repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
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bulkan/robotframework-requests | src/RequestsLibrary/RequestsKeywords.py | RequestsKeywords.delete_request | def delete_request(
self,
alias,
uri,
data=None,
json=None,
params=None,
headers=None,
allow_redirects=None,
timeout=None):
""" Send a DELETE request on the session object found using the
given `a... | python | def delete_request(
self,
alias,
uri,
data=None,
json=None,
params=None,
headers=None,
allow_redirects=None,
timeout=None):
""" Send a DELETE request on the session object found using the
given `a... | [
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``alias`` that will be used to identify the Session object in the cache
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bulkan/robotframework-requests | src/RequestsLibrary/RequestsKeywords.py | RequestsKeywords.head_request | def head_request(
self,
alias,
uri,
headers=None,
allow_redirects=None,
timeout=None):
""" Send a HEAD request on the session object found using the
given `alias`
``alias`` that will be used to identify the Session object i... | python | def head_request(
self,
alias,
uri,
headers=None,
allow_redirects=None,
timeout=None):
""" Send a HEAD request on the session object found using the
given `alias`
``alias`` that will be used to identify the Session object i... | [
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bulkan/robotframework-requests | src/RequestsLibrary/RequestsKeywords.py | RequestsKeywords.options_request | def options_request(
self,
alias,
uri,
headers=None,
allow_redirects=None,
timeout=None):
""" Send an OPTIONS request on the session object found using the
given `alias`
``alias`` that will be used to identify the Session o... | python | def options_request(
self,
alias,
uri,
headers=None,
allow_redirects=None,
timeout=None):
""" Send an OPTIONS request on the session object found using the
given `alias`
``alias`` that will be used to identify the Session o... | [
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``alias`` that will be used to identify the Session object in the cache
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bulkan/robotframework-requests | src/RequestsLibrary/RequestsKeywords.py | RequestsKeywords._get_url | def _get_url(self, session, uri):
"""
Helper method to get the full url
"""
url = session.url
if uri:
slash = '' if uri.startswith('/') else '/'
url = "%s%s%s" % (session.url, slash, uri)
return url | python | def _get_url(self, session, uri):
"""
Helper method to get the full url
"""
url = session.url
if uri:
slash = '' if uri.startswith('/') else '/'
url = "%s%s%s" % (session.url, slash, uri)
return url | [
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bulkan/robotframework-requests | src/RequestsLibrary/RequestsKeywords.py | RequestsKeywords._json_pretty_print | def _json_pretty_print(self, content):
"""
Pretty print a JSON object
``content`` JSON object to pretty print
"""
temp = json.loads(content)
return json.dumps(
temp,
sort_keys=True,
indent=4,
separators=(
'... | python | def _json_pretty_print(self, content):
"""
Pretty print a JSON object
``content`` JSON object to pretty print
"""
temp = json.loads(content)
return json.dumps(
temp,
sort_keys=True,
indent=4,
separators=(
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coddingtonbear/python-myfitnesspal | myfitnesspal/client.py | Client.get_measurements | def get_measurements(
self, measurement='Weight', lower_bound=None, upper_bound=None
):
""" Returns measurements of a given name between two dates."""
if upper_bound is None:
upper_bound = datetime.date.today()
if lower_bound is None:
lower_bound = upper_bound... | python | def get_measurements(
self, measurement='Weight', lower_bound=None, upper_bound=None
):
""" Returns measurements of a given name between two dates."""
if upper_bound is None:
upper_bound = datetime.date.today()
if lower_bound is None:
lower_bound = upper_bound... | [
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coddingtonbear/python-myfitnesspal | myfitnesspal/client.py | Client.set_measurements | def set_measurements(
self, measurement='Weight', value=None
):
""" Sets measurement for today's date."""
if value is None:
raise ValueError(
"Cannot update blank value."
)
# get the URL for the main check in page
# this is left in bec... | python | def set_measurements(
self, measurement='Weight', value=None
):
""" Sets measurement for today's date."""
if value is None:
raise ValueError(
"Cannot update blank value."
)
# get the URL for the main check in page
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coddingtonbear/python-myfitnesspal | myfitnesspal/client.py | Client.get_measurement_id_options | def get_measurement_id_options(self):
""" Returns list of measurement choices."""
# get the URL for the main check in page
document = self._get_document_for_url(
self._get_url_for_measurements()
)
# gather the IDs for all measurement types
measurement_ids = s... | python | def get_measurement_id_options(self):
""" Returns list of measurement choices."""
# get the URL for the main check in page
document = self._get_document_for_url(
self._get_url_for_measurements()
)
# gather the IDs for all measurement types
measurement_ids = s... | [
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joerick/pyinstrument | pyinstrument/__main__.py | file_supports_color | def file_supports_color(file_obj):
"""
Returns True if the running system's terminal supports color.
Borrowed from Django
https://github.com/django/django/blob/master/django/core/management/color.py
"""
plat = sys.platform
supported_platform = plat != 'Pocket PC' and (plat != 'win32' or
... | python | def file_supports_color(file_obj):
"""
Returns True if the running system's terminal supports color.
Borrowed from Django
https://github.com/django/django/blob/master/django/core/management/color.py
"""
plat = sys.platform
supported_platform = plat != 'Pocket PC' and (plat != 'win32' or
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joerick/pyinstrument | pyinstrument/__main__.py | load_report | def load_report(identifier=None):
'''
Returns the session referred to by identifier
'''
path = os.path.join(
report_dir(),
identifier + '.pyireport'
)
return ProfilerSession.load(path) | python | def load_report(identifier=None):
'''
Returns the session referred to by identifier
'''
path = os.path.join(
report_dir(),
identifier + '.pyireport'
)
return ProfilerSession.load(path) | [
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joerick/pyinstrument | pyinstrument/__main__.py | save_report | def save_report(session):
'''
Saves the session to a temp file, and returns that path.
Also prunes the number of reports to 10 so there aren't loads building up.
'''
# prune this folder to contain the last 10 sessions
previous_reports = glob.glob(os.path.join(report_dir(), '*.pyireport'))
pr... | python | def save_report(session):
'''
Saves the session to a temp file, and returns that path.
Also prunes the number of reports to 10 so there aren't loads building up.
'''
# prune this folder to contain the last 10 sessions
previous_reports = glob.glob(os.path.join(report_dir(), '*.pyireport'))
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joerick/pyinstrument | pyinstrument/session.py | ProfilerSession.root_frame | def root_frame(self, trim_stem=True):
'''
Parses the internal frame records and returns a tree of Frame objects
'''
root_frame = None
frame_stack = []
for frame_tuple in self.frame_records:
identifier_stack = frame_tuple[0]
time = frame_tuple[1]... | python | def root_frame(self, trim_stem=True):
'''
Parses the internal frame records and returns a tree of Frame objects
'''
root_frame = None
frame_stack = []
for frame_tuple in self.frame_records:
identifier_stack = frame_tuple[0]
time = frame_tuple[1]... | [
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joerick/pyinstrument | pyinstrument/frame.py | BaseFrame.remove_from_parent | def remove_from_parent(self):
'''
Removes this frame from its parent, and nulls the parent link
'''
if self.parent:
self.parent._children.remove(self)
self.parent._invalidate_time_caches()
self.parent = None | python | def remove_from_parent(self):
'''
Removes this frame from its parent, and nulls the parent link
'''
if self.parent:
self.parent._children.remove(self)
self.parent._invalidate_time_caches()
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joerick/pyinstrument | pyinstrument/frame.py | Frame.add_child | def add_child(self, frame, after=None):
'''
Adds a child frame, updating the parent link.
Optionally, insert the frame in a specific position by passing the frame to insert
this one after.
'''
frame.remove_from_parent()
frame.parent = self
if after is None... | python | def add_child(self, frame, after=None):
'''
Adds a child frame, updating the parent link.
Optionally, insert the frame in a specific position by passing the frame to insert
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'''
frame.remove_from_parent()
frame.parent = self
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joerick/pyinstrument | pyinstrument/frame.py | Frame.add_children | def add_children(self, frames, after=None):
'''
Convenience method to add multiple frames at once.
'''
if after is not None:
# if there's an 'after' parameter, add the frames in reverse so the order is
# preserved.
for frame in reversed(frames):
... | python | def add_children(self, frames, after=None):
'''
Convenience method to add multiple frames at once.
'''
if after is not None:
# if there's an 'after' parameter, add the frames in reverse so the order is
# preserved.
for frame in reversed(frames):
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joerick/pyinstrument | pyinstrument/frame.py | Frame.file_path_short | def file_path_short(self):
""" Return the path resolved against the closest entry in sys.path """
if not hasattr(self, '_file_path_short'):
if self.file_path:
result = None
for path in sys.path:
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joerick/pyinstrument | pyinstrument/frame.py | FrameGroup.exit_frames | def exit_frames(self):
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... | python | def exit_frames(self):
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joerick/pyinstrument | pyinstrument/profiler.py | Profiler.first_interesting_frame | def first_interesting_frame(self):
"""
Traverse down the frame hierarchy until a frame is found with more than one child
"""
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frame = root_frame
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Traverse down the frame hierarchy until a frame is found with more than one child
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joerick/pyinstrument | pyinstrument/processors.py | aggregate_repeated_calls | def aggregate_repeated_calls(frame, options):
'''
Converts a timeline into a time-aggregate summary.
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Converts a timeline into a time-aggregate summary.
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joerick/pyinstrument | pyinstrument/processors.py | merge_consecutive_self_time | def merge_consecutive_self_time(frame, options):
'''
Combines consecutive 'self time' frames
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return None
previous_self_time_frame = None
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... | python | def merge_consecutive_self_time(frame, options):
'''
Combines consecutive 'self time' frames
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if frame is None:
return None
previous_self_time_frame = None
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joerick/pyinstrument | pyinstrument/processors.py | remove_unnecessary_self_time_nodes | def remove_unnecessary_self_time_nodes(frame, options):
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'''
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joerick/pyinstrument | pyinstrument/renderers/html.py | HTMLRenderer.open_in_browser | def open_in_browser(self, session, output_filename=None):
"""
Open the rendered HTML in a webbrowser.
If output_filename=None (the default), a tempfile is used.
The filename of the HTML file is returned.
"""
if output_filename is None:
output_file = tempfil... | python | def open_in_browser(self, session, output_filename=None):
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Open the rendered HTML in a webbrowser.
If output_filename=None (the default), a tempfile is used.
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joerick/pyinstrument | setup.py | BuildPyCommand.run | def run(self):
'''compile the JS, then run superclass implementation'''
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'''compile the JS, then run superclass implementation'''
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joerick/pyinstrument | pyinstrument/util.py | deprecated | def deprecated(func, *args, **kwargs):
''' Marks a function as deprecated. '''
warnings.warn(
'{} is deprecated and should no longer be used.'.format(func),
DeprecationWarning,
stacklevel=3
)
return func(*args, **kwargs) | python | def deprecated(func, *args, **kwargs):
''' Marks a function as deprecated. '''
warnings.warn(
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jrief/django-angular | djng/app_settings.py | AppSettings.THUMBNAIL_OPTIONS | def THUMBNAIL_OPTIONS(self):
"""
Set the size as a 2-tuple for thumbnailed images after uploading them.
"""
from django.core.exceptions import ImproperlyConfigured
size = self._setting('DJNG_THUMBNAIL_SIZE', (200, 200))
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"""
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jrief/django-angular | djng/forms/angular_base.py | NgWidgetMixin.get_context | def get_context(self, name, value, attrs):
"""
Some widgets require a modified rendering context, if they contain angular directives.
"""
context = super(NgWidgetMixin, self).get_context(name, value, attrs)
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"""
Some widgets require a modified rendering context, if they contain angular directives.
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context = super(NgWidgetMixin, self).get_context(name, value, attrs)
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jrief/django-angular | djng/forms/angular_base.py | NgBoundField.css_classes | def css_classes(self, extra_classes=None):
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"""
if hasattr(extra_classes, 'split'):
extra_classes = extra_classes.split()
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... | python | def css_classes(self, extra_classes=None):
"""
Returns a string of space-separated CSS classes for the wrapping element of this input field.
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jrief/django-angular | djng/forms/angular_base.py | NgFormBaseMixin.get_field_errors | def get_field_errors(self, field):
"""
Return server side errors. Shall be overridden by derived forms to add their
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"""
identifier = format_html('{0}[\'{1}\']', self.form_name, field.name)
errors = self.errors.get(field.html_name, [])
r... | python | def get_field_errors(self, field):
"""
Return server side errors. Shall be overridden by derived forms to add their
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jrief/django-angular | djng/forms/angular_base.py | NgFormBaseMixin.update_widget_attrs | def update_widget_attrs(self, bound_field, attrs):
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widget_classes = getattr(self, 'widget_css_classes', None)
if wid... | python | def update_widget_attrs(self, bound_field, attrs):
"""
Updated the widget attributes which shall be added to the widget when rendering this field.
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jrief/django-angular | djng/forms/angular_base.py | NgFormBaseMixin.rectify_multipart_form_data | def rectify_multipart_form_data(self, data):
"""
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then these data fields must be converted to suit the Django Form validation
"""
for name, field in self.base_fields.items():
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"""
If a widget was converted and the Form data was submitted through a multipart request,
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jrief/django-angular | djng/forms/angular_base.py | NgFormBaseMixin.rectify_ajax_form_data | def rectify_ajax_form_data(self, data):
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"""
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jrief/django-angular | djng/templatetags/djng_tags.py | djng_locale_script | def djng_locale_script(context, default_language='en'):
"""
Returns a script tag for including the proper locale script in any HTML page.
This tag determines the current language with its locale.
Usage:
<script src="{% static 'node_modules/angular-i18n/' %}{% djng_locale_script %}"></script>
... | python | def djng_locale_script(context, default_language='en'):
"""
Returns a script tag for including the proper locale script in any HTML page.
This tag determines the current language with its locale.
Usage:
<script src="{% static 'node_modules/angular-i18n/' %}{% djng_locale_script %}"></script>
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jrief/django-angular | djng/forms/fields.py | DefaultFieldMixin.update_widget_attrs | def update_widget_attrs(self, bound_field, attrs):
"""
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"""
bound_field.form.update_widget_attrs(bound_field, attrs)
widget_classes = self.widget.attrs.get('class', None)
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... | python | def update_widget_attrs(self, bound_field, attrs):
"""
Update the dictionary of attributes used while rendering the input widget
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jrief/django-angular | djng/forms/fields.py | MultipleChoiceField.implode_multi_values | def implode_multi_values(self, name, data):
"""
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then for this kind of widget, the posted data must to be converted into a format suitable
for Django's Form validation.
"""
mkeys = [k for... | python | def implode_multi_values(self, name, data):
"""
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jrief/django-angular | djng/forms/fields.py | MultipleChoiceField.convert_ajax_data | def convert_ajax_data(self, field_data):
"""
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"""
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jrief/django-angular | djng/middleware.py | AngularUrlMiddleware.process_request | def process_request(self, request):
"""
Reads url name, args, kwargs from GET parameters, reverses the url and resolves view function
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Since the view function is called directly, it isn't ran through middle... | python | def process_request(self, request):
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jrief/django-angular | djng/views/crud.py | NgCRUDView.ng_delete | def ng_delete(self, request, *args, **kwargs):
"""
Delete object and return it's data in JSON encoding
The response is build before the object is actually deleted
so that we can still retrieve a serialization in the response
even with a m2m relationship
"""
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Delete object and return it's data in JSON encoding
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jrief/django-angular | djng/forms/angular_model.py | NgModelFormMixin._post_clean | def _post_clean(self):
"""
Rewrite the error dictionary, so that its keys correspond to the model fields.
"""
super(NgModelFormMixin, self)._post_clean()
if self._errors and self.prefix:
self._errors = ErrorDict((self.add_prefix(name), value) for name, value in self._... | python | def _post_clean(self):
"""
Rewrite the error dictionary, so that its keys correspond to the model fields.
"""
super(NgModelFormMixin, self)._post_clean()
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WoLpH/python-progressbar | progressbar/bar.py | ProgressBar.percentage | def percentage(self):
'''Return current percentage, returns None if no max_value is given
>>> progress = ProgressBar()
>>> progress.max_value = 10
>>> progress.min_value = 0
>>> progress.value = 0
>>> progress.percentage
0.0
>>>
>>> progress.value... | python | def percentage(self):
'''Return current percentage, returns None if no max_value is given
>>> progress = ProgressBar()
>>> progress.max_value = 10
>>> progress.min_value = 0
>>> progress.value = 0
>>> progress.percentage
0.0
>>>
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WoLpH/python-progressbar | examples.py | example | def example(fn):
'''Wrap the examples so they generate readable output'''
@functools.wraps(fn)
def wrapped():
try:
sys.stdout.write('Running: %s\n' % fn.__name__)
fn()
sys.stdout.write('\n')
except KeyboardInterrupt:
sys.stdout.write('\nSkippi... | python | def example(fn):
'''Wrap the examples so they generate readable output'''
@functools.wraps(fn)
def wrapped():
try:
sys.stdout.write('Running: %s\n' % fn.__name__)
fn()
sys.stdout.write('\n')
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rigetti/quantumflow | quantumflow/datasets/__init__.py | load_stdgraphs | def load_stdgraphs(size: int) -> List[nx.Graph]:
"""Load standard graph validation sets
For each size (from 6 to 32 graph nodes) the dataset consists of
100 graphs drawn from the Erdős-Rényi ensemble with edge
probability 50%.
"""
from pkg_resources import resource_stream
if size < 6 or si... | python | def load_stdgraphs(size: int) -> List[nx.Graph]:
"""Load standard graph validation sets
For each size (from 6 to 32 graph nodes) the dataset consists of
100 graphs drawn from the Erdős-Rényi ensemble with edge
probability 50%.
"""
from pkg_resources import resource_stream
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rigetti/quantumflow | quantumflow/datasets/__init__.py | load_mnist | def load_mnist(size: int = None,
border: int = _MNIST_BORDER,
blank_corners: bool = False,
nums: List[int] = None) \
-> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
"""Download and rescale the MNIST database of handwritten digits
MNIST is a dataset... | python | def load_mnist(size: int = None,
border: int = _MNIST_BORDER,
blank_corners: bool = False,
nums: List[int] = None) \
-> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
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rigetti/quantumflow | quantumflow/backend/tensorflow2bk.py | astensor | def astensor(array: TensorLike) -> BKTensor:
"""Covert numpy array to tensorflow tensor"""
tensor = tf.convert_to_tensor(value=array, dtype=CTYPE)
return tensor | python | def astensor(array: TensorLike) -> BKTensor:
"""Covert numpy array to tensorflow tensor"""
tensor = tf.convert_to_tensor(value=array, dtype=CTYPE)
return tensor | [
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rigetti/quantumflow | quantumflow/backend/tensorflow2bk.py | inner | def inner(tensor0: BKTensor, tensor1: BKTensor) -> BKTensor:
"""Return the inner product between two states"""
# Note: Relying on fact that vdot flattens arrays
N = rank(tensor0)
axes = list(range(N))
return tf.tensordot(tf.math.conj(tensor0), tensor1, axes=(axes, axes)) | python | def inner(tensor0: BKTensor, tensor1: BKTensor) -> BKTensor:
"""Return the inner product between two states"""
# Note: Relying on fact that vdot flattens arrays
N = rank(tensor0)
axes = list(range(N))
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rigetti/quantumflow | quantumflow/qaoa.py | graph_cuts | def graph_cuts(graph: nx.Graph) -> np.ndarray:
"""For the given graph, return the cut value for all binary assignments
of the graph.
"""
N = len(graph)
diag_hamiltonian = np.zeros(shape=([2]*N), dtype=np.double)
for q0, q1 in graph.edges():
for index, _ in np.ndenumerate(diag_hamiltonia... | python | def graph_cuts(graph: nx.Graph) -> np.ndarray:
"""For the given graph, return the cut value for all binary assignments
of the graph.
"""
N = len(graph)
diag_hamiltonian = np.zeros(shape=([2]*N), dtype=np.double)
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rigetti/quantumflow | quantumflow/dagcircuit.py | DAGCircuit.depth | def depth(self, local: bool = True) -> int:
"""Return the circuit depth.
Args:
local: If True include local one-qubit gates in depth
calculation. Else return the multi-qubit gate depth.
"""
G = self.graph
if not local:
def remove_local(da... | python | def depth(self, local: bool = True) -> int:
"""Return the circuit depth.
Args:
local: If True include local one-qubit gates in depth
calculation. Else return the multi-qubit gate depth.
"""
G = self.graph
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rigetti/quantumflow | quantumflow/dagcircuit.py | DAGCircuit.components | def components(self) -> List['DAGCircuit']:
"""Split DAGCircuit into independent components"""
comps = nx.weakly_connected_component_subgraphs(self.graph)
return [DAGCircuit(comp) for comp in comps] | python | def components(self) -> List['DAGCircuit']:
"""Split DAGCircuit into independent components"""
comps = nx.weakly_connected_component_subgraphs(self.graph)
return [DAGCircuit(comp) for comp in comps] | [
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rigetti/quantumflow | quantumflow/states.py | zero_state | def zero_state(qubits: Union[int, Qubits]) -> State:
"""Return the all-zero state on N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.zeros(shape=[2] * N)
ket[(0,) * N] = 1
return State(ket, qubits) | python | def zero_state(qubits: Union[int, Qubits]) -> State:
"""Return the all-zero state on N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.zeros(shape=[2] * N)
ket[(0,) * N] = 1
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rigetti/quantumflow | quantumflow/states.py | w_state | def w_state(qubits: Union[int, Qubits]) -> State:
"""Return a W state on N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.zeros(shape=[2] * N)
for n in range(N):
idx = np.zeros(shape=N, dtype=int)
idx[n] += 1
ket[tuple(idx)] = 1 / sqrt(N)
return State(ket, qubits) | python | def w_state(qubits: Union[int, Qubits]) -> State:
"""Return a W state on N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.zeros(shape=[2] * N)
for n in range(N):
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idx[n] += 1
ket[tuple(idx)] = 1 / sqrt(N)
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rigetti/quantumflow | quantumflow/states.py | ghz_state | def ghz_state(qubits: Union[int, Qubits]) -> State:
"""Return a GHZ state on N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.zeros(shape=[2] * N)
ket[(0, ) * N] = 1 / sqrt(2)
ket[(1, ) * N] = 1 / sqrt(2)
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"""Return a GHZ state on N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.zeros(shape=[2] * N)
ket[(0, ) * N] = 1 / sqrt(2)
ket[(1, ) * N] = 1 / sqrt(2)
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rigetti/quantumflow | quantumflow/states.py | random_state | def random_state(qubits: Union[int, Qubits]) -> State:
"""Return a random state from the space of N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.random.normal(size=([2] * N)) \
+ 1j * np.random.normal(size=([2] * N))
return State(ket, qubits).normalize() | python | def random_state(qubits: Union[int, Qubits]) -> State:
"""Return a random state from the space of N qubits"""
N, qubits = qubits_count_tuple(qubits)
ket = np.random.normal(size=([2] * N)) \
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return State(ket, qubits).normalize() | [
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rigetti/quantumflow | quantumflow/states.py | join_states | def join_states(*states: State) -> State:
"""Join two state vectors into a larger qubit state"""
vectors = [ket.vec for ket in states]
vec = reduce(outer_product, vectors)
return State(vec.tensor, vec.qubits) | python | def join_states(*states: State) -> State:
"""Join two state vectors into a larger qubit state"""
vectors = [ket.vec for ket in states]
vec = reduce(outer_product, vectors)
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rigetti/quantumflow | quantumflow/states.py | print_state | def print_state(state: State, file: TextIO = None) -> None:
"""Print a state vector"""
state = state.vec.asarray()
for index, amplitude in np.ndenumerate(state):
ket = "".join([str(n) for n in index])
print(ket, ":", amplitude, file=file) | python | def print_state(state: State, file: TextIO = None) -> None:
"""Print a state vector"""
state = state.vec.asarray()
for index, amplitude in np.ndenumerate(state):
ket = "".join([str(n) for n in index])
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rigetti/quantumflow | quantumflow/states.py | print_probabilities | def print_probabilities(state: State, ndigits: int = 4,
file: TextIO = None) -> None:
"""
Pretty print state probabilities.
Args:
state:
ndigits: Number of digits of accuracy
file: Output stream (Defaults to stdout)
"""
prob = bk.evaluate(state.probab... | python | def print_probabilities(state: State, ndigits: int = 4,
file: TextIO = None) -> None:
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Pretty print state probabilities.
Args:
state:
ndigits: Number of digits of accuracy
file: Output stream (Defaults to stdout)
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rigetti/quantumflow | quantumflow/states.py | mixed_density | def mixed_density(qubits: Union[int, Qubits]) -> Density:
"""Returns the completely mixed density matrix"""
N, qubits = qubits_count_tuple(qubits)
matrix = np.eye(2**N) / 2**N
return Density(matrix, qubits) | python | def mixed_density(qubits: Union[int, Qubits]) -> Density:
"""Returns the completely mixed density matrix"""
N, qubits = qubits_count_tuple(qubits)
matrix = np.eye(2**N) / 2**N
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rigetti/quantumflow | quantumflow/states.py | join_densities | def join_densities(*densities: Density) -> Density:
"""Join two mixed states into a larger qubit state"""
vectors = [rho.vec for rho in densities]
vec = reduce(outer_product, vectors)
memory = dict(ChainMap(*[rho.memory for rho in densities])) # TESTME
return Density(vec.tensor, vec.qubits, memory... | python | def join_densities(*densities: Density) -> Density:
"""Join two mixed states into a larger qubit state"""
vectors = [rho.vec for rho in densities]
vec = reduce(outer_product, vectors)
memory = dict(ChainMap(*[rho.memory for rho in densities])) # TESTME
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rigetti/quantumflow | quantumflow/states.py | State.normalize | def normalize(self) -> 'State':
"""Normalize the state"""
tensor = self.tensor / bk.ccast(bk.sqrt(self.norm()))
return State(tensor, self.qubits, self._memory) | python | def normalize(self) -> 'State':
"""Normalize the state"""
tensor = self.tensor / bk.ccast(bk.sqrt(self.norm()))
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rigetti/quantumflow | quantumflow/states.py | State.sample | def sample(self, trials: int) -> np.ndarray:
"""Measure the state in the computational basis the the given number
of trials, and return the counts of each output configuration.
"""
# TODO: Can we do this within backend?
probs = np.real(bk.evaluate(self.probabilities()))
r... | python | def sample(self, trials: int) -> np.ndarray:
"""Measure the state in the computational basis the the given number
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"""
# TODO: Can we do this within backend?
probs = np.real(bk.evaluate(self.probabilities()))
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rigetti/quantumflow | quantumflow/states.py | State.expectation | def expectation(self, diag_hermitian: bk.TensorLike,
trials: int = None) -> bk.BKTensor:
"""Return the expectation of a measurement. Since we can only measure
our computer in the computational basis, we only require the diagonal
of the Hermitian in that basis.
If the... | python | def expectation(self, diag_hermitian: bk.TensorLike,
trials: int = None) -> bk.BKTensor:
"""Return the expectation of a measurement. Since we can only measure
our computer in the computational basis, we only require the diagonal
of the Hermitian in that basis.
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rigetti/quantumflow | quantumflow/states.py | State.measure | def measure(self) -> np.ndarray:
"""Measure the state in the computational basis.
Returns:
A [2]*bits array of qubit states, either 0 or 1
"""
# TODO: Can we do this within backend?
probs = np.real(bk.evaluate(self.probabilities()))
indices = np.asarray(list(... | python | def measure(self) -> np.ndarray:
"""Measure the state in the computational basis.
Returns:
A [2]*bits array of qubit states, either 0 or 1
"""
# TODO: Can we do this within backend?
probs = np.real(bk.evaluate(self.probabilities()))
indices = np.asarray(list(... | [
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rigetti/quantumflow | quantumflow/states.py | State.asdensity | def asdensity(self) -> 'Density':
"""Convert a pure state to a density matrix"""
matrix = bk.outer(self.tensor, bk.conj(self.tensor))
return Density(matrix, self.qubits, self._memory) | python | def asdensity(self) -> 'Density':
"""Convert a pure state to a density matrix"""
matrix = bk.outer(self.tensor, bk.conj(self.tensor))
return Density(matrix, self.qubits, self._memory) | [
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rigetti/quantumflow | tools/benchmark.py | benchmark | def benchmark(N, gates):
"""Create and run a circuit with N qubits and given number of gates"""
qubits = list(range(0, N))
ket = qf.zero_state(N)
for n in range(0, N):
ket = qf.H(n).run(ket)
for _ in range(0, (gates-N)//3):
qubit0, qubit1 = random.sample(qubits, 2)
ket = qf... | python | def benchmark(N, gates):
"""Create and run a circuit with N qubits and given number of gates"""
qubits = list(range(0, N))
ket = qf.zero_state(N)
for n in range(0, N):
ket = qf.H(n).run(ket)
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rigetti/quantumflow | examples/weyl.py | sandwich_decompositions | def sandwich_decompositions(coords0, coords1, samples=SAMPLES):
"""Create composite gates, decompose, and return a list
of canonical coordinates"""
decomps = []
for _ in range(samples):
circ = qf.Circuit()
circ += qf.CANONICAL(*coords0, 0, 1)
circ += qf.random_gate([0])
c... | python | def sandwich_decompositions(coords0, coords1, samples=SAMPLES):
"""Create composite gates, decompose, and return a list
of canonical coordinates"""
decomps = []
for _ in range(samples):
circ = qf.Circuit()
circ += qf.CANONICAL(*coords0, 0, 1)
circ += qf.random_gate([0])
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rigetti/quantumflow | quantumflow/paulialgebra.py | sX | def sX(qubit: Qubit, coefficient: complex = 1.0) -> Pauli:
"""Return the Pauli sigma_X operator acting on the given qubit"""
return Pauli.sigma(qubit, 'X', coefficient) | python | def sX(qubit: Qubit, coefficient: complex = 1.0) -> Pauli:
"""Return the Pauli sigma_X operator acting on the given qubit"""
return Pauli.sigma(qubit, 'X', coefficient) | [
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rigetti/quantumflow | quantumflow/paulialgebra.py | sY | def sY(qubit: Qubit, coefficient: complex = 1.0) -> Pauli:
"""Return the Pauli sigma_Y operator acting on the given qubit"""
return Pauli.sigma(qubit, 'Y', coefficient) | python | def sY(qubit: Qubit, coefficient: complex = 1.0) -> Pauli:
"""Return the Pauli sigma_Y operator acting on the given qubit"""
return Pauli.sigma(qubit, 'Y', coefficient) | [
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rigetti/quantumflow | quantumflow/paulialgebra.py | sZ | def sZ(qubit: Qubit, coefficient: complex = 1.0) -> Pauli:
"""Return the Pauli sigma_Z operator acting on the given qubit"""
return Pauli.sigma(qubit, 'Z', coefficient) | python | def sZ(qubit: Qubit, coefficient: complex = 1.0) -> Pauli:
"""Return the Pauli sigma_Z operator acting on the given qubit"""
return Pauli.sigma(qubit, 'Z', coefficient) | [
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rigetti/quantumflow | quantumflow/paulialgebra.py | pauli_sum | def pauli_sum(*elements: Pauli) -> Pauli:
"""Return the sum of elements of the Pauli algebra"""
terms = []
key = itemgetter(0)
for term, grp in groupby(heapq.merge(*elements, key=key), key=key):
coeff = sum(g[1] for g in grp)
if not isclose(coeff, 0.0):
terms.append((term, c... | python | def pauli_sum(*elements: Pauli) -> Pauli:
"""Return the sum of elements of the Pauli algebra"""
terms = []
key = itemgetter(0)
for term, grp in groupby(heapq.merge(*elements, key=key), key=key):
coeff = sum(g[1] for g in grp)
if not isclose(coeff, 0.0):
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rigetti/quantumflow | quantumflow/paulialgebra.py | pauli_product | def pauli_product(*elements: Pauli) -> Pauli:
"""Return the product of elements of the Pauli algebra"""
result_terms = []
for terms in product(*elements):
coeff = reduce(mul, [term[1] for term in terms])
ops = (term[0] for term in terms)
out = []
key = itemgetter(0)
... | python | def pauli_product(*elements: Pauli) -> Pauli:
"""Return the product of elements of the Pauli algebra"""
result_terms = []
for terms in product(*elements):
coeff = reduce(mul, [term[1] for term in terms])
ops = (term[0] for term in terms)
out = []
key = itemgetter(0)
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rigetti/quantumflow | quantumflow/paulialgebra.py | pauli_pow | def pauli_pow(pauli: Pauli, exponent: int) -> Pauli:
"""
Raise an element of the Pauli algebra to a non-negative integer power.
"""
if not isinstance(exponent, int) or exponent < 0:
raise ValueError("The exponent must be a non-negative integer.")
if exponent == 0:
return Pauli.iden... | python | def pauli_pow(pauli: Pauli, exponent: int) -> Pauli:
"""
Raise an element of the Pauli algebra to a non-negative integer power.
"""
if not isinstance(exponent, int) or exponent < 0:
raise ValueError("The exponent must be a non-negative integer.")
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rigetti/quantumflow | quantumflow/paulialgebra.py | pauli_commuting_sets | def pauli_commuting_sets(element: Pauli) -> Tuple[Pauli, ...]:
"""Gather the terms of a Pauli polynomial into commuting sets.
Uses the algorithm defined in (Raeisi, Wiebe, Sanders,
arXiv:1108.4318, 2011) to find commuting sets. Except uses commutation
check from arXiv:1405.5749v2
"""
if len(ele... | python | def pauli_commuting_sets(element: Pauli) -> Tuple[Pauli, ...]:
"""Gather the terms of a Pauli polynomial into commuting sets.
Uses the algorithm defined in (Raeisi, Wiebe, Sanders,
arXiv:1108.4318, 2011) to find commuting sets. Except uses commutation
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rigetti/quantumflow | quantumflow/backend/numpybk.py | astensor | def astensor(array: TensorLike) -> BKTensor:
"""Converts a numpy array to the backend's tensor object
"""
array = np.asarray(array, dtype=CTYPE)
return array | python | def astensor(array: TensorLike) -> BKTensor:
"""Converts a numpy array to the backend's tensor object
"""
array = np.asarray(array, dtype=CTYPE)
return array | [
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rigetti/quantumflow | quantumflow/backend/numpybk.py | productdiag | def productdiag(tensor: BKTensor) -> BKTensor:
"""Returns the matrix diagonal of the product tensor""" # DOCME: Explain
N = rank(tensor)
tensor = reshape(tensor, [2**(N//2), 2**(N//2)])
tensor = np.diag(tensor)
tensor = reshape(tensor, [2]*(N//2))
return tensor | python | def productdiag(tensor: BKTensor) -> BKTensor:
"""Returns the matrix diagonal of the product tensor""" # DOCME: Explain
N = rank(tensor)
tensor = reshape(tensor, [2**(N//2), 2**(N//2)])
tensor = np.diag(tensor)
tensor = reshape(tensor, [2]*(N//2))
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rigetti/quantumflow | quantumflow/backend/numpybk.py | tensormul | def tensormul(tensor0: BKTensor, tensor1: BKTensor,
indices: typing.List[int]) -> BKTensor:
r"""
Generalization of matrix multiplication to product tensors.
A state vector in product tensor representation has N dimension, one for
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indices: typing.List[int]) -> BKTensor:
r"""
Generalization of matrix multiplication to product tensors.
A state vector in product tensor representation has N dimension, one for
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rigetti/quantumflow | quantumflow/utils.py | invert_map | def invert_map(mapping: dict, one_to_one: bool = True) -> dict:
"""Invert a dictionary. If not one_to_one then the inverted
map will contain lists of former keys as values.
"""
if one_to_one:
inv_map = {value: key for key, value in mapping.items()}
else:
inv_map = {}
for key,... | python | def invert_map(mapping: dict, one_to_one: bool = True) -> dict:
"""Invert a dictionary. If not one_to_one then the inverted
map will contain lists of former keys as values.
"""
if one_to_one:
inv_map = {value: key for key, value in mapping.items()}
else:
inv_map = {}
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rigetti/quantumflow | quantumflow/utils.py | bitlist_to_int | def bitlist_to_int(bitlist: Sequence[int]) -> int:
"""Converts a sequence of bits to an integer.
>>> from quantumflow.utils import bitlist_to_int
>>> bitlist_to_int([1, 0, 0])
4
"""
return int(''.join([str(d) for d in bitlist]), 2) | python | def bitlist_to_int(bitlist: Sequence[int]) -> int:
"""Converts a sequence of bits to an integer.
>>> from quantumflow.utils import bitlist_to_int
>>> bitlist_to_int([1, 0, 0])
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rigetti/quantumflow | quantumflow/utils.py | int_to_bitlist | def int_to_bitlist(x: int, pad: int = None) -> Sequence[int]:
"""Converts an integer to a binary sequence of bits.
Pad prepends with sufficient zeros to ensures that the returned list
contains at least this number of bits.
>>> from quantumflow.utils import int_to_bitlist
>>> int_to_bitlist(4, 4))
... | python | def int_to_bitlist(x: int, pad: int = None) -> Sequence[int]:
"""Converts an integer to a binary sequence of bits.
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contains at least this number of bits.
>>> from quantumflow.utils import int_to_bitlist
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rigetti/quantumflow | quantumflow/utils.py | spanning_tree_count | def spanning_tree_count(graph: nx.Graph) -> int:
"""Return the number of unique spanning trees of a graph, using
Kirchhoff's matrix tree theorem.
"""
laplacian = nx.laplacian_matrix(graph).toarray()
comatrix = laplacian[:-1, :-1]
det = np.linalg.det(comatrix)
count = int(round(det))
retu... | python | def spanning_tree_count(graph: nx.Graph) -> int:
"""Return the number of unique spanning trees of a graph, using
Kirchhoff's matrix tree theorem.
"""
laplacian = nx.laplacian_matrix(graph).toarray()
comatrix = laplacian[:-1, :-1]
det = np.linalg.det(comatrix)
count = int(round(det))
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rigetti/quantumflow | quantumflow/utils.py | rationalize | def rationalize(flt: float, denominators: Set[int] = None) -> Fraction:
"""Convert a floating point number to a Fraction with a small
denominator.
Args:
flt: A floating point number
denominators: Collection of standard denominators. Default is
1, 2, 3, 4, 5, 6, 7, 8... | python | def rationalize(flt: float, denominators: Set[int] = None) -> Fraction:
"""Convert a floating point number to a Fraction with a small
denominator.
Args:
flt: A floating point number
denominators: Collection of standard denominators. Default is
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rigetti/quantumflow | quantumflow/utils.py | symbolize | def symbolize(flt: float) -> sympy.Symbol:
"""Attempt to convert a real number into a simpler symbolic
representation.
Returns:
A sympy Symbol. (Convert to string with str(sym) or to latex with
sympy.latex(sym)
Raises:
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"""
try... | python | def symbolize(flt: float) -> sympy.Symbol:
"""Attempt to convert a real number into a simpler symbolic
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A sympy Symbol. (Convert to string with str(sym) or to latex with
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rigetti/quantumflow | quantumflow/forest/__init__.py | pyquil_to_image | def pyquil_to_image(program: pyquil.Program) -> PIL.Image: # pragma: no cover
"""Returns an image of a pyquil circuit.
See circuit_to_latex() for more details.
"""
circ = pyquil_to_circuit(program)
latex = circuit_to_latex(circ)
img = render_latex(latex)
return img | python | def pyquil_to_image(program: pyquil.Program) -> PIL.Image: # pragma: no cover
"""Returns an image of a pyquil circuit.
See circuit_to_latex() for more details.
"""
circ = pyquil_to_circuit(program)
latex = circuit_to_latex(circ)
img = render_latex(latex)
return img | [
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rigetti/quantumflow | quantumflow/forest/__init__.py | circuit_to_pyquil | def circuit_to_pyquil(circuit: Circuit) -> pyquil.Program:
"""Convert a QuantumFlow circuit to a pyQuil program"""
prog = pyquil.Program()
for elem in circuit.elements:
if isinstance(elem, Gate) and elem.name in QUIL_GATES:
params = list(elem.params.values()) if elem.params else []
... | python | def circuit_to_pyquil(circuit: Circuit) -> pyquil.Program:
"""Convert a QuantumFlow circuit to a pyQuil program"""
prog = pyquil.Program()
for elem in circuit.elements:
if isinstance(elem, Gate) and elem.name in QUIL_GATES:
params = list(elem.params.values()) if elem.params else []
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rigetti/quantumflow | quantumflow/forest/__init__.py | pyquil_to_circuit | def pyquil_to_circuit(program: pyquil.Program) -> Circuit:
"""Convert a protoquil pyQuil program to a QuantumFlow Circuit"""
circ = Circuit()
for inst in program.instructions:
# print(type(inst))
if isinstance(inst, pyquil.Declare): # Ignore
continue
if isinst... | python | def pyquil_to_circuit(program: pyquil.Program) -> Circuit:
"""Convert a protoquil pyQuil program to a QuantumFlow Circuit"""
circ = Circuit()
for inst in program.instructions:
# print(type(inst))
if isinstance(inst, pyquil.Declare): # Ignore
continue
if isinst... | [
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rigetti/quantumflow | quantumflow/forest/__init__.py | quil_to_program | def quil_to_program(quil: str) -> Program:
"""Parse a quil program and return a Program object"""
pyquil_instructions = pyquil.parser.parse(quil)
return pyquil_to_program(pyquil_instructions) | python | def quil_to_program(quil: str) -> Program:
"""Parse a quil program and return a Program object"""
pyquil_instructions = pyquil.parser.parse(quil)
return pyquil_to_program(pyquil_instructions) | [
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rigetti/quantumflow | quantumflow/forest/__init__.py | state_to_wavefunction | def state_to_wavefunction(state: State) -> pyquil.Wavefunction:
"""Convert a QuantumFlow state to a pyQuil Wavefunction"""
# TODO: qubits?
amplitudes = state.vec.asarray()
# pyQuil labels states backwards.
amplitudes = amplitudes.transpose()
amplitudes = amplitudes.reshape([amplitudes.size])
... | python | def state_to_wavefunction(state: State) -> pyquil.Wavefunction:
"""Convert a QuantumFlow state to a pyQuil Wavefunction"""
# TODO: qubits?
amplitudes = state.vec.asarray()
# pyQuil labels states backwards.
amplitudes = amplitudes.transpose()
amplitudes = amplitudes.reshape([amplitudes.size])
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rigetti/quantumflow | quantumflow/forest/__init__.py | QuantumFlowQVM.load | def load(self, binary: pyquil.Program) -> 'QuantumFlowQVM':
"""
Load a pyQuil program, and initialize QVM into a fresh state.
Args:
binary: A pyQuil program
"""
assert self.status in ['connected', 'done']
prog = quil_to_program(str(binary))
self._pr... | python | def load(self, binary: pyquil.Program) -> 'QuantumFlowQVM':
"""
Load a pyQuil program, and initialize QVM into a fresh state.
Args:
binary: A pyQuil program
"""
assert self.status in ['connected', 'done']
prog = quil_to_program(str(binary))
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rigetti/quantumflow | quantumflow/forest/__init__.py | QuantumFlowQVM.run | def run(self) -> 'QuantumFlowQVM':
"""Run a previously loaded program"""
assert self.status in ['loaded']
self.status = 'running'
self._ket = self._prog.run()
# Should set state to 'done' after run complete.
# Makes no sense to keep status at running. But pyQuil's
... | python | def run(self) -> 'QuantumFlowQVM':
"""Run a previously loaded program"""
assert self.status in ['loaded']
self.status = 'running'
self._ket = self._prog.run()
# Should set state to 'done' after run complete.
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rigetti/quantumflow | quantumflow/forest/__init__.py | QuantumFlowQVM.wavefunction | def wavefunction(self) -> pyquil.Wavefunction:
"""
Return the wavefunction of a completed program.
"""
assert self.status == 'done'
assert self._ket is not None
wavefn = state_to_wavefunction(self._ket)
return wavefn | python | def wavefunction(self) -> pyquil.Wavefunction:
"""
Return the wavefunction of a completed program.
"""
assert self.status == 'done'
assert self._ket is not None
wavefn = state_to_wavefunction(self._ket)
return wavefn | [
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rigetti/quantumflow | quantumflow/backend/torchbk.py | evaluate | def evaluate(tensor: BKTensor) -> TensorLike:
"""Return the value of a tensor"""
if isinstance(tensor, _DTYPE):
if torch.numel(tensor) == 1:
return tensor.item()
if tensor.numel() == 2:
return tensor[0].cpu().numpy() + 1.0j * tensor[1].cpu().numpy()
return tensor... | python | def evaluate(tensor: BKTensor) -> TensorLike:
"""Return the value of a tensor"""
if isinstance(tensor, _DTYPE):
if torch.numel(tensor) == 1:
return tensor.item()
if tensor.numel() == 2:
return tensor[0].cpu().numpy() + 1.0j * tensor[1].cpu().numpy()
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rigetti/quantumflow | quantumflow/backend/torchbk.py | rank | def rank(tensor: BKTensor) -> int:
"""Return the number of dimensions of a tensor"""
if isinstance(tensor, np.ndarray):
return len(tensor.shape)
return len(tensor[0].size()) | python | def rank(tensor: BKTensor) -> int:
"""Return the number of dimensions of a tensor"""
if isinstance(tensor, np.ndarray):
return len(tensor.shape)
return len(tensor[0].size()) | [
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rigetti/quantumflow | quantumflow/measures.py | state_fidelity | def state_fidelity(state0: State, state1: State) -> bk.BKTensor:
"""Return the quantum fidelity between pure states."""
assert state0.qubits == state1.qubits # FIXME
tensor = bk.absolute(bk.inner(state0.tensor, state1.tensor))**bk.fcast(2)
return tensor | python | def state_fidelity(state0: State, state1: State) -> bk.BKTensor:
"""Return the quantum fidelity between pure states."""
assert state0.qubits == state1.qubits # FIXME
tensor = bk.absolute(bk.inner(state0.tensor, state1.tensor))**bk.fcast(2)
return tensor | [
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rigetti/quantumflow | quantumflow/measures.py | state_angle | def state_angle(ket0: State, ket1: State) -> bk.BKTensor:
"""The Fubini-Study angle between states.
Equal to the Burrs angle for pure states.
"""
return fubini_study_angle(ket0.vec, ket1.vec) | python | def state_angle(ket0: State, ket1: State) -> bk.BKTensor:
"""The Fubini-Study angle between states.
Equal to the Burrs angle for pure states.
"""
return fubini_study_angle(ket0.vec, ket1.vec) | [
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rigetti/quantumflow | quantumflow/measures.py | states_close | def states_close(state0: State, state1: State,
tolerance: float = TOLERANCE) -> bool:
"""Returns True if states are almost identical.
Closeness is measured with the metric Fubini-Study angle.
"""
return vectors_close(state0.vec, state1.vec, tolerance) | python | def states_close(state0: State, state1: State,
tolerance: float = TOLERANCE) -> bool:
"""Returns True if states are almost identical.
Closeness is measured with the metric Fubini-Study angle.
"""
return vectors_close(state0.vec, state1.vec, tolerance) | [
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rigetti/quantumflow | quantumflow/measures.py | purity | def purity(rho: Density) -> bk.BKTensor:
"""
Calculate the purity of a mixed quantum state.
Purity, defined as tr(rho^2), has an upper bound of 1 for a pure state,
and a lower bound of 1/D (where D is the Hilbert space dimension) for a
competently mixed state.
Two closely related measures are ... | python | def purity(rho: Density) -> bk.BKTensor:
"""
Calculate the purity of a mixed quantum state.
Purity, defined as tr(rho^2), has an upper bound of 1 for a pure state,
and a lower bound of 1/D (where D is the Hilbert space dimension) for a
competently mixed state.
Two closely related measures are ... | [
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competently mixed state.
Two closely related measures are the linear entropy, 1- purity, and the
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rigetti/quantumflow | quantumflow/measures.py | bures_distance | def bures_distance(rho0: Density, rho1: Density) -> float:
"""Return the Bures distance between mixed quantum states
Note: Bures distance cannot be calculated within the tensor backend.
"""
fid = fidelity(rho0, rho1)
op0 = asarray(rho0.asoperator())
op1 = asarray(rho1.asoperator())
tr0 = np... | python | def bures_distance(rho0: Density, rho1: Density) -> float:
"""Return the Bures distance between mixed quantum states
Note: Bures distance cannot be calculated within the tensor backend.
"""
fid = fidelity(rho0, rho1)
op0 = asarray(rho0.asoperator())
op1 = asarray(rho1.asoperator())
tr0 = np... | [
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rigetti/quantumflow | quantumflow/measures.py | bures_angle | def bures_angle(rho0: Density, rho1: Density) -> float:
"""Return the Bures angle between mixed quantum states
Note: Bures angle cannot be calculated within the tensor backend.
"""
return np.arccos(np.sqrt(fidelity(rho0, rho1))) | python | def bures_angle(rho0: Density, rho1: Density) -> float:
"""Return the Bures angle between mixed quantum states
Note: Bures angle cannot be calculated within the tensor backend.
"""
return np.arccos(np.sqrt(fidelity(rho0, rho1))) | [
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rigetti/quantumflow | quantumflow/measures.py | density_angle | def density_angle(rho0: Density, rho1: Density) -> bk.BKTensor:
"""The Fubini-Study angle between density matrices"""
return fubini_study_angle(rho0.vec, rho1.vec) | python | def density_angle(rho0: Density, rho1: Density) -> bk.BKTensor:
"""The Fubini-Study angle between density matrices"""
return fubini_study_angle(rho0.vec, rho1.vec) | [
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rigetti/quantumflow | quantumflow/measures.py | densities_close | def densities_close(rho0: Density, rho1: Density,
tolerance: float = TOLERANCE) -> bool:
"""Returns True if densities are almost identical.
Closeness is measured with the metric Fubini-Study angle.
"""
return vectors_close(rho0.vec, rho1.vec, tolerance) | python | def densities_close(rho0: Density, rho1: Density,
tolerance: float = TOLERANCE) -> bool:
"""Returns True if densities are almost identical.
Closeness is measured with the metric Fubini-Study angle.
"""
return vectors_close(rho0.vec, rho1.vec, tolerance) | [
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rigetti/quantumflow | quantumflow/measures.py | entropy | def entropy(rho: Density, base: float = None) -> float:
"""
Returns the von-Neumann entropy of a mixed quantum state.
Args:
rho: A density matrix
base: Optional logarithm base. Default is base e, and entropy is
measures in nats. For bits set base to 2.
Returns:
... | python | def entropy(rho: Density, base: float = None) -> float:
"""
Returns the von-Neumann entropy of a mixed quantum state.
Args:
rho: A density matrix
base: Optional logarithm base. Default is base e, and entropy is
measures in nats. For bits set base to 2.
Returns:
... | [
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Args:
rho: A density matrix
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Returns:
The von-Neumann entropy of rho | [
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