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totalgood/pugnlp | src/pugnlp/util.py | sort_strings | def sort_strings(strings, sort_order=None, reverse=False, case_sensitive=False, sort_order_first=True):
"""Sort a list of strings according to the provided sorted list of string prefixes
TODO:
- Provide an option to use `.startswith()` rather than a fixed prefix length (will be much slower)
Argume... | python | def sort_strings(strings, sort_order=None, reverse=False, case_sensitive=False, sort_order_first=True):
"""Sort a list of strings according to the provided sorted list of string prefixes
TODO:
- Provide an option to use `.startswith()` rather than a fixed prefix length (will be much slower)
Argume... | [
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totalgood/pugnlp | src/pugnlp/util.py | clean_field_dict | def clean_field_dict(field_dict, cleaner=str.strip, time_zone=None):
r"""Normalize field values by stripping whitespace from strings, localizing datetimes to a timezone, etc
>>> (sorted(clean_field_dict({'_state': object(), 'x': 1, 'y': "\t Wash Me! \n" }).items()) ==
... [('x', 1), ('y', 'Wash Me!')])
... | python | def clean_field_dict(field_dict, cleaner=str.strip, time_zone=None):
r"""Normalize field values by stripping whitespace from strings, localizing datetimes to a timezone, etc
>>> (sorted(clean_field_dict({'_state': object(), 'x': 1, 'y': "\t Wash Me! \n" }).items()) ==
... [('x', 1), ('y', 'Wash Me!')])
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totalgood/pugnlp | src/pugnlp/util.py | generate_tuple_batches | def generate_tuple_batches(qs, batch_len=1):
"""Iterate through a queryset in batches of length `batch_len`
>>> [batch for batch in generate_tuple_batches(range(7), 3)]
[(0, 1, 2), (3, 4, 5), (6,)]
"""
num_items, batch = 0, []
for item in qs:
if num_items >= batch_len:
yield... | python | def generate_tuple_batches(qs, batch_len=1):
"""Iterate through a queryset in batches of length `batch_len`
>>> [batch for batch in generate_tuple_batches(range(7), 3)]
[(0, 1, 2), (3, 4, 5), (6,)]
"""
num_items, batch = 0, []
for item in qs:
if num_items >= batch_len:
yield... | [
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totalgood/pugnlp | src/pugnlp/util.py | find_count_label | def find_count_label(d):
"""Find the member of a set that means "count" or "frequency" or "probability" or "number of occurrences".
"""
for name in COUNT_NAMES:
if name in d:
return name
for name in COUNT_NAMES:
if str(name).lower() in d:
return name | python | def find_count_label(d):
"""Find the member of a set that means "count" or "frequency" or "probability" or "number of occurrences".
"""
for name in COUNT_NAMES:
if name in d:
return name
for name in COUNT_NAMES:
if str(name).lower() in d:
return name | [
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totalgood/pugnlp | src/pugnlp/util.py | fuzzy_get_value | def fuzzy_get_value(obj, approximate_key, default=None, **kwargs):
""" Like fuzzy_get, but assume the obj is dict-like and return the value without the key
Notes:
Argument order is in reverse order relative to `fuzzywuzzy.process.extractOne()`
but in the same order as get(self, key) method on dic... | python | def fuzzy_get_value(obj, approximate_key, default=None, **kwargs):
""" Like fuzzy_get, but assume the obj is dict-like and return the value without the key
Notes:
Argument order is in reverse order relative to `fuzzywuzzy.process.extractOne()`
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totalgood/pugnlp | src/pugnlp/util.py | joined_seq | def joined_seq(seq, sep=None):
r"""Join a sequence into a tuple or a concatenated string
>>> joined_seq(range(3), ', ')
'0, 1, 2'
>>> joined_seq([1, 2, 3])
(1, 2, 3)
"""
joined_seq = tuple(seq)
if isinstance(sep, basestring):
joined_seq = sep.join(str(item) for item in joined_se... | python | def joined_seq(seq, sep=None):
r"""Join a sequence into a tuple or a concatenated string
>>> joined_seq(range(3), ', ')
'0, 1, 2'
>>> joined_seq([1, 2, 3])
(1, 2, 3)
"""
joined_seq = tuple(seq)
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totalgood/pugnlp | src/pugnlp/util.py | dos_from_table | def dos_from_table(table, header=None):
"""Produce dictionary of sequences from sequence of sequences, optionally with a header "row".
>>> dos_from_table([['hello', 'world'], [1, 2], [3,4]]) == {'hello': [1, 3], 'world': [2, 4]}
True
"""
start_row = 0
if not table:
return table
if n... | python | def dos_from_table(table, header=None):
"""Produce dictionary of sequences from sequence of sequences, optionally with a header "row".
>>> dos_from_table([['hello', 'world'], [1, 2], [3,4]]) == {'hello': [1, 3], 'world': [2, 4]}
True
"""
start_row = 0
if not table:
return table
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totalgood/pugnlp | src/pugnlp/util.py | transposed_lists | def transposed_lists(list_of_lists, default=None):
"""Like `numpy.transposed`, but allows uneven row lengths
Uneven lengths will affect the order of the elements in the rows of the transposed lists
>>> transposed_lists([[1, 2], [3, 4, 5], [6]])
[[1, 3, 6], [2, 4], [5]]
>>> transposed_lists(transpo... | python | def transposed_lists(list_of_lists, default=None):
"""Like `numpy.transposed`, but allows uneven row lengths
Uneven lengths will affect the order of the elements in the rows of the transposed lists
>>> transposed_lists([[1, 2], [3, 4, 5], [6]])
[[1, 3, 6], [2, 4], [5]]
>>> transposed_lists(transpo... | [
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>>> transposed_lists([[1, 2], [3, 4, 5], [6]])
[[1, 3, 6], [2, 4], [5]]
>>> transposed_lists(transposed_lists([[], [1, 2, 3], [4]]))
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totalgood/pugnlp | src/pugnlp/util.py | hist_from_counts | def hist_from_counts(counts, normalize=False, cumulative=False, to_str=False, sep=',', min_bin=None, max_bin=None):
"""Compute an emprical histogram, PMF or CDF in a list of lists
TESTME: compare results to hist_from_values_list and hist_from_float_values_list
"""
counters = [dict((i, c)for i, c in enu... | python | def hist_from_counts(counts, normalize=False, cumulative=False, to_str=False, sep=',', min_bin=None, max_bin=None):
"""Compute an emprical histogram, PMF or CDF in a list of lists
TESTME: compare results to hist_from_values_list and hist_from_float_values_list
"""
counters = [dict((i, c)for i, c in enu... | [
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totalgood/pugnlp | src/pugnlp/util.py | get_similar | def get_similar(obj, labels, default=None, min_similarity=0.5):
"""Similar to fuzzy_get, but allows non-string keys and a list of possible keys
Searches attributes in addition to keys and indexes to find the closest match.
See Also:
`fuzzy_get`
"""
raise NotImplementedError(
"Unfi... | python | def get_similar(obj, labels, default=None, min_similarity=0.5):
"""Similar to fuzzy_get, but allows non-string keys and a list of possible keys
Searches attributes in addition to keys and indexes to find the closest match.
See Also:
`fuzzy_get`
"""
raise NotImplementedError(
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totalgood/pugnlp | src/pugnlp/util.py | update_file_ext | def update_file_ext(filename, ext='txt', sep='.'):
r"""Force the file or path str to end with the indicated extension
Note: a dot (".") is assumed to delimit the extension
>>> from __future__ import unicode_literals
>>> update_file_ext('/home/hobs/extremofile', 'bac')
'/home/hobs/extremofile.bac'
... | python | def update_file_ext(filename, ext='txt', sep='.'):
r"""Force the file or path str to end with the indicated extension
Note: a dot (".") is assumed to delimit the extension
>>> from __future__ import unicode_literals
>>> update_file_ext('/home/hobs/extremofile', 'bac')
'/home/hobs/extremofile.bac'
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totalgood/pugnlp | src/pugnlp/util.py | transcode | def transcode(infile, outfile=None, incoding="shift-jis", outcoding="utf-8"):
"""Change encoding of text file"""
if not outfile:
outfile = os.path.basename(infile) + '.utf8'
with codecs.open(infile, "rb", incoding) as fpin:
with codecs.open(outfile, "wb", outcoding) as fpout:
fpo... | python | def transcode(infile, outfile=None, incoding="shift-jis", outcoding="utf-8"):
"""Change encoding of text file"""
if not outfile:
outfile = os.path.basename(infile) + '.utf8'
with codecs.open(infile, "rb", incoding) as fpin:
with codecs.open(outfile, "wb", outcoding) as fpout:
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totalgood/pugnlp | src/pugnlp/util.py | dict2obj | def dict2obj(d):
"""Convert a dict to an object or namespace
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> obj = dict2obj(d)
>>> obj.b.c
2
>>> obj.d
['hi', {'foo': 'bar'}]
>>> d = {'a': 1, 'b': {'c': 2}, 'd': [("hi", {'foo': "bar"})]}
>>> obj = dict2obj(d)
>>... | python | def dict2obj(d):
"""Convert a dict to an object or namespace
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> obj = dict2obj(d)
>>> obj.b.c
2
>>> obj.d
['hi', {'foo': 'bar'}]
>>> d = {'a': 1, 'b': {'c': 2}, 'd': [("hi", {'foo': "bar"})]}
>>> obj = dict2obj(d)
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>>> obj = dict2obj(d)
>>> obj.d.hi.foo
'bar' | [
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totalgood/pugnlp | src/pugnlp/util.py | int_pair | def int_pair(s, default=(0, None)):
"""Return the digits to either side of a single non-digit character as a 2-tuple of integers
>>> int_pair('90210-007')
(90210, 7)
>>> int_pair('04321.0123')
(4321, 123)
"""
s = re.split(r'[^0-9]+', str(s).strip())
if len(s) and len(s[0]):
if l... | python | def int_pair(s, default=(0, None)):
"""Return the digits to either side of a single non-digit character as a 2-tuple of integers
>>> int_pair('90210-007')
(90210, 7)
>>> int_pair('04321.0123')
(4321, 123)
"""
s = re.split(r'[^0-9]+', str(s).strip())
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totalgood/pugnlp | src/pugnlp/util.py | make_float | def make_float(s, default='', ignore_commas=True):
r"""Coerce a string into a float
>>> make_float('12,345')
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>>> make_float('12.345')
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>>> make_float('1+2')
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4... | python | def make_float(s, default='', ignore_commas=True):
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totalgood/pugnlp | src/pugnlp/util.py | normalize_names | def normalize_names(names):
"""Coerce a string or nested list of strings into a flat list of strings."""
if isinstance(names, basestring):
names = names.split(',')
names = listify(names)
return [str(name).strip() for name in names] | python | def normalize_names(names):
"""Coerce a string or nested list of strings into a flat list of strings."""
if isinstance(names, basestring):
names = names.split(',')
names = listify(names)
return [str(name).strip() for name in names] | [
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totalgood/pugnlp | src/pugnlp/util.py | normalize_serial_number | def normalize_serial_number(sn,
max_length=None, left_fill='0', right_fill=str(), blank=str(),
valid_chars=' -0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ',
invalid_chars=None,
strip_whitesp... | python | def normalize_serial_number(sn,
max_length=None, left_fill='0', right_fill=str(), blank=str(),
valid_chars=' -0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ',
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totalgood/pugnlp | src/pugnlp/util.py | strip_HTML | def strip_HTML(s):
"""Simple, clumsy, slow HTML tag stripper"""
result = ''
total = 0
for c in s:
if c == '<':
total = 1
elif c == '>':
total = 0
result += ' '
elif total == 0:
result += c
return result | python | def strip_HTML(s):
"""Simple, clumsy, slow HTML tag stripper"""
result = ''
total = 0
for c in s:
if c == '<':
total = 1
elif c == '>':
total = 0
result += ' '
elif total == 0:
result += c
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totalgood/pugnlp | src/pugnlp/util.py | tabulate | def tabulate(lol, headers, eol='\n'):
"""Use the pypi tabulate package instead!"""
yield '| %s |' % ' | '.join(headers) + eol
yield '| %s:|' % ':| '.join(['-' * len(w) for w in headers]) + eol
for row in lol:
yield '| %s |' % ' | '.join(str(c) for c in row) + eol | python | def tabulate(lol, headers, eol='\n'):
"""Use the pypi tabulate package instead!"""
yield '| %s |' % ' | '.join(headers) + eol
yield '| %s:|' % ':| '.join(['-' * len(w) for w in headers]) + eol
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totalgood/pugnlp | src/pugnlp/util.py | listify | def listify(values, N=1, delim=None):
"""Return an N-length list, with elements values, extrapolating as necessary.
>>> listify("don't split into characters")
["don't split into characters"]
>>> listify("len = 3", 3)
['len = 3', 'len = 3', 'len = 3']
>>> listify("But split on a delimeter, if re... | python | def listify(values, N=1, delim=None):
"""Return an N-length list, with elements values, extrapolating as necessary.
>>> listify("don't split into characters")
["don't split into characters"]
>>> listify("len = 3", 3)
['len = 3', 'len = 3', 'len = 3']
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totalgood/pugnlp | src/pugnlp/util.py | unlistify | def unlistify(n, depth=1, typ=list, get=None):
"""Return the desired element in a list ignoring the rest.
>>> unlistify([1,2,3])
1
>>> unlistify([1,[4, 5, 6],3], get=1)
[4, 5, 6]
>>> unlistify([1,[4, 5, 6],3], depth=2, get=1)
5
>>> unlistify([1,(4, 5, 6),3], depth=2, get=1)
(4, 5, 6... | python | def unlistify(n, depth=1, typ=list, get=None):
"""Return the desired element in a list ignoring the rest.
>>> unlistify([1,2,3])
1
>>> unlistify([1,[4, 5, 6],3], get=1)
[4, 5, 6]
>>> unlistify([1,[4, 5, 6],3], depth=2, get=1)
5
>>> unlistify([1,(4, 5, 6),3], depth=2, get=1)
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totalgood/pugnlp | src/pugnlp/util.py | strip_keys | def strip_keys(d, nones=False, depth=0):
r"""Strip whitespace from all dictionary keys, to the depth indicated
>>> strip_keys({' a': ' a', ' b\t c ': {'d e ': 'd e '}}) == {'a': ' a', 'b\t c': {'d e ': 'd e '}}
True
>>> strip_keys({' a': ' a', ' b\t c ': {'d e ': 'd e '}}, depth=100) == {'a': ' a... | python | def strip_keys(d, nones=False, depth=0):
r"""Strip whitespace from all dictionary keys, to the depth indicated
>>> strip_keys({' a': ' a', ' b\t c ': {'d e ': 'd e '}}) == {'a': ' a', 'b\t c': {'d e ': 'd e '}}
True
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totalgood/pugnlp | src/pugnlp/util.py | get_table_from_csv | def get_table_from_csv(filename='ssg_report_aarons_returns.csv', delimiter=',', dos=False):
"""Dictionary of sequences from CSV file"""
table = []
with open(filename, 'rb') as f:
reader = csv.reader(f, dialect='excel', delimiter=delimiter)
for row in reader:
table += [row]
if... | python | def get_table_from_csv(filename='ssg_report_aarons_returns.csv', delimiter=',', dos=False):
"""Dictionary of sequences from CSV file"""
table = []
with open(filename, 'rb') as f:
reader = csv.reader(f, dialect='excel', delimiter=delimiter)
for row in reader:
table += [row]
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totalgood/pugnlp | src/pugnlp/util.py | shorten | def shorten(s, max_len=16):
"""Attempt to shorten a phrase by deleting words at the end of the phrase
>>> shorten('Hello World!')
'Hello World'
>>> shorten("Hello World! I'll talk your ear off!", 15)
'Hello World'
"""
short = s
words = [abbreviate(word) for word in get_words(s)]
for... | python | def shorten(s, max_len=16):
"""Attempt to shorten a phrase by deleting words at the end of the phrase
>>> shorten('Hello World!')
'Hello World'
>>> shorten("Hello World! I'll talk your ear off!", 15)
'Hello World'
"""
short = s
words = [abbreviate(word) for word in get_words(s)]
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'Hello World' | [
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totalgood/pugnlp | src/pugnlp/util.py | truncate | def truncate(s, max_len=20, ellipsis='...'):
r"""Return string at most `max_len` characters or sequence elments appended with the `ellipsis` characters
>>> truncate(OrderedDict(zip(list('ABCDEFGH'), range(8))), 1)
"{'A': 0..."
>>> truncate(list(range(5)), 3)
'[0, 1, 2...'
>>> truncate(np.arange... | python | def truncate(s, max_len=20, ellipsis='...'):
r"""Return string at most `max_len` characters or sequence elments appended with the `ellipsis` characters
>>> truncate(OrderedDict(zip(list('ABCDEFGH'), range(8))), 1)
"{'A': 0..."
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'[0, 1, 2...'
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totalgood/pugnlp | src/pugnlp/util.py | slash_product | def slash_product(string_or_seq, slash='/', space=' '):
"""Return a list of all possible meanings of a phrase containing slashes
TODO:
- Code is not in standard Sedgewick recursion form
- Simplify by removing one of the recursive calls?
- Simplify by using a list comprehension?
# d... | python | def slash_product(string_or_seq, slash='/', space=' '):
"""Return a list of all possible meanings of a phrase containing slashes
TODO:
- Code is not in standard Sedgewick recursion form
- Simplify by removing one of the recursive calls?
- Simplify by using a list comprehension?
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TODO:
- Code is not in standard Sedgewick recursion form
- Simplify by removing one of the recursive calls?
- Simplify by using a list comprehension?
# doctest: +NORMALIZE_WHITESPACE
>>> slash_product("The challe... | [
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DarkEnergySurvey/ugali | ugali/scratch/position_angle.py | create_header | def create_header(coord, radius, proj='ZEA', npix=30):
""" Create a header a new image """
gal = coord.name == 'galactic'
values = [
["NAXIS", 2, ],
["NAXIS1", npix, ],
["NAXIS2", npix, ],
["CTYPE1", 'GLON-%s'%proj if gal else 'RA---%... | python | def create_header(coord, radius, proj='ZEA', npix=30):
""" Create a header a new image """
gal = coord.name == 'galactic'
values = [
["NAXIS", 2, ],
["NAXIS1", npix, ],
["NAXIS2", npix, ],
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totalgood/pugnlp | src/pugnlp/penn_treebank_tokenizer.py | word_tokenize | def word_tokenize(text):
"""
Split string `text` into word tokens using the Penn Treebank rules
"""
for (regexp, replacement) in RULES1:
text = sub(regexp, replacement, text)
# add extra space to make things easier
text = " " + text + " "
for (regexp, replacement) in RULES2:
... | python | def word_tokenize(text):
"""
Split string `text` into word tokens using the Penn Treebank rules
"""
for (regexp, replacement) in RULES1:
text = sub(regexp, replacement, text)
# add extra space to make things easier
text = " " + text + " "
for (regexp, replacement) in RULES2:
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hootnot/postcode-api-wrapper | postcodepy/postcodepy.py | EndpointsMixin.get_postcodedata | def get_postcodedata(self, postcode, nr, addition="", **params):
"""get_postcodedata - fetch information for 'postcode'.
Parameters
----------
postcode : string
The full (dutch) postcode
nr : int
The housenumber
addition : string (optional)
... | python | def get_postcodedata(self, postcode, nr, addition="", **params):
"""get_postcodedata - fetch information for 'postcode'.
Parameters
----------
postcode : string
The full (dutch) postcode
nr : int
The housenumber
addition : string (optional)
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hootnot/postcode-api-wrapper | postcodepy/postcodepy.py | EndpointsMixin.get_signalcheck | def get_signalcheck(self, sar, **params):
"""get_signalcheck - perform a signal check.
Parameters
----------
sar : dict
signal-api-request specified as a dictionary of parameters.
All of these parameters are optional. For details
check https://api.po... | python | def get_signalcheck(self, sar, **params):
"""get_signalcheck - perform a signal check.
Parameters
----------
sar : dict
signal-api-request specified as a dictionary of parameters.
All of these parameters are optional. For details
check https://api.po... | [
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hootnot/postcode-api-wrapper | postcodepy/postcodepy.py | API.__request | def __request(self, endpoint, method='GET', params=None, convJSON=False):
"""request - Returns dict of response from postcode.nl API.
This method is called only by the EndpointMixin methods.
"""
url = '%s/%s' % (self.api_url, endpoint)
method = method.lower()
params = p... | python | def __request(self, endpoint, method='GET', params=None, convJSON=False):
"""request - Returns dict of response from postcode.nl API.
This method is called only by the EndpointMixin methods.
"""
url = '%s/%s' % (self.api_url, endpoint)
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totalgood/pugnlp | src/pugnlp/plots.py | regression_and_plot | def regression_and_plot(x, y=None):
"""
Fit a line to the x, y data supplied and plot it along with teh raw samples
>>> age = [25, 26, 33, 29, 27, 21, 26, 35, 21, 37, 21, 38, 18, 19, 36, 30, 29, 24, 24, 36, 36, 27,
... 33, 23, 21, 26, 27, 27, 24, 26, 25, 24, 22, 25, 40, 39, 19, 31, 33, 30, 33, 2... | python | def regression_and_plot(x, y=None):
"""
Fit a line to the x, y data supplied and plot it along with teh raw samples
>>> age = [25, 26, 33, 29, 27, 21, 26, 35, 21, 37, 21, 38, 18, 19, 36, 30, 29, 24, 24, 36, 36, 27,
... 33, 23, 21, 26, 27, 27, 24, 26, 25, 24, 22, 25, 40, 39, 19, 31, 33, 30, 33, 2... | [
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totalgood/pugnlp | src/pugnlp/plots.py | scatmat | def scatmat(df, category=None, colors='rgob',
num_plots=4, num_topics=100, num_columns=4,
show=False, block=False, data_path=DATA_PATH, save=False, verbose=1):
"""Scatter plot with colored markers depending on the discrete values in a "category" column
FIXME: empty plots that dont go aw... | python | def scatmat(df, category=None, colors='rgob',
num_plots=4, num_topics=100, num_columns=4,
show=False, block=False, data_path=DATA_PATH, save=False, verbose=1):
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totalgood/pugnlp | src/pugnlp/plots.py | point_cloud | def point_cloud(df, columns=[0, 1, 2]):
"""3-D Point cloud for plotting things like mesh models of horses ;)"""
df = df if isinstance(df, pd.DataFrame) else pd.DataFrame(df)
if not all(c in df.columns for c in columns):
columns = list(df.columns)[:3]
fig = plt.figure()
ax = fig.add_subplot(... | python | def point_cloud(df, columns=[0, 1, 2]):
"""3-D Point cloud for plotting things like mesh models of horses ;)"""
df = df if isinstance(df, pd.DataFrame) else pd.DataFrame(df)
if not all(c in df.columns for c in columns):
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totalgood/pugnlp | src/pugnlp/plots.py | ColorMap.show | def show(self, block=False):
""" Display the last image drawn """
try:
plt.show(block=block)
except ValueError:
plt.show() | python | def show(self, block=False):
""" Display the last image drawn """
try:
plt.show(block=block)
except ValueError:
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totalgood/pugnlp | src/pugnlp/plots.py | ColorMap.save | def save(self, filename):
""" save colormap to file"""
plt.savefig(filename, fig=self.fig, facecolor='black', edgecolor='black') | python | def save(self, filename):
""" save colormap to file"""
plt.savefig(filename, fig=self.fig, facecolor='black', edgecolor='black') | [
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DarkEnergySurvey/ugali | ugali/analysis/model.py | Model.getp | def getp(self, name):
"""
Get the named parameter.
Parameters
----------
name : string
The parameter name.
Returns
-------
param :
The parameter object.
"""
name = self._mapping.get(name,name)
return self... | python | def getp(self, name):
"""
Get the named parameter.
Parameters
----------
name : string
The parameter name.
Returns
-------
param :
The parameter object.
"""
name = self._mapping.get(name,name)
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DarkEnergySurvey/ugali | ugali/analysis/color_lut.py | readColorLUT | def readColorLUT(infile, distance_modulus, mag_1, mag_2, mag_err_1, mag_err_2):
"""
Take in a color look-up table and return the signal color evaluated for each object.
Consider making the argument a Catalog object rather than magnitudes and uncertainties.
"""
reader = pyfits.open(infile)
dist... | python | def readColorLUT(infile, distance_modulus, mag_1, mag_2, mag_err_1, mag_err_2):
"""
Take in a color look-up table and return the signal color evaluated for each object.
Consider making the argument a Catalog object rather than magnitudes and uncertainties.
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reader = pyfits.open(infile)
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consbio/ncdjango | ncdjango/utils.py | auto_memoize | def auto_memoize(func):
"""
Based on django.util.functional.memoize. Automatically memoizes instace methods for the lifespan of an object.
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consbio/ncdjango | ncdjango/utils.py | best_fit | def best_fit(li, value):
"""For a sorted list li, returns the closest item to value"""
index = min(bisect_left(li, value), len(li) - 1)
if index in (0, len(li)):
return index
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return index
else:
return index-1 | python | def best_fit(li, value):
"""For a sorted list li, returns the closest item to value"""
index = min(bisect_left(li, value), len(li) - 1)
if index in (0, len(li)):
return index
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consbio/ncdjango | ncdjango/utils.py | proj4_to_epsg | def proj4_to_epsg(projection):
"""Attempts to convert a PROJ4 projection object to an EPSG code and returns None if conversion fails"""
def make_definition(value):
return {x.strip().lower() for x in value.split('+') if x}
# Use the EPSG in the definition if available
match = EPSG_RE.search(pro... | python | def proj4_to_epsg(projection):
"""Attempts to convert a PROJ4 projection object to an EPSG code and returns None if conversion fails"""
def make_definition(value):
return {x.strip().lower() for x in value.split('+') if x}
# Use the EPSG in the definition if available
match = EPSG_RE.search(pro... | [
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consbio/ncdjango | ncdjango/utils.py | wkt_to_proj4 | def wkt_to_proj4(wkt):
"""Converts a well-known text string to a pyproj.Proj object"""
srs = osgeo.osr.SpatialReference()
srs.ImportFromWkt(wkt)
return pyproj.Proj(str(srs.ExportToProj4())) | python | def wkt_to_proj4(wkt):
"""Converts a well-known text string to a pyproj.Proj object"""
srs = osgeo.osr.SpatialReference()
srs.ImportFromWkt(wkt)
return pyproj.Proj(str(srs.ExportToProj4())) | [
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consbio/ncdjango | ncdjango/utils.py | proj4_to_wkt | def proj4_to_wkt(projection):
"""Converts a pyproj.Proj object to a well-known text string"""
srs = osgeo.osr.SpatialReference()
srs.ImportFromProj4(projection.srs)
return srs.ExportToWkt() | python | def proj4_to_wkt(projection):
"""Converts a pyproj.Proj object to a well-known text string"""
srs = osgeo.osr.SpatialReference()
srs.ImportFromProj4(projection.srs)
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consbio/ncdjango | ncdjango/utils.py | project_geometry | def project_geometry(geometry, source, target):
"""Projects a shapely geometry object from the source to the target projection."""
project = partial(
pyproj.transform,
source,
target
)
return transform(project, geometry) | python | def project_geometry(geometry, source, target):
"""Projects a shapely geometry object from the source to the target projection."""
project = partial(
pyproj.transform,
source,
target
)
return transform(project, geometry) | [
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DarkEnergySurvey/ugali | ugali/utils/config.py | Config._load | def _load(self, config):
""" Load this config from an existing config
Parameters:
-----------
config : filename, config object, or dict to load
Returns:
--------
params : configuration parameters
"""
if isstring(config):
self.filenam... | python | def _load(self, config):
""" Load this config from an existing config
Parameters:
-----------
config : filename, config object, or dict to load
Returns:
--------
params : configuration parameters
"""
if isstring(config):
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DarkEnergySurvey/ugali | ugali/utils/config.py | Config._validate | def _validate(self):
""" Enforce some structure to the config file """
# This could be done with a default config
# Check that specific keys exist
sections = odict([
('catalog',['dirname','basename',
'lon_field','lat_field','objid_field',
... | python | def _validate(self):
""" Enforce some structure to the config file """
# This could be done with a default config
# Check that specific keys exist
sections = odict([
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DarkEnergySurvey/ugali | ugali/utils/config.py | Config._formatFilepaths | def _formatFilepaths(self):
"""
Join dirnames and filenames from config.
"""
likedir=self['output']['likedir']
self.likefile = join(likedir,self['output']['likefile'])
self.mergefile = join(likedir,self['output']['mergefile'])
self.roifile = join(likedir,self['... | python | def _formatFilepaths(self):
"""
Join dirnames and filenames from config.
"""
likedir=self['output']['likedir']
self.likefile = join(likedir,self['output']['likefile'])
self.mergefile = join(likedir,self['output']['mergefile'])
self.roifile = join(likedir,self['... | [
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DarkEnergySurvey/ugali | ugali/utils/config.py | Config.write | def write(self, filename):
"""
Write a copy of this config object.
Parameters:
-----------
outfile : output filename
Returns:
--------
None
"""
ext = os.path.splitext(filename)[1]
writer = open(filename, 'w')
if ex... | python | def write(self, filename):
"""
Write a copy of this config object.
Parameters:
-----------
outfile : output filename
Returns:
--------
None
"""
ext = os.path.splitext(filename)[1]
writer = open(filename, 'w')
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DarkEnergySurvey/ugali | ugali/utils/config.py | Config.getFilenames | def getFilenames(self,pixels=None):
"""
Return the requested filenames.
Parameters:
-----------
pixels : requeseted pixels
Returns:
--------
filenames : recarray
"""
logger.debug("Getting filenames...")
if pixels is None:
... | python | def getFilenames(self,pixels=None):
"""
Return the requested filenames.
Parameters:
-----------
pixels : requeseted pixels
Returns:
--------
filenames : recarray
"""
logger.debug("Getting filenames...")
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | superpixel | def superpixel(subpix, nside_subpix, nside_superpix):
"""
Return the indices of the super-pixels which contain each of the sub-pixels.
"""
if nside_subpix==nside_superpix: return subpix
theta, phi = hp.pix2ang(nside_subpix, subpix)
return hp.ang2pix(nside_superpix, theta, phi) | python | def superpixel(subpix, nside_subpix, nside_superpix):
"""
Return the indices of the super-pixels which contain each of the sub-pixels.
"""
if nside_subpix==nside_superpix: return subpix
theta, phi = hp.pix2ang(nside_subpix, subpix)
return hp.ang2pix(nside_superpix, theta, phi) | [
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | ud_grade_ipix | def ud_grade_ipix(ipix, nside_in, nside_out, nest=False):
"""
Upgrade or degrade resolution of a pixel list.
Parameters:
-----------
ipix:array-like
the input pixel(s)
nside_in:int
the nside of the input pixel(s)
nside_out:int
the desired nside of the output pixel(s)
ord... | python | def ud_grade_ipix(ipix, nside_in, nside_out, nest=False):
"""
Upgrade or degrade resolution of a pixel list.
Parameters:
-----------
ipix:array-like
the input pixel(s)
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the nside of the input pixel(s)
nside_out:int
the desired nside of the output pixel(s)
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | index_pix_in_pixels | def index_pix_in_pixels(pix,pixels,sort=False,outside=-1):
"""
Find the indices of a set of pixels into another set of pixels.
!!! ASSUMES SORTED PIXELS !!!
Parameters:
-----------
pix : set of search pixels
pixels : set of reference pixels
Returns:
--------
index : index ... | python | def index_pix_in_pixels(pix,pixels,sort=False,outside=-1):
"""
Find the indices of a set of pixels into another set of pixels.
!!! ASSUMES SORTED PIXELS !!!
Parameters:
-----------
pix : set of search pixels
pixels : set of reference pixels
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--------
index : index ... | [
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | index_lonlat_in_pixels | def index_lonlat_in_pixels(lon,lat,pixels,nside,sort=False,outside=-1):
"""
Find the indices of a set of angles into a set of pixels
Parameters:
-----------
pix : set of search pixels
pixels : set of reference pixels
Returns:
--------
index : index into the reference pixels
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"""
Find the indices of a set of angles into a set of pixels
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-----------
pix : set of search pixels
pixels : set of reference pixels
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--------
index : index into the reference pixels
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | header_odict | def header_odict(nside,nest=False,coord=None, partial=True):
"""Mimic the healpy header keywords."""
hdr = odict([])
hdr['PIXTYPE']=odict([('name','PIXTYPE'),
('value','HEALPIX'),
('comment','HEALPIX pixelisation')])
ordering = 'NEST' if nest else 'RI... | python | def header_odict(nside,nest=False,coord=None, partial=True):
"""Mimic the healpy header keywords."""
hdr = odict([])
hdr['PIXTYPE']=odict([('name','PIXTYPE'),
('value','HEALPIX'),
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | write_partial_map | def write_partial_map(filename, data, nside, coord=None, nest=False,
header=None,dtype=None,**kwargs):
"""
Partial HEALPix maps are used to efficiently store maps of the sky by only
writing out the pixels that contain data.
Three-dimensional data can be saved by supplying a distan... | python | def write_partial_map(filename, data, nside, coord=None, nest=False,
header=None,dtype=None,**kwargs):
"""
Partial HEALPix maps are used to efficiently store maps of the sky by only
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DarkEnergySurvey/ugali | ugali/utils/healpix.py | merge_likelihood_headers | def merge_likelihood_headers(filenames, outfile):
"""
Merge header information from likelihood files.
Parameters:
-----------
filenames : input filenames
oufile : the merged file to write
Returns:
--------
data : the data being written
"""
filenames = np.atleas... | python | def merge_likelihood_headers(filenames, outfile):
"""
Merge header information from likelihood files.
Parameters:
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filenames : input filenames
oufile : the merged file to write
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data : the data being written
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DarkEnergySurvey/ugali | ugali/pipeline/run_05.0_followup.py | do_results | def do_results(args):
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DarkEnergySurvey/ugali | ugali/pipeline/run_05.0_followup.py | do_membership | def do_membership(args):
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DarkEnergySurvey/ugali | ugali/pipeline/run_05.0_followup.py | do_plot | def do_plot(args):
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totalgood/pugnlp | src/pugnlp/segmentation.py | generate_lines | def generate_lines(text, ext=['.txt', '.md', '.rst', '.asciidoc', '.asc']):
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alphagov/performanceplatform-collector | performanceplatform/collector/gcloud/aggregate.py | get_cumulative_spend | def get_cumulative_spend(key):
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Get the sum of spending for this category up to and including the given
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"""
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Get the sum of spending for this category up to and including the given
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"""
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DarkEnergySurvey/ugali | ugali/observation/roi.py | ROI.plot | def plot(self, value=None, pixel=None):
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"""
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"""
Plot the ROI
"""
# DEPRECATED
import ugali.utils.plotting
map_roi = np.array(hp.UNSEEN \
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DarkEnergySurvey/ugali | ugali/observation/roi.py | ROI.getCatalogPixels | def getCatalogPixels(self):
"""
Return the catalog pixels spanned by this ROI.
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filenames = self.config.getFilenames()
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nside_pixel = self.config.params['coords']['nside_pixel']
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"""
Return the catalog pixels spanned by this ROI.
"""
filenames = self.config.getFilenames()
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stevearc/dynamo3 | dynamo3/fields.py | BaseIndex.schema | def schema(self, hash_key):
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Create the index schema
Parameters
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hash_key : :class:`~.DynamoKey`
The hash key of the table
"""
key_schema = [hash_key.hash_schema()]
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Create the index schema
Parameters
----------
hash_key : :class:`~.DynamoKey`
The hash key of the table
"""
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stevearc/dynamo3 | dynamo3/fields.py | GlobalIndex.schema | def schema(self):
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stevearc/dynamo3 | dynamo3/fields.py | Table.from_response | def from_response(cls, response):
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stevearc/dynamo3 | dynamo3/fields.py | IndexUpdate.serialize | def serialize(self):
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payload = self.extra['index'].schema()
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payload = {
'IndexName': self.index_name,
}
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... | python | def serialize(self):
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delicb/mvvm | mvvm.py | _Messenger.instance | def instance(cls, interval=5):
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Returns existing instance of messenger. If one does not exist it will
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Number of miliseconds that represents interval when messages will
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Note that this param... | python | def instance(cls, interval=5):
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Returns existing instance of messenger. If one does not exist it will
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delicb/mvvm | mvvm.py | _Messenger.send | def send(self, message, *args, **kwargs):
'''
Sends provided message to all listeners. Message is only added to
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:param Message message:
Message to send.
'''
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'''
Sends provided message to all listeners. Message is only added to
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Message to send.
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Adds hander for specified message.
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delicb/mvvm | mvvm.py | _Messenger.unsubscribe | def unsubscribe(self, message, handler):
'''
Removes handler from message listeners.
:param str message:
Name of message to unsubscribe handler from.
:param callable handler:
Callable that should be removed as handler for `message`.
'''
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delicb/mvvm | mvvm.py | _Messenger._execute | def _execute(self, sender, event_args):
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Event handler for timer that processes all queued messages.
'''
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'''
Event handler for timer that processes all queued messages.
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delicb/mvvm | mvvm.py | Signal.emit | def emit(self, *args, **kwargs):
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delicb/mvvm | mvvm.py | ViewModel.RaisePropertyChanged | def RaisePropertyChanged(self, property_name):
'''
Raises event that property value has changed for provided property name.
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Name of property whose value has changed.
'''
args = PropertyChangedEventArgs(property_name)
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totalgood/pugnlp | src/pugnlp/futil.py | walk_level | def walk_level(path, level=1):
"""Like os.walk, but takes `level` kwarg that indicates how deep the recursion will go.
Notes:
TODO: refactor `level`->`depth`
References:
http://stackoverflow.com/a/234329/623735
Args:
path (str): Root path to begin file tree traversal (walk)
... | python | def walk_level(path, level=1):
"""Like os.walk, but takes `level` kwarg that indicates how deep the recursion will go.
Notes:
TODO: refactor `level`->`depth`
References:
http://stackoverflow.com/a/234329/623735
Args:
path (str): Root path to begin file tree traversal (walk)
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totalgood/pugnlp | src/pugnlp/futil.py | get_stat | def get_stat(full_path):
"""Use python builtin equivalents to unix `stat` command and return dict containing stat data about a file"""
status = {}
status['size'] = os.path.getsize(full_path)
status['accessed'] = datetime.datetime.fromtimestamp(os.path.getatime(full_path))
status['modified'] = dateti... | python | def get_stat(full_path):
"""Use python builtin equivalents to unix `stat` command and return dict containing stat data about a file"""
status = {}
status['size'] = os.path.getsize(full_path)
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DarkEnergySurvey/ugali | ugali/preprocess/maglims.py | split | def split(config,dirname='split',force=False):
""" Take a pre-existing maglim map and divide it into
chunks consistent with the catalog pixels. """
config = Config(config)
filenames = config.getFilenames()
#healpix = filenames['pix'].compressed()
# Check that things are ok
basedir,basename... | python | def split(config,dirname='split',force=False):
""" Take a pre-existing maglim map and divide it into
chunks consistent with the catalog pixels. """
config = Config(config)
filenames = config.getFilenames()
#healpix = filenames['pix'].compressed()
# Check that things are ok
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DarkEnergySurvey/ugali | ugali/preprocess/maglims.py | Maglims.run | def run(self,field=None,simple=False,force=False):
"""
Loop through pixels containing catalog objects and calculate
the magnitude limit. This gets a bit convoluted due to all
the different pixel resolutions...
"""
if field is None: fields = [1,2]
else: ... | python | def run(self,field=None,simple=False,force=False):
"""
Loop through pixels containing catalog objects and calculate
the magnitude limit. This gets a bit convoluted due to all
the different pixel resolutions...
"""
if field is None: fields = [1,2]
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consbio/ncdjango | ncdjango/interfaces/arcgis/views.py | ArcGISMapServerMixin.get_variable_set | def get_variable_set(self, variable_set, data):
"""Filters the given variable set based on request parameters"""
if data.get('dynamic_layers'):
variable_set = [] # TODO
elif data.get('layers'):
op, layer_ids = data['layers'].split(':', 1)
op = op.lower()
... | python | def get_variable_set(self, variable_set, data):
"""Filters the given variable set based on request parameters"""
if data.get('dynamic_layers'):
variable_set = [] # TODO
elif data.get('layers'):
op, layer_ids = data['layers'].split(':', 1)
op = op.lower()
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consbio/ncdjango | ncdjango/interfaces/arcgis/views.py | ArcGISMapServerMixin.apply_time_to_configurations | def apply_time_to_configurations(self, configurations, data):
"""Applies the correct time index to configurations"""
time_value = None
if data.get('time'):
time_value = data['time']
# Only single time values are supported. For extents, just grab the first value
... | python | def apply_time_to_configurations(self, configurations, data):
"""Applies the correct time index to configurations"""
time_value = None
if data.get('time'):
time_value = data['time']
# Only single time values are supported. For extents, just grab the first value
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consbio/ncdjango | ncdjango/interfaces/arcgis/views.py | GetImageView._get_form_defaults | def _get_form_defaults(self):
"""Returns default values for the get image form"""
return {
'response_format': 'html',
'bbox': self.service.full_extent,
'size': '400,400',
'dpi': 200,
'image_projection': pyproj.Proj(str(self.service.projection)... | python | def _get_form_defaults(self):
"""Returns default values for the get image form"""
return {
'response_format': 'html',
'bbox': self.service.full_extent,
'size': '400,400',
'dpi': 200,
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consbio/ncdjango | ncdjango/interfaces/arcgis/views.py | GetImageView.get_render_configurations | def get_render_configurations(self, request, **kwargs):
"""Render image interface"""
data = self.process_form_data(self._get_form_defaults(), kwargs)
variable_set = self.get_variable_set(self.service.variable_set.order_by('index'), data)
base_config = ImageConfiguration(
ex... | python | def get_render_configurations(self, request, **kwargs):
"""Render image interface"""
data = self.process_form_data(self._get_form_defaults(), kwargs)
variable_set = self.get_variable_set(self.service.variable_set.order_by('index'), data)
base_config = ImageConfiguration(
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consbio/ncdjango | ncdjango/interfaces/arcgis/views.py | IdentifyView._get_form_defaults | def _get_form_defaults(self):
"""Returns default values for the identify form"""
return {
'response_format': 'html',
'geometry_type': 'esriGeometryPoint',
'projection': pyproj.Proj(str(self.service.projection)),
'return_geometry': True,
'maxim... | python | def _get_form_defaults(self):
"""Returns default values for the identify form"""
return {
'response_format': 'html',
'geometry_type': 'esriGeometryPoint',
'projection': pyproj.Proj(str(self.service.projection)),
'return_geometry': True,
'maxim... | [
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juju/theblues | theblues/terms.py | Terms.get_terms | def get_terms(self, name, revision=None):
""" Retrieve a specific term and condition.
@param name of the terms.
@param revision of the terms,
if none provided it will return the latest.
@return The list of terms.
@raise ServerError
"""
url = '{}ter... | python | def get_terms(self, name, revision=None):
""" Retrieve a specific term and condition.
@param name of the terms.
@param revision of the terms,
if none provided it will return the latest.
@return The list of terms.
@raise ServerError
"""
url = '{}ter... | [
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consbio/ncdjango | ncdjango/views.py | NetCdfDatasetMixin.open_dataset | def open_dataset(self, service):
"""Opens and returns the NetCDF dataset associated with a service, or returns a previously-opened dataset"""
if not self.dataset:
path = os.path.join(SERVICE_DATA_ROOT, service.data_path)
self.dataset = netCDF4.Dataset(path, 'r')
return s... | python | def open_dataset(self, service):
"""Opens and returns the NetCDF dataset associated with a service, or returns a previously-opened dataset"""
if not self.dataset:
path = os.path.join(SERVICE_DATA_ROOT, service.data_path)
self.dataset = netCDF4.Dataset(path, 'r')
return s... | [
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consbio/ncdjango | ncdjango/views.py | GetImageViewBase._normalize_bbox | def _normalize_bbox(self, bbox, size):
"""Returns this bbox normalized to match the ratio of the given size."""
bbox_ratio = float(bbox.width) / float(bbox.height)
size_ratio = float(size[0]) / float(size[1])
if round(size_ratio, 4) == round(bbox_ratio, 4):
return bbox
... | python | def _normalize_bbox(self, bbox, size):
"""Returns this bbox normalized to match the ratio of the given size."""
bbox_ratio = float(bbox.width) / float(bbox.height)
size_ratio = float(size[0]) / float(size[1])
if round(size_ratio, 4) == round(bbox_ratio, 4):
return bbox
... | [
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