content stringlengths 1 1.04M | input_ids listlengths 1 774k | ratio_char_token float64 0.38 22.9 | token_count int64 1 774k |
|---|---|---|---|
import unittest
from AdditionalModules.type_checker import is_valid_number
if __name__ == '__main__':
unittest.main()
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# This code is part of Qiskit.
#
# (C) Copyright IBM 2018, 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""
StatevectorSimulator Integration Tests
"""
from numpy import exp, pi
from test.terra.reference import ref_measure
from test.terra.reference import ref_reset
from test.terra.reference import ref_initialize
from test.terra.reference import ref_conditionals
from test.terra.reference import ref_1q_clifford
from test.terra.reference import ref_2q_clifford
from test.terra.reference import ref_non_clifford
from test.terra.reference import ref_unitary_gate
from test.terra.reference import ref_diagonal_gate
from qiskit import execute, transpile, assemble
from qiskit.providers.aer import StatevectorSimulator
class StatevectorSimulatorTests:
"""StatevectorSimulator tests."""
SIMULATOR = StatevectorSimulator()
BACKEND_OPTS = {}
# ---------------------------------------------------------------------
# Test initialize
# ---------------------------------------------------------------------
def test_initialize_1(self):
"""Test StatevectorSimulator initialize"""
circuits = ref_initialize.initialize_circuits_1(final_measure=False)
targets = ref_initialize.initialize_statevector_1()
qobj = assemble(circuits, shots=1)
sim_job = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS)
result = sim_job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_initialize_2(self):
"""Test StatevectorSimulator initialize"""
circuits = ref_initialize.initialize_circuits_2(final_measure=False)
targets = ref_initialize.initialize_statevector_2()
qobj = assemble(circuits, shots=1)
sim_job = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS)
result = sim_job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test reset
# ---------------------------------------------------------------------
def test_reset_deterministic(self):
"""Test StatevectorSimulator reset with for circuits with deterministic counts"""
# For statevector output we can combine deterministic and non-deterministic
# count output circuits
circuits = ref_reset.reset_circuits_deterministic(final_measure=False)
targets = ref_reset.reset_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_reset_nondeterministic(self):
"""Test StatevectorSimulator reset with for circuits with non-deterministic counts"""
# For statevector output we can combine deterministic and non-deterministic
# count output circuits
circuits = ref_reset.reset_circuits_nondeterministic(
final_measure=False)
targets = ref_reset.reset_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test measure
# ---------------------------------------------------------------------
def test_measure(self):
"""Test StatevectorSimulator measure with deterministic counts"""
circuits = ref_measure.measure_circuits_deterministic(
allow_sampling=True)
targets = ref_measure.measure_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test conditional
# ---------------------------------------------------------------------
def test_conditional_gate_1bit(self):
"""Test conditional gates on 1-bit conditional register."""
circuits = ref_conditionals.conditional_circuits_1bit(
final_measure=False)
targets = ref_conditionals.conditional_statevector_1bit()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_conditional_unitary_1bit(self):
"""Test conditional unitaries on 1-bit conditional register."""
circuits = ref_conditionals.conditional_circuits_1bit(
final_measure=False, conditional_type='unitary')
targets = ref_conditionals.conditional_statevector_1bit()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_conditional_gate_2bit(self):
"""Test conditional gates on 2-bit conditional register."""
circuits = ref_conditionals.conditional_circuits_2bit(
final_measure=False)
targets = ref_conditionals.conditional_statevector_2bit()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_conditional_unitary_2bit(self):
"""Test conditional unitary on 2-bit conditional register."""
circuits = ref_conditionals.conditional_circuits_2bit(
final_measure=False, conditional_type='unitary')
targets = ref_conditionals.conditional_statevector_2bit()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test h-gate
# ---------------------------------------------------------------------
def test_h_gate_deterministic_default_basis_gates(self):
"""Test h-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.h_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_h_gate_deterministic_waltz_basis_gates(self):
"""Test h-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.h_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_h_gate_deterministic_minimal_basis_gates(self):
"""Test h-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.h_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_h_gate_nondeterministic_default_basis_gates(self):
"""Test h-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.h_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_h_gate_nondeterministic_waltz_basis_gates(self):
"""Test h-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.h_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_h_gate_nondeterministic_minimal_basis_gates(self):
"""Test h-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.h_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test x-gate
# ---------------------------------------------------------------------
def test_x_gate_deterministic_default_basis_gates(self):
"""Test x-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.x_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.x_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_x_gate_deterministic_waltz_basis_gates(self):
"""Test x-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.x_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.x_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_x_gate_deterministic_minimal_basis_gates(self):
"""Test x-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.x_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.x_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test z-gate
# ---------------------------------------------------------------------
def test_z_gate_deterministic_default_basis_gates(self):
"""Test z-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.z_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.z_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_z_gate_deterministic_waltz_basis_gates(self):
"""Test z-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.z_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.z_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_z_gate_deterministic_minimal_basis_gates(self):
"""Test z-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.z_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.z_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test y-gate
# ---------------------------------------------------------------------
def test_y_gate_deterministic_default_basis_gates(self):
"""Test y-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.y_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.y_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_y_gate_deterministic_waltz_basis_gates(self):
"""Test y-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.y_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.y_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_y_gate_deterministic_minimal_basis_gates(self):
"""Test y-gate gate circuits compiling to u3, cx."""
circuits = ref_1q_clifford.y_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.y_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test s-gate
# ---------------------------------------------------------------------
def test_s_gate_deterministic_default_basis_gates(self):
"""Test s-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.s_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.s_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_s_gate_deterministic_waltz_basis_gates(self):
"""Test s-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.s_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.s_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_s_gate_deterministic_minimal_basis_gates(self):
"""Test s-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.s_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.s_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_s_gate_nondeterministic_default_basis_gates(self):
"""Test s-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.s_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.s_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_s_gate_nondeterministic_waltz_basis_gates(self):
"""Test s-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.s_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.s_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_s_gate_nondeterministic_minimal_basis_gates(self):
"""Test s-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.s_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.s_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test sdg-gate
# ---------------------------------------------------------------------
def test_sdg_gate_deterministic_default_basis_gates(self):
"""Test sdg-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.sdg_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.sdg_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_sdg_gate_deterministic_waltz_basis_gates(self):
"""Test sdg-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.sdg_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.sdg_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_sdg_gate_deterministic_minimal_basis_gates(self):
"""Test sdg-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.sdg_gate_circuits_deterministic(
final_measure=False)
targets = ref_1q_clifford.sdg_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_sdg_gate_nondeterministic_default_basis_gates(self):
"""Test sdg-gate circuits compiling to backend default basis_gates."""
circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_sdg_gate_nondeterministic_waltz_basis_gates(self):
"""Test sdg-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_sdg_gate_nondeterministic_minimal_basis_gates(self):
"""Test sdg-gate gate circuits compiling to u3,cx"""
circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.sdg_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test cx-gate
# ---------------------------------------------------------------------
def test_cx_gate_deterministic_default_basis_gates(self):
"""Test cx-gate circuits compiling to backend default basis_gates."""
circuits = ref_2q_clifford.cx_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.cx_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cx_gate_deterministic_waltz_basis_gates(self):
"""Test cx-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_2q_clifford.cx_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.cx_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cx_gate_deterministic_minimal_basis_gates(self):
"""Test cx-gate gate circuits compiling to u3,cx"""
circuits = ref_2q_clifford.cx_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.cx_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cx_gate_nondeterministic_default_basis_gates(self):
"""Test cx-gate circuits compiling to backend default basis_gates."""
circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.cx_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cx_gate_nondeterministic_waltz_basis_gates(self):
"""Test cx-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.cx_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cx_gate_nondeterministic_minimal_basis_gates(self):
"""Test cx-gate gate circuits compiling to u3,cx"""
circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.cx_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test cz-gate
# ---------------------------------------------------------------------
def test_cz_gate_deterministic_default_basis_gates(self):
"""Test cz-gate circuits compiling to backend default basis_gates."""
circuits = ref_2q_clifford.cz_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.cz_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cz_gate_deterministic_waltz_basis_gates(self):
"""Test cz-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_2q_clifford.cz_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.cz_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cz_gate_deterministic_minimal_basis_gates(self):
"""Test cz-gate gate circuits compiling to u3,cx"""
circuits = ref_2q_clifford.cz_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.cz_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cz_gate_nondeterministic_default_basis_gates(self):
"""Test cz-gate circuits compiling to backend default basis_gates."""
circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.cz_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cz_gate_nondeterministic_waltz_basis_gates(self):
"""Test cz-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.cz_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cz_gate_nondeterministic_minimal_basis_gates(self):
"""Test cz-gate gate circuits compiling to u3,cx"""
circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.cz_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test swap-gate
# ---------------------------------------------------------------------
def test_swap_gate_deterministic_default_basis_gates(self):
"""Test swap-gate circuits compiling to backend default basis_gates."""
circuits = ref_2q_clifford.swap_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.swap_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_swap_gate_deterministic_waltz_basis_gates(self):
"""Test swap-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_2q_clifford.swap_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.swap_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_swap_gate_deterministic_minimal_basis_gates(self):
"""Test swap-gate gate circuits compiling to u3,cx"""
circuits = ref_2q_clifford.swap_gate_circuits_deterministic(
final_measure=False)
targets = ref_2q_clifford.swap_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_swap_gate_nondeterministic_default_basis_gates(self):
"""Test swap-gate circuits compiling to backend default basis_gates."""
circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.swap_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_swap_gate_nondeterministic_waltz_basis_gates(self):
"""Test swap-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.swap_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_swap_gate_nondeterministic_minimal_basis_gates(self):
"""Test swap-gate gate circuits compiling to u3,cx"""
circuits = ref_2q_clifford.swap_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_2q_clifford.swap_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test t-gate
# ---------------------------------------------------------------------
def test_t_gate_deterministic_default_basis_gates(self):
"""Test t-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.t_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.t_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_t_gate_deterministic_waltz_basis_gates(self):
"""Test t-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.t_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.t_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_t_gate_deterministic_minimal_basis_gates(self):
"""Test t-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.t_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.t_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_t_gate_nondeterministic_default_basis_gates(self):
"""Test t-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.t_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.t_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_t_gate_nondeterministic_waltz_basis_gates(self):
"""Test t-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.t_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.t_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_t_gate_nondeterministic_minimal_basis_gates(self):
"""Test t-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.t_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.t_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test tdg-gate
# ---------------------------------------------------------------------
def test_tdg_gate_deterministic_default_basis_gates(self):
"""Test tdg-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.tdg_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.tdg_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_tdg_gate_deterministic_waltz_basis_gates(self):
"""Test tdg-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.tdg_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.tdg_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_tdg_gate_deterministic_minimal_basis_gates(self):
"""Test tdg-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.tdg_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.tdg_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_tdg_gate_nondeterministic_default_basis_gates(self):
"""Test tdg-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.tdg_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_tdg_gate_nondeterministic_waltz_basis_gates(self):
"""Test tdg-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.tdg_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_tdg_gate_nondeterministic_minimal_basis_gates(self):
"""Test tdg-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.tdg_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test ccx-gate
# ---------------------------------------------------------------------
def test_ccx_gate_deterministic_default_basis_gates(self):
"""Test ccx-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.ccx_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.ccx_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_ccx_gate_deterministic_waltz_basis_gates(self):
"""Test ccx-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.ccx_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.ccx_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_ccx_gate_deterministic_minimal_basis_gates(self):
"""Test ccx-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.ccx_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.ccx_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_ccx_gate_nondeterministic_default_basis_gates(self):
"""Test ccx-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.ccx_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_ccx_gate_nondeterministic_waltz_basis_gates(self):
"""Test ccx-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.ccx_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_ccx_gate_nondeterministic_minimal_basis_gates(self):
"""Test ccx-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.ccx_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test unitary gate qobj instruction
# ---------------------------------------------------------------------
def test_unitary_gate(self):
"""Test simulation with unitary gate circuit instructions."""
circuits = ref_unitary_gate.unitary_gate_circuits_deterministic(
final_measure=False)
targets = ref_unitary_gate.unitary_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_diagonal_gate(self):
"""Test simulation with diagonal gate circuit instructions."""
circuits = ref_diagonal_gate.diagonal_gate_circuits_deterministic(
final_measure=False)
targets = ref_diagonal_gate.diagonal_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test cu1 gate
# ---------------------------------------------------------------------
def test_cu1_gate_nondeterministic_default_basis_gates(self):
"""Test cu1-gate gate circuits compiling to default basis."""
circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.cu1_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cu1_gate_nondeterministic_waltz_basis_gates(self):
"""Test cu1-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.cu1_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cu1_gate_nondeterministic_minimal_basis_gates(self):
"""Test cu1-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.cu1_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.cu1_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test cswap-gate (Fredkin)
# ---------------------------------------------------------------------
def test_cswap_gate_deterministic_default_basis_gates(self):
"""Test cswap-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.cswap_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.cswap_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cswap_gate_deterministic_minimal_basis_gates(self):
"""Test cswap-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.cswap_gate_circuits_deterministic(
final_measure=True)
targets = ref_non_clifford.cswap_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cswap_gate_deterministic_waltz_basis_gates(self):
"""Test cswap-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.cswap_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.cswap_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cswap_gate_nondeterministic_default_basis_gates(self):
"""Test cswap-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.cswap_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cswap_gate_nondeterministic_minimal_basis_gates(self):
"""Test cswap-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.cswap_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cswap_gate_nondeterministic_waltz_basis_gates(self):
"""Test cswap-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.cswap_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_non_clifford.cswap_gate_statevector_nondeterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test cu3-gate (Fredkin)
# ---------------------------------------------------------------------
def test_cu3_gate_deterministic_default_basis_gates(self):
"""Test cu3-gate circuits compiling to backend default basis_gates."""
circuits = ref_non_clifford.cu3_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.cu3_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cu3_gate_deterministic_minimal_basis_gates(self):
"""Test cu3-gate gate circuits compiling to u3,cx"""
circuits = ref_non_clifford.cu3_gate_circuits_deterministic(
final_measure=True)
targets = ref_non_clifford.cu3_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
def test_cu3_gate_deterministic_waltz_basis_gates(self):
"""Test cu3-gate gate circuits compiling to u1,u2,u3,cx"""
circuits = ref_non_clifford.cu3_gate_circuits_deterministic(
final_measure=False)
targets = ref_non_clifford.cu3_gate_statevector_deterministic()
job = execute(circuits,
self.SIMULATOR,
shots=1,
basis_gates=['u1', 'u2', 'u3', 'cx'],
backend_options=self.BACKEND_OPTS)
result = job.result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets)
# ---------------------------------------------------------------------
# Test global phase
# ---------------------------------------------------------------------
def test_qobj_global_phase(self):
"""Test qobj global phase."""
circuits = ref_1q_clifford.h_gate_circuits_nondeterministic(
final_measure=False)
targets = ref_1q_clifford.h_gate_statevector_nondeterministic()
qobj = assemble(transpile(circuits, self.SIMULATOR),
shots=1, backend_options=self.BACKEND_OPTS)
# Set global phases
for i, _ in enumerate(circuits):
global_phase = (-1) ** i * (pi / 4)
qobj.experiments[i].header.global_phase = global_phase
targets[i] = exp(1j * global_phase) * targets[i]
result = self.SIMULATOR.run(qobj).result()
self.assertSuccess(result)
self.compare_statevector(result, circuits, targets, ignore_phase=False)
| [
2,
770,
2438,
318,
636,
286,
1195,
1984,
270,
13,
198,
2,
198,
2,
357,
34,
8,
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19764,
2864,
11,
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13,
198,
2,
198,
2,
770,
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318,
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739,
262,
24843,
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11,
10628,
362,
13,
15,
13,
921,
743,
198,
2,
7330... | 2.132409 | 27,755 |
# Generated by Django 3.0.8 on 2020-11-05 19:38
from django.db import migrations
| [
2,
2980,
515,
416,
37770,
513,
13,
15,
13,
23,
319,
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12,
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198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
628
] | 2.766667 | 30 |
"""Configuration for the test app."""
ADMIN_USERNAME = "admin"
ADMIN_EMAIL = "admin@localhost"
ADMIN_PASSWORD = "9V0aGfEGAkQTfn8GICqHjAqCzodsUL6IVp02GmtKML8"
BCRYPT_LOG_ROUNDS = 4
SECRET_KEY = "lzlD6LdPmLI6rX-4eEMUeLsIcnkXaDDQYqrAIKahsdY"
SQLALCHEMY_DATABASE_URI = "sqlite://"
SQLALCHEMY_TRACK_MODIFICATIONS = False
TESTING = True
| [
37811,
38149,
329,
262,
1332,
598,
526,
15931,
198,
2885,
23678,
62,
29904,
20608,
796,
366,
28482,
1,
198,
2885,
23678,
62,
27630,
4146,
796,
366,
28482,
31,
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1,
198,
2885,
23678,
62,
47924,
54,
12532,
796,
366,
24,
53,
15,
6... | 1.970238 | 168 |
import wx
import wx.lib.mixins.inspection
from pynput import mouse
import sys
import os
import colordistance.core as core
import colordistance.screen as screen
from colordistance.components import ColorSelector, DifferenceLine
from colordistance.util import assoc
class Application(wx.Frame):
"""
Entry point for the application.
This is a quick and dirty tool for grabbing pixel colors
from any location / program on the the screen and listing their
values and distances in various color spaces.
"""
def updateState(self, nextState):
"""
Update the main component's state and project new views to children.
"""
# propagate the new info to the children
self.state = nextState
for child in [self.leftSwatch, self.rightSwatch]:
props = nextState[child.id]
isSelected = nextState['selected'] == child.id
child.updateProps(assoc(core.colorspaces(props), 'selected', isSelected))
self.difference.updateProps(core.computeDiff(nextState))
def onExternalMouseClick(self, x, y, button, pressed):
"""
Unhooks the external mouse listener when a click is registered.
"""
if core.isListening(self.state):
self.stopInputListers()
def onExternalMouseMove(self, x, y):
"""
Update the selected swatch with the color found
at the current mouse coordinates.
"""
selected = self.state['selected']
rgb = screen.get_pixel(x, y)
self.updateState(core.updateColor(self.state, selected, rgb))
def onStartColorSelection(self, swatchId):
"""
Select the supplied Swatch and install a global mouse listener.
"""
self.updateState(core.selectSwatch(self.state, swatchId))
self.startInputListeners()
def startInputListeners(self):
"""
Start a mouse listener on a separate thread.
"""
if self.mouseListener:
self.mouseListener.stop()
# it's got some weird threading setup that
# requires it to be destroyed / recreated
self.mouseListener = mouse.Listener(on_click=self.onExternalMouseClick, on_move=self.onExternalMouseMove)
self.mouseListener.start()
def stopInputListers(self):
"""
Shut down the current listener
"""
self.mouseListener.stop()
if __name__ == '__main__':
run() | [
11748,
266,
87,
198,
11748,
266,
87,
13,
8019,
13,
19816,
1040,
13,
1040,
14978,
198,
6738,
279,
2047,
1996,
1330,
10211,
198,
198,
11748,
25064,
198,
198,
11748,
28686,
198,
198,
11748,
951,
585,
9311,
13,
7295,
355,
4755,
198,
11748... | 2.642241 | 928 |
n = '10.5'
print(n)
float(n)
print(n)
cadena = "Un numero podría ser " + str(10) + ' y un decimal podria ser ' + str(12.4)
print(cadena)
# CONVERSION DE UN NUMERO A BINARIO
print(bin(10))
# CONVERSION DE UN NUMERO A HEXADECIMAL
print(hex(13))
#CONVERSION DE UNA CADENA A BINARIO
print(int('0b1010', 2))
#CONVERSION DE UNA CADENA A HEXADECIMAL
print(int('0xd', 16))
#VALOR ABSOLUTO
print(abs(-10))
print(abs(10))
#REDONDEAR NUMEROS
print(round(5.5))
print(round(5.4))
# FUNCION EVAL
print(eval('2+6'))
numero = 30
print(eval('(numero *3 +15)/2'))
# FUNCION LEN(largo de una variable)
print(len('Hola soy un pythonizado'))
print(len([]))
#FUNCION HELP | [
77,
796,
705,
940,
13,
20,
6,
198,
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7,
77,
8,
198,
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7,
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8,
198,
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7,
77,
8,
198,
198,
66,
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796,
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3118,
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81,
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366,
1343,
965,
7,
940,
8,
1343,
705,
331,
555,
32465,
245... | 2.242321 | 293 |
#!/bin/python
print('I am:', __name__)
if __name__ == '__main__':
print(minmax(lessthan, 4, 2, 1, 5, 6, 3))
print(minmax(grtrthan, 4, 2, 1, 5, 6, 3))
| [
2,
48443,
8800,
14,
29412,
198,
198,
4798,
10786,
40,
716,
25,
3256,
11593,
3672,
834,
8,
198,
198,
361,
11593,
3672,
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6624,
705,
834,
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198,
220,
220,
220,
3601,
7,
1084,
9806,
7,
829,
301,
7637,
11,
604,
11,... | 2 | 80 |
""" Convert a PCF file into a VPR io.place file. """
from __future__ import print_function
import argparse
import sys
import vpr_place_constraints
import sqlite3
import lxml.etree as ET
if __name__ == '__main__':
main()
| [
37811,
38240,
257,
4217,
37,
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656,
257,
569,
4805,
33245,
13,
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198,
11748,
25064,
198,
11748,
410,
1050,
62,
5372,
62,
1102,
2536,
... | 2.974026 | 77 |
# -*- generated by 1.0.9 -*-
import da
PatternExpr_243 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('newtok')])
PatternExpr_255 = da.pat.TuplePattern([da.pat.ConstantPattern('request'), da.pat.FreePattern('c'), da.pat.FreePattern('p')])
PatternExpr_283 = da.pat.TuplePattern([da.pat.ConstantPattern('request'), da.pat.FreePattern('c'), da.pat.BoundPattern('_BoundPattern288_')])
PatternExpr_318 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern(None)])
PatternExpr_339 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('token1')])
PatternExpr_361 = da.pat.TuplePattern([da.pat.ConstantPattern('access'), da.pat.FreePattern('token2')])
PatternExpr_424 = da.pat.TuplePattern([da.pat.ConstantPattern('Done')])
PatternExpr_429 = da.pat.BoundPattern('_BoundPattern430_')
PatternExpr_431 = da.pat.TuplePattern([da.pat.FreePattern(None), da.pat.TuplePattern([da.pat.FreePattern(None), da.pat.FreePattern(None), da.pat.BoundPattern('_BoundPattern437_')]), da.pat.TuplePattern([da.pat.ConstantPattern('Done')])])
_config_object = {}
import sys
| [
2,
532,
9,
12,
7560,
416,
352,
13,
15,
13,
24,
532,
9,
12,
198,
11748,
12379,
198,
47546,
3109,
1050,
62,
26660,
796,
12379,
13,
8071,
13,
51,
29291,
47546,
26933,
6814,
13,
8071,
13,
3103,
18797,
47546,
10786,
15526,
33809,
12379,
... | 2.837563 | 394 |
import logging
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Tuple, cast
from bugout.app import Bugout
from bugout.data import BugoutResource
from moonstreamdb.blockchain import AvailableBlockchainType, get_label_model
from sqlalchemy import and_, or_, text
from sqlalchemy.orm import Query, Session, query_expression
from sqlalchemy.sql.expression import label
from .. import data
from ..stream_boundaries import validate_stream_boundary
from ..stream_queries import StreamQuery
logger = logging.getLogger(__name__)
logger.setLevel(logging.WARN)
ethereum_event_type = "ethereum_blockchain"
polygon_event_type = "polygon_blockchain"
allowed_tags = ["tag:erc721"]
description = f"""Event provider for transactions from the Ethereum blockchain.
To restrict your queries to this provider, add a filter of \"type:{ethereum_event_type}\{polygon_event_type}\" to your query (query parameter: \"q\") on the /streams endpoint."""
default_time_interval_seconds: int = 5 * 60
# 200 transactions per block, 4 blocks per minute.
estimated_events_per_time_interval: float = 5 * 800
@dataclass
@dataclass
@dataclass
@dataclass
EthereumMoonwormProvider = MoonwormProvider(
event_type="ethereum_smartcontract",
blockchain=AvailableBlockchainType("ethereum"),
description="Provider for resiving transactions from Ethereum tables.",
streamboaundary_range_limit=2 * 60 * 60,
)
PolygonMoonwormProvider = MoonwormProvider(
event_type="polygon_smartcontract",
blockchain=AvailableBlockchainType("polygon"),
description="Provider for resiving transactions from Polygon tables.",
streamboaundary_range_limit=2 * 60 * 60,
)
| [
11748,
18931,
198,
6738,
4818,
330,
28958,
1330,
4818,
330,
31172,
11,
2214,
198,
6738,
19720,
1330,
4377,
11,
360,
713,
11,
7343,
11,
32233,
11,
309,
29291,
11,
3350,
198,
198,
6738,
5434,
448,
13,
1324,
1330,
15217,
448,
198,
6738,
... | 3.34585 | 506 |
from typing import Dict, List, Set, Callable
# https://github.com/cilium/cilium/blob/master/pkg/identity/numericidentity.go#L33
reserved_identities = {
0: ["reserved:unknown"],
1: ["reserved:host"],
2: ["reserved:world"],
3: ["reserved:cluster"],
4: ["reserved:health"],
5: ["reserved:init"]
}
class EndpointResolver:
"""EndpointResolver resolves various fields to the pod-name
endpoint_data: a list of lists of endpoint objects obtained from
cilium-agent or k8s CEPs
"""
def resolve_endpoint_ids(self, selectors: List[str],
pod_names: List[str],
ips: List[str],
namespace: str) -> Set[int]:
"""resolve_endpoint_ids returns endpoint ids that match
selectors, pod names and ips provided
"""
ids = set()
ids.update(
self.resolve_endpoint_ids_from_pods(pod_names),
self.resolve_endpoint_ids_from_selectors(selectors, namespace),
self.resolve_endpoint_ids_from_ips(ips)
)
return ids
| [
6738,
19720,
1330,
360,
713,
11,
7343,
11,
5345,
11,
4889,
540,
628,
198,
2,
3740,
1378,
12567,
13,
785,
14,
2856,
1505,
14,
2856,
1505,
14,
2436,
672,
14,
9866,
14,
35339,
14,
738,
414,
14,
77,
39223,
738,
414,
13,
2188,
2,
43,... | 2.137143 | 525 |
########
# Copyright (c) 2014 GigaSpaces Technologies Ltd. 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.
############
import unittest
import threading
import json
import uuid
import time
import pika
from influxdb.influxdb08 import InfluxDBClient
from amqp_influxdb import (InfluxDBPublisher,
AMQPTopicConsumer)
influx_database = 'influx'
amqp_exchange = 'exchange'
routing_key = 'routing_key'
| [
7804,
198,
2,
15069,
357,
66,
8,
1946,
402,
13827,
4561,
2114,
21852,
12052,
13,
1439,
2489,
10395,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
4... | 3.256849 | 292 |
print("<!DOCTYPE html><html><body>")
# arr =[[0, 152, 17, 252, 146, 88], [1, 260, 335, 63, 44, 17], [2, 53, 72, 130, 24, 80], [3, 352, 178, 32, 30, 287], [4, 80, 24, 17, 77, 28], [5, 85, 79, 276, 158, 63], [6, 376, 85, 16, 251, 382], [7, 17, 378, 16, 376, 384], [8, 79, 180, 183, 362, 85], [9, 80, 28, 17, 11, 36], [10, 33, 3, 25, 53, 152], [11, 28, 77, 80, 25, 85], [12, 6, 17, 378, 376, 16], [13, 210, 160, 356, 168, 63], [14, 362, 85, 125, 97, 118], [15, 25, 78, 353, 53, 43], [16, 251, 376, 382, 85, 6], [17, 80, 297, 152, 373, 75], [18, 360, 246, 377, 20, 347], [19, 104, 85, 362, 116, 125], [20, 347, 28, 374, 160, 53], [21, 14, 160, 35, 80, 28], [22, 85, 382, 258, 251, 79], [23, 24, 53, 78, 80, 28], [24, 80, 53, 130, 64, 72], [25, 160, 53, 74, 28, 130], [26, 371, 63, 88, 279, 145], [27, 30, 325, 37, 25, 210], [28, 25, 160, 14, 356, 8], [29, 371, 362, 118, 104, 125], [30, 61, 3, 32, 51, 76], [31, 181, 21, 294, 241, 43], [32, 76, 52, 3, 61, 30], [33, 53, 68, 130, 25, 24], [34, 89, 29, 246, 54, 48], [35, 371, 362, 125, 85, 14], [36, 28, 297, 14, 80, 16], [37, 90, 25, 368, 42, 48], [38, 63, 217, 44, 211, 39], [39, 45, 63, 61, 44, 46], [40, 17, 80, 25, 260, 152], [41, 63, 44, 276, 208, 61], [42, 368, 104, 22, 362, 48], [43, 25, 42, 54, 48, 89], [44, 63, 61, 276, 173, 335], [45, 39, 63, 44, 6, 386], [46, 63, 39, 61, 176, 276], [47, 347, 87, 95, 342, 80], [48, 54, 354, 368, 355, 34], [49, 80, 24, 75, 130, 53], [50, 63, 386, 83, 171, 192], [51, 30, 25, 352, 325, 160], [52, 32, 76, 337, 61, 63], [53, 130, 24, 25, 72, 80], [54, 48, 34, 89, 362, 368], [55, 178, 348, 3, 287, 352], [56, 80, 17, 75, 258, 8], [57, 42, 368, 158, 371, 116], [58, 118, 16, 22, 251, 297], [59, 80, 53, 130, 24, 363], [60, 67, 348, 287, 242, 55], [61, 63, 30, 335, 32, 52], [62, 297, 364, 6, 16, 251], [63, 44, 61, 39, 276, 371], [64, 24, 80, 53, 130, 78], [65, 382, 79, 258, 85, 22], [66, 71, 61, 260, 17, 81], [67, 60, 348, 242, 287, 178], [68, 53, 24, 130, 78, 80], [69, 85, 14, 77, 362, 97], [70, 80, 17, 49, 56, 130], [71, 343, 6, 45, 386, 376], [72, 53, 130, 2, 24, 80], [73, 6, 92, 343, 365, 105], [74, 25, 160, 28, 53, 80], [75, 258, 362, 80, 359, 17], [76, 32, 52, 61, 30, 63], [77, 80, 345, 85, 342, 22], [78, 80, 53, 24, 130, 68], [79, 85, 276, 125, 180, 153], [80, 24, 53, 130, 17, 78], [81, 28, 25, 160, 15, 11], [82, 168, 8, 210, 152, 160], [83, 79, 8, 276, 90, 356], [84, 25, 160, 28, 362, 61], [85, 79, 125, 382, 22, 276], [86, 80, 28, 347, 85, 297], [87, 80, 77, 342, 25, 47], [88, 17, 160, 350, 152, 278], [89, 256, 34, 189, 25, 368], [90, 25, 37, 53, 83, 28], [91, 22, 114, 128, 79, 258], [92, 376, 6, 73, 292, 229], [93, 80, 24, 53, 130, 78], [94, 364, 44, 17, 215, 297], [95, 80, 347, 20, 47, 28], [96, 25, 89, 42, 116, 368], [97, 362, 14, 371, 85, 104], [98, 25, 368, 104, 362, 116], [99, 107, 85, 341, 6, 297], [100, 16, 297, 17, 264, 315], [101, 20, 160, 25, 3, 34], [102, 145, 17, 88, 279, 371], [103, 25, 134, 43, 85, 320], [104, 118, 79, 116, 362, 180], [105, 112, 376, 16, 79, 251], [106, 241, 34, 22, 42, 294], [107, 123, 99, 386, 376, 85], [108, 195, 160, 328, 249, 123], [109, 364, 125, 294, 355, 241], [110, 28, 85, 160, 297, 11], [111, 29, 371, 104, 362, 355], [105, 112, 376, 16, 79, 251], [113, 158, 77, 83, 85, 256], [114, 79, 85, 125, 252, 8], [115, 34, 368, 246, 54, 161], [116, 118, 104, 362, 371, 180], [117, 211, 351, 22, 285, 336], [118, 125, 180, 116, 79, 104], [119, 85, 79, 125, 382, 22], [120, 17, 58, 376, 16, 384], [121, 160, 158, 362, 63, 347], [122, 153, 191, 79, 272, 125], [123, 107, 167, 160, 124, 290], [124, 63, 44, 123, 158, 276], [125, 79, 85, 276, 118, 333], [126, 377, 162, 160, 89, 256], [127, 290, 302, 124, 90, 295], [128, 91, 252, 79, 180, 328], [129, 297, 85, 16, 22, 376], [130, 53, 24, 80, 72, 25], [131, 63, 125, 85, 44, 158], [188, 132, 282, 246, 8, 372], [133, 284, 155, 252, 374, 247], [134, 34, 54, 246, 48, 25], [135, 251, 307, 6, 297, 77], [136, 299, 8, 114, 79, 83], [137, 85, 371, 251, 297, 382], [138, 125, 22, 79, 382, 85], [139, 374, 231, 160, 79, 166], [140, 63, 377, 44, 276, 215], [141, 42, 368, 241, 43, 89], [142, 79, 85, 276, 125, 153], [143, 114, 160, 337, 299, 252], [144, 44, 354, 127, 310, 63], [145, 160, 180, 371, 79, 25], [146, 359, 114, 351, 344, 289], [147, 114, 85, 382, 160, 133], [148, 158, 77, 161, 295, 106], [149, 46, 89, 63, 195, 82], [150, 44, 63, 371, 85, 158], [151, 63, 276, 44, 211, 176], [152, 17, 160, 297, 28, 130], [153, 79, 125, 85, 180, 276], [154, 263, 45, 44, 173, 171], [155, 133, 252, 166, 160, 139], [156, 63, 61, 44, 151, 217], [157, 345, 313, 85, 297, 382], [158, 79, 125, 85, 276, 371], [159, 367, 125, 8, 369, 353], [160, 25, 53, 28, 356, 8], [161, 104, 158, 362, 116, 8], [162, 195, 368, 115, 263, 54], [163, 377, 77, 20, 80, 342], [164, 85, 79, 382, 251, 22], [165, 79, 22, 114, 85, 180], [166, 160, 139, 252, 168, 374], [167, 206, 160, 20, 123, 270], [168, 82, 160, 210, 374, 8], [169, 51, 30, 43, 61, 25], [170, 297, 264, 80, 351, 363], [171, 44, 63, 158, 386, 240], [172, 190, 114, 63, 39, 163], [173, 44, 17, 63, 297, 215], [174, 290, 153, 85, 158, 256], [175, 290, 363, 17, 247, 211], [176, 63, 8, 350, 151, 85], [177, 251, 16, 376, 297, 308], [178, 3, 287, 352, 55, 348], [179, 160, 25, 8, 80, 362], [180, 79, 8, 85, 118, 125], [181, 44, 31, 63, 158, 276], [182, 166, 152, 160, 82, 168], [183, 79, 8, 125, 85, 180], [184, 25, 368, 256, 187, 153], [185, 303, 85, 238, 297, 382], [186, 79, 160, 180, 8, 374], [187, 160, 371, 25, 368, 256], [188, 132, 282, 246, 8, 372], [189, 89, 48, 104, 42, 118], [190, 172, 85, 297, 238, 215], [191, 367, 125, 114, 136, 321], [192, 44, 288, 5, 90, 158], [193, 359, 114, 225, 345, 297], [194, 125, 258, 79, 85, 22], [195, 160, 256, 371, 328, 263], [196, 386, 378, 17, 6, 16], [197, 255, 125, 297, 226, 262], [198, 82, 79, 20, 114, 374], [199, 359, 336, 152, 146, 161], [200, 183, 125, 85, 44, 158], [201, 203, 295, 199, 297, 17], [202, 377, 224, 211, 114, 136], [203, 201, 17, 297, 175, 295], [204, 98, 42, 25, 371, 368], [205, 263, 297, 77, 158, 17], [206, 374, 20, 167, 389, 160], 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321.7530108639234, 321.7607807051692]], [[328, 0, 239, 10, 67, 60], [0.0, 215.46229368499723, 216.34463247328324, 220.14086399394367, 220.54704713507275, 220.97284901091356]], [[329, 239, 0, 67, 60, 10], [0.0, 211.1989583307645, 212.02358359390118, 216.96313050838845, 217.51551668789057, 217.9587116864109]], [[330, 0, 239, 10, 67, 60], [0.0, 176.4822937294277, 177.87355059142436, 183.06829326784035, 183.14748155516637, 183.4747939091362]], [[331, 0, 239, 10, 67, 60], [0.0, 276.5736791525904, 278.5964823898536, 281.09606898709916, 281.3289889080043, 281.47824072208493]], [[332, 0, 239, 67, 10, 60], [0.0, 222.93272527827762, 222.9484245290825, 227.41591852814526, 227.56757238235855, 227.86399452304877]], [[333, 239, 0, 79, 42, 348], [0.0, 266.61957917602376, 268.47159998778267, 268.72662689060047, 270.138853184802, 271.66523517005265]], [[334, 0, 239, 60, 67, 10], [0.0, 153.18942522250026, 153.32318807016765, 158.5812094795597, 158.62534475927862, 158.83639381451596]], [[335, 0, 239, 67, 60, 352], [0.0, 253.81292323284092, 254.86074629098925, 256.4995126701024, 256.9591407208547, 257.1575392633862]], [[336, 0, 239, 10, 67, 60], [0.0, 251.13741258522197, 252.76273459511393, 256.1093516449565, 256.4039781282654, 256.5365471039166]], [[337, 0, 239, 67, 60, 10], [0.0, 174.4820907715173, 177.1863425888124, 180.0583238842348, 180.34688796871433, 180.5602392554906]], [[338, 239, 0, 67, 60, 348], [0.0, 215.03255567471638, 216.64717861075414, 220.44727260730625, 220.96379793984352, 221.14022700540036]], [[339, 0, 239, 67, 60, 10], [0.0, 263.79347982844456, 265.2998303806469, 267.9813426341468, 268.13429471069156, 268.2517474314007]], [[340, 0, 239, 67, 60, 10], [0.0, 202.52407264322926, 202.94580557380337, 207.73300171133135, 208.00240383226344, 208.0672968056249]], [[341, 239, 348, 0, 33, 67], [0.0, 348.3073355529567, 350.01714243733835, 350.22135857197514, 350.2984441872387, 350.7648785155093]], [[342, 239, 33, 0, 60, 10], [0.0, 277.65626231007286, 277.9568311806709, 278.3271456398028, 279.50491945581206, 279.5138636991017]], [[343, 0, 239, 10, 67, 60], [0.0, 458.0589481715208, 458.94770943975743, 460.72551481332135, 460.9566140104728, 461.015184131716]], [[344, 0, 239, 10, 67, 60], [0.0, 247.33580412063273, 247.7579463912308, 251.25087064525766, 251.46371507635052, 252.01190448072091]], [[345, 0, 239, 10, 60, 67], [0.0, 292.12839642869363, 293.5166094107793, 295.9138388112323, 296.2127613726323, 296.28027271487383]], [[346, 387, 0, 239, 67, 10], [0.0, 0.0, 307.3694844970789, 307.77751704762323, 310.6557580345164, 311.20732639190874]], [[347, 0, 239, 60, 67, 10], [0.0, 256.55798564846896, 256.7430622236948, 258.26149538791105, 258.55947091530027, 258.7817613356861]], [[348, 0, 67, 60, 239, 10], [0.0, 82.50454532933323, 82.64381404557754, 84.78207357690657, 88.40814442120137, 94.39809320108114]], [[349, 0, 239, 10, 67, 60], [0.0, 254.76655981505894, 255.6384165183316, 259.5765782962708, 259.5939136420575, 259.8518808860155]], [[350, 0, 239, 10, 67, 60], [0.0, 235.85164828764712, 237.11811402758752, 240.8485000991287, 240.9502023240487, 241.2156711327023]], [[351, 0, 239, 67, 348, 60], [0.0, 332.02861322482437, 332.1144381083123, 334.1376961673136, 334.36207918961145, 334.4248794572557]], [[352, 0, 239, 67, 60, 10], [0.0, 106.91585476438937, 108.7382177525455, 110.91438139393827, 111.6870628139177, 113.86395390991831]], [[353, 239, 0, 10, 33, 60], [0.0, 202.3635342644519, 203.43549346168678, 207.06037766796427, 207.64392598869827, 208.0264406271472]], [[354, 239, 0, 67, 60, 48], [0.0, 224.68199749868702, 226.04645540242387, 229.59965156767987, 229.95651762887695, 230.31065976198323]], [[355, 239, 42, 34, 0, 89], [0.0, 246.23972059763227, 247.69134017966798, 248.03628766775236, 248.23980341597115, 249.85795964907743]], [[356, 239, 0, 67, 10, 60], [0.0, 218.0619178123498, 218.26589289213283, 222.12383933292708, 222.46797522340154, 222.50617968946392]], [[357, 0, 239, 10, 67, 60], [0.0, 179.5995545651492, 180.4632926664035, 185.18099254513137, 185.52897347853784, 185.94891771666755]], [[358, 0, 239, 67, 60, 10], [0.0, 202.37835852679504, 203.90684147423792, 207.8076033257686, 207.9326814139615, 208.27145747797513]], [[359, 0, 239, 10, 67, 60], [0.0, 269.6182486405547, 270.42004363582225, 273.492230236985, 273.57814240176424, 274.27540903259995]], [[360, 0, 239, 10, 67, 60], [0.0, 196.43574012892867, 196.6011190202131, 200.70127054904262, 201.12185361118767, 201.6829194552677]], [[361, 0, 239, 67, 60, 10], [0.0, 182.09063677191094, 182.8879438344693, 187.1416575752176, 187.7391807801451, 188.03988938520465]], [[362, 42, 34, 239, 54, 89], [0.0, 258.47630452325797, 261.0383113644432, 262.16216355530787, 263.19764436635825, 263.24133414036635]], [[363, 0, 239, 67, 10, 60], [0.0, 321.69084537798085, 321.8105032468642, 324.6413405590853, 324.8491957816734, 324.93076185550666]], [[364, 0, 239, 10, 67, 60], [0.0, 223.5329953273118, 224.88219138028694, 228.9475922563939, 229.05021283552654, 229.23350540442382]], [[365, 0, 239, 67, 10, 60], [0.0, 444.285943959518, 444.5323385311804, 446.6911684822076, 446.89148570989806, 446.99776285793644]], [[366, 0, 239, 67, 60, 10], [0.0, 206.9081922012756, 207.92787210953705, 211.48522407014633, 211.68372634664195, 211.7616584748051]], [[367, 0, 239, 10, 67, 60], [0.0, 201.06715296139248, 202.06682063119615, 206.15528128088303, 206.26924152669974, 206.96618081222834]], [[368, 239, 42, 0, 67, 294], [0.0, 202.06434618705003, 202.89652535221, 203.11326889201504, 207.340299990137, 207.88698852982597]], [[369, 0, 239, 67, 60, 10], [0.0, 153.30688177638993, 154.92578868606736, 160.08122938058665, 160.59887919907786, 161.03105290595352]], [[370, 0, 239, 10, 67, 60], [0.0, 141.13468744429912, 142.53420642077467, 148.39474384222643, 148.95636945092346, 148.96308267486947]], [[371, 42, 89, 34, 104, 180], [0.0, 287.34648075102643, 287.43694960808364, 287.61606352914293, 288.43716820132596, 289.76369682898513]], [[372, 0, 239, 10, 67, 60], [0.0, 193.5794410571536, 194.6997688750554, 199.55199823604875, 199.81991892701788, 200.29478275781423]], [[373, 0, 239, 10, 67, 60], [0.0, 280.9644105576363, 282.86392488261913, 283.58596580225895, 284.66120213334307, 284.9666647171209]], [[374, 0, 239, 67, 10, 60], [0.0, 236.68967024354907, 236.70023236152517, 239.65183078791617, 239.70398411373975, 239.73109935926126]], [[375, 0, 239, 10, 67, 60], [0.0, 158.52444606432158, 159.06916734552928, 162.77591959500643, 163.78949905290023, 164.3198101264726]], [[376, 251, 42, 79, 239, 382], [0.0, 468.5242789866924, 468.7355331100897, 470.11487957732203, 472.84458334636764, 473.5894846805617]], [[377, 34, 239, 0, 42, 348], [0.0, 306.7034398242054, 306.9934852728963, 308.6000648088072, 308.7458501745408, 309.42042595795124]], [[378, 0, 239, 10, 67, 60], [0.0, 513.5231250878581, 513.9581695040949, 515.7402446968823, 515.7664200003719, 516.2354114161484]], [[379, 0, 239, 67, 10, 60], [0.0, 172.73679399595213, 174.92569851225406, 179.51323071016242, 179.91664736760742, 180.13050824332896]], [[380, 0, 239, 10, 67, 60], [0.0, 305.31786714832134, 306.52895458667524, 308.9158461458395, 309.434968935316, 309.5803611342296]], [[381, 0, 239, 10, 67, 60], [0.0, 231.8296788592867, 232.09049959013834, 236.17154782064668, 236.32604596192948, 236.7023447285641]], [[382, 79, 239, 42, 0, 180], [0.0, 280.4050641482782, 295.97128239070764, 296.0912021658192, 298.328677803526, 299.85829986845454]], [[383, 239, 0, 60, 10, 67], [0.0, 178.01685313475238, 178.64769799804307, 183.9347710466947, 184.23083346714796, 184.39088914585776]], [[384, 0, 239, 10, 60, 67], [0.0, 374.00802130435653, 374.626480644388, 376.16485747608056, 376.4080232938719, 376.5169318901874]], [[385, 79, 0, 239, 67, 60], [0.0, 288.2845816203149, 295.6163053689698, 296.81307248839295, 299.6164214458213, 299.7565679013556]], [[386, 42, 239, 0, 348, 67], [0.0, 565.054864592811, 566.1218950014211, 566.816548805696, 567.8485713638804, 567.982394093338]], [[346, 387, 0, 239, 67, 10], [0.0, 0.0, 307.3694844970789, 307.77751704762323, 310.6557580345164, 311.20732639190874]], [[388, 0, 239, 67, 60, 10], [0.0, 384.56728930058523, 385.5295060044043, 387.33577165038605, 387.50096774072705, 387.78086595395604]], [[389, 79, 239, 0, 42, 180], [0.0, 308.8705230351385, 311.9471109018322, 313.4230368048909, 313.8630274498734, 314.19579882614596]]]
#only on material count
# arr = [[[0, 13, 342, 303, 304, 335], [0.0, 9687.418541593008, 11335.890084153074, 11408.62406252393, 11560.403323413937, 11634.421085726612]], [[1, 6, 126, 25, 28, 3], [0.0, 8013.441208369847, 8492.494333233317, 11592.527075663873, 12147.094632050908, 12305.700630195746]], [[2, 159, 223, 281, 194, 257], [0.0, 42330.0846207517, 42776.655502738875, 43067.1848975528, 43157.37998303419, 43842.620667565025]], [[3, 69, 19, 33, 25, 92], [0.0, 5559.671842833892, 5840.552627962528, 7440.9936164466635, 8466.559986204551, 8515.833429559318]], [[4, 15, 6, 10, 126, 42], [0.0, 10411.519485646655, 10939.462601060437, 11086.787902724576, 11756.45422735954, 11958.056781935768]], [[46, 5, 214, 284, 242, 84], [0.0, 0.0, 12249.800284086268, 12582.802112407237, 12713.466757733706, 12732.93029903172]], [[6, 126, 15, 1, 28, 298], [0.0, 4320.728410812232, 6204.547364635071, 8013.441208369847, 8310.608521642684, 8578.706429293405]], [[7, 116, 109, 59, 104, 82], [0.0, 1523.9622698741593, 1576.8414631788448, 1597.5847395365292, 2123.8589877861477, 2176.944877574993]], [[8, 342, 339, 224, 172, 304], [0.0, 11182.32846950938, 11263.541538965443, 11553.886186041475, 11602.16178132334, 11692.529281554098]], [[9, 338, 163, 177, 38, 195], [0.0, 6997.112833161975, 7586.394400504102, 7645.985024834929, 7847.491446315823, 8485.491618050188]], [[10, 22, 23, 269, 171, 4], [0.0, 7164.204212611475, 8537.159890736497, 10800.238284408359, 11073.824994102082, 11086.787902724576]], [[11, 288, 227, 116, 109, 52], [0.0, 2621.9345910987176, 3169.057904172784, 3768.365958873952, 3771.1162803604984, 4019.8308422121445]], [[12, 150, 29, 15, 67, 157], [0.0, 4709.397307511865, 5284.6540094882275, 5627.924039999119, 5806.233632915575, 6318.48929729251]], [[13, 343, 335, 345, 211, 303], [0.0, 5951.2965814182035, 6129.670953648328, 6142.810431716089, 6752.343000766475, 6863.08640481817]], [[14, 13, 374, 343, 68, 192], [0.0, 7616.510355799433, 7839.158245628162, 7952.340850340861, 8349.228826664174, 8369.972401388191]], [[15, 29, 150, 157, 261, 12], [0.0, 4580.116264899833, 4651.190815264409, 5157.209322879962, 5419.697039503223, 5627.924039999119]], [[16, 67, 366, 175, 29, 308], [0.0, 7992.256064466404, 8088.71528736177, 8351.43957650416, 8888.816906652988, 8956.038912376385]], [[17, 246, 318, 389, 351, 244], [0.0, 4257.849926899726, 4670.002462526118, 5181.607376094797, 5187.10275587442, 5222.22816429922]], [[18, 33, 338, 25, 198, 177], [0.0, 7210.427241155686, 9529.757656939655, 9535.327000161033, 9572.189874840553, 9629.55180680804]], [[19, 69, 360, 92, 188, 3], [0.0, 4394.241914141733, 5003.515164361951, 5200.561315858125, 5736.203709771821, 5840.552627962528]], [[20, 198, 83, 358, 49, 330], [0.0, 3713.035281275954, 3814.6120379404247, 3941.8316808306263, 4410.9700747114575, 4703.398771101595]], [[21, 118, 295, 15, 12, 164], [0.0, 8494.58386267391, 9156.790977192828, 10083.269856549512, 10200.36244454088, 10283.18914539648]], [[22, 10, 23, 96, 206, 171], [0.0, 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3317.714424117905, 3625.5839529653704]], [[30, 322, 75, 70, 244, 190], [0.0, 10439.649275718031, 11206.710623550516, 11379.98110718994, 11442.969894218895, 11474.894117158554]], [[31, 42, 157, 218, 265, 261], [0.0, 6102.832948721438, 6353.740787913841, 6589.431007302527, 6594.2898025488685, 6664.441311918052]], [[32, 12, 164, 240, 67, 150], [0.0, 15082.319881238429, 15905.230020342366, 16173.47414750461, 16493.565290742932, 16535.59312513464]], [[33, 19, 18, 69, 3, 92], [0.0, 7089.571707797305, 7210.427241155686, 7422.513523059422, 7440.9936164466635, 7595.967943586913]], [[34, 291, 100, 125, 81, 101], [0.0, 2590.221805174221, 2728.716181650265, 3586.776268461695, 4311.905379295793, 4426.0125395213245]], [[35, 65, 300, 41, 357, 71], [0.0, 87633.22626150426, 98196.75400948852, 112560.06614248235, 113816.118304922, 122259.17191360328]], [[36, 83, 49, 358, 353, 177], [0.0, 8800.677928432558, 9801.314299623291, 9858.485076318775, 9887.2882531056, 9918.656915127169]], [[37, 43, 149, 107, 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#2048
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#128
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#1024
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[2.384185791015625e-07, 0.039878129959106445, 0.04100000858306885, 0.0510176420211792, 0.060056328773498535, 0.06205320358276367]], [[346, 387, 315, 297, 248, 264], [0.0, 0.0, 0.03713566064834595, 0.040827035903930664, 0.04180556535720825, 0.04437363147735596]], [[388, 248, 297, 215, 264, 349], [0.0, 0.03383636474609375, 0.03570961952209473, 0.03682076930999756, 0.03712153434753418, 0.045649588108062744]], [[389, 247, 164, 151, 46, 163], [5.960464477539063e-08, 0.04677700996398926, 0.05047893524169922, 0.05546367168426514, 0.057257115840911865, 0.05798715353012085]]]
#1024 with more training
# arr = [[[0, 242, 287, 162, 304, 239], [0.0, 0.02417755126953125, 0.027088820934295654, 0.02874159812927246, 0.0384824275970459, 0.04332250356674194]], [[1, 362, 88, 74, 50, 40], [5.960464477539063e-08, 0.33329272270202637, 0.34015023708343506, 0.34056055545806885, 0.34303873777389526, 0.36730706691741943]], [[2, 46, 51, 79, 30, 39], [5.960464477539063e-08, 0.017279505729675293, 0.03309130668640137, 0.034694015979766846, 0.04400724172592163, 0.057182133197784424]], [[3, 67, 60, 0, 55, 89], [0.0, 0.1310710906982422, 0.13108831644058228, 0.14222025871276855, 0.1442035436630249, 0.15213382244110107]], [[4, 16, 73, 22, 23, 45], [0.0, 0.09508335590362549, 0.1786431074142456, 0.1863243579864502, 0.20590192079544067, 0.2099645733833313]], [[5, 93, 80, 36, 40, 38], [0.0, 0.28011244535446167, 0.2918214201927185, 0.2989855408668518, 0.3083920478820801, 0.31730449199676514]], [[6, 71, 66, 12, 92, 7], [0.0, 0.07704448699951172, 0.08678042888641357, 0.1544513702392578, 0.1649916172027588, 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#2048
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0.04128897190093994]], [[373, 331, 288, 25, 363, 69], [0.0, 0.03210270404815674, 0.04745805263519287, 0.049719810485839844, 0.05109107494354248, 0.05379456281661987]], [[374, 139, 231, 281, 304, 13], [0.0, 0.051259756088256836, 0.05210977792739868, 0.052222251892089844, 0.052236199378967285, 0.05283236503601074]], [[375, 76, 84, 30, 309, 210], [2.980232238769531e-07, 0.04639464616775513, 0.05475902557373047, 0.05500936508178711, 0.05542290210723877, 0.058007240295410156]], [[376, 229, 378, 45, 71, 92], [1.1920928955078125e-07, 0.05503499507904053, 0.05789291858673096, 0.0647956132888794, 0.0661664605140686, 0.06734025478363037]], [[377, 202, 163, 151, 176, 313], [0.0, 0.034522414207458496, 0.0456504225730896, 0.05094647407531738, 0.052927613258361816, 0.05370604991912842]], [[378, 229, 154, 96, 45, 71], [0.0, 0.027566850185394287, 0.0352669358253479, 0.03636223077774048, 0.037140846252441406, 0.03851675987243652]], [[379, 213, 304, 323, 289, 347], [0.0, 0.03827625513076782, 0.04258298873901367, 0.04601097106933594, 0.04618537425994873, 0.048440515995025635]], [[380, 262, 305, 100, 36, 226], [1.1920928955078125e-07, 0.06650638580322266, 0.08381253480911255, 0.09024930000305176, 0.09478932619094849, 0.09635621309280396]], [[381, 127, 118, 167, 177, 266], [1.1920928955078125e-07, 0.10467958450317383, 0.11471152305603027, 0.12158674001693726, 0.1332908272743225, 0.13792860507965088]], [[382, 208, 332, 24, 22, 41], [0.0, 0.09446132183074951, 0.1030498743057251, 0.10537409782409668, 0.10602927207946777, 0.10604262351989746]], [[383, 18, 49, 53, 143, 353], [0.0, 0.07739043235778809, 0.08003437519073486, 0.08219456672668457, 0.08422672748565674, 0.08482646942138672]], [[384, 386, 292, 16, 171, 305], [5.960464477539063e-08, 0.04579782485961914, 0.05793106555938721, 0.06560969352722168, 0.06700634956359863, 0.06717205047607422]], [[385, 85, 124, 150, 371, 250], [1.7881393432617188e-07, 0.060361623764038086, 0.07818859815597534, 0.07880616188049316, 0.08771222829818726, 0.0902637243270874]], [[386, 292, 384, 305, 99, 232], [0.0, 0.042023658752441406, 0.04579782485961914, 0.04854476451873779, 0.05754208564758301, 0.06365704536437988]], [[387, 346, 297, 315, 264, 248], [2.980232238769531e-07, 2.980232238769531e-07, 0.04432255029678345, 0.04545408487319946, 0.04711806774139404, 0.047833144664764404]], [[388, 248, 264, 215, 297, 341], [0.0, 0.037600159645080566, 0.03965330123901367, 0.04084932804107666, 0.04194521903991699, 0.047194480895996094]], [[389, 164, 247, 151, 46, 163], [1.7881393432617188e-07, 0.042870163917541504, 0.04697549343109131, 0.05527430772781372, 0.057344913482666016, 0.05813324451446533]]]
pred = [2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
,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
,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,2,2,2,1,1,1,1,1,1,1,2,1
,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2
,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2
,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2
,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2
,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2
,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2
,2,2,2,2,2,2,2,2,3,0,0,3,0,3,3,3,3,3,3,3,3,3,0,3,3,3,3,3,3,3,3,3,3,3,3,3,3
,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3]
title = "Nearest neighbors on Model 3 : 3D CNN 2048"
print("<h3>"+title+"</h3>"+"<br/><br/>")
print("<table style=\"width:100%\">")
print("<td>")
print("<b>Original</b>")
print("</td>")
print("<td>")
print("<b>Nearest neighbors</b>")
print("</td>")
for i in range(0, 390):
print("</tr>")
typ = []
print("<tr id=\"a"+str(i)+"\">")
for j in range(0, 5):
print("<td>")
print("<figure>")
print("<a href=\"#a"+str(arr[i][0][j])+"\">")
print("<img src=\"./"+ str(arr[i][0][j]+1)+".png\" alt='missing' >")
print("</a>")
print("<figcaption>")
if arr[i][0][j] < 97 :
print("Ancient, ")
elif arr[i][0][j] < 131:
print("Asian,")
elif arr[i][0][j] < 341:
print("Medieval, ")
else:
print("Modern,")
if pred[arr[i][0][j]] == 0:
print("Ancient")
if pred[arr[i][0][j]] == 1:
print("Asian")
if pred[arr[i][0][j]] == 2:
print("Medieval")
if pred[arr[i][0][j]] == 3:
print("Modern")
# if pred[i] == 0 :
# print("Ancient, Ancient")
# elif pred[i] == 1:
# print("Asian, Asian")
# elif pred[i] == 2:
# print("Medieval, Medieval")
# else:
# print("Modern, Modern")
if j!=0:
print(", Distance: "+str(arr[i][1][j]))
print("</figcaption>")
print("</figure>")
print("</td>")
print("</tr>")
print("</table>")
print("</body></html>") | [
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2,
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37144,
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15... | 2.045765 | 237,651 |
# Open the input file
with open("Prob07.in.txt", "rt") as inputFile:
# Read the number of test cases (trim out the newline)
cases = int(inputFile.readline().replace("\n", ""))
# For each test case
for caseNum in range(cases):
# Read the number of words
wordCount = int(inputFile.readline().replace("\n", ""))
nonPalindromes = []
# For each word
for j in range(wordCount):
word = inputFile.readline().replace("\n", "")
# compare each pair of letters, moving inward
for k in range(len(word) // 2):
if word[k].upper() != word[-(k + 1)].upper():
# if any are unequal, note the index of the word
nonPalindromes.append(j + 1)
break
# end for k
# end for j
if len(nonPalindromes) == 0:
# all were palindromes
print("True")
else:
# at least one wasn't
# specify end to suppress the automatic newline
print("False - ", end="")
first = True
# print each index
for index in nonPalindromes:
if not first:
# add commas as needed
print(", ", end="")
first = False
print(str(index), end="")
# now print a newline
print("")
| [
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286,
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2663,
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320,
503,
262,
649,
1370,
8,
... | 1.956698 | 739 |
import sys
import mock
import libvirt
import difflib
import unittest
from see.context.resources import vbox
def compare(text1, text2):
"""Utility function for comparing text and returining differences."""
diff = difflib.ndiff(text1.splitlines(True), text2.splitlines(True))
return '\n' + '\n'.join(diff)
| [
11748,
25064,
198,
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15290,
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9195,
48940,
198,
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814,
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628,
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8996,
7,
5239,
16,
11,
2420,
17,
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198,
220,
... | 3.018692 | 107 |
""" Modifications Copyright (c) 2019 Uber Technologies, Inc. """
import numpy as np
import cv2
import torch
import gym
import argparse
import os
import utils
import TD3
import OurDDPG
import D3G
import Standard_QSS
# Runs policy for X episodes and returns average reward
# A fixed seed is used for the eval environment
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--policy", default="TD3") # Policy name (TD3, DDPG or OurDDPG)
parser.add_argument("--env", default="HalfCheetah-v2") # OpenAI gym environment name
parser.add_argument("--save_dir", default=".") # OpenAI gym environment name
parser.add_argument("--seed", default=0, type=int) # Sets Gym, PyTorch and Numpy seeds
parser.add_argument("--start_timesteps", default=1e4, type=int) # Time steps initial random policy is used
parser.add_argument("--train_vae", default=1e4, type=int) # Time steps for training vae
parser.add_argument("--eval_freq", default=5e3, type=int) # How often (time steps) we evaluate
parser.add_argument("--max_timesteps", default=1e6, type=int) # Max time steps to run environment
parser.add_argument("--expl_noise", default=0.1, type=float) # Std of Gaussian exploration noise
parser.add_argument("--batch_size", default=256, type=int) # Batch size for both actor and critic
parser.add_argument("--discount", default=0.99) # Discount factor
parser.add_argument("--tau", default=0.005) # Target network update rate
parser.add_argument("--policy_noise", default=0.2) # Noise added to target policy during critic update
parser.add_argument("--noise_clip", default=0.5) # Range to clip target policy noise
parser.add_argument("--policy_freq", default=2, type=int) # Frequency of delayed policy updates
parser.add_argument("--save_model", action="store_true") # Save model and optimizer parameters
parser.add_argument("--visualize", action="store_true") # Visualize model predictions
parser.add_argument("--is_discrete", action="store_true") # Save model and optimizer parameters
parser.add_argument("--load_model", default="") # Model load file name, "" doesn't load, "default" uses file_name
args = parser.parse_args()
if args.load_model:
file_name = f"{args.policy}_{args.env}_{args.seed}"
else:
file_name = f"{args.policy}_{args.env}_{args.seed}"
print("---------------------------------------")
print(f"Policy: {args.policy}, Env: {args.env}, Seed: {args.seed}")
print("---------------------------------------")
results_dir = os.path.join(args.save_dir, "results")
models_dir = os.path.join(args.save_dir, "models")
if not os.path.exists(results_dir):
os.makedirs(results_dir)
if args.save_model and not os.path.exists(models_dir):
os.makedirs(models_dir)
env = make_env(args.env)
# Set seeds
env.seed(args.seed)
torch.manual_seed(args.seed)
np.random.seed(args.seed)
state_dim = env.observation_space.shape[0]
if args.is_discrete:
action_dim = env.action_space.n
max_action = float(action_dim)
else:
action_dim = env.action_space.shape[0]
max_action = float(env.action_space.high[0])
kwargs = {
"state_dim": state_dim,
"action_dim": action_dim,
"max_action": max_action,
"discount": args.discount,
"is_discrete": args.is_discrete,
"tau": args.tau,
}
# Initialize policy
if args.policy == "TD3":
# Target policy smoothing is scaled wrt the action scale
kwargs["policy_noise"] = args.policy_noise * max_action
kwargs["noise_clip"] = args.noise_clip * max_action
kwargs["policy_freq"] = args.policy_freq
policy = TD3.TD3(**kwargs)
elif args.policy == "OurDDPG":
policy = OurDDPG.DDPG(**kwargs)
elif args.policy == "D3G":
kwargs["policy_freq"] = args.policy_freq
policy = D3G.D3G(**kwargs)
elif args.policy == "Standard_QSS":
kwargs["policy_freq"] = args.policy_freq
policy = Standard_QSS.Standard_QSS(**kwargs)
if args.load_model != "":
policy_file = file_name if args.load_model == "default" else args.load_model
policy.load(f"{models_dir}/{policy_file}")
replay_buffer = utils.ReplayBuffer(state_dim, action_dim, args.is_discrete)
# Evaluate untrained policy
evaluations = [eval_policy(policy, args.env, args.seed)]
state, done = env.reset(), False
episode_reward = 0
episode_timesteps = 0
episode_num = 0
for t in range(int(args.max_timesteps)):
episode_timesteps += 1
# Select action randomly or according to policy
if t < args.start_timesteps:
action = env.action_space.sample()
elif args.is_discrete:
if np.random.uniform(0,1) < .1:
action = env.action_space.sample()
else:
action = policy.select_action(np.array(state))
else:
action = (
policy.select_action(np.array(state))
+ np.random.normal(0, max_action * args.expl_noise, size=action_dim)
).clip(-max_action, max_action)
# Perform action
next_state, reward, done, _ = env.step(action)
done_bool = float(done) if episode_timesteps < env._max_episode_steps else 0
# Store data in replay buffer
replay_buffer.add(state, action, next_state, reward, done_bool)
state = next_state
episode_reward += reward
if t >= args.start_timesteps:
policy.train(replay_buffer, args.batch_size)
if done:
# +1 to account for 0 indexing. +0 on ep_timesteps since it will increment +1 even if done=True
print(f"Total T: {t+1} Episode Num: {episode_num+1} Episode T: {episode_timesteps} Reward: {episode_reward:.3f}")
# Reset environment
state, done = env.reset(), False
episode_reward = 0
episode_timesteps = 0
episode_num += 1
# Evaluate episode
if (t + 1) % args.eval_freq == 0:
evaluation = eval_policy(policy, args.env, args.seed)
evaluations.append(evaluation)
np.save(f"{results_dir}/{file_name}", evaluations)
if args.visualize:
visualize(policy, args.env)
elif args.save_model: policy.save(f"{models_dir}/{file_name}")
| [
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357,
66,
8,
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12024,
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11,
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13,
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198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
269,
85,
17,
198,
11748,
28034,
198,
11748,
11550,
198,
11748,
1822,
29572,
198,
11748,
28686,
198,
198... | 2.048687 | 3,656 |
#https://docs.python.org/3/libraty/functions.html#open
#costumase usar o bloco try para abrir arquivos
try:
file = open('abc.txt', 'w+')
file.write('Linha')# o arquivo esta vazio entao escrevemos
file.seek(0)
print(file.read())
finally: #para garantir que o arquivo sera fechado se holver erro
file.close()
| [
2,
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1378,
31628,
13,
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13,
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14,
18,
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265,
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13,
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2,
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198,
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589,
514,
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450,
29283,
610,
421,
452,
418,
198,
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25,
1... | 2.235294 | 153 |
# --------------
#Importing header files
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
#Path of the file is stored in the variable path
#Code starts here
# Data Loading
data=pd.read_csv(path)
data.rename(columns={'Total':'Total_Medals'},inplace=True)
data.head(10)
# Summer or Winter
data['Better_Event'] = np.where(data['Total_Summer'] > data['Total_Winter'] , 'Summer', 'Winter')
data['Better_Event'] = np.where(data['Total_Summer'] == data['Total_Winter'] , 'Both',data['Better_Event'])
better_event=data['Better_Event'].value_counts().index.values[0]
# Top 10
top_countries=data[['Country_Name','Total_Summer', 'Total_Winter','Total_Medals']]
top_countries=top_countries[:-1]
print(top_countries.head())
# Plotting top 10
# Top Performing Countries
top_10_summer=top_ten(top_countries,'Total_Summer')
print("Top 10 Summer:\n",top_10_summer, "\n")
top_10_winter=top_ten(top_countries,'Total_Winter')
print("Top 10 Winter:\n",top_10_winter, "\n")
top_10=top_ten(top_countries,'Total_Medals')
print("Top 10:\n",top_10, "\n")
# Best in the world
common=list(set(top_10_summer) & set(top_10_winter) & set(top_10))
print('Common Countries :\n', common, "\n")
# Plotting the best
summer_df= data[data['Country_Name'].isin(top_10_summer)]
winter_df=data[data['Country_Name'].isin(top_10_winter)]
top_df=data[data['Country_Name'].isin(top_10)]
plt.figure(figsize=(20, 6))
plt.bar(summer_df['Country_Name'], summer_df['Total_Summer'])
plt.xlabel('Countries')
plt.ylabel('Total')
plt.title('Top Summer')
plt.figure(figsize=(20, 6))
plt.bar(winter_df['Country_Name'], winter_df['Total_Winter'])
plt.xlabel('Countries')
plt.ylabel('Total')
plt.title('Top Winter')
plt.figure(figsize=(20, 6))
plt.bar(top_df['Country_Name'], top_df['Total_Medals'])
plt.xlabel('Countries')
plt.ylabel('Total')
plt.title('Top overall')
#Top Performing Countries
summer_df['Golden_Ratio']=summer_df['Gold_Summer']/summer_df['Total_Summer']
summer_max_ratio=max(summer_df['Golden_Ratio'])
summer_country_gold=summer_df.loc[summer_df['Golden_Ratio'].idxmax(),'Country_Name']
winter_df['Golden_Ratio']=winter_df['Gold_Winter']/winter_df['Total_Winter']
winter_max_ratio=max(winter_df['Golden_Ratio'])
winter_country_gold=winter_df.loc[winter_df['Golden_Ratio'].idxmax(),'Country_Name']
top_df['Golden_Ratio']=top_df['Gold_Total']/top_df['Total_Medals']
top_max_ratio=max(top_df['Golden_Ratio'])
top_country_gold=top_df.loc[top_df['Golden_Ratio'].idxmax(),'Country_Name']
#Best In World
data_1=data[:-1]
data_1['Total_Points']= data_1['Gold_Total']*3 + data_1['Silver_Total']*2 + data_1['Bronze_Total']*1
most_points=max(data_1['Total_Points'])
best_country=data_1.loc[data_1['Total_Points'].idxmax(),'Country_Name']
#Plot the best
best=data[data['Country_Name']==best_country]
best.reset_index(drop = True, inplace = True)
best=best[['Gold_Total','Silver_Total','Bronze_Total']]
best.plot.bar(stacked=True)
plt.xlabel('United States')
plt.ylabel('Medals Tally')
plt.xticks(rotation=45)
l=plt.legend()
l.get_texts()[0].set_text('Gold_Total :' + str(best['Gold_Total'].values))
l.get_texts()[1].set_text('Silver_Total :' + str(best['Silver_Total'].values))
l.get_texts()[2].set_text('Bronze_Total :' + str(best['Bronze_Total'].values))
| [
2,
220,
26171,
198,
2,
20939,
278,
13639,
3696,
198,
11748,
19798,
292,
355,
279,
67,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2603,
29487,
8019,
13,
9078,
29487,
355,
458,
83,
198,
198,
2,
15235,
286,
262,
2393,
318,
8574,
2... | 2.533385 | 1,288 |
from typing import Union
welder = Position(name='Alex', surname='Murphy', position='welder', wage=120000, bonus=30000)
print(welder)
print(welder.get_full_name())
miller = Position(name='Anne', surname='Lewis', position='miller', wage=150000, bonus=24000)
print(miller)
print(miller.get_total_income())
| [
6738,
19720,
1330,
4479,
628,
628,
198,
732,
6499,
796,
23158,
7,
3672,
11639,
15309,
3256,
40358,
11639,
23830,
6883,
3256,
2292,
11639,
732,
6499,
3256,
7699,
28,
1065,
2388,
11,
7202,
28,
18,
2388,
8,
198,
4798,
7,
732,
6499,
8,
... | 2.990291 | 103 |
#!/usr/bin/env python3
# -*- coding: utf8
# obstacle2osm
# Converts aviation obstacles from Kartverket WFS/GML files for import/update in OSM
# Usage: obstacle2.osm [county]
# Creates OSM file with name "Luftfartshinder_" + county + ".osm"
import html
import time
import sys
import urllib.request
import json
import zipfile
from io import BytesIO
from xml.etree import ElementTree
import utm # Local library
version = "1.0.0"
# Tagging per obstacle type
tagging_table = {
'Landbruksutstyr': [],
'Telemast': ['man_made=mast', 'tower:type=communication'],
'Bru': ['man_made=tower', 'tower:type=bridge'],
'Bygning': ['building=yes'],
'Gondolbane': ['aerialway=gondola'],
u'Kontrolltårn': ['man_made=tower', 'tower:type=airport_control'],
u'Kjøletårn': ['man_made=tower', 'tower_type=cooling'],
'Kran': ['man_made=crane'],
'Demning': ['waterway=dam'],
'Kuppel': ['man_made=tower', 'tower:construction=dome'],
'EL_Nettstasjon': ['power=substation', 'power=transformer'],
'Gjerde': ['barrier=fence'],
u'Fyrtårn': ['man_made=lighthouse'],
'Monument': ['man_made=tower', 'tower:type=monument'],
'Terrengpunkt': ['natural=peak'],
'Navigasjonshjelpemiddel': ['aeroway=navigationaid'],
'Stolpe': ['man_made=mast'],
'Kraftverk': ['power=plant'],
'Raffineri': ['man_made=tower'],
'Oljerigg': [],
'Skilt': [],
'Pipe': ['man_made=chimney'],
'Tank': ['man_made=storage_tank'],
'Forankret ballong': [],
u'Tårn': ['man_made=tower'],
'Kraftledning': [],
'Tre': ['natural=tree'],
u'Skogsområde': ['natural=wood'],
u'Vanntårn': ['man_made=storage_tank', 'content=water'],
u'Vindmølle': ['power=generator', 'generator:source=wind', 'generator:method=wind_turbine', 'generator:type=horizontal_axis'],
u'Vindmøllepark': ['type=site', 'power=plant', 'plant:source=wind'],
u'Hopptårn': ['man_made=tower', 'piste:type=ski_jump'],
u'Vindmåler': ['man_made=mast', 'tower:type=monitoring'],
'Lysmast': ['man_made=mast', 'tower:type=lighting'],
'Flaggstang': ['man_made=flagpole'],
'Petroleumsinnretning': [],
'Silo': ['man_made=silo'],
'Stolheis': ['aerialway=chairlift'],
'Skitrekk': ['aerialway=draglift'],
'Taubane': ['aerialway=cable_car'],
u'Fornøyelsesparkinnretning': ['man_made=tower'],
'Annet': []
}
# Namespace
ns_gml = 'http://www.opengis.net/gml/3.2'
ns_xlink = 'http://www.w3.org/1999/xlink'
ns_app = 'http://skjema.geonorge.no/SOSI/produktspesifikasjon/Luftfartshindre/20180322'
ns = {
'gml': ns_gml,
'xlink': ns_xlink,
'app': ns_app
}
# Produce a tag for OSM file
# Main program
if __name__ == '__main__':
start_time = time.time()
today = time.strftime("%Y-%m-%d", time.localtime())
# Load county id's and names from Kartverket api
file = urllib.request.urlopen("https://ws.geonorge.no/kommuneinfo/v1/fylker")
county_data = json.load(file)
file.close()
county = {}
for coun in county_data:
county[coun['fylkesnummer']] = coun['fylkesnavn'].strip()
county['21'] = "Svalbard"
county['00'] = "Norge"
# Load obstacle gml from GeoNorge
if (len(sys.argv) > 1) and (sys.argv[1] in county):
county_id = sys.argv[1]
county_name = county[county_id].replace(u"Ø", "O").replace(u"ø", "o").replace(" ", "_")
if county_id == "21":
county_id = "2100" # Svalbard
elif county_id == "00":
county_id = "0000" # Norway
else:
sys.exit ("County code not found. Norway is '00'.")
print ("Loading %s..." % county_name)
url = "https://nedlasting.geonorge.no/geonorge/Samferdsel/Luftfartshindre/GML/Samferdsel_%s_%s_6173_Luftfartshindre_GML.zip" % (county_id, county_name)
in_file = urllib.request.urlopen(url)
zip_file = zipfile.ZipFile(BytesIO(in_file.read()))
filename = zip_file.namelist()[0]
file = zip_file.open(filename)
tree = ElementTree.parse(file)
file.close()
root = tree.getroot()
feature_collection = root
obstacles = []
# Pass 1:
# Find all point obstacles (excluding lines)
for feature_member in feature_collection.iter('{%s}featureMember' % ns_gml):
vertical_object = feature_member.find('app:VertikalObjekt', ns)
if vertical_object != None:
xlink = vertical_object.find(u'app:bestårAvVertikalobjKompPunkt', ns)
status = vertical_object.find('app:status', ns).text
valid_date = vertical_object.find('app:gyldigTil', ns)
if (xlink != None) and (status in ["E", "P"]) and ((valid_date == None) or (valid_date.text > today)):
xlink_ref = xlink.get('{%s}href' % ns_xlink)
update_date = vertical_object.find('app:oppdateringsdato', ns).text[:10]
name = vertical_object.find('app:vertikalObjektNavn', ns).text
object_id = vertical_object.find('app:identifikasjonObjekt/app:IdentifikasjonObjekt/app:lokalId', ns).text
object_type = vertical_object.find('app:vertikalObjektType', ns).text
obstacle = {
'status': status,
'date_update': update_date,
'type': object_type,
'name': name,
'ref:hinder': object_id,
'xlink': xlink_ref
}
create_date = vertical_object.find('app:datafangstdato', ns)
if create_date != None:
obstacle['date_create'] = create_date.text[:10]
if valid_date != None:
obstacle['date_valid'] = valid_date.text[:10]
obstacles.append(obstacle)
# Pass 2:
# Find obstacle coordinates
print ("Matching coordinates for %i obstacles..." % len(obstacles))
for feature_member in feature_collection.iter('{%s}featureMember' % ns_gml):
point = feature_member.find('app:VertikalObjektKomponentPunkt', ns)
if point != None:
point_id = point.get('{%s}id' % ns_gml)
for obstacle in obstacles:
if obstacle['xlink'] == point_id:
coordinates = point.find('app:posisjon/gml:Point/gml:pos', ns).text
coordinates_split = coordinates.split(" ")
x = float(coordinates_split[0])
y = float(coordinates_split[1])
z = float(coordinates_split[2])
latitude, longitude = utm.UtmToLatLon(x, y, 33, "N")
obstacle['latitude'] = latitude
obstacle['longitude'] = longitude
height = point.find('app:vertikalUtstrekning', ns)
if height != None:
height = float(height.text)
obstacle['height'] = "%.0f" % height
z_ref = point.find('app:href', ns).text
top_ele = None
if z_ref == "TOP":
if height != None:
z = z - height
else:
top_ele = z
z = None
if z:
if z == round(z,0):
obstacle['ele'] = "%.0f" % z
else:
obstacle['ele'] = "%.1f" % z
elif top_ele:
if top_ele == round(top_ele,0):
obstacle['top_ele'] = "%.0f" % top_ele
else:
obstacle['top_ele'] = "%.1f" % top_ele
light = point.find('app:lyssetting', ns).text
obstacle['light'] = light
break
# Pass 3:
# Output file
filename = "Luftfartshindre_" + county_name + ".osm"
print ("Writing file '%s'..." % filename)
file_out = open(filename, "w")
file_out.write ('<?xml version="1.0" encoding="UTF-8"?>\n')
file_out.write ('<osm version="0.6" generator="obstacle2osm v%s">\n' % version)
node_id = -1000
for obstacle in obstacles:
node_id -= 1
file_out.write (' <node id="%i" lat="%f" lon="%f">\n' % (node_id, obstacle['latitude'], obstacle['longitude']))
name = obstacle['name']
if name == obstacle['ref:hinder']:
name = ""
elif name == name.upper():
name = name.title()
make_osm_line ("ref:hinder", obstacle['ref:hinder'])
make_osm_line ("description", name)
make_osm_line ("OBSTACLE_TYPE", obstacle['type'])
make_osm_line ("STATUS", obstacle['status'])
if "height" in obstacle:
make_osm_line ("height", obstacle['height'])
if "ele" in obstacle:
make_osm_line ("ele", obstacle['ele'])
elif "top_ele" in obstacle:
make_osm_line ("top_ele", obstacle['top_ele'])
if not("date_create" in obstacle) or (obstacle['date_update'] != obstacle['date_create']):
make_osm_line ("DATE_UPDATE", obstacle['date_update'])
if "date_create" in obstacle:
make_osm_line ("DATE_CREATE", obstacle['date_create'])
if "date_valid" in obstacle:
make_osm_line ("end_date", obstacle['date_valid'])
# Feature tagging (man_made, tower:type etc)
tag_found = False
for object_type, tags in iter(tagging_table.items()):
if object_type == obstacle['type']:
for tag in tags:
tag_split = tag.split("=")
make_osm_line (tag_split[0], tag_split[1])
tag_found = True
break
if not(tag_found):
print ("Object type '%s' not found in tagging table " % obstacle['type'])
# Light tagging
light = obstacle['light']
if not(light in ['IL', 'UKJ']):
colour = ""
character = ""
intensity = ""
icao_type = ""
make_osm_line ("aeroway:light", "obstacle")
if light in ['BR','FR','LIA','LIB','MIB','MIC']:
colour = "red"
elif light in ['BH','FH','MIA','HIA','HIB']:
colour = "white"
make_osm_line ("aeroway:light:colour", colour)
if light in ['FR','FH','LIA','LIB','MIC']:
character = "fixed"
elif light in ['BR','BH','MIA','MIB','HIA','HIB']:
character = "flashing"
elif light == "FLO":
character = "floodlight"
make_osm_line ("aeroway:light:character", character)
if light in ['LIA','LIB']:
intensity = "low"
elif light in ['MIA','MIB','MIC']:
intensity = "medium"
elif light in ['HIA','HIB']:
intensity = "high"
make_osm_line ("aeroway:light:intensity", intensity)
if light in ['LIA','MIA','HIA']:
icao_type = "A"
elif light in ['LIB','MIB','HIB']:
icao_type = "B"
elif light == "HIC":
icao_type = "C"
make_osm_line ("aeroway:light:icao_type", icao_type)
file_out.write (' </node>\n')
# Wrap up
file_out.write ('</osm>\n')
file_out.close()
print ("Done in %i seconds" % (time.time() - start_time))
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
23,
198,
198,
2,
22007,
17,
418,
76,
198,
2,
1482,
24040,
22548,
17648,
422,
32872,
332,
7126,
370,
10652,
14,
38,
5805,
3696,
329,
1330,
... | 2.273448 | 4,286 |
import time
from blinds import Blinds, NEUTRAL, UP, DOWN
# janky way to calibrate blinds to be open/closed to the right amount
# edit this file to change UP/DOWN to move blinds in desired direction,
# save and then run
if __name__ == '__main__':
main()
| [
11748,
640,
198,
198,
6738,
7770,
82,
1330,
24507,
82,
11,
10635,
3843,
35296,
11,
15958,
11,
30320,
198,
198,
2,
474,
39556,
835,
284,
33801,
378,
7770,
82,
284,
307,
1280,
14,
20225,
284,
262,
826,
2033,
198,
2,
4370,
428,
2393,
... | 3.25 | 80 |
import pytest
import os
from jinja2 import Environment, BaseLoader
from svl.compiler.compiler import _extract_additional_datasets, svl
from svl.compiler.errors import (
SvlSyntaxError,
SvlMissingFileError,
SvlPlotError,
SvlDataLoadError,
SvlDataProcessingError,
)
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
JINJA_ENV = Environment(loader=BaseLoader)
@pytest.fixture
def svl_source():
""" Self cleaning fixture for rendering an SVL script template into a file
to be called from a subprocess. Returns a factory that produces
rendered template locations and also renders the template.
"""
svl_script_template = JINJA_ENV.from_string(
"""
DATASETS
bigfoot "{{ test_dir }}/test_datasets/bigfoot_sightings.csv"
HISTOGRAM bigfoot
X temperature_mid BINS 25
"""
)
return svl_script_template.render(test_dir=CURRENT_DIR)
def test_extract_additional_datasets():
""" Tests that the _extract_additional_datasets function returns the
correct value.
"""
datasets = ["bigfoot=datasets/bigfoot.csv", "dogman=datasets/dogman.csv"]
truth = {
"bigfoot": "datasets/bigfoot.csv",
"dogman": "datasets/dogman.csv",
}
answer = _extract_additional_datasets(datasets)
assert truth == answer
def test_svl(svl_source):
""" Tests that the svl function works when the script is correct.
"""
svl(svl_source)
def test_svl_datasets(svl_source):
""" Tests that the svl function works when additional datasets are
specified.
"""
svl(
svl_source,
datasets=[
"bigfoot={}/test_datasets/bigfoot_sightings.csv".format(
CURRENT_DIR
)
],
)
def test_svl_debug(svl_source):
""" Tests that the svl function works when the debug option is specified.
"""
answer = svl(svl_source, debug=True)
assert "<" not in answer
def test_svl_offline_js(svl_source):
""" Tests that the svl function works when the offline_js option is
specified.
"""
svl(svl_source, offline_js=True)
def test_svl_dataset_error(svl_source):
""" Tests that the svl function raises a ValueError when the additional
datasets are incorrectly specified.
"""
with pytest.raises(ValueError, match="name=path"):
svl(
svl_source,
datasets=[
"bigfoot:{}/test_datasets/bigfoot_sightings.csv".format(
CURRENT_DIR
)
],
)
def test_svl_syntax_error(svl_source):
""" Tests that the svl function raises a SvlSyntaxError when there is a
syntax error in the source.
"""
svl_source = """{}
LINE bigfoot X X date BY YEAR Y report_number COUNT
""".format(
svl_source
)
with pytest.raises(SvlSyntaxError, match="Syntax error"):
svl(svl_source)
def test_svl_missing_file_error(svl_source):
""" Tests that the svl function raises a SvlMissingFileError when there is
a missing file.
"""
with pytest.raises(SvlMissingFileError, match="File"):
svl(svl_source, datasets=["ufos={}/test_datasets/ufo_sightings.csv"])
def test_svl_plot_error(svl_source):
""" Tests that the svl function raises a SvlPlotError when there is an
error in a plot specification.
"""
svl_source = """{}
LINE bigfoot X date BY YEAR TITLE "Annual Bigfoot Sightings"
""".format(
svl_source
)
with pytest.raises(SvlPlotError, match="Plot error:"):
svl(svl_source)
def test_svl_data_load_error():
""" Tests that the svl function raises a SvlDataLoadError when there's an
incorrectly specified SQL dataset.
"""
svl_source = """
DATASETS
bigfoot "{}/test_datasets/bigfoot_sightings.csv"
bigfoot_failure SQL "SELECT date FROM bigfoots"
HISTOGRAM bigfoot
X temperature_mid BINS 25
""".format(
CURRENT_DIR
)
with pytest.raises(SvlDataLoadError, match="Error loading data"):
svl(svl_source)
def test_svl_data_processing_error():
""" Tests that the svl function raises a SvlDataProcessingError when there
is an incorrectly specified custom SQL statement in the plot.
"""
svl_source = """
DATASETS
bigfoot "{}/test_datasets/bigfoot_sightings.csv"
LINE bigfoot
X date by year label "year"
Y date count label "number of sightings"
SPLIT BY classification
FILTER "daet > 1990-01-01"
""".format(
CURRENT_DIR
)
with pytest.raises(
SvlDataProcessingError, match="Error processing plot data"
):
svl(svl_source)
def test_svl_not_implemented_error(svl_source):
""" Tests that the svl function raises a NotImplementedError when the
selected backend has not been implemented.
"""
with pytest.raises(NotImplementedError, match="Unable to use"):
svl(svl_source, backend="vega")
| [
11748,
12972,
9288,
198,
11748,
28686,
198,
198,
6738,
474,
259,
6592,
17,
1330,
9344,
11,
7308,
17401,
198,
198,
6738,
264,
19279,
13,
5589,
5329,
13,
5589,
5329,
1330,
4808,
2302,
974,
62,
2860,
1859,
62,
19608,
292,
1039,
11,
264,
... | 2.411341 | 2,081 |
from djaveAPI.docs import docs
from djaveURL import protocol_and_host
| [
6738,
42625,
1015,
17614,
13,
31628,
1330,
34165,
198,
6738,
42625,
1015,
21886,
1330,
8435,
62,
392,
62,
4774,
628
] | 3.55 | 20 |
from pathlib import Path
import numpy as np
import pandas as pd
from pylab import plt
from progressbar import ProgressBar
from models import sklearn_model
| [
6738,
3108,
8019,
1330,
10644,
198,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
19798,
292,
355,
279,
67,
198,
6738,
279,
2645,
397,
1330,
458,
83,
198,
6738,
4371,
5657,
1330,
18387,
10374,
198,
198,
6738,
4981,
1330,
1341,
35720,
... | 3.590909 | 44 |
from __future__ import print_function
import math
import copy
import json
dancer = {
verbs : {}
adjs: {}
}
# dancer describes the state of a conscious being
# relation describes the feeling of one regarding another
dancer["adjs"]["lust"]
dancer["adjs"]["like"]
# define the archetypal relations
dancer["relation"]["arch"] = {
"lust" : 0,
"like" : 0,
"respect" : 0,
}
# define the dancer's abilities
## API:
# MODULE SETTINGS:
# These values used to calibrate action effects.
SMALL_MULTIPLIER = 0.1
MEDIUM_MULTIPLIER = 0.2
LARGE_MULTIPLIER = 0.4
# Key bindings. These are inserted into the game object during _setup_player.
keyDict = {
"y" : "touch",
"t" : "evade",
"r" : "jest",
"f" : "retreat",
"g" : "breathe",
"h" : "advance"
}
# Lists -- these are to be used by the client.
# (Mainly so display functions can be dynamic.)
# My dance_display.py should work for any moveList that is a list of strings
# and any statList that is a list of strings
# or a list of lists which contain only strings.
# BUT: moveList + statList MUST == the keys of p in _setup_player (-'choice')
# (I know that's ugly, sorry.)
moveList = [ 'advance', 'retreat', 'touch', 'evade', 'breathe', 'jest' ]
statList = [ ['earth', 'will'], ['air', 'calm'], ['fire', 'heat'], ['water', 'balance'] ]
playerList = ['0', '1']
# These are some special exceptions.
# Probably not necessary.
## BACKEND:
# UTILITY FUNCTIONS
# These are totally useless ;)
# SMALL
# MED
# LARGE
def _setup_player( e0, a0, f0, w0):
"""
Accepts initial values for eafw,
returns a complete player object.
"""
heat = f0/2
if f0%2 == 1: heat += 1
p = {
'earth' : float(e0),
'will' : float(e0),
'air' : float(a0),
'calm' : float(a0),
'fire' : float(f0),
'heat' :float(heat),
'water' : float(w0),
'balance' : -1.0,
'choice' : None,
'advance' : 1,
'retreat' : 1,
'touch' : 1,
'evade' : 1,
'breathe' : 1,
'jest' : 1
}
p.update( keyDict )
return p
def _execute( player, choice, game_data0, game_data1 ):
"""
Reads from gd0 and writes to gd1,
according to the move with the same name as the player's choice.
"""
# In theory, neither of the below exceptions should ever be raised
# since the client-side function should test both conditions
# before calling a new turn.
# First check to see if the move exists.
if choice in moveList:
pass
else:
raise NoSuchMove
# Second check to see if the move is currently allowed.
if game_data0[ str(player) ][ str(choice) ] == 1:
pass
else:
raise IllegalMove
# Then perform the move.
if player == 0:
other = 1
else:
other = 0
move = execList[ choice ]
game_data1 = move( str(player), str(other), game_data0, game_data1)
# Finally, return the modified object.
return game_data1
def _val_in( val_0, magnitude ):
"""
Returns magnitude with the sign such that abs(val_0 + mag2) < abs(val_0)
If mag < 0, does the opposite.
If abs(mag) > 1, may result in an overshoot.
"""
if val_0 < 0:
pass
elif val_0 > 0:
magnitude = -magnitude
else:
# Because one cannot draw closer to 0 if one is already there:
if magnitude > 0: magnitude = 0
# And since we don't want d to be always negative:
else: magnitude = -magnitude
return magnitude
def _gameover_check( game_data ):
"""
Checks to see if gameover should be declared.
This function defines the encounter-end conditions.
(Maybe it should take some cues from ## MODULE SETTINGS ?)
"""
if game_data["0"]["will"] <= 0 and game_data["1"]["will"] <= 0:
game_data['game']['gameover'] = 1
game_data['game']['gameover_message'] = ( 'SimultaneousExhaustion' )
else:
for p in range( 0, 1 ):
if game_data[ str(p) ]['will'] <= 0:
game_data['game']['gameover'] = 1
game_data['game']['gameover_message'] = ( 'Player ' + str(p) + ' exhaustion.' )
# VERBS SECTION
# This section should include callable functions for each move.
# Each move must accept actor, target, and distance arguments.
# All functions in this section accept a bin for actor or target.
# They read only from game_0 and write only to game_1,
# returning game_1
def _advance( actor, target, game_0, game_1):
"""
Signifies a closening, with or without physical contact.
A bold statement, a step forward, or a glorious charge.
Costs calm; reduces balance.
"""
# This part is the cost. It will always be the same.
game_1[actor]['calm'] -= _small( game_0[actor]["heat"] )
# Advancing does not increase one's balance
# if one pushes against the target.
# (Though frict may change balance.)
if not ( game_0['game']['d'] == 0 and _get_future_d( game_0 ) ):
game_1[actor]['balance'] += 1
# If the future distance is 0, a collision occurs.
# (As long as the target did not evade.)
if _get_future_d( game_0 ) == 0 and game_0[target]['choice'] != 'evade':
game_1 = _frict( actor, target, game_0, game_1 )
# If the two players are already grappling,
# (ie in the same space, at d=0)
# they cannot advance past each other.
# Otherwise, the distance will decrease.
# (If they are at d1, they will switch positions.)
game_1['game']['d'] += _val_in( game_0['game']['d'], 1 )
return game_1
def _retreat( actor, target, game_0, game_1):
"""
Signifies a distancing, a retreat, a coldness
a disreply, a shyness, a step back, or a flight.
Costs calm; reduces balance.
"""
# Reduce calm by small
game_1[actor]['calm'] -= _small( game_0[actor]["heat"] )
# Decrease balance by small
game_1[actor]['balance'] -= 1
# Open distance by 1
if game_0[target]['choice'] == 'advance' and game_0['game']['d'] == 0:
pass
else:
game_1['game']['d'] += _val_in( game_0['game']['d'], -1 )
return game_1
def _touch( actor, target, game_0, game_1):
"""
Signifies phsyical contact.
A brush, caress, strike, grope, or attempt.
"""
# This is the cost
game_1[actor]['calm'] -= _med( game_0[actor]['heat'] )
# Check to see if the move connects.
if abs( _get_future_d( game_0 ) ) <= 1 and game_0[target]['choice'] != 'evade':
# Below is a somewhat silly way of saying
# that a successful touch is like a frict,
# but only affecting the target.
save = copy.deepcopy( game_1[actor] )
_frict( actor, target, game_0, game_1 )
game_1[actor] = copy.deepcopy( save )
return game_1
def _evade( actor, target, game_0, game_1):
"""
A sort of dodge or refusal.
Counteracts the effect of a touch or advance. Rather embarassing against a tease.
Technically does nothing. Other acts may define exceptions for: if game_0[target]['choice'] == 'evade':
"""
if _frict_occurs( game_0 ):
# In this case, _frict_occurs() is _if_frict_would_occur()
# If successful, restores calm.
# (Since you look so cool.)
game_1[actor]['calm'] += _small( game_0[actor]['air'] )
else:
# Otherwise, costs a fair bit.
game_1[actor]['calm'] -= _med( game_0[actor]['heat'] )
return game_1
def _breathe( actor, target, game_0, game_1):
"""
A moment of rest, contemplation, and gathering.
Could signify literal breathing, but also meditation or inaction.
(Totally restores calm. Slightly reduces heat and restores will.)
"""
# See above.
if not _frict_occurs( game_0 ):
game_1[actor]['calm'] = game_0[actor]['air']
game_1[actor]['heat'] -= _small( game_0[actor]['air'] )
game_1[actor]['will'] += _small( game_0[actor]['air'] )
# Closes balance by one.
game_1[actor]['balance'] += _val_in( game_1[actor]['balance'], 1 )
# However: breathe is interrupted by a frict.
# You'll still get some breath back, but receive no other bonuses.
else:
game_1[actor]['calm'] += _large( game_0[actor]['air'] )
return game_1
def _jest( actor, target, game_0, game_1):
"""
A joke or strangeness, encouraging advance and curiosity
by inspiring a passion -- for example anger or desire.
(Adds heat and negative balance -- more effective if the target is retreating or evading.)
"""
game_1[actor]['calm'] -= _small( game_0[actor]['heat'] )
if not game_0[target]['choice'] == 'breathe':
game_1[target]['heat'] += _small( game_0[actor]['heat'] )
# By reducing balance, tease can force the target to advance or suffer in fricts
# It is less useful if the player is already forward-balanced.
game_1[target]['balance'] -= 1
if game_0[target]['choice'] == 'retreat' or game_0[target]['choice'] == 'evade':
game_1[target]['heat'] += _med( game_0[actor]['heat'] )
return game_1
def _frict( actor, target, game_0, game_1):
"""
Represents a kind of clash, collision, or rubbing-together.
Depends on balances.
"""
# Both players receive heat. The one with less receives more.
game_1[target]['heat'] += _small( game_0[actor]['fire'])
game_1[actor]['heat'] += _small( game_0[target]['fire'])
if game_0[actor]['heat'] > game_0[target]['heat']:
game_1[target]['heat'] += _small( game_0[actor]['heat'] )
elif game_0[actor]['heat'] < game_0[target]['heat']:
game_1[actor]['heat'] += _small( game_0[target]['heat'] )
else:
game_1[target]['heat'] += _small( game_0[actor]['heat'] )
game_1[actor]['heat'] += _small( game_0[target]['heat'] )
# If one player's will is less than 25% of the other's
# that player will be pushed back.
if game_0[actor]['will'] > 4 * game_0[target]['will']:
game_1[target]['balance'] -= 1
elif 4 * game_0[actor]['will'] < game_0[target]['will']:
game_1[actor]['balance'] -= 1
# Adds heat to each player, giving the advantage to the player
# whose absolute balance is the smaller percent of their water.
# (So if p0.bal = 1/10 and p1.bal = -1/11, then p1 will have the advantage.)
a_bal = float( abs(game_0[actor]['balance'] )) / game_0[actor]['water']
t_bal = float( abs(game_0[target]['balance'] )) / game_0[target]['water']
if a_bal == t_bal:
game_1[actor]['heat'] += _med( game_0[target]['heat'] )
game_1[target]['heat'] += _med( game_0[actor]['heat'] )
elif a_bal > t_bal:
game_1[actor]['heat'] += _large( game_0[target]['heat'] )
game_1[target]['heat'] += _small( game_0[actor]['heat'] )
elif a_bal < t_bal:
game_1[actor]['heat'] += _small( game_0[target]['heat'] )
game_1[target]['heat'] += _large( game_0[actor]['heat'] )
else:
print( "I think this is impossible, right?" )
return game_1
def _get_future_d( game_0 ):
"""
This somewhat kludgy function calculates the future distance
based on the present distance and the player choices.
Used in collision detection.
"""
d = game_0['game']['d']
if d == 0 and ( game_0['0']['choice'] == 'advance' or game_0['1']['choice'] == 'advance' ):
pass
else:
for p in range( 2 ):
choice = game_0[str(p)]['choice']
if choice == 'advance':
d -= math.copysign(1, d)
elif choice == 'retreat':
d += math.copysign(1, d)
else:
pass
d = int(d)
return d
# The below is used by _execute() to link strings with actions.
# This is a little silly, but I don't know a better way.
# (For some reason, this list can't be written until after the functions it contains.
# Fuck you, Python.)
execList = {
"advance" : _advance,
"retreat" : _retreat,
"touch" : _touch,
"evade" : _evade,
"breathe" : _breathe,
"jest" : _jest
}
# ADJECTIVES SECTION
# This section should include rules for checking and correcting element statuses.
def _earth_check( game_data ):
"""
Without will,
an individual is unable to continue.
"""
for p in range(2):
if game_data[str(p)]['will'] > game_data[str(p)]['earth']:
game_data[str(p)]['will'] = game_data[str(p)]['earth']
if game_data['0']['will'] <= 0 and game_data['1']['will'] <= 0:
game_data['game']['gameover'] = 1
game_data['game']['gameover_message'] = 2
else:
for p in range( 2 ):
if game_data[str(p)]['will'] <= 0:
game_data['game']['gameover'] = 1
game_data['game']['gameover_message'] = p
return game_data
def _air_check( game_data ):
"""
Below-min breath is called exhaustion.
Knowing when to breathe is important.
"""
for p in range( 2 ):
c = game_data[str(p)]['calm']
# Punish will if calm is below zero
if c < 0:
game_data[str(p)]['calm'] = 0
game_data[str(p)]['will'] += c
# Treat Air as maximum Calm
if c > game_data[str(p)]['air']:
game_data[str(p)]['calm'] = game_data[str(p)]['air']
return game_data
def _fire_check( game_data ):
"""
Above-max heat is called mania,
while below-min heat is called depression.
High heat will power-up some moves, but it is risky.
"""
for p in range(2):
h = game_data[str(p)]['heat']
f = game_data[str(p)]['fire']
if h < 0:
game_data[str(p)]['heat'] = 0
game_data[str(p)]['will'] += h
if h > f:
game_data[str(p)]['heat'] = f
game_data[str(p)]['will'] -= ( h - f )
return game_data
def _water_check( game_data ):
"""
Balance is not a magnitude, but a distance from zero.
Zero represents perfect balance,
while the positive represents forwardness and the negative backwardness.
"""
for p in range( 2 ):
b = game_data[str(p)]['balance']
w = game_data[str(p)]['water']
if abs( b ) > w:
game_data[str(p)]['will'] -= ( abs( b ) - w )
if b < 0:
game_data[str(p)]['balance'] = -w
elif b > 0:
game_data[str(p)]['balance'] = w
return game_data
# THESE ARE MINOR AND NONMANDATORY API FUNCTIONS,
# BUT THEIR USE IS RECOMMENDED
def get_stat( dance, player, stat ):
"""
Accepts a bin representing the player
and a string representing the stat
and returns the stat's value.
"""
return dance[ str(player) ][ str(stat) ]
# THE TWO FUNCTIONS BELOW
# ARE THE ONLY ESSENTIAL API FUNCTIONS
def set_stage( p0_e, p0_a, p0_f, p0_w, p1_e, p1_a, p1_f, p1_w, d0, d_max ):
"""
Accepts initial element values for p0 and p1,
as well as initial and maximum distance,
then returns a JSON object describing the game-stage.
"""
game_data = {
'0' : _setup_player( p0_e, p0_a, p0_f, p0_w ),
'1' : _setup_player( p1_e, p1_a, p1_f, p1_w ),
'game' : {
'd' : d0,
'd_max' : d_max,
'turn' : 0,
'0choice' : None,
'1choice' : None,
'gameover' : 0,
'gameover_message' : "ERROR"
# in 'gameover_message', a bool will symbolize that player, a 2 will symbolize both players
}
}
json_data = json.dumps( game_data )
return json_data
def turn( json_data ):
"""
Accepts a JSON object describing the game-stage,
plus a binary representing the active player
and a string representing that player's choice.
Returns a modified JSON object.
"""
# Open the game data
game_data0 = json.loads( json_data )
# These exceptions should make it easy
# to learn if player behavior has violated the rules.
if game_data0['game']['gameover'] == 1:
raise GameOver
for player in playerList:
choice = game_data0[player]['choice']
if not choice in moveList:
raise NoSuchMove
if game_data0[player][choice] == 0:
raise IllegalMove
# Split the game_data into two branches: 0 for reading and 1 for writing.
# For this reason, all action functions must use +/-=, not just =
game_data1 = copy.deepcopy( game_data0 )
# Execute the moves of each player
game_data1 = _execute( 0, game_data0['0']['choice'], game_data0, game_data1 )
game_data1 = _execute( 1, game_data0['1']['choice'], game_data0, game_data1 )
# Reenable all moves.
game_data1 = _enables( game_data1 )
# Disable for next round the moves that were just used.
game_data1 = _disables( game_data1 )
# Check to see if any stat is outside legal bounds
game_data1 = _adj_check( game_data1 )
# Check to see if the game has ended
_gameover_check( game_data1 )
# Finally, increment the turn counter.
game_data1['game']['turn'] += 1
# Write the log
# Repackage and return the game data
new_json_data = json.dumps( game_data1 )
return new_json_data
| [
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198,
197,
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324,
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25,
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198,
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197,
92,
198,
198,... | 2.637519 | 5,901 |
##### CLASSE ARBRE #####
#Initialise l'arbre
#Emplacement du sous arbre gauche
#Feuille la plus lourde de l'arbre
#Liste des feuille de l'arbre
#Largeur du noeud
#Place les arbres
#Largeur de l'arbre pour le dessin
#Longueur de l'arbre pour le dessin
#Profondeur de l'arbre
#Construit le mobile
###### CLASSE FEUILLE #####
| [
4242,
2,
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1921,
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489,
5592,
7043,
264,
516,
610,
4679,
14885,
2395,
628,
220,
220,
... | 2.06 | 200 |
import cv2
import math
from pynput.mouse import Button
| [
11748,
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17,
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10688,
198,
6738,
279,
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1996,
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20969,
628
] | 3.294118 | 17 |
import re
def elem2dict(node):
"""
Convert an lxml.etree node tree into a dict.
"""
d = {}
for e in node.iterchildren():
key = e.tag.split('}')[1] if '}' in e.tag else e.tag
value = e.text if e.text else elem2dict(e)
d[key] = value
return d
| [
11748,
302,
628,
198,
4299,
9766,
76,
17,
11600,
7,
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2599,
198,
220,
220,
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257,
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... | 2.130435 | 138 |
from setuptools import setup, find_packages
import codecs
import pathlib
import re
here = pathlib.Path(__file__).parent.resolve()
def read(*parts):
"""
Build an absolute path from *parts* and and return the contents of the
resulting file. Assume UTF-8 encoding.
"""
with codecs.open(pathlib.PurePath(here, *parts), "rb", "utf-8") as f:
return f.read()
def find_version(*file_paths):
"""
Build a path from *file_paths* and search for a ``__version__``
string inside.
"""
version_file = read(*file_paths)
version_match = re.search(
r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M
)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
meta_path = pathlib.PurePath('src', 'nspyre', '__init__.py')
version = find_version(meta_path)
long_description = (here / 'README.md').read_text(encoding='utf-8')
setup(
name='nspyre',
version=version,
license='BSD 3-Clause License',
description='Networked Scientific Python Research Environment',
long_description=long_description,
long_description_content_type='text/markdown',
url='https://github.com/nspyre-org/nspyre',
author='Alexandre Bourassa',
author_email='abourassa@uchicago.edu',
maintainer='Michael Solomon',
maintainer_email='msolo@uchicago.edu',
classifiers=[
'Development Status :: 4 - Beta',
'Framework :: IPython',
'Framework :: Jupyter',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: BSD License',
'Natural Language :: English',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Operating System :: Unix',
'Programming Language :: Python',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3 :: Only',
'Programming Language :: Python :: Implementation :: CPython',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Physics',
'Topic :: Scientific/Engineering :: Visualization',
'Topic :: Software Development :: Libraries',
'Topic :: Software Development :: Libraries :: Application Frameworks',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Software Development :: User Interfaces',
'Topic :: System :: Distributed Computing',
'Topic :: System :: Logging',
],
keywords='nspyre, measurement toolkit, experimentation platform, physics, science, research',
package_dir={'': 'src'},
packages=find_packages(where='src'),
zip_safe=False,
python_requires='>=3.8, <4',
install_requires=[
# SciPy
'numpy>=1.19.1',
'scipy>=1.5.2',
'pandas>=1.1.2',
# MongoDB
'pymongo>=3.10.1',
# Qt
'pyqt5>=5.12.3',
'pyqtgraph>=0.11.0',
'qscintilla>=2.11.2',
# VISA
'pyvisa>=1.10.1',
# Lantz
'pint>=0.15',
'pimpmyclass>=0.4.3',
'lantzdev>=0.5.2',
# Utilities
'parse>=1.18.0',
'tqdm>=4.49.0',
'rpyc>=4.1.5',
],
extras_require={
'dev': [
'pytest>=6.1.2',
'pytest-cov',
'psutil>=5.7.3',
]
},
test_requires=[
'pytest>=6.1.2',
'pytest-cov',
'psutil>=5.7.3',
],
test_suite='tests',
entry_points={
'console_scripts': [
'nspyre=nspyre.gui:main',
'nspyre-config=nspyre.config.config_cli:main',
'nspyre-mongodb=nspyre.mongodb:main',
'nspyre-inserv=nspyre.inserv:main',
],
},
project_urls={
'Bug Reports': 'https://github.com/nspyre-org/nspyre/issues',
'Source': 'https://github.com/nspyre-org/nspyre/',
},
include_package_data=True,
options={'bdist_wheel': {'universal': '1'}},
)
| [
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198,
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3108,
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7,
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7753,
834,
737,
8000,
13,
411,
6442,
3419,
628,
198,
4299,
... | 2.249724 | 1,810 |
###############################################################################
import numpy as np
import random as rn
#DO NOT CHANGE THIS
np.random.seed(1478)
rn.seed(2264)
###################
from utils import load_datasets_filenames, load_experiment_configuration
from utils import load_dataset, save_predictions
from utils import select_validation_set
from utils import get_voting_pool_size, calculate_pool_diversity
from sklearn.model_selection import StratifiedKFold
if __name__ == "__main__":
print "Step 1 - Loading configurations"
datasets_filenames = load_datasets_filenames()
config = load_experiment_configuration()
predictions = {}
exp = 1
print "Step 2 - Starting experiment"
for dataset_filename in datasets_filenames:
instances, gold_labels = load_dataset(dataset_filename)
skfold = StratifiedKFold(n_splits = config["num_folds"],
shuffle = True)
gold_labels = (gold_labels["defects"] == 'true').astype(int)
predictions[dataset_filename] = {}
for fold, division in enumerate(skfold.split(X=instances, y=gold_labels), 1):
train_idxs = division[0]
test_idxs = division[1]
train_instances = instances.iloc[train_idxs].values
train_gold_labels = gold_labels.iloc[train_idxs].values.ravel()
test_instances = instances.iloc[test_idxs].values
test_gold_labels = gold_labels.iloc[test_idxs].values.ravel()
predictions[dataset_filename][fold] = {}
predictions[dataset_filename][fold]["gold_labels"] = test_gold_labels.tolist()
for hardness_type, filter_func in config["validation_hardnesses"]:
validation_instances, validation_gold_labels = select_validation_set(
train_instances, train_gold_labels, filter_func, config["kdn"])
predictions[dataset_filename][fold][hardness_type] = {}
subpredictions = predictions[dataset_filename][fold][hardness_type]
base_clf = config["base_classifier"]()
clf_pool = config["generation_strategy"](base_clf, config["pool_size"])
clf_pool.fit(train_instances, train_gold_labels)
for strategy_name, pruning_strategy in config["pruning_strategies"]:
pruned_pool = pruning_strategy(clf_pool, validation_instances,
validation_gold_labels)
pool_rem_size = get_voting_pool_size(pruned_pool)
cur_predictions = pruned_pool.predict(test_instances)
data_arr = [cur_predictions.astype(int).tolist(), pool_rem_size]
for measure in config["diversity_measures"]:
measure_value = calculate_pool_diversity(measure,
pruned_pool,
validation_instances,
validation_gold_labels,
pool_rem_size)
data_arr.append(measure_value)
subpredictions[strategy_name] = data_arr
print "Experiment " + str(exp)
exp+=1
print "Step 2 - Finished experiment"
print "Step 3 - Storing predictions"
save_predictions(predictions) | [
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241... | 2.486667 | 1,200 |
#!/usr/bin/env python3
import evdev
import select
import requests
import subprocess
import re
from datetime import datetime
roon_base_url = "http://greenspeaker:3000/api/v1"
harmony_base_url = "http://m1:8282/hubs/harmony-hub/devices/schiit-amp/commands"
p = re.compile('"zone_id": "([a-z0-9]+)",\n *"display_name": "Hifi \+ 1"')
devices = {}
for fn in evdev.list_devices():
print(fn)
dev = evdev.InputDevice(fn)
if dev.name.find('HBGIC') >= 0:
devices[dev.fd] = dev
print(devices)
last_volume_change = datetime.now()
while True:
r, w, x = select.select(devices, [], [])
for fd in r:
for event in devices[fd].read():
url = None
cmd = None
if event.type == evdev.ecodes.EV_KEY:
myzone = None
zones = requests.get("%s/zones" % roon_base_url).json()
for z in zones:
if zones[z]['display_name'] == "Hifi + 1":
myzone = zones[z]['zone_id']
break
if not myzone:
myzone = requests.get('http://greenspeaker:3000/api/v1/default_zone').text
if myzone == "undefined":
myzone = "default"
print("My zone is %s" % myzone)
keyev = evdev.categorize(event)
code = keyev.keycode[4:]
state = keyev.keystate
if state == evdev.events.KeyEvent.key_down:
state = "DOWN"
elif state == evdev.events.KeyEvent.key_up:
state = "UP"
elif state == evdev.events.KeyEvent.key_hold:
state = "HOLD"
print(code, state)
method = "POST"
if state == "DOWN":
if code == "PLAYPAUSE":
url = "%s/zone/%s/control/playpause" % (roon_base_url, myzone)
elif code == "STOP":
# url = "%s/zone/all/control/pause" % roon_base_url
url = "%s/zone/%s/control/stop" % (roon_base_url, myzone)
elif code == "REWIND":
url = "%s/zone/%s/control/previous" % (roon_base_url, myzone)
elif code == "FASTFORWARD":
url = "%s/zone/%s/control/next" % (roon_base_url, myzone)
elif code == "INFO":
url = "%s/mute" % harmony_base_url
if state == "HOLD" or state == "DOWN":
# Make sure volume doesn't change too fast
if myzone.lower() == "greenspeaker":
if code == "UP":
url = "%s/zone/%s/volume/relative_step/2" % (roon_base_url, myzone)
if code == "DOWN":
url = "%s/zone/%s/volume/relative_step/-2" % (roon_base_url, myzone)
else:
if code == "UP":
url = "%s/volume-up" % harmony_base_url
if (datetime.now() - last_volume_change).total_seconds() < 0.5:
print("Skipped vol change")
continue
else:
last_volume_change = datetime.now()
print("Changed volume up")
elif code == "DOWN":
url = "%s/volume-down" % harmony_base_url
if (datetime.now() - last_volume_change).total_seconds() < 0.5:
print("Skipped vol change")
continue
else:
last_volume_change = datetime.now()
print("Changed volume down")
if url:
print(method, url)
try:
if method == "GET":
req = requests.get(url)
else:
req = requests.post(url)
except:
print("Request to %s failed" % (url))
if cmd:
print(" ".join(cmd))
subprocess.call(cmd)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
11748,
819,
7959,
198,
11748,
2922,
198,
11748,
7007,
198,
11748,
850,
14681,
198,
11748,
302,
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
305,
261,
62,
8692,
62,
6371,... | 1.669225 | 2,606 |
"""
Manipulate images in specific ways based on commands used on input.
This module is used in order to manipulate images in a number of ways.
All of this is done through the ImageO object. The ImageO object reads in a file and allows for
manipulations to be done on an image and for that image to be output after the manipulation.
All different things this module allows for are:
- make an image only all of its red values
- make an image only all of its green values
- make an image only all of its blue values
- zero out all red values of an image
- zero out all green values of an image
- zero out all blue values of an image
- darken an image by moving all values to be in the lower half of 255
- bright an image by moving all values to be in the upper half of 255
- make image in-to a gray-scaled image
- invert the colors of an image
- block or blur an image, making all pixel of a block the same rgb value
All of these option can be called after importing and creating an ImageO object or from calling
this module from the command line with the proper options.
Joshua Shequin
"""
import argparse
import sys
import numpy as np
from PIL import Image
def common_denominator(number_one, number_two, range_one, range_two):
"""
Recursion solution to this problem even though it is not the best way of doing it.
Base case is when the modulo of both numbers and the second range value is zero,
or if they are the same.
Parameters
----------
number_one : int
the first number of the two numbers to find the common denominator between.
number_two : int
the second number of the two numbers to find the common denominator between.
range_one : int
the lowest integer for a range of values to find the common denominator in.
range_two : int
the highest integer for a range of values to find the common denominator in.
Returns
------
Integer
the value that the two input have number both have a denominator with, or the lowest int
in the range given if no denominator was found.
"""
if number_one % range_two == 0 and number_two % range_two == 0:
return range_two
if range_one == range_two:
return range_one
return common_denominator(number_one, number_two, range_one, range_two-1)
class ImageO:
"""
Object that handles images, allowing for a number of manipulations.
Image object that takes an input file as the input and reads that input file and turns that
image in to an array. From that array the object allows for a number of manipulations to be
done to the image. Every manipulation also by default outputs the file.
"""
def __init__(self, input_file):
"""
Initialize the object by taking an input_file and loading the image to an array.
Parameter
---------
input_file : string
string of the file location to be read, relative or full path.
"""
try:
self.infile = np.array(Image.open(input_file)) # read in the file and store as a
# numpy array.
except FileNotFoundError:
# if that file did not exist then we warn the user and close the program.
print("Check your infile parameter, I can't find the file you put in!")
sys.exit()
def clear_red(self, output_file, returnable=False):
"""
Clear all red in our image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[0] = 0
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def clear_green(self, output_file, returnable=False):
"""
Clear all green in our image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[1] = 0
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def clear_blue(self, output_file, returnable=False):
"""
Clear all blue in our image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[2] = 0
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def red_only(self, output_file, returnable=False):
"""
Clear all green and all blue of our image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[1] = 0
column[2] = 0
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def green_only(self, output_file, returnable=False):
"""
Clear all red and all blue of our image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[0] = 0
column[2] = 0
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def blue_only(self, output_file, returnable=False):
"""
Clear all red and all green of our image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[0] = 0
column[1] = 0
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def lower_half(self, output_file, returnable=False):
"""
Scale all shades to be only in the lower 127 of color ints.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[0] = column[0]/2
column[1] = column[1]/2
column[2] = column[2]/2
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def upper_half(self, output_file, returnable=True):
"""
Scale all shades to be only in the upper 127 of color ints.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[0] = column[0]/2 + 128
column[1] = column[1]/2 + 128
column[2] = column[2]/2 + 128
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def gray_scale(self, output_file, returnable=False):
"""
Convert the image to a grey-scale image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
# to transform a pixel to its gray-scale form we find the average of the three
# colors.
new_value = (column[0]*(1/3)) + (column[1]*(1/3)) +\
(column[2]*(1/3))
column[0] = new_value
column[1] = new_value
column[2] = new_value
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def invert_color(self, output_file, returnable=False):
"""
Invert all rgb values of the image.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
for row in self.infile:
for column in row:
column[0] = 255 - column[0]
column[1] = 255 - column[1]
column[2] = 255 - column[2]
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
def block_image(self, output_file, returnable=False):
"""
Blurs or blocks an image, assigning a block size for an image making all pixels the same.
Calls the common_denominator function to find a common denominator within a range of two
numbers for two numbers. This will be used to determine the block width and height.
Parameter
---------
output_file : string
the name of the file we want to output to.
Return
------
numpy array
Return the numpy array of the image if returnable=True
"""
number_of_blocks = common_denominator(len(self.infile), len(self.infile[0]), 2, 100)
block_dimensions = (len(self.infile)//number_of_blocks,
len(self.infile[0])//number_of_blocks)
for block_row in range(number_of_blocks):
for block in range(number_of_blocks):
block_rgb = [[], [], []]
for row in range((block_row * block_dimensions[0]),
(block_row * block_dimensions[0]) + block_dimensions[0]):
for column in range((block * block_dimensions[1]),
(block * block_dimensions[1]) + block_dimensions[1]):
# go through every pixel in the block and store the rgb values in their
# respective lists.
block_rgb[0].append(self.infile[row][column][0])
block_rgb[1].append(self.infile[row][column][1])
block_rgb[2].append(self.infile[row][column][2])
# find the average of the values in our rgb lists
avg_of_red = sum(block_rgb[0]) // len(block_rgb[0])
avg_of_green = sum(block_rgb[1]) // len(block_rgb[1])
avg_of_blue = sum(block_rgb[2]) // len(block_rgb[2])
for row in range((block_row * block_dimensions[0]),
(block_row * block_dimensions[0]) + block_dimensions[0]):
for column in range((block * block_dimensions[1]),
(block * block_dimensions[1]) + block_dimensions[1]):
# go through every pixel in the block and change its rgb values
self.infile[row][column][0] = avg_of_red
self.infile[row][column][1] = avg_of_green
self.infile[row][column][2] = avg_of_blue
if returnable:
return self.infile
Image.fromarray(self.infile, "RGB").save(output_file)
return None
if __name__ == "__main__":
PARSER = argparse.ArgumentParser(description='Manipulate an Image.')
PARSER.add_argument('Infile', metavar='I', type=str,
help='The file to have the operation performed on it.')
PARSER.add_argument('Outfile', metavar='O', type=str,
help="The name of the outfile from the script.")
PARSER.add_argument("Operation", metavar="o", type=str,
help='Which operation would you like performed? Options:'
' cr - clear all red;'
' cg - clear all green;'
' cb - clear all blue;'
' ro - make the image only shades of red;'
' go - make the image only shades of green;'
' bo - make the image only shades of blue;'
' lh - make colors all be in lower half;'
' uh - make colors all be in upper half;'
' gs - make the image gray-scale;'
' ic - invert the colors of the image;'
' bi - block the image in to same color cubes of pixels')
ARGS = PARSER.parse_args()
if ARGS.Operation not in ["cr", "cg", "cb", "ro", "go", "bo", "lh", "uh", "gs", "ic", "bi"]:
print("Not a valid operation, please use the argument -h for extra help.")
sys.exit()
if ARGS.Operation == "cr":
ImageO(ARGS.Infile).clear_red(ARGS.Outfile)
elif ARGS.Operation == "cg":
ImageO(ARGS.Infile).clear_green(ARGS.Outfile)
elif ARGS.Operation == "cb":
ImageO(ARGS.Infile).clear_blue(ARGS.Outfile)
elif ARGS.Operation == "ro":
ImageO(ARGS.Infile).red_only(ARGS.Outfile)
elif ARGS.Operation == "go":
ImageO(ARGS.Infile).green_only(ARGS.Outfile)
elif ARGS.Operation == "bo":
ImageO(ARGS.Infile).blue_only(ARGS.Outfile)
elif ARGS.Operation == "lh":
ImageO(ARGS.Infile).lower_half(ARGS.Outfile)
elif ARGS.Operation == "uh":
ImageO(ARGS.Infile).upper_half(ARGS.Outfile)
elif ARGS.Operation == "gs":
ImageO(ARGS.Infile).gray_scale(ARGS.Outfile)
elif ARGS.Operation == "ic":
ImageO(ARGS.Infile).invert_color(ARGS.Outfile)
elif ARGS.Operation == "bi":
ImageO(ARGS.Infile).block_image(ARGS.Outfile)
| [
37811,
198,
5124,
541,
5039,
4263,
287,
2176,
2842,
1912,
319,
9729,
973,
319,
5128,
13,
198,
198,
1212,
8265,
318,
973,
287,
1502,
284,
18510,
4263,
287,
257,
1271,
286,
2842,
13,
198,
198,
3237,
286,
428,
318,
1760,
832,
262,
7412... | 2.195083 | 6,915 |
# 导入了 time.ctime()和 socket 模块的所有属性
from socket import *
from time import ctime
HOST = '' # HOST 变量是空白的，这是对 bind()方法的标识，表示它可以使用任何可用的地址
PORT = 21567 # 选择了一个随机的端口号，并且该端口号似乎没有被使用或被系统保留
BZUGSIZ = 1024 # 对于该 应用程序，将缓冲区大小设置为 1KB。可以根据网络性能和程序需要改变这个容量
ADDR = (HOST, PORT)
tcpSerSock = socket(AF_INET, SOCK_STREAM) # 分配了 TCP 服务器套接字
tcpSerSock.bind(ADDR) # 将套接字绑定到服 务器地址以及开启 TCP 监听器的调用
tcpSerSock.listen(5) # listen() 方法的参数是在连接被转接或拒绝之前，传入连接请求的最大数。
'''
# 一旦进入服务器的无限循环之中，就(被动地)等待客户端的连接。当一个连接请求出现时，进入对话循环中，
# 在该循环中等待客户端发送的消息。如果消息是空白的，这意味着客户端已经退出，所以此时将跳出对话循环，
# 关闭当前客户端连接，然后等待另一个客户端连接。如果确实得到了客户端发送的消息，就将其格式化并返回
# 相同的数据，但是会在这些数据中加上当前时间戳的前缀。最后一行永远不会执行，它只是用来提醒读者，
# 如果写了一个处理程序来考虑一个更加优雅的退出方式，正如前面讨论的，那么应该调用 close()方法
'''
while True:
print('waiting for connection...')
tcpCliSock, addr = tcpSerSock.accept()
print('...connected from:', addr)
while True:
data = tcpCliSock.recv(BZUGSIZ)
if not data:
break
tcpCliSock.send(('[{}] {}'.format(ctime(), data.decode())).encode())
tcpCliSock.close()
# tcpSerSock.close()
| [
198,
2,
10263,
107,
120,
17739,
98,
12859,
228,
640,
13,
310,
524,
3419,
161,
240,
234,
17802,
10545,
101,
94,
161,
251,
245,
21410,
33699,
222,
17312,
231,
161,
109,
252,
45250,
100,
198,
198,
6738,
17802,
1330,
1635,
198,
6738,
64... | 0.912746 | 1,169 |
# -*- coding: utf-8 -*-
import uuid
from tinymce import HTMLField
from django.db import models
from django.urls import reverse
from django.core.mail import EmailMessage
from django.conf import settings
from django.contrib.postgres.fields import JSONField
from crm.utils import print_pdf
CONFERENCE_REGISTRATION_TYPE = (
("normal", "Normal registration"),
("presenter", "Presenter registration"),
)
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
334,
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198,
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7009,
76,
344,
1330,
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198,
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13,
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1330,
4981,
198,
6738,
42625,
14208,
13,
6371,
82,
1330,
9575,
1... | 3.167939 | 131 |
import re
import pytest
from sqlalchemy import Column
from sqlalchemy import MetaData
from sqlalchemy import Table
from sqlalchemy.sql import func
from sqlalchemy.sql import insert
from sqlalchemy.sql import text
from geoalchemy2.exc import ArgumentError
from geoalchemy2.types import Geography
from geoalchemy2.types import Geometry
from geoalchemy2.types import Raster
from . import select
@pytest.fixture
@pytest.fixture
@pytest.fixture
| [
11748,
302,
198,
198,
11748,
12972,
9288,
198,
6738,
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282,
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1330,
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198,
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44161,
282,
26599,
1330,
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198,
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44161,
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1330,
8655,
198,
6738,
44161,
282,
26599,
13,
25410,
1330,
25439,
198,
673... | 3.323741 | 139 |
from homeassistant import config_entries
from homeassistant.core import callback
from collections import OrderedDict
from .auth import get_master_token, get_access_token
from .const import (
DOMAIN,
CONF_USERNAME,
CONF_PASSWORD,
CONF_MASTER_TOKEN,
CONF_DEVICE_TYPES,
CONF_RSSI_THRESHOLD,
CONF_TRACK_ALARMS,
CONF_TRACK_DEVICES,
CONF_TRACK_NEW_DEVICES,
CONF_CONSIDER_HOME,
DEFAULT_DEVICE_TYPES,
DEFAULT_RSSI_THRESHOLD,
)
from homeassistant.components.device_tracker.const import DEFAULT_CONSIDER_HOME, DEFAULT_TRACK_NEW
import homeassistant.helpers.config_validation as cv
import voluptuous as vol
| [
6738,
1363,
562,
10167,
1330,
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62,
298,
1678,
198,
6738,
1363,
562,
10167,
13,
7295,
1330,
23838,
198,
6738,
17268,
1330,
14230,
1068,
35,
713,
198,
6738,
764,
18439,
1330,
651,
62,
9866,
62,
30001,
11,
651,
62,
15526,
62,
30001,... | 2.456274 | 263 |
import os.path as osp
from mmcv.utils import TORCH_VERSION
from mmcv.runner.dist_utils import master_only
from mmcv.runner import HOOKS
from torch.utils.data import DataLoader
from mmcv.runner.hooks.logger import LoggerHook
import torch
import numpy as np
from .utils import CompareMultiLayerDist
@HOOKS.register_module() | [
11748,
28686,
13,
6978,
355,
267,
2777,
198,
6738,
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33967,
13,
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62,
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1330,
4958,
62,
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198,
6738,
8085,
33967,
13,
16737,
1330,
367,
15308,... | 3.285714 | 98 |
from typing import Dict, Tuple
import torch
from classifier.classes.core.Model import Model
from classifier.classes.modules.text.transformer.Transformer import Transformer
| [
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360,
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198,
198,
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28034,
198,
198,
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1330,
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37724,
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18170,
13,
5239,
13,
7645,
16354,
13,
8291,
16354,
1330... | 3.888889 | 45 |
#!/usr/bin/env python
import tarfile
import urllib
import re
import StringIO
import os
basedir = 'src/jvm/io/fsq/twofishes/indexer/data/downloaded'
flickr_shapes_file_name = os.path.join(basedir, 'flickr_shapes_public_dataset_2.0.tar.gz')
try:
open(flickr_shapes_file_name)
except IOError as e:
print 'Downloading Flickr Shapes File to %s' % flickr_shapes_file_name
urllib.urlretrieve ('http://www.flickr.com/services/shapefiles/2.0/', flickr_shapes_file_name)
print 'done downloading'
old_tar = tarfile.open(flickr_shapes_file_name)
for file_info in old_tar:
print 'Processing %s' % file_info.name
old_data = old_tar.extractfile(file_info.name).read()
p = re.compile(',(\s+})')
new_data = p.sub('\\1', old_data)
print 'Writing updated %s' % file_info.name
new_file = open(os.path.join(basedir, file_info.name), "w")
new_file.write(new_data)
new_file.close()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
11748,
13422,
7753,
198,
11748,
2956,
297,
571,
198,
11748,
302,
198,
11748,
10903,
9399,
198,
11748,
28686,
198,
198,
3106,
343,
796,
705,
10677,
14,
73,
14761,
14,
952,
14,
9501... | 2.498599 | 357 |
from abc import ABC, abstractmethod
from typing import Optional
storage: Optional[AbstractStorage] = None
# Функция понадобится при внедрении зависимостей
| [
6738,
450,
66,
1330,
9738,
11,
12531,
24396,
198,
6738,
19720,
1330,
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628,
198,
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58,
23839,
31425,
60,
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6045,
628,
198,
2,
12466,
97,
35072,
22177,
31583,
141,
228,
18849,
40623,
12466,
123,
15166,
22177,... | 2.051282 | 78 |
import argparse
import os
import sys
import keras
import tensorflow as tf
# print(__name__,'__package__:',__package__)
if __name__ == "__main__" and __package__ is None:
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
import convnet3d.bin # noqa: F401
__package__ = "convnet3d.bin"
from .. import models
from .. import losses
from ..preprocessing.generator import Generator
from ..preprocessing.val_generator import ValidationGenerator
from ..utils.transform import randomTransformGenerator
from ..callbacks import (RedirectModel, Evaluate)
def get_session():
'''Construct a modified tf session
'''
# config = tf.ConfigProto(allow_soft_placement=True, log_device_placement=True)
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
return tf.Session(config=config)
def parse_args(args):
'''Parse the arguments
'''
parser = argparse.ArgumentParser(description='Simple training script for training the candidate screening model & false positive reduction model.')
subparsers = parser.add_subparsers(help='Specitic the model type: cs/fpr.', dest='model_type')
subparsers.required = True
cs_parser = subparsers.add_parser('cs') # noqa: F841
fpr_parser = subparsers.add_parser('fpr')
fpr_parser.add_argument('--val-cs-model', help='Path to candidate screening model, then the two model are combined to biuld a convnet3d model for validation.')
group = parser.add_mutually_exclusive_group()
group.add_argument('--snapshot')
group.add_argument('--no-weights', dest='val_cs_weights', action='store_const', const=False)
group.add_argument('--val-cs-weights', action='store_true')
parser.add_argument('annotations')
parser.add_argument('classes')
parser.add_argument('--val-annotations')
parser.add_argument('--batch-size', type=int, default=32)
parser.add_argument('--epochs', type=int, default=50)
parser.add_argument('--gpu', metavar='GPUs', type=devices, default=None)
parser.add_argument('--snapshot-path', default='./snapshots')
parser.add_argument('--tensorboard-dir', default='./logs')
parser.add_argument('--no-snapshots', dest='snapshots', action='store_false')
parser.add_argument('--random-transform', action='store_true')
parser.add_argument('--data-channels', default=1, type=int)
return check_args(parser.parse_args(args))
if __name__ == '__main__':
main()
| [
11748,
1822,
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198,
11748,
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198,
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198,
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4032,
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26495,
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25,
3256,
834,
26495,
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8,
198,
198,
361,
115... | 2.916766 | 841 |
import logging
import subprocess
logging.basicConfig(level = logging.INFO)
logger = logging.getLogger(__name__)
news_sites_uid = ['elpais']
if __name__ == '__main__':
main() | [
11748,
18931,
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62,
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7... | 2.710145 | 69 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
Update or create an Apple XCode project localization strings file.
TODO: handle localization domains
'''
from __future__ import with_statement
import sys
import os
import os.path
import re
import tempfile
import subprocess
import codecs
import unittest
import optparse
import shutil
import logging
ENCODINGS = ['utf16', 'utf8']
class LocalizedString(object):
''' A localized string from a strings file '''
COMMENT_EXPR = re.compile(
# Line start
'^\w*'
# Comment
'/\* (?P<comment>.+) \*/'
# End of line
'\w*$'
)
LOCALIZED_STRING_EXPR = re.compile(
# Line start
'^'
# Key
'"(?P<key>.+)"'
# Equals
' ?= ?'
# Value
'"(?P<value>.+)"'
# Whitespace
';'
# Comment
'(?: /\* (?P<comment>.+) \*/)?'
# End of line
'$'
)
@classmethod
def parse_comment(cls, comment):
'''
Extract the content of a comment line from a strings file.
Returns the comment string or None if the line doesn't match.
'''
result = cls.COMMENT_EXPR.match(comment)
if result != None:
return result.group('comment')
else:
return None
@classmethod
def from_line(cls, line):
'''
Extract the content of a string line from a strings file.
Returns a LocalizedString instance or None if the line doesn't match.
TODO: handle whitespace restore
'''
result = cls.LOCALIZED_STRING_EXPR.match(line)
if result != None:
return cls(
result.group('key'),
result.group('value'),
result.group('comment')
)
else:
return None
def is_raw(self):
'''
Return True if the localized string has not been translated.
'''
return self.value == self.key
def strings_from_folder(folder_path, extensions=None, exclude=None):
'''
Recursively scan folder_path for files containing localizable strings.
Run genstrings on these files and extract the strings.
Returns a dictionnary of LocalizedString instances, indexed by key.
'''
localized_strings = {}
code_file_paths = []
if extensions == None:
extensions = frozenset(['m', 'mm'])
if exclude == None:
exclude = frozenset(['ImportedSources','Pods'])
logging.debug('Scanning for source files in %s', folder_path)
for dir_path, dir_names, file_names in os.walk(folder_path):
dir_names[:] = [d for d in dir_names if d not in exclude]
for file_name in file_names:
extension = file_name.rpartition('.')[2]
if extension in extensions:
code_file_path = os.path.join(dir_path, file_name)
code_file_paths.append(code_file_path)
logging.debug('Found %d files', len(code_file_paths))
logging.debug('Running genstrings')
temp_folder_path = tempfile.mkdtemp()
arguments = ['genstrings', '-u', '-o', temp_folder_path]
arguments.extend(code_file_paths)
logging.debug('Here are the argumengts %s', arguments)
subprocess.call(arguments)
temp_file_path = os.path.join(temp_folder_path, 'Localizable.strings')
if os.path.exists(temp_file_path):
logging.debug('Analysing genstrings content')
localized_strings = strings_from_file(temp_file_path)
os.remove(temp_file_path)
else:
logging.debug('No translations found')
shutil.rmtree(temp_folder_path)
return localized_strings
def strings_from_file(file_path):
'''
Try to autodetect file encoding and call strings_from_encoded_file on the
file at file_path.
Returns a dictionnary of LocalizedString instances, indexed by key.
Returns an empty dictionnary if the encoding is wrong.
'''
for current_encoding in ENCODINGS:
try:
return strings_from_encoded_file(file_path, current_encoding)
except UnicodeError:
pass
logging.error(
'Cannot determine encoding for file %s among %s',
file_path,
', '.join(ENCODINGS)
)
return {}
def strings_from_encoded_file(file_path, encoding):
'''
Extract the strings from the file at file_path.
Returns a dictionnary of LocalizedString instances, indexed by key.
'''
localized_strings = {}
with codecs.open(file_path, 'r', encoding) as content:
comment = None
for line in content:
line = line.strip()
if not line:
comment = None
continue
current_comment = LocalizedString.parse_comment(line)
if current_comment:
if current_comment != 'No comment provided by engineer.':
comment = current_comment
continue
localized_string = LocalizedString.from_line(line)
if localized_string:
if not localized_string.comment:
localized_string.comment = comment
localized_strings[localized_string.key] = localized_string
else:
logging.error('Could not parse: %s', line.strip())
return localized_strings
def strings_to_file(localized_strings, file_path, encoding='utf16'):
'''
Write a strings file at file_path containing string in
the localized_strings dictionnary.
The strings are alphabetically sorted.
'''
with codecs.open(file_path, 'w', encoding) as output:
for localized_string in sorted_strings_from_dict(localized_strings):
output.write('%s\n' % localized_string)
def update_file_with_strings(file_path, localized_strings):
'''
Try to autodetect file encoding and call update_encoded_file_with_strings
on the file at file_path.
The file at file_path must exist or this function will raise an exception.
'''
for current_encoding in ENCODINGS:
try:
return update_encoded_file_with_strings(
file_path,
localized_strings,
current_encoding
)
except UnicodeError:
pass
logging.error(
'Cannot determine encoding for file %s among %s',
file_path,
', '.join(ENCODINGS)
)
return {}
def update_encoded_file_with_strings(
file_path,
localized_strings,
encoding='utf16'
):
'''
Update file at file_path with translations from localized_strings, trying
to preserve the initial formatting by only removing the old translations,
updating the current ones and adding the new translations at the end of
the file.
The file at file_path must exist or this function will raise an exception.
'''
output_strings = []
keys = set()
with codecs.open(file_path, 'r', encoding) as content:
for line in content:
current_string = LocalizedString.from_line(line.strip())
if current_string:
key = current_string.key
localized_string = localized_strings.get(key, None)
if localized_string:
keys.add(key)
output_strings.append(unicode(localized_string))
else:
output_strings.append(line[:-1])
new_strings = []
for value in localized_strings.itervalues():
if value.key not in keys:
new_strings.append(unicode(value))
if len(new_strings) != 0:
output_strings.append('')
output_strings.append('/* New strings */')
new_strings.sort()
output_strings.extend(new_strings)
with codecs.open(file_path, 'w', encoding) as output:
output.write('\n'.join(output_strings))
# Always add a new line at the end of the file
output.write('\n')
def match_strings(scanned_strings, reference_strings):
'''
Complete scanned_strings with translations from reference_strings.
Return the completed scanned_strings dictionnary.
scanned_strings is not affected.
Strings in reference_strings and not in scanned_strings are not copied.
'''
final_strings = {}
for key, value in scanned_strings.iteritems():
reference_value = reference_strings.get(key, None)
if reference_value:
if reference_value.is_raw():
# Mark non-translated strings
logging.debug('[raw] %s', key)
final_strings[key] = value
else:
# Reference comment comes from the code
reference_value.comment = value.comment
final_strings[key] = reference_value
else:
logging.debug('[new] %s', key)
final_strings[key] = value
final_keys = set(final_strings.keys())
for key in reference_strings.iterkeys():
if key not in final_keys:
logging.debug('[deleted] %s', key)
return final_strings
def merge_dictionaries(reference_dict, import_dict):
'''
Return a dictionnary containing key/values from reference_dict
and import_dict.
In case of conflict, the value from reference_dict is chosen.
'''
final_dict = reference_dict.copy()
reference_dict_keys = set(reference_dict.keys())
for key, value in import_dict.iteritems():
if key not in reference_dict_keys:
final_dict[key] = value
return final_dict
def sorted_strings_from_dict(strings):
'''
Return an array containing the string objects sorted alphabetically.
'''
keys = strings.keys()
keys.sort()
values = []
for key in keys:
values.append(strings[key])
return values
class Tests(unittest.TestCase):
''' Unit Tests '''
def test_comment(self):
''' Test comment pattern '''
result = LocalizedString.COMMENT_EXPR.match('/* Testing Comments */')
self.assertNotEqual(result, None, 'Pattern not recognized')
self.assertEqual(result.group('comment'), 'Testing Comments',
'Incorrect pattern content: [%s]' % result.group('comment')
)
def test_localized_string(self):
''' Test localized string pattern '''
result = LocalizedString.LOCALIZED_STRING_EXPR.match(
'"KEY" = "VALUE";'
)
self.assertNotEqual(result, None, 'Pattern not recognized')
self.assertEqual(result.group('key'), 'KEY',
'Incorrect comment content: [%s]' % result.group('key')
)
self.assertEqual(result.group('value'), 'VALUE',
'Incorrect comment content: [%s]' % result.group('value')
)
self.assertEqual(result.group('comment'), None,
'Incorrect comment content: [%s]' % result.group('comment')
)
def test_localized_comment_string(self):
''' Test localized string with comment pattern '''
result = LocalizedString.LOCALIZED_STRING_EXPR.match(
'"KEY" = "VALUE"; /* COMMENT */'
)
self.assertNotEqual(result, None, 'Pattern not recognized')
self.assertEqual(result.group('key'), 'KEY',
'Incorrect comment content: [%s]' % result.group('key')
)
self.assertEqual(result.group('value'), 'VALUE',
'Incorrect comment content: [%s]' % result.group('value')
)
self.assertEqual(result.group('comment'), 'COMMENT',
'Incorrect comment content: [%s]' % result.group('comment')
)
def main():
''' Parse the command line and do what it is telled to do '''
parser = optparse.OptionParser(
'usage: %prog [options] Localizable.strings [source folders]'
)
parser.add_option(
'-v',
'--verbose',
action='store_true',
dest='verbose',
default=False,
help='Show debug messages'
)
parser.add_option(
'',
'--dry-run',
action='store_true',
dest='dry_run',
default=False,
help='Do not write to the strings file'
)
parser.add_option(
'',
'--import',
dest='import_file',
help='Import strings from FILENAME'
)
parser.add_option(
'',
'--overwrite',
action='store_true',
dest='overwrite',
default=False,
help='Overwrite the strings file, ignores original formatting'
)
parser.add_option(
'',
'--unittests',
action='store_true',
dest='unittests',
default=False,
help='Run unit tests (debug)'
)
(options, args) = parser.parse_args()
logging.basicConfig(
format='%(message)s',
level=options.verbose and logging.DEBUG or logging.INFO
)
if options.unittests:
suite = unittest.TestLoader().loadTestsFromTestCase(Tests)
return unittest.TextTestRunner(verbosity=2).run(suite)
if len(args) == 0:
parser.error('Please specify a strings file')
strings_file = args[0]
input_folders = ['.']
if len(args) > 1:
input_folders = args[1:]
scanned_strings = {}
for input_folder in input_folders:
if not os.path.isdir(input_folder):
logging.error('Input path is not a folder: %s', input_folder)
return 1
# TODO: allow to specify file extensions to scan
scanned_strings = merge_dictionaries(
scanned_strings,
strings_from_folder(input_folder)
)
if options.import_file:
logging.debug(
'Reading import file: %s',
options.import_file
)
reference_strings = strings_from_file(options.import_file)
scanned_strings = match_strings(
scanned_strings,
reference_strings
)
if os.path.isfile(strings_file):
logging.debug(
'Reading strings file: %s',
strings_file
)
reference_strings = strings_from_file(
strings_file
)
scanned_strings = match_strings(
scanned_strings,
reference_strings
)
if options.dry_run:
logging.info(
'Dry run: the strings file has not been updated'
)
else:
try:
if os.path.exists(strings_file) and not options.overwrite:
update_file_with_strings(strings_file, scanned_strings)
else:
strings_to_file(scanned_strings, strings_file)
except IOError, exc:
logging.error('Error writing to file %s: %s', strings_file, exc)
return 1
logging.info(
'Strings were generated in %s',
strings_file
)
return 0
if __name__ == '__main__':
sys.exit(main())
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
198,
7061,
6,
198,
10260,
393,
2251,
281,
4196,
1395,
10669,
1628,
42842,
13042,
2393,
13,
198,
198,
51,
3727,
46,
25... | 2.315552 | 6,430 |
from enum import Enum, auto
| [
6738,
33829,
1330,
2039,
388,
11,
8295,
628
] | 3.625 | 8 |
"""
Sending additional var-binds
++++++++++++++++++++++++++++
Send SNMP notification using the following options:
* SNMPv2c
* with community name 'public'
* over IPv4/UDP
* send INFORM notification
* with TRAP ID 'coldStart' specified as a MIB symbol
* include managed object information specified as a MIB symbol
Functionally similar to:
| $ snmpinform -v2c -c public demo.snmplabs.com 12345 1.3.6.1.6.3.1.1.5.1 1.3.6.1.2.1.1.1.0 s "my system"
"""#
from pysnmp.hlapi import *
errorIndication, errorStatus, errorIndex, varBinds = next(
sendNotification(
SnmpEngine(),
CommunityData('public'),
UdpTransportTarget(('demo.snmplabs.com', 162)),
ContextData(),
'inform',
NotificationType(
ObjectIdentity('SNMPv2-MIB', 'coldStart')
).addVarBinds(
ObjectType(ObjectIdentity('SNMPv2-MIB', 'sysName', 0), 'my system')
)
)
)
if errorIndication:
print(errorIndication)
elif errorStatus:
print('%s at %s' % (errorStatus.prettyPrint(),
errorIndex and varBinds[int(errorIndex) - 1][0] or '?'))
else:
for varBind in varBinds:
print(' = '.join([x.prettyPrint() for x in varBind]))
| [
37811,
198,
50,
1571,
3224,
1401,
12,
21653,
82,
198,
44627,
25128,
14030,
198,
198,
25206,
11346,
7378,
14483,
1262,
262,
1708,
3689,
25,
198,
198,
9,
11346,
7378,
85,
17,
66,
198,
9,
351,
2055,
1438,
705,
11377,
6,
198,
9,
625,
... | 2.390533 | 507 |
"""
Author: Remy Priem (remy.priem@onera.fr)
This package is distributed under New BSD license.
"""
from __future__ import division
import numpy as np
from scipy import linalg
from smt.utils.kriging_utils import differences
from smt.surrogate_models.krg_based import KrgBased
from smt.utils.kriging_utils import componentwise_distance
"""
The Active kriging class.
"""
| [
37811,
198,
13838,
25,
32912,
4389,
368,
357,
260,
1820,
13,
3448,
368,
31,
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13,
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8,
198,
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1212,
5301,
318,
9387,
739,
968,
347,
10305,
5964,
13,
198,
37811,
198,
198,
6738,
11593,
37443,
834,
1330,
7297,
198,
117... | 3.090909 | 121 |
import FWCore.ParameterSet.Config as cms
TrackerTFPProducer_params = cms.PSet (
LabelDTC = cms.string( "TrackerDTCProducer" ), #
LabelGP = cms.string( "TrackerTFPProducerGP" ), #
LabelHT = cms.string( "TrackerTFPProducerHT" ), #
LabelMHT = cms.string( "TrackerTFPProducerMHT" ), #
LabelZHT = cms.string( "TrackerTFPProducerZHT" ), #
LabelZHTout = cms.string( "TrackerTFPProducerZHTout" ), #
LabelKFin = cms.string( "TrackerTFPProducerKFin" ), #
LabelKF = cms.string( "TrackerTFPProducerKF" ), #
LabelDR = cms.string( "TrackerTFPProducerDR" ), #
LabelTT = cms.string( "TrackerTFPProducerTT" ), #
LabelAS = cms.string( "TrackerTFPProducerAS" ), #
BranchAcceptedStubs = cms.string( "StubAccepted" ), # branch for prodcut with passed stubs
BranchAcceptedTracks = cms.string( "TrackAccepted" ), # branch for prodcut with passed tracks
BranchLostStubs = cms.string( "StubLost" ), # branch for prodcut with lost stubs
BranchLostTracks = cms.string( "TracksLost" ), # branch for prodcut with lost tracks
CheckHistory = cms.bool ( False ), # checks if input sample production is configured as current process
EnableTruncation = cms.bool ( True ) # enable emulation of truncation, lost stubs are filled in BranchLost
) | [
11748,
48849,
14055,
13,
36301,
7248,
13,
16934,
355,
269,
907,
198,
198,
35694,
51,
5837,
11547,
2189,
62,
37266,
796,
269,
907,
13,
3705,
316,
357,
628,
220,
36052,
35,
4825,
220,
220,
220,
220,
220,
220,
220,
220,
796,
269,
907,
... | 2.268519 | 648 |
from organization.views import OrgView,AddUserAskView,OrgHomeView,OrgCourseView,OrgDescView,\
OrgTeacherView,AddFavView,TeacherListView,TeacherDetailView
from django.conf.urls import url,include
#from django.urls import path,re_path
# 要写上app的名字
app_name = "organization"
urlpatterns = [
#课程机构列表页
url(r'^list/$', OrgView.as_view(), name="org_list"),
url(r'^add_ask/$', AddUserAskView.as_view(), name="add_ask"),
url(r'^home/(?P<org_id>\d+)/$', OrgHomeView.as_view(), name="org_home"),
url(r'^course/(?P<org_id>\d+)/$', OrgCourseView.as_view(), name="org_course"),
url(r'^desc/(?P<org_id>\d+)/', OrgDescView.as_view(), name="org_desc"),
url(r'^teacher/(?P<org_id>\d+)/', OrgTeacherView.as_view(), name="org_teacher"),
url(r'^add_fav/$', AddFavView.as_view(), name="add_fav"),
# 讲师列表
url(r'^teacher/list/', TeacherListView.as_view(), name="teacher_list"),
# 讲师详情
url(r'teacher/detail/(?P<teacher_id>\d+)/', TeacherDetailView.as_view(), name="teacher_detail"),
] | [
6738,
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1471,
70,
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7680,
11,
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37,
615,
7680,
11,
... | 2.121593 | 477 |
"""Tests for rhasspyhermes.wake"""
from rhasspyhermes.wake import HotwordDetected, HotwordToggleOff, HotwordToggleOn
wakeword_id = "testWakeWord"
def test_hotword_detected():
"""Test HotwordDetected."""
assert HotwordDetected.is_topic(HotwordDetected.topic(wakeword_id=wakeword_id))
assert (
HotwordDetected.get_wakeword_id(HotwordDetected.topic(wakeword_id=wakeword_id))
== wakeword_id
)
def test_hotword_toggle_on():
"""Test HotwordToggleOn."""
assert HotwordToggleOn.topic() == "hermes/hotword/toggleOn"
def test_hotword_toggle_off():
"""Test HotwordToggleOff."""
assert HotwordToggleOff.topic() == "hermes/hotword/toggleOff"
| [
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4... | 2.581132 | 265 |
import json
import os
from tqdm import tqdm
import geojson
import shapefile
from geography.models import Geometry
| [
11748,
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] | 3.441176 | 34 |
"""Provide tests for the node value."""
from openzwavemqtt.const import (
EVENT_VALUE_ADDED,
EVENT_VALUE_CHANGED,
EVENT_VALUE_REMOVED,
)
def test_value_events(mgr):
"""Test value events."""
events = []
# Fill parent data.
mgr.mock_receive_json("OpenZWave/1/node/2", {})
mgr.mock_receive_json("OpenZWave/1/node/2/instance/1", {})
mgr.mock_receive_json("OpenZWave/1/node/2/instance/1/commandclass/4", {})
# Listen for value added
mgr.options.listen(EVENT_VALUE_ADDED, events.append)
mgr.mock_receive_json(
"OpenZWave/1/node/2/instance/1/commandclass/4/value/3", {"Value": "yo"}
)
assert len(events) == 1
assert events[0].id == 3
assert events[0].value == "yo"
assert events[0].parent.id == 4
# Test OZWNode.values shortcut
assert list(mgr.get_instance(1).get_node(2).values())[0].id == 3
# Listen for value changed
mgr.options.listen(EVENT_VALUE_CHANGED, events.append)
mgr.mock_receive_json(
"OpenZWave/1/node/2/instance/1/commandclass/4/value/3", {"Value": "yo2"}
)
assert len(events) == 2
assert events[0].id == 3
assert events[0].value == "yo2"
# Show how to use collection helpers
assert (
list(mgr.get_instance(1).get_node(2).get_instance(1).commandclasses())[0]
.get_value(3)
.value
== "yo2"
)
# Listen for value removed
mgr.options.listen(EVENT_VALUE_REMOVED, events.append)
mgr.receive_message("OpenZWave/1/node/2/instance/1/commandclass/4/value/3", "")
assert len(events) == 3
assert events[0].id == 3
| [
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155... | 2.291845 | 699 |
#!/usr/bin/python
# Import the PCA9685 module.
import Adafruit_PCA9685
import time
import random
import sys
import json
# Initialise the PCA9685 using the default address (0x40).
pwm = Adafruit_PCA9685.PCA9685(0x40)
pwm.set_pwm_freq(60)
SRV_OPTIONS = []
ACTIONS = {}
STATUS=""
thingfile = "/home/pi/pimeup/thingbox/thing.json"
thingactionfile = "/home/pi/pimeup/thingbox/thingactions.json"
if __name__ == "__main__":
main()
| [
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20... | 2.445055 | 182 |
## Copyright 2015-2019 Ilgar Lunin, Pedro Cabrera
## 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 nine import str
from blinker import Signal
from PyFlow.Core.GraphBase import GraphBase
from PyFlow.Core.Common import *
from PyFlow.Core import version
ROOT_GRAPH_NAME = str('root')
class GraphManager(object):
"""Data structure that holds graph tree
This class switches active graph. Can insert or remove graphs to tree,
can search nodes and variables across all graphs. Also this class responsible
for giving unique names.
"""
def findRootGraph(self):
"""Returns top level root graph
:rtype: :class:`~PyFlow.Core.GraphBase.GraphBase`
"""
roots = []
for graph in self.getAllGraphs():
if graph.isRoot():
roots.append(graph)
assert(len(roots) == 1), "Fatal! Multiple roots!"
return roots[0]
def selectRootGraph(self):
"""Selects root graph
"""
self.selectGraph(self.findRootGraph())
def serialize(self):
"""Serializes itself to json.
All child graphs will be serialized.
:rtype: dict
"""
rootGraph = self.findRootGraph()
saved = rootGraph.serialize()
saved["fileVersion"] = str(version.currentVersion())
saved["activeGraph"] = self.activeGraph().name
return saved
def removeGraphByName(self, name):
"""Removes graph by :attr:`~PyFlow.Core.GraphBase.GraphBase.name`
:param name: name of graph to be removed
:type name: str
"""
graph = self.findGraph(name)
if graph is not None:
graph.clear()
self._graphs.pop(graph.uid)
if graph.parentGraph is not None:
if graph in graph.parentGraph.childGraphs:
graph.parentGraph.childGraphs.remove(graph)
del graph
def removeGraph(self, graph):
"""Removes supplied graph
:param graph: Graph to be removed
:type graph: :class:`~PyFlow.Core.GraphBase.GraphBase`
"""
if graph.uid in self._graphs:
graph.clear()
self._graphs.pop(graph.uid)
if graph.parentGraph is not None:
if graph in graph.parentGraph.childGraphs:
graph.parentGraph.childGraphs.remove(graph)
del graph
def deserialize(self, data):
"""Populates itself from serialized data
:param data: Serialized data
:type data: dict
"""
if "fileVersion" in data:
fileVersion = version.Version.fromString(data["fileVersion"])
else:
# handle older version
pass
self.clear(keepRoot=False)
self._activeGraph = GraphBase(str('root'), self)
self._activeGraph.populateFromJson(data)
self._activeGraph.setIsRoot(True)
self.selectGraph(self._activeGraph)
def clear(self, keepRoot=True, *args, **kwargs):
"""Wipes everything.
:param keepRoot: Whether to remove root graph or not
:type keepRoot: bool
"""
self.selectGraphByName(ROOT_GRAPH_NAME)
self.removeGraphByName(ROOT_GRAPH_NAME)
self._graphs.clear()
self._graphs = {}
del self._activeGraph
self._activeGraph = None
if keepRoot:
self._activeGraph = GraphBase(ROOT_GRAPH_NAME, self)
self.selectGraph(self._activeGraph)
self._activeGraph.setIsRoot(True)
def Tick(self, deltaTime):
"""Periodically calls :meth:`~PyFlow.Core.GraphBase.GraphBase.Tick` on all graphs
:param deltaTime: Elapsed time from last call
:type deltaTime: float
"""
for graph in self._graphs.values():
graph.Tick(deltaTime)
def findVariableRefs(self, variable):
"""Returns a list of variable accessors spawned across all graphs
:param variable: Variable to search accessors for
:type variable: :class:`~PyFlow.Core.Variable.Variable`
:rtype: list(:class:`~PyFlow.Core.NodeBase.NodeBase`)
"""
result = []
for node in self.getAllNodes(classNameFilters=['getVar', 'setVar']):
if node.variableUid() == variable.uid:
result.append(node)
return result
def findGraph(self, name):
"""Tries to find graph by :attr:`~PyFlow.Core.GraphBase.GraphBase.name`
:param name: Name of target graph
:type name: str
:rtype: :class:`~PyFlow.Core.GraphBase.GraphBase` or None
"""
graphs = self.getGraphsDict()
if name in graphs:
return graphs[name]
return None
def findPinByName(self, pinFullName):
"""Tries to find pin by name across all graphs
:param pinFullName: Full name of pin including node namespace
:type pinFullName: str
:rtype: :class:`~PyFlow.Core.PinBase.PinBase` or None
"""
result = None
for graph in self.getAllGraphs():
result = graph.findPin(pinFullName)
if result is not None:
break
return result
def findNode(self, name):
"""Finds a node across all graphs
:param name: Node name to search by
:type name: str
:rtype: :class:`~PyFlow.Core.NodeBase.NodeBase`
"""
result = None
for graph in self.getAllGraphs():
result = graph.findNode(name)
if result is not None:
break
return result
def findVariableByUid(self, uuid):
"""Finds a variable across all graphs
:param uuid: Variable unique identifier
:type uuid: :class:`~uuid.UUID`
:rtype: :class:`~PyFlow.Core.Variable.Variable` or None
"""
result = None
for graph in self._graphs.values():
if uuid in graph.getVars():
result = graph.getVars()[uuid]
break
return result
def findVariableByName(self, name):
"""Finds a variable across all graphs
:param name: Variable name
:type name: str
:rtype: :class:`~PyFlow.Core.Variable.Variable` or None
"""
for graph in self._graphs.values():
for var in graph.getVars().values():
if var.name == name:
return var
return None
def location(self):
"""Returns location of active graph
.. seealso ::
:meth:`PyFlow.Core.GraphBase.GraphBase.location`
"""
return self.activeGraph().location()
def getGraphsDict(self):
"""Creates and returns dictionary where graph name associated with graph
:rtype: dict(str, :class:`~PyFlow.Core.GraphBase.GraphBase`)
"""
result = {}
for graph in self.getAllGraphs():
result[graph.name] = graph
return result
def add(self, graph):
"""Adds graph to storage and ensures that graph name is unique
:param graph: Graph to add
:type graph: :class:`~PyFlow.Core.GraphBase.GraphBase`
"""
graph.name = self.getUniqGraphName(graph.name)
self._graphs[graph.uid] = graph
def activeGraph(self):
"""Returns active graph
:rtype: :class:`~PyFlow.Core.GraphBase.GraphBase`
"""
return self._activeGraph
def selectGraphByName(self, name):
"""Sets active graph by graph name and fires event
:param name: Name of target graph
:type name: str
"""
graphs = self.getGraphsDict()
if name in graphs:
if name != self.activeGraph().name:
oldGraph = self.activeGraph()
newGraph = graphs[name]
self._activeGraph = newGraph
self.graphChanged.send(self.activeGraph())
def selectGraph(self, graph):
"""Sets supplied graph as active and fires event
:param graph: Target graph
:type graph: :class:`~PyFlow.Core.GraphBase.GraphBase`
"""
for newGraph in self.getAllGraphs():
if newGraph.name == graph.name:
if newGraph.name != self.activeGraph().name:
oldGraph = self.activeGraph()
self._activeGraph = newGraph
self.graphChanged.send(self.activeGraph())
break
def getAllGraphs(self):
"""Returns all graphs
:rtype: list(:class:`~PyFlow.Core.GraphBase.GraphBase`)
"""
return [g for g in self._graphs.values()]
def getAllNodes(self, classNameFilters=[]):
"""Returns all nodes across all graphs
:param classNameFilters: If class name filters specified, only those node classes will be considered
:type classNameFilters: list(str)
:rtype: list(:class:`~PyFlow.Core.NodeBase.NodeBase`)
"""
allNodes = []
for graph in self.getAllGraphs():
if len(classNameFilters) == 0:
allNodes.extend(list(graph.getNodes().values()))
else:
allNodes.extend([node for node in graph.getNodes().values() if node.__class__.__name__ in classNameFilters])
return allNodes
def getAllVariables(self):
"""Returns a list of all variables
:rtype: list(:class:`~PyFlow.Core.Variable.Variable`)
"""
result = []
for graph in self.getAllGraphs():
result.extend(list(graph.getVars().values()))
return result
def getUniqGraphPinName(self, graph, name):
"""Returns unique pin name for graph
Used by compound node and graphInputs graphOutputs nodes.
To make all exposed to compound pins names unique.
:param graph: Target graph
:type graph: :class:`~PyFlow.Core.GraphBase.GraphBase`
:param name: Target pin name
:type name: str
:rtype: str
"""
existingNames = []
for node in graph.getNodesList(classNameFilters=['graphInputs', 'graphOutputs']):
existingNames.extend([pin.name for pin in node.pins])
return getUniqNameFromList(existingNames, name)
def getAllNames(self):
"""Returns list of all registered names
Includes graphs, nodes, pins, variables names
:rtype: list(str)
"""
existingNames = [g.name for g in self.getAllGraphs()]
existingNames.extend([n.name for n in self.getAllNodes()])
existingNames.extend([var.name for var in self.getAllVariables()])
for node in self.getAllNodes():
existingNames.extend([pin.name for pin in node.pins])
return existingNames
def getUniqName(self, name):
"""Returns unique name
:param name: Source name
:type name: str
:rtype: str
"""
existingNames = self.getAllNames()
return getUniqNameFromList(existingNames, name)
def getUniqGraphName(self, name):
"""Returns unique graph name
:param name: Source name
:type name: str
:rtype: str
"""
existingNames = [g.name for g in self.getAllGraphs()]
return getUniqNameFromList(existingNames, name)
def getUniqNodeName(self, name):
"""Returns unique node name
:param name: Source name
:type name: str
:rtype: str
"""
existingNames = [n.name for n in self.getAllNodes()]
return getUniqNameFromList(existingNames, name)
def getUniqVariableName(self, name):
"""Returns unique variable name
:param name: Source name
:type name: str
:rtype: str
"""
existingNames = [var.name for var in self.getAllVariables()]
return getUniqNameFromList(existingNames, name)
def plot(self):
"""Prints all data to console. May be useful for debugging
"""
root = self.findRootGraph()
print("Active graph: {0}".format(str(self.activeGraph().name)), "All graphs:", [g.name for g in self._graphs.values()])
root.plot()
@SingletonDecorator
class GraphManagerSingleton(object):
"""Singleton class that holds graph manager instance inside. Used by app as main graph manager
"""
def get(self):
"""Returns graph manager instance
:rtype: :class:`~PyFlow.Core.GraphManager.GraphManager`
"""
return self.man
| [
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... | 2.342471 | 5,545 |
# (C) Datadog, Inc. 2020-present
# All rights reserved
# Licensed under a 3-clause BSD style license (see LICENSE)
import os
from typing import Callable, Dict, List, Set, Tuple, Union
import pytest
from datadog_checks.base.stubs.aggregator import AggregatorStub
from datadog_checks.dev import get_docker_hostname, get_here
from .types import ServerName
HERE = get_here()
IMAGE = os.environ.get('RETHINKDB_IMAGE', '')
RAW_VERSION = os.environ.get('RETHINKDB_RAW_VERSION', '')
IS_RETHINKDB_2_3 = RAW_VERSION.startswith('2.3.')
HOST = get_docker_hostname()
TAGS = ['rethinkdb_env:testing']
# Servers.
# NOTE: server information is tightly coupled to the Docker Compose setup.
SERVERS = {'server0', 'server1', 'server2'} # type: Set[ServerName]
BOOTSTRAP_SERVER = 'server0' # type: ServerName
SERVER_PORTS = {'server0': 28015, 'server1': 28016, 'server2': 28017, 'proxy': 28018} # type: Dict[ServerName, int]
FORMATTED_SERVER_TAGS = {
'server0': ['server_tag:default', 'server_tag:us'],
'server1': ['server_tag:default', 'server_tag:us', 'server_tag:primary'],
'server2': ['server_tag:default', 'server_tag:eu'],
} # type: Dict[ServerName, List[str]]
# Users.
if IS_RETHINKDB_2_3:
# In RethinkDB 2.3.x, granting permissions onto `rethinkdb` database to non-admin users is not supported.
# So we must use the admin account.
# See: https://github.com/rethinkdb/rethinkdb/issues/5692
AGENT_USER = 'admin'
AGENT_PASSWORD = ''
else:
# Use a dedicated user for metric collection.
AGENT_USER = 'datadog-agent'
AGENT_PASSWORD = 'r3th1nK'
CLIENT_USER = 'doggo'
# TLS.
TLS_SERVER = 'server1' # type: ServerName
TLS_DRIVER_KEY = os.path.join(HERE, 'data', 'tls', 'server.key')
TLS_DRIVER_CERT = os.path.join(HERE, 'data', 'tls', 'server.pem')
TLS_CLIENT_CERT = os.path.join(HERE, 'data', 'tls', 'client.pem')
# Database content.
DATABASE = 'doghouse'
HEROES_TABLE = 'heroes'
HEROES_TABLE_CONFIG = {
'shards': 1,
'replicas': {'primary': 1, 'eu': 1},
'primary_replica_tag': 'primary',
}
HEROES_TABLE_SERVERS = {'server1', 'server2'} # type: Set[ServerName]
HEROES_TABLE_PRIMARY_REPLICA = 'server1' # type: ServerName
HEROES_TABLE_REPLICAS_BY_SHARD = {0: HEROES_TABLE_SERVERS}
HEROES_TABLE_DOCUMENTS = [
{
"hero": "Magneto",
"name": "Max Eisenhardt",
"aka": ["Magnus", "Erik Lehnsherr", "Lehnsherr"],
"magazine_titles": ["Alpha Flight", "Avengers", "Avengers West Coast"],
"appearances_count": 42,
},
{
"hero": "Professor Xavier",
"name": "Charles Francis Xavier",
"magazine_titles": ["Alpha Flight", "Avengers", "Bishop", "Defenders"],
"appearances_count": 72,
},
{
"hero": "Storm",
"name": "Ororo Monroe",
"magazine_titles": ["Amazing Spider-Man vs. Wolverine", "Excalibur", "Fantastic Four", "Iron Fist"],
"appearances_count": 72,
},
]
HEROES_TABLE_INDEX_FIELD = 'appearances_count'
# Metrics lists.
# NOTE: jobs metrics are not listed here as they're hard to trigger, so they're covered by unit tests instead.
CONFIG_METRICS = (
(
'rethinkdb.config.servers',
AggregatorStub.GAUGE,
lambda disconnected_servers: len(SERVERS) - len(disconnected_servers),
[],
),
('rethinkdb.config.databases', AggregatorStub.GAUGE, 1, []),
('rethinkdb.config.tables_per_database', AggregatorStub.GAUGE, 1, ['database:{}'.format(DATABASE)]),
('rethinkdb.config.secondary_indexes_per_table', AggregatorStub.GAUGE, 1, ['table:{}'.format(HEROES_TABLE)]),
) # type: Tuple[Tuple[str, int, Union[int, Callable[[set], int]], List[str]], ...]
CLUSTER_STATISTICS_METRICS = (
('rethinkdb.stats.cluster.query_engine.queries_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.cluster.query_engine.read_docs_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.cluster.query_engine.written_docs_per_sec', AggregatorStub.GAUGE),
) # type: Tuple[Tuple[str, int], ...]
SERVER_STATISTICS_METRICS = (
('rethinkdb.stats.server.query_engine.queries_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.server.query_engine.queries_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.server.query_engine.read_docs_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.server.query_engine.read_docs_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.server.query_engine.written_docs_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.server.query_engine.written_docs_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.server.query_engine.client_connections', AggregatorStub.GAUGE),
(
# NOTE: submitted but not documented on the RethinkDB website.
'rethinkdb.stats.server.query_engine.clients_active',
AggregatorStub.GAUGE,
),
) # type: Tuple[Tuple[str, int], ...]
TABLE_STATISTICS_METRICS = (
('rethinkdb.stats.table.query_engine.read_docs_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.table.query_engine.written_docs_per_sec', AggregatorStub.GAUGE),
) # type: Tuple[Tuple[str, int], ...]
REPLICA_STATISTICS_METRICS = (
('rethinkdb.stats.table_server.query_engine.read_docs_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.query_engine.read_docs_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.table_server.query_engine.written_docs_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.query_engine.written_docs_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.table_server.storage_engine.cache.in_use_bytes', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.storage_engine.disk.read_bytes_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.storage_engine.disk.read_bytes_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.table_server.storage_engine.disk.written_bytes_per_sec', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.storage_engine.disk.written_bytes_total', AggregatorStub.MONOTONIC_COUNT),
('rethinkdb.stats.table_server.storage_engine.disk.space_usage.metadata_bytes', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.storage_engine.disk.space_usage.data_bytes', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.storage_engine.disk.space_usage.garbage_bytes', AggregatorStub.GAUGE),
('rethinkdb.stats.table_server.storage_engine.disk.space_usage.preallocated_bytes', AggregatorStub.GAUGE),
) # type: Tuple[Tuple[str, int], ...]
TABLE_STATUS_SERVICE_CHECKS = (
'rethinkdb.table_status.status.ready_for_outdated_reads',
'rethinkdb.table_status.status.ready_for_reads',
'rethinkdb.table_status.status.ready_for_writes',
'rethinkdb.table_status.status.all_replicas_ready',
)
TABLE_STATUS_METRICS = (('rethinkdb.table_status.shards', AggregatorStub.GAUGE),) # type: Tuple[Tuple[str, int], ...]
TABLE_STATUS_SHARDS_METRICS = (
('rethinkdb.table_status.shards.replicas', AggregatorStub.GAUGE),
('rethinkdb.table_status.shards.primary_replicas', AggregatorStub.GAUGE),
) # type: Tuple[Tuple[str, int], ...]
SERVER_STATUS_METRICS = (
('rethinkdb.server_status.network.time_connected', AggregatorStub.GAUGE),
('rethinkdb.server_status.network.connected_to', AggregatorStub.GAUGE),
('rethinkdb.server_status.process.time_started', AggregatorStub.GAUGE),
) # type: Tuple[Tuple[str, int], ...]
JOBS_METRICS = (
(
'rethinkdb.system_jobs.jobs',
AggregatorStub.GAUGE,
1,
['job_type:query'],
),
) # type: Tuple[Tuple[str, int, int, List[str]], ...]
CURRENT_ISSUES_METRICS = (
('rethinkdb.current_issues.issues', AggregatorStub.GAUGE),
('rethinkdb.current_issues.critical_issues', AggregatorStub.GAUGE),
) # type: Tuple[Tuple[str, int], ...]
CURRENT_ISSUE_TYPES_SUBMITTED_IF_DISCONNECTED_SERVERS = ['table_availability']
E2E_METRICS = (
tuple((name, typ) for name, typ, _, _ in CONFIG_METRICS)
+ CLUSTER_STATISTICS_METRICS
+ SERVER_STATISTICS_METRICS
+ TABLE_STATISTICS_METRICS
+ REPLICA_STATISTICS_METRICS
+ TABLE_STATUS_METRICS
+ TABLE_STATUS_SHARDS_METRICS
+ SERVER_STATUS_METRICS
+ tuple((name, typ) for name, typ, _, _ in JOBS_METRICS)
) # type: Tuple[Tuple[str, int], ...]
# Docker Compose configuration.
COMPOSE_FILE = os.path.join(HERE, 'compose', 'docker-compose.yaml')
COMPOSE_ENV_VARS = env_vars = {
'RETHINKDB_IMAGE': IMAGE,
'RETHINKDB_PORT_SERVER0': str(SERVER_PORTS['server0']),
'RETHINKDB_PORT_SERVER1': str(SERVER_PORTS['server1']),
'RETHINKDB_PORT_SERVER2': str(SERVER_PORTS['server2']),
'RETHINKDB_PORT_PROXY': str(SERVER_PORTS['proxy']),
'RETHINKDB_TLS_DRIVER_KEY': TLS_DRIVER_KEY,
'RETHINKDB_TLS_DRIVER_CERT': TLS_DRIVER_CERT,
}
# Pytest common test data.
MALFORMED_VERSION_STRING_PARAMS = [
pytest.param('rethinkdb (GCC 4.9.2)', id='no-version'),
pytest.param('rethinkdb', id='prefix-only'),
pytest.param('abc 2.4.0~0bionic (GCC 4.9.2)', id='wrong-prefix'),
]
| [
2,
357,
34,
8,
16092,
324,
519,
11,
3457,
13,
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12,
25579,
198,
2,
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2489,
10395,
198,
2,
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739,
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12,
565,
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357,
3826,
38559,
24290,
8,
198,
11748,
28686,
198,
6738,
19720,
1330,
... | 2.410003 | 3,739 |
# Copyright (c) 2010 Noah Kantrowitz <noah@coderanger.net>
__version__ = (0, 3, 0)
from chef.api import ChefAPI, autoconfigure
from chef.client import Client
from chef.data_bag import DataBag, DataBagItem
from chef.exceptions import ChefError
from chef.node import Node
from chef.role import Role
from chef.environment import Environment
from chef.search import Search
from chef.acl import Acl
| [
2,
15069,
357,
66,
8,
3050,
18394,
29576,
808,
4224,
1279,
3919,
993,
31,
66,
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13,
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9641,
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796,
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11,
657,
8,
198,
198,
6738,
21221,
13,
15042,
1330,
26383,
17614,
11,
1960,
... | 3.443478 | 115 |
"""
===========
NH2D fitter: ortho- and para- in the same file, but not modeled together
===========
Reference for line params:
F. Daniel et al. (2016) line frequencies and line strengths.
It includes HFS due to D
http://adsabs.harvard.edu/abs/2016A%26A...586L...4D
"""
from . import hyperfine
import astropy.units as u
freq_dict_cen ={
'o-1_01-1_11': 85.926263e9,
'p-1_01-1_11': 110.153599e9,
'o-1_01-0_00': 332.82251e9,
'p-1_01-0_00': 332.78189e9,
}
freq_dict={
####### ortho-NH2D J=1_01-1_11
'o-1_01-1_11_01': 85.924691e9,
'o-1_01-1_11_02': 85.924749e9,
'o-1_01-1_11_03': 85.924781e9,
'o-1_01-1_11_04': 85.925273e9,
'o-1_01-1_11_05': 85.925370e9,
'o-1_01-1_11_06': 85.925644e9,
'o-1_01-1_11_07': 85.925662e9,
'o-1_01-1_11_08': 85.925688e9,
'o-1_01-1_11_09': 85.925694e9,
'o-1_01-1_11_10': 85.925702e9,
'o-1_01-1_11_11': 85.925734e9,
'o-1_01-1_11_12': 85.926186e9,
'o-1_01-1_11_13': 85.926191e9,
'o-1_01-1_11_14': 85.926212e9,
'o-1_01-1_11_15': 85.926225e9,
'o-1_01-1_11_16': 85.926243e9,
'o-1_01-1_11_17': 85.926244e9,
'o-1_01-1_11_18': 85.926270e9,
'o-1_01-1_11_19': 85.926282e9,
'o-1_01-1_11_20': 85.926284e9,
'o-1_01-1_11_21': 85.926288e9,
'o-1_01-1_11_22': 85.926301e9,
'o-1_01-1_11_23': 85.926314e9,
'o-1_01-1_11_24': 85.926323e9,
'o-1_01-1_11_25': 85.926333e9,
'o-1_01-1_11_26': 85.926806e9,
'o-1_01-1_11_27': 85.926825e9,
'o-1_01-1_11_28': 85.926864e9,
'o-1_01-1_11_29': 85.926877e9,
'o-1_01-1_11_30': 85.926904e9,
'o-1_01-1_11_31': 85.926922e9,
'o-1_01-1_11_32': 85.927104e9,
'o-1_01-1_11_33': 85.927143e9,
'o-1_01-1_11_34': 85.927698e9,
'o-1_01-1_11_35': 85.927724e9,
'o-1_01-1_11_36': 85.927743e9,
####### ortho-NH2D J=1_01-0_00
'o-1_01-0_00_01': 332.780875e9,
'o-1_01-0_00_02': 332.780875e9,
'o-1_01-0_00_03': 332.780875e9,
'o-1_01-0_00_04': 332.781695e9,
'o-1_01-0_00_05': 332.781695e9,
'o-1_01-0_00_06': 332.781695e9,
'o-1_01-0_00_07': 332.781735e9,
'o-1_01-0_00_08': 332.781793e9,
'o-1_01-0_00_09': 332.781793e9,
'o-1_01-0_00_10': 332.782285e9,
'o-1_01-0_00_11': 332.782285e9,
'o-1_01-0_00_12': 332.782285e9,
'o-1_01-0_00_13': 332.782317e9,
'o-1_01-0_00_14': 332.782317e9,
'o-1_01-0_00_15': 332.782375e9,
####### para-NH2D J=1_01-1_11
'p-1_01-1_11_01': 110.151982e9,
'p-1_01-1_11_02': 110.152040e9,
'p-1_01-1_11_03': 110.152072e9,
'p-1_01-1_11_04': 110.152565e9,
'p-1_01-1_11_05': 110.152662e9,
'p-1_01-1_11_06': 110.152935e9,
'p-1_01-1_11_07': 110.152954e9,
'p-1_01-1_11_08': 110.152980e9,
'p-1_01-1_11_09': 110.152986e9,
'p-1_01-1_11_10': 110.152993e9,
'p-1_01-1_11_11': 110.153025e9,
'p-1_01-1_11_12': 110.153478e9,
'p-1_01-1_11_13': 110.153484e9,
'p-1_01-1_11_14': 110.153504e9,
'p-1_01-1_11_15': 110.153517e9,
'p-1_01-1_11_16': 110.153534e9,
'p-1_01-1_11_17': 110.153536e9,
'p-1_01-1_11_18': 110.153562e9,
'p-1_01-1_11_19': 110.153574e9,
'p-1_01-1_11_20': 110.153576e9,
'p-1_01-1_11_21': 110.153580e9,
'p-1_01-1_11_22': 110.153592e9,
'p-1_01-1_11_23': 110.153606e9,
'p-1_01-1_11_24': 110.153615e9,
'p-1_01-1_11_25': 110.153625e9,
'p-1_01-1_11_26': 110.154098e9,
'p-1_01-1_11_27': 110.154117e9,
'p-1_01-1_11_28': 110.154156e9,
'p-1_01-1_11_29': 110.154170e9,
'p-1_01-1_11_30': 110.154196e9,
'p-1_01-1_11_31': 110.154215e9,
'p-1_01-1_11_32': 110.154397e9,
'p-1_01-1_11_33': 110.154437e9,
'p-1_01-1_11_34': 110.154991e9,
'p-1_01-1_11_35': 110.155017e9,
'p-1_01-1_11_36': 110.155036e9,
####### para-NH2D J=1_01-0_00
'p-1_01-0_00_01': 332.821618e9,
'p-1_01-0_00_02': 332.821618e9,
'p-1_01-0_00_03': 332.821618e9,
'p-1_01-0_00_04': 332.822439e9,
'p-1_01-0_00_05': 332.822439e9,
'p-1_01-0_00_06': 332.822439e9,
'p-1_01-0_00_07': 332.822479e9,
'p-1_01-0_00_08': 332.822537e9,
'p-1_01-0_00_09': 332.822537e9,
'p-1_01-0_00_10': 332.823029e9,
'p-1_01-0_00_11': 332.823029e9,
'p-1_01-0_00_12': 332.823029e9,
'p-1_01-0_00_13': 332.823062e9,
'p-1_01-0_00_14': 332.823062e9,
'p-1_01-0_00_15': 332.823120e9
}
line_strength_dict = {
####### ortho-NH2D J=1_01-1_11
'o-1_01-1_11_01': 0.01310,
'o-1_01-1_11_02': 0.06187,
'o-1_01-1_11_03': 0.03562,
'o-1_01-1_11_04': 0.00016,
'o-1_01-1_11_05': 0.00035,
'o-1_01-1_11_06': 0.01595,
'o-1_01-1_11_07': 0.01758,
'o-1_01-1_11_08': 0.05965,
'o-1_01-1_11_09': 0.04054,
'o-1_01-1_11_10': 0.00064,
'o-1_01-1_11_11': 0.00556,
'o-1_01-1_11_12': 0.09296,
'o-1_01-1_11_13': 0.00000,
'o-1_01-1_11_14': 0.02677,
'o-1_01-1_11_15': 0.02341,
'o-1_01-1_11_16': 0.00798,
'o-1_01-1_11_17': 0.01984,
'o-1_01-1_11_18': 0.17288,
'o-1_01-1_11_19': 0.03609,
'o-1_01-1_11_20': 0.01423,
'o-1_01-1_11_21': 0.01265,
'o-1_01-1_11_22': 0.00934,
'o-1_01-1_11_23': 0.01131,
'o-1_01-1_11_24': 0.06547,
'o-1_01-1_11_25': 0.00541,
'o-1_01-1_11_26': 0.00769,
'o-1_01-1_11_27': 0.03419,
'o-1_01-1_11_28': 0.06657,
'o-1_01-1_11_29': 0.01395,
'o-1_01-1_11_30': 0.00325,
'o-1_01-1_11_31': 0.01385,
'o-1_01-1_11_32': 0.00002,
'o-1_01-1_11_33': 0.00006,
'o-1_01-1_11_34': 0.01043,
'o-1_01-1_11_35': 0.06026,
'o-1_01-1_11_36': 0.04034,
####### ortho-NH2D J=1_01-0_00
'o-1_01-0_00_01': 0.06298,
'o-1_01-0_00_02': 0.03129,
'o-1_01-0_00_03': 0.01683,
'o-1_01-0_00_04': 0.00007,
'o-1_01-0_00_05': 0.04185,
'o-1_01-0_00_06': 0.06918,
'o-1_01-0_00_07': 0.25920,
'o-1_01-0_00_08': 0.05735,
'o-1_01-0_00_09': 0.12788,
'o-1_01-0_00_10': 0.03796,
'o-1_01-0_00_11': 0.04805,
'o-1_01-0_00_12': 0.02509,
'o-1_01-0_00_13': 0.05735,
'o-1_01-0_00_14': 0.12788,
'o-1_01-0_00_15': 0.03703,
####### para-NH2D J=1_01-1_11
'p-1_01-1_11_01': 0.01310,
'p-1_01-1_11_02': 0.06188,
'p-1_01-1_11_03': 0.03562,
'p-1_01-1_11_04': 0.00016,
'p-1_01-1_11_05': 0.00035,
'p-1_01-1_11_06': 0.01595,
'p-1_01-1_11_07': 0.01758,
'p-1_01-1_11_08': 0.05965,
'p-1_01-1_11_09': 0.04054,
'p-1_01-1_11_10': 0.00064,
'p-1_01-1_11_11': 0.00556,
'p-1_01-1_11_12': 0.09296,
'p-1_01-1_11_13': 0.00000,
'p-1_01-1_11_14': 0.02675,
'p-1_01-1_11_15': 0.02341,
'p-1_01-1_11_16': 0.00798,
'p-1_01-1_11_17': 0.01984,
'p-1_01-1_11_18': 0.17288,
'p-1_01-1_11_19': 0.03609,
'p-1_01-1_11_20': 0.01424,
'p-1_01-1_11_21': 0.01266,
'p-1_01-1_11_22': 0.00934,
'p-1_01-1_11_23': 0.01131,
'p-1_01-1_11_24': 0.06546,
'p-1_01-1_11_25': 0.00541,
'p-1_01-1_11_26': 0.00769,
'p-1_01-1_11_27': 0.03419,
'p-1_01-1_11_28': 0.06658,
'p-1_01-1_11_29': 0.01395,
'p-1_01-1_11_30': 0.00325,
'p-1_01-1_11_31': 0.01385,
'p-1_01-1_11_32': 0.00002,
'p-1_01-1_11_33': 0.00006,
'p-1_01-1_11_34': 0.01043,
'p-1_01-1_11_35': 0.06026,
'p-1_01-1_11_36': 0.04034,
####### para-NH2D J=1_01-0_00
'p-1_01-0_00_01': 0.06298,
'p-1_01-0_00_02': 0.03130,
'p-1_01-0_00_03': 0.01683,
'p-1_01-0_00_04': 0.00007,
'p-1_01-0_00_05': 0.04185,
'p-1_01-0_00_06': 0.06918,
'p-1_01-0_00_07': 0.25920,
'p-1_01-0_00_08': 0.05734,
'p-1_01-0_00_09': 0.12788,
'p-1_01-0_00_10': 0.03795,
'p-1_01-0_00_11': 0.04805,
'p-1_01-0_00_12': 0.02510,
'p-1_01-0_00_13': 0.05734,
'p-1_01-0_00_14': 0.12788,
'p-1_01-0_00_15': 0.03703,
}
# Get offset velocity dictionary in km/s based on the lines frequencies and rest frequency
conv_o1_1=u.doppler_radio(freq_dict_cen['o-1_01-1_11']*u.Hz)
conv_p1_1=u.doppler_radio(freq_dict_cen['p-1_01-1_11']*u.Hz)
conv_o1_0=u.doppler_radio(freq_dict_cen['o-1_01-0_00']*u.Hz)
conv_p1_0=u.doppler_radio(freq_dict_cen['p-1_01-0_00']*u.Hz)
voff_lines_dict = {
name: ((freq_dict[name]*u.Hz).to(u.km/u.s, equivalencies=conv_o1_1).value) for name in freq_dict.keys() if "o-1_01-1_11" in name
}
voff_lines_dict.update({
name: ((freq_dict[name]*u.Hz).to(u.km/u.s, equivalencies=conv_p1_1).value) for name in freq_dict.keys() if "p-1_01-1_11" in name
})
voff_lines_dict.update({
name: ((freq_dict[name]*u.Hz).to(u.km/u.s, equivalencies=conv_o1_0).value) for name in freq_dict.keys() if "o-1_01-0_00" in name
})
voff_lines_dict.update({
name: ((freq_dict[name]*u.Hz).to(u.km/u.s, equivalencies=conv_p1_0).value) for name in freq_dict.keys() if "p-1_01-0_00" in name
})
# I don't know yet how to use this parameter... in CLASS it does not exist
# Note to Jaime: this is the sum of the degeneracy values for all hyperfines
# for a given line; it gives the relative weights between the J=2-1 and J=3-2
# lines, for example (the hyperfine weights are treated as normalized within
# one rotational transition)
wo1_1 = sum(val for name,val in line_strength_dict.items() if 'o-1_01-1_11' in name)
wp1_1 = sum(val for name,val in line_strength_dict.items() if 'p-1_01-1_11' in name)
wo1_0 = sum(val for name,val in line_strength_dict.items() if 'o-1_01-0_00' in name)
wp1_0 = sum(val for name,val in line_strength_dict.items() if 'p-1_01-0_00' in name)
relative_strength_total_degeneracy = {
name : wo1_1 for name in line_strength_dict.keys() if "o-1_01-1_11" in name
}
relative_strength_total_degeneracy.update({
name : wp1_1 for name in line_strength_dict.keys() if "p-1_01-1_11" in name
})
relative_strength_total_degeneracy.update({
name : wo1_0 for name in line_strength_dict.keys() if "o-1_01-0_00" in name
})
relative_strength_total_degeneracy.update({
name : wp1_0 for name in line_strength_dict.keys() if "p-1_01-0_00" in name
})
# Get the list of line names from the previous lists
line_names = [name for name in voff_lines_dict.keys()]
nh2d_vtau = hyperfine.hyperfinemodel(line_names, voff_lines_dict, freq_dict,
line_strength_dict,
relative_strength_total_degeneracy)
nh2d_vtau_fitter = nh2d_vtau.fitter
nh2d_vtau_vheight_fitter = nh2d_vtau.vheight_fitter
nh2d_vtau_tbg_fitter = nh2d_vtau.background_fitter
| [
37811,
198,
2559,
18604,
198,
33863,
17,
35,
277,
1967,
25,
29617,
78,
12,
290,
31215,
12,
287,
262,
976,
2393,
11,
475,
407,
29563,
1978,
198,
2559,
18604,
198,
26687,
329,
1627,
42287,
25,
198,
198,
37,
13,
7806,
2123,
435,
13,
... | 1.603803 | 6,416 |
password="4bd9270216a6d2e7bc330cf396f7c8f2"
| [
28712,
2625,
19,
17457,
24,
1983,
2999,
1433,
64,
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22,
15630,
26073,
12993,
34107,
69,
22,
66,
23,
69,
17,
1,
198
] | 1.692308 | 26 |
from typing import List
from typing import Dict
from typing import NamedTuple
# from typing import Optional
| [
6738,
19720,
1330,
7343,
198,
6738,
19720,
1330,
360,
713,
198,
6738,
19720,
1330,
34441,
51,
29291,
198,
2,
422,
19720,
1330,
32233,
628,
198
] | 4.4 | 25 |
#!/usr/bin/env python3
import asyncio
import websockets
import threading
import queue
import secrets
asyncio.run(main())
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
198,
11748,
30351,
952,
198,
11748,
2639,
11603,
198,
11748,
4704,
278,
198,
11748,
16834,
198,
11748,
13141,
198,
198,
292,
13361,
952,
13,
5143,
7,
12417,
28955,
198
] | 3.153846 | 39 |
"""
A demultiplexing element that splits packet streams by flow_id.
"""
class FlowDemux:
"""
The constructor takes a list of downstream elements for the
corresponding output ports as its input.
"""
def put(self, packet):
""" Sends a packet to this element. """
self.packets_received += 1
flow_id = packet.flow_id
if flow_id < len(self.outs):
self.outs[flow_id].put(packet)
else:
if self.default:
self.default.put(packet)
| [
37811,
198,
32,
1357,
586,
2480,
87,
278,
5002,
326,
30778,
19638,
15190,
416,
5202,
62,
312,
13,
198,
37811,
628,
198,
4871,
27782,
11522,
2821,
25,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
383,
23772,
2753,
257,
1351,
286,
3... | 2.371041 | 221 |
# author: Mahmud Ahsan
# code: https://github.com/mahmudahsan/thinkdiff
# blog: http://thinkdiff.net
# http://pythonbangla.com
# MIT License
# --------------------------
# Files
# --------------------------
## Reading full contents of a text file
'''
Encouraged way
with keyword close the file automatically
'''
try:
with open('data/article.txt') as fobj:
contents = fobj.read()
print (contents)
except Exception as e:
print ("File Error: " , e)
print()
### Another way
'''
In this way, file need to close manually
'''
try:
fobj = open('data/article.txt')
except Exception as e:
print ("File Error: " , e)
else:
contents = fobj.read()
print (contents)
finally:
fobj.close()
print()
'''
MacOS and Linux
Relative path:
data/article.txt
Absolute path:
/user/mahmud/python/data/article.txt
'''
# Windows:
# data\article.txt
# C:\Users\mahmud\python\data\article.txt
### Reading line by line and make uppercase
with open("data/article.txt") as fobj:
for num, line in enumerate(fobj):
print ( num+1, line.upper() )
print()
### Reading list of lines
with open("data/names.txt") as fobj:
lines = fobj.readlines()
print (lines)
## Write text in a file
'''
w = write # erase existing content if any
a = append
r = read # default
OR
wt = write
at = append
rt = read
t is for text mode which is set by default
'''
with open ('data/number.txt', 'w') as fobj:
fobj.write('1')
fobj.write('\n')
fobj.write('28484')
## Append text in an existing file
'''
# uncomment to run this program
with open ('data/message.txt', 'a') as fobj:
fobj.write("life is good \n")
'''
## Encoding during writing file
# latin-1 other encoding
with open ('data/bangla.txt', 'w', encoding='UTF-8') as fobj:
fobj.write('আমার দেশ বাংলাদেশ')
fobj.write('\n')
fobj.write('আমি আমার দেশকে ভালবাসি')
## Redirect print output to file
with open ('data/print.txt', 'w') as fobj:
print ("Nothing goes unpaid", file=fobj)
## Write a binary data to a file
with open ('data/binary', 'wb') as fobj:
fobj.write(b'Life is good')
## Read a binary data file
with open ('data/binary', 'rb') as fobj:
binary_data = fobj.read()
decoded_data = binary_data.decode('utf-8')
print ( decoded_data )
## File existence checking
import os
if os.path.exists('data/article.txt'):
print ("Yes, file exist")
## Temporary file
'''
w+ = reading and writing same time
With auto destroyed when file closed
'''
from tempfile import TemporaryFile
with TemporaryFile('w+') as fobj:
fobj.write("Life is cool.\n")
fobj.seek(0) # seek to the beginning
data = fobj.read()
print (data)
## pyserial serial port access library
'''
Controlling hardware device like robot, sensor
by using serial port
https://github.com/pyserial/pyserial
'''
## Serialize python object to a byte stream
import pickle
dict_data = {'name':'Ahsan', 'country':'Bangladesh'}
# serialize_data = pickle.dumps(dict_data)
with open ('data/serialize', 'wb') as fobj:
pickle.dump(dict_data, fobj)
with open ('data/serialize', 'rb') as fobj:
dict_data = pickle.load(fobj)
print ( dict_data )
print()
## CSV file read
import csv
with open('data/expense.csv', 'r') as fobj:
fcsv = csv.reader(fobj)
sum = 0
for i, row in enumerate(fcsv):
print (i, row[0], row[1])
sum += int(row[1]) if i > 0 else 0
print ("Total Cost: ", sum)
'''
https://docs.python.org/3/library/csv.html
http://pandas.pydata.org
Pandas has pandas.read_csv() function to load CSV data to a DataFrame object.
'''
## CSV file write
list_items = [["name", 'age', 'country'],
['Bill Gates', 55, 'US'],
['Mark Zuckerberg', 34, 'US'],
['Swift', 35, 'Canada']
]
import csv
with open('data/people.csv', 'w') as fobj:
fcsv = csv.writer(fobj)
fcsv.writerows(list_items)
print()
## JSON Data Encode and Decode
'''
JSON (JavaScript Object Notation) is a common standard to exchange data between server and client in web application.
'''
import json
data = {
'name' : 'Bill Gates',
'age' : 55,
'country' : 'US',
'is_retired': True
}
json_encoded_str = json.dumps(data)
print(json_encoded_str)
json_decode = json.loads(json_encoded_str)
print(json_decode)
### Dumping data in file and load from file
with open('data/json_data.json', 'w') as fobj:
json.dump(data, fobj)
with open('data/json_data.json', 'r') as fobj:
json_data = json.load(fobj)
print (json_data)
| [
2,
1772,
25,
31556,
463,
7900,
12807,
198,
2,
2438,
25,
3740,
1378,
12567,
13,
785,
14,
76,
993,
41650,
993,
12807,
14,
14925,
26069,
198,
2,
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25,
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1378,
14925,
26069,
13,
3262,
198,
2,
2638,
1378,
29412,
36668,
5031,
13,
... | 2.420639 | 1,909 |
from flask import Flask
from flask import json
from multiprocessing import Queue
responses_ = Queue()
port = 4001
app = Flask(__name__)
@app.route("/state/<int:time>")
| [
6738,
42903,
1330,
46947,
198,
6738,
42903,
1330,
33918,
198,
6738,
18540,
305,
919,
278,
1330,
4670,
518,
198,
198,
16733,
274,
62,
796,
4670,
518,
3419,
198,
634,
796,
7337,
16,
198,
198,
1324,
796,
46947,
7,
834,
3672,
834,
8,
62... | 2.932203 | 59 |
from numbers import Number
from typing import Iterable, Tuple, Union, List, Optional
import copy
import numpy as np
from .cell import Cell
from .cell_indices import CellIndices
from .serialization import Serialization
# Acceptable values for the slice
T_slice = Union[np.ndarray,
List[Number], List[str], List[Cell],
str, Number, Cell]
class CellSlice(Serialization):
"""Encapsulate aggregating functionality and setting of the slices.
Attributes:
start_idx (Tuple[int, int]): Integer position of the starting cell
inside the spreadsheet. Top left cell of the slice.
end_idx (Tuple[int, int]): Integer position of the ending cell
inside the spreadsheet. Bottom right cell of the slice.
start_cell (Cell): Top left cell of the slice.
end_cell (Cell): Bottom right cell of the slice.
cell_subset (Iterable[Cell]): The list of all cells in the slice.
driving_sheet (Sheet): Reference to the spreadsheet.
"""
def __init__(self,
start_idx: Tuple[int, int],
end_idx: Tuple[int, int],
cell_subset: Iterable[Cell],
driving_sheet
):
"""Create a cell slice from the spreadsheet.
Args:
start_idx (Tuple[int, int]): Integer position of the starting cell
inside the spreadsheet. Top left cell of the slice.
end_idx (Tuple[int, int]): Integer position of the ending cell
inside the spreadsheet. Bottom right cell of the slice.
cell_subset (Iterable[Cell]): The list of all cells in the slice.
driving_sheet (Sheet): Reference to the spreadsheet.
"""
# Initialise functionality for serialization:
super().__init__(export_offset=start_idx,
warning_logger=driving_sheet.warning_logger,
export_subset=True)
self.start_idx: Tuple[int, int] = start_idx
self.end_idx: Tuple[int, int] = end_idx
self.start_cell: Cell = driving_sheet.iloc[start_idx]
self.end_cell: Cell = driving_sheet.iloc[end_idx]
self.cell_subset: Iterable[Cell] = cell_subset
self.driving_sheet = driving_sheet
def sum(self, skip_none_cell: bool = True) -> Cell:
"""Compute the sum of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.sum(self.start_cell, self.end_cell, cell_subset)
def product(self, skip_none_cell: bool = True) -> Cell:
"""Compute the product of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.product(self.start_cell, self.end_cell, cell_subset)
def min(self, skip_none_cell: bool = True) -> Cell:
"""Find the minimum of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.min(self.start_cell, self.end_cell, cell_subset)
def max(self, skip_none_cell: bool = True) -> Cell:
"""Find the maximum of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.max(self.start_cell, self.end_cell, cell_subset)
def mean(self, skip_none_cell: bool = True) -> Cell:
"""Compute the mean-average of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.mean(self.start_cell, self.end_cell, cell_subset)
def average(self, skip_none_cell: bool = True) -> Cell:
"""Compute the mean-average of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
return self.mean(skip_none_cell=skip_none_cell)
def stdev(self, skip_none_cell: bool = True) -> Cell:
"""Compute the standard deviation of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.stdev(self.start_cell, self.end_cell, cell_subset)
def median(self, skip_none_cell: bool = True) -> Cell:
"""Compute the median of the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.median(self.start_cell, self.end_cell, cell_subset)
def count(self, skip_none_cell: bool = True) -> Cell:
"""Compute the number of items in the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.count(self.start_cell, self.end_cell, cell_subset)
def irr(self, skip_none_cell: bool = True) -> Cell:
"""Compute the Internal Rate of Return (IRR) of items in the aggregate.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: a new cell with the result.
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.irr(self.start_cell, self.end_cell, cell_subset)
def match_negative_before_positive(self,
skip_none_cell: bool = True) -> Cell:
"""Find the position of the last negative number in the series that
is located just before the first non-negative number.
Args:
skip_none_cell (bool): If true, skips all the cells with None as
a value (and does not raise exception).
Returns:
Cell: Return the position of the negative number in a series that
is located just before the first positive number (or zero).
"""
if skip_none_cell:
cell_subset = [nn_cell for nn_cell in self.cell_subset
if nn_cell.value is not None]
else:
cell_subset = self.cell_subset
return Cell.match_negative_before_positive(self.start_cell,
self.end_cell, cell_subset)
@property
def excel_format(self):
"""Should not be accessible for slides."""
raise NotImplementedError
@excel_format.setter
def excel_format(self, new_format: dict):
"""Set the Excel cell format/style.
Read the documentation: https://xlsxwriter.readthedocs.io/format.html
Args:
new_format (dict): New format definition.
"""
if not isinstance(new_format, dict):
raise ValueError("New format has to be a dictionary!")
for row in range(self.start_idx[0], self.end_idx[0] + 1):
for col in range(self.start_idx[1],
self.end_idx[1] + 1):
self.driving_sheet.iloc[row, col].excel_format = new_format
@property
def description(self) -> Optional[str]:
"""Not implementable.
"""
raise NotImplementedError
@description.setter
def description(self, new_description: Optional[str]):
"""Set the cell description.
Args:
new_description (Optional[str]): description of the cell.
"""
if (new_description is not None
and not isinstance(new_description, str)):
raise ValueError("Cell description has to be a string value!")
for row in range(self.start_idx[0], self.end_idx[0] + 1):
for col in range(self.start_idx[1],
self.end_idx[1] + 1):
self.driving_sheet.iloc[row, col].description = new_description
def _set_value_on_position(self, other: Union[Cell, Number],
row: int, col: int) -> None:
"""Set the cell on given position in the spreadsheet to the value
'other'.
Args:
other (Union[Cell, Number]): new value to be set.
row (int): the row integer position in the spreadsheet (indexed
from 0).
col (int): the column integer position in the spreadsheet (indexed
from 0).
"""
if isinstance(other, Cell):
if other.anchored:
_value = Cell.reference(other)
elif other.is_variable:
# Set value
_value = Cell.variable(other)
# Anchor it:
_value.coordinates = (row, col)
else:
# Create a deep copy
_value = copy.deepcopy(other)
# Anchor it:
_value.coordinates = (row, col)
self.driving_sheet.iloc[row, col] = _value
else:
# Call the external logic to manage the same
self.driving_sheet.iloc[row, col] = other
# Set to scalar / Other cells:
def set(self, other: T_slice) -> None:
"""Set all the values in the slice to the new one (or the list of
values).
Args:
other: Union[np.ndarray, List[Number], List[Cell], Number, Cell]:
Some value or list (or numpy array) of values that should be
set for all the cells inside slice.
"""
if isinstance(other, (np.ndarray, list, tuple)):
dim_match = True
is_list = True
is_1d = False
by_row = self.shape[0] > self.shape[1]
if hasattr(other, "shape"):
dim_match = other.shape == self.shape
is_list = False
is_1d = len(other.shape) == 1
if is_1d:
dim_match = max(other.shape) == max(self.shape)
else:
is_list = True
if min(self.shape) == 1:
dim_match = len(other) == max(self.shape)
is_1d = True
if not dim_match:
raise ValueError("Shape of the input does not match to the "
"shape of the slice!")
if is_1d:
col = self.start_idx[1]
row = self.start_idx[0]
for val in other:
self._set_value_on_position(val, row, col)
if by_row:
row += 1
else:
col += 1
else:
# If is N-dimensional
for row in range(self.start_idx[0], self.end_idx[0] + 1):
for col in range(self.start_idx[1],
self.end_idx[1] + 1):
if is_list:
val = other[row - self.start_idx[0]][
col - self.start_idx[1]
]
else:
val = other[
row - self.start_idx[0],
col - self.start_idx[1]
]
self._set_value_on_position(val, row, col)
else:
for row in range(self.start_idx[0], self.end_idx[0] + 1):
for col in range(self.start_idx[1], self.end_idx[1] + 1):
# Set the right values
self._set_value_on_position(other, row, col)
def __ilshift__(self, other: T_slice):
"""Overrides operator <<= to do a set functionality.
"""
self.set(other)
# ==== OVERRIDE ABSTRACT METHODS AND PROPERTIES OF SERIALIZATION CLASS ====
@Serialization.shape.getter
def shape(self) -> Tuple[int, int]:
"""Return the shape of the sheet in the NumPy logic.
Returns:
Tuple[int]: Number of rows, Number of columns
"""
return (self.end_idx[0] - self.start_idx[0] + 1,
self.end_idx[1] - self.start_idx[1] + 1)
@Serialization.cell_indices.getter
def cell_indices(self) -> CellIndices:
"""Get the cell indices.
Returns:
CellIndices: Cell indices of the spreadsheet.
"""
return self.driving_sheet._cell_indices
def _get_cell_at(self, row: int, column: int) -> 'Cell':
"""Get the particular cell on the (row, column) position.
Returns:
Cell: The call on given position.
"""
return self.driving_sheet.iloc[self.start_idx[0] + row,
self.start_idx[1] + column]
def _get_variables(self):
"""Return the sheet variables as _SheetVariables object.
Returns:
_SheetVariables: Sheet variables.
"""
return self.driving_sheet.var
# =========================================================================
| [
6738,
3146,
1330,
7913,
198,
6738,
19720,
1330,
40806,
540,
11,
309,
29291,
11,
4479,
11,
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11,
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198,
11748,
4866,
198,
198,
11748,
299,
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355,
45941,
198,
198,
6738,
764,
3846,
1330,
12440,
198,
6738,
764,
3846,
62,
52... | 2.044063 | 7,739 |
from shlex import quote
from subprocess import getoutput, getstatusoutput
# from flask import current_app
| [
6738,
427,
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1330,
9577,
198,
6738,
850,
14681,
1330,
651,
22915,
11,
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22915,
198,
198,
2,
422,
42903,
1330,
1459,
62,
1324,
628,
628,
628
] | 4 | 28 |
# _________________________________________________________________________
#
# PyUtilib: A Python utility library.
# Copyright (c) 2008 Sandia Corporation.
# This software is distributed under the BSD License.
# Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
# the U.S. Government retains certain rights in this software.
# _________________________________________________________________________
#
# Class to encapsulate a progress indicator
__all__ = ['progress']
import sys
import time
import unittest
class progressException(Exception):
'Error to raise for any recursive problem.'
if __name__ == '__main__':
widgetTestSuite = unittest.TestSuite()
widgetTestSuite.addTest(TestCase("testProgress"))
runner = unittest.TextTestRunner()
runner.run(widgetTestSuite)
| [
2,
220,
220,
27193,
2602,
62,
198,
2,
198,
2,
220,
9485,
18274,
22282,
25,
317,
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10361,
5888,
13,
198,
2,
220,
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357,
66,
8,
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3837,
544,
10501,
13,
198,
2,
220,
770,
3788,
318,
9387,
739,
262,
347,
10305,
13789,
... | 3.767123 | 219 |
from rest_framework.serializers import Serializer, DecimalField, IntegerField
from pss_project.api.serializers.rest.metrics.LatencyMetricsSerializer \
import LatencyMetricsSerializer
from pss_project.api.models.rest.metrics.IncrementalMetrics \
import IncrementalMetrics
from pss_project.api.serializers.rest.metrics.MemoryMetricsSerializer \
import MemoryMetricsSerializer
| [
6738,
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11,
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198,
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279,
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62,
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13,
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13,
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13,
4164,
10466,
13,
24220,
1387,
9171,
10466,
32634,
7509,
3467... | 3.336207 | 116 |
#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
from ._fst import FST
from ._results import FailedTestResult, PassedTestResult
from .exceptions import TestCaseDefinitionError
class TestCase:
"""
An executable test case.
"""
@staticmethod
def from_description(
raw_test_case: Dict[str, Any], location: Optional[Path] = None
) -> "TestCase":
"""
Given a dictionary, parses and returns an executable test case.
"""
# Parse a few things
if "expect" not in raw_test_case:
raise TestCaseDefinitionError('Missing "expect" in test case')
raw_expected = raw_test_case["expect"]
if isinstance(raw_expected, str):
expected = [raw_expected]
elif isinstance(raw_expected, list):
if len(raw_expected) == 0:
raise TestCaseDefinitionError(
"Must provide at least one expected transduction"
)
expected = raw_expected
else:
raise TestCaseDefinitionError(
'"expect" MUST be either a single string or a list of strings;'
f"instead got {raw_expected!r}"
)
if "upper" in raw_test_case:
direction = "down"
fst_input = raw_test_case["upper"]
elif "lower" in raw_test_case:
direction = "up"
fst_input = raw_test_case["lower"]
else:
raise TestCaseDefinitionError('Missing "upper" or "lower" in test case')
return TestCase(fst_input, expected, direction, location)
| [
2,
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14,
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14,
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18,
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10644,
198,
6738,
19720,
1330,
4377,
11,
360,
713,
11,
7343,
11,
32233,
11,
4479,
198,
... | 2.294925 | 729 |
#!/usr/bin/env python
import copy
from collections import deque, defaultdict
from utils.intcode import Machine
from utils.utils import get_input, ints
if __name__ == "__main__":
main()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
11748,
4866,
198,
6738,
17268,
1330,
390,
4188,
11,
4277,
11600,
198,
198,
6738,
3384,
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13,
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8189,
1330,
10850,
198,
6738,
3384,
4487,
13,
26791,
1330,
651,
62,
15414,
11... | 3.030769 | 65 |
from __future__ import absolute_import, unicode_literals
import logging
import functools
import threading
import time
from django.http import HttpResponse
from libs import send_email, util
from libs import call_inception
from .models import (
Usermessage,
DatabaseList,
Account,
globalpermissions,
SqlOrder,
SqlRecord,
grained
)
from core.models import Account
from core.utils.send_feishu_mess import send_msg as fs_send_msg
CUSTOM_ERROR = logging.getLogger('Yearning.core.views')
def grained_permissions(func):
'''
:argument 装饰器函数,校验细化权限。非法请求直接返回401交由前端判断状态码
'''
@functools.wraps(func)
return wrapper
class order_push_message(threading.Thread):
'''
:argument 同意执行工单调用该方法异步处理数据
'''
def execute(self):
'''
:argument 将获得的sql语句提交给inception执行并将返回结果写入SqlRecord表,最后更改该工单SqlOrder表中的status
:param
self.order
self.id
:return: none
'''
time.sleep(self.order.delay * 60)
try:
detail = DatabaseList.objects.filter(id=self.order.bundle_id).first()
with call_inception.Inception(
LoginDic={
'host': detail.ip,
'user': detail.username,
'password': detail.password,
'db': self.order.basename,
'port': detail.port
}
) as f:
res = f.Execute(sql=self.order.sql, backup=self.order.backup)
for i in res:
if i['errlevel'] != 0:
SqlOrder.objects.filter(work_id=self.order.work_id).update(status=4)
SqlRecord.objects.get_or_create(
state=i['stagestatus'],
sql=i['sql'],
error=i['errormessage'],
workid=self.order.work_id,
affectrow=i['affected_rows'],
sequence=i['sequence'],
execute_time=i['execute_time'],
SQLSHA1=i['SQLSHA1'],
backup_dbname=i['backup_dbname']
)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}')
finally:
status = SqlOrder.objects.filter(work_id=self.order.work_id).first()
if status.status != 4:
SqlOrder.objects.filter(id=self.id).update(status=1)
def agreed(self):
'''
:argument 将执行的结果通过站内信,email,dingding 发送
:param self.from_user
self.to_user
self.title
self.order
self.addr_ip
:return: none
'''
t = threading.Thread(target=order_push_message.con_close, args=(self,))
t.start()
t.join()
class rejected_push_messages(threading.Thread):
'''
:argument 驳回工单调用该方法异步处理数据
'''
def execute(self):
'''
:argument 更改该工单SqlOrder表中的status
:param
self._tmpData
self.addr_ip
self.text
self.to_user
:return: none
'''
content = DatabaseList.objects.filter(id=self._tmpData['bundle_id']).first()
mail = Account.objects.filter(username=self.to_user).first()
tag = globalpermissions.objects.filter(authorization='global').first()
if tag.message['ding']:
try:
if content.url:
util.dingding(
content='工单驳回通知\n工单编号:%s\n发起人:%s\n操作人:%s\n地址:%s\n驳回说明:%s\n状态:驳回'
% (self._tmpData['work_id'], self.to_user,self.from_user, self.addr_ip, self.text), url=content.url)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}')
if tag.message['feishu']:
try:
user_mail = Account.objects.filter(username=self.to_user).values('email').first()
user = {'mail': user_mail.get('email')}
fs_send_msg(
msg='工单驳回通知\n工单编号:%s\n发起人:%s\n操作人:%s\n地址:%s\n驳回说明:%s\n状态:驳回'
% (self._tmpData['work_id'], self.to_user,self.from_user, self.addr_ip, self.text),user=user)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}')
if tag.message['mail']:
try:
if mail.email:
mess_info = {
'workid': self._tmpData['work_id'],
'to_user': self.to_user,
'addr': self.addr_ip,
'rejected': self.text}
put_mess = send_email.send_email(to_addr=mail.email)
put_mess.send_mail(mail_data=mess_info, type=1)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}')
class submit_push_messages(threading.Thread):
'''
:argument 提交工单调用该方法异步处理数据
'''
def submit(self):
'''
:argument 更改该工单SqlOrder表中的status
:param
self.workId
self.user
self.addr_ip
self.text
self.assigned
self.id
:return: none
'''
content = DatabaseList.objects.filter(id=self.id).first()
mail = Account.objects.filter(username=self.assigned).first()
tag = globalpermissions.objects.filter(authorization='global').first()
if tag.message['ding']:
if content.url:
try:
util.dingding(
content='工单提交通知\n工单编号:%s\n发起人:%s\n审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s'
% (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before), url=content.url)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}')
if tag.message['feishu']:
try:
user_mail = Account.objects.filter(username=self.assigned).values('email').first()
user = {'mail': user_mail.get('email')}
fs_send_msg(
msg='工单提交通知\n工单编号:%s\n发起人:%s\n审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s'
% (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before),user=user)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}')
if tag.message['mail']:
if mail.email:
mess_info = {
'workid': self.workId,
'to_user': self.user,
'addr': self.addr_ip,
'text': self.text,
'note': content.before}
try:
put_mess = send_email.send_email(to_addr=mail.email)
put_mess.send_mail(mail_data=mess_info, type=99)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}')
class forward_push_messages(threading.Thread):
'''
:argument 提交工单调用该方法异步处理数据
'''
def submit(self):
'''
:argument 更改该工单SqlOrder表中的status
:param
self.workId
self.user
self.addr_ip
self.text
self.assigned
self.id
:return: none
'''
content = DatabaseList.objects.filter(id=self.id).first()
mail = Account.objects.filter(username=self.assigned).first()
tag = globalpermissions.objects.filter(authorization='global').first()
if tag.message['ding']:
if content.url:
try:
util.dingding(
content='工单转发通知\n工单编号:%s\n发起人:%s\n当前审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s'
% (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before), url=content.url)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--钉钉推送失败: {e}')
if tag.message['feishu']:
try:
user_mail = Account.objects.filter(username=self.assigned).values('email').first()
user = {'mail': user_mail.get('email')}
fs_send_msg(
msg='工单转发通知\n工单编号:%s\n发起人:%s\n当前审批人:%s\n地址:%s\n工单说明:%s\n状态:已提交\n备注:%s'
% (self.workId, self.user,self.assigned, self.addr_ip, self.text, content.before),user=user)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--飞书推送失败: {e}')
if tag.message['mail']:
if mail.email:
mess_info = {
'workid': self.workId,
'to_user': self.user,
'addr': self.addr_ip,
'text': self.text,
'note': content.before}
try:
put_mess = send_email.send_email(to_addr=mail.email)
put_mess.send_mail(mail_data=mess_info, type=99)
except Exception as e:
CUSTOM_ERROR.error(f'{e.__class__.__name__}--邮箱推送失败: {e}')
| [
6738,
11593,
37443,
834,
1330,
4112,
62,
11748,
11,
28000,
1098,
62,
17201,
874,
198,
11748,
18931,
198,
11748,
1257,
310,
10141,
198,
11748,
4704,
278,
198,
11748,
640,
198,
6738,
42625,
14208,
13,
4023,
1330,
367,
29281,
31077,
198,
6... | 1.568614 | 6,041 |
#!/usr/bin/env python
from __future__ import print_function
from datetime import datetime, timedelta, tzinfo
import boto3
from botocore.exceptions import ClientError
DEFAULT_RETENTION_DAYS = None
"""If None, no default retention is applied"""
ZERO = timedelta(0)
class UTC(tzinfo):
"""
Implements UTC timezone for datetime interaction
"""
def get_snapshots(ec2, filters, retention):
"""
Generator of snapshots that exceed retention policy.
"""
for snapshot in ec2.snapshots.filter(Filters=filters):
# If the retention is specified in a tag override the default
if snapshot.tags:
for tag in snapshot.tags:
if tag['Key'] == 'ops:retention':
retention = int(tag['Value'])
utc = UTC()
if retention and \
snapshot.start_time < (datetime.now(utc) - timedelta(days=retention)):
yield snapshot
def lambda_handler(event, context):
"""
Delete EBS snapshots that exceed retention policy.
"""
if not 'DryRun' in event:
event['DryRun'] = False
if not 'Filters' in event:
event['Filters'] = [{
'Name': 'tag-key',
'Values': [
'ops:retention'
]
}]
# Set the default retention period if none was provided to the lambda
# invocation
if not 'Retention' in event:
event['Retention'] = DEFAULT_RETENTION_DAYS
ec2 = boto3.resource('ec2')
snapshots = get_snapshots(ec2, filters=event['Filters'],
retention=event['Retention'])
for snapshot in snapshots:
print('Deleting: %s' % snapshot)
try:
snapshot.delete(DryRun=event['DryRun'])
except ClientError as e:
if e.response['Error']['Code'] == 'DryRunOperation':
pass
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
6738,
4818,
8079,
1330,
4818,
8079,
11,
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12514,
11,
256,
89,
10951,
198,
11748,
275,
2069,
18,
198,
6738,
10214,
420... | 2.35019 | 791 |
#!/usr/bin/env python
import argparse
import requests
try:
import simplejson as json
except ImportError:
import json
version = '%(prog)s 20180912'
### From Domain
### From IP address
### From Sample
### From AV
### From Report
### Search APINotes
if __name__ == '__main__':
if ArgParse().type == 'domain':
print(json.dumps(ThreatMiner().getURIFromDomain(ArgParse().resource)))
print(json.dumps(ThreatMiner().getSamplesFromDomain(ArgParse().resource)))
print(json.dumps(ThreatMiner().getSubdomainsFromDomain(ArgParse().resource)))
print(json.dumps(ThreatMiner().getReportFromDomain(ArgParse().resource)))
elif ArgParse().type == 'ip':
print(json.dumps(ThreatMiner().getURIFromIP(ArgParse().resource)))
print(json.dumps(ThreatMiner().getSamplesFromIP(ArgParse().resource)))
print(json.dumps(ThreatMiner().getReportFromIP(ArgParse().resource)))
elif ArgParse().type == 'hash':
print(json.dumps(ThreatMiner().getMetaFromSample(ArgParse().resource)))
print(json.dumps(ThreatMiner().getHttpFromSample(ArgParse().resource)))
print(json.dumps(ThreatMiner().getHostsFromSample(ArgParse().resource)))
print(json.dumps(ThreatMiner().getMutantsFromSample(ArgParse().resource)))
print(json.dumps(ThreatMiner().getRegistryFromSample(ArgParse().resource)))
print(json.dumps(ThreatMiner().getAVFromSample(ArgParse().resource)))
print(json.dumps(ThreatMiner().getReportFromSample(ArgParse().resource)))
elif ArgParse().type == 'av':
print(json.dumps(ThreatMiner().getSamplesFromAV(ArgParse().resource)))
print(json.dumps(ThreatMiner().getReportFromAV(ArgParse().resource)))
elif ArgParse().type == 'report':
print(json.dumps(ThreatMiner().getDomainFromReport(ArgParse().resource)))
print(json.dumps(ThreatMiner().getHostsFromReport(ArgParse().resource)))
print(json.dumps(ThreatMiner().getEmailFromReport(ArgParse().resource)))
print(json.dumps(ThreatMiner().getSamplesFromReport(ArgParse().resource)))
elif ArgParse().type == 'keyword':
print(json.dumps(ThreatMiner().getReportFromKeyword(ArgParse().resource)))
elif ArgParse().type == 'year':
print(json.dumps(ThreatMiner().getReportFromYear(ArgParse().resource)))
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
11748,
1822,
29572,
198,
11748,
7007,
198,
198,
28311,
25,
198,
220,
220,
220,
1330,
2829,
17752,
355,
33918,
198,
16341,
17267,
12331,
25,
198,
220,
220,
220,
1330,
33918,
198,
1... | 2.57629 | 911 |
import logging
from .api_client import APIClient
# child class of APIClient --> Extends error handling functionality
# ConnectionsClient class contains a series of functions corresponding to all
# pod admin endpoints on the REST API.
| [
11748,
18931,
198,
198,
6738,
764,
15042,
62,
16366,
1330,
3486,
2149,
75,
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628,
198,
2,
1200,
1398,
286,
3486,
2149,
75,
1153,
14610,
5683,
2412,
4049,
9041,
11244,
198,
2,
8113,
507,
11792,
1398,
4909,
257,
2168,
286,
5499,
111... | 4.25 | 56 |
"""
Handle all actions on the weather resource.
"""
import json
import requests
from server.utils import call_openwhisk
from server.exceptions import ResourceDoesNotExistException, APIException
def get_recommendations(demoGuid):
"""
Get recommendations
"""
try:
payload = dict()
payload['demoGuid'] = demoGuid
response = call_openwhisk('retrieve', payload)
except Exception as e:
raise APIException('KO', internal_details=str(e))
return response
def acknowledge_recommendation(demoGuid, recommendationId):
"""
Acknowledge the given recommendation
"""
try:
payload = dict()
payload['demoGuid'] = demoGuid
payload['recommendationId'] = recommendationId
response = call_openwhisk('acknowledge', payload)
except Exception as e:
raise APIException('KO', internal_details=str(e))
return response
def trigger_simulation(demoGuid):
"""
Trigger a simulation in the given demo
Creates a Snow Storm in the DC area
"""
try:
payload = dict()
payload['demoGuid'] = demoGuid
event = dict()
event = json.loads(open('./sample_event.json').read())
payload['event'] = event
response = call_openwhisk('recommend', payload)
except Exception as e:
raise APIException('KO', internal_details=str(e))
return response
| [
37811,
198,
37508,
477,
4028,
319,
262,
6193,
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198,
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198,
6738,
4382,
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1069,
11755,
1330,
20857,
13921,
3673,
3109,
396,... | 2.722868 | 516 |
"""GDB pretty-printers for CSD.
"""
import enum
import gdb
import gdb.xmethod
import re
_csd_printer_name = 'csd_pretty_printer'
_csd_xmethod_name = 'csd_xmethods'
_nttpIntegralSuffix = {
'long' : 'l',
'long long' : 'll',
'unsigned int' : 'u',
'unsigned long' : 'ul',
'unsigned long long' : 'ull'
}
def _get_entry_extractor_typename(ty):
"""Return the adjusted typename of an entry extractor for the purpose of
performing symbol lookups.
offset_extractor takes, as its third argument, a non-type template parameter
of type `std::size_t`. When gcc prints the NTTP argument, it prints it as just
a number, e.g., "8". In the symbol name, however, it must appear as something
like "8ul" (unsigned long) because the symbol must encode the type according
to the ABI rules.
"""
templateName = _remove_generics(ty.strip_typedefs().name)
if templateName != 'csg::offset_extractor':
return ty.strip_typedefs().name
offset = ty.template_argument(2)
assert type(offset) is gdb.Value, 'offset_extractor template arg 2 not an NTTP?'
suffix = _nttpIntegralSuffix.get(offset.type.name, None)
fixedOffset = f'{offset}{suffix}' if suffix else str(offset)
return f'csg::offset_extractor<{ty.template_argument(0)}, ' \
f'{ty.template_argument(1)}, {fixedOffset}>'
def _lookup_entry_ref_codec_functions(elementTy, entryTy, entryExTy,
entryRefUnionTy):
"""To iterate over CSD lists in the debugger, we need access to the functions
entry_ref_codec<...>::get_entry and entry_ref_codec<...>::get_value, which
are looked up using this helper.
"""
entryExTyName = _get_entry_extractor_typename(entryExTy)
entryRefCodecClassName = \
f'csg::detail::entry_ref_codec<{entryTy}, {elementTy}, {entryExTyName}>'
def lookupEntryRefCodecSymbol(fnName):
"""Look up symbol for entry_ref_codec<...> static member functions."""
symName = f'{entryRefCodecClassName}::{fnName}'
sym, _ = gdb.lookup_symbol(symName)
if not sym or not sym.is_function:
raise Exception(f'required symbol {symName} does not exist or is not a function')
return sym
getEntryFnName = f'get_entry({entryExTyName} &, {entryRefUnionTy})'
getEntrySym = lookupEntryRefCodecSymbol(getEntryFnName)
getValueFnName = f'get_value({entryRefUnionTy})'
getValueSym = lookupEntryRefCodecSymbol(getValueFnName)
return getEntrySym.value(), getValueSym.value()
class EntryRefPrinter:
"""Printer for csg::entry_ref_union<EntryType, T>"""
class ListPrinter:
"""Printer for all CSD list types."""
def register_csd_pretty_printers():
"""Register event handlers to load csd pretty-printers."""
gdb.events.new_objfile.connect(_register_csd_printers)
gdb.events.clear_objfiles.connect(_unregister_csd_printers)
| [
37811,
38,
11012,
2495,
12,
1050,
20193,
329,
9429,
35,
13,
198,
37811,
198,
198,
11748,
33829,
198,
11748,
308,
9945,
198,
11748,
308,
9945,
13,
87,
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198,
11748,
302,
198,
198,
62,
6359,
67,
62,
1050,
3849,
62,
3672,
796,
705... | 2.751479 | 1,014 |
import math
import megengine.module as M
import megengine.functional as F
class PositionEncodingSine(M.Module):
"""
This is a sinusoidal position encoding that generalized to 2-dimensional images
"""
def __init__(self, d_model, max_shape=(256, 256)):
"""
Args:
max_shape (tuple): for 1/8 featmap, the max length of 256 corresponds to 2048 pixels
"""
super().__init__()
pe = F.zeros((d_model, *max_shape))
y_position = F.expand_dims(F.cumsum(F.ones(max_shape), 0), 0)
x_position = F.expand_dims(F.cumsum(F.ones(max_shape), 1), 0)
div_term = F.exp(
F.arange(0, d_model // 2, 2) * (-math.log(10000.0) / d_model // 2)
)
div_term = F.expand_dims(div_term, (1, 2)) # [C//4, 1, 1]
pe[0::4, :, :] = F.sin(x_position * div_term)
pe[1::4, :, :] = F.cos(x_position * div_term)
pe[2::4, :, :] = F.sin(y_position * div_term)
pe[3::4, :, :] = F.cos(y_position * div_term)
self.pe = F.expand_dims(pe, 0)
def forward(self, x):
"""
Args:
x: [N, C, H, W]
"""
return x + self.pe[:, :, : x.shape[2], : x.shape[3]].to(x.device)
| [
11748,
10688,
198,
11748,
17243,
18392,
13,
21412,
355,
337,
198,
11748,
17243,
18392,
13,
45124,
355,
376,
628,
198,
4871,
23158,
27195,
7656,
50,
500,
7,
44,
13,
26796,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
770,
318,
... | 1.96463 | 622 |
# Copyright 2013, Michael H. Goldwasser
#
# Developed for use with the book:
#
# Data Structures and Algorithms in Python
# Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser
# John Wiley & Sons, 2013
#
# 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/>.
"""Basic example of an adapter class to provide a stack interface to Python's list."""
class ArrayStack:
"""LIFO Stack implementation using a Python list as underlying storage."""
def __init__(self):
"""Create an empty stack."""
self._data = [] # nonpublic list instance
def __len__(self):
"""Return the number of elements in the stack."""
return len(self._data)
def is_empty(self):
"""Return True if the stack is empty."""
return len(self._data) == 0
def push(self, e):
"""Add element e to the top of the stack."""
self._data.append(e) # new item stored at end of list
def top(self):
"""Return (but do not remove) the element at the top of the stack.
Raise Empty exception if the stack is empty.
"""
if self.is_empty():
raise AssertionError('Stack is empty')
return self._data[-1] # the last item in the list
def pop(self):
"""Remove and return the element from the top of the stack (i.e., LIFO).
Raise Empty exception if the stack is empty.
"""
if self.is_empty():
raise AssertionError('Stack is empty')
return self._data.pop() # remove last item from list
if __name__ == '__main__':
S = ArrayStack() # contents: [ ]
S.push(5) # contents: [5]
S.push(3) # contents: [5, 3]
print(len(S)) # contents: [5, 3]; outputs 2
print(S.pop()) # contents: [5]; outputs 3
print(S.is_empty()) # contents: [5]; outputs False
print(S.pop()) # contents: [ ]; outputs 5
print(S.is_empty()) # contents: [ ]; outputs True
S.push(7) # contents: [7]
S.push(9) # contents: [7, 9]
print(S.top()) # contents: [7, 9]; outputs 9
S.print_contents()
S.push(4) # contents: [7, 9, 4]
print(len(S)) # contents: [7, 9, 4]; outputs 3
print(S.pop()) # contents: [7, 9]; outputs 4
S.push(6) # contents: [7, 9, 6]
S.push(8) # contents: [7, 9, 6, 8]
S.print_contents()
print(S.pop()) # contents: [7, 9, 6]; outputs 8
#you can push anything in a stack, for instance you can push strings...
S1 = ArrayStack()
S1.push("John")
S1.push("Doe")
S1.print_contents()
#...or an array!
S2 = ArrayStack()
S2.push(["Basic English", 60, 'B+'])
S2.push(["ADSA", 95, 'A+'])
S2.print_contents()
| [
2,
15069,
2211,
11,
3899,
367,
13,
3561,
86,
24929,
198,
2,
198,
2,
6013,
276,
329,
779,
351,
262,
1492,
25,
198,
2,
198,
2,
220,
220,
220,
6060,
32112,
942,
290,
978,
7727,
907,
287,
11361,
198,
2,
220,
220,
220,
3899,
309,
1... | 2.231849 | 1,639 |
FEATURES = {
"DWI": [
"MD",
"FA",
"AD",
"RD",
"EigenValue",
"EigenVector",
"CS",
"CP",
"CL",
],
"SMRI": [
"Thickness",
"Volume",
"Sulc",
],
}
| [
15112,
47471,
796,
1391,
198,
220,
220,
220,
366,
35,
36326,
1298,
685,
198,
220,
220,
220,
220,
220,
220,
220,
366,
12740,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366,
7708,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
366... | 1.451429 | 175 |
import pytest
from aiohttp import web
from aiohttp_middlewares import https_middleware
@pytest.mark.parametrize(
"match_headers, request_headers, expected",
[
(None, None, "http"),
(None, {"X-Forwarded-Proto": "http"}, "http"),
(None, {"X-Forwarded-Proto": "https"}, "https"),
({}, None, "http"),
({}, {"X-Forwarded-Proto": "http"}, "http"),
({"Forwarded": "https"}, None, "http"),
({"Forwarded": "https"}, {"X-Forwarded-Proto": "http"}, "http"),
({"Forwarded": "https"}, {"X-Forwarded-Proto": "https"}, "http"),
({"Forwarded": "https"}, {"Forwarded": "http"}, "http"),
({"Forwarded": "https"}, {"Forwarded": "https"}, "https"),
],
)
| [
11748,
12972,
9288,
198,
6738,
257,
952,
4023,
1330,
3992,
198,
198,
6738,
257,
952,
4023,
62,
27171,
86,
3565,
1330,
3740,
62,
27171,
1574,
628,
628,
198,
31,
9078,
9288,
13,
4102,
13,
17143,
316,
380,
2736,
7,
198,
220,
220,
220,
... | 2.358065 | 310 |
# holds mapping between human key prefixes and real Redis prefixes
minute = 60
hour = 60 * minute
day = 24 * hour
week = 7 * day
month = 31 * day
redis_scheme = {
#
# human-readable table name
# |
# | prefix for key in Redis +
# | key placeholder
# | |
# | |
# | |
# | |
# | |
# | |
# | |
# | |
# | | key TTL in Redis (sec), None - never expire
# V V V
# mapping between token (key) and user id (value)
'ACCESS_TOKENS_BY_HASH': {'prefix': 'at:%s', 'ttl': None},
# mapping of user id and his roles
'USER_ROLES': {'prefix': 'ur:%s', 'ttl': -1},
# mapping between role id and its permissions
'ROLE_PERMISSIONS': {'prefix': 'rp:%s', 'ttl': -1},
}
| [
2,
6622,
16855,
1022,
1692,
1994,
21231,
274,
290,
1103,
2297,
271,
21231,
274,
198,
11374,
796,
3126,
198,
9769,
796,
3126,
1635,
5664,
198,
820,
796,
1987,
1635,
1711,
198,
10464,
796,
767,
1635,
1110,
198,
8424,
796,
3261,
1635,
11... | 1.64 | 650 |
# Copyright (c) 2018 PaddlePaddle Authors. 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.
import unittest
import numpy as np
from op_test import OpTest
import paddle
if __name__ == "__main__":
unittest.main()
| [
2,
220,
220,
15069,
357,
66,
8,
2864,
350,
37382,
47,
37382,
46665,
13,
1439,
6923,
33876,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
... | 3.559809 | 209 |
"""
extractor
=========
Extract path info from flask application.
"""
from .base import Extractor
from .mark import MarkExtractor
__all__ = ['Extractor', 'MarkExtractor']
| [
37811,
198,
2302,
40450,
198,
2559,
28,
198,
198,
11627,
974,
3108,
7508,
422,
42903,
3586,
13,
198,
198,
37811,
198,
6738,
764,
8692,
1330,
29677,
273,
198,
6738,
764,
4102,
1330,
2940,
11627,
40450,
198,
198,
834,
439,
834,
796,
372... | 3.411765 | 51 |
# Copyright 2014 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Process related utilities."""
from __future__ import print_function
import errno
import os
import signal
import sys
import time
def GetExitStatus(status):
"""Get the exit status of a child from an os.waitpid call.
Args:
status: The return value of os.waitpid(pid, 0)[1]
Returns:
The exit status of the process. If the process exited with a signal,
the return value will be 128 plus the signal number.
"""
if os.WIFSIGNALED(status):
return 128 + os.WTERMSIG(status)
else:
assert os.WIFEXITED(status), 'Unexpected exit status %r' % status
return os.WEXITSTATUS(status)
def ExitAsStatus(status):
"""Exit the same way as |status|.
If the status field says it was killed by a signal, then we'll do that to
ourselves. Otherwise we'll exit with the exit code.
See http://www.cons.org/cracauer/sigint.html for more details.
Args:
status: A status as returned by os.wait type funcs.
"""
exit_status = os.WEXITSTATUS(status)
if os.WIFSIGNALED(status):
# Kill ourselves with the same signal.
sig_status = os.WTERMSIG(status)
pid = os.getpid()
os.kill(pid, sig_status)
time.sleep(0.1)
# Still here? Maybe the signal was masked.
try:
signal.signal(sig_status, signal.SIG_DFL)
except RuntimeError as e:
if e.args[0] != errno.EINVAL:
raise
os.kill(pid, sig_status)
time.sleep(0.1)
# Still here? Just exit.
exit_status = 127
# Exit with the code we want.
sys.exit(exit_status)
| [
2,
15069,
1946,
383,
18255,
1505,
7294,
46665,
13,
1439,
2489,
10395,
13,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
257,
347,
10305,
12,
7635,
5964,
326,
460,
307,
198,
2,
1043,
287,
262,
38559,
24290,
2393,
13,
198,
198,... | 2.816807 | 595 |
import soaculib
import test_helpers as th
import time
import numpy as np
import pickle
# Locals.
import spem_model
import util
parser = util.get_parser()
parser.add_argument('mode', default='passive', nargs='?')
args = parser.parse_args()
SPEM_KEYS = [
'IA', 'IE',
'TF', 'TFS',
'TFC',
'AN', 'AW',
# 'AN2', 'AW2',
'NPAE',
'CA',
# 'AES', 'AEC', 'AES2', 'AEC2',
#'EES' ... no elevation ellipticity.
]
IGNORE_WRITEBACK = [] #'AN2', 'AW2']
class SpemHelper:
"""This works with simple parameter names (IA, etc) and values in
degrees (rather than ACU internal mdeg).
"""
DSET = 'DataSets.CmdSPEMParameter'
GLOBAL_EN = ('DataSets.CmdPointingCorrection',
'Systematic error model (SPEM) on')
MDEG = 0.001
keep_going = True
acu = soaculib.AcuControl(args.config)
banner('Check Datasets Present')
for dset in [
'DataSets.StatusSATPDetailed8100',
'DataSets.StatusPointingCorrection',
'DataSets.CmdSPEMParameter',
]:
try:
v1 = acu.Values(dset)
print(' Retrieved %-40s - %i keys' % (dset, len(v1)))
except soaculib.http.HttpError as e:
print(' ! Failed to retrieve %s' % dset)
keep_going = False
check_ok()
banner('Check SPEM Against Schema')
spemh = SpemHelper(acu)
excess_keys = spemh.get().keys()
missing_keys = [k for k in SPEM_KEYS]
print(' Read %i keys (expecting %i)' % (len(excess_keys), len(missing_keys)))
both = set(missing_keys).intersection(excess_keys)
missing_keys = list(set(missing_keys).difference(both))
excess_keys = list(set(excess_keys).difference(both))
if len(missing_keys):
print(' Expected but did not find these keys:')
print(' ' + ', '.join(missing_keys))
keep_going = False
if len(excess_keys):
print(' Found but did not expect these keys:')
print(' ' + ', '.join(excess_keys))
#keep_going = False
check_ok()
banner('Check write-back all SPEM parameters')
if not th.check_remote(acu):
print('ACU is not in remote mode!')
keep_going = False
check_ok()
for k, v in spemh.get().items():
try:
spemh.set({k: v})
except:
print(' Failed to write %s!' % k)
if k not in IGNORE_WRITEBACK:
keep_going = False
continue
print(' Write-back test complete.')
check_ok()
banner('Confirm ACU in Stop')
if acu.mode() != 'Stop':
print(' Any further testing requires ACU to be in stop.')
keep_going = False
else:
print(' ACU is in stop.')
check_ok()
banner('Check SPEM responsiveness')
pos0 = th.get_positions(acu)
print('Current position:', pos0)
# Test basic offsets.
for param in ['IA', 'IE']:
val = 0.1 # deg
print('Set %s=%f deg' % (param, val))
spemh.set({param: val})
print(' new position:', th.get_positions(acu))
spemh.set({param: 0})
banner('Check global enable')
spemh.clear(ignore=IGNORE_WRITEBACK)
pos0 = th.get_positions(acu)
print(' Starting position is az=%8.4f, el=%8.4f' % tuple(pos0))
spemh.set({'IA': 0.3, 'IE': -0.4})
pos1 = th.get_positions(acu)
print(' After SPEM model az=%8.4f, el=%8.4f' % tuple(pos1))
spemh.global_enable(False)
pos2 = th.get_positions(acu)
print(' After SPEM disable az=%8.4f, el=%8.4f' % tuple(pos2))
spemh.global_enable(True)
pos3 = th.get_positions(acu)
print(' After SPEM enable az=%8.4f, el=%8.4f' % tuple(pos3))
spemh.clear(ignore=IGNORE_WRITEBACK)
pos4 = th.get_positions(acu)
print(' After SPEM clear az=%8.4f, el=%8.4f' % tuple(pos4))
if args.mode == 'singles':
# A good mode for debugging individual parameter equations.
banner('Test response to each parameter.')
spemh.clear(ignore=IGNORE_WRITEBACK)
model0 = spemh.get()
pos0 = th.get_positions(acu)
print(' Starting position is az=%8.4f, el=%8.4f' % tuple(pos0))
for k in SPEM_KEYS:
if k in IGNORE_WRITEBACK:
continue
D = 0.4
spemh.set({k: D})
model = dict(model0)
model[k] = D
time.sleep(.2)
pos1 = th.get_positions(acu)
spemh.set({k: 0})
expected = spem_model.delta(pos0, model)
print(' For %-4s = %4.2f only: ' % (k, D) +
'expect [%+7.4f,%+7.4f] ' % tuple(expected) +
'and measure [%+7.4f,%+7.4f]' % tuple(pos1 - pos0),
end='')
if (abs(expected - (pos1-pos0)).sum() > 1e-4):
print(' ! Mismatch.')
else:
print(' * ok')
if args.mode == 'survey':
# A good mode for checking that model makes sense across the sky.
banner('Make a survey of corrections over many pointings.')
model = {'IA': .1,
'IE': .2,
'TF': .3,
#'TFC': .4,
'TFS': .5,
'AN': -.1,
'AW': -.2,
}
# Move through various positions, apply the model at each and
# measure the offsets.
data = [] # [cmd, meas0, meas1]
for el in [40, 45, 55]:
for az in [160, 180, 200]:
print('Moving to az=%.2f el=%.2f' % (az, el))
acu.go_to(az, el)
spemh.clear(ignore=IGNORE_WRITEBACK)
while not th.check_positions(acu, az, el):
time.sleep(.5)
print(' setting stop mode.')
acu.stop()
time.sleep(.2)
pos0 = th.get_positions(acu)
spemh.set(model)
time.sleep(.2)
pos1 = th.get_positions(acu)
print(' delta pos is ', pos1-pos0)
data.append([np.array([az, el]), pos0, pos1])
data = np.array(data)
print(data.shape)
# Write out model and params.
filename = 'spem_survey_%i.pik' % int(time.time())
with open(filename, 'wb') as fout:
pickle.dump({'model': model,
'data': data}, fout)
| [
11748,
523,
330,
377,
571,
198,
11748,
1332,
62,
16794,
364,
355,
294,
198,
11748,
640,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
2298,
293,
198,
198,
2,
15181,
874,
13,
198,
11748,
599,
368,
62,
19849,
198,
11748,
7736,
198,
... | 2.098455 | 2,783 |
from ledger.models import LedgerData
| [
6738,
37208,
13,
27530,
1330,
22964,
1362,
6601,
198
] | 4.111111 | 9 |
#!/usr/bin/env python
#
# Copyright 2014 cloudysunny14.
#
# 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.
"""
How to run this test
edit linc config file. LINC-Switch/rel/linc/releases/1.0/sys.config
You can find the sample config I used for the test below:
[
{linc,
[
{of_config, enabled},
{capable_switch_ports,
[
{port, 1, [{interface, "tap0"}]},
{port, 2, [{interface, "tap1"}]}
]},
{capable_switch_queues,
[
{queue, 1, [{min_rate, 100}, {max_rate, 100}]},
{queue, 2, [{min_rate, 100}, {max_rate, 100}]}
]},
{logical_switches,
[
{switch, 0,
[
{backend, linc_us4},
{controllers,
[
{"Switch0-DefaultController", "localhost", 6633, tcp}
]},
{queues_status, enabled},
{ports, [
{port, 1, {queues, [1,2]}},
{port, 2, {queues, [1,2]}}
]}
]}
]}
]},
{enetconf,
[
{capabilities, [{base, {1, 1}},
{startup, {1, 0}},
{'writable-running', {1, 0}}]},
{callback_module, linc_ofconfig},
{sshd_ip, any},
{sshd_port, 1830},
{sshd_user_passwords,
[
{"linc", "linc"}
]}
]},
{lager,
[
{handlers,
[
{lager_console_backend, info},
{lager_file_backend,
[
{"log/error.log", error, 10485760, "$D0", 5},
{"log/console.log", info, 10485760, "$D0", 5}
]}
]}
]},
{sasl,
[
{sasl_error_logger, {file, "log/sasl-error.log"}},
{errlog_type, error},
{error_logger_mf_dir, "log/sasl"}, % Log directory
{error_logger_mf_maxbytes, 10485760}, % 10 MB max file size
{error_logger_mf_maxfiles, 5} % 5 files max
]},
{sync,
[
{excluded_modules, [procket]}
]}
].
Then run linc
# sudo rel/linc/bin/linc console
Then run ryu
# cd of_mangle
# export RYUHOME=$HOME/ryu
# PYTHONPATH=$RYUHOME:. $RYUHOME/bin/ryu-manager --verbose\
tests/test_of_mangle.py
"""
import logging
from ryu.base import app_manager
from ryu.controller import dpset
from ryu.controller.handler import set_ev_cls
from ryu.exception import OFPUnknownVersion
from ryu.lib import ofctl_v1_0
from ryu.lib import ofctl_v1_2
from ryu.lib import ofctl_v1_3
from ryu.lib import hub
from ryu.lib.of_config import capable_switch
from ryu.controller import ofp_event
from ryu.controller import dpset
from ryu.controller.handler import MAIN_DISPATCHER
from ryu.ofproto import ofproto_v1_0
from ryu.ofproto import ofproto_v1_2
from ryu.ofproto import ofproto_v1_3
from app import qoslib
LOG = logging.getLogger(__name__)
LOG_TEST_FINISH = 'TEST_FINISHED: Tests=[%s] (OK=%s NG=%s SKIP=%s)'
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
198,
2,
15069,
1946,
6279,
893,
16948,
1415,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,... | 2.245028 | 1,408 |
from collections import defaultdict
from django.utils import timezone
class RecordStorage(object):
"""
list-dict implementation for fast lookups of record types
"""
def format_hostmaster(hostmaster):
"""
The DNS encodes the <local-part> as a single label, and encodes the
<mail-domain> as a domain name. The single label from the <local-part>
is prefaced to the domain name from <mail-domain> to form the domain
name corresponding to the mailbox. Thus the mailbox HOSTMASTER@SRI-
NIC.ARPA is mapped into the domain name HOSTMASTER.SRI-NIC.ARPA. If the
<local-part> contains dots or other special characters, its
representation in a master file will require the use of backslash
quoting to ensure that the domain name is properly encoded. For
example, the mailbox Action.domains@ISI.EDU would be represented as
Action\.domains.ISI.EDU.
http://www.ietf.org/rfc/rfc1035.txt
"""
name, domain = hostmaster.split('@')
if '.' in name:
name = name.replace('.', '\.')
return "%s.%s." % (name, domain)
| [
6738,
17268,
1330,
4277,
11600,
198,
198,
6738,
42625,
14208,
13,
26791,
1330,
640,
11340,
628,
198,
4871,
13266,
31425,
7,
15252,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1351,
12,
11600,
7822,
329,
3049,
804,
4739,
286,
... | 2.975342 | 365 |
import yaml
import json
import sqlite3
from functools import reduce
import operator
import time
f=open('./tmp/sde/typeIDs.json', 'r', encoding='utf-8')
j=json.load(f)
#y=load("./tmp/sde/fsd/typeIDs.yaml")
#f=open('./tmp/sde/typeIDs.json', 'w', encoding='utf-8')
#json.dump(y, f)
#f.write(json.dump(y))
#f.close()
#db = sqlite3.connect(':memory:')
db = sqlite3.connect("./tmp/db.sqlite")
c = db.cursor()
c.execute('''
CREATE TABLE invCategories (
"categoryID" tinyint(3) NOT NULL,
"categoryName" TEXT(100),
"published" tinyint(1),
PRIMARY KEY ("categoryID")
);
''')
c.execute('''
CREATE TABLE invGroups (
"groupID" smallint(6) NOT NULL,
"groupName" varchar(100) DEFAULT NULL,
"categoryID" tinyint(3) default NULL,
"published" tinyint(1),
PRIMARY KEY ("groupID")
);
''')
c.execute('''
CREATE TABLE invTypes (
"typeID" int(11) NOT NULL,
"groupID" smallint(6) default NULL,
"typeName" varchar(100) default NULL,
"radius" double default NULL,
"mass" double default NULL,
"volume" double default NULL,
"capacity" double default NULL,
"portionSize" int(11) default NULL,
"raceID" tinyint(3) default NULL,
"published" tinyint(1) default NULL,
"metaGroupID" integer default NULL,
"parentTypeID" integer default NULL,
PRIMARY KEY ("typeID")
);
''')
c.execute('''
CREATE TABLE dgmAttributeTypes (
"attributeID" smallint(6) NOT NULL,
"attributeName" varchar(100) default NULL,
"displayName" varchar(100) default NULL,
"maxAttributeID" smallint(6) default NULL,
"defaultValue" double default NULL,
"stackable" tinyint(1) default NULL,
"highIsGood" tinyint(1) default NULL,
"categoryID" tinyint(3) default NULL,
PRIMARY KEY ("attributeID")
);
''')
c.execute('''
CREATE TABLE dgmTypeAttributes (
"typeID" smallint(6) NOT NULL,
"attributeID" smallint(6) NOT NULL,
"value" double default NULL,
PRIMARY KEY ("typeID","attributeID")
);
''')
c.execute('''
CREATE TABLE dgmTypeEffects (
"typeID" smallint(6) NOT NULL,
"effectID" smallint(6) NOT NULL,
"isDefault" tinyint(1) default NULL,
PRIMARY KEY ("typeID","effectID")
);
''')
c.execute('''
CREATE TABLE dgmEffects (
"effectID" smallint(6),
"effectName" TEXT(400),
"effectCategory" TEXT(100),
"isOffensive" INTEGER,
"isAssistance" INTEGER,
"modifierInfo" TEXT,
PRIMARY KEY ("effectID")
);
''')
c.execute('''
CREATE TABLE planetSchematics (
"schematicID" smallint(6) NOT NULL,
"schematicName" varchar(255) DEFAULT NULL,
"cycleTime" integer DEFAULT NULL,
PRIMARY KEY ("schematicID")
);
''')
c.execute('''
CREATE TABLE planetSchematicsPinMap (
"schematicID" smallint(6) NOT NULL,
"pinTypeID" integer NOT NULL,
PRIMARY KEY ("schematicID","pinTypeID")
);
''')
c.execute('''
CREATE TABLE planetSchematicsTypeMap (
"schematicID" smallint(6) NOT NULL,
"typeID" integer NOT NULL,
"quantity" integer DEFAULT NULL,
"isInput" integer DEFAULT NULL,
PRIMARY KEY ("schematicID","typeID")
);
''')
for id, row in load("./tmp/sde/fsd/categoryIDs.yaml"):
insert('invCategories', id, ['name.en', 'published'], row)
for id, row in load("./tmp/sde/fsd/groupIDs.yaml"):
insert('invGroups', id, ['name.en', 'categoryID', 'published'], row)
for id, row in load("./tmp/sde/fsd/dogmaAttributes.yaml"):
insert('dgmAttributeTypes', id, ['name', 'displayNameID.en', 'maxAttributeID', 'defaultValue', 'stackable', 'highIsGood', 'categoryID'], row)
for id, row in load("./tmp/sde/fsd/dogmaEffects.yaml"):
modifierInfo = find('modifierInfo', row)
if modifierInfo:
row['modifierInfo'] = yaml.dump(modifierInfo)
insert('dgmEffects', id, ['effectName', 'effectCategory', 'isOffensive', 'isAssistance', 'modifierInfo'], row)
for id, row in load("./tmp/sde/fsd/typeIDs.yaml"):
insert('invTypes', id, ['groupID', 'name.en', 'radius', 'mass', 'valume', 'capacity', 'portionSize', 'raceID', 'published', 'metaGroupID', 'variationParentTypeID'], row)
for id, type in load("./tmp/sde/fsd/typeDogma.yaml"):
try:
for row in find("dogmaAttributes", type):
insert('dgmTypeAttributes', id, ['attributeID', 'value'], row)
except:
pass
try:
for row in find("dogmaEffects", type):
insert('dgmTypeEffects', id, ['effectID', 'isDefault'], row)
except:
pass
for row in load("./tmp/sde/bsd/planetSchematics.yaml"):
insert('planetSchematics', row['schematicID'], ['schematicName', 'cycleTime'], row)
for row in load("./tmp/sde/bsd/planetSchematicsPinMap.yaml"):
insert('planetSchematicsPinMap', row['schematicID'], ['pinTypeID'], row)
for row in load("./tmp/sde/bsd/planetSchematicsTypeMap.yaml"):
insert('planetSchematicsTypeMap', row['schematicID'], ['typeID', 'quantity', 'isInput'], row)
db.commit()
db.close()
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... | 2.568872 | 1,844 |
import warnings
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
import theano
import pymc3 as pm
from functools import wraps
theano.config.compute_test_value = "ignore"
theano.config.on_opt_error = "raise"
theano.config.mode = "FAST_COMPILE"
theano.config.cxx = ""
| [
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27... | 2.859649 | 114 |
import os
from MachineLearning.load_datasets import load_filenames_2nd, load_data, keep_t2
from glob2 import glob
import nibabel as nib
import numpy as np
import keras
from Segmentation.model_keras import *
from sklearn.metrics import precision_recall_curve, precision_score, \
recall_score, roc_auc_score, f1_score, \
precision_recall_fscore_support, matthews_corrcoef, jaccard_similarity_score, accuracy_score
import pandas as pd
from pylab import rcParams
import seaborn as sns
# Set up plotting properties
sns.set(style='ticks', palette='Spectral', font_scale=1.5)
rcParams['figure.figsize'] = 6, 4
RAND_SEED = 42
def load_models(paths):
"""
Loads a list of models
Args:
paths (list): list of paths to models (not including the filename)
Returns:
"""
model = []
for path in paths:
model_path = os.path.join(path, 'Trained_model.h5')
model.append(keras.models.load_model(model_path,
custom_objects={'dice_loss': dice_loss,
'dice_metric': dice_metric}))
return model
def score_pred(Y_lab, Y_prob, threshold):
"""
Calculate a set of scores for the predictions
Args:
Y_lab (numpy array): labels
Y_prob (numpy array): predictions as probablilities
threshold (float): threshold for predictions
Returns:
(float): precision
(float): recall
(float): f1 score (Dice)
(float): support
(float): volume overlap error
(float): binary accuracy
"""
Y_thresh = Y_prob >= threshold
precision = []
recall = []
fbeta_score = []
support = []
voe = []
acc = []
Y_lab = Y_lab.reshape(-1)
Y_thresh = Y_thresh.reshape(-1)
# Compute precision/recall scores
scores = precision_recall_fscore_support(y_true=Y_lab, y_pred=Y_thresh)
precision.append(scores[0][1])
recall.append(scores[1][1])
fbeta_score.append(scores[2][1])
support.append(scores[3][1]/(scores[3][0] + scores[3][1])) # percent of volume occupied by tumor
voe.append(jaccard_similarity_score(y_true=Y_lab, y_pred=Y_thresh))
acc.append(accuracy_score(y_true=Y_lab, y_pred=Y_thresh, normalize=True))
return precision, recall, fbeta_score, support, voe, acc
def main(paths, spath):
"""
Args:
paths (list of str): path to t2_only and all_contrast models
thresholds (list of float): training thresholds
Returns:
"""
# Set up data constants
block_size = [18, 142, 142]
oversamp_test = 1.0
lab_trun = 2
test_split = 0.1
# Load models
models = load_models(paths)
# Set up data generator
gen_t2 = load_test_volumes(only_t2=True)
gen = load_test_volumes()
nsets = next(gen)
nsets = next(gen_t2)
print('Testing using {} sets'.format(nsets))
# Set up metric lists
df = pd.DataFrame(columns=['Loss', 'Data', 'Precision', 'Recall', 'Dice', 'Support', 'VOE', 'Accuracy'])
df_cat = pd.DataFrame(columns=['Loss', 'Data', 'Metric', 'Value']) # Concatenated dataframe
contrasts = ['Multi-modal', 'T2 only']
con_lab = ['t2', 'all']
# Process
clear_vol_stats()
thresholds = []
flag = True
z = 0
while flag:
try:
print('\tVolume %d' % (z + 1))
print('Loading test batch')
[xall, yall, szall] = next(gen)
[xt2, yt2, szt2] = next(gen_t2)
for model, path in zip(models, paths):
# Load model threshold
file = os.path.join(path, 'metrics2.txt')
with open(file, 'r') as f:
dat = f.readlines()
thr_ind = -7
tmp = [i for i in dat[thr_ind] if i.isdigit() or i == '.']
threshold = float(''.join(tmp))
thresholds.append(threshold)
# Get model loss
if 'dice' in path.lower():
loss = 'Dice'
else:
loss = 'Xentropy'
# Get skip status
if 'skip' in path.lower():
skip = 'Yes'
else:
skip = 'No'
# Get number of model inputs
mod_input_ch = model.input_shape[-1]
# Get correct contrast
if mod_input_ch == 1:
x, y, sz = xt2, yt2, szt2
contrast = contrasts[1]
else:
x, y, sz = xall, yall, szall
contrast = contrasts[0]
# Predict using model
print('Making predictions')
y_pred = model.predict(x)
# Compute metrics
print('Evaluating predictions')
res = score_pred(y, y_pred, threshold)
# Concatenate metrics
df = df.append(pd.DataFrame({'Loss': loss,
'Data': contrast,
'Skip': skip,
'Precision': res[0],
'Recall': res[1],
'Dice': res[2],
'Support': res[3],
'VOE': res[4],
'Accuracy': res[5]
}))
for ii in range(6):
df_cat = df_cat.append(pd.DataFrame({'Loss': loss,
'Data': contrast,
'Metric': df.keys()[ii+3],
'Value': res[ii]
}))
# Reconstruct images
# _, y = recon_test_3D(X=x, Y=y, orig_size=sz, block_size=block_size, oversamp=oversamp_test,
# lab_trun=lab_trun)
# x, y_pred = recon_test_3D(X=x, Y=y_pred, orig_size=sz, block_size=block_size, oversamp=oversamp_test,
# lab_trun=lab_trun)
#
# # Swap axes
# x = np.rollaxis(x, 0, 2).swapaxes(1, 2)
# y = np.rollaxis(y, 0, 2).swapaxes(1, 2)
# y_pred = np.rollaxis(y_pred, 0, 2).swapaxes(1, 2)
# Threshold segmentation
y_thresh = y_pred > threshold
# Record volume measurements
write_volumes(y, y_thresh, spath)
z += 1
except StopIteration:
print('Exhausted generator')
flag = False
# Plot results
# print('Saving plots')
# plot_results_cat(df_cat, spath)
# plot_results(df, spath)
# Write statistics
write_stats(df, thresholds, spath)
# Update dataframes to include stds
losses = df['Loss'].unique().tolist()
datas = df['Data'].unique().tolist()
skips = df['Skip'].unique().tolist()
metrics = ['Accuracy', 'Dice', 'Precision', 'Recall', 'Support', 'VOE']
df_out = {i: [] for i in df.keys()}
for loss in losses:
ind1 = df['Loss'] == loss
for data in datas:
ind2 = df['Data'] == data
for skip in skips:
ind3 = df['Skip'] == skip
# Create output df
df_out['Loss'].append(loss)
df_out['Data'].append(data)
df_out['Skip'].append(skip)
for metric in metrics:
# Get measurements
vals = df.loc[ind1 & ind2 & ind3, metric]
df_out[metric].append('{:0.3f} \xb1 {:0.3f}'.format(vals.mean(), vals.std()))
# std_metric = metric + '_std'
# df_out[std_metric].append(vals.std())
df_out = pd.DataFrame.from_dict(df_out)
# Save dataframes
print('Saving data')
save_df(df_out, spath, descriptor='metrics')
save_df(df_cat, spath, descriptor='cat')
if __name__ == '__main__':
"""
Example of how to test train networks.
"""
paths = ['/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_08_14-36-46_cnn_model_3D_3lyr_relu_dice',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_08_21-50-21_cnn_model_3D_3lyr_do_relu_dice_skip',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_06-49-45_cnn_model_3D_3lyr_do_relu_xentropy',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_14-12-47_cnn_model_3D_3lyr_do_relu_xentropy_skip',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_09_23-04-28_t2_cnn_model_3D_3lyr_relu_dice',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_04-50-05_t2_cnn_model_3D_3lyr_do_relu_dice_skip',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_12-28-23_t2_cnn_model_3D_3lyr_do_relu_xentropy',
'/media/matt/Seagate Expansion Drive/MR Data/ML_Results/2019_11_10_18-43-24_t2_cnn_model_3D_3lyr_do_relu_xentropy_skip']
spath = '/media/matt/Seagate Expansion Drive/b7TData_19/b7TData/Results/Analysis/Segmentation_images'
main(paths, spath)
| [
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... | 1.872265 | 5,073 |
import torch
from torch import nn
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import numpy as np
from fixed_stack_models import BeamItems, FixedStack, FixedStackRNNG, StackState
| [
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11748... | 3.442857 | 70 |
import numpy as np
from linear_models.logistic_regression import LogisticRegression
class Perceptron(LogisticRegression):
"""A simple (binary classification) perceptron. Uses binary cross-entropy loss for updating weights.
>>NOTE: it inherits most of the code from logistic regression for simplicity.<<
Parameters
----------
learning_rate : float, default = 0.2
The learning rate for gradient descent or SGD.
method : str, default = 'gradient'
Method of fitting the model.
'gradient' for gradient descent, 'sgd' for stochastic gradient descent.
reg : str, default = None
Regularization method.
For L1 or L2, use 'l1' or 'l2' respectively.
For elastic net method, use 'elastic'.
None for no regularization.
alpha : float, default = 0
Alpha parameter controlling the 'strength' of regularization.
l1_ratio : float, default = 0
Defines the ratio of L1 regularization. Only for elastic regularization option.
The penalty added to cost is l1_ratio * L1 + 0.5 * (1 - l1_ratio) * L2.
"""
def predict(self, x):
"""Predict the class for given input.
Parameters
----------
x : array-like
Input array.
"""
return np.heaviside(np.dot(x, self.coef) + self.intercept, 1)
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394... | 2.730223 | 493 |
import subprocess
import io
import random
INF = 10 ** 20
stress(100)
exit()
data = (16, 8, [8, 10, 15, 16, 4, 11])
"""
16 6 8
8 10 15 16 4 11
"""
ans = solve(*data)
print(test(*data, ans))
print(data, ans)
"""
[Error] (18, 3, [18, 8, 11, 2, 17, 10, 15, 5, 16]) (0, 1, 6)
[Error] (80, 5, [61, 2]) (0, 1, 16)
[Error] (9, 3, [9, 1]) (0, 1, 3)
[Error] (2, 2, [1, 2]) (0, 1, 1)
[Error] (8, 8, [3, 6]) (1, 1, 1)
[Error] (24, 3, [4, 5, 17, 23, 7, 24, 12, 10, 8, 2, 9]) (2, 3, 1)
""" | [
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... | 1.85348 | 273 |
import numpy as np
from meta_policy_search.envs.base import MetaEnv
from meta_policy_search.utils import logger
import gym
from gym.envs.mujoco.mujoco_env import MujocoEnv
IterationBound1 = 200
IterationBound2 = 600 | [
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import pycuda.autoinit
from pycuda.compiler import SourceModule
cu_matrix_kernel = SourceModule("""
#include <math.h>
#include <stdio.h>
#include "texture_fetch_functions.h"
#include "texture_types.h"
#define THREADS_PER_BLOCK 256
#define FIT_RADIUS 6
texture<float, cudaTextureType2DLayered, cudaReadModeElementType> tex;
__device__ void deconvolve3_columns(int width,int height,int rowstride,
double *data,double *buffer,double a,double b) {
double *row;
double q;
int i, j;
/*
// if (( height < 2) || (rowstride > width)) {
// printf("Failure in deconvolve3_rows: height, rowstride, width, a, b = %//d %d %d %f %f\n",height, rowstride, width, a, b );
// return;
// }
*/
if (!height || !width)
return;
if (height == 1) {
q = a + 2.0*b;
for (j = 0; j < width; j++)
data[j] /= q;
return;
}
if (height == 2) {
q = a*(a + 2.0*b);
for (j = 0; j < width; j++) {
buffer[0] = (a + b)/q*data[j] - b/q*data[rowstride + j];
data[rowstride + j] = (a + b)/q*data[rowstride + j] - b/q*data[j];
data[j] = buffer[0];
}
return;
}
/* Special-case first row */
buffer[0] = a + b;
/* Inner rows */
for (i = 1; i < height-1; i++) {
q = b/buffer[i-1];
buffer[i] = a - q*b;
row = data + (i - 1)*rowstride;
for (j = 0; j < width; j++)
row[rowstride + j] -= q*row[j];
}
/* Special-case last row */
q = b/buffer[i-1];
buffer[i] = a + b*(1.0 - q);
row = data + (i - 1)*rowstride;
for (j = 0; j < width; j++)
row[rowstride + j] -= q*row[j];
/* Go back */
row += rowstride;
for (j = 0; j < width; j++)
row[j] /= buffer[i];
do {
i--;
row = data + i*rowstride;
for (j = 0; j < width; j++)
row[j] = (row[j] - b*row[rowstride + j])/buffer[i];
} while (i > 0);
}
__device__ void deconvolve3_rows(int width,int height,int rowstride,double *data,
double *buffer,double a,double b) {
double *row;
double q;
int i, j;
/*
// if (( height < 2) || (rowstride > width)) {
// printf("Failure in deconvolve3_rows\n");
// return;
// }
*/
if (!height || !width)
return;
if (width == 1) {
q = a + 2.0*b;
for (i = 0; i < height; i++)
data[i*rowstride] /= q;
return;
}
if (width == 2) {
q = a*(a + 2.0*b);
for (i = 0; i < height; i++) {
row = data + i*rowstride;
buffer[0] = (a + b)/q*row[0] - b/q*row[1];
row[1] = (a + b)/q*row[1] - b/q*row[0];
row[0] = buffer[0];
}
return;
}
/* Special-case first item */
buffer[0] = a + b;
/* Inner items */
for (j = 1; j < width-1; j++) {
q = b/buffer[j-1];
buffer[j] = a - q*b;
data[j] -= q*data[j-1];
}
/* Special-case last item */
q = b/buffer[j-1];
buffer[j] = a + b*(1.0 - q);
data[j] -= q*data[j-1];
/* Go back */
data[j] /= buffer[j];
do {
j--;
data[j] = (data[j] - b*data[j+1])/buffer[j];
} while (j > 0);
/* Remaining rows */
for (i = 1; i < height; i++) {
row = data + i*rowstride;
/* Forward */
for (j = 1; j < width-1; j++)
row[j] -= b*row[j-1]/buffer[j-1];
row[j] -= b*row[j-1]/buffer[j-1];
/* Back */
row[j] /= buffer[j];
do {
j--;
row[j] = (row[j] - b*row[j+1])/buffer[j];
} while (j > 0);
}
}
__device__ void resolve_coeffs_2d(int width, int height, int rowstride, double *data) {
double *buffer;
int max;
max = width > height ? width : height;
buffer = (double *)malloc(max*sizeof(double));
deconvolve3_rows(width, height, rowstride, data, buffer, 13.0/21.0, 4.0/21.0);
deconvolve3_columns(width, height, rowstride, data, buffer, 13.0/21.0, 4.0/21.0);
free(buffer);
}
__device__ double interpolate_2d(double x,double y,int rowstride,double *coeff) {
double wx[4], wy[4];
int i, j;
double v, vx;
/*
// if (x < 0.0 || x > 1.0 || y < 0.0 || y > 1.0) {
// printf("interpolate_2d: x or y out of bounds %f %f\n",x,y);
// return(-1.0);
// }
*/
wx[0] = 4.0/21.0 + (-11.0/21.0 + (0.5 - x/6.0)*x)*x;
wx[1] = 13.0/21.0 + (1.0/14.0 + (-1.0 + x/2.0)*x)*x;
wx[2] = 4.0/21.0 + (3.0/7.0 + (0.5 - x/2.0)*x)*x;
wx[3] = (1.0/42.0 + x*x/6.0)*x;
wy[0] = 4.0/21.0 + (-11.0/21.0 + (0.5 - y/6.0)*y)*y;
wy[1] = 13.0/21.0 + (1.0/14.0 + (-1.0 + y/2.0)*y)*y;
wy[2] = 4.0/21.0 + (3.0/7.0 + (0.5 - y/2.0)*y)*y;
wy[3] = (1.0/42.0 + y*y/6.0)*y;
v = 0.0;
for (i = 0; i < 4; i++) {
vx = 0.0;
for (j = 0; j < 4; j++)
vx += coeff[i*rowstride + j]*wx[j];
v += wy[i]*vx;
}
return v;
}
__device__ float integrated_profile(int profile_type, int idx, int idy, float xpos,
float ypos, float *psf_parameters, float *lut_0,
float *lut_xd, float *lut_yd) {
int psf_size;
float psf_height, psf_sigma_x, psf_sigma_y, psf_xpos, psf_ypos;
float p0;
int ip, jp;
double pi=3.14159265,fwtosig=0.8493218;
psf_size = (int) psf_parameters[0];
psf_height = psf_parameters[1];
psf_sigma_x = psf_parameters[2];
psf_sigma_y = psf_parameters[3];
psf_ypos = psf_parameters[4];
psf_xpos = psf_parameters[5];
if (profile_type == 0) {
// gaussian
// PSF at location (Idx,Idy). PSF is centred at (7.5,7.5)
// Analytic part
p0 = 0.5*psf_height*pi*fwtosig*fwtosig*
(erf((idx-7.5+0.5)/(1.41421356*psf_sigma_x)) -
erf((idx-7.5-0.5)/(1.41421356*psf_sigma_x))) *
(erf((idy-7.5+0.5)/(1.41421356*psf_sigma_y)) -
erf((idy-7.5-0.5)/(1.41421356*psf_sigma_y)));
// Index into the lookup table
ip = psf_size/2 + 2*idx - 15;
jp = psf_size/2 + 2*idy - 15;
if ((ip>=0) && (ip<=psf_size-1) && (jp>=0) && (jp<=psf_size-1)) {
p0 += lut_0[ip+psf_size*jp] + lut_xd[ip+psf_size*jp]*(xpos-psf_xpos) +
lut_yd[ip+psf_size*jp]*(ypos-psf_ypos);
}
return p0;
} else if (profile_type == 1) {
// moffat25
// From iraf/noao/digiphot/daophot/daolib/profile.x
float d[4][4] = {{ 0.0, 0.0, 0.0, 0.0},
{-0.28867513, 0.28867513, 0.0, 0.0},
{-0.38729833, 0.0, 0.38729833, 0.0},
{-0.43056816, -0.16999052, 0.16999052, 0.43056816}};
float w[4][4] = {{1.0, 0.0, 0.0, 0.0},
{0.5, 0.5, 0.0, 0.0},
{0.27777778, 0.44444444, 0.27777778, 0.0},
{0.17392742, 0.32607258, 0.32607258, 0.17392742}};
double alpha = 0.3195079;
float p1sq, p2sq, p1p2, dx, dy, xy, denom, func, x[4], xsq[4], p1xsq[4];
float y, ysq, p2ysq, wt, p4fod, wp4fod, wf;
int npt, ix, iy;
p1sq = psf_parameters[2]*psf_parameters[2];
p2sq = psf_parameters[3]*psf_parameters[3];
p1p2 = psf_parameters[2]*psf_parameters[3];
dx = idx-7.5+0.5;
dy = idy-7.5+0.5;
xy = dx * dy;
denom = 1.0 + alpha * (dx*dx/p1sq + dy*dy/p2sq + xy*psf_parameters[4]);
if (denom > 1.0e4) {
return 0.0;
}
p0 = 0.0;
func = 1.0 / (p1p2*pow(double(denom),double(2.5)));
if (func >= 0.046) {
npt = 4;
} else if (func >= 0.0022) {
npt = 3;
} else if (func >= 0.0001) {
npt = 2;
} else if (func >= 1.0e-10) {
p0 = (2.5 - 1.0) * func;
}
if (func >= 0.0001) {
for (ix=0; ix<npt; ix++) {
x[ix] = dx + d[npt][ix];
xsq[ix] = x[ix]*x[ix];
p1xsq[ix] = xsq[ix]/p1sq;
}
for (iy=0; iy<npt; iy++) {
y = dy + d[npt][iy];
ysq = y*y;
p2ysq = ysq/p2sq;
for (ix=0; ix<npt; ix++) {
wt = w[npt][iy] * w[npt][ix];
xy = x[ix] * y;
denom = 1.0 + alpha * (p1xsq[ix] + p2ysq + xy*psf_parameters[4]);
func = (2.5 - 1.0) / (p1p2 * pow(double(denom),double(2.5)) );
p4fod = 2.5 * alpha * func / denom;
wp4fod = wt * p4fod;
wf = wt * func;
p0 += wf;
}
}
}
p0 *= psf_parameters[1];
// Index into the lookup table
ip = psf_size/2 + 2*idx - 15;
jp = psf_size/2 + 2*idy - 15;
if ((ip>=0) && (ip<=psf_size-1) && (jp>=0) && (jp<=psf_size-1)) {
p0 += lut_0[ip+psf_size*jp] + lut_xd[ip+psf_size*jp]*(xpos-psf_xpos) +
lut_yd[ip+psf_size*jp]*(ypos-psf_ypos);
}
return p0;
} else {
return 0.0;
}
}
__global__ void convolve_image_psf(int profile_type, int nx, int ny, int dx, int dy,
int dp, int ds, int n_coeff, int nkernel,
int kernel_radius,int *kxindex,
int *kyindex, int* ext_basis, float *psf_parameters,
float *psf_0, float *psf_xd, float *psf_yd,
float *coeff,float *cim1, float* cim2) {
int id, txa, tyb, txag, tybg;
int np, ns, i, j, ii, ip, jp, ic, ki, a, b;
int d1, sidx, l, m, l1, m1, ig, jg;
int psf_size, ix, jx;
float x, y, p0, p1, p1g, cpsf_pixel, xpos, ypos;
float psf_height, psf_sigma_x, psf_sigma_y, psf_sigma_xy, psf_xpos, psf_ypos;
float gain,psf_rad,psf_rad2, px, py;
float sx2, sy2, sxy2, sx2msy2, sx2psy2;
double psf_norm,dd;
double pi=3.14159265,fwtosig=0.8493218;
__shared__ double psf_sum[256];
__shared__ double cpsf[256];
__shared__ double cpix1[256];
__shared__ double cpix2[256];
// initialise memory
id = threadIdx.x+threadIdx.y*16;
cpsf[id] = 0.0;
// star position in normalised units
xpos = blockIdx.x*dx + dx/2;
ypos = blockIdx.y*dy + dy/2;
x = (xpos - 0.5*(nx-1))/(nx-1);
y = (ypos - 0.5*(ny-1))/(ny-1);
// number of polynomial coefficients per basis function
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
// PSF parameters
psf_size = (int) psf_parameters[0];
psf_height = psf_parameters[1];
psf_sigma_x = psf_parameters[2];
psf_sigma_y = psf_parameters[3];
psf_ypos = psf_parameters[4];
psf_xpos = psf_parameters[5];
psf_rad = psf_parameters[6];
gain = psf_parameters[7];
if (psf_rad > 5.0) {
psf_rad = 5.0;
}
psf_rad2 = psf_rad*psf_rad;
// PSF integral
__syncthreads();
psf_sum[id] = 0.0;
for (i=threadIdx.x+1; i<psf_size-1; i+=blockDim.x) {
for (j=threadIdx.y+1; j<psf_size-1; j+=blockDim.y) {
psf_sum[id] += psf_0[i+j*psf_size];
}
}
__syncthreads();
i = 128;
while (i != 0) {
if (id < i) {
psf_sum[id] += psf_sum[id + i];
}
__syncthreads();
i /= 2;
}
__syncthreads();
if (profile_type == 0) {
// gaussian
psf_norm = 0.25*psf_sum[0] + psf_height*2*pi*fwtosig*fwtosig;
} else if (profile_type == 1) {
// moffat25
psf_sigma_xy = psf_parameters[8];
sx2 = psf_sigma_x*psf_sigma_x;
sy2 = psf_sigma_y*psf_sigma_y;
sxy2 = psf_sigma_xy*psf_sigma_xy;
sx2msy2 = 1.0/sx2 - 1.0/sy2;
sx2psy2 = 1.0/sx2 + 1.0/sy2;
px = 1.0/sqrt( sx2psy2 + sqrt(sx2msy2*sx2msy2 + sxy2) );
py = 1.0/sqrt( sx2psy2 - sqrt(sx2msy2*sx2msy2 + sxy2) );
psf_norm = 0.25*psf_sum[0] + psf_height*pi*(px*py)/(psf_sigma_x*psf_sigma_y);
}
// Construct the convolved PSF
// PSF at location (Idx,Idy). PSF is centred at (7.5,7.5)
// Analytic part
p0 = integrated_profile(profile_type, threadIdx.x, threadIdx.y, xpos, ypos,
psf_parameters, psf_0, psf_xd, psf_yd);
__syncthreads();
cpsf_pixel = 0.0;
// Iterate over coefficients
for (ic=0; ic<n_coeff; ic++) {
// basis function position
ki = ic < np ? 0 : (ic-np)/ns + 1;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
// Set the polynomial degree for the subvector and the
// index within the subvector
if (ki == 0) {
d1 = dp;
sidx = ic;
} else {
d1 = ds;
sidx = ic - np - (ki-1)*ns;
}
// Compute the polynomial index (l,m) values corresponding
// to the index within the subvector
l1 = m1 = 0;
if (d1 > 0) {
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == sidx) {
l1 = l;
m1 = m;
}
i++;
}
}
}
// Indices into the PSF
if (ki > 0) {
txa = threadIdx.x + a;
tyb = threadIdx.y + b;
p1 = integrated_profile(profile_type, txa, tyb, xpos, ypos,
psf_parameters, psf_0, psf_xd, psf_yd);
__syncthreads();
// If we have an extended basis function, we need to
// average the PSF over a 3x3 grid
if (ext_basis[ki]) {
p1 = 0.0;
for (ig=-1; ig<2; ig++) {
for (jg=-1; jg<2; jg++) {
txag = txa + ig;
tybg = tyb + jg;
p1g = integrated_profile(profile_type, txag, tybg, xpos, ypos,
psf_parameters, psf_0, psf_xd, psf_yd);
__syncthreads();
p1 += p1g;
}
}
p1 /= 9.0;
}
cpsf_pixel += coeff[ic]*(p1-p0)*pow(x,l1)*pow(y,m1);
} else {
cpsf_pixel += coeff[ic]*p0*pow(x,l1)*pow(y,m1);
}
}
} //end ic loop
__syncthreads();
cpsf[id] = cpsf_pixel/psf_norm;
__syncthreads();
// Now convolve the image section with the convolved PSF
for (i=xpos-dx/2; i<xpos+dx/2; i++) {
for (j=ypos-dy/2; j<ypos+dy/2; j++) {
ix = (int)floor(i+0.5)+threadIdx.x-8.0;
jx = (int)floor(j+0.5)+threadIdx.y-8.0;
cpix1[id] = cpsf[id]*tex2DLayered(tex,ix,jx,0);
cpix2[id] = cpsf[id]*tex2DLayered(tex,ix,jx,1);
__syncthreads();
// Parallel sum
ii = 128;
while (ii != 0) {
if (id < ii) {
cpix1[id] += cpix1[id + ii];
cpix2[id] += cpix2[id + ii];
}
__syncthreads();
ii /= 2;
}
if (id == 0) {
cim1[i+j*nx] = cpix1[0];
cim2[i+j*nx] = cpix2[0];
}
__syncthreads();
}
}
return;
}
__global__ void cu_photom(int profile_type,
int nx, int ny, int dp, int ds, int n_coeff, int nkernel,
int kernel_radius,int *kxindex,
int *kyindex, int* ext_basis, float *psf_parameters,
float *psf_0, float *psf_xd, float *psf_yd,
float *posx,
float *posy, float *coeff,
float *flux, float *dflux, float *star_sky) {
int id, txa, tyb, txag, tybg;
int np, ns, i, j, ip, jp, ic, ki, a, b;
int d1, sidx, l, m, l1, m1, ig, jg;
int psf_size, ix, jx;
float x, y, p0, p1, p1g, cpsf_pixel, xpos, ypos, dd;
float psf_height, psf_sigma_x, psf_sigma_y, psf_sigma_xy, psf_xpos, psf_ypos;
float psf_rad, psf_rad2, gain, fl, inv_var, px, py;
float sx2, sy2, sxy2, sx2msy2, sx2psy2;
double subx, suby, psf_norm, bgnd;
double pi=3.14159265, fwtosig=0.8493218, RON=5.0;
__shared__ double psf_sum[256];
__shared__ double cpsf[256];
__shared__ float mpsf[256];
__shared__ float fsum1[256];
__shared__ float fsum2[256];
__shared__ float fsum3[256];
__shared__ float fsum4[256];
__shared__ float fsum5[256];
// initialise memory
id = threadIdx.x+threadIdx.y*16;
cpsf[id] = 0.0;
mpsf[id] = 0.0;
// star position in normalised units
xpos = posx[blockIdx.x];
ypos = posy[blockIdx.x];
x = (xpos - 0.5*(nx-1))/(nx-1);
y = (ypos - 0.5*(ny-1))/(ny-1);
// number of polynomial coefficients per basis function
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
// PSF parameters
psf_size = (int) psf_parameters[0];
psf_height = psf_parameters[1];
psf_sigma_x = psf_parameters[2];
psf_sigma_y = psf_parameters[3];
psf_ypos = psf_parameters[4];
psf_xpos = psf_parameters[5];
psf_rad = psf_parameters[6];
gain = psf_parameters[7];
if (psf_rad > 7.0) {
psf_rad = 7.0;
}
psf_rad2 = psf_rad*psf_rad;
// PSF integral
__syncthreads();
psf_sum[id] = 0.0;
for (i=threadIdx.x; i<psf_size; i+=blockDim.x) {
for (j=threadIdx.y; j<psf_size; j+=blockDim.y) {
psf_sum[id] += psf_0[i+j*psf_size];
//if (blockIdx.x == 120) {
// printf("i, j, id, psf_0: %d %d %d %f\\n",i,j,id,psf_0[i+j*psf_size]);
//}
}
}
__syncthreads();
i = 128;
while (i != 0) {
if (id < i) {
psf_sum[id] += psf_sum[id + i];
}
__syncthreads();
i /= 2;
}
__syncthreads();
if (profile_type == 0) {
// gaussian
psf_norm = 0.25*psf_sum[0] + psf_height*2*pi*fwtosig*fwtosig;
//if ((id == 0) && (blockIdx.x==120)){
// printf("psf_sum0, psf_height, psf_norm: %f %f %f\\n",psf_sum[0],psf_height,psf_norm);
//}
} else if (profile_type == 1) {
// moffat25
psf_sigma_xy = psf_parameters[8];
sx2 = psf_sigma_x*psf_sigma_x;
sy2 = psf_sigma_y*psf_sigma_y;
sxy2 = psf_sigma_xy*psf_sigma_xy;
sx2msy2 = 1.0/sx2 - 1.0/sy2;
sx2psy2 = 1.0/sx2 + 1.0/sy2;
px = 1.0/sqrt( sx2psy2 + sqrt(sx2msy2*sx2msy2 + sxy2) );
py = 1.0/sqrt( sx2psy2 - sqrt(sx2msy2*sx2msy2 + sxy2) );
psf_norm = 0.25*psf_sum[0] + psf_height*pi*(px*py)/(psf_sigma_x*psf_sigma_y);
//if ((id == 0) && (blockIdx.x==120)){
// printf("psf_sum0, psf_height, psf_norm: %f %f %f\\n",psf_sum[0],psf_height, psf_norm);
//}
}
// Construct the convolved PSF
// PSF at location (Idx,Idy). PSF is centred at (7.5,7.5)
// Analytic part
p0 = integrated_profile(profile_type, threadIdx.x, threadIdx.y, xpos, ypos,
psf_parameters, psf_0, psf_xd, psf_yd);
__syncthreads();
// Spatially variable part
//
// +
// psf_xd[ipsf+psf_size*jpsf]*(xpos-psf_xpos) +
// psf_yd[ipsf+psf_size*jpsf]*(ypos-psf_ypos);
// }
//
cpsf_pixel = 0.0;
// Iterate over coefficients
for (ic=0; ic<n_coeff; ic++) {
// basis function position
ki = ic < np ? 0 : (ic-np)/ns + 1;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
// Set the polynomial degree for the subvector and the
// index within the subvector
if (ki == 0) {
d1 = dp;
sidx = ic;
} else {
d1 = ds;
sidx = ic - np - (ki-1)*ns;
}
// Compute the polynomial index (l,m) values corresponding
// to the index within the subvector
l1 = m1 = 0;
if (d1 > 0) {
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == sidx) {
l1 = l;
m1 = m;
}
i++;
}
}
}
// Indices into the PSF
if (ki > 0) {
txa = threadIdx.x + a;
tyb = threadIdx.y + b;
p1 = integrated_profile(profile_type, txa, tyb, xpos, ypos,
psf_parameters, psf_0, psf_xd, psf_yd);
__syncthreads();
//
// +
// psf_xd[ipsf+psf_size*jpsf]*(xpos-psf_xpos) +
// psf_yd[ipsf+psf_size*jpsf]*(ypos-psf_ypos);
// }
//
// If we have an extended basis function, we need to
// average the PSF over a 3x3 grid
if (ext_basis[ki]) {
p1 = 0.0;
for (ig=-1; ig<2; ig++) {
for (jg=-1; jg<2; jg++) {
txag = txa + ig;
tybg = tyb + jg;
p1g = integrated_profile(profile_type, txag, tybg, xpos, ypos,
psf_parameters, psf_0, psf_xd, psf_yd);
__syncthreads();
//
// +
// psf_xd[ipsf+psf_size*jpsf]*(xpos-psf_xpos) +
// psf_yd[ipsf+psf_size*jpsf]*(ypos-psf_ypos);
// }
//
p1 += p1g;
}
}
p1 /= 9.0;
}
cpsf_pixel += coeff[ic]*(p1-p0)*pow(x,l1)*pow(y,m1);
} else {
cpsf_pixel += coeff[ic]*p0*pow(x,l1)*pow(y,m1);
}
}
} //end ic loop
__syncthreads();
cpsf[id] = cpsf_pixel/psf_norm;
__syncthreads();
/* Uncomment to print convolved PSF
if ((id == 0) && (blockIdx.x==14)){
txa = 7;
tyb = 7;
ip = psf_size/2 + 2*txa - 15;
jp = psf_size/2 + 2*tyb - 15;
if (profile_type == 0) {
printf("psf_test: %lf %lf %lf %lf\\n",
0.5*psf_height*pi*fwtosig*fwtosig*
(erf((txa-7.5+0.5)/(1.41421356*psf_sigma_x)) -
erf((txa-7.5-0.5)/(1.41421356*psf_sigma_x))) *
(erf((tyb-7.5+0.5)/(1.41421356*psf_sigma_y)) -
erf((tyb-7.5-0.5)/(1.41421356*psf_sigma_y))),
psf_0[ip+psf_size*jp],
psf_xd[ip+psf_size*jp]*(xpos-psf_xpos),
psf_yd[ip+psf_size*jp]*(ypos-psf_ypos));
}
dd = 0.0;
printf("cpsf\\n");
for (j=15; j>=0; j--) {
printf("%2d ",j);
for (i=0; i<16; i++) {
printf("%6.4f ",cpsf[i+j*16]);
dd += cpsf[i+j*16];
}
printf("\\n");
}
printf("sum = %f\\n",dd);
printf("psf lookup table fraction: %f\\n",psf_sum[0]/psf_norm);
}
*/
__syncthreads();
// Map the convolved PSF to the subpixel star coordinates
if (id == 0) {
resolve_coeffs_2d(16,16,16,cpsf);
}
__syncthreads();
mpsf[id] = 0.0;
subx = ceil(xpos+0.5+0.0000000001) - (xpos+0.5);
suby = ceil(ypos+0.5+0.0000000001) - (ypos+0.5);
if ((threadIdx.x > 1) && (threadIdx.x < 14) &&
(threadIdx.y > 1) && (threadIdx.y < 14)) {
mpsf[id] = (float)interpolate_2d(subx,suby,16,&cpsf[threadIdx.x-2+(threadIdx.y-2)*16]);
}
__syncthreads();
// force negative pixels to zero
mpsf[id] = mpsf[id] > 0.0 ? mpsf[id] : 0.0;
__syncthreads();
//
// Normalise mapped PSF
// (No - the convolved PSF contains the phot scale)
/*
cpsf[id] = mpsf[id];
__syncthreads();
i = 128;
while (i != 0) {
if (id < i) {
cpsf[id] += cpsf[id + i];
}
__syncthreads();
i /= 2;
}
mpsf[id] /= cpsf[0];
*/
/* Uncomment to print mapped PSF */
if ((id == 0) && (blockIdx.x==14)){
printf("xpos, ypos: %f %f\\n",xpos,ypos);
printf("subx, suby: %f %f\\n",subx,suby);
printf("mpsf\\n");
dd = 0.0;
for (j=15; j>=0; j--) {
printf("%2d ",j);
for (i=0; i<16; i++) {
printf("%6.4f ",mpsf[i+j*16]);
dd += mpsf[i+j*16];
}
printf("\\n");
}
printf("sum = %f\\n",dd);
}
__syncthreads();
// Fit the mapped PSF to the difference image to compute an
// optimal flux estimate.
// Assume the difference image is in tex(:,:,0)
// and the inverse variance in tex(:,:,1).
// We need to iterate to get the variance correct
//
fl = 0.0;
for (j=0; j<3; j++) {
fsum1[id] = 0.0;
fsum2[id] = 0.0;
fsum3[id] = 0.0;
__syncthreads();
/*
if ((id == 0) && (blockIdx.x==14)){
printf("photom, j=%d\\n",j);
}
*/
if (pow(threadIdx.x-8.0,2)+pow(threadIdx.y-8.0,2) < psf_rad2) {
ix = (int)floor(xpos+0.5)+threadIdx.x-8.0;
jx = (int)floor(ypos+0.5)+threadIdx.y-8.0;
inv_var = 1.0/(1.0/tex2DLayered(tex,ix,jx,1) + fl*mpsf[id]/gain);
fsum1[id] = mpsf[id]*tex2DLayered(tex,ix,jx,0)*inv_var;
fsum2[id] = mpsf[id]*mpsf[id]*inv_var;
fsum3[id] = mpsf[id];
/*
if ((blockIdx.x==14)){
printf("ix jx mpsf im: %03d %03d %6.5f %12.2f\\n",ix,jx,mpsf[id],tex2DLayered(tex,ix,jx,0));
}
*/
}
__syncthreads();
// Parallel sum
i = 128;
while (i != 0) {
if (id < i) {
fsum1[id] += fsum1[id + i];
fsum2[id] += fsum2[id + i];
fsum3[id] += fsum3[id + i];
}
__syncthreads();
i /= 2;
}
fl = fsum1[0]/fsum2[0];
}
if (id == 0) {
flux[blockIdx.x] = fl;
dflux[blockIdx.x] = sqrt(fsum3[0]*fsum3[0]/fsum2[0]);
}
/* Uncomment for debug info */
/*
__syncthreads();
i = 128;
while (i != 0) {
if (id < i) {
mpsf[id] += mpsf[id + i];
}
__syncthreads();
i /= 2;
}
__syncthreads();
if (id == 0) {
if (blockIdx.x == 120) {
printf("result: %f %f %f %f %f %f %f %f %f %f %f %f\\n",fsum1[0],fsum2[0],fsum3[0],mpsf[0],psf_norm,psf_sum[0],bgnd,flux[blockIdx.x],flux[blockIdx.x]*fsum3[0],flux[blockIdx.x]*mpsf[0],fsum4[0],dflux[blockIdx.x]);
}
}
*/
__syncthreads();
return;
}
__global__ void cu_compute_model(int dp, int ds, int db, int *kxindex,
int *kyindex, int* ext_basis, int nkernel, float *coefficient,
float *M) {
int np, ns, nb, hs, idx, ki, a, b, d1, sidx, l, m, l1, m1, i;
double x, y, Bi;
__shared__ double count[THREADS_PER_BLOCK];
// Calculate number of terms in subvectors
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
nb = (db+1)*(db+2)/2;
hs = (nkernel-1)*ns+np+nb;
x = (blockIdx.x - 0.5*(gridDim.x-1))/(gridDim.x-1);
y = (blockIdx.y - 0.5*(gridDim.y-1))/(gridDim.y-1);
count[threadIdx.x] = 0.0;
for (idx = threadIdx.x; idx < hs; idx += blockDim.x) {
// This is the index of the subvector and its kernel offsets
ki = idx < np ? 0 : (idx-np)/ns + 1;
a = b = 0;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
}
// Set the polynomial degree for the subvector and the
// index within the subvector
if (ki == 0) {
d1 = dp;
sidx = idx;
} else if (ki < nkernel) {
d1 = ds;
sidx = idx - np - (ki-1)*ns;
} else {
d1 = db;
sidx = idx - np - (ki-1)*ns;
}
// Compute the (l,m) values corresponding to the index within
// the subvector
l1 = m1 = 0;
if (d1 > 0) {
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == sidx) {
l1 = l;
m1 = m;
}
i++;
}
}
}
if (ki == 0) {
Bi = tex2DLayered(tex,blockIdx.x,blockIdx.y,0);
} else if (ki < nkernel) {
if (ext_basis[ki]) {
Bi = tex2DLayered(tex,blockIdx.x+a,blockIdx.y+b,1)-
tex2DLayered(tex,blockIdx.x,blockIdx.y,0);
} else {
Bi = tex2DLayered(tex,blockIdx.x+a,blockIdx.y+b,0)-
tex2DLayered(tex,blockIdx.x,blockIdx.y,0);
}
} else {
Bi = 1.0;
}
count[threadIdx.x] += coefficient[idx]*pow(x,l1)*pow(y,m1)*Bi;
}
__syncthreads();
// Then parallel-sum the results
i = blockDim.x/2;
while (i != 0) {
if (threadIdx.x < i) {
count[threadIdx.x] += count[threadIdx.x + i];
}
__syncthreads();
i /= 2;
}
if (threadIdx.x == 0) {
M[blockIdx.x+gridDim.x*blockIdx.y] = count[0];
}
}
__global__ void cu_compute_vector(int dp, int ds, int db, int nx,
int ny, int *kxindex, int *kyindex, int *ext_basis, int nkernel,
int kernelRadius,float *V) {
int idx;
int np, ns, ki, a, b, d1, i, j;
int l, m, l1, m1;
float py, x, y, Bi;
double temp;
__shared__ double count[THREADS_PER_BLOCK];
// Calculate number of terms in subvectors
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
// This is the index of the subvector and its kernel offsets
ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1;
a = b = 0;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
}
// Set the polynomial degrees for the submatrix and the
// indices within the submatrix
if (ki == 0) {
d1 = dp;
idx = blockIdx.x;
} else if (ki < nkernel) {
d1 = ds;
idx = blockIdx.x - np - (ki-1)*ns;
} else {
d1 = db;
idx = blockIdx.x - np - (ki-1)*ns;
}
// Compute the (l,m) values corresponding to the index within
// the subvector
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == idx) {
l1 = l;
m1 = m;
}
i++;
}
}
// Compute the contribution to V from each image location.
// Use individual threads to sum over columns.
// tex[:,:,0] is the reference image,
// tex[:,:,1] is the blurred reference image,
// tex[:,:,2] is the target image,
// tex[:,:,3] is the inverse variance,
// tex[:,:,4] is the mask.
// Bi is the basis image value.
temp = 0.0;
Bi = 1.0;
__syncthreads();
for (j=kernelRadius; j<ny-kernelRadius; j++) {
y = (j - 0.5*(ny-1))/(ny-1);
py = pow(y,m1);
for (i=threadIdx.x+kernelRadius; i<nx-kernelRadius; i+=blockDim.x) {
x = (i - 0.5*(nx-1))/(nx-1);
if (ki == 0) {
Bi = tex2DLayered(tex,i,j,0);
} else if (ki < nkernel) {
if (ext_basis[ki]) {
Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0);
} else {
Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0);
}
} else {
Bi = 1.0;
}
temp += pow(x,l1)*py*Bi*tex2DLayered(tex,i,j,2)*tex2DLayered(tex,i,j,3)*
tex2DLayered(tex,i,j,4);
}
}
count[threadIdx.x] = temp;
__syncthreads();
// Then parallel-sum the rows
i = blockDim.x/2;
while (i != 0) {
if (threadIdx.x < i) {
count[threadIdx.x] += count[threadIdx.x + i];
}
__syncthreads();
i /= 2;
}
if (threadIdx.x == 0) {
V[blockIdx.x] = count[0];
}
}
__global__ void cu_compute_vector_stamps(int dp, int ds, int db, int nx,
int ny, int nstamps, int stamp_half_width, float *stamp_xpos, float* stamp_ypos,
int *kxindex, int *kyindex, int *ext_basis, int nkernel,
int kernelRadius,float *V) {
int idx;
int np, ns, ki, a, b, d1, i, j, i1, i2, j1, j2;
int l, m, l1, m1;
float py, x, y, Bi;
double temp;
__shared__ double count[THREADS_PER_BLOCK];
// Calculate number of terms in subvectors
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
// This is the index of the subvector and its kernel offsets
ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1;
a = b = 0;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
}
// Set the polynomial degrees for the submatrix and the
// indices within the submatrix
if (ki == 0) {
d1 = dp;
idx = blockIdx.x;
} else if (ki < nkernel) {
d1 = ds;
idx = blockIdx.x - np - (ki-1)*ns;
} else {
d1 = db;
idx = blockIdx.x - np - (ki-1)*ns;
}
// Compute the (l,m) values corresponding to the index within
// the subvector
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == idx) {
l1 = l;
m1 = m;
}
i++;
}
}
// Compute the contribution to V from each image location.
// Use individual threads to sum over columns.
// tex[:,:,0] is the reference image,
// tex[:,:,1] is the blurred reference image,
// tex[:,:,2] is the target image,
// tex[:,:,3] is the inverse variance,
// tex[:,:,4] is the mask.
// Bi is the basis image value.
temp = 0.0;
Bi = 1.0;
__syncthreads();
for (idx = threadIdx.x; idx<nstamps; idx += blockDim.x) {
j1 = max(0,(int)stamp_ypos[idx]-stamp_half_width);
j2 = min(ny,(int)stamp_ypos[idx]+stamp_half_width);
for (j=j1; j<j2; j++) {
y = (j - 0.5*(ny-1))/(ny-1);
py = pow(y,m1);
i1 = max(0,(int)stamp_xpos[idx]-stamp_half_width);
i2 = min(nx,(int)stamp_xpos[idx]+stamp_half_width);
for (i=i1; i<i2; i++) {
x = (i - 0.5*(nx-1))/(nx-1);
if (ki == 0) {
Bi = tex2DLayered(tex,i,j,0);
} else if (ki < nkernel) {
if (ext_basis[ki]) {
Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0);
} else {
Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0);
}
} else {
Bi = 1.0;
}
temp += pow(x,l1)*py*Bi*tex2DLayered(tex,i,j,2)*tex2DLayered(tex,i,j,3)*
tex2DLayered(tex,i,j,4);
}
}
}
count[threadIdx.x] = temp;
__syncthreads();
// Then parallel-sum the rows
i = blockDim.x/2;
while (i != 0) {
if (threadIdx.x < i) {
count[threadIdx.x] += count[threadIdx.x + i];
}
__syncthreads();
i /= 2;
}
if (threadIdx.x == 0) {
V[blockIdx.x] = count[0];
}
}
__global__ void cu_compute_matrix(int dp, int ds, int db, int nx,
int ny, int *kxindex, int *kyindex, int *ext_basis, int nkernel,
int kernelRadius,float *H) {
int idx, idy, idx0, idy0, idx1, idy1;
int np, ns, ki, kj, a, b, c, d, d1, d2, i, j;
int l, m, l1, m1, l2, m2;
float py, x, y, Bi, Bj;
double temp;
__shared__ double count[THREADS_PER_BLOCK];
// Terminate if we are not in the lower triangle
if (blockIdx.x > blockIdx.y) {
return;
}
// Calculate number of terms in submatrices
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
// These are indices of the submatrix and their kernel offsets
ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1;
kj = blockIdx.y < np ? 0 : (blockIdx.y-np)/ns + 1;
a = b = 0;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
}
if (kj<nkernel) {
c = kxindex[kj];
d = kyindex[kj];
}
// Set the polynomial degrees for the submatrix and the
// indices within the submatrix
if (ki == 0) {
d1 = dp;
idx = blockIdx.x;
} else if (ki < nkernel) {
d1 = ds;
idx = blockIdx.x - np - (ki-1)*ns;
} else {
d1 = db;
idx = blockIdx.x - np - (ki-1)*ns;
}
if (kj == 0) {
d2 = dp;
idy = blockIdx.y;
} else if (kj < nkernel) {
d2 = ds;
idy = blockIdx.y - np - (kj-1)*ns;
} else {
d2 = db;
idy = blockIdx.y - np - (kj-1)*ns;
}
if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel) && (idx > idy)) {
return;
}
idx0 = idx;
idy0 = idy;
// Compute the (l,m) values corresponding to the indices within
// the submatrix
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == idx) {
l1 = l;
m1 = m;
}
i++;
}
}
i = 0;
for (l=0; l<=d2; l++) {
for (m=0; m<=d2-l; m++) {
if (i == idy) {
l2 = l;
m2 = m;
}
i++;
}
}
// Compute the contribution to H from each image location.
// Use individual threads to sum over columns.
// tex[:,:,0] is the reference image,
// tex[:,:,1] is the blurred reference image,
// tex[:,:,2] is the target image,
// tex[:,:,3] is the inverse variance,
// tex[:,:,4] is the mask.
// Bi and Bj are the basis image values.
temp = 0.0;
Bi = Bj = 1.0;
__syncthreads();
for (j=kernelRadius; j<ny-kernelRadius; j++) {
y = (j - 0.5*(ny-1))/(ny-1);
py = pow(y,m1+m2);
for (i=threadIdx.x+kernelRadius; i<nx-kernelRadius; i+=blockDim.x) {
x = (i - 0.5*(nx-1))/(nx-1);
if (ki == 0) {
Bi = tex2DLayered(tex,i,j,0);
} else if (ki < nkernel) {
if (ext_basis[ki]) {
Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0);
} else {
Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0);
}
} else {
Bi = 1.0;
}
if (kj == 0) {
Bj = tex2DLayered(tex,i,j,0);
} else if (kj < nkernel) {
if (ext_basis[kj]) {
Bj = tex2DLayered(tex,i+c,j+d,1)-tex2DLayered(tex,i,j,0);
} else {
Bj = tex2DLayered(tex,i+c,j+d,0)-tex2DLayered(tex,i,j,0);
}
} else {
Bj = 1.0;
}
temp += pow(x,l1+l2)*py*Bi*Bj*tex2DLayered(tex,i,j,3)*tex2DLayered(tex,i,j,4);
}
}
count[threadIdx.x] = temp;
__syncthreads();
// Then parallel-sum the rows
i = blockDim.x/2;
while (i != 0) {
if (threadIdx.x < i) {
count[threadIdx.x] += count[threadIdx.x + i];
}
__syncthreads();
i /= 2;
}
if (threadIdx.x == 0) {
H[blockIdx.x+gridDim.x*blockIdx.y] = count[0];
H[blockIdx.y+gridDim.x*blockIdx.x] = count[0];
if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel)) {
idx1 = np + (ki-1)*ns;
idy1 = np + (kj-1)*ns;
H[(idx1+idy0)+gridDim.x*(idy1+idx0)] = count[0];
H[(idy1+idx0)+gridDim.x*(idx1+idy0)] = count[0];
}
}
}
__global__ void cu_compute_matrix_stamps(int dp, int ds, int db, int nx,
int ny, int nstamps, int stamp_half_width, float *stamp_xpos, float* stamp_ypos,
int *kxindex, int *kyindex, int *ext_basis, int nkernel,
int kernelRadius,float *H) {
int idx, idy, idx0, idy0, idx1, idy1;
int np, ns, ki, kj, a, b, c, d, d1, d2, i, j, i1, i2, j1, j2;
int l, m, l1, m1, l2, m2;
float px, py, x, y, Bi, Bj;
double temp;
__shared__ double count[THREADS_PER_BLOCK];
// Terminate if we are not in the lower triangle
if (blockIdx.x > blockIdx.y) {
return;
}
// Calculate number of terms in submatrices
np = (dp+1)*(dp+2)/2;
ns = (ds+1)*(ds+2)/2;
// These are indices of the submatrix and their kernel offsets
ki = blockIdx.x < np ? 0 : (blockIdx.x-np)/ns + 1;
kj = blockIdx.y < np ? 0 : (blockIdx.y-np)/ns + 1;
a = b = 0;
if (ki<nkernel) {
a = kxindex[ki];
b = kyindex[ki];
}
if (kj<nkernel) {
c = kxindex[kj];
d = kyindex[kj];
}
// Set the polynomial degrees for the submatrix and the
// indices within the submatrix
if (ki == 0) {
d1 = dp;
idx = blockIdx.x;
} else if (ki < nkernel) {
d1 = ds;
idx = blockIdx.x - np - (ki-1)*ns;
} else {
d1 = db;
idx = blockIdx.x - np - (ki-1)*ns;
}
if (kj == 0) {
d2 = dp;
idy = blockIdx.y;
} else if (kj < nkernel) {
d2 = ds;
idy = blockIdx.y - np - (kj-1)*ns;
} else {
d2 = db;
idy = blockIdx.y - np - (kj-1)*ns;
}
if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel) && (idx > idy)) {
return;
}
idx0 = idx;
idy0 = idy;
// Compute the (l,m) values corresponding to the indices within
// the submatrix
i = 0;
for (l=0; l<=d1; l++) {
for (m=0; m<=d1-l; m++) {
if (i == idx) {
l1 = l;
m1 = m;
}
i++;
}
}
i = 0;
for (l=0; l<=d2; l++) {
for (m=0; m<=d2-l; m++) {
if (i == idy) {
l2 = l;
m2 = m;
}
i++;
}
}
// Compute the contribution to H from each image location.
// Use individual threads to sum over stamps.
// tex[:,:,0] is the reference image,
// tex[:,:,1] is the blurred reference image,
// tex[:,:,2] is the target image,
// tex[:,:,3] is the inverse variance,
// tex[:,:,4] is the mask.
// Bi and Bj are the basis image values.
temp = 0.0;
Bi = Bj = 1.0;
__syncthreads();
for (idx = threadIdx.x; idx<nstamps; idx += blockDim.x) {
i1 = max(0,(int)stamp_xpos[idx]-stamp_half_width);
i2 = min(nx,(int)stamp_xpos[idx]+stamp_half_width);
for (i=i1; i<i2; i++) {
x = (i - 0.5*(nx-1))/(nx-1);
px = pow(x,l1+l2);
j1 = max(0,(int)stamp_ypos[idx]-stamp_half_width);
j2 = min(ny,(int)stamp_ypos[idx]+stamp_half_width);
for (j=j1; j<j2; j++) {
y = (j - 0.5*(ny-1))/(ny-1);
py = pow(y,m1+m2);
if (ki == 0) {
Bi = tex2DLayered(tex,i,j,0);
} else if (ki < nkernel) {
if (ext_basis[ki]) {
Bi = tex2DLayered(tex,i+a,j+b,1)-tex2DLayered(tex,i,j,0);
} else {
Bi = tex2DLayered(tex,i+a,j+b,0)-tex2DLayered(tex,i,j,0);
}
} else {
Bi = 1.0;
}
if (kj == 0) {
Bj = tex2DLayered(tex,i,j,0);
} else if (kj < nkernel) {
if (ext_basis[kj]) {
Bj = tex2DLayered(tex,i+c,j+d,1)-tex2DLayered(tex,i,j,0);
} else {
Bj = tex2DLayered(tex,i+c,j+d,0)-tex2DLayered(tex,i,j,0);
}
} else {
Bj = 1.0;
}
temp += px*py*Bi*Bj*tex2DLayered(tex,i,j,3)*tex2DLayered(tex,i,j,4);
}
}
}
count[threadIdx.x] = temp;
__syncthreads();
// Then parallel-sum the rows
i = blockDim.x/2;
while (i != 0) {
if (threadIdx.x < i) {
count[threadIdx.x] += count[threadIdx.x + i];
}
__syncthreads();
i /= 2;
}
if (threadIdx.x == 0) {
H[blockIdx.x+gridDim.x*blockIdx.y] = count[0];
H[blockIdx.y+gridDim.x*blockIdx.x] = count[0];
if ((ki>0) && (ki<nkernel) && (kj>0) && (kj<nkernel)) {
idx1 = np + (ki-1)*ns;
idy1 = np + (kj-1)*ns;
H[(idx1+idy0)+gridDim.x*(idy1+idx0)] = count[0];
H[(idy1+idx0)+gridDim.x*(idx1+idy0)] = count[0];
}
}
}
""")
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"""
Job framework defines components used for job submission and management.
It is built upon :mod:`execution` framework.
It provides constructs for:
1. Creating of job definition
2. Implementing of job instance
3. Implementing of job observer
There are two type of clients of the framework:
1. Job users
2. Job management implementation
"""
import abc
from collections import namedtuple
from fnmatch import fnmatch
from taro.jobs.execution import ExecutionError
class JobInfo:
"""
Immutable snapshot of job instance state
"""
@property
@property
@property
@property
@property
@property
@property
DisabledJob = namedtuple('DisabledJob', 'job_id regex created expires')
Warn = namedtuple('Warn', 'name params')
WarnEventCtx = namedtuple('WarnEventCtx', 'count')
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18558,
1009,
63,
9355,
13,
198,
1026,
3769,
34175,
329,
25,
198,
220,
352,
13,
30481,
286,
1693,
6770,
198,
... | 3.337349 | 249 |
import pbt
import sys
import unittest
@pbt.command(name="test")
| [
11748,
279,
18347,
198,
11748,
25064,
198,
11748,
555,
715,
395,
198,
198,
31,
79,
18347,
13,
21812,
7,
3672,
2625,
9288,
4943,
628
] | 2.75 | 24 |
import unittest
from pynvg.api import nvgli
if(__name__=="main"):
unittest.main() | [
11748,
555,
715,
395,
198,
6738,
279,
2047,
45119,
13,
15042,
1330,
299,
45119,
4528,
198,
198,
361,
7,
834,
3672,
834,
855,
1,
12417,
1,
2599,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419
] | 2.324324 | 37 |
# Generated by Django 3.0 on 2020-03-25 09:09
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
15,
319,
12131,
12,
3070,
12,
1495,
7769,
25,
2931,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.966667 | 30 |
import os
from django.template.loaders.filesystem import Loader as FileSystemLoader
from accounts.models import get_template
import settings
| [
11748,
28686,
198,
6738,
42625,
14208,
13,
28243,
13,
2220,
364,
13,
16624,
6781,
1330,
8778,
263,
355,
9220,
11964,
17401,
198,
6738,
5504,
13,
27530,
1330,
651,
62,
28243,
198,
11748,
6460,
628
] | 4.176471 | 34 |
import ipaddress
if __name__ == "__main__":
ip1 = IPAddress("10.1.1.1/25")
print(ip1 + 5)
print(5 + ip1)
print(ip1.__radd__(5))
| [
11748,
20966,
21975,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
20966,
16,
796,
27966,
1860,
601,
7203,
940,
13,
16,
13,
16,
13,
16,
14,
1495,
4943,
198,
220,
220,
220,
3601,
7,
541... | 1.934211 | 76 |