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train | Vehicle.wait_for_alt | Wait for the vehicle to reach the specified altitude.
Wait for the vehicle to get within epsilon meters of the
given altitude. If rel is True (the default), use the
global_relative_frame. If rel is False, use the global_frame.
If timeout is nonzero, raise a TimeoutError if the specifie... | dronekit/__init__.py | def wait_for_alt(self, alt, epsilon=0.1, rel=True, timeout=None):
'''Wait for the vehicle to reach the specified altitude.
Wait for the vehicle to get within epsilon meters of the
given altitude. If rel is True (the default), use the
global_relative_frame. If rel is False, use the glob... | def wait_for_alt(self, alt, epsilon=0.1, rel=True, timeout=None):
'''Wait for the vehicle to reach the specified altitude.
Wait for the vehicle to get within epsilon meters of the
given altitude. If rel is True (the default), use the
global_relative_frame. If rel is False, use the glob... | [
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train | Vehicle.simple_takeoff | Take off and fly the vehicle to the specified altitude (in metres) and then wait for another command.
.. note::
This function should only be used on Copter vehicles.
The vehicle must be in GUIDED mode and armed before this is called.
There is no mechanism for notification when t... | dronekit/__init__.py | def simple_takeoff(self, alt=None):
"""
Take off and fly the vehicle to the specified altitude (in metres) and then wait for another command.
.. note::
This function should only be used on Copter vehicles.
The vehicle must be in GUIDED mode and armed before this is called... | def simple_takeoff(self, alt=None):
"""
Take off and fly the vehicle to the specified altitude (in metres) and then wait for another command.
.. note::
This function should only be used on Copter vehicles.
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train | Vehicle.simple_goto | Go to a specified global location (:py:class:`LocationGlobal` or :py:class:`LocationGlobalRelative`).
There is no mechanism for notification when the target location is reached, and if another command arrives
before that point that will be executed immediately.
You can optionally set the desir... | dronekit/__init__.py | def simple_goto(self, location, airspeed=None, groundspeed=None):
'''
Go to a specified global location (:py:class:`LocationGlobal` or :py:class:`LocationGlobalRelative`).
There is no mechanism for notification when the target location is reached, and if another command arrives
before t... | def simple_goto(self, location, airspeed=None, groundspeed=None):
'''
Go to a specified global location (:py:class:`LocationGlobal` or :py:class:`LocationGlobalRelative`).
There is no mechanism for notification when the target location is reached, and if another command arrives
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train | Vehicle.send_capabilties_request | An alias for send_capabilities_request.
The word "capabilities" was misspelled in previous versions of this code. This is simply
an alias to send_capabilities_request using the legacy name. | dronekit/__init__.py | def send_capabilties_request(self, vehicle, name, m):
'''An alias for send_capabilities_request.
The word "capabilities" was misspelled in previous versions of this code. This is simply
an alias to send_capabilities_request using the legacy name.
'''
return self.send_capabilitie... | def send_capabilties_request(self, vehicle, name, m):
'''An alias for send_capabilities_request.
The word "capabilities" was misspelled in previous versions of this code. This is simply
an alias to send_capabilities_request using the legacy name.
'''
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train | Vehicle.send_capabilities_request | Request an AUTOPILOT_VERSION packet | dronekit/__init__.py | def send_capabilities_request(self, vehicle, name, m):
'''Request an AUTOPILOT_VERSION packet'''
capability_msg = vehicle.message_factory.command_long_encode(0, 0, mavutil.mavlink.MAV_CMD_REQUEST_AUTOPILOT_CAPABILITIES, 0, 1, 0, 0, 0, 0, 0, 0)
vehicle.send_mavlink(capability_msg) | def send_capabilities_request(self, vehicle, name, m):
'''Request an AUTOPILOT_VERSION packet'''
capability_msg = vehicle.message_factory.command_long_encode(0, 0, mavutil.mavlink.MAV_CMD_REQUEST_AUTOPILOT_CAPABILITIES, 0, 1, 0, 0, 0, 0, 0, 0)
vehicle.send_mavlink(capability_msg) | [
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train | Vehicle.play_tune | Play a tune on the vehicle | dronekit/__init__.py | def play_tune(self, tune):
'''Play a tune on the vehicle'''
msg = self.message_factory.play_tune_encode(0, 0, tune)
self.send_mavlink(msg) | def play_tune(self, tune):
'''Play a tune on the vehicle'''
msg = self.message_factory.play_tune_encode(0, 0, tune)
self.send_mavlink(msg) | [
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train | Vehicle.wait_ready | Waits for specified attributes to be populated from the vehicle (values are initially ``None``).
This is typically called "behind the scenes" to ensure that :py:func:`connect` does not return until
attributes have populated (via the ``wait_ready`` parameter). You can also use it after connecting to
... | dronekit/__init__.py | def wait_ready(self, *types, **kwargs):
"""
Waits for specified attributes to be populated from the vehicle (values are initially ``None``).
This is typically called "behind the scenes" to ensure that :py:func:`connect` does not return until
attributes have populated (via the ``wait_rea... | def wait_ready(self, *types, **kwargs):
"""
Waits for specified attributes to be populated from the vehicle (values are initially ``None``).
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train | Vehicle.reboot | Requests an autopilot reboot by sending a ``MAV_CMD_PREFLIGHT_REBOOT_SHUTDOWN`` command. | dronekit/__init__.py | def reboot(self):
"""Requests an autopilot reboot by sending a ``MAV_CMD_PREFLIGHT_REBOOT_SHUTDOWN`` command."""
reboot_msg = self.message_factory.command_long_encode(
0, 0, # target_system, target_component
mavutil.mavlink.MAV_CMD_PREFLIGHT_REBOOT_SHUTDOWN, # command
... | def reboot(self):
"""Requests an autopilot reboot by sending a ``MAV_CMD_PREFLIGHT_REBOOT_SHUTDOWN`` command."""
reboot_msg = self.message_factory.command_long_encode(
0, 0, # target_system, target_component
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train | Vehicle.send_calibrate_magnetometer | Request magnetometer calibration. | dronekit/__init__.py | def send_calibrate_magnetometer(self):
"""Request magnetometer calibration."""
# ArduPilot requires the MAV_CMD_DO_START_MAG_CAL command, only present in the ardupilotmega.xml definition
if self._autopilot_type == mavutil.mavlink.MAV_AUTOPILOT_ARDUPILOTMEGA:
calibration_command = se... | def send_calibrate_magnetometer(self):
"""Request magnetometer calibration."""
# ArduPilot requires the MAV_CMD_DO_START_MAG_CAL command, only present in the ardupilotmega.xml definition
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train | Vehicle.send_calibrate_accelerometer | Request accelerometer calibration.
:param simple: if True, perform simple accelerometer calibration | dronekit/__init__.py | def send_calibrate_accelerometer(self, simple=False):
"""Request accelerometer calibration.
:param simple: if True, perform simple accelerometer calibration
"""
calibration_command = self.message_factory.command_long_encode(
self._handler.target_system, 0, # target_system,... | def send_calibrate_accelerometer(self, simple=False):
"""Request accelerometer calibration.
:param simple: if True, perform simple accelerometer calibration
"""
calibration_command = self.message_factory.command_long_encode(
self._handler.target_system, 0, # target_system,... | [
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train | Vehicle.send_calibrate_barometer | Request barometer calibration. | dronekit/__init__.py | def send_calibrate_barometer(self):
"""Request barometer calibration."""
calibration_command = self.message_factory.command_long_encode(
self._handler.target_system, 0, # target_system, target_component
mavutil.mavlink.MAV_CMD_PREFLIGHT_CALIBRATION, # command
0, #... | def send_calibrate_barometer(self):
"""Request barometer calibration."""
calibration_command = self.message_factory.command_long_encode(
self._handler.target_system, 0, # target_system, target_component
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train | Gimbal.rotate | Rotate the gimbal to a specific vector.
.. code-block:: python
#Point the gimbal straight down
vehicle.gimbal.rotate(-90, 0, 0)
:param pitch: Gimbal pitch in degrees relative to the vehicle (see diagram for :ref:`attitude <figure_attitude>`).
A value of 0 represent... | dronekit/__init__.py | def rotate(self, pitch, roll, yaw):
"""
Rotate the gimbal to a specific vector.
.. code-block:: python
#Point the gimbal straight down
vehicle.gimbal.rotate(-90, 0, 0)
:param pitch: Gimbal pitch in degrees relative to the vehicle (see diagram for :ref:`attitude... | def rotate(self, pitch, roll, yaw):
"""
Rotate the gimbal to a specific vector.
.. code-block:: python
#Point the gimbal straight down
vehicle.gimbal.rotate(-90, 0, 0)
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train | Gimbal.target_location | Point the gimbal at a specific region of interest (ROI).
.. code-block:: python
#Set the camera to track the current home location.
vehicle.gimbal.target_location(vehicle.home_location)
The target position must be defined in a :py:class:`LocationGlobalRelative` or :py:class:`L... | dronekit/__init__.py | def target_location(self, roi):
"""
Point the gimbal at a specific region of interest (ROI).
.. code-block:: python
#Set the camera to track the current home location.
vehicle.gimbal.target_location(vehicle.home_location)
The target position must be defined in ... | def target_location(self, roi):
"""
Point the gimbal at a specific region of interest (ROI).
.. code-block:: python
#Set the camera to track the current home location.
vehicle.gimbal.target_location(vehicle.home_location)
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train | Gimbal.release | Release control of the gimbal to the user (RC Control).
This should be called once you've finished controlling the mount with either :py:func:`rotate`
or :py:func:`target_location`. Control will automatically be released if you change vehicle mode. | dronekit/__init__.py | def release(self):
"""
Release control of the gimbal to the user (RC Control).
This should be called once you've finished controlling the mount with either :py:func:`rotate`
or :py:func:`target_location`. Control will automatically be released if you change vehicle mode.
"""
... | def release(self):
"""
Release control of the gimbal to the user (RC Control).
This should be called once you've finished controlling the mount with either :py:func:`rotate`
or :py:func:`target_location`. Control will automatically be released if you change vehicle mode.
"""
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train | Parameters.add_attribute_listener | Add a listener callback on a particular parameter.
The callback can be removed using :py:func:`remove_attribute_listener`.
.. note::
The :py:func:`on_attribute` decorator performs the same operation as this method, but with
a more elegant syntax. Use ``add_attribute_listener``... | dronekit/__init__.py | def add_attribute_listener(self, attr_name, *args, **kwargs):
"""
Add a listener callback on a particular parameter.
The callback can be removed using :py:func:`remove_attribute_listener`.
.. note::
The :py:func:`on_attribute` decorator performs the same operation as this ... | def add_attribute_listener(self, attr_name, *args, **kwargs):
"""
Add a listener callback on a particular parameter.
The callback can be removed using :py:func:`remove_attribute_listener`.
.. note::
The :py:func:`on_attribute` decorator performs the same operation as this ... | [
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train | Parameters.remove_attribute_listener | Remove a paremeter listener that was previously added using :py:func:`add_attribute_listener`.
For example to remove the ``thr_min_callback()`` callback function:
.. code:: python
vehicle.parameters.remove_attribute_listener('thr_min', thr_min_callback)
See :ref:`vehicle_state_ob... | dronekit/__init__.py | def remove_attribute_listener(self, attr_name, *args, **kwargs):
"""
Remove a paremeter listener that was previously added using :py:func:`add_attribute_listener`.
For example to remove the ``thr_min_callback()`` callback function:
.. code:: python
vehicle.parameters.remov... | def remove_attribute_listener(self, attr_name, *args, **kwargs):
"""
Remove a paremeter listener that was previously added using :py:func:`add_attribute_listener`.
For example to remove the ``thr_min_callback()`` callback function:
.. code:: python
vehicle.parameters.remov... | [
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train | Parameters.on_attribute | Decorator for parameter listeners.
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"""
Decorator for parameter listeners.
.. note::
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Decorator for parameter listeners.
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train | CommandSequence.download | Download all waypoints from the vehicle.
The download is asynchronous. Use :py:func:`wait_ready()` to block your thread until the download is complete. | dronekit/__init__.py | def download(self):
'''
Download all waypoints from the vehicle.
The download is asynchronous. Use :py:func:`wait_ready()` to block your thread until the download is complete.
'''
self.wait_ready()
self._vehicle._ready_attrs.remove('commands')
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'''
Download all waypoints from the vehicle.
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train | CommandSequence.clear | Clear the command list.
This command will be sent to the vehicle only after you call :py:func:`upload() <Vehicle.commands.upload>`. | dronekit/__init__.py | def clear(self):
'''
Clear the command list.
This command will be sent to the vehicle only after you call :py:func:`upload() <Vehicle.commands.upload>`.
'''
# Add home point again.
self.wait_ready()
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'''
Clear the command list.
This command will be sent to the vehicle only after you call :py:func:`upload() <Vehicle.commands.upload>`.
'''
# Add home point again.
self.wait_ready()
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train | CommandSequence.add | Add a new command (waypoint) at the end of the command list.
.. note::
Commands are sent to the vehicle only after you call ::py:func:`upload() <Vehicle.commands.upload>`.
:param Command cmd: The command to be added. | dronekit/__init__.py | def add(self, cmd):
'''
Add a new command (waypoint) at the end of the command list.
.. note::
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Add a new command (waypoint) at the end of the command list.
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train | CommandSequence.upload | Call ``upload()`` after :py:func:`adding <CommandSequence.add>` or :py:func:`clearing <CommandSequence.clear>` mission commands.
After the return from ``upload()`` any writes are guaranteed to have completed (or thrown an
exception) and future reads will see their effects.
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train | arm_and_takeoff_nogps | Arms vehicle and fly to aTargetAltitude without GPS data. | examples/set_attitude_target/set_attitude_target.py | def arm_and_takeoff_nogps(aTargetAltitude):
"""
Arms vehicle and fly to aTargetAltitude without GPS data.
"""
##### CONSTANTS #####
DEFAULT_TAKEOFF_THRUST = 0.7
SMOOTH_TAKEOFF_THRUST = 0.6
print("Basic pre-arm checks")
# Don't let the user try to arm until autopilot is ready
# If y... | def arm_and_takeoff_nogps(aTargetAltitude):
"""
Arms vehicle and fly to aTargetAltitude without GPS data.
"""
##### CONSTANTS #####
DEFAULT_TAKEOFF_THRUST = 0.7
SMOOTH_TAKEOFF_THRUST = 0.6
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train | send_attitude_target | use_yaw_rate: the yaw can be controlled using yaw_angle OR yaw_rate.
When one is used, the other is ignored by Ardupilot.
thrust: 0 <= thrust <= 1, as a fraction of maximum vertical thrust.
Note that as of Copter 3.5, thrust = 0.5 triggers a special case in
the code for mai... | examples/set_attitude_target/set_attitude_target.py | def send_attitude_target(roll_angle = 0.0, pitch_angle = 0.0,
yaw_angle = None, yaw_rate = 0.0, use_yaw_rate = False,
thrust = 0.5):
"""
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thrust = 0.5):
"""
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train | set_attitude | Note that from AC3.3 the message should be re-sent more often than every
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In AC3.2.1 and earlier the specified attitude persists until it is canceled.
The code below should work on either version.
Sending the message multiple times is the recommend... | examples/set_attitude_target/set_attitude_target.py | def set_attitude(roll_angle = 0.0, pitch_angle = 0.0,
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thrust = 0.5, duration = 0):
"""
Note that from AC3.3 the message should be re-sent more often than every
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"""
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train | to_quaternion | Convert degrees to quaternions | examples/set_attitude_target/set_attitude_target.py | def to_quaternion(roll = 0.0, pitch = 0.0, yaw = 0.0):
"""
Convert degrees to quaternions
"""
t0 = math.cos(math.radians(yaw * 0.5))
t1 = math.sin(math.radians(yaw * 0.5))
t2 = math.cos(math.radians(roll * 0.5))
t3 = math.sin(math.radians(roll * 0.5))
t4 = math.cos(math.radians(pitch * 0... | def to_quaternion(roll = 0.0, pitch = 0.0, yaw = 0.0):
"""
Convert degrees to quaternions
"""
t0 = math.cos(math.radians(yaw * 0.5))
t1 = math.sin(math.radians(yaw * 0.5))
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t3 = math.sin(math.radians(roll * 0.5))
t4 = math.cos(math.radians(pitch * 0... | [
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train | SumBasicSummarizer._compute_tf | Computes the normalized term frequency as explained in http://www.tfidf.com/ | sumy/summarizers/sum_basic.py | def _compute_tf(self, sentences):
"""
Computes the normalized term frequency as explained in http://www.tfidf.com/
"""
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train | f_score | Computation of F-Score measure. It is computed as
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Computation of F-Score measure. It is computed as
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- P(E) is precision metrics of extract E.
- R(E) is recall metrics of extract E.
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"""
Computation of F-Score measure. It is computed as
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train | _len_lcs | Returns the length of the Longest Common Subsequence between sequences x
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Source: http://www.algorithmist.com/index.php/Longest_Common_Subsequence
:param x: sequence of words
:param y: sequence of words
:returns integer: Length of LCS between x and y | sumy/evaluation/rouge.py | def _len_lcs(x, y):
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Source: http://www.algorithmist.com/index.php/Longest_Common_Subsequence
:param x: sequence of words
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train | _recon_lcs | Returns the Longest Subsequence between x and y.
Source: http://www.algorithmist.com/index.php/Longest_Common_Subsequence
:param x: sequence of words
:param y: sequence of words
:returns sequence: LCS of x and y | sumy/evaluation/rouge.py | def _recon_lcs(x, y):
"""
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Source: http://www.algorithmist.com/index.php/Longest_Common_Subsequence
:param x: sequence of words
:param y: sequence of words
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"""
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"""
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Source: http://www.algorithmist.com/index.php/Longest_Common_Subsequence
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:param y: sequence of words
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train | _f_lcs | Computes the LCS-based F-measure score
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rouge-working-note-v1.3.1.pdf
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rouge-working-note-v1.3.1.pdf
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train | rouge_l_sentence_level | Computes ROUGE-L (sentence level) of two text collections of sentences.
http://research.microsoft.com/en-us/um/people/cyl/download/papers/
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"""
Computes ROUGE-L (sentence level) of two text collections of sentences.
http://research.microsoft.com/en-us/um/people/cyl/download/papers/
rouge-working-note-v1.3.1.pdf
Calculated according to:
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Computes ROUGE-L (sentence level) of two text collections of sentences.
http://research.microsoft.com/en-us/um/people/cyl/download/papers/
rouge-working-note-v1.3.1.pdf
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train | _union_lcs | Returns LCS_u(r_i, C) which is the LCS score of the union longest common subsequence
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train | TfDocumentModel.magnitude | Lenght/norm/magnitude of vector representation of document.
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"""
Lenght/norm/magnitude of vector representation of document.
This is usually denoted by ||d||.
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train | TfDocumentModel.most_frequent_terms | Returns ``count`` of terms sorted by their frequency
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"""
Returns ``count`` of terms sorted by their frequency
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train | TfDocumentModel.normalized_term_frequency | Returns normalized frequency of term in document.
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http://nlp.stanford.edu/IR-book/html/htmledition/maximum-tf-normalization-1.html
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http://nlp.stanford.edu/IR-book/html/htmledition/maximum-tf-normalization-1.html
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train | EdmundsonCueMethod._count_words | Counts number of bonus/stigma words.
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train | cached_property | Decorator that converts a method into memoized property.
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"""
Decorator that converts a method into memoized property.
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"""
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Computes cosine similarity of two text documents. Each document
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train | LsaSummarizer._create_dictionary | Creates mapping key = word, value = row index | sumy/summarizers/lsa.py | def _create_dictionary(self, document):
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words = map(self.normalize_word, document.words)
unique_words = frozenset(self.stem_word(w) for w in words if w not in self._stop_words)
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Creates matrix of shape |unique words|×|sentences| where cells
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"""
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Creates matrix of shape |unique words|×|sentences| where cells
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train | KLSummarizer.compute_tf | Computes the normalized term frequency as explained in http://www.tfidf.com/
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train | KLSummarizer._kl_divergence | Note: Could import scipy.stats and use scipy.stats.entropy(doc_freq, summary_freq)
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train | LuhnSummarizer.__remove_trailing_zeros | Removes trailing zeroes from indexable collection of numbers | sumy/summarizers/luhn.py | def __remove_trailing_zeros(self, collection):
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index -= 1
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train | LexRankSummarizer._create_matrix | Creates matrix of shape |sentences|×|sentences|. | sumy/summarizers/lex_rank.py | def _create_matrix(self, sentences, threshold, tf_metrics, idf_metrics):
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train | LexRankSummarizer.cosine_similarity | We compute idf-modified-cosine(sentence1, sentence2) here.
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Sentences are represented as vector TF*IDF metrics.
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"""
We compute idf-modified-cosine(sentence1, sentence2) here.
It's cosine similarity of these two sentences (vectors) A, B computed as cos(x, y) = A . B / (|A| . |B|)
Sentences are represented as vector TF*IDF metrics.
... | def cosine_similarity(sentence1, sentence2, tf1, tf2, idf_metrics):
"""
We compute idf-modified-cosine(sentence1, sentence2) here.
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train | unicode_compatible | Decorator for unicode compatible classes. Method ``__unicode__``
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Decorator for unicode compatible classes. Method ``__unicode__``
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cls.__str__ = cls.__unicode__
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Decorator for unicode compatible classes. Method ``__unicode__``
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train | to_weld_type | Summary
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weld_type (TYPE): Description
dim (TYPE): Description
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TYPE: Description | python/grizzly/grizzly/lazy_op.py | def to_weld_type(weld_type, dim):
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train | weldarray._process_ufunc_inputs | Helper function for __array_ufunc__ that deals with the input/output checks and determines
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@input_args: args to __array_ufunc__
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train | weldarray._handle_call | TODO: add description | python/numpy/weldnumpy/weldarray.py | def _handle_call(self, ufunc, input_args, outputs):
'''
TODO: add description
'''
# if output is not None, choose the first one - since we don't support any ops with
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if outputs: output = outputs[0]
else: output = None
# check for suppo... | def _handle_call(self, ufunc, input_args, outputs):
'''
TODO: add description
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train | weldarray._reduce_op | TODO: support for multidimensional arrays. | python/numpy/weldnumpy/weldarray.py | def _reduce_op(self, op, result=None):
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TODO: support for multidimensional arrays.
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FIXME: the common indexing pattern for parent/child in _update_view might be too expensive
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train | DataFrameWeld._get_column_names | Summary
Returns:
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"""Summary
Returns:
TYPE: Description
"""
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train | SeriesWeld.sort_values | Sorts the values of this series | python/grizzly/grizzly/seriesweld.py | def sort_values(self, ascending=False):
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train | SeriesWeld.unique | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def unique(self):
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Returns:
TYPE: Description
"""
return SeriesWeld(
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train | SeriesWeld.lower | Summary
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TYPE: Description | python/grizzly/grizzly/seriesweld.py | def lower(self):
"""Summary
Returns:
TYPE: Description
"""
# TODO : Bug in nested map operating on strings
# TODO : Check that self.weld_type is a string type
vectype = self.weld_type
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train | SeriesWeld.contains | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def contains(self, string):
"""Summary
Returns:
TYPE: Description
"""
# Check that self.weld_type is a string type
vectype = self.weld_type
if isinstance(vectype, WeldVec):
elem_type = vectype.elemType
if isinstance(elem_type, WeldChar):
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# Check that self.weld_type is a string type
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... | [
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train | SeriesWeld.prod | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def prod(self):
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Returns:
TYPE: Description
"""
return LazyOpResult(
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] | 8ddd6db6b28878bef0892da44b1d2002b564389c |
train | SeriesWeld.sum | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def sum(self):
"""Summary
Returns:
TYPE: Description
"""
return LazyOpResult(
grizzly_impl.aggr(
self.expr,
"+",
0,
self.weld_type
),
self.weld_type,
0
) | def sum(self):
"""Summary
Returns:
TYPE: Description
"""
return LazyOpResult(
grizzly_impl.aggr(
self.expr,
"+",
0,
self.weld_type
),
self.weld_type,
0
) | [
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] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/seriesweld.py#L268-L283 | [
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train | SeriesWeld.count | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def count(self):
"""Summary
Returns:
TYPE: Description
"""
return LazyOpResult(
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train | SeriesWeld.mask | Summary
Args:
predicates (TYPE): Description
new_value (TYPE): Description
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def mask(self, predicates, new_value):
"""Summary
Args:
predicates (TYPE): Description
new_value (TYPE): Description
Returns:
TYPE: Description
"""
if isinstance(predicates, SeriesWeld):
predicates = predicates.expr
return... | def mask(self, predicates, new_value):
"""Summary
Args:
predicates (TYPE): Description
new_value (TYPE): Description
Returns:
TYPE: Description
"""
if isinstance(predicates, SeriesWeld):
predicates = predicates.expr
return... | [
"Summary"
] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/seriesweld.py#L316-L338 | [
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train | SeriesWeld.add | Summary
Args:
other (TYPE): Description
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def add(self, other):
"""Summary
Args:
other (TYPE): Description
Returns:
TYPE: Description
"""
if isinstance(other, SeriesWeld):
other = other.expr
return SeriesWeld(
grizzly_impl.element_wise_op(
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"""Summary
Args:
other (TYPE): Description
Returns:
TYPE: Description
"""
if isinstance(other, SeriesWeld):
other = other.expr
return SeriesWeld(
grizzly_impl.element_wise_op(
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] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/seriesweld.py#L354-L375 | [
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train | StringSeriesWeld.slice | Summary
Args:
start (TYPE): Description
size (TYPE): Description
Returns:
TYPE: Description | python/grizzly/grizzly/seriesweld.py | def slice(self, start, size):
"""Summary
Args:
start (TYPE): Description
size (TYPE): Description
Returns:
TYPE: Description
"""
return SeriesWeld(
grizzly_impl.slice(
self.expr,
start,
... | def slice(self, start, size):
"""Summary
Args:
start (TYPE): Description
size (TYPE): Description
Returns:
TYPE: Description
"""
return SeriesWeld(
grizzly_impl.slice(
self.expr,
start,
... | [
"Summary"
] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/seriesweld.py#L686-L706 | [
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train | WeldObject.update | Update this context. if value is another context,
the names from that context are added into this one.
Otherwise, a new name is assigned and returned.
TODO tys for inputs. | python/pyweld/weld/weldobject.py | def update(self, value, tys=None, override=True):
"""
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TODO tys for inputs.
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"""
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TODO tys for inputs.
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train | GroupByWeld.sum | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/groupbyweld.py | def sum(self):
"""Summary
Returns:
TYPE: Description
"""
return GroupedDataFrameWeld(
grizzly_impl.groupby_sum(
self.columns,
self.column_types,
self.grouping_columns,
self.grouping_column_types
... | def sum(self):
"""Summary
Returns:
TYPE: Description
"""
return GroupedDataFrameWeld(
grizzly_impl.groupby_sum(
self.columns,
self.column_types,
self.grouping_columns,
self.grouping_column_types
... | [
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] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/groupbyweld.py#L81-L98 | [
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train | GroupByWeld.sort_values | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/groupbyweld.py | def sort_values(self, by, ascending=True):
"""Summary
Returns:
TYPE: Description
"""
if len(self.column_types) == 1:
vec_type = [WeldVec(self.column_types[0])]
else:
vec_type = [WeldVec(WeldStruct(self.column_types))]
if len(self.colu... | def sort_values(self, by, ascending=True):
"""Summary
Returns:
TYPE: Description
"""
if len(self.column_types) == 1:
vec_type = [WeldVec(self.column_types[0])]
else:
vec_type = [WeldVec(WeldStruct(self.column_types))]
if len(self.colu... | [
"Summary"
] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/groupbyweld.py#L100-L129 | [
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train | GroupByWeld.size | Returns the sizes of the groups as series.
Returns:
TYPE: Description | python/grizzly/grizzly/groupbyweld.py | def size(self):
"""Returns the sizes of the groups as series.
Returns:
TYPE: Description
"""
if len(self.grouping_column_types) > 1:
index_type = WeldStruct([self.grouping_column_types])
# Figure out what to use for multi-key index name
# ... | def size(self):
"""Returns the sizes of the groups as series.
Returns:
TYPE: Description
"""
if len(self.grouping_column_types) > 1:
index_type = WeldStruct([self.grouping_column_types])
# Figure out what to use for multi-key index name
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train | GroupedDataFrameWeld.get_column | Summary
Args:
column_name (TYPE): Description
column_type (TYPE): Description
index (TYPE): Description
Returns:
TYPE: Description | python/grizzly/grizzly/groupbyweld.py | def get_column(self, column_name, column_type, index, verbose=True):
"""Summary
Args:
column_name (TYPE): Description
column_type (TYPE): Description
index (TYPE): Description
Returns:
TYPE: Description
"""
return LazyOpResult(
... | def get_column(self, column_name, column_type, index, verbose=True):
"""Summary
Args:
column_name (TYPE): Description
column_type (TYPE): Description
index (TYPE): Description
Returns:
TYPE: Description
"""
return LazyOpResult(
... | [
"Summary"
] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/groupbyweld.py#L236-L255 | [
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train | GroupedDataFrameWeld.reset_index | Flattens the grouped data structure.
#TODO: The parameters here are meaningless
Flattens the grouped data structure.
What is returned is a DataFrameWeld object. | python/grizzly/grizzly/groupbyweld.py | def reset_index(self, inplace=True, drop=True):
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#TODO: The parameters here are meaningless
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What is returned is a DataFrameWeld object.
"""
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#TODO: The parameters here are meaningless
Flattens the grouped data structure.
What is returned is a DataFrameWeld object.
"""
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train | GroupedDataFrameWeld.evaluate | Summary
Returns:
TYPE: Description | python/grizzly/grizzly/groupbyweld.py | def evaluate(self, verbose=True, passes=None):
"""Summary
Returns:
TYPE: Description
"""
i = 0
exprs = []
for column_name in self.column_names:
if len(self.column_names) > 1:
index = "1.$%d" % i
else:
in... | def evaluate(self, verbose=True, passes=None):
"""Summary
Returns:
TYPE: Description
"""
i = 0
exprs = []
for column_name in self.column_names:
if len(self.column_names) > 1:
index = "1.$%d" % i
else:
in... | [
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train | GroupByWeldSeries.std | Standard deviation
Note that is by default normalizd by n - 1
# TODO, what does pandas do for multiple grouping columns?
# Currently we are just going to use one grouping column | python/grizzly/grizzly/groupbyweld.py | def std(self):
"""Standard deviation
Note that is by default normalizd by n - 1
# TODO, what does pandas do for multiple grouping columns?
# Currently we are just going to use one grouping column
"""
std_expr = grizzly_impl.groupby_std(
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... | def std(self):
"""Standard deviation
Note that is by default normalizd by n - 1
# TODO, what does pandas do for multiple grouping columns?
# Currently we are just going to use one grouping column
"""
std_expr = grizzly_impl.groupby_std(
[self.column],
... | [
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train | WeldModule.run | WeldContext is currently hidden from the Python API. We create a new
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NOTE: This can leak the context if the result of the Weld run is an
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WeldContext is currently hidden from the Python API. We create a new
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NOTE: This can leak the context if the result of the Weld run is an
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weld_conte... | def run(self, conf, arg, err):
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train | aggr | Computes the aggregate of elements in the array.
Args:
array (WeldObject / Numpy.ndarray): Input array to aggregate
op (str): Op string used to aggregate the array (+ / *)
initial_value (int): Initial value for aggregation
ty (WeldType): Type of each element in the input array
... | python/grizzly/grizzly/numpy_weld_impl.py | def aggr(array, op, initial_value, ty):
"""
Computes the aggregate of elements in the array.
Args:
array (WeldObject / Numpy.ndarray): Input array to aggregate
op (str): Op string used to aggregate the array (+ / *)
initial_value (int): Initial value for aggregation
ty (Weld... | def aggr(array, op, initial_value, ty):
"""
Computes the aggregate of elements in the array.
Args:
array (WeldObject / Numpy.ndarray): Input array to aggregate
op (str): Op string used to aggregate the array (+ / *)
initial_value (int): Initial value for aggregation
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train | dot | Computes the dot product between a matrix and a vector.
Args:
matrix (WeldObject / Numpy.ndarray): 2-d input matrix
vector (WeldObject / Numpy.ndarray): 1-d input vector
ty (WeldType): Type of each element in the input matrix and vector
Returns:
A WeldObject representing this c... | python/grizzly/grizzly/numpy_weld_impl.py | def dot(matrix, vector, matrix_ty, vector_ty):
"""
Computes the dot product between a matrix and a vector.
Args:
matrix (WeldObject / Numpy.ndarray): 2-d input matrix
vector (WeldObject / Numpy.ndarray): 1-d input vector
ty (WeldType): Type of each element in the input matrix and ve... | def dot(matrix, vector, matrix_ty, vector_ty):
"""
Computes the dot product between a matrix and a vector.
Args:
matrix (WeldObject / Numpy.ndarray): 2-d input matrix
vector (WeldObject / Numpy.ndarray): 1-d input vector
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train | exp | Computes the per-element exponenet of the passed-in array.
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array (WeldObject / Numpy.ndarray): Input array
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array (WeldObject / Numpy.ndarray): Input array
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train | is_view_child | Checks the base address of the given arrays to figure out if child and par
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'''
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'''
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# par is the base array.
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# par is the base array.
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train | get_supported_binary_ops | Returns a dictionary of the Weld supported binary ops, with values being their Weld symbol. | python/numpy/weldnumpy/weldnumpy.py | def get_supported_binary_ops():
'''
Returns a dictionary of the Weld supported binary ops, with values being their Weld symbol.
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binary_ops = {}
binary_ops[np.add.__name__] = '+'
binary_ops[np.subtract.__name__] = '-'
binary_ops[np.multiply.__name__] = '*'
binary_ops[np.divide.__name_... | def get_supported_binary_ops():
'''
Returns a dictionary of the Weld supported binary ops, with values being their Weld symbol.
'''
binary_ops = {}
binary_ops[np.add.__name__] = '+'
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train | get_supported_unary_ops | Returns a dictionary of the Weld supported unary ops, with values being their Weld symbol. | python/numpy/weldnumpy/weldnumpy.py | def get_supported_unary_ops():
'''
Returns a dictionary of the Weld supported unary ops, with values being their Weld symbol.
'''
unary_ops = {}
unary_ops[np.exp.__name__] = 'exp'
unary_ops[np.log.__name__] = 'log'
unary_ops[np.sqrt.__name__] = 'sqrt'
return unary_ops | def get_supported_unary_ops():
'''
Returns a dictionary of the Weld supported unary ops, with values being their Weld symbol.
'''
unary_ops = {}
unary_ops[np.exp.__name__] = 'exp'
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train | WeldVec.ctype_class | Summary
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TYPE: Description | python/pyweld/weld/types.py | def ctype_class(self):
"""Summary
Returns:
TYPE: Description
"""
def vec_factory(elemType):
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Args:
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Returns:
TYPE: Description
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class Vec(St... | def ctype_class(self):
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TYPE: Description
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TYPE: Description
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train | WeldStruct.ctype_class | Summary
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Returns:
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train | get_field | Fetch a field from a struct expr | python/grizzly/grizzly/grizzly_impl.py | def get_field(expr, field):
""" Fetch a field from a struct expr
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weld_obj = WeldObject(encoder_, decoder_)
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if isinstance(expr, WeldObject):
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weld_obj.dependencies[struct_var] = expr
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predicates (WeldObject / Numpy.ndarray<bool>): Predicate set
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array (WeldObject / Numpy.ndarray): Input array
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array (WeldObject / Numpy.ndarray): Input array
predicates (WeldObject / Numpy.ndarray<bool>): Predicate set
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... | python/grizzly/grizzly/grizzly_impl.py | def filter(array, predicates, ty=None):
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Args:
array (WeldObject / Numpy.ndarray): Input array
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train | pivot_filter | Returns a new array, with each element in the original array satisfying the
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array (WeldObject / Numpy.ndarray): Input array
predicates (WeldObject / Numpy.ndarray<bool>): Predicate set
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Args:
array (WeldObject / Numpy.ndarray): Input array
predicates (WeldObject / Numpy.ndarray<bool>): Predicate set
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train | element_wise_op | Operation of series and other, element-wise (binary operator add)
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other (WeldObject / Numpy.ndarray): Second Input array
op (str): Op string used to compute element-wise operation (+ / *)
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Operation of series and other, element-wise (binary operator add)
Args:
array (WeldObject / Numpy.ndarray): Input array
other (WeldObject / Numpy.ndarray): Second Input array
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train | unzip_columns | Zip together multiple columns.
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columns (WeldObject / Numpy.ndarray): lust of columns
Returns:
A WeldObject representing this computation | python/grizzly/grizzly/grizzly_impl.py | def unzip_columns(expr, column_types):
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Zip together multiple columns.
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columns (WeldObject / Numpy.ndarray): lust of columns
Returns:
A WeldObject representing this computation
"""
weld_obj = WeldObject(encoder_, decoder_)
column_appenders = []
struct_fields = ... | def unzip_columns(expr, column_types):
"""
Zip together multiple columns.
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columns (WeldObject / Numpy.ndarray): lust of columns
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A WeldObject representing this computation
"""
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train | sort | Sorts the vector.
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Args:
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field (Int) | python/grizzly/grizzly/grizzly_impl.py | def sort(expr, field = None, keytype=None, ascending=True):
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Args:
expr (WeldObject)
field (Int)
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train | slice_vec | Slices the vector.
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expr (WeldObject)
start (Long)
stop (Long) | python/grizzly/grizzly/grizzly_impl.py | def slice_vec(expr, start, stop):
"""
Slices the vector.
Args:
expr (WeldObject)
start (Long)
stop (Long)
"""
weld_obj = WeldObject(encoder_, decoder_)
expr_var = weld_obj.update(expr)
if isinstance(expr, WeldObject):
expr_var = expr.obj_id
weld_obj.depend... | def slice_vec(expr, start, stop):
"""
Slices the vector.
Args:
expr (WeldObject)
start (Long)
stop (Long)
"""
weld_obj = WeldObject(encoder_, decoder_)
expr_var = weld_obj.update(expr)
if isinstance(expr, WeldObject):
expr_var = expr.obj_id
weld_obj.depend... | [
"Slices",
"the",
"vector",
"."
] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/grizzly_impl.py#L409-L431 | [
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... | 8ddd6db6b28878bef0892da44b1d2002b564389c |
train | zip_columns | Zip together multiple columns.
Args:
columns (WeldObject / Numpy.ndarray): lust of columns
Returns:
A WeldObject representing this computation | python/grizzly/grizzly/grizzly_impl.py | def zip_columns(columns):
"""
Zip together multiple columns.
Args:
columns (WeldObject / Numpy.ndarray): lust of columns
Returns:
A WeldObject representing this computation
"""
weld_obj = WeldObject(encoder_, decoder_)
column_vars = []
for column in columns:
col... | def zip_columns(columns):
"""
Zip together multiple columns.
Args:
columns (WeldObject / Numpy.ndarray): lust of columns
Returns:
A WeldObject representing this computation
"""
weld_obj = WeldObject(encoder_, decoder_)
column_vars = []
for column in columns:
col... | [
"Zip",
"together",
"multiple",
"columns",
"."
] | weld-project/weld | python | https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/grizzly/grizzly/grizzly_impl.py#L433-L467 | [
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"if"... | 8ddd6db6b28878bef0892da44b1d2002b564389c |
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