xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

40e70b9686412d0723cd23f536473c204625ea82

16,835

py

Python

boardfarm/lib/wifi_snmp.py

mattsm/boardfarm

100521fde1fb67536682cafecc2f91a6e2e8a6f8

[ "BSD-3-Clause-Clear" ]

40

2018-03-23T14:17:13.000Z

2022-02-05T05:59:41.000Z

boardfarm/lib/wifi_snmp.py

mattsm/boardfarm

100521fde1fb67536682cafecc2f91a6e2e8a6f8

[ "BSD-3-Clause-Clear" ]

1

2020-04-17T01:20:12.000Z

2020-04-20T20:42:00.000Z

boardfarm/lib/wifi_snmp.py

mattsm/boardfarm

100521fde1fb67536682cafecc2f91a6e2e8a6f8

[ "BSD-3-Clause-Clear" ]

9

2018-04-11T08:31:14.000Z

2020-08-06T14:55:35.000Z

import pexpect from . import SnmpHelper from .common import retry_on_exception, snmp_mib_get, snmp_mib_set from .wifi import wifi_stub class wifi_snmp(wifi_stub): """Class for wifi settings via SNMP Inherits wifi_stub from lib/wifi.py """ def __init__(self, device, board): """ Constructor method to get the mib names for wifi This mib name has to be provided via a vendor specific json file and initialised in the board method """ self.device = device self.board = board self.mib_value = self.board.wifi_snmp_file self.parser = SnmpHelper.SnmpMibs.default_mibs self.iface_ip = None def enable_wifi(self, wifi_mode): """To enable wifi network via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_5 :type wifi_mode: string :raises assertion: Mib query return value for enable wifi """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Wifi_enable"], index, "i", "1") if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Wifi_enable"], index) assert mib_out == "1", "Mib query return value for enable wifi: %s" % mib_out def set_ssid(self, wifi_mode, ssid_name): """To set wifi ssid via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_5 :type wifi_mode: string :param ssid_name: Name for wifi ssid :type ssid_name: string :raises assertion: Mib query return value for setting the SSID """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["SSID_set"], index, "s", ssid_name) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["SSID_set"], index) assert mib_out == ssid_name, "Mib query return value for setting the SSID: %s" % mib_out def set_security(self, wifi_mode, security): """To set wifi security via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_5 :type wifi_mode: string :param security: security string eg:WPA-PSK/WPA2-PSK :type security: string :raises assertion: Mib query return value for setting the security mode """ index = self.mib_value["mib_index"][wifi_mode] security_mode = self.mib_value["security_mode"][security] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Security_mode"], index, "i", security_mode) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Security_mode"], index) assert mib_out == security_mode, "Mib query return value for setting the security mode: %s" % mib_out def set_password(self, wifi_mode, password): """To set wifi password via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_5 :type wifi_mode: string :param password: wifi password :type password: string :raises assertion: Mib query return value for setting the password """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Password_set"], index, "s", password) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Password_set"], index) assert mib_out == password, "Mib query return value for setting the password: %s" % mib_out def enable_channel_utilization(self, wifi_mode): """To enable channel utilization via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :raises assertion: Mib query return value for setting the channel utilisation """ mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Channel_Util"], "0", "i", "2") if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Channel_Util"], "0") assert mib_out == "2", "Mib query return value for setting the channel utilisation: %s" % mib_out def set_operating_mode(self, wifi_mode, operating_mode): """To set wifi operating mode via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :param operating_mode: wifi operating mode eg:802.11b/g mixed :type operating_mode: string :raises assertion: Mib query return value for setting the operating mode """ index = self.mib_value["mib_index"][wifi_mode] operating_mode = self.mib_value["operating_mode"][operating_mode] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Operating_mode"], index, "i", operating_mode) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get( self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Operating_mode"], index) assert mib_out == operating_mode, "Mib query return value for setting the operating mode: %s" % mib_out def set_bandwidth(self, wifi_mode, bandwidth, channel_number=0): """To set wifi bandwidth via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :param bandwidth: wifi bandwidth eg:20/40 MHz :type bandwidth: string :param channel_number: Always 0 in snmp, defaults to 0 :type channel_number: Integer, optional :raises assertion: Mib query return value for setting the bandwidth """ index = self.mib_value["mib_index"][wifi_mode] bandwidth = self.mib_value["bandwidth"][bandwidth] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Bandwidth"], index, "i", bandwidth) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Bandwidth"], index) assert mib_out == bandwidth, "Mib query return value for setting the bandwidth: %s" % mib_out def set_channel_number(self, wifi_mode, channel_number): """To set wifi channel number via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :param channel_number: Wifi channel number :type channel_number: string :raises assertion: Mib query return value for setting the channel number """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Channel_mode"], index, "u", channel_number) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Channel_mode"], index) assert mib_out == channel_number, "Mib query return value for setting the channel number: %s" % mib_out def set_broadcast(self, wifi_mode, broadcast="enable"): """To set wifi broadcast via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :param broadcast: enable or disable, defaults to enable :type broadcast: string, optional :raises assertion: Mib query return value for setting the broadcast for SSID """ if broadcast == "enable": broadcast_value = "2" elif broadcast == "disable": broadcast_value = "1" index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_set(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Broadcast"], index, "i", broadcast_value) if self.apply_changes_no_delay: self.apply_changes() mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Broadcast"], index) assert mib_out == broadcast_value, "Mib query return value for setting the broadcast for SSID: %s" % mib_out def apply_changes(self): """To apply changes to the wifi settings :return: True or False :rtype: boolean """ retry_on_exception(snmp_mib_set, ( self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Wifi_Apply_setting"], '0', 'i', '1', )) for _ in range(4): self.board.expect(pexpect.TIMEOUT, timeout=20) try: mib_out = snmp_mib_set( self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Wifi_diag_command"], '0', 's', '"echo 1"') mib_out = snmp_mib_get( self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Wifi_diag_result"], '0') if mib_out != '1': continue wifi_2G_channel = snmp_mib_get( self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Current_channel"], '32') wifi_5G_channel = snmp_mib_get( self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Current_channel"], '92') if wifi_2G_channel != '0' and wifi_5G_channel != '0': return True break except: pass return False def get_wifi_enabled(self, wifi_mode): """To verify wifi enabled via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: mib output wifi enabled or not :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Wifi_enable"], index) return mib_out def get_ssid(self, wifi_mode): """To get ssid via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi ssid :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["SSID_set"], index) return mib_out def get_security(self, wifi_mode): """To get security via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi security :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Security_mode"], index) return mib_out def get_password(self, wifi_mode): """To get password via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi password :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Password_set"], index) return mib_out def get_channel_utilization(self): """To get channel utilization via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi channel utilization :rtype: string """ mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Channel_Util"], "0") return mib_out def get_operating_mode(self, wifi_mode): """To get operating mode via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi operating mode :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Operating_mode"], index) return mib_out def get_bandwidth(self, wifi_mode): """To get bandwidth via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi bandwidth :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Bandwidth"], index) return mib_out def get_broadcast(self, wifi_mode): """To get broadcast via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi broadcast :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Broadcast"], index) return mib_out def get_channel_number(self, wifi_mode): """To get channel number via SNMP :param wifi_mode: wifi network mode eg:private_2.4, guest_2.4, private_5, guest_5 :type wifi_mode: string :return: wifi channel number :rtype: string """ index = self.mib_value["mib_index"][wifi_mode] mib_out = snmp_mib_get(self.device, self.parser, self.iface_ip, self.mib_value["mib_name"]["Current_channel"], index) return mib_out

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py

Python

python/kyu-7/vowel-count/test_vowel_count.py

ledwindra/codewars

0552669a69e801cfe5f9a3696a4d98be63a96951

[ "WTFPL" ]

1

2020-11-13T16:55:04.000Z

python/kyu-7/vowel-count/test_vowel_count.py

ledwindra/codewars

0552669a69e801cfe5f9a3696a4d98be63a96951

[ "WTFPL" ]

1

2020-01-28T15:48:17.000Z

python/kyu-7/vowel-count/test_vowel_count.py

ledwindra/codewars

0552669a69e801cfe5f9a3696a4d98be63a96951

[ "WTFPL" ]

null

from vowel_count import get_count class TestVowelCount: def test_0(self): assert get_count("abracadabra") == 5

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src/slowo.py

grzegorzwojdyga/SDA_excercises2

4106e95884a7aceb7f9bd74b91997b5e1a08d83c

[ "MIT" ]

null

src/slowo.py

grzegorzwojdyga/SDA_excercises2

4106e95884a7aceb7f9bd74b91997b5e1a08d83c

[ "MIT" ]

null

src/slowo.py

grzegorzwojdyga/SDA_excercises2

4106e95884a7aceb7f9bd74b91997b5e1a08d83c

[ "MIT" ]

null

""" Napisz program, który pobiera od użytkownika słowo, a następnie wyświetla słowo złożone z co drugiego znaku pobranego. W drugiej kolejności program powinien wyświetlić słowo z pozostałych liter. """

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py

Python

CodeSignal/Arcade/The_Core/Level_03_Corner_Of_Zeros_And_Ones/020_Mirror_Bits.py

Zubieta/CPP

fb4a3cbf2e4edcc590df15663cd28fb9ecab679c

[ "MIT" ]

8

2017-03-02T07:56:45.000Z

2021-08-07T20:20:19.000Z

CodeSignal/Arcade/The_Core/Level_03_Corner_Of_Zeros_And_Ones/020_Mirror_Bits.py

zubie7a/Algorithms

fb4a3cbf2e4edcc590df15663cd28fb9ecab679c

[ "MIT" ]

null

CodeSignal/Arcade/The_Core/Level_03_Corner_Of_Zeros_And_Ones/020_Mirror_Bits.py

zubie7a/Algorithms

fb4a3cbf2e4edcc590df15663cd28fb9ecab679c

[ "MIT" ]

1

2021-08-07T20:20:20.000Z

# https://app.codesignal.com/arcade/code-arcade/corner-of-0s-and-1s/e3zfPNTwTa9qTQzcX def mirrorBits(a): # Reverse the order of the bits in a given integer. # 1. Convert to a binary string with bin(), but mind that it # will start with "0b" so remove that. # 2. Reverse the string. # 3. Convert the result back to int giving source base as 2. return int("".join(reversed(bin(a)[2:])), 2)

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9063f3d367d9d5baaed65072d31d98c424492368

190

py

Python

borges/delivery/delivery/app.py

thcborges/curso-flask

5cfe24c8525f3c23844e2b9f5e2b60ad647d5d54

[ "Unlicense" ]

null

borges/delivery/delivery/app.py

thcborges/curso-flask

5cfe24c8525f3c23844e2b9f5e2b60ad647d5d54

[ "Unlicense" ]

null

borges/delivery/delivery/app.py

thcborges/curso-flask

5cfe24c8525f3c23844e2b9f5e2b60ad647d5d54

[ "Unlicense" ]

null

from flask import Flask app = Flask(__name__) @app.route('/') def index(): return '<h1>Hello, Codeshow</h1>' @app.route('/sobre') def sobre(): return '<h1>site de delivery</h1>'

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119

py

Python

run.py

MeghanaAnvekar/project_52

a621730af7333f3c5fab2f96c54f97ce4ec9db1e

[ "MIT" ]

8

2020-03-19T17:52:19.000Z

2021-06-04T17:33:03.000Z

run.py

MeghanaAnvekar/project_52

a621730af7333f3c5fab2f96c54f97ce4ec9db1e

[ "MIT" ]

10

2020-03-23T07:26:49.000Z

2021-06-10T18:44:23.000Z

run.py

MeghanaAnvekar/project_52

a621730af7333f3c5fab2f96c54f97ce4ec9db1e

[ "MIT" ]

9

2020-03-21T06:23:48.000Z

2020-04-03T17:59:18.000Z

#!/usr/bin/env python # -*- coding: UTF-8 -*- from app import app if __name__ == '__main__': app.run(debug=True)

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py

Python

wagtail_localize_git/test/apps.py

kaedroho/wagtail-localize-pontoo

24319685a2fa4df5515fda872032088faaf07415

[ "BSD-3-Clause" ]

5

2021-02-10T01:32:30.000Z

2022-03-03T05:57:30.000Z

wagtail_localize_git/test/apps.py

kaedroho/wagtail-localize-pontoon

24319685a2fa4df5515fda872032088faaf07415

[ "BSD-3-Clause" ]

9

2020-11-17T13:41:16.000Z

2022-03-25T13:12:43.000Z

wagtail_localize_git/test/apps.py

kaedroho/wagtail-localize-pontoon

24319685a2fa4df5515fda872032088faaf07415

[ "BSD-3-Clause" ]

1

2021-11-29T10:12:59.000Z

from django.apps import AppConfig class WagtailLocalizeGitTestAppConfig(AppConfig): label = "wagtail_localize_git_test" name = "wagtail_localize_git.test" verbose_name = "Localize Git tests" default_auto_field = "django.db.models.AutoField"

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90c7d2bbda443232ee00aeb7b402bd20b09b1af1

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bzl

Python

k8s/kustomize/assets.bzl

f110/rules_k8s_controller

f7c59a6616ab7c24d83fde97d96bc05c07cb1c7c

[ "MIT" ]

null

k8s/kustomize/assets.bzl

f110/rules_k8s_controller

f7c59a6616ab7c24d83fde97d96bc05c07cb1c7c

[ "MIT" ]

null

k8s/kustomize/assets.bzl

f110/rules_k8s_controller

f7c59a6616ab7c24d83fde97d96bc05c07cb1c7c

[ "MIT" ]

null

KUSTOMIZE_ASSETS = { "3.8.1": { "linux": ( "https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize%2Fv3.8.1/kustomize_v3.8.1_linux_amd64.tar.gz", "9d5b68f881ba89146678a0399469db24670cba4813e0299b47cb39a240006f37", ), "darwin": ( "https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize%2Fv3.8.1/kustomize_v3.8.1_darwin_amd64.tar.gz", "db8a283c7edfc10c0e661b31916f4e60096eae558657730177e4f103c84ddc00", ), }, "v3.9.1": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.1/kustomize_v3.9.1_darwin_amd64.tar.gz", "a15ced11ef9e26061c9f9204f3dec1e15e96e566cc99f443a45a1eeb638f5ce7"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.1/kustomize_v3.9.1_linux_amd64.tar.gz", "0fb2c3299ca3668205eac3a3a5be9a8e4a79d7c4fba18542a6c444e0d33ddbdd"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.1/kustomize_v3.9.1_windows_amd64.tar.gz", "35adf766750ac2f9fe15128218cfe53f59d3e984ab04ed2555a875496368e00b")}, "v3.9.2": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.2/kustomize_v3.9.2_darwin_amd64.tar.gz", "6d01be3adee9cb0b118988ddd4879fcae575baa0b6210836c1d0aa83c9199678"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.2/kustomize_v3.9.2_linux_amd64.tar.gz", "f5c76a726cbd27b74587fcd2816e86b3f6279d84043b7ed3725bf48b1bc8ca4a"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.2/kustomize_v3.9.2_windows_amd64.tar.gz", "f2de820ff6c00d5e93141bd887c577b962e249cf395466d304b7bff1f8bb5860")}, "v3.9.3": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.3/kustomize_v3.9.3_darwin_amd64.tar.gz", "5909b9515339d6fcb5f1d6ddd406ab5c6cef697425a6abbc9ad4659d585fa4d7"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.3/kustomize_v3.9.3_linux_amd64.tar.gz", "16b42caddcde36cfeaffbd459bedc0349e66f52e7afa12083d4630b1358f0aa5"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.3/kustomize_v3.9.3_windows_amd64.tar.gz", "42f9837c72f010461688a61217f885474bf5c439a64f83db8898d62ab3f9c478")}, "v3.9.4": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.4/kustomize_v3.9.4_darwin_amd64.tar.gz", "d7579f24a7ccc3bcadf13ff0578bd2f6dedfcbe12699914c1331ac2993b11904"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.4/kustomize_v3.9.4_linux_amd64.tar.gz", "439c6bda9086399477e4f847b16b9b45ee695391b4f5d6e4107374ad149050b0"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.9.4/kustomize_v3.9.4_windows_amd64.tar.gz", "8b0fc48843ee66b4ca8115f07fa92d536d773c04a76567176cb5e5e83f5cadf5")}, "v3.10.0": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.10.0/kustomize_v3.10.0_darwin_amd64.tar.gz", "8fc809455a282f1c9a8574304f61dcaf1f709012739cbddf5d122b1e953588b3"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.10.0/kustomize_v3.10.0_linux_amd64.tar.gz", "bab4ab8881718c29ba174bdf677fd89986ad25c40eb363fec9e78c1aff2ff0ea"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v3.10.0/kustomize_v3.10.0_windows_amd64.tar.gz", "aa1db87c2ef85bb4780e96299873a6b7960385f1599a2193dbd449e90a58c20d")}, "v4.0.0": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.0/kustomize_v4.0.0_darwin_amd64.tar.gz", "334985ae01bdbac329005207f57400db04394b846eb29f75a223c57541bd6b5b"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.0/kustomize_v4.0.0_linux_amd64.tar.gz", "6d8da061bbd9e7c57b2f39f34ef5f4cce76321e94bfe6cae4e972a7483f3bf30"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.0/kustomize_v4.0.0_windows_amd64.tar.gz", "b7494313d0b45ab57d2bb4a26c44c18180565e30661dcf53b78314fac761db5b")}, "v4.0.1": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.1/kustomize_v4.0.1_darwin_amd64.tar.gz", "0d72f74369d91acda33b08a3c979b1f2fc5f76f603c1e04545bbef84d39e1858"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.1/kustomize_v4.0.1_linux_amd64.tar.gz", "914c006a4c00e92e09c050e5be594ef1270d47ea41b84dd7bdcab6b3b05b9297"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.1/kustomize_v4.0.1_windows_amd64.tar.gz", "2a6793b6809bb99e4e9c93914c62233d018ec170acbf2ec086d87091f7f0cbff")}, "v4.0.2": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.2/kustomize_v4.0.2_darwin_amd64.tar.gz", "3f0b46728a16d844439de36f9766d8b1eb8dda37503d3eff1f0c3eb5160b0feb"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.2/kustomize_v4.0.2_linux_amd64.tar.gz", "94f31d5c1d1b4bc025a920f7460c3ad2e2b41b8bc21e101aa918c8820f523f27"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.2/kustomize_v4.0.2_windows_amd64.tar.gz", "661b8c970c98c9e86bb645216423807631d214576f82cfb5e30be1b64e404c30")}, "v4.0.3": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.3/kustomize_v4.0.3_darwin_amd64.tar.gz", "9e7c69c83eef4bd2641e4a8a79ffb900fa8fd05e125392086def5f78707f9b84"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.3/kustomize_v4.0.3_linux_amd64.tar.gz", "7cfaa86f8323d9deaa8233c31f3843dbce71e56875b7bf22292e5bc56b13e259"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.3/kustomize_v4.0.3_windows_amd64.tar.gz", "3824c30bb16b9515978ae7d0a2b6a2e87f69b71d8fa6b8dfc2d08fcd265d37d0")}, "v4.0.4": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.4/kustomize_v4.0.4_darwin_amd64.tar.gz", "46520fcd13aed85e944b7562702fcad69a6d024fd1de65234ecd2edbbf41ac99"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.4/kustomize_v4.0.4_linux_amd64.tar.gz", "df1e23bb1f801faadbd1e2d2c4ba6839979dd58d26aeb2a6d46baf62039e25f0"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.4/kustomize_v4.0.4_windows_amd64.tar.gz", "04ef445997b3220fa023eef2455a64c144d9811208ae6b74c251aa1e95a29373")}, "v4.0.5": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.5/kustomize_v4.0.5_darwin_amd64.tar.gz", "a0d50c943105684bb809970a9d2677fca7affbf4c2acff7c0f7663de980674a5"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.5/kustomize_v4.0.5_linux_amd64.tar.gz", "3ef93195ede4b7664b7ec65284461dd8eeb9f5404e7db5eb5bf59003085a0c98"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.0.5/kustomize_v4.0.5_windows_amd64.tar.gz", "ba54b5e707d172b79e2cd9fcaabdb3688a56f3d8cde0ddff4b0c4e1c47f1a30d")}, "v4.1.0": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.0/kustomize_v4.1.0_darwin_amd64.tar.gz", "9f969a393a63af80e78d63f6a7afab441c14fb8a44f15fd4e2c1b498cb7e4987"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.0/kustomize_v4.1.0_linux_amd64.tar.gz", "77263c66afd04106348bebd019096933e26c0054d5b0ade8265f3426cf440ae6"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.0/kustomize_v4.1.0_windows_amd64.tar.gz", "87077b1719473a1711c1e406f06bf648ee07ab9f54e2e374f14ac53d0a4d203d")}, "v4.1.1": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.1/kustomize_v4.1.1_darwin_amd64.tar.gz", "12d418e190b0523b2ca300254d3e17c201aee87db24d04ad1db91c3b742fb654"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.1/kustomize_v4.1.1_linux_amd64.tar.gz", "0405346be25f5282a00b43344d57185be339804c8a1071658c7d6f9912c10d1c"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.1/kustomize_v4.1.1_windows_amd64.tar.gz", "a68d179749453cdfbe5dc29c9747801f48728345888f752ba584d83a50127625")}, "v4.1.2": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.2/kustomize_v4.1.2_darwin_amd64.tar.gz", "08bf3888391a526d247aead55b6bd940574bba238d9d32aa40c0adb4998f812e"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.2/kustomize_v4.1.2_linux_amd64.tar.gz", "4efb7d0dadba7fab5191c680fcb342c2b6f252f230019cf9cffd5e4b0cad1d12"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.2/kustomize_v4.1.2_windows_amd64.tar.gz", "6074f536a4ded829cc56e75078932836a1a8a5bd154d82c1470999128022b2ed")}, "v4.1.3": {"darwin": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.3/kustomize_v4.1.3_darwin_amd64.tar.gz", "f1e54fdb659a68e5ec0a65aa52868bcc32b18fd3bc2b545db890ba261d3781c4"), "linux": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.3/kustomize_v4.1.3_linux_amd64.tar.gz", "f028cd2b675d215572d54634311777aa475eb5612fb8a70d84b957c4a27a861e"), "windows": ("https://github.com/kubernetes-sigs/kustomize/releases/download/kustomize/v4.1.3/kustomize_v4.1.3_windows_amd64.tar.gz", "67a21b674a8dad5e027224c3426e496028e10a65e779e950d07e5d6d8c1d9d2d")}, }

349.285714

622

0.81636

1,084

9,780

7.234317

0.068266

0.084162

0.083907

0.143841

0.602015

0.512369

0

0.245747

0.032209

9,780

27

623

362.222222

0.582779

0

0.074074

0

1.740741

0.904499

0.307566

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

4

90e90d45d713ef64f7220850b039861f4d214924

2,023

py

Python

nonebot1_qqbot/plugins/hyly/ecysj.py

freesrz93/nonebot1_qqbot

ec8dfb5f7dcf222185b0215db97e4557861c93dd

[ "MIT" ]

null

nonebot1_qqbot/plugins/hyly/ecysj.py

freesrz93/nonebot1_qqbot

ec8dfb5f7dcf222185b0215db97e4557861c93dd

[ "MIT" ]

null

nonebot1_qqbot/plugins/hyly/ecysj.py

freesrz93/nonebot1_qqbot

ec8dfb5f7dcf222185b0215db97e4557861c93dd

[ "MIT" ]

null

ecysj = """呐呐呐，米娜桑，扣祢起哇，瓦达西二刺猿の烧酒嚏!历布布，迁我仞一起守折，最好の二刺猿肥!呐呐，不憧我的，愚蠢の人们呵，果畔那塞，我二刺猿の烧酒是不会和祢有共同语言的jio豆麻袋,迅祥子拼活有什幺错喝?呐,告诉我呵。搜嚆祢仞已经不喜炊了呵..真是冷酷の人昵，果鲜纳塞,止祢看到不愉快の龙西了。像我送祥的人，果然消失就好了昵。也午只有在二次元的世界里，才有真正的美好存在的肥，呐?权元权元标元，果然灰惠了呵，带jio不，瓦达西，二刺猿の烧酒!博古哇zeidei不会人输!米娜桑!呐!瓦达西- _刺猿拓拓!哦晦吻扣赛伊弓斯! 呐呐呐!米娜桑!我要幵劫了~一十打去鄂死!诶多诶多~「多洗忒」?为什么要「妄.图.抹.杀」这样的「自己」呢?★(笑)呐、「中二病的你」也好、「二次元的你」也好...「全部」daisuki~呐~二次元民那赛高desuwa! 今后也.请.多.多.指.教.喔?~啊啊... .是C鲜V血γσγ味V道V呐凹~! ( 眯眼笑) kukuku-汝の「血」、会是什么样的「气味」呢★?诶多多~说着说着有些期待了呢J品尝「挚:爱:之:人」の) 「鲜血」什么的~嘛.... .如果是「你」的话，-定可以的!是的呢,那些可恶的三元狗怎么呢理解我们高贵的二★次仑元女人众呢。喵呜，要将那些人全部杀掉呐呐呐_..同类真是可爱得很.... w≌)不得不说万恶的三次元有点可取的，比如表情包。我们可以接受他们，他们排斥我们呢...抹爱小姐有错吗? 呐呐呐呐呐呐呐--遇到同类了啊啊啊啊美子式尖叫。(≥w≌)喵呜~果然万恶的三次元中也有★清流★呢。君果然是可爱得很呢.... .芽衣本甜子们会开心的要死吧.. .. 呐呐呐呐呐嗦嘎，二次元的美好，一定得守护的说，呐，三次元的愚蠢的人类最讨厌了的说，金木的痛，也许只有我明白的吧，啊啊啊啊，我也有要守护的事物，我即将化生恶魔8.(■n▲)&. 诶多...★是V同V类呢V喵」(由乃逆光捧脸.jpg)那群八嘎是不会懂的呀.. ... .关于「二次元の美好」V呐，如果说吾の存在有意义的话、那-定是因为「二次元」吧★? 所以呢--妄图污染这份「爱」的人类、都会被吾「抹」「杀」「掉」喔小(小声)...过厌二次元的八嘎三次元最恶心了啊魂淡!★呐、二次元の民那....都:是:最最:善良0)存.在呐★多洗.... .要「嘲笑」这样的孩子呢?吾辈不明白啊--? ....说到底，你们都只是污秽の「来自三次元的大人」吧?大人什么的、最讨厌了★」啊嘞啊嘞QAQ?多洗忒....欧尼酱ww?呐、桥豆麻袋...已经「厌烦」吾辈了嘛?哼唧..真是「冷酷の人」呢QuQ--★(向° o°)嘛.....即便是这样的哇达西,-定也是有「存在の意义」的吧、内~★快来「肯定」啊?不然.... .咱可就要「黑化」了哦」呐? 呐。。。(伸出的小手又迅速垂下去)嗦嘎(表情有点失落)，米娜桑已经不喜欢了呀(紧咬嘴唇)，得磨，米娜桑忘了当初吗(握紧小手)，莫以得丝(强忍住眼泪)，已经大丈夫了呦(挤出笑脸)，瓦大喜瓦，滋多滋多，滋多滋多(语气越来越用力了)滋多戴斯给! ! ! - 滋嘛迭磨瓦撕裂嘛赛! ! !至死都不会瓦斯裂嘛斯(认真的表情) 诶多..看起来阁下对于「二次元」の理解、似乎满是谬误:哦~!嘛，连最为基本の)「礼义廉耻」都早已失去了啊... (笑)呐，我说啊一- -这样Okimino、也会有自称「二次V元」の资格吗★?fufufu--说到底、阁下已经「二次元失格」了吧?呐~ 唔噗噗~汝等「劣等生物」...他配去「妄想」吗?呐、「真正的二次元」什么的--吾辈看汝是一-点都不懂啊★(笑 )嘛嘛.... .不过看着汝试图伪装成「二次元」の可笑姿态，倒是让吾辈对于「三次元の白痴」稍微有了些许兴趣哦? 诶多...★是V同类V呢Y喵)那群八嘎是不会懂的呀... .关于「二次元の美好」V呐，如果说吾の存在有意义的话、那一定是因为「二次元」吧★?所以呢--妄图污染这份「爱」的人类、都会被吾「抹」「杀」「掉」喔」(小声) 讨厌二次元的八嘎三次元最恶心了啊魂淡!★呐、二次元0民那...都:是最最善良の存在:呐★多....要「嘲笑」这样的孩子呢? 吾辈不明白啊--? ....说到底，你们都只是污秽の「来自三次元的大人」吧?大人什么的、最讨厌了★」啊嘞啊嘞QAQ?多洗....欧尼酱ww?呐、桥豆麻...已经「厌烦」吾辈了嘛?哼唧...真是「冷酷叨人呢QuQ--你(o° o°●)....即便是这样的哇达西,一定也是有「存在の意义」的吧、内~★快来「肯定」啊?不然... .咱可就要「黑化」了哦」呐?的呐。。。(伸出的小手又迅速垂下去)嗦嘎(有点失落)""" if __name__ == '__main__': print(len(ecysj.split('\n')))

106.473684

166

0.708354

367

2,023

3.959128

0.6703

0.004129

0.024776

0.027529

0.200964

0.140399

0

0.001536

0.034602

2,023

19

167

106.473684

0.727087

0

0.833333

0.966897

0.830534

0

1

0

false

0

0.055556

0

null

0

1

0

1

null

0

4

2916a4bbe14feab8580a0b3bbc3de05322ec648f

306

py

Python

run_spyder_infoworld.py

hack-learning/DataScience-Scrapers

6c2af7867b7c64085268808c1ec69b7df4aea026

[ "MIT" ]

3

2021-02-18T16:10:22.000Z

2021-07-20T15:45:04.000Z

run_spyder_infoworld.py

hack-learning/DataScience-Scrapers

6c2af7867b7c64085268808c1ec69b7df4aea026

[ "MIT" ]

null

run_spyder_infoworld.py

hack-learning/DataScience-Scrapers

6c2af7867b7c64085268808c1ec69b7df4aea026

[ "MIT" ]

null

from scrapy.crawler import CrawlerProcess from scrapy.utils.project import get_project_settings from news_scraper.spiders.infoworld import InfoworldSpider from news_scraper.spiders.devmozilla import MozillaDev process = CrawlerProcess(get_project_settings()) process.crawl(InfoworldSpider) process.start()

38.25

58

0.872549

37

306

7.054054

0.513514

0.076628

0.137931

0.168582

0

0.068627

306

8

59

38.25

0.915789

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2929e4a4ae593e878d77a64992ded57ef5c4dd14

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py

Python

kivyMD/docs/_templates/sphinx_theme_pd/__init__.py

We8Punk/ValutoPy

792bcc0083a8ac1c4227a545e1e0c3b3a6ab5b87

[ "MIT" ]

64

2018-09-17T20:14:39.000Z

2022-02-19T21:39:33.000Z

kivymd/docs/_templates/sphinx_theme_pd/__init__.py

elizabwth/kivy-widget-background-blur

592c8f3d253f22a6c48e40b8eeb3024ce144bbb7

[ "MIT" ]

13

2018-09-22T17:09:22.000Z

2020-09-02T14:11:17.000Z

kivymd/docs/_templates/sphinx_theme_pd/__init__.py

elizabwth/kivy-widget-background-blur

592c8f3d253f22a6c48e40b8eeb3024ce144bbb7

[ "MIT" ]

34

2018-09-20T20:19:47.000Z

2022-02-20T10:35:18.000Z

import os def get_html_theme_path(): theme_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__))) return theme_dir

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293b9da7cdc158335a1c31dd676666dc839bceac

284

py

Python

tornado_hello_word/hello_handler.py

Normanno2/MicroservicesExample

4588be17828b7113c5ca90dabfd45f8cccb9cb47

[ "Apache-2.0" ]

null

tornado_hello_word/hello_handler.py

Normanno2/MicroservicesExample

4588be17828b7113c5ca90dabfd45f8cccb9cb47

[ "Apache-2.0" ]

null

tornado_hello_word/hello_handler.py

Normanno2/MicroservicesExample

4588be17828b7113c5ca90dabfd45f8cccb9cb47

[ "Apache-2.0" ]

null

from tornado.web import RequestHandler class SimpleHelloHandler(RequestHandler): def get(self): print("Get") self.write("Hello Word") class HelloMateHandler(RequestHandler): def get(self, mate): print("Get") self.write("Hello "+str(mate))

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29403ee20e48e6a58b3bf2ba97b74e8711d66ecf

844

py

Python

utils/progress/setup.py

djzgroup/wau

565a7d90e28b71970c0c5f8b8430ff45e3afc8d5

[ "MIT" ]

null

utils/progress/setup.py

djzgroup/wau

565a7d90e28b71970c0c5f8b8430ff45e3afc8d5

[ "MIT" ]

null

utils/progress/setup.py

djzgroup/wau

565a7d90e28b71970c0c5f8b8430ff45e3afc8d5

[ "MIT" ]

null

#!/usr/bin/env python from setuptools import setup import progress setup( name='progress', version=progress.__version__, description='Easy to use progress bars', long_description=open('README.rst').read(), author='Giorgos Verigakis', author_email='verigak@gmail.com', url='http://github.com/verigak/progress/', license='ISC', packages=['progress'], classifiers=[ 'Environment :: Console', 'Intended Audience :: Developers', 'License :: OSI Approved :: ISC License (ISCL)', 'Programming Language :: Python :: 2.6', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', ] )

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29638593dc9f5f16ef7b5fac20ce66049db61f69

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py

Python

textractplus/__init__.py

VaibhavHaswani/textract2

333bc3a2ed646a6e8ddd8dbb57ea7524fe503f0c

[ "MIT" ]

null

textractplus/__init__.py

VaibhavHaswani/textract2

333bc3a2ed646a6e8ddd8dbb57ea7524fe503f0c

[ "MIT" ]

null

textractplus/__init__.py

VaibhavHaswani/textract2

333bc3a2ed646a6e8ddd8dbb57ea7524fe503f0c

[ "MIT" ]

null

from .parsers import process VERSION = "0.1"

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null

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4632709f6ab4728ae7c38a8588a1852c7a0be232

341

py

Python

app/home/views/contact_us.py

ThanlonSmith/computer-bysj

760005980f1fb8f83ca369ae40061ec38f5058ef

[ "Apache-2.0" ]

1

2019-10-20T16:22:49.000Z

app/home/views/contact_us.py

ThanlonSmith/computer-bysj

760005980f1fb8f83ca369ae40061ec38f5058ef

[ "Apache-2.0" ]

1

2021-09-29T17:42:36.000Z

app/home/views/contact_us.py

ThanlonSmith/computer-bysj

760005980f1fb8f83ca369ae40061ec38f5058ef

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # @Time : 2019/12/25 下午3:46 # @Author : Thanlon # @Wechat：18512152005 # @Email : thanlon@sina.com # @File : about_website.py # @Software: PyCharm from .. import home_bp from flask import render_template @home_bp.route('/v1/contact-us') def contact_us(): return render_template('/home/contact_us.html')

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465b73d767abc4adda75bce921dd19d40a7799b0

368

py

Python

pyezviz/exceptions.py

Shamshala/pyEzviz

2008c76fa249154c3244c3ce05f456833737334d

[ "Apache-2.0" ]

46

2020-03-27T10:32:47.000Z

2022-03-28T19:34:47.000Z

pyezviz/exceptions.py

Shamshala/pyEzviz

2008c76fa249154c3244c3ce05f456833737334d

[ "Apache-2.0" ]

59

2020-01-14T12:54:59.000Z

2022-02-17T13:59:12.000Z

pyezviz/exceptions.py

Shamshala/pyEzviz

2008c76fa249154c3244c3ce05f456833737334d

[ "Apache-2.0" ]

39

2020-03-22T17:37:51.000Z

2022-03-22T10:48:37.000Z

"""PyEzviz Exceptions.""" class PyEzvizError(Exception): """Ezviz api exception.""" class InvalidURL(PyEzvizError): """Invalid url exception.""" class HTTPError(PyEzvizError): """Invalid host exception.""" class InvalidHost(PyEzvizError): """Invalid host exception.""" class AuthTestResultFailed(PyEzvizError): """Authentication failed"""

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46860c3ecd47fe076400100ba25e64236900feff

60

py

Python

hydra_notebook/exceptions.py

lordoftheflies/hydra-notebook

eab70f082a1dbbc85e27c3114994b61031cf3cd8

[ "Apache-2.0" ]

null

hydra_notebook/exceptions.py

lordoftheflies/hydra-notebook

eab70f082a1dbbc85e27c3114994b61031cf3cd8

[ "Apache-2.0" ]

4

2020-02-11T22:59:43.000Z

2021-06-10T20:32:57.000Z

hydra_notebook/exceptions.py

lordoftheflies/hydra-notebook

eab70f082a1dbbc85e27c3114994b61031cf3cd8

[ "Apache-2.0" ]

null

#python class NotebookNotFindException(Exception): pass

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468b2a9b2d9628ae2406bb50afe8056e9ec1a300

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py

Python

test/test_pythoscope_generator_method_call_context.py

h4ck3rm1k3/pythoscope

0cefb34b86e2e81e29c0b93d27e3d4657db79912

[ "MIT" ]

null

test/test_pythoscope_generator_method_call_context.py

h4ck3rm1k3/pythoscope

0cefb34b86e2e81e29c0b93d27e3d4657db79912

[ "MIT" ]

null

test/test_pythoscope_generator_method_call_context.py

h4ck3rm1k3/pythoscope

0cefb34b86e2e81e29c0b93d27e3d4657db79912

[ "MIT" ]

null

import unittest class TestMethodCallContext(unittest.TestCase): def test___getattr__(self): # method_call_context = MethodCallContext(call, user_object) # self.assertEqual(expected, method_call_context.__getattr__(name)) assert False # TODO: implement your test here def test___init__(self): # method_call_context = MethodCallContext(call, user_object) assert False # TODO: implement your test here def test___repr__(self): # method_call_context = MethodCallContext(call, user_object) # self.assertEqual(expected, method_call_context.__repr__()) assert False # TODO: implement your test here if __name__ == '__main__': unittest.main()

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d3c12d855bdd7ce4f49d338bfb717ff30899067b

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py

Python

tests/test_.py

ChristophRaab/prototorch_models

75a39f5b03110a56b3d93ee00b3397858f4222a3

[ "MIT" ]

4

2021-05-05T07:27:11.000Z

2021-12-24T08:01:45.000Z

tests/test_.py

ChristophRaab/prototorch_models

75a39f5b03110a56b3d93ee00b3397858f4222a3

[ "MIT" ]

6

2021-05-06T09:49:37.000Z

2021-11-15T10:43:09.000Z

tests/test_.py

ChristophRaab/prototorch_models

75a39f5b03110a56b3d93ee00b3397858f4222a3

[ "MIT" ]

5

2021-05-12T14:16:35.000Z

2021-10-20T14:21:42.000Z

"""prototorch.models test suite.""" import unittest class TestDummy(unittest.TestCase): def setUp(self): pass def test_dummy(self): pass def tearDown(self): pass

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d3f2542bd10eebc273dfef4d78d3a5fb13f804c8

1,141

py

Python

utest/test_templates/test_protocol.py

dedie/Rammbock

ace46d50db1f41de570cdcb93987c99c7f79107f

[ "Apache-2.0" ]

37

2015-06-01T03:47:19.000Z

2021-11-15T09:39:11.000Z

utest/test_templates/test_protocol.py

dedie/Rammbock

ace46d50db1f41de570cdcb93987c99c7f79107f

[ "Apache-2.0" ]

55

2015-02-24T09:25:29.000Z

2022-02-04T13:11:55.000Z

utest/test_templates/test_protocol.py

dedie/Rammbock

ace46d50db1f41de570cdcb93987c99c7f79107f

[ "Apache-2.0" ]

38

2015-02-05T15:31:25.000Z

2020-04-03T03:40:04.000Z

from unittest import TestCase from Rammbock.templates.containers import Protocol from Rammbock.templates.primitives import UInt, PDU class TestProtocol(TestCase): def setUp(self): self._protocol = Protocol('Test') def test_header_length(self): self._protocol.add(UInt(1, 'name1', None)) self.assertEquals(self._protocol.header_length(), 1) def test_header_length_with_pdu(self): self._protocol.add(UInt(1, 'name1', None)) self._protocol.add(UInt(2, 'name2', 5)) self._protocol.add(UInt(2, 'length', None)) self._protocol.add(PDU('length')) self.assertEquals(self._protocol.header_length(), 5) def test_verify_undefined_length(self): self._protocol.add(UInt(1, 'name1', None)) self._protocol.add(UInt(2, 'name2', 5)) self.assertRaises(Exception, self._protocol.add, PDU('length')) def test_verify_calculated_length(self): self._protocol.add(UInt(1, 'name1', 1)) self._protocol.add(UInt(2, 'length', None)) self._protocol.add(PDU('length-8')) self.assertEquals(self._protocol.header_length(), 3)

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311bd5765475274f6d8a77122d6eb291b6c7ffc1

226

py

Python

LeetCode/Weekly Contests/Biweekly Contest 50/Queries on Number of Points Inside a Circle.py

UtkarshPathrabe/Competitive-Coding

ba322fbb1b88682d56a9b80bdd92a853f1caa84e

[ "MIT" ]

13

2021-09-02T07:30:02.000Z

2022-03-22T19:32:03.000Z

LeetCode/Weekly Contests/Biweekly Contest 50/Queries on Number of Points Inside a Circle.py

UtkarshPathrabe/Competitive-Coding

ba322fbb1b88682d56a9b80bdd92a853f1caa84e

[ "MIT" ]

null

LeetCode/Weekly Contests/Biweekly Contest 50/Queries on Number of Points Inside a Circle.py

UtkarshPathrabe/Competitive-Coding

ba322fbb1b88682d56a9b80bdd92a853f1caa84e

[ "MIT" ]

3

2021-08-24T16:06:22.000Z

2021-09-17T15:39:53.000Z

class Solution: def countPoints(self, points: List[List[int]], queries: List[List[int]]) -> List[int]: return [len([p for p in points if pow(p[0] - q[0], 2) + pow(p[1] - q[1], 2) <= pow(q[2], 2)]) for q in queries]

75.333333

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null

0

1

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4

315ad1915bde379e6d517b854ca96943f4d2f961

450

py

Python

app/service/interfaces/i_contact_svc.py

a6n1/caldera

a9a37ca1b54c1a4e0ecbd5144a2745fce3bdc36b

[ "Apache-2.0" ]

1

2021-04-04T02:30:11.000Z

app/service/interfaces/i_contact_svc.py

TylerJThomas/caldera

93b2d1b761d1e0eea87e6667206088610b7c1822

[ "Apache-2.0" ]

null

app/service/interfaces/i_contact_svc.py

TylerJThomas/caldera

93b2d1b761d1e0eea87e6667206088610b7c1822

[ "Apache-2.0" ]

null

import abc class ContactServiceInterface(abc.ABC): @abc.abstractmethod def register(self, contact): pass @abc.abstractmethod def handle_heartbeat(self): """ Accept all components of an agent profile and save a new agent or register an updated heartbeat. :return: the agent object, instructions to execute """ pass @abc.abstractmethod def build_filename(self): pass

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317ffd193d6a27adc970871a46d76c0db6f63947

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py

Python

code/asphericity_stats.py

astroandes/SatelliteShapeLG

8715e8779ce89fe720b979b148183a99ae06ec23

[ "MIT" ]

1

2015-05-01T04:41:51.000Z

code/asphericity_stats.py

VeronicaArias/AlineacionesIllustris

8715e8779ce89fe720b979b148183a99ae06ec23

[ "MIT" ]

2

2016-06-29T21:06:24.000Z

2016-12-15T19:26:33.000Z

code/asphericity_stats.py

VeronicaArias/AlineacionesIllustris

8715e8779ce89fe720b979b148183a99ae06ec23

[ "MIT" ]

null

import numpy as np import glob import os import matplotlib.pyplot as plt import corner def load_summary(filename): dtype=[('minr', 'f8'), ('maxr', 'f8'), ('ca_ratio', 'f8'), ('ba_ratio', 'f8'), ('a', 'f8'), ('center', 'f8'), ('width', 'f8'), ('mu', 'f8')] summary = np.loadtxt(filename, dtype=dtype) return summary def load_experiment(input_path="../data/mstar_selected_summary/vmax_sorted/", n_sat=11, full_data=False): files = glob.glob(input_path+"M31_group_*_nsat_{}.dat".format(n_sat)) group_id = [] for f in files: i = int(f.split("_")[-3]) if i not in group_id: group_id.append(i) #print(group_id, len(group_id)) n_groups = len(group_id) fields = ['width','mu', 'a', 'ba_ratio', 'ca_ratio'] M31_all = {} MW_all = {} if full_data: for field in fields: M31_all[field] = np.empty((0)) MW_all[field] = np.empty((0)) M31_all[field+'_random'] = np.empty((0)) MW_all[field+'_random'] = np.empty((0)) else: for field in fields: M31_all[field] = np.ones(n_groups) MW_all[field] = np.ones(n_groups) M31_all[field+'_sigma'] = np.ones(n_groups) MW_all[field+'_sigma'] = np.ones(n_groups) M31_all[field+'_random'] = np.ones(n_groups) MW_all[field+'_random'] = np.ones(n_groups) M31_all[field+'_random_sigma'] = np.ones(n_groups) MW_all[field+'_random_sigma'] = np.ones(n_groups) M31_all[field+'_normed'] = np.ones(n_groups) MW_all[field+'_normed'] = np.ones(n_groups) MW_summary = {} M31_summary = {} for g in range(n_groups): filename_MW = os.path.join(input_path,"MW_group_{}_nsat_{}.dat".format(group_id[g],n_sat)) filename_M31 = os.path.join(input_path,"M31_group_{}_nsat_{}.dat".format(group_id[g],n_sat)) MW_summary[g] = load_summary(filename_MW) M31_summary[g] = load_summary(filename_M31) for field in fields: a = np.empty((0)) b = np.empty((0)) a_random = np.empty((0)) b_random = np.empty((0)) for g in range(n_groups): data = M31_summary[g] a = data[field][0] a_random = data[field][1:] data = MW_summary[g] b = data[field][0] b_random = data[field][1:] #print('a_random {} iter: {} {}'.format(field, i, a_random)) if full_data: M31_all[field] = np.append(M31_all[field], a) MW_all[field] = np.append(MW_all[field], b) M31_all[field+'_random'] = np.append(M31_all[field+'_random'], a_random) MW_all[field+'_random'] = np.append(MW_all[field+'_random'], b_random) else: M31_all[field][g] = np.average(a) MW_all[field][g] = np.average(b) M31_all[field+'_sigma'][g] = np.std(a) MW_all[field+'_sigma'][g] = np.std(b) M31_all[field+'_random'][g] = np.average(a_random) MW_all[field+'_random'][g] = np.average(b_random) M31_all[field+'_random_sigma'][g] = np.std(a_random) MW_all[field+'_random_sigma'][g] = np.std(b_random) M31_all[field+'_normed'][g] = (M31_all[field][g] - M31_all[field+'_random'][g])/M31_all[field+'_random_sigma'][g] MW_all[field+'_normed'][g] = (MW_all[field][g] - MW_all[field+'_random'][g])/MW_all[field+'_random_sigma'][g] return M31_all, MW_all def points_in_experiment(experiment): keys = list(experiment.keys()) n_points = len(experiment[keys[0]]) return n_points def copy_experiment(experiment, id_to_remove=None): copy = {} n_points = points_in_experiment(experiment) for k in experiment.keys(): if id_to_remove is None: copy[k] = experiment[k].copy() else: ii = np.arange(n_points) copy[k] = experiment[k][ii!=id_to_remove] return copy def get_data_obs(obs_data, normed=True): fields = {0:'width', 1:'ca_ratio', 2:'ba_ratio'} n_fields = len(fields) data_obs = np.zeros((n_fields, len(obs_data['width']))) for i in range(n_fields): field = fields[i] if normed: x_obs = (obs_data[field] - obs_data[field+'_random'])/obs_data[field+'_random_sigma'] else: x_obs = obs_data[field] data_obs[i,:] = x_obs[:] return {'data_obs': data_obs, 'fields':fields} def covariance_and_mean(experiment): fields = {0:'width', 1:'ca_ratio', 2:'ba_ratio'} n_fields = len(fields) n_points = points_in_experiment(experiment) data_sim = np.zeros((n_fields, n_points)) for i in range(n_fields): field = fields[i] x_sim = (experiment[field] - experiment[field+'_random'])/experiment[field+'_random_sigma'] data_sim[i,:] = x_sim[:] data_cov = np.cov(data_sim) data_mean = np.mean(data_sim, axis=1) return {'covariance':data_cov, 'mean':data_mean, 'fields':fields} def jacknife_covariance(experiment): cov_and_mean = {} n_points = points_in_experiment(experiment) for i in range(n_points): tmp = copy_experiment(experiment, id_to_remove=i) cov_and_mean[i] = covariance_and_mean(tmp) covariance_avg = cov_and_mean[0]['covariance'] - cov_and_mean[0]['covariance'] for i in range(n_points): covariance_avg += cov_and_mean[i]['covariance'] covariance_avg = covariance_avg/n_points covariance_std = cov_and_mean[0]['covariance'] - cov_and_mean[0]['covariance'] for i in range(n_points): covariance_std += (cov_and_mean[i]['covariance']-covariance_avg)**2 covariance_std = np.sqrt(covariance_std/n_points) mean_avg = cov_and_mean[0]['mean'] - cov_and_mean[0]['mean'] for i in range(n_points): mean_avg += cov_and_mean[i]['mean'] mean_avg = mean_avg/n_points mean_std = cov_and_mean[0]['mean'] - cov_and_mean[0]['mean'] for i in range(n_points): mean_std += (cov_and_mean[i]['mean'] - mean_avg)**2 mean_std = np.sqrt(mean_std/20) return {'covariance': covariance_avg, 'covariance_error': covariance_std, 'mean': mean_avg, 'mean_error': mean_std} def print_table_obs_shape(): fields = ['width','ca_ratio', 'ba_ratio'] names = {'width':'Plane width (kpc)', 'ca_ratio':'$c/a$ ratio', 'ba_ratio':'$b/a$ ratio'} for n_sat in range(11,16): print("OBSERVATIONS - NSAT = {}".format(n_sat)) in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) print("M31(phys) - MW(phys) | M31(rand) | MW (rand) | M31(norm) | MW (norm)|") for field in fields: print("{} & ${:.2f}$ & ${:.2f}$ & ${:.2f}\pm{:.2f}$ & ${:.2f}\pm{:.2f}$ & ${:.2f}$ & ${:.2f}$\\\\\\hline".format( names[field], M31_obs_stats[field][0], MW_obs_stats[field][0], M31_obs_stats[field+'_random'][0], M31_obs_stats[field+'_random_sigma'][0], MW_obs_stats[field+'_random'][0],MW_obs_stats[field+'_random_sigma'][0], (M31_obs_stats[field][0]-M31_obs_stats[field+'_random'][0])/M31_obs_stats[field+'_random_sigma'][0], (MW_obs_stats[field][0]-MW_obs_stats[field+'_random'][0])/MW_obs_stats[field+'_random_sigma'][0])) print() def print_table_sim_shape(): fields = ['width','ca_ratio', 'ba_ratio'] names = {'width':'Plane width (kpc)', 'ca_ratio':'$c/a$ ratio', 'ba_ratio':'$b/a$ ratio'} for n_sat in range(11,16): print("IllustrisDark / Illustris / Elvis - NSAT = {}".format(n_sat)) in_path = "../data/illustris1_mstar_selected_summary/" M31_illu_stats, MW_illu_stats = load_experiment(input_path=in_path, n_sat=n_sat) in_path = "../data/illustris1dark_mstar_selected_summary/" M31_illudark_stats, MW_illudark_stats = load_experiment(input_path=in_path, n_sat=n_sat) in_path = "../data/elvis_mstar_selected_summary/" M31_elvis_stats, MW_elvis_stats = load_experiment(input_path=in_path, n_sat=n_sat) print("M31(phys) - MW(phys)|") for field in fields: print("{} & ${:.2f}\pm {:.2f}$ & ${:.2f} \pm {:.2f}$ & ${:.2f}\pm {:.2f}$ & ${:.2f}\pm {:.2f}$ & ${:.2f}\pm {:.2f}$ & ${:.2f}\pm {:.2f}$\\\\\\hline".format( names[field], np.mean(M31_illudark_stats[field]), np.std(M31_illudark_stats[field]), np.mean(MW_illudark_stats[field]), np.std(MW_illudark_stats[field]), np.mean(M31_illu_stats[field]), np.std(M31_illu_stats[field]), np.mean(MW_illu_stats[field]), np.std(MW_illu_stats[field]), np.mean(M31_elvis_stats[field]), np.std(M31_elvis_stats[field]), np.mean(MW_elvis_stats[field]), np.std(MW_elvis_stats[field]))) print() def plot_covariance(simulation, n_sat): simulation_name = {'illustris1':'Illustris1', 'illustris1dark':'Illustris1Dark', 'elvis':'ELVIS'} print('simulation {}'.format(simulation)) in_path = "../data/{}_mstar_selected_summary/".format(simulation) M31_sim_stats, MW_sim_stats = load_experiment(input_path=in_path, n_sat=n_sat) in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) M31_obs = get_data_obs(M31_obs_stats) MW_obs = get_data_obs(MW_obs_stats) cov_illustris_M31 = jacknife_covariance(M31_sim_stats) cov_illustris_MW = jacknife_covariance(MW_sim_stats) data_random_illustris_M31 = np.random.multivariate_normal( cov_illustris_M31['mean'], cov_illustris_M31['covariance'], size=100000) data_random_illustris_MW = np.random.multivariate_normal( cov_illustris_MW['mean'], cov_illustris_MW['covariance'], size=100000) s = np.array([1.0,2.0,3.0]) levels = 1-np.exp(-(s**2)/2.0) plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner( data_random_illustris_M31, quantiles=[0.16, 0.5, 0.84],levels=levels, labels=[r"$w$ M31", r"$c/a$ M31", r"$b/a$ M31"], show_titles=True, title_kwargs={"fontsize": 12}, truths=M31_obs['data_obs']) min_w = -4; max_w = 4; min_ac = -4; max_ac = 4 ; min_ab = -4; max_ab = 4 ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab); ax.scatter(M31_sim_stats['ca_ratio_normed'], M31_sim_stats['ba_ratio_normed']) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax.scatter(M31_sim_stats['width_normed'], M31_sim_stats['ca_ratio_normed']) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) ax.scatter(M31_sim_stats['width_normed'], M31_sim_stats['ba_ratio_normed']) children = ax.get_children() ax.legend([children[5], children[7], children[4]], [simulation_name[simulation], 'Observations', 'Gaussian Model'], loc='upper right', bbox_to_anchor=(3.0, 3.0), fontsize=20, markerscale=2) filename = "../paper/gaussian_model_{}_M31_n_{}.pdf".format(simulation, n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner(data_random_illustris_MW, quantiles=[0.16, 0.5, 0.84],levels=levels, labels=[r"$w$ MW", r"$c/a$ MW", r"$b/a$ MW"], show_titles=True, title_kwargs={"fontsize": 12}, truths=MW_obs['data_obs']) min_w = -4; max_w = 4; min_ac = -4; max_ac = 4 ; min_ab = -4; max_ab = 4 ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab); ax.scatter(MW_sim_stats['ca_ratio_normed'], MW_sim_stats['ba_ratio_normed']) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax.scatter(MW_sim_stats['width_normed'], MW_sim_stats['ca_ratio_normed']) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) ax.scatter(MW_sim_stats['width_normed'], MW_sim_stats['ba_ratio_normed']) children = ax.get_children() ax.legend([children[5], children[7], children[4]], [simulation_name[simulation], 'Observations', 'Gaussian Model'], loc='upper right', bbox_to_anchor=(3.0, 3.0), fontsize=20, markerscale=2) filename = "../paper/gaussian_model_{}_MW_n_{}.pdf".format(simulation, n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.close('all') def plot_asphericity_obs(field): plt.figure(figsize=(7,7)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) for n_sat in range(11,16): in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) M31_obs = get_data_obs(M31_obs_stats) MW_obs = get_data_obs(MW_obs_stats) print(n_sat, M31_obs['fields'][field], MW_obs['fields'][field],M31_obs['data_obs'][field], MW_obs['data_obs'][field]) if n_sat==11: plt.scatter(n_sat, M31_obs['data_obs'][field], marker='*', s=300, color='black', alpha=0.9, label='M31') plt.scatter(n_sat, MW_obs['data_obs'][field], marker='o', s=300, color='black', alpha=0.9, label='MW') else: plt.scatter(n_sat, M31_obs['data_obs'][field], marker='*', s=300, color='black', alpha=0.9) plt.scatter(n_sat, MW_obs['data_obs'][field], marker='o', s=300, color='black', alpha=0.9) ylabel = {'width': 'Normalized Plane Width', 'ca_ratio':'Normalized $c/a$ ratio', 'ba_ratio':'Normalized $b/a$ ratio'} plt.legend() plt.xlabel("$N_s$") plt.ylabel(ylabel[M31_obs['fields'][field]]) plt.grid() filename = "../paper/normalized_{}_n_dependence.pdf".format(M31_obs['fields'][field]) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() def number_LG(sim_cov_M31, sim_mean_M31, sim_cov_MW, sim_mean_MW, obs_M31, obs_MW, n_sample=20): n_try = 1000 n_out = np.ones(n_try) n_MW = np.ones(n_try) n_M31 = np.ones(n_try) for i in range(n_try): sim_M31 = np.random.multivariate_normal(sim_mean_M31, sim_cov_M31, size=n_sample) sim_MW = np.random.multivariate_normal(sim_mean_MW, sim_cov_MW, size=n_sample) like_M31_from_M31 = sim_M31[:,0]<1E6 like_MW_from_MW = sim_MW[:,0]<1E6 for j in range(3): like_M31_from_M31 &= (np.abs(sim_M31[:,j]-sim_mean_M31[j]) > np.abs(obs_M31[j]-sim_mean_M31[j])) like_MW_from_MW &= (np.abs(sim_MW[:,j]-sim_mean_MW[j]) > np.abs(obs_MW[j]-sim_mean_MW[j])) #print(sim_M31[like_M31_from_M31,:]) n_out[i] = np.count_nonzero(like_M31_from_M31 & like_MW_from_MW) n_MW[i] = np.count_nonzero(like_MW_from_MW) n_M31[i] = np.count_nonzero(like_M31_from_M31) #print(n_M31[i]) return {'n_LG': n_out, 'n_MW':n_MW, 'n_M31':n_M31} def get_numbers(simulation, n_sat): print('simulation {}'.format(simulation)) in_path = "../data/{}_mstar_selected_summary/".format(simulation) M31_sim_stats, MW_sim_stats = load_experiment(input_path=in_path, n_sat=n_sat) in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) M31_obs = get_data_obs(M31_obs_stats) MW_obs = get_data_obs(MW_obs_stats) cov_sim_M31 = jacknife_covariance(M31_sim_stats) cov_sim_MW = jacknife_covariance(MW_sim_stats) n_out_list_sim = number_LG(cov_sim_M31['covariance'], cov_sim_M31['mean'], cov_sim_MW['covariance'], cov_sim_MW['mean'], M31_obs['data_obs'], MW_obs['data_obs'], n_sample=10000) return {'mean_n_M31':np.mean(n_out_list_sim['n_M31']), 'std_n_M31':np.std(n_out_list_sim['n_M31']), 'mean_n_MW':np.mean(n_out_list_sim['n_MW']), 'std_n_MW':np.std(n_out_list_sim['n_MW']), 'mean_n_LG':np.mean(n_out_list_sim['n_LG']), 'std_n_LG':np.std(n_out_list_sim['n_LG'])} print() def print_numbers(): LG_out = open('../data/numbers/LG_numbers.txt', 'w') M31_out = open('../data/numbers/M31_numbers.txt', 'w') MW_out = open('../data/numbers/MW_numbers.txt', 'w') for i in range(11,16): a = get_numbers('illustris1dark', i) b = get_numbers('illustris1', i) c = get_numbers('elvis', i) LG_out.write("{} {} {} {} {} {} {}\n".format(i, a['mean_n_LG'], a['std_n_LG'], b['mean_n_LG'], b['std_n_LG'], c['mean_n_LG'], c['std_n_LG'])) M31_out.write("{} {} {} {} {} {} {}\n".format(i, a['mean_n_M31'], a['std_n_M31'], b['mean_n_M31'], b['std_n_M31'], c['mean_n_M31'], c['std_n_M31'])) MW_out.write("{} {} {} {} {} {} {}\n".format(i, a['mean_n_MW'], a['std_n_MW'], b['mean_n_MW'], b['std_n_MW'], c['mean_n_MW'], c['std_n_MW'])) MW_out.close() M31_out.close() LG_out.close() def plot_numbers(): LG_data = np.loadtxt('../data/numbers/LG_numbers.txt') M31_data = np.loadtxt('../data/numbers/M31_numbers.txt') MW_data = np.loadtxt('../data/numbers/MW_numbers.txt') LG_data[:,1:] = LG_data[:,1:]/1E2 M31_data[:,1:] = M31_data[:,1:]/1E2 MW_data[:,1:] = MW_data[:,1:]/1E2 plt.figure(figsize=(7,7)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) plt.errorbar(LG_data[:,0], LG_data[:,1], yerr=LG_data[:,2], fmt='*', markersize=20, color='black', alpha=0.5, label='Illustris1Dark') plt.errorbar(LG_data[:,0], LG_data[:,3], yerr=LG_data[:,4], fmt='o', markersize=20, color='black', alpha=0.5, label='Illustris1') plt.errorbar(LG_data[:,0], LG_data[:,5], yerr=LG_data[:,6], fmt='>', markersize=20, color='black', alpha=0.5, label='ELVIS') plt.legend() plt.xlabel("$N_s$") plt.ylabel("Local Group Systems $(\%)$") plt.grid() filename = "../paper/LG_numbers.pdf" print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.figure(figsize=(7,7)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) plt.errorbar(MW_data[:,0], MW_data[:,1], yerr=MW_data[:,2], fmt='*', markersize=20, color='black', alpha=0.5, label='Illustris1Dark') plt.errorbar(MW_data[:,0], MW_data[:,3], yerr=MW_data[:,4], fmt='o', markersize=20, color='black', alpha=0.5, label='Illustris1') plt.errorbar(MW_data[:,0], MW_data[:,5], yerr=MW_data[:,6], fmt='>', markersize=20, color='black', alpha=0.5, label='ELVIS') plt.xlabel("$N_s$") plt.ylabel("MW Galaxies $(\%)$") plt.grid() filename = "../paper/MW_numbers.pdf" print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.figure(figsize=(7,7)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) plt.errorbar(M31_data[:,0], M31_data[:,1], yerr=M31_data[:,2], fmt='*', markersize=20, color='black', alpha=0.5, label='Illustris1Dark') plt.errorbar(M31_data[:,0], M31_data[:,3], yerr=M31_data[:,4], fmt='o', markersize=20, color='black', alpha=0.5, label='Illustris1') plt.errorbar(M31_data[:,0], M31_data[:,5], yerr=M31_data[:,6], fmt='>', markersize=20, color='black', alpha=0.5, label='ELVIS') plt.xlabel("$N_s$") plt.ylabel("M31 Galaxies $(\%)$") plt.grid() filename = "../paper/M31_numbers.pdf" print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() def plot_shape_obs_randoms(n_sat): in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) M31_obs = get_data_obs(M31_obs_stats, normed=False) MW_obs = get_data_obs(MW_obs_stats, normed=False) M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=True) data_random_obs_M31 = np.array([M31_obs_stats['width_random'], M31_obs_stats['ca_ratio_random'], M31_obs_stats['ba_ratio_random']]).T data_random_obs_MW = np.array([MW_obs_stats['width_random'], MW_obs_stats['ca_ratio_random'], MW_obs_stats['ba_ratio_random']]).T print(np.shape(data_random_obs_MW)) print(MW_obs) plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner(data_random_obs_M31, quantiles=[0.16, 0.5, 0.84], labels=[r"$w$ M31", r"$c/a$ M31", r"$b/a$ M31"], show_titles=True, title_kwargs={"fontsize": 12}, truths=M31_obs['data_obs']) min_w = 10; max_w = 90; min_ac = 0.0; max_ac = 1.0 ; min_ab = 0.6; max_ab = 1.0 ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) filename = "../paper/input_obs_M31_n_{}.pdf".format(n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner(data_random_obs_MW, quantiles=[0.16, 0.5, 0.84], labels=[r"$w$ MW", r"$c/a$ MW", r"$b/a$ MW"], show_titles=True, title_kwargs={"fontsize": 12}, truths=MW_obs['data_obs']) ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) filename = "../paper/input_obs_MW_n_{}.pdf".format(n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.close('all') def plot_shape_obs_sims(simulation, n_sat): print('simulation {}'.format(simulation)) simulation_name = {'illustris1':'Illustris1', 'illustris1dark':'Illustris1Dark', 'elvis':'ELVIS'} in_path = "../data/{}_mstar_selected_summary/".format(simulation) M31_sim_stats, MW_sim_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=True) in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) M31_obs = get_data_obs(M31_obs_stats, normed=False) MW_obs = get_data_obs(MW_obs_stats, normed=False) M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=True) data_random_obs_M31 = np.array([M31_obs_stats['width_random'], M31_obs_stats['ca_ratio_random'], M31_obs_stats['ba_ratio_random']]).T data_random_obs_MW = np.array([MW_obs_stats['width_random'], MW_obs_stats['ca_ratio_random'], MW_obs_stats['ba_ratio_random']]).T print(np.shape(data_random_obs_MW)) print(MW_obs) s = np.array([1.0,2.0,3.0]) levels = 1-np.exp(-(s**2)/2.0) plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) plt.title("Physical Quantities") figure = corner.corner(data_random_obs_M31, levels = levels, quantiles=[0.16, 0.5, 0.84], labels=[r"$w$ (kpc) M31", r"$c/a$ M31", r"$b/a$ M31"], show_titles=True, title_kwargs={"fontsize": 12}, truths=M31_obs['data_obs']) min_w = 10; max_w = 90; min_ac = 0.0; max_ac = 1.0 ; min_ab = 0.6; max_ab = 1.0 ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab); ax.scatter(M31_sim_stats['ca_ratio'], M31_sim_stats['ba_ratio']) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax.scatter(M31_sim_stats['width'], M31_sim_stats['ca_ratio']) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) ax.scatter(M31_sim_stats['width'], M31_sim_stats['ba_ratio']) children = ax.get_children() ax.legend([children[5], children[7], children[4]], [simulation_name[simulation], 'Observations', 'Randomized Obs.'], loc='upper right', bbox_to_anchor=(3.0, 3.0), fontsize=20, markerscale=2) filename = "../paper/input_{}_obs_M31_n_{}.pdf".format(simulation, n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner(data_random_obs_MW, quantiles=[0.16, 0.5, 0.84], levels = levels, labels=[r"$w$ (kpc) MW", r"$c/a$ MW", r"$b/a$ MW"], show_titles=True, title_kwargs={"fontsize": 12}, truths=MW_obs['data_obs']) ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab); ax.scatter(MW_sim_stats['ca_ratio'], MW_sim_stats['ba_ratio']) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax.scatter(MW_sim_stats['width'], MW_sim_stats['ca_ratio']) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) ax.scatter(MW_sim_stats['width'], MW_sim_stats['ba_ratio']) children = ax.get_children() ax.legend([children[5], children[7], children[4]], [simulation_name[simulation], 'Observations', 'Randomized Obs.'], loc='upper right', bbox_to_anchor=(3.0, 3.0), fontsize=20, markerscale=2) filename = "../paper/input_{}_obs_MW_n_{}.pdf".format(simulation, n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.close('all') def plot_shape_obs_sims_normed(simulation, n_sat): print('simulation {}'.format(simulation)) simulation_name = {'illustris1':'Illustris1', 'illustris1dark':'Illustris1Dark', 'elvis':'ELVIS'} in_path = "../data/{}_mstar_selected_summary/".format(simulation) M31_sim_stats, MW_sim_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) in_path = "../data/obs_summary/" M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=False) M31_obs = get_data_obs(M31_obs_stats, normed=True) MW_obs = get_data_obs(MW_obs_stats, normed=True) M31_obs_stats, MW_obs_stats = load_experiment(input_path=in_path, n_sat=n_sat, full_data=True) data_random_obs_M31 = np.array([ (M31_obs_stats['width_random'] - np.mean(M31_obs_stats['width_random']))/np.std(M31_obs_stats['width_random']), (M31_obs_stats['ca_ratio_random'] - np.mean(M31_obs_stats['ca_ratio_random']))/np.std(M31_obs_stats['ca_ratio_random']), (M31_obs_stats['ba_ratio_random'] - np.mean(M31_obs_stats['ba_ratio_random']))/np.std(M31_obs_stats['ba_ratio_random'])]).T data_random_obs_MW = np.array([ (MW_obs_stats['width_random'] - np.mean(MW_obs_stats['width_random']))/np.std(MW_obs_stats['width_random']), (MW_obs_stats['ca_ratio_random'] - np.mean(MW_obs_stats['ca_ratio_random']))/np.std(MW_obs_stats['ca_ratio_random']), (MW_obs_stats['ba_ratio_random'] - np.mean(MW_obs_stats['ba_ratio_random']))/np.std(MW_obs_stats['ba_ratio_random'])]).T s = np.array([1.0,2.0,3.0]) levels = 1-np.exp(-(s**2)/2.0) print(np.shape(data_random_obs_MW)) print(MW_obs) plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner(data_random_obs_M31, quantiles=[0.16, 0.5, 0.84],levels=levels, labels=[r"$w$ M31", r"$c/a$ M31", r"$b/a$ M31"], show_titles=True, title_kwargs={"fontsize": 12}, truths=M31_obs['data_obs']) min_w = -4; max_w = 4; min_ac = -4; max_ac = 4 ; min_ab = -4; max_ab = 4 ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab); ax.scatter(M31_sim_stats['ca_ratio_normed'], M31_sim_stats['ba_ratio_normed']) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax.scatter(M31_sim_stats['width_normed'], M31_sim_stats['ca_ratio_normed']) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) ax.scatter(M31_sim_stats['width_normed'], M31_sim_stats['ba_ratio_normed']) children = ax.get_children() ax.legend([children[5], children[7], children[4]], [simulation_name[simulation], 'Observations', 'Randomized Obs.'], loc='upper right', bbox_to_anchor=(3.0, 3.0), fontsize=20, markerscale=2) filename = "../paper/input_{}_obs_M31_n_{}_normed.pdf".format(simulation, n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.figure(figsize=(8,5)) plt.rc('text', usetex=True,) plt.rc('font', family='serif', size=25) figure = corner.corner(data_random_obs_MW, quantiles=[0.16, 0.5, 0.84],levels=levels, labels=[r"$w$ MW", r"$c/a$ MW", r"$b/a$ MW"], show_titles=True, title_kwargs={"fontsize": 12}, truths=MW_obs['data_obs']) ndim = 3 axes = np.array(figure.axes).reshape(ndim,ndim) ax = axes[1,1];ax.set_xlim(min_ac, max_ac) ax = axes[2,1];ax.set_xlim(min_ac, max_ac);ax.set_ylim(min_ab, max_ab); ax.scatter(MW_sim_stats['ca_ratio_normed'], MW_sim_stats['ba_ratio_normed']) ax = axes[2,2];ax.set_xlim(min_ab, max_ab) ax = axes[0,0];ax.set_xlim(min_w, max_w) ax = axes[1,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ac, max_ac) ax.scatter(MW_sim_stats['width_normed'], MW_sim_stats['ca_ratio_normed']) ax = axes[2,0];ax.set_xlim(min_w, max_w);ax.set_ylim(min_ab, max_ab) ax.scatter(MW_sim_stats['width_normed'], MW_sim_stats['ba_ratio_normed']) children = ax.get_children() ax.legend([children[5], children[7], children[4]], [simulation_name[simulation], 'Observations', 'Randomized Obs.'], loc='upper right', bbox_to_anchor=(3.0, 3.0), fontsize=20, markerscale=2) filename = "../paper/input_{}_obs_MW_n_{}_normed.pdf".format(simulation, n_sat) print('saving figure to {}'.format(filename)) plt.savefig(filename, bbox_inches='tight') plt.clf() plt.close('all') def print_covariance(simulation, n_sat): def print_ab(a, b, c, d, e, f): print("{:.2f} \\pm {:.2f} & {:.2f} \\pm {:.2f} & {:.2f} \\pm {:.2f}\\\\".format(a,b,c,d,e,f)) simulation_name = {'illustris1':'Illustris-1', 'illustris1dark':'Illustris-1-Dark', 'elvis':'ELVIS'} print() in_path = "../data/{}_mstar_selected_summary/".format(simulation) M31_sim_stats, MW_sim_stats = load_experiment(input_path=in_path, n_sat=n_sat) cov_sim_M31 = jacknife_covariance(M31_sim_stats) cov_sim_MW = jacknife_covariance(MW_sim_stats) print('\\subsection{'+'{}'.format(simulation_name[simulation])+', M31, ' + '$N_s={}$'.format(n_sat) + '}') print('\\[') print('\\Sigma=') print('\\begin{bmatrix}') for i in range(3): print_ab(cov_sim_M31['covariance'][i][0], cov_sim_M31['covariance_error'][i][0], cov_sim_M31['covariance'][i][1], cov_sim_M31['covariance_error'][i][1], cov_sim_M31['covariance'][i][2], cov_sim_M31['covariance_error'][i][2]) print('\\end{bmatrix}') print('\\]') print('\\[') print('\\mu=') print('\\begin{bmatrix}') print_ab(cov_sim_M31['mean'][0], cov_sim_M31['mean_error'][0], cov_sim_M31['mean'][1], cov_sim_M31['mean_error'][1], cov_sim_M31['mean'][2], cov_sim_M31['mean_error'][2]) print('\\end{bmatrix}') print('\\]') print('\\subsection{'+'{}'.format(simulation_name[simulation])+', MW, ' + '$N_s={}$'.format(n_sat) + '}') print('\\[') print('\\Sigma=') print('\\begin{bmatrix}') for i in range(3): print_ab(cov_sim_MW['covariance'][i][0], cov_sim_MW['covariance_error'][i][0], cov_sim_MW['covariance'][i][1], cov_sim_MW['covariance_error'][i][1], cov_sim_MW['covariance'][i][2], cov_sim_MW['covariance_error'][i][2]) print('\\end{bmatrix}') print('\\]') print('\\[') print('\\mu=') print('\\begin{bmatrix}') print_ab(cov_sim_MW['mean'][0], cov_sim_MW['mean_error'][0], cov_sim_MW['mean'][1], cov_sim_MW['mean_error'][1], cov_sim_MW['mean'][2], cov_sim_MW['mean_error'][2]) print('\\end{bmatrix}') print('\\]')

46.463636

169

0.604634

5,480

35,777

3.637591

0.045985

0.029698

0.021672

0.028895

0.826477

0.76061

0.708438

0.659928

0.63028

0.622203

0

0.038867

0.220449

35,777

769

170

46.524057

0.675869

0.003885

0

0.568992

0

0.006202

0.163496

0.027642

0

1

0.031008

false

0

0.007752

0

0.052713

0.100775

0

null

0

1

0

1

0

null

0

4

319c579643cee83e15cc503481391b13ae5f2e49

324

py

Python

DRL/log_analysis/tracks/class_pointer.py

EXYNOS-999/AWS_JPL_DRL

ea9df7f293058b0ca2dc63753e68182fcc5380f5

[ "Apache-2.0" ]

null

DRL/log_analysis/tracks/class_pointer.py

EXYNOS-999/AWS_JPL_DRL

ea9df7f293058b0ca2dc63753e68182fcc5380f5

[ "Apache-2.0" ]

1

2020-01-08T06:52:03.000Z

2020-01-08T07:05:44.000Z

DRL/log_analysis/tracks/class_pointer.py

EXYNOS-999/AWS_JPL_DRL

ea9df7f293058b0ca2dc63753e68182fcc5380f5

[ "Apache-2.0" ]

null

def some_global_function(a): print(type(a)) def some_global_function_with_self(self, a): print(type(a)) class Object(): def __init__(self): #self.fp = some_global_function self.fp = some_global_function_with_self def call(self): self.fp('Hello') if __name__ == "__main__": o = Object() o.call()

17.052632

44

0.685185

49

324

4.040816

0.387755

0.20202

0.363636

0.212121

0.414141

0

0.175926

324

18

45

18

0.741573

0.092593

0

0.166667

0

0.044369

0

1

0.333333

false

0

0.416667

0.166667

0

null

1

0

null

0

1

0

4

31c559a76cd2ba048ad26c83f4055662a2b6a23c

992

py

Python

redescendl/__init__.py

harry-zuzan/Redescend-Likelihood

c203f1430e0200226b3dd0ec19621a2408ee1648

[ "MIT" ]

null

redescendl/__init__.py

harry-zuzan/Redescend-Likelihood

c203f1430e0200226b3dd0ec19621a2408ee1648

[ "MIT" ]

null

redescendl/__init__.py

harry-zuzan/Redescend-Likelihood

c203f1430e0200226b3dd0ec19621a2408ee1648

[ "MIT" ]

null

from .redescend_likelihood \ import redescend_residuals_normal_1d as redescend_normal1 from .redescend_likelihood \ import redescend_residuals_normal_2d as redescend_normal2 from .redescend_likelihood \ import redescend_residuals_normal_3d as redescend_normal3 #from .redescend_likelihood \ # import get_redescend_weights_normal_1d as get_weights_normal1 from .redescend_likelihood \ import get_redescend_weights_normal_1d as normal_weights1 from .redescend_likelihood \ import get_redescend_weights_normal_2d as normal_weights2 from .redescend_likelihood \ import get_redescend_weights_normal_3d as normal_weights3 from .redescend_likelihood \ import redescend_residuals_logistic_2d as redescend_logistic2 from .redescend_likelihood \ import get_redescend_weights_logistic_2d as get_weights_logistic2 del redescend_likelihood __all__ = ["redescend_normal2", "redescend_normal1"] __all__ += ["get_weights_normal2", "get_weights_normal1"] __all__ += ["redescend_logistic2"]

29.176471

66

0.859879

124

992

6.298387

0.177419

0.243278

0.265045

0.334187

0.629962

0.612036

0.551857

0.286812

0.148528

0

0.02567

0.096774

992

33

67

30.060606

0.845982

0.090726

0

0.4

0

0.101224

0

1

0

false

0

0.4

0

0.4

0

null

1

0

null

0

1

0

4

31c703509bb56a8a815db6055d6e71b40f47e5c5

44

py

Python

pyVulkan/__init__.py

realitix/pyVulkan

a0fc720fe993d3f31d09088566ce711f613e3c50

[ "MIT" ]

null

pyVulkan/__init__.py

realitix/pyVulkan

a0fc720fe993d3f31d09088566ce711f613e3c50

[ "MIT" ]

null

pyVulkan/__init__.py

realitix/pyVulkan

a0fc720fe993d3f31d09088566ce711f613e3c50

[ "MIT" ]

null

__version__ = '0.6' from ._vulkan import *

11

22

0.681818

6

44

4.166667

1

0

0.055556

0.181818

44

3

23

14.666667

0.638889

0

0.068182

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

31d98462b341b544d2603f78bcc49a983b7964bd

6,012

py

Python

scripts/crio/communication.py

nowireless/lib_crio

9a0be3d8d790f799527120c6710560a2b7e42d77

[ "MIT" ]

null

scripts/crio/communication.py

nowireless/lib_crio

9a0be3d8d790f799527120c6710560a2b7e42d77

[ "MIT" ]

null

scripts/crio/communication.py

nowireless/lib_crio

9a0be3d8d790f799527120c6710560a2b7e42d77

[ "MIT" ]

null

import crio import logging import network as net import time import socket from packets import DriverStation2RobotPacket from packets import Robot2DriverStationPacket from threading import Thread from threading import RLock import ds.joysticks.joysticks as joystick class RobotState: def __init__(self, team): self.team = team self.reset = False self.enabled = False self.estoped = False self.auto = False self.test = False self.joystick_axis = [ [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]] self.buttons = [ [False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], [False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], [False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], [False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], [False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False], [False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False]] def reset_robot(self): self.reset = True def no_reset(self): self.reset = False def enable(self): if not self.estoped: self.enabled = True def disable(self): self.enabled = False def estop(self): self.estoped = True self.disable() def teleop(self): self.auto = False self.test = False def auto(self): self.auto = True self.test = False def test(self): self.auto = False self.test = True def make_packet(self, index): pkt = DriverStation2RobotPacket.make_packet(index, self.team) pkt.control_byte.reset = self.reset pkt.control_byte.enabled = self.enabled pkt.control_byte.not_estop = not self.estoped pkt.control_byte.autonmous = self.auto pkt.control_byte.test = self.test return pkt class DSException(RuntimeError): pass class DS(Thread): def __init__(self, team, joystick_thread=None): super(DS, self).__init__() self.running = True self.team = team self.joystick_thread = joystick_thread self.log = crio.make_logger("DS", logging.INFO) if net.check_interfaces(team): self.log.info("Interfaces look ok") else: self.log.fatal("Network does not seem to configured correctly") raise DSException self.state_lock = RLock() self.state = RobotState(team) def run(self): if self.joystick_thread is not None: self.log.info("Starting Joystick Update Thread") self.joystick_thread.start() send = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) receive = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) receive.settimeout(crio.SOCKET_TIME_OUT) self.log.info("Binding to socket") receive.bind((crio.team_to_ds(self.team), crio.TO_DS_PORT)) crio_ip = crio.team_to_ip(self.team) packet_number = 0 # Start out with not being connected to the crio alive = False while self.running: if not alive: self.log.info("Pinging robot") if net.is_host_alive(crio_ip): self.log.info("Robot is alive, restarting communication") alive = True packet_number = 0 # Reset packet index self.state_lock.acquire() self.state.disable() self.state_lock.release() time.sleep(1) # Send DS->Robot Packet self.state_lock.acquire() to_robot_packet = self.state.make_packet(packet_number) if self.state.reset: # Do this so only one packet is sent with the reset flag self.state.reset = False self.state_lock.release() # Populate Joystick Data if self.joystick_thread is not None: self.joystick_thread.lock() if len(self.joystick_thread.joysticks) > 0: to_robot_packet.joystick_1_axis_1 = self.joystick_thread.joysticks[0].axis[0] to_robot_packet.joystick_1_axis_2 = self.joystick_thread.joysticks[0].axis[1] print to_robot_packet.joystick_1_axis_1, to_robot_packet.joystick_1_axis_2 self.joystick_thread.unlock() send.sendto(to_robot_packet.pack(), (crio_ip, crio.TO_ROBOT_PORT)) # Wait for Robot Packet data = None try: data, addr = receive.recvfrom(1024) except socket.timeout: self.log.warn("Received timeout, robot is not alive") alive = False continue from_crio_packet = Robot2DriverStationPacket.from_data(data) self.log.info("Sent %i | Got %i | %s | Enabled %s", packet_number, from_crio_packet.packet_index, str(from_crio_packet.packet_index == packet_number), from_crio_packet.control_byte.enabled) # Increment packet index packet_number = (packet_number + 1) % 65535 time.sleep(crio.LOOP_TIME) receive.close() send.close() if self.joystick_thread is not None: self.log.info("Stopping Joystick Update Thread & joining") self.joystick_thread.stop() self.joystick_thread.join() def stop(self): self.running = False if __name__ == "__main__": ds = DS(3081) ds.start()

34.751445

201

0.597305

749

6,012

4.639519

0.194927

0.273381

0.405755

0.535252

0.319137

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0

0.016766

0.305556

6,012

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34.953488

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0

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0

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null

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null

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0

null

1

0

null

0

1

0

4

31d9bc3e81f5c545c2092f105f2f70f5c9c94695

513

py

Python

abm/agent.py

OOP-Group-3/abm

78a6b05643f5ec0dde21b892d7b10d65354d57ab

[ "MIT" ]

null

abm/agent.py

OOP-Group-3/abm

78a6b05643f5ec0dde21b892d7b10d65354d57ab

[ "MIT" ]

1

2020-10-25T08:46:54.000Z

2020-10-25T13:40:08.000Z

abm/agent.py

OOP-Group-3/abm

78a6b05643f5ec0dde21b892d7b10d65354d57ab

[ "MIT" ]

1

2020-10-09T08:43:14.000Z

from model import Model from random import Random class Agent: """ Base class for a model agent. """ def __init__(self, unique_id: int, model: Model) -> None: """ Create a new agent. """ self.unique_id = unique_id self.model = model self.pos = None def step(self) -> None: """ A single step of the agent. """ pass # TODO: what does advance do that step() doesn't? def advance(self) -> None: pass # TODO: what is this for? @property def random(self) -> Random: return self.model.random

21.375

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0.662768

79

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0.455696

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0.212476

513

24

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false

0.142857

0.071429

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null

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null

0

1

0

1

0

1

0

1

0

4

31eafa552ca00b18866736fe4f0c9f67f321c41b

261

py

Python

gaia/db/mongo_client.py

caiyunapp/gaia

6e12b5beda095164f46e567fa04d7f13ad8a6965

[ "MIT" ]

null

gaia/db/mongo_client.py

caiyunapp/gaia

6e12b5beda095164f46e567fa04d7f13ad8a6965

[ "MIT" ]

null

gaia/db/mongo_client.py

caiyunapp/gaia

6e12b5beda095164f46e567fa04d7f13ad8a6965

[ "MIT" ]

1

2019-05-06T06:28:47.000Z

# -*- coding: utf-8 -*- from pymongo import MongoClient import gaia.config as cfg config = cfg.load_config('app.yaml') or cfg.load_config('mongo.yaml') or cfg.load_config('mongo.json') or cfg.load_config('mongo.cfg') client = MongoClient(**config['mongo'])

26.1

134

0.720307

40

261

4.6

0.45

0.152174

0.282609

0.244565

0.369565

0.26087

0

0.00431

0.111111

261

9

135

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0.788793

0.08046

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0.176471

0

1

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false

0

0.5

0

0.5

0

null

0

1

0

1

0

null

0

1

0

4

9ec5db9dc8db71f59ae8083f6621a7334097664d

83

py

Python

q/qapp/apps.py

llennox/projects

b52e9a56260a67a290492479a8792fad690b327a

[ "MIT" ]

2

2018-01-03T08:15:02.000Z

2018-01-03T08:15:03.000Z

qapp/apps.py

llennox/anonAPI

3ea2032919521e2d701f57f552bba475bd87dba2

[ "MIT" ]

null

qapp/apps.py

llennox/anonAPI

3ea2032919521e2d701f57f552bba475bd87dba2

[ "MIT" ]

null

from django.apps import AppConfig class QappConfig(AppConfig): name = 'qapp'

13.833333

33

0.73494

10

83

6.1

0.9

0

0.180723

83

5

34

16.6

0.897059

0

0.048193

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

9ec86ebca9801574b960b3466fc268270d1b8f64

8

py

Python

python/testData/inspections/PyArgumentListInspection/unfilledSentinelInBuiltinIter.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/inspections/PyArgumentListInspection/unfilledSentinelInBuiltinIter.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/inspections/PyArgumentListInspection/unfilledSentinelInBuiltinIter.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

iter([])

8

0.5

1

8

4

1

0

8

1

8

0.5

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

4

9ecc8f8cfe83f7f123a535ee4998cf01fe4683a3

18,932

py

Python

kinetics.py

kaustubhhakim/chili

f3301c3173a39614f1e55c6a5caa1e61f6b56301

[ "BSD-3-Clause" ]

null

kinetics.py

kaustubhhakim/chili

f3301c3173a39614f1e55c6a5caa1e61f6b56301

[ "BSD-3-Clause" ]

null

kinetics.py

kaustubhhakim/chili

f3301c3173a39614f1e55c6a5caa1e61f6b56301

[ "BSD-3-Clause" ]

null

# %% #!/usr/bin/env python # # Copyright (c) 2021, Kaustubh Hakim # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. # # CHILI 1.0 # # kinetics.py (generates all figures (+ additional) from the published paper) # # Minerals included: kaolinite: kaol, wollastonite: woll, enstatite: enst, # forsterite: fors, fayalite: faya, anorthite: anor, # albite: albi, K-feldspar: kfel, muscovite: musc, # phlogopite: phlo, quartz: quar # # If you are using this code, please cite the following publication # Hakim et al. (2021) Lithologic Controls on Silicate Weathering Regimes of # Temperate Planets. The Planetary Science Journal 2. doi:10.3847/PSJ/abe1b8 # %% # Import packages import numpy as np import csv import pandas as pd pd.options.mode.chained_assignment = None import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec from scipy.optimize import curve_fit from scipy.optimize import newton from scipy.interpolate import interp1d from scipy.interpolate import interp2d from scipy.interpolate import RegularGridInterpolator as interpnd import astropy.units as u u.imperial.enable() from astropy.constants import R from parameters import * # %% def import_kinetics_data(): '''Import mineral dissolution rates from Palandri & Kharaka (2004). Column names: Mineral, A_acid, log10(k_acid), E_acid, n_acid, A_neut, log10(k_neut), A_base, log10(k_base), E_base, n_base Note ---- Units of A, k, and E are in mol/m2/s, mol/m2/s and kJ/mol, respectively. Imports a csv file with a specific format and a predefined path. Returns ------- logkDict : dict of {str : float} Kinetics data with 4-letter keys ''' logkDict = {} df = pd.read_csv('./database/kinetics_data.csv', \ skiprows=lambda x: x in [1, 1], \ usecols=['Mineral','log10(k_acid)','E_acid', \ 'n_acid','log10(k_neut)','E_neut', \ 'log10(k_base)','E_base','n_base']) logkDict['quar'] = df.loc[df['Mineral'] == 'quartz'] logkDict['albi'] = df.loc[df['Mineral'] == 'albite'] logkDict['anor'] = df.loc[df['Mineral'] == 'anorthite'] logkDict['kfel'] = df.loc[df['Mineral'] == 'K-feldspar'] logkDict['fors'] = df.loc[df['Mineral'] == 'forsterite'] logkDict['faya'] = df.loc[df['Mineral'] == 'fayalite'] logkDict['enst'] = df.loc[df['Mineral'] == 'enstatite'] logkDict['woll'] = df.loc[df['Mineral'] == 'wollastonite'] logkDict['anth'] = df.loc[df['Mineral'] == 'anthophyllite'] logkDict['musc'] = df.loc[df['Mineral'] == 'muscovite'] logkDict['phlo'] = df.loc[df['Mineral'] == 'phlogopite'] return logkDict # %% def get_keff(Temp, pHall, logkDict): '''Import mineral dissolution rates from Palandri & Kharaka (2004). Column names: Mineral, A_acid, log10(k_acid), E_acid, n_acid, A_neut, log10(k_neut), A_base, log10(k_base), E_base, n_base Note ---- Units of A, k, and E are in mol/m2/s, mol/m2/s and kJ/mol, respectively. Imports a csv file with a specific format and a predefined path. Parameters ---------- Temp : float Temperature of the reactions (K) pH : float pH of the reactions logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : dict of {str : float} Kinetics data with 4-letter keys (mol/m2/yr) ''' kFuncs = {} names = np.array(['quar','albi','anor','kfel','fors','faya','enst','ferr',\ 'woll','anth','grun','musc','phlo','anni','albh','anoh',\ 'kfeh','mush','phlh','annh']) f_names = np.array([quar_ki,albi_ki,anor_ki,kfel_ki,fors_ki,faya_ki,enst_ki,ferr_ki,\ woll_ki,anth_ki,grun_ki,musc_ki,phlo_ki,anni_ki,albi_ki,anor_ki,\ kfel_ki,musc_ki,phlo_ki,anni_ki]) k_eff = np.zeros((len(names), len(Temp), len(pHall))) # Points for interpolation points = (Temp, pHall) # Make a 2D grid for each of the parameters Temp, pHall = np.meshgrid(Temp, pHall, indexing='ij') for i, func in enumerate(f_names): # Ellipsis notation is equivalent to doing :, :, : (and so on) k_eff[i, ...] = func(Temp, pHall, logkDict) kFuncs[names[i]] = interpnd(points=points, values=k_eff[i]) return kFuncs # %% def quar_ki(Temp, pH, logkDict): '''Calculate k_eff for quartz dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_n = 10**(logkDict['quar']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s k_b = 10**(logkDict['quar']['log10(k_base)'].values[0])*u.mol/u.m/u.m/u.s E_n = logkDict['quar']['E_neut'].values[0] * u.kJ/u.mol E_b = logkDict['quar']['E_base'].values[0] * u.kJ/u.mol n_b = logkDict['quar']['n_base'].values[0] neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) base = k_b * 10**(-pH*n_b) * np.exp(-E_b/R*(1/Temp-1/T0)/u.K) return (neut + base).to(u.mol/(u.m)**2/u.a) # %% def kfel_ki(Temp, pH, logkDict): '''Calculate k_eff for K-feldspar dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['kfel']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['kfel']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s k_b = 10**(logkDict['kfel']['log10(k_base)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['kfel']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['kfel']['E_neut'].values[0] * u.kJ/u.mol E_b = logkDict['kfel']['E_base'].values[0] * u.kJ/u.mol n_a = logkDict['kfel']['n_acid'].values[0] n_b = logkDict['kfel']['n_base'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) base = k_b * 10**(-pH*n_b) * np.exp(-E_b/R*(1/Temp-1/T0)/u.K) return (acid + neut + base).to(u.mol/(u.m)**2/u.a) # %% def albi_ki(Temp, pH, logkDict): '''Calculate k_eff for albite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['albi']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['albi']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s k_b = 10**(logkDict['albi']['log10(k_base)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['albi']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['albi']['E_neut'].values[0] * u.kJ/u.mol E_b = logkDict['albi']['E_base'].values[0] * u.kJ/u.mol n_a = logkDict['albi']['n_acid'].values[0] n_b = logkDict['albi']['n_base'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) base = k_b * 10**(-pH*n_b) * np.exp(-E_b/R*(1/Temp-1/T0)/u.K) return (acid + neut + base).to(u.mol/(u.m)**2/u.a) # %% def musc_ki(Temp, pH, logkDict): '''Calculate k_eff for muscovite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['musc']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['musc']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s k_b = 10**(logkDict['musc']['log10(k_base)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['musc']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['musc']['E_neut'].values[0] * u.kJ/u.mol E_b = logkDict['musc']['E_base'].values[0] * u.kJ/u.mol n_a = logkDict['musc']['n_acid'].values[0] n_b = logkDict['musc']['n_base'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) base = k_b * 10**(-pH*n_b) * np.exp(-E_b/R*(1/Temp-1/T0)/u.K) return (acid + neut + base).to(u.mol/(u.m)**2/u.a) # %% def kaol_ki(Temp, pH, logkDict): '''Calculate k_eff for kaolinite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['kaol']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['kaol']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s k_b = 10**(logkDict['kaol']['log10(k_base)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['kaol']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['kaol']['E_neut'].values[0] * u.kJ/u.mol E_b = logkDict['kaol']['E_base'].values[0] * u.kJ/u.mol n_a = logkDict['kaol']['n_acid'].values[0] n_b = logkDict['kaol']['n_base'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) base = k_b * 10**(-pH*n_b) * np.exp(-E_b/R*(1/Temp-1/T0)/u.K) return (acid + neut + base).to(u.mol/(u.m)**2/u.a) # %% def woll_ki(Temp, pH, logkDict): '''Calculate k_eff for wollastonite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['woll']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['woll']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['woll']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['woll']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['woll']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def enst_ki(Temp, pH, logkDict): '''Calculate k_eff for enstatite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['enst']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['enst']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['enst']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['enst']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['enst']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def ferr_ki(Temp, pH, logkDict): '''Calculate k_eff for ferrosilite dissolution. Calculations based on enstatite due to lack of data. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['enst']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['enst']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['enst']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['enst']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['enst']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def fors_ki(Temp, pH, logkDict): '''Calculate k_eff for forsterite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['fors']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['fors']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['fors']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['fors']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['fors']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def faya_ki(Temp, pH, logkDict): '''Calculate k_eff for fayalite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['faya']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['faya']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['faya']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['faya']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['faya']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def anor_ki(Temp, pH, logkDict): '''Calculate k_eff for anorthite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['anor']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['anor']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['anor']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['anor']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['anor']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def anth_ki(Temp, pH, logkDict): '''Calculate k_eff for anthophyllite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['anth']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['anth']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['anth']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['anth']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['anth']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def grun_ki(Temp, pH, logkDict): '''Calculate k_eff for grunerite dissolution. Calculations based on anthophyllite due to lack of data. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_a = 10**(logkDict['anth']['log10(k_acid)'].values[0])*u.mol/u.m/u.m/u.s k_n = 10**(logkDict['anth']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_a = logkDict['anth']['E_acid'].values[0] * u.kJ/u.mol E_n = logkDict['anth']['E_neut'].values[0] * u.kJ/u.mol n_a = logkDict['anth']['n_acid'].values[0] acid = k_a * 10**(-pH*n_a) * np.exp(-E_a/R*(1/Temp-1/T0)/u.K) neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return (acid + neut).to(u.mol/(u.m)**2/u.a) # %% def phlo_ki(Temp, pH, logkDict): '''Calculate k_eff for phlogopite dissolution. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_n = 10**(logkDict['phlo']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_n = logkDict['phlo']['E_neut'].values[0] * u.kJ/u.mol neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return neut.to(u.mol/(u.m)**2/u.a) # %% def anni_ki(Temp, pH, logkDict): '''Calculate k_eff for annite dissolution. Calculations based on phlogopite due to lack of data. Parameters ---------- Temp : float Temperature of the reaction (K) pH : float pH of the reaction logkDict : dict of {str : float} Kinetics data with 4-letter keys Returns ------- keff : float Kinetic rate coefficient (mol/m2/yr) ''' k_n = 10**(logkDict['phlo']['log10(k_neut)'].values[0])*u.mol/u.m/u.m/u.s E_n = logkDict['phlo']['E_neut'].values[0] * u.kJ/u.mol neut = k_n * np.exp(-E_n/R*(1/Temp-1/T0)/u.K) return neut.to(u.mol/(u.m)**2/u.a)

31.765101

89

0.563807

3,121

18,932

3.313361

0.075617

0.05483

0.049512

0.02727

0.760371

0.751862

0.747026

0.727299

0.680882

0.678948

0

0.030746

0.240651

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595

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31.818487

0.688578

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0

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0

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1

0.088542

false

0

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0

null

0

1

0

1

0

null

0

4

9ee45edef7d619770c4f741e2b2def2be3bb08d5

3,431

py

Python

src/peltak/core/templates/__init__.py

novopl/peltak

7c8ac44f994d923091a534870960fdae1e15e95e

[ "Apache-2.0" ]

6

2015-09-10T13:20:34.000Z

2021-02-15T08:10:27.000Z

src/peltak/core/templates/__init__.py

novopl/peltak

7c8ac44f994d923091a534870960fdae1e15e95e

[ "Apache-2.0" ]

41

2015-09-09T12:44:55.000Z

2021-06-01T23:25:56.000Z

src/peltak/core/templates/__init__.py

novopl/peltak

7c8ac44f994d923091a534870960fdae1e15e95e

[ "Apache-2.0" ]

null

# Copyright 2017-2020 Mateusz Klos # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """ .. module: peltak.core.templates :synopsis: Jinja2 templates support. ######################### Script template reference ######################### Using jinja filters ~~~~~~~~~~~~~~~~~~~ Let's suppose you have a scripts that runs pytest over your project and you want to pass the verbosity flag down to the pytest command. The verbosity option can be accessed with ``{{ opts.verbose }}`` but it is an ``int`` so we need to somehow convert it to the appropriate flag ``-v``, or ``-vv`` etc. Thankfully peltak already implements a filter to do just that, it's called ``count_flag`` and will convert a given number **N** to a flag that has the given letter appear **N** times. Here's a quick example. .. code-block:: yaml scripts: test: about: Run tests with pytest command: | pytest {{ opts.verbose | count_flag('v') }} {{ conf.src_dir }} This will result in the following command being invoked: .. code-block:: bash peltak run test # will result in: pytest src peltak run test -v # will result in: pytest src -v peltak run test -vv # will result in: pytest src -vv Template context ================ Peltak will inject the following context into the template. ================== ================================================================ Name Description ------------------ ---------------------------------------------------------------- ``conf`` | The entire configuration object. This is the dictionary | representation of `pelconf.yaml` and makes it easy to acess | any global configuration values from within a script. ``opts`` | Script command line options. This will contains all command | line options the script was called with. ``script`` | The script configuration as read from `pelconf.yaml`. | This will only contain the configuration for the currently | running script, not the entire **scripts:** section. ``ctx`` | Current runtime context. This is a value store that exists | only when peltak is running and is recreated on every run. | This is a way to share runtime information between commands | (things like **verbosity** or **pretend**). ``proj_path`` | A helper function. Given any project relative path (relative | to `pelconf.yaml`) it will convert it to an absolute path. ================== ================================================================ On top of all the values in the context, you can also use `/reference/script_filters`. Dev Reference ============= .. autoclass:: peltak.core.templates.Engine :members: """ from .engine import Engine # noqa: F401

36.892473

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0.598951

429

3,431

4.778555

0.482517

0.029268

0.023415

0.026341

0.030732

0

0.006088

0.234043

3,431

92

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null

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null

0

1

0

1

0

1

0

4

7331a964b4267b5974e1e6bb7f3874c7e54e7407

197

py

Python

Python/Database/test.py

SahaanaIyer/SEM4-folders

32721985cd40a18594313b04ade62dc5e486e3e5

[ "MIT" ]

null

Python/Database/test.py

SahaanaIyer/SEM4-folders

32721985cd40a18594313b04ade62dc5e486e3e5

[ "MIT" ]

null

Python/Database/test.py

SahaanaIyer/SEM4-folders

32721985cd40a18594313b04ade62dc5e486e3e5

[ "MIT" ]

null

import mysql.connector mydb = mysql.connector.connect(host="localhost",user="root",passwd="") print(mydb) if(mydb): print("Connection successful") else: print("Connection not successful")

21.888889

70

0.730964

24

197

6

0.666667

0.194444

0

0.111675

197

8

71

24.625

0.822857

0

0.299492

0

1

0

false

0.142857

0

0.142857

0.428571

1

0

null

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1

0

null

0

1

0

1

0

4

7338a09d01d6acfcf1188f71fb11fe7a6a4ec780

3,928

py

Python

tests/data/residues/HIS.py

uw-ipd/privileged_residues

78078c22ba537651a1b6bd1404c05246ab73a3e3

[ "Apache-2.0" ]

null

tests/data/residues/HIS.py

uw-ipd/privileged_residues

78078c22ba537651a1b6bd1404c05246ab73a3e3

[ "Apache-2.0" ]

20

2018-08-13T22:50:46.000Z

2018-11-03T22:29:03.000Z

tests/data/residues/HIS.py

uw-ipd/privileged_residues

78078c22ba537651a1b6bd1404c05246ab73a3e3

[ "Apache-2.0" ]

1

2018-08-25T06:03:43.000Z

from tests.util import pick_ray from pyrosetta import Pose from pyrosetta.rosetta.core.import_pose import pose_from_pdbstring name = "HIS" contents = """ ATOM 1 N ALA A 1 0.000 0.000 0.000 1.00 0.00 N ATOM 2 CA ALA A 1 1.458 0.000 0.000 1.00 0.00 C ATOM 3 C ALA A 1 2.009 1.420 0.000 1.00 0.00 C ATOM 4 O ALA A 1 1.251 2.390 0.000 1.00 0.00 O ATOM 5 CB ALA A 1 1.988 -0.773 -1.199 1.00 0.00 C ATOM 6 1H ALA A 1 -0.334 -0.943 -0.000 1.00 0.00 H ATOM 7 2H ALA A 1 -0.334 0.471 0.816 1.00 0.00 H ATOM 8 3H ALA A 1 -0.334 0.471 -0.816 1.00 0.00 H ATOM 9 HA ALA A 1 1.797 -0.490 0.913 1.00 0.00 H ATOM 10 1HB ALA A 1 3.078 -0.764 -1.185 1.00 0.00 H ATOM 11 2HB ALA A 1 1.633 -1.802 -1.154 1.00 0.00 H ATOM 12 3HB ALA A 1 1.633 -0.307 -2.117 1.00 0.00 H ATOM 13 N HIS A 2 3.332 1.536 0.000 1.00 0.00 N ATOM 14 CA HIS A 2 3.988 2.839 0.000 1.00 0.00 C ATOM 15 C HIS A 2 5.504 2.693 0.000 1.00 0.00 C ATOM 16 O HIS A 2 6.030 1.580 0.000 1.00 0.00 O ATOM 17 CB HIS A 2 3.548 3.665 1.213 1.00 0.00 C ATOM 18 CG HIS A 2 2.569 2.960 2.099 1.00 0.00 C ATOM 19 ND1 HIS A 2 2.113 1.685 1.837 1.00 0.00 N ATOM 20 CD2 HIS A 2 1.959 3.351 3.242 1.00 0.00 C ATOM 21 CE1 HIS A 2 1.264 1.322 2.782 1.00 0.00 C ATOM 22 NE2 HIS A 2 1.153 2.315 3.646 1.00 0.00 N ATOM 23 H HIS A 2 3.899 0.700 0.000 1.00 0.00 H ATOM 24 HA HIS A 2 3.702 3.361 -0.913 1.00 0.00 H ATOM 25 1HB HIS A 2 4.422 3.927 1.810 1.00 0.00 H ATOM 26 2HB HIS A 2 3.093 4.595 0.874 1.00 0.00 H ATOM 27 HD2 HIS A 2 2.083 4.309 3.748 1.00 0.00 H ATOM 28 HE1 HIS A 2 0.744 0.366 2.840 1.00 0.00 H ATOM 29 HE2 HIS A 2 0.571 2.317 4.472 1.00 0.00 H ATOM 30 N ALA A 3 6.202 3.823 0.000 1.00 0.00 N ATOM 31 CA ALA A 3 7.660 3.823 0.000 1.00 0.00 C ATOM 32 C ALA A 3 8.211 5.243 0.000 1.00 0.00 C ATOM 33 O ALA A 3 8.260 5.868 1.023 1.00 0.00 O ATOM 34 OXT ALA A 3 8.596 5.737 -1.023 1.00 0.00 O ATOM 35 CB ALA A 3 8.190 3.050 -1.199 1.00 0.00 C ATOM 36 H ALA A 3 5.710 4.705 -0.000 1.00 0.00 H ATOM 37 HA ALA A 3 7.999 3.333 0.913 1.00 0.00 H ATOM 38 1HB ALA A 3 9.280 3.059 -1.185 1.00 0.00 H ATOM 39 2HB ALA A 3 7.835 2.021 -1.154 1.00 0.00 H ATOM 40 3HB ALA A 3 7.835 3.516 -2.117 1.00 0.00 H TER """ pose = Pose() pose_from_pdbstring(pose, contents) n_rays = { 1: pick_ray(pose.residue(1), "1H", "N"), 2: pick_ray(pose.residue(2), "H", "N"), 3: pick_ray(pose.residue(3), "H", "N") } c_rays = { 1: pick_ray(pose.residue(1), "O", "C"), 2: pick_ray(pose.residue(2), "O", "C"), 3: pick_ray(pose.residue(3), "O", "C") } sc_donor = { 2: [ pick_ray(pose.residue(2), "HE2", "NE2") ] } sc_acceptor = { 2: [ pick_ray(pose.residue(2), "ND1", "CG") ] } cat_pi = [ (pick_ray(pose.residue(2), "CD2", "ND1"), pick_ray(pose.residue(2), "NE2", "ND1")) ]

47.902439

86

0.4389

799

3,928

2.131414

0.222778

0.070464

0.093952

0.140928

0.49677

0.453318

0.303582

0.262478

0.032883

0

0.414692

0.462831

3,928

81

87

48.493827

0.392417

0

0.027778

0

0.555556

0.815682

0

1

0

false

0

0.041667

0

0.041667

0

null

0

1

0

1

0

1

0

null

0

4

734bab73024ca1e585578dd27fa564806385bafa

447

py

Python

test/arithmetic-op.py

yalina2787/NovPython

363fccc0d5b7b234e8b86668cc4b41f3a86d227e

[ "Apache-2.0" ]

null

test/arithmetic-op.py

yalina2787/NovPython

363fccc0d5b7b234e8b86668cc4b41f3a86d227e

[ "Apache-2.0" ]

null

test/arithmetic-op.py

yalina2787/NovPython

363fccc0d5b7b234e8b86668cc4b41f3a86d227e

[ "Apache-2.0" ]

null

a=5 b=10 print("This file tests arithmetic operators") # test + - * / % < ( ) ^ # test assignment print("a:") print(a) print("b:") print(b) # test + print("a + b:") print(a + b) # test - print("a - b:") print(a - b) # test * print("a * b:") print(a * b) # test / print("a / b:") print(a / b) # test % print("a % b:") print(a % b) # test ^ print("a ^ b:") print(a ^ b) d = 1 print("d:") print(d) print("d^=10:") d ^= 10 print(d)

8.433962

45

0.498881

76

447

2.934211

0.184211

0.376682

0.295964

0.488789

0

0.023599

0.241611

447

52

46

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0.634218

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0

0.08

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false

0

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0

null

1

0

null

0

1

0

4

b41327b6d79c8138998b0068d5ddfa0bc399815b

10,177

py

Python

koocook_core/migrations/0001_initial.py

KooCook/koocook-dj

33bfaf48e8363013ddd083d5d8542496c50fd5d3

[ "BSD-3-Clause" ]

1

2020-10-19T04:44:49.000Z

koocook_core/migrations/0001_initial.py

KooCook/koocook-dj

33bfaf48e8363013ddd083d5d8542496c50fd5d3

[ "BSD-3-Clause" ]

26

2019-11-11T03:37:03.000Z

2019-12-15T23:18:18.000Z

koocook_core/migrations/0001_initial.py

KooCook/koocook-dj

33bfaf48e8363013ddd083d5d8542496c50fd5d3

[ "BSD-3-Clause" ]

1

2020-11-08T14:36:21.000Z

# Generated by Django 3.0 on 2019-12-15 22:07 import django.contrib.postgres.fields import django.contrib.postgres.fields.jsonb from django.db import migrations, models import django.db.models.deletion import koocook_core.models.base import koocook_core.models.review import koocook_core.support.markdown import koocook_core.support.quantity class Migration(migrations.Migration): initial = True dependencies = [ ('koocook_auth', '0001_initial'), ] operations = [ migrations.CreateModel( name='AggregateRating', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('rating_value', models.DecimalField(decimal_places=10, max_digits=13)), ('rating_count', models.IntegerField()), ('best_rating', models.IntegerField(default=5)), ('worst_rating', models.IntegerField(default=1)), ], ), migrations.CreateModel( name='Author', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=100)), ('user', models.OneToOneField(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='koocook_auth.KoocookUser')), ], bases=(koocook_core.models.base.SerialisableModel, models.Model), ), migrations.CreateModel( name='Comment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('date_published', models.DateTimeField(auto_now_add=True)), ('body', koocook_core.support.markdown.FormattedField()), ('aggregate_rating', models.OneToOneField(blank=True, null=True, on_delete=django.db.models.deletion.PROTECT, to='koocook_core.AggregateRating')), ('author', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='koocook_core.Author')), ('reviewed_comment', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Comment')), ], bases=(koocook_core.models.review.ReviewerModel, koocook_core.models.base.SerialisableModel, koocook_core.models.review.ReviewableModel, models.Model), ), migrations.CreateModel( name='MetaIngredient', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('nutrient', django.contrib.postgres.fields.jsonb.JSONField(default=dict)), ('description', models.CharField(blank=True, max_length=255, null=True)), ], ), migrations.CreateModel( name='Post', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('date_published', models.DateTimeField(auto_now_add=True)), ('body', koocook_core.support.markdown.FormattedField()), ('aggregate_rating', models.OneToOneField(blank=True, on_delete=django.db.models.deletion.PROTECT, to='koocook_core.AggregateRating')), ('author', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='koocook_core.Author')), ], bases=(koocook_core.models.base.SerialisableModel, koocook_core.models.review.ReviewableModel, models.Model), ), migrations.CreateModel( name='Recipe', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('image', django.contrib.postgres.fields.ArrayField(base_field=models.CharField(max_length=200), blank=True, null=True, size=None)), ('video', models.URLField(blank=True, null=True)), ('date_published', models.DateTimeField(auto_now_add=True, null=True)), ('description', models.TextField()), ('prep_time', models.DurationField(null=True)), ('cook_time', models.DurationField(null=True)), ('recipe_instructions', django.contrib.postgres.fields.ArrayField(base_field=models.TextField(), default=list, size=None)), ('recipe_yield', koocook_core.support.quantity.QuantityField(null=True)), ('aggregate_rating', models.OneToOneField(blank=True, on_delete=django.db.models.deletion.PROTECT, to='koocook_core.AggregateRating')), ('author', models.ForeignKey(null=True, on_delete=django.db.models.deletion.PROTECT, to='koocook_core.Author')), ], bases=(koocook_core.models.review.ReviewableModel, models.Model), ), migrations.CreateModel( name='RecipeEquipment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255, unique=True)), ], bases=(koocook_core.models.base.SerialisableModel, models.Model), ), migrations.CreateModel( name='TagLabel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ('level', models.IntegerField(default=1)), ], bases=(koocook_core.models.base.SerialisableModel, models.Model), ), migrations.CreateModel( name='Tag', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ('label', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='koocook_core.TagLabel')), ], options={ 'unique_together': {('name', 'label')}, }, bases=(koocook_core.models.base.SerialisableModel, models.Model), ), migrations.CreateModel( name='RecipeIngredient', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('quantity', koocook_core.support.quantity.QuantityField()), ('description', models.CharField(blank=True, max_length=255, null=True)), ('meta', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='koocook_core.MetaIngredient')), ('recipe', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Recipe')), ('substitute_set', models.ManyToManyField(blank=True, related_name='_recipeingredient_substitute_set_+', to='koocook_core.RecipeIngredient')), ], ), migrations.AddField( model_name='recipe', name='equipment_set', field=models.ManyToManyField(blank=True, to='koocook_core.RecipeEquipment'), ), migrations.AddField( model_name='recipe', name='tag_set', field=models.ManyToManyField(blank=True, to='koocook_core.Tag'), ), migrations.CreateModel( name='Rating', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('rating_value', models.IntegerField()), ('best_rating', models.IntegerField(default=5)), ('worst_rating', models.IntegerField(default=1)), ('used', models.BooleanField(blank=True, default=False)), ('author', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='koocook_core.Author')), ('reviewed_comment', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Comment')), ('reviewed_post', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Post')), ('reviewed_recipe', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Recipe')), ], bases=(koocook_core.models.review.ReviewerModel, models.Model), ), migrations.AddField( model_name='comment', name='reviewed_post', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Post'), ), migrations.AddField( model_name='comment', name='reviewed_recipe', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Recipe'), ), migrations.CreateModel( name='RecipeVisit', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('ip_address', models.CharField(max_length=45)), ('date_first_visited', models.DateTimeField(auto_now_add=True)), ('date_last_visited', models.DateTimeField(auto_now=True)), ('recipe', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='koocook_core.Recipe')), ('user', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='koocook_auth.KoocookUser')), ], options={ 'verbose_name': 'Recipe visit count', 'db_table': 'koocook_core_recipe_visit', 'unique_together': {('ip_address', 'user', 'recipe'), ('user', 'recipe')}, }, ), ]

55.612022

163

0.616783

1,036

10,177

5.892857

0.140927

0.072072

0.045864

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1

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1

0

null

0

4

b41988010feb4bbd03caeec15cac58f98225d3eb

481

py

Python

FIRMCORN/procedures/open_.py

mrTavas/owasp-fstm-auto

6e9ff36e46d885701c7419db3eca15f12063a7f3

[ "CC0-1.0" ]

2

2021-05-05T12:03:01.000Z

2021-06-04T14:27:15.000Z

FIRMCORN/procedures/open_.py

mrTavas/owasp-fstm-auto

6e9ff36e46d885701c7419db3eca15f12063a7f3

[ "CC0-1.0" ]

null

FIRMCORN/procedures/open_.py

mrTavas/owasp-fstm-auto

6e9ff36e46d885701c7419db3eca15f12063a7f3

[ "CC0-1.0" ]

2

2021-05-05T12:03:09.000Z

2021-06-04T14:27:21.000Z

from unicorn import * from unicorn.arm_const import * from unicorn.arm64_const import * from unicorn.x86_const import * from unicorn.mips_const import * class open_(): """ open """ def __init__(self , fc ,hc , enable_debug=True): self.fc = fc # firmcorn class, inherited from uc class self.hc = hc # hookcode class, inherited from object self.enable_debug = enable_debug def run(self ): print "open" return 1

24.05

62

0.640333

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481

4.698413

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0.22973

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0

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0.276507

481

20

63

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null

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0

null

0

1

0

null

0

1

0

1

0

4

b45ea5676f6973a759cfcf27b1ecb2916ddb9602

11,274

py

Python

pwnlib/dynelf.py

alexpark07/pwntools

c86022e844c8264ba4c35ed1dd5d55f1c76be90b

[ "MIT" ]

1

2015-04-21T11:30:28.000Z

pwnlib/dynelf.py

alexpark07/pwntools

c86022e844c8264ba4c35ed1dd5d55f1c76be90b

[ "MIT" ]

null

pwnlib/dynelf.py

alexpark07/pwntools

c86022e844c8264ba4c35ed1dd5d55f1c76be90b

[ "MIT" ]

null

from . import elf, log, memleak def sysv_hash(symbol): """sysv_hash(str) -> int Fallback hash function used in ELF files if .gnuhash is not present """ h = 0 g = 0 for c in symbol: h = (h << 4) + ord(c) g = h & 0xf0000000 h ^= (g >> 24) h &= ~g return h & 0xffffffff def gnu_hash(s): """gnu_hash(str) -> int Hash function used in the .gnuhash section of ELF files """ h = 5381 for c in s: h = h * 33 + ord(c) return h & 0xffffffff class DynELF(object): """DynELF is a tool for finding symbol addresses by leaking data from the .dynsym section. Args: path (filename/ELF object): the ELF file leak (MemLeak object): a memory leak for the ELF file base (int): base address for the binary """ def __init__(self, path, leak, base = None): if isinstance(path, elf.ELF): self.elf = path else: self.elf = elf.load(path) if isinstance(leak, memleak.MemLeak): self.leak = leak else: log.error('Leak must be a MemLeak object') self.PIE = (self.elf.elftype == 'DYN') self.base = base if self.PIE is False and self.base is None: for x in self.elf.segments: if x['type'] == 'LOAD' and 'E' in x['flg']: self.base = x['virtaddr'] break if self.base is None: log.error('Position independent ELF needs a base address') def bases(self): """Resolve base addresses of all loaded libraries. Return a dictionary mapping library path to its base address. """ if self.elf.elfclass == 'ELF32': return self._bases32() if self.elf.elfclass == 'ELF64': return self._bases64() def lookup (self, symb = None, lib = 'libc'): """Find the address of symbol, which is found in lib""" if self.elf.elfclass == 'ELF32': return self._lookup32(symb, lib) if self.elf.elfclass == 'ELF64': return self._lookup64(symb, lib) def _gotoff(self): sections = self.elf.sections return (sections['.got.plt'] if '.got.plt' in sections else sections['.got'])['addr'] def _bases32(self): bases = { } base = self.base leak = self.leak gotoff = self._gotoff() if base is None: pass # XXX: Read base address # else: # log.error('Position independent ELF needs a base address') else: if gotoff > base: gotplt = gotoff else: gotplt = base + gotoff link_map = leak.d(gotplt, 1) cur = link_map while cur: addr = leak.d(cur + 4) name = leak.s(addr) bases[name] = leak.d(cur) cur = leak.d(cur + 12) return bases def _bases64(self): bases = { } base = self.base leak = self.leak gotoff = self._gotoff() if base is None: pass # XXX: Read base address # else: # log.error('Position independent ELF needs a base address') else: if gotoff > base: gotplt = gotoff else: gotplt = base + gotoff link_map = leak.q(gotplt, 1) cur = link_map while cur: addr = leak.q(cur + 8) name = leak.s(addr) bases[name] = leak.q(cur) cur = leak.q(cur + 24) return bases def _lookup32 (self, symb, lib): base = self.base leak = self.leak gotoff = self._gotoff() if base is None: pass # XXX: Read base address # else: # log.error('Position independent ELF needs a base address') else: if gotoff > base: gotplt = gotoff else: gotplt = base + gotoff log.waitfor('Resolving "%s"' % symb) def status(s): log.status('Leaking %s' % s) status('link_map') link_map = leak.d(gotplt, 1) status('%s load address' % lib) cur = link_map while True: addr = leak.d(cur + 4) name = leak.s(addr) if lib in name: break cur = leak.d(cur + 12) libbase = leak.d(cur) if symb is None: return libbase dyn = leak.d(cur, 2) status('.gnu.hash, .strtab and .symtab offsets') cur = dyn hshtag = None hshtab = None strtab = None symtab = None while None in [hshtab, strtab, symtab]: tag = leak.d(dyn) if tag == 4: hshtab = leak.d(dyn, 1) hshtag = tag elif tag == 5: strtab = leak.d(dyn, 1) elif tag == 6: symtab = leak.d(dyn, 1) elif tag == 0x6ffffef5: hshtab = leak.d(dyn, 1) hshtag = tag dyn += 8 # with glibc the pointers are relocated whereas with f.x. uclibc they # are not if libbase > strtab: strtab += libbase symtab += libbase hshtab += libbase if hshtag == 4: status('.hash parms') nbuckets = leak.d(hshtab) bucketaddr = hshtab + 8 chain = hshtab + 8 + nbuckets * 4 status('hashmap') h = sysv_hash(symb) % nbuckets idx = leak.d(bucketaddr, h) while idx: sym = symtab + (idx * 16) symtype = leak.b(sym + 12) & 0xf if symtype == 2: #Function type symbol name = leak.s(strtab + leak.d(sym)) if name == symb: #Bingo log.done_success() return libbase + leak.d(sym, 1) idx = leak.d(chain, idx) else: status('.gnu.hash parms') nbuckets = leak.d(hshtab) symndx = leak.d(hshtab, 1) maskwords = leak.d(hshtab, 2) buckets = hshtab + 16 + 4 * maskwords chains = buckets + 4 * nbuckets status('hash chain index') hsh = gnu_hash(symb) bucket = hsh % nbuckets ndx = leak.d(buckets, bucket) chain = chains + 4 * (ndx - symndx) if ndx == 0: log.done_failure('Empty chain') return None status('hash chain') i = 0 hsh &= ~1 while True: hsh2 = leak.d(chain + (i * 4)) if hsh == (hsh2 & ~1): #Hash matches, but this may be a collision #Check symbol name too. sym = symtab + 16 * (ndx + i) name = leak.s(strtab + leak.d(sym)) if name == symb: break if hsh2 & 1: log.done_failure('No hash') return None i += 1 status('symbol offset') offset = leak.d(sym, 1) log.done_success() return offset + libbase def _lookup64 (self, symb, lib): base = self.base leak = self.leak gotoff = self._gotoff() if base is None: pass # XXX: Read base address # else: # log.error('Position independent ELF needs a base address') else: if gotoff > base: gotplt = gotoff else: gotplt = base + gotoff log.waitfor('Resolving "%s"' % symb) def status(s): log.status('Leaking %s' % s) status('link_map') link_map = leak.q(gotplt, 1) status('%s load address' % lib) cur = link_map while True: addr = leak.q(cur + 8) name = leak.s(addr) if lib in name: break cur = leak.q(cur + 24) libbase = leak.q(cur) if symb is None: return libbase dyn = leak.q(cur, 2) status('.gnu.hash/.hash, .strtab and .symtab offsets') cur = dyn hshtag = None hshtab = None strtab = None symtab = None while None in [hshtab, strtab, symtab]: tag = leak.q(cur) if tag == 4: hshtab = leak.q(cur, 1) hshtag = tag elif tag == 5: strtab = leak.q(cur, 1) elif tag == 6: symtab = leak.q(cur, 1) elif tag == 0x6ffffef5: hshtab = leak.q(cur, 1) hshtag = tag cur += 16 # with glibc the pointers are relocated whereas with f.x. uclibc they # are not if libbase > strtab: strtab += libbase symtab += libbase hshtab += libbase if hshtag == 4: status('.hash parms') nbuckets = leak.d(hshtab) bucketaddr = hshtab + 8 chain = hshtab + 8 + nbuckets * 4 status('hashmap') h = sysv_hash(symb) % nbuckets idx = leak.d(bucketaddr, h) while idx: sym = symtab + (idx * 24) symtype = leak.b(sym + 4) & 0xf if symtype == 2: #Function type symbol name = leak.s(strtab + leak.d(sym)) if name == symb: #Bingo log.done_success() return libbase + leak.q(sym, 1) idx = leak.d(chain, idx) else: status('.gnu.hash parms') nbuckets = leak.d(hshtab) symndx = leak.d(hshtab, 1) maskwords = leak.d(hshtab, 2) buckets = hshtab + 16 + 8 * maskwords chains = buckets + 4 * nbuckets status('hash chain index') hsh = gnu_hash(symb) bucket = hsh % nbuckets ndx = leak.d(buckets, bucket) chain = chains + 4 * (ndx - symndx) if ndx == 0: log.done_failure('Empty chain') return None status('hash chain') i = 0 hsh &= ~1 while True: hsh2 = leak.d(chain + (i * 4)) if hsh == (hsh2 & ~1): #Hash matches, but this may be a collision #Check symbol name too. sym = symtab + 24 * (ndx + i) name = leak.s(strtab + leak.d(sym)) if name == symb: break if hsh2 & 1: log.done_failure('No hash') return None i += 1 status('symbol offset') offset = leak.q(sym, 1) log.done_success() return offset + libbase

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4.011102

0.147502

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0.02669

0.755042

0.738039

0.719454

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0.64828

0.603005

0

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0.450417

11,274

368

95

30.63587

0.792608

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0

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1

0.041522

false

0.013841

0.00346

0

0.114187

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null

0

1

0

1

0

1

0

null

0

4

b4613159a0905c7c24dc1fcf3cb6fb3eaa90467b

3,389

py

Python

stubs.min/System/Windows/Forms/__init___parts/DataGridViewAdvancedBorderStyle.py

ricardyn/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

1

2021-02-02T13:39:16.000Z

stubs.min/System/Windows/Forms/__init___parts/DataGridViewAdvancedBorderStyle.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

stubs.min/System/Windows/Forms/__init___parts/DataGridViewAdvancedBorderStyle.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

class DataGridViewAdvancedBorderStyle(object,ICloneable): """ Contains border styles for the cells in a System.Windows.Forms.DataGridView control. DataGridViewAdvancedBorderStyle() """ def Equals(self,other): """ Equals(self: DataGridViewAdvancedBorderStyle,other: object) -> bool Determines whether the specified object is equal to the current System.Windows.Forms.DataGridViewAdvancedBorderStyle. other: An System.Object to be compared. Returns: true if other is a System.Windows.Forms.DataGridViewAdvancedBorderStyle and the values for the System.Windows.Forms.DataGridViewAdvancedBorderStyle.Top, System.Windows.Forms.DataGridViewAdvancedBorderStyle.Bottom, System.Windows.Forms.DataGridViewAdvancedBorderStyle.Left,and System.Windows.Forms.DataGridViewAdvancedBorderStyle.Right properties are equal to their counterpart in the current System.Windows.Forms.DataGridViewAdvancedBorderStyle; otherwise,false. """ pass def GetHashCode(self): """ GetHashCode(self: DataGridViewAdvancedBorderStyle) -> int """ pass def ToString(self): """ ToString(self: DataGridViewAdvancedBorderStyle) -> str Returns a string that represents the System.Windows.Forms.DataGridViewAdvancedBorderStyle. Returns: A string that represents the System.Windows.Forms.DataGridViewAdvancedBorderStyle. """ pass def __eq__(self,*args): """ x.__eq__(y) <==> x==y """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __ne__(self,*args): pass def __repr__(self,*args): """ __repr__(self: object) -> str """ pass def __str__(self,*args): pass All=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets or sets the border style for all of the borders of a cell. Get: All(self: DataGridViewAdvancedBorderStyle) -> DataGridViewAdvancedCellBorderStyle Set: All(self: DataGridViewAdvancedBorderStyle)=value """ Bottom=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets or sets the style for the bottom border of a cell. Get: Bottom(self: DataGridViewAdvancedBorderStyle) -> DataGridViewAdvancedCellBorderStyle Set: Bottom(self: DataGridViewAdvancedBorderStyle)=value """ Left=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the style for the left border of a cell. Get: Left(self: DataGridViewAdvancedBorderStyle) -> DataGridViewAdvancedCellBorderStyle Set: Left(self: DataGridViewAdvancedBorderStyle)=value """ Right=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the style for the right border of a cell. Get: Right(self: DataGridViewAdvancedBorderStyle) -> DataGridViewAdvancedCellBorderStyle Set: Right(self: DataGridViewAdvancedBorderStyle)=value """ Top=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the style for the top border of a cell. Get: Top(self: DataGridViewAdvancedBorderStyle) -> DataGridViewAdvancedCellBorderStyle Set: Top(self: DataGridViewAdvancedBorderStyle)=value """

36.44086

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365

3,389

6.627397

0.227397

0.062009

0.074411

0.182307

0.352212

0.304258

0.255477

0

0.168486

3,389

92

216

36.836957

0.85841

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0

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0

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false

0.363636

0

0.636364

0

null

0

1

0

null

0

1

0

1

0

1

0

4

b47743f3b6a0989a98dbe116e1d2b7d5c2061ec2

353

py

Python

academics/admin.py

judeakinwale/SMS-backup

30636591b43bec94e7406f4c02fde402a5a2e38f

[ "MIT" ]

null

academics/admin.py

judeakinwale/SMS-backup

30636591b43bec94e7406f4c02fde402a5a2e38f

[ "MIT" ]

null

academics/admin.py

judeakinwale/SMS-backup

30636591b43bec94e7406f4c02fde402a5a2e38f

[ "MIT" ]

null

from django.contrib import admin from academics import models # Register your models here. admin.site.register(models.Faculty) admin.site.register(models.Department) admin.site.register(models.Specialization) admin.site.register(models.Course) admin.site.register(models.Level) admin.site.register(models.Semester) admin.site.register(models.Session)

27.153846

42

0.830028

48

353

6.104167

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0.215017

0.406143

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0

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353

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0.885196

0.073654

0

1

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true

0

0.222222

0

0.222222

0

null

1

0

null

0

1

0

4

c30399fd9df446316351c0ad05bdc170e2502cba

191

py

Python

boa3_test/test_sc/built_in_methods_test/ExtendMutableSequence.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/built_in_methods_test/ExtendMutableSequence.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/built_in_methods_test/ExtendMutableSequence.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from typing import MutableSequence from boa3.builtin import public @public def Main() -> MutableSequence[int]: a: MutableSequence[int] = [1, 2, 3] a.extend([4, 5, 6]) return a

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4

c30be8414e501be2b04fd0a0e4d0eefbf4a5f188

225

py

Python

api/keyword_analysis/serializers.py

gpiechnik2/senter

6f64f5410fe02a5215ba148553dec45feaadcc09

[ "CC0-1.0" ]

2

2021-12-08T19:38:33.000Z

2022-01-26T15:02:57.000Z

api/keyword_analysis/serializers.py

gpiechnik2/senter

6f64f5410fe02a5215ba148553dec45feaadcc09

[ "CC0-1.0" ]

null

api/keyword_analysis/serializers.py

gpiechnik2/senter

6f64f5410fe02a5215ba148553dec45feaadcc09

[ "CC0-1.0" ]

1

2021-12-08T19:38:39.000Z

from rest_framework import serializers #from accounts.models import User class KeywordAnalysisSerializer(serializers.Serializer): keyword = serializers.CharField(max_length = 60, allow_null = False, allow_blank = False)

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225

6.923077

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null

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1

0

1

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4

c30f38601dc3996d4cb650cb32b340641846e026

137

py

Python

gym_poly_reactor/envs/__init__.py

cu-rie/gym-poly-reactor-rl

393b6023d3594222869b00e64be172c70ff9e0d1

[ "MIT" ]

2

2020-07-12T12:38:35.000Z

2020-12-29T11:45:27.000Z

gym_poly_reactor/envs/__init__.py

Junyoungpark/gym-poly-reactor

57e93cf8e5d84477846364434c09397ca62f7db4

[ "MIT" ]

null

gym_poly_reactor/envs/__init__.py

Junyoungpark/gym-poly-reactor

57e93cf8e5d84477846364434c09397ca62f7db4

[ "MIT" ]

null

from gym.envs.registration import register register( id='poly-reactor-v0', entry_point='gym_poly_reactor.envs:PolyReactor', )

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null

1

0

1

0

null

0

1

0

4

c316d6dea2ba8ac8d3c53151855a4cff64e68a07

90

py

Python

bala.py

Jonathan339/Asteroid

e134fb1a06d20230212e4c0a0965345d414acdec

[ "MIT" ]

null

bala.py

Jonathan339/Asteroid

e134fb1a06d20230212e4c0a0965345d414acdec

[ "MIT" ]

null

bala.py

Jonathan339/Asteroid

e134fb1a06d20230212e4c0a0965345d414acdec

[ "MIT" ]

null

class Bala: def __init__(self): self.image self.rect = self.image.get_rect(x=x, y=y)

18

43

0.688889

17

90

3.352941

0.588235

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0.155556

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null

1

0

1

0

null

0

1

0

4

c33dbcbfcdcd1fbf5208ee4c7d9047f62a25372f

2,232

py

Python

passwordlock_1.py

Anabella1109/Password-Lock

3b4dcad6b64d8392504e68e28bb98c8f318def66

[ "Unlicense" ]

null

passwordlock_1.py

Anabella1109/Password-Lock

3b4dcad6b64d8392504e68e28bb98c8f318def66

[ "Unlicense" ]

null

passwordlock_1.py

Anabella1109/Password-Lock

3b4dcad6b64d8392504e68e28bb98c8f318def66

[ "Unlicense" ]

null

import random class Credentials: ''' Class that generates new instances for acount credentials ''' credentials_list=[] # password_list=[a,,b,c,d,e,f] def __init__(self,account_name,username,password): ''' __init__ method that helps us define properties for our objects. Args: account_name: New account name username : New account username password: New account password ''' self.account_name=account_name self.username=username self.password=password def save_credentials(self): ''' save_credentials method saves credentials objects into credentials_list ''' Credentials.credentials_list.append(self) def delete_credentials(self): ''' delete_credentials method deletes saved credentials from the credentials_list ''' Credentials.credentials_list.remove(self) # def generate_password(self): # ''' # generate_password methods generates a random password for the user # ''' @classmethod def find_by_accountname(cls,accountname): ''' Method that takes in a name of an account and returns credentials that matches that account name. Args: accountname: account to search for Returns : Credentials of person that matches the account name. ''' for account in cls.credentials_list: if account.account_name == accountname: return account @classmethod def credentials_exist(cls,accountname): ''' Method that checks if a credentials exists from the credentials list. Args: number: Account name to search if it exists Returns : Boolean: True or false depending if the credentials exist ''' for account in cls.credentials_list: if account.account_name == accountname: return True return False @classmethod def display_credentials(cls): ''' method that returns the credentials list ''' return cls.credentials_list

27.555556

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2,232

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0.112782

0.058647

0.055639

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0.327957

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null

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1

0

1

0

1

0

4

c357f6ae7bee9431ac3ff6ba1f0174bf1561f36f

150

py

Python

tests/fixtures/bar_buc_command.py

rominf/cleo

72f6a8a19f26eefc32c3fcf9844484fc9a38583f

[ "MIT" ]

null

tests/fixtures/bar_buc_command.py

rominf/cleo

72f6a8a19f26eefc32c3fcf9844484fc9a38583f

[ "MIT" ]

null

tests/fixtures/bar_buc_command.py

rominf/cleo

72f6a8a19f26eefc32c3fcf9844484fc9a38583f

[ "MIT" ]

null

# -*- coding: utf-8 -*- from cleo.commands import Command class BarBucCommand(Command): def configure(self): self.set_name('bar:buc')

15

33

0.653333

19

150

5.105263

0.894737

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0.008333

0.2

150

9

34

16.666667

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false

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0.75

0

1

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null

0

1

0

null

0

1

0

1

0

4

c369221081db946d5f163231d9fc70c357679ed1

67

py

Python

rouse/response.py

baifei2014/crawl

2f6c1bb210b5f98f3ab60952184565aac6efc12e

[ "MIT" ]

14

2019-11-29T03:18:23.000Z

2020-04-07T20:25:19.000Z

rouse/response.py

baifei2014/crawl

2f6c1bb210b5f98f3ab60952184565aac6efc12e

[ "MIT" ]

null

rouse/response.py

baifei2014/crawl

2f6c1bb210b5f98f3ab60952184565aac6efc12e

[ "MIT" ]

null

from dss.Serializer import serializer class Response(object):

11.166667

37

0.776119

8

67

6.5

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0.164179

67

5

38

13.4

0.928571

0

null

0

0.5

null

0

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null

0

1

0

null

0

1

0

1

0

4

5eda8eabc5de0cf904805a2cf5c45813647c66a4

29

py

Python

mysql-utilities-1.6.0/mysql/utilities/common/__init__.py

bopopescu/mysql-dbcompare

1e912fd87282be3b3bed48487e6beb0ecb1de339

[ "Apache-2.0" ]

2

2018-03-20T07:42:58.000Z

2018-03-20T07:43:49.000Z

mysql-utilities-1.6.0/mysql/utilities/common/__init__.py

bopopescu/mysql-dbcompare

1e912fd87282be3b3bed48487e6beb0ecb1de339

[ "Apache-2.0" ]

null

mysql-utilities-1.6.0/mysql/utilities/common/__init__.py

bopopescu/mysql-dbcompare

1e912fd87282be3b3bed48487e6beb0ecb1de339

[ "Apache-2.0" ]

1

2020-07-23T23:07:08.000Z

"""mysql.utilities.common"""

14.5

28

0.689655

3

29

6.666667

1

0

0.034483

29

1

29

0.714286

0.758621

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

5edbd9d64db4ed4794a28a03ca8ca3b9f03c79fe

199

py

Python

src/app/server.py

procrastination-team/boombox.api

7ace839bfdd4c5fe0eaa5b7cbcef4f627673859b

[ "MIT" ]

null

src/app/server.py

procrastination-team/boombox.api

7ace839bfdd4c5fe0eaa5b7cbcef4f627673859b

[ "MIT" ]

11

2021-11-24T18:49:17.000Z

2021-12-21T14:31:57.000Z

src/app/server.py

procrastination-team/boombox.api

7ace839bfdd4c5fe0eaa5b7cbcef4f627673859b

[ "MIT" ]

null

import uvicorn from utils.log import get_uvicorn_config from .main import app def run_server(port: int): uvicorn.run(app, host="0.0.0.0", port=port, log_config=get_uvicorn_config())

19.9

81

0.718593

33

199

4.151515

0.484848

0.043796

0.233577

0

0.024242

0.170854

199

9

82

22.111111

0.806061

0

0.036842

0

1

0.2

false

0

0.6

0

0.8

0

null

0

1

0

1

0

null

0

1

0

1

0

4

5ee18efbf67a1e63a606f38350d5d23249cfaaef

183

py

Python

Save Model/load_model.py

Shubbair/machine-learning

93292911dd9fa526106b355e7c220153af263535

[ "MIT" ]

null

Save Model/load_model.py

Shubbair/machine-learning

93292911dd9fa526106b355e7c220153af263535

[ "MIT" ]

null

Save Model/load_model.py

Shubbair/machine-learning

93292911dd9fa526106b355e7c220153af263535

[ "MIT" ]

null

""" *** Hussain Salih Mahdi *** _________Shubbair__________ TODO Load a model """ import joblib house_model = joblib.load('house_model') print(house_model.predict([[5000]]))

13.071429

40

0.704918

21

183

5.095238

0.666667

0.280374

0

0.025641

0.147541

183

13

41

14.076923

0.660256

0.415301

0

0.114583

0

0.076923

0

1

0

false

0

0.333333

0

0.333333

1

0

null

1

0

null

0

1

0

1

0

4

5ef50aeb84019d260900de58d8452a1e5bb7e665

49

py

Python

fibonacci_serie.py

bssayla/something

beb550fa9867567dd77d009aa7766d1d5abb2f5e

[ "Unlicense" ]

2

2021-01-27T06:11:52.000Z

2021-05-10T22:46:53.000Z

fibonacci_serie.py

bssayla/something

beb550fa9867567dd77d009aa7766d1d5abb2f5e

[ "Unlicense" ]

null

fibonacci_serie.py

bssayla/something

beb550fa9867567dd77d009aa7766d1d5abb2f5e

[ "Unlicense" ]

null

a=0 b=1 while (True): a,b=b,a+b print(a)

8.166667

13

0.489796

13

49

1.846154

0.538462

0.166667

0

0.057143

0.285714

49

5

14

9.8

0.628571

0

1

0

false

0

0.2

1

null

0

1

0

null

0

4

6f0aa528b4b8a3288c90ecba6ebb50d2787533dc

261

py

Python

app/views/models/sessions.py

zhiyong-lv/flask-login

d8bf0719bae19ba8f7f44ea6d6a8ca65ba22aa63

[ "MIT" ]

null

app/views/models/sessions.py

zhiyong-lv/flask-login

d8bf0719bae19ba8f7f44ea6d6a8ca65ba22aa63

[ "MIT" ]

null

app/views/models/sessions.py

zhiyong-lv/flask-login

d8bf0719bae19ba8f7f44ea6d6a8ca65ba22aa63

[ "MIT" ]

null

from flask_restplus import Model, fields session_json = Model('Session Input', { 'username': fields.String(required=True, description='The user name', attribute='username'), 'password': fields.String(required=True, description='The user password'), })

37.285714

96

0.739464

31

261

6.16129

0.612903

0.125654

0.209424

0.251309

0.439791

0

0.118774

261

6

97

43.5

0.830435

0

0.256705

0

1

0

false

0.2

0

0.2

0

null

0

1

0

1

0

null

0

1

0

4

6f0d0757698c480899eb52326f372a63d0e95c72

32

py

Python

Taekwon/Python/baseGrammar/codeup052.py

sonnysorry/codingtest

478e0168e3209eb97b6b16910027bf12ccc3ccd0

[ "MIT" ]

2

2021-09-27T19:10:36.000Z

2021-11-09T05:40:39.000Z

Taekwon/Python/baseGrammar/codeup052.py

sonnysorry/codingtest

478e0168e3209eb97b6b16910027bf12ccc3ccd0

[ "MIT" ]

1

2021-11-15T14:56:54.000Z

Taekwon/Python/baseGrammar/codeup052.py

sonnysorry/codingtest

478e0168e3209eb97b6b16910027bf12ccc3ccd0

[ "MIT" ]

null

n = int(input()) print(bool(n))

10.666667

16

0.59375

6

32

3.166667

0.833333

0

0.125

32

2

17

16

0.678571

0

1

0

false

0

0.5

1

0

null

0

1

0

null

0

1

0

4

6f321d32c1a1f9716efb1fce076593f7c41533b0

230

py

Python

lib/eco/__init__.py

Existever/PyCFTrackers

3221e47aecca40de21ad9be875b2f8d960b4e09c

[ "MIT" ]

231

2019-04-01T08:04:40.000Z

2020-02-19T10:16:12.000Z

lib/eco/__init__.py

Existever/PyCFTrackers

3221e47aecca40de21ad9be875b2f8d960b4e09c

[ "MIT" ]

18

2020-04-17T03:52:02.000Z

2021-10-15T13:36:46.000Z

lib/eco/__init__.py

Existever/PyCFTrackers

3221e47aecca40de21ad9be875b2f8d960b4e09c

[ "MIT" ]

63

2020-02-24T15:21:12.000Z

2022-03-26T21:44:40.000Z

from .tracker import ECOTracker from .scale_filter import ScaleFilter from .optimize_score import optimize_score from .sample_space_model import GMM from .train import * from .config import gpu_config from .fourier_tools import *

28.75

42

0.83913

33

230

5.636364

0.545455

0.139785

0

0.121739

230

7

43

32.857143

0.920792

0

1

0

true

0

1

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1

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null

0

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null

0

1

0

1

0

1

0

4

6f402c1af305c7924e0cf51ca3dfe345f4e42f5f

226

py

Python

src/python/competition/client/__init__.py

miyamotok0105/Mario_AI_Competition2009

2fb527b45c9590deabb781f2959e458bc3882b72

[ "MIT" ]

1

2020-12-22T03:46:18.000Z

src/python/competition/client/__init__.py

miyamotok0105/Mario_AI_Competition2009

2fb527b45c9590deabb781f2959e458bc3882b72

[ "MIT" ]

null

src/python/competition/client/__init__.py

miyamotok0105/Mario_AI_Competition2009

2fb527b45c9590deabb781f2959e458bc3882b72

[ "MIT" ]

3

2020-11-22T11:49:41.000Z

2020-12-07T02:21:27.000Z

__author__="Sergey Karakovskiy, sergey at idsia fullstop ch" __date__ ="$May 13, 2009 12:17:14 AM$" from environment import Environment from tcpenvironment import TCPEnvironment from marioenvironment import MarioEnvironment

28.25

60

0.827434

28

226

6.392857

0.714286

0

0.060302

0.119469

226

7

61

32.285714

0.839196

0

0.324444

0

1

0

false

0

0.6

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6f4cbfe6639dc5c70fe6ae80c7ce86c5afa38295

93

py

Python

session02/redsocial/apps.py

Ngynx/Django-Projects

b9117eecb08b8517017c16b0303426c59b7fb482

[ "MIT" ]

null

session02/redsocial/apps.py

Ngynx/Django-Projects

b9117eecb08b8517017c16b0303426c59b7fb482

[ "MIT" ]

null

session02/redsocial/apps.py

Ngynx/Django-Projects

b9117eecb08b8517017c16b0303426c59b7fb482

[ "MIT" ]

null

from django.apps import AppConfig class RedsocialConfig(AppConfig): name = 'redsocial'

15.5

33

0.763441

10

93

7.1

0.9

0

0.16129

93

5

34

18.6

0.910256

0

0.096774

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6f5798fcd7a673d7a8e11ee3893164b7a7d82bd6

41

py

Python

5_Sorting_And_Searching/merge_sort.py

AnthonyRChao/Problem-Solving-With-Algorithms-And-Data-Structures

be29b46b9f4e579644ca2d44675c0ce7dcb29b3b

[ "MIT" ]

6

2020-09-28T08:18:01.000Z

2022-01-15T19:38:38.000Z

5_Sorting_And_Searching/merge_sort.py

AnthonyRChao/Problem-Solving-With-Algorithms-And-Data-Structures

be29b46b9f4e579644ca2d44675c0ce7dcb29b3b

[ "MIT" ]

null

5_Sorting_And_Searching/merge_sort.py

AnthonyRChao/Problem-Solving-With-Algorithms-And-Data-Structures

be29b46b9f4e579644ca2d44675c0ce7dcb29b3b

[ "MIT" ]

3

2020-09-28T08:18:05.000Z

2021-04-24T21:22:28.000Z

""" Implement a merge sort function. """

10.25

32

0.658537

5

41

5.4

1

0

0.170732

41

3

33

13.666667

0.794118

0.780488

0

null

0

null

0

null

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1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

6f5f58af266018bfe6619ca4e0e9b965c1a0e583

1,028

py

Python

credentials.py

Vector254/Password-locker

fd2b60d175a585bd9c73c117071a0434827facf0

[ "MIT" ]

null

credentials.py

Vector254/Password-locker

fd2b60d175a585bd9c73c117071a0434827facf0

[ "MIT" ]

null

credentials.py

Vector254/Password-locker

fd2b60d175a585bd9c73c117071a0434827facf0

[ "MIT" ]

null

class Credentials: """Class that generates new instances of credentials""" credentials_list=[] def __init__(self,account,username,password): """define properties for our objects.""" """object instantiaton""" self.account= account self.username = username self.password = password """function to add a new account to the credentials list""" def save_credential(self): Credentials.credentials_list.append(self) """function to display all available accounts""" def display_credential(): """ method that returns the credential array """ return Credentials.credentials_list def del_account(credential): Credentials.credentials_list.remove(credential) return credential def find_account(account): for credential in Credentials.credentials_list: if credential.account == account: return credential

26.358974

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0.144462

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26.358974

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null

0

1

0

1

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4

6f734b89eab0829dfdfcbda44b3e3cc9d7ed2e07

161

py

Python

dqn_zoo/constants.py

amarack/dqn_zoo

8d960fd37bd6dcf9dfd9fa87316630e78eb42350

[ "Apache-2.0" ]

null

dqn_zoo/constants.py

amarack/dqn_zoo

8d960fd37bd6dcf9dfd9fa87316630e78eb42350

[ "Apache-2.0" ]

null

dqn_zoo/constants.py

amarack/dqn_zoo

8d960fd37bd6dcf9dfd9fa87316630e78eb42350

[ "Apache-2.0" ]

1

2021-11-18T10:23:11.000Z

NO_PENALTY = 'no_penalty' HARD_CODED_PENALTY = 'hard_coded_penalty' UNCERTAINTY_PENALTY = 'uncertainty_penalty' POLICY_ENTROPY_PENALTY = 'policy_entropy_penalty'

40.25

49

0.857143

20

161

6.3

0.35

0.142857

0.253968

0.365079

0

0.068323

161

4

49

40.25

0.84

0

0.425926

0.135802

0

1

0

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0

1

0

null

0

1

0

1

0

null

0

4

488a71ce7275702b27474b80f62b6ac1df62d39b

50

py

Python

databases/seeds/__init__.py

vaibhavmule/sponsors

70256e14404e920087f291b0577477652ed4ab26

[ "MIT" ]

95

2018-02-22T23:54:00.000Z

2021-04-17T03:39:21.000Z

databases/seeds/__init__.py

vaibhavmule/sponsors

70256e14404e920087f291b0577477652ed4ab26

[ "MIT" ]

840

2018-01-27T04:26:20.000Z

2021-01-24T12:28:58.000Z

databases/seeds/__init__.py

vaibhavmule/sponsors

70256e14404e920087f291b0577477652ed4ab26

[ "MIT" ]

100

2018-02-23T00:19:55.000Z

2020-08-28T07:59:31.000Z

import os import sys sys.path.append(os.getcwd())

12.5

28

0.76

9

50

4.222222

0.666667

0

0.1

50

3

29

16.666667

0.844444

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0

0.666667

0

0.666667

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null

0

1

0

null

0

1

0

1

0

4

488d6f444d0deb176644334d8077164b7b4e1aae

614

py

Python

SVM/svm_solution.py

AxoyTO/ML-DL-DS-Python-Studies

ffef653190d1106e01244a4ea7f3f953b9d97882

[ "Unlicense" ]

null

SVM/svm_solution.py

AxoyTO/ML-DL-DS-Python-Studies

ffef653190d1106e01244a4ea7f3f953b9d97882

[ "Unlicense" ]

null

SVM/svm_solution.py

AxoyTO/ML-DL-DS-Python-Studies

ffef653190d1106e01244a4ea7f3f953b9d97882

[ "Unlicense" ]

1

2021-12-08T13:00:41.000Z

import numpy as np from sklearn.svm import SVC def train_svm_and_predict(train_features, train_target, test_features): """ train_features: np.array, (num_elements_train x num_features) - train data description, the same features and the same order as in train data train_target: np.array, (num_elements_train) - train data target test_features: np.array, (num_elements_test x num_features) -- some test data, features are in the same order as train features return: np.array, (num_elements_test) - test data predicted target, 1d array """ return np.ones(test_features.shape[0])

40.933333

145

0.750814

95

614

4.642105

0.347368

0.063492

0.090703

0.163265

0.240363

0

0.003945

0.174267

614

14

146

43.857143

0.865878

0.67101

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1

0.25

false

0

0.5

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1

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null

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1

0

null

0

1

0

1

0

1

0

4

4890bdfff154ea5a8a8d6bb68bcb66dfc8039907

147

py

Python

Week1/7. Euclid's division to get greatest common denominator.py

HawkingLaugh/Data-Processing-Using-Python

6c4d7e09317aee41684731d5611f2f0dab217b2b

[ "MIT" ]

null

Week1/7. Euclid's division to get greatest common denominator.py

HawkingLaugh/Data-Processing-Using-Python

6c4d7e09317aee41684731d5611f2f0dab217b2b

[ "MIT" ]

null

Week1/7. Euclid's division to get greatest common denominator.py

HawkingLaugh/Data-Processing-Using-Python

6c4d7e09317aee41684731d5611f2f0dab217b2b

[ "MIT" ]

null

x = eval(input('x = ')) y = eval(input('y = ')) if x < y: x, y = y, x while x % y != 0: r = x % y x = y y = r print('result = ', y)

16.333333

23

0.387755

29

147

1.965517

0.344828

0.210526

0.105263

0.140351

0.175439

0

0.01087

0.37415

147

9

24

16.333333

0.608696

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0.114865

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0.111111

1

0

1

null

1

0

1

0

null

0

4

48b69695bf08e6464bb695b2fb4086569ec20b88

142

py

Python

Desafios/desafio_014.py

romulogoleniesky/Python_C_E_V

2dcf5fb3505a20443788a284c52114c6434118ce

[ "MIT" ]

null

Desafios/desafio_014.py

romulogoleniesky/Python_C_E_V

2dcf5fb3505a20443788a284c52114c6434118ce

[ "MIT" ]

null

Desafios/desafio_014.py

romulogoleniesky/Python_C_E_V

2dcf5fb3505a20443788a284c52114c6434118ce

[ "MIT" ]

null

# Conversão de temperatura: temp = float(input("Digite uma temperatura em °C: ")) print(f'A temperatura de {temp}°C é {(temp * 9/5) + 32}°F')

35.5

59

0.661972

27

142

3.592593

0.666667

0.041237

0

0.033333

0.15493

142

3

60

47.333333

0.75

0.176056

0

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0

1

0

1

0

null

0

1

0

4

48c9b934eb1e8a48f0cb3886aeb4a8eeb6361100

4,335

py

Python

app/utility/terminal.py

venturiscm/hcp

74ad18180822301274daa9218d7bd9fbdb7807f7

[ "Apache-2.0" ]

1

2020-06-22T21:25:52.000Z

app/utility/terminal.py

venturiscm/hcp

74ad18180822301274daa9218d7bd9fbdb7807f7

[ "Apache-2.0" ]

1

2020-05-21T02:46:24.000Z

2020-05-25T07:19:23.000Z

app/utility/terminal.py

venturiscm/hcp

74ad18180822301274daa9218d7bd9fbdb7807f7

[ "Apache-2.0" ]

null

from zoneinfo import ZoneInfo from django.conf import settings from .runtime import Runtime import sys import re import colorful def colorize_data(data): if isinstance(data, dict): for key, value in data.items(): data[key] = colorize_data(value) elif isinstance(data, (list, tuple)): data = list(data) for index, value in enumerate(data): data[index] = colorize_data(value) elif isinstance(data, str): try: return colorful.format(data) except Exception as e: pass return data class TerminalMixin(object): def exit(self, code = 0): sys.exit(code) def format_time(self, date_time, format = "%Y-%m-%d %I:%M:%S %p"): return date_time.astimezone(ZoneInfo(settings.TIME_ZONE)).strftime(format) def print(self, message = '', stream = sys.stdout): with settings.DISPLAY_LOCK: plain_text = self.raw_text(message) if Runtime.color() and plain_text != message: try: colorful.print(message, file = stream) except Exception: stream.write(plain_text + "\n") else: stream.write(plain_text + "\n") def raw_text(self, message): message = re.sub(r'\{c\.[^\}]+\}', '', message) return message def style(self, style, message = None, func = True): def _format(output): if Runtime.color(): output = re.sub(r'([\{\}])', r'\1\1', str(output)) lines = [] for line in output.split("\n"): lines.append('{c.' + style + '}' + line + '{c.reset}') return "\n".join(lines) else: return output if not func or message is not None: return _format(str(message)) else: return _format def yellow(self, message = None, func = True): return self.style('yellow', message, func) def orange(self, message = None, func = True): return self.style('orange', message, func) def red(self, message = None, func = True): return self.style('red', message, func) def magenta(self, message = None, func = True): return self.style('magenta', message, func) def violet(self, message = None, func = True): return self.style('violet', message, func) def blue(self, message = None, func = True): return self.style('blue', message, func) def cyan(self, message = None, func = True): return self.style('cyan', message, func) def green(self, message = None, func = True): return self.style('green', message, func) def command_color(self, message = None, func = True): return self.style(settings.COMMAND_COLOR, message, func) def header_color(self, message = None, func = True): return self.style(settings.HEADER_COLOR, message, func) def key_color(self, message = None, func = True): return self.style(settings.KEY_COLOR, message, func) def value_color(self, message = None, func = True): return self.style(settings.VALUE_COLOR, message, func) def encrypted_color(self, message = None, func = True): return self.style(settings.ENCRYPTED_COLOR, message, func) def dynamic_color(self, message = None, func = True): return self.style(settings.DYNAMIC_COLOR, message, func) def relation_color(self, message = None, func = True): return self.style(settings.RELATION_COLOR, message, func) def prefix_color(self, message = None, func = True): return self.style(settings.PREFIX_COLOR, message, func) def success_color(self, message = None, func = True): return self.style(settings.SUCCESS_COLOR, message, func) def notice_color(self, message = None, func = True): return self.style(settings.NOTICE_COLOR, message, func) def warning_color(self, message = None, func = True): return self.style(settings.WARNING_COLOR, message, func) def error_color(self, message = None, func = True): return self.style(settings.ERROR_COLOR, message, func) def traceback_color(self, message = None, func = True): return self.style(settings.TRACEBACK_COLOR, message, func)

32.350746

82

0.609919

535

4,335

4.861682

0.198131

0.09727

0.126874

0.160707

0.41484

0.398693

0.37178

0.254902

0

0.000949

0.27105

4,335

133

83

32.593985

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0

0.074468

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0.024683

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0.297872

false

0.010638

0.06383

0.234043

0.680851

0.021277

0

null

0

1

0

null

0

1

0

1

0

4

48da3edc55edf95801a409e24f82cd03c46fa499

180

py

Python

mininetlab/test_ovs_afxdp.py

bobuhiro11/mininetlab

07c90ee8cdd6a0db66661ad103507a1aaef8f43a

[ "MIT" ]

5

2021-07-12T15:50:40.000Z

2022-03-04T15:23:56.000Z

mininetlab/test_ovs_afxdp.py

bobuhiro11/mininetlab

07c90ee8cdd6a0db66661ad103507a1aaef8f43a

[ "MIT" ]

null

mininetlab/test_ovs_afxdp.py

bobuhiro11/mininetlab

07c90ee8cdd6a0db66661ad103507a1aaef8f43a

[ "MIT" ]

null

import unittest from mininetlab.ovs_afxdp import run class TestRun(unittest.TestCase): def test_run(self): loss_rate = run() self.assertEqual(0.0, loss_rate)

20

40

0.705556

25

180

4.92

0.68

0.113821

0

0.013986

0.205556

180

8

41

22.5

0.846154

0

0.166667

1

0.166667

false

0

0.333333

0

0.666667

0

1

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null

0

1

0

null

0

1

0

1

0

4

48e9bed1a31581adb6fb010b800dd2c01d010a95

89

py

Python

pymba/__init__.py

sudheerExperiments/pymba

3284016df2b110e69493f45a19daef902005d9c3

[ "MIT" ]

null

pymba/__init__.py

sudheerExperiments/pymba

3284016df2b110e69493f45a19daef902005d9c3

[ "MIT" ]

null

pymba/__init__.py

sudheerExperiments/pymba

3284016df2b110e69493f45a19daef902005d9c3

[ "MIT" ]

null

from .vimba import Vimba, VimbaException from .frame import Frame __version__ = '0.3.4'

17.8

40

0.764045

13

89

4.923077

0.692308

0

0.039474

0.146067

89

4

41

22.25

0.802632

0

0.05618

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

48f084f5d73a645d904ad689de7aa76d307971a7

224

py

Python

evalml/preprocessing/data_splitters/__init__.py

RG4421/evalml

33c62abe6d107d1da2f54e9e44a90f18aaf916a9

[ "BSD-3-Clause" ]

null

evalml/preprocessing/data_splitters/__init__.py

RG4421/evalml

33c62abe6d107d1da2f54e9e44a90f18aaf916a9

[ "BSD-3-Clause" ]

13

2021-03-04T19:29:09.000Z

2022-03-07T01:00:43.000Z

evalml/preprocessing/data_splitters/__init__.py

RG4421/evalml

33c62abe6d107d1da2f54e9e44a90f18aaf916a9

[ "BSD-3-Clause" ]

null

from .training_validation_split import TrainingValidationSplit from .time_series_split import TimeSeriesSplit from .balanced_classification_splitter import BalancedClassificationSampler from .sampler_base import SamplerBase

44.8

75

0.910714

23

224

8.565217

0.695652

0.111675

0

0.071429

224

4

76

56

0.947115

0

1

0

true

0

1

0

1

0

1

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null

0

1

0

null

0

1

0

1

0

4

d29faec739bdc00ea40569f3eb3d5e7531ca08d1

114

py

Python

eb_sqs/apps.py

rebotics/django-eb-sqs

10de0ebfca1de0bce3a300a4280f92649f10c97e

[ "MIT" ]

null

eb_sqs/apps.py

rebotics/django-eb-sqs

10de0ebfca1de0bce3a300a4280f92649f10c97e

[ "MIT" ]

null

eb_sqs/apps.py

rebotics/django-eb-sqs

10de0ebfca1de0bce3a300a4280f92649f10c97e

[ "MIT" ]

null

from django.apps import AppConfig class EbSqsConfig(AppConfig): name = 'eb_sqs' verbose_name = 'EB SQS'

16.285714

33

0.710526

15

114

5.266667

0.733333

0.151899

0.227848

0

0.201754

114

6

34

19

0.868132

0

0.105263

0

1

0

false

0

0.25

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

4

d2bc237a95b3258f1a7bede6065ddf5da53dcd8a

413

py

Python

tests/test_colmet_collector.py

oar-team/colmet-collector

b962a84574093adfd4a1c1877277b96119d5fe77

[ "BSD-3-Clause" ]

null

tests/test_colmet_collector.py

oar-team/colmet-collector

b962a84574093adfd4a1c1877277b96119d5fe77

[ "BSD-3-Clause" ]

null

tests/test_colmet_collector.py

oar-team/colmet-collector

b962a84574093adfd4a1c1877277b96119d5fe77

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ test_colmet_collector ---------------------------------- Tests for `colmet_collector` module. """ import unittest from colmet_collector import colmet_collector class TestColmetCollector(object): @classmethod def setup_class(cls): pass def test_something(self): pass @classmethod def teardown_class(cls): pass

14.241379

45

0.615012

43

413

5.72093

0.627907

0.243902

0.097561

0

0.003077

0.213075

413

28

46

14.75

0.753846

0.331719

0

0.454545

0

1

0.272727

false

0.272727

0.181818

0

0.545455

0

null

1

0

null

0

1

0

1

0

1

0

4

d2ff509e87d8b7f52defaee619e29e7278e5f322

56

py

Python

src/atomate2/vasp/sets/__init__.py

Zhuoying/atomate2

4501c8ff2a72243dee51afb17d93ecff426b3e8c

[ "BSD-3-Clause-LBNL" ]

14

2021-09-24T05:18:02.000Z

2022-03-31T23:12:47.000Z

src/atomate2/vasp/sets/__init__.py

Zhuoying/atomate2

4501c8ff2a72243dee51afb17d93ecff426b3e8c

[ "BSD-3-Clause-LBNL" ]

83

2021-11-02T17:19:57.000Z

2022-03-31T17:27:00.000Z

src/atomate2/vasp/sets/__init__.py

Zhuoying/atomate2

4501c8ff2a72243dee51afb17d93ecff426b3e8c

[ "BSD-3-Clause-LBNL" ]

11

2021-11-19T09:50:45.000Z

2022-03-31T05:56:39.000Z

"""Module defining VASP input sets used in atomate2."""

28

55

0.732143

8

56

5.125

1

0

0.020833

0.142857

56

1

56

0.833333

0.875

0

null

0

null

0

null

0

null

1

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true

0

null

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0

1

0

1

0

null

0

1

0

4

960007724a367b039c3b131b8d6eacc11c38786a

149

py

Python

news_crawler/news_crawler/items.py

guimaraescca/scrapy-examples

1d6d5d222f598719f37b1dea4347873ad719ad2d

[ "MIT" ]

null

news_crawler/news_crawler/items.py

guimaraescca/scrapy-examples

1d6d5d222f598719f37b1dea4347873ad719ad2d

[ "MIT" ]

null

news_crawler/news_crawler/items.py

guimaraescca/scrapy-examples

1d6d5d222f598719f37b1dea4347873ad719ad2d

[ "MIT" ]

null

import scrapy class NewsItem(scrapy.Item): date = scrapy.Field() title = scrapy.Field() url = scrapy.Field() text = scrapy.Field()

16.555556

28

0.637584

18

149

5.277778

0.555556

0.463158

0

0.228188

149

8

29

18.625

0.826087

0

1

0

false

0

0.166667

0

1

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1

0

null

1

0

1

0

null

0

1

0

4

960f832fd3ae8fb15c7f803fd4847e0262718280

706

py

Python

Shishkin_Anatoliy_lesson_11/checker/__init__.py

amilykh/2074_GB_Python_1-

0112ad710154623ad1dafffbdb413caeff424813

[ "MIT" ]

3

2022-01-17T20:38:22.000Z

2022-01-19T04:19:50.000Z

Shishkin_Anatoliy_lesson_11/checker/__init__.py

amilykh/2074_GB_Python_1-

0112ad710154623ad1dafffbdb413caeff424813

[ "MIT" ]

5

2022-01-24T11:08:42.000Z

2022-03-03T00:15:22.000Z

Shishkin_Anatoliy_lesson_11/checker/__init__.py

amilykh/2074_GB_Python_1-

0112ad710154623ad1dafffbdb413caeff424813

[ "MIT" ]

18

2022-01-18T05:56:00.000Z

2022-02-28T10:30:18.000Z

""" Модуль checker предназначен для проверки доступности внешних сайтов * Импортируйте через 'from checker import Checker' * Инициализируйте объект `checker = Checker() * Подготовьте словарь с данными по проверяемым ресурсами. Формат словаря: data = {'Название': 'Адрес проверяемого ресурса', ...} * Подготовьте чекер к работе с ресурсами 'cheker.prepare_app(data)' * Запускайте автоматическую проверку всех ресурсов 'checker.get_info()' * Лог ошибок отсматривайте в файле checker.log, который создаётся автоматически на одном уровне местом хранения корневой директории модуля checker """ from .component.models import SiteInfo, Storage from .models import Checker

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0

4

825795a59164d2d424dfa95ff34576a76dedb07b

42

py

Python

examples/bool_op.py

doboy/Underscore

d98273db3144cda79191d2c90f45d81b6d700b1f

[ "MIT" ]

7

2016-09-23T00:44:05.000Z

2021-10-04T21:19:12.000Z

examples/bool_op.py

jameswu1991/Underscore

d98273db3144cda79191d2c90f45d81b6d700b1f

[ "MIT" ]

1

2016-09-23T00:45:05.000Z

2019-02-16T19:05:37.000Z

examples/bool_op.py

jameswu1991/Underscore

d98273db3144cda79191d2c90f45d81b6d700b1f

[ "MIT" ]

3

2016-09-23T01:13:15.000Z

2018-07-20T21:22:17.000Z

x = False y = 3 z = 9 print(x or y and z)

8.4

19

0.547619

12

42

1.916667

0.75

0

0.071429

0.333333

42

4

20

10.5

0.75

0

1

0

false

0

0.25

1

null

0

1

0

null

0

4

82736a429b0e32268f61930af81df864ed824453

93

py

Python

deprecated/goal_util.py

djp42/IntentionPrediction

9f260133f4b649e446166775b54885147d78393c

[ "MIT" ]

25

2019-02-21T18:47:11.000Z

2022-03-21T02:53:33.000Z

lib/goal_util.py

zhangzhangzf/IntentionPrediction

558a2c0487e23151624ff4b1f284f654860579cc

[ "MIT" ]

6

2020-01-28T22:48:39.000Z

2022-02-10T00:12:09.000Z

lib/goal_util.py

zhangzhangzf/IntentionPrediction

558a2c0487e23151624ff4b1f284f654860579cc

[ "MIT" ]

6

2018-07-11T08:38:42.000Z

2021-09-28T08:02:30.000Z

# -*- coding: utf-8 -*- """ Created on Mon Aug 1 11:15:21 2016 @author: LordPhillips """ s

11.625

35

0.591398

15

93

3.666667

1

0

0.162162

0.204301

93

8

36

11.625

0.581081

0.870968

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

4

828127f6dc54c67f460746b06b25a1040daf6bc5

44

py

Python

text/_elisp/window/_op/display.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/_elisp/window/_op/display.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/_elisp/window/_op/display.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

""" Operators for displaying buffers. """

7.333333

33

0.659091

4

44

7.25

1

0

0.181818

44

5

34

8.8

0.805556

0.75

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

829cb6816126c1d26b1b14b6403804c992c47ad6

43

py

Python

pepperbot/__init__.py

SSmJaE/PepperBot

0f34c90fc8f6d90fd8881193992d0dde756c2dde

[ "MIT" ]

27

2021-03-26T16:17:38.000Z

2022-03-30T21:39:07.000Z

pepperbot/__init__.py

SSmJaE/PepperBot

0f34c90fc8f6d90fd8881193992d0dde756c2dde

[ "MIT" ]

null

pepperbot/__init__.py

SSmJaE/PepperBot

0f34c90fc8f6d90fd8881193992d0dde756c2dde

[ "MIT" ]

7

2021-05-27T17:28:37.000Z

2021-12-22T11:22:08.000Z

__version__ = "0.1.0" from .main import *

10.75

21

0.651163

7

43

3.428571

0.857143

0

0.085714

0.186047

43

3

22

14.333333

0.6

0

0.116279

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

82bb10cb289063a12ba7730b3efa772eb7b9c4d1

2,145

py

Python

lenstools/utils/fft.py

asabyr/LensTools

e155d6d39361e550906cec00dbbc57686a4bca5c

[ "MIT" ]

1

2021-04-27T02:03:11.000Z

lenstools/utils/fft.py

asabyr/LensTools

e155d6d39361e550906cec00dbbc57686a4bca5c

[ "MIT" ]

null

lenstools/utils/fft.py

asabyr/LensTools

e155d6d39361e550906cec00dbbc57686a4bca5c

[ "MIT" ]

null

from __future__ import division from abc import ABCMeta,abstractproperty,abstractmethod import numpy as np ############################################## ###########FFTEngine abstract class########### ############################################## class FFTEngine(object): __metaclass__ = ABCMeta """ Class handler of Fourier transforms needed for lenstools computations """ ##################################################################### ######################Abstract methods############################### ##################################################################### @abstractmethod def fft2(self,x): pass @abstractmethod def ifft2(self,x): pass @abstractmethod def rfft2(self,x): pass @abstractmethod def irfft2(self,x): pass @abstractmethod def rfftn(self,x): pass @abstractmethod def irfftn(self,x): pass ################################################################################### ######################Default, non--abstract methods############################### ################################################################################### def fftfreq(self,n): return np.fft.fftfreq(n) def rfftfreq(self,n,d=1.0): if not (isinstance(n,int)): raise ValueError("n should be an integer") val = 1.0/(n*d) n_half = n//2 + 1 results = np.arange(0, n_half, dtype=int) return results * val ############################################## ###########NUMPYFFTPack class################# ############################################## class NUMPYFFTPack(FFTEngine): ############################################################################################### #########################Abstract methods implementation####################################### ############################################################################################### def fft2(self,x): return np.fft.fft2(x) def ifft2(self,x): return np.fft.ifft2(x) def rfft2(self,x): return np.fft.rfft2(x) def irfft2(self,x): return np.fft.irfft2(x) def rfftn(self,x): return np.fft.rfftn(x) def irfftn(self,x): return np.fft.irfftn(x)

22.819149

96

0.402797

184

2,145

4.641304

0.342391

0.070258

0.090164

0.091335

0.264637

0

0.009995

0.113753

2,145

93

97

23.064516

0.439243

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0

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0

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1

0.311111

false

0.133333

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0.155556

0.622222

0

null

0

1

0

null

0

1

0

1

0

1

0

4

82d43e30f0a28b08269b15a6371c30a6607c5fb1

140

py

Python

pyalp/apps/music/admin.py

Mause/pyalp

fb0f723070e11f8c9ed57e2475eb963599f442a6

[ "MIT" ]

null

pyalp/apps/music/admin.py

Mause/pyalp

fb0f723070e11f8c9ed57e2475eb963599f442a6

[ "MIT" ]

2

2021-06-08T19:32:48.000Z

2022-03-11T23:17:45.000Z

pyalp/apps/music/admin.py

Mause/pyalp

fb0f723070e11f8c9ed57e2475eb963599f442a6

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from apps.music.models import Song, Vote admin.site.register([Song, Vote])

17.5

40

0.771429

21

140

5.142857

0.666667

0.148148

0

0.135714

140

7

41

20

0.892562

0.185714

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

82dfd077d5358e7730a873236fe831a809a644f6

799

py

Python

app/models/__init__.py

Anioko/landingpage_cms

b2d68d28287dd163de7d420b2c20b19050a2326a

[ "MIT" ]

null

app/models/__init__.py

Anioko/landingpage_cms

b2d68d28287dd163de7d420b2c20b19050a2326a

[ "MIT" ]

null

app/models/__init__.py

Anioko/landingpage_cms

b2d68d28287dd163de7d420b2c20b19050a2326a

[ "MIT" ]

null

""" These imports enable us to make all defined models members of the models module (as opposed to just their python files) """ from .user import * # noqa from .miscellaneous import * # noqa from .services import * # noqa from .team import * # noqa from .portfolio import * # noqa from .about import * # noqa from .contact import * # noqa from .organisation import * # noqa from .photo import * # noqa from .logo import * # noqa from .call2action import * # noqa from .testimonial import * # noqa from .social import * # noqa from .tracking import * # noqa from .html import * # noqa from .brands import * # noqa from .newslink import * # noqa from .blog import * # noqa from .orgstaff import * # noqa from .teamsection import * # noqa from .testimonialsection import * # noqa

29.592593

72

0.697121

105

799

5.304762

0.409524

0.37702

0.502693

0

0.001592

0.214018

799

26

73

30.730769

0.88535

0.281602

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

4

7d57a03d5d0b9eb620b5f123e03ecfc8fe13daf4

662

py

Python

env/lib/python3.5/site-packages/terminado/uimodule.py

riordan/who-owns-what

62538fdb6d40ed1e0cdafb0df388be95fb388907

[ "Apache-2.0" ]

4

2018-01-19T17:15:06.000Z

2018-01-24T00:06:42.000Z

Python/PythonProgrammingLanguage/Encapsulation/encap_env/lib/python3.5/site-packages/terminado/uimodule.py

nitin-cherian/LifeLongLearning

84084792058358365162c645742c70064a2d5fd6

[ "MIT" ]

10

2017-07-13T00:24:03.000Z

2017-07-17T07:39:03.000Z

Python/PythonProgrammingLanguage/Encapsulation/encap_env/lib/python3.5/site-packages/terminado/uimodule.py

nitin-cherian/LifeLongLearning

84084792058358365162c645742c70064a2d5fd6

[ "MIT" ]

7

2017-08-01T04:02:07.000Z

2018-10-06T21:07:20.000Z

import os.path import tornado.web class Terminal(tornado.web.UIModule): def render(self, ws_url, cols=80, rows=25): return ('<div class="terminado-container" ' 'data-ws-url="{ws_url}" ' 'data-rows="{rows}" data-cols="{cols}"/>').format( ws_url=ws_url, rows=rows, cols=cols) def javascript_files(self): # TODO: Can we calculate these dynamically? return ['/xstatic/termjs/term.js', '/static/terminado.js'] def embedded_javascript(self): file = os.path.join(os.path.dirname(__file__), 'uimod_embed.js') with open(file) as f: return f.read()

34.842105

72

0.595166

86

662

4.453488

0.546512

0.065274

0.036554

0.052219

0

0.008114

0.255287

662

18

73

36.777778

0.768763

0.061934

0

0.245557

0.116317

0

0.055556

0

1

0.214286

false

0

0.142857

0.642857

0

null

0

null

0

1

0

1

0

1

0

4

7d9b8e0c84f08776bba6b7718f6f08413f10857f

10,717

py

Python

catkin_ws/devel/lib/python2.7/dist-packages/duckietown_msgs/msg/_LEDDetection.py

bendychua/final

35fd0477ec5950479f0e082a65db2aa05a92db82

[ "CC-BY-2.0" ]

1

2019-05-13T00:40:11.000Z

catkin_ws/devel/lib/python2.7/dist-packages/duckietown_msgs/msg/_LEDDetection.py

bendychua/final

35fd0477ec5950479f0e082a65db2aa05a92db82

[ "CC-BY-2.0" ]

null

catkin_ws/devel/lib/python2.7/dist-packages/duckietown_msgs/msg/_LEDDetection.py

bendychua/final

35fd0477ec5950479f0e082a65db2aa05a92db82

[ "CC-BY-2.0" ]

null

# This Python file uses the following encoding: utf-8 """autogenerated by genpy from duckietown_msgs/LEDDetection.msg. Do not edit.""" import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct import duckietown_msgs.msg import genpy class LEDDetection(genpy.Message): _md5sum = "d1ac8691d7a30e838dc372a724aee94b" _type = "duckietown_msgs/LEDDetection" _has_header = False #flag to mark the presence of a Header object _full_text = """time timestamp1 # initial timestamp of the camera stream used time timestamp2 # final timestamp of the camera stream used Vector2D pixels_normalized float32 frequency string color # will be ‘r’, ‘g’ or ‘b’ float32 confidence # some value of confidence for the detection (TBD) # for debug/visualization float64[] signal_ts float32[] signal float32[] fft_fs float32[] fft ================================================================================ MSG: duckietown_msgs/Vector2D float32 x float32 y """ __slots__ = ['timestamp1','timestamp2','pixels_normalized','frequency','color','confidence','signal_ts','signal','fft_fs','fft'] _slot_types = ['time','time','duckietown_msgs/Vector2D','float32','string','float32','float64[]','float32[]','float32[]','float32[]'] def __init__(self, *args, **kwds): """ Constructor. Any message fields that are implicitly/explicitly set to None will be assigned a default value. The recommend use is keyword arguments as this is more robust to future message changes. You cannot mix in-order arguments and keyword arguments. The available fields are: timestamp1,timestamp2,pixels_normalized,frequency,color,confidence,signal_ts,signal,fft_fs,fft :param args: complete set of field values, in .msg order :param kwds: use keyword arguments corresponding to message field names to set specific fields. """ if args or kwds: super(LEDDetection, self).__init__(*args, **kwds) #message fields cannot be None, assign default values for those that are if self.timestamp1 is None: self.timestamp1 = genpy.Time() if self.timestamp2 is None: self.timestamp2 = genpy.Time() if self.pixels_normalized is None: self.pixels_normalized = duckietown_msgs.msg.Vector2D() if self.frequency is None: self.frequency = 0. if self.color is None: self.color = '' if self.confidence is None: self.confidence = 0. if self.signal_ts is None: self.signal_ts = [] if self.signal is None: self.signal = [] if self.fft_fs is None: self.fft_fs = [] if self.fft is None: self.fft = [] else: self.timestamp1 = genpy.Time() self.timestamp2 = genpy.Time() self.pixels_normalized = duckietown_msgs.msg.Vector2D() self.frequency = 0. self.color = '' self.confidence = 0. self.signal_ts = [] self.signal = [] self.fft_fs = [] self.fft = [] def _get_types(self): """ internal API method """ return self._slot_types def serialize(self, buff): """ serialize message into buffer :param buff: buffer, ``StringIO`` """ try: _x = self buff.write(_struct_4I3f.pack(_x.timestamp1.secs, _x.timestamp1.nsecs, _x.timestamp2.secs, _x.timestamp2.nsecs, _x.pixels_normalized.x, _x.pixels_normalized.y, _x.frequency)) _x = self.color length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) if python3: buff.write(struct.pack('<I%sB'%length, length, *_x)) else: buff.write(struct.pack('<I%ss'%length, length, _x)) buff.write(_struct_f.pack(self.confidence)) length = len(self.signal_ts) buff.write(_struct_I.pack(length)) pattern = '<%sd'%length buff.write(struct.pack(pattern, *self.signal_ts)) length = len(self.signal) buff.write(_struct_I.pack(length)) pattern = '<%sf'%length buff.write(struct.pack(pattern, *self.signal)) length = len(self.fft_fs) buff.write(_struct_I.pack(length)) pattern = '<%sf'%length buff.write(struct.pack(pattern, *self.fft_fs)) length = len(self.fft) buff.write(_struct_I.pack(length)) pattern = '<%sf'%length buff.write(struct.pack(pattern, *self.fft)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(_x)))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(_x)))) def deserialize(self, str): """ unpack serialized message in str into this message instance :param str: byte array of serialized message, ``str`` """ try: if self.timestamp1 is None: self.timestamp1 = genpy.Time() if self.timestamp2 is None: self.timestamp2 = genpy.Time() if self.pixels_normalized is None: self.pixels_normalized = duckietown_msgs.msg.Vector2D() end = 0 _x = self start = end end += 28 (_x.timestamp1.secs, _x.timestamp1.nsecs, _x.timestamp2.secs, _x.timestamp2.nsecs, _x.pixels_normalized.x, _x.pixels_normalized.y, _x.frequency,) = _struct_4I3f.unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.color = str[start:end].decode('utf-8') else: self.color = str[start:end] start = end end += 4 (self.confidence,) = _struct_f.unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sd'%length start = end end += struct.calcsize(pattern) self.signal_ts = struct.unpack(pattern, str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sf'%length start = end end += struct.calcsize(pattern) self.signal = struct.unpack(pattern, str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sf'%length start = end end += struct.calcsize(pattern) self.fft_fs = struct.unpack(pattern, str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sf'%length start = end end += struct.calcsize(pattern) self.fft = struct.unpack(pattern, str[start:end]) self.timestamp1.canon() self.timestamp2.canon() return self except struct.error as e: raise genpy.DeserializationError(e) #most likely buffer underfill def serialize_numpy(self, buff, numpy): """ serialize message with numpy array types into buffer :param buff: buffer, ``StringIO`` :param numpy: numpy python module """ try: _x = self buff.write(_struct_4I3f.pack(_x.timestamp1.secs, _x.timestamp1.nsecs, _x.timestamp2.secs, _x.timestamp2.nsecs, _x.pixels_normalized.x, _x.pixels_normalized.y, _x.frequency)) _x = self.color length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) if python3: buff.write(struct.pack('<I%sB'%length, length, *_x)) else: buff.write(struct.pack('<I%ss'%length, length, _x)) buff.write(_struct_f.pack(self.confidence)) length = len(self.signal_ts) buff.write(_struct_I.pack(length)) pattern = '<%sd'%length buff.write(self.signal_ts.tostring()) length = len(self.signal) buff.write(_struct_I.pack(length)) pattern = '<%sf'%length buff.write(self.signal.tostring()) length = len(self.fft_fs) buff.write(_struct_I.pack(length)) pattern = '<%sf'%length buff.write(self.fft_fs.tostring()) length = len(self.fft) buff.write(_struct_I.pack(length)) pattern = '<%sf'%length buff.write(self.fft.tostring()) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(_x)))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(_x)))) def deserialize_numpy(self, str, numpy): """ unpack serialized message in str into this message instance using numpy for array types :param str: byte array of serialized message, ``str`` :param numpy: numpy python module """ try: if self.timestamp1 is None: self.timestamp1 = genpy.Time() if self.timestamp2 is None: self.timestamp2 = genpy.Time() if self.pixels_normalized is None: self.pixels_normalized = duckietown_msgs.msg.Vector2D() end = 0 _x = self start = end end += 28 (_x.timestamp1.secs, _x.timestamp1.nsecs, _x.timestamp2.secs, _x.timestamp2.nsecs, _x.pixels_normalized.x, _x.pixels_normalized.y, _x.frequency,) = _struct_4I3f.unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.color = str[start:end].decode('utf-8') else: self.color = str[start:end] start = end end += 4 (self.confidence,) = _struct_f.unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sd'%length start = end end += struct.calcsize(pattern) self.signal_ts = numpy.frombuffer(str[start:end], dtype=numpy.float64, count=length) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sf'%length start = end end += struct.calcsize(pattern) self.signal = numpy.frombuffer(str[start:end], dtype=numpy.float32, count=length) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sf'%length start = end end += struct.calcsize(pattern) self.fft_fs = numpy.frombuffer(str[start:end], dtype=numpy.float32, count=length) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) pattern = '<%sf'%length start = end end += struct.calcsize(pattern) self.fft = numpy.frombuffer(str[start:end], dtype=numpy.float32, count=length) self.timestamp1.canon() self.timestamp2.canon() return self except struct.error as e: raise genpy.DeserializationError(e) #most likely buffer underfill _struct_I = genpy.struct_I _struct_4I3f = struct.Struct("<4I3f") _struct_f = struct.Struct("<f")

35.963087

189

0.632826

1,402

10,717

4.697575

0.139087

0.060735

0.043425

0.036137

0.721379

0.71652

0.684634

0.672335

0.655481

0.639994

0

0.019156

0.230382

10,717

297

190

36.084175

0.77934

0.123915

0

0.753036

1

0

0.104625

0.020362

0

0.001083

0

1

0.024292

false

0

0.020243

0

0.08502

0

null

0

1

0

1

0

1

0

null

0

4

7d9fb9312f0da12407b3b0f16de2751d5031c5bc

264

py

Python

game/khet/strategies/human_strategy.py

xelahalo/khet

c4aca94703c24c01d106959849240b890fa6744b

[ "MIT" ]

null

game/khet/strategies/human_strategy.py

xelahalo/khet

c4aca94703c24c01d106959849240b890fa6744b

[ "MIT" ]

null

game/khet/strategies/human_strategy.py

xelahalo/khet

c4aca94703c24c01d106959849240b890fa6744b

[ "MIT" ]

1

2022-03-19T22:25:54.000Z

from game.khet.strategies.strategy import Strategy class HumanStrategy(Strategy): def __init__(self, color, ui): super().__init__(color) self._ui = ui def get_action(self, game): return self._ui.get_action(self._color, game.board)

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null

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1

0

1

0

4

7dc51192c0f03a5b378a5cecc37357c4f3aa7d49

321

py

Python

rqalpha_backtest/test_update_bundle.py

stevenchen521/quant_ml

f7d5efc49c934724f97fcafacc560f4a35b24551

[ "MIT" ]

5

2019-02-14T03:12:22.000Z

2022-01-24T18:43:07.000Z

rqalpha_backtest/test_update_bundle.py

stevenchen521/quant_ml

f7d5efc49c934724f97fcafacc560f4a35b24551

[ "MIT" ]

null

rqalpha_backtest/test_update_bundle.py

stevenchen521/quant_ml

f7d5efc49c934724f97fcafacc560f4a35b24551

[ "MIT" ]

2

2019-11-13T18:56:13.000Z

2021-12-31T01:25:22.000Z

import os def test_update_bundle(): # os.system("activate python3.5") # os.system("rqalpha update-bundle") import rqalpha.utils.bundle_helper rqalpha.utils.bundle_helper.update_bundle(data_bundle_path='D:\\rqalpha\data_bundle', locale="zh_Hans_CN") if __name__ == '__main__': test_update_bundle()

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111

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null

0

1

0

1

0

4

7dcce6ea158df7d2bc5aa68e596ea5004bffabb4

490

py

Python

badge_earning/api/views.py

andela-Taiwo/Badge-Earning

8d9073b552410391b2b54b6c7b4a2e71ae0632eb

[ "MIT" ]

null

badge_earning/api/views.py

andela-Taiwo/Badge-Earning

8d9073b552410391b2b54b6c7b4a2e71ae0632eb

[ "MIT" ]

null

badge_earning/api/views.py

andela-Taiwo/Badge-Earning

8d9073b552410391b2b54b6c7b4a2e71ae0632eb

[ "MIT" ]

null

from django.contrib.auth import get_user_model # from rest_framework import status # from rest_framework.decorators import action from rest_framework.mixins import ListModelMixin, RetrieveModelMixin, UpdateModelMixin # from rest_framework.response import Response from rest_framework.viewsets import GenericViewSet # from users.serializers import UserSerializer User = get_user_model() class UserViewSet(RetrieveModelMixin, ListModelMixin, UpdateModelMixin, GenericViewSet): pass

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null

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4

7de103a6cb46bbd75ba4bc2d9428f101fdbedcdf

142

py

Python

lib/iana/ripe/__init__.py

sschwetz/network_tech

fc65166e71bfdb5a0e99ca7e7ce9f7814b92869b

[ "Apache-2.0" ]

73

2017-05-04T06:35:20.000Z

2022-02-03T13:57:00.000Z

lib/iana/ripe/__init__.py

sschwetz/network_tech

fc65166e71bfdb5a0e99ca7e7ce9f7814b92869b

[ "Apache-2.0" ]

35

2017-11-09T16:28:48.000Z

2022-01-12T08:15:48.000Z

lib/iana/ripe/__init__.py

sschwetz/network_tech

fc65166e71bfdb5a0e99ca7e7ce9f7814b92869b

[ "Apache-2.0" ]

20

2017-11-08T05:07:59.000Z

2021-12-09T17:41:06.000Z

12.909091

60

0.732394

23

142

4.521739

0.695652

0.134615

0

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0.133803

142

11

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12.909091

0.813008

0.760563

0

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0

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0

null

0

null

0

1

0

1

0

1

0

4

8187f32f636a41836e6bcddf20b893841022962a

92

py

Python

2015/misc/test-table-1/graphic_config.py

nprapps/graphics-archive

97b0ef326b46a959df930f5522d325e537f7a655

[ "FSFAP" ]

14

2015-05-08T13:41:51.000Z

2021-02-24T12:34:55.000Z

2015/misc/test-table-1/graphic_config.py

nprapps/graphics-archive

97b0ef326b46a959df930f5522d325e537f7a655

[ "FSFAP" ]

null

2015/misc/test-table-1/graphic_config.py

nprapps/graphics-archive

97b0ef326b46a959df930f5522d325e537f7a655

[ "FSFAP" ]

7

2015-04-04T04:45:54.000Z

2021-02-18T11:12:48.000Z

#!/usr/bin/env python COPY_GOOGLE_DOC_KEY = '1yUpR-uFHjHoZvh9fOAmiF_-3KXZw01F1Ysi2qUhe0Ns'

23

68

0.826087

11

92

6.545455

1

0

0.093023

0.065217

92

3

69

30.666667

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0.217391

0

0.619718

0

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0

1

0

null

0

1

0

1

null

0

4

81bd109523b2f67861ad007e571124bea0e9f0a3

115

py

Python

tensor__cpu/http/download_from_ftp.py

Zhang-O/small

bfb41b2267159bd5e408dba524713d3bc0b28074

[ "MIT" ]

1

2017-09-25T03:16:00.000Z

tensor__cpu/http/download_from_ftp.py

Zhang-O/small

bfb41b2267159bd5e408dba524713d3bc0b28074

[ "MIT" ]

null

tensor__cpu/http/download_from_ftp.py

Zhang-O/small

bfb41b2267159bd5e408dba524713d3bc0b28074

[ "MIT" ]

null

# -*- coding:utf-8 -*- # Filename: try.py # Author：zhang # Date: 2018/3/4 22:41 """ 直接从服务器下载文件，需要服务器搭建了文件服务器 """

14.375

26

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7

27

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null

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1

0

1

0

null

0

1

0

4

81cbb1594f40f65be1c2dd74214d0e8ff41f0dc9

236

py

Python

thenewboston_node/business_logic/tests/fixtures/settings.py

AbhayAysola/thenewboston-node

8a24cfd814eed590a7a1066e45b8b4877501aa35

[ "MIT" ]

null

thenewboston_node/business_logic/tests/fixtures/settings.py

AbhayAysola/thenewboston-node

8a24cfd814eed590a7a1066e45b8b4877501aa35

[ "MIT" ]

null

thenewboston_node/business_logic/tests/fixtures/settings.py

AbhayAysola/thenewboston-node

8a24cfd814eed590a7a1066e45b8b4877501aa35

[ "MIT" ]

null

from django.test import override_settings import pytest @pytest.fixture(autouse=True) def unittest_settings(): with override_settings(SIGNING_KEY='46a23fd52b2690f5acf56654489fd67b3734a52f35a2b7827f5caeaa06c0c0a5'): yield

23.6

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0.822034

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236

8.636364

0.772727

0.168421

0

0.191388

0.114407

236

9

108

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0

0.271186

0

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0.333333

0

0.5

0

1

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null

0

1

0

null

0

1

0

1

0

4

81e0a59447326ba3a02566bc459d0fa3b787f9a7

984

py

Python

sdk/test/test_categories_api.py

yapily/yapily-sdk-python

c09930c44e8795e270e2846a2c0fb783200df76a

[ "MIT" ]

11

2018-05-18T14:38:49.000Z

2021-09-08T13:24:37.000Z

sdk/test/test_categories_api.py

yapily/yapily-sdk-python

c09930c44e8795e270e2846a2c0fb783200df76a

[ "MIT" ]

5

2019-10-23T15:06:33.000Z

2021-08-03T21:18:50.000Z

sdk/test/test_categories_api.py

yapily/yapily-sdk-python

c09930c44e8795e270e2846a2c0fb783200df76a

[ "MIT" ]

8

2019-04-27T00:02:18.000Z

2021-11-21T02:54:12.000Z

# coding: utf-8 """ Yapily API To access endpoints that require authentication, use your application key and secret created in the Dashboard (https://dashboard.yapily.com) # noqa: E501 The version of the OpenAPI document: 1.154.0 Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import unittest import yapily from yapily.api.categories_api import CategoriesApi # noqa: E501 from yapily.rest import ApiException class TestCategoriesApi(unittest.TestCase): """CategoriesApi unit test stubs""" def setUp(self): self.api = yapily.api.categories_api.CategoriesApi() # noqa: E501 def tearDown(self): pass def test_get_categories_using_get(self): """Test case for get_categories_using_get Retrieves a list of categories returned by the Yapily Categorisation engine for a given locale # noqa: E501 """ pass if __name__ == '__main__': unittest.main()

24

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984

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0.563492

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0.023166

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984

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159

24.6

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0.480691

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0.142857

0

0.017467

0

1

0.214286

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0.142857

0.357143

0

0.642857

0

null

0

null

0

1

0

1

0

1

0

4

c48f9428e7fa15750e78147958a8a1213dfb089a

89

py

Python

build/python_loader/cv2/config-2.7.py

pat4life360/LEAP-Camera-Face-Tracker-

be31183f9047f432ae400888aef1e0b0c58ff72b

[ "Apache-2.0" ]

null

build/python_loader/cv2/config-2.7.py

pat4life360/LEAP-Camera-Face-Tracker-

be31183f9047f432ae400888aef1e0b0c58ff72b

[ "Apache-2.0" ]

null

build/python_loader/cv2/config-2.7.py

pat4life360/LEAP-Camera-Face-Tracker-

be31183f9047f432ae400888aef1e0b0c58ff72b

[ "Apache-2.0" ]

null

PYTHON_EXTENSIONS_PATHS = [ '/home/pi/opencv/build/lib/' ] + PYTHON_EXTENSIONS_PATHS

22.25

32

0.741573

11

89

5.636364

0.727273

0.516129

0.677419

0

0.123596

89

3

33

29.666667

0.794872

0

0.292135

0

1

0

false

0

1

0

null

1

0

1

0

null

0

4

c4968a72cf0e6dc648c4d866d40a6bf802c814b8

143

py

Python

src/process_builtins/say.py

matthewlucock/mysh

efee6e951419fb56072b20ed5b36bedfbde9fa5e

[ "0BSD" ]

null

src/process_builtins/say.py

matthewlucock/mysh

efee6e951419fb56072b20ed5b36bedfbde9fa5e

[ "0BSD" ]

null

src/process_builtins/say.py

matthewlucock/mysh

efee6e951419fb56072b20ed5b36bedfbde9fa5e

[ "0BSD" ]

null

import sys if len(sys.argv) > 1: print(' '.join(sys.argv[1:])) else: try: print(input()) except EOFError: print()

14.3

33

0.524476

19

143

3.947368

0.684211

0.186667

0.213333

0

0.02

0.300699

143

9

34

15.888889

0.73

0

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0

1

0

true

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0.125

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1

0

null

0

1

0

1

0

null

0

1

0

4

c49a283b8c9d66f083305855859c3f8ce222c3de

119

py

Python

bdd/features/steps/python.py

dunossauro/qaninja-liveclass

89bdb42a771a1a4f9d5fc63e12e3584e8334a72a

[ "MIT" ]

7

2018-05-03T12:04:18.000Z

2020-05-02T13:11:03.000Z

bdd/features/steps/python.py

dunossauro/qaninja-liveclass

89bdb42a771a1a4f9d5fc63e12e3584e8334a72a

[ "MIT" ]

null

bdd/features/steps/python.py

dunossauro/qaninja-liveclass

89bdb42a771a1a4f9d5fc63e12e3584e8334a72a

[ "MIT" ]

4

2018-05-02T23:55:20.000Z

2020-05-02T13:07:40.000Z

from behave import given, then @given('que o usuário acesse a página "{link}"') def acessa_link(context, link):

17

48

0.697479

18

119

4.555556

0.833333

0

0.184874

119

6

49

19.833333

0.845361

0

0.319328

0

null

0

0.333333

null

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null

0

1

0

null

0

1

0

1

0

4

c4a7c5961656993da9eb95d8d70f04ef69911565

61

py

Python

emol/emol/views/user/__init__.py

lrt512/emol

e1dd3462632a525c3b9701d4fd9a332d19c93b85

[ "MIT" ]

null

emol/emol/views/user/__init__.py

lrt512/emol

e1dd3462632a525c3b9701d4fd9a332d19c93b85

[ "MIT" ]

null

emol/emol/views/user/__init__.py

lrt512/emol

e1dd3462632a525c3b9701d4fd9a332d19c93b85

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Module for user-related views."""

20.333333

36

0.57377

8

61

4.375

1

0

0.019231

0.147541

61

2

37

30.5

0.653846

0.868852

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

c4cd3244c8fe3d13e32af31e2ab9664a34f18c0e

8,800

py

Python

tests/python/relay/test_op_qnn_mul.py

wjj19950828/tvm

9c63f4fc318652f6fff68342da2d11b26592a3e0

[ "Zlib", "Unlicense", "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0" ]

90

2019-01-26T00:38:49.000Z

2022-03-11T23:12:34.000Z

tests/python/relay/test_op_qnn_mul.py

wjj19950828/tvm

9c63f4fc318652f6fff68342da2d11b26592a3e0

[ "Zlib", "Unlicense", "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0" ]

91

2019-02-27T00:17:01.000Z

2022-02-21T18:08:21.000Z

tests/python/relay/test_op_qnn_mul.py

wjj19950828/tvm

9c63f4fc318652f6fff68342da2d11b26592a3e0

[ "Zlib", "Unlicense", "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0" ]

41

2019-01-28T14:37:03.000Z

2022-03-31T03:58:57.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import tvm from tvm import te import numpy as np from tvm import relay from tvm.contrib import graph_executor import tvm.topi.testing # "unquantize" a quantized tensor def recover(data, scale, zp): return scale * (np.asarray(data) - zp) def generate_golden_output(x_recovered, y_recovered, scale, zp): mul = x_recovered * y_recovered output = np.around(mul / scale + zp) q_min = np.iinfo(np.uint8).min q_max = np.iinfo(np.uint8).max return np.clip(output, q_min, q_max) def test_tflite_same_io_qnn_params(): data_dtype = "uint8" lhs_scale = rhs_scale = output_scale = 0.00784314 lhs_zero_point = rhs_zero_point = output_zero_point = 127 x = relay.var("x", shape=(1, 4), dtype=data_dtype) y = relay.var("y", shape=(1, 4), dtype=data_dtype) z = relay.qnn.op.mul( lhs=x, rhs=y, lhs_scale=relay.const(lhs_scale, "float32"), lhs_zero_point=relay.const(lhs_zero_point, "int32"), rhs_scale=relay.const(rhs_scale, "float32"), rhs_zero_point=relay.const(rhs_zero_point, "int32"), output_scale=relay.const(output_scale, "float32"), output_zero_point=relay.const(output_zero_point, "int32"), ) func = relay.Function([x, y], z) mod = tvm.IRModule.from_expr(func) mod = relay.transform.InferType()(mod) mod = relay.qnn.transform.CanonicalizeOps()(mod) func = mod["main"] x_datas = [ np.array((1, 153, 2, 178)).reshape((1, 4)), np.array((25, 1, 178, 216)).reshape((1, 4)), np.array((25, 153, 1, 165)).reshape((1, 4)), ] y_datas = [ np.array((204, 178, 1, 8)).reshape((1, 4)), np.array((204, 178, 191, 1)).reshape((1, 4)), np.array((204, 178, 1, 191)).reshape((1, 4)), ] for i in range(0, 3): x_data = x_datas[i] y_data = y_datas[i] x_rec = recover(x_data, lhs_scale, lhs_zero_point) y_rec = recover(y_data, rhs_scale, rhs_zero_point) golden = generate_golden_output(x_rec, y_rec, output_scale, output_zero_point) intrp = relay.create_executor("graph", device=tvm.cpu(0), target="llvm") op_res = intrp.evaluate(func)(x_data, y_data) np.testing.assert_equal(op_res.numpy(), np.uint8(golden)) def test_tflite_different_io_qnn_params(): data_dtype = "uint8" lhs_scale = 0.0156863 lhs_zero_point = 127 rhs_scale = 0.0117647 rhs_zero_point = 85 output_scale = 0.0235294 output_zero_point = 128 x = relay.var("x", shape=(1, 4), dtype=data_dtype) y = relay.var("y", shape=(1, 4), dtype=data_dtype) z = relay.qnn.op.mul( lhs=x, rhs=y, lhs_scale=relay.const(lhs_scale, "float32"), lhs_zero_point=relay.const(lhs_zero_point, "int32"), rhs_scale=relay.const(rhs_scale, "float32"), rhs_zero_point=relay.const(rhs_zero_point, "int32"), output_scale=relay.const(output_scale, "float32"), output_zero_point=relay.const(output_zero_point, "int32"), ) func = relay.Function([x, y], z) mod = tvm.IRModule.from_expr(func) mod = relay.transform.InferType()(mod) mod = relay.qnn.transform.CanonicalizeOps()(mod) func = mod["main"] x_datas = [ np.array((76, 140, 153, 172)).reshape((1, 4)), np.array((133, 140, 146, 153)).reshape((1, 4)), np.array((76, 140, 172, 146)).reshape((1, 4)), ] y_datas = [ np.array((136, 119, 128, 17)).reshape((1, 4)), np.array((136, 119, 111, 94)).reshape((1, 4)), np.array((136, 119, 17, 128)).reshape((1, 4)), ] for i in range(0, 3): x_data = x_datas[i] y_data = y_datas[i] x_rec = recover(x_data, lhs_scale, lhs_zero_point) y_rec = recover(y_data, rhs_scale, rhs_zero_point) golden = generate_golden_output(x_rec, y_rec, output_scale, output_zero_point) intrp = relay.create_executor("graph", device=tvm.cpu(0), target="llvm") op_res = intrp.evaluate(func)(x_data, y_data) np.testing.assert_equal(op_res.numpy(), np.uint8(golden)) def test_saturation(): # Same params data_dtype = "uint8" lhs_scale = rhs_scale = output_scale = 0.125 lhs_zero_point = rhs_zero_point = output_zero_point = 0 x = relay.var("x", shape=(1, 4), dtype=data_dtype) y = relay.var("y", shape=(1, 4), dtype=data_dtype) z = relay.qnn.op.mul( lhs=x, rhs=y, lhs_scale=relay.const(lhs_scale, "float32"), lhs_zero_point=relay.const(lhs_zero_point, "int32"), rhs_scale=relay.const(rhs_scale, "float32"), rhs_zero_point=relay.const(rhs_zero_point, "int32"), output_scale=relay.const(output_scale, "float32"), output_zero_point=relay.const(output_zero_point, "int32"), ) func = relay.Function([x, y], z) mod = tvm.IRModule.from_expr(func) mod = relay.transform.InferType()(mod) mod = relay.qnn.transform.CanonicalizeOps()(mod) func = mod["main"] x_data = np.array((255, 1, 1, 0)).reshape((1, 4)) y_data = np.array((255, 255, 128, 0)).reshape((1, 4)) x_rec = recover(x_data, lhs_scale, lhs_zero_point) y_rec = recover(y_data, rhs_scale, rhs_zero_point) golden = generate_golden_output(x_rec, y_rec, output_scale, output_zero_point) intrp = relay.create_executor("graph", device=tvm.cpu(0), target="llvm") op_res = intrp.evaluate(func)(x_data, y_data) np.testing.assert_equal(op_res.numpy(), np.uint8(golden)) # Same params, different scale lhs_scale = rhs_scale = 0.125 output_scale = 0.25 z = relay.qnn.op.mul( lhs=x, rhs=y, lhs_scale=relay.const(lhs_scale, "float32"), lhs_zero_point=relay.const(lhs_zero_point, "int32"), rhs_scale=relay.const(rhs_scale, "float32"), rhs_zero_point=relay.const(rhs_zero_point, "int32"), output_scale=relay.const(output_scale, "float32"), output_zero_point=relay.const(output_zero_point, "int32"), ) func = relay.Function([x, y], z) mod = tvm.IRModule.from_expr(func) mod = relay.transform.InferType()(mod) mod = relay.qnn.transform.CanonicalizeOps()(mod) func = mod["main"] x_data = np.array((255, 1, 1, 0)).reshape((1, 4)) y_data = np.array((255, 255, 127, 0)).reshape((1, 4)) x_rec = recover(x_data, lhs_scale, lhs_zero_point) y_rec = recover(y_data, rhs_scale, rhs_zero_point) golden = generate_golden_output(x_rec, y_rec, output_scale, output_zero_point) intrp = relay.create_executor("graph", device=tvm.cpu(0), target="llvm") op_res = intrp.evaluate(func)(x_data, y_data) np.testing.assert_equal(op_res.numpy(), np.uint8(golden)) # All params different lhs_scale = 0.5 rhs_scale = 0.25 output_scale = 0.125 z = relay.qnn.op.mul( lhs=x, rhs=y, lhs_scale=relay.const(lhs_scale, "float32"), lhs_zero_point=relay.const(lhs_zero_point, "int32"), rhs_scale=relay.const(rhs_scale, "float32"), rhs_zero_point=relay.const(rhs_zero_point, "int32"), output_scale=relay.const(output_scale, "float32"), output_zero_point=relay.const(output_zero_point, "int32"), ) func = relay.Function([x, y], z) mod = tvm.IRModule.from_expr(func) mod = relay.transform.InferType()(mod) mod = relay.qnn.transform.CanonicalizeOps()(mod) func = mod["main"] x_data = np.array((255, 0, 1, 0)).reshape((1, 4)) y_data = np.array((0, 128, 64, 0)).reshape((1, 4)) x_rec = recover(x_data, lhs_scale, lhs_zero_point) y_rec = recover(y_data, rhs_scale, rhs_zero_point) golden = generate_golden_output(x_rec, y_rec, output_scale, output_zero_point) intrp = relay.create_executor("graph", device=tvm.cpu(0), target="llvm") op_res = intrp.evaluate(func)(x_data, y_data) np.testing.assert_equal(op_res.numpy(), np.uint8(golden)) if __name__ == "__main__": test_tflite_same_io_qnn_params() test_tflite_different_io_qnn_params() test_saturation()

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c4d839170925b51f58f58a79861c1d008abd7f8b

228

py

Python

profiles/serializers.py

BookShareBG/BackEnd

07a114313501fa3a8a5d2d8462179b69a6b56c06

[ "MIT" ]

null

profiles/serializers.py

BookShareBG/BackEnd

07a114313501fa3a8a5d2d8462179b69a6b56c06

[ "MIT" ]

4

2020-11-05T12:18:41.000Z

2021-06-10T20:22:16.000Z

profiles/serializers.py

BookShareBG/BackEnd

07a114313501fa3a8a5d2d8462179b69a6b56c06

[ "MIT" ]

null

from rest_framework import serializers from .models import Profile class ProfileSerializer(serializers.ModelSerializer): class Meta: model = Profile fields = ('id', 'user_id', 'city', 'country', 'address')

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c4f4bbe694333d65b69ac0e37b34b451d787eb9e

412

py

Python

lizard/util/cl/mux.py

cornell-brg/lizard

7f9a78a913e64b5cfdee3a26223539ad225bd6da

[ "BSD-3-Clause" ]

50

2019-05-22T08:43:15.000Z

2022-03-21T23:58:50.000Z

lizard/util/cl/mux.py

cornell-brg/lizard

7f9a78a913e64b5cfdee3a26223539ad225bd6da

[ "BSD-3-Clause" ]

1

2019-07-27T18:51:52.000Z

2019-08-02T01:20:22.000Z

lizard/util/cl/mux.py

cornell-brg/lizard

7f9a78a913e64b5cfdee3a26223539ad225bd6da

[ "BSD-3-Clause" ]

11

2019-12-26T06:00:48.000Z

2022-03-27T02:29:35.000Z

from pymtl import * from lizard.model.hardware_model import HardwareModel from lizard.model.clmodel import CLModel from lizard.util.rtl.mux import MuxInterface class MuxCL(CLModel): @HardwareModel.validate def __init__(s, dtype, nports): super(MuxCL, s).__init__(MuxInterface(dtype, nports)) @s.model_method def mux(in_, select): return in_[select] def line_trace(s): return ''

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f2245ca62a7234bff395ffed52d098a69322f89a

264

py

Python

hackerrank/regex/backreferences/01-failed-groups.py

everarch/psets

7fddb2a01ce8c4e601d63c3be3b11cd2113be035

[ "MIT" ]

null

hackerrank/regex/backreferences/01-failed-groups.py

everarch/psets

7fddb2a01ce8c4e601d63c3be3b11cd2113be035

[ "MIT" ]

null

hackerrank/regex/backreferences/01-failed-groups.py

everarch/psets

7fddb2a01ce8c4e601d63c3be3b11cd2113be035

[ "MIT" ]

null

# # Backreferences To Failed Groups # # https://www.hackerrank.com/challenges/backreferences-to-failed-groups/problem # Regex_Pattern = r"^\d{2}(-?)\d{2}\1\d{2}\1\d{2}$" # Do not delete 'r'. import re print(str(bool(re.search(Regex_Pattern, input()))).lower())

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480cecff9bb3a538c96ea9d2e5f3ef760f853af3

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py

Python

OcCo_TF/pc_distance/__init__.py

sun-pyo/OcCo

e2e12dbaa8f9b98fb8c42fc32682f49e99be302f

[ "MIT" ]

158

2020-08-19T18:13:28.000Z

2022-03-30T13:55:32.000Z

OcCo_TF/pc_distance/__init__.py

sun-pyo/OcCo

e2e12dbaa8f9b98fb8c42fc32682f49e99be302f

[ "MIT" ]

28

2020-05-30T04:02:33.000Z

2022-03-30T15:46:38.000Z

OcCo_TF/pc_distance/__init__.py

sun-pyo/OcCo

e2e12dbaa8f9b98fb8c42fc32682f49e99be302f

[ "MIT" ]

18

2020-08-19T19:52:38.000Z

2022-02-06T11:42:26.000Z

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4840ded7b02799a486e7fe66da3dd9ffca709f04

86

py

Python

draw_table/__init__.py

pedrudehuere/py_draw_table

d8971e5fcac24f8429742e568bd01059b0696d85

[ "MIT" ]

null

draw_table/__init__.py

pedrudehuere/py_draw_table

d8971e5fcac24f8429742e568bd01059b0696d85

[ "MIT" ]

null

draw_table/__init__.py

pedrudehuere/py_draw_table

d8971e5fcac24f8429742e568bd01059b0696d85

[ "MIT" ]

null

# -*- coding: utf-8 -*- from .draw_table import draw_table __all__ = ['draw_table']

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