division/country:us/state:ma/sldl:19th_middlesex'],
'137': ['ocd-division/country:us/state:ma/sldl:20th_middlesex'],
'138': ['ocd-division/country:us/state:ma/sldl:21st_middlesex'],
'139': ['ocd-division/country:us/state:ma/sldl:22nd_middlesex'],
'140': ['ocd-division/country:us/state:ma/sldl:23rd_middlesex'],
'141': ['ocd-division/country:us/state:ma/sldl:24th_middlesex'],
'142': ['ocd-division/country:us/state:ma/sldl:25th_middlesex'],
'143': ['ocd-division/country:us/state:ma/sldl:26th_middlesex'],
'144': ['ocd-division/country:us/state:ma/sldl:27th_middlesex'],
'145': ['ocd-division/country:us/state:ma/sldl:28th_middlesex'],
'146': ['ocd-division/country:us/state:ma/sldl:29th_middlesex'],
'147': ['ocd-division/country:us/state:ma/sldl:30th_middlesex'],
'148': ['ocd-division/country:us/state:ma/sldl:31st_middlesex'],
'149': ['ocd-division/country:us/state:ma/sldl:32nd_middlesex'],
'150': ['ocd-division/country:us/state:ma/sldl:33rd_middlesex'],
'151': ['ocd-division/country:us/state:ma/sldl:34th_middlesex'],
'152': ['ocd-division/country:us/state:ma/sldl:35th_middlesex'],
'153': ['ocd-division/country:us/state:ma/sldl:36th_middlesex'],
'154': ['ocd-division/country:us/state:ma/sldl:37th_middlesex'],
'155': ['ocd-division/country:us/state:ma/sldl:18th_worcester'],
'156': ['ocd-division/country:us/state:ma/sldl:5th_barnstable'],
'157': ['ocd-division/country:us/state:ma/sldl:1st_norfolk'],
'158': ['ocd-division/country:us/state:ma/sldl:2nd_norfolk'],
'159': ['ocd-division/country:us/state:ma/sldl:3rd_norfolk'],
'160': ['ocd-division/country:us/state:ma/sldl:4th_norfolk'],
'161': ['ocd-division/country:us/state:ma/sldl:5th_norfolk'],
'162': ['ocd-division/country:us/state:ma/sldl:6th_norfolk'],
'163': ['ocd-division/country:us/state:ma/sldl:7th_norfolk'],
'164': ['ocd-division/country:us/state:ma/sldl:8th_norfolk'],
'165': ['ocd-division/country:us/state:ma/sldl:9th_norfolk'],
'166': ['ocd-division/country:us/state:ma/sldl:10th_norfolk'],
'167': ['ocd-division/country:us/state:ma/sldl:11th_norfolk'],
'168': ['ocd-division/country:us/state:ma/sldl:12th_norfolk'],
'169': ['ocd-division/country:us/state:ma/sldl:13th_norfolk'],
'170': ['ocd-division/country:us/state:ma/sldl:14th_norfolk'],
'171': ['ocd-division/country:us/state:ma/sldl:15th_norfolk'],
'172': ['ocd-division/country:us/state:ma/sldl:1st_plymouth'],
'173': ['ocd-division/country:us/state:ma/sldl:2nd_plymouth'],
'174': ['ocd-division/country:us/state:ma/sldl:3rd_plymouth'],
'175': ['ocd-division/country:us/state:ma/sldl:4th_plymouth'],
'176': ['ocd-division/country:us/state:ma/sldl:5th_plymouth'],
'177': ['ocd-division/country:us/state:ma/sldl:6th_plymouth'],
'178': ['ocd-division/country:us/state:ma/sldl:7th_plymouth'],
'179': ['ocd-division/country:us/state:ma/sldl:8th_plymouth'],
'180': ['ocd-division/country:us/state:ma/sldl:9th_plymouth'],
'181': ['ocd-division/country:us/state:ma/sldl:10th_plymouth'],
'182': ['ocd-division/country:us/state:ma/sldl:11th_plymouth'],
'183': ['ocd-division/country:us/state:ma/sldl:12th_plymouth'],
'184': ['ocd-division/country:us/state:ma/sldl:1st_suffolk'],
'185': ['ocd-division/country:us/state:ma/sldl:2nd_suffolk'],
'186': ['ocd-division/country:us/state:ma/sldl:3rd_suffolk'],
'187': ['ocd-division/country:us/state:ma/sldl:4th_suffolk'],
'188': ['ocd-division/country:us/state:ma/sldl:5th_suffolk'],
'189': ['ocd-division/country:us/state:ma/sldl:6th_suffolk'],
'190': ['ocd-division/country:us/state:ma/sldl:7th_suffolk'],
'191': ['ocd-division/country:us/state:ma/sldl:8th_suffolk'],
'192': ['ocd-division/country:us/state:ma/sldl:9th_suffolk'],
'193': ['ocd-division/country:us/state:ma/sldl:10th_suffolk'],
'194': ['ocd-division/country:us/state:ma/sldl:11th_suffolk'],
'195': ['ocd-division/country:us/state:ma/sldl:12th_suffolk'],
'196': ['ocd-division/country:us/state:ma/sldl:13th_suffolk'],
'197': ['ocd-division/country:us/state:ma/sldl:14th_suffolk'],
'198': ['ocd-division/country:us/state:ma/sldl:15th_suffolk'],
'199': ['ocd-division/country:us/state:ma/sldl:16th_suffolk'],
'200': ['ocd-division/country:us/state:ma/sldl:17th_suffolk'],
'201': ['ocd-division/country:us/state:ma/sldl:18th_suffolk'],
'202': ['ocd-division/country:us/state:ma/sldl:19th_suffolk'],
'203': ['ocd-division/country:us/state:ma/sldl:1st_worcester'],
'204': ['ocd-division/country:us/state:ma/sldl:2nd_worcester'],
'205': ['ocd-division/country:us/state:ma/sldl:3rd_worcester'],
'206': ['ocd-division/country:us/state:ma/sldl:4th_worcester'],
'207': ['ocd-division/country:us/state:ma/sldl:5th_worcester'],
'208': ['ocd-division/country:us/state:ma/sldl:6th_worcester'],
'209': ['ocd-division/country:us/state:ma/sldl:7th_worcester'],
'210': ['ocd-division/country:us/state:ma/sldl:8th_worcester'],
'211': ['ocd-division/country:us/state:ma/sldl:9th_worcester'],
'212': ['ocd-division/country:us/state:ma/sldl:10th_worcester'],
'213': ['ocd-division/country:us/state:ma/sldl:11th_worcester'],
'214': ['ocd-division/country:us/state:ma/sldl:12th_worcester'],
'215': ['ocd-division/country:us/state:ma/sldl:13th_worcester'],
'216': ['ocd-division/country:us/state:ma/sldl:14th_worcester'],
'217': ['ocd-division/country:us/state:ma/sldl:15th_worcester'],
'218': ['ocd-division/country:us/state:ma/sldl:16th_worcester'],
'219': ['ocd-division/country:us/state:ma/sldl:17th_worcester']
},
'MD': {
'1A': ['ocd-division/country:us/state:md/sldl:1a'],
'1B': ['ocd-division/country:us/state:md/sldl:1b'],
'2A': ['ocd-division/country:us/state:md/sldl:2a'],
'2B': ['ocd-division/country:us/state:md/sldl:2b'],
'3A': ['ocd-division/country:us/state:md/sldl:3a'],
'3B': ['ocd-division/country:us/state:md/sldl:3b'],
'9A': ['ocd-division/country:us/state:md/sldl:9a'],
'9B': ['ocd-division/country:us/state:md/sldl:9b'],
'23A': ['ocd-division/country:us/state:md/sldl:23a'],
'23B': ['ocd-division/country:us/state:md/sldl:23b'],
'27A': ['ocd-division/country:us/state:md/sldl:27a'],
'27B': ['ocd-division/country:us/state:md/sldl:27b'],
'27C': ['ocd-division/country:us/state:md/sldl:27c'],
'29A': ['ocd-division/country:us/state:md/sldl:29a'],
'29B': ['ocd-division/country:us/state:md/sldl:29b'],
'29C': ['ocd-division/country:us/state:md/sldl:29c'],
'30A': ['ocd-division/country:us/state:md/sldl:30a'],
'30B': ['ocd-division/country:us/state:md/sldl:30b'],
'31A': ['ocd-division/country:us/state:md/sldl:31a'],
'31B': ['ocd-division/country:us/state:md/sldl:31b'],
'34A': ['ocd-division/country:us/state:md/sldl:34a'],
'34B': ['ocd-division/country:us/state:md/sldl:34b'],
'35A': ['ocd-division/country:us/state:md/sldl:35a'],
'35B': ['ocd-division/country:us/state:md/sldl:35b'],
'37A': ['ocd-division/country:us/state:md/sldl:37a'],
'37B': ['ocd-division/country:us/state:md/sldl:37b'],
'38A': ['ocd-division/country:us/state:md/sldl:38a'],
'38B': ['ocd-division/country:us/state:md/sldl:38b'],
'38C': ['ocd-division/country:us/state:md/sldl:38c'],
'42A': ['ocd-division/country:us/state:md/sldl:42a'],
'42B': ['ocd-division/country:us/state:md/sldl:42b'],
'44A': ['ocd-division/country:us/state:md/sldl:44a'],
'44B': ['ocd-division/country:us/state:md/sldl:44b'],
'47A': ['ocd-division/country:us/state:md/sldl:47a'],
'47B': ['ocd-division/country:us/state:md/sldl:47b']
},
'MN': {
'1A': ['ocd-division/country:us/state:mn/sldl:1a'],
'1B': ['ocd-division/country:us/state:mn/sldl:1b'],
'2A': ['ocd-division/country:us/state:mn/sldl:2a'],
'2B': ['ocd-division/country:us/state:mn/sldl:2b'],
'3A': ['ocd-division/country:us/state:mn/sldl:3a'],
'3B': ['ocd-division/country:us/state:mn/sldl:3b'],
'4A': ['ocd-division/country:us/state:mn/sldl:4a'],
'4B': ['ocd-division/country:us/state:mn/sldl:4b'],
'5A': ['ocd-division/country:us/state:mn/sldl:5a'],
'5B': ['ocd-division/country:us/state:mn/sldl:5b'],
'6A': ['ocd-division/country:us/state:mn/sldl:6a'],
'6B': ['ocd-division/country:us/state:mn/sldl:6b'],
'7A': ['ocd-division/country:us/state:mn/sldl:7a'],
'7B': ['ocd-division/country:us/state:mn/sldl:7b'],
'8A': ['ocd-division/country:us/state:mn/sldl:8a'],
'8B': ['ocd-division/country:us/state:mn/sldl:8b'],
'9A': ['ocd-division/country:us/state:mn/sldl:9a'],
'9B': ['ocd-division/country:us/state:mn/sldl:9b'],
'10A': ['ocd-division/country:us/state:mn/sldl:10a'],
'10B': ['ocd-division/country:us/state:mn/sldl:10b'],
'11A': ['ocd-division/country:us/state:mn/sldl:11a'],
'11B': ['ocd-division/country:us/state:mn/sldl:11b'],
'12A': ['ocd-division/country:us/state:mn/sldl:12a'],
'12B': ['ocd-division/country:us/state:mn/sldl:12b'],
'13A': ['ocd-division/country:us/state:mn/sldl:13a'],
'13B': ['ocd-division/country:us/state:mn/sldl:13b'],
'14A': ['ocd-division/country:us/state:mn/sldl:14a'],
'14B': ['ocd-division/country:us/state:mn/sldl:14b'],
'15A': ['ocd-division/country:us/state:mn/sldl:15a'],
'15B': ['ocd-division/country:us/state:mn/sldl:15b'],
'16A': ['ocd-division/country:us/state:mn/sldl:16a'],
'16B': ['ocd-division/country:us/state:mn/sldl:16b'],
'17A': ['ocd-division/country:us/state:mn/sldl:17a'],
'17B': ['ocd-division/country:us/state:mn/sldl:17b'],
'18A': ['ocd-division/country:us/state:mn/sldl:18a'],
'18B': ['ocd-division/country:us/state:mn/sldl:18b'],
'19A': ['ocd-division/country:us/state:mn/sldl:19a'],
'19B': ['ocd-division/country:us/state:mn/sldl:19b'],
'20A': ['ocd-division/country:us/state:mn/sldl:20a'],
'20B': ['ocd-division/country:us/state:mn/sldl:20b'],
'21A': ['ocd-division/country:us/state:mn/sldl:21a'],
'21B': ['ocd-division/country:us/state:mn/sldl:21b'],
'22A': ['ocd-division/country:us/state:mn/sldl:22a'],
'22B': ['ocd-division/country:us/state:mn/sldl:22b'],
'23A': ['ocd-division/country:us/state:mn/sldl:23a'],
'23B': ['ocd-division/country:us/state:mn/sldl:23b'],
'24A': ['ocd-division/country:us/state:mn/sldl:24a'],
'24B': ['ocd-division/country:us/state:mn/sldl:24b'],
'25A': ['ocd-division/country:us/state:mn/sldl:25a'],
'25B': ['ocd-division/country:us/state:mn/sldl:25b'],
'26A': ['ocd-division/country:us/state:mn/sldl:26a'],
'26B': ['ocd-division/country:us/state:mn/sldl:26b'],
'27A': ['ocd-division/country:us/state:mn/sldl:27a'],
'27B': ['ocd-division/country:us/state:mn/sldl:27b'],
'28A': ['ocd-division/country:us/state:mn/sldl:28a'],
'28B': ['ocd-division/country:us/state:mn/sldl:28b'],
'29A': ['ocd-division/country:us/state:mn/sldl:29a'],
'29B': ['ocd-division/country:us/state:mn/sldl:29b'],
'30A': ['ocd-division/country:us/state:mn/sldl:30a'],
'30B': ['ocd-division/country:us/state:mn/sldl:30b'],
'31A': ['ocd-division/country:us/state:mn/sldl:31a'],
'31B': ['ocd-division/country:us/state:mn/sldl:31b'],
'32A': ['ocd-division/country:us/state:mn/sldl:32a'],
'32B': ['ocd-division/country:us/state:mn/sldl:32b'],
'33A': ['ocd-division/country:us/state:mn/sldl:33a'],
'33B': ['ocd-division/country:us/state:mn/sldl:33b'],
'34A': ['ocd-division/country:us/state:mn/sldl:34a'],
'34B': ['ocd-division/country:us/state:mn/sldl:34b'],
'35A': ['ocd-division/country:us/state:mn/sldl:35a'],
'35B': ['ocd-division/country:us/state:mn/sldl:35b'],
'36A': ['ocd-division/country:us/state:mn/sldl:36a'],
'36B': ['ocd-division/country:us/state:mn/sldl:36b'],
'37A': ['ocd-division/country:us/state:mn/sldl:37a'],
'37B': ['ocd-division/country:us/state:mn/sldl:37b'],
'38A': ['ocd-division/country:us/state:mn/sldl:38a'],
'38B': ['ocd-division/country:us/state:mn/sldl:38b'],
'39A': ['ocd-division/country:us/state:mn/sldl:39a'],
'39B': ['ocd-division/country:us/state:mn/sldl:39b'],
'40A': ['ocd-division/country:us/state:mn/sldl:40a'],
'40B': ['ocd-division/country:us/state:mn/sldl:40b'],
'41A': ['ocd-division/country:us/state:mn/sldl:41a'],
'41B': ['ocd-division/country:us/state:mn/sldl:41b'],
'42A': ['ocd-division/country:us/state:mn/sldl:42a'],
'42B': ['ocd-division/country:us/state:mn/sldl:42b'],
'43A': ['ocd-division/country:us/state:mn/sldl:43a'],
'43B': ['ocd-division/country:us/state:mn/sldl:43b'],
'44A': ['ocd-division/country:us/state:mn/sldl:44a'],
'44B': ['ocd-division/country:us/state:mn/sldl:44b'],
'45A': ['ocd-division/country:us/state:mn/sldl:45a'],
'45B': ['ocd-division/country:us/state:mn/sldl:45b'],
'46A': ['ocd-division/country:us/state:mn/sldl:46a'],
'46B': ['ocd-division/country:us/state:mn/sldl:46b'],
'47A': ['ocd-division/country:us/state:mn/sldl:47a'],
'47B': ['ocd-division/country:us/state:mn/sldl:47b'],
'48A': ['ocd-division/country:us/state:mn/sldl:48a'],
'48B': ['ocd-division/country:us/state:mn/sldl:48b'],
'49A': ['ocd-division/country:us/state:mn/sldl:49a'],
'49B': ['ocd-division/country:us/state:mn/sldl:49b'],
'50A': ['ocd-division/country:us/state:mn/sldl:50a'],
'50B': ['ocd-division/country:us/state:mn/sldl:50b'],
'51A': ['ocd-division/country:us/state:mn/sldl:51a'],
'51B': ['ocd-division/country:us/state:mn/sldl:51b'],
'52A': ['ocd-division/country:us/state:mn/sldl:52a'],
'52B': ['ocd-division/country:us/state:mn/sldl:52b'],
'53A': ['ocd-division/country:us/state:mn/sldl:53a'],
'53B': ['ocd-division/country:us/state:mn/sldl:53b'],
'54A': ['ocd-division/country:us/state:mn/sldl:54a'],
'54B': ['ocd-division/country:us/state:mn/sldl:54b'],
'55A': ['ocd-division/country:us/state:mn/sldl:55a'],
'55B': ['ocd-division/country:us/state:mn/sldl:55b'],
'56A': ['ocd-division/country:us/state:mn/sldl:56a'],
'56B': ['ocd-division/country:us/state:mn/sldl:56b'],
'57A': ['ocd-division/country:us/state:mn/sldl:57a'],
'57B': ['ocd-division/country:us/state:mn/sldl:57b'],
'58A': ['ocd-division/country:us/state:mn/sldl:58a'],
'58B': ['ocd-division/country:us/state:mn/sldl:58b'],
'59A': ['ocd-division/country:us/state:mn/sldl:59a'],
'59B': ['ocd-division/country:us/state:mn/sldl:59b'],
'60A': ['ocd-division/country:us/state:mn/sldl:60a'],
'60B': ['ocd-division/country:us/state:mn/sldl:60b'],
'61A': ['ocd-division/country:us/state:mn/sldl:61a'],
'61B': ['ocd-division/country:us/state:mn/sldl:61b'],
'62A': ['ocd-division/country:us/state:mn/sldl:62a'],
'62B': ['ocd-division/country:us/state:mn/sldl:62b'],
'63A': ['ocd-division/country:us/state:mn/sldl:63a'],
'63B': ['ocd-division/country:us/state:mn/sldl:63b'],
'64A': ['ocd-division/country:us/state:mn/sldl:64a'],
'64B': ['ocd-division/country:us/state:mn/sldl:64b'],
'65A': ['ocd-division/country:us/state:mn/sldl:65a'],
'65B': ['ocd-division/country:us/state:mn/sldl:65b'],
'66A': ['ocd-division/country:us/state:mn/sldl:66a'],
'66B': ['ocd-division/country:us/state:mn/sldl:66b'],
'67A': ['ocd-division/country:us/state:mn/sldl:67a'],
'67B': ['ocd-division/country:us/state:mn/sldl:67b']
},
'NH': {
'1': ['ocd-division/country:us/state:nh/sldl:belknap_1'],
'2': ['ocd-division/country:us/state:nh/sldl:belknap_2'],
'3': ['ocd-division/country:us/state:nh/sldl:belknap_3',
'ocd-division/country:us/state:nh/sldl:belknap_9'],
'4': ['ocd-division/country:us/state:nh/sldl:belknap_4'],
'5': ['ocd-division/country:us/state:nh/sldl:belknap_5',
'ocd-division/country:us/state:nh/sldl:belknap_8'],
'6': ['ocd-division/country:us/state:nh/sldl:belknap_6',
'ocd-division/country:us/state:nh/sldl:belknap_9'],
'7': ['ocd-division/country:us/state:nh/sldl:belknap_7',
'ocd-division/country:us/state:nh/sldl:belknap_8'],
'101': ['ocd-division/country:us/state:nh/sldl:carroll_1',
'ocd-division/country:us/state:nh/sldl:carroll_7'],
'102': ['ocd-division/country:us/state:nh/sldl:carroll_2',
'ocd-division/country:us/state:nh/sldl:carroll_7'],
'103': ['ocd-division/country:us/state:nh/sldl:carroll_3',
'ocd-division/country:us/state:nh/sldl:carroll_7'],
'104': ['ocd-division/country:us/state:nh/sldl:carroll_4',
'ocd-division/country:us/state:nh/sldl:carroll_8'],
'105': ['ocd-division/country:us/state:nh/sldl:carroll_5',
'ocd-division/country:us/state:nh/sldl:carroll_8'],
'106': ['ocd-division/country:us/state:nh/sldl:carroll_6'],
'201': ['ocd-division/country:us/state:nh/sldl:cheshire_1'],
'202': ['ocd-division/country:us/state:nh/sldl:cheshire_2'],
'203': ['ocd-division/country:us/state:nh/sldl:cheshire_3'],
'204': ['ocd-division/country:us/state:nh/sldl:cheshire_4',
'ocd-division/country:us/state:nh/sldl:cheshire_16'],
'205': ['ocd-division/country:us/state:nh/sldl:cheshire_5',
'ocd-division/country:us/state:nh/sldl:cheshire_16'],
'206': ['ocd-division/country:us/state:nh/sldl:cheshire_6',
'ocd-division/country:us/state:nh/sldl:cheshire_16'],
'207': ['ocd-division/country:us/state:nh/sldl:cheshire_7',
'ocd-division/country:us/state:nh/sldl:cheshire_16'],
'208': ['ocd-division/country:us/state:nh/sldl:cheshire_8',
'ocd-division/country:us/state:nh/sldl:cheshire_16'],
'209': ['ocd-division/country:us/state:nh/sldl:cheshire_9',
'ocd-division/country:us/state:nh/sldl:cheshire_14'],
'210': ['ocd-division/country:us/state:nh/sldl:cheshire_10',
'ocd-division/country:us/state:nh/sldl:cheshire_15'],
'211': ['ocd-division/country:us/state:nh/sldl:cheshire_11',
'ocd-division/country:us/state:nh/sldl:cheshire_14'],
'212': ['ocd-division/country:us/state:nh/sldl:cheshire_12',
'ocd-division/country:us/state:nh/sldl:cheshire_15'],
'213': ['ocd-division/country:us/state:nh/sldl:cheshire_13',
'ocd-division/country:us/state:nh/sldl:cheshire_15'],
'301': ['ocd-division/country:us/state:nh/sldl:coos_1'],
'302': ['ocd-division/country:us/state:nh/sldl:coos_2',
'ocd-division/country:us/state:nh/sldl:coos_7'],
'303': ['ocd-division/country:us/state:nh/sldl:coos_3'],
'304': ['ocd-division/country:us/state:nh/sldl:coos_4',
'ocd-division/country:us/state:nh/sldl:coos_7'],
'305': ['ocd-division/country:us/state:nh/sldl:coos_5',
'ocd-division/country:us/state:nh/sldl:coos_7'],
'306': ['ocd-division/country:us/state:nh/sldl:coos_6'],
'401': ['ocd-division/country:us/state:nh/sldl:grafton_1',
'ocd-division/country:us/state:nh/sldl:grafton_14'],
'402': ['ocd-division/country:us/state:nh/sldl:grafton_2',
'ocd-division/country:us/state:nh/sldl:grafton_14'],
'403': ['ocd-division/country:us/state:nh/sldl:grafton_3',
'ocd-division/country:us/state:nh/sldl:grafton_15'],
'404': ['ocd-division/country:us/state:nh/sldl:grafton_4',
'ocd-division/country:us/state:nh/sldl:grafton_15'],
'405': ['ocd-division/country:us/state:nh/sldl:grafton_5'],
'406': ['ocd-division/country:us/state:nh/sldl:grafton_6',
'ocd-division/country:us/state:nh/sldl:grafton_16'],
'407': ['ocd-division/country:us/state:nh/sldl:grafton_7'],
'408': ['ocd-division/country:us/state:nh/sldl:grafton_8'],
'409': ['ocd-division/country:us/state:nh/sldl:grafton_9',
'ocd-division/country:us/state:nh/sldl:grafton_17'],
'410': ['ocd-division/country:us/state:nh/sldl:grafton_10',
'ocd-division/country:us/state:nh/sldl:grafton_17'],
'411': ['ocd-division/country:us/state:nh/sldl:grafton_11',
'ocd-division/country:us/state:nh/sldl:grafton_16'],
'412': ['ocd-division/country:us/state:nh/sldl:grafton_12'],
'413': ['ocd-division/country:us/state:nh/sldl:grafton_13'],
'501': ['ocd-division/country:us/state:nh/sldl:hillsborough_1',
'ocd-division/country:us/state:nh/sldl:hillsborough_38'],
'502': ['ocd-division/country:us/state:nh/sldl:hillsborough_2',
'ocd-division/country:us/state:nh/sldl:hillsborough_39'],
'503': ['ocd-division/country:us/state:nh/sldl:hillsborough_3',
'ocd-division/country:us/state:nh/sldl:hillsborough_38'],
'504': ['ocd-division/country:us/state:nh/sldl:hillsborough_4',
'ocd-division/country:us/state:nh/sldl:hillsborough_38'],
'505': ['ocd-division/country:us/state:nh/sldl:hillsborough_5',
'ocd-division/country:us/state:nh/sldl:hillsborough_40'],
'506': ['ocd-division/country:us/state:nh/sldl:hillsborough_6',
'ocd-division/country:us/state:nh/sldl:hillsborough_39'],
'507': ['ocd-division/country:us/state:nh/sldl:hillsborough_7',
'ocd-division/country:us/state:nh/sldl:hillsborough_41'],
'508': ['ocd-division/country:us/state:nh/sldl:hillsborough_8',
'ocd-division/country:us/state:nh/sldl:hillsborough_42'],
'509': ['ocd-division/country:us/state:nh/sldl:hillsborough_9',
'ocd-division/country:us/state:nh/sldl:hillsborough_42'],
'510': ['ocd-division/country:us/state:nh/sldl:hillsborough_10',
'ocd-division/country:us/state:nh/sldl:hillsborough_42'],
'511': ['ocd-division/country:us/state:nh/sldl:hillsborough_11',
'ocd-division/country:us/state:nh/sldl:hillsborough_43'],
'512': ['ocd-division/country:us/state:nh/sldl:hillsborough_12',
'ocd-division/country:us/state:nh/sldl:hillsborough_43'],
'513': ['ocd-division/country:us/state:nh/sldl:hillsborough_13',
'ocd-division/country:us/state:nh/sldl:hillsborough_43'],
'514': ['ocd-division/country:us/state:nh/sldl:hillsborough_14',
'ocd-division/country:us/state:nh/sldl:hillsborough_43'],
'515': ['ocd-division/country:us/state:nh/sldl:hillsborough_15',
'ocd-division/country:us/state:nh/sldl:hillsborough_44'],
'516': ['ocd-division/country:us/state:nh/sldl:hillsborough_16',
'ocd-division/country:us/state:nh/sldl:hillsborough_44'],
'517': ['ocd-division/country:us/state:nh/sldl:hillsborough_17',
'ocd-division/country:us/state:nh/sldl:hillsborough_45'],
'518': ['ocd-division/country:us/state:nh/sldl:hillsborough_18',
'ocd-division/country:us/state:nh/sldl:hillsborough_45'],
'519': ['ocd-division/country:us/state:nh/sldl:hillsborough_19',
'ocd-division/country:us/state:nh/sldl:hillsborough_45'],
'520': ['ocd-division/country:us/state:nh/sldl:hillsborough_20',
'ocd-division/country:us/state:nh/sldl:hillsborough_44'],
'521': ['ocd-division/country:us/state:nh/sldl:hillsborough_21'],
'522': ['ocd-division/country:us/state:nh/sldl:hillsborough_22',
'ocd-division/country:us/state:nh/sldl:hillsborough_41'],
'523': ['ocd-division/country:us/state:nh/sldl:hillsborough_23',
'ocd-division/country:us/state:nh/sldl:hillsborough_40'],
'524': ['ocd-division/country:us/state:nh/sldl:hillsborough_24'],
'525': ['ocd-division/country:us/state:nh/sldl:hillsborough_25'],
'526': ['ocd-division/country:us/state:nh/sldl:hillsborough_26'],
'527': ['ocd-division/country:us/state:nh/sldl:hillsborough_27',
'ocd-division/country:us/state:nh/sldl:hillsborough_40'],
'528': ['ocd-division/country:us/state:nh/sldl:hillsborough_28'],
'529': ['ocd-division/country:us/state:nh/sldl:hillsborough_29'],
'530': ['ocd-division/country:us/state:nh/sldl:hillsborough_30'],
'531': ['ocd-division/country:us/state:nh/sldl:hillsborough_31'],
'532': ['ocd-division/country:us/state:nh/sldl:hillsborough_32'],
'533': ['ocd-division/country:us/state:nh/sldl:hillsborough_33'],
'534': ['ocd-division/country:us/state:nh/sldl:hillsborough_34'],
'535': ['ocd-division/country:us/state:nh/sldl:hillsborough_35'],
'536': ['ocd-division/country:us/state:nh/sldl:hillsborough_36'],
'537': ['ocd-division/country:us/state:nh/sldl:hillsborough_37'],
'601': ['ocd-division/country:us/state:nh/sldl:merrimack_1',
'ocd-division/country:us/state:nh/sldl:merrimack_25'],
'602': ['ocd-division/country:us/state:nh/sldl:merrimack_2'],
'603': ['ocd-division/country:us/state:nh/sldl:merrimack_3',
'ocd-division/country:us/state:nh/sldl:merrimack_26'],
'604': ['ocd-division/country:us/state:nh/sldl:merrimack_4'],
'605': ['ocd-division/country:us/state:nh/sldl:merrimack_5'],
'606': ['ocd-division/country:us/state:nh/sldl:merrimack_6'],
'607': ['ocd-division/country:us/state:nh/sldl:merrimack_7',
'ocd-division/country:us/state:nh/sldl:merrimack_25'],
'608': ['ocd-division/country:us/state:nh/sldl:merrimack_8',
'ocd-division/country:us/state:nh/sldl:merrimack_26'],
'609': ['ocd-division/country:us/state:nh/sldl:merrimack_9',
'ocd-division/country:us/state:nh/sldl:merrimack_26'],
'610': ['ocd-division/country:us/state:nh/sldl:merrimack_10'],
'611': ['ocd-division/country:us/state:nh/sldl:merrimack_11',
'ocd-division/country:us/state:nh/sldl:merrimack_27'],
'612': ['ocd-division/country:us/state:nh/sldl:merrimack_12',
'ocd-division/country:us/state:nh/sldl:merrimack_27'],
'613': ['ocd-division/country:us/state:nh/sldl:merrimack_13',
'ocd-division/country:us/state:nh/sldl:merrimack_27'],
'614': ['ocd-division/country:us/state:nh/sldl:merrimack_14',
'ocd-division/country:us/state:nh/sldl:merrimack_27'],
'615': ['ocd-division/country:us/state:nh/sldl:merrimack_15',
'ocd-division/country:us/state:nh/sldl:merrimack_27'],
'616': ['ocd-division/country:us/state:nh/sldl:merrimack_16',
'ocd-division/country:us/state:nh/sldl:merrimack_27'],
'617': ['ocd-division/country:us/state:nh/sldl:merrimack_17',
'ocd-division/country:us/state:nh/sldl:merrimack_28'],
'618': ['ocd-division/country:us/state:nh/sldl:merrimack_18',
'ocd-division/country:us/state:nh/sldl:merrimack_28'],
'619': ['ocd-division/country:us/state:nh/sldl:merrimack_19',
'ocd-division/country:us/state:nh/sldl:merrimack_28'],
'620': ['ocd-division/country:us/state:nh/sldl:merrimack_20'],
'621': ['ocd-division/country:us/state:nh/sldl:merrimack_21',
'ocd-division/country:us/state:nh/sldl:merrimack_29'],
'622': ['ocd-division/country:us/state:nh/sldl:merrimack_22',
'ocd-division/country:us/state:nh/sldl:merrimack_29'],
'623': ['ocd-division/country:us/state:nh/sldl:merrimack_23'],
'624': ['ocd-division/country:us/state:nh/sldl:merrimack_24'],
'701': ['ocd-division/country:us/state:nh/sldl:rockingham_1',
'ocd-division/country:us/state:nh/sldl:rockingham_32'],
'702': ['ocd-division/country:us/state:nh/sldl:rockingham_2',
'ocd-division/country:us/state:nh/sldl:rockingham_32'],
'703': ['ocd-division/country:us/state:nh/sldl:rockingham_3'],
'704': ['ocd-division/country:us/state:nh/sldl:rockingham_4'],
'705': ['ocd-division/country:us/state:nh/sldl:rockingham_5'],
'706': ['ocd-division/country:us/state:nh/sldl:rockingham_6'],
'707': ['ocd-division/country:us/state:nh/sldl:rockingham_7'],
'708': ['ocd-division/country:us/state:nh/sldl:rockingham_8'],
'709': ['ocd-division/country:us/state:nh/sldl:rockingham_9'],
'710': ['ocd-division/country:us/state:nh/sldl:rockingham_10',
'ocd-division/country:us/state:nh/sldl:rockingham_33'],
'711': ['ocd-division/country:us/state:nh/sldl:rockingham_11',
'ocd-division/country:us/state:nh/sldl:rockingham_33'],
'712': ['ocd-division/country:us/state:nh/sldl:rockingham_12',
'ocd-division/country:us/state:nh/sldl:rockingham_33'],
'713': ['ocd-division/country:us/state:nh/sldl:rockingham_13',
'ocd-division/country:us/state:nh/sldl:rockingham_34'],
'714': ['ocd-division/country:us/state:nh/sldl:rockingham_14',
'ocd-division/country:us/state:nh/sldl:rockingham_34'],
'715': ['ocd-division/country:us/state:nh/sldl:rockingham_15',
'ocd-division/country:us/state:nh/sldl:rockingham_35'],
'716': ['ocd-division/country:us/state:nh/sldl:rockingham_16',
'ocd-division/country:us/state:nh/sldl:rockingham_35'],
'717': ['ocd-division/country:us/state:nh/sldl:rockingham_17',
'ocd-division/country:us/state:nh/sldl:rockingham_36'],
'718': ['ocd-division/country:us/state:nh/sldl:rockingham_18',
'ocd-division/country:us/state:nh/sldl:rockingham_36'],
'719': ['ocd-division/country:us/state:nh/sldl:rockingham_19',
'ocd-division/country:us/state:nh/sldl:rockingham_36'],
'720': ['ocd-division/country:us/state:nh/sldl:rockingham_20',
'ocd-division/country:us/state:nh/sldl:rockingham_37'],
'721': ['ocd-division/country:us/state:nh/sldl:rockingham_21',
'ocd-division/country:us/state:nh/sldl:rockingham_37'],
'722': ['ocd-division/country:us/state:nh/sldl:rockingham_22',
'ocd-division/country:us/state:nh/sldl:rockingham_31'],
'723': ['ocd-division/country:us/state:nh/sldl:rockingham_23',
'ocd-division/country:us/state:nh/sldl:rockingham_31'],
'724': ['ocd-division/country:us/state:nh/sldl:rockingham_24'],
'725': ['ocd-division/country:us/state:nh/sldl:rockingham_25',
'ocd-division/country:us/state:nh/sldl:rockingham_30'],
'726': ['ocd-division/country:us/state:nh/sldl:rockingham_26',
'ocd-division/country:us/state:nh/sldl:rockingham_30'],
'727': ['ocd-division/country:us/state:nh/sldl:rockingham_27',
'ocd-division/country:us/state:nh/sldl:rockingham_31'],
'728': ['ocd-division/country:us/state:nh/sldl:rockingham_28',
'ocd-division/country:us/state:nh/sldl:rockingham_30'],
'729': ['ocd-division/country:us/state:nh/sldl:rockingham_29',
'ocd-division/country:us/state:nh/sldl:rockingham_30'],
'801': ['ocd-division/country:us/state:nh/sldl:strafford_1'],
'802': ['ocd-division/country:us/state:nh/sldl:strafford_2'],
'803': ['ocd-division/country:us/state:nh/sldl:strafford_3'],
'804': ['ocd-division/country:us/state:nh/sldl:strafford_4',
'ocd-division/country:us/state:nh/sldl:strafford_25'],
'805': ['ocd-division/country:us/state:nh/sldl:strafford_5',
'ocd-division/country:us/state:nh/sldl:strafford_25'],
'806': ['ocd-division/country:us/state:nh/sldl:strafford_6'],
'807': ['ocd-division/country:us/state:nh/sldl:strafford_7',
'ocd-division/country:us/state:nh/sldl:strafford_22'],
'808': ['ocd-division/country:us/state:nh/sldl:strafford_8',
'ocd-division/country:us/state:nh/sldl:strafford_22'],
'809': ['ocd-division/country:us/state:nh/sldl:strafford_9',
'ocd-division/country:us/state:nh/sldl:strafford_23'],
'810': ['ocd-division/country:us/state:nh/sldl:strafford_10',
'ocd-division/country:us/state:nh/sldl:strafford_23'],
'811': ['ocd-division/country:us/state:nh/sldl:strafford_11',
'ocd-division/country:us/state:nh/sldl:strafford_24'],
'812': ['ocd-division/country:us/state:nh/sldl:strafford_12',
'ocd-division/country:us/state:nh/sldl:strafford_24'],
'813': ['ocd-division/country:us/state:nh/sldl:strafford_13',
'ocd-division/country:us/state:nh/sldl:strafford_19'],
'814': ['ocd-division/country:us/state:nh/sldl:strafford_14',
'ocd-division/country:us/state:nh/sldl:strafford_19'],
'815': ['ocd-division/country:us/state:nh/sldl:strafford_15',
'ocd-division/country:us/state:nh/sldl:strafford_20'],
'816': ['ocd-division/country:us/state:nh/sldl:strafford_16',
'ocd-division/country:us/state:nh/sldl:strafford_20'],
'817': ['ocd-division/country:us/state:nh/sldl:strafford_17',
'ocd-division/country:us/state:nh/sldl:strafford_21'],
'818': ['ocd-division/country:us/state:nh/sldl:strafford_18',
'ocd-division/country:us/state:nh/sldl:strafford_21'],
'901': ['ocd-division/country:us/state:nh/sldl:sullivan_1',
'ocd-division/country:us/state:nh/sldl:sullivan_9'],
'902': ['ocd-division/country:us/state:nh/sldl:sullivan_2',
'ocd-division/country:us/state:nh/sldl:sullivan_9'],
'903': ['ocd-division/country:us/state:nh/sldl:sullivan_3',
'ocd-division/country:us/state:nh/sldl:sullivan_10'],
'904': ['ocd-division/country:us/state:nh/sldl:sullivan_4',
'ocd-division/country:us/state:nh/sldl:sullivan_10'],
'905': ['ocd-division/country:us/state:nh/sldl:sullivan_5',
'ocd-division/country:us/state:nh/sldl:sullivan_10'],
'906': ['ocd-division/country:us/state:nh/sldl:sullivan_6',
'ocd-division/country:us/state:nh/sldl:sullivan_9'],
'907': ['ocd-division/country:us/state:nh/sldl:sullivan_7',
'ocd-division/country:us/state:nh/sldl:sullivan_11'],
'908': ['ocd-division/country:us/state:nh/sldl:sullivan_8',
'ocd-division/country:us/state:nh/sldl:sullivan_11']
},
'SD': {
'26A': ['ocd-division/country:us/state:sd/sldl:26a'],
'26B': ['ocd-division/country:us/state:sd/sldl:26b'],
'28A': ['ocd-division/country:us/state:sd/sldl:28a'],
'28B': ['ocd-division/country:us/state:sd/sldl:28b']
},
'VT': {
'A-1': ['ocd-division/country:us/state:vt/sldl:addison-1'],
'A-2': ['ocd-division/country:us/state:vt/sldl:addison-2'],
'A-3': ['ocd-division/country:us/state:vt/sldl:addison-3'],
'A-4': ['ocd-division/country:us/state:vt/sldl:addison-4'],
'A-5': ['ocd-division/country:us/state:vt/sldl:addison-5'],
'A-R': ['ocd-division/country:us/state:vt/sldl:addison-rutland'],
'B-1': ['ocd-division/country:us/state:vt/sldl:bennington-1'],
'B-3': ['ocd-division/country:us/state:vt/sldl:bennington-3'],
'B-4': ['ocd-division/country:us/state:vt/sldl:bennington-4'],
'B-R': ['ocd-division/country:us/state:vt/sldl:bennington-rutland'],
'B21': ['ocd-division/country:us/state:vt/sldl:bennington-2-1'],
'B22': ['ocd-division/country:us/state:vt/sldl:bennington-2-2'],
'C-1': ['ocd-division/country:us/state:vt/sldl:chittenden-1'],
'C-2': ['ocd-division/country:us/state:vt/sldl:chittenden-2'],
'C-3': ['ocd-division/country:us/state:vt/sldl:chittenden-3'],
'C10': ['ocd-division/country:us/state:vt/sldl:chittenden-10'],
'C41': ['ocd-division/country:us/state:vt/sldl:chittenden-4-1'],
'C42': ['ocd-division/country:us/state:vt/sldl:chittenden-4-2'],
'C51': ['ocd-division/country:us/state:vt/sldl:chittenden-5-1'],
'C52': ['ocd-division/country:us/state:vt/sldl:chittenden-5-2'],
'C61': ['ocd-division/country:us/state:vt/sldl:chittenden-6-1'],
'C62': ['ocd-division/country:us/state:vt/sldl:chittenden-6-2'],
'C63': ['ocd-division/country:us/state:vt/sldl:chittenden-6-3'],
'C64': ['ocd-division/country:us/state:vt/sldl:chittenden-6-4'],
'C65': ['ocd-division/country:us/state:vt/sldl:chittenden-6-5'],
'C66': ['ocd-division/country:us/state:vt/sldl:chittenden-6-6'],
'C67': ['ocd-division/country:us/state:vt/sldl:chittenden-6-7'],
'C71': ['ocd-division/country:us/state:vt/sldl:chittenden-7-1'],
'C72': ['ocd-division/country:us/state:vt/sldl:chittenden-7-2'],
'C73': ['ocd-division/country:us/state:vt/sldl:chittenden-7-3'],
'C74': ['ocd-division/country:us/state:vt/sldl:chittenden-7-4'],
'C81': ['ocd-division/country:us/state:vt/sldl:chittenden-8-1'],
'C82': ['ocd-division/country:us/state:vt/sldl:chittenden-8-2'],
'C83': ['ocd-division/country:us/state:vt/sldl:chittenden-8-3'],
'C91': ['ocd-division/country:us/state:vt/sldl:chittenden-9-1'],
'C92': ['ocd-division/country:us/state:vt/sldl:chittenden-9-2'],
'CA1': ['ocd-division/country:us/state:vt/sldl:caledonia-1'],
'CA2': ['ocd-division/country:us/state:vt/sldl:caledonia-2'],
'CA3': ['ocd-division/country:us/state:vt/sldl:caledonia-3'],
'CA4': ['ocd-division/country:us/state:vt/sldl:caledonia-4'],
'CAW': ['ocd-division/country:us/state:vt/sldl:caledonia-washington'],
'E-C': ['ocd-division/country:us/state:vt/sldl:essex-caledonia'],
'ECO': ['ocd-division/country:us/state:vt/sldl:essex-caledonia-orleans'],
'F-1': ['ocd-division/country:us/state:vt/sldl:franklin-1'],
'F-2': ['ocd-division/country:us/state:vt/sldl:franklin-2'],
'F-4': ['ocd-division/country:us/state:vt/sldl:franklin-4'],
'F-5': ['ocd-division/country:us/state:vt/sldl:franklin-5'],
'F-6': ['ocd-division/country:us/state:vt/sldl:franklin-6'],
'F-7': ['ocd-division/country:us/state:vt/sldl:franklin-7'],
'F31': ['ocd-division/country:us/state:vt/sldl:franklin-3-1'],
'F32': ['ocd-division/country:us/state:vt/sldl:franklin-3-2'],
'GIC': ['ocd-division/country:us/state:vt/sldl:grand_isle-chittenden'],
'LM1': ['ocd-division/country:us/state:vt/sldl:lamoille-1'],
'LM2': ['ocd-division/country:us/state:vt/sldl:lamoille-2'],
'LM3': ['ocd-division/country:us/state:vt/sldl:lamoille-3'],
'LMW': ['ocd-division/country:us/state:vt/sldl:lamoille-washington'],
'O-1': ['ocd-division/country:us/state:vt/sldl:orleans-1'],
'O-2': ['ocd-division/country:us/state:vt/sldl:orleans-2'],
'O-C': ['ocd-division/country:us/state:vt/sldl:orange-caledonia'],
'O-L': ['ocd-division/country:us/state:vt/sldl:orleans-lamoille'],
'OLC': ['ocd-division/country:us/state:vt/sldl:orleans-caledonia'],
'OR1': ['ocd-division/country:us/state:vt/sldl:orange-1'],
'OR2': ['ocd-division/country:us/state:vt/sldl:orange-2'],
'OWA': ['ocd-division/country:us/state:vt/sldl:orange-washington-addison'],
'R-1': ['ocd-division/country:us/state:vt/sldl:rutland-1'],
'R-2': ['ocd-division/country:us/state:vt/sldl:rutland-2'],
'R-3': ['ocd-division/country:us/state:vt/sldl:rutland-3'],
'R-4': ['ocd-division/country:us/state:vt/sldl:rutland-4'],
'R-6': ['ocd-division/country:us/state:vt/sldl:rutland-6'],
'R-B': ['ocd-division/country:us/state:vt/sldl:rutland-bennington'],
'R-W': ['ocd-division/country:us/state:vt/sldl:rutland-windsor-1'],
'R51': ['ocd-division/country:us/state:vt/sldl:rutland-5-1'],
'R52': ['ocd-division/country:us/state:vt/sldl:rutland-5-2'],
'R53': ['ocd-division/country:us/state:vt/sldl:rutland-5-3'],
'R54': ['ocd-division/country:us/state:vt/sldl:rutland-5-4'],
'RW2': ['ocd-division/country:us/state:vt/sldl:rutland-windsor-2'],
'W-1': ['ocd-division/country:us/state:vt/sldl:windham-1'],
'W-3': ['ocd-division/country:us/state:vt/sldl:windham-3'],
'W-4': ['ocd-division/country:us/state:vt/sldl:windham-4'],
'W-5': ['ocd-division/country:us/state:vt/sldl:windham-5'],
'W-6': ['ocd-division/country:us/state:vt/sldl:windham-6'],
'W21': ['ocd-division/country:us/state:vt/sldl:windham-2-1'],
'W22': ['ocd-division/country:us/state:vt/sldl:windham-2-2'],
'W23': ['ocd-division/country:us/state:vt/sldl:windham-2-3'],
'WA1': ['ocd-division/country:us/state:vt/sldl:washington-1'],
'WA2': ['ocd-division/country:us/state:vt/sldl:washington-2'],
'WA3': ['ocd-division/country:us/state:vt/sldl:washington-3'],
'WA4': ['ocd-division/country:us/state:vt/sldl:washington-4'],
'WA5': ['ocd-division/country:us/state:vt/sldl:washington-5'],
'WA6': ['ocd-division/country:us/state:vt/sldl:washington-6'],
'WA7': ['ocd-division/country:us/state:vt/sldl:washington-7'],
'WAC': ['ocd-division/country:us/state:vt/sldl:washington-chittenden'],
'WBW': ['ocd-division/country:us/state:vt/sldl:windham-bennington-windsor'],
'WIB': ['ocd-division/country:us/state:vt/sldl:windham-bennington'],
'Y-1': ['ocd-division/country:us/state:vt/sldl:windsor-1'],
'Y-2': ['ocd-division/country:us/state:vt/sldl:windsor-2'],
'Y-5': ['ocd-division/country:us/state:vt/sldl:windsor-5'],
'Y-R': ['ocd-division/country:us/state:vt/sldl:windsor-rutland'],
'Y31': ['ocd-division/country:us/state:vt/sldl:windsor-3-1'],
'Y32': ['ocd-division/country:us/state:vt/sldl:windsor-3-2'],
'Y41': ['ocd-division/country:us/state:vt/sldl:windsor-4-1'],
'Y42': ['ocd-division/country:us/state:vt/sldl:windsor-4-2'],
'YO1': ['ocd-division/country:us/state:vt/sldl:windsor-orange-1'],
'YO2': ['ocd-division/country:us/state:vt/sldl:windsor-orange-2']
}
}
| 66.632156 | 97 | 0.627456 | 7,749 | 54,705 | 4.361724 | 0.088528 | 0.257434 | 0.421255 | 0.468061 | 0.878843 | 0.878695 | 0.870973 | 0.688689 | 0.224711 | 0.00284 | 0 | 0.056421 | 0.161192 | 54,705 | 820 | 98 | 66.713415 | 0.680149 | 0.001517 | 0 | 0.139877 | 0 | 0 | 0.731324 | 0.697048 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
4c8121102197e31600852f88ffd5484bbea74bfa | 496 | py | Python | tests/context.py | petermartigny/NeMo | b20821e637314940e36b63d32c601c43d1b74051 | [
"Apache-2.0"
] | 1 | 2020-03-22T11:23:11.000Z | 2020-03-22T11:23:11.000Z | tests/context.py | petermartigny/NeMo | b20821e637314940e36b63d32c601c43d1b74051 | [
"Apache-2.0"
] | null | null | null | tests/context.py | petermartigny/NeMo | b20821e637314940e36b63d32c601c43d1b74051 | [
"Apache-2.0"
] | 1 | 2019-10-23T01:19:19.000Z | 2019-10-23T01:19:19.000Z | # Copyright (c) 2019 NVIDIA Corporation
import nemo
import nemo_asr
import nemo_nlp
import os
import sys
sys.path.insert(0, os.path.abspath(
os.path.join(os.path.dirname(__file__), '..')))
sys.path.insert(0, os.path.abspath(
os.path.join(os.path.dirname(__file__), '../nemo')))
sys.path.insert(0, os.path.abspath(
os.path.join(os.path.dirname(__file__), '../collections/')))
sys.path.insert(0, os.path.abspath(
os.path.join(os.path.dirname(__file__), '../collections/nemo_asr')))
| 33.066667 | 72 | 0.709677 | 78 | 496 | 4.269231 | 0.24359 | 0.216216 | 0.156156 | 0.168168 | 0.714715 | 0.714715 | 0.714715 | 0.714715 | 0.714715 | 0.714715 | 0 | 0.017857 | 0.096774 | 496 | 14 | 73 | 35.428571 | 0.725446 | 0.074597 | 0 | 0.307692 | 0 | 0 | 0.102845 | 0.050328 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.384615 | 0 | 0.384615 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 9 |
4c853ead15a9b02b56354f3a4e52023f2ca14225 | 5,913 | py | Python | retools/tests/test_limiter.py | szaydel/retools | 4e7ee27dd3c1b969d9cf63b29dc70e451aa20b43 | [
"MIT"
] | 52 | 2015-01-20T05:43:25.000Z | 2021-12-18T08:45:45.000Z | retools/tests/test_limiter.py | szaydel/retools | 4e7ee27dd3c1b969d9cf63b29dc70e451aa20b43 | [
"MIT"
] | 2 | 2020-01-23T23:26:01.000Z | 2021-01-04T17:02:26.000Z | retools/tests/test_limiter.py | szaydel/retools | 4e7ee27dd3c1b969d9cf63b29dc70e451aa20b43 | [
"MIT"
] | 15 | 2015-05-15T10:45:39.000Z | 2021-05-12T16:39:37.000Z | # coding: utf-8
import unittest
import time
import redis
from nose.tools import eq_
from mock import Mock
from mock import patch
from retools.limiter import Limiter
from retools import global_connection
class TestLimiterWithMockRedis(unittest.TestCase):
def test_can_create_limiter_without_prefix_and_without_connection(self):
limiter = Limiter(limit=10)
eq_(limiter.redis, global_connection.redis)
eq_(limiter.limit, 10)
eq_(limiter.prefix, 'retools_limiter')
def test_can_create_limiter_without_prefix(self):
mock_redis = Mock(spec=redis.Redis)
limiter = Limiter(limit=10, redis=mock_redis)
eq_(limiter.redis, mock_redis)
eq_(limiter.prefix, 'retools_limiter')
def test_can_create_limiter_with_prefix(self):
mock_redis = Mock(spec=redis.Redis)
limiter = Limiter(limit=10, redis=mock_redis, prefix='something')
eq_(limiter.redis, mock_redis)
eq_(limiter.prefix, 'something')
def test_can_create_limiter_with_expiration(self):
mock_redis = Mock(spec=redis.Redis)
limiter = Limiter(limit=10, redis=mock_redis, expiration_in_seconds=20)
eq_(limiter.expiration_in_seconds, 20)
def test_has_limit(self):
mock_time = Mock()
mock_time.return_value = 40.5
mock_redis = Mock(spec=redis.Redis)
mock_redis.zcard.return_value = 0
limiter = Limiter(limit=10, redis=mock_redis, expiration_in_seconds=20)
with patch('time.time', mock_time):
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
mock_redis.zadd.assert_called_once_with('retools_limiter', 'test1', 60.5)
def test_acquire_limit_after_removing_items(self):
mock_time = Mock()
mock_time.return_value = 40.5
mock_redis = Mock(spec=redis.Redis)
mock_redis.zcard.side_effect = [10, 8]
limiter = Limiter(limit=10, redis=mock_redis, expiration_in_seconds=20)
with patch('time.time', mock_time):
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
mock_redis.zadd.assert_called_once_with('retools_limiter', 'test1', 60.5)
mock_redis.zremrangebyscore.assert_called_once_with('retools_limiter', '-inf', 40.5)
def test_acquire_limit_fails_even_after_removing_items(self):
mock_time = Mock()
mock_time.return_value = 40.5
mock_redis = Mock(spec=redis.Redis)
mock_redis.zcard.side_effect = [10, 10]
limiter = Limiter(limit=10, redis=mock_redis, expiration_in_seconds=20)
with patch('time.time', mock_time):
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, False)
eq_(mock_redis.zadd.called, False)
mock_redis.zremrangebyscore.assert_called_once_with('retools_limiter', '-inf', 40.5)
def test_release_limit(self):
mock_redis = Mock(spec=redis.Redis)
limiter = Limiter(limit=10, redis=mock_redis, expiration_in_seconds=20)
limiter.release_limit(key='test1')
mock_redis.zrem.assert_called_once_with('retools_limiter', 'test1')
class TestLimiterWithActualRedis(unittest.TestCase):
def test_has_limit(self):
limiter = Limiter(prefix='test-%.6f' % time.time(), limit=2, expiration_in_seconds=400)
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test2')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test3')
eq_(has_limit, False)
def test_has_limit_after_removing_items(self):
limiter = Limiter(prefix='test-%.6f' % time.time(), limit=2, expiration_in_seconds=400)
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test2', expiration_in_seconds=-1)
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test3')
eq_(has_limit, True)
def test_has_limit_after_releasing_items(self):
limiter = Limiter(prefix='test-%.6f' % time.time(), limit=2, expiration_in_seconds=400)
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test2')
eq_(has_limit, True)
limiter.release_limit(key='test2')
has_limit = limiter.acquire_limit(key='test3')
eq_(has_limit, True)
class TestLimiterWithStrictRedis(unittest.TestCase):
def setUp(self):
self.redis = redis.StrictRedis()
def test_has_limit(self):
limiter = Limiter(prefix='test-%.6f' % time.time(), limit=2, expiration_in_seconds=400, redis=self.redis)
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test2')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test3')
eq_(has_limit, False)
def test_has_limit_after_removing_items(self):
limiter = Limiter(prefix='test-%.6f' % time.time(), limit=2, expiration_in_seconds=400, redis=self.redis)
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test2', expiration_in_seconds=-1)
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test3')
eq_(has_limit, True)
def test_has_limit_after_releasing_items(self):
limiter = Limiter(prefix='test-%.6f' % time.time(), limit=2, expiration_in_seconds=400, redis=self.redis)
has_limit = limiter.acquire_limit(key='test1')
eq_(has_limit, True)
has_limit = limiter.acquire_limit(key='test2')
eq_(has_limit, True)
limiter.release_limit(key='test2')
has_limit = limiter.acquire_limit(key='test3')
eq_(has_limit, True)
| 31.790323 | 113 | 0.680027 | 783 | 5,913 | 4.813538 | 0.097063 | 0.104006 | 0.083577 | 0.122579 | 0.84797 | 0.825949 | 0.817724 | 0.795967 | 0.779782 | 0.779782 | 0 | 0.025422 | 0.208354 | 5,913 | 185 | 114 | 31.962162 | 0.779748 | 0.002199 | 0 | 0.722689 | 0 | 0 | 0.058834 | 0 | 0 | 0 | 0 | 0 | 0.042017 | 1 | 0.12605 | false | 0 | 0.067227 | 0 | 0.218487 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
4cf8a8c55e6e0e5acf9f2040e37acad83d1faff9 | 926 | py | Python | web/huluwa/dinnerplanner/models.py | heguangzhu/huluwa | 7f799c75600227a03a0e42890d9a3ca2cb261cb7 | [
"Apache-2.0"
] | null | null | null | web/huluwa/dinnerplanner/models.py | heguangzhu/huluwa | 7f799c75600227a03a0e42890d9a3ca2cb261cb7 | [
"Apache-2.0"
] | null | null | null | web/huluwa/dinnerplanner/models.py | heguangzhu/huluwa | 7f799c75600227a03a0e42890d9a3ca2cb261cb7 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
# Create your models here.
from django.db import models
class Person(models.Model):
nick_name = models.CharField(max_length=30)
gender = models.CharField(max_length=2)
state = models.CharField(max_length=100)
class Dish(models.Model):
dish_name = models.CharField(max_length=30)
dish_type = models.CharField(max_length=30)
caixi = models.CharField(max_length=30)
flavor = models.CharField(max_length=30)
class TrainingItem(models.Model):
nick_name = models.CharField(max_length=30)
gender = models.CharField(max_length=2)
state = models.CharField(max_length=100)
dish_name = models.CharField(max_length=30)
dish_type = models.CharField(max_length=30)
caixi = models.CharField(max_length=30)
flavor = models.CharField(max_length=30)
rank = models.IntegerField()
| 28.9375 | 47 | 0.736501 | 127 | 926 | 5.173228 | 0.267717 | 0.319635 | 0.383562 | 0.511416 | 0.800609 | 0.727549 | 0.727549 | 0.727549 | 0.727549 | 0.727549 | 0 | 0.037132 | 0.156587 | 926 | 31 | 48 | 29.870968 | 0.804097 | 0.049676 | 0 | 0.761905 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 11 |
4cf8fdd37efe2d5459faccb4d5d52dd7426ed881 | 3,252 | py | Python | utils/scripts/OOOlevelGen/src/levels/Triple_Touch.py | fullscreennl/monkeyswipe | c56192e202674dd5ab18023f6cf14cf51e95fbd0 | [
"MIT"
] | null | null | null | utils/scripts/OOOlevelGen/src/levels/Triple_Touch.py | fullscreennl/monkeyswipe | c56192e202674dd5ab18023f6cf14cf51e95fbd0 | [
"MIT"
] | null | null | null | utils/scripts/OOOlevelGen/src/levels/Triple_Touch.py | fullscreennl/monkeyswipe | c56192e202674dd5ab18023f6cf14cf51e95fbd0 | [
"MIT"
] | null | null | null | import LevelBuilder
from sprites import *
def render(name,bg):
lb = LevelBuilder.LevelBuilder(name+".plist",background=bg)
lb.addObject(Bomb.BombSprite(x=21, y=15,width=32,height=32 ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Bomb.BombSprite(x=111, y=15,width=32,height=32 ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Beam.BeamSprite(x=65, y=38,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Hero.HeroSprite(x=66, y=61,width=32,height=32))
lb.addObject(Beam.BeamSprite(x=65, y=225,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=23, y=248,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=111, y=248,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Beam.BeamSprite(x=65, y=272,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=66, y=299,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Star.StarSprite(x=66, y=249,width=32,height=32))
lb.addObject(Beam.BeamSprite(x=233, y=226,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=191, y=249,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=279, y=249,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Beam.BeamSprite(x=233, y=273,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=234, y=300,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Star.StarSprite(x=234, y=250,width=32,height=32))
lb.addObject(Bomb.BombSprite(x=368, y=20,width=32,height=32 ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Bomb.BombSprite(x=458, y=20,width=32,height=32 ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Beam.BeamSprite(x=412, y=43,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Hero.HeroSprite(x=413, y=66,width=32,height=32))
lb.addObject(Beam.BeamSprite(x=412, y=230,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=370, y=253,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=458, y=253,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Beam.BeamSprite(x=412, y=277,width=127,height=14,angle='0' ,restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Enemy.EnemySprite(x=413, y=304,width=32,height=32,angle='0',restitution=0.2,static='false',friction=0.5,density=20 ))
lb.addObject(Star.StarSprite(x=413, y=254,width=32,height=32))
lb.render() | 104.903226 | 134 | 0.728167 | 574 | 3,252 | 4.125436 | 0.123693 | 0.120777 | 0.115287 | 0.168497 | 0.915541 | 0.891047 | 0.878378 | 0.872044 | 0.872044 | 0.820101 | 0 | 0.129763 | 0.063961 | 3,252 | 31 | 135 | 104.903226 | 0.64816 | 0 | 0 | 0 | 0 | 0 | 0.039348 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.032258 | false | 0 | 0.064516 | 0 | 0.096774 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
2c6c9d1a2c772fc1c0c6253e900b145d5744ea4e | 92 | py | Python | sfaira/ui/__init__.py | johnmous/sfaira | c50240a74530e614ab7681bf9c63b04cb815b361 | [
"BSD-3-Clause"
] | 110 | 2020-09-08T07:47:15.000Z | 2022-03-29T03:33:56.000Z | sfaira/ui/__init__.py | johnmous/sfaira | c50240a74530e614ab7681bf9c63b04cb815b361 | [
"BSD-3-Clause"
] | 405 | 2020-09-15T15:05:46.000Z | 2022-03-16T14:44:23.000Z | sfaira/ui/__init__.py | johnmous/sfaira | c50240a74530e614ab7681bf9c63b04cb815b361 | [
"BSD-3-Clause"
] | 20 | 2021-03-30T15:30:14.000Z | 2022-03-07T12:52:58.000Z | from sfaira.ui.model_zoo import ModelZoo
from sfaira.ui.user_interface import UserInterface
| 30.666667 | 50 | 0.869565 | 14 | 92 | 5.571429 | 0.714286 | 0.25641 | 0.307692 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.086957 | 92 | 2 | 51 | 46 | 0.928571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
2ca87af74dd1806b893064b80dc23194d62067e0 | 5,345 | py | Python | model/main.py | lucaswerner90/upc_dl_project_2021 | c02061da0e25a0b24a9b742074b87ac30f36586d | [
"MIT"
] | 2 | 2021-07-15T12:30:43.000Z | 2021-11-04T07:50:16.000Z | model/main.py | lucaswerner90/upc_dl_project_2021 | c02061da0e25a0b24a9b742074b87ac30f36586d | [
"MIT"
] | 30 | 2021-05-03T07:37:37.000Z | 2021-07-01T18:53:23.000Z | model/main.py | lucaswerner90/upc_dl_project_2021 | c02061da0e25a0b24a9b742074b87ac30f36586d | [
"MIT"
] | 1 | 2021-06-21T11:12:32.000Z | 2021-06-21T11:12:32.000Z | import os
import torch
from torch import nn
#from encoder import Encoder
from model.encoder import Encoder_VGG16, Encoder_ViT_Pretrained
from dataset.vocabulary import Vocabulary
from model.transformer.decoder import TransformerDecoder
class ImageCaptioningModel(nn.Module):
def __init__(self, image_features_dim:int,embed_size:int, vocab:Vocabulary, caption_max_length:int,decoder_num_layers=4):
super(ImageCaptioningModel, self).__init__()
self.vocab = vocab
self.vocab_size = len(self.vocab.word_to_index)
self.encoder = Encoder_VGG16()
self.decoder = TransformerDecoder(image_features_dim,vocab_size=self.vocab_size,embed_size=embed_size,num_layers=decoder_num_layers)
self.caption_max_length = caption_max_length
def forward(self, images, captions):
"""
images => (batch_size, channels, W, H)
captions => (batch_size, captions_length)
"""
images_features = self.encoder.forward(images)
predictions = self.decoder.forward(images_features, captions)
return predictions
def generate(self,image):
image_features = self.encoder.forward(image)
output = torch.LongTensor([self.vocab.word_to_index['<START>']])\
.expand(image_features.size(0),1).to(image_features.device)
for i in range(self.caption_max_length):
next_word=self.decoder.forward(image_features,output).argmax(-1)[:,-1]
output = torch.cat([output,next_word.unsqueeze(0)],dim=1)
return self.vocab.generate_caption(output.squeeze(0))
def inference(self, image):
image_features = self.encoder(image)
hidden = self.decoder.init_hidden(image.shape[0])
if torch.cuda.is_available():
word = torch.cuda.IntTensor([self.vocab.word_to_index['<START>']])
else:
word = torch.tensor(self.vocab.word_to_index['<START>'])
sentence = [word.item()]
attention_weights=[]
for i in range(self.caption_max_length):
alphas, weighted_features = self.attention.forward(image_features, hidden)
predictions_t, hidden = self.decoder.forward(weighted_features, word, hidden)
word = torch.argmax(predictions_t, dim=-1)
if word[0].item()==self.vocab.word_to_index['<END>']:
break
sentence.append(word.item())
attention_weights.append(alphas)
if torch.cuda.is_available():
sentence=torch.cuda.IntTensor(sentence[1:])
else:
sentence=torch.tensor(sentence[1:])
sentence=self.vocab.generate_caption(sentence)
return sentence, attention_weights
def save_model(self,epoch):
string_fn='transformer_model_epoch_'+str(epoch)+'.pth'
filename = os.path.join('model','trained_models',string_fn)
dirname = os.path.join('model','trained_models')
if not os.path.exists(dirname):
os.makedirs(dirname)
model_state = {
'epoch':epoch,
'model':self.state_dict()
}
torch.save(model_state, filename)
class ViTImageCaptioningModel(nn.Module):
def __init__(self,embed_size:int, vocab:Vocabulary, caption_max_length:int,decoder_num_layers=4):
super(ViTImageCaptioningModel, self).__init__()
self.vocab = vocab
self.vocab_size = len(self.vocab.word_to_index)
self.encoder = Encoder_ViT_Pretrained()
image_features_dim = self.encoder.pretrained_model.encoder.config.hidden_size
self.decoder = TransformerDecoder(image_features_dim,vocab_size=self.vocab_size,embed_size=embed_size,num_layers=decoder_num_layers)
self.caption_max_length = caption_max_length
def forward(self, images, captions):
"""
images => (batch_size, channels, W, H)
captions => (batch_size, captions_length)
"""
images_features = self.encoder.forward(images)
predictions = self.decoder.forward(images_features, captions)
return predictions
def generate(self,image):
image_features = self.encoder.forward(image)
output = torch.LongTensor([self.vocab.word_to_index['<START>']])\
.expand(image_features.size(0),1).to(image_features.device)
for i in range(self.caption_max_length):
next_word=self.decoder.forward(image_features,output).argmax(-1)[:,-1]
output = torch.cat([output,next_word.unsqueeze(0)],dim=1)
return self.vocab.generate_caption(output.squeeze(0))
def inference(self, image):
image_features = self.encoder(image)
hidden = self.decoder.init_hidden(image.shape[0])
if torch.cuda.is_available():
word = torch.cuda.IntTensor([self.vocab.word_to_index['<START>']])
else:
word = torch.tensor(self.vocab.word_to_index['<START>'])
sentence = [word.item()]
attention_weights=[]
for i in range(self.caption_max_length):
alphas, weighted_features = self.attention.forward(image_features, hidden)
predictions_t, hidden = self.decoder.forward(weighted_features, word, hidden)
word = torch.argmax(predictions_t, dim=-1)
if word[0].item()==self.vocab.word_to_index['<END>']:
break
sentence.append(word.item())
attention_weights.append(alphas)
if torch.cuda.is_available():
sentence=torch.cuda.IntTensor(sentence[1:])
else:
sentence=torch.tensor(sentence[1:])
sentence=self.vocab.generate_caption(sentence)
return sentence, attention_weights
def save_model(self,epoch):
string_fn='ViT_model_epoch_'+str(epoch)+'.pth'
filename = os.path.join('model','trained_models',string_fn)
dirname = os.path.join('model','trained_models')
if not os.path.exists(dirname):
os.makedirs(dirname)
model_state = {
'epoch':epoch,
'model':self.state_dict()
}
torch.save(model_state, filename)
| 36.609589 | 134 | 0.751356 | 732 | 5,345 | 5.259563 | 0.142077 | 0.046753 | 0.041558 | 0.038961 | 0.892468 | 0.882597 | 0.882597 | 0.882597 | 0.882597 | 0.882597 | 0 | 0.006345 | 0.115435 | 5,345 | 145 | 135 | 36.862069 | 0.807953 | 0.03536 | 0 | 0.834783 | 0 | 0 | 0.038214 | 0.004679 | 0 | 0 | 0 | 0 | 0 | 1 | 0.086957 | false | 0 | 0.052174 | 0 | 0.208696 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
e2ccb9bd7548339d4be8152e4c263bdc9bb23b51 | 75,982 | py | Python | radian-server/test.py | moses-lee/Radian | 9d5ef496cc1e4247b2bcb3f509a7332d09d49be3 | [
"MIT"
] | 1 | 2020-12-18T05:11:37.000Z | 2020-12-18T05:11:37.000Z | radian-server/test.py | moses-lee/Radian | 9d5ef496cc1e4247b2bcb3f509a7332d09d49be3 | [
"MIT"
] | 6 | 2020-09-25T22:04:43.000Z | 2022-02-10T01:19:27.000Z | radian-server/test.py | moses-lee/Radian | 9d5ef496cc1e4247b2bcb3f509a7332d09d49be3 | [
"MIT"
] | null | null | null | import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
import base64
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import load_model
img_data="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"
model = load_model('model.h5', compile=False)
img = base64.b64decode(img_data)
img = np.fromstring(base64.b64decode(img), np.uint8)
img = cv2.resize(img, (224, 224), interpolation=cv2.INTER_NEAREST)
img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
img = np.expand_dims(img, axis=0)
print(model.predict(img))
img = mpimg.imread('C:\\Users\spotzdevelopment\\Desktop\\lung_images\\Covid_sample2.png')
print(type(img))
img = cv2.resize(img, (224, 224), interpolation=cv2.INTER_NEAREST)
img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
img = np.expand_dims(img, axis=0)
print(model.predict(img)) | 2,814.148148 | 75,187 | 0.9542 | 3,191 | 75,982 | 22.717017 | 0.951739 | 0.000497 | 0.000497 | 0.000414 | 0.003449 | 0.003449 | 0.003449 | 0.003449 | 0.003449 | 0.003449 | 0 | 0.178805 | 0.001027 | 75,982 | 27 | 75,188 | 2,814.148148 | 0.776217 | 0 | 0 | 0.363636 | 0 | 0.045455 | 0.990366 | 0.990261 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.363636 | 0 | 0.363636 | 0.136364 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
392b63486dd444059be1e10b1f4e2a78a999d19e | 13,968 | py | Python | porerefiner/protocols/minknow/rpc/protocol_grpc.py | CFSAN-Biostatistics/porerefiner | 64f96498bd6c036cfac46def1d9d94362001e67c | [
"MIT"
] | 8 | 2019-10-10T20:05:18.000Z | 2021-02-19T21:53:43.000Z | porerefiner/protocols/minknow/rpc/protocol_grpc.py | CFSAN-Biostatistics/porerefiner | 64f96498bd6c036cfac46def1d9d94362001e67c | [
"MIT"
] | 2 | 2020-07-17T07:24:17.000Z | 2021-02-19T22:28:12.000Z | porerefiner/protocols/minknow/rpc/protocol_grpc.py | CFSAN-Biostatistics/porerefiner | 64f96498bd6c036cfac46def1d9d94362001e67c | [
"MIT"
] | 2 | 2019-10-01T15:45:59.000Z | 2019-10-28T19:15:32.000Z | # Generated by the Protocol Buffers compiler. DO NOT EDIT!
# source: minknow/rpc/protocol.proto
# plugin: grpclib.plugin.main
import abc
import typing
import grpclib.const
import grpclib.client
if typing.TYPE_CHECKING:
import grpclib.server
from . import acquisition_pb2
from . import device_pb2
from . import rpc_options_pb2
import google.protobuf.timestamp_pb2
import google.protobuf.wrappers_pb2
from . import protocol_pb2
class ProtocolServiceBase(abc.ABC):
@abc.abstractmethod
async def start_protocol(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.StartProtocolRequest, minknow.rpc.protocol_pb2.StartProtocolResponse]') -> None:
pass
@abc.abstractmethod
async def stop_protocol(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.StopProtocolRequest, minknow.rpc.protocol_pb2.StopProtocolResponse]') -> None:
pass
@abc.abstractmethod
async def wait_for_finished(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.WaitForFinishedRequest, minknow.rpc.protocol_pb2.ProtocolRunInfo]') -> None:
pass
@abc.abstractmethod
async def get_run_info(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.GetRunInfoRequest, minknow.rpc.protocol_pb2.ProtocolRunInfo]') -> None:
pass
@abc.abstractmethod
async def list_protocol_runs(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.ListProtocolRunsRequest, minknow.rpc.protocol_pb2.ListProtocolRunsResponse]') -> None:
pass
@abc.abstractmethod
async def get_current_protocol_run(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.GetCurrentProtocolRunRequest, minknow.rpc.protocol_pb2.ProtocolRunInfo]') -> None:
pass
@abc.abstractmethod
async def watch_current_protocol_run(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.WatchCurrentProtocolRunRequest, minknow.rpc.protocol_pb2.ProtocolRunInfo]') -> None:
pass
@abc.abstractmethod
async def list_protocols(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.ListProtocolsRequest, minknow.rpc.protocol_pb2.ListProtocolsResponse]') -> None:
pass
@abc.abstractmethod
async def get_context_info(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.GetContextInfoRequest, minknow.rpc.protocol_pb2.GetContextInfoResponse]') -> None:
pass
@abc.abstractmethod
async def set_context_info(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.SetContextInfoRequest, minknow.rpc.protocol_pb2.SetContextInfoResponse]') -> None:
pass
@abc.abstractmethod
async def get_sample_id(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.GetSampleIdRequest, minknow.rpc.protocol_pb2.GetSampleIdResponse]') -> None:
pass
@abc.abstractmethod
async def set_sample_id(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.SetSampleIdRequest, minknow.rpc.protocol_pb2.SetSampleIdResponse]') -> None:
pass
@abc.abstractmethod
async def get_protocol_purpose(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.GetProtocolPurposeRequest, minknow.rpc.protocol_pb2.GetProtocolPurposeResponse]') -> None:
pass
@abc.abstractmethod
async def set_protocol_purpose(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.SetProtocolPurposeRequest, minknow.rpc.protocol_pb2.SetProtocolPurposeResponse]') -> None:
pass
@abc.abstractmethod
async def add_epi2me_workflow(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.AddEpi2meWorkflowRequest, minknow.rpc.protocol_pb2.AddEpi2meWorkflowResponse]') -> None:
pass
@abc.abstractmethod
async def list_protocol_group_ids(self, stream: 'grpclib.server.Stream[minknow.rpc.protocol_pb2.ListProtocolGroupIdsRequest, minknow.rpc.protocol_pb2.ListProtocolGroupIdsResponse]') -> None:
pass
def __mapping__(self) -> typing.Dict[str, grpclib.const.Handler]:
return {
'/ont.rpc.protocol.ProtocolService/start_protocol': grpclib.const.Handler(
self.start_protocol,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.StartProtocolRequest,
minknow.rpc.protocol_pb2.StartProtocolResponse,
),
'/ont.rpc.protocol.ProtocolService/stop_protocol': grpclib.const.Handler(
self.stop_protocol,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.StopProtocolRequest,
minknow.rpc.protocol_pb2.StopProtocolResponse,
),
'/ont.rpc.protocol.ProtocolService/wait_for_finished': grpclib.const.Handler(
self.wait_for_finished,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.WaitForFinishedRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
),
'/ont.rpc.protocol.ProtocolService/get_run_info': grpclib.const.Handler(
self.get_run_info,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.GetRunInfoRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
),
'/ont.rpc.protocol.ProtocolService/list_protocol_runs': grpclib.const.Handler(
self.list_protocol_runs,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.ListProtocolRunsRequest,
minknow.rpc.protocol_pb2.ListProtocolRunsResponse,
),
'/ont.rpc.protocol.ProtocolService/get_current_protocol_run': grpclib.const.Handler(
self.get_current_protocol_run,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.GetCurrentProtocolRunRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
),
'/ont.rpc.protocol.ProtocolService/watch_current_protocol_run': grpclib.const.Handler(
self.watch_current_protocol_run,
grpclib.const.Cardinality.UNARY_STREAM,
minknow.rpc.protocol_pb2.WatchCurrentProtocolRunRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
),
'/ont.rpc.protocol.ProtocolService/list_protocols': grpclib.const.Handler(
self.list_protocols,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.ListProtocolsRequest,
minknow.rpc.protocol_pb2.ListProtocolsResponse,
),
'/ont.rpc.protocol.ProtocolService/get_context_info': grpclib.const.Handler(
self.get_context_info,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.GetContextInfoRequest,
minknow.rpc.protocol_pb2.GetContextInfoResponse,
),
'/ont.rpc.protocol.ProtocolService/set_context_info': grpclib.const.Handler(
self.set_context_info,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.SetContextInfoRequest,
minknow.rpc.protocol_pb2.SetContextInfoResponse,
),
'/ont.rpc.protocol.ProtocolService/get_sample_id': grpclib.const.Handler(
self.get_sample_id,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.GetSampleIdRequest,
minknow.rpc.protocol_pb2.GetSampleIdResponse,
),
'/ont.rpc.protocol.ProtocolService/set_sample_id': grpclib.const.Handler(
self.set_sample_id,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.SetSampleIdRequest,
minknow.rpc.protocol_pb2.SetSampleIdResponse,
),
'/ont.rpc.protocol.ProtocolService/get_protocol_purpose': grpclib.const.Handler(
self.get_protocol_purpose,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.GetProtocolPurposeRequest,
minknow.rpc.protocol_pb2.GetProtocolPurposeResponse,
),
'/ont.rpc.protocol.ProtocolService/set_protocol_purpose': grpclib.const.Handler(
self.set_protocol_purpose,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.SetProtocolPurposeRequest,
minknow.rpc.protocol_pb2.SetProtocolPurposeResponse,
),
'/ont.rpc.protocol.ProtocolService/add_epi2me_workflow': grpclib.const.Handler(
self.add_epi2me_workflow,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.AddEpi2meWorkflowRequest,
minknow.rpc.protocol_pb2.AddEpi2meWorkflowResponse,
),
'/ont.rpc.protocol.ProtocolService/list_protocol_group_ids': grpclib.const.Handler(
self.list_protocol_group_ids,
grpclib.const.Cardinality.UNARY_UNARY,
minknow.rpc.protocol_pb2.ListProtocolGroupIdsRequest,
minknow.rpc.protocol_pb2.ListProtocolGroupIdsResponse,
),
}
class ProtocolServiceStub:
def __init__(self, channel: grpclib.client.Channel) -> None:
self.start_protocol = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/start_protocol',
minknow.rpc.protocol_pb2.StartProtocolRequest,
minknow.rpc.protocol_pb2.StartProtocolResponse,
)
self.stop_protocol = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/stop_protocol',
minknow.rpc.protocol_pb2.StopProtocolRequest,
minknow.rpc.protocol_pb2.StopProtocolResponse,
)
self.wait_for_finished = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/wait_for_finished',
minknow.rpc.protocol_pb2.WaitForFinishedRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
)
self.get_run_info = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/get_run_info',
minknow.rpc.protocol_pb2.GetRunInfoRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
)
self.list_protocol_runs = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/list_protocol_runs',
minknow.rpc.protocol_pb2.ListProtocolRunsRequest,
minknow.rpc.protocol_pb2.ListProtocolRunsResponse,
)
self.get_current_protocol_run = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/get_current_protocol_run',
minknow.rpc.protocol_pb2.GetCurrentProtocolRunRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
)
self.watch_current_protocol_run = grpclib.client.UnaryStreamMethod(
channel,
'/ont.rpc.protocol.ProtocolService/watch_current_protocol_run',
minknow.rpc.protocol_pb2.WatchCurrentProtocolRunRequest,
minknow.rpc.protocol_pb2.ProtocolRunInfo,
)
self.list_protocols = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/list_protocols',
minknow.rpc.protocol_pb2.ListProtocolsRequest,
minknow.rpc.protocol_pb2.ListProtocolsResponse,
)
self.get_context_info = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/get_context_info',
minknow.rpc.protocol_pb2.GetContextInfoRequest,
minknow.rpc.protocol_pb2.GetContextInfoResponse,
)
self.set_context_info = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/set_context_info',
minknow.rpc.protocol_pb2.SetContextInfoRequest,
minknow.rpc.protocol_pb2.SetContextInfoResponse,
)
self.get_sample_id = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/get_sample_id',
minknow.rpc.protocol_pb2.GetSampleIdRequest,
minknow.rpc.protocol_pb2.GetSampleIdResponse,
)
self.set_sample_id = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/set_sample_id',
minknow.rpc.protocol_pb2.SetSampleIdRequest,
minknow.rpc.protocol_pb2.SetSampleIdResponse,
)
self.get_protocol_purpose = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/get_protocol_purpose',
minknow.rpc.protocol_pb2.GetProtocolPurposeRequest,
minknow.rpc.protocol_pb2.GetProtocolPurposeResponse,
)
self.set_protocol_purpose = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/set_protocol_purpose',
minknow.rpc.protocol_pb2.SetProtocolPurposeRequest,
minknow.rpc.protocol_pb2.SetProtocolPurposeResponse,
)
self.add_epi2me_workflow = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/add_epi2me_workflow',
minknow.rpc.protocol_pb2.AddEpi2meWorkflowRequest,
minknow.rpc.protocol_pb2.AddEpi2meWorkflowResponse,
)
self.list_protocol_group_ids = grpclib.client.UnaryUnaryMethod(
channel,
'/ont.rpc.protocol.ProtocolService/list_protocol_group_ids',
minknow.rpc.protocol_pb2.ListProtocolGroupIdsRequest,
minknow.rpc.protocol_pb2.ListProtocolGroupIdsResponse,
)
| 48.839161 | 194 | 0.684278 | 1,334 | 13,968 | 6.949025 | 0.081709 | 0.153074 | 0.18835 | 0.217476 | 0.927616 | 0.898274 | 0.837325 | 0.744121 | 0.702805 | 0.6274 | 0 | 0.0105 | 0.229525 | 13,968 | 285 | 195 | 49.010526 | 0.850864 | 0.008519 | 0 | 0.554264 | 1 | 0.062016 | 0.255327 | 0.254171 | 0 | 0 | 0 | 0 | 0 | 1 | 0.007752 | false | 0.062016 | 0.042636 | 0.003876 | 0.062016 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 10 |
1a5cf8490a663dd2cf717b2b63a022d5303bd5f4 | 331 | py | Python | src/dagos/commands/wsl/cli.py | DAG-OS/dagos | ac663ecf1cb9abe12669136e2b2e22b936ec88b5 | [
"MIT"
] | null | null | null | src/dagos/commands/wsl/cli.py | DAG-OS/dagos | ac663ecf1cb9abe12669136e2b2e22b936ec88b5 | [
"MIT"
] | 8 | 2022-02-20T15:43:03.000Z | 2022-03-27T19:04:16.000Z | src/dagos/commands/wsl/cli.py | DAG-OS/dagos | ac663ecf1cb9abe12669136e2b2e22b936ec88b5 | [
"MIT"
] | null | null | null | import click
from dagos.commands.wsl.import_wsl_distro import import_wsl_distro
from dagos.commands.wsl.prepare_wsl_distro import prepare_wsl_distro
@click.group(no_args_is_help=True)
def wsl():
"""
Prepare or import WSL distros.
"""
pass
wsl.add_command(import_wsl_distro)
wsl.add_command(prepare_wsl_distro)
| 19.470588 | 68 | 0.785498 | 51 | 331 | 4.764706 | 0.392157 | 0.222222 | 0.185185 | 0.164609 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.132931 | 331 | 16 | 69 | 20.6875 | 0.84669 | 0.090634 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.125 | true | 0.125 | 0.5 | 0 | 0.625 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 7 |
64ba47831ef1cf3610b98ded3d47df6a3ca74d19 | 525 | py | Python | python/testData/highlighting/builtinDecorator.py | jnthn/intellij-community | 8fa7c8a3ace62400c838e0d5926a7be106aa8557 | [
"Apache-2.0"
] | 2 | 2019-04-28T07:48:50.000Z | 2020-12-11T14:18:08.000Z | python/testData/highlighting/builtinDecorator.py | Cyril-lamirand/intellij-community | 60ab6c61b82fc761dd68363eca7d9d69663cfa39 | [
"Apache-2.0"
] | 173 | 2018-07-05T13:59:39.000Z | 2018-08-09T01:12:03.000Z | python/testData/highlighting/builtinDecorator.py | Cyril-lamirand/intellij-community | 60ab6c61b82fc761dd68363eca7d9d69663cfa39 | [
"Apache-2.0"
] | 2 | 2020-03-15T08:57:37.000Z | 2020-04-07T04:48:14.000Z | <info descr="PY.DECORATOR">@</info> <info descr="PY.DECORATOR">foo</info>
def <info descr="PY.FUNC_DEFINITION">f</info>():
pass
class <info descr="PY.CLASS_DEFINITION">C</info>:
<info descr="PY.DECORATOR">@</info> <info descr="PY.DECORATOR">f</info>
def <info descr="PY.FUNC_DEFINITION">bar</info>(<info descr="PY.SELF_PARAMETER">self</info>):
pass
<info descr="PY.DECORATOR">@</info><info descr="PY.DECORATOR">staticmethod</info>
def <info descr="PY.FUNC_DEFINITION">bar</info>():
pass | 40.384615 | 97 | 0.662857 | 75 | 525 | 4.573333 | 0.213333 | 0.28863 | 0.35277 | 0.349854 | 0.717201 | 0.705539 | 0.705539 | 0.612245 | 0.612245 | 0 | 0 | 0 | 0.12381 | 525 | 13 | 98 | 40.384615 | 0.745652 | 0 | 0 | 0.3 | 0 | 0 | 0.307985 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.3 | 0 | null | null | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 7 |
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