xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

48dc631b1c4a2cb88ce03ced0e0bc40234df9515

66,039

py

Python

nidaqmx/stream_writers.py

TheWiselyBearded/nidaqmx-python

4aff91f8302d6e75a954ceed88d55cf1836c2d04

[ "MIT" ]

1

2022-03-14T19:46:36.000Z

nidaqmx/stream_writers.py

TheWiselyBearded/nidaqmx-python

4aff91f8302d6e75a954ceed88d55cf1836c2d04

[ "MIT" ]

null

nidaqmx/stream_writers.py

TheWiselyBearded/nidaqmx-python

4aff91f8302d6e75a954ceed88d55cf1836c2d04

[ "MIT" ]

2

2022-03-14T19:46:51.000Z

2022-03-14T20:16:57.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy from nidaqmx import DaqError from nidaqmx._task_modules.write_functions import ( _write_analog_f_64, _write_analog_scalar_f_64, _write_binary_i_16, _write_binary_i_32, _write_binary_u_16, _write_binary_u_32, _write_ctr_freq, _write_ctr_ticks, _write_ctr_time, _write_ctr_freq_scalar, _write_ctr_ticks_scalar, _write_ctr_time_scalar, _write_digital_u_8, _write_digital_u_16, _write_digital_u_32, _write_digital_lines, _write_digital_scalar_u_32) from nidaqmx.error_codes import DAQmxErrors __all__ = ['AnalogSingleChannelWriter', 'AnalogMultiChannelWriter', 'AnalogUnscaledWriter', 'CounterWriter', 'DigitalSingleChannelWriter', 'DigitalMultiChannelWriter'] class UnsetAutoStartSentinel(object): pass AUTO_START_UNSET = UnsetAutoStartSentinel() del UnsetAutoStartSentinel class ChannelWriterBase(object): """ Defines base class for all NI-DAQmx stream writers. """ def __init__(self, task_out_stream, auto_start=AUTO_START_UNSET): """ Args: task_out_stream: Specifies the output stream associated with an NI-DAQmx task which to write samples. auto_start (Optional[bool]): Specifies if the write method automatically starts the task if you did not explicitly start it with the DAQmx Start Task method. If you do not specify a value for this parameter, NI-DAQmx determines its value based on the type of write method used. If you use a one sample write method, the value is True; conversely, if you use a many sample write method, the value is False. """ print("Out stream calls ChannelWriter Base") self._out_stream = task_out_stream self._task = task_out_stream._task self._handle = task_out_stream._task._handle self._verify_array_shape = True self._auto_start = auto_start @property def auto_start(self): """ bool: Specifies if the write method automatically starts the task if you did not explicitly start it with the DAQmx Start Task method. If you do not specify a value for this parameter, NI-DAQmx determines its value based on the type of write method used. If you use a one sample write method, its value is True; conversely, if you use a many sample write method, its value is False. """ return self._auto_start @auto_start.setter def auto_start(self, val): self._auto_start = val @auto_start.deleter def auto_start(self): self._auto_start = AUTO_START_UNSET @property def verify_array_shape(self): """ bool: Indicates whether the size and shape of the user-defined NumPy arrays passed to read methods are verified. Defaults to True when this object is instantiated. Setting this property to True may marginally adversely impact the performance of read methods. """ return self._verify_array_shape @verify_array_shape.setter def verify_array_shape(self, val): self._verify_array_shape = val def _verify_array(self, data, is_many_chan, is_many_samp): """ Verifies that the shape of the specified NumPy array can be used with the specified write method type, if the "verify_array_shape" property is set to True. Args: data (numpy.ndarray): Specifies the NumPy array to verify. is_many_chan (bool): Specifies if the write method is a many channel version. is_many_samp (bool): Specifies if the write method is a many sample version. """ if not self._verify_array_shape: return channels_to_write = self._task.channels number_of_channels = len(channels_to_write.channel_names) expected_num_dimensions = None if is_many_chan: if is_many_samp: expected_num_dimensions = 2 else: expected_num_dimensions = 1 if data.shape[0] != number_of_channels: self._task._raise_invalid_write_num_chans_error( number_of_channels, data.shape[0]) else: if is_many_samp: expected_num_dimensions = 1 if expected_num_dimensions is not None: self._raise_error_if_invalid_write_dimensions( expected_num_dimensions, len(data.shape)) def _verify_array_digital_lines( self, data, is_many_chan, is_many_line): """ Verifies that the shape of the specified NumPy array can be used to read samples from the current task which contains one or more channels that have one or more digital lines per channel, if the "verify_array_shape" property is set to True. Args: data (numpy.ndarray): Specifies the NumPy array to verify. is_many_chan (bool): Specifies if the write method is a many channel version. is_many_line (bool): Specifies if the write method is a many line version. """ if not self._verify_array_shape: return channels_to_write = self._task.channels number_of_channels = len(channels_to_write.channel_names) number_of_lines = self._out_stream.do_num_booleans_per_chan expected_num_dimensions = None if is_many_chan: if data.shape[0] != number_of_channels: self._task._raise_invalid_write_num_chans_error( number_of_channels, data.shape[0]) if is_many_line: expected_num_dimensions = 2 if data.shape[1] != number_of_lines: self._task._raise_invalid_num_lines_error( number_of_lines, data.shape[1]) else: expected_num_dimensions = 1 else: if is_many_line: expected_num_dimensions = 1 if data.shape[0] != number_of_lines: self._task._raise_invalid_num_lines_error( number_of_lines, data.shape[0]) if expected_num_dimensions is not None: self._raise_error_if_invalid_write_dimensions( expected_num_dimensions, len(data.shape)) def _raise_error_if_invalid_write_dimensions( self, num_dimensions_expected, num_dimensions_in_data): if num_dimensions_expected != num_dimensions_in_data: raise DaqError( 'Write cannot be performed because the NumPy array passed ' 'into this function is not shaped correctly. ' 'You must pass in a NumPy array of the correct number of ' 'dimensions based on the write method you use.\n\n' 'No. of dimensions of NumPy Array provided: {0}\n' 'No. of dimensions of NumPy Array required: {1}' .format(num_dimensions_in_data, num_dimensions_expected), DAQmxErrors.UNKNOWN.value, task_name=self._task.name) class AnalogSingleChannelWriter(ChannelWriterBase): """ Writes samples to an analog output channel in an NI-DAQmx task. """ def write_many_sample(self, data, timeout=10.0): """ Writes one or more floating-point samples to a single analog output channel in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 1D NumPy array of floating-point samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(data, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_analog_f_64( self._handle, data, data.shape[0], auto_start, timeout) def write_one_sample(self, data, timeout=10): """ Writes a single floating-point sample to a single analog output channel in a task. Args: data (float): Specifies the floating-point sample to write to the task. auto_start (Optional[bool]): Specifies if this method automatically starts the task if you did not explicitly start it with the DAQmx Start Task method. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_analog_scalar_f_64( self._handle, data, auto_start, timeout) class AnalogMultiChannelWriter(ChannelWriterBase): """ Writes samples to one or more analog output channels in an NI-DAQmx task. """ def write_many_sample(self, data, timeout=10.0): """ Writes one or more floating-point samples to one or more analog output channels in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of floating-point samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_analog_f_64( self._handle, data, data.shape[1], auto_start, timeout) def write_one_sample(self, data, timeout=10): """ Writes a single floating-point sample to one or more analog output channels in a task. Args: data (numpy.ndarray): Contains a 1D NumPy array of floating-point samples to write to the task. Each element of the array corresponds to a channel in the task. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array(data, True, False) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_analog_f_64( self._handle, data, 1, auto_start, timeout) class AnalogUnscaledWriter(ChannelWriterBase): """ Writes unscaled samples to one or more analog output channels in an NI-DAQmx task. """ def write_int16(self, data, timeout=10.0): """ Writes one or more unscaled 16-bit integer samples to one or more analog output channels in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of unscaled 16-bit integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_binary_i_16( self._handle, data, data.shape[1], auto_start, timeout) def write_int32(self, data, timeout=10.0): """ Writes one or more unscaled 32-bit integer samples to one or more analog output channels in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of unscaled 32-bit integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_binary_i_32( self._handle, data, data.shape[1], auto_start, timeout) def write_uint16(self, data, timeout=10.0): """ Writes one or more unscaled 16-bit unsigned integer samples to one or more analog output channels in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of unscaled 16-bit unsigned integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_binary_u_16( self._handle, data, data.shape[1], auto_start, timeout) def write_uint32(self, data, timeout=10.0): """ Writes one or more unscaled 32-bit unsigned integer samples to one or more analog output channels in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of unscaled 32-bit unsigned integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_binary_u_32( self._handle, data, data.shape[1], auto_start, timeout) class CounterWriter(ChannelWriterBase): """ Writes samples to a counter output channel in an NI-DAQmx task. """ def write_many_sample_pulse_frequency( self, frequencies, duty_cycles, timeout=10.0): """ Writes one or more pulse samples in terms of frequency to a single counter output channel in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: frequencies (numpy.ndarray): Contains a 1D NumPy array of floating-point values that holds the frequency portion of the pulse samples to write to the task. Each element of the array corresponds to a sample to write. duty_cycles (numpy.ndarray): Contains a 1D NumPy array of floating-point values that holds the duty cycle portion of the pulse samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(frequencies, False, True) self._verify_array(duty_cycles, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_ctr_freq( self._handle, frequencies, duty_cycles, frequencies.shape[0], auto_start, timeout) def write_many_sample_pulse_ticks( self, high_ticks, low_ticks, timeout=10.0): """ Writes one or more pulse samples in terms of ticks to a single counter output channel in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: high_ticks (numpy.ndarray): Contains a 1D NumPy array of 32-bit unsigned integer values that holds the high ticks portion of the pulse samples to write to the task. Each element of the array corresponds to a sample to write. low_ticks (numpy.ndarray): Contains a 1D NumPy array of 32-bit unsigned integer values that holds the low ticks portion of the pulse samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(high_ticks, False, True) self._verify_array(low_ticks, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_ctr_ticks( self._handle, high_ticks, low_ticks, high_ticks.shape[0], auto_start, timeout) def write_many_sample_pulse_time( self, high_times, low_times, timeout=10.0): """ Writes one or more pulse samples in terms of time to a single counter output channel in a task. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: high_times (numpy.ndarray): Contains a 1D NumPy array of floating-point values that holds the high time portion of the pulse samples to write to the task. Each element of the array corresponds to a sample to write. low_times (numpy.ndarray): Contains a 1D NumPy array of floating-point values that holds the low time portion of the pulse samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(high_times, False, True) self._verify_array(low_times, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_ctr_time( self._handle, high_times, low_times, high_times.shape[0], auto_start, timeout) def write_one_sample_pulse_frequency( self, frequency, duty_cycle, timeout=10): """ Writes a new pulse frequency and duty cycle to a single counter output channel in a task. Args: frequency (float): Specifies at what frequency to generate pulses. duty_cycle (float): Specifies the width of the pulse divided by the pulse period. NI-DAQmx uses this ratio combined with frequency to determine pulse width and the interval between pulses. auto_start (Optional[bool]): Specifies if this method automatically starts the task if you did not explicitly start it with the DAQmx Start Task method. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_ctr_freq_scalar( self._handle, frequency, duty_cycle, auto_start, timeout) def write_one_sample_pulse_ticks( self, high_ticks, low_ticks, timeout=10): """ Writes a new pulse high tick count and low tick count to a single counter output channel in a task. Args: high_ticks (float): Specifies the number of ticks the pulse is high. low_ticks (float): Specifies the number of ticks the pulse is low. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_ctr_ticks_scalar( self._handle, high_ticks, low_ticks, auto_start, timeout) def write_one_sample_pulse_time( self, high_time, low_time, timeout=10): """ Writes a new pulse high time and low time to a single counter output channel in a task. Args: high_time (float): Specifies the amount of time the pulse is high. low_time (float): Specifies the amount of time the pulse is low. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_ctr_time_scalar( self._handle, high_time, low_time, auto_start, timeout) class DigitalSingleChannelWriter(ChannelWriterBase): """ Writes samples to a single digital output channel in an NI-DAQmx task. """ def write_many_sample_port_byte(self, data, timeout=10.0): """ Writes one or more 8-bit unsigned integer samples to a single digital output channel in a task. Use this method for devices with up to 8 lines per port. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 1D NumPy array of 8-bit unsigned integer samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(data, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_digital_u_8( self._handle, data, data.shape[0], auto_start, timeout) def write_many_sample_port_uint16(self, data, timeout=10.0): """ Writes one or more 16-bit unsigned integer samples to a single digital output channel in a task. Use this method for devices with up to 16 lines per port. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 1D NumPy array of 16-bit unsigned integer samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(data, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_digital_u_16( self._handle, data, data.shape[0], auto_start, timeout) def write_many_sample_port_uint32(self, data, timeout=10.0): """ Writes one or more 32-bit unsigned integer samples to a single digital output channel in a task. Use this method for devices with up to 32 lines per port. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 1D NumPy array of 32-bit unsigned integer samples to write to the task. Each element of the array corresponds to a sample to write. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote. """ self._verify_array(data, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_digital_u_32( self._handle, data, data.shape[0], auto_start, timeout) def write_one_sample_multi_line(self, data, timeout=10): """ Writes a single boolean sample to a single digital output channel in a task. The channel can contain multiple digital lines. Args: data (numpy.ndarray): Contains a 1D NumPy array of boolean samples to write to the task. Each element of the array corresponds to a line in the channel. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array_digital_lines(data, False, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_lines( self._handle, data, 1, auto_start, timeout) def write_one_sample_one_line(self, data, timeout=10): """ Writes a single boolean sample to a single digital output channel in a task. The channel can contain only one digital line. Args: data (int): Specifies the boolean sample to write to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) numpy_array = numpy.asarray([data], dtype=numpy.bool) return _write_digital_lines( self._handle, numpy_array, 1, auto_start, timeout) def write_one_sample_port_byte(self, data, timeout=10): """ Writes a single 8-bit unsigned integer sample to a single digital output channel in a task. Use this method for devices with up to 8 lines per port. Args: data (int): Specifies the 8-bit unsigned integer sample to write to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) numpy_array = numpy.asarray([data], dtype=numpy.uint8) return _write_digital_u_8( self._handle, numpy_array, 1, auto_start, timeout) def write_one_sample_port_uint16(self, data, timeout=10): """ Writes a single 16-bit unsigned integer sample to a single digital output channel in a task. Use this method for devices with up to 16 lines per port. Args: data (int): Specifies the 16-bit unsigned integer sample to write to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) numpy_array = numpy.asarray([data], dtype=numpy.uint16) return _write_digital_u_16( self._handle, numpy_array, 1, auto_start, timeout) def write_one_sample_port_uint32(self, data, timeout=10): """ Writes a single 32-bit unsigned integer sample to a single digital output channel in a task. Use this method for devices with up to 32 lines per port. Args: data (int): Specifies the 32-bit unsigned integer sample to write to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_scalar_u_32( self._handle, data, auto_start, timeout) class DigitalMultiChannelWriter(ChannelWriterBase): """ Writes samples to one or more digital output channels in an NI-DAQmx task. """ def write_many_sample_port_byte(self, data, timeout=10.0): """ Writes one or more 8-bit unsigned integer samples to one or more digital output channels in a task. Use this method for devices with up to 8 lines per port. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of 8-bit unsigned integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_digital_u_8( self._handle, data, data.shape[1], auto_start, timeout) def write_many_sample_port_uint16(self, data, timeout=10.0): """ Writes one or more 16-bit unsigned integer samples to one or more digital output channels in a task. Use this method for devices with up to 16 lines per port. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of 16-bit unsigned integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_digital_u_16( self._handle, data, data.shape[1], auto_start, timeout) def write_many_sample_port_uint32(self, data, timeout=10.0): """ Writes one or more 32-bit unsigned integer samples to one or more digital output channels in a task. Use this method for devices with up to 32 lines per port. If the task uses on-demand timing, this method returns only after the device generates all samples. On-demand is the default timing type if you do not use the timing property on the task to configure a sample timing type. If the task uses any timing type other than on-demand, this method returns immediately and does not wait for the device to generate all samples. Your application must determine if the task is done to ensure that the device generated all samples. Args: data (numpy.ndarray): Contains a 2D NumPy array of 32-bit unsigned integer samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a sample to write to each channel. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. Returns: int: Specifies the actual number of samples this method successfully wrote to each channel in the task. """ self._verify_array(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else False) return _write_digital_u_32( self._handle, data, data.shape[1], auto_start, timeout) def write_one_sample_multi_line(self, data, timeout=10): """ Writes a single boolean sample to one or more digital output channels in a task. The channel can contain multiple digital lines. Args: data (numpy.ndarray): Contains a 2D NumPy array of boolean samples to write to the task. Each row corresponds to a channel in the task. Each column corresponds to a line from each channel. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array_digital_lines(data, True, True) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_lines( self._handle, data, 1, auto_start, timeout) def write_one_sample_one_line(self, data, timeout=10): """ Writes a single boolean sample to one or more digital output channels in a task. The channel can contain only one digital line. Args: data (numpy.ndarray): Contains a 1D NumPy array of boolean samples to write to the task. Each element in the array corresponds to a channel in the task. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array_digital_lines(data, True, False) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_lines( self._handle, data, 1, auto_start, timeout) def write_one_sample_port_byte(self, data, timeout=10): """ Writes a single 8-bit unsigned integer sample to one or more digital output channels in a task. Use this method for devices with up to 8 lines per port. Args: data (numpy.ndarray): Contains a 1D NumPy array of 8-bit unsigned integer samples to write to the task. Each element in the array corresponds to a channel in the task. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array(data, True, False) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_u_8( self._handle, data, 1, auto_start, timeout) def write_one_sample_port_uint16(self, data, timeout=10): """ Writes a single 16-bit unsigned integer sample to one or more digital output channels in a task. Use this method for devices with up to 16 lines per port. Args: data (numpy.ndarray): Contains a 1D NumPy array of 16-bit unsigned integer samples to write to the task. Each element in the array corresponds to a channel in the task. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array(data, True, False) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_u_16( self._handle, data, 1, auto_start, timeout) def write_one_sample_port_uint32(self, data, timeout=10): """ Writes a single 32-bit unsigned integer sample to one or more digital output channels in a task. Use this method for devices with up to 32 lines per port. Args: data (numpy.ndarray): Contains a 1D NumPy array of 32-bit unsigned integer samples to write to the task. Each element in the array corresponds to a channel in the task. The order of the channels in the array corresponds to the order in which you add the channels to the task. timeout (Optional[float]): Specifies the amount of time in seconds to wait for the method to write all samples. NI-DAQmx performs a timeout check only if the method must wait before it writes data. This method returns an error if the time elapses. The default timeout is 10 seconds. If you set timeout to nidaqmx.constants.WAIT_INFINITELY, the method waits indefinitely. If you set timeout to 0, the method tries once to write the submitted samples. If the method could not write all the submitted samples, it returns an error and the number of samples successfully written. """ self._verify_array(data, True, False) auto_start = (self._auto_start if self._auto_start is not AUTO_START_UNSET else True) return _write_digital_u_32( self._handle, data, 1, auto_start, timeout)

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Python

tvof/cms/migrations/0010_auto_20180509_1800.py

kingsdigitallab/tvof-django

12cb0aec4e155345a13602c7d7dfd0882ec92129

[ "MIT" ]

null

tvof/cms/migrations/0010_auto_20180509_1800.py

kingsdigitallab/tvof-django

12cb0aec4e155345a13602c7d7dfd0882ec92129

[ "MIT" ]

33

2019-12-04T22:37:50.000Z

2022-02-10T07:15:35.000Z

tvof/cms/migrations/0010_auto_20180509_1800.py

kingsdigitallab/tvof-django

12cb0aec4e155345a13602c7d7dfd0882ec92129

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.10 on 2018-05-09 17:00 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('cms', '0009_auto_20180509_1742'), ] operations = [ migrations.AddField( model_name='blogpost', name='title_fr', field=models.CharField(blank=True, default=b'', help_text="The page title as you'd like it to be seen by the public", max_length=255, verbose_name=b'Title'), ), migrations.AddField( model_name='homepage', name='title_fr', field=models.CharField(blank=True, default=b'', help_text="The page title as you'd like it to be seen by the public", max_length=255, verbose_name=b'Title'), ), migrations.AddField( model_name='indexpage', name='title_fr', field=models.CharField(blank=True, default=b'', help_text="The page title as you'd like it to be seen by the public", max_length=255, verbose_name=b'Title'), ), migrations.AddField( model_name='richtextpage', name='title_fr', field=models.CharField(blank=True, default=b'', help_text="The page title as you'd like it to be seen by the public", max_length=255, verbose_name=b'Title'), ), ]

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Python

tests/test_engine/test_queries/test_queryop_array_elemMatch.py

gitter-badger/MontyDB

849d03dc2cfed35739481e9acb1ff0bd8095c91b

[ "BSD-3-Clause" ]

null

tests/test_engine/test_queries/test_queryop_array_elemMatch.py

gitter-badger/MontyDB

849d03dc2cfed35739481e9acb1ff0bd8095c91b

[ "BSD-3-Clause" ]

null

tests/test_engine/test_queries/test_queryop_array_elemMatch.py

gitter-badger/MontyDB

849d03dc2cfed35739481e9acb1ff0bd8095c91b

[ "BSD-3-Clause" ]

null

import pytest from montydb.errors import OperationFailure def test_qop_elemMatch_1(monty_find, mongo_find): docs = [ {"a": [3, 2, 1]}, {"a": [4, 5]} ] spec = {"a": {"$elemMatch": {"$eq": 1}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_2(monty_find, mongo_find): docs = [ {"a": [{"b": 1}, {"b": 2}]}, {"a": [{"b": 3}, {"b": 4}]}, ] spec = {"a": {"$elemMatch": {"b": 1}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_3(monty_find, mongo_find): docs = [ {"a": [{"b": [10, 11]}, {"b": 2}]}, {"a": [{"b": [20, 21]}, {"b": 4}]}, ] spec = {"a.0": {"$elemMatch": {"b": {"$gt": 20}}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 0 assert monty_c.count() == mongo_c.count() def test_qop_elemMatch_4(monty_find, mongo_find): docs = [ {"a": [{"b": 1}, {"b": 2}]}, {"a": [{"b": 3}, {"b": 4}]}, ] spec = {"a.0.b": {"$elemMatch": {"$eq": 1}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 0 assert monty_c.count() == mongo_c.count() def test_qop_elemMatch_5(monty_find, mongo_find): docs = [ {"a": [{"b": [1]}, {"b": 2}]}, {"a": [{"b": 3}, {"b": 4}]}, ] spec = {"a.0.b": {"$elemMatch": {"$eq": 1}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_6(monty_find, mongo_find): docs = [ {"a": [75, 82]}, {"a": [75, 88]}, ] spec = {"a": {"$elemMatch": {"$gte": 80, "$lt": 85}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_7(monty_find, mongo_find): docs = [ {"a": [{"b": "x", "c": 9}, {"b": "z", "c": 8}]}, {"a": [{"b": "x", "c": 8}, {"b": "z", "c": 6}]}, ] spec = {"a": {"$elemMatch": {"b": "z", "c": {"$gte": 8}}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_8(monty_find, mongo_find): docs = [ {"a": [{"b": "x", "c": 9}, {"b": "z", "c": 8}]}, {"a": [{"b": "x", "c": 8}, {"b": "z", "c": 6}]}, {"a": [{"b": "y", "c": 8}, {"b": "z", "c": 7}]}, ] spec = {"a": {"$elemMatch": {"$or": [{"b": "x"}, {"c": 6}]}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 2 assert monty_c.count() == mongo_c.count() for i in range(2): assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_9(monty_find, mongo_find): docs = [ {"a": [[[1, 2], True], [[1, 2], True]]}, {"a": [[[1, 0], True], [[1, 3], False]]}, ] spec = {"a": {"$elemMatch": {"$or": [{"0": [1, 0]}, {"1": False}]}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_10(monty_find, mongo_find): docs = [ {"a": [[[1, 2], True], [[1, 2], True], {"0": [1, 0], "1": False}]}, {"a": [[[1, 2], True], [[1, 2], True], {"0": [1, 0]}]}, {"a": [[[1, 0], True], [[1, 3], False]]}, ] spec = {"a": {"$elemMatch": {"$or": [{"0": [1, 0]}, {"1": False}]}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 3 assert monty_c.count() == mongo_c.count() for i in range(3): assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_11(monty_find, mongo_find): docs = [ {"a": [{"b": [10, 11]}, {"b": 2}]}, # won't get picked {"a": [[{"b": [10, 11]}], {"b": 2}]}, {"a": [[{"b": [20, 21]}], {"b": 4}]}, ] spec = {"a.0": {"$elemMatch": {"$and": [{"b": [10, 11]}]}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_12(monty_find, mongo_find): docs = [ {"a": [[{"b": [10, 11]}]]}, {"a": [[{"b": [20, 21]}]]}, ] spec = {"a.0.b": {"$elemMatch": {"$and": [{"0": 10}]}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 0 assert monty_c.count() == mongo_c.count() def test_qop_elemMatch_13(monty_find, mongo_find): docs = [ {"a": [[{"b": [[10], 11]}]]}, {"a": [[{"b": [[20], 21]}]]}, ] spec = {"a.0.b": {"$elemMatch": {"$and": [{"0": 10}]}}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert mongo_c.count() == 1 assert monty_c.count() == mongo_c.count() assert next(mongo_c) == next(monty_c) def test_qop_elemMatch_14(monty_find, mongo_find): docs = [ {"a": [3, 2, 1]} ] spec = {"a": {"$elemMatch": True}} # $elemMatch needs an Object monty_c = monty_find(docs, spec) with pytest.raises(OperationFailure): next(monty_c)

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Python

comingsoon/views.py

epool/giftxme

22bedb03772fcfcb71762863d40c96b113e2ac32

[ "Apache-2.0" ]

1

2017-09-22T03:03:41.000Z

comingsoon/views.py

epool/giftxme

22bedb03772fcfcb71762863d40c96b113e2ac32

[ "Apache-2.0" ]

null

comingsoon/views.py

epool/giftxme

22bedb03772fcfcb71762863d40c96b113e2ac32

[ "Apache-2.0" ]

null

# Create your views here. from django.shortcuts import render def index(request): return render(request, 'comingsoon/index.html')

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py

Python

pydscpack/__init__.py

aligirayhanozbay/pydscpack

48d1df0775e4b063cf387b3884b8b463b3660e89

[ "BSD-3-Clause" ]

null

pydscpack/__init__.py

aligirayhanozbay/pydscpack

48d1df0775e4b063cf387b3884b8b463b3660e89

[ "BSD-3-Clause" ]

null

pydscpack/__init__.py

aligirayhanozbay/pydscpack

48d1df0775e4b063cf387b3884b8b463b3660e89

[ "BSD-3-Clause" ]

null

from .AnnulusMap import AnnulusMap

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py

Python

tests/layer_tests/onnx_tests/test_squeeze.py

ryanloney/openvino-1

4e0a740eb3ee31062ba0df88fcf438564f67edb7

[ "Apache-2.0" ]

1,127

2018-10-15T14:36:58.000Z

2020-04-20T09:29:44.000Z

tests/layer_tests/onnx_tests/test_squeeze.py

ryanloney/openvino-1

4e0a740eb3ee31062ba0df88fcf438564f67edb7

[ "Apache-2.0" ]

439

2018-10-20T04:40:35.000Z

2020-04-19T05:56:25.000Z

tests/layer_tests/onnx_tests/test_squeeze.py

ryanloney/openvino-1

4e0a740eb3ee31062ba0df88fcf438564f67edb7

[ "Apache-2.0" ]

414

2018-10-17T05:53:46.000Z

2020-04-16T17:29:53.000Z

# Copyright (C) 2018-2022 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import pytest from common.onnx_layer_test_class import Caffe2OnnxLayerTest class TestSqueeze(Caffe2OnnxLayerTest): def create_squeeze_net(self, axes, input_shape, output_shape, ir_version): """ ONNX net IR net Input->Squeeze(axes=0)->Output => Input->Reshape """ # # Create ONNX model # import onnx from onnx import helper from onnx import TensorProto input = helper.make_tensor_value_info('input', TensorProto.FLOAT, input_shape) output = helper.make_tensor_value_info('output', TensorProto.FLOAT, output_shape) node_squeeze_def = onnx.helper.make_node( 'Squeeze', inputs=['input'], outputs=['output'], axes=axes ) # Create the graph (GraphProto) graph_def = helper.make_graph( [node_squeeze_def], 'test_squeeze_model', [input], [output], ) # Create the model (ModelProto) onnx_net = helper.make_model(graph_def, producer_name='test_squeeze_model') # # Create reference IR net # Please, specify 'type': 'Input' for input node # Moreover, do not forget to validate ALL layer attributes!!! # ref_net = None return onnx_net, ref_net def create_squeeze_net_const(self, axes, input_shape, output_shape, ir_version): """ ONNX net IR net Input->Concat(+squeezed const)->Output => Input->Concat(+const) """ # # Create ONNX model # import onnx from onnx import helper from onnx import TensorProto import numpy as np concat_axis = 0 concat_output_shape = output_shape.copy() concat_output_shape[concat_axis] *= 2 input = helper.make_tensor_value_info('input', TensorProto.FLOAT, output_shape) output = helper.make_tensor_value_info('output', TensorProto.FLOAT, concat_output_shape) const_number = np.prod(input_shape) constant = np.random.randint(-127, 127, const_number).astype(np.float) constant = np.reshape(constant, input_shape) node_const_def = onnx.helper.make_node( 'Constant', inputs=[], outputs=['const1'], value=helper.make_tensor( name='const_tensor', data_type=TensorProto.FLOAT, dims=constant.shape, vals=constant.flatten(), ), ) node_squeeze_def = onnx.helper.make_node( 'Squeeze', inputs=['const1'], outputs=['squeeze1'], axes=axes ) node_concat_def = onnx.helper.make_node( 'Concat', inputs=['input', 'squeeze1'], outputs=['output'], axis=concat_axis ) # Create the graph (GraphProto) graph_def = helper.make_graph( [node_const_def, node_squeeze_def, node_concat_def], 'test_squeeze_model', [input], [output], ) # Create the model (ModelProto) onnx_net = helper.make_model(graph_def, producer_name='test_squeeze_model') # # Create reference IR net # Please, specify 'type': 'Input' for input node # Moreover, do not forget to validate ALL layer attributes!!! # ref_net = None return onnx_net, ref_net test_data_5D = [ dict(axes=[0], input_shape=[1, 2, 3, 10, 10], output_shape=[2, 3, 10, 10]), dict(axes=[1], input_shape=[2, 1, 3, 10, 10], output_shape=[2, 3, 10, 10]), dict(axes=[2], input_shape=[2, 3, 1, 10, 10], output_shape=[2, 3, 10, 10]), dict(axes=[3], input_shape=[2, 3, 10, 1, 10], output_shape=[2, 3, 10, 10]), dict(axes=[4], input_shape=[2, 3, 10, 10, 1], output_shape=[2, 3, 10, 10]), dict(axes=[0, 1], input_shape=[1, 1, 3, 10, 10], output_shape=[3, 10, 10]), dict(axes=[0, 2], input_shape=[1, 3, 1, 10, 10], output_shape=[3, 10, 10]), dict(axes=[0, 3], input_shape=[1, 3, 10, 1, 10], output_shape=[3, 10, 10]), dict(axes=[0, 4], input_shape=[1, 3, 10, 10, 1], output_shape=[3, 10, 10]), dict(axes=[1, 2], input_shape=[3, 1, 1, 10, 10], output_shape=[3, 10, 10]), dict(axes=[1, 3], input_shape=[3, 1, 10, 1, 10], output_shape=[3, 10, 10]), dict(axes=[1, 4], input_shape=[3, 1, 10, 10, 1], output_shape=[3, 10, 10]), dict(axes=[2, 3], input_shape=[3, 10, 1, 1, 10], output_shape=[3, 10, 10]), dict(axes=[2, 4], input_shape=[3, 10, 1, 10, 1], output_shape=[3, 10, 10]), dict(axes=[3, 4], input_shape=[3, 10, 10, 1, 1], output_shape=[3, 10, 10]), dict(axes=[0, 1, 2], input_shape=[1, 1, 1, 10, 10], output_shape=[10, 10]), dict(axes=[0, 1, 3], input_shape=[1, 1, 10, 1, 10], output_shape=[10, 10]), dict(axes=[0, 1, 4], input_shape=[1, 1, 10, 10, 1], output_shape=[10, 10]), dict(axes=[0, 2, 3], input_shape=[1, 10, 1, 1, 10], output_shape=[10, 10]), dict(axes=[0, 2, 4], input_shape=[1, 10, 1, 10, 1], output_shape=[10, 10]), dict(axes=[0, 3, 4], input_shape=[1, 10, 10, 1, 1], output_shape=[10, 10]), dict(axes=[1, 2, 3], input_shape=[10, 1, 1, 1, 10], output_shape=[10, 10]), dict(axes=[1, 2, 4], input_shape=[10, 1, 1, 10, 1], output_shape=[10, 10]), dict(axes=[1, 3, 4], input_shape=[10, 1, 10, 1, 1], output_shape=[10, 10]), dict(axes=[2, 3, 4], input_shape=[10, 10, 1, 1, 1], output_shape=[10, 10])] test_data_4D = [ dict(axes=[0], input_shape=[1, 3, 10, 10], output_shape=[3, 10, 10]), dict(axes=[1], input_shape=[3, 1, 10, 10], output_shape=[3, 10, 10]), dict(axes=[2], input_shape=[3, 10, 1, 10], output_shape=[3, 10, 10]), dict(axes=[3], input_shape=[3, 10, 10, 1], output_shape=[3, 10, 10]), dict(axes=[0, 1], input_shape=[1, 1, 10, 10], output_shape=[10, 10]), dict(axes=[0, 2], input_shape=[1, 10, 1, 10], output_shape=[10, 10]), dict(axes=[0, 3], input_shape=[1, 10, 10, 1], output_shape=[10, 10]), dict(axes=[1, 2], input_shape=[10, 1, 1, 10], output_shape=[10, 10]), dict(axes=[1, 3], input_shape=[10, 1, 10, 1], output_shape=[10, 10]), dict(axes=[2, 3], input_shape=[10, 10, 1, 1], output_shape=[10, 10])] test_data_3D = [ dict(axes=[0], input_shape=[1, 10, 10], output_shape=[10, 10]), dict(axes=[1], input_shape=[10, 1, 10], output_shape=[10, 10]), dict(axes=[2], input_shape=[10, 10, 1], output_shape=[10, 10])] @pytest.mark.parametrize("params", test_data_5D) @pytest.mark.nightly def test_squeeze_5D(self, params, ie_device, precision, ir_version, temp_dir, api_2): self._test(*self.create_squeeze_net(**params, ir_version=ir_version), ie_device, precision, ir_version, temp_dir=temp_dir, api_2=api_2) @pytest.mark.parametrize("params", test_data_4D) @pytest.mark.nightly def test_squeeze_4D(self, params, ie_device, precision, ir_version, temp_dir, api_2): self._test(*self.create_squeeze_net(**params, ir_version=ir_version), ie_device, precision, ir_version, temp_dir=temp_dir, api_2=api_2) @pytest.mark.parametrize("params", test_data_3D) @pytest.mark.nightly def test_squeeze_3D(self, params, ie_device, precision, ir_version, temp_dir, api_2): self._test(*self.create_squeeze_net(**params, ir_version=ir_version), ie_device, precision, ir_version, temp_dir=temp_dir, api_2=api_2) @pytest.mark.parametrize("params", test_data_5D) @pytest.mark.nightly def test_squeeze_const_5D(self, params, ie_device, precision, ir_version, temp_dir, api_2): self._test(*self.create_squeeze_net_const(**params, ir_version=ir_version), ie_device, precision, ir_version, temp_dir=temp_dir, api_2=api_2) @pytest.mark.parametrize("params", test_data_4D) @pytest.mark.nightly def test_squeeze_const_4D(self, params, ie_device, precision, ir_version, temp_dir, api_2): self._test(*self.create_squeeze_net_const(**params, ir_version=ir_version), ie_device, precision, ir_version, temp_dir=temp_dir, api_2=api_2) @pytest.mark.parametrize("params", test_data_3D) @pytest.mark.nightly def test_squeeze_const_3D(self, params, ie_device, precision, ir_version, temp_dir, api_2): self._test(*self.create_squeeze_net_const(**params, ir_version=ir_version), ie_device, precision, ir_version, temp_dir=temp_dir, api_2=api_2)

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Python

__init__.py

afernandezrti/rticonnextdds-connector-py

56cf102ccbf7ba9e01e56fce55439bef84e888b7

[ "CNRI-Python" ]

24

2019-04-22T15:40:19.000Z

2022-01-17T06:39:38.000Z

__init__.py

afernandezrti/rticonnextdds-connector-py

56cf102ccbf7ba9e01e56fce55439bef84e888b7

[ "CNRI-Python" ]

46

2019-04-04T14:59:45.000Z

2022-03-22T06:57:37.000Z

__init__.py

afernandezrti/rticonnextdds-connector-py

56cf102ccbf7ba9e01e56fce55439bef84e888b7

[ "CNRI-Python" ]

17

2018-10-03T20:42:36.000Z

2022-01-06T02:36:32.000Z

from .rticonnextdds_connector import *

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Python

tests/api/v3_1_0/test_hotspot_portal.py

CiscoISE/ciscoisesdk

860b0fc7cc15d0c2a39c64608195a7ab3d5f4885

[ "MIT" ]

36

2021-05-18T16:24:19.000Z

2022-03-05T13:44:41.000Z

tests/api/v3_1_0/test_hotspot_portal.py

CiscoISE/ciscoisesdk

860b0fc7cc15d0c2a39c64608195a7ab3d5f4885

[ "MIT" ]

15

2021-06-08T19:03:37.000Z

2022-02-25T14:47:33.000Z

tests/api/v3_1_0/test_hotspot_portal.py

CiscoISE/ciscoisesdk

860b0fc7cc15d0c2a39c64608195a7ab3d5f4885

[ "MIT" ]

6

2021-06-10T09:32:01.000Z

2022-01-12T08:34:39.000Z

# -*- coding: utf-8 -*- """IdentityServicesEngineAPI hotspot_portal API fixtures and tests. Copyright (c) 2021 Cisco and/or its affiliates. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import pytest from fastjsonschema.exceptions import JsonSchemaException from ciscoisesdk.exceptions import MalformedRequest from ciscoisesdk.exceptions import ciscoisesdkException from tests.environment import IDENTITY_SERVICES_ENGINE_VERSION pytestmark = pytest.mark.skipif(IDENTITY_SERVICES_ENGINE_VERSION != '3.1.0', reason='version does not match') def is_valid_get_hotspot_portal_by_id(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_6cbcecf65a0155fcad602d3ac16531a7_v3_1_0').validate(obj.response) return True def get_hotspot_portal_by_id(api): endpoint_result = api.hotspot_portal.get_hotspot_portal_by_id( id='string' ) return endpoint_result @pytest.mark.hotspot_portal def test_get_hotspot_portal_by_id(api, validator): try: assert is_valid_get_hotspot_portal_by_id( validator, get_hotspot_portal_by_id(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print("ERROR: {error}".format(error=original_e)) raise original_e def get_hotspot_portal_by_id_default(api): endpoint_result = api.hotspot_portal.get_hotspot_portal_by_id( id='string' ) return endpoint_result @pytest.mark.hotspot_portal def test_get_hotspot_portal_by_id_default(api, validator): try: assert is_valid_get_hotspot_portal_by_id( validator, get_hotspot_portal_by_id_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_update_hotspot_portal_by_id(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_0ae4af25df565334b20a24c4878b68e4_v3_1_0').validate(obj.response) return True def update_hotspot_portal_by_id(api): endpoint_result = api.hotspot_portal.update_hotspot_portal_by_id( active_validation=False, customizations={'portalTheme': {'id': 'string', 'name': 'string', 'themeData': 'string'}, 'portalTweakSettings': {'bannerColor': 'string', 'bannerTextColor': 'string', 'pageBackgroundColor': 'string', 'pageLabelAndTextColor': 'string'}, 'language': {'viewLanguage': 'string'}, 'globalCustomizations': {'mobileLogoImage': {'data': 'string'}, 'desktopLogoImage': {'data': 'string'}, 'backgroundImage': {'data': 'string'}, 'bannerImage': {'data': 'string'}, 'bannerTitle': 'string', 'contactText': 'string', 'footerElement': 'string'}, 'pageCustomizations': {'data': [{'key': 'string', 'value': 'string'}]}}, description='string', id='string', name='string', payload=None, portal_test_url='string', portal_type='string', settings={'portalSettings': {'httpsPort': 0, 'allowedInterfaces': ['string'], 'certificateGroupTag': 'string', 'endpointIdentityGroup': 'string', 'coaType': 'string', 'displayLang': 'string', 'fallbackLanguage': 'string', 'alwaysUsedLanguage': 'string'}, 'aupSettings': {'requireAccessCode': True, 'accessCode': 'string', 'includeAup': True, 'requireScrolling': True}, 'postAccessBannerSettings': {'includePostAccessBanner': True}, 'authSuccessSettings': {'successRedirect': 'string', 'redirectUrl': 'string'}, 'postLoginBannerSettings': {'includePostAccessBanner': True}, 'supportInfoSettings': {'includeSupportInfoPage': True, 'includeMacAddr': True, 'includeIpAddress': True, 'includeBrowserUserAgent': True, 'includePolicyServer': True, 'includeFailureCode': True, 'emptyFieldDisplay': 'string', 'defaultEmptyFieldValue': 'string'}} ) return endpoint_result @pytest.mark.hotspot_portal def test_update_hotspot_portal_by_id(api, validator): try: assert is_valid_update_hotspot_portal_by_id( validator, update_hotspot_portal_by_id(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print("ERROR: {error}".format(error=original_e)) raise original_e def update_hotspot_portal_by_id_default(api): endpoint_result = api.hotspot_portal.update_hotspot_portal_by_id( active_validation=False, id='string', customizations=None, description=None, name=None, payload=None, portal_test_url=None, portal_type=None, settings=None ) return endpoint_result @pytest.mark.hotspot_portal def test_update_hotspot_portal_by_id_default(api, validator): try: assert is_valid_update_hotspot_portal_by_id( validator, update_hotspot_portal_by_id_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_delete_hotspot_portal_by_id(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_1a344d1c6f535789b7badbaa502e8d3b_v3_1_0').validate(obj.response) return True def delete_hotspot_portal_by_id(api): endpoint_result = api.hotspot_portal.delete_hotspot_portal_by_id( id='string' ) return endpoint_result @pytest.mark.hotspot_portal def test_delete_hotspot_portal_by_id(api, validator): try: assert is_valid_delete_hotspot_portal_by_id( validator, delete_hotspot_portal_by_id(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print("ERROR: {error}".format(error=original_e)) raise original_e def delete_hotspot_portal_by_id_default(api): endpoint_result = api.hotspot_portal.delete_hotspot_portal_by_id( id='string' ) return endpoint_result @pytest.mark.hotspot_portal def test_delete_hotspot_portal_by_id_default(api, validator): try: assert is_valid_delete_hotspot_portal_by_id( validator, delete_hotspot_portal_by_id_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_get_hotspot_portal(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_d912b1c21e2b5dca8b56332d3a8ad13d_v3_1_0').validate(obj.response) return True def get_hotspot_portal(api): endpoint_result = api.hotspot_portal.get_hotspot_portal( filter='value1,value2', filter_type='string', page=0, size=0, sortasc='string', sortdsc='string' ) return endpoint_result @pytest.mark.hotspot_portal def test_get_hotspot_portal(api, validator): try: assert is_valid_get_hotspot_portal( validator, get_hotspot_portal(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print("ERROR: {error}".format(error=original_e)) raise original_e def get_hotspot_portal_default(api): endpoint_result = api.hotspot_portal.get_hotspot_portal( filter=None, filter_type=None, page=None, size=None, sortasc=None, sortdsc=None ) return endpoint_result @pytest.mark.hotspot_portal def test_get_hotspot_portal_default(api, validator): try: assert is_valid_get_hotspot_portal( validator, get_hotspot_portal_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_create_hotspot_portal(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_0df78c9a3f72584dbd1c7b667b0e312f_v3_1_0').validate(obj.response) return True def create_hotspot_portal(api): endpoint_result = api.hotspot_portal.create_hotspot_portal( active_validation=False, customizations={'portalTheme': {'id': 'string', 'name': 'string', 'themeData': 'string'}, 'portalTweakSettings': {'bannerColor': 'string', 'bannerTextColor': 'string', 'pageBackgroundColor': 'string', 'pageLabelAndTextColor': 'string'}, 'language': {'viewLanguage': 'string'}, 'globalCustomizations': {'mobileLogoImage': {'data': 'string'}, 'desktopLogoImage': {'data': 'string'}, 'backgroundImage': {'data': 'string'}, 'bannerImage': {'data': 'string'}, 'bannerTitle': 'string', 'contactText': 'string', 'footerElement': 'string'}, 'pageCustomizations': {'data': [{'key': 'string', 'value': 'string'}]}}, description='string', name='string', payload=None, portal_test_url='string', portal_type='string', settings={'portalSettings': {'httpsPort': 0, 'allowedInterfaces': ['string'], 'certificateGroupTag': 'string', 'endpointIdentityGroup': 'string', 'coaType': 'string', 'displayLang': 'string', 'fallbackLanguage': 'string', 'alwaysUsedLanguage': 'string'}, 'aupSettings': {'requireAccessCode': True, 'accessCode': 'string', 'includeAup': True, 'requireScrolling': True}, 'postAccessBannerSettings': {'includePostAccessBanner': True}, 'authSuccessSettings': {'successRedirect': 'string', 'redirectUrl': 'string'}, 'postLoginBannerSettings': {'includePostAccessBanner': True}, 'supportInfoSettings': {'includeSupportInfoPage': True, 'includeMacAddr': True, 'includeIpAddress': True, 'includeBrowserUserAgent': True, 'includePolicyServer': True, 'includeFailureCode': True, 'emptyFieldDisplay': 'string', 'defaultEmptyFieldValue': 'string'}} ) return endpoint_result @pytest.mark.hotspot_portal def test_create_hotspot_portal(api, validator): try: assert is_valid_create_hotspot_portal( validator, create_hotspot_portal(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print("ERROR: {error}".format(error=original_e)) raise original_e def create_hotspot_portal_default(api): endpoint_result = api.hotspot_portal.create_hotspot_portal( active_validation=False, customizations=None, description=None, name=None, payload=None, portal_test_url=None, portal_type=None, settings=None ) return endpoint_result @pytest.mark.hotspot_portal def test_create_hotspot_portal_default(api, validator): try: assert is_valid_create_hotspot_portal( validator, create_hotspot_portal_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e def is_valid_get_version(json_schema_validate, obj): if not obj: return False assert hasattr(obj, 'headers') assert hasattr(obj, 'content') assert hasattr(obj, 'text') assert hasattr(obj, 'response') json_schema_validate('jsd_91257d81be4f5a0486cc085499c19b1c_v3_1_0').validate(obj.response) return True def get_version(api): endpoint_result = api.hotspot_portal.get_version( ) return endpoint_result @pytest.mark.hotspot_portal def test_get_version(api, validator): try: assert is_valid_get_version( validator, get_version(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest)): print("ERROR: {error}".format(error=original_e)) raise original_e def get_version_default(api): endpoint_result = api.hotspot_portal.get_version( ) return endpoint_result @pytest.mark.hotspot_portal def test_get_version_default(api, validator): try: assert is_valid_get_version( validator, get_version_default(api) ) except Exception as original_e: with pytest.raises((JsonSchemaException, MalformedRequest, TypeError)): raise original_e

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9620a38834ef8e8605baf91690ea5302de6f3247

21,005

py

Python

comport/department/views.py

isabella232/comport

117123862415261095a917ed7f2037c1f986b474

[ "BSD-3-Clause" ]

35

2015-11-14T18:32:45.000Z

2022-01-23T15:15:05.000Z

comport/department/views.py

codeforamerica/comport

117123862415261095a917ed7f2037c1f986b474

[ "BSD-3-Clause" ]

119

2015-11-20T22:45:34.000Z

2022-02-10T23:02:36.000Z

comport/department/views.py

isabella232/comport

117123862415261095a917ed7f2037c1f986b474

[ "BSD-3-Clause" ]

19

2015-11-20T20:41:52.000Z

2022-01-26T04:12:34.000Z

# -*- coding: utf-8 -*- from flask import Blueprint, render_template, request, redirect, url_for, flash, Response, abort from .models import Department, Extractor from comport.data.models import DemographicValue, DenominatorValue from flask.ext.login import login_required from comport.decorators import admin_or_department_required, authorized_access_only import uuid import datetime blueprint = Blueprint("department", __name__, url_prefix='/department', static_folder="../static") # <<<<<<<< ADMIN ENDPOINTS >>>>>>>>>> @blueprint.route("/<int:department_id>") @login_required @admin_or_department_required() def department_dashboard(department_id): department = Department.get_by_id(department_id) if not department: abort(404) current_date = datetime.datetime.now() return render_template("department/dashboard.html", department=department, current_month=current_date.month, current_year=current_date.year) @blueprint.route("/<int:department_id>/activate", methods=['POST']) @login_required @admin_or_department_required() def activate_extractor(department_id): department = Department.get_by_id(department_id) if not department: abort(404) if request.method == 'POST': if request.form['submit'] == 'Activate': password = str(uuid.uuid4()) extractor, envs = Extractor.from_department_and_password(department=department, password=password) return render_template("department/extractorEnvs.html", department=department, envs=envs) @blueprint.route("/<int:department_id>/start", methods=['POST']) @login_required @admin_or_department_required() def start_extractor(department_id): department = Department.get_by_id(department_id) if not department: abort(404) if request.method == 'POST': if request.form['submit'] == 'Set': extractor = department.get_extractor() extractor.next_year = request.form["year"] extractor.next_month = request.form["month"] extractor.save() flash("Extractor start date set to {}/{}".format(extractor.next_month, extractor.next_year), "info") return redirect(url_for('department.department_dashboard', department_id=department.id)) # <<<<<<<< EDIT ENDPOINTS >>>>>>>>>> @blueprint.route("/<int:department_id>/edit/ois") @login_required @admin_or_department_required() def edit_ois(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/ois.html", department=department, chart_blocks=department.get_ois_blocks(), editing=True) @blueprint.route("/<int:department_id>/edit/useofforce") @login_required @admin_or_department_required() def edit_use_of_force(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/useofforce.html", department=department, chart_blocks=department.get_uof_blocks(), editing=True) @blueprint.route("/<int:department_id>/edit/complaints") @login_required @admin_or_department_required() def edit_complaints(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/complaints.html", department=department, chart_blocks=department.get_complaint_blocks(), editing=True) @blueprint.route("/<int:department_id>/edit/pursuits") @login_required @admin_or_department_required() def edit_pursuits(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/pursuits.html", department=department, chart_blocks=department.get_pursuits_blocks(), editing=True) @blueprint.route("/<int:department_id>/edit/assaultsonofficers") @login_required @admin_or_department_required() def edit_assaultsonofficers(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/assaults.html", department=department, chart_blocks=department.get_assaults_blocks(), editing=True) @blueprint.route("/<int:department_id>/edit/demographics") @login_required @admin_or_department_required() def edit_demographics(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template( "department/demographics.html", department=department, department_values=department.get_raw_department_demographics(), city_values=department.get_raw_city_demographics()) @blueprint.route("/<int:department_id>/demographicValue/create", methods=["POST"]) @login_required @admin_or_department_required() def new_demographic_row(department_id): department = Department.get_by_id(department_id) if not department: abort(404) DemographicValue.create( department_id=department_id, race=request.form["race"], count=int(request.form["count"]), department_value=request.form["department_or_city"] == "department") return redirect(url_for( 'department.edit_demographics', department_id=department_id )) @blueprint.route("/<int:department_id>/demographicValue/<int:value_id>/delete", methods=["POST"]) @login_required @admin_or_department_required() def delete_demographic_row(department_id, value_id): department = Department.get_by_id(department_id) value = DemographicValue.get_by_id(value_id) if not department or not value: abort(404) value.delete() return redirect(url_for( 'department.edit_demographics', department_id=department_id )) @blueprint.route("/<int:department_id>/edit/denominators") @login_required @admin_or_department_required() def edit_denominators(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template( "department/denominators.html", department=department, denominator_values=department.denominator_values ) @blueprint.route("/<int:department_id>/denominatorValue/create", methods=["POST"]) @login_required @admin_or_department_required() def new_denominator_row(department_id): department = Department.get_by_id(department_id) if not department: abort(404) DenominatorValue.create( department_id=department_id, month=int(request.form["month"]), year=int(request.form["year"]), officers_out_on_service=int(request.form["officersOutOnService"]) ) return redirect(url_for( 'department.edit_denominators', department_id=department_id )) @blueprint.route("/<int:department_id>/denominatorValue/<int:value_id>/delete", methods=["POST"]) @login_required @admin_or_department_required() def delete_denominator_row(department_id, value_id): department = Department.get_by_id(department_id) value = DenominatorValue.get_by_id(value_id) if not department or not value: abort(404) value.delete() return redirect(url_for( 'department.edit_denominators', department_id=department_id )) @blueprint.route("/<int:department_id>/edit/index", methods=["GET", "POST"]) @login_required @admin_or_department_required() def edit_index(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/index.html", department=department, chart_blocks=department.get_introduction_blocks(), editing=True) # <<<<<<<< PREVIEW ENDPOINTS >>>>>>>>>> @blueprint.route("/<int:department_id>/preview/ois") @login_required @admin_or_department_required() def preview_ois(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/ois.html", department=department, chart_blocks=department.get_ois_blocks(), editing=False) @blueprint.route("/<int:department_id>/preview/useofforce") @login_required @admin_or_department_required() def preview_use_of_force(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/useofforce.html", department=department, chart_blocks=department.get_uof_blocks(), editing=False) @blueprint.route("/<int:department_id>/preview/complaints") @login_required @admin_or_department_required() def preview_complaints(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/complaints.html", department=department, chart_blocks=department.get_complaint_blocks(), editing=False) @blueprint.route("/<int:department_id>/preview/pursuits") @login_required @admin_or_department_required() def preview_pursuits(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/pursuits.html", department=department, chart_blocks=department.get_pursuits_blocks(), editing=False) @blueprint.route("/<int:department_id>/preview/assaultsonofficers") @login_required @admin_or_department_required() def preview_assaults(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/assaults.html", department=department, chart_blocks=department.get_assaults_blocks(), editing=False) @blueprint.route("/<int:department_id>/preview/index") @login_required @admin_or_department_required() def preview_index(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/index.html", chart_blocks=department.get_introduction_blocks(), department=department, editing=False) # <<<<<<<< SCHEMA ENDPOINTS >>>>>>>>>> @blueprint.route('/<int:department_id>/preview/schema/complaints') @login_required @admin_or_department_required() def complaints_schema_preview(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/complaints.html", department=department, chart_blocks=department.get_complaint_schema_blocks(), editing=False) @blueprint.route('/<int:department_id>/edit/schema/complaints') @login_required @admin_or_department_required() def complaints_schema_edit(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/complaints.html", department=department, chart_blocks=department.get_complaint_schema_blocks(), editing=True) @blueprint.route('/<int:department_id>/preview/schema/useofforce') @login_required @admin_or_department_required() def useofforce_schema_preview(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/useofforce.html", department=department, chart_blocks=department.get_uof_schema_blocks(), editing=False) @blueprint.route('/<int:department_id>/edit/schema/useofforce') @login_required @admin_or_department_required() def useofforce_schema_edit(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/useofforce.html", department=department, chart_blocks=department.get_uof_schema_blocks(), editing=True) @blueprint.route('/<int:department_id>/edit/schema/ois') @login_required @admin_or_department_required() def ois_schema_edit(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/ois.html", department=department, chart_blocks=department.get_ois_schema_blocks(), editing=True) @blueprint.route('/<int:department_id>/preview/schema/ois') @login_required @admin_or_department_required() def ois_schema_preview(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/ois.html", department=department, chart_blocks=department.get_ois_schema_blocks(), editing=False) @blueprint.route('/<int:department_id>/preview/schema/pursuits') @login_required @admin_or_department_required() def pursuits_schema_preview(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/pursuits.html", department=department, chart_blocks=department.get_pursuits_schema_blocks(), editing=False) @blueprint.route('/<int:department_id>/edit/schema/pursuits') @login_required @admin_or_department_required() def pursuits_schema_edit(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/pursuits.html", department=department, chart_blocks=department.get_pursuits_schema_blocks(), editing=True) @blueprint.route('/<int:department_id>/preview/schema/assaultsonofficers') @login_required @admin_or_department_required() def assaults_schema_preview(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/assaults.html", department=department, chart_blocks=department.get_assaults_schema_blocks(), editing=False) @blueprint.route('/<int:department_id>/edit/schema/assaultsonofficers') @login_required @admin_or_department_required() def assaults_schema_edit(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return render_template("department/site/schema/assaults.html", department=department, chart_blocks=department.get_assaults_schema_blocks(), editing=True) # <<<<<<<< DATA ENDPOINTS >>>>>>>>>> @blueprint.route('/<int:department_id>/uof.csv') @authorized_access_only(dataset="use_of_force_incidents") def use_of_force_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_uof_csv(), mimetype="text/csv") @blueprint.route('/<int:department_id>/complaints.csv') @authorized_access_only(dataset="citizen_complaints") def complaints_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_complaint_csv(), mimetype="text/csv") @blueprint.route('/<int:department_id>/pursuits.csv') @authorized_access_only(dataset="pursuits") def pursuits_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_pursuits_csv(), mimetype="text/csv") @blueprint.route('/<int:department_id>/assaultsonofficers.csv') @authorized_access_only(dataset="assaults_on_officers") def assaults_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_assaults_csv(), mimetype="text/csv") @blueprint.route('/<int:department_id>/ois.csv') @authorized_access_only(dataset="officer_involved_shootings") def ois_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_ois_csv(), mimetype="text/csv") @blueprint.route('/<int:department_id>/officerCalls.csv') @authorized_access_only() def denominator_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_denominator_csv(), mimetype="text/csv") @blueprint.route('/<int:department_id>/demographics.csv') @authorized_access_only() def demographics_csv(department_id): department = Department.get_by_id(department_id) if not department: abort(404) return Response(department.get_demographic_csv(), mimetype="text/csv") # <<<<<<<< PUBLIC ENDPOINTS >>>>>>>>>> @blueprint.route("/<short_name>/") @authorized_access_only() def public_intro(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/index.html", chart_blocks=department.get_introduction_blocks(), department=department, editing=False, published=True) @blueprint.route("/<short_name>/complaints/") @authorized_access_only(dataset="citizen_complaints") def public_complaints(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/complaints.html", department=department, chart_blocks=department.get_complaint_blocks(), editing=False, published=True) @blueprint.route('/<short_name>/schema/complaints/') @authorized_access_only(dataset="citizen_complaints") def public_complaints_schema(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/schema/complaints.html", department=department, chart_blocks=department.get_complaint_schema_blocks(), published=True) @blueprint.route("/<short_name>/pursuits/") @authorized_access_only(dataset="pursuits") def public_pursuits(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/pursuits.html", department=department, chart_blocks=department.get_pursuits_blocks(), editing=False, published=True) @blueprint.route('/<short_name>/schema/pursuits/') @authorized_access_only(dataset="pursuits") def public_pursuits_schema(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/schema/pursuits.html", department=department, chart_blocks=department.get_pursuits_schema_blocks(), published=True) @blueprint.route("/<short_name>/assaultsonofficers/") @authorized_access_only(dataset="assaults_on_officers") def public_assaults(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/assaults.html", department=department, chart_blocks=department.get_assaults_blocks(), editing=False, published=True) @blueprint.route('/<short_name>/schema/assaultsonofficers/') @authorized_access_only(dataset="assaults_on_officers") def public_assaults_schema(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/schema/assaults.html", department=department, chart_blocks=department.get_assaults_schema_blocks(), editing=False, published=True) @blueprint.route("/<short_name>/useofforce/") @authorized_access_only(dataset="use_of_force_incidents") def public_uof(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/useofforce.html", department=department, chart_blocks=department.get_uof_blocks(), editing=False, published=True) @blueprint.route('/<short_name>/schema/useofforce/') @authorized_access_only(dataset="use_of_force_incidents") def public_uof_schema(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/schema/useofforce.html", department=department, chart_blocks=department.get_uof_schema_blocks(), editing=False, published=True) @blueprint.route("/<short_name>/officerinvolvedshootings/") @authorized_access_only(dataset="officer_involved_shootings") def public_ois(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/ois.html", department=department, chart_blocks=department.get_ois_blocks(), editing=False, published=True) @blueprint.route('/<short_name>/schema/officerinvolvedshootings/') @authorized_access_only(dataset="officer_involved_shootings") def public_ois_schema(short_name): department = Department.query.filter_by(short_name=short_name.upper()).first() if not department: abort(404) return render_template("department/site/schema/ois.html", department=department, chart_blocks=department.get_ois_schema_blocks(), editing=False, published=True)

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0.047715

0.061023

0.881459

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0.765256

0.700792

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0.112402

21,005

498

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42.178715

0.818226

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0.119718

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null

0

1

0

null

0

6

829573989fd9375f501363497c29204dc8eccee7

4,359

py

Python

ngsutils/gtf/t/test_junctions.py

bgruening/ngsutils

417e90dc1918fb553dd84990f2c54bd8cea8f44d

[ "BSD-3-Clause" ]

57

2015-03-09T01:26:45.000Z

2022-02-22T07:26:01.000Z

ngsutils/gtf/t/test_junctions.py

bgruening/ngsutils

417e90dc1918fb553dd84990f2c54bd8cea8f44d

[ "BSD-3-Clause" ]

33

2015-02-03T23:24:46.000Z

2022-03-16T20:08:10.000Z

ngsutils/gtf/t/test_junctions.py

bgruening/ngsutils

417e90dc1918fb553dd84990f2c54bd8cea8f44d

[ "BSD-3-Clause" ]

33

2015-01-18T16:47:47.000Z

2022-02-22T07:28:09.000Z

#!/usr/bin/env python ''' Tests for gtfutils / junctions ''' import os import unittest import StringIO import ngsutils.gtf.junctions from ngsutils.gtf import GTF # >test1 # 1 2 3 4 5 6 7 8 9 100 # 1234567890123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890 # aaaaaaaaaCCCCCCCATGCtttttttttGCGCTTTGATCcccccccccCTGAGGGGGGGGGGGGGATCGgggggggggACTgggggggTCGAGGGGGGG # exons: # 10,20 # 30,40 # 50,70 # 90,100 # opt: 80-82 fa = os.path.join(os.path.dirname(__file__), 'test-junc.fa') class GTFJunctionsTest(unittest.TestCase): def testJunctionsSimple(self): gtf = GTF(fileobj=StringIO.StringIO('''\ test1|test|exon|10|20|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|30|40|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|50|70|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|90|100|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" '''.replace('|', '\t')), quiet=True) valid = '''\ >test1:16-20,29-33 ATGCGCGC >test1:16-20,49-53 ATGCCTGA >test1:16-20,89-93 ATGCTCGA >test1:36-40,49-53 GATCCTGA >test1:36-40,89-93 GATCTCGA >test1:66-70,89-93 ATCGTCGA ''' out = StringIO.StringIO('') ngsutils.gtf.junctions.gtf_junctions(gtf, fa, fragment_size=4, min_size=8, out=out, quiet=True) self.assertEqual(out.getvalue(), valid) def testJunctionsMultiExon(self): gtf = GTF(fileobj=StringIO.StringIO('''\ test1|test|exon|30|40|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|50|70|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|80|82|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|90|100|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" '''.replace('|', '\t')), quiet=True) valid = '''\ >test1:36-40,49-53 GATCCTGA >test1:36-40,79-82,89-93 GATCACTTCGA >test1:36-40,89-93 GATCTCGA >test1:66-70,79-82,89-93 ATCGACTTCGA >test1:66-70,89-93 ATCGTCGA ''' out = StringIO.StringIO('') ngsutils.gtf.junctions.gtf_junctions(gtf, fa, fragment_size=4, min_size=8, out=out, quiet=True) self.assertEqual(out.getvalue(), valid) def testJunctionsIsoforms(self): gtf = GTF(fileobj=StringIO.StringIO('''\ test1|test|exon|10|20|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|30|40|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|90|100|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|10|20|0|+|.|gene_id "foo1"; transcript_id "bar2"; isoform_id "iso1" test1|test|exon|50|70|0|+|.|gene_id "foo1"; transcript_id "bar2"; isoform_id "iso1" test1|test|exon|90|100|0|+|.|gene_id "foo1"; transcript_id "bar2"; isoform_id "iso1" '''.replace('|', '\t')), quiet=True) valid = '''\ >test1:16-20,29-33 ATGCGCGC >test1:16-20,49-53 ATGCCTGA >test1:16-20,89-93 ATGCTCGA >test1:36-40,49-53 GATCCTGA >test1:36-40,89-93 GATCTCGA >test1:66-70,89-93 ATCGTCGA ''' out = StringIO.StringIO('') ngsutils.gtf.junctions.gtf_junctions(gtf, fa, fragment_size=4, min_size=8, out=out, quiet=True) self.assertEqual(out.getvalue(), valid) def testJunctionsIsoformsKnown(self): gtf = GTF(fileobj=StringIO.StringIO('''\ test1|test|exon|10|20|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|30|40|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|90|100|0|+|.|gene_id "foo1"; transcript_id "bar1"; isoform_id "iso1" test1|test|exon|10|20|0|+|.|gene_id "foo1"; transcript_id "bar2"; isoform_id "iso1" test1|test|exon|50|70|0|+|.|gene_id "foo1"; transcript_id "bar2"; isoform_id "iso1" test1|test|exon|90|100|0|+|.|gene_id "foo1"; transcript_id "bar2"; isoform_id "iso1" '''.replace('|', '\t')), quiet=True) valid = '''\ >test1:16-20,29-33 ATGCGCGC >test1:36-40,89-93 GATCTCGA >test1:16-20,49-53 ATGCCTGA >test1:66-70,89-93 ATCGTCGA ''' out = StringIO.StringIO('') ngsutils.gtf.junctions.gtf_junctions(gtf, fa, fragment_size=4, min_size=8, known=True, out=out, quiet=True) self.assertEqual(out.getvalue(), valid) if __name__ == '__main__': unittest.main()

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6

82a2f6300b87eb5407f5a32ba6e167f583497783

319

py

Python

src/python/WMCore/WMBS/Oracle/Workflow/CheckInjectedWorkflow.py

khurtado/WMCore

f74e252412e49189a92962945a94f93bec81cd1e

[ "Apache-2.0" ]

21

2015-11-19T16:18:45.000Z

2021-12-02T18:20:39.000Z

src/python/WMCore/WMBS/Oracle/Workflow/CheckInjectedWorkflow.py

khurtado/WMCore

f74e252412e49189a92962945a94f93bec81cd1e

[ "Apache-2.0" ]

5,671

2015-01-06T14:38:52.000Z

2022-03-31T22:11:14.000Z

src/python/WMCore/WMBS/Oracle/Workflow/CheckInjectedWorkflow.py

khurtado/WMCore

f74e252412e49189a92962945a94f93bec81cd1e

[ "Apache-2.0" ]

67

2015-01-21T15:55:38.000Z

2022-02-03T19:53:13.000Z

#!/usr/bin/env python """ _CheckInjectedWorkflow_ Oracle implementation of Workflow.CheckInjectedWorkflow """ from WMCore.WMBS.MySQL.Workflow.CheckInjectedWorkflow import CheckInjectedWorkflow as MySQLCheckInjectedWorkflow class CheckInjectedWorkflow(MySQLCheckInjectedWorkflow): """ Oracle version """

21.266667

112

0.805643

25

319

10.2

0.72

0.227451

0

0.115987

319

14

113

22.785714

0.904255

0.363636

0

1

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true

0

0.5

0

1

0

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null

1

0

null

0

1

0

1

0

1

0

6

82e97b7361be0a1d6efa1f81c7f4932ef26aa802

353

py

Python

typet/__init__.py

contains-io/typet

1bbbaa57e5de636f834215b7878af652562c1e14

[ "MIT" ]

17

2017-11-12T08:40:30.000Z

2021-12-15T20:30:23.000Z

typet/__init__.py

contains-io/typet

1bbbaa57e5de636f834215b7878af652562c1e14

[ "MIT" ]

19

2017-11-12T21:57:10.000Z

2018-10-11T02:29:02.000Z

typet/__init__.py

contains-io/typet

1bbbaa57e5de636f834215b7878af652562c1e14

[ "MIT" ]

1

2017-11-12T08:40:34.000Z

# -*- coding: utf-8 -*- # pragma pylint: disable=wildcard-import,redefined-builtin """Contains all typet classes and functions.""" from __future__ import unicode_literals from .meta import * # noqa: F401 from .objects import * # noqa: F401 from .path import * # noqa: F401 from .types import * # noqa: F401 from .validation import * # noqa: F401

29.416667

58

0.708215

46

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0.204082

0.285714

0.293878

0

0.054795

0.172805

353

11

59

32.090909

0.784247

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true

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null

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null

0

1

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1

0

1

0

6

7d85a098b047bf2819391ee1b76f2cebfe1d518e

16,794

py

Python

tests/stream/test_v1.py

rune-labs/runeq-python

5fb487af9d55a16665a0ac8c07f761b4927ca4c3

[ "MIT" ]

4

2020-05-18T20:52:24.000Z

2022-01-21T13:41:08.000Z

tests/stream/test_v1.py

rune-labs/runeq-python

5fb487af9d55a16665a0ac8c07f761b4927ca4c3

[ "MIT" ]

1

2020-09-08T22:26:46.000Z

2020-09-08T23:23:35.000Z

tests/stream/test_v1.py

rune-labs/runeq-python

5fb487af9d55a16665a0ac8c07f761b4927ca4c3

[ "MIT" ]

null

from unittest import mock, TestCase from typing import List, Dict import numpy as np from runeq import Config, stream, errors def mock_get_json_response( bodies: List[dict], calls: List, status_code=200, headers: List[Dict[str, str]] = None ): """Return a function that can be used to mock .get_json_response() Args: bodies: list of JSON bodies to return from response.json() calls: list. Every time the function is called, args and kwargs will be appended to this list. status_code: status code to return for each response headers: the response header to apply """ headers = headers or [{}] * len(bodies) num = 0 def _func(*args, **kwargs): nonlocal num # add inputs to the list of calls that was provided calls.append((args, kwargs)) resp = mock.MagicMock() resp.headers = headers[num] resp.status_code = status_code resp.ok = (status_code < 400) resp.json.return_value = bodies[num] num += 1 return resp return _func def mock_get_csv_response( bodies: List[str], calls: List, status_code=200, headers: List[Dict[str, str]] = None ): """Return a function that can be used to mock .get_csv_response() Args: bodies: list of response bodies to return from response.text calls: list. Every time the function is called, args and kwargs will be appended to this list. status_code: status code to return for each response headers: the response header to apply """ headers = headers or [{}] * len(bodies) num = 0 def _func(*args, **kwargs): nonlocal num # keep track of the kwargs that were used to call this calls.append((args, kwargs)) resp = mock.MagicMock() resp.headers = headers[num] resp.status_code = status_code resp.ok = (status_code < 400) resp.text = bodies[num] num += 1 return resp return _func class TestStreamV1Client(TestCase): """ Test stream.V1Client and the associated accessors. """ def setUp(self) -> None: """ Initialize a client, set up basic mocking. """ self.cfg = Config( client_key_id='abc', client_access_key='abc123', ) self.client = stream.V1Client(self.cfg) self.use_np_orig = stream.v1.USE_NUMPY stream.v1.USE_NUMPY = False def tearDown(self) -> None: """ Tear down monkey-patching. """ stream.v1.USE_NUMPY = self.use_np_orig @mock.patch('runeq.stream.v1.requests') def test_get_json_response(self, requests): """ Test the signature of JSON requests. """ for test_num, case in enumerate(( (self.client.Accel, '/v1/accel.json'), (self.client.BandPower, '/v1/band_power.json'), (self.client.Event, '/v1/event.json'), (self.client.HeartRate, '/v1/heartrate.json'), (self.client.LFP, '/v1/lfp.json'), ( self.client.ProbabilitySymptom, '/v1/probability_symptom.json' ), (self.client.Rotation, '/v1/rotation.json'), (self.client.Span, '/v1/span.json'), (self.client.State, '/v1/state.json'), )): resource_creator, endpoint = case resource = resource_creator(leslie='knope') resource.get_json_response(ron='swanson', test_num=test_num) requests.get.assert_has_calls([ mock.call( self.cfg.stream_url + endpoint, headers=self.cfg.auth_headers, params={ 'leslie': 'knope', 'ron': 'swanson', 'test_num': test_num, } ), ]) @mock.patch('runeq.stream.v1.requests') def test_get_csv_response(self, requests): """ Test the signature of CSV requests. """ for test_num, case in enumerate(( (self.client.Accel, '/v1/accel.csv'), (self.client.BandPower, '/v1/band_power.csv'), (self.client.HeartRate, '/v1/heartrate.csv'), (self.client.LFP, '/v1/lfp.csv'), ( self.client.ProbabilitySymptom, '/v1/probability_symptom.csv' ), (self.client.Rotation, '/v1/rotation.csv'), (self.client.State, '/v1/state.csv'), )): resource_creator, endpoint = case resource = resource_creator(leslie='knope') resource.get_csv_response(ron='swanson', test_num=test_num) requests.get.assert_has_calls([ mock.call( self.cfg.stream_url + endpoint, stream=True, headers=self.cfg.auth_headers, params={ 'leslie': 'knope', 'ron': 'swanson', 'test_num': test_num, } ), ]) def test_iter_json_data_with_token(self): """ Test the iterator over JSON responses, paginating with the next page token header. """ for test_num, resource_creator in enumerate(( self.client.Accel, self.client.BandPower, self.client.Event, self.client.HeartRate, self.client.LFP, self.client.ProbabilitySymptom, self.client.Rotation, self.client.Span, self.client.State, )): resource = resource_creator() mock_responses = [ {'success': True, 'result': [], 'next_page': 1}, {'success': True, 'result': []} ] calls = [] resource.get_json_response = mock_get_json_response( mock_responses, calls, 200, [ {'X-Rune-Next-Page-Token': 'MTIzNDU2MDAwMA=='}, {}, ] ) iterator = resource.iter_json_data(test_num=test_num) self.assertEqual(len(list(iterator)), 2) # Check that all parameters were kept the same across calls, # except for "next_page_token" self.assertEqual(calls, [ ((), {'test_num': test_num}), ( (), { 'test_num': test_num, 'next_page_token': 'MTIzNDU2MDAwMA==' } ) ]) def test_iter_json_data(self): """ Test the iterator over JSON responses, following pagination with the page number. """ results = [ {'a': 1}, {'b': 2} ] mock_responses = [ {'success': True, 'result': results[0], 'next_page': 1}, {'success': True, 'result': results[1]} ] for test_num, resource_creator in enumerate(( self.client.Accel, self.client.BandPower, self.client.Event, self.client.HeartRate, self.client.LFP, self.client.ProbabilitySymptom, self.client.Rotation, self.client.State, )): resource = resource_creator() # # Successful Requests # calls = [] resource.get_json_response = mock_get_json_response( mock_responses, calls ) # Check the results num_results = 0 iterator = resource.iter_json_data(test_num=test_num) for i, actual in enumerate(iterator): self.assertEqual(results[i], actual) num_results += 1 self.assertEqual(num_results, 2) # Check that all parameters were kept the same across calls, # except for "page" (which must be incremented) self.assertEqual(calls, [ ((), {'test_num': test_num}), ((), {'test_num': test_num, 'page': 1}) ]) # # Request Error # Iterator should check the response status for each request # err_details = { "message": "i am an intentional error!", "type": "TestError", } resource.get_json_response = mock_get_json_response( [{'success': False, 'error': err_details}], [], status_code=404, ) with self.assertRaises(errors.APIError) as e: next(resource.iter_json_data()) err = e.exception self.assertEqual(err.status_code, 404) self.assertEqual(err.details, err_details) def test_iter_csv_data_with_token(self): """ Test the iterator over CSV responses, which follows new pagination """ mock_responses = [ 'good,better\nskiing,hiking\n', 'good,better\ncupcakes,brownies\n', '', ] for test_num, resource_creator in enumerate(( self.client.Accel, self.client.BandPower, self.client.HeartRate, self.client.LFP, self.client.ProbabilitySymptom, self.client.Rotation, self.client.State, )): resource = resource_creator() # # Successful Requests # calls = [] resource.get_csv_response = mock_get_csv_response( mock_responses, calls, 200, [ {'X-Rune-Next-Page-Token': 'MTIzNDU2MDAwMA=='}, {'X-Rune-Next-Page-Token': 'MTIzNDU2MDAwMA=='}, {}, ], ) # Check the results iterator = resource.iter_csv_text(test_num=test_num) self.assertEqual(len(list(iterator)), 2) # Check that all parameters were kept the same across calls, # except for "next_page_token" (which will normally be different # for each response) self.assertEqual(calls, [ ((), {'test_num': test_num}), ( (), { 'test_num': test_num, 'next_page_token': 'MTIzNDU2MDAwMA==' } ), ( (), { 'test_num': test_num, 'next_page_token': 'MTIzNDU2MDAwMA==' } ), ]) def test_iter_csv_data(self): """ Test the iterator over CSV responses, which follows pagination """ mock_responses = [ 'good,better\nskiing,hiking\n', 'good,better\ncupcakes,brownies\n', '', ] for test_num, resource_creator in enumerate(( self.client.Accel, self.client.BandPower, self.client.HeartRate, self.client.LFP, self.client.ProbabilitySymptom, self.client.Rotation, self.client.State, )): resource = resource_creator() # # Successful Requests # calls = [] resource.get_csv_response = mock_get_csv_response( mock_responses, calls, ) # Check the results num_results = 0 iterator = resource.iter_csv_text(test_num=test_num) for i, actual in enumerate(iterator): self.assertEqual(mock_responses[i], actual) num_results += 1 # although there are 3 responses, the last (empty) body should not # be returned by the iterator self.assertEqual(num_results, 2) # Check that all parameters were kept the same across calls, # except for "page" (which must be incremented) self.assertEqual(calls, [ ((), {'test_num': test_num}), ((), {'test_num': test_num, 'page': 1}), ((), {'test_num': test_num, 'page': 2}), ]) # # Request Error # Iterator should check the response status for each request # err_details = { "message": "i am an intentional error!", "type": "TestError", } # note: CSV endpoints return JSON on API errors resource.get_csv_response = mock_get_json_response( [{'success': False, 'error': err_details}], [], status_code=404, ) with self.assertRaises(errors.APIError) as e: next(resource.iter_csv_text()) err = e.exception self.assertEqual(err.status_code, 404) self.assertEqual(err.details, err_details) def test_iter_points(self): """ Test iterating over data as points. Uses the CSV endpoint. """ mock_responses = [ 'lower,higher,label\n1,2,ints\n3.5,6.7,floats\n', 'lower,higher,label\n,8.9,missing data\n', '', ] expected = [ {'lower': 1, 'higher': 2, 'label': 'ints'}, {'lower': 3.5, 'higher': 6.7, 'label': 'floats'}, {'lower': None, 'higher': 8.9, 'label': 'missing data'}, ] for test_num, resource_creator in enumerate(( self.client.Accel, self.client.BandPower, self.client.HeartRate, self.client.LFP, self.client.ProbabilitySymptom, self.client.Rotation, self.client.State, )): resource = resource_creator() # replace get_csv_response on the resource resource.get_csv_response = mock_get_csv_response( mock_responses, [], ) for i, point in enumerate(resource.points()): self.assertDictEqual(expected[i], point) # replace get_csv_response again, to restart the mock responses resource.get_csv_response = mock_get_csv_response( mock_responses, [], ) for i, point in enumerate(resource): self.assertDictEqual(expected[i], point) # check dtype for "higher", which always has a numeric # value in the test data self.assertNotIsInstance(point['higher'], np.float64) def test_iter_points_numpy(self): """ Test iterating over data as points, using Numpy to convert. """ stream.v1.USE_NUMPY = True mock_responses = [ 'lower,higher,label\n1,2,ints\n3.5,6.7,floats\n', 'lower,higher,label\n,8.9,missing data\n', '', ] expected = [ {'lower': 1, 'higher': 2, 'label': 'ints'}, {'lower': 3.5, 'higher': 6.7, 'label': 'floats'}, {'lower': np.NaN, 'higher': 8.9, 'label': 'missing data'}, ] for test_num, resource_creator in enumerate(( self.client.Accel, self.client.BandPower, self.client.HeartRate, self.client.LFP, self.client.ProbabilitySymptom, self.client.Rotation, self.client.State, )): resource = resource_creator() # replace get_csv_response on the resource resource.get_csv_response = mock_get_csv_response( mock_responses, [], ) for i, point in enumerate(resource.points()): self.assertDictEqual(expected[i], point) # check dtype for "higher", which always has a numeric # value in the test data self.assertIsInstance(point['higher'], np.float64)

32.483559

78

0.495891

1,638

16,794

4.934676

0.147741

0.076704

0.029939

0.038105

0.841148

0.787331

0.750217

0.726587

0.710504

0.680317

0

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16,794

516

79

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0.793877

0.150411

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0.692958

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false

0

0.011268

0

0.064789

0

null

0

1

0

null

0

6

7dad60f91a776a2483da20380918c138b1e31a04

5,082

py

Python

VScodePython/graphs.py

horbosis556/Scientific-Calculator-

98ab96fa04b4719f786fa65089700697e74f0386

[ "MIT" ]

1

2021-01-16T10:05:43.000Z

VScodePython/graphs.py

horbosis556/Scientific-Calculator-

98ab96fa04b4719f786fa65089700697e74f0386

[ "MIT" ]

null

VScodePython/graphs.py

horbosis556/Scientific-Calculator-

98ab96fa04b4719f786fa65089700697e74f0386

[ "MIT" ]

null

from tkinter import * import math import numpy as np import matplotlib.pyplot as plt from matplotlib.figure import Figure from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk def plot_sin(): # TkInter Window For The Graph. win = Tk() win.title('Graph') win.geometry("500x500") # Figsize = (5x5)inches, rads -> (0 <= rads <= 2π), vals -> (-1 <= vals <= 1) # Use Default Dots Per Inch(100). x = np.arange(0, math.pi*2, 0.05) fig = plt.figure() axe = fig.add_axes([0.1, 0.1, 0.8, 0.8]) y = np.sin(x) axe.plot(x, y, 'r') axe.grid(True) # I Added Grid And Color To Each Graph, For The Eyes To Read Them Easier. axe.set_xlabel('Angles') axe.set_title('Y = Sin(x)') # axe.set_xticks() Provides Accurate Distance Measurement Between Each Quadrant. axe.set_xticks([0, 1.5, 3.1, 4.7]) axe.set_xticklabels(['(0° To 90°)','(90° To 180°)','(180° To 270°)','(270° To 360°)']) axe.spines['left'].set_color('red') # Figure Axes Plot On A Canvas, Which Is Then Placed In TkInter Window by .get_tk_widget() method. canvas = FigureCanvasTkAgg(fig, master = win) canvas.draw() canvas.get_tk_widget().pack() # Toolbars For Each Graph. toolbar = NavigationToolbar2Tk(canvas, win) toolbar.update() canvas.get_tk_widget().pack() def plot_cos(): win = Tk() win.title('Y = Cos(x)') win.geometry("500x500") x = np.arange(0, math.pi*2, 0.05) fig = plt.figure() axe = fig.add_axes([0.1, 0.1, 0.8, 0.8]) y = np.cos(x) axe.plot(x, y, 'g') axe.grid(True) axe.set_xlabel('Angles') axe.set_title('Y = Cos(x)') axe.set_xticks([0, 1.6, 3.1, 4.7]) axe.set_xticklabels(['(0° To 90°)','(90° To 180°)','(180° To 270°)','(270° To 360°)']) axe.spines['left'].set_color('red') canvas = FigureCanvasTkAgg(fig, master = win) canvas.draw() canvas.get_tk_widget().pack() toolbar = NavigationToolbar2Tk(canvas, win) toolbar.update() canvas.get_tk_widget().pack() def plot_tan(): win = Tk() win.title('Y = Tan(x)') win.geometry("500x500") x = np.arange(0, math.pi*2, 0.05) fig = plt.figure() axe = fig.add_axes([0.1, 0.1, 0.8, 0.8]) y = np.tan(x) axe.plot(x, y, 'm') axe.grid(True) axe.set_xlabel('Angles') axe.set_title('Y = Tan(x)') axe.set_xticks([0, 1.5, 3, 4.7]) axe.set_xticklabels(['(0° To 90°)','(90° To 180°)','(180° To 270°)','(270° To 360°)']) axe.spines['left'].set_color('red') canvas = FigureCanvasTkAgg(fig, master = win) canvas.draw() canvas.get_tk_widget().pack() toolbar = NavigationToolbar2Tk(canvas, win) toolbar.update() canvas.get_tk_widget().pack() # Unable to Use SymPy and mpmath def plot_csc(): win = Tk() win.title('Y = Csc(x)') win.geometry("500x500") x = np.arange(0, math.pi*2, 0.05) fig = plt.figure() axe = fig.add_axes([0.1, 0.1, 0.8, 0.8]) y = [1 / np.sin(i) for i in x] axe.plot(x, y, 'c') axe.grid(True) axe.set_xlabel('Angles') axe.set_title('Y = Csc(x)') axe.set_xticks([0, 1.5, 3, 4.7]) axe.set_xticklabels(['(0° To 90°)','(90° To 180°)','(180° To 270°)','(270° To 360°)']) axe.spines['left'].set_color('red') canvas = FigureCanvasTkAgg(fig, master = win) canvas.draw() canvas.get_tk_widget().pack() toolbar = NavigationToolbar2Tk(canvas, win) toolbar.update() canvas.get_tk_widget().pack() def plot_sec(): win = Tk() win.title('Y = Csc(x)') win.geometry("500x500") x = np.arange(0, math.pi*2, 0.05) fig = plt.figure() axe = fig.add_axes([0.1, 0.1, 0.8, 0.8]) y = [1 / np.cos(j) for j in x] axe.plot(x, y, 'y') axe.grid(True) axe.set_xlabel('Angles') axe.set_title('Y = Sec(x)') axe.set_xticks([0, 1.5, 3, 4.7]) axe.set_xticklabels(['(0° To 90°)','(90° To 180°)','(180° To 270°)','(270° To 360°)']) axe.spines['left'].set_color('red') canvas = FigureCanvasTkAgg(fig, master = win) canvas.draw() canvas.get_tk_widget().pack() toolbar = NavigationToolbar2Tk(canvas, win) toolbar.update() canvas.get_tk_widget().pack() def plot_cot(): win = Tk() win.title('Y = Csc(x)') win.geometry("500x500") x = np.arange(0, math.pi*2, 0.05) fig = plt.figure() axe = fig.add_axes([0.1, 0.1, 0.8, 0.8]) y = [1/ np.tan(k) for k in x] axe.plot(x, y, 'b') axe.grid(True) axe.set_xlabel('Angles') axe.set_title('Y = Cot(x)') axe.set_xticks([0, 1.5, 3, 4.7]) axe.set_xticklabels(['(0° To 90°)','(90° To 180°)','(180° To 270°)','(270° To 360°)']) axe.spines['left'].set_color('red') canvas = FigureCanvasTkAgg(fig, master = win) canvas.draw() canvas.get_tk_widget().pack() toolbar = NavigationToolbar2Tk(canvas, win) toolbar.update() canvas.get_tk_widget().pack()

29.206897

103

0.571232

837

5,082

3.442055

0.145759

0.052065

0.049636

0.070809

0.775425

0.755293

0.737591

0.732385

0.721972

0

0.075213

0.238686

5,082

173

104

29.375723

0.657017

0.086777

0

0.734848

0

0.124381

0

1

0.045455

false

0

0.045455

0

0.090909

0

null

0

1

0

1

0

null

0

6

7dc1514eec4a445105b35cbc0e5ffb0113daffdf

1,135

py

Python

tests/test_mqtt.py

sourcesimian/mqtt-kube

a199a27fd377b9a742f123d50b45d12f6cb58184

[ "MIT" ]

null

tests/test_mqtt.py

sourcesimian/mqtt-kube

a199a27fd377b9a742f123d50b45d12f6cb58184

[ "MIT" ]

null

tests/test_mqtt.py

sourcesimian/mqtt-kube

a199a27fd377b9a742f123d50b45d12f6cb58184

[ "MIT" ]

null

from mqtt_kube.mqtt import TopicMatcher class TestTopicMatcher: def test_basic(self): assert TopicMatcher('topic/one').match('topic/one') == True assert TopicMatcher('topic/two').match('topic/one') == False def test_plus(self): assert TopicMatcher('topic/+/plus').match('topic/one/plus') == True assert TopicMatcher('topic/+/plus').match('topic/one/extra/plus') == False assert TopicMatcher('++/plus').match('topic/one/plus') == False assert TopicMatcher('+one/plus').match('topic/one/plus') == False assert TopicMatcher('+ne/plus').match('one/plus') == False def test_hash(self): assert TopicMatcher('#').match('topic/one/plus') == True assert TopicMatcher('topic/#').match('topic/one/plus') == True assert TopicMatcher('topic/two/#').match('topic/one/plus') == False assert TopicMatcher('#/plus').match('one/plus') == False def test_plus_and_hash(self): assert TopicMatcher('+/+/plus/#').match('topic/one/plus/many/more') == True assert TopicMatcher('+/+/minus/#').match('topic/one/plus/many/more') == False

45.4

85

0.638767

137

1,135

5.240876

0.189781

0.325905

0.199164

0.189415

0.703343

0.644847

0.388579

0

0.168282

1,135

24

86

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0.042291

0

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1

0.210526

false

0

0.052632

0

0.315789

0

null

1

0

1

0

null

0

1

0

1

0

6

7dc8dab4e7aa21ce5e8156ec657c478f099bfac1

32

py

Python

stubbs/defs/item.py

holy-crust/reclaimer

0aa693da3866ce7999c68d5f71f31a9c932cdb2c

[ "MIT" ]

null

stubbs/defs/item.py

holy-crust/reclaimer

0aa693da3866ce7999c68d5f71f31a9c932cdb2c

[ "MIT" ]

null

stubbs/defs/item.py

holy-crust/reclaimer

0aa693da3866ce7999c68d5f71f31a9c932cdb2c

[ "MIT" ]

null

from ...hek.defs.item import *

16

31

0.65625

5

32

4.2

1

0

0.15625

32

1

32

0.777778

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

7dcb115d63475624e95679351b87856244a03ed5

1,306

py

Python

build.py

thommyho/conan-oatpp

30084af0252e9b30486ed022f4aa5357aebafa16

[ "Apache-2.0" ]

null

build.py

thommyho/conan-oatpp

30084af0252e9b30486ed022f4aa5357aebafa16

[ "Apache-2.0" ]

null

build.py

thommyho/conan-oatpp

30084af0252e9b30486ed022f4aa5357aebafa16

[ "Apache-2.0" ]

null

from cpt.packager import ConanMultiPackager import platform if __name__ == "__main__": builder = ConanMultiPackager() if platform.system() == "Windows": builder.add(settings={"arch": "x86_64", "build_type": "Debug", "compiler": "Visual Studio", "compiler.version": 16, "compiler.runtime": "MDd"}, options={}, env_vars={}, build_requires={}) builder.add(settings={"arch": "x86_64", "build_type": "Release", "compiler": "Visual Studio", "compiler.version": 16, "compiler.runtime": "MD"}, options={}, env_vars={}, build_requires={}) builder.add(settings={"arch": "x86_64", "build_type": "RelWithDebInfo", "compiler": "Visual Studio", "compiler.version": 16, "compiler.runtime": "MD"}, options={}, env_vars={}, build_requires={}) else: builder.add(settings={"arch": "x86_64", "build_type": "Debug"}, options={}, env_vars={}, build_requires={}) builder.add(settings={"arch": "x86_64", "build_type": "Release"}, options={}, env_vars={}, build_requires={}) builder.add(settings={"arch": "x86_64", "build_type": "RelWithDebInfo"}, options={}, env_vars={}, build_requires={}) builder.run()

62.190476

159

0.574273

130

1,306

5.523077

0.276923

0.083565

0.150418

0.183844

0.831476

0.784123

0.711699

0.597493

0

0.03003

0.235069

1,306

20

160

65.3

0.688689

0

0.315789

0

0.270291

0

1

0

false

0

0.105263

0

0.105263

0

null

0

1

0

null

0

6

815548806e275795fcda4717d0fe69721e0b8d55

27

py

Python

PythonMisc/__init__.py

jwbrooks0/johnspythonlibrary2

10ca519276d8c32da0fbd41a597f75c0c98a8736

[ "MIT" ]

null

PythonMisc/__init__.py

jwbrooks0/johnspythonlibrary2

10ca519276d8c32da0fbd41a597f75c0c98a8736

[ "MIT" ]

null

PythonMisc/__init__.py

jwbrooks0/johnspythonlibrary2

10ca519276d8c32da0fbd41a597f75c0c98a8736

[ "MIT" ]

null

from ._pythonmisc import *

13.5

26

0.777778

3

27

6.666667

1

0

0.148148

27

1

27

0.869565

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

817161a4114dd4bc2f2aea716e123f38982a1bb0

14,140

py

Python

registry/application/handlers/service_handlers.py

anandrgitnirman/snet-marketplace-service

f31bf741094476b9cb26277f1165deb2856257b1

[ "MIT" ]

14

2019-02-12T09:14:52.000Z

2021-03-11T18:42:22.000Z

registry/application/handlers/service_handlers.py

prashantramangupta/snet-marketplace-service

7c293054e4b0207deefecc46defd743c064472a4

[ "MIT" ]

1,079

2019-01-10T04:31:24.000Z

2022-03-29T06:16:42.000Z

registry/application/handlers/service_handlers.py

prashantramangupta/snet-marketplace-service

7c293054e4b0207deefecc46defd743c064472a4

[ "MIT" ]

20

2018-12-18T13:06:41.000Z

2021-09-17T11:13:01.000Z

import sys sys.path.append('/opt') import json from common.constant import StatusCode from common.exception_handler import exception_handler from common.exceptions import BadRequestException from common.logger import get_logger from common.utils import generate_lambda_response, validate_dict from registry.application.access_control.authorization import secured from registry.application.services.service_publisher_service import ServicePublisherService from registry.application.services.service_transaction_status import ServiceTransactionStatus from registry.config import NETWORK_ID, SLACK_HOOK from registry.constants import Action, EnvironmentType from registry.exceptions import EnvironmentNotFoundException, EXCEPTIONS from registry.application.services.update_service_assets import UpdateServiceAssets logger = get_logger(__name__) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def verify_service_id(event, context): username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] query_parameters = event["queryStringParameters"] if "org_uuid" not in path_parameters and "service_id" not in query_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_id = query_parameters["service_id"] response = ServicePublisherService(username, org_uuid, None).get_service_id_availability_status(service_id) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def save_transaction_hash_for_published_service(event, context): username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] payload = json.loads(event["body"]) if "org_uuid" not in path_parameters and "service_uuid" not in path_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(username, org_uuid, service_uuid).save_transaction_hash_for_published_service( payload) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def save_service(event, context): logger.info(f"Event for save service {event}") username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] payload = json.loads(event["body"]) if not path_parameters.get("org_uuid", "") and not path_parameters.get("service_uuid", ""): raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(username, org_uuid, service_uuid).save_service(payload) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def save_service_attributes(event, context): logger.info(f"Event for save service {event}") username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] payload = json.loads(event["body"]) if not path_parameters.get("org_uuid", "") and not path_parameters.get("service_uuid", ""): raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(username, org_uuid, service_uuid).save_service_attributes(payload) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def create_service(event, context): username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] payload = json.loads(event["body"]) if not path_parameters.get("org_uuid", ""): raise BadRequestException() org_uuid = path_parameters["org_uuid"] response = ServicePublisherService(username, org_uuid, None).create_service(payload) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def get_services_for_organization(event, context): username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] payload = json.loads(event["body"]) if "org_uuid" not in path_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] response = ServicePublisherService(username, org_uuid, None).get_services_for_organization(payload) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def get_service_for_service_uuid(event, context): username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] if "org_uuid" not in path_parameters and "service_uuid" not in path_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(username, org_uuid, service_uuid).get_service_for_given_service_uuid() return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def publish_service_metadata_to_ipfs(event, context): username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] if "org_uuid" not in path_parameters and "service_uuid" not in path_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(username, org_uuid, service_uuid).publish_service_data_to_ipfs() return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def get_daemon_config_for_current_network(event, context): logger.info(f"event for get_daemon_config_for_current_network:: {event}") username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] query_parameters = event["queryStringParameters"] if not validate_dict(path_parameters, ["org_uuid", "service_uuid", "group_id"]) or 'network' not in query_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] group_id = path_parameters["group_id"] if query_parameters["network"] == EnvironmentType.TEST.value: response = ServicePublisherService(username, org_uuid, service_uuid).daemon_config( environment=EnvironmentType.TEST.value) elif query_parameters["network"] == EnvironmentType.MAIN.value: response = ServicePublisherService(username, org_uuid, service_uuid).daemon_config( environment=EnvironmentType.MAIN.value) else: raise EnvironmentNotFoundException() return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) def get_service_details_using_org_id_service_id(event, context): logger.info(f"event: {event}") query_parameters = event["queryStringParameters"] if not validate_dict(query_parameters, ["org_id", "service_id"]): raise BadRequestException() org_id = query_parameters["org_id"] service_id = query_parameters["service_id"] response = ServicePublisherService.get_service_for_org_id_and_service_id(org_id, service_id) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) def service_deployment_status_notification_handler(event, context): logger.info(f"Service Build status event {event}") org_id = event['org_id'] service_id = event['service_id'] build_status = int(event['build_status']) ServicePublisherService("BUILD_PROCESS", "", "").service_build_status_notifier(org_id, service_id, build_status) return generate_lambda_response( StatusCode.CREATED, {"status": "success", "data": "Build failure notified", "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) def update_transaction(event, context): logger.info(f"Update transaction event :: {event}") ServiceTransactionStatus().update_transaction_status() return generate_lambda_response(StatusCode.OK, "OK") @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) def get_code_build_status_for_service(event, context): logger.info(f"Get code build status event :: {event}") path_parameters = event["pathParameters"] org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(org_uuid=org_uuid, service_uuid=service_uuid, username=None) \ .get_service_demo_component_build_status() return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) def update_service_assets(event, context): logger.info(f"Update service assets event :: {event}") response = UpdateServiceAssets().validate_and_process_service_assets(payload=event) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) def update_demo_component_build_status(event, context): logger.info(f"Demo component build status update event :: {event}") org_uuid = event['org_uuid'] service_uuid = event['service_uuid'] build_status = event['build_status'] build_id = event['build_id'] filename = event['filename'] response = UpdateServiceAssets()\ .update_demo_component_build_status(org_uuid=org_uuid, service_uuid=service_uuid, build_status=build_status, build_id=build_id, filename=filename) return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True ) @exception_handler(SLACK_HOOK=SLACK_HOOK, NETWORK_ID=NETWORK_ID, logger=logger, EXCEPTIONS=EXCEPTIONS) @secured(action=Action.CREATE, org_uuid_path=("pathParameters", "org_uuid"), username_path=("requestContext", "authorizer", "claims", "email")) def publish_service(event, context): logger.info(f"Publish service event::{event}") username = event["requestContext"]["authorizer"]["claims"]["email"] path_parameters = event["pathParameters"] if "org_uuid" not in path_parameters and "service_uuid" not in path_parameters: raise BadRequestException() org_uuid = path_parameters["org_uuid"] service_uuid = path_parameters["service_uuid"] response = ServicePublisherService(username, org_uuid, service_uuid).publish_service_data() return generate_lambda_response( StatusCode.OK, {"status": "success", "data": response, "error": {}}, cors_enabled=True )

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null

0

6

819e70addddb3290dffdeb3c906eab23eb0bcb75

38

py

Python

onelinerizer/__init__.py

mayl8822/onelinerizer

bad341f261d35e56872b4c22297a44dc6d5cfab3

[ "MIT" ]

1,062

2015-11-18T01:04:33.000Z

2022-03-29T07:13:30.000Z

onelinerizer/__init__.py

mayl8822/onelinerizer

bad341f261d35e56872b4c22297a44dc6d5cfab3

[ "MIT" ]

26

2015-11-17T06:58:07.000Z

2022-01-15T18:11:16.000Z

onelinerizer/__init__.py

mayl8822/onelinerizer

bad341f261d35e56872b4c22297a44dc6d5cfab3

[ "MIT" ]

100

2015-11-17T09:01:22.000Z

2021-09-12T13:58:28.000Z

from .onelinerizer import onelinerize

19

37

0.868421

4

38

8.25

1

0

0.105263

38

1

38

0.970588

0

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null

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1

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1

0

1

0

6

819eee92e1b01ffcddcab758721e62152875f417

6,020

py

Python

test/pytest/test_regexes.py

showipintbri/ttp

10b8767e67ec39ed4e30769d36e6fb6e5b0ed265

[ "MIT" ]

254

2019-09-23T15:37:13.000Z

2022-03-24T18:56:56.000Z

test/pytest/test_regexes.py

showipintbri/ttp

10b8767e67ec39ed4e30769d36e6fb6e5b0ed265

[ "MIT" ]

71

2019-09-26T16:32:55.000Z

2022-03-31T15:57:12.000Z

test/pytest/test_regexes.py

showipintbri/ttp

10b8767e67ec39ed4e30769d36e6fb6e5b0ed265

[ "MIT" ]

38

2019-10-18T03:43:42.000Z

2022-01-19T20:03:33.000Z

import sys sys.path.insert(0, "../..") import pprint import logging logging.basicConfig(level="INFO") from ttp import ttp def test_pipe_separated_regexes(): template = """ <input load="text"> Protocol Address Age (min) Hardware Addr Type Interface Internet 10.12.13.1 98 0950.5785.5cd1 ARPA FastEthernet2.13 Internet 10.12.13.2 98 0950.5785.5cd2 ARPA Loopback0 Internet 10.12.13.3 131 0150.7685.14d5 ARPA GigabitEthernet2.13 Internet 10.12.13.4 198 0950.5C8A.5c41 ARPA GigabitEthernet2.17 </input> <vars> INTF_RE = r"GigabitEthernet\\S+|Fast\\S+" </vars> <group name="arp_test"> Internet {{ ip | re("IP")}} {{ age | re(r"\\d+") }} {{ mac }} ARPA {{ interface | re("INTF_RE") }} </group> """ parser = ttp(template=template) parser.parse() res = parser.result() # pprint.pprint(res) assert res == [ [ { "arp_test": [ { "age": "98", "interface": "FastEthernet2.13", "ip": "10.12.13.1", "mac": "0950.5785.5cd1", }, { "age": "131", "interface": "GigabitEthernet2.13", "ip": "10.12.13.3", "mac": "0150.7685.14d5", }, { "age": "198", "interface": "GigabitEthernet2.17", "ip": "10.12.13.4", "mac": "0950.5C8A.5c41", }, ] } ] ] # test_pipe_separated_regexes() def test_multiple_inline_regexes(): template = """ <input load="text"> Protocol Address Age (min) Hardware Addr Type Interface Internet 10.12.13.1 98 0950.5785.5cd1 ARPA FastEthernet2.13 Internet 10.12.13.2 98 0950.5785.5cd2 ARPA Loopback0 Internet 10.12.13.3 131 0150.7685.14d5 ARPA GigabitEthernet2.13 Internet 10.12.13.4 198 0950.5C8A.5c41 ARPA GigabitEthernet2.17 </input> <vars> INTF_RE = r"GigabitEthernet\\S+|Fast\\S+" </vars> <group name="arp_test"> Internet {{ ip }} {{ age }} {{ mac }} ARPA {{ interface | re(r"GigabitEthernet\\S+") | re(r"Fast\\S+") }} </group> """ parser = ttp(template=template) parser.parse() res = parser.result() # pprint.pprint(res) assert res == [ [ { "arp_test": [ { "age": "98", "interface": "FastEthernet2.13", "ip": "10.12.13.1", "mac": "0950.5785.5cd1", }, { "age": "131", "interface": "GigabitEthernet2.13", "ip": "10.12.13.3", "mac": "0150.7685.14d5", }, { "age": "198", "interface": "GigabitEthernet2.17", "ip": "10.12.13.4", "mac": "0950.5C8A.5c41", }, ] } ] ] # test_multiple_inline_regexes() def test_MAC_regex_formatter(): template = """ <input load="text"> Protocol Address Age (min) Hardware Addr Type Interface Internet 10.12.13.2 98 0950:5785:5cd2 ARPA Loopback0 Internet 10.12.13.3 131 0150.7685.14d5 ARPA GigabitEthernet2.13 Internet 10.12.13.1 98 0950-5785-5cd1 ARPA FastEthernet2.13 Internet 10.12.13.4 198 09:50:5C:8A:5c:41 ARPA GigabitEthernet2.17 Internet 10.12.13.5 198 09.50.5C.8A.5c.41 ARPA GigabitEthernet2.17 Internet 10.12.13.6 198 09-50-5C-8A-5c-41 ARPA GigabitEthernet2.17 Internet 10.12.13.6 198 09505C8A5c41 ARPA GigabitEthernet2.will_not_match Internet 10.12.13.6 198 09505C8:A5c41 ARPA GigabitEthernet2.will_not_match Internet 10.12.13.6 198 09505C.8.A5c41 ARPA GigabitEthernet2.will_not_match </input> <group name="arp_test"> Internet {{ ip }} {{ age }} {{ mac | MAC }} ARPA {{ interface }} </group> """ parser = ttp(template=template) parser.parse() res = parser.result() # pprint.pprint(res) assert res == [ [ { "arp_test": [ { "age": "98", "interface": "Loopback0", "ip": "10.12.13.2", "mac": "0950:5785:5cd2", }, { "age": "131", "interface": "GigabitEthernet2.13", "ip": "10.12.13.3", "mac": "0150.7685.14d5", }, { "age": "98", "interface": "FastEthernet2.13", "ip": "10.12.13.1", "mac": "0950-5785-5cd1", }, { "age": "198", "interface": "GigabitEthernet2.17", "ip": "10.12.13.4", "mac": "09:50:5C:8A:5c:41", }, { "age": "198", "interface": "GigabitEthernet2.17", "ip": "10.12.13.5", "mac": "09.50.5C.8A.5c.41", }, { "age": "198", "interface": "GigabitEthernet2.17", "ip": "10.12.13.6", "mac": "09-50-5C-8A-5c-41", }, ] } ] ] # test_MAC_regex_formatter()

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1

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null

0

6

81a712fc0a1ca3fd1d60c1d20884115c33cc34d5

77

py

Python

tst/test_fireFoxBrowser.py

Xiaoyu-Xing/youtube-algorithmic-bias

2643f9ba59fa5ad1757bc645a5a6bcf45061e21b

[ "MIT" ]

2

2019-02-20T16:35:00.000Z

2019-02-22T02:29:34.000Z

tst/test_fireFoxBrowser.py

Xiaoyu-Xing/youtube-algorithmic-bias

2643f9ba59fa5ad1757bc645a5a6bcf45061e21b

[ "MIT" ]

null

tst/test_fireFoxBrowser.py

Xiaoyu-Xing/youtube-algorithmic-bias

2643f9ba59fa5ad1757bc645a5a6bcf45061e21b

[ "MIT" ]

2

2020-06-10T04:42:05.000Z

2021-04-30T01:09:56.000Z

from unittest import TestCase class TestFireFoxBrowser(TestCase): pass

12.833333

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1

0

6

81ddf4efd987baa173741271f80cf21b6476eb8a

231

py

Python

src/config/utils/custom_pagination.py

amirpsd/drf_blog_api

58be081a450840114af021e7412e469fad90456d

[ "MIT" ]

33

2022-02-11T12:16:29.000Z

2022-03-26T15:08:47.000Z

src/config/utils/custom_pagination.py

amirpsd/django_blog_api

58be081a450840114af021e7412e469fad90456d

[ "MIT" ]

null

src/config/utils/custom_pagination.py

amirpsd/django_blog_api

58be081a450840114af021e7412e469fad90456d

[ "MIT" ]

5

2022-02-11T13:03:52.000Z

2022-03-28T16:04:32.000Z

from rest_framework.pagination import PageNumberPagination from rest_framework.response import Response class CustomPagination(PageNumberPagination): def get_paginated_response(self, data): return Response(data)

25.666667

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1

0

null

0

1

0

6

c4eca49ca3e8a8cdb08d085684aeb077bcb0da95

110

py

Python

ch01/helloworld/src/pages/views.py

Redhat8983/Redhat8983-learning-django2

fc0d5a9d93a7b15f1235d2c172e4bba50b884018

[ "Unlicense" ]

1

2022-02-21T06:48:26.000Z

ch01/helloworld/src/pages/views.py

Redhat8983/learning-django2

fc0d5a9d93a7b15f1235d2c172e4bba50b884018

[ "Unlicense" ]

null

ch01/helloworld/src/pages/views.py

Redhat8983/learning-django2

fc0d5a9d93a7b15f1235d2c172e4bba50b884018

[ "Unlicense" ]

null

from django.http import HttpResponse def home_page_view(request): return HttpResponse('Hello, Worlds!!')

22

42

0.772727

14

110

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0.928571

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0.127273

110

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0.333333

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null

0

1

0

null

0

1

0

1

0

6

1eeade2b2eff7c021bdf24444d77665b69e99e87

116

py

Python

core/message_handler/message_sender_from_db.py

taimaskhanov11/AsyncVkAccount

58c48886545aa581eb28a1071d52e0a60aa1b8ea

[ "MIT" ]

1

2021-12-26T20:40:39.000Z

core/message_handler/message_sender_from_db.py

taimaskhanov11/AsyncVkAccount

58c48886545aa581eb28a1071d52e0a60aa1b8ea

[ "MIT" ]

1

2021-12-03T18:38:38.000Z

2021-12-03T18:39:08.000Z

core/message_handler/message_sender_from_db.py

taimaskhanov11/AsyncVkAccount

58c48886545aa581eb28a1071d52e0a60aa1b8ea

[ "MIT" ]

null

from core.message_handler.message_sender import MessageSender class MessageSenderFromDb(MessageSender): pass

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6f8fb06b522d444ecf71afd635cd35139e725c57

558

py

Python

lib/python/pyflyby/importdb.py

azjps/pyflyby

fd837e9686e56a7f88eefcf1d28313915affbd3e

[ "BSD-3-Clause" ]

null

lib/python/pyflyby/importdb.py

azjps/pyflyby

fd837e9686e56a7f88eefcf1d28313915affbd3e

[ "BSD-3-Clause" ]

null

lib/python/pyflyby/importdb.py

azjps/pyflyby

fd837e9686e56a7f88eefcf1d28313915affbd3e

[ "BSD-3-Clause" ]

null

# pyflyby/importdb.py. # Copyright (C) 2011, 2012, 2013, 2014 Karl Chen. # License: MIT http://opensource.org/licenses/MIT # Deprecated stub for backwards compatibility. from __future__ import absolute_import, division, with_statement from pyflyby._importdb import ImportDB def global_known_imports(): # Deprecated stub for backwards compatibility. return ImportDB.get_default(".").known_imports def global_mandatory_imports(): # Deprecated stub for backwards compatibility. return ImportDB.get_default(".").mandatory_imports

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6

6fa864c45ec99157d37fc19a4b427bdda37a627d

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py

Python

yolo/vedanet/network/head/brick/__init__.py

hilman-dayo/ObjectDetection-OneStageDet

44054ad335e24e99a98fdad0d18b9bf3a80c941c

[ "MIT" ]

331

2020-06-05T05:10:21.000Z

2022-03-29T07:32:42.000Z

vedanet/network/head/brick/__init__.py

xiongcaihua/ObjectDetection-OneStageDet

d29f69cdce32b006bd040edb6e66427b3c987c70

[ "Apache-2.0" ]

10

2020-06-12T07:53:42.000Z

2021-05-11T00:09:10.000Z

vedanet/network/head/brick/__init__.py

xiongcaihua/ObjectDetection-OneStageDet

d29f69cdce32b006bd040edb6e66427b3c987c70

[ "Apache-2.0" ]

84

2020-06-05T10:21:11.000Z

2022-03-27T23:42:44.000Z

from . import yolov3

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6fa958a127643df28e086c6eed2e50b037d9b74b

812

py

Python

sorceress/test___init__.py

altunenes/sorceress

1ee36bbd27ebe3ae41293e3df44c7d3dd150502c

[ "MIT" ]

6

2021-09-20T14:47:34.000Z

2022-03-09T12:35:48.000Z

sorceress/test___init__.py

altunenes/sorceress

1ee36bbd27ebe3ae41293e3df44c7d3dd150502c

[ "MIT" ]

null

sorceress/test___init__.py

altunenes/sorceress

1ee36bbd27ebe3ae41293e3df44c7d3dd150502c

[ "MIT" ]

null

from unittest import TestCase class Testsorcerer(TestCase): def test_chromatic(self): return def test_dotill(self): return def test_realtimegrid(self): return def test_addlines(self): return def test_addlines_alpha(self): return def test_eyecolour(self): return def test_dakin_pex(self): return def test_bruno(self): return def test_dolboeuf(self): return def test_kanizsa(self): return def test_ponzol(self): return def test_t_aki2001(self): return def test_cafe_wall(self): return def test_ccob(self): return def test_ebbinghaus(self): return def test_whiteill(self): return def test_enigma(self): return

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82ea330aae6d4f6b9f65440d120a2656dcb64e13

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py

Python

Python Snippets/sorting/__init__.py

wolfnfox/Code-Snippets

993cb2b273d538bdeb76ff3a39fa41a92a6282de

[ "MIT" ]

null

Python Snippets/sorting/__init__.py

wolfnfox/Code-Snippets

993cb2b273d538bdeb76ff3a39fa41a92a6282de

[ "MIT" ]

null

Python Snippets/sorting/__init__.py

wolfnfox/Code-Snippets

993cb2b273d538bdeb76ff3a39fa41a92a6282de

[ "MIT" ]

null

# import os, sys # parentdir = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) # if parentdir not in sys.path: # sys.path.insert(0,parentdir)

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d21c785473a527861d4b0848610313159a104f91

232

py

Python

installer_scoring/installer_scoring/doctype/installer_scoring_sub_parameter_value_and_score/installer_scoring_sub_parameter_value_and_score.py

Manisvb123/TestAll

39fc4e59e1fe58e9778f57f9bbfcfd8e2555e938

[ "MIT" ]

null

installer_scoring/installer_scoring/doctype/installer_scoring_sub_parameter_value_and_score/installer_scoring_sub_parameter_value_and_score.py

Manisvb123/TestAll

39fc4e59e1fe58e9778f57f9bbfcfd8e2555e938

[ "MIT" ]

null

installer_scoring/installer_scoring/doctype/installer_scoring_sub_parameter_value_and_score/installer_scoring_sub_parameter_value_and_score.py

Manisvb123/TestAll

39fc4e59e1fe58e9778f57f9bbfcfd8e2555e938

[ "MIT" ]

null

# Copyright (c) 2021, mani.v@gmail.com and contributors # For license information, please see license.txt # import frappe from frappe.model.document import Document class InstallerScoringSubParameterValueandScore(Document): pass

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1

0

1

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6

d2238e7f4be6a0a7ebca49eb61c9c09919f05f0d

115

py

Python

QuickCoders/views.py

hpathipati/Quick-Tutor

17476d79b87f51b12a6c8fc435d1a6506bff1e04

[ "PostgreSQL", "Unlicense", "MIT" ]

null

QuickCoders/views.py

hpathipati/Quick-Tutor

17476d79b87f51b12a6c8fc435d1a6506bff1e04

[ "PostgreSQL", "Unlicense", "MIT" ]

null

QuickCoders/views.py

hpathipati/Quick-Tutor

17476d79b87f51b12a6c8fc435d1a6506bff1e04

[ "PostgreSQL", "Unlicense", "MIT" ]

null

from django.shortcuts import redirect, render def homepage(request): return render(request, 'study/home.html')

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1

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1

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6

968f657c4f13e635a498fb57cd2f6c0bf9f3b053

35

py

Python

src/lib/dis.py

DTenore/skulpt

098d20acfb088d6db85535132c324b7ac2f2d212

[ "MIT" ]

2,671

2015-01-03T08:23:25.000Z

2022-03-31T06:15:48.000Z

src/lib/dis.py

wakeupmuyunhe/skulpt

a8fb11a80fb6d7c016bab5dfe3712517a350b347

[ "MIT" ]

972

2015-01-05T08:11:00.000Z

2022-03-29T13:47:15.000Z

src/lib/dis.py

wakeupmuyunhe/skulpt

a8fb11a80fb6d7c016bab5dfe3712517a350b347

[ "MIT" ]

845

2015-01-03T19:53:36.000Z

2022-03-29T18:34:22.000Z

import _sk_fail; _sk_fail._("dis")

17.5

34

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6

35

3.5

0.666667

0.571429

0

0.085714

35

1

35

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1

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1

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6

96a030ae4b62523a577060ac279fb7753433f9f5

28

py

Python

skssl/meta/__init__.py

YannDubs/Semi-Supervised-Neural-Processes

77176131923817f3a165883dd6fca7b9f1e9d0b3

[ "MIT" ]

5

2019-06-19T11:11:56.000Z

2020-07-03T08:42:36.000Z

skssl/meta/__init__.py

YannDubs/Semi-Supervised-Neural-Processes

77176131923817f3a165883dd6fca7b9f1e9d0b3

[ "MIT" ]

null

skssl/meta/__init__.py

YannDubs/Semi-Supervised-Neural-Processes

77176131923817f3a165883dd6fca7b9f1e9d0b3

[ "MIT" ]

null

from .selftraining import *

14

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1

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0

1

0

1

0

6

73792c24fe46fc36ce796ed077332b0f6d4f0760

26

py

Python

hogwarts/utils/__init__.py

PingchuanMa/hogwarts

404e1d524fee4f190d8de1c1e8bc0711d895089a

[ "MIT" ]

4

2019-10-12T04:55:03.000Z

2019-11-25T22:30:41.000Z

hogwarts/utils/__init__.py

PingchuanMa/hogwarts

404e1d524fee4f190d8de1c1e8bc0711d895089a

[ "MIT" ]

null

hogwarts/utils/__init__.py

PingchuanMa/hogwarts

404e1d524fee4f190d8de1c1e8bc0711d895089a

[ "MIT" ]

null

from . import tensorboard

13

25

0.807692

3

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26

1

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1

0

null

0

1

0

1

0

1

0

6

739253a8461f536eb86edbee8c872a23faa56bb0

4,180

py

Python

applications/plot_data_paper2.py

RaulRPrado/tev-binaries-model

c60959caaffbcdf3398914b03531647f95e97da0

[ "Apache-2.0" ]

1

2020-06-03T15:39:38.000Z

applications/plot_data_paper2.py

RaulRPrado/tev-binaries-model

c60959caaffbcdf3398914b03531647f95e97da0

[ "Apache-2.0" ]

null

applications/plot_data_paper2.py

RaulRPrado/tev-binaries-model

c60959caaffbcdf3398914b03531647f95e97da0

[ "Apache-2.0" ]

null

#!/usr/bin/python3 import matplotlib.pyplot as plt import logging import math from astropy import units as u from tgblib import util from tgblib.data import get_data, get_data_ul logging.getLogger().setLevel(logging.INFO) if __name__ == '__main__': util.set_my_fonts(mode='talk') show = False label = 'std' NU_TITLE = { 0: 'Nu1a', 1: 'Nu1b', 2: 'Nu2a', 3: 'none', 4: 'Nu2b' } VTS_TITLE = { 0: 'Ve1a', 1: 'Ve1b', 2: 'Ve2a', 3: 'Ve2b', 4: 'Ve2c' } MARKERS = { 0: 'o', 1: 's', 2: 'o', 3: 's', 4: '*' } COLORS = { 0: 'k', 1: 'r', 2: 'k', 3: 'r', 4: 'b' } MINOR_TICK = 7.5 MAJOR_TICK = 12 keV_to_TeV = u.keV.to(u.TeV) # 2017 plt.figure(figsize=(8, 6), tight_layout=True) ax = plt.gca() ax.set_yscale('log') ax.set_xscale('log') ax.set_ylabel(r'$E^2\;\mathrm{d}N/\mathrm{d}E\;[\mathrm{erg\;s^{-1}\;cm^{-2}}]$') ax.set_xlabel(r'$E\;[\mathrm{TeV}]$') ax.tick_params(which='minor', length=MINOR_TICK) ax.tick_params(which='major', length=MAJOR_TICK) for nn, iper in enumerate([0, 1]): vtsEnergy, vtsFlux, vtsFluxErr = get_data(iper, onlyVTS=True, GT=True) vtsEnergyUL, vtsFluxUL = get_data_ul(iper, GT=True) ax.errorbar( [e * (1 + 0.02 * nn) * keV_to_TeV for e in vtsEnergy], vtsFlux, yerr=vtsFluxErr, color=COLORS[iper], linestyle='none', label=VTS_TITLE[iper], marker=MARKERS[iper] ) if len(vtsEnergyUL) > 0: vtsFluxErrUL = [p - pow(10, math.log10(p) - 0.1) for p in vtsFluxUL] ax.errorbar( [e * keV_to_TeV for e in vtsEnergyUL], vtsFluxUL, yerr=vtsFluxErrUL, uplims=True, color=COLORS[iper], linestyle='none', marker=MARKERS[iper] ) ax.set_ylim(0.8e-13, 5e-12) ax.set_xlim(3e-1, 2e1) myTicks = [1e0, 1e1] myLabels = [r'$10^{0}$', r'$10^{1}$'] ax.set_xticks(myTicks) ax.set_xticklabels(myLabels) ax.legend(loc='best', frameon=False) plt.savefig( 'figures/DataVTS_2017.png', format='png', bbox_inches='tight' ) plt.savefig( 'figures/DataVTS_2017.pdf', format='pdf', bbox_inches='tight' ) # 2019 plt.figure(figsize=(8, 6), tight_layout=True) ax = plt.gca() ax.set_yscale('log') ax.set_xscale('log') ax.set_ylabel(r'$E^2\;\mathrm{d}N/\mathrm{d}E\;[\mathrm{erg\;s^{-1}\;cm^{-2}}]$') ax.set_xlabel(r'$E\;[\mathrm{TeV}]$') ax.tick_params(which='minor', length=MINOR_TICK) ax.tick_params(which='major', length=MAJOR_TICK) for nn, iper in enumerate([2, 3, 4]): vtsEnergy, vtsFlux, vtsFluxErr = get_data(iper, onlyVTS=True) vtsEnergyUL, vtsFluxUL = get_data_ul(iper) ax.errorbar( [e * (1 + 0.02 * nn) * keV_to_TeV for e in vtsEnergy], vtsFlux, yerr=vtsFluxErr, color=COLORS[iper], linestyle='none', label=VTS_TITLE[iper], marker=MARKERS[iper] ) if len(vtsEnergyUL) > 0: vtsFluxErrUL = [p - pow(10, math.log10(p) - 0.1) for p in vtsFluxUL] ax.errorbar( [e * keV_to_TeV for e in vtsEnergyUL], vtsFluxUL, yerr=vtsFluxErrUL, uplims=True, color=COLORS[iper], linestyle='none', marker=MARKERS[iper] ) ax.set_ylim(0.8e-13, 5e-12) ax.set_xlim(3e-1, 2e1) myTicks = [1e0, 1e1] myLabels = [r'$10^{0}$', r'$10^{1}$'] ax.set_xticks(myTicks) ax.set_xticklabels(myLabels) ax.legend(loc='best', frameon=False) plt.savefig( 'figures/DataVTS_2019.png', format='png', bbox_inches='tight' ) plt.savefig( 'figures/DataVTS_2019.pdf', format='pdf', bbox_inches='tight' )

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6

fb4ab11cea1f2df276c4d6fd660056e068eff33a

14,976

py

Python

s3tests_boto3/functional/test_sts.py

TheRealGchen/s3-tests

67caf0f85489a50ef628aa1fd28cbea9be989bdd

[ "MIT" ]

null

s3tests_boto3/functional/test_sts.py

TheRealGchen/s3-tests

67caf0f85489a50ef628aa1fd28cbea9be989bdd

[ "MIT" ]

null

s3tests_boto3/functional/test_sts.py

TheRealGchen/s3-tests

67caf0f85489a50ef628aa1fd28cbea9be989bdd

[ "MIT" ]

2

2021-06-23T16:09:24.000Z

2021-10-01T17:00:42.000Z

import boto3 import botocore.session from botocore.exceptions import ClientError from botocore.exceptions import ParamValidationError from nose.tools import eq_ as eq from nose.plugins.attrib import attr from nose.plugins.skip import SkipTest import isodate import email.utils import datetime import threading import re import pytz from collections import OrderedDict import requests import json import base64 import hmac import hashlib import xml.etree.ElementTree as ET import time import operator import nose import os import string import random import socket import ssl import logging from collections import namedtuple from email.header import decode_header from . import( get_iam_client, get_sts_client, get_client, get_alt_user_id, get_config_endpoint, get_new_bucket_name, get_parameter_name, get_main_aws_access_key, get_main_aws_secret_key, get_thumbprint, get_aud, get_token, get_realm_name, check_webidentity ) log = logging.getLogger(__name__) def create_role(iam_client,path,rolename,policy_document,description,sessionduration,permissionboundary): role_err=None if rolename is None: rolename=get_parameter_name() try: role_response = iam_client.create_role(Path=path,RoleName=rolename,AssumeRolePolicyDocument=policy_document,) except ClientError as e: role_err = e.response['Code'] return (role_err,role_response,rolename) def put_role_policy(iam_client,rolename,policyname,role_policy): role_err=None if policyname is None: policyname=get_parameter_name() try: role_response = iam_client.put_role_policy(RoleName=rolename,PolicyName=policyname,PolicyDocument=role_policy) except ClientError as e: role_err = e.response['Code'] return (role_err,role_response) def put_user_policy(iam_client,username,policyname,policy_document): role_err=None if policyname is None: policyname=get_parameter_name() try: role_response = iam_client.put_user_policy(UserName=username,PolicyName=policyname,PolicyDocument=policy_document) except ClientError as e: role_err = e.response['Code'] return (role_err,role_response) @attr(resource='get session token') @attr(method='get') @attr(operation='check') @attr(assertion='s3 ops only accessible by temporary credentials') @attr('test_of_sts') def test_get_session_token(): iam_client=get_iam_client() sts_client=get_sts_client() sts_user_id=get_alt_user_id() default_endpoint=get_config_endpoint() user_policy = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Deny\",\"Action\":\"s3:*\",\"Resource\":[\"*\"],\"Condition\":{\"BoolIfExists\":{\"sts:authentication\":\"false\"}}},{\"Effect\":\"Allow\",\"Action\":\"sts:GetSessionToken\",\"Resource\":\"*\",\"Condition\":{\"BoolIfExists\":{\"sts:authentication\":\"false\"}}}]}" (resp_err,resp)=put_user_policy(iam_client,sts_user_id,None,user_policy) eq(resp['ResponseMetadata']['HTTPStatusCode'],200) response=sts_client.get_session_token() eq(response['ResponseMetadata']['HTTPStatusCode'],200) s3_client=boto3.client('s3', aws_access_key_id = response['Credentials']['AccessKeyId'], aws_secret_access_key = response['Credentials']['SecretAccessKey'], aws_session_token = response['Credentials']['SessionToken'], endpoint_url=default_endpoint, region_name='', ) bucket_name = get_new_bucket_name() s3bucket = s3_client.create_bucket(Bucket=bucket_name) eq(s3bucket['ResponseMetadata']['HTTPStatusCode'],200) finish=s3_client.delete_bucket(Bucket=bucket_name) @attr(resource='get session token') @attr(method='get') @attr(operation='check') @attr(assertion='s3 ops denied by permanent credentials') @attr('test_of_sts') def test_get_session_token_permanent_creds_denied(): s3bucket_error=None iam_client=get_iam_client() sts_client=get_sts_client() sts_user_id=get_alt_user_id() default_endpoint=get_config_endpoint() s3_main_access_key=get_main_aws_access_key() s3_main_secret_key=get_main_aws_secret_key() user_policy = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Deny\",\"Action\":\"s3:*\",\"Resource\":[\"*\"],\"Condition\":{\"BoolIfExists\":{\"sts:authentication\":\"false\"}}},{\"Effect\":\"Allow\",\"Action\":\"sts:GetSessionToken\",\"Resource\":\"*\",\"Condition\":{\"BoolIfExists\":{\"sts:authentication\":\"false\"}}}]}" (resp_err,resp)=put_user_policy(iam_client,sts_user_id,None,user_policy) eq(resp['ResponseMetadata']['HTTPStatusCode'],200) response=sts_client.get_session_token() eq(response['ResponseMetadata']['HTTPStatusCode'],200) s3_client=boto3.client('s3', aws_access_key_id = s3_main_access_key, aws_secret_access_key = s3_main_secret_key, aws_session_token = response['Credentials']['SessionToken'], endpoint_url=default_endpoint, region_name='', ) bucket_name = get_new_bucket_name() try: s3bucket = s3_client.create_bucket(Bucket=bucket_name) except ClientError as e: s3bucket_error = e.response.get("Error", {}).get("Code") eq(s3bucket_error,'AccessDenied') @attr(resource='assume role') @attr(method='get') @attr(operation='check') @attr(assertion='role policy allows all s3 ops') @attr('test_of_sts') def test_assume_role_allow(): iam_client=get_iam_client() sts_client=get_sts_client() sts_user_id=get_alt_user_id() default_endpoint=get_config_endpoint() role_session_name=get_parameter_name() policy_document = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Allow\",\"Principal\":{\"AWS\":[\"arn:aws:iam:::user/"+sts_user_id+"\"]},\"Action\":[\"sts:AssumeRole\"]}]}" (role_error,role_response,general_role_name)=create_role(iam_client,'/',None,policy_document,None,None,None) eq(role_response['Role']['Arn'],'arn:aws:iam:::role/'+general_role_name+'') role_policy = "{\"Version\":\"2012-10-17\",\"Statement\":{\"Effect\":\"Allow\",\"Action\":\"s3:*\",\"Resource\":\"arn:aws:s3:::*\"}}" (role_err,response)=put_role_policy(iam_client,general_role_name,None,role_policy) eq(response['ResponseMetadata']['HTTPStatusCode'],200) resp=sts_client.assume_role(RoleArn=role_response['Role']['Arn'],RoleSessionName=role_session_name) eq(resp['ResponseMetadata']['HTTPStatusCode'],200) s3_client = boto3.client('s3', aws_access_key_id = resp['Credentials']['AccessKeyId'], aws_secret_access_key = resp['Credentials']['SecretAccessKey'], aws_session_token = resp['Credentials']['SessionToken'], endpoint_url=default_endpoint, region_name='', ) bucket_name = get_new_bucket_name() s3bucket = s3_client.create_bucket(Bucket=bucket_name) eq(s3bucket['ResponseMetadata']['HTTPStatusCode'],200) bkt = s3_client.delete_bucket(Bucket=bucket_name) eq(bkt['ResponseMetadata']['HTTPStatusCode'],204) @attr(resource='assume role') @attr(method='get') @attr(operation='check') @attr(assertion='role policy denies all s3 ops') @attr('test_of_sts') def test_assume_role_deny(): s3bucket_error=None iam_client=get_iam_client() sts_client=get_sts_client() sts_user_id=get_alt_user_id() default_endpoint=get_config_endpoint() role_session_name=get_parameter_name() policy_document = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Allow\",\"Principal\":{\"AWS\":[\"arn:aws:iam:::user/"+sts_user_id+"\"]},\"Action\":[\"sts:AssumeRole\"]}]}" (role_error,role_response,general_role_name)=create_role(iam_client,'/',None,policy_document,None,None,None) eq(role_response['Role']['Arn'],'arn:aws:iam:::role/'+general_role_name+'') role_policy = "{\"Version\":\"2012-10-17\",\"Statement\":{\"Effect\":\"Deny\",\"Action\":\"s3:*\",\"Resource\":\"arn:aws:s3:::*\"}}" (role_err,response)=put_role_policy(iam_client,general_role_name,None,role_policy) eq(response['ResponseMetadata']['HTTPStatusCode'],200) resp=sts_client.assume_role(RoleArn=role_response['Role']['Arn'],RoleSessionName=role_session_name) eq(resp['ResponseMetadata']['HTTPStatusCode'],200) s3_client = boto3.client('s3', aws_access_key_id = resp['Credentials']['AccessKeyId'], aws_secret_access_key = resp['Credentials']['SecretAccessKey'], aws_session_token = resp['Credentials']['SessionToken'], endpoint_url=default_endpoint, region_name='', ) bucket_name = get_new_bucket_name() try: s3bucket = s3_client.create_bucket(Bucket=bucket_name) except ClientError as e: s3bucket_error = e.response.get("Error", {}).get("Code") eq(s3bucket_error,'AccessDenied') @attr(resource='assume role') @attr(method='get') @attr(operation='check') @attr(assertion='creds expire so all s3 ops fails') @attr('test_of_sts') def test_assume_role_creds_expiry(): iam_client=get_iam_client() sts_client=get_sts_client() sts_user_id=get_alt_user_id() default_endpoint=get_config_endpoint() role_session_name=get_parameter_name() policy_document = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Allow\",\"Principal\":{\"AWS\":[\"arn:aws:iam:::user/"+sts_user_id+"\"]},\"Action\":[\"sts:AssumeRole\"]}]}" (role_error,role_response,general_role_name)=create_role(iam_client,'/',None,policy_document,None,None,None) eq(role_response['Role']['Arn'],'arn:aws:iam:::role/'+general_role_name+'') role_policy = "{\"Version\":\"2012-10-17\",\"Statement\":{\"Effect\":\"Allow\",\"Action\":\"s3:*\",\"Resource\":\"arn:aws:s3:::*\"}}" (role_err,response)=put_role_policy(iam_client,general_role_name,None,role_policy) eq(response['ResponseMetadata']['HTTPStatusCode'],200) resp=sts_client.assume_role(RoleArn=role_response['Role']['Arn'],RoleSessionName=role_session_name,DurationSeconds=900) eq(resp['ResponseMetadata']['HTTPStatusCode'],200) time.sleep(900) s3_client = boto3.client('s3', aws_access_key_id = resp['Credentials']['AccessKeyId'], aws_secret_access_key = resp['Credentials']['SecretAccessKey'], aws_session_token = resp['Credentials']['SessionToken'], endpoint_url=default_endpoint, region_name='', ) bucket_name = get_new_bucket_name() try: s3bucket = s3_client.create_bucket(Bucket=bucket_name) except ClientError as e: s3bucket_error = e.response.get("Error", {}).get("Code") eq(s3bucket_error,'AccessDenied') @attr(resource='assume role with web identity') @attr(method='get') @attr(operation='check') @attr(assertion='assuming role through web token') @attr('webidentity_test') def test_assume_role_with_web_identity(): check_webidentity() iam_client=get_iam_client() sts_client=get_sts_client() default_endpoint=get_config_endpoint() role_session_name=get_parameter_name() thumbprint=get_thumbprint() aud=get_aud() token=get_token() realm=get_realm_name() oidc_response = iam_client.create_open_id_connect_provider( Url='http://localhost:8080/auth/realms/{}'.format(realm), ThumbprintList=[ thumbprint, ], ) policy_document = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Allow\",\"Principal\":{\"Federated\":[\""+oidc_response["OpenIDConnectProviderArn"]+"\"]},\"Action\":[\"sts:AssumeRoleWithWebIdentity\"],\"Condition\":{\"StringEquals\":{\"localhost:8080/auth/realms/"+realm+":app_id\":\""+aud+"\"}}}]}" (role_error,role_response,general_role_name)=create_role(iam_client,'/',None,policy_document,None,None,None) eq(role_response['Role']['Arn'],'arn:aws:iam:::role/'+general_role_name+'') role_policy = "{\"Version\":\"2012-10-17\",\"Statement\":{\"Effect\":\"Allow\",\"Action\":\"s3:*\",\"Resource\":\"arn:aws:s3:::*\"}}" (role_err,response)=put_role_policy(iam_client,general_role_name,None,role_policy) eq(response['ResponseMetadata']['HTTPStatusCode'],200) resp=sts_client.assume_role_with_web_identity(RoleArn=role_response['Role']['Arn'],RoleSessionName=role_session_name,WebIdentityToken=token) eq(resp['ResponseMetadata']['HTTPStatusCode'],200) s3_client = boto3.client('s3', aws_access_key_id = resp['Credentials']['AccessKeyId'], aws_secret_access_key = resp['Credentials']['SecretAccessKey'], aws_session_token = resp['Credentials']['SessionToken'], endpoint_url=default_endpoint, region_name='', ) bucket_name = get_new_bucket_name() s3bucket = s3_client.create_bucket(Bucket=bucket_name) eq(s3bucket['ResponseMetadata']['HTTPStatusCode'],200) bkt = s3_client.delete_bucket(Bucket=bucket_name) eq(bkt['ResponseMetadata']['HTTPStatusCode'],204) oidc_remove=iam_client.delete_open_id_connect_provider( OpenIDConnectProviderArn=oidc_response["OpenIDConnectProviderArn"] ) ''' @attr(resource='assume role with web identity') @attr(method='get') @attr(operation='check') @attr(assertion='assume_role_with_web_token creds expire') @attr('webidentity_test') def test_assume_role_with_web_identity_invalid_webtoken(): resp_error=None iam_client=get_iam_client() sts_client=get_sts_client() default_endpoint=get_config_endpoint() role_session_name=get_parameter_name() thumbprint=get_thumbprint() aud=get_aud() token=get_token() realm=get_realm_name() oidc_response = iam_client.create_open_id_connect_provider( Url='http://localhost:8080/auth/realms/{}'.format(realm), ThumbprintList=[ thumbprint, ], ) policy_document = "{\"Version\":\"2012-10-17\",\"Statement\":[{\"Effect\":\"Allow\",\"Principal\":{\"Federated\":[\""+oidc_response["OpenIDConnectProviderArn"]+"\"]},\"Action\":[\"sts:AssumeRoleWithWebIdentity\"],\"Condition\":{\"StringEquals\":{\"localhost:8080/auth/realms/"+realm+":app_id\":\""+aud+"\"}}}]}" (role_error,role_response,general_role_name)=create_role(iam_client,'/',None,policy_document,None,None,None) eq(role_response['Role']['Arn'],'arn:aws:iam:::role/'+general_role_name+'') role_policy = "{\"Version\":\"2012-10-17\",\"Statement\":{\"Effect\":\"Allow\",\"Action\":\"s3:*\",\"Resource\":\"arn:aws:s3:::*\"}}" (role_err,response)=put_role_policy(iam_client,general_role_name,None,role_policy) eq(response['ResponseMetadata']['HTTPStatusCode'],200) resp="" try: resp=sts_client.assume_role_with_web_identity(RoleArn=role_response['Role']['Arn'],RoleSessionName=role_session_name,WebIdentityToken='abcdef') except InvalidIdentityTokenException as e: log.debug('{}'.format(resp)) log.debug('{}'.format(e.response.get("Error", {}).get("Code"))) log.debug('{}'.format(e)) resp_error = e.response.get("Error", {}).get("Code") eq(resp_error,'AccessDenied') oidc_remove=iam_client.delete_open_id_connect_provider( OpenIDConnectProviderArn=oidc_response["OpenIDConnectProviderArn"] ) '''

41.94958

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14,976

5.432505

0.102052

0.033098

0.05248

0.017891

0.844946

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0.815426

0.811848

0.801809

0

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0.116119

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0.741935

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0.014652

0

null

0

1

0

null

0

6

fb61153d6890ae1969964e8e7074586cfa3bb578

1,901

py

Python

test/test_mice.py

drkarthi/fancyimpute

f89df71bc7253057aea9ac27f397a4af26579836

[ "Apache-2.0" ]

null

test/test_mice.py

drkarthi/fancyimpute

f89df71bc7253057aea9ac27f397a4af26579836

[ "Apache-2.0" ]

null

test/test_mice.py

drkarthi/fancyimpute

f89df71bc7253057aea9ac27f397a4af26579836

[ "Apache-2.0" ]

null

from fancyimpute import MICE from low_rank_data import XY, XY_incomplete, missing_mask from common import reconstruction_error def test_mice_column_with_low_rank_random_matrix(): mice = MICE(n_imputations=100, impute_type='col') XY_completed = mice.complete(XY_incomplete) _, missing_mae = reconstruction_error( XY, XY_completed, missing_mask, name="MICE (impute_type=col)") assert missing_mae < 0.1, "Error too high with column method!" def test_mice_row_with_low_rank_random_matrix(): mice = MICE(n_imputations=100, impute_type='pmm') XY_completed = mice.complete(XY_incomplete) _, missing_mae = reconstruction_error( XY, XY_completed, missing_mask, name="MICE (impute_type=row)") assert missing_mae < 0.1, "Error too high with PMM method!" def test_mice_column_with_low_rank_random_matrix_approximate(): mice = MICE(n_imputations=100, impute_type='col', n_nearest_columns=5) XY_completed = mice.complete(XY_incomplete) _, missing_mae = reconstruction_error( XY, XY_completed, missing_mask, name="MICE (impute_type=col)") assert missing_mae < 0.1, "Error too high with approximate column method!" def test_mice_row_with_low_rank_random_matrix_approximate(): mice = MICE(n_imputations=100, impute_type='pmm', n_nearest_columns=5) XY_completed = mice.complete(XY_incomplete) _, missing_mae = reconstruction_error( XY, XY_completed, missing_mask, name="MICE (impute_type=row)") assert missing_mae < 0.1, "Error too high with approximate PMM method!" if __name__ == "__main__": test_mice_column_with_low_rank_random_matrix() test_mice_row_with_low_rank_random_matrix() test_mice_column_with_low_rank_random_matrix_approximate() test_mice_row_with_low_rank_random_matrix_approximate()

33.946429

78

0.730668

260

1,901

4.876923

0.169231

0.049685

0.069401

0.107256

0.894322

0.828864

0.728707

0

0.014249

0.187796

1,901

55

79

34.563636

0.806995

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0.545455

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0.137822

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0

0.159091

0

null

0

1

0

null

0

6

fb68719b6dcde4eb60da15aa4735aa5c76592150

243

py

Python

winter_ddd/__init__.py

zhukovqs/winter

20c361f29f89ffa0dc27501e12df8ef6e22a8e4c

[ "MIT" ]

9

2019-01-24T11:50:19.000Z

2019-07-05T07:58:46.000Z

winter_ddd/__init__.py

zhukovqs/winter

20c361f29f89ffa0dc27501e12df8ef6e22a8e4c

[ "MIT" ]

100

2019-01-29T08:11:38.000Z

2020-04-03T12:00:42.000Z

winter_ddd/__init__.py

zhukovqs/winter

20c361f29f89ffa0dc27501e12df8ef6e22a8e4c

[ "MIT" ]

8

2020-07-16T13:56:50.000Z

2021-12-27T03:33:23.000Z

from .aggregate_root import AggregateRoot from .domain_event import DomainEvent from .domain_event_dispatcher import global_domain_event_dispatcher from .domain_event_handler import domain_event_handler from .domain_events import DomainEvents

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6.4375

0.40625

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0.218447

0

0.082305

243

5

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null

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null

0

1

0

1

0

1

0

6

fb9f75f2e8a4372fcd7438f0866036a2eb9346c6

3,065

py

Python

source-code.py

eberkeaydin/dijkstra-graph

4208a4c311d7668fcd1daa4ef24a6acc2a951987

[ "MIT" ]

null

source-code.py

eberkeaydin/dijkstra-graph

4208a4c311d7668fcd1daa4ef24a6acc2a951987

[ "MIT" ]

null

source-code.py

eberkeaydin/dijkstra-graph

4208a4c311d7668fcd1daa4ef24a6acc2a951987

[ "MIT" ]

null

import networkx as netx import matplotlib.pyplot as plt graph=netx.DiGraph() graph.add_node(0) graph.add_node(1) graph.add_node(2) graph.add_node(3) graph.add_node(4) graph.nodes[0]['pos']=(0,4) graph.nodes[1]['pos']=(3,2.5) graph.nodes[2]['pos']=(2,0) graph.nodes[3]['pos']=(-2,0) graph.nodes[4]['pos']=(-3,2.5) graph.add_edge(0,1,weight=5) graph.add_edge(0,2,weight=3) graph.add_edge(0,4,weight=2) graph.add_edge(1,2,weight=2) graph.add_edge(1,3,weight=6) graph.add_edge(2,1,weight=1) graph.add_edge(2,3,weight=2) graph.add_edge(4,1,weight=6) graph.add_edge(4,2,weight=10) graph.add_edge(4,3,weight=4) node_pos=netx.get_node_attributes(graph,'pos') arc_weight=netx.get_edge_attributes(graph,'weight') netx.draw_networkx(graph, node_pos, node_size=450) netx.draw_networkx_edges(graph, node_pos,edge_color= 'black') netx.draw_networkx_edge_labels(graph, node_pos,label_pos=0.3, edge_labels=arc_weight) plt.axis('off') plt.show() print("There is no way to nodes from 4. node.") uzunluk1=0 uzunluk2=0 uzunluk3=0 dortten_bire = netx.dijkstra_path(graph,source=4,target=1) print("\nShortest path(4,1):",end="") print(dortten_bire) temp=4 for integer in dortten_bire: if integer==4: continue else: uzunluk1+=arc_weight[(temp,integer)] temp=integer print("Shortest path length(4,1):",uzunluk1) dortten_ikiye=netx.dijkstra_path(graph,source=4,target=2) print("\nShortest path(4,2):",end="") print(dortten_ikiye) temp=4 for integer in dortten_ikiye: if integer==4: continue else: uzunluk2+=arc_weight[(temp,integer)] temp=integer print("Shortest path length(4,2):",uzunluk2) dortten_uce=netx.dijkstra_path(graph,source=4,target=3) print("\nShortest path(4,3):",end="") print(dortten_uce) temp=4 for integer in dortten_uce: if integer==4: continue else: uzunluk3+=arc_weight[(temp,integer)] temp=integer print("Shortest path length(4,3):",uzunluk3) print("##################################################") graph.remove_node(3) node_pos=netx.get_node_attributes(graph,'pos') arc_weight=netx.get_edge_attributes(graph,'weight') netx.draw_networkx(graph, node_pos, node_size=450) netx.draw_networkx_edges(graph, node_pos,edge_color= 'black') netx.draw_networkx_edge_labels(graph, node_pos,label_pos=0.3, edge_labels=arc_weight) plt.axis('off') plt.show() print("There is no way to 0 from 4. node") uzunluk1=0 uzunluk2=0 uzunluk3=0 dortten_bire=netx.dijkstra_path(graph,source=4,target=1) print("\nShortest path(4,1):",end="") print(dortten_bire) temp=4 for integer in dortten_bire: if integer==4: continue else: uzunluk1+=arc_weight[(temp,integer)] temp=integer print("Shortest path length(4,1):",uzunluk1) dortten_ikiye=netx.dijkstra_path(graph,source=4,target=2) print("\nShortest path(4,2):",end="") print(dortten_ikiye) temp=4 for integer in dortten_ikiye: if integer==4: continue else: uzunluk2+=arc_weight[(temp,integer)] temp=integer print("Shortest path length(4,2):",uzunluk2) input()

24.717742

85

0.709951

509

3,065

4.115914

0.133595

0.057279

0.050119

0.832458

0.759427

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3,065

123

86

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0.725194

0

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0

0.132613

0.016372

0

1

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false

0

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0

0.019417

0.174757

0

null

0

1

0

null

0

6

8380609679d9bfa4892139ddeca0602c8f1071a2

112

py

Python

docs/source/working/include/snippets/processes/functions/signature_plain_python_call_default.py

pranavmodx/aiida-core

0edbbf82dfb97ab130914d1674a6f2217eba5971

[ "BSD-2-Clause", "MIT" ]

1

2019-07-31T04:08:13.000Z

docs/source/working/include/snippets/processes/functions/signature_plain_python_call_default.py

odarbelaeze/aiida_core

934b4ccdc73a993f2a6656caf516500470e3da08

[ "BSD-2-Clause" ]

null

docs/source/working/include/snippets/processes/functions/signature_plain_python_call_default.py

odarbelaeze/aiida_core

934b4ccdc73a993f2a6656caf516500470e3da08

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python def add_multiply(x, y, z=1): return (x + y) * z add_multiply(1, 2) # x=1, y=2, z=1

16

35

0.5625

25

112

2.44

0.52

0.360656

0.098361

0

0.068966

0.223214

112

6

36

18.666667

0.632184

0.303571

0

1

0.333333

false

0

0.333333

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

838c2bace5e78b6fcf465bb33012058e19d06ba5

235

py

Python

effdet/__init__.py

Jay9z/gwhd_efficentdet

2ee45a51172faa9fc448d4ee4cd3931eaaa87c53

[ "Apache-2.0" ]

null

effdet/__init__.py

Jay9z/gwhd_efficentdet

2ee45a51172faa9fc448d4ee4cd3931eaaa87c53

[ "Apache-2.0" ]

null

effdet/__init__.py

Jay9z/gwhd_efficentdet

2ee45a51172faa9fc448d4ee4cd3931eaaa87c53

[ "Apache-2.0" ]

null

from .efficientdet import EfficientDet from .bench import DetBenchEval, DetBenchTrain #from .config.config import get_efficientdet_config from .config import get_efficientdet_config from .helpers import load_checkpoint, load_pretrained

47

53

0.87234

29

235

6.862069

0.413793

0.100503

0.150754

0.271357

0.371859

0

0.089362

235

5

53

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0.929907

0.212766

0

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true

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null

0

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1

0

null

0

1

0

1

0

1

0

6

83908d395811dd55647f059eb45b14cab1dbc558

84

py

Python

payments/tests/__init__.py

Elijah-glitch/Hey

00c09a0c8bfa9868d8048f697b36849569f9e127

[ "MIT" ]

25

2016-07-14T06:16:17.000Z

2021-12-21T06:52:42.000Z

payments/tests/__init__.py

Elijah-glitch/Hey

00c09a0c8bfa9868d8048f697b36849569f9e127

[ "MIT" ]

4

2017-11-29T20:20:30.000Z

2017-12-01T00:04:29.000Z

payments/tests/__init__.py

Elijah-glitch/Hey

00c09a0c8bfa9868d8048f697b36849569f9e127

[ "MIT" ]

5

2016-07-19T18:26:24.000Z

2020-05-31T18:40:15.000Z

# flake8: noqa from .bitcoin import * from .paypal import * from .stripe import *

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py

Python

naf2conll/naf2conll/__main__.py

Filter-Bubble/FormatConversions

91c313d66edba077462740c1403a705aa1f96df4

[ "Apache-2.0" ]

3

2019-11-21T13:43:37.000Z

2021-05-12T20:46:49.000Z

naf2conll/naf2conll/__main__.py

Filter-Bubble/FormatConversions

91c313d66edba077462740c1403a705aa1f96df4

[ "Apache-2.0" ]

3

2018-05-22T13:07:43.000Z

2020-03-14T17:31:15.000Z

naf2conll/naf2conll/__main__.py

Filter-Bubble/FormatConversions

91c313d66edba077462740c1403a705aa1f96df4

[ "Apache-2.0" ]

2

2020-03-05T15:55:47.000Z

2021-05-12T20:46:50.000Z

from .main import Main Main.main()

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83f54030d300d5175c80417b42d2cd1a74e5099f

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py

Python

Python/packages/databricks-test/tests/library_test.py

anandmrya/DataOps

1a671c707e27b30030687a2a88e5fa94374ce780

[ "MIT" ]

42

2019-12-04T04:10:53.000Z

2022-03-31T13:04:17.000Z

Python/packages/databricks-test/tests/library_test.py

anandmrya/DataOps

1a671c707e27b30030687a2a88e5fa94374ce780

[ "MIT" ]

2

2020-02-25T11:24:34.000Z

2020-03-05T06:12:59.000Z

Python/packages/databricks-test/tests/library_test.py

anandmrya/DataOps

1a671c707e27b30030687a2a88e5fa94374ce780

[ "MIT" ]

18

2020-01-25T06:25:08.000Z

2021-11-16T08:40:09.000Z

import databricks_test def test_library(): with databricks_test.session() as dbrickstest: # Run notebook dbrickstest.run_notebook(".", "library_notebook")

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f7c0b8dc42c03443b567c05ec27bebae83f29cd8

171

py

Python

detection.py

devSeungGwan/CSI-Camera

9fa5b01511153959a30ef7d4ab375dba3897d21f

[ "BSD-3-Clause" ]

null

detection.py

devSeungGwan/CSI-Camera

9fa5b01511153959a30ef7d4ab375dba3897d21f

[ "BSD-3-Clause" ]

null

detection.py

devSeungGwan/CSI-Camera

9fa5b01511153959a30ef7d4ab375dba3897d21f

[ "BSD-3-Clause" ]

null

import capture from face_detection import face_detection if __name__ == "__main__": face = face_detection() cam = capture.cam() face.detection(cam.capture())

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6

792375712560b837a3f3607bd6e18617500b6a9c

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py

Python

src/Fig_6_supplement_1_Plotting.py

fmi-basel/gzenke-nonlinear-transient-amplification

f3b0c8c89b42c34f1aad740c7026865cf3164f1d

[ "MIT" ]

null

src/Fig_6_supplement_1_Plotting.py

fmi-basel/gzenke-nonlinear-transient-amplification

f3b0c8c89b42c34f1aad740c7026865cf3164f1d

[ "MIT" ]

3

2021-12-16T10:15:10.000Z

2021-12-16T12:54:24.000Z

src/Fig_6_supplement_1_Plotting.py

fmi-basel/gzenke-nonlinear-transient-amplification

f3b0c8c89b42c34f1aad740c7026865cf3164f1d

[ "MIT" ]

1

2021-12-16T10:02:43.000Z

import numpy as np import seaborn as sns import matplotlib.pyplot as plt from matplotlib import patches import matplotlib.patches as mpatches import scipy.io as sio # plotting configuration ratio = 1.5 figure_len, figure_width = 15*ratio, 12*ratio font_size_1, font_size_2 = 36*ratio, 36*ratio legend_size = 18*ratio line_width, tick_len = 3*ratio, 10*ratio marker_size = 15*ratio marker_edge_width = 3 * ratio plot_line_width = 5*ratio hfont = {'fontname': 'Arial'} ratio_80, ratio_85, ratio_90, ratio_95, ratio_100, ratio_105, ratio_110, ratio_115, ratio_120, ratio_125, ratio_130, ratio_135, ratio_140 = [], [], [], [], [], [], [], [], [], [], [], [], [] n_loop = 20 for loop_idx in range(n_loop): bs_80 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_80_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_80 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_80_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_85 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_85_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_85 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_85_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_90 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_90_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_90 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_90_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_95 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_95_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_95 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_95_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_100 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_100_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_100 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_100_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_105 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_105_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_105 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_105_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_110 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_110_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_110 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_110_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_115 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_115_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_115 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_115_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_120 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_120_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_120 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_120_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_125 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_125_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_125 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_125_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_130 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_130_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_130 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_130_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_135 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_135_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_135 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_135_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] bs_140 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_bl_firing_amp_140_' + str( loop_idx) + '.mat')['mean_bl_firing_4_2'][0] ss_140 = sio.loadmat( 'data_sum/spiking_neural_network/Revision_Fig_Point_1_2_Spiking_neural_networks_EE_STP_total_mean_ss_firing_amp_140_' + str( loop_idx) + '.mat')['mean_ss_firing_4_2'][0] ratio_80.append(ss_80 / bs_80) ratio_85.append(ss_85 / bs_85) ratio_90.append(ss_90 / bs_90) ratio_95.append(ss_95 / bs_95) ratio_100.append(ss_100 / bs_100) ratio_105.append(ss_105 / bs_105) ratio_110.append(ss_110 / bs_110) ratio_115.append(ss_115 / bs_115) ratio_120.append(ss_120 / bs_120) ratio_125.append(ss_125 / bs_125) ratio_130.append(ss_130 / bs_130) ratio_135.append(ss_135 / bs_135) ratio_140.append(ss_140 / bs_140) # plotting plt.figure(figsize=(figure_len, figure_width)) ax = plt.gca() ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.spines['bottom'].set_visible(True) ax.spines['left'].set_visible(True) for axis in ['top', 'bottom', 'left', 'right']: ax.spines[axis].set_linewidth(line_width) plt.tick_params(width=line_width, length=tick_len) # plt.yscale('symlog', linthreshy=1) # sns.boxplot(data=[ratio_80, ratio_85, ratio_90, ratio_95, ratio_100, ratio_105, ratio_110, ratio_115, ratio_120, ratio_125, ratio_130, ratio_135, ratio_140], width=0.4, linewidth=line_width) ax = sns.boxplot(data=[ratio_80, ratio_90, ratio_100, ratio_110, ratio_120, ratio_130, ratio_140], width=0.45, linewidth=line_width, color='white') # , showfliers = False) print(len(ax.lines)) # iterate over boxes for m, box in enumerate(ax.artists): print(m) box.set_edgecolor('black') box.set_facecolor('white') # iterate over whiskers and median lines for j in range(6 * m, 6 * (m + 1)): # print(j) ax.lines[j].set_color('black') # plot the data points for i in range(len(ratio_80)): if i % 2 == 0: plt.plot(0 - 0.1, ratio_80[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(0 + 0.1, ratio_80[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') # for i in range(len(ratio_85)): # if i%2 == 0: # plt.plot(1 - 0.1, ratio_85[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') # else: # plt.plot(1 + 0.1, ratio_85[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') for i in range(len(ratio_90)): if i % 2 == 0: plt.plot(1 - 0.1, ratio_90[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(1 + 0.1, ratio_90[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') # for i in range(len(ratio_95)): # if i%2 == 0: # plt.plot(3 - 0.1, ratio_95[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') # else: # plt.plot(3 + 0.1, ratio_95[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') for i in range(len(ratio_100)): if i % 2 == 0: plt.plot(2 - 0.1, ratio_100[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(2 + 0.1, ratio_100[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') # for i in range(len(ratio_105)): # if i%2 == 0: # plt.plot(5 - 0.1, ratio_105[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') # else: # plt.plot(5 + 0.1, ratio_105[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') for i in range(len(ratio_110)): if i % 2 == 0: plt.plot(3 - 0.1, ratio_110[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(3 + 0.1, ratio_110[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') # for i in range(len(ratio_115)): # if i%2 == 0: # plt.plot(7 - 0.1, ratio_115[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') # else: # plt.plot(7 + 0.1, ratio_115[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') for i in range(len(ratio_120)): if i % 2 == 0: plt.plot(4 - 0.1, ratio_120[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(4 + 0.1, ratio_120[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') # for i in range(len(ratio_125)): # if i%2 == 0: # plt.plot(9 - 0.1, ratio_125[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') # else: # plt.plot(9 + 0.1, ratio_125[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') for i in range(len(ratio_130)): if i % 2 == 0: plt.plot(5 - 0.1, ratio_130[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(5 + 0.1, ratio_130[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') # for i in range(len(ratio_135)): # if i%2 == 0: # plt.plot(11 - 0.1, ratio_135[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') # else: # plt.plot(11 + 0.1, ratio_135[i], linestyle='none', marker='o', fillstyle='full', # markeredgewidth=marker_edge_width, markersize=marker_size, # markeredgecolor='black', markerfacecolor='none') for i in range(len(ratio_140)): if i % 2 == 0: plt.plot(6 - 0.1, ratio_140[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') else: plt.plot(6 + 0.1, ratio_140[i], linestyle='none', marker='o', fillstyle='full', markeredgewidth=marker_edge_width, markersize=marker_size, markeredgecolor='black', markerfacecolor='none') plt.xticks([0, 2, 4, 6], ['8/30', '10/30', '12/30', '14/30'], fontsize=font_size_1, **hfont) # plt.xticks([0, 1, 2, 3], ['8/30', '8.5/30', '9/30', '10/30'], fontsize=font_size_1, **hfont) plt.yticks([0, 1, 2, 3, 4, 5], fontsize=font_size_1, **hfont) plt.xlabel('Feedforward input', fontsize=font_size_1, **hfont) plt.ylabel('Fixed point to baseline ratio', fontsize=font_size_1, **hfont) plt.xlim([-0.5, 6.5]) # plt.xlim([-0.5, 12.5]) plt.ylim([0, 5]) plt.hlines(y=1, xmin=-0.5, xmax=6.5, colors='k', linestyles=[(0, (6, 6, 6, 6))], linewidth=line_width) plt.savefig('paper_figures/png/Revision_Fig_Point_1_2_Unstimulated_cotuned_neuron_SNN.png') plt.savefig('paper_figures/pdf/Revision_Fig_Point_1_2_Unstimulated_cotuned_neuron_SNN.pdf')

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131

py

Python

app/repositories/__init__.py

VadymHutei/ukubuka-back

acd56c545b50fb65ed764c19bdd03a42be969ce4

[ "MIT" ]

null

app/repositories/__init__.py

VadymHutei/ukubuka-back

acd56c545b50fb65ed764c19bdd03a42be969ce4

[ "MIT" ]

null

app/repositories/__init__.py

VadymHutei/ukubuka-back

acd56c545b50fb65ed764c19bdd03a42be969ce4

[ "MIT" ]

null

from repositories.category import CategoryRepo from repositories.product import ProductRepo from repositories.menu import MenuRepo

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f75aef27b08c20cde9e42b88d25434d9c7e5324d

17,363

py

Python

tests/test_pascal_style_byte_stream.py

scottcwang/openssh_key_parser

f8ba2b841620abd9166e99176e033111daaf0570

[ "MIT" ]

15

2020-08-15T02:34:34.000Z

2022-03-27T05:41:24.000Z

tests/test_pascal_style_byte_stream.py

scottcwang/openssh_key_parser

f8ba2b841620abd9166e99176e033111daaf0570

[ "MIT" ]

3

2022-01-26T23:38:10.000Z

2022-01-30T15:41:06.000Z

tests/test_pascal_style_byte_stream.py

scottcwang/openssh_key_parser

f8ba2b841620abd9166e99176e033111daaf0570

[ "MIT" ]

1

2022-01-27T10:47:26.000Z

import pytest from openssh_key.pascal_style_byte_stream import ( PascalStyleByteStream, PascalStyleFormatInstruction, PascalStyleFormatInstructionStringLengthSize ) def test_read_fixed_bytes(): test_bytes = b'\x01\x02\x03\x04' byte_stream = PascalStyleByteStream(test_bytes) result = byte_stream.read_fixed_bytes(4) assert result == test_bytes def test_read_fixed_bytes_underfull(): test_bytes = b'\x01\x02\x03\x04' byte_stream = PascalStyleByteStream(test_bytes) with pytest.raises(EOFError): byte_stream.read_fixed_bytes(5) def test_read_fixed_bytes_overfull(): test_bytes = b'\x01\x02\x03\x04' byte_stream = PascalStyleByteStream(test_bytes) byte_stream.read_fixed_bytes(3) assert byte_stream.read() == b'\x04' def test_read_fixed_bytes_zero(): test_bytes = b'\x01\x02\x03\x04' byte_stream = PascalStyleByteStream(test_bytes) byte_stream.read_fixed_bytes(0) assert byte_stream.read() == test_bytes def test_read_pascal_bytes(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x02' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_pascal_bytes(4) assert result == b'\x02' def test_read_negative_pascal_bytes(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x02' byte_stream = PascalStyleByteStream(pascal_bytes) with pytest.raises( ValueError, match='string_length_size must be positive' ): byte_stream.read_pascal_bytes(-1) def test_read_pascal_bytes_underfull_length(): pascal_bytes = b'\x00\x00\x00' byte_stream = PascalStyleByteStream(pascal_bytes) with pytest.raises(EOFError): byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) def test_read_pascal_bytes_underfull_string(): pascal_bytes = b'\x00\x00\x00\x04' + b'\x00\x00\x00' byte_stream = PascalStyleByteStream(pascal_bytes) with pytest.raises(EOFError): byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) def test_read_pascal_bytes_overfull(): pascal_bytes = b'\x00\x00\x00\x04' + b'abcd' + b'\x00' byte_stream = PascalStyleByteStream(pascal_bytes) byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) assert byte_stream.read() == b'\x00' def test_read_from_struct_single_format_instruction(): test_bytes = b'\x00\x00\x00\x01' byte_stream = PascalStyleByteStream(test_bytes) result = byte_stream.read_from_format_instruction('>I') assert result == 1 def test_read_from_struct_multiple_format_instruction(): test_bytes = b'\x00\x00\x00\x01\x00\x00\x00\x02' byte_stream = PascalStyleByteStream(test_bytes) result = byte_stream.read_from_format_instruction('>II') assert result == (1, 2) def test_read_from_string_format_instruction(): pascal_bytes = b'\x00\x00\x00\x04' + b'abcd' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) assert result == 'abcd' def test_read_from_bytes_format_instruction(): pascal_bytes = b'\x00\x00\x00\x04' + b'\x01\x02\x03\x04' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.BYTES) assert result == b'\x01\x02\x03\x04' def test_read_from_pos_mpint_format_instruction(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x7f' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.MPINT) assert result == 0x7f def test_read_from_neg_mpint_format_instruction(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x80' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.MPINT) assert result == -0x80 def test_read_from_zero_mpint_format_instruction(): pascal_bytes = b'\x00\x00\x00\x00' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.MPINT) assert result == 0 def test_read_from_string_format_instruction_length(): pascal_bytes = b'\x00\x00\x00\x00\x00\x00\x00\x04' + b'abcd' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING, string_length_size=8 ) assert result == 'abcd' def test_read_from_pascal_underfull_length(): pascal_bytes = b'\x00\x00\x00' byte_stream = PascalStyleByteStream(pascal_bytes) with pytest.raises(EOFError): byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) def test_read_from_pascal_underfull_string(): pascal_bytes = b'\x00\x00\x00\x04' + b'\x00\x00\x00' byte_stream = PascalStyleByteStream(pascal_bytes) with pytest.raises(EOFError): byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) def test_read_from_pascal_overfull(): pascal_bytes = b'\x00\x00\x00\x04' + b'abcd' + b'\x00' byte_stream = PascalStyleByteStream(pascal_bytes) byte_stream.read_from_format_instruction( PascalStyleFormatInstruction.STRING) assert byte_stream.read() == b'\x00' def test_read_from_format_instructions_dict(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x00' \ + b'\x00\x00\x00\x02' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instructions_dict({ 'first': PascalStyleFormatInstruction.BYTES, 'second': '>I' }) assert result == { 'first': b'\x00', 'second': 2 } def test_read_from_empty_format_instructions_dict(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x00' \ + b'\x00\x00\x00\x02' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instructions_dict({}) assert result == {} def test_read_from_format_instructions_dict_underfull(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x00' \ + b'\x00\x00\x00' byte_stream = PascalStyleByteStream(pascal_bytes) with pytest.raises(EOFError): byte_stream.read_from_format_instructions_dict({ 'first': PascalStyleFormatInstruction.BYTES, 'second': '>I', }) def test_read_from_format_instructions_dict_overfull(): pascal_bytes = b'\x00\x00\x00\x01' + b'\x00' \ + b'\x00\x00\x00\x02' \ + b'\x03' byte_stream = PascalStyleByteStream(pascal_bytes) byte_stream.read_from_format_instructions_dict({ 'first': PascalStyleFormatInstruction.BYTES, 'second': '>I', }) assert byte_stream.read() == b'\x03' def test_read_from_format_instructions_dict_length(): pascal_bytes = b'\x01' + b'\x00' byte_stream = PascalStyleByteStream(pascal_bytes) result = byte_stream.read_from_format_instructions_dict({ 'first': PascalStyleFormatInstructionStringLengthSize( PascalStyleFormatInstruction.BYTES, 1 ) }) assert result == { 'first': b'\x00' } def test_write_from_struct_format_instruction(): test_int = 1 byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction('>I', test_int) assert byte_stream.getvalue() == b'\x00\x00\x00\x01' def test_write_from_bytes_format_instruction(): test_bytes = b'\x00' byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.BYTES, test_bytes ) assert byte_stream.getvalue() == b'\x00\x00\x00\x01' + b'\x00' def test_write_from_string_format_instruction(): test_string = 'abcd' byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.STRING, test_string ) assert byte_stream.getvalue() == b'\x00\x00\x00\x04' + b'abcd' def test_write_from_string_format_instruction_string_length_size(): test_string = 'abcd' byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.STRING, test_string, 8 ) assert byte_stream.getvalue() == \ b'\x00\x00\x00\x00\x00\x00\x00\x04' + b'abcd' def test_write_from_pos_no_prefix_mpint_format_instruction(): test_int = 0x1000 byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.MPINT, test_int ) assert byte_stream.getvalue() == b'\x00\x00\x00\x02' + b'\x10\x00' def test_write_from_pos_with_prefix_mpint_format_instruction(): test_int = 0x8000 byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.MPINT, test_int ) assert byte_stream.getvalue() == b'\x00\x00\x00\x03' + b'\x00\x80\x00' def test_write_from_neg_mpint_format_instruction(): test_int = -0x8000 byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.MPINT, test_int ) assert byte_stream.getvalue() == b'\x00\x00\x00\x02' + b'\x80\x00' def test_write_from_zero_mpint_format_instruction(): test_int = 0 byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.MPINT, test_int ) assert byte_stream.getvalue() == b'\x00\x00\x00\x00' def test_write_from_bytes_format_instruction_bad_class_str(): test = 'random' byte_stream = PascalStyleByteStream() with pytest.raises( ValueError, match='value must be a bytes instance for bytes format instruction' ): byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.BYTES, test ) def test_write_from_bytes_format_instruction_bad_class_int(): test = 1 byte_stream = PascalStyleByteStream() with pytest.raises( ValueError, match='value must be a bytes instance for bytes format instruction' ): byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.BYTES, test ) def test_write_from_str_format_instruction_bad_class_bytes(): test = b'random' byte_stream = PascalStyleByteStream() with pytest.raises( ValueError, match='value must be a str instance for string format instruction' ): byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.STRING, test ) def test_write_from_str_format_instruction_bad_class_int(): test = 1 byte_stream = PascalStyleByteStream() with pytest.raises( ValueError, match='value must be a str instance for string format instruction' ): byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.STRING, test ) def test_write_from_mpint_format_instruction_bad_class_bytes(): test = b'random' byte_stream = PascalStyleByteStream() with pytest.raises( ValueError, match='value must be an int instance for mpint format instruction' ): byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.MPINT, test ) def test_write_from_mpint_format_instruction_bad_class_str(): test = 'random' byte_stream = PascalStyleByteStream() with pytest.raises( ValueError, match='value must be an int instance for mpint format instruction' ): byte_stream.write_from_format_instruction( PascalStyleFormatInstruction.MPINT, test ) def test_write_from_format_instructions_dict(): byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instructions_dict({ 'first': PascalStyleFormatInstruction.BYTES, 'second': '>I', }, { 'first': b'\x00', 'second': 2, }) assert byte_stream.getvalue() == b'\x00\x00\x00\x01' + b'\x00' \ + b'\x00\x00\x00\x02' def test_write_from_empty_format_instructions_dict(): byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instructions_dict({}, { 'first': b'\x00', 'second': 2, }) assert byte_stream.getvalue() == b'' def test_write_from_format_instructions_dict_missing_key(): byte_stream = PascalStyleByteStream() with pytest.raises(KeyError): byte_stream.write_from_format_instructions_dict({ 'missing': '>I' }, { 'first': b'\x00', 'second': 2, }) def test_write_from_format_instructions_dict_length(): byte_stream = PascalStyleByteStream() byte_stream.write_from_format_instructions_dict({ 'first': PascalStyleFormatInstructionStringLengthSize( PascalStyleFormatInstruction.BYTES, 2 ) }, { 'first': b'\x00' }) assert byte_stream.getvalue() == b'\x00\x01' + b'\x00' def test_check_dict_str(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 'string' }, { 'a': PascalStyleFormatInstruction.STRING } ) assert not warnings_list def test_check_dict_bytes(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': b'\x00' }, { 'a': PascalStyleFormatInstruction.BYTES } ) assert not warnings_list def test_check_dict_mpint(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 1 }, { 'a': PascalStyleFormatInstruction.MPINT } ) assert not warnings_list def test_check_dict_incorrect_type(): with pytest.warns(UserWarning, match='a should be of class int'): PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 'string' }, { 'a': PascalStyleFormatInstruction.MPINT } ) def test_check_dict_format_string(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 1 }, { 'a': '>i' } ) assert not warnings_list def test_check_dict_format_string_too_large(): with pytest.warns(UserWarning, match='a should be formatted as >i'): PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 2 ** 33 }, { 'a': '>i' } ) def test_check_dict_two_attributes(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 1, 'b': 2 }, { 'a': PascalStyleFormatInstruction.MPINT, 'b': PascalStyleFormatInstruction.MPINT } ) assert not warnings_list def test_check_dict_missing_attribute(): with pytest.warns(UserWarning, match='b missing'): PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 1 }, { 'a': PascalStyleFormatInstruction.MPINT, 'b': PascalStyleFormatInstruction.MPINT } ) def test_check_dict_extra_attribute(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 1, 'b': 2, 'c': 3 }, { 'a': PascalStyleFormatInstruction.MPINT, 'b': PascalStyleFormatInstruction.MPINT } ) assert not warnings_list def test_check_dict_length(): with pytest.warns(None) as warnings_list: PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 'string' }, { 'a': PascalStyleFormatInstructionStringLengthSize( PascalStyleFormatInstruction.STRING, 1 ) } ) assert not warnings_list def test_check_dict_length_incorrect_type(): with pytest.warns(UserWarning, match='a should be of class int'): PascalStyleByteStream.check_dict_matches_format_instructions_dict( { 'a': 'string' }, { 'a': PascalStyleFormatInstructionStringLengthSize( PascalStyleFormatInstruction.MPINT, 1 ) } )

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null

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6

f760aefd9a8a0f0b01d937621f42741411b78ab9

77

py

Python

maxwell_slice/__init__.py

flatironinstitute/maxwell-slice

5941ca10098070f7df7f44cf662174c598a7521c

[ "Apache-2.0" ]

1

2021-09-23T01:11:18.000Z

maxwell_slice/__init__.py

flatironinstitute/maxwell-slice

5941ca10098070f7df7f44cf662174c598a7521c

[ "Apache-2.0" ]

9

2021-01-04T18:30:43.000Z

2021-02-09T19:30:51.000Z

maxwell_slice/__init__.py

flatironinstitute/maxwell-slice

5941ca10098070f7df7f44cf662174c598a7521c

[ "Apache-2.0" ]

1

2021-09-23T01:11:19.000Z

from .test_function import test_function from .sphere_scat import sphere_scat

38.5

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py

Python

lasier/adapters/caches/__init__.py

rafa-acioly/lasier

b518f93207ff15ba32b286f466f3ca3cea231b4c

[ "MIT" ]

null

lasier/adapters/caches/__init__.py

rafa-acioly/lasier

b518f93207ff15ba32b286f466f3ca3cea231b4c

[ "MIT" ]

null

lasier/adapters/caches/__init__.py

rafa-acioly/lasier

b518f93207ff15ba32b286f466f3ca3cea231b4c

[ "MIT" ]

null

from .aiocache import Adapter as AiocacheAdapter # noqa from .redis import Adapter as RedisAdapter # noqa

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e38cd6662e93ae5781017f3bd4903fd9e54605d6

24,003

py

Python

backend/tests/baserow/api/users/test_user_views.py

LiuJun666888/baserow

bc5b7f8ebe319f90ed1aabdb7f5dfd8916c3dad1

[ "MIT" ]

null

backend/tests/baserow/api/users/test_user_views.py

LiuJun666888/baserow

bc5b7f8ebe319f90ed1aabdb7f5dfd8916c3dad1

[ "MIT" ]

null

backend/tests/baserow/api/users/test_user_views.py

LiuJun666888/baserow

bc5b7f8ebe319f90ed1aabdb7f5dfd8916c3dad1

[ "MIT" ]

null

import os import pytest from unittest.mock import patch from freezegun import freeze_time from rest_framework.status import ( HTTP_200_OK, HTTP_201_CREATED, HTTP_400_BAD_REQUEST, HTTP_404_NOT_FOUND, ) from django.contrib.auth import get_user_model from django.shortcuts import reverse from django.conf import settings from baserow.api.user.registries import user_data_registry, UserDataType from baserow.contrib.database.models import Database, Table from baserow.core.handler import CoreHandler from baserow.core.models import Group, GroupUser from baserow.core.user.handler import UserHandler User = get_user_model() @pytest.mark.django_db def test_create_user(client, data_fixture): valid_password = "thisIsAValidPassword" short_password = "short" response = client.post( reverse("api:user:index"), {"name": "Test1", "email": "test@test.nl", "password": valid_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_200_OK user = User.objects.get(email="test@test.nl") assert user.first_name == "Test1" assert user.email == "test@test.nl" assert user.password != "" assert "password" not in response_json["user"] assert response_json["user"]["username"] == "test@test.nl" assert response_json["user"]["first_name"] == "Test1" assert response_json["user"]["is_staff"] is True assert response_json["user"]["id"] == user.id # Test profile properties response = client.post( reverse("api:user:index"), { "name": "Test1Bis", "email": "test1bis@test.nl", "password": valid_password, "language": "fr", }, format="json", ) response_json = response.json() assert response.status_code == HTTP_200_OK user = User.objects.get(email="test1bis@test.nl") assert user.profile.language == "fr" assert response_json["user"]["language"] == "fr" response_failed = client.post( reverse("api:user:index"), {"name": "Test1", "email": "test@test.nl", "password": valid_password}, format="json", ) assert response_failed.status_code == 400 assert response_failed.json()["error"] == "ERROR_EMAIL_ALREADY_EXISTS" response_failed = client.post( reverse("api:user:index"), {"name": "Test1", "email": " teSt@teST.nl ", "password": valid_password}, format="json", ) assert response_failed.status_code == 400 assert response_failed.json()["error"] == "ERROR_EMAIL_ALREADY_EXISTS" too_long_name = "x" * 151 response_failed = client.post( reverse("api:user:index"), { "name": too_long_name, "email": "new@example.com ", "password": valid_password, }, format="json", ) assert response_failed.status_code == 400 assert response_failed.json()["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert response_failed.json()["detail"] == { "name": [ { "code": "max_length", "error": "Ensure this field has no more than 150 characters.", } ] } data_fixture.update_settings(allow_new_signups=False) response_failed = client.post( reverse("api:user:index"), {"name": "Test1", "email": "test10@test.nl", "password": valid_password}, format="json", ) assert response_failed.status_code == 400 assert response_failed.json()["error"] == "ERROR_DISABLED_SIGNUP" data_fixture.update_settings(allow_new_signups=True) response_failed_2 = client.post( reverse("api:user:index"), {"email": "test"}, format="json" ) assert response_failed_2.status_code == 400 long_password = "x" * 256 response = client.post( reverse("api:user:index"), {"name": "Test2", "email": "test2@test.nl", "password": long_password}, format="json", ) assert response.status_code == HTTP_200_OK user = User.objects.get(email="test2@test.nl") assert user.check_password(long_password) long_password = "x" * 257 response = client.post( reverse("api:user:index"), {"name": "Test2", "email": "test2@test.nl", "password": long_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert ( response_json["detail"]["password"][0]["code"] == "password_validation_failed" ) assert ( response_json["detail"]["password"][0]["error"] == "This password is too long. It must not exceed 256 characters." ) response = client.post( reverse("api:user:index"), {"name": "Test2", "email": "random@test.nl", "password": short_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert ( response_json["detail"]["password"][0]["code"] == "password_validation_failed" ) assert ( response_json["detail"]["password"][0]["error"] == "This password is too short. It must contain at least 8 characters." ) # Test profile attribute errors response_failed = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test20@test.nl", "password": valid_password, "language": "invalid", }, format="json", ) response_json = response_failed.json() assert response_failed.status_code == 400 assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert response_json["detail"]["language"][0]["code"] == "invalid_language" assert response_json["detail"]["language"][0]["error"] == ( "Only the following language keys are " f"valid: {','.join([l[0] for l in settings.LANGUAGES])}" ) @pytest.mark.django_db def test_user_account(data_fixture, api_client): user, token = data_fixture.create_user_and_token( email="test@localhost.nl", language="en", first_name="Nikolas" ) response = api_client.patch( reverse("api:user:account"), { "first_name": "NewOriginalName", "language": "fr", }, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) response_json = response.json() assert response.status_code == HTTP_200_OK assert response_json["first_name"] == "NewOriginalName" assert response_json["language"] == "fr" user.refresh_from_db() assert user.first_name == "NewOriginalName" assert user.profile.language == "fr" response = api_client.patch( reverse("api:user:account"), { "language": "invalid", }, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) response_json = response.json() assert response.status_code == 400 assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert response_json["detail"]["language"][0]["code"] == "invalid_language" assert response_json["detail"]["language"][0]["error"] == ( "Only the following language keys are " f"valid: {','.join([l[0] for l in settings.LANGUAGES])}" ) @pytest.mark.django_db def test_create_user_with_invitation(data_fixture, client): core_handler = CoreHandler() valid_password = "thisIsAValidPassword" invitation = data_fixture.create_group_invitation(email="test0@test.nl") signer = core_handler.get_group_invitation_signer() response_failed = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test@test.nl", "password": valid_password, "group_invitation_token": "INVALID", }, format="json", ) assert response_failed.status_code == HTTP_400_BAD_REQUEST assert response_failed.json()["error"] == "BAD_TOKEN_SIGNATURE" response_failed = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test0@test.nl", "password": valid_password, "group_invitation_token": f"{signer.dumps(invitation.id)}2", }, format="json", ) assert response_failed.status_code == HTTP_400_BAD_REQUEST assert response_failed.json()["error"] == "BAD_TOKEN_SIGNATURE" assert User.objects.all().count() == 1 response_failed = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test@test.nl", "password": valid_password, "group_invitation_token": signer.dumps(99999), }, format="json", ) assert response_failed.status_code == HTTP_404_NOT_FOUND assert response_failed.json()["error"] == "ERROR_GROUP_INVITATION_DOES_NOT_EXIST" response_failed = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test@test.nl", "password": valid_password, "group_invitation_token": signer.dumps(invitation.id), }, format="json", ) assert response_failed.status_code == HTTP_400_BAD_REQUEST assert response_failed.json()["error"] == "ERROR_GROUP_INVITATION_EMAIL_MISMATCH" assert User.objects.all().count() == 1 response_failed = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test0@test.nl", "password": valid_password, "group_invitation_token": signer.dumps(invitation.id), }, format="json", ) assert response_failed.status_code == HTTP_200_OK assert User.objects.all().count() == 2 assert Group.objects.all().count() == 1 assert Group.objects.all().first().id == invitation.group_id assert GroupUser.objects.all().count() == 2 assert Database.objects.all().count() == 0 assert Table.objects.all().count() == 0 @pytest.mark.django_db def test_create_user_with_template(data_fixture, client): old_templates = settings.APPLICATION_TEMPLATES_DIR valid_password = "thisIsAValidPassword" settings.APPLICATION_TEMPLATES_DIR = os.path.join( settings.BASE_DIR, "../../../tests/templates" ) template = data_fixture.create_template(slug="example-template") response = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test0@test.nl", "password": valid_password, "template_id": -1, }, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert response_json["detail"]["template_id"][0]["code"] == "does_not_exist" response = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test0@test.nl", "password": valid_password, "template_id": "random", }, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert response_json["detail"]["template_id"][0]["code"] == "incorrect_type" response = client.post( reverse("api:user:index"), { "name": "Test1", "email": "test0@test.nl", "password": valid_password, "template_id": template.id, }, format="json", ) assert response.status_code == HTTP_200_OK assert Group.objects.all().count() == 2 assert GroupUser.objects.all().count() == 1 # We expect the example template to be installed assert Database.objects.all().count() == 1 assert Database.objects.all().first().name == "Event marketing" assert Table.objects.all().count() == 2 settings.APPLICATION_TEMPLATES_DIR = old_templates @pytest.mark.django_db(transaction=True) def test_send_reset_password_email(data_fixture, client, mailoutbox): data_fixture.create_user(email="test@localhost.nl") response = client.post( reverse("api:user:send_reset_password_email"), {}, format="json" ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" response = client.post( reverse("api:user:send_reset_password_email"), {"email": "unknown@localhost.nl", "base_url": "http://localhost:3000"}, format="json", ) assert response.status_code == 204 assert len(mailoutbox) == 0 response = client.post( reverse("api:user:send_reset_password_email"), {"email": "test@localhost.nl", "base_url": "http://test.nl"}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_HOSTNAME_IS_NOT_ALLOWED" assert len(mailoutbox) == 0 response = client.post( reverse("api:user:send_reset_password_email"), {"email": "test@localhost.nl", "base_url": "http://localhost:3000"}, format="json", ) assert response.status_code == 204 assert len(mailoutbox) == 1 response = client.post( reverse("api:user:send_reset_password_email"), {"email": " teST@locAlhost.nl ", "base_url": "http://localhost:3000"}, format="json", ) assert response.status_code == 204 assert len(mailoutbox) == 2 email = mailoutbox[0] assert "test@localhost.nl" in email.to assert email.body.index("http://localhost:3000") @pytest.mark.django_db def test_password_reset(data_fixture, client): user = data_fixture.create_user(email="test@localhost") handler = UserHandler() valid_password = "thisIsAValidPassword" short_password = "short" long_password = ( "Bgvmt95en6HGJZ9Xz0F8xysQ6eYgo2Y54YzRPxxv10b5n16F4rZ6YH4ulonocwiFK6970KiAxoYhU" "LYA3JFDPIQGj5gMZZl25M46sO810Zd3nyBg699a2TDMJdHG7hAAi0YeDnuHuabyBawnb4962OQ1OO" "f1MxzFyNWG7NR2X6MZQL5G1V61x56lQTXbvK1AG1IPM87bQ3YAtIBtGT2vK3Wd83q3he5ezMtUfzK" "2ibj0WWhf86DyQB4EHRUJjYcBiI78iEJv5hcu33X2I345YosO66cTBWK45SqJEDudrCOq" ) signer = handler.get_reset_password_signer() response = client.post(reverse("api:user:reset_password"), {}, format="json") response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" response = client.post( reverse("api:user:reset_password"), {"token": "test", "password": valid_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "BAD_TOKEN_SIGNATURE" with freeze_time("2020-01-01 12:00"): token = signer.dumps(user.id) with freeze_time("2020-01-04 12:00"): response = client.post( reverse("api:user:reset_password"), {"token": token, "password": valid_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "EXPIRED_TOKEN_SIGNATURE" with freeze_time("2020-01-01 12:00"): token = signer.dumps(9999) with freeze_time("2020-01-02 12:00"): response = client.post( reverse("api:user:reset_password"), {"token": token, "password": valid_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_USER_NOT_FOUND" with freeze_time("2020-01-01 12:00"): token = signer.dumps(user.id) with freeze_time("2020-01-02 12:00"): response = client.post( reverse("api:user:reset_password"), {"token": token, "password": valid_password}, format="json", ) assert response.status_code == 204 user.refresh_from_db() assert user.check_password(valid_password) with freeze_time("2020-01-02 12:00"): token = signer.dumps(user.id) with freeze_time("2020-01-02 12:00"): response = client.post( reverse("api:user:reset_password"), {"token": token, "password": short_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert ( response_json["detail"]["password"][0]["code"] == "password_validation_failed" ) assert ( response_json["detail"]["password"][0]["error"] == "This password is too short. It must contain at least 8 characters." ) user.refresh_from_db() assert not user.check_password(short_password) with freeze_time("2020-01-02 12:00"): response = client.post( reverse("api:user:reset_password"), {"token": token, "password": long_password}, format="json", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert ( response_json["detail"]["password"][0]["code"] == "password_validation_failed" ) assert ( response_json["detail"]["password"][0]["error"] == "This password is too long. It must not exceed 256 characters." ) user.refresh_from_db() assert not user.check_password(long_password) @pytest.mark.django_db def test_change_password(data_fixture, client): valid_old_password = "thisIsAValidPassword" valid_new_password = "thisIsAValidNewPassword" short_password = "short" long_password = ( "Bgvmt95en6HGJZ9Xz0F8xysQ6eYgo2Y54YzRPxxv10b5n16F4rZ6YH4ulonocwiFK6970KiAxoYhU" "LYA3JFDPIQGj5gMZZl25M46sO810Zd3nyBg699a2TDMJdHG7hAAi0YeDnuHuabyBawnb4962OQ1OO" "f1MxzFyNWG7NR2X6MZQL5G1V61x56lQTXbvK1AG1IPM87bQ3YAtIBtGT2vK3Wd83q3he5ezMtUfzK" "2ibj0WWhf86DyQB4EHRUJjYcBiI78iEJv5hcu33X2I345YosO66cTBWK45SqJEDudrCOq" ) user, token = data_fixture.create_user_and_token( email="test@localhost", password=valid_old_password ) response = client.post( reverse("api:user:change_password"), {}, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" response = client.post( reverse("api:user:change_password"), {"old_password": "INCORRECT", "new_password": valid_new_password}, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_INVALID_OLD_PASSWORD" user.refresh_from_db() assert user.check_password(valid_old_password) response = client.post( reverse("api:user:change_password"), {"old_password": valid_old_password, "new_password": short_password}, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert ( response_json["detail"]["new_password"][0]["code"] == "password_validation_failed" ) assert ( response_json["detail"]["new_password"][0]["error"] == "This password is too short. It must contain at least 8 characters." ) user.refresh_from_db() assert user.check_password(valid_old_password) response = client.post( reverse("api:user:change_password"), {"old_password": valid_old_password, "new_password": long_password}, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) response_json = response.json() assert response.status_code == HTTP_400_BAD_REQUEST assert response_json["error"] == "ERROR_REQUEST_BODY_VALIDATION" assert ( response_json["detail"]["new_password"][0]["code"] == "password_validation_failed" ) assert ( response_json["detail"]["new_password"][0]["error"] == "This password is too long. It must not exceed 256 characters." ) user.refresh_from_db() assert user.check_password(valid_old_password) response = client.post( reverse("api:user:change_password"), {"old_password": valid_old_password, "new_password": valid_new_password}, format="json", HTTP_AUTHORIZATION=f"JWT {token}", ) assert response.status_code == 204 user.refresh_from_db() assert user.check_password(valid_new_password) @pytest.mark.django_db def test_dashboard(data_fixture, client): user, token = data_fixture.create_user_and_token(email="test@localhost") group_1 = data_fixture.create_group(name="Test1") group_2 = data_fixture.create_group() invitation_1 = data_fixture.create_group_invitation( group=group_1, email="test@localhost" ) data_fixture.create_group_invitation(group=group_1, email="test2@localhost") data_fixture.create_group_invitation(group=group_2, email="test3@localhost") response = client.get( reverse("api:user:dashboard"), format="json", HTTP_AUTHORIZATION=f"JWT {token}" ) response_json = response.json() assert len(response_json["group_invitations"]) == 1 assert response_json["group_invitations"][0]["id"] == invitation_1.id assert response_json["group_invitations"][0]["email"] == invitation_1.email assert response_json["group_invitations"][0]["invited_by"] == ( invitation_1.invited_by.first_name ) assert response_json["group_invitations"][0]["group"] == "Test1" assert response_json["group_invitations"][0]["message"] == invitation_1.message assert "created_on" in response_json["group_invitations"][0] @pytest.mark.django_db def test_additional_user_data(api_client, data_fixture): class TmpUserDataType(UserDataType): type = "type" def get_user_data(self, user, request) -> dict: return True plugin_mock = TmpUserDataType() with patch.dict(user_data_registry.registry, {"tmp": plugin_mock}): response = api_client.post( reverse("api:user:index"), { "name": "Test1", "email": "test@test.nl", "password": "thisIsAValidPassword", "authenticate": True, }, format="json", ) response_json = response.json() assert response.status_code == HTTP_200_OK assert response_json["tmp"] is True response = api_client.post( reverse("api:user:token_auth"), {"username": "test@test.nl", "password": "thisIsAValidPassword"}, format="json", ) response_json = response.json() assert response.status_code == HTTP_201_CREATED assert response_json["tmp"] is True response = api_client.post( reverse("api:user:token_refresh"), {"token": response_json["token"]}, format="json", ) response_json = response.json() assert response.status_code == HTTP_201_CREATED assert response_json["tmp"] is True

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0.641045

2,666

24,003

5.524381

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0.084737

0.06233

0.05296

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0.760796

0.729155

0.711366

0.683732

0.616852

0

0.029775

0.227638

24,003

684

88

35.092105

0.764658

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0.001658

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0

1

0

1

0

null

0

1

0

6

e3a1f3f45077d112795da5ac34b5f3557d6232aa

45

py

Python

test.py

RusherRG/Hack-it

3a14bf4a1dc129d567fa9bc56d77b4f96a0d4b8c

[ "MIT" ]

1

2021-04-09T06:45:05.000Z

test.py

RusherRG/Hack-it

3a14bf4a1dc129d567fa9bc56d77b4f96a0d4b8c

[ "MIT" ]

null

test.py

RusherRG/Hack-it

3a14bf4a1dc129d567fa9bc56d77b4f96a0d4b8c

[ "MIT" ]

null

print(add(5, 3)) def add(x, y): return x+y

9

16

0.577778

11

45

2.363636

0.727273

0.153846

0

0.055556

0.2

45

4

17

11.25

0.666667

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1

0.333333

false

0

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0.666667

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1

0

null

0

1

0

null

0

1

0

1

0

6

54191d23ae6c2f8e839496e36509dee873489bcc

5,083

py

Python

tests/server/extensions/test_loqusdb_extension_init.py

gmc-norr/scout

ea8eaaa079c63e4033af6216ec08da4a314f9b5c

[ "BSD-3-Clause" ]

null

tests/server/extensions/test_loqusdb_extension_init.py

gmc-norr/scout

ea8eaaa079c63e4033af6216ec08da4a314f9b5c

[ "BSD-3-Clause" ]

null

tests/server/extensions/test_loqusdb_extension_init.py

gmc-norr/scout

ea8eaaa079c63e4033af6216ec08da4a314f9b5c

[ "BSD-3-Clause" ]

null

"""Tests for loqusdb extension""" import subprocess import pytest from flask import Flask from scout.server.extensions.loqus_extension import LoqusDB def test_init_loqusextension(loqus_exe): """Test a init a loqus extension object""" # GIVEN a loqusdb binary # WHEN initialising a loqusdb extension loqus_obj = LoqusDB(loqusdb_binary=loqus_exe) # THEN assert that the binary is correct assert loqus_obj.loqusdb_binary == loqus_exe # THEN assert that the base call is correct assert loqus_obj.base_call == [loqus_exe] # THEN assert that the version is 0 assert loqus_obj.version == 0 # THEN assert that there is no config assert loqus_obj.loqusdb_config is None def test_init_loqusextension_version(loqus_exe, loqus_version): """Test a init a loqus extension object with a specified version""" # GIVEN a loqusdb binary and a version # WHEN initialising a loqusdb extension loqus_obj = LoqusDB(loqusdb_binary=loqus_exe, version=loqus_version) # THEN assert that the binary is correct assert loqus_obj.loqusdb_binary == loqus_exe # THEN assert that the base call is correct assert loqus_obj.base_call == [loqus_exe] # THEN assert that the version is correct assert loqus_obj.version == loqus_version # THEN assert that there is no config assert loqus_obj.loqusdb_config is None def test_init_loqusextension_config(loqus_exe, loqus_config, loqus_version): """Test a init a loqus extension object with a specified version""" # GIVEN a loqusdb binary, a version and a config # WHEN initialising a loqusdb extension loqus_obj = LoqusDB( loqusdb_binary=loqus_exe, loqusdb_config=loqus_config, version=loqus_version ) # THEN assert that the binary is correct assert loqus_obj.loqusdb_binary == loqus_exe # THEN assert that the base call is correct assert loqus_obj.base_call == [loqus_exe, "--config", loqus_config] # THEN assert that the version is correct assert loqus_obj.version == loqus_version # THEN assert that there is no config assert loqus_obj.loqusdb_config == loqus_config def test_init_loqusextension_init_app(loqus_exe, loqus_version): """Test a init a loqus extension object with flask app with version""" # GIVEN a loqusdb binary configs = {"LOQUSDB_SETTINGS": {"binary_path": loqus_exe, "version": loqus_version}} # WHEN initialising a loqusdb extension with init app app = Flask(__name__) loqus_obj = LoqusDB() with app.app_context(): app.config = configs loqus_obj.init_app(app) # THEN assert that the binary is correct assert loqus_obj.loqusdb_binary == loqus_exe # THEN assert that the version is correct assert loqus_obj.version == loqus_version # THEN assert that there is no config assert loqus_obj.loqusdb_config is None def test_init_loqusextension_init_app_no_version(mocker, loqus_exe, loqus_version): """Test a init a loqus extension object with flask app""" # GIVEN a loqusdb binary configs = {"LOQUSDB_SETTINGS": {"binary_path": loqus_exe}} mocker.patch.object(subprocess, "check_output") subprocess.check_output.return_value = b"loqusdb, version %f" % loqus_version # WHEN initialising a loqusdb extension with init app app = Flask(__name__) loqus_obj = LoqusDB() with app.app_context(): app.config = configs loqus_obj.init_app(app) # THEN assert that the binary is correct assert loqus_obj.loqusdb_binary == loqus_exe assert loqus_obj.version == loqus_version # THEN assert that there is no config assert loqus_obj.loqusdb_config is None def test_init_loqusextension_init_app_wrong_version(loqus_exe): """Test a init a loqus extension object with flask app""" # GIVEN a loqusdb binary configs = {"LOQUSDB_SETTINGS": {"binary_path": loqus_exe, "version": 1.0}} # WHEN initialising a loqusdb extension with init app app = Flask(__name__) loqus_obj = LoqusDB() with pytest.raises(SyntaxError): with app.app_context(): app.config = configs loqus_obj.init_app(app) def test_init_loqusextension_init_app_with_config(loqus_exe, loqus_config): """Test a init a loqus extension object with flask app with version and config""" # GIVEN a loqusdb binary version = 2.5 configs = { "LOQUSDB_SETTINGS": { "binary_path": loqus_exe, "version": version, "config_path": loqus_config, } } # WHEN initialising a loqusdb extension with init app app = Flask(__name__) loqus_obj = LoqusDB() with app.app_context(): app.config = configs loqus_obj.init_app(app) # THEN assert that the binary is correct assert loqus_obj.loqusdb_binary == loqus_exe # THEN assert that the version is correct assert loqus_obj.version == version # THEN assert that the config is correct assert loqus_obj.loqusdb_config == loqus_config

39.1

88

0.70962

701

5,083

4.917261

0.088445

0.074267

0.085292

0.073977

0.86597

0.844502

0.817813

0.803597

0.789962

0.776617

0

0.001519

0.223097

5,083

129

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39.403101

0.87136

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0

0.15493

0

null

0

1

0

null

0

6

5868699cc6110ca103ca272a66e68d03e48fa922

954

py

Python

pycurlutil.py

MattLud/FacebookFilterTracker

3e28d1401b18b2296a96c2e970958f5c75629a14

[ "Apache-2.0" ]

3

2017-12-04T19:39:59.000Z

2019-01-10T06:36:37.000Z

pycurlutil.py

MattLud/FacebookFilterTracker

3e28d1401b18b2296a96c2e970958f5c75629a14

[ "Apache-2.0" ]

null

pycurlutil.py

MattLud/FacebookFilterTracker

3e28d1401b18b2296a96c2e970958f5c75629a14

[ "Apache-2.0" ]

null

import pycurl import urllib.parse from collections import defaultdict from io import BytesIO import json def pycurlgetURL(url): buffer = BytesIO() c = pycurl.Curl() c.setopt(c.URL, url) c.setopt(c.WRITEDATA, buffer) c.perform() c.close() body = buffer.getvalue() return json.loads(body.decode('iso-8859-1')) def pycurlget(url, params): buffer = BytesIO() c = pycurl.Curl() pairs = urllib.parse.urlencode(params) c.setopt(c.URL, url+'?'+pairs) c.setopt(c.WRITEDATA, buffer) c.perform() c.close() body = buffer.getvalue() return json.loads(body.decode('iso-8859-1')) def pycurlpost(url, params): buffer = BytesIO() c = pycurl.Curl() pairs = urllib.parse.urlencode(params) c.setopt(c.URL, url) c.setopt(c.POSTFIELDS, pairs) c.setopt(c.WRITEDATA, buffer) c.perform() c.close() body = buffer.getvalue() return json.loads(body.decode('iso-8859-1'))

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null

0

6

54536adc105da17f7b301e5af756ef81eb01d793

72

py

Python

futures_then/__init__.py

dvdotsenko/python-future-then

77cfd26bde5cc367226e57eed75853afb85277a7

[ "MIT" ]

19

2016-02-10T07:09:11.000Z

2020-12-10T18:20:07.000Z

futures_then/__init__.py

dvdotsenko/python-future-then

77cfd26bde5cc367226e57eed75853afb85277a7

[ "MIT" ]

1

2020-04-05T08:44:47.000Z

futures_then/__init__.py

dvdotsenko/python-future-then

77cfd26bde5cc367226e57eed75853afb85277a7

[ "MIT" ]

1

2018-07-25T20:35:40.000Z

from .futures_then import ThenableFuture, CircularFuturesChainException

36

71

0.902778

6

72

10.666667

1

0

0.069444

72

1

72

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1

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1

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0

null

0

1

0

1

0

1

0

6

545e03f12e75de2482a261f3b9e881782b8f0ab7

20

py

Python

tests/assets/dependenciespackage/dependenciespackage/subpackage/.hidden/hidden.py

SimonBiggs/layer_linter

9eb518b74118e4a2d8079e2f32ecc12612ca9e86

[ "BSD-3-Clause" ]

63

2018-06-21T10:39:54.000Z

2021-06-04T14:28:44.000Z

tests/assets/dependenciespackage/dependenciespackage/subpackage/.hidden/hidden.py

SimonBiggs/layer_linter

9eb518b74118e4a2d8079e2f32ecc12612ca9e86

[ "BSD-3-Clause" ]

86

2018-06-20T13:30:30.000Z

2019-06-04T12:47:28.000Z

tests/assets/dependenciespackage/dependenciespackage/subpackage/.hidden/hidden.py

SimonBiggs/layer_linter

9eb518b74118e4a2d8079e2f32ecc12612ca9e86

[ "BSD-3-Clause" ]

4

2018-08-14T08:49:55.000Z

2019-02-16T09:24:47.000Z

from . import three

10

19

0.75

3

20

5

1

0

0.2

20

1

20

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

5471f45dc1bc4eb25dd3bcbc1cbaf956490b5e4e

144

py

Python

PythonBackend/calc_model/__init__.py

goo-goo-goo-joob/CreditRisks

c874941f3787a0c73063883a019a61672e7bef2f

[ "Apache-2.0" ]

1

2020-09-19T12:32:45.000Z

PythonBackend/calc_model/__init__.py

goo-goo-goo-joob/CreditRisks

c874941f3787a0c73063883a019a61672e7bef2f

[ "Apache-2.0" ]

null

PythonBackend/calc_model/__init__.py

goo-goo-goo-joob/CreditRisks

c874941f3787a0c73063883a019a61672e7bef2f

[ "Apache-2.0" ]

null

from .abstract_model import AbstractModel from .bank_model import BankModel from .cb_model import CatBoostModel from .sgd_model import SGDModel

28.8

41

0.861111

20

144

6

0.55

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0

0.111111

144

4

42

36

0.9375

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true

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null

1

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null

0

1

0

1

0

1

0

6

54ba823e4ecb19a5d30399f968df953816f1fb53

35

tac

Python

src/main/resources/examples2/taf-A5-2.tac

saeidrastak/IWXXMConverter

f2c881ce1ec0269791148bd3ed8de3de01ba31dd

[ "BSD-3-Clause" ]

5

2016-10-26T06:40:29.000Z

2021-06-22T19:21:25.000Z

src/main/resources/examples2/taf-A5-2.tac

saeidrastak/IWXXMConverter

f2c881ce1ec0269791148bd3ed8de3de01ba31dd

[ "BSD-3-Clause" ]

null

src/main/resources/examples2/taf-A5-2.tac

saeidrastak/IWXXMConverter

f2c881ce1ec0269791148bd3ed8de3de01ba31dd

[ "BSD-3-Clause" ]

1

2020-09-03T14:06:00.000Z

TAF AMD YUDO 161500Z 1606/1624 CNL

17.5

34

0.8

7

35

4

1

0

0.482759

0.171429

35

1

35

0.482759

0

null

0

null

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

54c511eaced277fb6dfde11e6a06e59b79926c6c

489

py

Python

Python_Img_Humor/src/data/__init__.py

limorigu/ComplexCauses

e047bea494329e4c4ca0f124c1a44daf900055df

[ "CC0-1.0" ]

4

2021-06-11T15:03:05.000Z

2022-03-28T10:41:11.000Z

Python_Img_Humor/src/data/__init__.py

limorigu/ComplexCauses

e047bea494329e4c4ca0f124c1a44daf900055df

[ "CC0-1.0" ]

null

Python_Img_Humor/src/data/__init__.py

limorigu/ComplexCauses

e047bea494329e4c4ca0f124c1a44daf900055df

[ "CC0-1.0" ]

null

from data.PertImgSim import get_img_sim_loaders_by_cov, \ ImgSimPert_data_by_cov, get_full_vector_img_sim from data.Humicroedit import get_humicroedit_loaders_by_cov, \ Humicroedit_data_by_cov, get_full_vector_humicroedit from data.data_utils import DataIter __all__ = ['get_img_sim_loaders_by_cov', 'ImgSimPert_data_by_cov', 'get_full_vector_img_sim', 'get_humicroedit_loaders_by_cov', 'Humicroedit_data_by_cov', 'get_full_vector_humicroedit', 'DataIter']

44.454545

93

0.813906

72

489

4.847222

0.236111

0.114613

0.137536

0.739255

0

0.120654

489

10

94

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0.811628

0

0.32582

0.309426

0

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false

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0

null

0

1

0

null

0

1

0

6

54c8235fb8a45ea16b9962c644b5fa38adb247b9

104

py

Python

tdsbconnects/__init__.py

tylertian123/pytdsbconnects

b5f820e125c37150c3f6700fdf0a0d5998f71c52

[ "MIT" ]

3

2020-09-17T21:57:25.000Z

2020-11-30T06:19:45.000Z

tdsbconnects/__init__.py

tylertian123/pytdsbconnects

b5f820e125c37150c3f6700fdf0a0d5998f71c52

[ "MIT" ]

null

tdsbconnects/__init__.py

tylertian123/pytdsbconnects

b5f820e125c37150c3f6700fdf0a0d5998f71c52

[ "MIT" ]

null

from .tdsbconnects import * from .objects import * from .util import * from .version import __version__

20.8

32

0.778846

13

104

5.923077

0.461538

0.38961

0

0.153846

104

4

33

26

0.875

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

49dcb55e57c100f835cd8b5bbdba1b91dbf69186

18,654

py

Python

fonts/vector/symbol.py

szczys/st7789_mpy

bc854ec453d7644ce1773f7ed4d41504f37d376b

[ "MIT" ]

153

2020-02-02T11:03:14.000Z

2022-03-30T05:47:07.000Z

fonts/vector/symbol.py

skylin008/st7789_mpy

f304991fc5558be653df5f0de928494b85cbc60d

[ "MIT" ]

58

2020-04-11T23:23:02.000Z

2022-03-26T20:45:23.000Z

fonts/vector/symbol.py

skylin008/st7789_mpy

f304991fc5558be653df5f0de928494b85cbc60d

[ "MIT" ]

50

2020-02-02T11:05:23.000Z

2022-03-22T15:24:42.000Z

WIDTH = 87 HEIGHT = 87 FIRST = 0x20 LAST = 0x7f _font =\ b'\x00\x4a\x5a\x02\x44\x60\x44\x52\x60\x52\x02\x44\x60\x44\x60'\ b'\x60\x44\x02\x52\x52\x52\x3e\x52\x66\x02\x44\x60\x44\x44\x60'\ b'\x60\x02\x44\x60\x44\x52\x60\x52\x02\x46\x5e\x46\x59\x5e\x4b'\ b'\x02\x4b\x59\x4b\x5e\x59\x46\x02\x52\x52\x52\x44\x52\x60\x02'\ b'\x4b\x59\x4b\x46\x59\x5e\x02\x46\x5e\x46\x4b\x5e\x59\x02\x4b'\ b'\x59\x4b\x52\x59\x52\x02\x4d\x57\x4d\x57\x57\x4d\x02\x52\x52'\ b'\x52\x4b\x52\x59\x02\x4d\x57\x4d\x4d\x57\x57\x07\x47\x52\x52'\ b'\x47\x50\x47\x4d\x48\x4a\x4a\x48\x4d\x47\x50\x47\x52\x07\x47'\ b'\x52\x47\x52\x47\x54\x48\x57\x4a\x5a\x4d\x5c\x50\x5d\x52\x5d'\ b'\x07\x52\x5d\x52\x5d\x54\x5d\x57\x5c\x5a\x5a\x5c\x57\x5d\x54'\ b'\x5d\x52\x07\x52\x5d\x5d\x52\x5d\x50\x5c\x4d\x5a\x4a\x57\x48'\ b'\x54\x47\x52\x47\x08\x44\x60\x44\x4f\x47\x51\x4b\x53\x50\x54'\ b'\x54\x54\x59\x53\x5d\x51\x60\x4f\x08\x50\x55\x55\x44\x53\x47'\ b'\x51\x4b\x50\x50\x50\x54\x51\x59\x53\x5d\x55\x60\x08\x4f\x54'\ b'\x4f\x44\x51\x47\x53\x4b\x54\x50\x54\x54\x53\x59\x51\x5d\x4f'\ b'\x60\x08\x44\x60\x44\x55\x47\x53\x4b\x51\x50\x50\x54\x50\x59'\ b'\x51\x5d\x53\x60\x55\x04\x4b\x59\x52\x4a\x59\x4e\x4b\x56\x52'\ b'\x5a\x04\x4a\x5a\x4a\x52\x4e\x4b\x56\x59\x5a\x52\x04\x4b\x59'\ b'\x4b\x56\x4b\x4e\x59\x56\x59\x4e\x04\x4a\x5a\x4c\x58\x4a\x50'\ b'\x5a\x54\x58\x4c\x16\x4a\x5a\x4a\x5d\x4c\x5d\x4f\x5c\x51\x5b'\ b'\x54\x58\x55\x56\x56\x53\x56\x4f\x55\x4c\x54\x4a\x53\x49\x51'\ b'\x49\x50\x4a\x4f\x4c\x4e\x4f\x4e\x53\x4f\x56\x50\x58\x53\x5b'\ b'\x55\x5c\x58\x5d\x5a\x5d\x16\x49\x5d\x5d\x5a\x5d\x58\x5c\x55'\ b'\x5b\x53\x58\x50\x56\x4f\x53\x4e\x4f\x4e\x4c\x4f\x4a\x50\x49'\ b'\x51\x49\x53\x4a\x54\x4c\x55\x4f\x56\x53\x56\x56\x55\x58\x54'\ b'\x5b\x51\x5c\x4f\x5d\x4c\x5d\x4a\x16\x4a\x5a\x5a\x47\x58\x47'\ b'\x55\x48\x53\x49\x50\x4c\x4f\x4e\x4e\x51\x4e\x55\x4f\x58\x50'\ b'\x5a\x51\x5b\x53\x5b\x54\x5a\x55\x58\x56\x55\x56\x51\x55\x4e'\ b'\x54\x4c\x51\x49\x4f\x48\x4c\x47\x4a\x47\x16\x47\x5b\x47\x4a'\ 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b'\x70\x53\x74\x51\x77\x20\x52\x52\x54\x50\x57\x4f\x5a\x4f\x5d'\ b'\x50\x60\x54\x68\x55\x6c\x55\x70\x54\x73\x53\x75\x51\x77\x4e'\ b'\x79\x1f\x49\x5b\x56\x2e\x53\x31\x51\x34\x4f\x38\x4e\x3d\x4e'\ b'\x43\x4f\x49\x50\x4d\x53\x58\x54\x5c\x55\x62\x55\x67\x54\x6c'\ b'\x53\x6f\x51\x73\x20\x52\x53\x31\x51\x35\x50\x38\x4f\x3d\x4f'\ b'\x42\x50\x48\x51\x4c\x54\x57\x55\x5b\x56\x61\x56\x67\x55\x6c'\ b'\x53\x70\x51\x73\x4e\x76\x1f\x49\x5b\x4e\x2e\x51\x31\x53\x34'\ b'\x55\x38\x56\x3d\x56\x43\x55\x49\x54\x4d\x51\x58\x50\x5c\x4f'\ b'\x62\x4f\x67\x50\x6c\x51\x6f\x53\x73\x20\x52\x51\x31\x53\x35'\ b'\x54\x38\x55\x3d\x55\x42\x54\x48\x53\x4c\x50\x57\x4f\x5b\x4e'\ b'\x61\x4e\x67\x4f\x6c\x51\x70\x53\x73\x56\x76\x0d\x37\x5a\x3a'\ b'\x52\x41\x52\x52\x6f\x20\x52\x40\x52\x51\x6f\x20\x52\x3f\x52'\ b'\x52\x72\x20\x52\x5a\x22\x56\x4a\x52\x72\x1a\x49\x5b\x54\x4d'\ b'\x56\x4e\x58\x50\x58\x4f\x57\x4e\x54\x4d\x51\x4d\x4e\x4e\x4d'\ b'\x4f\x4c\x51\x4c\x53\x4d\x55\x4f\x57\x53\x5a\x20\x52\x51\x4d'\ b'\x4f\x4e\x4e\x4f\x4d\x51\x4d\x53\x4e\x55\x53\x5a\x54\x5c\x54'\ b'\x5e\x53\x5f\x51\x5f\x2c\x47\x5d\x4c\x4d\x4b\x4e\x4a\x50\x4a'\ b'\x52\x4b\x55\x4f\x59\x50\x5b\x20\x52\x4a\x52\x4b\x54\x4f\x58'\ b'\x50\x5b\x50\x5d\x4f\x60\x4d\x62\x4c\x62\x4b\x61\x4a\x5f\x4a'\ b'\x5c\x4b\x58\x4d\x54\x4f\x51\x52\x4e\x54\x4d\x56\x4d\x59\x4e'\ b'\x5a\x50\x5a\x54\x59\x58\x57\x5a\x55\x5b\x54\x5b\x53\x5a\x53'\ b'\x58\x54\x57\x55\x58\x54\x59\x20\x52\x56\x4d\x58\x4e\x59\x50'\ b'\x59\x54\x58\x58\x57\x5a\x44\x45\x5f\x59\x47\x58\x48\x59\x49'\ b'\x5a\x48\x59\x47\x57\x46\x54\x46\x51\x47\x4f\x49\x4e\x4b\x4d'\ b'\x4e\x4c\x52\x4a\x5b\x49\x5f\x48\x61\x20\x52\x54\x46\x52\x47'\ b'\x50\x49\x4f\x4b\x4e\x4e\x4c\x57\x4b\x5b\x4a\x5e\x49\x60\x48'\ b'\x61\x46\x62\x44\x62\x43\x61\x43\x60\x44\x5f\x45\x60\x44\x61'\ b'\x20\x52\x5f\x47\x5e\x48\x5f\x49\x60\x48\x60\x47\x5f\x46\x5d'\ b'\x46\x5b\x47\x5a\x48\x59\x4a\x58\x4d\x55\x5b\x54\x5f\x53\x61'\ b'\x20\x52\x5d\x46\x5b\x48\x5a\x4a\x59\x4e\x57\x57\x56\x5b\x55'\ b'\x5e\x54\x60\x53\x61\x51\x62\x4f\x62\x4e\x61\x4e\x60\x4f\x5f'\ b'\x50\x60\x4f\x61\x20\x52\x49\x4d\x5e\x4d\x33\x46\x5e\x5b\x47'\ b'\x5a\x48\x5b\x49\x5c\x48\x5b\x47\x58\x46\x55\x46\x52\x47\x50'\ b'\x49\x4f\x4b\x4e\x4e\x4d\x52\x4b\x5b\x4a\x5f\x49\x61\x20\x52'\ b'\x55\x46\x53\x47\x51\x49\x50\x4b\x4f\x4e\x4d\x57\x4c\x5b\x4b'\ b'\x5e\x4a\x60\x49\x61\x47\x62\x45\x62\x44\x61\x44\x60\x45\x5f'\ b'\x46\x60\x45\x61\x20\x52\x59\x4d\x57\x54\x56\x58\x56\x5a\x57'\ b'\x5b\x5a\x5b\x5c\x59\x5d\x57\x20\x52\x5a\x4d\x58\x54\x57\x58'\ b'\x57\x5a\x58\x5b\x20\x52\x4a\x4d\x5a\x4d\x35\x46\x5e\x59\x47'\ b'\x58\x48\x59\x49\x5a\x48\x5a\x47\x58\x46\x20\x52\x5c\x46\x55'\ b'\x46\x52\x47\x50\x49\x4f\x4b\x4e\x4e\x4d\x52\x4b\x5b\x4a\x5f'\ b'\x49\x61\x20\x52\x55\x46\x53\x47\x51\x49\x50\x4b\x4f\x4e\x4d'\ b'\x57\x4c\x5b\x4b\x5e\x4a\x60\x49\x61\x47\x62\x45\x62\x44\x61'\ b'\x44\x60\x45\x5f\x46\x60\x45\x61\x20\x52\x5b\x46\x57\x54\x56'\ b'\x58\x56\x5a\x57\x5b\x5a\x5b\x5c\x59\x5d\x57\x20\x52\x5c\x46'\ b'\x58\x54\x57\x58\x57\x5a\x58\x5b\x20\x52\x4a\x4d\x59\x4d\x55'\ b'\x40\x63\x54\x47\x53\x48\x54\x49\x55\x48\x54\x47\x52\x46\x4f'\ b'\x46\x4c\x47\x4a\x49\x49\x4b\x48\x4e\x47\x52\x45\x5b\x44\x5f'\ b'\x43\x61\x20\x52\x4f\x46\x4d\x47\x4b\x49\x4a\x4b\x49\x4e\x47'\ b'\x57\x46\x5b\x45\x5e\x44\x60\x43\x61\x41\x62\x3f\x62\x3e\x61'\ b'\x3e\x60\x3f\x5f\x40\x60\x3f\x61\x20\x52\x60\x47\x5f\x48\x60'\ b'\x49\x61\x48\x60\x47\x5d\x46\x5a\x46\x57\x47\x55\x49\x54\x4b'\ b'\x53\x4e\x52\x52\x50\x5b\x4f\x5f\x4e\x61\x20\x52\x5a\x46\x58'\ b'\x47\x56\x49\x55\x4b\x54\x4e\x52\x57\x51\x5b\x50\x5e\x4f\x60'\ b'\x4e\x61\x4c\x62\x4a\x62\x49\x61\x49\x60\x4a\x5f\x4b\x60\x4a'\ b'\x61\x20\x52\x5e\x4d\x5c\x54\x5b\x58\x5b\x5a\x5c\x5b\x5f\x5b'\ b'\x61\x59\x62\x57\x20\x52\x5f\x4d\x5d\x54\x5c\x58\x5c\x5a\x5d'\ b'\x5b\x20\x52\x44\x4d\x5f\x4d\x57\x40\x63\x54\x47\x53\x48\x54'\ b'\x49\x55\x48\x54\x47\x52\x46\x4f\x46\x4c\x47\x4a\x49\x49\x4b'\ b'\x48\x4e\x47\x52\x45\x5b\x44\x5f\x43\x61\x20\x52\x4f\x46\x4d'\ b'\x47\x4b\x49\x4a\x4b\x49\x4e\x47\x57\x46\x5b\x45\x5e\x44\x60'\ b'\x43\x61\x41\x62\x3f\x62\x3e\x61\x3e\x60\x3f\x5f\x40\x60\x3f'\ b'\x61\x20\x52\x5e\x47\x5d\x48\x5e\x49\x5f\x48\x5f\x47\x5d\x46'\ b'\x20\x52\x61\x46\x5a\x46\x57\x47\x55\x49\x54\x4b\x53\x4e\x52'\ b'\x52\x50\x5b\x4f\x5f\x4e\x61\x20\x52\x5a\x46\x58\x47\x56\x49'\ b'\x55\x4b\x54\x4e\x52\x57\x51\x5b\x50\x5e\x4f\x60\x4e\x61\x4c'\ b'\x62\x4a\x62\x49\x61\x49\x60\x4a\x5f\x4b\x60\x4a\x61\x20\x52'\ b'\x60\x46\x5c\x54\x5b\x58\x5b\x5a\x5c\x5b\x5f\x5b\x61\x59\x62'\ b'\x57\x20\x52\x61\x46\x5d\x54\x5c\x58\x5c\x5a\x5d\x5b\x20\x52'\ b'\x44\x4d\x5e\x4d\x13\x4c\x59\x4d\x51\x4e\x4f\x50\x4d\x53\x4d'\ b'\x54\x4e\x54\x51\x52\x57\x52\x5a\x53\x5b\x20\x52\x52\x4d\x53'\ b'\x4e\x53\x51\x51\x57\x51\x5a\x52\x5b\x55\x5b\x57\x59\x58\x57'\ b'\x15\x4c\x58\x52\x4c\x4e\x57\x58\x50\x4c\x50\x56\x57\x52\x4c'\ b'\x20\x52\x52\x52\x52\x4c\x20\x52\x52\x52\x4c\x50\x20\x52\x52'\ b'\x52\x4e\x57\x20\x52\x52\x52\x56\x57\x20\x52\x52\x52\x58\x50'\ b'\x17\x46\x5e\x49\x55\x49\x53\x4a\x50\x4c\x4f\x4e\x4f\x50\x50'\ b'\x54\x53\x56\x54\x58\x54\x5a\x53\x5b\x51\x20\x52\x49\x53\x4a'\ b'\x51\x4c\x50\x4e\x50\x50\x51\x54\x54\x56\x55\x58\x55\x5a\x54'\ b'\x5b\x51\x5b\x4f' _index =\ b'\x00\x00\x03\x00\x0a\x00\x11\x00\x18\x00\x1f\x00\x26\x00\x2d'\ b'\x00\x34\x00\x3b\x00\x42\x00\x49\x00\x50\x00\x57\x00\x5e\x00'\ b'\x65\x00\x76\x00\x87\x00\x98\x00\xa9\x00\xbc\x00\xcf\x00\xe2'\ b'\x00\xf5\x00\x00\x01\x0b\x01\x16\x01\x21\x01\x50\x01\x7f\x01'\ b'\xae\x01\xdd\x01\x08\x02\x2f\x02\x64\x02\x7b\x02\x8e\x02\x99'\ b'\x02\xa6\x02\xb9\x02\xcc\x02\xf1\x02\xfe\x02\x09\x03\x16\x03'\ b'\x2f\x03\x3c\x03\x49\x03\x5c\x03\xa3\x03\xda\x03\xfd\x03\x20'\ b'\x04\x43\x04\x66\x04\x7d\x04\xa8\x04\xc3\x04\xda\x04\xf7\x04'\ b'\x1c\x05\x23\x05\x3a\x05\x57\x05\x98\x05\xad\x05\xf2\x05\x73'\ b'\x06\x30\x07\x81\x07\xc2\x07\xe1\x07\x1a\x08\x89\x08\xe6\x08'\ b'\x23\x09\x94\x09\xb9\x09\xfc\x09\x31\x0a\x5a\x0a\xbb\x0a\x1c'\ b'\x0b\x7d\x0b\xbe\x0b\xff\x0b\x1c\x0c\x53\x0c\xae\x0c\x39\x0d'\ b'\xa2\x0d\x0f\x0e\xbc\x0e\x6d\x0f\x96\x0f\xc3\x0f' INDEX = memoryview(_index) FONT = memoryview(_font)

62.597315

64

0.707462

4,578

18,654

2.881826

0.03495

0.08459

0.04366

0.013644

0.238308

0.174259

0.14394

0.102554

0.0689

0.05321

0

0.38805

0.016672

18,654

297

65

62.808081

0.331189

0

0.969388

0.916908

0.91605

0

1

0.000429

0

1

0

false

0

null

0

1

0

1

0

1

null

1

0

6

49e790b5c991b0fbfc57fdccf92057294e4f2557

9,324

py

Python

tests/unit/test_dataset.py

victorbadenas/frarch

e75e2a63aaf14cf797ffffc901ca382b3d88b7b0

[ "Apache-2.0" ]

null

tests/unit/test_dataset.py

victorbadenas/frarch

e75e2a63aaf14cf797ffffc901ca382b3d88b7b0

[ "Apache-2.0" ]

4

2022-02-16T20:53:24.000Z

2022-02-16T21:39:26.000Z

tests/unit/test_dataset.py

victorbadenas/frarch

e75e2a63aaf14cf797ffffc901ca382b3d88b7b0

[ "Apache-2.0" ]

1

2022-03-20T23:47:16.000Z

import shutil import unittest from pathlib import Path import torch from frarch import datasets from frarch.utils.exceptions import DatasetNotFoundError DATA_FOLDER = Path(__file__).resolve().parent.parent / "data" class TestCaltech101(unittest.TestCase): MOCK_DATASET_ROOT = DATA_FOLDER / "caltech101" trainlst_path = MOCK_DATASET_ROOT / "train.lst" validlst_path = MOCK_DATASET_ROOT / "valid.lst" classjson_path = MOCK_DATASET_ROOT / "classes.json" classes = (DATA_FOLDER / "caltech101_classes.txt").read_text().split(",") @classmethod def setUpClass(cls): if cls.MOCK_DATASET_ROOT.exists(): shutil.rmtree(cls.MOCK_DATASET_ROOT) for c in cls.classes: (cls.MOCK_DATASET_ROOT / c).mkdir(parents=True, exist_ok=True) for i in range(10): (cls.MOCK_DATASET_ROOT / c / f"{i}.jpg").touch() @classmethod def tearDownClass(cls): if cls.MOCK_DATASET_ROOT.exists(): shutil.rmtree(cls.MOCK_DATASET_ROOT) def tearDown(self): if self.trainlst_path.exists(): self.trainlst_path.unlink() if self.validlst_path.exists(): self.validlst_path.unlink() if self.classjson_path.exists(): self.classjson_path.unlink() return super().tearDown() def test_build_caltech101_train(self): dataset = datasets.Caltech101("train", root=self.MOCK_DATASET_ROOT) self.assertIsInstance(dataset, torch.utils.data.Dataset) self.assertIsInstance(dataset.classes, dict) self.assertEquals(len(dataset.classes), 101) self.assertEquals(len(dataset.images), 909) self.assertEquals(dataset.train_lst_path, self.trainlst_path) self.assertEquals(dataset.valid_lst_path, self.validlst_path) self.assertEquals(dataset.mapper_path, self.classjson_path) self.assertTrue(self.trainlst_path.exists()) self.assertTrue(self.validlst_path.exists()) self.assertTrue(self.classjson_path.exists()) def test_build_caltech101_valid(self): dataset = datasets.Caltech101("valid", root=self.MOCK_DATASET_ROOT) self.assertIsInstance(dataset, torch.utils.data.Dataset) self.assertIsInstance(dataset.classes, dict) self.assertEquals(len(dataset.classes), 101) self.assertEquals(len(dataset.images), 101) self.assertEquals(dataset.train_lst_path, self.trainlst_path) self.assertEquals(dataset.valid_lst_path, self.validlst_path) self.assertEquals(dataset.mapper_path, self.classjson_path) self.assertTrue(self.trainlst_path.exists()) self.assertTrue(self.validlst_path.exists()) self.assertTrue(self.classjson_path.exists()) def test_caltech101_not_valid_subset(self): with self.assertRaises(ValueError): datasets.Caltech101("nope", root=self.MOCK_DATASET_ROOT) def test_caltech101_path_no_files(self): with self.assertRaises(DatasetNotFoundError): datasets.Caltech101("train", root="./nope/") def test_caltech101_get_length(self): dataset = datasets.Caltech101("valid", root=self.MOCK_DATASET_ROOT) self.assertEqual(len(dataset), 101) def test_caltech101_get_num_classes(self): dataset = datasets.Caltech101("valid", root=self.MOCK_DATASET_ROOT) self.assertEqual(dataset.get_number_classes(), 101) class TestMit67(unittest.TestCase): MOCK_DATASET_ROOT = DATA_FOLDER / "mit67" trainlst_path = MOCK_DATASET_ROOT / "train.lst" validlst_path = MOCK_DATASET_ROOT / "valid.lst" classjson_path = MOCK_DATASET_ROOT / "class_map.json" classes = (DATA_FOLDER / "mit67_classes.txt").read_text().split(",") @classmethod def setUpClass(cls): if cls.MOCK_DATASET_ROOT.exists(): shutil.rmtree(cls.MOCK_DATASET_ROOT) for c in cls.classes: (cls.MOCK_DATASET_ROOT / "Images" / c).mkdir(parents=True, exist_ok=True) for i in range(10): (cls.MOCK_DATASET_ROOT / "Images" / c / f"{i}.jpg").touch() @classmethod def tearDownClass(cls): if cls.MOCK_DATASET_ROOT.exists(): shutil.rmtree(cls.MOCK_DATASET_ROOT) def tearDown(self): if self.trainlst_path.exists(): self.trainlst_path.unlink() if self.validlst_path.exists(): self.validlst_path.unlink() if self.classjson_path.exists(): self.classjson_path.unlink() return super().tearDown() def test_build_mit67_train(self): dataset = datasets.Mit67(True, root=self.MOCK_DATASET_ROOT) self.assertIsInstance(dataset, torch.utils.data.Dataset) self.assertIsInstance(dataset.classes, dict) self.assertEquals(len(dataset.classes), 67) self.assertEquals(len(dataset.images), 603) self.assertEquals(dataset.train_lst_path, self.trainlst_path) self.assertEquals(dataset.valid_lst_path, self.validlst_path) self.assertEquals(dataset.mapper_path, self.classjson_path) self.assertTrue(self.trainlst_path.exists()) self.assertTrue(self.validlst_path.exists()) self.assertTrue(self.classjson_path.exists()) def test_build_mit67_valid(self): dataset = datasets.Mit67(False, root=self.MOCK_DATASET_ROOT) self.assertIsInstance(dataset, torch.utils.data.Dataset) self.assertIsInstance(dataset.classes, dict) self.assertEquals(len(dataset.classes), 67) self.assertEquals(len(dataset.images), 67) self.assertEquals(dataset.train_lst_path, self.trainlst_path) self.assertEquals(dataset.valid_lst_path, self.validlst_path) self.assertEquals(dataset.mapper_path, self.classjson_path) self.assertTrue(self.trainlst_path.exists()) self.assertTrue(self.validlst_path.exists()) self.assertTrue(self.classjson_path.exists()) def test_mit67_path_no_files(self): with self.assertRaises(DatasetNotFoundError): datasets.Mit67(True, root="./nope/", download=False) def test_caltech101_get_length(self): dataset = datasets.Mit67(False, root=self.MOCK_DATASET_ROOT) self.assertEqual(len(dataset), 67) def test_caltech101_get_num_classes(self): dataset = datasets.Mit67(False, root=self.MOCK_DATASET_ROOT) self.assertEqual(dataset.get_number_classes(), 67) class TestOxfordPets(unittest.TestCase): MOCK_DATASET_ROOT = DATA_FOLDER / "oxfordpets" trainlst_path = MOCK_DATASET_ROOT / "annotations" / "trainval.txt" validlst_path = MOCK_DATASET_ROOT / "annotations" / "test.txt" @classmethod def setUpClass(cls): if cls.MOCK_DATASET_ROOT.exists(): shutil.rmtree(cls.MOCK_DATASET_ROOT) cls.MOCK_DATASET_ROOT.mkdir(exist_ok=True, parents=True) (cls.MOCK_DATASET_ROOT / "images").mkdir(exist_ok=True, parents=True) shutil.copytree( str(DATA_FOLDER / "oxford_pets_lst"), str(cls.trainlst_path.parent) ) with open(DATA_FOLDER / "oxford_pets_lst" / "trainval.txt") as f: for line in f: fname = line.split(" ")[0] (cls.MOCK_DATASET_ROOT / "images" / f"{fname}.jpg").touch() @classmethod def tearDownClass(cls): if cls.MOCK_DATASET_ROOT.exists(): shutil.rmtree(cls.MOCK_DATASET_ROOT) def test_build_OxfordPets_train(self): dataset = datasets.OxfordPets("train", root=self.MOCK_DATASET_ROOT) self.assertIsInstance(dataset, torch.utils.data.Dataset) self.assertIsInstance(dataset.classes, set) self.assertEquals(len(dataset.classes), 37) self.assertEquals(len(dataset.images), 3680) self.assertEquals(dataset.train_lst_path, self.trainlst_path) self.assertEquals(dataset.valid_lst_path, self.validlst_path) self.assertTrue(self.trainlst_path.exists()) self.assertTrue(self.validlst_path.exists()) def test_build_OxfordPets_valid(self): dataset = datasets.OxfordPets("valid", root=self.MOCK_DATASET_ROOT) self.assertIsInstance(dataset, torch.utils.data.Dataset) self.assertIsInstance(dataset.classes, set) self.assertEquals(len(dataset.classes), 37) self.assertEquals(len(dataset.images), 3669) self.assertEquals(dataset.train_lst_path, self.trainlst_path) self.assertEquals(dataset.valid_lst_path, self.validlst_path) self.assertTrue(self.trainlst_path.exists()) self.assertTrue(self.validlst_path.exists()) def test_OxfordPets_path_no_files(self): with self.assertRaises(DatasetNotFoundError): datasets.OxfordPets("valid", root="./nope/", download=False) def test_OxfordPets_not_valid_subset(self): with self.assertRaises(ValueError): datasets.OxfordPets("nope", root=self.MOCK_DATASET_ROOT, download=False) def test_OxfordPets_get_length(self): dataset = datasets.OxfordPets("valid", root=self.MOCK_DATASET_ROOT) self.assertEqual(len(dataset), 3669) def test_OxfordPets_get_num_classes(self): dataset = datasets.OxfordPets("valid", root=self.MOCK_DATASET_ROOT) self.assertEqual(dataset.get_number_classes(), 37) if __name__ == "__main__": unittest.main()

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b721245ec6635464eec11f01500c633ddbfbbed4

21

py

Python

mva/__init__.py

garovent/mva

47ec8690003bbabbbdb59eb6ed8f7e02b0019fe5

[ "Apache-2.0" ]

1

2022-02-02T15:30:19.000Z

mva/__init__.py

garovent/mva

47ec8690003bbabbbdb59eb6ed8f7e02b0019fe5

[ "Apache-2.0" ]

null

mva/__init__.py

garovent/mva

47ec8690003bbabbbdb59eb6ed8f7e02b0019fe5

[ "Apache-2.0" ]

null

from .mva import mva

10.5

20

0.761905

4

21

4

0.75

0

0.190476

21

1

21

0.941176

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true

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1

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

b741cda8ba7c53c12f6d0359562d0130f04c95e0

24

py

Python

learning/__init__.py

BarryZM/KnowYouAI

8c9d96238090fa8fd70b8581ac536bb1b0691eb5

[ "MIT" ]

null

learning/__init__.py

BarryZM/KnowYouAI

8c9d96238090fa8fd70b8581ac536bb1b0691eb5

[ "MIT" ]

null

learning/__init__.py

BarryZM/KnowYouAI

8c9d96238090fa8fd70b8581ac536bb1b0691eb5

[ "MIT" ]

1

2020-12-31T11:13:30.000Z

from .learn import Learn

24

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4

24

5

0.75

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1

24

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true

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null

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1

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6

3f96e12f2cc3c9d04813e8a782b2e456aead8bec

26,280

py

Python

pkgs/conf-pkg/src/genie/libs/conf/l2vpn/iosxr/xconnect.py

kecorbin/genielibs

5d3951b8911013691822e73e9c3d0f557ca10f43

[ "Apache-2.0" ]

null

pkgs/conf-pkg/src/genie/libs/conf/l2vpn/iosxr/xconnect.py

kecorbin/genielibs

5d3951b8911013691822e73e9c3d0f557ca10f43

[ "Apache-2.0" ]

null

pkgs/conf-pkg/src/genie/libs/conf/l2vpn/iosxr/xconnect.py

kecorbin/genielibs

5d3951b8911013691822e73e9c3d0f557ca10f43

[ "Apache-2.0" ]

null

# Xconnect # DeviceAttributes (device_attr) # AutodiscoveryBgpAttributes (autodiscovery_bgp) # parent = xconnect.autodiscovery_bgp # SignalingProtocolBgpAttributes (signaling_protocol_bgp) # parent = xconnect.autodiscovery_bgp.signaling_protocol_bgp # CeAttributes (ce_attr) # InterfaceAttributes (interface_attr) # # DeviceAutodiscoveryBgpAttributesDefaults (autodiscovery_bgp) (no config) # DeviceSignalingProtocolBgpAttributesDefaults (signaling_protocol_bgp) (no config) from abc import ABC import warnings import contextlib from genie.conf.base.attributes import UnsupportedAttributeWarning,\ AttributesHelper from genie.conf.base.cli import CliConfigBuilder from genie.conf.base.config import CliConfig from genie.libs.conf.l2vpn.pseudowire import PseudowireNeighbor,\ PseudowireIPv4Neighbor, PseudowireIPv6Neighbor, PseudowireEviNeighbor from ..xconnect import Xconnect as _Xconnect class Xconnect(ABC): class DeviceAttributes(ABC): class NeighborAttributes(ABC): def build_config(self, apply=True, attributes=None, unconfig=False, **kwargs): assert not apply assert not kwargs, kwargs attributes = AttributesHelper(self, attributes) configurations = CliConfigBuilder(unconfig=unconfig) nbr_ctx = None nbr_is_submode = True if isinstance(self.neighbor, PseudowireIPv4Neighbor): # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 (config-l2vpn) assert self.ip is not None assert self.pw_id is not None nbr_ctx = attributes.format('neighbor ipv4 {ip} pw-id {pw_id}', force=True) elif isinstance(self.neighbor, PseudowireIPv6Neighbor): # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 (config-l2vpn) assert self.ip is not None assert self.pw_id is not None nbr_ctx = attributes.format('neighbor ipv6 {ip} pw-id {pw_id}', force=True) elif isinstance(self.neighbor, PseudowireEviNeighbor): # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor evpn evi 1 target 1 source 1 assert self.evi is not None assert self.ac_id is not None assert self.source_ac_id is not None nbr_ctx = attributes.format('neighbor evpn evi {evi.evi_id} target {ac_id} source {source_ac_id}', force=True) nbr_is_submode = False else: raise ValueError(self.neighbor) assert nbr_ctx if not nbr_is_submode: configurations.append_line(nbr_ctx) else: with configurations.submode_context(nbr_ctx): # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / backup neighbor 1.2.3.4 pw-id 1 (config-l2vpn) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / backup neighbor 1.2.3.4 pw-id 1 / mpls static label local 16 remote 16 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / backup neighbor 1.2.3.4 pw-id 1 / pw-class someword3 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / backup neighbor 1.2.3.4 pw-id 1 (config-l2vpn) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / backup neighbor 1.2.3.4 pw-id 1 / mpls static label local 16 remote 16 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / backup neighbor 1.2.3.4 pw-id 1 / pw-class someword3 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / bandwidth <0-4294967295> # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / bandwidth <0-4294967295> # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static (config-l2vpn) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / local cookie size 0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / local cookie size 4 value 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / local cookie size 8 value 0x0 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / local session 1 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / remote cookie size 0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / remote cookie size 4 value 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / remote cookie size 8 value 0x0 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / l2tp static / remote session 1 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static (config-l2vpn) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local cookie secondary size 0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local cookie secondary size 4 value 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local cookie secondary size 8 value 0x0 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local cookie size 0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local cookie size 4 value 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local cookie size 8 value 0x0 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / local session 1 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / remote cookie size 0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / remote cookie size 4 value 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / remote cookie size 8 value 0x0 0x0 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / l2tp static / remote session 1 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / mpls static label local 16 remote 16 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / mpls static label local 16 remote 16 remote_label = attributes.value('mpls_static_label') if remote_label is not None: local_label = self.parent.neighbor_attr[self.remote_neighbor].mpls_static_label if local_label is None: warnings.warn( 'neighbor {!r} mpls_static_label missing'.format(self.remote_neighbor), UnsupportedAttributeWarning) else: configurations.append_line('mpls static label local {} remote {}'.\ format(local_label, remote_label)) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / pw-class someword3 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / pw-class someword3 v = attributes.value('pw_class') if v is not None: configurations.append_line('pw-class {}'.\ format(v.device_attr[self.device].name)) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / source 1:2::3 elif isinstance(self.neighbor, PseudowireIPv6Neighbor): configurations.append_line(attributes.format('ipv6 source {ipv6_source}')) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor [ipv4] 1.2.3.4 pw-id 1 / tag-impose vlan 1 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 / tag-impose vlan 1 return str(configurations) def build_unconfig(self, apply=True, attributes=None, **kwargs): return self.build_config(apply=apply, attributes=attributes, unconfig=True, **kwargs) class AutodiscoveryBgpAttributes(ABC): class SignalingProtocolBgpAttributes(ABC): class CeAttributes(ABC): class InterfaceAttributes(ABC): def build_config(self, apply=True, attributes=None, unconfig=False, **kwargs): assert not apply assert not kwargs, kwargs attributes = AttributesHelper(self, attributes) configurations = CliConfigBuilder(unconfig=unconfig) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / ce-id 1 / interface Bundle-Ether1 remote-ce-id 1 configurations.append_line(attributes.format('interface {interface_name} remote-ce-id {remote_ce_id}', force=True)) return str(configurations) def build_unconfig(self, apply=True, attributes=None, **kwargs): return self.build_config(apply=apply, attributes=attributes, unconfig=True, **kwargs) #CeAttributes def build_config(self, apply=True, attributes=None, unconfig=False, **kwargs): assert not apply assert not kwargs, kwargs attributes = AttributesHelper(self, attributes) configurations = CliConfigBuilder(unconfig=unconfig) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / ce-id 1 (config-l2vpn) with configurations.submode_context(attributes.format('ce-id {ce_id}', force=True)): if unconfig and attributes.iswildcard: configurations.submode_unconfig() # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / ce-id 1 / interface Bundle-Ether1 remote-ce-id 1 for ns, attributes2 in attributes.mapping_values('interface_attr', keys=self.interfaces, sort=True): configurations.append_block(ns.build_config(apply=False, unconfig=unconfig, attributes=attributes2)) return str(configurations) def build_unconfig(self, apply=True, attributes=None, **kwargs): return self.build_config(apply=apply, attributes=attributes, unconfig=True, **kwargs) #SignalingProtocolBgpAttributes def build_config(self, apply=True, attributes=None, unconfig=False, **kwargs): assert not apply assert not kwargs, kwargs attributes = AttributesHelper(self, attributes) configurations = CliConfigBuilder(unconfig=unconfig) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp (config-l2vpn) with configurations.submode_context('signaling-protocol bgp'): if not attributes.value('enabled', force=True): configurations.submode_cancel() # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / ce-range 11 configurations.append_line(attributes.format('ce-range {ce_range}')) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / ce-id 1 (config-l2vpn) for ns, attributes2 in attributes.mapping_values('ce_attr', keys=self.ce_ids, sort=True): configurations.append_block(ns.build_config(apply=False, unconfig=unconfig, attributes=attributes2)) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label both # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label both static # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label receive # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label receive static # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label transmit # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label transmit static # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label both # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label both static # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label receive # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label receive static # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label transmit # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp / load-balancing flow-label transmit static return str(configurations) def build_unconfig(self, apply=True, attributes=None, **kwargs): return self.build_config(apply=apply, attributes=attributes, unconfig=True, **kwargs) #AutodiscoveryBgpAttributes def build_config(self, apply=True, attributes=None, unconfig=False, **kwargs): assert not apply assert not kwargs, kwargs attributes = AttributesHelper(self, attributes) configurations = CliConfigBuilder(unconfig=unconfig) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp (config-l2vpn) with configurations.submode_context('autodiscovery bgp'): if not attributes.value('enabled', force=True): configurations.submode_cancel() # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / rd 100000:200 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / rd 100:200000 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / rd 1.2.3.4:1 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / rd auto configurations.append_line(attributes.format('rd {rd}')) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-policy export <rtepol> # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target 100000:200 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target 100:200000 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target 1.2.3.4:1 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target export 100000:200 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target export 100:200000 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target export 1.2.3.4:1 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target export import 100000:200 (bug) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target export import 100:200000 (bug) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target export import 1.2.3.4:1 (bug) both_route_targets = set(self.export_route_targets) & set(self.import_route_targets) for v, attributes2 in attributes.sequence_values('export_route_targets', sort=True): if v in both_route_targets: cfg = 'route-target {}'.format(v.route_target) else: cfg = 'route-target export {}'.format(v.route_target) if v.stitching: warning.warn(UnsupportedAttributeWarning, 'route-target export/import stitching') configurations.append_line(cfg) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target import 100000:200 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target import 100:200000 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / route-target import 1.2.3.4:1 for v, attributes2 in attributes.sequence_values('import_route_targets', sort=True): if v not in both_route_targets: cfg = 'route-target import {}'.format(v.route_target) if v.stitching: warning.warn(UnsupportedAttributeWarning, 'route-target export/import stitching') configurations.append_line(cfg) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp / signaling-protocol bgp (config-l2vpn) ns, attributes2 = attributes.namespace('signaling_protocol_bgp') if ns: configurations.append_block(ns.build_config(apply=False, unconfig=unconfig, attributes=attributes2)) return str(configurations) def build_unconfig(self, apply=True, attributes=None, **kwargs): return self.build_config(apply=apply, attributes=attributes, unconfig=True, **kwargs) def build_config(self, apply=True, attributes=None, unconfig=False, contained=False, **kwargs): assert not kwargs, kwargs attributes = AttributesHelper(self, attributes) configurations = CliConfigBuilder(unconfig=unconfig) # iosxr: l2vpn (config-l2vpn) submode_stack = contextlib.ExitStack() if not contained: submode_stack.enter_context( configurations.submode_context('l2vpn')) # iosxr: l2vpn / xconnect group someword (config-l2vpn) with configurations.submode_context(attributes.format('xconnect group {group_name}', force=True, cancel_empty=True)): if self.xconnect_type is _Xconnect.Type.mp2mp: # iosxr: l2vpn / xconnect group someword / mp2mp someword2 (config-l2vpn) with configurations.submode_context(attributes.format('mp2mp {name}', force=True)): if unconfig and attributes.iswildcard: configurations.submode_unconfig() # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / control-word disable # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / interworking ethernet # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / l2-encapsulation ethernet # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / l2-encapsulation vlan # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / mtu 64 # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / shutdown # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / vpn-id 1 configurations.append_line(attributes.format('vpn-id {vpn_id}')) # iosxr: l2vpn / xconnect group someword / mp2mp someword2 / autodiscovery bgp (config-l2vpn) ns, attributes2 = attributes.namespace('autodiscovery_bgp') if ns: configurations.append_block(ns.build_config(apply=False, unconfig=unconfig, attributes=attributes2)) elif self.xconnect_type is _Xconnect.Type.p2p: # iosxr: l2vpn / xconnect group someword / p2p someword2 (config-l2vpn) with configurations.submode_context(attributes.format('p2p {name}', force=True)): if unconfig and attributes.iswildcard: configurations.submode_unconfig() # iosxr: l2vpn / xconnect group someword / p2p someword2 / backup interface Bundle-Ether1 # iosxr: l2vpn / xconnect group someword / p2p someword2 / description someword3 configurations.append_line(attributes.format('description {description}')) # iosxr: l2vpn / xconnect group someword / p2p someword2 / interface Bundle-Ether1 for interface, attributes2 in attributes.sequence_values('interfaces', sort=True): configurations.append_line('interface {}'.\ format(interface.name)) # iosxr: l2vpn / xconnect group someword / p2p someword2 / interworking ethernet # iosxr: l2vpn / xconnect group someword / p2p someword2 / interworking ipv4 configurations.append_line(attributes.format('interworking {interworking}')) # iosxr: l2vpn / xconnect group someword / p2p someword2 / monitor-session someword3 # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor 1.2.3.4 pw-id 1 (config-l2vpn) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv4 1.2.3.4 pw-id 1 (config-l2vpn) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor ipv6 1:2::3 pw-id 1 (config-l2vpn) for sub, attributes2 in attributes.mapping_values('neighbor_attr', keys=self.pseudowire_neighbors, sort=True): configurations.append_block( sub.build_config(apply=False, attributes=attributes2, unconfig=unconfig)) # iosxr: l2vpn / xconnect group someword / p2p someword2 / neighbor evpn evi 1 target 1 source 1 else: warnings.warn( 'xconnect type mode {}'.format(self.xconnect_type), UnsupportedAttributeWarning) submode_stack.close() if apply: if configurations: self.device.configure(str(configurations), fail_invalid=True) else: return CliConfig(device=self.device, unconfig=unconfig, cli_config=configurations, fail_invalid=True) def build_unconfig(self, apply=True, attributes=None, **kwargs): return self.build_config(apply=apply, attributes=attributes, unconfig=True, **kwargs)

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Python

pyne/tests/test_source_sampling.py

AllSafeCyberSecur1ty/Nuclear-Engineering

302d6dcc7c0a85a9191098366b076cf9cb5a9f6e

[ "MIT" ]

1

2022-03-26T20:01:13.000Z

pyne/tests/test_source_sampling.py

AllSafeCyberSecur1ty/Nuclear-Engineering

302d6dcc7c0a85a9191098366b076cf9cb5a9f6e

[ "MIT" ]

null

pyne/tests/test_source_sampling.py

AllSafeCyberSecur1ty/Nuclear-Engineering

302d6dcc7c0a85a9191098366b076cf9cb5a9f6e

[ "MIT" ]

1

2022-03-26T19:59:13.000Z

import os import warnings import itertools from operator import itemgetter from nose.tools import assert_equal, with_setup, assert_almost_equal, assert_raises from random import uniform, seed import numpy as np from numpy.testing import assert_array_equal, assert_array_almost_equal try: from pyne.mesh import Mesh # see if the source sampling module exists but do not import it import imp pyne_info = imp.find_module("pyne") pyne_mod = imp.load_module("pyne", *pyne_info) imp.find_module("source_sampling", pyne_mod.__path__) except ImportError: from nose.plugins.skip import SkipTest raise SkipTest from pyne.source_sampling import Sampler, AliasTable from pyne.mesh import Mesh, NativeMeshTag from pyne.r2s import tag_e_bounds from pymoab import core as mb_core, types from pyne.utils import QAWarning warnings.simplefilter("ignore", QAWarning) # Define modes DEFAULT_ANALOG = 0 DEFAULT_UNIFORM = 1 DEFAULT_USER = 2 SUBVOXEL_ANALOG = 3 SUBVOXEL_UNIFORM = 4 SUBVOXEL_USER = 5 def try_rm_file(filename): return lambda: os.remove(filename) if os.path.exists(filename) else None @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_single_hex_tag_names_map(): """This test tests uniform sampling within a single hex volume element. This is done by dividing the volume element in 4 smaller hex and ensuring that each sub-hex is sampled equally. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 3, 3.5], [0, 1], [0, 1]], mats=None ) m.src = NativeMeshTag(2, float) m.src[:] = [[2.0, 1.0], [9.0, 3.0]] e_bounds = np.array([0, 0.5, 1.0]) m = tag_e_bounds(m, e_bounds) m.bias = NativeMeshTag(2, float) cell_fracs = np.zeros( 2, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0), (1, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) m.bias[:] = [[1.0, 2.0], [3.0, 3.0]] filename = "sampling_mesh.h5m" m.write_hdf5(filename) # right condition with e_bounds in 'source.h5m' tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, DEFAULT_ANALOG) # right condition with e_bounds provided by both 'e_bounds' and 'source.h5m' tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, DEFAULT_ANALOG) # src_tag_name not given tag_names = { "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_ANALOG) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_UNIFORM) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_USER) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_ANALOG) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_UNIFORM) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_USER) # bias_tag_name not given tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_USER) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_USER) # cell_number_tag_name not given tag_names = { "src_tag_name": "src", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_ANALOG) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_UNIFORM) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_USER) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_ANALOG) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_UNIFORM) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_USER) # cell_fracs_tag_name not given tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "e_bounds_tag_name": "e_bounds", } assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_ANALOG) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_UNIFORM) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, DEFAULT_USER) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_ANALOG) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_UNIFORM) assert_raises(ValueError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_USER) # wrong bias_tag data (non-zero source_density biased to zero -> NAN weight) m.src = NativeMeshTag(2, float) m.src[:] = [[1.0, 1.0]] m.bias = NativeMeshTag(2, float) m.bias[:] = [[0.0, 0.0]] m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "bias_tag_name": "bias", "e_bounds_tag_name": "e_bounds", } assert_raises(RuntimeError, Sampler, filename, tag_names, e_bounds, SUBVOXEL_USER) @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_analog_single_hex(): """This test tests that particles of sampled evenly within the phase-space of a single mesh volume element with one energy group in an analog sampling scheme. This done by dividing each dimension (x, y, z, E) in half, then sampling particles and tallying on the basis of which of the 2^4 = 8 regions of phase space the particle is born into. """ seed(1953) m = Mesh(structured=True, structured_coords=[[0, 1], [0, 1], [0, 1]], mats=None) m.src = NativeMeshTag(1, float) m.src[0] = 1.0 cell_fracs = np.zeros( 1, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) e_bounds = np.array([0, 1.0]) m = tag_e_bounds(m, e_bounds) filename = "sampling_mesh.h5m" m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, DEFAULT_ANALOG) num_samples = 5000 score = 1.0 / num_samples num_divs = 2 tally = np.zeros(shape=(num_divs, num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0, 1) for x in range(6)])) assert_equal(s.w, 1.0) # analog: all weights must be one tally[ int(s.x * num_divs), int(s.y * num_divs), int(s.z * num_divs), int(s.e * num_divs), ] += score # Test that each half-space of phase space (e.g. x > 0.5) is sampled about # half the time. for i in range(0, 4): for j in range(0, 2): assert abs(np.sum(np.rollaxis(tally, i)[j, :, :, :]) - 0.5) < 0.05 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_analog_multiple_hex(): """This test tests that particle are sampled uniformly from a uniform source defined on eight mesh volume elements in two energy groups. This is done using the exact same method ass test_analog_multiple_hex. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 0.5, 1], [0, 0.5, 1], [0, 0.5, 1]], mats=None, ) m.src = NativeMeshTag(2, float) m.src[:] = np.ones(shape=(8, 2)) cell_fracs = np.zeros( 8, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [ (0, 11, 1.0, 0.0), (1, 11, 1.0, 0.0), (2, 11, 1.0, 0.0), (3, 11, 1.0, 0.0), (4, 11, 1.0, 0.0), (5, 11, 1.0, 0.0), (6, 11, 1.0, 0.0), (7, 11, 1.0, 0.0), ] m.tag_cell_fracs(cell_fracs) filename = "sampling_mesh.h5m" e_bounds = np.array([0, 0.5, 1]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, DEFAULT_ANALOG) num_samples = 5000 score = 1.0 / num_samples num_divs = 2 tally = np.zeros(shape=(num_divs, num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth([uniform(0, 1) for x in range(6)]) assert_equal(s.w, 1.0) tally[ int(s.x * num_divs), int(s.y * num_divs), int(s.z * num_divs), int(s.e * num_divs), ] += score for i in range(0, 4): for j in range(0, 2): halfspace_sum = np.sum(np.rollaxis(tally, i)[j, :, :, :]) assert abs(halfspace_sum - 0.5) / 0.5 < 0.1 @with_setup(None, try_rm_file("tet.h5m")) def test_analog_single_tet(): """This test tests uniform sampling within a single tetrahedron. This is done by dividing the tetrahedron in 4 smaller tetrahedrons and ensuring that each sub-tet is sampled equally. """ seed(1953) mesh = mb_core.Core() v1 = [0.0, 0.0, 0.0] v2 = [1.0, 0.0, 0.0] v3 = [0.0, 1.0, 0.0] v4 = [0.0, 0.0, 1.0] verts = mesh.create_vertices([v1, v2, v3, v4]) mesh.create_element(types.MBTET, verts) m = Mesh(structured=False, mesh=mesh) m.src = NativeMeshTag(1, float) m.src[:] = np.array([1]) filename = "tet.h5m" e_bounds = np.array([0.0, 1.0]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) center = m.ve_center(list(m.iter_ve())[0]) subtets = [ [center, v1, v2, v3], [center, v1, v2, v4], [center, v1, v3, v4], [center, v2, v3, v4], ] tag_names = {"src_tag_name": "src", "e_bounds_tag_name": "e_bounds"} sampler = Sampler(filename, tag_names, np.array([0.0, 1.0]), DEFAULT_ANALOG) num_samples = 5000 score = 1.0 / num_samples tally = np.zeros(shape=(4)) for i in range(num_samples): s = sampler.particle_birth([uniform(0.0, 1.0) for x in range(6)]) assert_equal(s.w, 1.0) for i, tet in enumerate(subtets): if point_in_tet(tet, [s.x, s.y, s.z]): tally[i] += score break for t in tally: assert abs(t - 0.25) / 0.25 < 0.2 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_uniform(): """This test tests that the uniform biasing scheme: 1. Samples space uniformly. This is checked using the same method described in test_analog_single_hex(). 2. Adjusts weights accordingly. Sample calculations are provided in Case 1 in the Theory Manual. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 3, 3.5], [0.0, 1.0], [0.0, 1.0]], mats=None, ) m.src = NativeMeshTag(2, float) m.src[:] = [[2.0, 1.0], [9.0, 3.0]] e_bounds = np.array([0.0, 0.5, 1.0]) filename = "sampling_mesh.h5m" cell_fracs = np.zeros( 2, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0), (1, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, DEFAULT_UNIFORM) num_samples = 10000 score = 1.0 / num_samples num_divs = 2 num_e = 2 spatial_tally = np.zeros(shape=(num_divs, num_divs, num_divs)) e_tally = np.zeros(shape=(4)) # number of phase space groups for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0, 1) for x in range(6)])) if s.x < 3.0: assert_almost_equal(s.w, 0.7) # hand calcs else: assert_almost_equal(s.w, 2.8) # hand calcs spatial_tally[ int(s.x * num_divs / 3.5), int(s.y * num_divs / 1.0), int(s.z * num_divs / 1.0), ] += score if s.x < 3 and s.e < 0.5: e_tally[0] += score elif s.x < 3 and s.e > 0.5: e_tally[1] += score if s.x > 3 and s.e < 0.5: e_tally[2] += score if s.x > 3 and s.e > 0.5: e_tally[3] += score for i in range(0, 3): for j in range(0, 2): halfspace_sum = np.sum(np.rollaxis(spatial_tally, i)[j, :, :]) assert abs(halfspace_sum - 0.5) / 0.5 < 0.1 expected_e_tally = [4.0 / 7, 2.0 / 7, 3.0 / 28, 1.0 / 28] # hand calcs for i in range(4): assert abs(e_tally[i] - expected_e_tally[i]) / expected_e_tally[i] < 0.1 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_single_hex_single_subvoxel_analog(): """This test tests that particles of sampled evenly within the phase-space of a single mesh volume element (also a sub-voxel) with one energy group in an analog sampling scheme. This done by dividing each dimension (x, y, z, E) in half, then sampling particles and tallying on the basis of which of the 2^4 = 16 regions of phase space the particle is born into. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]], mats=None, ) m.src = NativeMeshTag(1, float) m.src[0] = 1.0 cell_fracs = np.zeros( 1, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) filename = "sampling_mesh.h5m" e_bounds = np.array([0.0, 1.0]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_ANALOG) num_samples = 5000 score = 1.0 / num_samples num_divs = 2 tally = np.zeros(shape=(num_divs, num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0.0, 1.0) for x in range(6)])) assert_equal(s.w, 1.0) # analog: all weights must be one assert_equal(s.cell_list[0], 11) # analog: the cell number tally[ int(s.x * num_divs), int(s.y * num_divs), int(s.z * num_divs), int(s.e * num_divs), ] += score # Test that each half-space of phase space (e.g. x > 0.5) is sampled about # half the time. for i in range(0, 4): for j in range(0, 2): assert abs(np.sum(np.rollaxis(tally, i)[j, :, :, :]) - 0.5) < 0.05 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_single_hex_multiple_subvoxel_analog(): """This test tests that particles of sampled analog within the phase-space of a single mesh volume element but multiple sub-voxels with one energy group in an analog sampling scheme. Then sampling particles and tallying the particles and check the probability of particles born in each sub-voxel and the cell_number. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]], mats=None, ) m.src = NativeMeshTag(3, float) m.src[:] = np.empty(shape=(1, 3)) m.src[0] = [0, 0.2, 0.8] cell_fracs = np.zeros( 3, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 0.4, 0.0), (0, 12, 0.3, 0.0), (0, 13, 0.3, 0.0)] m.tag_cell_fracs(cell_fracs) # cell_fracs will be sorted filename = "sampling_mesh.h5m" e_bounds = np.array([0, 1]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_ANALOG) num_samples = 50000 score = 1.0 / num_samples num_divs = 2 tally = [0.0] * 3 for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0, 1) for x in range(6)])) assert_equal(s.w, 1.0) # analog: all weights must be one if s.cell_list[0] == 11: tally[0] += score elif s.cell_list[0] == 12: tally[1] += score elif s.cell_list[0] == 13: tally[2] += score # Test that each source particle in each cell has right frequency assert_equal(tally[0], 0.0) assert abs(tally[1] - 0.2) / 0.2 < 0.05 assert abs(tally[2] - 0.8) / 0.8 < 0.05 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_multiple_hex_multiple_subvoxel_analog(): """This test tests that particle are sampled analog from a uniform source defined on eight mesh volume elements in two energy groups. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 0.5, 1], [0, 0.5, 1], [0, 0.5, 1]], mats=None, ) m.src = NativeMeshTag(2, float) m.src[:] = np.ones(shape=(8, 2)) cell_fracs = np.zeros( 8, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [ (0, 1, 1.0, 0.0), (1, 2, 1.0, 0.0), (2, 3, 1.0, 0.0), (3, 4, 1.0, 0.0), (4, 5, 1.0, 0.0), (5, 6, 1.0, 0.0), (6, 7, 1.0, 0.0), (7, 8, 1.0, 0.0), ] m.tag_cell_fracs(cell_fracs) filename = "sampling_mesh.h5m" e_bounds = np.array([0, 0.5, 1]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_ANALOG) num_samples = 5000 score = 1.0 / num_samples num_divs = 2 tally = np.zeros(shape=(num_divs, num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth([uniform(0, 1) for x in range(6)]) assert_equal(s.w, 1.0) assert_equal( s.cell_list[0], 4 * int(s.x * num_divs) + 2 * int(s.y * num_divs) + int(s.z * num_divs) + 1, ) tally[ int(s.x * num_divs), int(s.y * num_divs), int(s.z * num_divs), int(s.e * num_divs), ] += score for i in range(0, 4): for j in range(0, 2): halfspace_sum = np.sum(np.rollaxis(tally, i)[j, :, :, :]) assert abs(halfspace_sum - 0.5) / 0.5 < 0.1 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_single_hex_subvoxel_uniform(): """This test tests that particles of sampled evenly within the phase-space of a single mesh volume element with one energy group in an uniform sampling scheme. This done by dividing each dimension (x, y, z, E) in half, then sampling particles and tallying on the basis of which of the 2^4 = 8 regions of phase space the particle is born into. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]], mats=None, ) m.src = NativeMeshTag(1, float) m.src[0] = 1.0 cell_fracs = np.zeros( 1, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) filename = "sampling_mesh.h5m" e_bounds = np.array([0.0, 1.0]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_UNIFORM) num_samples = 5000 score = 1.0 / num_samples num_divs = 2 tally = np.zeros(shape=(num_divs, num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0.0, 1.0) for x in range(6)])) assert_equal(s.w, 1.0) # analog: all weights must be one assert_equal(s.cell_list[0], 11) # analog: the cell number tally[ int(s.x * num_divs), int(s.y * num_divs), int(s.z * num_divs), int(s.e * num_divs), ] += score # Test that each half-space of phase space (e.g. x > 0.5) is sampled about # half the time. for i in range(0, 4): for j in range(0, 2): assert abs(np.sum(np.rollaxis(tally, i)[j, :, :, :]) - 0.5) < 0.05 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_single_hex_multiple_subvoxel_uniform(): """This test tests that particles of sampled evenly within the phase-space of a single mesh volume element with one energy group in an uniform sampling scheme. This done by dividing each dimension (x, y, z, E) in half, then sampling particles and tallying on the basis of which of the 2^4 = 8 regions of phase space the particle is born into. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]], mats=None, ) m.src = NativeMeshTag(3, float) m.src[:] = np.empty(shape=(1, 3)) m.src[0] = [0, 0.2, 0.8] cell_fracs = np.zeros( 3, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 0.4, 0.0), (0, 12, 0.3, 0.0), (0, 13, 0.3, 0.0)] m.tag_cell_fracs(cell_fracs) filename = "sampling_mesh.h5m" e_bounds = np.array([0.0, 1.0]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_UNIFORM) num_samples = 5000 score = 1.0 / num_samples num_divs = 2 tally = [0.0] * 3 for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0.0, 1.0) for x in range(6)])) if s.cell_list[0] == 11: tally[0] += score if s.cell_list[0] == 12: tally[1] += score # analog: all weights must be one assert abs(s.w - 0.4) / 0.4 < 0.05 if s.cell_list[0] == 13: tally[2] += score assert abs(s.w - 1.6) / 1.6 < 0.05 # Test that each source particle in each cell has right frequency assert_equal(tally[0], 0.0) assert abs(tally[1] - 0.5) < 0.05 assert abs(tally[2] - 0.5) < 0.05 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_multiple_hex_multiple_subvoxel_uniform(): """This test tests that particle are sampled uniformly from a uniform source defined on eight mesh volume elements in two energy groups. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 0.5, 1], [0, 0.5, 1], [0, 0.5, 1]], mats=None, ) m.src = NativeMeshTag(2, float) m.src[:] = np.empty(shape=(8, 2), dtype=float) m.src[:] = [[0, 0], [1, 0], [0, 0], [2, 0], [0, 0], [3, 0], [0, 0], [4, 0]] cell_fracs = np.zeros( 8, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [ (0, 0, 1.0, 0.0), (1, 1, 1.0, 0.0), (2, 2, 1.0, 0.0), (3, 3, 1.0, 0.0), (4, 4, 1.0, 0.0), (5, 5, 1.0, 0.0), (6, 6, 1.0, 0.0), (7, 7, 1.0, 0.0), ] empty_cells = [0, 2, 4, 6] m.tag_cell_fracs(cell_fracs) filename = "sampling_mesh.h5m" e_bounds = np.array([0, 0.5, 1]) m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_UNIFORM) num_samples = 50000 score = 1.0 / num_samples num_divs = 2 tally = [0.0] * 8 for i in range(num_samples): s = sampler.particle_birth([uniform(0, 1) for x in range(6)]) # check the cell_number assert_equal( s.cell_list[0], 4 * int(s.x * num_divs) + 2 * int(s.y * num_divs) + int(s.z * num_divs), ) # check the weight of each subvoxel if s.cell_list[0] not in empty_cells: # weight for cell 1, 3, 5, 7 should be: 0.4, 0.8, 1.2, 1.6 exp_w = (s.cell_list[0] + 1) / 2 * 0.4 out_w = s.w assert abs(out_w - exp_w) / exp_w < 0.05 # hand calculate # count the tally tally[s.cell_list[0]] += score # check the real sample rate for i, item in enumerate(tally): if i not in empty_cells: assert abs(item - 0.25) / 0.25 < 0.05 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_bias(): """This test tests that a user-specified biasing scheme: 1. Samples space uniformly according to the scheme. 2. Adjusts weights accordingly. Sample calculations are provided in Case 2 in the Theory Manual. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 3, 3.5], [0, 1], [0, 1]], mats=None ) m.src = NativeMeshTag(2, float) m.src[:] = [[2.0, 1.0], [9.0, 3.0]] e_bounds = np.array([0, 0.5, 1.0]) m.bias = NativeMeshTag(2, float) m.bias[:] = [[1.0, 2.0], [3.0, 3.0]] cell_fracs = np.zeros( 2, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0), (1, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "bias_tag_name": "bias", "e_bounds_tag_name": "e_bounds", } filename = "sampling_mesh.h5m" m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) sampler = Sampler(filename, tag_names, e_bounds, DEFAULT_USER) num_samples = 10000 score = 1.0 / num_samples num_divs = 2 tally = np.zeros(shape=(4)) for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0, 1) for x in range(6)])) if s.x < 3: if s.e < 0.5: assert_almost_equal(s.w, 1.6) # hand calcs tally[0] += score else: assert_almost_equal(s.w, 0.4) # hand calcs tally[1] += score else: if s.e < 0.5: assert_almost_equal(s.w, 2.4) # hand calcs tally[2] += score else: assert_almost_equal(s.w, 0.8) # hand calcs tally[3] += score expected_tally = [0.25, 0.5, 0.125, 0.125] # hand calcs for a, b in zip(tally, expected_tally): assert abs(a - b) / b < 0.25 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_bias_spatial(): """This test tests a user-specified biasing scheme for which the only 1 bias group is supplied for a source distribution containing two energy groups. This bias group is applied to both energy groups. In this test, the user-supplied bias distribution that was choosen, correspondes to uniform sampling, so that results can be checked against Case 1 in the theory manual. """ seed(1953) m = Mesh( structured=True, structured_coords=[[0, 3, 3.5], [0, 1], [0, 1]], mats=None ) m.src = NativeMeshTag(2, float) m.src[:] = [[2.0, 1.0], [9.0, 3.0]] m.bias = NativeMeshTag(1, float) m.bias[:] = [1, 1] e_bounds = np.array([0, 0.5, 1.0]) filename = "sampling_mesh.h5m" cell_fracs = np.zeros( 2, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [(0, 11, 1.0, 0.0), (1, 11, 1.0, 0.0)] m.tag_cell_fracs(cell_fracs) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "bias_tag_name": "bias", "e_bounds_tag_name": "e_bounds", } m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) sampler = Sampler(filename, tag_names, e_bounds, DEFAULT_USER) num_samples = 10000 score = 1.0 / num_samples num_divs = 2 num_e = 2 spatial_tally = np.zeros(shape=(num_divs, num_divs, num_divs)) e_tally = np.zeros(shape=(4)) # number of phase space groups for i in range(num_samples): s = sampler.particle_birth(np.array([uniform(0, 1) for x in range(6)])) if s.x < 3.0: assert_almost_equal(s.w, 0.7) # hand calcs else: assert_almost_equal(s.w, 2.8) # hand calcs spatial_tally[ int(s.x * num_divs / 3.5), int(s.y * num_divs / 1.0), int(s.z * num_divs / 1.0), ] += score if s.x < 3 and s.e < 0.5: e_tally[0] += score elif s.x < 3 and s.e > 0.5: e_tally[1] += score if s.x > 3 and s.e < 0.5: e_tally[2] += score if s.x > 3 and s.e > 0.5: e_tally[3] += score for i in range(0, 3): for j in range(0, 2): halfspace_sum = np.sum(np.rollaxis(spatial_tally, i)[j, :, :]) assert abs(halfspace_sum - 0.5) / 0.5 < 0.1 expected_e_tally = [4.0 / 7, 2.0 / 7, 3.0 / 28, 1.0 / 28] # hand calcs for i in range(4): assert abs(e_tally[i] - expected_e_tally[i]) / expected_e_tally[i] < 0.1 @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_subvoxel_multiple_hex_bias_1(): """This test tests that particle are sampled from a biased source defined on two voxels (2*2 = 4 sub-voxels) with the biased tag length of 1. """ seed(1953) # mesh contains two voxels. 2 * 1 * 1 = 2 m = Mesh( structured=True, structured_coords=[[0, 0.5, 1], [0, 1], [0, 1]], mats=None ) # max_num_cells = 2. 4 sub-voxels cell_fracs = np.zeros( 4, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [ (0, 11, 0.5, 0.0), (0, 12, 0.5, 0.0), (1, 21, 0.5, 0.0), (1, 22, 0.5, 0.0), ] m.tag_cell_fracs(cell_fracs) # the photon emitting rate of 4 sub-voxels is 0.1, 0.2, 0.3, 0.4 m.src = NativeMeshTag(4, float) m.src[:] = np.empty(shape=(2, 4), dtype=float) m.src[:] = [[0.05, 0.05, 0.10, 0.10], [0.15, 0.15, 0.20, 0.20]] e_bounds = np.array([0, 0.5, 1.0]) # bias, tag size = 1 m.bias = NativeMeshTag(1, float) m.bias[:] = [[0.4], [0.6]] filename = "sampling_mesh.h5m" m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "bias_tag_name": "bias", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_USER) num_samples = 50000 score = 1.0 / num_samples num_divs = 2 # tally shape (v, c, e) tally = np.zeros(shape=(num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth([uniform(0, 1) for x in range(6)]) vid = s.cell_list[0] // 10 - 1 cid = s.cell_list[0] % 10 - 1 eid = 0 if s.e < 0.5 else 1 # check the cell_number if s.x < 0.5: assert s.cell_list[0] in [11, 12] if s.x > 0.5: assert s.cell_list[0] in [21, 22] # check the weight of each subvoxel if vid == 0: assert abs(s.w - 0.746) / 0.746 < 0.05 if vid == 1: assert abs(s.w - 1.163) / 1.163 < 0.05 # count the tally tally[vid, cid, eid] += score # check the real sample rate # exp_tally calculated by hand exp_tally = np.zeros(shape=(2, 2, 2)) exp_tally[:] = [[[0.067, 0.067], [0.133, 0.133]], [[0.129, 0.129], [0.171, 0.171]]] for v in range(2): for c in range(2): for e in range(2): assert ( abs(tally[v, c, e] - exp_tally[v, c, e]) / exp_tally[v, c, e] < 0.05 ) @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_subvoxel_multiple_hex_bias_max_num_cells_num_e_groups(): """This test tests that particle are sampled from a biased source defined on two voxels (2*2 = 4 sub-voxels) with the biased tag length of max_num_cells*num_e_group. """ seed(1953) # mesh contains two voxels. 2 * 1 * 1 = 2 m = Mesh( structured=True, structured_coords=[[0, 0.5, 1], [0, 1], [0, 1]], mats=None ) # max_num_cells = 2. 4 sub-voxels cell_fracs = np.zeros( 4, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [ (0, 11, 0.5, 0.0), (0, 12, 0.5, 0.0), (1, 21, 0.5, 0.0), (1, 22, 0.5, 0.0), ] m.tag_cell_fracs(cell_fracs) # the photon emitting rate of 4 sub-voxels is 0.1, 0.2, 0.3, 0.4 m.src = NativeMeshTag(4, float) m.src[:] = np.empty(shape=(2, 4), dtype=float) m.src[:] = [[0.125, 0.125, 0.125, 0.125], [0.125, 0.125, 0.125, 0.125]] e_bounds = np.array([0, 0.5, 1.0]) # bias, tag size = 1 m.bias = NativeMeshTag(4, float) m.bias[:] = [[0.125, 0.125, 0.1, 0.15], [0.1, 0.1, 0.15, 0.15]] filename = "sampling_mesh.h5m" m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "bias_tag_name": "bias", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_USER) num_samples = 50000 score = 1.0 / num_samples num_divs = 2 # tally shape (v, c, e) tally = np.zeros(shape=(num_divs, num_divs, num_divs)) exp_wgt = np.zeros(shape=(num_divs, num_divs, num_divs)) exp_wgt[:] = [[[1.0, 1.0], [1.25, 0.83]], [[1.25, 1.25], [0.83, 0.83]]] for i in range(num_samples): s = sampler.particle_birth([uniform(0, 1) for x in range(6)]) vid = s.cell_list[0] // 10 - 1 cid = s.cell_list[0] % 10 - 1 eid = 0 if s.e < 0.5 else 1 # check the cell_number if s.x < 0.5: assert s.cell_list[0] in [11, 12] if s.x > 0.5: assert s.cell_list[0] in [21, 22] # check the weight of each subvoxel assert abs(s.w - exp_wgt[vid, cid, eid]) / exp_wgt[vid, cid, eid] < 0.05 # count the tally tally[vid, cid, eid] += score # check the real sample rate exp_tally = np.zeros(shape=(2, 2, 2)) exp_tally[:] = [[[0.125, 0.125], [0.100, 0.150]], [[0.100, 0.100], [0.150, 0.150]]] for v in range(2): for c in range(2): for e in range(2): assert ( abs(tally[v, c, e] - exp_tally[v, c, e]) / exp_tally[v, c, e] < 0.05 ) @with_setup(None, try_rm_file("sampling_mesh.h5m")) def test_subvoxel_multiple_hex_bias_e_groups(): """This test tests that particle are sampled from a biased source defined on two voxels (2*2 = 4 sub-voxels) with the biased tag length of energy groups. """ seed(1953) # mesh contains two voxels. 2 * 1 * 1 = 2 m = Mesh( structured=True, structured_coords=[[0, 0.5, 1], [0, 1], [0, 1]], mats=None ) # max_num_cells = 2. 4 sub-voxels cell_fracs = np.zeros( 4, dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = [ (0, 11, 0.5, 0.0), (0, 12, 0.5, 0.0), (1, 21, 0.5, 0.0), (1, 22, 0.5, 0.0), ] m.tag_cell_fracs(cell_fracs) # the photon emitting rate of 4 sub-voxels is 0.1, 0.2, 0.3, 0.4 m.src = NativeMeshTag(4, float) m.src[:] = np.empty(shape=(2, 4), dtype=float) m.src[:] = [[0.05, 0.05, 0.10, 0.10], [0.15, 0.15, 0.20, 0.20]] e_bounds = np.array([0, 0.5, 1.0]) # bias, tag size = 1 m.bias = NativeMeshTag(2, float) m.bias[:] = [[0.1, 0.3], [0.2, 0.4]] filename = "sampling_mesh.h5m" m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "bias_tag_name": "bias", "e_bounds_tag_name": "e_bounds", } sampler = Sampler(filename, tag_names, e_bounds, SUBVOXEL_USER) num_samples = 50000 score = 1.0 / num_samples num_divs = 2 # tally shape (v, c, e) tally = np.zeros(shape=(num_divs, num_divs, num_divs)) for i in range(num_samples): s = sampler.particle_birth([uniform(0, 1) for x in range(6)]) vid = s.cell_list[0] // 10 - 1 cid = s.cell_list[0] % 10 - 1 eid = 0 if s.e < 0.5 else 1 # check the cell_number if s.x < 0.5: assert s.cell_list[0] in [11, 12] if s.x > 0.5: assert s.cell_list[0] in [21, 22] # check the weight of each subvoxel if vid == 0 and eid == 0: assert abs(s.w - 1.5) / 1.5 < 0.05 if vid == 0 and eid == 1: assert abs(s.w - 0.5) / 0.5 < 0.05 if vid == 1 and eid == 0: assert abs(s.w - 1.75) / 1.75 < 0.05 if vid == 1 and eid == 1: assert abs(s.w - 0.875) / 0.875 < 0.05 # count the tally tally[vid, cid, eid] += score # check the real sample rate exp_tally = np.zeros(shape=(2, 2, 2)) exp_tally[:] = [ [[0.0333, 0.1000], [0.0667, 0.2000]], [[0.0857, 0.1714], [0.1143, 0.2286]], ] for v in range(2): for c in range(2): for e in range(2): assert ( abs(tally[v, c, e] - exp_tally[v, c, e]) / exp_tally[v, c, e] < 0.05 ) def test_alias_table(): """This tests that the AliasTable class produces samples in the ratios consistant with the supplied PDF. """ seed(1953) pdf = np.array([0.1, 0.2, 0.7]) at = AliasTable(pdf) num_samples = 50000 score = 1.0 / num_samples tally = np.zeros(shape=(3)) for i in range(num_samples): s = at.sample_pdf(uniform(0, 1), uniform(0, 1)) tally[s] += score for i in range(0, 3): assert abs(tally[i] - pdf[i]) / pdf[i] < 0.05 def point_in_tet(t, p): """This function determines if some point <p> lies within some tetrahedron <t> using the method described here: http://steve.hollasch.net/cgindex/geometry/ptintet.html """ matricies = [ np.array( [ [t[0][0], t[0][1], t[0][2], 1], [t[1][0], t[1][1], t[1][2], 1], [t[2][0], t[2][1], t[2][2], 1], [t[3][0], t[3][1], t[3][2], 1], ] ), np.array( [ [p[0], p[1], p[2], 1], [t[1][0], t[1][1], t[1][2], 1], [t[2][0], t[2][1], t[2][2], 1], [t[3][0], t[3][1], t[3][2], 1], ] ), np.array( [ [t[0][0], t[0][1], t[0][2], 1], [p[0], p[1], p[2], 1], [t[2][0], t[2][1], t[2][2], 1], [t[3][0], t[3][1], t[3][2], 1], ] ), np.array( [ [t[0][0], t[0][1], t[0][2], 1], [t[1][0], t[1][1], t[1][2], 1], [p[0], p[1], p[2], 1], [t[3][0], t[3][1], t[3][2], 1], ] ), np.array( [ [t[0][0], t[0][1], t[0][2], 1], [t[1][0], t[1][1], t[1][2], 1], [t[2][0], t[2][1], t[2][2], 1], [p[0], p[1], p[2], 1], ] ), ] determinates = [np.linalg.det(x) for x in matricies] return all(x >= 0 for x in determinates) or all(x < 0 for x in determinates) def test_template_examples(): """ An example of using source_sampling test template to do the test """ # DEFAULT and SUBVOXEL for mode in ( DEFAULT_ANALOG, DEFAULT_UNIFORM, DEFAULT_USER, SUBVOXEL_ANALOG, SUBVOXEL_UNIFORM, SUBVOXEL_USER, ): for num_e_groups in (1, 2): # num_bias_groups could be: # 1, num_e_groups, and max_num_cells*num_e_groups # test case: 1 voxel, 1 subvoxel cell_fracs_list = [(0, 1, 1.0, 0.0)] src_tag = [[1.0] * num_e_groups] if mode == DEFAULT_USER or mode == SUBVOXEL_USER: for num_bias_groups in (1, num_e_groups): bias_tag = [[1.0] * num_bias_groups] _source_sampling_test_template( mode, cell_fracs_list, src_tag, bias_tag ) else: _source_sampling_test_template(mode, cell_fracs_list, src_tag) # test case: 1 voxel, 2 subvoxels # create src and cell_fracs tag data if mode in (0, 1, 2): src_tag = [[1.0] * num_e_groups] cell_fracs_list = [(0, 1, 1.0, 0.0)] elif mode in (3, 4, 5): src_tag = [[1.0, 1.0] * num_e_groups] cell_fracs_list = [(0, 1, 0.5, 0.0), (0, 2, 0.5, 0.0)] if mode == DEFAULT_USER: for num_bias_groups in (1, num_e_groups): bias_tag = [[1.0] * num_bias_groups] _source_sampling_test_template( mode, cell_fracs_list, src_tag, bias_tag ) elif mode == SUBVOXEL_USER: for num_bias_groups in (1, num_e_groups, 2 * num_e_groups): bias_tag = [[1.0] * num_bias_groups] _source_sampling_test_template( mode, cell_fracs_list, src_tag, bias_tag ) else: _source_sampling_test_template(mode, cell_fracs_list, src_tag) # test case: 2 voxel, 2 subvoxels cell_fracs_list = [(0, 1, 1.0, 0.0), (1, 2, 1.0, 0.0)] src_tag = [[1.0] * num_e_groups, [1.0] * num_e_groups] if mode == DEFAULT_USER or mode == SUBVOXEL_USER: for num_bias_groups in (1, num_e_groups): bias_tag = [[1.0] * num_bias_groups, [1.0] * num_bias_groups] _source_sampling_test_template( mode, cell_fracs_list, src_tag, bias_tag ) else: _source_sampling_test_template(mode, cell_fracs_list, src_tag) # test case: 2 voxel, 4 subvoxels # create src and cell_fracs tag data if mode in (0, 1, 2): src_tag = [[1.0] * num_e_groups, [1.0] * num_e_groups] cell_fracs_list = [(0, 1, 1.0, 0.0), (1, 2, 1.0, 0.0)] elif mode in (3, 4, 5): src_tag = [[1.0, 1.0] * num_e_groups, [1.0, 1.0] * num_e_groups] cell_fracs_list = [ (0, 1, 0.5, 0.0), (0, 2, 0.5, 0.0), (1, 3, 0.5, 0.0), (1, 4, 0.5, 0.0), ] if mode == DEFAULT_USER: for num_bias_groups in (1, num_e_groups): bias_tag = [[1.0] * num_bias_groups, [1.0] * num_bias_groups] _source_sampling_test_template( mode, cell_fracs_list, src_tag, bias_tag ) elif mode == SUBVOXEL_USER: for num_bias_groups in (1, num_e_groups, 2 * num_e_groups): bias_tag = [[1.0] * num_bias_groups, [1.0] * num_bias_groups] _source_sampling_test_template( mode, cell_fracs_list, src_tag, bias_tag ) else: _source_sampling_test_template(mode, cell_fracs_list, src_tag) def _get_num_ve_sve_and_max_num_cells(cell_fracs): """ Calculate the num_ve, num_sve and max_num_cells Parameters ---------- cell_fracs : structured array, optional A sorted, one dimensional array, each entry containing the following fields: :idx: int The volume element index. :cell: int The geometry cell number. :vol_frac: float The volume fraction of the cell withing the mesh ve. :rel_error: float The relative error associated with the volume fraction. Returns ------- num_ve : int Number of the total voxels num_sve : int Number of the total subvoxels, eqaul to or greater than num_ve max_num_cells : int Max number of cells (subvoxels) in a voxel """ num_sve = len(cell_fracs) num_ve = len(set(cell_fracs["idx"])) max_num_cells = -1 for i in range(num_sve): max_num_cells = max(max_num_cells, len(cell_fracs[cell_fracs["idx"] == i])) return num_ve, num_sve, max_num_cells def _create_mesh_via_num_ve(num_ve): """ This function creates mesh from number of voxels Parameters ---------- num_ve : int Number of voxels Returns ------- mesh. MOAB mesh. """ x_bounds = [v * 1.0 / (num_ve) for v in range(num_ve + 1)] mesh = Mesh( structured=True, structured_coords=[x_bounds, [0, 1], [0, 1]], mats=None ) return mesh def _cal_pdf_and_biased_pdf(cell_fracs, src_tag, bias_tag=None): """ This function calcualtes the normalized pdf of source. Parameters ---------- cell_fracs : structured array A sorted, one dimensional array, each entry containing the following fields: :idx: int The volume element index. :cell: int The geometry cell number. :vol_frac: float The volume fraction of the cell withing the mesh ve. :rel_error: float The relative error associated with the volume fraction. src_tag : numpy array An one or two dimentional array contains data of the source tag. bias_tag : numpy array, optional An one or two dimentional array contains data of bias tag Returns ------- pdf : numpy array A three dimentional numpy array, shape=(num_ve, num_sve, num_e_groups) biased_pdf : numpy array A three dimentional numpy array, shape=(num_ve, num_sve, num_e_groups) """ num_ve, num_sve, max_num_cells = _get_num_ve_sve_and_max_num_cells(cell_fracs) num_e_groups = len(src_tag[0]) // max_num_cells pdf = np.empty(shape=(num_ve, max_num_cells, num_e_groups), dtype=np.float64) pdf.fill(0.0) for vid in range(num_ve): for svid in range(max_num_cells): for eid in range(num_e_groups): pdf[vid, svid, eid] = ( src_tag[vid][svid * num_e_groups + eid] * cell_fracs[vid * max_num_cells + svid]["vol_frac"] ) # normalize pdf = pdf / pdf.sum() # calculate biased_pdf biased_pdf = np.empty(shape=(num_ve, max_num_cells, num_e_groups), dtype=np.float64) biased_pdf.fill(0.0) # set up bias_array to proper value if bias_tag == None: # UNIFORM mode, set default bias_group and bias_array num_bias_groups = 1 bias_array = np.empty( shape=(num_ve, max_num_cells, num_e_groups), dtype=np.float64 ) for vid in range(num_ve): for svid in range(max_num_cells): for eid in range(num_e_groups): bias_array[vid, svid, eid] = ( src_tag[vid][svid * num_e_groups + eid] / np.array(src_tag[vid]).sum() ) else: # USER mode, set bias_array according to bias_tag num_bias_groups = len(bias_tag[0]) bias_array = np.empty( shape=(num_ve, max_num_cells, num_e_groups), dtype=np.float64 ) bias_array.fill(0.0) for vid in range(num_ve): for svid in range(max_num_cells): for eid in range(num_e_groups): if num_bias_groups == 1: bias_array[vid, svid, eid] = bias_tag[vid][0] elif num_bias_groups == num_e_groups: bias_array[vid, svid, eid] = bias_tag[vid][eid] elif num_bias_groups == max_num_cells * num_e_groups: bias_array[vid, svid, eid] = bias_tag[vid][ svid * num_e_groups + eid ] else: raise ValueError("Wrong bias_tag length") # calculate biased_pdf if num_bias_groups == 1: for vid in range(num_ve): for svid in range(max_num_cells): current_ve = cell_fracs[cell_fracs["idx"] == vid] biased_pdf[vid, svid, :] = ( bias_array[vid, svid, :] * current_ve[svid]["vol_frac"] ) elif num_bias_groups == num_e_groups: for vid in range(num_ve): for eid in range(num_e_groups): for svid in range(max_num_cells): current_ve = cell_fracs[cell_fracs["idx"] == vid] biased_pdf[vid, svid, eid] = ( bias_array[vid, svid, eid] * current_ve[svid]["vol_frac"] ) elif num_bias_groups == max_num_cells * num_e_groups: for vid in range(num_ve): for svid in range(max_num_cells): for eid in range(num_e_groups): biased_pdf[vid, svid, eid] = ( bias_array[vid, svid, eid] * cell_fracs[vid]["vol_frac"] ) # normalize biased_pdf biased_pdf = np.divide(biased_pdf, biased_pdf.sum()) return pdf, biased_pdf def _cal_exp_w_c(s, mode, cell_fracs, src_tag, bias_tag): """ This function calcualtes the exptected weight and cell_number for a given particle (according to it's x coordinate) Parameters ---------- s : SourceParticle The given particle mode : int Mode of the source_sampling cell_fracs : structured array A sorted, one dimensional array, each entry containing the following fields: :idx: int The volume element index. :cell: int The geometry cell number. :vol_frac: float The volume fraction of the cell withing the mesh ve. :rel_error: float The relative error associated with the volume fraction. src_tag : numpy array An one or two dimentional array contains data of the source tag. bias_tag : numpy array, optional An one or two dimentional array contains data of bias tag Returns ------- exp_w : float Expected weight of the source particle exp_c : set of available cell numbers Expected cell number of the source particle """ num_ve, num_sve, max_num_cells = _get_num_ve_sve_and_max_num_cells(cell_fracs) # calculate vid x_bounds = [v * 1.0 / (num_ve) for v in range(num_ve + 1)] vid = -1 for i in range(num_ve): if x_bounds[i] <= s.x <= x_bounds[i + 1]: vid = i break if vid == -1: raise ValueError( "x coordinate of particle not in (0, 1), s.x = {0}".format(str(s.x)) ) # calculate svid # get number of cells/subvoxels of current voxel current_cell_fracs = cell_fracs[cell_fracs["idx"] == vid] num_cells = len(current_cell_fracs) x_bounds = np.array([0.0] * (num_cells + 1)) # the x_bounds of the vid start from 1.0/num_ve*vid x_bounds[0] = 1.0 / num_ve * vid for svid in range(num_cells): x_bounds[svid + 1] = ( x_bounds[svid] + 1.0 / num_ve * current_cell_fracs[svid]["vol_frac"] ) svid = -1 for i in range(num_cells): if x_bounds[i] <= s.x <= x_bounds[i + 1]: svid = i break if svid == -1: raise ValueError("x coordinate not in the voxel, s.x = {0}".format(str(s.x))) # get the cell_number exp_c = set(list(current_cell_fracs["cell"])) # calculate eid if mode in (0, 1, 2): num_e_groups = len(src_tag[0]) elif mode in (3, 4, 5): num_e_groups = len(src_tag[0]) // max_num_cells e_bounds = np.array([i * 1.0 / num_e_groups for i in range(num_e_groups + 1)]) eid = -1 for i in range(num_e_groups): if e_bounds[i] <= s.e <= e_bounds[i + 1]: eid = i break if eid == -1: raise ValueError("energy not in (0, 1), s.e = ".format(str(s.e))) # calculate exp_w, weight is determined by mode, vid, svid and energy if mode in (0, 3): # ANALOG exp_w = 1.0 elif mode in (1, 4): # UNIFORM pdf, biased_pdf = _cal_pdf_and_biased_pdf(cell_fracs, src_tag, bias_tag) exp_w = pdf[vid, svid, eid] / biased_pdf[vid, svid, eid] else: # USER pdf, biased_pdf = _cal_pdf_and_biased_pdf(cell_fracs, src_tag, bias_tag) exp_w = pdf[vid, svid, eid] / biased_pdf[vid, svid, eid] return exp_w, exp_c def _get_p_y_z_halfspace(particles): """ This function calcualtes the probabilities of y and z half space for a given set of particles Parameters ---------- particles : list List of SourceParticle Returns ------- p_y_halfspace : float The probability of y half space p_z_halfspace : float The probability of z half space """ y_count, z_count = 0, 0 for s in particles: if s.y < 0.5: y_count = y_count + 1 if s.z < 0.5: z_count = z_count + 1 p_y_halfspace = float(y_count) / len(particles) p_z_halfspace = float(z_count) / len(particles) return p_y_halfspace, p_z_halfspace def _get_x_dis(particles, num_ve): """ This function calcualtes the particle distribution along x direction for a given set of particles Parameters ---------- particles : list List of SourceParticle num_ve : int Number of voxels Returns ------- x_dis : one dimentional numpy array The particle direction along x direction """ x_bounds = [v * 1.0 / (num_ve) for v in range(num_ve + 1)] x_dis = np.array([0.0] * num_ve) for i in range(num_ve): for s in particles: if x_bounds[i] <= s.x <= x_bounds[i + 1]: x_dis[i] = x_dis[i] + 1 x_dis = np.divide(x_dis, len(particles)) return x_dis def _get_x_dis_exp(mode, cell_fracs, src_tag, bias_tag=None): """ This function calcualtes the exptected particle distribution along x direction. Parameters ---------- mode : int Mode of the source_sampling cell_fracs : structured array A sorted, one dimensional array, each entry containing the following fields: :idx: int The volume element index. :cell: int The geometry cell number. :vol_frac: float The volume fraction of the cell withing the mesh ve. :rel_error: float The relative error associated with the volume fraction. src_tag : numpy array An one or two dimentional array contains data of the source tag. bias_tag : numpy array, optional An one or two dimentional array contains data of bias tag Returns ------- x_dis_exp : one dimentional numpy array The expected particle direction along x direction """ num_ve, num_sve, max_num_cells = _get_num_ve_sve_and_max_num_cells(cell_fracs) if mode in (0, 1, 2): num_e_groups = len(src_tag[0]) elif mode in (3, 4, 5): num_e_groups = len(src_tag[0]) // max_num_cells x_bounds = [v * 1.0 / (num_ve) for v in range(num_ve + 1)] x_dis_exp = np.array([0.0] * num_ve) if mode in (0, 3): # ANALOG, particles distribution according to the src_tag for vid in range(num_ve): current_ve = cell_fracs[cell_fracs["idx"] == vid] for svid in range(len(current_ve)): x_dis_exp[vid] += ( current_ve[svid]["vol_frac"] * np.array( src_tag[vid][svid * num_e_groups : (svid + 1) * num_e_groups] ).sum() ) elif mode in (1, 4): # UNIFORM, particles distribution uniformly in x direction x_dis_exp = np.array([1.0 / num_ve] * num_ve) elif mode in (2, 5): if bias_tag == None: raise ValueError( "bias_tag must be provided when mode is {0}".format(str(mode)) ) # USER, particles distribute accroding to the bias_tag for vid in range(num_ve): current_ve = cell_fracs[cell_fracs["idx"] == vid] for svid in range(len(current_ve)): x_dis_exp[vid] += ( current_ve[svid]["vol_frac"] * np.array( bias_tag[vid][svid * num_e_groups : (svid + 1) * num_e_groups] ).sum() ) # normalize x_dis_exp x_dis_exp = np.divide(x_dis_exp, x_dis_exp.sum()) return x_dis_exp def _get_e_dis(particles, num_e_groups): """ This function calcualtes the particle distribution along energy for a given set of particles Parameters ---------- particles : list List of SourceParticle num_e_groups : int Number of energy groups Returns ------- e_dis : one dimentional numpy array The particle direction along energy """ e_bounds = [e * 1.0 / (num_e_groups) for e in range(num_e_groups + 1)] e_dis = np.array([0.0] * num_e_groups) for i in range(num_e_groups): for s in particles: if e_bounds[i] <= s.e <= e_bounds[i + 1]: e_dis[i] = e_dis[i] + 1 e_dis = np.divide(e_dis, len(particles)) return e_dis def _get_e_dis_exp(mode, cell_fracs, src_tag, bias_tag=None): """ This function calcualtes the exptected particle distribution along energy Parameters ---------- mode : int Mode of the source_sampling cell_fracs : structured array A sorted, one dimensional array, each entry containing the following fields: :idx: int The volume element index. :cell: int The geometry cell number. :vol_frac: float The volume fraction of the cell withing the mesh ve. :rel_error: float The relative error associated with the volume fraction. src_tag : numpy array An one or two dimentional array contains data of the source tag. bias_tag : numpy array, optional An one or two dimentional array contains data of bias tag Returns ------- e_dis_exp : one dimentional numpy array The expected particle direction along energy """ # input check if mode in (2, 5) and bias_tag == None: raise ValueError("bias_tag must be provided when mode is {0}".format(str(mode))) num_ve, num_sve, max_num_cells = _get_num_ve_sve_and_max_num_cells(cell_fracs) if mode in (0, 1, 2): num_e_groups = len(src_tag[0]) elif mode in (3, 4, 5): num_e_groups = len(src_tag[0]) // max_num_cells e_bounds = [e * 1.0 / (num_e_groups) for e in range(num_e_groups + 1)] e_dis_exp = np.array([0.0] * num_e_groups) if mode in (0, 1, 3, 4) or (mode in (2, 5) and len(bias_tag[0]) == 1): # when mode is ANALOG and UNIFORM, or mode is USER but num_bias_groups is 1 # particles distribution according to the src_tag for vid in range(num_ve): current_ve = cell_fracs[cell_fracs["idx"] == vid] for svid in range(len(current_ve)): for eid in range(num_e_groups): e_dis_exp[eid] += ( current_ve[svid]["vol_frac"] * src_tag[vid][svid * num_e_groups + eid] ) elif mode == 2 or (mode == 5 and len(bias_tag[0]) == num_e_groups): # Energy is biased according to the bias_tag for vid in range(num_ve): current_ve = cell_fracs[cell_fracs["idx"] == vid] for svid in range(len(current_ve)): for eid in range(num_e_groups): e_dis_exp[eid] += current_ve[svid]["vol_frac"] * bias_tag[vid][eid] else: for vid in range(num_ve): current_ve = cell_fracs[cell_fracs["idx"] == vid] for svid in range(len(current_ve)): for eid in range(num_e_groups): e_dis_exp[eid] += ( current_ve[svid]["vol_frac"] * bias_tag[vid][svid * num_e_groups + eid] ) # normalize x_dis_exp e_dis_exp = np.divide(e_dis_exp, e_dis_exp.sum()) return e_dis_exp @with_setup(None, try_rm_file("sampling_mesh.h5m")) def _source_sampling_test_template(mode, cell_fracs_list, src_tag, bias_tag=None): """ This function serve as a template for all source_sampling test cases. It constrcut Sampler from input parameters. And then perform a standardized sampling and tally, Finally, it compares tallied results with exp_answers. Assumptions: * Use unit cube for all the meshes * Use structured meshes for all the tests * filename will always be: "sampling_mesh.h5m" * distribution changes only on X direction * uniform distribution in Y and Z directions * cell_number always equal to the index of sve + 1, no void cell * voxels have the same volume For example: cell_fracs = [(0, 1, 0.4, 0.0), (0, 2, 0.6, 0.0), (1, 3, 1.0, 0.0), (2, 4, 1.0, 0.0), ...] voxel idx v0 v1 v2 |------------|------------|------------|--- y | | | | | ^ z subvoxel | sve0| sve1 | sve2 | sve3 | . . . | / | | | | | |/ |------------|------------|------------|--- ----> x cell_number c1 c2 c3 c4 * Energy have only two options: - [0.0, 1.0] - [0.0, 0.5, 1.0] * Voxel number of meshes could be: - 1 voxel 1 subvoxel -> Single voxel single subvoxel - 1 voxel 2 subvoxel -> Single voxel multiple subvoxel - 2 voxel 2 subvoxel -> Multiple voxel multiple subvoxel - 2 voxel 4 subvoxel -> Multiple voxel multiple subvoxel Under these assumptions: * Mesh could be derived from cell_fracs * e_bounds could be derived from src_tag * construct_paras contain: - mode - cell_fracs - src_tag - bias_tag (optional, required for bias_mode == USER) Check items: * weight for each particle * cell_number for each particle * position distribution * energy distribution Parameters ---------- mode : int Mode of the source sampling, could be 0, 1, 2, 3, 4 or 5 cell_fracs_list : numpy array A one dimentional numpy array used to construct cell_fracs, Element: (idx, cell, vol_frac, rel_error) src_tag : numpy array An one or two dimentional array contains data of the source tag. bias_tag : numpy array, optional An one or two dimentional array contains data of bias tag Returns ------- None """ sub_mode_r2s = (0, 1, 2) sub_mode_subvoxel = (3, 4, 5) avail_mode = (0, 1, 2, 3, 4, 5) # input check # check mode if mode not in avail_mode: raise ValueError("mode must be in (0, 1, 2, 3, 4, 5)") # set cell_fracs cell_fracs = np.zeros( len(cell_fracs_list), dtype=[ ("idx", np.int64), ("cell", np.int64), ("vol_frac", np.float64), ("rel_error", np.float64), ], ) cell_fracs[:] = cell_fracs_list # check bias_tag if mode in (2, 5) and bias_tag == None: # bias_mode == USER raise ValueError("bias_tag must be given when mode is {0}".format(str(mode))) # get number of voxel, max_num_cells num_ve, num_sve, max_num_cells = _get_num_ve_sve_and_max_num_cells(cell_fracs) # set up e_bounds if mode in (0, 1, 2): num_e_groups = len(src_tag[0]) elif mode in (3, 4, 5): num_e_groups = len(src_tag[0]) // max_num_cells e_bounds = [i * 1.0 / num_e_groups for i in range(num_e_groups + 1)] e_bounds = np.array(e_bounds) # set up mesh m = _create_mesh_via_num_ve(num_ve) # set up src tag if mode in (0, 1, 2): m.src = NativeMeshTag(num_e_groups, float) elif mode in (3, 4, 5): m.src = NativeMeshTag(max_num_cells * num_e_groups, float) m.src[:] = src_tag # set up cell_number and cell_fracs tag m.tag_cell_fracs(cell_fracs) # set up bias tag if mode in (2, 5): bias_tag_lenght = len(bias_tag[0]) m.bias = NativeMeshTag(bias_tag_lenght, float) m.bias[:] = bias_tag # set up tag_names tag_names = { "src_tag_name": "src", "cell_number_tag_name": "cell_number", "cell_fracs_tag_name": "cell_fracs", "e_bounds_tag_name": "e_bounds", } if mode in (2, 5): tag_names["bias_tag_name"] = "bias" # save the mesh into h5m file filename = "sampling_mesh.h5m" m = tag_e_bounds(m, e_bounds) m.write_hdf5(filename) # construct Sampler sampler = Sampler(filename, tag_names, mode) # remove the temporary file os.remove(filename) # sampling and tally, tally should be defined by the mesh cell_fracs num_samples = 5000 particles = [] seed(1953) for i in range(num_samples): rands = np.array([uniform(0, 1) for x in range(6)]) s = sampler.particle_birth(rands) # check w, and c for each particle # calculate the expected weight and cell_number exp_w, exp_c = _cal_exp_w_c(s, mode, cell_fracs, src_tag, bias_tag) assert_equal(s.w, exp_w) # when mode in (0, 1, 2), the set exp_c is (-1), otherwise it contains # several available cell number if mode in (0, 1, 2): assert set(s.cell_list) == exp_c elif mode in (3, 4, 5): assert set(s.cell_list).issubset(exp_c) # store all the particles for the convinent of distribution check particles.append(s) # check position distribution # X direction follow specified distribution x_dis = _get_x_dis(particles, num_ve) x_dis_exp = _get_x_dis_exp(mode, cell_fracs, src_tag, bias_tag) for i in range(len(x_dis)): assert abs(x_dis[i] - x_dis_exp[i]) / x_dis_exp[i] < 0.05 # uniform in Y and Z directions p_y_halfspace, p_z_halfspace = _get_p_y_z_halfspace(particles) assert abs(p_y_halfspace - 0.5) / 0.5 < 0.05 assert abs(p_z_halfspace - 0.5) / 0.5 < 0.05 # check energy distribution e_dis = _get_e_dis(particles, num_e_groups) e_dis_exp = _get_e_dis_exp(mode, cell_fracs, src_tag, bias_tag) for i in range(len(e_dis)): if e_dis_exp[i] > 0: assert abs(e_dis[i] - e_dis_exp[i]) / e_dis_exp[i] < 0.05 else: assert_equal(e_dis[i], 0.0)

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py

Python

listenclosely/admin.py

jlmadurga/listenclosely

d6df9110c3ed6fd337e0236cccbe4d931bf217b0

[ "BSD-3-Clause" ]

7

2016-01-25T15:15:54.000Z

2018-02-17T18:48:54.000Z

listenclosely/admin.py

jlmadurga/listenclosely

d6df9110c3ed6fd337e0236cccbe4d931bf217b0

[ "BSD-3-Clause" ]

3

2016-03-11T13:22:17.000Z

2017-10-18T13:28:39.000Z

listenclosely/admin.py

jlmadurga/listenclosely

d6df9110c3ed6fd337e0236cccbe4d931bf217b0

[ "BSD-3-Clause" ]

3

2016-12-08T17:12:35.000Z

2018-01-06T22:57:40.000Z

from django.contrib import admin from listenclosely.models import Message, Chat, Agent, Asker admin.site.register(Message) admin.site.register(Chat) admin.site.register(Agent) admin.site.register(Asker)

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py

Python

src/bfg/modules/__init__.py

rvrsh3ll/bl-bfg

655ada530b32d9843c36dbecef9ec682154c005a

[ "MIT" ]

6

2022-02-16T18:37:59.000Z

2022-03-03T20:47:55.000Z

src/bfg/modules/__init__.py

rvrsh3ll/bl-bfg

655ada530b32d9843c36dbecef9ec682154c005a

[ "MIT" ]

null

src/bfg/modules/__init__.py

rvrsh3ll/bl-bfg

655ada530b32d9843c36dbecef9ec682154c005a

[ "MIT" ]

4

2022-02-16T16:50:09.000Z

2022-03-13T06:02:24.000Z

from . import http from . import testing #from . import smb

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py

Python

libs/msv/python/__init__.py

ITBE-Lab/ma

039e2833dd2e50df9285f183ff774bd87bbae710

[ "MIT" ]

40

2019-04-28T21:16:45.000Z

2022-02-05T05:54:47.000Z

libs/msv/python/__init__.py

ITBE-Lab/ma

039e2833dd2e50df9285f183ff774bd87bbae710

[ "MIT" ]

11

2019-04-28T22:29:12.000Z

2022-02-21T14:07:10.000Z

libs/msv/python/__init__.py

ITBE-Lab/ma

039e2833dd2e50df9285f183ff774bd87bbae710

[ "MIT" ]

2

2019-05-06T15:29:23.000Z

2021-01-08T13:22:17.000Z

from ._lib_init import * import MA from .computeSvJumps import * from .insertReads import * from .sweepSvJumps import * from .computeAccuracyRecall import *

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py

Python

tests/unit/models/utils/__init__.py

RaenonX/Jelly-Bot-API

c7da1e91783dce3a2b71b955b3a22b68db9056cf

[ "MIT" ]

5

2020-08-26T20:12:00.000Z

2020-12-11T16:39:22.000Z

tests/unit/models/utils/__init__.py

RaenonX/Jelly-Bot

c7da1e91783dce3a2b71b955b3a22b68db9056cf

[ "MIT" ]

234

2019-12-14T03:45:19.000Z

2020-08-26T18:55:19.000Z

tests/unit/models/utils/__init__.py

RaenonX/Jelly-Bot-API

c7da1e91783dce3a2b71b955b3a22b68db9056cf

[ "MIT" ]

2

2019-10-23T15:21:15.000Z

2020-05-22T09:35:55.000Z

from .validator import * # noqa from .checker import * # noqa

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6

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209

py

Python

experiment/AIClient.py

adhocmaster/pyns

607feb56baf0900535130195163eac331e131a2e

[ "MIT" ]

1

2021-06-15T06:21:14.000Z

event/AIClient.py

adhocmaster/pyns

607feb56baf0900535130195163eac331e131a2e

[ "MIT" ]

null

event/AIClient.py

adhocmaster/pyns

607feb56baf0900535130195163eac331e131a2e

[ "MIT" ]

1

2021-06-15T06:21:18.000Z

from core.TCPClient import TCPClient from event.PacketEvent import PacketEvent from event.EventTypes import EventTypes from core.SenderType import SenderType import logging class AIClient(TCPClient): pass

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4d67af64d56116da62993595b723329bee185928

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py

Python

tensordata/paper/WACV/__init__.py

Hourout/tensordata

cbef6742ee0d3bfc4b886358fc01618bb5b63603

[ "Apache-2.0" ]

13

2019-01-08T10:22:39.000Z

2020-06-17T10:02:47.000Z

tensordata/paper/WACV/__init__.py

Hourout/tensordata

cbef6742ee0d3bfc4b886358fc01618bb5b63603

[ "Apache-2.0" ]

null

tensordata/paper/WACV/__init__.py

Hourout/tensordata

cbef6742ee0d3bfc4b886358fc01618bb5b63603

[ "Apache-2.0" ]

1

2020-06-17T10:02:49.000Z

from tensordata.paper.WACV._wacv import *

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0

6

128d94f18e49792a9cc0f0c06d86c9887c857967

34

py

Python

python/oops.py

Floozutter/silly

8273b4a33e2001c0a530e859c12dbc30b9590a94

[ "Unlicense" ]

null

python/oops.py

Floozutter/silly

8273b4a33e2001c0a530e859c12dbc30b9590a94

[ "Unlicense" ]

null

python/oops.py

Floozutter/silly

8273b4a33e2001c0a530e859c12dbc30b9590a94

[ "Unlicense" ]

null

""" oops """ print(0, 1 == 1, 0)

5.666667

19

0.382353

6

34

2.166667

0.666667

0

0.16

0.264706

34

5

20

6.8

0.36

0.117647

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

12fc9abbbe6f805ac58294346c4e0f32cf3a77fb

204

py

Python

support/admin.py

gurupratap-matharu/django-tickets-app

8200af606e382f8806511c318961589f34375cdf

[ "MIT" ]

1

2020-10-16T16:37:04.000Z

support/admin.py

gurupratap-matharu/django-tickets-app

8200af606e382f8806511c318961589f34375cdf

[ "MIT" ]

null

support/admin.py

gurupratap-matharu/django-tickets-app

8200af606e382f8806511c318961589f34375cdf

[ "MIT" ]

null

from django.contrib import admin from .models import Holiday, Vendor, Category, Ticket admin.site.register(Holiday) admin.site.register(Vendor) admin.site.register(Category) admin.site.register(Ticket)

22.666667

53

0.813725

28

204

5.928571

0.428571

0.216867

0.409639

0

0.083333

204

8

54

25.5

0.887701

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

4236ceac66256b2c5cf2bcd12bce120d53a13c2a

4,782

py

Python

ifx_db/tests/test_159_FetchAssocSeveralRows_01.py

ifxdb/PythonIfxDB

a9c64e8ade1329b7102f0bf356c0e4b6d230ca95

[ "Apache-2.0" ]

3

2017-05-01T10:22:27.000Z

2021-12-29T11:02:34.000Z

ifx_db/tests/test_159_FetchAssocSeveralRows_01.py

ifxdb/PythonIfxDB

a9c64e8ade1329b7102f0bf356c0e4b6d230ca95

[ "Apache-2.0" ]

1

2020-01-07T12:56:26.000Z

ifx_db/tests/test_159_FetchAssocSeveralRows_01.py

ifxdb/PythonIfxDB

a9c64e8ade1329b7102f0bf356c0e4b6d230ca95

[ "Apache-2.0" ]

3

2017-05-10T16:03:25.000Z

2018-03-19T14:59:41.000Z

# # Licensed Materials - Property of IBM # # (c) Copyright IBM Corp. 2007-2008 # import unittest, sys import ifx_db import config from testfunctions import IfxDbTestFunctions class IfxDbTestCase(unittest.TestCase): def test_159_FetchAssocSeveralRows_01(self): obj = IfxDbTestFunctions() obj.assert_expect(self.run_test_159) def run_test_159(self): conn = ifx_db.connect(config.ConnStr, config.user, config.password) server = ifx_db.server_info( conn ) if (server.DBMS_NAME[0:3] == 'Inf'): op = {ifx_db.ATTR_CASE: ifx_db.CASE_UPPER} ifx_db.set_option(conn, op, 1) result = ifx_db.exec_immediate(conn, "select name,job from staff") i = 1 row = ifx_db.fetch_assoc(result) while ( row ): #printf("%3d %10s %10s\n",i, row['NAME'], row['JOB']) print "%3d %10s %10s" % (i, row['NAME'], row['JOB']) i += 1 row = ifx_db.fetch_assoc(result) #__END__ #__LUW_EXPECTED__ # 1 Sanders Mgr # 2 Pernal Sales # 3 Marenghi Mgr # 4 OBrien Sales # 5 Hanes Mgr # 6 Quigley Sales # 7 Rothman Sales # 8 James Clerk # 9 Koonitz Sales # 10 Plotz Mgr # 11 Ngan Clerk # 12 Naughton Clerk # 13 Yamaguchi Clerk # 14 Fraye Mgr # 15 Williams Sales # 16 Molinare Mgr # 17 Kermisch Clerk # 18 Abrahams Clerk # 19 Sneider Clerk # 20 Scoutten Clerk # 21 Lu Mgr # 22 Smith Sales # 23 Lundquist Clerk # 24 Daniels Mgr # 25 Wheeler Clerk # 26 Jones Mgr # 27 Lea Mgr # 28 Wilson Sales # 29 Quill Mgr # 30 Davis Sales # 31 Graham Sales # 32 Gonzales Sales # 33 Burke Clerk # 34 Edwards Sales # 35 Gafney Clerk #__ZOS_EXPECTED__ # 1 Sanders Mgr # 2 Pernal Sales # 3 Marenghi Mgr # 4 OBrien Sales # 5 Hanes Mgr # 6 Quigley Sales # 7 Rothman Sales # 8 James Clerk # 9 Koonitz Sales # 10 Plotz Mgr # 11 Ngan Clerk # 12 Naughton Clerk # 13 Yamaguchi Clerk # 14 Fraye Mgr # 15 Williams Sales # 16 Molinare Mgr # 17 Kermisch Clerk # 18 Abrahams Clerk # 19 Sneider Clerk # 20 Scoutten Clerk # 21 Lu Mgr # 22 Smith Sales # 23 Lundquist Clerk # 24 Daniels Mgr # 25 Wheeler Clerk # 26 Jones Mgr # 27 Lea Mgr # 28 Wilson Sales # 29 Quill Mgr # 30 Davis Sales # 31 Graham Sales # 32 Gonzales Sales # 33 Burke Clerk # 34 Edwards Sales # 35 Gafney Clerk #__SYSTEMI_EXPECTED__ # 1 Sanders Mgr # 2 Pernal Sales # 3 Marenghi Mgr # 4 OBrien Sales # 5 Hanes Mgr # 6 Quigley Sales # 7 Rothman Sales # 8 James Clerk # 9 Koonitz Sales # 10 Plotz Mgr # 11 Ngan Clerk # 12 Naughton Clerk # 13 Yamaguchi Clerk # 14 Fraye Mgr # 15 Williams Sales # 16 Molinare Mgr # 17 Kermisch Clerk # 18 Abrahams Clerk # 19 Sneider Clerk # 20 Scoutten Clerk # 21 Lu Mgr # 22 Smith Sales # 23 Lundquist Clerk # 24 Daniels Mgr # 25 Wheeler Clerk # 26 Jones Mgr # 27 Lea Mgr # 28 Wilson Sales # 29 Quill Mgr # 30 Davis Sales # 31 Graham Sales # 32 Gonzales Sales # 33 Burke Clerk # 34 Edwards Sales # 35 Gafney Clerk #__IDS_EXPECTED__ # 1 Sanders Mgr # 2 Pernal Sales # 3 Marenghi Mgr # 4 OBrien Sales # 5 Hanes Mgr # 6 Quigley Sales # 7 Rothman Sales # 8 James Clerk # 9 Koonitz Sales # 10 Plotz Mgr # 11 Ngan Clerk # 12 Naughton Clerk # 13 Yamaguchi Clerk # 14 Fraye Mgr # 15 Williams Sales # 16 Molinare Mgr # 17 Kermisch Clerk # 18 Abrahams Clerk # 19 Sneider Clerk # 20 Scoutten Clerk # 21 Lu Mgr # 22 Smith Sales # 23 Lundquist Clerk # 24 Daniels Mgr # 25 Wheeler Clerk # 26 Jones Mgr # 27 Lea Mgr # 28 Wilson Sales # 29 Quill Mgr # 30 Davis Sales # 31 Graham Sales # 32 Gonzales Sales # 33 Burke Clerk # 34 Edwards Sales # 35 Gafney Clerk

26.566667

71

0.508783

563

4,782

4.234458

0.257549

0.018876

0.026846

0.031879

0.778523

0.766779

0.744966

0

0.102925

0.435174

4,782

179

72

26.715084

0.779711

0.773317

0

0.095238

0

0.052688

0

0.047619

0

null

0.047619

0.190476

null

0.047619

0

null

0

1

0

null

0

1

0

6

423966a1f3ad6f82b1548613963497a3a9697e4e

6,263

py

Python

sdk/python/pulumi_aws/directoryservice/_inputs.py

mdop-wh/pulumi-aws

05bb32e9d694dde1c3b76d440fd2cd0344d23376

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/directoryservice/_inputs.py

mdop-wh/pulumi-aws

05bb32e9d694dde1c3b76d440fd2cd0344d23376

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/directoryservice/_inputs.py

mdop-wh/pulumi-aws

05bb32e9d694dde1c3b76d440fd2cd0344d23376

[ "ECL-2.0", "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Dict, List, Mapping, Optional, Tuple, Union from .. import _utilities, _tables __all__ = [ 'DirectoryConnectSettingsArgs', 'DirectoryVpcSettingsArgs', ] @pulumi.input_type class DirectoryConnectSettingsArgs: def __init__(__self__, *, customer_dns_ips: pulumi.Input[List[pulumi.Input[str]]], customer_username: pulumi.Input[str], subnet_ids: pulumi.Input[List[pulumi.Input[str]]], vpc_id: pulumi.Input[str], availability_zones: Optional[pulumi.Input[List[pulumi.Input[str]]]] = None, connect_ips: Optional[pulumi.Input[List[pulumi.Input[str]]]] = None): """ :param pulumi.Input[List[pulumi.Input[str]]] customer_dns_ips: The DNS IP addresses of the domain to connect to. :param pulumi.Input[str] customer_username: The username corresponding to the password provided. :param pulumi.Input[List[pulumi.Input[str]]] subnet_ids: The identifiers of the subnets for the directory servers (2 subnets in 2 different AZs). :param pulumi.Input[str] vpc_id: The identifier of the VPC that the directory is in. :param pulumi.Input[List[pulumi.Input[str]]] connect_ips: The IP addresses of the AD Connector servers. """ pulumi.set(__self__, "customer_dns_ips", customer_dns_ips) pulumi.set(__self__, "customer_username", customer_username) pulumi.set(__self__, "subnet_ids", subnet_ids) pulumi.set(__self__, "vpc_id", vpc_id) if availability_zones is not None: pulumi.set(__self__, "availability_zones", availability_zones) if connect_ips is not None: pulumi.set(__self__, "connect_ips", connect_ips) @property @pulumi.getter(name="customerDnsIps") def customer_dns_ips(self) -> pulumi.Input[List[pulumi.Input[str]]]: """ The DNS IP addresses of the domain to connect to. """ return pulumi.get(self, "customer_dns_ips") @customer_dns_ips.setter def customer_dns_ips(self, value: pulumi.Input[List[pulumi.Input[str]]]): pulumi.set(self, "customer_dns_ips", value) @property @pulumi.getter(name="customerUsername") def customer_username(self) -> pulumi.Input[str]: """ The username corresponding to the password provided. """ return pulumi.get(self, "customer_username") @customer_username.setter def customer_username(self, value: pulumi.Input[str]): pulumi.set(self, "customer_username", value) @property @pulumi.getter(name="subnetIds") def subnet_ids(self) -> pulumi.Input[List[pulumi.Input[str]]]: """ The identifiers of the subnets for the directory servers (2 subnets in 2 different AZs). """ return pulumi.get(self, "subnet_ids") @subnet_ids.setter def subnet_ids(self, value: pulumi.Input[List[pulumi.Input[str]]]): pulumi.set(self, "subnet_ids", value) @property @pulumi.getter(name="vpcId") def vpc_id(self) -> pulumi.Input[str]: """ The identifier of the VPC that the directory is in. """ return pulumi.get(self, "vpc_id") @vpc_id.setter def vpc_id(self, value: pulumi.Input[str]): pulumi.set(self, "vpc_id", value) @property @pulumi.getter(name="availabilityZones") def availability_zones(self) -> Optional[pulumi.Input[List[pulumi.Input[str]]]]: return pulumi.get(self, "availability_zones") @availability_zones.setter def availability_zones(self, value: Optional[pulumi.Input[List[pulumi.Input[str]]]]): pulumi.set(self, "availability_zones", value) @property @pulumi.getter(name="connectIps") def connect_ips(self) -> Optional[pulumi.Input[List[pulumi.Input[str]]]]: """ The IP addresses of the AD Connector servers. """ return pulumi.get(self, "connect_ips") @connect_ips.setter def connect_ips(self, value: Optional[pulumi.Input[List[pulumi.Input[str]]]]): pulumi.set(self, "connect_ips", value) @pulumi.input_type class DirectoryVpcSettingsArgs: def __init__(__self__, *, subnet_ids: pulumi.Input[List[pulumi.Input[str]]], vpc_id: pulumi.Input[str], availability_zones: Optional[pulumi.Input[List[pulumi.Input[str]]]] = None): """ :param pulumi.Input[List[pulumi.Input[str]]] subnet_ids: The identifiers of the subnets for the directory servers (2 subnets in 2 different AZs). :param pulumi.Input[str] vpc_id: The identifier of the VPC that the directory is in. """ pulumi.set(__self__, "subnet_ids", subnet_ids) pulumi.set(__self__, "vpc_id", vpc_id) if availability_zones is not None: pulumi.set(__self__, "availability_zones", availability_zones) @property @pulumi.getter(name="subnetIds") def subnet_ids(self) -> pulumi.Input[List[pulumi.Input[str]]]: """ The identifiers of the subnets for the directory servers (2 subnets in 2 different AZs). """ return pulumi.get(self, "subnet_ids") @subnet_ids.setter def subnet_ids(self, value: pulumi.Input[List[pulumi.Input[str]]]): pulumi.set(self, "subnet_ids", value) @property @pulumi.getter(name="vpcId") def vpc_id(self) -> pulumi.Input[str]: """ The identifier of the VPC that the directory is in. """ return pulumi.get(self, "vpc_id") @vpc_id.setter def vpc_id(self, value: pulumi.Input[str]): pulumi.set(self, "vpc_id", value) @property @pulumi.getter(name="availabilityZones") def availability_zones(self) -> Optional[pulumi.Input[List[pulumi.Input[str]]]]: return pulumi.get(self, "availability_zones") @availability_zones.setter def availability_zones(self, value: Optional[pulumi.Input[List[pulumi.Input[str]]]]): pulumi.set(self, "availability_zones", value)

39.14375

153

0.660706

790

6,263

5.046835

0.127848

0.16002

0.119388

0.115877

0.839227

0.755204

0.745924

0.683471

0.637321

0

0.001837

0.217627

6,263

159

154

39.389937

0.811837

0.22114

0

0.616162

1

0

0.105923

0.011241

0

1

0.20202

false

0

0.050505

0.020202

0.363636

0

null

0

1

0

1

0

1

0

null

0

1

0

6

424f648d196dac7e2486685ff9c4e899613672c5

108,792

py

Python

tests/samsung_multiroom/api/test_api.py

kusma/samsung_multiroom

09ca86d27b87a4aa0c97ec2accbd4ec67dd0cc61

[ "MIT" ]

6

2019-04-05T19:10:39.000Z

2021-11-23T17:26:49.000Z

tests/samsung_multiroom/api/test_api.py

kusma/samsung_multiroom

09ca86d27b87a4aa0c97ec2accbd4ec67dd0cc61

[ "MIT" ]

3

2020-09-25T06:58:00.000Z

2021-12-13T19:57:50.000Z

tests/samsung_multiroom/api/test_api.py

kusma/samsung_multiroom

09ca86d27b87a4aa0c97ec2accbd4ec67dd0cc61

[ "MIT" ]

4

2019-04-05T18:58:11.000Z

2021-07-22T19:54:56.000Z

import re import unittest from unittest.mock import MagicMock import httpretty import requests import xmltodict from samsung_multiroom.api import COMMAND_CPM from samsung_multiroom.api import COMMAND_UIC from samsung_multiroom.api import METHOD_GET from samsung_multiroom.api import SamsungMultiroomApi from samsung_multiroom.api import SamsungMultiroomApiException from samsung_multiroom.api import paginator def _get_api(): return SamsungMultiroomApi('public', '192.168.1.129', 55001) class TestApi(unittest.TestCase): def test_invalid_method_raises_exception(self): api = _get_api() self.assertRaises(ValueError, api.request, 'post', COMMAND_CPM, '<name>GetSpkName</name>') def test_invalid_command_raises_exception(self): api = _get_api() self.assertRaises(ValueError, api.request, METHOD_GET, 'INVALIDCOMMAND', '<name>GetSpkName</name>') @httpretty.activate(allow_net_connect=False) def test_request_timeout_raises_exception(self): def exception_response(): raise requests.exceptions.TimeoutException() httpretty.register_uri( httpretty.GET, re.compile(r'http://192.168.1.129:55001/.*'), body=exception_response ) api = _get_api() self.assertRaises(SamsungMultiroomApiException, api.request, METHOD_GET, COMMAND_UIC, '<name>GetSpkName</name>') @httpretty.activate(allow_net_connect=False) def test_request_bad_result_raises_exception(self): httpretty.register_uri( httpretty.GET, re.compile(r'http://192.168.1.129:55001/.*'), body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SpkName</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ng"></response> </UIC>""" ) api = _get_api() self.assertRaises(SamsungMultiroomApiException, api.request, METHOD_GET, COMMAND_UIC, '<name>GetSpkName</name>') @httpretty.activate(allow_net_connect=False) def test_request_returns_valid_response(self): httpretty.register_uri( httpretty.GET, re.compile(r'http://192.168.1.129:55001/.*'), body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SpkName</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <spkname><![CDATA[Living Room]]></spkname> </response> </UIC>""" ) api = _get_api() response = api.request(METHOD_GET, COMMAND_UIC, '<name>GetSpkName</name>') self.assertEqual(response, { 'spkname': 'Living Room' }) @httpretty.activate(allow_net_connect=False) def test_get_speaker_name(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetSpkName%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SpkName</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <spkname><![CDATA[Living Room]]></spkname> </response> </UIC>""" ) api = _get_api() speaker_name = api.get_speaker_name() self.assertEqual(speaker_name, 'Living Room') @httpretty.activate(allow_net_connect=False) def test_set_speaker_name(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetSpkName%3C/name%3E%3Cp%20type=%22cdata%22%20name=%22spkname%22%20val=%22empty%22%3E%3C![CDATA[Living%20Room]]%3E%3C/p%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SpkName</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <spkname><![CDATA[Living Room]]></spkname> </response> </UIC>""" ) api = _get_api() speaker_name = api.set_speaker_name('Living Room') @unittest.mock.patch('socket.socket') def test_get_main_info(self, s): s.return_value.recv.side_effect = [ b"""HTTP/1.1 200 OK Date: Fri, 02 Jan 1970 10:53:13 GMT Server: Samsung/1.0 Content-Type: text/html Content-Length: 215 Connection: close Last-Modified: Fri, 02 Jan 1970 10:53:13 GMT <?xml version="1.0" encoding="UTF-8"?><UIC><method>RequestDeviceInfo</method><version>1.0</version><speakerip>192.168.1.129</speakerip><user_identifier>public</user_identifier><response result="ok"></response></UIC>""", b"""HTTP/1.1 200 OK Date: Fri, 02 Jan 1970 10:53:13 GMT Server: Samsung/1.0 Content-Type: text/html Content-Length: 678 Connection: close Last-Modified: Fri, 02 Jan 1970 10:53:13 GMT <?xml version="1.0" encoding="UTF-8"?><UIC><method>MainInfo</method><version>1.0</version><speakerip>192.168.1.129</speakerip><user_identifier></user_identifier><response result="ok"><party>off</party><partymain></partymain><grouptype>N</grouptype><groupmainip>0.0.0.0</groupmainip><groupmainmacaddr>00:00:00:00:00:00</groupmainmacaddr><spkmacaddr>xx:xx:xx:xx:xx:xx</spkmacaddr><spkmodelname>HW-K650</spkmodelname><groupmode>none</groupmode><channeltype>front</channeltype><channelvolume>0</channelvolume><multichinfo>on</multichinfo><groupspknum>1</groupspknum><dfsstatus>dfsoff</dfsstatus><protocolver>2.3</protocolver><btmacaddr>yy:yy:yy:yy:yy:yy</btmacaddr></response></UIC>""", b'', ] api = _get_api() main_info = api.get_main_info() self.assertEqual(main_info, { 'party': 'off', 'partymain': None, 'grouptype': 'N', 'groupmainip': '0.0.0.0', 'groupmainmacaddr': '00:00:00:00:00:00', 'spkmacaddr': 'xx:xx:xx:xx:xx:xx', 'spkmodelname': 'HW-K650', 'groupmode': 'none', 'channeltype': 'front', 'channelvolume': '0', 'multichinfo': 'on', 'groupspknum': '1', 'dfsstatus': 'dfsoff', 'protocolver': '2.3', 'btmacaddr': 'yy:yy:yy:yy:yy:yy', }) @httpretty.activate(allow_net_connect=False) def test_get_volume(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetVolume%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>VolumeLevel</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <volume>10</volume> </response> </UIC>""" ) api = _get_api() volume = api.get_volume() self.assertEqual(volume, 10) @httpretty.activate(allow_net_connect=False) def test_set_volume(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetVolume%3C/name%3E%3Cp%20type=%22dec%22%20name=%22volume%22%20val=%2210%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>VolumeLevel</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <volume>10</volume> </response> </UIC>""" ) api = _get_api() api.set_volume(10) @httpretty.activate(allow_net_connect=False) def test_get_mute(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetMute%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>MuteStatus</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <mute>off</mute> </response> </UIC>""" ) api = _get_api() mute = api.get_mute() self.assertEqual(mute, False) @httpretty.activate(allow_net_connect=False) def test_set_mute(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetMute%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22mute%22%20val%3D%22on%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>MuteStatus</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <mute>on</mute> </response> </UIC>""" ) api = _get_api() api.set_mute(True) @httpretty.activate(allow_net_connect=False) def test_get_func(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetFunc%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>CurrentFunc</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <function>wifi</function> <submode>dlna</submode> <connection></connection> <devicename><![CDATA[]]></devicename> </response> </UIC>""" ) api = _get_api() func = api.get_func() self.assertEqual(func, { 'function': 'wifi', 'submode': 'dlna', 'connection': None, 'devicename': None, }) @httpretty.activate(allow_net_connect=False) def test_set_func(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetFunc%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22function%22%20val%3D%22bt%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>PlayStatus</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <function>bt</function> <playstatus>pause</playstatus> </response> </UIC>""" ) api = _get_api() api.set_func('bt') @httpretty.activate(allow_net_connect=False) def test_get_shuffle_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetShuffleMode%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>ShuffleMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <shuffle>on</shuffle> </response> </UIC>""" ) api = _get_api() shuffle_mode = api.get_shuffle_mode() self.assertEqual(shuffle_mode, True) @httpretty.activate(allow_net_connect=False) def test_set_shuffle_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetShuffleMode%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22shufflemode%22%20val%3D%22on%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>ShuffleMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <shuffle>on</shuffle> </response> </UIC>""" ) api = _get_api() api.set_shuffle_mode(True) @httpretty.activate(allow_net_connect=False) def test_set_trick_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetTrickMode%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22trickmode%22%20val%3D%22next%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>CurrentFunc</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <function>wifi</function> <submode>dlna</submode> <connection></connection> <devicename><![CDATA[]]></devicename> </response> </UIC>""" ) api = _get_api() api.set_trick_mode('next') @httpretty.activate(allow_net_connect=False) def test_set_playback_control(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetPlaybackControl%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22playbackcontrol%22%20val%3D%22pause%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>PlaybackStatus</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <playstatus>pause</playstatus> </response> </UIC>""" ) api = _get_api() api.set_playback_control('pause') @httpretty.activate(allow_net_connect=False) def test_get_music_info(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetMusicInfo%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>MusicInfo</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> <playertype>allshare</playertype> <playbacktype>folder</playbacktype> <sourcename><![CDATA[]]></sourcename> <parentid>22$30224</parentid> <parentid2></parentid2> <playindex>8</playindex> <objectid><![CDATA[22$@52947]]></objectid> <title><![CDATA[New star in the sky]]></title> <artist><![CDATA[Air]]></artist> <album><![CDATA[Moon Safari]]></album> <thumbnail><![CDATA[http://192.168.1.111:50002/transcoder/jpegtnscaler.cgi/folderart/52947.jpg]]></thumbnail> <timelength>0:05:40.000</timelength> <playtime>325067</playtime> <seek>enable</seek> <pause>enable</pause> </response> </UIC>""" ) api = _get_api() music_info = api.get_music_info() self.assertEqual(music_info['title'], 'New star in the sky') self.assertEqual(music_info['artist'], 'Air') self.assertEqual(music_info['album'], 'Moon Safari') self.assertEqual(music_info['thumbnail'], 'http://192.168.1.111:50002/transcoder/jpegtnscaler.cgi/folderart/52947.jpg') self.assertEqual(music_info['timelength'], '0:05:40.000') self.assertEqual(music_info['playtime'], '325067') self.assertEqual(music_info['seek'], 'enable') self.assertEqual(music_info['pause'], 'enable') @httpretty.activate(allow_net_connect=False) def test_get_play_status(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetPlayStatus%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>PlayStatus</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier></user_identifier> <response result="ok"> <function>wifi</function> <submode>dlna</submode> <playstatus>play</playstatus> </response> </UIC>""" ) api = _get_api() func = api.get_play_status() self.assertEqual(func, { 'function': 'wifi', 'submode': 'dlna', 'playstatus': 'play', }) @httpretty.activate(allow_net_connect=False) def test_set_search_time(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetSearchTime%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22playtime%22%20val%3D%2250%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>MusicPlayTime</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <timelength>431</timelength> <playtime>50</playtime> </response> </UIC>""" ) api = _get_api() api.set_search_time(50) @httpretty.activate(allow_net_connect=False) def test_get_preset_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetPresetList%3C%2Fname%3E%3Cp%20type=%22dec%22%20name=%22startindex%22%20val=%220%22/%3E%3Cp%20type=%22dec%22%20name=%22listcount%22%20val=%2210%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>PresetList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <totallistcount>6</totallistcount> <startindex>0</startindex> <listcount>6</listcount> <timestamp>2018-12-28T17:44:10Z</timestamp> <presetlisttype>0</presetlisttype> <presetlist> <preset> <kind>speaker</kind> <title>Radio Swiss Jazz (Jazz Music)</title> <description>Manu Dibango - Milady's Song</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s6814t.png</thumbnail> <contentid>0</contentid> <mediaid>s6814</mediaid> </preset> <preset> <kind>speaker</kind> <title>93.5 | BBC Radio 4 (US News)</title> <description>Intelligent speech</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s25419t.png</thumbnail> <contentid>1</contentid> <mediaid>s25419</mediaid> </preset> <preset> <kind>speaker</kind> <title>89.1 | BBC Radio 2 (Adult Hits)</title> <description>Amazing music. Played by an amazing line up.</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24940t.png</thumbnail> <contentid>2</contentid> <mediaid>s24940</mediaid> </preset> <preset> <kind>my</kind> <title>Radio Swiss Jazz (Jazz Music)</title> <description>Groovin' J 5 - This Here</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s6814t.png</thumbnail> <contentid>3</contentid> <mediaid>s6814</mediaid> </preset> <preset> <kind>my</kind> <title>91.3 | BBC Radio 3 (Classical Music)</title> <description>Live music and arts</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24941t.png</thumbnail> <contentid>4</contentid> <mediaid>s24941</mediaid> </preset> <preset> <kind>my</kind> <title>93.5 | BBC Radio 4 (US News)</title> <description>Intelligent speech</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s25419t.png</thumbnail> <contentid>5</contentid> <mediaid>s25419</mediaid> </preset> </presetlist> </response> </CPM>""" ) api = _get_api() preset_list = api.get_preset_list(0, 10) self.assertEqual(len(preset_list), 6) self.assertEqual(preset_list[0]['kind'], 'speaker') self.assertEqual(preset_list[0]['title'], 'Radio Swiss Jazz (Jazz Music)') self.assertEqual(preset_list[0]['description'], 'Manu Dibango - Milady\'s Song') self.assertEqual(preset_list[0]['thumbnail'], 'http://cdn-radiotime-logos.tunein.com/s6814t.png') self.assertEqual(preset_list[0]['contentid'], '0') self.assertEqual(preset_list[0]['mediaid'], 's6814') @httpretty.activate(allow_net_connect=False) def test_get_radio_info(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetRadioInfo%3C%2Fname%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioInfo</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <root>Favorites</root> <presetindex>0</presetindex> <title>Radio Swiss Jazz (Jazz Music)</title> <description>Manu Dibango - Milady's Song</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s6814d.png</thumbnail> <mediaid>s6814</mediaid> <allowfeedback>0</allowfeedback> <timestamp>2018-12-28T18:07:07Z</timestamp> <no_queue>1</no_queue> <playstatus>play</playstatus> </response> </CPM>""" ) api = _get_api() func = api.get_radio_info() self.assertEqual(func, { 'cpname': 'TuneIn', 'root': 'Favorites', 'presetindex': '0', 'title': 'Radio Swiss Jazz (Jazz Music)', 'description': 'Manu Dibango - Milady\'s Song', 'thumbnail': 'http://cdn-radiotime-logos.tunein.com/s6814d.png', 'mediaid': 's6814', 'allowfeedback': '0', 'timestamp': '2018-12-28T18:07:07Z', 'no_queue': '1', 'playstatus': 'play', }) @httpretty.activate(allow_net_connect=False) def test_set_play_preset(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetPlayPreset%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22presettype%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22presetindex%22%20val%3D%220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>StopPlaybackEvent</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <playtime>0</playtime> </response> </UIC>""" ) api = _get_api() api.set_play_preset(1, 0) @httpretty.activate(allow_net_connect=False) def test_set_select_radio(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetSelectRadio%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioSelected</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <signinstatus>0</signinstatus> <timestamp>2018-12-28T18:35:17Z</timestamp> <audioinfo> <title>Radio Swiss Jazz (Jazz Music)</title> <thumbnail>http://cdn-radiotime-logos.tunein.com/s6814d.png</thumbnail> <playstatus>play</playstatus> </audioinfo> </response> </CPM>""" ) api = _get_api() api.set_select_radio() @httpretty.activate(allow_net_connect=False) def test_get_dms_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetDmsList%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22liststartindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>DmsList</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <listtotalcount>1</listtotalcount> <liststartindex>0</liststartindex> <listcount>1</listcount> <dmslist> <dms device_id="0"> <dmsid>uuid:00113249-398f-0011-8f39-8f3949321100</dmsid> <dmsname><![CDATA[nas]]></dmsname> <devicetype>network</devicetype> <thumbnail_PNG_LRG><![CDATA[http://192.168.1.111:50001/tmp_icon/dmsicon120.png]]></thumbnail_PNG_LRG> <thumbnail_JPG_LRG><![CDATA[http://192.168.1.111:50001/tmp_icon/dmsicon120.jpg]]></thumbnail_JPG_LRG> <thumbnail_PNG_SM><![CDATA[http://192.168.1.111:50001/tmp_icon/dmsicon48.png]]></thumbnail_PNG_SM> <thumbnail_JPG_SM><![CDATA[http://192.168.1.111:50001/tmp_icon/dmsicon48.jpg]]></thumbnail_JPG_SM> </dms> </dmslist> </response> </UIC>""" ) api = _get_api() dms_list = api.get_dms_list(0, 20) self.assertEqual(len(dms_list), 1) self.assertEqual(dms_list[0], { '@device_id': '0', 'dmsid': 'uuid:00113249-398f-0011-8f39-8f3949321100', 'dmsname': 'nas', 'devicetype': 'network', 'thumbnail_PNG_LRG': 'http://192.168.1.111:50001/tmp_icon/dmsicon120.png', 'thumbnail_JPG_LRG': 'http://192.168.1.111:50001/tmp_icon/dmsicon120.jpg', 'thumbnail_PNG_SM': 'http://192.168.1.111:50001/tmp_icon/dmsicon48.png', 'thumbnail_JPG_SM': 'http://192.168.1.111:50001/tmp_icon/dmsicon48.jpg', }) @httpretty.activate(allow_net_connect=False) def test_pc_get_music_list_by_category(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EPCGetMusicListByCategory%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22device_udn%22%20val%3D%22uuid%3A00113249-398f-0011-8f39-8f3949321100%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22filter%22%20val%3D%22folder%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22categoryid%22%20val%3D%22folder%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22liststartindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>PCMusicList</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <listtotalcount>3</listtotalcount> <liststartindex>0</liststartindex> <listcount>3</listcount> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> <filter>folder</filter> <playertype>myphone</playertype> <playbacktype>playlist</playbacktype> <sourcename><![CDATA[nas]]></sourcename> <parentid>0</parentid> <parentid2 /> <musiclist> <music object_id="21"> <type>CONTAINER</type> <playindex>-1</playindex> <name /> <title><![CDATA[Music]]></title> <artist /> <album /> <thumbnail /> <timelength /> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> </music> <music object_id="37"> <type>CONTAINER</type> <playindex>-1</playindex> <name /> <title><![CDATA[Photo]]></title> <artist /> <album /> <thumbnail /> <timelength /> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> </music> <music object_id="44"> <type>CONTAINER</type> <playindex>-1</playindex> <name /> <title><![CDATA[Video]]></title> <artist /> <album /> <thumbnail /> <timelength /> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> </music> </musiclist> </response> </UIC>""" ) api = _get_api() music_list = api.pc_get_music_list_by_category('uuid:00113249-398f-0011-8f39-8f3949321100', 0, 20) self.assertEqual(len(music_list), 3) self.assertEqual(music_list[0], { '@object_id': '21', 'type': 'CONTAINER', 'playindex': '-1', 'name': None, 'title': 'Music', 'artist': None, 'album': None, 'thumbnail': None, 'timelength': None, 'device_udn': 'uuid:00113249-398f-0011-8f39-8f3949321100', }) @httpretty.activate(allow_net_connect=False) def test_pc_get_music_list_by_id(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EPCGetMusicListByID%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22device_udn%22%20val%3D%22uuid%3A00113249-398f-0011-8f39-8f3949321100%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22filter%22%20val%3D%22folder%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22parentid%22%20val%3D%2222%2430224%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22liststartindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>PCMusicList</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <listtotalcount>2</listtotalcount> <liststartindex>0</liststartindex> <listcount>2</listcount> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> <filter>folder</filter> <playertype>myphone</playertype> <playbacktype>playlist</playbacktype> <sourcename><![CDATA[nas]]></sourcename> <parentid>22$30224</parentid> <parentid2 /> <musiclist> <music object_id="22$@52941"> <type>AUDIO</type> <playindex>0</playindex> <name><![CDATA[La femme d'argent.mp3]]></name> <title><![CDATA[La femme d'argent]]></title> <artist><![CDATA[Air]]></artist> <album><![CDATA[Moon Safari]]></album> <thumbnail><![CDATA[http://192.168.1.111:50002/transcoder/jpegtnscaler.cgi/folderart/52941.jpg]]></thumbnail> <timelength>0:07:11.000</timelength> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> </music> <music object_id="22$@52942"> <type>AUDIO</type> <playindex>1</playindex> <name><![CDATA[Sexy boy.mp3]]></name> <title><![CDATA[Sexy boy]]></title> <artist><![CDATA[Air]]></artist> <album><![CDATA[Moon Safari]]></album> <thumbnail><![CDATA[http://192.168.1.111:50002/transcoder/jpegtnscaler.cgi/folderart/52942.jpg]]></thumbnail> <timelength>0:04:58.000</timelength> <device_udn>uuid:00113249-398f-0011-8f39-8f3949321100</device_udn> </music> </musiclist> </response> </UIC>""" ) api = _get_api() music_list = api.pc_get_music_list_by_id('uuid:00113249-398f-0011-8f39-8f3949321100', '22$30224', 0, 20) self.assertEqual(len(music_list), 2) self.assertEqual(music_list[0], { '@object_id': '22$@52941', 'type': 'AUDIO', 'playindex': '0', 'name': 'La femme d\'argent.mp3', 'title': 'La femme d\'argent', 'artist': 'Air', 'album': 'Moon Safari', 'thumbnail': 'http://192.168.1.111:50002/transcoder/jpegtnscaler.cgi/folderart/52941.jpg', 'timelength': '0:07:11.000', 'device_udn': 'uuid:00113249-398f-0011-8f39-8f3949321100', }) @httpretty.activate(allow_net_connect=False) def test_set_playlist_playback_control(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetPlaylistPlaybackControl%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22playbackcontrol%22%20val%3D%22play%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22playertype%22%20val%3D%22allshare%22/%3E%3Cp%20type%3D%22cdata%22%20name%3D%22sourcename%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5B%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22dec%22%20name%3D%22playindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22playtime%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22totalobjectcount%22%20val%3D%221%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22device_udn%22%20val%3D%22uuid%3A00113249-398f-0011-8f39-8f3949321100%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22objectid%22%20val%3D%2222%24%4052942%22/%3E%3Cp%20type%3D%22cdata%22%20name%3D%22songtitle%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BSexy%20boy%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22cdata%22%20name%3D%22thumbnail%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5Bhttp%3A//192.168.1.111%3A50002/transcoder/jpegtnscaler.cgi/folderart/52941.jpg%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22cdata%22%20name%3D%22artist%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BAir%5D%5D%3E%3C/p%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>StopPlaybackEvent</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <playtime>0</playtime> </response> </UIC>""" ) items = [ { 'device_udn': 'uuid:00113249-398f-0011-8f39-8f3949321100', 'object_id': '22$@52942', 'title': 'Sexy boy', 'thumbnail': 'http://192.168.1.111:50002/transcoder/jpegtnscaler.cgi/folderart/52941.jpg', 'artist': 'Air', } ] api = _get_api() api.set_playlist_playback_control(items) @httpretty.activate(allow_net_connect=False) def test_browse_main(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EBrowseMain%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <root>Browse</root> <browsemode>0</browsemode> <category isroot="1">Browse</category> <totallistcount>4</totallistcount> <startindex>0</startindex> <listcount>4</listcount> <timestamp>2018-12-31T16:06:37Z</timestamp> <menulist> <menuitem type="0"> <title>Favorites</title> <contentid>0</contentid> </menuitem> <menuitem type="0"> <title>Local Radio</title> <contentid>1</contentid> </menuitem> <menuitem type="0"> <title>Recents</title> <contentid>2</contentid> </menuitem> <menuitem type="0"> <title>Trending</title> <contentid>3</contentid> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() items = api.browse_main(0, 30) self.assertEqual(len(items), 4) self.assertEqual(items[0], { '@type': '0', 'title': 'Favorites', 'contentid': '0', }) @httpretty.activate(allow_net_connect=False) def test_get_select_radio_list_with_folders(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetSelectRadioList%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22contentid%22%20val%3D%2210%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <root>Browse</root> <browsemode>0</browsemode> <category isroot="0">By Language</category> <totallistcount>4</totallistcount> <startindex>0</startindex> <listcount>4</listcount> <timestamp>2018-12-31T16:23:16Z</timestamp> <menulist> <menuitem type="0"> <title>Aboriginal</title> <contentid>0</contentid> </menuitem> <menuitem type="0"> <title>Afrikaans</title> <contentid>1</contentid> </menuitem> <menuitem type="0"> <title>Akan</title> <contentid>2</contentid> </menuitem> <menuitem type="0"> <title>Albanian</title> <contentid>3</contentid> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() items = api.get_select_radio_list(10, 0, 30) self.assertEqual(len(items), 4) self.assertEqual(items[0], { '@type': '0', 'title': 'Aboriginal', 'contentid': '0', }) @httpretty.activate(allow_net_connect=False) def test_get_select_radio_list_with_radios(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetSelectRadioList%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22contentid%22%20val%3D%223%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <root>Browse</root> <browsemode>0</browsemode> <category isroot="0">Trending</category> <totallistcount>4</totallistcount> <startindex>0</startindex> <listcount>4</listcount> <timestamp>2018-12-31T16:30:03Z</timestamp> <menulist> <menuitem type="2"> <thumbnail>http://cdn-profiles.tunein.com/s297990/images/logot.png</thumbnail> <description>MSNBC Live with Velshi & Ruhle</description> <mediaid>s297990</mediaid> <title>MSNBC</title> <contentid>0</contentid> </menuitem> <menuitem type="2"> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24940t.png</thumbnail> <description>Amazing music. Played by an amazing line up.</description> <mediaid>s24940</mediaid> <title>BBC Radio 2</title> <contentid>1</contentid> </menuitem> <menuitem type="2"> <thumbnail>http://cdn-radiotime-logos.tunein.com/s17077t.png</thumbnail> <description>Drive with Adrian Durham & Matt Holland</description> <mediaid>s17077</mediaid> <title>talkSPORT</title> <contentid>2</contentid> </menuitem> <menuitem type="2"> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24939t.png</thumbnail> <description>The best new music</description> <mediaid>s24939</mediaid> <title>BBC Radio 1</title> <contentid>3</contentid> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() items = api.get_select_radio_list(3, 0, 30) self.assertEqual(len(items), 4) self.assertEqual(items[0], { '@type': '2', 'thumbnail': 'http://cdn-profiles.tunein.com/s297990/images/logot.png', 'description': 'MSNBC Live with Velshi & Ruhle', 'mediaid': 's297990', 'title': 'MSNBC', 'contentid': '0', }) @httpretty.activate(allow_net_connect=False) def test_get_current_radio_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetCurrentRadioList%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <root>Browse</root> <browsemode>0</browsemode> <category isroot="0">Trending</category> <totallistcount>4</totallistcount> <startindex>0</startindex> <listcount>4</listcount> <timestamp>2018-12-31T16:30:03Z</timestamp> <menulist> <menuitem type="2"> <thumbnail>http://cdn-profiles.tunein.com/s297990/images/logot.png</thumbnail> <description>MSNBC Live with Velshi & Ruhle</description> <mediaid>s297990</mediaid> <title>MSNBC</title> <contentid>0</contentid> </menuitem> <menuitem type="2"> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24940t.png</thumbnail> <description>Amazing music. Played by an amazing line up.</description> <mediaid>s24940</mediaid> <title>BBC Radio 2</title> <contentid>1</contentid> </menuitem> <menuitem type="2"> <thumbnail>http://cdn-radiotime-logos.tunein.com/s17077t.png</thumbnail> <description>Drive with Adrian Durham & Matt Holland</description> <mediaid>s17077</mediaid> <title>talkSPORT</title> <contentid>2</contentid> </menuitem> <menuitem type="2"> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24939t.png</thumbnail> <description>The best new music</description> <mediaid>s24939</mediaid> <title>BBC Radio 1</title> <contentid>3</contentid> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() items = api.get_current_radio_list(0, 30) self.assertEqual(len(items), 4) self.assertEqual(items[0], { '@type': '2', 'thumbnail': 'http://cdn-profiles.tunein.com/s297990/images/logot.png', 'description': 'MSNBC Live with Velshi & Ruhle', 'mediaid': 's297990', 'title': 'MSNBC', 'contentid': '0', }) @httpretty.activate(allow_net_connect=False) def test_get_upper_radio_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetUpperRadioList%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <root>Browse</root> <browsemode>0</browsemode> <category isroot="0">By Language</category> <totallistcount>4</totallistcount> <startindex>0</startindex> <listcount>4</listcount> <timestamp>2018-12-31T16:23:16Z</timestamp> <menulist> <menuitem type="0"> <title>Aboriginal</title> <contentid>0</contentid> </menuitem> <menuitem type="0"> <title>Afrikaans</title> <contentid>1</contentid> </menuitem> <menuitem type="0"> <title>Akan</title> <contentid>2</contentid> </menuitem> <menuitem type="0"> <title>Albanian</title> <contentid>3</contentid> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() items = api.get_upper_radio_list(0, 30) self.assertEqual(len(items), 4) self.assertEqual(items[0], { '@type': '0', 'title': 'Aboriginal', 'contentid': '0', }) @httpretty.activate(allow_net_connect=False) def test_set_play_select_single(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetPlaySelect%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22selectitemid%22%20val%3D%220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>StopPlaybackEvent</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <playtime>131</playtime> </response> </UIC>""" ) api = _get_api() api.set_play_select('0') @httpretty.activate(allow_net_connect=False) def test_set_play_select_multiple(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetPlaySelect%3C/name%3E%3Cp%20type%3D%22dec_arr%22%20name%3D%22selectitemids%22%20val%3D%22empty%22%3E%3Citem%3E1%3C/item%3E%3Citem%3E2%3C/item%3E%3Citem%3E3%3C/item%3E%3C/p%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>StopPlaybackEvent</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <playtime>131</playtime> </response> </UIC>""" ) api = _get_api() api.set_play_select(['1', '2', '3']) @httpretty.activate(allow_net_connect=False) def test_get_station_data(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetStationData%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22selectitemid%22%20val%3D%223%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>StationData</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>TuneIn</cpname> <title>BBC Radio 2</title> <browsemode>0</browsemode> <description>Amazing music. Played by an amazing line up.</description> <thumbnail>http://cdn-radiotime-logos.tunein.com/s24940d.png</thumbnail> <stationurl>http://opml.radiotime.com/Tune.ashx?id=s24940&partnerId=qDDAbg6M&serial=14BB6E87BBDB&formats=mp3,wma,aac,qt,hls</stationurl> <timestamp>2019-01-08T15:21:47Z</timestamp> </response> </CPM>""" ) api = _get_api() station_data = api.get_station_data(3) self.assertEqual(station_data, { 'cpname': 'TuneIn', 'title': 'BBC Radio 2', 'browsemode': '0', 'description': 'Amazing music. Played by an amazing line up.', 'thumbnail': 'http://cdn-radiotime-logos.tunein.com/s24940d.png', 'stationurl': 'http://opml.radiotime.com/Tune.ashx?id=s24940&partnerId=qDDAbg6M&serial=14BB6E87BBDB&formats=mp3,wma,aac,qt,hls', 'timestamp': '2019-01-08T15:21:47Z', }) @httpretty.activate(allow_net_connect=False) def test_get_7band_eq_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGet7BandEQList%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>7BandEQList</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <listcount>5</listcount> <presetlistcount>4</presetlistcount> <presetlist> <preset index="0"> <presetindex>0</presetindex> <presetname>None</presetname> </preset> <preset index="1"> <presetindex>1</presetindex> <presetname>Pop</presetname> </preset> <preset index="2"> <presetindex>2</presetindex> <presetname>Jazz</presetname> </preset> <preset index="3"> <presetindex>3</presetindex> <presetname>Classic</presetname> </preset> <preset index="4"> <presetindex>4</presetindex> <presetname>customtitle</presetname> </preset> </presetlist> </response> </UIC>""" ) api = _get_api() presets = api.get_7band_eq_list() self.assertEqual(len(presets), 5) self.assertEqual(presets[0], { '@index': '0', 'presetindex': '0', 'presetname': 'None' }) @httpretty.activate(allow_net_connect=False) def test_get_current_eq_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetCurrentEQMode%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>CurrentEQMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <presetindex>3</presetindex> <presetname>Classic</presetname> <eqvalue1>2</eqvalue1> <eqvalue2>0</eqvalue2> <eqvalue3>0</eqvalue3> <eqvalue4>5</eqvalue4> <eqvalue5>0</eqvalue5> <eqvalue6>1</eqvalue6> <eqvalue7>0</eqvalue7> </response> </UIC>""" ) api = _get_api() equalizer = api.get_current_eq_mode() self.assertEqual(equalizer, { 'presetindex': '3', 'presetname': 'Classic', 'eqvalue1': '2', 'eqvalue2': '0', 'eqvalue3': '0', 'eqvalue4': '5', 'eqvalue5': '0', 'eqvalue6': '1', 'eqvalue7': '0', }) @httpretty.activate(allow_net_connect=False) def test_set_7band_eq_value(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESet7bandEQValue%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22presetindex%22%20val%3D%224%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue1%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue2%22%20val%3D%222%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue3%22%20val%3D%223%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue4%22%20val%3D%224%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue5%22%20val%3D%225%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue6%22%20val%3D%226%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue7%22%20val%3D%22-6%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>7bandEQValue</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <presetindex>4</presetindex> <eqvalue1>1</eqvalue1> <eqvalue2>2</eqvalue2> <eqvalue3>3</eqvalue3> <eqvalue4>4</eqvalue4> <eqvalue5>5</eqvalue5> <eqvalue6>6</eqvalue6> <eqvalue7>-6</eqvalue7> </response> </UIC>""" ) api = _get_api() api.set_7band_eq_value(4, [1,2,3,4,5,6,-6]) @httpretty.activate(allow_net_connect=False) def test_set_7band_eq_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESet7bandEQMode%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22presetindex%22%20val%3D%221%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>7bandEQMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <presetindex>1</presetindex> <presetname>Pop</presetname> <eqvalue1>0</eqvalue1> <eqvalue2>-3</eqvalue2> <eqvalue3>3</eqvalue3> <eqvalue4>1</eqvalue4> <eqvalue5>-5</eqvalue5> <eqvalue6>0</eqvalue6> <eqvalue7>0</eqvalue7> </response> </UIC>""" ) api = _get_api() api.set_7band_eq_mode(1) @httpretty.activate(allow_net_connect=False) def test_reset_7band_eq_value(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EReset7bandEQValue%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22presetindex%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue1%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue2%22%20val%3D%222%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue3%22%20val%3D%223%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue4%22%20val%3D%224%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue5%22%20val%3D%225%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue6%22%20val%3D%226%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22eqvalue7%22%20val%3D%22-6%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>Reset7bandEQValue</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <presetindex>1</presetindex> <eqvalue1>1</eqvalue1> <eqvalue2>2</eqvalue2> <eqvalue3>3</eqvalue3> <eqvalue4>4</eqvalue4> <eqvalue5>5</eqvalue5> <eqvalue6>6</eqvalue6> <eqvalue7>-6</eqvalue7> </response> </UIC>""" ) api = _get_api() api.reset_7band_eq_value(1, [1,2,3,4,5,6,-6]) @httpretty.activate(allow_net_connect=False) def test_del_custom_eq_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EDelCustomEQMode%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22presetindex%22%20val%3D%225%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>DelCustomEQMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <presetindex>5</presetindex> <presetname>Custom 2</presetname> </response> </UIC>""" ) api = _get_api() api.del_custom_eq_mode(5) @httpretty.activate(allow_net_connect=False) def test_add_custom_eq_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EAddCustomEQMode%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22presetindex%22%20val%3D%225%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22presetname%22%20val%3D%22my%20custom%20preset%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>AddCustomEQMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <presetindex>5</presetindex> <presetname>my custom preset</presetname> </response> </UIC>""" ) api = _get_api() api.add_custom_eq_mode(5, 'my custom preset') @httpretty.activate(allow_net_connect=False) def test_set_speaker_time(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetSpeakerTime%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22year%22%20val%3D%222019%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22month%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22day%22%20val%3D%226%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22hour%22%20val%3D%2212%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22min%22%20val%3D%2255%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22sec%22%20val%3D%2224%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SpeakerTime</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <year>2019</year> <month>1</month> <day>6</day> <hour>12</hour> <min>55</min> <sec>24</sec> </response> </UIC>""" ) import datetime api = _get_api() api.set_speaker_time(datetime.datetime(2019, 1, 6, 12, 55, 24)) @httpretty.activate(allow_net_connect=False) def test_get_sleep_timer(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetSleepTimer%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SleepTime</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <sleepoption>off</sleepoption> <sleeptime>0</sleeptime> </response> </UIC>""" ) api = _get_api() timer = api.get_sleep_timer() self.assertEqual(timer, { 'sleepoption': 'off', 'sleeptime': '0', }) @httpretty.activate(allow_net_connect=False) def test_set_sleep_timer(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetSleepTimer%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22option%22%20val%3D%22start%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22sleeptime%22%20val%3D%22300%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>SleepTime</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <sleepoption>start</sleepoption> <sleeptime>300</sleeptime> </response> </UIC>""" ) api = _get_api() api.set_sleep_timer('start', 300) @httpretty.activate(allow_net_connect=False) def test_get_alarm_info(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetAlarmInfo%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>AllAlarmInfo</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <totalindexcount>2</totalindexcount> <alarmList> <alarm index="0"> <hour>13</hour> <min>27</min> <week>0x40</week> <volume>20</volume> <title /> <description /> <thumbnail /> <stationurl /> <set>on</set> <soundenable>on</soundenable> <sound>1</sound> <alarmsoundname>Disco</alarmsoundname> <duration>10</duration> </alarm> <alarm index="1"> <hour>14</hour> <min>25</min> <week>0x28</week> <volume>6</volume> <title><![CDATA[MSNBC]]></title> <description><![CDATA[MSNBC is the premier...]]></description> <thumbnail /> <stationurl><![CDATA[http://]]></stationurl> <set>on</set> <soundenable>off</soundenable> <sound>-1</sound> <alarmsoundname /> <duration>0</duration> </alarm> </alarmList> </response> </UIC>""" ) api = _get_api() alarm_info = api.get_alarm_info() self.assertEqual(len(alarm_info), 2) self.assertEqual(alarm_info[0], { '@index': '0', 'hour': '13', 'min': '27', 'week': '0x40', 'volume': '20', 'title': None, 'description': None, 'thumbnail': None, 'stationurl': None, 'set': 'on', 'soundenable': 'on', 'sound': '1', 'alarmsoundname': 'Disco', 'duration': '10', }) @httpretty.activate(allow_net_connect=False) def test_set_alarm_on_off(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetAlarmOnOff%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%220%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22alarm%22%20val%3D%22on%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>AlarmOnOff</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <index>0</index> <alarm>on</alarm> </response> </UIC>""" ) api = _get_api() api.set_alarm_on_off(0, 'on') @httpretty.activate(allow_net_connect=False) def test_get_alarm_sound_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetAlarmSoundList%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>AlarmSoundList</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <listcount>4</listcount> <alarmlist> <alarmsound index="0"> <alarsoundindex>0</alarsoundindex> <alarmsoundname>Active Morning</alarmsoundname> </alarmsound> <alarmsound index="1"> <alarsoundindex>1</alarsoundindex> <alarmsoundname>Disco</alarmsoundname> </alarmsound> <alarmsound index="2"> <alarsoundindex>2</alarsoundindex> <alarmsoundname>Vintage</alarmsoundname> </alarmsound> <alarmsound index="3"> <alarsoundindex>3</alarsoundindex> <alarmsoundname>Waltz</alarmsoundname> </alarmsound> </alarmlist> </response> </UIC>""" ) api = _get_api() sounds = api.get_alarm_sound_list() self.assertEqual(len(sounds), 4) self.assertEqual(sounds[0], { '@index': '0', 'alarsoundindex': '0', 'alarmsoundname': 'Active Morning', }) @httpretty.activate(allow_net_connect=False) def test_set_alarm_info(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetAlarmInfo%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22hour%22%20val%3D%2218%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22min%22%20val%3D%2221%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22week%22%20val%3D%220x1c%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22volume%22%20val%3D%222%22/%3E%3Cp%20type%3D%22cdata%22%20name%3D%22title%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BBBC%20Radio%204%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22cdata%22%20name%3D%22description%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BIntelligent%20speech%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22cdata%22%20name%3D%22thumbnail%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5Bhttp%3A//cdn-radiotime-logos.tunein.com/s25419d.png%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22cdata%22%20name%3D%22stationurl%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5Bhttp%3A//opml.radiotime.com/Tune.ashx%3Fid%3Ds25419%26partnerId%3DqDDAbg6M%26serial%3D90F1AAD31D82%26formats%3Dmp3%2Cwma%2Caac%2Cqt%2Chls%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22str%22%20name%3D%22soundenable%22%20val%3D%22off%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22sound%22%20val%3D%22-1%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22duration%22%20val%3D%220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>AlarmInfo</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <index>0</index> <hour>18</hour> <min>21</min> <week>0x1c</week> <volume>2</volume> <title><![CDATA[BBC Radio 4]]></title> <description><![CDATA[Intelligent speech]]></description> <thumbnail><![CDATA[http://cdn-radiotime-logos.tunein.com/s25419d.png]]></thumbnail> <stationurl><![CDATA[http://opml.radiotime.com/Tune.ashx?id=s25419&partnerId=qDDAbg6M&serial=90F1AAD31D82&formats=mp3,wma,aac,qt,hls]]></stationurl> <alarm>on</alarm> <soundenable>off</soundenable> <sound>-1</sound> <duration>0</duration> </response> </UIC>""" ) api = _get_api() api.set_alarm_info( index=0, hour=18, minute=21, week='0x1C', duration=0, volume=2, station_data={ 'title': 'BBC Radio 4', 'description': 'Intelligent speech', 'thumbnail': 'http://cdn-radiotime-logos.tunein.com/s25419d.png', 'stationurl': 'http://opml.radiotime.com/Tune.ashx?id=s25419&partnerId=qDDAbg6M&serial=90F1AAD31D82&formats=mp3,wma,aac,qt,hls', } ) @httpretty.activate(allow_net_connect=False) def test_del_alarm(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EDelAlarm%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22totaldelnum%22%20val%3D%224%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%222%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%224%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>DelAlarm</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier /> <response result="ok"> <index>0</index> <index>1</index> <index>2</index> </response> </UIC>""" ) api = _get_api() api.del_alarm([0, 1, 2, 4]) @unittest.skip('API call doesn\'t give any response') def test_spk_in_group(self): api = SamsungMultiroomApi(ip, 55001) api.spk_in_group('select') @httpretty.activate(allow_net_connect=False) def test_set_multispk_group(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetMultispkGroup%3C/name%3E%3Cp%20type%3D%22cdata%22%20name%3D%22name%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BTest%20group%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22dec%22%20name%3D%22index%22%20val%3D%221%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22type%22%20val%3D%22main%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22spknum%22%20val%3D%223%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22audiosourcemacaddr%22%20val%3D%2200%3A00%3A00%3A00%3A00%3A00%22/%3E%3Cp%20type%3D%22cdata%22%20name%3D%22audiosourcename%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BLiving%20Room%5D%5D%3E%3C/p%3E%3Cp%20type%3D%22str%22%20name%3D%22audiosourcetype%22%20val%3D%22speaker%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22subspkip%22%20val%3D%22192.168.1.165%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22subspkmacaddr%22%20val%3D%2211%3A11%3A11%3A11%3A11%3A11%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22subspkip%22%20val%3D%22192.168.1.216%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22subspkmacaddr%22%20val%3D%2222%3A22%3A22%3A22%3A22%3A22%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>MultispkGroupStartEvent</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <groupname><![CDATA[Test group]]></groupname> <grouptype>M</grouptype> </response> </UIC>""" ) api = _get_api() api.set_multispk_group('Test group', [ { 'name': 'Living Room', 'ip': '192.168.1.129', 'mac': '00:00:00:00:00:00', }, { 'name': 'Kitchen', 'ip': '192.168.1.165', 'mac': '11:11:11:11:11:11', }, { 'name': 'Bedroom', 'ip': '192.168.1.216', 'mac': '22:22:22:22:22:22', } ]) @httpretty.activate(allow_net_connect=False) def test_set_ungroup(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetUngroup%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>Ungroup</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok" /> </UIC>""" ) api = _get_api() api.set_ungroup() @httpretty.activate(allow_net_connect=False) def test_set_group_name(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetGroupName%3C/name%3E%3Cp%20type%3D%22cdata%22%20name%3D%22groupname%22%20val%3D%22empty%22%3E%3C%21%5BCDATA%5BUpdated%20group%20name%5D%5D%3E%3C/p%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>GroupName</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <groupname><![CDATA[Updated group name]]></groupname> </response> </UIC>""" ) api = _get_api() api.set_group_name('Updated group name') @httpretty.activate(allow_net_connect=False) def test_get_cp_list(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetCpList%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22liststartindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>CpList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <listtotalcount>24</listtotalcount> <liststartindex>0</liststartindex> <listcount>24</listcount> <cplist> <cp> <cpid>0</cpid> <cpname>Pandora</cpname> <signinstatus>0</signinstatus> </cp> <cp> <cpid>1</cpid> <cpname>Spotify</cpname> <signinstatus>0</signinstatus> </cp> <cp> <cpid>2</cpid> <cpname>Deezer</cpname> <signinstatus>1</signinstatus> <username>test_username</username> </cp> </cplist> </response> </CPM>""" ) api = _get_api() cps = api.get_cp_list(0, 30) self.assertEqual(len(cps), 3) self.assertEqual(cps[0], { 'cpid': '0', 'cpname': 'Pandora', 'signinstatus': '0', }) @httpretty.activate(allow_net_connect=False) def test_set_cp_service(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetCpService%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22cpservice_id%22%20val%3D%222%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="utf-8" ?> <CPM> <method>CpChanged</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> </response> </CPM>""" ) api = _get_api() api.set_cp_service(2) @httpretty.activate(allow_net_connect=False) def test_get_cp_info(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetCpInfo%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>CpInfo</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T09:50:46Z</timestamp> <category /> <signinstatus>1</signinstatus> <username>test_username</username> <subscription_info>Listening is limited to 30-second clips. Subscribe to enjoy unlimited music!</subscription_info> <audioinfo> <title>Introduction And Yaqui Indian Folk Song</title> <streamtype>station</streamtype> <thumbnail>https://e-cdns-images.dzcdn.net/images/cover/a9b4964ab775575efa2719827b9e88b9/500x500-000000-80-0-0.jpg</thumbnail> <playstatus>play</playstatus> </audioinfo> </response> </CPM>""" ) api = _get_api() cp_info = api.get_cp_info() self.assertEqual(cp_info, { 'cpname': 'Deezer', 'timestamp': '2019-01-14T09:50:46Z', 'category': None, 'signinstatus': '1', 'username': 'test_username', 'subscription_info': 'Listening is limited to 30-second clips. Subscribe to enjoy unlimited music!', 'audioinfo': { 'title': 'Introduction And Yaqui Indian Folk Song', 'streamtype': 'station', 'thumbnail': 'https://e-cdns-images.dzcdn.net/images/cover/a9b4964ab775575efa2719827b9e88b9/500x500-000000-80-0-0.jpg', 'playstatus': 'play', }, }) @httpretty.activate(allow_net_connect=False) def test_set_sign_in(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetSignIn%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22username%22%20val%3D%22test_username%22/%3E%3Cp%20type%3D%22str%22%20name%3D%22password%22%20val%3D%22test_password%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>SignInStatus</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T10:09:49Z</timestamp> <category isroot="1" /> <category_localized /> <signinstatus>1</signinstatus> <root>Playlist Picks</root> <root_index>2</root_index> <root_localized>Playlist Picks</root_localized> </response> </CPM>""" ) api = _get_api() api.set_sign_in('test_username', 'test_password') @httpretty.activate(allow_net_connect=False) def test_set_sign_out(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetSignOut%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>SignOutStatus</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T10:17:05Z</timestamp> <category isroot="1" /> <category_localized /> <signoutstatus>1</signoutstatus> </response> </CPM>""" ) api = _get_api() api.set_sign_out() @httpretty.activate(allow_net_connect=False) def test_get_cp_submenu(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetCpSubmenu%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>SubMenu</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T10:23:16Z</timestamp> <totallistcount>10</totallistcount> <submenu selected_id="0"> <submenuitem id="0"> <submenuitem_localized><![CDATA[Flow]]></submenuitem_localized> </submenuitem> <submenuitem id="1"> <submenuitem_localized><![CDATA[Browse]]></submenuitem_localized> </submenuitem> <submenuitem id="2"> <submenuitem_localized><![CDATA[Playlist Picks]]></submenuitem_localized> </submenuitem> </submenu> </response> </CPM>""" ) api = _get_api() submenu = api.get_cp_submenu() self.assertEqual(len(submenu), 3) self.assertEqual(submenu[0], { '@id': '0', 'submenuitem_localized': 'Flow', }) @httpretty.activate(allow_net_connect=False) def test_set_select_cp_submenu(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetSelectCpSubmenu%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22contentid%22%20val%3D%221%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2210%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T10:40:56Z</timestamp> <root>Browse</root> <root_index>1</root_index> <root_localized>Browse</root_localized> <category isroot="1">Genres</category> <category_localized>Genres</category_localized> <totallistcount>23</totallistcount> <startindex>0</startindex> <listcount>10</listcount> <menulist> <menuitem type="0"> <title>All</title> <contentid>0</contentid> </menuitem> <menuitem type="0"> <title>Pop</title> <contentid>1</contentid> </menuitem> <menuitem type="0"> <title>Rap/Hip Hop</title> <contentid>2</contentid> </menuitem> <menuitem type="0"> <title>Rock</title> <contentid>3</contentid> </menuitem> <menuitem type="0"> <title>Dance</title> <contentid>4</contentid> </menuitem> <menuitem type="0"> <title>R&B</title> <contentid>5</contentid> </menuitem> <menuitem type="0"> <title>Alternative</title> <contentid>6</contentid> </menuitem> <menuitem type="0"> <title>Electro</title> <contentid>7</contentid> </menuitem> <menuitem type="0"> <title>Folk</title> <contentid>8</contentid> </menuitem> <menuitem type="0"> <title>Reggae</title> <contentid>9</contentid> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() submenu = api.set_select_cp_submenu(1, 0, 10) self.assertEqual(len(submenu), 10) self.assertEqual(submenu[0], { '@type': '0', 'title': 'All', 'contentid': '0', }) @httpretty.activate(allow_net_connect=False) def test_get_cp_player_playlist(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3EGetCpPlayerPlaylist%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22startindex%22%20val%3D%220%22/%3E%3Cp%20type%3D%22dec%22%20name%3D%22listcount%22%20val%3D%2230%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>RadioPlayList</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T11:10:39Z</timestamp> <root>Playlist Picks</root> <root_index>2</root_index> <root_localized>Playlist Picks</root_localized> <category isroot="0">Playlist</category> <category_localized>Playlist</category_localized> <totallistcount>3</totallistcount> <startindex>0</startindex> <listcount>3</listcount> <menulist> <menuitem type="1" available="1" currentplaying="1"> <artist>Madeleine Peyroux</artist> <album>Careless Love</album> <mediaid>881851</mediaid> <tracklength>0</tracklength> <title>Don't Wait Too Long</title> <contentid>0</contentid> <thumbnail>http://api.deezer.com/album/100127/image</thumbnail> </menuitem> <menuitem type="1" available="1"> <artist>Marcus Strickland's Twi-Life</artist> <album>Nihil Novi</album> <mediaid>122883722</mediaid> <tracklength>0</tracklength> <title>Cycle</title> <contentid>1</contentid> <thumbnail>http://api.deezer.com/album/12864776/image</thumbnail> </menuitem> <menuitem type="1" available="1"> <artist>Bill Evans Trio</artist> <album>Everybody Digs Bill Evans (Remastered)</album> <mediaid>4156086</mediaid> <tracklength>0</tracklength> <title>What Is There To Say? (Album Version)</title> <contentid>2</contentid> <thumbnail>http://api.deezer.com/album/387401/image</thumbnail> </menuitem> </menulist> </response> </CPM>""" ) api = _get_api() playlist = api.get_cp_player_playlist(0, 30) self.assertEqual(len(playlist), 3) self.assertEqual(playlist[0], { '@type': '1', '@available': '1', '@currentplaying': '1', 'artist': 'Madeleine Peyroux', 'album': 'Careless Love', 'mediaid': '881851', 'tracklength': '0', 'title': 'Don\'t Wait Too Long', 'contentid': '0', 'thumbnail': 'http://api.deezer.com/album/100127/image', }) @httpretty.activate(allow_net_connect=False) def test_set_skip_current_track(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetSkipCurrentTrack%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <CPM> <method>SkipInfo</method> <version>0.1</version> <speakerip>192.168.1.129</speakerip> <user_identifier>407c385a-17ef-11e9-b3ee-48e244f52360</user_identifier> <response result="ok"> <cpname>Deezer</cpname> <timestamp>2019-01-14T11:21:25Z</timestamp> <category isroot="1" /> <category_localized /> <skipstatus>1</skipstatus> <root>Flow</root> <root_index>0</root_index> <root_localized>Flow</root_localized> </response> </CPM>""" ) api = _get_api() api.set_skip_current_track() @httpretty.activate(allow_net_connect=False) def test_get_current_play_time(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetCurrentPlayTime%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>MusicPlayTime</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <timelength>168</timelength> <playtime>121</playtime> </response> </UIC>""" ) api = _get_api() play_time = api.get_current_play_time() self.assertEqual(play_time, { 'timelength': '168', 'playtime': '121', }) @httpretty.activate(allow_net_connect=False) def test_set_play_cp_playlist_track(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/CPM?cmd=%3Cname%3ESetPlayCpPlaylistTrack%3C/name%3E%3Cp%20type%3D%22dec%22%20name%3D%22selectitemid%22%20val%3D%220%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>StopPlaybackEvent</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <playtime>3</playtime> </response> </UIC>""" ) api = _get_api() api.set_play_cp_playlist_track(0) @httpretty.activate(allow_net_connect=False) def test_get_repeat_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3EGetRepeatMode%3C/name%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>RepeatMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <repeat>off</repeat> </response> </UIC>""" ) api = _get_api() repeat_mode = api.get_repeat_mode() self.assertEqual(repeat_mode, 'off') @httpretty.activate(allow_net_connect=False) def test_set_repeat_mode(self): httpretty.register_uri( httpretty.GET, 'http://192.168.1.129:55001/UIC?cmd=%3Cname%3ESetRepeatMode%3C/name%3E%3Cp%20type%3D%22str%22%20name%3D%22repeatmode%22%20val%3D%22one%22/%3E', match_querystring=True, body="""<?xml version="1.0" encoding="UTF-8"?> <UIC> <method>RepeatMode</method> <version>1.0</version> <speakerip>192.168.1.129</speakerip> <user_identifier>public</user_identifier> <response result="ok"> <repeat>one</repeat> </response> </UIC>""" ) api = _get_api() api.set_repeat_mode('one')

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null

0

6

4252a73ac5bfc9f57f305e588d8bf00c7b953753

68

py

Python

lib/__init__.py

harshareddy794/web-scanner

c71157991810d1288029705a3dfec17fcb869230

[ "Apache-2.0" ]

null

lib/__init__.py

harshareddy794/web-scanner

c71157991810d1288029705a3dfec17fcb869230

[ "Apache-2.0" ]

null

lib/__init__.py

harshareddy794/web-scanner

c71157991810d1288029705a3dfec17fcb869230

[ "Apache-2.0" ]

null

from lib.port_scanner import scanner from lib.spyder import crawler

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4253eabb486b805e15d3e45d643290e0bbeba860

57

py

Python

tests/test_import.py

DocLM/pynonymizer

1ab2b6323a2b7324fef3a4224231329936a2356f

[ "MIT" ]

40

2020-10-19T14:08:05.000Z

2021-11-19T10:44:52.000Z

tests/test_import.py

DocLM/pynonymizer

1ab2b6323a2b7324fef3a4224231329936a2356f

[ "MIT" ]

51

2020-09-21T19:59:03.000Z

2021-11-12T09:19:00.000Z

tests/test_import.py

DocLM/pynonymizer

1ab2b6323a2b7324fef3a4224231329936a2356f

[ "MIT" ]

19

2020-10-20T13:18:41.000Z

2021-11-11T13:22:00.000Z

def test_main_imports(): from pynonymizer import run

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6

c40f6dd663fc398171fee772ad854c042a3bc538

3,490

py

Python

asyncapi_schema_pydantic/v2_3_0/web_sockets_bindings.py

albertnadal/asyncapi-schema-pydantic

83966bdc11f2d465a10b52cec5ff79d18fa6f5fe

[ "MIT" ]

null

asyncapi_schema_pydantic/v2_3_0/web_sockets_bindings.py

albertnadal/asyncapi-schema-pydantic

83966bdc11f2d465a10b52cec5ff79d18fa6f5fe

[ "MIT" ]

null

asyncapi_schema_pydantic/v2_3_0/web_sockets_bindings.py

albertnadal/asyncapi-schema-pydantic

83966bdc11f2d465a10b52cec5ff79d18fa6f5fe

[ "MIT" ]

null

from typing import Optional from enum import Enum from pydantic import BaseModel, Extra from .schema import Schema class WebSocketsMethod(str, Enum): get = 'GET' post = 'POST' class WebSocketsChannelBinding(BaseModel): """ When using WebSockets, the channel represents the connection. Unlike other protocols that support multiple virtual channels (topics, routing keys, etc.) per connection, WebSockets doesn't support virtual channels or, put it another way, there's only one channel and its characteristics are strongly related to the protocol used for the handshake, i.e., HTTP. """ method: Optional[WebSocketsMethod] = None """ The HTTP method to use when establishing the connection. Its value MUST be either GET or POST. """ query: Optional[Schema] = None """ A Schema object containing the definitions for each query parameter. This schema MUST be of type object and have a properties key. """ headers: Optional[Schema] = None """ A Schema object containing the definitions of the HTTP headers to use when establishing the connection. This schema MUST be of type object and have a properties key. """ bindingVersion: Optional[str] = None """ The version of this binding. If omitted, "latest" MUST be assumed. """ class WebSocketsMessageBinding(BaseModel): """ This document defines how to describe WebSockets-specific information on AsyncAPI. This object MUST NOT contain any properties. Its name is reserved for future use. """ class Config: extra = Extra.forbid class WebSocketsOperationBinding(BaseModel): """ This document defines how to describe WebSockets-specific information on AsyncAPI. This object MUST NOT contain any properties. Its name is reserved for future use. """ class Config: extra = Extra.forbid class WebSocketsServerBinding(BaseModel): """ This document defines how to describe WebSockets-specific information on AsyncAPI. This object MUST NOT contain any properties. Its name is reserved for future use. """ class Config: extra = Extra.forbid class WebSocketsChannelBinding(BaseModel): """ This document defines how to describe WebSockets-specific information on AsyncAPI. When using WebSockets, the channel represents the connection. Unlike other protocols that support multiple virtual channels (topics, routing keys, etc.) per connection, WebSockets doesn't support virtual channels or, put it another way, there's only one channel and its characteristics are strongly related to the protocol used for the handshake, i.e., HTTP. """ method: Optional[WebSocketsMethod] = None """ The HTTP method to use when establishing the connection. Its value MUST be either GET or POST. """ query: Optional[Schema] = None """ A Schema object containing the definitions for each query parameter. This schema MUST be of type object and have a properties key. """ headers: Optional[Schema] = None """ A Schema object containing the definitions of the HTTP headers to use when establishing the connection. This schema MUST be of type object and have a properties key. """ bindingVersion: Optional[str] = None """ The version of this binding. If omitted, "latest" MUST be assumed. """ class Config: extra = Extra.forbid

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0

null

0

1

0

null

0

6

c41e02d072565bccfb2d540639fe976b16426bd2

3,248

py

Python

validation.py

RoRyou/lost_

c0fd3be6808edb126974f606285e15332849f8be

[ "Apache-2.0" ]

null

validation.py

RoRyou/lost_

c0fd3be6808edb126974f606285e15332849f8be

[ "Apache-2.0" ]

null

validation.py

RoRyou/lost_

c0fd3be6808edb126974f606285e15332849f8be

[ "Apache-2.0" ]

null

import pandas as pd df5 = pd.read_csv('D:/data/final_data_5.csv') df6 = pd.read_csv('D:/data/final_data_6.csv') df7 = pd.read_csv('D:/data/final_data_7.csv') df8 = pd.read_csv('D:/data/final_data_8.csv') df9 = pd.read_csv('D:/data/final_data_9.csv') df10 = pd.read_csv('D:/data/final_data_10.csv') dict = {} for key in df10['LOST'].tolist(): dict[key] = dict.get(key, 0) + 1 print('A5服务器总流失率') print("%.2f%%" %(dict[1]/(dict[0]+dict[1]))) # print('------------') # ACT_lists=['isparty', 'isXMSL','isLYQ','isKTT','isXMHJ','isSYZC','isPTY','isFBJL','isFBRH','dyLMZ', 'dyXMSL', 'dyLYQ', 'dyKTT', 'dyXMHJ', 'dySYZC', 'dyPTY', 'dyFBJL', 'dyFBRH', 'dybanggong','dyfee', 'isfee', 'dyForge_time', 'dyrate', 'dykilltimes','dykilledtimes'] # for ACT in ACT_lists: # dict = {} # for key in df5[df5[ACT] == 0]['LOST'].tolist(): # dict[key] = dict.get(key, 0) + 1 # if dict[1] == dict[0] + dict[1]: # print('所有人都参与了该活动') # else: # print('未玩过', ACT, '该活动流失率') # print("%.2f%%" %(dict[1]/(dict[0]+dict[1]))) # # dict = {} # for key in df5[df5[ACT] == 1]['LOST'].tolist(): # dict[key] = dict.get(key, 0) + 1 # if dict[1] == dict[0] + dict[1]: # print('所有人都参与了该活动') # else: # print('玩过',ACT,'该活动流失率') # print("%.2f%%" %(dict[1]/(dict[0]+dict[1]))) # print('------------') # # print('------------') # ACT_lists=['isparty', 'dyLMZ', 'dyXMSL', 'isXMSL', 'dyLYQ','isLYQ', 'dyKTT', 'isKTT', 'dyXMHJ', 'isXMHJ', 'dySYZC', 'isSYZC','dyPTY', 'isPTY', 'dyFBJL', 'isFBJL', 'dyFBRH', 'isFBRH', 'dybanggong','dyfee', 'isfee', 'dyForge_time', 'dyrate', 'dykilltimes','dykilledtimes'] # for ACT in ACT_lists: # dict = {} # for key in df6[df6[ACT] == 0]['LOST'].tolist(): # dict[key] = dict.get(key, 0) + 1 # if dict[1] == dict[0] + dict[1]: # print('所有人都参与了该活动') # else: # print('未玩过', ACT, '该活动流失率') # print(dict[1]/(dict[0]+dict[1])) # # dict = {} # for key in df6[df6[ACT] == 1]['LOST'].tolist(): # dict[key] = dict.get(key, 0) + 1 # if dict[1] == dict[0] + dict[1]: # print('所有人都参与了该活动') # else: # print('玩过',ACT,'该活动流失率') # print(dict[1]/(dict[0]+dict[1])) # print('------------') print('------------') ACT_lists=['isparty', 'isXMSL','isLYQ', 'isKTT','isXMHJ','isSYZC','isPTY','isFBJL','isFBRH','dyLMZ', 'dyXMSL', 'dyLYQ', 'dyKTT', 'dyXMHJ', 'dySYZC', 'dyPTY', 'dyFBJL', 'dyFBRH', 'dybanggong','dyfee', 'isfee', 'dyForge_time', 'dyrate', 'dykilltimes','dykilledtimes'] for ACT in ACT_lists: dict = {} for key in df5[df5[ACT] == 0]['LOST'].tolist(): dict[key] = dict.get(key, 0) + 1 if dict[1] == dict[0] + dict[1]: print('所有人都参与了该活动') else: print('未玩过', ACT, '该活动流失率') print("%.2f%%" %(dict[1]/(dict[0]+dict[1]))) dict = {} for key in df5[df5[ACT] == 1]['LOST'].tolist(): dict[key] = dict.get(key, 0) + 1 if dict[1] == dict[0] + dict[1]: print('所有人都参与了该活动') else: print('玩过',ACT,'该活动流失率') print("%.2f%%" %(dict[1]/(dict[0]+dict[1]))) print('------------')

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c48168f80c7427a7a5d9e3479c339e3caba1294b

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py

Python

nipy/algorithms/statistics/models/tests/test_olsR.py

bpinsard/nipy

d49e8292adad6619e3dac710752131b567efe90e

[ "BSD-3-Clause" ]

236

2015-01-09T21:28:37.000Z

2022-03-27T11:51:58.000Z

nipy/algorithms/statistics/models/tests/test_olsR.py

bpinsard/nipy

d49e8292adad6619e3dac710752131b567efe90e

[ "BSD-3-Clause" ]

171

2015-03-23T00:31:43.000Z

2021-11-22T12:43:00.000Z

nipy/algorithms/statistics/models/tests/test_olsR.py

bpinsard/nipy

d49e8292adad6619e3dac710752131b567efe90e

[ "BSD-3-Clause" ]

94

2015-02-01T12:39:47.000Z

2022-01-27T06:38:19.000Z

from __future__ import absolute_import import numpy as np from ..regression import OLSModel import nipy.testing as niptest import scipy.stats from .exampledata import x, y Rscript = ''' d = read.table('data.csv', header=T, sep=' ') y.lm = lm(Y ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 + X10 + X11 + X12 + X13 + X14, data=d) print(summary(y.lm)) y.lm2 = lm(Y ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 + X10 + X11 + X12 + X13 + X14 - 1, data=d) print(summary(y.lm2)) SSE = sum(resid(y.lm)^2) SST = sum((d$Y - mean(d$Y))^2) SSR = SST - SSE print(data.frame(SSE, SST, SSR)) MSE = SSE / y.lm$df.resid MST = SST / (length(d$Y) - 1) MSR = SSR / (length(d$Y) - y.lm$df.resid - 1) print(data.frame(MSE, MST, MSR)) print(AIC(y.lm)) print(AIC(y.lm2)) ''' # lines about "Signif. codes" were deleted due to a character encoding issue Rresults = \ """ These are the results from fitting the model in R, i.e. running the commands Rscript in R A few things to note, X8 is a column of 1s, so by not including a '-1' in the formula, X8 gets thrown out of the model, with its coefficients being the "(Intercept)" term. An alternative is to use "-1" in the formula, but then R gives nonsensical F, R2 and adjusted R2 values. This means that R2, R2a and F cannot fully be trusted in R. In OLSModel, we have checked whether a column of 1s is in the column space, in which case the F, R2, and R2a are seneible. > source('test.R') [1] "Without using '-1'" [1] "------------------" Call: lm(formula = Y ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 + X10 + X11 + X12 + X13 + X14, data = d) Residuals: Min 1Q Median 3Q Max -2.125783 -0.567850 0.004305 0.532145 2.372263 Coefficients: (1 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 2.603e+02 8.226e-01 316.463 < 2e-16 *** X1 1.439e-02 2.649e-02 0.543 0.5881 X2 -6.975e+00 1.022e+01 -0.683 0.4963 X3 4.410e+01 5.740e+00 7.682 6.42e-12 *** X4 3.864e+00 5.770e+00 0.670 0.5044 X5 2.458e+02 4.594e+02 0.535 0.5937 X6 9.789e+02 3.851e+02 2.542 0.0124 * X7 1.339e+03 8.418e+02 1.591 0.1145 X8 NA NA NA NA X9 -1.955e-02 1.539e-02 -1.270 0.2066 X10 7.042e-05 2.173e-04 0.324 0.7465 X11 -3.743e-08 6.770e-07 -0.055 0.9560 X12 3.060e-06 2.094e-06 1.461 0.1469 X13 1.440e-06 1.992e-06 0.723 0.4711 X14 -1.044e-05 7.215e-06 -1.448 0.1505 --- Residual standard error: 0.8019 on 112 degrees of freedom Multiple R-squared: 0.5737,Adjusted R-squared: 0.5242 F-statistic: 11.59 on 13 and 112 DF, p-value: 1.818e-15 [1] "Using '-1'" [1] "------------------" Call: lm(formula = Y ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 + X10 + X11 + X12 + X13 + X14 - 1, data = d) Residuals: Min 1Q Median 3Q Max -2.125783 -0.567850 0.004305 0.532145 2.372263 Coefficients: Estimate Std. Error t value Pr(>|t|) X1 1.439e-02 2.649e-02 0.543 0.5881 X2 -6.975e+00 1.022e+01 -0.683 0.4963 X3 4.410e+01 5.740e+00 7.682 6.42e-12 *** X4 3.864e+00 5.770e+00 0.670 0.5044 X5 2.458e+02 4.594e+02 0.535 0.5937 X6 9.789e+02 3.851e+02 2.542 0.0124 * X7 1.339e+03 8.418e+02 1.591 0.1145 X8 2.603e+02 8.226e-01 316.463 < 2e-16 *** X9 -1.955e-02 1.539e-02 -1.270 0.2066 X10 7.042e-05 2.173e-04 0.324 0.7465 X11 -3.743e-08 6.770e-07 -0.055 0.9560 X12 3.060e-06 2.094e-06 1.461 0.1469 X13 1.440e-06 1.992e-06 0.723 0.4711 X14 -1.044e-05 7.215e-06 -1.448 0.1505 --- Residual standard error: 0.8019 on 112 degrees of freedom Multiple R-squared: 1,Adjusted R-squared: 1 F-statistic: 9.399e+05 on 14 and 112 DF, p-value: < 2.2e-16 SSE SST SSR 1 72.02328 168.9401 96.91685 MSE MST MSR 1 0.643065 1.351521 7.455142 [1] "AIC" [1] 317.1017 [1] "BIC" [1] 359.6459 """ def test_results(): m = OLSModel(x) r = m.fit(y) # results hand compared with R's printout yield niptest.assert_equal, '%0.4f' % r.R2, '0.5737' yield niptest.assert_equal, '%0.4f' % r.R2_adj, '0.5242' f = r.F_overall yield niptest.assert_equal, '%0.2f' % f['F'], '11.59' yield niptest.assert_equal, f['df_num'], 13 yield niptest.assert_equal, f['df_den'], 112 yield niptest.assert_equal, '%0.3e' % f['p_value'], '1.818e-15' # test Fcontrast, the 8th column of m.design is all 1s # let's construct a contrast matrix that tests everything # but column 8 is zero M = np.identity(14) M = np.array([M[i] for i in [0,1,2,3,4,5,6,8,9,10,11,12,13]]) Fc = r.Fcontrast(M) yield niptest.assert_array_almost_equal, [Fc.F], [f['F']], 6 yield niptest.assert_array_almost_equal, [Fc.df_num], [f['df_num']], 6 yield niptest.assert_array_almost_equal, [Fc.df_den], [f['df_den']], 6 thetas = [] sds = [] ts = [] ps = [] # the model has an intercept yield niptest.assert_true, r.model.has_intercept # design matrix has full rank yield niptest.assert_equal, r.model.rank, 14 # design matrix has full rank yield niptest.assert_equal, r.df_model, 14 yield niptest.assert_equal, r.df_total, 126 yield niptest.assert_equal, r.df_resid, 112 # entries with '*****' are not tested as they were a different format resultstr = \ ''' X1 1.439e-02 2.649e-02 0.543 0.5881 X2 -6.975e+00 1.022e+01 -0.683 0.4963 X3 4.410e+01 5.740e+00 7.682 ****** X4 3.864e+00 5.770e+00 0.670 0.5044 X5 2.458e+02 4.594e+02 0.535 0.5937 X6 9.789e+02 3.851e+02 2.542 0.0124 X7 1.339e+03 8.418e+02 1.591 0.1145 X8 2.603e+02 8.226e-01 316.463 ****** X9 -1.955e-02 1.539e-02 -1.270 0.2066 X10 7.042e-05 2.173e-04 0.324 0.7465 X11 -3.743e-08 6.770e-07 -0.055 0.9560 X12 3.060e-06 2.094e-06 1.461 0.1469 X13 1.440e-06 1.992e-06 0.723 0.4711 X14 -1.044e-05 7.215e-06 -1.448 0.1505 X1 1.439e-02 2.649e-02 0.543 0.5881 X2 -6.975e+00 1.022e+01 -0.683 0.4963 X3 4.410e+01 5.740e+00 7.682 ****** X4 3.864e+00 5.770e+00 0.670 0.5044 X5 2.458e+02 4.594e+02 0.535 0.5937 X6 9.789e+02 3.851e+02 2.542 0.0124 X7 1.339e+03 8.418e+02 1.591 0.1145 X8 2.603e+02 8.226e-01 316.463 ****** X9 -1.955e-02 1.539e-02 -1.270 0.2066 X10 7.042e-05 2.173e-04 0.324 0.7465 X11 -3.743e-08 6.770e-07 -0.055 0.9560 X12 3.060e-06 2.094e-06 1.461 0.1469 X13 1.440e-06 1.992e-06 0.723 0.4711 X14 -1.044e-05 7.215e-06 -1.448 0.1505 ''' for row in resultstr.strip().split('\n'): row = row.strip() _, th, sd, t, p = row.split() thetas.append(th) sds.append(sd) ts.append(t) ps.append(p) for th, thstr in zip(r.theta, thetas): yield niptest.assert_equal, '%0.3e' % th, thstr for sd, sdstr in zip([np.sqrt(r.vcov(column=i)) for i in range(14)], sds): yield niptest.assert_equal, '%0.3e' % sd, sdstr for t, tstr in zip([r.t(column=i) for i in range(14)], ts): yield niptest.assert_equal, '%0.3f' % t, tstr for i, t in enumerate([r.t(column=i) for i in range(14)]): m = np.zeros((14,)) m[i] = 1. tv = r.Tcontrast(m) e = r.theta[i] sd = np.sqrt(r.vcov(column=i)) yield niptest.assert_almost_equal, tv.t, t, 6 yield niptest.assert_almost_equal, tv.sd, sd, 6 yield niptest.assert_almost_equal, tv.effect, e, 6 for p, pstr in zip([2*scipy.stats.t.sf(np.fabs(r.t(column=i)), r.df_resid) for i in range(14)], ps): if pstr.find('*') < 0: yield niptest.assert_equal, '%0.4f' % p, pstr yield niptest.assert_equal, "%0.5f" % r.SSE, "72.02328" yield niptest.assert_equal, "%0.4f" % r.SST, "168.9401" yield niptest.assert_equal, "%0.5f" % r.SSR, "96.91685" yield niptest.assert_equal, "%0.6f" % r.MSE, "0.643065" yield niptest.assert_equal, "%0.6f" % r.MST, "1.351521" yield niptest.assert_equal, "%0.6f" % r.MSR, "7.455142" yield niptest.assert_equal, "%0.4f" % np.sqrt(r.MSE), "0.8019" # the difference here comes from the fact that # we've treated sigma as a nuisance parameter, # so our AIC is the AIC of the profiled log-likelihood... yield niptest.assert_equal, '%0.4f'% (r.AIC + 2,), '317.1017' yield niptest.assert_equal, '%0.4f'% (r.BIC + np.log(126),), '359.6459' # this is the file "data.csv" referred to in Rscript above Rdata = ''' Y X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 2.558020266818153345e+02 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Python

climpred/tests/test_alignment.py

raybellwaves/climpred

4ce5e3d30dbaa98fb974b54d82a5403c424a79db

[ "MIT" ]

104

2020-09-17T16:46:37.000Z

2022-03-29T16:49:44.000Z

climpred/tests/test_alignment.py

raybellwaves/climpred

4ce5e3d30dbaa98fb974b54d82a5403c424a79db

[ "MIT" ]

303

2020-09-17T16:05:24.000Z

2022-03-28T19:59:31.000Z

climpred/tests/test_alignment.py

kpegion/climpred

b3562311af253b9ee0e0cd97d196b0fd34936031

[ "MIT" ]

18

2020-10-08T15:40:42.000Z

2022-03-29T19:07:54.000Z

import logging import numpy as np import pytest import xskillscore as xs from climpred.exceptions import CoordinateError from climpred.prediction import compute_hindcast def test_same_inits_initializations( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, caplog ): """Tests that inits are identical at all leads for `same_inits` alignment.""" with caplog.at_level(logging.INFO): compute_hindcast( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, alignment="same_inits", ) for i, record in enumerate(caplog.record_tuples): if i >= 2: print(record) assert "inits: 1954-01-01 00:00:00-2007-01-01 00:00:00" in record[2] def test_same_inits_verification_dates( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, caplog ): """Tests that appropriate verifs are being used at each lead for `same_inits` alignment.""" with caplog.at_level(logging.INFO): FIRST_INIT, LAST_INIT = 1954, 2007 compute_hindcast( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, alignment="same_inits", ) nleads = hind_ds_initialized_1d_cftime["lead"].size for i, record in zip( np.arange(nleads + 2), caplog.record_tuples, ): if i >= 2: print(record) assert ( f"verifs: {FIRST_INIT+i}-01-01 00:00:00-{LAST_INIT+i}-01-01" in record[2] ) @pytest.mark.parametrize("alignment", ["same_inits", "same_verifs"]) def test_disjoint_verif_time(small_initialized_da, small_verif_da, alignment): """Tests that alignment works with disjoint time in the verification data, i.e., non-continuous time sampling to verify against.""" hind = small_initialized_da verif = small_verif_da.drop_sel(time=1992) actual = compute_hindcast(hind, verif, alignment=alignment, metric="mse") assert actual.notnull().all() # hindcast inits: [1990, 1991, 1992, 1993] # verif times: [1990, 1991, 1993, 1994] a = hind.sel(init=[1990, 1992, 1993]).rename({"init": "time"}) b = verif.sel(time=[1991, 1993, 1994]) a["time"] = b["time"] expected = xs.mse(a, b, "time") assert actual == expected @pytest.mark.parametrize("alignment", ["same_inits", "same_verifs"]) def test_disjoint_inits(small_initialized_da, small_verif_da, alignment): """Tests that alignment works with disjoint inits in the verification data, i.e., non-continuous initializing to verify with.""" hind = small_initialized_da.drop_sel(init=1991) verif = small_verif_da actual = compute_hindcast(hind, verif, alignment=alignment, metric="mse") assert actual.notnull().all() # hindcast inits: [1990, 1992, 1993] # verif times: [1990, 1991, 1992, 1993, 1994] a = hind.rename({"init": "time"}) b = verif.sel(time=[1991, 1993, 1994]) a["time"] = b["time"] expected = xs.mse(a, b, "time") assert actual == expected def test_same_verifs_verification_dates( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, caplog ): """Tests that verifs are identical at all leads for `same_verifs` alignment.""" with caplog.at_level(logging.INFO): compute_hindcast( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, alignment="same_verifs", ) for i, record in enumerate(caplog.record_tuples): if i >= 2: print(record) assert "verifs: 1964-01-01 00:00:00-2017-01-01 00:00:00" in record[2] def test_same_verifs_initializations( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, caplog ): """Tests that appropriate verifs are being used at each lead for `same_inits` alignment.""" with caplog.at_level(logging.INFO): FIRST_INIT, LAST_INIT = 1964, 2017 compute_hindcast( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, alignment="same_verifs", ) nleads = hind_ds_initialized_1d_cftime["lead"].size for i, record in zip( np.arange(nleads + 2), caplog.record_tuples, ): if i >= 2: print(record) assert ( f"inits: {FIRST_INIT-i}-01-01 00:00:00-{LAST_INIT-i}-01-01 00:00:00" in record[2] ) def test_same_verifs_raises_error_when_not_possible( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime ): """Tests that appropriate error is raised when a common set of verification dates cannot be found with the supplied initializations.""" hind = hind_ds_initialized_1d_cftime.isel(lead=slice(0, 3), init=[1, 3, 5, 7, 9]) with pytest.raises(CoordinateError): compute_hindcast(hind, reconstruction_ds_1d_cftime, alignment="same_verifs") def test_maximize_alignment_inits( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, caplog ): """Tests that appropriate inits are selected for `maximize` alignment.""" with caplog.at_level(logging.INFO): compute_hindcast( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, alignment="maximize", ) # Add dummy values for the first two lines since they are just metadata. for i, record in zip( np.concatenate(([0, 0], hind_ds_initialized_1d_cftime.lead.values)), caplog.record_tuples, ): if i >= 1: print(record) assert ( f"inits: 1954-01-01 00:00:00-{2016-i}-01-01 00:00:00" in record[2] ) def test_maximize_alignment_verifs( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, caplog ): """Tests that appropriate verifs are selected for `maximize` alignment.""" with caplog.at_level(logging.INFO): compute_hindcast( hind_ds_initialized_1d_cftime, reconstruction_ds_1d_cftime, alignment="maximize", ) # Add dummy values for the first two lines since they are just metadata. for i, record in zip( np.concatenate(([0, 0], hind_ds_initialized_1d_cftime.lead.values)), caplog.record_tuples, ): if i >= 1: print(record) assert ( f"verifs: {1955+i}-01-01 00:00:00-2017-01-01 00:00:00" in record[2] )

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672669c234855969496e3d70836e376ca328b213

12,033

py

Python

neuvol/individs/initialization_network.py

Qwinpin/Neural_evolution

f8ebc8a171a6954718aa25f461e9b93afd698b8a

[ "Apache-2.0" ]

6

2019-06-28T10:02:02.000Z

2021-03-02T10:03:48.000Z

neuvol/individs/initialization_network.py

Qwinpin/Neural_evolution

f8ebc8a171a6954718aa25f461e9b93afd698b8a

[ "Apache-2.0" ]

13

2018-11-27T13:45:33.000Z

2019-10-04T11:22:32.000Z

neuvol/individs/initialization_network.py

Qwinpin/Neuvol

f8ebc8a171a6954718aa25f461e9b93afd698b8a

[ "Apache-2.0" ]

2

2018-09-26T12:07:18.000Z

2018-09-26T12:09:46.000Z

import torch import numpy as np class Network(torch.nn.Module): def __init__(self, structure): super(Network, self).__init__() self.structure = structure self.layers_pool_inited = self.init_layers(self.structure) def init_layers(self, structure): # pool of layers, which should be initialised and connected layers_pool = [0] # pool of initialised layers layers_pool_inited = {} # pool of broken (invalid) layers) such as inconsistent number of dimensions layers_pool_removed = [] while layers_pool: # take first layer in a pool layer_index = layers_pool[0] # find all connections before this layer enter_layers = set(np.where(self.structure.matrix[:, layer_index] == 1)[0]) # check if some of previous layers were not initialized # that means - we should initialise them first not_inited_layers = [i for i in enter_layers if i not in (layers_pool_inited.keys())] not_inited_layers_selected = [layer for layer in not_inited_layers if layer not in layers_pool_removed] if not_inited_layers_selected: # remove layers, which are in pool already # this is possible due to complex connections with different orders not_inited_layers_selected = [layer for layer in not_inited_layers_selected if layer not in layers_pool] # add not initialised layers to the pool layers_pool.extend(not_inited_layers_selected) # current layer should be shift to the end of the queue acc = layers_pool.pop(0) layers_pool.append(acc) continue # take Layer instance of the previous layers input_layers = [self.structure.layers_index_reverse[layer] for layer in enter_layers] # layer without rank is broken and we ignore that input_layers = [layer for layer in input_layers if layer.config.get('rank', False)] enter_layers = [i for i in enter_layers if i not in layers_pool_removed] # if curent layer is the Input - initialise without any input connections if not input_layers and self.structure.layers_index_reverse[layer_index].layer_type == 'input': inited_layer = (None, None, self.structure.layers_index_reverse[layer_index].init_layer(None)) # detect hanging node - some of mutations could remove connection to the layer elif not input_layers: layers_pool_removed.append(layers_pool.pop(0)) continue # if there are multiple input connections elif len(input_layers) > 1: # this case does not require additional processing - all logic is inside Layer instance, # which handles multiple connections inited_layer = self.structure.layers_index_reverse[layer_index]([None for _ in range(len(input_layers))], input_layers) else: input_layers_inited = [layers_pool_inited[layer] for layer in enter_layers][0] inited_layer = self.structure.layers_index_reverse[layer_index](None, input_layers[0]) # add new initialised layer layers_pool_inited[layer_index] = inited_layer setattr(self, 'layer_{}'.format(layer_index), inited_layer[2]) # find outgoing connections and add them to the pool output_layers = [layer for layer in np.where(self.structure.matrix[layer_index] == 1)[0] if layer not in layers_pool and layer not in layers_pool_inited.keys()] layers_pool.extend(output_layers) # remove current layer from the pool layers_pool.pop(layers_pool.index(layer_index)) self.layers_pool_removed = layers_pool_removed return layers_pool_inited def forward(self, x): # pool of layers, which should be initialised and connected layers_pool = [0] buffer_x = {-1: x} last_value = None while layers_pool: # take first layer in a pool layer_index = layers_pool[0] # find all connections before this layer enter_layers = set(np.where(self.structure.matrix[:, layer_index] == 1)[0]) enter_layers = [i for i in enter_layers if i not in self.layers_pool_removed] # check if some of previous layers were not initialized # that means - we should initialise them first not_inited_layers = [i for i in enter_layers if i not in (buffer_x.keys())] not_inited_layers_selected = [layer for layer in not_inited_layers if layer not in self.layers_pool_removed] if not_inited_layers_selected: # remove layers, which are in pool already # this is possible due to complex connections with different orders not_inited_layers_selected = [layer for layer in not_inited_layers_selected if layer not in layers_pool] # add not initialised layers to the pool layers_pool.extend(not_inited_layers_selected) # current layer should be shift to the end of the queue layers_pool.append(layers_pool.pop(0)) continue # take Layer instance of the previous layers temp_x = [buffer_x[layer] for layer in enter_layers] # if curent layer is the Input - initialise without any input connections if not enter_layers and self.structure.layers_index_reverse[layer_index].layer_type == 'input': if self.layers_pool_inited[layer_index][0] is not None: raise "Input layer is not the first one. Incorrect graph structure" if self.layers_pool_inited[layer_index][1] is not None: reshaper = self.layers_pool_inited[layer_index][1] # .init_layer(None) temp_x = reshaper(buffer_x[-1]) else: temp_x = buffer_x[-1] result_x = self.process_layer_output(self.layers_pool_inited[layer_index][2](temp_x), self.structure.layers_index_reverse[layer_index].layer_type) buffer_x[layer_index] = result_x # detect hanging node - some of mutations could remove connection to the layer elif not enter_layers: continue # if there are multiple input connections elif len(enter_layers) > 1: if self.layers_pool_inited[layer_index][0] is not None: reshapers = self.layers_pool_inited[layer_index][0][0] axis = self.layers_pool_inited[layer_index][0][1] if reshapers is not None: reshapers = [i.init_layer(None) for i in reshapers] temp_x = [r(temp_x[i]) for i, r in enumerate(reshapers)] temp_x = torch.cat(temp_x, axis) if self.layers_pool_inited[layer_index][1] is not None: temp_x = self.layers_pool_inited[layer_index][1](temp_x) result_x = self.process_layer_output(self.layers_pool_inited[layer_index][2](temp_x), self.structure.layers_index_reverse[layer_index].layer_type) buffer_x[layer_index] = result_x else: temp_x = temp_x[0] if self.layers_pool_inited[layer_index][1] is not None: reshaper = self.layers_pool_inited[layer_index][1] # .init_layer(None) temp_x = reshaper(temp_x) result_x = self.process_layer_output(self.layers_pool_inited[layer_index][2](temp_x), self.structure.layers_index_reverse[layer_index].layer_type) buffer_x[layer_index] = result_x # find outgoing connections and add them to the pool output_layers = [layer for layer in np.where(self.structure.matrix[layer_index] == 1)[0] if layer not in layers_pool and layer not in buffer_x.keys()] last_value = result_x layers_pool.extend(output_layers) # remove current layer from the pool layers_pool.pop(layers_pool.index(layer_index)) return last_value def process_layer_output(self, x, layer_type): """ Some layer returns intermediate results, usually we dont need that """ if layer_type == 'lstm': return x[0] else: return x def recalculate_shapes(structure): # pool of layers, which should be initialised and connected layers_pool = [0] # pool of initialised layers layers_pool_inited = {} # pool of broken (invalid) layers) such as inconsistent number of dimensions layers_pool_removed = [] while layers_pool: # take first layer in a pool layer_index = layers_pool[0] # find all connections before this layer enter_layers = set(np.where(structure.matrix[:, layer_index] == 1)[0]) # check if some of previous layers were not initialized # that means - we should initialise them first not_inited_layers = [i for i in enter_layers if i not in (layers_pool_inited.keys())] not_inited_layers_selected = [layer for layer in not_inited_layers if layer not in layers_pool_removed] if not_inited_layers_selected: # remove layers, which are in pool already # this is possible due to complex connections with different orders not_inited_layers_selected = [layer for layer in not_inited_layers_selected if layer not in layers_pool] # add not initialised layers to the pool layers_pool.extend(not_inited_layers_selected) # current layer should be shift to the end of the queue acc = layers_pool.pop(0) layers_pool.append(acc) continue # take Layer instance of the previous layers input_layers = [structure.layers_index_reverse[layer] for layer in enter_layers] # layer without rank is broken and we ignore that input_layers = [layer for layer in input_layers if layer.config.get('rank', False)] enter_layers = [i for i in enter_layers if i not in layers_pool_removed] # if curent layer is the Input - initialise without any input connections if not input_layers and structure.layers_index_reverse[layer_index].layer_type == 'input': inited_layer = (None, None, None) # detect hanging node - some of mutations could remove connection to the layer elif not input_layers: layers_pool_removed.append(layers_pool.pop(0)) continue # if there are multiple input connections elif len(input_layers) > 1: # this case does not require additional processing - all logic is inside Layer instance, # which handles multiple connections inited_layer = structure.layers_index_reverse[layer_index]([None for _ in range(len(input_layers))], input_layers, init=False) else: input_layers_inited = [layers_pool_inited[layer] for layer in enter_layers][0] inited_layer = structure.layers_index_reverse[layer_index](None, input_layers[0], init=False) # add new initialised layer layers_pool_inited[layer_index] = inited_layer # find outgoing connections and add them to the pool output_layers = [layer for layer in np.where(structure.matrix[layer_index] == 1)[0] if layer not in layers_pool and layer not in layers_pool_inited.keys()] layers_pool.extend(output_layers) # remove current layer from the pool layers_pool.pop(layers_pool.index(layer_index))

46.639535

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null

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null

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6

677e440453d9f9ce5d3a0e9f426abf7cd35c3066

191

py

Python

platform/hwconf_data/efm32pg12b/modules/PIN/PIN_Snippets.py

lenloe1/v2.7

9ac9c4a7bb37987af382c80647f42d84db5f2e1d

[ "Zlib" ]

null

platform/hwconf_data/efm32pg12b/modules/PIN/PIN_Snippets.py

lenloe1/v2.7

9ac9c4a7bb37987af382c80647f42d84db5f2e1d

[ "Zlib" ]

1

2020-08-25T02:36:22.000Z

platform/hwconf_data/efm32pg12b/modules/PIN/PIN_Snippets.py

lenloe1/v2.7

9ac9c4a7bb37987af382c80647f42d84db5f2e1d

[ "Zlib" ]

1

2020-08-25T01:56:04.000Z

""" Generated from a template """ import efm32pg12b.PythonSnippet.RuntimeModel as RuntimeModel from efm32pg12b.modules.PIN.PIN_Defs import PORT_PINS def activate_runtime(): pass

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0.157068

191

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null

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1

0

null

0

1

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6

67c23c3fe298c711154bfea1ebfc6c851d164708

67

py

Python

example/tests/test.py

cristinasewell/pyenvbuilder

610674473c7d0f3b1733231f624ba9a9f7a9f908

[ "BSD-3-Clause-LBNL" ]

1

2021-01-08T19:44:59.000Z

example/tests/test.py

cristinasewell/pyenvbuilder

610674473c7d0f3b1733231f624ba9a9f7a9f908

[ "BSD-3-Clause-LBNL" ]

19

2020-04-02T18:37:02.000Z

2021-05-27T18:04:53.000Z

example/tests/test.py

cristinasewell/pyenvbuilder

610674473c7d0f3b1733231f624ba9a9f7a9f908

[ "BSD-3-Clause-LBNL" ]

3

2020-04-02T17:37:38.000Z

2020-12-13T00:02:40.000Z

import platform print 'Python version', platform.python_version()

16.75

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67

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6

67f78d2d25e83f23ad38ea3e2472e785cf44ff44

4,225

py

Python

src/test/scripting/test_assignment.py

vincent-lg/talismud

645bdae3d2e71cde51a25fe48c8f1bde15319631

[ "BSD-3-Clause" ]

4

2020-05-16T21:58:55.000Z

2020-08-29T11:17:31.000Z

src/test/scripting/test_assignment.py

vincent-lg/talismud

645bdae3d2e71cde51a25fe48c8f1bde15319631

[ "BSD-3-Clause" ]

1

2020-12-15T11:22:32.000Z

src/test/scripting/test_assignment.py

vincent-lg/talismud

645bdae3d2e71cde51a25fe48c8f1bde15319631

[ "BSD-3-Clause" ]

null

"""Assigning values in different tests.""" from test.scripting.abc import ScriptingTest class TestAssignment(ScriptingTest): """Test to assign values.""" def test_int(self): """Create a variable with a simple integer value.""" script = self.write_script("variable = 5") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, 5) def test_float(self): """Create a variable with a simple float value.""" script = self.write_script("variable = 2.5") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, 2.5) def test_var(self): """Create a copy variable.""" script = self.write_script(""" variable1 = 12 variable2 = variable1 """) variable2 = script.get_variable_or_attribute("variable2") self.assertEqual(variable2, 12) def test_str_apostrophes(self): """Create a variable with a simple string surrounded by apostrophes.""" script = self.write_script("variable = 'ok'") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, "ok") def test_str_double_quotes(self): """Create a variable with a string surrounded by double quotes.""" script = self.write_script("variable = \"thanks\"") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, "thanks") def test_str_mul_ded(self): """Create a variable with a multiline string using ""> <"".""" script = self.write_script(""" variable = ""> This is a string with at least three lines. <"" """) variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, "This is a string with at least three lines.") def test_str_mul_pre(self): """Create a variable with a multiline string using ""| |"".""" script = self.write_script(""" variable = ""| This is a string with at least three lines. |"" """) variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, "This is a string\nwith at least\nthree lines.") def test_negative_int(self): """Create a variable with a simple integer value.""" script = self.write_script("variable = -5") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, -5) def test_negative_float(self): """Create a variable with a simple float value.""" script = self.write_script("variable = -2.5") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, -2.5) def test_negative_var(self): """Create a copy variable, the second is negative.""" script = self.write_script(""" variable1 = 12 variable2 = -variable1 """) variable2 = script.get_variable_or_attribute("variable2") self.assertEqual(variable2, -12) def test_add(self): """Affect a variable to an addition.""" script = self.write_script("variable = 2 + 8") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, 10) def test_sub(self): """Affect a variable to a subtraction.""" script = self.write_script("variable = 2 - 8") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, -6) def test_mul(self): """Affect a variable to a multiplication.""" script = self.write_script("variable = 2 * 8") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, 16) def test_div(self): """Affect a variable to a division.""" script = self.write_script("variable = 2 / 8") variable = script.get_variable_or_attribute("variable") self.assertEqual(variable, 0.25)

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null

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null

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6

67fa82922158b5bd9625df6a883f524686dcfffe

131

py

Python

source/miniworldmaker/connectors/physics_connector.py

zormit/miniworldmaker

8003aece905b0cffec9850af3805b03372f3dc97

[ "MIT" ]

9

2019-04-16T13:45:02.000Z

2022-02-23T08:46:57.000Z

source/miniworldmaker/connectors/physics_connector.py

zormit/miniworldmaker

8003aece905b0cffec9850af3805b03372f3dc97

[ "MIT" ]

11

2019-08-08T11:31:50.000Z

2022-02-14T19:53:17.000Z

source/miniworldmaker/connectors/physics_connector.py

zormit/miniworldmaker

8003aece905b0cffec9850af3805b03372f3dc97

[ "MIT" ]

3

2019-04-18T22:43:53.000Z

2020-04-29T13:46:08.000Z

from miniworldmaker.connectors import pixel_connector class PhysicsBoardConnector(pixel_connector.PixelBoardConnector): pass

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db21c453bbb6f1fcdf0c55c7c430135a1c0e7113

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py

Python

isonet/models/__init__.py

bpicnbnk/ResNeXt.pytorch

53bae425c20a5b8ec69b3441ec12cfdc7d7231a6

[ "MIT" ]

null

isonet/models/__init__.py

bpicnbnk/ResNeXt.pytorch

53bae425c20a5b8ec69b3441ec12cfdc7d7231a6

[ "MIT" ]

null

isonet/models/__init__.py

bpicnbnk/ResNeXt.pytorch

53bae425c20a5b8ec69b3441ec12cfdc7d7231a6

[ "MIT" ]

null

from isonet.models.isonext import *

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py

Python

src/conversation_engine/__init__.py

tue-robotics/conversation_engine

7cc5a734e57fbea9afdf1618358e777677b8df06

[ "BSD-2-Clause" ]

1

2019-04-12T13:02:01.000Z

src/conversation_engine/__init__.py

tue-robotics/conversation_engine

7cc5a734e57fbea9afdf1618358e777677b8df06

[ "BSD-2-Clause" ]

17

2018-05-01T12:52:18.000Z

2019-08-12T13:29:47.000Z

src/conversation_engine/__init__.py

tue-robotics/conversation_engine

7cc5a734e57fbea9afdf1618358e777677b8df06

[ "BSD-2-Clause" ]

null

from .engine import ConversationEngine, ConversationEngineUsingTopic, ConversationState

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py

Python

src/app/api/crud/__init__.py

pyronear/pyro-api

9244b79b29bd5171ea1d02ed3c9cbb3eea75b60d

[ "Apache-2.0" ]

8

2020-11-13T14:21:34.000Z

2022-03-11T18:34:54.000Z

src/app/api/crud/__init__.py

pyronear/pyro-api

9244b79b29bd5171ea1d02ed3c9cbb3eea75b60d

[ "Apache-2.0" ]

169

2020-11-11T15:47:07.000Z

2022-02-17T23:10:34.000Z

src/app/api/crud/__init__.py

pyronear/pyro-api

9244b79b29bd5171ea1d02ed3c9cbb3eea75b60d

[ "Apache-2.0" ]

2

2021-02-15T10:41:48.000Z

2021-11-06T01:02:09.000Z

from .base import * from . import accesses from . import alerts from . import authorizations from . import groups from . import webhooks

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Python

feature_selection_plots.py

ashu-vyas-github/Flemish_Sign_Language_Openpose

6a7365b9d06a822ea6ece280031c193f582da4c3

[ "MIT" ]

null

feature_selection_plots.py

ashu-vyas-github/Flemish_Sign_Language_Openpose

6a7365b9d06a822ea6ece280031c193f582da4c3

[ "MIT" ]

null

feature_selection_plots.py

ashu-vyas-github/Flemish_Sign_Language_Openpose

6a7365b9d06a822ea6ece280031c193f582da4c3

[ "MIT" ]

null

# import numpy as np # import pandas as pd # from datetime import datetime # import matplotlib.pyplot as plt # from os.path import join as pjoin # import util.vis as V # import util.helpers as H # import data_analysis # import csv # import random # import gc # from glob import glob # import sklearn as sk # from sklearn import preprocessing # import feature_engineering.feature_preprocessing as feat_prepro # import feature_engineering.feature_extractors_4D_array as feat_extract # from feature_engineering.data_augmentation import SLRImbAugmentation # import feature_engineering.data_augmentation as data_augm # from sklearn.preprocessing import StandardScaler # from sklearn.decomposition import PCA # from sklearn.model_selection import train_test_split, StratifiedShuffleSplit, GroupKFold # from util.stratified_group_cv import StratifiedGroupKFold # from sklearn.feature_selection import SelectKBest # from sklearn.pipeline import Pipeline # from sklearn.model_selection import GridSearchCV # from util.results_plots_evaluation import map3_scorer # import util.results_plots_evaluation as results # from sklearn.metrics import accuracy_score # import util.helpers as kaggle_submission # from sklearn.linear_model import LogisticRegression # np.seterr(all='raise', divide='raise', over='raise', under='raise', invalid='raise') # rng = np.random.RandomState(42) # startTime= datetime.now() # n_splits = 5 # remove_keypoints = True # save_plot = False # unwanted_keypoints=[10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94] # face_body_hand = [True, True, True, False, False, False, False, False, False, False] # physics1 = [False, False, False, True, False, True, False, False, False, False] # physics2 = [False, False, False, True, False, True, True, False, False, False] # physics3 = [False, False, False, True, False, True, False, False, True, False] # physics4 = [False, False, False, True, False, True, False, False, False, True] # physics5 = [False, False, False, True, False, False, False, True, False, False] # physics6 = [False, False, False, True, False, False, True, True, False, False] # physics7 = [False, False, False, True, False, False, False, True, True, False] # physics8 = [False, False, False, True, False, False, False, True, False, True] # trajectory = [False, False, False, False, True, False, False, False, False, False] # all_feat = [True, True, True, True, True, True, True, True, True, True] # # PATHS # DATA_DIR = '../data' # POSE_DIR = '../data/pose' # TRAIN_DIR = POSE_DIR + "/train" # TEST_DIR = POSE_DIR + "/test" # # Read CSV file of labels # full_dataframe = pd.read_csv(pjoin(DATA_DIR, "labels.csv")) # full_dataframe['Data'] = full_dataframe['File'].apply(lambda title: np.load(pjoin(TRAIN_DIR, title + ".npy"))) # print("\n~~~~~##### Start #####~~~~~\n") # num_frames_list = [2, 4, 8, 15, 24, 48, 60] # gscv_best_score_list = [] # validtt_map3_trn = [] # validtt_map3_vld = [] # for interpolated_total_frames in num_frames_list: # print("\n\n\nRunning interpolated_total_frames:", interpolated_total_frames) # # 4D data as (n_samples, n_frames, n_keypoints, n_coords) # samples_centered_4D_array = feat_prepro.interpolate_allsamples(full_dataframe.Data, interpolated_total_frames=interpolated_total_frames, x_resolution=1.0, y_resolution=1.0) # print("Interplated data shape",samples_centered_4D_array.shape) # # Train and test split # X_traintt, X_validtt, y_traintt, y_validtt, group_traintt, group_validtt = train_test_split(samples_centered_4D_array, np.asarray(full_dataframe.Label), np.asarray(full_dataframe.Person), test_size=0.25, random_state=42, shuffle=True, stratify=None)#=np.asarray(full_dataframe.Label)) # face_flag=True # body_flag=True # hand_flag=True # physics_flag=True # trajectory_flag=True # linear_flag=True # std_flag=True # angular_flag=False # velocity_flag=False # acceleration_flag=False # X_train = feat_extract.main_feature_extractor(array_4D_data=X_traintt, face=face_flag, body=body_flag, hands=hand_flag, physics=physics_flag, trajectory=trajectory_flag, linear_flag=linear_flag, angular_flag=angular_flag, std_flag=std_flag, velocity_flag=velocity_flag, acceleration_flag=acceleration_flag, remove_keypoints=remove_keypoints, unwanted_keypoints=unwanted_keypoints) # X_valid = feat_extract.main_feature_extractor(array_4D_data=X_validtt, face=face_flag, body=body_flag, hands=hand_flag, physics=physics_flag, trajectory=trajectory_flag, linear_flag=linear_flag, angular_flag=angular_flag, std_flag=std_flag, velocity_flag=velocity_flag, acceleration_flag=acceleration_flag, remove_keypoints=remove_keypoints, unwanted_keypoints=unwanted_keypoints) # ### Standard Scaler # stdscl = StandardScaler() # ### Cross validator # # cvld = StratifiedShuffleSplit(n_splits=n_splits, test_size=0.2, train_size=None, random_state=42) # # cvld = StratifiedGroupKFold(n_splits=n_splits, shuffle=True, random_state=42) # cvld = GroupKFold(n_splits=n_splits) # ### Estimator # estimator = LogisticRegression(C=1.0, tol=1e-4, class_weight=None, solver='lbfgs', max_iter=5000, multi_class='ovr', penalty='l2', dual=False, fit_intercept=True, intercept_scaling=1, random_state=42, verbose=0, warm_start=False, n_jobs=-1, l1_ratio=None) # print("\nTraining the model", str(estimator)) # pipe = Pipeline([('scale', stdscl), ('clf', estimator)]) # ### Grid Search CV # param_grid = dict(clf__C=np.logspace(-3, 1, 5)) # print("Running GSCV.....") # grid = GridSearchCV(pipe, param_grid=param_grid, cv=cvld, n_jobs=-1, verbose=0, scoring=map3_scorer) # grid.fit(X_train, y_traintt, group_traintt) # print(grid.best_params_) # print(grid.best_score_) # gscv_best_score_list.append(grid.best_score_) # map3_trn, map3_vld = results.predict_print_results(grid, X_train, X_valid, y_traintt, y_validtt) # validtt_map3_trn.append(map3_trn) # validtt_map3_vld.append(map3_vld) # plt.rcParams.update({'font.size':6}) # bar_width = 0.25 # dpi_setting = 1200 # labels = num_frames_list # fname = 'num_frames_logreg_mean_raw_groupK' # plt.figure(num=None, figsize=None, dpi=dpi_setting, facecolor='w', edgecolor='w') # plt.title("Optimum #Frames LogReg GroupK") # plt.xlabel('Interpolated #Frames') # plt.ylabel('map@3 score') # plt.ylim(0.0,1.1) # plt.bar(x=np.arange(len(gscv_best_score_list))-bar_width, height=gscv_best_score_list, width=bar_width, label='Best GSCV Score', align='center') # plt.bar(x=np.arange(len(gscv_best_score_list)), height=validtt_map3_trn, width=bar_width, label='Training score', align='center') # plt.bar(x=np.arange(len(gscv_best_score_list))+bar_width, height=validtt_map3_vld, width=bar_width, label='Test Score', align='center') # plt.xticks(ticks=np.arange(len(gscv_best_score_list)), labels=labels, rotation=0) # plt.grid(b=True, which='major', axis='both', linestyle=':', linewidth=0.5, alpha=1) # plt.legend() # plt.savefig("{txt1}.png".format(txt1=fname), dpi=dpi_setting, facecolor='w', edgecolor='w', orientation='portrait', papertype=None, format='png', transparent=False, bbox_inches='tight', pad_inches=0.1, metadata=None) # plt.show() # print("\n~~~~~##### Done #####~~~~~\n") # timeElapsed = datetime.now() - startTime # print('Time elpased (hh:mm:ss.ms) {}'.format(timeElapsed)) ############################################################################### ############################################################################### ########### BELOW IS THE CODE FOR FEATURE SELECTION ############################################################################### ############################################################################### import numpy as np import pandas as pd from datetime import datetime import matplotlib.pyplot as plt from os.path import join as pjoin import util.vis as V import util.helpers as H import data_analysis import csv import random import gc from glob import glob import sklearn as sk from sklearn import preprocessing import feature_engineering.feature_preprocessing as feat_prepro import feature_engineering.feature_extractors_4D_array as feat_extract from feature_engineering.data_augmentation import SLRImbAugmentation import feature_engineering.data_augmentation as data_augm from sklearn.preprocessing import StandardScaler from sklearn.decomposition import PCA from sklearn.feature_selection import VarianceThreshold from sklearn.model_selection import train_test_split, StratifiedShuffleSplit, GroupKFold from util.stratified_group_cv import StratifiedGroupKFold from sklearn.feature_selection import SelectKBest from sklearn.pipeline import Pipeline from sklearn.model_selection import GridSearchCV from util.results_plots_evaluation import map3_scorer import util.results_plots_evaluation as results from sklearn.metrics import accuracy_score import util.helpers as kaggle_submission from sklearn.linear_model import LogisticRegression from sklearn.svm import SVC np.seterr(all='raise', divide='raise', over='raise', under='raise', invalid='raise') rng = np.random.RandomState(42) startTime= datetime.now() interpolated_total_frames = 15 n_splits = 7 face_flag = None body_flag = None hand_flag = None physics_flag = None trajectory_flag = None linear_flag = None std_flag = None angular_flag = None velocity_flag = None acceleration_flag = None remove_keypoints = False save_plot = False unwanted_keypoints=[10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94] face_body_hand = [True, True, True, False, False, False, False, False, False, False] physics1 = [False, False, False, True, False, True, False, False, False, False] physics2 = [False, False, False, True, False, True, True, False, False, False] physics3 = [False, False, False, True, False, True, False, False, True, False] physics4 = [False, False, False, True, False, True, False, False, False, True] physics5 = [False, False, False, True, False, False, False, True, False, False] physics6 = [False, False, False, True, False, False, True, True, False, False] physics7 = [False, False, False, True, False, False, False, True, True, False] physics8 = [False, False, False, True, False, False, False, True, False, True] trajectory = [False, False, False, False, True, False, False, False, False, False] all_feat = [True, True, True, True, True, True, True, True, True, True] features_selection_array = np.array([face_body_hand, physics1, physics2, physics3, physics4, physics5, physics6, physics7, physics8, trajectory, all_feat]) print(features_selection_array.shape) # PATHS DATA_DIR = '../data' POSE_DIR = '../data/pose' TRAIN_DIR = POSE_DIR + "/train" TEST_DIR = POSE_DIR + "/test" # Read CSV file of labels full_dataframe = pd.read_csv(pjoin(DATA_DIR, "labels.csv")) full_dataframe['Data'] = full_dataframe['File'].apply(lambda title: np.load(pjoin(TRAIN_DIR, title + ".npy"))) # Resampling and augmentation setp print("\n~~~~~##### Start #####~~~~~\n") # 4D data as (n_samples, n_frames, n_keypoints, n_coords) samples_centered_4D_array = feat_prepro.interpolate_allsamples(full_dataframe.Data, interpolated_total_frames=interpolated_total_frames, x_resolution=1.0, y_resolution=1.0) print("Interpolated data shape",samples_centered_4D_array.shape) # Train and test split # X_traintt, X_validtt, y_traintt, y_validtt, group_traintt, group_validtt = train_test_split(samples_centered_4D_array, np.asarray(full_dataframe.Label), np.asarray(full_dataframe.Person), test_size=0.25, random_state=42, shuffle=True, stratify=None)#=np.asarray(full_dataframe.Label)) # print("Training shape 4D split",X_traintt.shape) # print("Validation shape 4D split",X_validtt.shape) y_train = np.asarray(full_dataframe.Label) group_train = np.asarray(full_dataframe.Person) #### Augmentation # slr_obj = SLRImbAugmentation() # X_traintt, y_traintt, group_traintt = slr_obj.fit(X=X_traintt, y=y_traintt, groups=group_traintt, augmentation_factor=2) # X_traintt, y_traintt, group_traintt = data_augm.resample_data(X=X_traintt, y=y_traintt, groups=group_traintt) gscv_best_score_list = [] validtt_map3_trn = [] # validtt_map3_vld = [] for one_feature_set_idx in range(features_selection_array.shape[0]): print("\n\n\nRunning feature set:", one_feature_set_idx) face_flag, body_flag, hand_flag, physics_flag, trajectory_flag, linear_flag, std_flag, angular_flag, velocity_flag, acceleration_flag = features_selection_array[one_feature_set_idx, :].ravel() X_train = feat_extract.main_feature_extractor(array_4D_data=samples_centered_4D_array, face=face_flag, body=body_flag, hands=hand_flag, physics=physics_flag, trajectory=trajectory_flag, linear_flag=linear_flag, angular_flag=angular_flag, std_flag=std_flag, velocity_flag=velocity_flag, acceleration_flag=acceleration_flag, remove_keypoints=remove_keypoints, unwanted_keypoints=unwanted_keypoints) # X_valid = feat_extract.main_feature_extractor(array_4D_data=X_validtt, face=face_flag, body=body_flag, hands=hand_flag, physics=physics_flag, trajectory=trajectory_flag, linear_flag=linear_flag, angular_flag=angular_flag, std_flag=std_flag, velocity_flag=velocity_flag, acceleration_flag=acceleration_flag, remove_keypoints=remove_keypoints, unwanted_keypoints=unwanted_keypoints) ### Standard Scaler stdscl = StandardScaler() ### Feature selection selection = VarianceThreshold(threshold=0.0) ### Cross validator # cvld = StratifiedShuffleSplit(n_splits=n_splits, test_size=0.2, train_size=None, random_state=42) # cvld = StratifiedGroupKFold(n_splits=n_splits, shuffle=True, random_state=42) cvld = GroupKFold(n_splits=n_splits) ### Estimator # estimator = LogisticRegression(C=1.0, tol=1e-4, class_weight=None, solver='lbfgs', max_iter=5000, multi_class='ovr', penalty='l2', dual=False, fit_intercept=True, intercept_scaling=1, random_state=42, verbose=0, warm_start=False, n_jobs=-1, l1_ratio=None) estimator = SVC(C=1.0, kernel='rbf', degree=3, gamma='scale', coef0=0.0, shrinking=True, probability=True, tol=0.001, cache_size=200, class_weight=None, verbose=False, max_iter=-1, decision_function_shape='ovo', break_ties=False, random_state=42) print("\nTraining the model", str(estimator)) pipe = Pipeline([('feat_select', selection), ('scale', stdscl), ('clf', estimator)]) ### Grid Search CV param_grid = dict( clf__C=[0.01, 0.1, 0.5, 1.0, 4.0, 8.0, 10.0]) print("Running GSCV.....") grid = GridSearchCV(pipe, param_grid=param_grid, cv=cvld, n_jobs=-1, verbose=0, scoring=map3_scorer) # grid.fit(X_train, y_traintt, group_traintt) grid.fit(X_train, y_train, groups=group_train) print(grid.best_params_) print(grid.best_score_) gscv_best_score_list.append(grid.best_score_) map3_trn, map3_vld = results.predict_print_results(grid, X_train, X_train, y_train, y_train) validtt_map3_trn.append(map3_trn) # validtt_map3_vld.append(map3_vld) plt.rcParams.update({'font.size':6}) bar_width = 0.25 dpi_setting = 1200 labels = [int(x+1) for x in range(features_selection_array.shape[0])] fname = 'feat_sets_confidence_svcRBFovo_mean_raw_groupK' plt.figure(num=None, figsize=None, dpi=dpi_setting, facecolor='w', edgecolor='w') plt.title("Feature set comparison SVC-RBF GroupK") plt.xlabel('Features set') plt.ylabel('map@3 score') plt.ylim(0.0,1.1) plt.bar(x=np.arange(len(gscv_best_score_list))-bar_width/2.0, height=gscv_best_score_list, width=bar_width, label='Best GSCV Score', align='center') plt.bar(x=np.arange(len(gscv_best_score_list))+bar_width/2.0, height=validtt_map3_trn, width=bar_width, label='Training score', align='center') # plt.bar(x=np.arange(len(gscv_best_score_list))+bar_width, height=validtt_map3_vld, width=bar_width, label='Test Score', align='center') plt.xticks(ticks=np.arange(len(gscv_best_score_list)), labels=labels, rotation=0) plt.grid(b=True, which='major', axis='both', linestyle=':', linewidth=0.5, alpha=1) plt.legend() plt.savefig("{txt1}.png".format(txt1=fname), dpi=dpi_setting, facecolor='w', edgecolor='w', orientation='portrait', papertype=None, format='png', transparent=False, bbox_inches='tight', pad_inches=0.1, metadata=None) plt.show() print("\n~~~~~##### Done #####~~~~~\n") timeElapsed = datetime.now() - startTime print('Time elpased (hh:mm:ss.ms) {}'.format(timeElapsed)) # clf__C=[0.2, 0.4, 0.6, 0.8, 1.0, 2.0, 3.0, 5.0, 10.0] for Logreg OVR # clf__C=[0.01, 0.1, 0.5, 1.0, 4.0, 8.0, 10.0] for SVC RBF OVO #

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py

Python

mime/agent/__init__.py

rjgpinel/mime-release

26a850c4ba5b702b86d068995614163338fb01df

[ "MIT" ]

13

2020-06-24T10:52:28.000Z

2021-07-23T03:05:27.000Z

mime/agent/__init__.py

rjgpinel/mime-release

26a850c4ba5b702b86d068995614163338fb01df

[ "MIT" ]

1

2020-08-18T12:45:15.000Z

mime/agent/__init__.py

rjgpinel/mime-release

26a850c4ba5b702b86d068995614163338fb01df

[ "MIT" ]

3

2020-09-09T18:17:46.000Z

2021-09-06T09:43:45.000Z

from .script_agent import ScriptAgent from .vr_agent import VRAgent from .replay_agent import ReplayAgent

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Python

bfrs/migrations/0005_auto_20170919_1340.py

xzzy/bfrs

07eeaffff207bf4fca1c95a5ba25c9118c9eab7a

[ "Apache-2.0" ]

null

bfrs/migrations/0005_auto_20170919_1340.py

xzzy/bfrs

07eeaffff207bf4fca1c95a5ba25c9118c9eab7a

[ "Apache-2.0" ]

3

2020-02-12T00:03:12.000Z

2021-12-13T19:45:47.000Z

bfrs/migrations/0005_auto_20170919_1340.py

xzzy/bfrs

07eeaffff207bf4fca1c95a5ba25c9118c9eab7a

[ "Apache-2.0" ]

5

2018-02-16T02:05:40.000Z

2022-01-18T03:35:41.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.10.7 on 2017-09-19 05:40 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('bfrs', '0004_auto_20170911_1051'), ] operations = [ migrations.AlterField( model_name='bushfire', name='dispatch_aerial', field=models.NullBooleanField(verbose_name=b'Aerial support requested'), ), migrations.AlterField( model_name='bushfire', name='dispatch_aerial_date', field=models.DateTimeField(blank=True, null=True, verbose_name=b'Aerial support request date'), ), migrations.AlterField( model_name='bushfiresnapshot', name='dispatch_aerial', field=models.NullBooleanField(verbose_name=b'Aerial support requested'), ), migrations.AlterField( model_name='bushfiresnapshot', name='dispatch_aerial_date', field=models.DateTimeField(blank=True, null=True, verbose_name=b'Aerial support request date'), ), ]

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Python

tests/test_fleur_vis.py

soumyajyotih/masci-tools

e4d9ea2fbf6e16378d0cbfb8828a11bdb09c2139

[ "MIT" ]

null

tests/test_fleur_vis.py

soumyajyotih/masci-tools

e4d9ea2fbf6e16378d0cbfb8828a11bdb09c2139

[ "MIT" ]

null

tests/test_fleur_vis.py

soumyajyotih/masci-tools

e4d9ea2fbf6e16378d0cbfb8828a11bdb09c2139

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Test of the DOS/bandstructure visualizations """ import os import pytest from matplotlib.pyplot import gcf CURRENT_DIR = os.path.dirname(os.path.abspath(__file__)) HDFTEST_DIR = os.path.join(CURRENT_DIR, 'files/hdf5_reader') @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_defaults.png') def test_plot_bands_defaults_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands(data, attributes, show=False, markersize=30) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_weighted_non_spinpol.png') def test_plot_bands_weighted_non_spinpol_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands(data, attributes, show=False, weight='MT:1d') return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_defaults_spinpol.png') def test_plot_bands_spinpol_defaults_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands(data, attributes, show=False, markersize=30) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_weighted_spinpol.png') def test_plot_bands_weighted_spinpol_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands(data, attributes, show=False, weight='MT:1d') return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_spinpol_hide.png') def test_plot_bands_spinpol_no_spinpol_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands(data, attributes, show=False, markersize=30, spinpol=False) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_only_spin.png') def test_plot_bands_spinpol_only_spin_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands(data, attributes, show=False, markersize=30, only_spin='up') return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='dos_defaults.png') def test_plot_dos_defaults_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurDOS from masci_tools.vis.fleur import plot_fleur_dos TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_dos.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurDOS) gcf().clear() plot_fleur_dos(data, attributes, show=False) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='dos_param_by_label.png') def test_plot_dos_param_change_by_label_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurDOS from masci_tools.vis.fleur import plot_fleur_dos TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_dos.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurDOS) gcf().clear() plot_fleur_dos(data, attributes, show=False, color={'MT:1_up': 'red'}, linewidth={'Total_up': 6}) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='dos_param_by_label_with_general_params.png') def test_plot_dos_param_change_by_label_general_dicts_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurDOS from masci_tools.vis.fleur import plot_fleur_dos TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_dos.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurDOS) gcf().clear() plot_fleur_dos(data, attributes, show=False, color={'MT:1_up': 'red'}, linewidth={'Total_up': 6}, limits={'energy': (-5, 5)}, lines={'vertical': [-1, 0, 1]}) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='spinpol_dos_defaults.png') def test_plot_spinpol_dos_defaults_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurDOS from masci_tools.vis.fleur import plot_fleur_dos TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_dos.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurDOS) gcf().clear() plot_fleur_dos(data, attributes, show=False) return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='dos_selection.png') def test_plot_dos_selection_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurDOS from masci_tools.vis.fleur import plot_fleur_dos TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_dos.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurDOS) gcf().clear() plot_fleur_dos(data, attributes, show=False, show_total=False, show_interstitial=False, show_atoms=1, show_lresolved=2, plot_keys='MT:1p') return gcf() @pytest.mark.mpl_image_compare(baseline_dir='files/fleur_vis/', filename='bands_character.png') def test_plot_bands_characterize_mpl(): from masci_tools.io.parsers.hdf5 import HDF5Reader from masci_tools.io.parsers.hdf5.recipes import FleurBands from masci_tools.vis.fleur import plot_fleur_bands_characterize TEST_BANDDOS_FILE = os.path.join(HDFTEST_DIR, 'banddos_spinpol_bands.hdf') with HDF5Reader(TEST_BANDDOS_FILE) as h5reader: data, attributes = h5reader.read(recipe=FleurBands) gcf().clear() plot_fleur_bands_characterize(data, attributes, ['MT:1s', 'MT:1p', 'MT:1d', 'MT:1f'], ['darkblue', 'darkred', 'darkgreen', 'darkorange'], show=False, markersize=30, only_spin='up') return gcf()

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22642b807bee2172ec8fe3b8d3664d96c5eba11f

5,409

py

Python

tests/marketmaking/orderchain/test_preventpostonlycrossingbookelement.py

bednie/mango-explorer

4575395488e97a1f8cb52cc567e3307f11a28932

[ "MIT" ]

null

tests/marketmaking/orderchain/test_preventpostonlycrossingbookelement.py

bednie/mango-explorer

4575395488e97a1f8cb52cc567e3307f11a28932

[ "MIT" ]

null

tests/marketmaking/orderchain/test_preventpostonlycrossingbookelement.py

bednie/mango-explorer

4575395488e97a1f8cb52cc567e3307f11a28932

[ "MIT" ]

null

import argparse from ...context import mango from ...fakes import fake_context, fake_model_state, fake_loaded_market, fake_order from decimal import Decimal from mango.marketmaking.orderchain.preventpostonlycrossingbookelement import ( PreventPostOnlyCrossingBookElement, ) # The top bid is the highest price someone is willing to pay to BUY top_bid: mango.Order = fake_order( price=Decimal(90), side=mango.Side.BUY, order_type=mango.OrderType.POST_ONLY ) # The top ask is the lowest price someone is willing to pay to SELL top_ask: mango.Order = fake_order( price=Decimal(110), side=mango.Side.SELL, order_type=mango.OrderType.POST_ONLY ) orderbook: mango.OrderBook = mango.OrderBook( "TEST", mango.NullLotSizeConverter(), [top_bid], [top_ask] ) model_state = fake_model_state(market=fake_loaded_market(), orderbook=orderbook) def test_from_args() -> None: args: argparse.Namespace = argparse.Namespace() actual: PreventPostOnlyCrossingBookElement = ( PreventPostOnlyCrossingBookElement.from_command_line_parameters(args) ) assert actual is not None def test_not_crossing_results_in_no_change() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(100), order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() result = actual.process(context, model_state, [order]) assert result == [order] def test_bid_too_high_results_in_new_bid() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(120), side=mango.Side.BUY, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() result = actual.process(context, model_state, [order]) assert result[0].price == 109 def test_bid_too_low_results_in_no_change() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(80), side=mango.Side.BUY, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() result = actual.process(context, model_state, [order]) assert result == [order] def test_ask_too_low_results_in_new_ask() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(80), side=mango.Side.SELL, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() result = actual.process(context, model_state, [order]) assert result[0].price == 91 def test_ask_too_high_results_in_no_change() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(120), side=mango.Side.SELL, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() result = actual.process(context, model_state, [order]) assert result == [order] def test_bid_too_high_no_bid_results_in_new_bid() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(120), side=mango.Side.BUY, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() orderbook: mango.OrderBook = mango.OrderBook( "TEST", mango.NullLotSizeConverter(), [], [top_ask] ) model_state = fake_model_state(market=fake_loaded_market(), orderbook=orderbook) result = actual.process(context, model_state, [order]) assert result[0].price == 109 def test_ask_too_low_no_ask_results_in_new_ask() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(80), side=mango.Side.SELL, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() orderbook: mango.OrderBook = mango.OrderBook( "TEST", mango.NullLotSizeConverter(), [top_bid], [] ) model_state = fake_model_state(market=fake_loaded_market(), orderbook=orderbook) result = actual.process(context, model_state, [order]) assert result[0].price == 91 def test_ask_no_orderbook_results_in_no_change() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(120), side=mango.Side.SELL, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() orderbook: mango.OrderBook = mango.OrderBook( "TEST", mango.NullLotSizeConverter(), [], [] ) model_state = fake_model_state(market=fake_loaded_market(), orderbook=orderbook) result = actual.process(context, model_state, [order]) assert result == [order] def test_bid_no_orderbook_results_in_no_change() -> None: context = fake_context() order: mango.Order = fake_order( price=Decimal(80), side=mango.Side.BUY, order_type=mango.OrderType.POST_ONLY ) actual: PreventPostOnlyCrossingBookElement = PreventPostOnlyCrossingBookElement() orderbook: mango.OrderBook = mango.OrderBook( "TEST", mango.NullLotSizeConverter(), [], [] ) model_state = fake_model_state(market=fake_loaded_market(), orderbook=orderbook) result = actual.process(context, model_state, [order]) assert result == [order]

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py

Python

mpxapi/publish/__init__.py

colde/mpxapi

cda7d06c5c709ba7d652c59156ab7bb213bc2de1

[ "MIT" ]

3

2018-01-23T10:27:41.000Z

2019-03-29T21:12:25.000Z

mpxapi/publish/__init__.py

colde/mpxapi

cda7d06c5c709ba7d652c59156ab7bb213bc2de1

[ "MIT" ]

null

mpxapi/publish/__init__.py

colde/mpxapi

cda7d06c5c709ba7d652c59156ab7bb213bc2de1

[ "MIT" ]

3

2018-06-27T14:05:49.000Z

2019-09-16T11:28:37.000Z

from .publish_profile import PublishProfile

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py

Python

src/model/linearDistance.py

Bocampagni/Shipping-api

4cdf074467e4478885fe55d7c82a16e1a577b045

[ "MIT" ]

null

src/model/linearDistance.py

Bocampagni/Shipping-api

4cdf074467e4478885fe55d7c82a16e1a577b045

[ "MIT" ]

null

src/model/linearDistance.py

Bocampagni/Shipping-api

4cdf074467e4478885fe55d7c82a16e1a577b045

[ "MIT" ]

null

from pydantic import BaseModel class linearDistance(BaseModel): first_lon_coordinate: float first_lat_coordinate: float second_lon_coordinate: float second_lat_coordinate: float

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py

Python

jupyterprobe/__init__.py

vermashresth/jupyter-probe

cec35399dbe0d19d4264df02df305504bea0f695

[ "MIT" ]

8

2020-12-15T14:19:29.000Z

2021-09-23T03:39:21.000Z

build/lib/jupyterprobe/__init__.py

vermashresth/jupyter-probe

cec35399dbe0d19d4264df02df305504bea0f695

[ "MIT" ]

null

build/lib/jupyterprobe/__init__.py

vermashresth/jupyter-probe

cec35399dbe0d19d4264df02df305504bea0f695

[ "MIT" ]

null

from jupyterprobe.jupyterprobe import Probe

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py

Python

lcu_driver/__init__.py

TheodorStraube/lcu-driver

892e5695807a0ad27afa411b103a99fd64397f87

[ "MIT" ]

57

2019-06-07T09:35:00.000Z

2022-03-09T06:31:47.000Z

lcu_driver/__init__.py

TheodorStraube/lcu-driver

892e5695807a0ad27afa411b103a99fd64397f87

[ "MIT" ]

11

2020-10-31T02:42:59.000Z

2022-03-18T02:46:33.000Z

lcu_driver/__init__.py

TheodorStraube/lcu-driver

892e5695807a0ad27afa411b103a99fd64397f87

[ "MIT" ]

11

2021-01-07T19:09:09.000Z

2022-03-20T06:54:06.000Z

from .connector import Connector, MultipleClientConnector

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