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mrstephenneal/dirutility | dirutility/walk/walk.py | DirPaths.files | def files(self):
"""Return list of files in root directory"""
self._printer('\tFiles Walk')
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isfile(full_path):
... | python | def files(self):
"""Return list of files in root directory"""
self._printer('\tFiles Walk')
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isfile(full_path):
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mrstephenneal/dirutility | dirutility/walk/walk.py | DirPaths.folders | def folders(self):
"""Return list of folders in root directory"""
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for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isdir(full_path):
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... | python | def folders(self):
"""Return list of folders in root directory"""
for directory in self.directory:
for path in os.listdir(directory):
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mrstephenneal/dirutility | dirutility/walk/walk.py | DirTree.get | def get(self):
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drongo-framework/drongo | drongo/app.py | Drongo.url | def url(self, pattern, method=None, name=None):
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drongo-framework/drongo | drongo/app.py | Drongo.add_url | def add_url(self, pattern, method=None, call=None):
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | convert_other_format | def convert_other_format(filename, format):
"""
转换为png图片
:param filename: 图片文件名
:return:
"""
img = Image.open(filename)
rp = ReParser()
c_filename = rp.replace(r'\..*$', format, filename)
img.save(c_filename) | python | def convert_other_format(filename, format):
"""
转换为png图片
:param filename: 图片文件名
:return:
"""
img = Image.open(filename)
rp = ReParser()
c_filename = rp.replace(r'\..*$', format, filename)
img.save(c_filename) | [
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | binarizing | def binarizing(img,threshold):
"""
二值化
:param img:
:param threshold:
:return:
"""
pixdata = img.load()
w, h = img.size
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pixdata[x... | python | def binarizing(img,threshold):
"""
二值化
:param img:
:param threshold:
:return:
"""
pixdata = img.load()
w, h = img.size
for y in range(h):
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | remove_interference_line | def remove_interference_line(img):
"""
去除干扰线
:param img:
:return:
"""
pixdata = img.load()
w,h = img.size
for y in range(1,h-1):
for x in range(1,w-1):
count = 0
if pixdata[x,y-1] > 245:
count = count + 1
if pixdata[x,y+1] > 245... | python | def remove_interference_line(img):
"""
去除干扰线
:param img:
:return:
"""
pixdata = img.load()
w,h = img.size
for y in range(1,h-1):
for x in range(1,w-1):
count = 0
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count = count + 1
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | create_thumbnail | def create_thumbnail(img, width, height):
"""
创建缩略图
缩略图的意思就是缩小
:param img: 图片对象
:param width: 宽
:param height: 高
:return:
"""
size = (width, height)
img.thumbnail(size)
return img | python | def create_thumbnail(img, width, height):
"""
创建缩略图
缩略图的意思就是缩小
:param img: 图片对象
:param width: 宽
:param height: 高
:return:
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | cut | def cut(img, left, above, right, down):
"""
从图像中复制出一个矩形选区
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region = im.crop(box)
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:param left: 左
:param above: 上
:param right: 右
:param down: 下
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"""
从图像中复制出一个矩形选区
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region = im.crop(box)
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | paste | def paste(region, img, left, above, right, down):
"""
将扣的图粘贴到制定图片上
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:param left: 左
:param above: 上
:param right: 右
:param down: 下
:return: 被修改过的图片对象，还在内存中... | python | def paste(region, img, left, above, right, down):
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | resize | def resize(img, width, height):
"""
更改图片大小，只能更改磁盘空间的大小。
:param img:
:param width:
:param height:
:return: 更改后的图片
"""
return img.resize((width, height), Image.ANTIALIAS) | python | def resize(img, width, height):
"""
更改图片大小，只能更改磁盘空间的大小。
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:param width:
:param height:
:return: 更改后的图片
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | GPS.get_exif_data | def get_exif_data(self, image):
"""Returns a dictionary from the exif data of an PIL Image item. Also converts the GPS Tags"""
exif_data = {}
info = image._getexif()
if info:
for tag, value in info.items():
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if decod... | python | def get_exif_data(self, image):
"""Returns a dictionary from the exif data of an PIL Image item. Also converts the GPS Tags"""
exif_data = {}
info = image._getexif()
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | GPS._convert_to_degress | def _convert_to_degress(self, value):
"""Helper function to convert the GPS coordinates stored in the EXIF to degress in float format"""
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d1 = value[0][1]
d = float(d0) / float(d1)
m0 = value[1][0]
m1 = value[1][1]
m = float(m0) / float(m1)
... | python | def _convert_to_degress(self, value):
"""Helper function to convert the GPS coordinates stored in the EXIF to degress in float format"""
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d1 = value[0][1]
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | GPS.get_lat_lon | def get_lat_lon(self, exif_data):
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shi-cong/PYSTUDY | PYSTUDY/image/pillib.py | GPS.get_gps | def get_gps(self, image):
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robertchase/ergaleia | ergaleia/config.py | Config._load | def _load(self, path='config', filetype=None, relaxed=False, ignore=False):
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filetype - type component of dot-delimited path
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tBaxter/tango-shared-core | build/lib/tango_shared/models.py | set_img_path | def set_img_path(instance, filename):
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Apitax/Apitax | apitax/api/controllers/migrations/developers_controller.py | create_script | def create_script(create=None): # noqa: E501
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Create a new script # noqa: E501
:param Scripts: The data needed to create this script
:type Scripts: dict | bytes
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Apitax/Apitax | apitax/api/controllers/migrations/developers_controller.py | delete_script | def delete_script(delete=None): # noqa: E501
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"""Delete a script
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treystout/Agner | agner/queue.py | Queue.enqueue | def enqueue(self, job):
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | generate_headline_from_description | def generate_headline_from_description(sender, instance, *args, **kwargs):
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | story_root_for_new_outline | def story_root_for_new_outline(sender, instance, created, *args, **kwargs):
'''
If a new instance of a Outline is created, also create
the root node of the story tree.
'''
if created and isinstance(instance, Outline):
streeroot = StoryElementNode.add_root(outline=instance, story_element_type... | python | def story_root_for_new_outline(sender, instance, created, *args, **kwargs):
'''
If a new instance of a Outline is created, also create
the root node of the story tree.
'''
if created and isinstance(instance, Outline):
streeroot = StoryElementNode.add_root(outline=instance, story_element_type... | [
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | arc_node_edit_add_missing_characters_and_locations_to_related_story_node | def arc_node_edit_add_missing_characters_and_locations_to_related_story_node(
sender,
instance,
action,
reverse,
pk_set,
*args,
**kwargs
):
'''
If an arc_element is modified and it's characters/locations are not already in the story node, add them.
We ... | python | def arc_node_edit_add_missing_characters_and_locations_to_related_story_node(
sender,
instance,
action,
reverse,
pk_set,
*args,
**kwargs
):
'''
If an arc_element is modified and it's characters/locations are not already in the story node, add them.
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | story_node_add_arc_element_update_characters_locations | def story_node_add_arc_element_update_characters_locations(sender, instance, created, *args, **kwargs):
'''
If an arc element is added to a story element node, add any missing elements or locations.
'''
arc_node = ArcElementNode.objects.get(pk=instance.pk)
logger.debug('Scanning arc_node %s' % arc_n... | python | def story_node_add_arc_element_update_characters_locations(sender, instance, created, *args, **kwargs):
'''
If an arc element is added to a story element node, add any missing elements or locations.
'''
arc_node = ArcElementNode.objects.get(pk=instance.pk)
logger.debug('Scanning arc_node %s' % arc_n... | [
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | validate_arc_links_same_outline | def validate_arc_links_same_outline(sender, instance, *args, **kwargs):
'''
Evaluates attempts to link an arc to a story node from another outline.
'''
if instance.story_element_node:
if instance.story_element_node.outline != instance.parent_outline:
raise IntegrityError(_('An arc ca... | python | def validate_arc_links_same_outline(sender, instance, *args, **kwargs):
'''
Evaluates attempts to link an arc to a story node from another outline.
'''
if instance.story_element_node:
if instance.story_element_node.outline != instance.parent_outline:
raise IntegrityError(_('An arc ca... | [
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | validate_character_instance_valid_for_arc | def validate_character_instance_valid_for_arc(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Evaluate attempts to assign a character instance to ensure it is from same
outline.
'''
if action == 'pre_add':
if reverse:
# Fetch arc definition through link.
... | python | def validate_character_instance_valid_for_arc(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Evaluate attempts to assign a character instance to ensure it is from same
outline.
'''
if action == 'pre_add':
if reverse:
# Fetch arc definition through link.
... | [
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | validate_location_instance_valid_for_arc | def validate_location_instance_valid_for_arc(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Evaluates attempts to add location instances to arc, ensuring they are from same outline.
'''
if action == 'pre_add':
if reverse:
# Fetch arc definition through link.
... | python | def validate_location_instance_valid_for_arc(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Evaluates attempts to add location instances to arc, ensuring they are from same outline.
'''
if action == 'pre_add':
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | validate_character_for_story_element | def validate_character_for_story_element(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Validates that character is from the same outline as the story node.
'''
if action == 'pre_add':
if reverse:
for spk in pk_set:
story_node = StoryElementNode.obje... | python | def validate_character_for_story_element(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Validates that character is from the same outline as the story node.
'''
if action == 'pre_add':
if reverse:
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | validate_location_for_story_element | def validate_location_for_story_element(sender, instance, action, reverse, pk_set, *args, **kwargs):
'''
Validates that location is from same outline as story node.
'''
if action == 'pre_add':
if reverse:
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'''
Validates that location is from same outline as story node.
'''
if action == 'pre_add':
if reverse:
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maceoutliner/django-fiction-outlines | fiction_outlines/receivers.py | validate_generations_for_story_elements | def validate_generations_for_story_elements(
sender,
instance,
action,
target_node_type=None,
target_node=None,
pos=None,
*args,
**kwargs
):
'''
Unlike arc nodes, for which we just warn about structure, the story tree
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sender,
instance,
action,
target_node_type=None,
target_node=None,
pos=None,
*args,
**kwargs
):
'''
Unlike arc nodes, for which we just warn about structure, the story tree
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rsalmaso/django-fluo | fluo/views/base.py | View.options | def options(self, request, *args, **kwargs):
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Handles responding to requests for the OPTIONS HTTP verb
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Handles responding to requests for the OPTIONS HTTP verb
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response = HttpResponse()
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DasIch/argvard | argvard/utils.py | is_python2_identifier | def is_python2_identifier(possible_identifier):
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Returns `True` if the given `possible_identifier` can be used as an
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"""
match = _python2_identifier_re.match(possible_identifier)
return bool(match) and not iskeyword(possible_identifier) | python | def is_python2_identifier(possible_identifier):
"""
Returns `True` if the given `possible_identifier` can be used as an
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"""
match = _python2_identifier_re.match(possible_identifier)
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DasIch/argvard | argvard/utils.py | unique | def unique(iterable):
"""
Returns an iterator that yields the first occurence of a hashable item in
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"""
seen = set()
for obj in iterable:
if obj not in seen:
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"""
Returns an iterator that yields the first occurence of a hashable item in
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krinj/k-util | k_util/region.py | Region.contains | def contains(self, x, y) -> bool:
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return False
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krinj/k-util | k_util/region.py | Region.is_in_bounds | def is_in_bounds(self, width, height) -> bool:
""" Check if this entire region is contained within the bounds of a given stage size."""
if self._top < 0 \
or self._bottom > height \
or self._left < 0 \
or self._right > width:
return False
... | python | def is_in_bounds(self, width, height) -> bool:
""" Check if this entire region is contained within the bounds of a given stage size."""
if self._top < 0 \
or self._bottom > height \
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krinj/k-util | k_util/region.py | Region.canvas_resize | def canvas_resize(self, scale):
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self._top *= scale
self._bottom *= scale
self._left *= scale
self._right *= scale
self._calibrate_to_rect() | python | def canvas_resize(self, scale):
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krinj/k-util | k_util/region.py | Region.distance | def distance(r1: 'Region', r2: 'Region'):
""" Calculate distance between the x and y of the two regions."""
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""" Calculate distance between the x and y of the two regions."""
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""" A quicker way of calculating approximate distance. Lower accuracy but faster results."""
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hobson/pug-invest | pug/invest/util.py | rms | def rms(x):
""""Root Mean Square"
Arguments:
x (seq of float): A sequence of numerical values
Returns:
The square root of the average of the squares of the values
math.sqrt(sum(x_i**2 for x_i in x) / len(x))
or
return (np.array(x) ** 2).mean() ** 0.5
>>> rms... | python | def rms(x):
""""Root Mean Square"
Arguments:
x (seq of float): A sequence of numerical values
Returns:
The square root of the average of the squares of the values
math.sqrt(sum(x_i**2 for x_i in x) / len(x))
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hobson/pug-invest | pug/invest/util.py | rmse | def rmse(target, prediction, relative=False, percent=False):
"""Root Mean Square Error
This seems like a simple formula that you'd never need to create a function for.
But my mistakes on coding challenges have convinced me that I do need it,
as a reminder of important tweaks, if nothing else.
>>> ... | python | def rmse(target, prediction, relative=False, percent=False):
"""Root Mean Square Error
This seems like a simple formula that you'd never need to create a function for.
But my mistakes on coding challenges have convinced me that I do need it,
as a reminder of important tweaks, if nothing else.
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hobson/pug-invest | pug/invest/util.py | clean_dataframe | def clean_dataframe(df):
"""Fill NaNs with the previous value, the next value or if all are NaN then 1.0"""
df = df.fillna(method='ffill')
df = df.fillna(0.0)
return df | python | def clean_dataframe(df):
"""Fill NaNs with the previous value, the next value or if all are NaN then 1.0"""
df = df.fillna(method='ffill')
df = df.fillna(0.0)
return df | [
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hobson/pug-invest | pug/invest/util.py | clean_dataframes | def clean_dataframes(dfs):
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TODO:
Linear interpolation and extrapolation
Arguments:
dfs (list of dataframes): list of dataframes that contain NaNs to be removed
Returns:
list of dataframes: list of datafr... | python | def clean_dataframes(dfs):
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hobson/pug-invest | pug/invest/util.py | get_symbols_from_list | def get_symbols_from_list(list_name):
"""Retrieve a named (symbol list name) list of strings (symbols)
If you've installed the QSTK Quantitative analysis toolkit
`get_symbols_from_list('sp5002012')` will produce a list of the symbols that
were members of the S&P 500 in 2012.
Otherwise an im... | python | def get_symbols_from_list(list_name):
"""Retrieve a named (symbol list name) list of strings (symbols)
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hobson/pug-invest | pug/invest/util.py | make_symbols | def make_symbols(symbols, *args):
"""Return a list of uppercase strings like "GOOG", "$SPX, "XOM"...
Arguments:
symbols (str or list of str): list of market ticker symbols to normalize
If `symbols` is a str a get_symbols_from_list() call is used to retrieve the list of symbols
Returns:
... | python | def make_symbols(symbols, *args):
"""Return a list of uppercase strings like "GOOG", "$SPX, "XOM"...
Arguments:
symbols (str or list of str): list of market ticker symbols to normalize
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hobson/pug-invest | pug/invest/util.py | make_time_series | def make_time_series(x, t=pd.Timestamp(datetime.datetime(1970, 1, 1)), freq=None):
"""Convert a 2-D array of time/value pairs (or pair of time/value vectors) into a pd.Series time-series
>>> make_time_series(range(3), freq='15min') # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
1970-01-01 00:00:00 NaN
... | python | def make_time_series(x, t=pd.Timestamp(datetime.datetime(1970, 1, 1)), freq=None):
"""Convert a 2-D array of time/value pairs (or pair of time/value vectors) into a pd.Series time-series
>>> make_time_series(range(3), freq='15min') # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
1970-01-01 00:00:00 NaN
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hobson/pug-invest | pug/invest/util.py | pandas_mesh | def pandas_mesh(df):
"""Create numpy 2-D "meshgrid" from 3+ columns in a Pandas DataFrame
Arguments:
df (DataFrame): Must have 3 or 4 columns of numerical data
Returns:
OrderedDict: column labels from the data frame are the keys, values are 2-D matrices
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"""Create numpy 2-D "meshgrid" from 3+ columns in a Pandas DataFrame
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df (DataFrame): Must have 3 or 4 columns of numerical data
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hobson/pug-invest | pug/invest/util.py | integrated_change | def integrated_change(ts, integrator=integrate.trapz, clip_floor=None, clip_ceil=float('inf')):
"""Total value * time above the starting value within a TimeSeries"""
integrator = get_integrator(integrator)
if clip_floor is None:
clip_floor = ts[0]
if clip_ceil < clip_floor:
polarity = -1... | python | def integrated_change(ts, integrator=integrate.trapz, clip_floor=None, clip_ceil=float('inf')):
"""Total value * time above the starting value within a TimeSeries"""
integrator = get_integrator(integrator)
if clip_floor is None:
clip_floor = ts[0]
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hobson/pug-invest | pug/invest/util.py | insert_crossings | def insert_crossings(ts, thresh):
"""Insert/append threshold crossing points (time and value) into a timeseries (pd.Series)
Arguments:
ts (pandas.Series): Time series of values to be interpolated at `thresh` crossings
thresh (float or np.float64):
"""
# import time
# tic0 = time.clock()... | python | def insert_crossings(ts, thresh):
"""Insert/append threshold crossing points (time and value) into a timeseries (pd.Series)
Arguments:
ts (pandas.Series): Time series of values to be interpolated at `thresh` crossings
thresh (float or np.float64):
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hobson/pug-invest | pug/invest/util.py | get_integrator | def get_integrator(integrator):
"""Return the scipy.integrator indicated by an index, name, or integrator_function
>> get_integrator(0)
"""
integrator_types = set(['trapz', 'cumtrapz', 'simps', 'romb'])
integrator_funcs = [integrate.trapz, integrate.cumtrapz, integrate.simps, integrate.romb]
i... | python | def get_integrator(integrator):
"""Return the scipy.integrator indicated by an index, name, or integrator_function
>> get_integrator(0)
"""
integrator_types = set(['trapz', 'cumtrapz', 'simps', 'romb'])
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hobson/pug-invest | pug/invest/util.py | clipped_area | def clipped_area(ts, thresh=0, integrator=integrate.trapz):
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ts (pandas.Series): Time series to be integrated.
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ts (pandas.Series): Time series to be integrated.
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hobson/pug-invest | pug/invest/util.py | clipping_params | def clipping_params(ts, capacity=100, rate_limit=float('inf'), method=None, max_attempts=100):
"""Start, end, and threshold that clips the value of a time series the most, given a limitted "capacity" and "rate"
Assumes that signal can be linearly interpolated between points (trapezoidal integration)
Argum... | python | def clipping_params(ts, capacity=100, rate_limit=float('inf'), method=None, max_attempts=100):
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hobson/pug-invest | pug/invest/util.py | discrete_clipping_params | def discrete_clipping_params(ts, capacity=100, rate_limit=float('inf')):
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Assumes that the integrated maximum includes the peak (instantaneous maximum).
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hobson/pug-invest | pug/invest/util.py | square_off | def square_off(series, time_delta=None, transition_seconds=1):
"""Insert samples in regularly sampled data to produce stairsteps from ramps when plotted.
New samples are 1 second (1e9 ns) before each existing samples, to facilitate plotting and sorting
>>> square_off(pd.Series(range(3), index=pd.date_rang... | python | def square_off(series, time_delta=None, transition_seconds=1):
"""Insert samples in regularly sampled data to produce stairsteps from ramps when plotted.
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hobson/pug-invest | pug/invest/util.py | clipping_threshold | def clipping_threshold(ts, capacity=100, rate_limit=10):
"""Start and end index (datetime) that clips the price/value of a time series the most
Assumes that the integrated maximum includes the peak (instantaneous maximum).
Arguments:
ts (TimeSeries): Time series of prices or power readings to be "cl... | python | def clipping_threshold(ts, capacity=100, rate_limit=10):
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hobson/pug-invest | pug/invest/util.py | join_time_series | def join_time_series(serieses, ignore_year=False, T_s=None, aggregator='mean'):
"""Combine a dict of pd.Series objects into a single pd.DataFrame with optional downsampling
FIXME:
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366 days per year (leap year). So 3 ou... | python | def join_time_series(serieses, ignore_year=False, T_s=None, aggregator='mean'):
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hobson/pug-invest | pug/invest/util.py | simulate | def simulate(t=1000, poly=(0.,), sinusoids=None, sigma=0, rw=0, irw=0, rrw=0):
"""Simulate a random signal with seasonal (sinusoids), linear and quadratic trend, RW, IRW, and RRW
Arguments:
t (int or list of float): number of samples or time vector, default = 1000
poly (list of float): polynomial c... | python | def simulate(t=1000, poly=(0.,), sinusoids=None, sigma=0, rw=0, irw=0, rrw=0):
"""Simulate a random signal with seasonal (sinusoids), linear and quadratic trend, RW, IRW, and RRW
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hobson/pug-invest | pug/invest/util.py | normalize_symbols | def normalize_symbols(symbols, *args, **kwargs):
"""Coerce into a list of uppercase strings like "GOOG", "$SPX, "XOM"
Flattens nested lists in `symbols` and converts all list elements to strings
Arguments:
symbols (str or list of str): list of market ticker symbols to normalize
If `symbols` ... | python | def normalize_symbols(symbols, *args, **kwargs):
"""Coerce into a list of uppercase strings like "GOOG", "$SPX, "XOM"
Flattens nested lists in `symbols` and converts all list elements to strings
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symbols (str or list of str): list of market ticker symbols to normalize
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hobson/pug-invest | pug/invest/util.py | smooth | def smooth(x, window_len=11, window='hanning', fill='reflect'):
"""smooth the data using a window with requested size.
Convolve a normalized window with the signal.
input:
x: signal to be smoothed
window_len: the width of the smoothing window
window: the type of window from 'flat',... | python | def smooth(x, window_len=11, window='hanning', fill='reflect'):
"""smooth the data using a window with requested size.
Convolve a normalized window with the signal.
input:
x: signal to be smoothed
window_len: the width of the smoothing window
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hobson/pug-invest | pug/invest/util.py | estimate_shift | def estimate_shift(x, y, smoother=None, w=None, index_and_value=False, ignore_edge=1/3.,
method='valid'):
"""Estimate the time shift between two signals based on their cross correlation
Arguements:
smoother: Smoothing function applied to correlation values before finding peak
w:... | python | def estimate_shift(x, y, smoother=None, w=None, index_and_value=False, ignore_edge=1/3.,
method='valid'):
"""Estimate the time shift between two signals based on their cross correlation
Arguements:
smoother: Smoothing function applied to correlation values before finding peak
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hobson/pug-invest | pug/invest/util.py | fuzzy_index_match | def fuzzy_index_match(possiblities, label, **kwargs):
"""Find the closest matching column label, key, or integer indexed value
Returns:
type(label): sequence of immutable objects corresponding to best matches to each object in label
if label is an int returns the object (value) in the list ... | python | def fuzzy_index_match(possiblities, label, **kwargs):
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Returns:
type(label): sequence of immutable objects corresponding to best matches to each object in label
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hobson/pug-invest | pug/invest/util.py | get_column_labels | def get_column_labels(obj):
"""Retrieve the column labels/keys from any DataFrame or QuerySet-like table object
>>> from collections import OrderedDict
>>> get_column_labels(OrderedDict(zip('ABC', pd.np.arange(12).reshape((3,4)))))
['A', 'B', 'C']
"""
if not isinstance(obj, (list, tuple, pd.np.... | python | def get_column_labels(obj):
"""Retrieve the column labels/keys from any DataFrame or QuerySet-like table object
>>> from collections import OrderedDict
>>> get_column_labels(OrderedDict(zip('ABC', pd.np.arange(12).reshape((3,4)))))
['A', 'B', 'C']
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hobson/pug-invest | pug/invest/util.py | make_dataframe | def make_dataframe(obj, columns=None, exclude=None, limit=1e8):
"""Coerce an iterable, queryset, list or rows, dict of columns, etc into a Pandas DataFrame"""
try:
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hobson/pug-invest | pug/invest/util.py | hist | def hist(table, field=-1, class_column=None,
title='', verbosity=2, **kwargs):
"""Plot discrete PDFs
>>> df = pd.DataFrame(pd.np.random.randn(99,3), columns=list('ABC'))
>>> df['Class'] = pd.np.array((pd.np.matrix([1,1,1])*pd.np.matrix(df).T).T > 0)
>>> len(hist(df, verbosity=0, class_column='... | python | def hist(table, field=-1, class_column=None,
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political-memory/django-representatives | representatives/migrations/0021_update_fr_committees.py | update_kinds | def update_kinds(apps, schema_editor):
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"""
Downgrade FR special committees to delegations
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"""
Migrate to new FR committee abbreviations
"""
# Get model managers
Group = apps.get_model("representatives", "Group")
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EnigmaBridge/client.py | ebclient/eb_utils.py | EBUtils.build_api_object | def build_api_object(uo=None, api_key=None, uo_id=None, uo_type=None):
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Archived-Object/ligament | ligament/ligament.py | run_skeleton | def run_skeleton(skeleton_path, tasks, watch=True):
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tBaxter/tango-shared-core | build/lib/tango_shared/templatetags/tango_site_tags.py | get_fresh_content | def get_fresh_content(top=4, additional=10, featured=False):
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bretth/djset | djset/backends.py | UnencryptedKeyring.file_path | def file_path(self):
"""
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] | train | https://github.com/bretth/djset/blob/e04cbcadc311f6edec50a718415d0004aa304034/djset/backends.py#L56-L79 |
ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.account | def account(self, account=None):
''' Fetches account information and stores the
result in a class variable. Returns that variable
if the account has not changed.
'''
for num_of_retries in range(default.max_retry):
if account is None:
account = self.mai... | python | def account(self, account=None):
''' Fetches account information and stores the
result in a class variable. Returns that variable
if the account has not changed.
'''
for num_of_retries in range(default.max_retry):
if account is None:
account = self.mai... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.steem_instance | def steem_instance(self):
''' Returns the steem instance if it already exists
otherwise uses the goodnode method to fetch a node
and instantiate the Steem class.
'''
if self.s:
return self.s
for num_of_retries in range(default.max_retry):
node = se... | python | def steem_instance(self):
''' Returns the steem instance if it already exists
otherwise uses the goodnode method to fetch a node
and instantiate the Steem class.
'''
if self.s:
return self.s
for num_of_retries in range(default.max_retry):
node = se... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.verify_key | def verify_key (self, acctname=None, tokenkey=None):
''' This can be used to verify either a private
posting key or to verify a steemconnect refresh
token and retreive the access token.
'''
if (re.match( r'^[A-Za-z0-9]+$', tokenkey)
and tokenkey is not Non... | python | def verify_key (self, acctname=None, tokenkey=None):
''' This can be used to verify either a private
posting key or to verify a steemconnect refresh
token and retreive the access token.
'''
if (re.match( r'^[A-Za-z0-9]+$', tokenkey)
and tokenkey is not Non... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.reward_pool_balances | def reward_pool_balances(self):
''' Fetches and returns the 3 values
needed to calculate the reward pool
and other associated values such as rshares.
Returns the reward balance, all recent claims
and the current price of steem.
'''
if self.reward_balance > 0:
... | python | def reward_pool_balances(self):
''' Fetches and returns the 3 values
needed to calculate the reward pool
and other associated values such as rshares.
Returns the reward balance, all recent claims
and the current price of steem.
'''
if self.reward_balance > 0:
... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.rshares_to_steem | def rshares_to_steem (self, rshares):
''' Gets the reward pool balances
then calculates rshares to steem
'''
self.reward_pool_balances()
return round(
rshares
* self.reward_balance
/ self.recent_claims
* self.base, 4) | python | def rshares_to_steem (self, rshares):
''' Gets the reward pool balances
then calculates rshares to steem
'''
self.reward_pool_balances()
return round(
rshares
* self.reward_balance
/ self.recent_claims
* self.base, 4) | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.global_props | def global_props(self):
''' Retrieves the global properties
used to determine rates used for calculations
in converting steempower to vests etc.
Stores these in the Utilities class as that
is where the conversions take place, however
SimpleSteem is the class that contains... | python | def global_props(self):
''' Retrieves the global properties
used to determine rates used for calculations
in converting steempower to vests etc.
Stores these in the Utilities class as that
is where the conversions take place, however
SimpleSteem is the class that contains... | [
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Stores these in the Utilities class as that
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.current_vote_value | def current_vote_value(self, **kwargs):
''' Ensures the needed variables are
created and set to defaults although
a variable number of variables are given.
'''
try:
kwargs.items()
except:
pass
else:
for key, value in kwargs.item... | python | def current_vote_value(self, **kwargs):
''' Ensures the needed variables are
created and set to defaults although
a variable number of variables are given.
'''
try:
kwargs.items()
except:
pass
else:
for key, value in kwargs.item... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.check_balances | def check_balances(self, account=None):
''' Fetches an account balance and makes
necessary conversions
'''
a = self.account(account)
if a is not False and a is not None:
self.sbdbal = Amount(a['sbd_balance']).amount
self.steembal = Amount(a['balance']).amo... | python | def check_balances(self, account=None):
''' Fetches an account balance and makes
necessary conversions
'''
a = self.account(account)
if a is not False and a is not None:
self.sbdbal = Amount(a['sbd_balance']).amount
self.steembal = Amount(a['balance']).amo... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.transfer_funds | def transfer_funds(self, to, amount, denom, msg):
''' Transfer SBD or STEEM to the given account
'''
try:
self.steem_instance().commit.transfer(to,
float(amount), denom, msg, self.mainaccount)
except Exception as e:
self.msg.error_message(e)
... | python | def transfer_funds(self, to, amount, denom, msg):
''' Transfer SBD or STEEM to the given account
'''
try:
self.steem_instance().commit.transfer(to,
float(amount), denom, msg, self.mainaccount)
except Exception as e:
self.msg.error_message(e)
... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.get_my_history | def get_my_history(self, account=None, limit=10000):
''' Fetches the account history from
most recent back
'''
if not account:
account = self.mainaccount
try:
h = self.steem_instance().get_account_history(
account, -1, limit)
except... | python | def get_my_history(self, account=None, limit=10000):
''' Fetches the account history from
most recent back
'''
if not account:
account = self.mainaccount
try:
h = self.steem_instance().get_account_history(
account, -1, limit)
except... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.post | def post(self, title, body, permlink, tags):
''' Used for creating a main post
to an account's blog. Waits 20 seconds
after posting as that is the required
amount of time between posting.
'''
for num_of_retries in range(default.max_retry):
try:
... | python | def post(self, title, body, permlink, tags):
''' Used for creating a main post
to an account's blog. Waits 20 seconds
after posting as that is the required
amount of time between posting.
'''
for num_of_retries in range(default.max_retry):
try:
... | [
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ArtoLabs/SimpleSteem | simplesteem/simplesteem.py | SimpleSteem.reply | def reply(self, permlink, msgbody):
''' Used for creating a reply to a
post. Waits 20 seconds
after posting as that is the required
amount of time between posting.
'''
for num_of_retries in range(default.max_retry):
try:
self.steem_instance(... | python | def reply(self, permlink, msgbody):
''' Used for creating a reply to a
post. Waits 20 seconds
after posting as that is the required
amount of time between posting.
'''
for num_of_retries in range(default.max_retry):
try:
self.steem_instance(... | [
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