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def remove_constant_features(sfm):
"""
Remove features that are constant across all samples
"""
# boolean matrix of whether x == first column (feature)
x_not_equal_to_1st_row = sfm._x != sfm._x[0]
non_const_f_bool_ind = x_not_equal_to_1st_row.sum(axis=0) >= 1
return sfm.ind_x(selected_f_inds=non_const_f_bool_ind) | ae8c6e1d14b7260c8d2491b2f8a00ba352d7375a | 709,647 |
def readByte (file):
""" Read a byte from file. """
return ord (file.read (1)) | 4e82d1b688d7742fd1dd1025cd7ac1ccb13bbca0 | 709,655 |
def sdfGetMolBlock(mol):
"""
sdfGetMolBlock() returns the MOL block of the molecule
"""
return mol["molblock"] | 399874a696f30f492ee878ef661094119bd5f96f | 709,657 |
def noop_chew_func(_data, _arg):
"""
No-op chew function.
"""
return 0 | 82ef82b350c2a01e5ba22f288c003032bf6e63e0 | 709,662 |
from datetime import datetime
def set_clock(child, timestamp=None):
"""Set the device's clock.
:param pexpect.spawn child: The connection in a child application object.
:param datetime timestamp: A datetime tuple (year, month, day, hour, minute, second).
:returns: The updated connection in a child application object.
:rtype: pexpect.spawn
"""
if not timestamp:
timestamp = datetime.utcnow()
child.sendline("clock set {0}\r".format(timestamp.strftime("%H:%M:%S %d %b %Y")))
child.expect_exact("{0}, configured from console by console".format(timestamp.strftime("%H:%M:%S UTC %a %b %d %Y")))
return child | b6299ab780ffc9e9d27b0715decf095b3d6a6272 | 709,664 |
def uniquify_contacts(contacts):
"""
Return a sequence of contacts with all duplicates removed.
If any duplicate names are found without matching numbers, an exception is raised.
"""
ctd = {}
for ct in contacts:
stored_ct = ctd.setdefault(ct.name, ct)
if stored_ct.dmrid != ct.dmrid:
raise RuntimeError(
"Two contacts named {} have different IDs: {} {}".format(
ct.name, ct.dmrid, stored_ct.dmrid
)
)
return list(ctd.values()) | f4bf001abcccad1307633e6de6ed6228516ba0b2 | 709,669 |
def determine_if_is_hmmdb(infp):
"""Return True if the given file is an HMM database (generated using
hmmpress from the HMMer3 software package), and return False otherwise.
"""
#if open(infp, 'r').read().startswith('HMMER3/f'):
if open(infp, 'r').readline().startswith('HMMER3/f'):
return True
else:
return False | 33b962e24c76e9e25f2cc76d4e7f78565adf8a3e | 709,671 |
def template_footer(in_template):
"""Extracts footer from the notebook template.
Args:
in_template (str): Input notebook template file path.
Returns:
list: List of lines.
"""
footer = []
template_lines = []
footer_start_index = 0
with open(in_template) as f:
template_lines = f.readlines()
for index, line in enumerate(template_lines):
if '## Display Earth Engine data layers' in line:
footer_start_index = index - 3
footer = ['\n'] + template_lines[footer_start_index:]
return footer | cb872076b82b2012b2e27fcb1be9b8704cd60d27 | 709,672 |
def post_step1(records):
"""Apply whatever extensions we have for GISTEMP step 1, that run
after the main step 1. None at present."""
return records | 98287f6930db6aa025715356084b3bef8c851774 | 709,673 |
import math
def spatial_shift_crop_list(size, images, spatial_shift_pos, boxes=None):
"""
Perform left, center, or right crop of the given list of images.
Args:
size (int): size to crop.
image (list): ilist of images to perform short side scale. Dimension is
`height` x `width` x `channel` or `channel` x `height` x `width`.
spatial_shift_pos (int): option includes 0 (left), 1 (middle), and
2 (right) crop.
boxes (list): optional. Corresponding boxes to images.
Dimension is `num boxes` x 4.
Returns:
cropped (ndarray): the cropped list of images with dimension of
`height` x `width` x `channel`.
boxes (list): optional. Corresponding boxes to images. Dimension is
`num boxes` x 4.
"""
assert spatial_shift_pos in [0, 1, 2]
height = images[0].shape[0]
width = images[0].shape[1]
y_offset = int(math.ceil((height - size) / 2))
x_offset = int(math.ceil((width - size) / 2))
if height > width:
if spatial_shift_pos == 0:
y_offset = 0
elif spatial_shift_pos == 2:
y_offset = height - size
else:
if spatial_shift_pos == 0:
x_offset = 0
elif spatial_shift_pos == 2:
x_offset = width - size
cropped = [
image[y_offset : y_offset + size, x_offset : x_offset + size, :]
for image in images
]
assert cropped[0].shape[0] == size, "Image height not cropped properly"
assert cropped[0].shape[1] == size, "Image width not cropped properly"
if boxes is not None:
for i in range(len(boxes)):
boxes[i][:, [0, 2]] -= x_offset
boxes[i][:, [1, 3]] -= y_offset
return cropped, boxes | c80d8ab83f072c94887d48c3d1cfe5bb18285dbb | 709,675 |
def _checker(word: dict):
"""checks if the 'word' dictionary is fine
:param word: the node in the list of the text
:type word: dict
:return: if "f", "ref" and "sig" in word, returns true, else, returns false
:rtype: bool
"""
if "f" in word and "ref" in word and "sig" in word:
return True
return False | ee6ec5a7ee393ddcbc97b13f6c09cdd9019fb1a6 | 709,680 |
def to_n_class(digit_lst, data, labels):
"""to make a subset of MNIST dataset, which has particular digits
Parameters
----------
digit_lst : list
for example, [0,1,2] or [1, 5, 8]
data : numpy.array, shape (n_samples, n_features)
labels : numpy.array or list of str
Returns
-------
numpy.array, list of int
"""
if not set(digit_lst) <= set(range(10)):
raise ValueError
indices = []
new_labels = []
for i, x in enumerate(data):
for digit in digit_lst:
if labels[i] == str(digit):
indices.append(i)
new_labels.append(digit)
return data[indices], new_labels | 79652687ec0670ec00d67681711903ae01f4cc87 | 709,682 |
def max_tb(collection): # pragma: no cover
"""Returns the maximum number of TB recorded in the collection"""
max_TB = 0
for doc in collection.find({}).sort([('total_TB',-1)]).limit(1):
max_TB = doc['total_TB']
return max_TB | bde417de0b38de7a7b5e4e3db8c05e87fa6c55ca | 709,687 |
import time
def datetime_to_timestamp(d):
"""convert a datetime object to seconds since Epoch.
Args:
d: a naive datetime object in default timezone
Return:
int, timestamp in seconds
"""
return int(time.mktime(d.timetuple())) | 356ac090b0827d49e9929a7ef26041b26c6cc690 | 709,688 |
def update_coverage(coverage, path, func, line, status):
"""Add to coverage the coverage status of a single line"""
coverage[path] = coverage.get(path, {})
coverage[path][func] = coverage[path].get(func, {})
coverage[path][func][line] = coverage[path][func].get(line, status)
coverage[path][func][line] = coverage[path][func][line].combine(status)
return coverage | 46e5a1e5c4ebba3a9483f90ada96a0f7f94d8c1d | 709,690 |
def cross_product(v1, v2):
"""Calculate the cross product of 2 vectors as (x1 * y2 - x2 * y1)."""
return v1.x * v2.y - v2.x * v1.y | 871d803ef687bf80facf036549b4b2062f713994 | 709,691 |
import re
def _xfsdump_output(data):
"""
Parse CLI output of the xfsdump utility.
"""
out = {}
summary = []
summary_block = False
for line in [l.strip() for l in data.split("\n") if l.strip()]:
line = re.sub("^xfsdump: ", "", line)
if line.startswith("session id:"):
out["Session ID"] = line.split(" ")[-1]
elif line.startswith("session label:"):
out["Session label"] = re.sub("^session label: ", "", line)
elif line.startswith("media file size"):
out["Media size"] = re.sub(r"^media file size\s+", "", line)
elif line.startswith("dump complete:"):
out["Dump complete"] = re.sub(r"^dump complete:\s+", "", line)
elif line.startswith("Dump Status:"):
out["Status"] = re.sub(r"^Dump Status:\s+", "", line)
elif line.startswith("Dump Summary:"):
summary_block = True
continue
if line.startswith(" ") and summary_block:
summary.append(line.strip())
elif not line.startswith(" ") and summary_block:
summary_block = False
if summary:
out["Summary"] = " ".join(summary)
return out | dbc7fbf9dced99b83a7dc5917c473a1dee16d749 | 709,705 |
def parseParams(opt):
"""Parse a set of name=value parameters in the input value.
Return list of (name,value) pairs.
Raise ValueError if a parameter is badly formatted.
"""
params = []
for nameval in opt:
try:
name, val = nameval.split("=")
except ValueError:
raise ValueError("Bad name=value format for '%s'" % nameval)
params.append((name, val))
return params | b932f74c8e5502ebdd7a8749c2de4b30921d518b | 709,708 |
def _get_name(dist):
"""Attempts to get a distribution's short name, excluding the name scope."""
return getattr(dist, 'parameters', {}).get('name', dist.name) | fd57e523c1a84a36f9ed56236e4b8db1e887575c | 709,709 |
def NO_MERGE(writer, segments):
"""This policy does not merge any existing segments.
"""
return segments | 0742365f30d59cb219ac60483b867180bd910ba8 | 709,712 |
from typing import Union
def parse_boolean(val: str) -> Union[str, bool]:
"""Try to parse a string into boolean.
The string is returned as-is if it does not look like a boolean value.
"""
val = val.lower()
if val in ('y', 'yes', 't', 'true', 'on', '1'):
return True
if val in ('n', 'no', 'f', 'false', 'off', '0'):
return False
return val | e2cbda5a849e1166e0f2a3953220c93d1f3ba119 | 709,716 |
import re
def safe_htcondor_attribute(attribute: str) -> str:
"""Convert input attribute name into a valid HTCondor attribute name
HTCondor ClassAd attribute names consist only of alphanumeric characters or
underscores. It is not clearly documented, but the alphanumeric characters
are probably restricted to ASCII. Attribute names created from multiple
words typically capitalize the first letter in each word for readability,
although all comparisions are case-insensitive.
e.g., "central-manager" -> "CentralManager"
Args:
attribute: a string representing the name of an attribute
Returns:
The attribute name stripped of invalid characters and re-capitalized in
the manner typical of HTCondor ClassAd attributes.
Raises:
None
"""
# splitting by invalid characters removes them from the resulting array
split_attr = re.split(r"[^\w]", attribute, flags=re.ASCII)
safe_attr = "".join([word.capitalize() for word in split_attr if word])
return safe_attr | 7a4dda539b2379120e68737d72a80226c45f5602 | 709,720 |
def make_csv(headers, data):
"""
Creates a CSV given a set of headers and a list of database query results
:param headers: A list containg the first row of the CSV
:param data: The list of query results from the Database
:returns: A str containing a csv of the query results
"""
# Create a list where each entry is one row of the CSV file, starting
# with the headers
csvRows =[','.join(headers),]
# Iterate through the provided data and create the rest of the CSV's rows
for datum in data:
currentRow = ''
for header in headers:
# Get this rows value for the given header
val = getattr(datum, header)
if type(val) is str:
# Escape the strings
currentRow += '"' + val + '",'
elif type(val) is float:
# Don't Escape the floats
currentRow += str(val) + ','
else:
# If it is empty and a place holder
currentRow += ','
csvRows.append(currentRow[:-1])
# Combine all of the rows into a single single string and return it.
return "\n".join(csvRows) | 5101d53de8dd09d8ebe743d77d71bff9aeb26334 | 709,721 |
from typing import Tuple
def extract_value_from_config(
config: dict,
keys: Tuple[str, ...],
):
"""
Traverse a config dictionary to get some hyper-parameter's value.
Parameters
----------
config
A config dictionary.
keys
The possible names of a hyper-parameter.
Returns
-------
The hyper-parameter value.
"""
result = []
for k, v in config.items():
if k in keys:
result.append(v)
elif isinstance(v, dict):
result += extract_value_from_config(v, keys)
else:
pass
return result | d545d4c9298c74776ec52fb6b2c8d54d0e653489 | 709,722 |
def vision_matched_template_get_pose(template_match):
"""
Get the pose of a previously detected template match. Use list operations
to get specific entries, otherwise returns value of first entry.
Parameters:
template_match (List[MatchedTemplate3D] or MatchedTemplate3D): The template match(s)
Return (Pose): The pose of the template match
"""
if isinstance(template_match,list):
template_match = template_match[0]
return template_match.pose.pose.pose | b854da7a085934f4f3aba510e76852fb8c0a440a | 709,724 |
def get_vocabulary(query_tree):
"""Extracts the normalized search terms from the leaf nodes of a parsed
query to construct the vocabulary for the text vectorization.
Arguments
---------
query_tree: pythonds.trees.BinaryTree
The binary tree object representing a parsed search query. Each leaf
node is a search term and internal nodes represent boolean operations.
See parse_query() for details.
Returns
-------
vocabulary: list
List of strings representing unique normalized search terms.
"""
def _getleafnodes(node):
terms = []
if node.isLeaf():
return terms + [node.normedterm]
elif node.leftChild and not node.rightChild:
return terms + _getleafnodes(node.getLeftChild())
elif node.rightChild and not node.leftChild:
return terms + _getleafnodes(node.getRightChild())
else: # has two children
return terms + _getleafnodes(node.getLeftChild()) \
+ _getleafnodes(node.getRightChild())
# extract terms from the leaf nodes of the query object.
terms = _getleafnodes(query_tree)
# remove duplicates.
vocabulary = list(set(terms))
return vocabulary | bd03f4894cd3f9a7964196bfb163335f84a048d7 | 709,728 |
def find_point_in_section_list(point, section_list):
"""Returns the start of the section the given point belongs to.
The given list is assumed to contain start points of consecutive
sections, except for the final point, assumed to be the end point of the
last section. For example, the list [5, 8, 30, 31] is interpreted as the
following list of sections: [5-8), [8-30), [30-31], so the points -32, 4.5,
32 and 100 all match no section, while 5 and 7.5 match [5-8) and so for
them the function returns 5, and 30, 30.7 and 31 all match [30-31].
Parameters
---------
point : float
The point for which to match a section.
section_list : sortedcontainers.SortedList
A list of start points of consecutive sections.
Returns
-------
float
The start of the section the given point belongs to. None if no match
was found.
Example
-------
>>> from sortedcontainers import SortedList
>>> seclist = SortedList([5, 8, 30, 31])
>>> find_point_in_section_list(4, seclist)
>>> find_point_in_section_list(5, seclist)
5
>>> find_point_in_section_list(27, seclist)
8
>>> find_point_in_section_list(31, seclist)
30
"""
if point < section_list[0] or point > section_list[-1]:
return None
if point in section_list:
if point == section_list[-1]:
return section_list[-2]
ind = section_list.bisect(point)-1
if ind == 0:
return section_list[0]
return section_list[ind]
try:
ind = section_list.bisect(point)
return section_list[ind-1]
except IndexError:
return None | 47d5cda15b140ba8505ee658fd46ab090b2fda8a | 709,729 |
def choose(population, sample):
"""
Returns ``population`` choose ``sample``, given
by: n! / k!(n-k)!, where n == ``population`` and
k == ``sample``.
"""
if sample > population:
return 0
s = max(sample, population - sample)
assert s <= population
assert population > -1
if s == population:
return 1
numerator = 1
denominator = 1
for i in range(s+1, population + 1):
numerator *= i
denominator *= (i - s)
return numerator/denominator | 659eac683cae737888df74c0db21aa3ece746b33 | 709,731 |
def eea(m, n):
"""
Compute numbers a, b such that a*m + b*n = gcd(m, n)
using the Extended Euclidean algorithm.
"""
p, q, r, s = 1, 0, 0, 1
while n != 0:
k = m // n
m, n, p, q, r, s = n, m - k*n, q, p - k*q, s, r - k*s
return (p, r) | 56e1c59ac3a51e26d416fe5c65cf6612dbe56b8c | 709,733 |
def maximum_value(tab):
"""
brief: return maximum value of the list
args:
tab: a list of numeric value expects at leas one positive value
return:
the max value of the list
the index of the max value
raises:
ValueError if expected a list as input
ValueError if no positive value found
"""
if not(isinstance(tab, list)):
raise ValueError('Expected a list as input')
valMax = 0.0
valMaxIndex = -1;
nPositiveValues = 0
for i in range(len(tab)):
if tab[i] >= 0 and tab[i] > valMax:
valMax = float(tab[i])
valMaxIndex = i
nPositiveValues += 1
if nPositiveValues <= 0:
raise ValueError('No positive value found')
return valMax, valMaxIndex | 1c31daf3a953a9d781bc48378ef53323313dc22a | 709,739 |
import math
def dsh(
incidence1: float, solar_az1: float, incidence2: float, solar_az2: float
):
"""Returns the Shadow-Tip Distance (dsh) as detailed in
Becker et al.(2015).
The input angles are assumed to be in radians.
This is defined as the distance between the tips of the shadows
in the two images for a hypothetical vertical post of unit
height. The "shadow length" describes the shadow of a hypothetical
pole so it applies whether there are actually shadows in the
image or not. It's a simple and consistent geometrical way to
quantify the difference in illumination. This quantity is
computed analogously to dp.
"""
def shx(inc: float, sunazgnd: float):
return -1 * math.tan(inc) * math.cos(sunazgnd)
def shy(inc: float, sunazgnd: float):
return math.tan(inc) * math.sin(sunazgnd)
shx1 = shx(incidence1, solar_az1)
shx2 = shx(incidence2, solar_az2)
shy1 = shy(incidence1, solar_az1)
shy2 = shy(incidence2, solar_az2)
return math.sqrt(math.pow(shx1 - shx2, 2) + math.pow(shy1 - shy2, 2)) | 5aef1c9d7ffeb3e8534568a53cf537d26d97324a | 709,740 |
from typing import Optional
def convert_postgres_array_as_string_to_list(array_as_string: str) -> Optional[list]:
"""
Postgres arrays are stored in CSVs as strings. Elasticsearch is able to handle lists of items, but needs to
be passed a list instead of a string. In the case of an empty array, return null.
For example, "{this,is,a,postgres,array}" -> ["this", "is", "a", "postgres", "array"].
"""
return array_as_string[1:-1].split(",") if len(array_as_string) > 2 else None | cc64fe8e0cc765624f80abc3900985a443f76792 | 709,749 |
import functools
import logging
def disable_log_warning(fun):
"""Temporarily set FTP server's logging level to ERROR."""
@functools.wraps(fun)
def wrapper(self, *args, **kwargs):
logger = logging.getLogger('pyftpdlib')
level = logger.getEffectiveLevel()
logger.setLevel(logging.ERROR)
try:
return fun(self, *args, **kwargs)
finally:
logger.setLevel(level)
return wrapper | 6990a2a1a60ea5a24e4d3ac5c5e7fbf443825e48 | 709,752 |
import json
def read_json(file_name):
"""Read json from file."""
with open(file_name) as f:
return json.load(f) | 2eccab7dddb1c1038de737879c465f293a00e5de | 709,758 |
def _decode_end(_fp):
"""Decode the end tag, which has no data in the file, returning 0.
:type _fp: A binary `file object`
:rtype: int
"""
return 0 | 5e8da3585dda0b9c3c7cd428b7e1606e585e15c6 | 709,759 |
def get_camelcase_name_chunks(name):
"""
Given a name, get its parts.
E.g: maxCount -> ["max", "count"]
"""
out = []
out_str = ""
for c in name:
if c.isupper():
if out_str:
out.append(out_str)
out_str = c.lower()
else:
out_str += c
out.append(out_str)
return out | 134a8b1d98af35f185b37c999fbf499d18bf76c5 | 709,760 |
import json
def get_node_to_srn_mapping(match_config_filename):
"""
Returns the node-to-srn map from match_conf.json
"""
with open(match_config_filename) as config_file:
config_json = json.loads(config_file.read())
if "node_to_srn_mapping" in config_json:
return config_json["node_to_srn_mapping"]
else:
node_to_srn = {}
for node_info in config_json["NodeData"]:
node_id = node_info["TrafficNode"]
srn_num = node_info["srn_number"]
node_to_srn[node_id] = srn_num
return node_to_srn | 37bf2f266f4e5163cc4d6e9290a8eaf17e220cd3 | 709,765 |
def nest_dictionary(flat_dict, separator):
""" Nests a given flat dictionary.
Nested keys are created by splitting given keys around the `separator`.
"""
nested_dict = {}
for key, val in flat_dict.items():
split_key = key.split(separator)
act_dict = nested_dict
final_key = split_key.pop()
for new_key in split_key:
if not new_key in act_dict:
act_dict[new_key] = {}
act_dict = act_dict[new_key]
act_dict[final_key] = val
return nested_dict | f5b8649d916055fa5911fd1f80a8532e5dbee274 | 709,766 |
def list_a_minus_b(list1, list2):
"""Given two lists, A and B, returns A-B."""
return filter(lambda x: x not in list2, list1) | 8fbac6452077ef7cf73e0625303822a35d0869c3 | 709,767 |
def tempo_para_percorrer_uma_distancia(distancia, velocidade):
""" Recebe uma distância e a velocidade de movimentação, e retorna
as horas que seriam gastas para percorrer em linha reta"""
horas = distancia / velocidade
return round(horas,2) | e7754e87e010988284a6f89497bb1c5582ea0e85 | 709,773 |
def find_last_index(l, x):
"""Returns the last index of element x within the list l"""
for idx in reversed(range(len(l))):
if l[idx] == x:
return idx
raise ValueError("'{}' is not in list".format(x)) | f787b26dd6c06507380bf2e336a58887d1f1f7ea | 709,774 |
def _CheckUploadStatus(status_code):
"""Validates that HTTP status for upload is 2xx."""
return status_code / 100 == 2 | d799797af012e46945cf413ff54d2ee946d364ba | 709,776 |
import random
def pick_op(r, maxr, w, maxw):
"""Choose a read or a write operation"""
if r == maxr or random.random() >= float(w) / maxw:
return "write"
else:
return "read" | a45f53bf12538412b46f78e2c076966c26cf61ac | 709,779 |
def min_index(array, i, j):
"""Pomocna funkce pro razeni vyberem. Vrati index nejmensiho prvku
v poli 'array' mezi 'i' a 'j'-1.
"""
index = i
for k in range(i, j):
if array[k] < array[index]:
index = k
return index | 4c59362fac2e918ba5a0dfe9f6f1670b3e95d68c | 709,782 |
def average_precision(gt, pred):
"""
Computes the average precision.
This function computes the average prescision at k between two lists of
items.
Parameters
----------
gt: set
A set of ground-truth elements (order doesn't matter)
pred: list
A list of predicted elements (order does matter)
Returns
-------
score: double
The average precision over the input lists
"""
if not gt:
return 0.0
score = 0.0
num_hits = 0.0
for i,p in enumerate(pred):
if p in gt and p not in pred[:i]:
num_hits += 1.0
score += num_hits / (i + 1.0)
return score / max(1.0, len(gt)) | ca265471d073b6a0c7543e24ef0ba4f872737997 | 709,784 |
def Flatten(matrix):
"""Flattens a 2d array 'matrix' to an array."""
array = []
for a in matrix:
array += a
return array | 00389b4dd295274d8081331d6ae78f233f0b5b59 | 709,790 |
def escape_name(name):
"""Escape sensor and request names to be valid Python identifiers."""
return name.replace('.', '_').replace('-', '_') | 856b8fe709e216e027f5ab085dcab91604c93c2e | 709,792 |
def multiset_counter(mset):
"""
Return the sum of occurences of elements present in a token ids multiset,
aka. the multiset cardinality.
"""
return sum(mset.values()) | 36885abd5bf666aa6c77a262a647c227e46d2e88 | 709,793 |
def lengthenFEN(fen):
"""Lengthen FEN to 71-character form (ex. '3p2Q' becomes '111p11Q')"""
return fen.replace('8','11111111').replace('7','1111111') \
.replace('6','111111').replace('5','11111') \
.replace('4','1111').replace('3','111').replace('2','11') | f49cdf8ad6919fbaaad1abc83e24b1a33a3ed3f8 | 709,794 |
def get_list_of_encodings() -> list:
"""
Get a list of all implemented encodings.
! Adapt if new encoding is added !
:return: List of all possible encodings
"""
return ['raw', '012', 'onehot', '101'] | 6e0749eb45f85afe4e5c7414e4d23e67335ba2b5 | 709,799 |
def region_to_bin(chr_start_bin, bin_size, chr, start):
"""Translate genomic region to Cooler bin idx.
Parameters:
----------
chr_start_bin : dict
Dictionary translating chromosome id to bin start index
bin_size : int
Size of the bin
chr : str
Chromosome
start : int
Start of the genomic region
"""
return chr_start_bin[chr] + start // bin_size | f17b132048b0ceb4bbf2a87b77327d0d63b3fd64 | 709,800 |
def word_distance(word1, word2):
"""Computes the number of differences between two words.
word1, word2: strings
Returns: integer
"""
assert len(word1) == len(word2)
count = 0
for c1, c2 in zip(word1, word2):
if c1 != c2:
count += 1
return count | b3279744c628f3adc05a28d9ab7cc520744b540c | 709,803 |
def CheckVPythonSpec(input_api, output_api, file_filter=None):
"""Validates any changed .vpython files with vpython verification tool.
Args:
input_api: Bag of input related interfaces.
output_api: Bag of output related interfaces.
file_filter: Custom function that takes a path (relative to client root) and
returns boolean, which is used to filter files for which to apply the
verification to. Defaults to any path ending with .vpython, which captures
both global .vpython and <script>.vpython files.
Returns:
A list of input_api.Command objects containing verification commands.
"""
file_filter = file_filter or (lambda f: f.LocalPath().endswith('.vpython'))
affected_files = input_api.AffectedTestableFiles(file_filter=file_filter)
affected_files = map(lambda f: f.AbsoluteLocalPath(), affected_files)
commands = []
for f in affected_files:
commands.append(input_api.Command(
'Verify %s' % f,
['vpython', '-vpython-spec', f, '-vpython-tool', 'verify'],
{'stderr': input_api.subprocess.STDOUT},
output_api.PresubmitError))
return commands | d6e888b5ce6fec4bbdb35452b3c0572702430c06 | 709,804 |
def convertInt(s):
"""Tells if a string can be converted to int and converts it
Args:
s : str
Returns:
s : str
Standardized token 'INT' if s can be turned to an int, s otherwise
"""
try:
int(s)
return "INT"
except:
return s | a0eae31b69d4efcf8f8595e745316ea8622e24b3 | 709,809 |
import torch
def pairwise_distance(A, B):
"""
Compute distance between points in A and points in B
:param A: (m,n) -m points, each of n dimension. Every row vector is a point, denoted as A(i).
:param B: (k,n) -k points, each of n dimension. Every row vector is a point, denoted as B(j).
:return: Matrix with (m, k). And the ele in (i,j) is the distance between A(i) and B(j)
"""
A_square = torch.sum(A * A, dim=1, keepdim=True)
B_square = torch.sum(B * B, dim=1, keepdim=True)
distance = A_square + B_square.t() - 2 * torch.matmul(A, B.t())
return distance | 2142b94f91f9e762d1a8b134fdda4789c564455d | 709,810 |
def coerce(from_, to, **to_kwargs):
"""
A preprocessing decorator that coerces inputs of a given type by passing
them to a callable.
Parameters
----------
from : type or tuple or types
Inputs types on which to call ``to``.
to : function
Coercion function to call on inputs.
**to_kwargs
Additional keywords to forward to every call to ``to``.
Examples
--------
>>> @preprocess(x=coerce(float, int), y=coerce(float, int))
... def floordiff(x, y):
... return x - y
...
>>> floordiff(3.2, 2.5)
1
>>> @preprocess(x=coerce(str, int, base=2), y=coerce(str, int, base=2))
... def add_binary_strings(x, y):
... return bin(x + y)[2:]
...
>>> add_binary_strings('101', '001')
'110'
"""
def preprocessor(func, argname, arg):
if isinstance(arg, from_):
return to(arg, **to_kwargs)
return arg
return preprocessor | 61ccce8b9ffbec3e76aa9e78face469add28437e | 709,817 |
import configparser
def parse_config_to_dict(cfg_file, section):
""" Reads config file and returns a dict of parameters.
Args:
cfg_file: <String> path to the configuration ini-file
section: <String> section of the configuration file to read
Returns:
cfg: <dict> configuration parameters of 'section' as a dict
"""
cfg = configparser.ConfigParser()
cfg.read(cfg_file)
if cfg.has_section(section):
return dict(cfg.items(section))
else:
print("Section '%s' not found in file %s!" % (section, cfg_file))
return None | 021e3594f3130e502934379c0f5c1ecea228017b | 709,820 |
import math
def mag_inc(x, y, z):
"""
Given *x* (north intensity), *y* (east intensity), and *z*
(vertical intensity) all in [nT], return the magnetic inclincation
angle [deg].
"""
h = math.sqrt(x**2 + y**2)
return math.degrees(math.atan2(z, h)) | f4036358625dd9d032936afc373e53bef7c1e6e1 | 709,825 |
def _parse_disambiguate(disambiguatestatsfilename):
"""Parse disambiguation stats from given file.
"""
disambig_stats = [-1, -1, -1]
with open(disambiguatestatsfilename, "r") as in_handle:
header = in_handle.readline().strip().split("\t")
if header == ['sample', 'unique species A pairs', 'unique species B pairs', 'ambiguous pairs']:
disambig_stats_tmp = in_handle.readline().strip().split("\t")[1:]
if len(disambig_stats_tmp) == 3:
disambig_stats = [int(x) for x in disambig_stats_tmp]
return disambig_stats | bb05ec857181f032ae9c0916b4364b772ff7c412 | 709,826 |
def clean_vigenere(text):
"""Convert text to a form compatible with the preconditions imposed by Vigenere cipher."""
return ''.join(ch for ch in text.upper() if ch.isupper()) | d7c3fc656ede6d07d6e9bac84a051581364c63a0 | 709,827 |
def f_score(r: float, p: float, b: int = 1):
"""
Calculate f-measure from recall and precision.
Args:
r: recall score
p: precision score
b: weight of precision in harmonic mean
Returns:
val: value of f-measure
"""
try:
val = (1 + b ** 2) * (p * r) / (b ** 2 * p + r)
except ZeroDivisionError:
val = 0
return val | d12af20e30fd80cb31b2cc119d5ea79ce2507c4b | 709,829 |
def role_generator(role):
"""Closure function returning a role function."""
return lambda *args, **kwargs: role.run(*args, **kwargs) | 35dd1a54cb53a6435633c39608413c2d0b9fe841 | 709,831 |
def identity_show(client, resource_group_name, account_name):
"""
Show the identity for Azure Cognitive Services account.
"""
sa = client.get(resource_group_name, account_name)
return sa.identity if sa.identity else {} | 19018c895f3fdf0b2b79788547bf80a400724336 | 709,835 |
import math
def get_angle(p1, p2):
"""Get the angle between two points."""
return math.atan2(p2[1] - p1[1], p2[0] - p1[0]) | a29ea1ed74a6c071cf314d1c38c6e2f920bd1c3a | 709,836 |
def simulation_test(**kwargs):
"""Decorate a unit test and mark it as a simulation test.
The arguments provided to this decorator will be passed to
:py:meth:`~reviewbot.tools.testing.testcases.BaseToolTestCase
.setup_simulation_test`.
Args:
**kwargs (dict):
Keyword arguments to pass during setup.
Returns:
callable:
The new unit test function.
"""
def _dec(func):
func.simulation_setup_kwargs = kwargs
return func
return _dec | 56aa51374e66bb765bfc3d4da51e3254d06c0b55 | 709,839 |
def region_filter(annos, annotation):
"""filter for Region annotations.
The 'time' parameter can match either 'time' or 'timeEnd' parameters.
"""
result = []
for anno in annos:
time = annotation.get("time")
timeEnd = annotation.get("timeEnd")
for key in ['text', 'tags']:
if anno.get(key) != annotation.get(key):
continue
if anno.get("regionId") == 0:
continue
if anno.get("time") not in [time, timeEnd]:
continue
result.append(anno)
return result | 3ca4c6ba39d44370b3022f5eb17a25e0e1c9f056 | 709,840 |
def social_bonus_count(user, count):
"""Returns True if the number of social bonus the user received equals to count."""
return user.actionmember_set.filter(social_bonus_awarded=True).count() >= count | b2469833f315410df266cd0a9b36933edb1f9ac6 | 709,842 |
def read_labels(labels_path):
"""Reads list of labels from a file"""
with open(labels_path, 'rb') as f:
return [w.strip() for w in f.readlines()] | 3ebc61c76dd1ae83b73aa8b77584661c08a51321 | 709,844 |
def _gcs_uri_rewriter(raw_uri):
"""Rewrite GCS file paths as required by the rewrite_uris method.
The GCS rewriter performs no operations on the raw_path and simply returns
it as the normalized URI. The docker path has the gs:// prefix replaced
with gs/ so that it can be mounted inside a docker image.
Args:
raw_uri: (str) the raw GCS URI, prefix, or pattern.
Returns:
normalized: a cleaned version of the uri provided by command line.
docker_path: the uri rewritten in the format required for mounting inside
a docker worker.
"""
docker_path = raw_uri.replace('gs://', 'gs/', 1)
return raw_uri, docker_path | 6e476860cb175dd2936cc0c080d3be1d09e04b77 | 709,845 |
def remove_apostrophe(text):
"""Remove apostrophes from text"""
return text.replace("'", " ") | c7d918e56646a247564a639462c4f4d26bb27fc4 | 709,846 |
def generate_initials(text):
"""
Extract initials from a string
Args:
text(str): The string to extract initials from
Returns:
str: The initials extracted from the string
"""
if not text:
return None
text = text.strip()
if text:
split_text = text.split(" ")
if len(split_text) > 1:
return (split_text[0][0] + split_text[-1][0]).upper()
else:
return split_text[0][0].upper()
return None | 709e53392c790585588da25290a80ab2d19309f8 | 709,847 |
def part_allocation_count(build, part, *args, **kwargs):
""" Return the total number of <part> allocated to <build> """
return build.getAllocatedQuantity(part) | 84c94ca4e1b1006e293851189d17f63fc992b420 | 709,848 |
def __parse_sql(sql_rows):
"""
Parse sqlite3 databse output. Modify this function if you have a different
database setup. Helper function for sql_get().
Parameters:
sql_rows (str): output from SQL SELECT query.
Returns:
dict
"""
column_names = ['id', 'requester', 'item_name', 'custom_name',
'quantity', 'crafting_discipline', 'special_instruction',
'status', 'rarity', 'resource_provided', 'pub-date', 'crafter', 'stats']
request_dict = {str(row[0]): {column_names[i]: row[i] for i,_ in enumerate(column_names)} for row in sql_rows}
return request_dict | 09c61da81af069709dd020b8643425c4c6964137 | 709,850 |
import json
def load_default_data() -> dict[str, str]:
"""Finds and opens a .json file with streamer data.
Reads from the file and assigns the data to streamer_list.
Args:
None
Returns:
A dict mapping keys (Twitch usernames) to their corresponding URLs.
Each row is represented as a seperate streamer. For example:
{
"GMHikaru":"https://www.twitch.tv/GMHikaru"
}
"""
with open("statum\static\streamers.json", "r") as default_streamers:
streamer_list: dict[str, str] = json.load(default_streamers)
default_streamers.close()
return streamer_list | bfeef64922fb4144228e031b9287c06525c4254d | 709,851 |
def get_value_key(generator, name):
"""
Return a key for the given generator and name pair.
If name None, no key is generated.
"""
if name is not None:
return f"{generator}+{name}"
return None | 0ad630299b00a23d029ea15543982125b792ad53 | 709,852 |
def int_to_bigint(value):
"""Convert integers larger than 64 bits to bytearray
Smaller integers are left alone
"""
if value.bit_length() > 63:
return value.to_bytes((value.bit_length() + 9) // 8, 'little', signed=True)
return value | 0f2d64887dc15d1902b8e10b0257a187ed75187f | 709,854 |
def convert_where_clause(clause: dict) -> str:
"""
Convert a dictionary of clauses to a string for use in a query
Parameters
----------
clause : dict
Dictionary of clauses
Returns
-------
str
A string representation of the clauses
"""
out = "{"
for key in clause.keys():
out += "{}: ".format(key)
#If the type of the right hand side is string add the string quotes around it
if type(clause[key]) == str:
out += '"{}"'.format(clause[key])
else:
out += "{}".format(clause[key])
out += ","
out += "}"
return out | 8b135c799df8d16c116e6a5282679ba43a054684 | 709,863 |
def truncate_string(string: str, max_length: int) -> str:
"""
Truncate a string to a specified maximum length.
:param string: String to truncate.
:param max_length: Maximum length of the output string.
:return: Possibly shortened string.
"""
if len(string) <= max_length:
return string
else:
return string[:max_length] | c7d159feadacae5a692b1f4d95da47a25dd67c16 | 709,864 |
def clamp(minVal, val, maxVal):
"""Clamp a `val` to be no lower than `minVal`, and no higher than `maxVal`."""
return max(minVal, min(maxVal, val)) | 004b9a393e69ca30f925da4cb18a8f93f12aa4ef | 709,868 |
def notNone(arg,default=None):
""" Returns arg if not None, else returns default. """
return [arg,default][arg is None] | 71e6012db54b605883491efdc389448931f418d0 | 709,872 |
import hashlib
def calculate_hash(filepath, hash_name):
"""Calculate the hash of a file. The available hashes are given by the hashlib module. The available hashes can be listed with hashlib.algorithms_available."""
hash_name = hash_name.lower()
if not hasattr(hashlib, hash_name):
raise Exception('Hash algorithm not available : {}'\
.format(hash_name))
with open(filepath, 'rb') as f:
checksum = getattr(hashlib, hash_name)()
for chunk in iter(lambda: f.read(4096), b''):
checksum.update(chunk)
return checksum.hexdigest() | 975fe0a2a4443ca3abc67ed950fb7200409f2497 | 709,878 |
def deep_copy(obj):
"""Make deep copy of VTK object."""
copy = obj.NewInstance()
copy.DeepCopy(obj)
return copy | c00c4ff44dad5c0c018152f489955f08e633f5ed | 709,880 |
def matrix2list(mat):
"""Create list of lists from blender Matrix type."""
return list(map(list, list(mat))) | 9b4b598eb33e4d709e15fd826f23d06653659318 | 709,890 |
def get_height(img):
"""
Returns the number of rows in the image
"""
return len(img) | 765babc9fbc1468ef5045fa925843934462a3d32 | 709,893 |
def sum_squares(n):
"""
Returns: sum of squares from 1 to n-1
Example: sum_squares(5) is 1+4+9+16 = 30
Parameter n: The number of steps
Precondition: n is an int > 0
"""
# Accumulator
total = 0
for x in range(n):
total = total + x*x
return total | 669a5aa03a9d9a9ffe74e48571250ffa38a7d319 | 709,895 |
def save(self, fname="", ext="", slab="", **kwargs):
"""Saves all current database information.
APDL Command: SAVE
Parameters
----------
fname
File name and directory path (248 characters maximum,
including the characters needed for the directory path).
An unspecified directory path defaults to the working
directory; in this case, you can use all 248 characters
for the file name.
ext
Filename extension (eight-character maximum).
slab
Mode for saving the database:
ALL - Save the model data, solution data and post data
(element tables, etc.). This value is the default.
MODEL - Save the model data (solid model, finite element
model, loadings, etc.) only.
SOLU - Save the model data and the solution data (nodal
and element results).
Notes
-----
Saves all current database information to a file (File.DB).
In interactive mode, an existing File.DB is first written to a
backup file (File.DBB). In batch mode, an existing File.DB is
replaced by the current database information with no backup.
The command should be issued periodically to ensure a current
file backup in case of a system "crash" or a "line drop." It
may also be issued before a "doubtful" command so that if the
result is not what was intended the database may be easily
restored to the previous state. A save may be time consuming
for large models. Repeated use of this command overwrites the
previous data on the file (but a backup file is first written
during an interactive run). When issued from within POST1,
the nodal boundary conditions in the database (which were read
from the results file) will overwrite the nodal boundary
conditions existing on the database file.
Internal nodes may be created during solution (for example,
via the mixed u-P formulation or generalized plane strain
option for current- technology elements, the Lagrangian
multiplier method for contact elements or the MPC184 elements,
or the quadratic or cubic option of the BEAM188 and PIPE288
elements). It is sometimes necessary to save the internal
nodes in the database for later operations, such as cutting
boundary interpolations (CBDOF) for submodeling. To do so,
issue the SAVE command after the first SOLVE command.
In general, saving after solving is always a good practice.
This command is valid in any processor.
"""
return self.run(f"SAVE,{fname},{ext},,{slab}", **kwargs) | ddc79dc0f54e32d6cd96e115ad9842c1689c17b1 | 709,900 |
def get_dict_or_generate(dictionary, key, generator):
"""Get value from dict or generate one using a function on the key"""
if key in dictionary:
return dictionary[key]
value = generator(key)
dictionary[key] = value
return value | e31cd2b6661cf45e5345ce57d1e628174e6fd732 | 709,902 |
import random
def get_random_instance() -> random.Random:
"""
Returns the Random instance in the random module level.
"""
return random._inst | ee66055275153ce8c3eae67eade6e32e50fe1d79 | 709,904 |
import cgitb
def FormatException(exc_info):
"""Gets information from exception info tuple.
Args:
exc_info: exception info tuple (type, value, traceback)
Returns:
exception description in a list - wsgi application response format.
"""
return [cgitb.handler(exc_info)] | 733c2170a08f9880f8c191c1c6a52ee1ab455b7f | 709,905 |
def get_smallerI(x, i):
"""Return true if string x is smaller or equal to i. """
if len(x) <= i:
return True
else:
return False | 1588ef998f4914aa943a063546112766060a9cbf | 709,908 |
def unfold(raw_log_line):
"""Take a raw syslog line and unfold all the multiple levels of
newline-escaping that have been inflicted on it by various things.
Things that got python-repr()-ized, have '\n' sequences in them.
Syslog itself looks like it uses #012.
"""
lines = raw_log_line \
.replace('#012', '\n') \
.replace('\\n', '\n') \
.splitlines()
return lines | 9e23bdd82ac15086468a383a1ef98989aceee25e | 709,909 |
from datetime import datetime
def ts(timestamp_string: str):
"""
Convert a DataFrame show output-style timestamp string into a datetime value
which will marshall to a Hive/Spark TimestampType
:param timestamp_string: A timestamp string in "YYYY-MM-DD HH:MM:SS" format
:return: A datetime object
"""
return datetime.strptime(timestamp_string, '%Y-%m-%d %H:%M:%S') | 1902e75ab70c7869686e3a374b22fa80a6dfcf1a | 709,911 |
def nl_to_break( text ):
"""
Text may have newlines, which we want to convert to <br />
when formatting for HTML display
"""
text=text.replace("<", "<") # To avoid HTML insertion
text=text.replace("\r", "")
text=text.replace("\n", "<br />")
return text | d2baf1c19fae686ae2c4571416b4cad8be065474 | 709,912 |
import requests
import logging
def get_page_state(url):
"""
Checks page's current state by sending HTTP HEAD request
:param url: Request URL
:return: ("ok", return_code: int) if request successful,
("error", return_code: int) if error response code,
(None, error_message: str) if page fetching failed (timeout, invalid URL, ...)
"""
try:
response = requests.head(url, verify=False, timeout=10)
except requests.exceptions.RequestException as exception:
logging.error(exception)
return None, "Error fetching page"
if response.status_code >= 400:
return "error", response.status_code
return "ok", response.status_code | f7b7db656968bed5e5e7d332725e4d4707f2b14b | 709,913 |
def unique(list_, key=lambda x: x):
"""efficient function to uniquify a list preserving item order"""
seen = set()
result = []
for item in list_:
seenkey = key(item)
if seenkey in seen:
continue
seen.add(seenkey)
result.append(item)
return result | 57c82081d92db74a7cbad15262333053a2acd3a7 | 709,914 |
import random
def weight(collection):
"""Choose an element from a dict based on its weight and return its key.
Parameters:
- collection (dict): dict of elements with weights as values.
Returns:
string: key of the chosen element.
"""
# 1. Get sum of weights
weight_sum = sum([value for value in collection.values()])
# 2. Generate random number between 1 and sum of weights
random_value = random.randint(1, weight_sum)
# 3. Iterate through items
for key, value in collection.items():
# 4. Subtract weight of each item from random number
random_value -= value
# 5. Compare with 0, if <= 0, that item has been chosen
if random_value <= 0:
return key
# 6. Else continue subtracting
# Should not reach here.
raise ValueError("Invalid argument value.") | 383ddadd4a47fb9ac7be0292ecc079fcc59c4481 | 709,917 |
from typing import List
def make_matrix(points: List[float], degree: int) -> List[List[float]]:
"""Return a nested list representation of a matrix consisting of the basis
elements of the polynomial of degree n, evaluated at each of the points.
In other words, each row consists of 1, x, x^2, ..., x^n, where n is the degree,
and x is a value in points.
Preconditions:
- degree < len(points)
>>> make_matrix([1, 2, 3], 2)
[[1, 1, 1], [1, 2, 4], [1, 3, 9]]
"""
matrix = []
for point in points:
row = [point ** index for index in range(degree + 1)]
matrix.append(row)
return matrix | d8fbea3a0f9536cb681b001a852b07ac7b17f6c2 | 709,918 |
def adjust_seconds_fr(samples_per_channel_in_frame,fs,seconds_fr,num_frame):
"""
Get the timestamp for the first sample in this frame.
Parameters
----------
samples_per_channel_in_frame : int
number of sample components per channel.
fs : int or float
sampling frequency.
seconds_fr : int or float
seconds for this frame (from frame header)
num_frame : int
frame number (from frame header).
Returns
-------
time_first_frame : float
timestamp [s] corresponding to the first sample of this frame.
"""
seconds_per_frame=samples_per_channel_in_frame/float(fs)
time_first_sample=float(seconds_fr)+num_frame*seconds_per_frame
return(time_first_sample) | a19775db3ebcdbe66b50c30bc531e2980ca10082 | 709,919 |
def is_success(msg):
"""
Whether message is success
:param msg:
:return:
"""
return msg['status'] == 'success' | 43ecbf3c7ac8d03ce92ab059e7ec902e51505d0a | 709,921 |
def list_strip_comments(list_item: list, comment_denominator: str = '#') -> list:
"""
Strips all items which are comments from a list.
:param list_item: The list object to be stripped of comments.
:param comment_denominator: The character with which comment lines start with.
:return list: A cleaned list object.
"""
_output = list()
for _item in list_item:
if not _item[0] == comment_denominator:
_output.append(_item)
return _output | e5dd6e0c34a1d91586e12e5c39a3a5413746f731 | 709,922 |
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