xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

cc35e47ddd8b88da87844c5c131307aad3888dab

35,799

py

Python

pyEX/economic/economic.py

majacQ/pyEX

def9280fbaa17a2afe4434b6f584f1a602f4bc55

[ "Apache-2.0" ]

null

pyEX/economic/economic.py

majacQ/pyEX

def9280fbaa17a2afe4434b6f584f1a602f4bc55

[ "Apache-2.0" ]

null

pyEX/economic/economic.py

majacQ/pyEX

def9280fbaa17a2afe4434b6f584f1a602f4bc55

[ "Apache-2.0" ]

null

# ***************************************************************************** # # Copyright (c) 2020, the pyEX authors. # # This file is part of the pyEX library, distributed under the terms of # the Apache License 2.0. The full license can be found in the LICENSE file. # from enum import Enum from functools import lru_cache from ..common import _expire, _UTC, _timeseriesWrapper from ..points import points from ..timeseries import timeSeries, timeSeriesDF class EconomicPoints(Enum): """Economic data points https://iexcloud.io/docs/api/#economic-data Attributes: US0; US 30-Year fixed rate mortgage average US5; US 15-Year fixed rate mortgage average US; US 5/1-Year adjustable rate mortgage average FEDFUNDS; Effective federal funds rate CREDITCARD; Commercial bank credit card interest rate as a percent, not seasonally adjusted CDNJ; CD Rate Non-Jumbo less than $100,000 Money market CDJ; CD Rate Jumbo more than $100,000 Money market GDP; Real Gross Domestic Product INDPRO; Industrial Production Index CPI; Consumer Price Index All Urban Consumers PAYROLL; Total nonfarm employees in thousands of persons seasonally adjusted HOUSING; Total Housing Starts in thousands of units, seasonally adjusted annual rate UNEMPLOYMENT; Unemployment rate returned as a percent, seasonally adjusted VEHICLES; Total Vehicle Sales in millions of units RECESSION; US Recession Probabilities. Smoothed recession probabilities for the United States are obtained from a dynamic-factor markov-switching model applied to four monthly coincident variables. non-farm payroll employment, the index of industrial production, real personal income excluding transfer payments, and real manufacturing and trade sales. INITIALCLAIMS; Initial claims returned as a number, seasonally adjusted RETAILMONEY; Retail money funds returned as billions of dollars, seasonally adjusted INSTITUTIONALMONEY; Institutional money funds returned as billions of dollars, seasonally adjusted """ US30 = "MORTGAGE30US" US15 = "MORTGAGE15US" US5 = "MORTGAGE5US" FEDFUNDS = "FEDFUNDS" CREDITCARD = "TERMCBCCALLNS" CDNJ = "MMNRNJ" CDJ = "MMNRJD" GDP = "A191RL1Q225SBEA" INDPRO = "INDPRO" CPI = "CPIAUCSL" PAYROLL = "PAYEMS" HOUSING = "HOUST" UNEMPLOYMENT = "UNRATE" VEHICLES = "TOTALSA" RECESSION_PROB = "RECPROUSM156N" INITIALCLAIMS = "IC4WSA" RETAILMONEY = "WRMFSL" INSTITUTIONALMONEY = "WIMFSL" @staticmethod @lru_cache(1) def options(): """Return a list of the available economic points options""" return list(map(lambda c: c.value, EconomicPoints)) @_expire(hour=8, tz=_UTC) def us30(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data US0; US 30-Year fixed rate mortgage average """ return points("MORTGAGE30US", token=token, version=version) @_expire(hour=8, tz=_UTC) def us30History( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="MORTGAGE30US", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def us30HistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="MORTGAGE30US", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def us15(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data US5; US 15-Year fixed rate mortgage average """ return points("MORTGAGE15US", token=token, version=version) @_expire(hour=8, tz=_UTC) def us15History( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="MORTGAGE15US", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def us15HistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="MORTGAGE15US", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def us5(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data US; US 5/1-Year adjustable rate mortgage average """ return points("MORTGAGE5US", token=token, version=version) @_expire(hour=8, tz=_UTC) def us5History( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="MORTGAGE5US", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def us5HistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="MORTGAGE5US", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def fedfunds(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data FEDFUNDS; Effective federal funds rate """ return points("FEDFUNDS", token=token, version=version) @_expire(hour=8, tz=_UTC) def fedfundsHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="FEDFUNDS", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def fedfundsHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="FEDFUNDS", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def creditcard(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data CREDITCARD; Commercial bank credit card interest rate as a percent, not seasonally adjusted """ return points("TERMCBCCALLNS", token=token, version=version) @_expire(hour=8, tz=_UTC) def creditcardHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="RATES", key="TERMCBCCALLNS", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def creditcardHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="RATES", key="TERMCBCCALLNS", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def cdnj(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data CDNJ; CD Rate Non-Jumbo less than $100,000 Money market """ return points("MMNRNJ", token=token, version=version) @_expire(hour=8, tz=_UTC) def cdnjHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="RATES", key="MMNRNJ", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def cdnjHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="RATES", key="MMNRNJ", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def cdj(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data CDJ; CD Rate Jumbo more than $100,000 Money market """ return points("MMNRJD", token=token, version=version) @_expire(hour=8, tz=_UTC) def cdjHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="RATES", key="MMNRJD", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def cdjHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="RATES", key="MMNRJD", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def gdp(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data GDP; Real Gross Domestic Product """ return points("A191RL1Q225SBEA", token=token, version=version) @_expire(hour=8, tz=_UTC) def gdpHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="A191RL1Q225SBEA", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def gdpHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="A191RL1Q225SBEA", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def indpro(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data INDPRO; Industrial Production Index """ return points("INDPRO", token=token, version=version) @_expire(hour=8, tz=_UTC) def indproHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="INDPRO", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def indproHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="INDPRO", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def cpi(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data CPI; Consumer Price Index All Urban Consumers """ return points("CPIAUCSL", token=token, version=version) @_expire(hour=8, tz=_UTC) def cpiHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="CPIAUCSL", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def cpiHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="CPIAUCSL", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def payroll(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data PAYROLL; Total nonfarm employees in thousands of persons seasonally adjusted """ return points("PAYEMS", token=token, version=version) @_expire(hour=8, tz=_UTC) def payrollHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="PAYEMS", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def payrollHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="PAYEMS", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def housing(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data HOUSING; Total Housing Starts in thousands of units, seasonally adjusted annual rate """ return points("HOUST", token=token, version=version) @_expire(hour=8, tz=_UTC) def housingHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="HOUST", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def housingHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="HOUST", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def unemployment(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data UNEMPLOYMENT; Unemployment rate returned as a percent, seasonally adjusted """ return points("UNRATE", token=token, version=version) @_expire(hour=8, tz=_UTC) def unemploymentHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="UNRATE", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def unemploymentHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="UNRATE", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def vehicles(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data VEHICLES; Total Vehicle Sales in millions of units """ return points("TOTALSA", token=token, version=version) @_expire(hour=8, tz=_UTC) def vehiclesHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="TOTALSA", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def vehiclesHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="TOTALSA", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def recessionProb(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data RECESSION; US Recession Probabilities. Smoothed recession probabilities for the United States are obtained from a dynamic-factor markov-switching model applied to four monthly coincident variables. non-farm payroll employment, the index of industrial production, real personal income excluding transfer payments, and real manufacturing and trade sales. """ return points("RECPROUSM156N", token=token, version=version) @_expire(hour=8, tz=_UTC) def recessionProbHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="RECPROUSM156N", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def recessionProbHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="RECPROUSM156N", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def initialClaims(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data INITIALCLAIMS; Initial claims returned as a number, seasonally adjusted """ return points("IC4WSA", token=token, version=version) @_expire(hour=8, tz=_UTC) def initialClaimsHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="IC4WSA", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def initialClaimsHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="IC4WSA", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def institutionalMoney(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data INSTITUTIONALMONEY; Institutional money funds returned as billions of dollars, seasonally adjusted """ return points("WRMFSL", token=token, version=version) @_expire(hour=8, tz=_UTC) def institutionalMoneyHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="WRMFSL", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def institutionalMoneyHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="WRMFSL", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def retailMoney(token="", version="stable"): """Economic data points https://iexcloud.io/docs/api/#economic-data RETAILMONEY; Retail money funds returned as billions of dollars, seasonally adjusted """ return points("WIMFSL", token=token, version=version) @_expire(hour=8, tz=_UTC) def retailMoneyHistory( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeries( id="ECONOMIC", key="WIMFSL", token=token, version=version, filter=filter, format=format, **timeseries_kwargs ) @_expire(hour=8, tz=_UTC) def retailMoneyHistoryDF( token="", version="stable", filter="", format="json", **timeseries_kwargs ): """Economic data https://iexcloud.io/docs/api/#economic-data Args: token (str): Access token version (str): API version filter (str): filters: https://iexcloud.io/docs/api/#filter-results format (str): return format, defaults to json Supports all kwargs from `pyEX.timeseries.timeSeries` Returns: dict or DataFrame: result """ _timeseriesWrapper(timeseries_kwargs) return timeSeriesDF( id="ECONOMIC", key="WIMFSL", token=token, version=version, filter=filter, format=format, **timeseries_kwargs )

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null

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1

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null

0

7

cc520c2c4f845c6e00f80fd02390564baef88ab8

592

py

Python

TwitchChatCode/twitchlogo.py

AdamSmif/Sportsball-Adventures

10de2ebf4ff2eb8e1ee77e52149b713841882a04

[ "MIT" ]

2

2020-11-28T01:42:10.000Z

2022-01-21T07:49:27.000Z

TwitchChatCode/twitchlogo.py

AdamSmif/Sportsball-Adventures

10de2ebf4ff2eb8e1ee77e52149b713841882a04

[ "MIT" ]

2

2020-11-28T01:33:55.000Z

2020-11-28T01:36:30.000Z

TwitchChatCode/twitchlogo.py

AdamSmif/Sportsball-Adventures

10de2ebf4ff2eb8e1ee77e52149b713841882a04

[ "MIT" ]

null

def print_twitch_logo(): print(' _______ _ _ _ _____ _ _ _ ') print('|__ __| (_) | | | / ____| | | | | | ') print(' | |_ ___| |_ ___| |__ | | ___ _ __ | |_ _ __ ___ | | | ___ _ __ ') print(" | \ \ /\ / / | __/ __| '_ \ | | / _ \| '_ \| __| '__/ _ \| | |/ _ \ '__|") print(" | |\ V V /| | || (__| | | | | |___| (_) | | | | |_| | | (_) | | | __/ | ") print(" |_| \_/\_/ |_|\__\___|_| |_| \_____\___/|_| |_|\__|_| \___/|_|_|\___|_| ")

65.777778

92

0.280405

12

592

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0.416667

0.8

0.9

0.8

0

0.466216

592

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93

65.777778

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0.571429

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0

1

0

null

0

1

0

1

0

10

cc638c85cc8035da764c4fa28c2a98ed49f5b5db

75

py

Python

dacy/utils.py

HLasse/DaCy

67ca82f3c1637193b140ecea7a683cd5d4c6749e

[ "Apache-2.0" ]

1

2021-07-24T19:14:34.000Z

dacy/utils.py

MalteHB/DaCy

1c3d348b14368c772d13344d35dc076b01d5bf07

[ "Apache-2.0" ]

null

dacy/utils.py

MalteHB/DaCy

1c3d348b14368c772d13344d35dc076b01d5bf07

[ "Apache-2.0" ]

null

import numpy as np def softmax(x): return np.exp(x) / sum(np.exp(x))

12.5

37

0.626667

15

75

3.133333

0.666667

0.212766

0.255319

0

0.213333

75

5

38

15

0.79661

0

1

0.333333

false

0

0.333333

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

cc766b470e7c9eef6ede7334e5b72e57feb42a21

121

py

Python

geco/mips/knapsack/__init__.py

FreestyleBuild/GeCO

6db1a549b3145b3bc5d3025a9bccc03be6575564

[ "MIT" ]

8

2020-12-16T09:59:05.000Z

2022-03-18T09:48:43.000Z

geco/mips/knapsack/__init__.py

FreestyleBuild/GeCO

6db1a549b3145b3bc5d3025a9bccc03be6575564

[ "MIT" ]

101

2020-11-09T10:20:03.000Z

2022-03-24T13:50:06.000Z

geco/mips/knapsack/__init__.py

FreestyleBuild/GeCO

6db1a549b3145b3bc5d3025a9bccc03be6575564

[ "MIT" ]

3

2021-04-06T13:26:03.000Z

2022-03-22T13:22:16.000Z

from geco.mips.knapsack.generic import * from geco.mips.knapsack.yang import * from geco.mips.knapsack.pisinger import *

30.25

41

0.801653

18

121

5.388889

0.444444

0.247423

0.371134

0.618557

0.536082

0

0.099174

121

3

42

40.333333

0.889908

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true

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1

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0

null

0

1

0

1

0

1

0

8

aee46ac4bf1a513c7231f0d9b518309429d5345e

2,031

py

Python

appengine/networkx/algorithms/tests/test_graphical.py

CSE512-15S/a3-haynesb-Pending

881c3872304f2cd796bd4db7211ab8c3f108586b

[ "Apache-2.0" ]

12

2015-03-25T20:20:26.000Z

2021-11-14T19:44:56.000Z

appengine/networkx/algorithms/tests/test_graphical.py

CSE512-15S/a3-haynesb-Pending

881c3872304f2cd796bd4db7211ab8c3f108586b

[ "Apache-2.0" ]

71

2015-01-05T16:50:55.000Z

2020-09-30T19:17:47.000Z

appengine/networkx/algorithms/tests/test_graphical.py

CSE512-15S/a3-haynesb-Pending

881c3872304f2cd796bd4db7211ab8c3f108586b

[ "Apache-2.0" ]

14

2015-02-15T22:19:18.000Z

2020-09-30T18:54:54.000Z

#!/usr/bin/env python from nose.tools import * import networkx as nx def test_valid_degree_sequence1(): n = 100 p = .3 for i in range(10): G = nx.erdos_renyi_graph(n,p) deg = list(G.degree().values()) assert_true( nx.is_valid_degree_sequence(deg, method='eg') ) assert_true( nx.is_valid_degree_sequence(deg, method='hh') ) def test_valid_degree_sequence2(): n = 100 for i in range(10): G = nx.barabasi_albert_graph(n,1) deg = list(G.degree().values()) assert_true( nx.is_valid_degree_sequence(deg, method='eg') ) assert_true( nx.is_valid_degree_sequence(deg, method='hh') ) def test_atlas(): for graph in nx.graph_atlas_g(): deg = list(graph.degree().values()) assert_true( nx.is_valid_degree_sequence(deg, method='eg') ) assert_true( nx.is_valid_degree_sequence(deg, method='hh') ) def test_small_graph_true(): z=[5,3,3,3,3,2,2,2,1,1,1] assert_true(nx.is_valid_degree_sequence(z, method='hh')) assert_true(nx.is_valid_degree_sequence(z, method='eg')) z=[10,3,3,3,3,2,2,2,2,2,2] assert_true(nx.is_valid_degree_sequence(z, method='hh')) assert_true(nx.is_valid_degree_sequence(z, method='eg')) z=[1, 1, 1, 1, 1, 2, 2, 2, 3, 4] assert_true(nx.is_valid_degree_sequence(z, method='hh')) assert_true(nx.is_valid_degree_sequence(z, method='eg')) def test_small_graph_false(): z=[1000,3,3,3,3,2,2,2,1,1,1] assert_false(nx.is_valid_degree_sequence(z, method='hh')) assert_false(nx.is_valid_degree_sequence(z, method='eg')) z=[6,5,4,4,2,1,1,1] assert_false(nx.is_valid_degree_sequence(z, method='hh')) assert_false(nx.is_valid_degree_sequence(z, method='eg')) z=[1, 1, 1, 1, 1, 1, 2, 2, 2, 3, 4] assert_false(nx.is_valid_degree_sequence(z, method='hh')) assert_false(nx.is_valid_degree_sequence(z, method='eg'))

38.320755

76

0.622846

335

2,031

3.504478

0.155224

0.187394

0.13799

0.229983

0.798978

0.796422

0.763203

0

0.050826

0.225012

2,031

52

77

39.057692

0.695044

0.009847

0

0.571429

0

0.017928

0

0.428571

1

0.119048

false

0

0.047619

0

0.166667

0

null

0

1

0

1

0

null

0

1

0

7

4e3a2c28b52894460e5e4e01fa8a0952116c9c5e

3,205

py

Python

arackodu1.py

IMekatronik/OFFICE-BOY1

4feee0a9823aa9fd97946484e991f628c50a915f

[ "MIT" ]

null

arackodu1.py

IMekatronik/OFFICE-BOY1

4feee0a9823aa9fd97946484e991f628c50a915f

[ "MIT" ]

null

arackodu1.py

IMekatronik/OFFICE-BOY1

4feee0a9823aa9fd97946484e991f628c50a915f

[ "MIT" ]

null

from gpiozero import Button, LED from time import sleep mr_2 = LED(17) mr_1 = LED(27) mr_e = LED(22) ml_2 = LED(18) ml_1 = LED(23) ml_e = LED(24) button_1 = Button(5) button_2 = Button(6) button_3 = Button(13) button_4 = Button(19) button_5 = Button(26) button_6 = Button(12) button_7 = Button(16) while True: mr_1.on() mr_2.off() mr_e.off() ml_1.on() ml_2.off() ml_e.off() if button_4.is_pressed == 1 and button_5.is_pressed == 1: while not button_6.is_pressed == 1 or not button_7.is_pressed == 1: if button_1.is_pressed and not button_2.is_pressed and not button_3.is_pressed: mr_1.on() mr_2.off() mr_e.off() ml_1.on() ml_2.off() ml_e.on() if not button_1.is_pressed and button_2.is_pressed and not button_3.is_pressed: mr_1.on() mr_2.off() mr_e.on() ml_1.on() ml_2.off() ml_e.on() if not button_1.is_pressed and not button_2.is_pressed and button_3.is_pressed: mr_1.on() mr_2.off() mr_e.on() ml_1.on() ml_2.off() ml_e.off() if button_4.is_pressed == 0 and button_5.is_pressed == 1: while not button_6.is_pressed == 0 or not button_7.is_pressed == 1: if button_1.is_pressed and not button_2.is_pressed and not button_3.is_pressed: mr_1.on() mr_2.off() mr_e.off() ml_1.on() ml_2.off() ml_e.on() if not button_1.is_pressed and button_2.is_pressed and not button_3.is_pressed: mr_1.on() mr_2.off() mr_e.on() ml_1.on() ml_2.off() ml_e.on() if not button_1.is_pressed and not button_2.is_pressed and button_3.is_pressed: mr_1.on() mr_2.off() mr_e.on() ml_1.on() ml_2.off() ml_e.off() if button_4.is_pressed == 1 and button_5.is_pressed == 0: while not button_6.is_pressed == 1 or not button_7.is_pressed == 0: if button_1.is_pressed and not button_2.is_pressed and not button_3.is_pressed: mr_1.on() mr_2.off() mr_e.off() ml_1.on() ml_2.off() ml_e.on() if not button_1.is_pressed and button_2.is_pressed and not button_3.is_pressed: mr_1.on() mr_2.off() mr_e.on() ml_1.on() ml_2.off() ml_e.on() if not button_1.is_pressed and not button_2.is_pressed and button_3.is_pressed: mr_1.on() mr_2.off() mr_e.on() ml_1.on() ml_2.off() ml_e.off()

27.869565

92

0.468331

474

3,205

2.848101

0.082278

0.26

0.16

0.133333

0.844444

0

0.07

0.438378

3,205

115

93

27.869565

0.68

0

0.758242

0

1

0

false

0

0.021978

0

0.021978

0

null

1

0

1

0

1

0

null

0

8

9d65ffd42ceb90dd769072f383041240207a07d2

33

py

Python

gputools/deconv/__init__.py

gmazzamuto/gputools

73a4dee76a119f94d8163781a85b691fd080d506

[ "BSD-3-Clause" ]

89

2015-08-28T14:17:33.000Z

2022-01-20T16:19:34.000Z

gputools/deconv/__init__.py

gmazzamuto/gputools

73a4dee76a119f94d8163781a85b691fd080d506

[ "BSD-3-Clause" ]

24

2015-08-28T19:06:22.000Z

2022-02-21T21:10:13.000Z

gputools/deconv/__init__.py

gmazzamuto/gputools

73a4dee76a119f94d8163781a85b691fd080d506

[ "BSD-3-Clause" ]

17

2015-08-28T18:56:43.000Z

2021-09-15T23:15:36.000Z

from .deconv_rl import deconv_rl

16.5

32

0.848485

6

33

4.333333

0.666667

0.615385

0

0.121212

33

1

33

0.896552

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

9d8ec0b8bd732c6af67a276c249bdeb5b7383efe

29,455

py

Python

annotation_scripts/annotate_synthetic_YCBV_train.py

sThalham/UDAPose

d23edcce18f6e8aec4f35e0894b676d4ae19686e

[ "Apache-2.0" ]

2

2020-12-03T03:02:45.000Z

2022-01-13T17:50:41.000Z

annotation_scripts/annotate_synthetic_YCBV_train.py

sThalham/UDAPose

d23edcce18f6e8aec4f35e0894b676d4ae19686e

[ "Apache-2.0" ]

2

2021-02-08T16:14:40.000Z

2021-03-25T09:04:09.000Z

annotation_scripts/annotate_synthetic_YCBV_train.py

sThalham/UDAPose

d23edcce18f6e8aec4f35e0894b676d4ae19686e

[ "Apache-2.0" ]

null

import os import yaml import cv2 import numpy as np import datetime import copy import transforms3d as tf3d import time import random import json import math import OpenEXR, Imath from pathlib import Path from misc import manipulate_RGB, toPix_array, toPix from Augmentations import augmentDepth, maskDepth, augmentRGB, augmentAAEext, augmentRGB_V2, augmentRGB_V3, get_normal def get_cont_sympose(rot_pose, sym): cam_in_obj = np.dot(np.linalg.inv(rot_pose), (0, 0, 0, 1)) alpha = math.atan2(cam_in_obj[1], cam_in_obj[0]) rot_pose[:3, :3] = np.dot(rot_pose[:3, :3], tf3d.euler.euler2mat(0.0, 0.0, alpha, 'sxyz')) return rot_pose def get_disc_sympose(rot_pose, sym, oid): if len(sym) > 3: sym = np.array(sym, dtype=np.float32) if sym[0, 0] == 1: c_alpha = np.dot([0, 1, 0], np.dot(rot_pose[0:3, 0:3], [0, 1, 0])) if c_alpha < 0: rot_pose_new = np.dot(rot_pose, sym) else: rot_pose_new = rot_pose if sym[1, 1] == 1: c_alpha = np.dot([1, 0, 0], np.dot(rot_pose[0:3, 0:3], [1, 0, 0])) if c_alpha < 0: rot_pose_new = np.dot(rot_pose, sym) else: rot_pose_new = rot_pose if sym[2, 2] == 1: c_alpha = np.dot([1, 0, 0], np.dot(rot_pose[0:3, 0:3], [1, 0, 0])) if c_alpha < 0: rot_pose_new = np.dot(rot_pose, sym) else: rot_pose_new = rot_pose else: rot_pose_new = rot_pose else: rot_pose1 = np.dot(rot_pose, sym[0]) rot_pose2 = np.dot(rot_pose, sym[1]) rot_pose3 = np.dot(rot_pose, sym[2]) alpha_0 = np.dot([1, 0, 0], np.dot(rot_pose[0:3, 0:3], [1, 0, 0])) alpha_1 = np.dot([1, 0, 0], np.dot(rot_pose1[0:3, 0:3], [1, 0, 0])) alpha_2 = np.dot([1, 0, 0], np.dot(rot_pose2[0:3, 0:3], [1, 0, 0])) alpha_3 = np.dot([1, 0, 0], np.dot(rot_pose3[0:3, 0:3], [1, 0, 0])) if alpha_1 < alpha_0 and alpha_1 < alpha_2 and alpha_1 < alpha_3: rot_pose_new = rot_pose1 elif alpha_2 < alpha_0 and alpha_2 < alpha_1 and alpha_2 < alpha_3: rot_pose_new = rot_pose2 elif alpha_3 < alpha_0 and alpha_3 < alpha_1 and alpha_3 < alpha_1: rot_pose_new = rot_pose3 else: rot_pose_new = rot_pose return rot_pose_new if __name__ == "__main__": <<<<<<< HEAD root = '/home/stefan/data/rendered_data/ycbv_rgbd/patches' root2 = '/home/stefan/data/rendered_data/ycbv_rgbd_2/patches' target = '/home/stefan/data/train_data/ycbv_RGBD_V2/' mesh_info = '/home/stefan/data/Meshes/ycb_video_st/models/models_info.json' ======= root = '/home/sthalham/ycb_test/patches' target = '/home/sthalham/data/prepro/ycbv_RGBD/' mesh_info = '/home/sthalham/data/Meshes/ycbv_st/models/models_info.json' >>>>>>> 177484e6aa32844a6e9ebe9a55dc81406dd72afc visu = False resX = 640 resY = 480 fxkin = 579.68 # blender calculated fykin = 542.31 # blender calculated cxkin = 320 cykin = 240 depthCut = 2000 threeD_boxes = np.ndarray((22, 8, 3), dtype=np.float32) sym_cont = np.ndarray((22, 3), dtype=np.float32) sym_disc = np.ndarray((28, 4, 4), dtype=np.float32) for key, value in json.load(open(mesh_info)).items(): fac = 0.001 x_minus = value['min_x'] * fac y_minus = value['min_y'] * fac z_minus = value['min_z'] * fac x_plus = value['size_x'] * fac + x_minus y_plus = value['size_y'] * fac + y_minus z_plus = value['size_z'] * fac + z_minus three_box_solo = np.array([[x_plus, y_plus, z_plus], [x_plus, y_plus, z_minus], [x_plus, y_minus, z_minus], [x_plus, y_minus, z_plus], [x_minus, y_plus, z_plus], [x_minus, y_plus, z_minus], [x_minus, y_minus, z_minus], [x_minus, y_minus, z_plus]]) threeD_boxes[int(key), :, :] = three_box_solo if "symmetries_continuous" in value: sym_cont[int(key), :] = np.asarray(value['symmetries_continuous'][0]['axis'], dtype=np.float32) elif "symmetries_discrete" in value: syms = value['symmetries_discrete'] #Obj 16 if len(syms) > 1: sym_disc[int(key), :, :] = np.asarray(syms[0], dtype=np.float32).reshape((4, 4)) sym_disc[22, :, :] = np.asarray(syms[1], dtype=np.float32).reshape((4, 4)) sym_disc[23, :, :] = np.asarray(syms[2], dtype=np.float32).reshape((4, 4)) sym_disc[24, :, :] = np.asarray(syms[3], dtype=np.float32).reshape((4, 4)) sym_disc[25, :, :] = np.asarray(syms[4], dtype=np.float32).reshape((4, 4)) sym_disc[26, :, :] = np.asarray(syms[5], dtype=np.float32).reshape((4, 4)) sym_disc[27, :, :] = np.asarray(syms[6], dtype=np.float32).reshape((4, 4)) else: sym_disc[int(key), :, :] = np.asarray(syms[0], dtype=np.float32).reshape((4,4)) else: pass now = datetime.datetime.now() dateT = str(now) dict = {"info": { "description": "tless", "url": "cmp.felk.cvut.cz/t-less/", "version": "1.0", "year": 2018, "contributor": "Stefan Thalhammer", "date_created": dateT }, "licenses": [], "images": [], "annotations": [], "categories": [] } dictVal = copy.deepcopy(dict) annoID = 0 gloCo = 0 times = [] trainN = 1 testN = 1 valN = 1 depPath = root + "/depth/" partPath = root + "/part/" gtPath = root maskPath = root + "/mask/" rgbPath = root + "/rgb/" excludedImgs = [] boxWidths = [] boxHeights = [] meanRGBD = np.zeros((6), np.float64) syns = os.listdir(root) syns2 = os.listdir(root2) all = len(syns) + len(syns2) for fileInd in syns: if fileInd.endswith(".yaml"): start_time = time.time() gloCo = gloCo + 1 redname = fileInd[:-8] gtfile = gtPath + '/' + fileInd depfile = depPath + redname + "_depth.exr" partfile = partPath + redname + "_part.png" maskfile = maskPath + redname + "_mask.npy" rgbfile = rgbPath + redname + "_rgb.png" depth_refine, rgb_refine, mask, bboxes, poses, mask_ids, visibilities = manipulate_RGB(gtfile, depfile, partfile, rgbfile) try: obj_mask = np.load(maskfile) except Exception: continue obj_mask = obj_mask.astype(np.int8) if bboxes is None: excludedImgs.append(int(redname)) continue depth_refine = np.multiply(depth_refine, 1000.0) # to millimeters rows, cols = depth_refine.shape for k in range(0, 1): newredname = redname[1:] + str(k) fileName = target + "images/train/" + newredname + '_rgb.jpg' myFile = Path(fileName) print(myFile) if myFile.exists(): print('File exists, skip encoding and safing.') else: depthAug = maskDepth(depth_refine, obj_mask, mask) rgbAug = rgb_refine depthAug[depthAug > depthCut] = 0 aug_dep = depthAug.astype(np.uint16) meanRGBD[0] += np.nanmean(rgbAug[:, :, 0]) meanRGBD[1] += np.nanmean(rgbAug[:, :, 1]) meanRGBD[2] += np.nanmean(rgbAug[:, :, 2]) meanRGBD[3] += np.nanmean(aug_dep[:, :]) meanRGBD[4] += np.nanmean(aug_dep[:, :]) meanRGBD[5] += np.nanmean(aug_dep[:, :]) cv2.imwrite(fileName, rgbAug) cv2.imwrite(fileName[:-8] + '_dep.png', aug_dep) imgID = int(newredname) imgName = newredname + '.jpg' # print(imgName) # bb scaling because of image scaling bbvis = [] bb3vis = [] cats = [] posvis = [] postra = [] # for i, bbox in enumerate(bboxes[:-1]): for i, bbox in enumerate(bboxes[:-1]): if visibilities[i] < 0.5: # print('visivility: ', visibilities[i], ' skip!') continue #print(visibilities[i]) #if (np.asscalar(bbox[0]) + 1) > 13: # continue bbvis.append(bbox.astype(int)) objID = np.asscalar(bbox[0]) + 1 #objID = np.asscalar(bboxes[i+1][0]) + 1 cats.append(objID) bbox = (bbox).astype(int) #rot = tf3d.quaternions.quat2mat(poses[i, 3:]) #rot = np.asarray(rot, dtype=np.float32) rot = tf3d.quaternions.quat2mat(poses[i, 3:]) tra = poses[i, 0:3] pose = np.zeros((4, 4), dtype=np.float32) pose[:3, :3] = rot pose[:3, 3] = tra pose[3, 3] = 1 if objID in [13, 18]: rot = get_cont_sympose(pose, sym_cont[objID, :]) elif objID in [1, 19, 20, 21]: rot = get_disc_sympose(pose, sym_disc[objID, :, :], objID) #elif objID == 16: # rot = get_disc_sympose(pose, [sym_disc[16, :, :], sym_disc[22, :, :], sym_disc[23, :, :], sym_disc[24, :, :], sym_disc[25, :, :], sym_disc[26, :, :], sym_disc[27, :, :]], # objID) rot = np.asarray(rot, dtype=np.float32) <<<<<<< HEAD tDbox = rot[:3, :3].dot(threeD_boxes[objID, :, :].T).T tDbox = tDbox + np.repeat(poses[i, np.newaxis, 0:3], 8, axis=0) # if objID == 10 or objID == 11: # print(tf3d.euler.quat2euler(poses[i, 3:])) box3D = toPix_array(tDbox, fx=fxkin, fy=fykin, cx=cxkin, cy=cykin) box3D = np.reshape(box3D, (16)) box3D = box3D.tolist() bb3vis.append(box3D) bbox = bbox.astype(int) x1 = np.asscalar(bbox[2]) y1 = np.asscalar(bbox[1]) x2 = np.asscalar(bbox[4]) y2 = np.asscalar(bbox[3]) nx1 = bbox[2] ny1 = bbox[1] nx2 = bbox[4] ny2 = bbox[3] w = (x2 - x1) h = (y2 - y1) boxWidths.append(w) boxHeights.append(h) bb = [x1, y1, w, h] area = w * h npseg = np.array([nx1, ny1, nx2, ny1, nx2, ny2, nx1, ny2]) seg = npseg.tolist() pose = [np.asscalar(poses[i, 0]), np.asscalar(poses[i, 1]), np.asscalar(poses[i, 2]), np.asscalar(poses[i, 3]), np.asscalar(poses[i, 4]), np.asscalar(poses[i, 5]), np.asscalar(poses[i, 6])] if i != len(bboxes): pose[0:2] = toPix(pose[0:3], fx=fxkin, fy=fykin, cx=cxkin, cy=cykin) posvis.append(pose) tra = np.asarray(poses[i, :3], dtype=np.float32) postra.append(tra) annoID = annoID + 1 tempTA = { "id": annoID, "image_id": imgID, "category_id": objID, "bbox": bb, "pose": pose, "segmentation": box3D, "area": area, "iscrowd": 0, # "feature_visibility": feat_vis } # print('norm q: ', np.linalg.norm(pose[3:])) dict["annotations"].append(tempTA) tempTL = { "url": "cmp.felk.cvut.cz/t-less/", "id": imgID, "name": imgName } dict["licenses"].append(tempTL) tempTV = { "license": 2, "url": "cmp.felk.cvut.cz/t-less/", "file_name": imgName, "height": resY, "width": resX, "date_captured": dateT, "id": imgID } dict["images"].append(tempTV) gloCo += 1 elapsed_time = time.time() - start_time times.append(elapsed_time) meantime = sum(times) / len(times) eta = ((all - gloCo) * meantime) / 60 if gloCo % 100 == 0: print('eta: ', eta, ' min') times = [] if visu is True: img = rgbAug for i, bb in enumerate(bbvis): # if cats[i] not in [19, 20, 23]: # continue bb = np.array(bb) cv2.rectangle(img, (int(bb[2]), int(bb[1])), (int(bb[4]), int(bb[3])), (255, 255, 255), 2) cv2.rectangle(img, (int(bb[2]), int(bb[1])), (int(bb[4]), int(bb[3])), (0, 0, 0), 1) font = cv2.FONT_HERSHEY_SIMPLEX bottomLeftCornerOfText = (int(bb[2]), int(bb[1])) fontScale = 1 fontColor = (0, 0, 0) fontthickness = 1 lineType = 2 gtText = str(cats[i]) # print(cats[i]) fontColor2 = (255, 255, 255) fontthickness2 = 3 cv2.putText(img, gtText, bottomLeftCornerOfText, font, fontScale, fontColor2, fontthickness2, lineType) cv2.putText(img, gtText, bottomLeftCornerOfText, font, fontScale, fontColor, fontthickness, lineType) # print(posvis[i]) if i is not poses.shape[0]: pose = np.asarray(bb3vis[i], dtype=np.float32) print(pose) colR = 250 colG = 25 colB = 175 img = cv2.line(img, tuple(pose[0:2].ravel()), tuple(pose[2:4].ravel()), (130, 245, 13), 2) img = cv2.line(img, tuple(pose[2:4].ravel()), tuple(pose[4:6].ravel()), (50, 112, 220), 2) img = cv2.line(img, tuple(pose[4:6].ravel()), tuple(pose[6:8].ravel()), (50, 112, 220), 2) img = cv2.line(img, tuple(pose[6:8].ravel()), tuple(pose[0:2].ravel()), (50, 112, 220), 2) img = cv2.line(img, tuple(pose[0:2].ravel()), tuple(pose[8:10].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[2:4].ravel()), tuple(pose[10:12].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[4:6].ravel()), tuple(pose[12:14].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[6:8].ravel()), tuple(pose[14:16].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[8:10].ravel()), tuple(pose[10:12].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[10:12].ravel()), tuple(pose[12:14].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[12:14].ravel()), tuple(pose[14:16].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[14:16].ravel()), tuple(pose[8:10].ravel()), (colR, colG, colB), 2) cv2.imwrite(fileName, img) print('STOP') for fileInd in syns2: if fileInd.endswith(".yaml"): start_time = time.time() gloCo = gloCo + 1 redname = fileInd[:-8] gtfile = gtPath + '/' + fileInd depfile = depPath + redname + "_depth.exr" partfile = partPath + redname + "_part.png" maskfile = maskPath + redname + "_mask.npy" rgbfile = rgbPath + redname + "_rgb.png" depth_refine, rgb_refine, mask, bboxes, poses, mask_ids, visibilities = manipulate_RGB(gtfile, depfile, partfile, rgbfile) try: obj_mask = np.load(maskfile) except Exception: continue obj_mask = obj_mask.astype(np.int8) if bboxes is None: excludedImgs.append(int(redname)) continue depth_refine = np.multiply(depth_refine, 1000.0) # to millimeters rows, cols = depth_refine.shape for k in range(0, 1): newredname = str(2) + redname[1:] + str(k) fileName = target + "images/train/" + newredname + '_rgb.jpg' myFile = Path(fileName) print(myFile) if myFile.exists(): print('File exists, skip encoding and safing.') else: depthAug = maskDepth(depth_refine, obj_mask, mask) rgbAug = rgb_refine depthAug[depthAug > depthCut] = 0 aug_dep = depthAug.astype(np.uint16) meanRGBD[0] += np.nanmean(rgbAug[:, :, 0]) meanRGBD[1] += np.nanmean(rgbAug[:, :, 1]) meanRGBD[2] += np.nanmean(rgbAug[:, :, 2]) meanRGBD[3] += np.nanmean(aug_dep[:, :]) meanRGBD[4] += np.nanmean(aug_dep[:, :]) meanRGBD[5] += np.nanmean(aug_dep[:, :]) cv2.imwrite(fileName, rgbAug) cv2.imwrite(fileName[:-8] + '_dep.png', aug_dep) imgID = int(newredname) imgName = newredname + '.jpg' # print(imgName) # bb scaling because of image scaling bbvis = [] bb3vis = [] cats = [] posvis = [] postra = [] # for i, bbox in enumerate(bboxes[:-1]): for i, bbox in enumerate(bboxes[:-1]): if visibilities[i] < 0.5: # print('visivility: ', visibilities[i], ' skip!') continue #print(visibilities[i]) #if (np.asscalar(bbox[0]) + 1) > 13: # continue bbvis.append(bbox.astype(int)) objID = np.asscalar(bbox[0]) + 1 #objID = np.asscalar(bboxes[i+1][0]) + 1 cats.append(objID) bbox = (bbox).astype(int) #rot = tf3d.quaternions.quat2mat(poses[i, 3:]) #rot = np.asarray(rot, dtype=np.float32) rot = tf3d.quaternions.quat2mat(poses[i, 3:]) tra = poses[i, 0:3] pose = np.zeros((4, 4), dtype=np.float32) pose[:3, :3] = rot pose[:3, 3] = tra pose[3, 3] = 1 if objID in [13, 18]: rot = get_cont_sympose(pose, sym_cont[objID, :]) elif objID in [1, 19, 20, 21]: rot = get_disc_sympose(pose, sym_disc[objID, :, :], objID) # elif objID == 16: # rot = get_disc_sympose(pose, [sym_disc[16, :, :], sym_disc[22, :, :], sym_disc[23, :, :], sym_disc[24, :, :], sym_disc[25, :, :], sym_disc[26, :, :], sym_disc[27, :, :]], # objID) rot = np.asarray(rot, dtype=np.float32) ======= cls = objID >>>>>>> 177484e6aa32844a6e9ebe9a55dc81406dd72afc tDbox = rot[:3, :3].dot(threeD_boxes[objID, :, :].T).T tDbox = tDbox + np.repeat(poses[i, np.newaxis, 0:3], 8, axis=0) # if objID == 10 or objID == 11: # print(tf3d.euler.quat2euler(poses[i, 3:])) box3D = toPix_array(tDbox, fx=fxkin, fy=fykin, cx=cxkin, cy=cykin) box3D = np.reshape(box3D, (16)) box3D = box3D.tolist() bb3vis.append(box3D) bbox = bbox.astype(int) x1 = np.asscalar(bbox[2]) y1 = np.asscalar(bbox[1]) x2 = np.asscalar(bbox[4]) y2 = np.asscalar(bbox[3]) nx1 = bbox[2] ny1 = bbox[1] nx2 = bbox[4] ny2 = bbox[3] w = (x2 - x1) h = (y2 - y1) boxWidths.append(w) boxHeights.append(h) bb = [x1, y1, w, h] area = w * h npseg = np.array([nx1, ny1, nx2, ny1, nx2, ny2, nx1, ny2]) seg = npseg.tolist() pose = [np.asscalar(poses[i, 0]), np.asscalar(poses[i, 1]), np.asscalar(poses[i, 2]), np.asscalar(poses[i, 3]), np.asscalar(poses[i, 4]), np.asscalar(poses[i, 5]), np.asscalar(poses[i, 6])] if i != len(bboxes): pose[0:2] = toPix(pose[0:3], fx=fxkin, fy=fykin, cx=cxkin, cy=cykin) posvis.append(pose) tra = np.asarray(poses[i, :3], dtype=np.float32) postra.append(tra) annoID = annoID + 1 tempTA = { "id": annoID, "image_id": imgID, "category_id": objID, "bbox": bb, "pose": pose, "segmentation": box3D, "area": area, "iscrowd": 0, # "feature_visibility": feat_vis } # print('norm q: ', np.linalg.norm(pose[3:])) dict["annotations"].append(tempTA) tempTL = { "url": "cmp.felk.cvut.cz/t-less/", "id": imgID, "name": imgName } dict["licenses"].append(tempTL) tempTV = { "license": 2, "url": "cmp.felk.cvut.cz/t-less/", "file_name": imgName, "height": resY, "width": resX, "date_captured": dateT, "id": imgID } dict["images"].append(tempTV) gloCo += 1 elapsed_time = time.time() - start_time times.append(elapsed_time) meantime = sum(times) / len(times) eta = ((all - gloCo) * meantime) / 60 if gloCo % 100 == 0: print('eta: ', eta, ' min') times = [] if visu is True: img = rgbAug for i, bb in enumerate(bbvis): # if cats[i] not in [19, 20, 23]: # continue bb = np.array(bb) cv2.rectangle(img, (int(bb[2]), int(bb[1])), (int(bb[4]), int(bb[3])), (255, 255, 255), 2) cv2.rectangle(img, (int(bb[2]), int(bb[1])), (int(bb[4]), int(bb[3])), (0, 0, 0), 1) font = cv2.FONT_HERSHEY_SIMPLEX bottomLeftCornerOfText = (int(bb[2]), int(bb[1])) fontScale = 1 fontColor = (0, 0, 0) fontthickness = 1 lineType = 2 gtText = str(cats[i]) # print(cats[i]) fontColor2 = (255, 255, 255) fontthickness2 = 3 cv2.putText(img, gtText, bottomLeftCornerOfText, font, fontScale, fontColor2, fontthickness2, lineType) cv2.putText(img, gtText, bottomLeftCornerOfText, font, fontScale, fontColor, fontthickness, lineType) # print(posvis[i]) if i is not poses.shape[0]: pose = np.asarray(bb3vis[i], dtype=np.float32) print(pose) colR = 250 colG = 25 colB = 175 img = cv2.line(img, tuple(pose[0:2].ravel()), tuple(pose[2:4].ravel()), (130, 245, 13), 2) img = cv2.line(img, tuple(pose[2:4].ravel()), tuple(pose[4:6].ravel()), (50, 112, 220), 2) img = cv2.line(img, tuple(pose[4:6].ravel()), tuple(pose[6:8].ravel()), (50, 112, 220), 2) img = cv2.line(img, tuple(pose[6:8].ravel()), tuple(pose[0:2].ravel()), (50, 112, 220), 2) img = cv2.line(img, tuple(pose[0:2].ravel()), tuple(pose[8:10].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[2:4].ravel()), tuple(pose[10:12].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[4:6].ravel()), tuple(pose[12:14].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[6:8].ravel()), tuple(pose[14:16].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[8:10].ravel()), tuple(pose[10:12].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[10:12].ravel()), tuple(pose[12:14].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[12:14].ravel()), tuple(pose[14:16].ravel()), (colR, colG, colB), 2) img = cv2.line(img, tuple(pose[14:16].ravel()), tuple(pose[8:10].ravel()), (colR, colG, colB), 2) cv2.imwrite(fileName, img) print('STOP') catsInt = range(1, 22) for s in catsInt: objName = str(s) tempC = { "id": s, "name": objName, "supercategory": "object" } dict["categories"].append(tempC) traAnno = target + "annotations/instances_train.json" with open(traAnno, 'w') as fpT: json.dump(dict, fpT) excludedImgs.sort() print('excluded images: ') for ex in excludedImgs: print(ex) all_rendered = len(os.listdir(target + "images/train/")) * 0.5 means = meanRGBD / all_rendered print('means: ', means) print('Chill for once in your life... everything\'s done')

40.129428

195

0.420268

3,105

29,455

3.892432

0.125282

0.035744

0.019858

0.025815

0.79439

0.77718

0.772299

0.753847

0.731425

0.730018

0

0.064141

0.447938

29,455

733

196

40.184175

0.67911

0

0.72711

0

0.049519

0.018835

0

null

0.001795

0.02693

null

0.025135

0

null

0

1

0

1

0

null

0

1

0

7

9d9f32a3082b6602ec52717c309388735777bb65

20,861

py

Python

chess_rules.py

cakesterman/Chess-Bot

9c0d2d5c4636ae1bee9ac8e3ec7408b076fb0c93

[ "MIT" ]

null

chess_rules.py

cakesterman/Chess-Bot

9c0d2d5c4636ae1bee9ac8e3ec7408b076fb0c93

[ "MIT" ]

null

chess_rules.py

cakesterman/Chess-Bot

9c0d2d5c4636ae1bee9ac8e3ec7408b076fb0c93

[ "MIT" ]

null

def check_valid_move(game_piece, current_pos, pos_to_move, chess_board): #rules = {"Rook": } # print(game_piece) if game_piece == "Black Rook" or game_piece == "White Rook": moves, captures = rook_calculate_all_possible_moves(current_pos, chess_board) if pos_to_move in moves: return True, moves, captures elif pos_to_move in captures: # print("Capturing") return True, moves, captures return False, moves, captures elif game_piece == "Black Knight" or game_piece == "White Knight": moves, captures = knight_calculate_all_possible_moves(current_pos, chess_board) #print(f"Can capture {captures}") if pos_to_move in moves: return True, moves, captures elif pos_to_move in captures: # print("Capturing") return True, moves, captures else: return False, moves, captures elif game_piece == "Black Bishop" or game_piece == "White Bishop": moves, captures = bishop_calculate_all_possible_moves(current_pos, chess_board) if pos_to_move in moves: return True, moves, captures elif pos_to_move in captures: # print("Capturing") return True, moves, captures else: return False, moves, captures #print(bishop_calculate_all_possible_moves(current_pos, chess_board)) elif game_piece == "Black Queen" or game_piece == "White Queen": moves, captures = queen_calculate_all_possible_moves(current_pos, chess_board) if pos_to_move in moves: return True, moves, captures elif pos_to_move in captures: return True, moves, captures else: return False, moves, captures elif game_piece == "Black King" or game_piece == "White King": moves, captures = king_calculate_all_possible_moves(current_pos, chess_board) if pos_to_move in moves: return True, moves, captures elif pos_to_move in captures: return True, moves, captures else: return False, moves, captures elif game_piece == "Black Pawn" or game_piece == "White Pawn": moves, captures = pawn_calculate_all_possible_moves(current_pos, chess_board) if pos_to_move in moves: chess_board[current_pos].set_first_move_false() return True, moves, captures elif pos_to_move in captures: chess_board[current_pos].set_first_move_false() return True, moves, captures else: return False, moves, captures # Temporary else for testing and moving all other game pieces else: return True def rook_calculate_all_possible_moves(current_pos, chess_board): player = chess_board.get(current_pos).get_player_side() all_possible_moves = [] all_possible_captures = [] x = current_pos[0] y = current_pos[1] # New code for Rook, probably broke some shit, ill find out later # Checking x axis going left and right if 0 <= x <= 7: # x is between 0 and 7 # Check x axis going left for index in range(x - 1, 0, -1): # If the position is empty, add to all_possible_moves if chess_board.get((index, y)) is None: all_possible_moves.append( (index, y) ) # If the position is not empty and is an enemy piece, add to all_possible_captures elif chess_board.get((index, y)).get_player_side() != player: all_possible_captures.append( (index, y) ) break else: break # Checking x axis going right for index in range(x + 1, 7): # If the position is empty, add to all_possible_moves if chess_board.get((index, y)) is None: all_possible_moves.append((index, y)) # If the position is not empty and is an enemy piece, add to all_possible_captures elif chess_board.get((index, y)).get_player_side() != player: all_possible_captures.append((index, y)) break else: break # Checking y axis if 0 <= y <= 7: # Check y axis going up for index in range(y - 1, 0, -1): if chess_board.get((x, index)) is None: all_possible_moves.append( (x, index) ) elif chess_board.get((x, index)).get_player_side() != player: all_possible_captures.append((x, index)) else: break # Check y axis going down for index in range(y + 1, 7): if chess_board.get((x, index)) is None: all_possible_moves.append((x, index)) elif chess_board.get((x, index)).get_player_side() != player: all_possible_captures.append((x, index)) else: break return all_possible_moves, all_possible_captures def knight_calculate_all_possible_moves(current_pos, chess_board): player = chess_board.get(current_pos).get_player_side() all_possible_moves = [] all_possible_captures = [] def check_bounds_and_chess_board(x, y): if 0 <= x < 8 and 0 <= y < 8: if chess_board.get((x, y)) is None: all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: all_possible_captures.append((x, y)) for x in range(8): for y in range(8): if x == (current_pos[0] - 1) and y == (current_pos[1] + 2): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] + 1) and y == (current_pos[1] + 2): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] - 1) and y == (current_pos[1] - 2): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] + 1) and y == (current_pos[1] - 2): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] - 2) and y == (current_pos[1] + 1): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] - 2) and y == (current_pos[1] - 1): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] + 2) and y == (current_pos[1] + 1): check_bounds_and_chess_board(x, y) elif x == (current_pos[0] + 2) and y == (current_pos[1] - 1): check_bounds_and_chess_board(x, y) # print(all_possible_captures) return all_possible_moves, all_possible_captures def bishop_calculate_all_possible_moves(current_pos, chess_board): player = chess_board.get(current_pos).get_player_side() all_possible_moves = [] all_possible_captures = [] def search_left_down_diagonally(): x = current_pos[0] y = current_pos[1] possible = True while possible: x -= 1 y += 1 if chess_board.get((x, y)) is None: if x < 0 or y > 7: possible = False break #print("At location ({}, {})".format(x, y)) all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if x < 0 or y > 7: possible = False break all_possible_captures.append((x, y)) possible = False else: possible = False def search_right_down_diagonally(): x = current_pos[0] y = current_pos[1] possible = True while possible: x += 1 y += 1 # if x == 7 or y == 7: # possible = False if chess_board.get((x, y)) is None: if x > 7 or y > 7: possible = False break #print("At location ({}, {})".format(x, y)) all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if x > 7 or y > 7: possible = False break all_possible_captures.append((x, y)) possible = False else: possible = False def search_left_up_diagonally(): x = current_pos[0] y = current_pos[1] possible = True while possible: x -= 1 y -= 1 if chess_board.get((x, y)) is None: if x < 0 or y < 0: possible = False break #print("At location ({}, {})".format(x, y)) all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if x < 0 or y < 0: possible = False break all_possible_captures.append((x, y)) possible = False else: possible = False def search_right_up_diagonally(): x = current_pos[0] y = current_pos[1] possible = True while possible: x += 1 y -= 1 if chess_board.get((x, y)) is None: if x > 7 or y < 0: possible = False break #print("At location ({}, {})".format(x, y)) all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if x > 7 or y < 0: possible = False break all_possible_captures.append((x, y)) possible = False else: possible = False if current_pos[1] == 0: if current_pos[0] > 0: # Search left down diagonally search_left_down_diagonally() if current_pos[0] < 7: # Search right down diagonally search_right_down_diagonally() else: if current_pos[1] == 7 and 0 < current_pos[0] < 7: search_left_up_diagonally() search_right_up_diagonally() else: if current_pos[0] > 0: search_left_down_diagonally() search_right_down_diagonally() search_left_up_diagonally() search_right_up_diagonally() if current_pos[0] == 0 and current_pos[1] < 7: search_right_up_diagonally() search_right_down_diagonally() if current_pos[0] == 7 and current_pos[1] < 7: search_left_up_diagonally() search_left_down_diagonally() if current_pos[1] == 7 and current_pos[0] == 0: search_right_up_diagonally() return all_possible_moves, all_possible_captures def queen_calculate_all_possible_moves(current_pos, chess_board): player = chess_board.get(current_pos).get_player_side() all_possible_moves = [] all_possible_captures = [] moves, captures = bishop_calculate_all_possible_moves(current_pos, chess_board) all_possible_moves.extend(moves) all_possible_captures.extend(captures) def search_down(): x = current_pos[0] y = current_pos[1] possible = True while possible: y += 1 if chess_board.get((x, y)) is None: if y == 7: possible = False all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if y == 7: possible = False all_possible_captures.append((x, y)) possible = False else: possible = False def search_up(): x = current_pos[0] y = current_pos[1] possible = True while possible: y -= 1 if chess_board.get((x, y)) is None: if y == 0: possible = False all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if y == 0: possible = False all_possible_captures.append((x, y)) possible = False else: possible = False def search_left(): x = current_pos[0] y = current_pos[1] possible = True while possible: x -= 1 if chess_board.get((x, y)) is None: if x == 0: possible = False all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if x == 0: possible = False all_possible_captures.append((x, y)) possible = False else: possible = False def search_right(): x = current_pos[0] y = current_pos[1] possible = True while possible: x += 1 if chess_board.get((x, y)) is None: if x == 7: possible = False all_possible_moves.append((x, y)) elif chess_board.get((x, y)).get_player_side() != player: if x == 7: possible = False all_possible_captures.append((x, y)) possible = False else: possible = False if current_pos[1] == 0 and 0 < current_pos[0] < 7: search_down() search_left() search_right() if current_pos[1] == 0 and current_pos[0] == 0: search_right() search_down() if current_pos[1] == 0 and current_pos[0] == 7: search_left() search_down() if current_pos[1] == 7 and 0 < current_pos[0] < 7: search_up() search_left() search_right() if current_pos[1] == 7 and current_pos[0] == 0: search_right() search_up() if current_pos[1] == 7 and current_pos[0] == 7: search_left() search_up() if 0 < current_pos[1] < 7 and 0 < current_pos[0] < 7: search_right() search_left() search_up() search_down() if 0 < current_pos[1] < 7 and current_pos[0] == 0: search_up() search_right() search_down() #print(all_possible_moves) return all_possible_moves, all_possible_captures def king_calculate_all_possible_moves(current_pos, chess_board): player = chess_board.get(current_pos).get_player_side() all_possible_moves = [] all_possible_captures = [] x = current_pos[0] y = current_pos[1] def search_down(): if chess_board.get((x, y + 1)) is None: all_possible_moves.append((current_pos[0], (current_pos[1] + 1))) elif chess_board.get((x, y + 1)).get_player_side() != player: all_possible_captures.append((x, y + 1)) def search_up(): if chess_board.get((x, y - 1)) is None: all_possible_moves.append((current_pos[0], (current_pos[1] - 1))) elif chess_board.get((x, y - 1)).get_player_side() != player: all_possible_captures.append((x, y - 1)) def search_left(): if chess_board.get((x - 1, y)) is None: all_possible_moves.append((current_pos[0] - 1, current_pos[1])) elif chess_board.get((x - 1, y)).get_player_side() != player: all_possible_captures.append((x - 1, y)) def search_right(): if chess_board.get((x + 1, y)) is None: all_possible_moves.append((current_pos[0] + 1, current_pos[1])) elif chess_board.get((x + 1, y)).get_player_side() != player: all_possible_captures.append((x + 1, y)) def search_left_up_diagonally(): if chess_board.get((x - 1, y - 1)) is None: all_possible_moves.append((current_pos[0] - 1, current_pos[1] - 1)) elif chess_board.get((x - 1, y - 1)).get_player_side() != player: all_possible_captures.append((x - 1, y - 1)) def search_left_down_diagonally(): if chess_board.get((x - 1, y + 1)) is None: all_possible_moves.append((current_pos[0] - 1, current_pos[1] + 1)) elif chess_board.get((x - 1, y + 1)).get_player_side() != player: all_possible_captures.append((x - 1, y + 1)) def search_right_up_diagonally(): if chess_board.get((x + 1, y - 1)) is None: all_possible_moves.append((current_pos[0] + 1, current_pos[1] - 1)) elif chess_board.get((x + 1, y - 1)).get_player_side() != player: all_possible_captures.append((x + 1, y - 1)) def search_right_down_diagonally(): if chess_board.get((x + 1, y + 1)) is None: all_possible_moves.append((current_pos[0] + 1, current_pos[1] + 1)) elif chess_board.get((x + 1, y + 1)).get_player_side() != player: all_possible_captures.append((x + 1, y + 1)) # y == 0 and 0 < x < 7 if current_pos[1] == 0 and 0 < current_pos[0] < 7: search_down() search_left() search_right() search_left_down_diagonally() search_right_down_diagonally() # y == 0 and x == 0 if current_pos[1] == 0 and current_pos[0] == 0: search_right() search_down() search_right_down_diagonally() # y == 0 and x == 7 if current_pos[1] == 0 and current_pos[0] == 7: search_left() search_down() search_left_down_diagonally() # y == 7 and 0 < x < 7 if current_pos[1] == 7 and 0 < current_pos[0] < 7: search_up() search_left() search_right() search_left_up_diagonally() search_right_up_diagonally() # y == 7 and x == 0 if current_pos[1] == 7 and current_pos[0] == 0: search_right() search_up() search_right_up_diagonally() # y == 7 and x == 7 if current_pos[1] == 7 and current_pos[0] == 7: search_left() search_up() search_left_up_diagonally() if 0 < current_pos[1] < 7 and current_pos[0] == 0: search_up() search_right() search_down() search_right_down_diagonally() search_right_up_diagonally() if 0 < current_pos[1] < 7 and current_pos[0] == 7: search_up() search_left() search_down() search_left_up_diagonally() search_left_down_diagonally() if 0 < current_pos[1] < 7 and 0 < current_pos[0] < 7: search_right() search_left() search_up() search_down() search_right_up_diagonally() search_left_up_diagonally() search_left_down_diagonally() search_right_down_diagonally() return all_possible_moves, all_possible_captures def pawn_calculate_all_possible_moves(current_pos, chess_board): #print(current_pos) player = chess_board.get(current_pos).get_player_side() all_possible_moves = [] all_possible_captures = [] x = current_pos[0] y = current_pos[1] # If this is pawns first move, it can move two spaces if chess_board[current_pos].get_is_first_move(): if y == 1: all_possible_moves.append((x, y + 2)) if y == 6: all_possible_moves.append((x, y - 2)) if chess_board[current_pos].get_name()[0:5] == "Black": if y < 7: if chess_board.get((x, y + 1)) is None: all_possible_moves.append((x, y + 1)) if chess_board.get((x - 1, y + 1)) is not None and chess_board.get((x - 1, y + 1)).get_player_side() != player: all_possible_captures.append((x - 1, y + 1)) if chess_board.get((x + 1, y + 1)) is not None and chess_board.get((x + 1, y + 1)).get_player_side() != player: all_possible_captures.append((x + 1, y + 1)) # else pawn is a white piece else: if y > 0: if chess_board.get((x, y - 1)) is None: all_possible_moves.append((x, y - 1)) if chess_board.get((x - 1, y - 1)) is not None and chess_board.get((x - 1, y - 1)).get_player_side() != player: all_possible_captures.append((x - 1, y - 1)) if chess_board.get((x + 1, y - 1)) is not None and chess_board.get((x + 1, y - 1)).get_player_side() != player: all_possible_captures.append((x + 1, y - 1)) return all_possible_moves, all_possible_captures

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0

7

9dbe250bb3ec584374e58cf5b830aaf5accb4f5c

183

py

Python

cassandra_s3_incremental_backup_watcher/util.py

Cobliteam/cassandra-s3-incremental-backup-watcher

65e7f798ebdb3bc3fdb60847799fa736348f602d

[ "MIT" ]

1

2020-06-01T09:41:06.000Z

cassandra_s3_incremental_backup_watcher/util.py

Cobliteam/cassandra-s3-incremental-backup-watcher

65e7f798ebdb3bc3fdb60847799fa736348f602d

[ "MIT" ]

null

cassandra_s3_incremental_backup_watcher/util.py

Cobliteam/cassandra-s3-incremental-backup-watcher

65e7f798ebdb3bc3fdb60847799fa736348f602d

[ "MIT" ]

null

from __future__ import absolute_import, unicode_literals import re def clean_s3_path(path): path = re.sub(r'^/+', '', path) path = re.sub(r'/+$', '', path) return path

18.3

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null

0

1

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1

0

7

d1a3f1be28accc2299cc8b40a4eff31e1a0666df

1,103

py

Python

blog/models.py

bilal-yousuf/django_local_library

18dbf298253a097412a2bf365dc6b3a557a634a2

[ "MIT" ]

null

blog/models.py

bilal-yousuf/django_local_library

18dbf298253a097412a2bf365dc6b3a557a634a2

[ "MIT" ]

7

2020-02-12T00:31:18.000Z

2022-03-12T00:34:07.000Z

blog/models.py

bilal-yousuf/django_local_library

18dbf298253a097412a2bf365dc6b3a557a634a2

[ "MIT" ]

null

from django.db import models from django.urls import reverse from datetime import date #from ckeditor.fields import RichTextField # Create your models here. class Blog(models.Model): """Model representing a blog post.""" title = models.CharField(max_length=200) body = models.TextField(help_text="What is the body of your blog post?") pub_date = models.DateField(auto_now_add=True) pub_time = models.TimeField(auto_now_add=True) def get_absolute_url(self): return reverse('blog-detail', args=[str(self.id)]) def __str__(self): return self.title class Meta: ordering = ['-pub_date', '-pub_time'] # Create your models here. class Note(models.Model): """Model representing a blog post.""" title = models.CharField(max_length=200) body = models.TextField(help_text="What is the body of your blog post?") pub_date = models.DateField(auto_now_add=True) pub_time = models.TimeField(auto_now_add=True) def get_absolute_url(self): return reverse('note-detail', args=[str(self.id)]) def __str__(self): return self.title class Meta: ordering = ['-pub_date', '-pub_time']

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0.329341

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0.071429

0.839286

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0.006303

0.136899

1,103

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24.511111

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1

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null

0

1

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9

d1c4193d3edb2bf7c45e926be8a31f3f9568643e

140

py

Python

convoy/utils/__init__.py

frain-dev/convoy-python

7607a6b65615cc83c38bfb7dba4ad6ed564860bc

[ "MIT" ]

null

convoy/utils/__init__.py

frain-dev/convoy-python

7607a6b65615cc83c38bfb7dba4ad6ed564860bc

[ "MIT" ]

null

convoy/utils/__init__.py

frain-dev/convoy-python

7607a6b65615cc83c38bfb7dba4ad6ed564860bc

[ "MIT" ]

null

from convoy.utils.helpers import responseHelper from convoy.utils.helpers import verifySignature from convoy.utils.helpers import hashString

46.666667

48

0.878571

18

140

6.833333

0.444444

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0.365854

0.536585

0.682927

0

0.078571

140

3

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46.666667

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1

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1

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null

0

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0

7

d1ef2734f13f6cdbaf17c5709cb943fed9d03cb8

767

py

Python

src/tf_transformers/utils/__init__.py

s4sarath/tf-transformers

361f7b01c7816034ddfc8661f8b6a967835bc1de

[ "Apache-2.0" ]

1

2021-09-13T07:21:15.000Z

src/tf_transformers/utils/__init__.py

Vibha111094/tf-transformers

f26d440a4de0557e0e481279bfd70a732aaa8825

[ "Apache-2.0" ]

null

src/tf_transformers/utils/__init__.py

Vibha111094/tf-transformers

f26d440a4de0557e0e481279bfd70a732aaa8825

[ "Apache-2.0" ]

null

from tf_transformers.utils.convert.convert_albert import convert_albert_hf_to_tf_transformers from tf_transformers.utils.convert.convert_bert import convert_bert_hf_to_tf_transformers from tf_transformers.utils.convert.convert_gpt2 import convert_gpt2_hf_to_tf_transformers from tf_transformers.utils.convert.convert_roberta import convert_roberta_hf_to_tf_transformers from tf_transformers.utils.convert.convert_t5 import convert_t5_hf_to_tf_transformers from tf_transformers.utils.convert.convert_mt5 import convert_mt5_hf_to_tf_transformers from tf_transformers.utils.fast_sp_alignment import fast_sp_alignment from tf_transformers.utils.tokenization import BasicTokenizer from tf_transformers.utils.utils import get_config, get_model_wrapper, validate_model_name

76.7

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116

767

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0.215517

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0.543914

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767

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true

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null

0

1

0

1

0

1

0

7

ae3c160751268fe8a0b62fa16ae7bea32cddb36e

114

py

Python

django_changeset/models/__init__.py

beachmachine/django-changeset

9ce8edbcbdf9d721c683f6890a8ee76486380ded

[ "BSD-3-Clause" ]

7

2016-04-29T19:46:43.000Z

2020-03-30T16:19:14.000Z

django_changeset/models/__init__.py

beachmachine/django-changeset

9ce8edbcbdf9d721c683f6890a8ee76486380ded

[ "BSD-3-Clause" ]

3

2019-06-03T12:35:16.000Z

2021-10-15T07:31:56.000Z

django_changeset/models/__init__.py

beachmachine/django-changeset

9ce8edbcbdf9d721c683f6890a8ee76486380ded

[ "BSD-3-Clause" ]

7

2020-01-08T09:13:33.000Z

2020-10-09T12:05:31.000Z

# -*- coding: utf-8 -*- from django_changeset.models.models import * from django_changeset.models.mixins import *

28.5

44

0.754386

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0

0.009901

0.114035

114

3

45

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0.821782

0.184211

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true

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null

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null

0

1

0

1

0

1

0

8

ae623763da0ebbd1a9caf0577b2912b6db545c78

11,025

py

Python

lang/python/github/com/metaprov/modelaapi/services/lab/v1/lab_pb2_grpc.py

metaprov/modeldapi

ee05693832051dcd990ee4f061715d7ae0787340

[ "Apache-2.0" ]

5

2022-02-18T03:40:10.000Z

2022-03-01T16:11:24.000Z

lang/python/github/com/metaprov/modelaapi/services/lab/v1/lab_pb2_grpc.py

metaprov/modeldapi

ee05693832051dcd990ee4f061715d7ae0787340

[ "Apache-2.0" ]

1

2022-01-07T19:59:25.000Z

2022-02-04T01:21:14.000Z

lang/python/github/com/metaprov/modelaapi/services/lab/v1/lab_pb2_grpc.py

metaprov/modeldapi

ee05693832051dcd990ee4f061715d7ae0787340

[ "Apache-2.0" ]

1

2022-03-25T10:21:43.000Z

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from github.com.metaprov.modelaapi.services.lab.v1 import lab_pb2 as github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2 class LabServiceStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.ListLabs = channel.unary_unary( '/github.com.metaprov.modelaapi.services.lab.v1.LabService/ListLabs', request_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.ListLabsRequest.SerializeToString, response_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.ListLabsResponse.FromString, ) self.CreateLab = channel.unary_unary( '/github.com.metaprov.modelaapi.services.lab.v1.LabService/CreateLab', request_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.CreateLabRequest.SerializeToString, response_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.CreateLabResponse.FromString, ) self.GetLab = channel.unary_unary( '/github.com.metaprov.modelaapi.services.lab.v1.LabService/GetLab', request_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.GetLabRequest.SerializeToString, response_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.GetLabResponse.FromString, ) self.UpdateLab = channel.unary_unary( '/github.com.metaprov.modelaapi.services.lab.v1.LabService/UpdateLab', request_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.UpdateLabRequest.SerializeToString, response_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.UpdateLabResponse.FromString, ) self.DeleteLab = channel.unary_unary( '/github.com.metaprov.modelaapi.services.lab.v1.LabService/DeleteLab', request_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.DeleteLabRequest.SerializeToString, response_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.DeleteLabResponse.FromString, ) class LabServiceServicer(object): """Missing associated documentation comment in .proto file.""" def ListLabs(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def CreateLab(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetLab(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def UpdateLab(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DeleteLab(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_LabServiceServicer_to_server(servicer, server): rpc_method_handlers = { 'ListLabs': grpc.unary_unary_rpc_method_handler( servicer.ListLabs, request_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.ListLabsRequest.FromString, response_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.ListLabsResponse.SerializeToString, ), 'CreateLab': grpc.unary_unary_rpc_method_handler( servicer.CreateLab, request_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.CreateLabRequest.FromString, response_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.CreateLabResponse.SerializeToString, ), 'GetLab': grpc.unary_unary_rpc_method_handler( servicer.GetLab, request_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.GetLabRequest.FromString, response_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.GetLabResponse.SerializeToString, ), 'UpdateLab': grpc.unary_unary_rpc_method_handler( servicer.UpdateLab, request_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.UpdateLabRequest.FromString, response_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.UpdateLabResponse.SerializeToString, ), 'DeleteLab': grpc.unary_unary_rpc_method_handler( servicer.DeleteLab, request_deserializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.DeleteLabRequest.FromString, response_serializer=github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.DeleteLabResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'github.com.metaprov.modelaapi.services.lab.v1.LabService', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class LabService(object): """Missing associated documentation comment in .proto file.""" @staticmethod def ListLabs(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/github.com.metaprov.modelaapi.services.lab.v1.LabService/ListLabs', github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.ListLabsRequest.SerializeToString, github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.ListLabsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def CreateLab(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/github.com.metaprov.modelaapi.services.lab.v1.LabService/CreateLab', github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.CreateLabRequest.SerializeToString, github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.CreateLabResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetLab(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/github.com.metaprov.modelaapi.services.lab.v1.LabService/GetLab', github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.GetLabRequest.SerializeToString, github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.GetLabResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def UpdateLab(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/github.com.metaprov.modelaapi.services.lab.v1.LabService/UpdateLab', github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.UpdateLabRequest.SerializeToString, github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.UpdateLabResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def DeleteLab(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/github.com.metaprov.modelaapi.services.lab.v1.LabService/DeleteLab', github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.DeleteLabRequest.SerializeToString, github_dot_com_dot_metaprov_dot_modelaapi_dot_services_dot_lab_dot_v1_dot_lab__pb2.DeleteLabResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

55.40201

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0.050325

0.062906

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1

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null

0

7

ae89e6a6b575079c9003b3e252e49ef8aae70b5a

103,198

py

Python

Architectures/x86/x86disassembly.py

Ernest1338/Threebe

8b2ffc8e7dd3a1bfb70e3194abef4b5a61704dcb

[ "MIT" ]

2

2020-08-18T18:41:37.000Z

2021-03-22T04:10:47.000Z

Architectures/x86/x86disassembly.py

Ernest1338/Threebe

8b2ffc8e7dd3a1bfb70e3194abef4b5a61704dcb

[ "MIT" ]

2

2021-08-11T09:38:45.000Z

2021-08-12T09:17:13.000Z

Architectures/x86/x86disassembly.py

Ernest1338/Threebe

8b2ffc8e7dd3a1bfb70e3194abef4b5a61704dcb

[ "MIT" ]

null

# This file contains function(s) that translates raw bytes into assembly instructions using x86opcodesTable and some python logic. import Architectures.x86.x86opcodesTable as x86opT times = 0 def cancle_function_iteration(howmany): global times times += int(howmany) def disassemble_x86(bytes, ascii_dict, colors): global times bcolors = colors if bcolors.HEADER == '': class bcolors: HEADER = '\033[95m' OKBLUE = '\033[94m' OKGREEN = '\033[92m' WARNING = '\033[93m' FAIL = '\033[91m' BOLD = '\033[01m' UNDERLINE = '\033[04m' RESET = '\033[00m' isClean = True else: isClean = False offset1 = 134512640 counter1 = 0 for i in bytes: if isClean: class bcolors: HEADER = '\033[95m' OKBLUE = '\033[94m' OKGREEN = '\033[92m' WARNING = '\033[93m' FAIL = '\033[91m' BOLD = '\033[01m' UNDERLINE = '\033[04m' RESET = '\033[00m' if times == 0: to_display = i after_instruction = "" after_byte = "" if i in x86opT.x86opcodes: instruction = x86opT.x86opcodes[i] intruction_len_for_check = 51+len(instruction) # need to add to this after_instruction every time this variable (after_instruction) is usesd inside an if should_print = True # 1 byte instructions if (i == "06" or i == "07" or i == "0E" or i == "16" or i == "17" or i == "1E" or i == "1F" or i == "27" or i == "2F" or i == "40" or i == "41" or i == "42" or i == "43" or i == "44" or i == "45" or i == "46" or i == "47" or i == "48" or i == "49" or i == "4A" or i == "4B" or i == "4C" or i == "4D" or i == "4E" or i == "4F" or i == "50" or i == "51" or i == "52" or i == "53" or i == "54" or i == "55" or i == "56" or i == "57" or i == "58" or i == "59" or i == "5A" or i == "5B" or i == "5C" or i == "5D" or i == "5E" or i == "5F" or i == "61" or i == "90" or i == "98" or i == "99" or i == "C3" or i == "C9" or i == "CF" or i == "EC" or i == "ED" or i == "EE" or i == "EF" or i == "F8"): check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+" "+instruction.split(" ")[2]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" elif i == "01": # ADD after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="CA": after_instruction = " edx, ecx" elif bytes[counter1+1]=="D0": after_instruction = " eax, edx" elif bytes[counter1+1]=="01": after_instruction = " dword [ecx], eax" elif bytes[counter1+1]=="00": after_instruction = " dword [eax], eax" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "04": # ADD al, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " al, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "08": # OR after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="00": after_instruction = " byte [eax], al" elif bytes[counter1+1]=="01": after_instruction = " byte [ecx], al" elif bytes[counter1+1]=="02": after_instruction = " byte [edx], al" elif bytes[counter1+1]=="03": after_instruction = " byte [ebx], al" elif bytes[counter1+1]=="06": after_instruction = " byte [esi], al" elif bytes[counter1+1]=="07": after_instruction = " byte [edi], al" elif bytes[counter1+1]=="08": after_instruction = " byte [eax], cl" elif bytes[counter1+1]=="09": after_instruction = " byte [ecx], cl" elif bytes[counter1+1]=="0A": after_instruction = " byte [edx], cl" elif bytes[counter1+1]=="0B": after_instruction = " byte [ebx], cl" elif bytes[counter1+1]=="0E": after_instruction = " byte [esx], cl" elif bytes[counter1+1]=="0F": after_instruction = " byte [edi], cl" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "0A": # OR after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="36": after_instruction = " dh, byte [esi]" elif bytes[counter1+1]=="00": after_instruction = " al, byte [eax]" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "0B": # OR after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="00": after_instruction = " eax, dword [eax]" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "0C": # OR al, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " al, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "20": # AND after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="00": after_instruction = " byte [eax], al" elif bytes[counter1+1]=="01": after_instruction = " byte [ecx], al" elif bytes[counter1+1]=="02": after_instruction = " byte [edx], al" elif bytes[counter1+1]=="03": after_instruction = " byte [ebx], al" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "24": # AND al, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " al, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "29": # SUB after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="C6": after_instruction = " esi, eax" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "2C": # SUB al, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " al, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "30": # XOR after_byte = " "+bytes[counter1+1] XOR30var = 1 if bytes[counter1+1]=="00": after_instruction = " byte [eax], al" elif bytes[counter1+1]=="4D": XOR30var2 = str(bytes[counter1+2]) if str(bytes[counter1+2][0])=="0": XOR30var2 = str(bytes[counter1+2][1]) after_instruction = " byte [ebp + 0x"+XOR30var2+"], cl" XOR30var = 2 else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(XOR30var) elif i == "31": # XOR after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="ED": after_instruction = " ebp, ebp" elif bytes[counter1+1]=="FF": after_instruction = " edi, edi" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "32": # XOR after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="00": after_instruction = " al, byte [eax]" elif bytes[counter1+1]=="2E": after_instruction = " ch, byte [esi]" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "34": # XOR al, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " al, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif (i == "64" or i == "65" or i == "66" or i == "67"): # NOP after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="90": after_instruction = "" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "68": # PUSH string after_byte = " "+bytes[counter1+1]+" "+bytes[counter1+2]+" "+bytes[counter1+3]+" "+bytes[counter1+4] TEMPoffset = " 0x"+bytes[counter1+4]+bytes[counter1+3]+bytes[counter1+2]+bytes[counter1+1] TEMPoffset_to_dict2 = hex(int(TEMPoffset,16)+1) TEMPoffset_to_dict = hex(int(TEMPoffset,16)) if TEMPoffset_to_dict in ascii_dict: after_instruction = TEMPoffset lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; str: "+str(ascii_dict[TEMPoffset_to_dict]) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; str: {bcolors.WARNING}"+str(ascii_dict[TEMPoffset_to_dict]) elif TEMPoffset_to_dict2 in ascii_dict: after_instruction = TEMPoffset lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; str: "+str(ascii_dict[TEMPoffset_to_dict2]) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; str: {bcolors.WARNING}"+str(ascii_dict[TEMPoffset_to_dict2]) else: after_instruction = TEMPoffset check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(4) elif i == "70" or i == "71" or i == "72" or i == "73" or i == "74" or i == "75" or i == "7E" or i == "7F": # JE, JNE, JLE, JG, JO, JNO, JB, JAE after_byte = " "+bytes[counter1+1] if int(bytes[counter1+1],16)>=128: if int(bytes[counter1+1],16)==255: after_instruction = " "+hex(offset1+1) elif int(bytes[counter1+1],16)==254: after_instruction = " "+hex(offset1) else: after_instruction = " "+hex(offset1-(256-(int(bytes[counter1+1],16)+2))) else: after_instruction = " "+hex(offset1+(int(bytes[counter1+1],16)+2)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "81": # ADD, ... after_byte = " "+bytes[counter1+1]+" "+bytes[counter1+2]+" "+bytes[counter1+3]+" "+bytes[counter1+4]+" "+bytes[counter1+5] _81var = "" if bytes[counter1+1]=="C3": if bytes[counter1+5]!="00": _81var += str(bytes[counter1+5]) if bytes[counter1+4]!="00": _81var += str(bytes[counter1+4]) if bytes[counter1+3]!="00": _81var += str(bytes[counter1+3]) if bytes[counter1+2]!="00": _81var += str(bytes[counter1+2]) after_instruction = " ebx, 0x"+_81var lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(_81var,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(_81var,16)) elif bytes[counter1+1]=="EC": instruction = "SUB" if bytes[counter1+5]!="00": _81var += str(bytes[counter1+5]) if bytes[counter1+4]!="00": _81var += str(bytes[counter1+4]) if bytes[counter1+3]!="00": _81var += str(bytes[counter1+3]) if bytes[counter1+2]!="00": _81var += str(bytes[counter1+2]) after_instruction = " esp, 0x"+_81var lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(_81var,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(_81var,16)) else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(5) elif i == "83": # ADD, CMP, SUB, OR after_byte = " "+bytes[counter1+1]+" "+bytes[counter1+2] TEMPvar = bytes[counter1+2] TEMPvar2 = 2 TEMPvar3 = bytes[counter1+3] TEMPvar4 = str(int(TEMPvar,16)) if bytes[counter1+2][0]=="0": TEMPvar = bytes[counter1+2][1] if bytes[counter1+3][0]=="0": TEMPvar3 = bytes[counter1+3][1] if bytes[counter1+1]=="C2": after_instruction = " edx, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="C4": after_instruction = " esp, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="C7": after_instruction = " edi, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="C0": after_instruction = " eax, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="F8": instruction = "CMP" after_instruction = " eax, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="3B": instruction = "CMP" after_instruction = " dword [ebx], "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="EC": instruction = "SUB" after_instruction = " esp, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="EA": instruction = "SUB" after_instruction = " edx, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="08": instruction = "OR" if TEMPvar=="FF": TEMPvar4 = "-1" after_instruction = " dword [eax], "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 elif bytes[counter1+1]=="E4": instruction = "AND" if TEMPvar=="FF": TEMPvar4 = "-1" elif TEMPvar[0]=="F": TEMPvar = "FFFFFF"+TEMPvar after_instruction = " esp, "+"0x"+str(TEMPvar.lower()) elif bytes[counter1+1]=="45" and bytes[counter1+2]=="FC": TEMPvar4 = str(int(bytes[counter1+3],16)) after_instruction = " dword [var_4h], "+"0x"+str(TEMPvar3.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 after_byte += " "+bytes[counter1+3] TEMPvar2 = 4 elif bytes[counter1+1]=="7D" and bytes[counter1+2]=="08": TEMPvar4 = str(int(bytes[counter1+3],16)) instruction = "CMP" after_instruction = " dword [arg_8h], "+"0x"+str(TEMPvar3.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+TEMPvar4 else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+TEMPvar4 after_byte += " "+bytes[counter1+3] TEMPvar2 = 4 else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(TEMPvar2) elif i == "84": # TEST after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="C0": after_instruction = " al, al" elif bytes[counter1+1]=="C1": after_instruction = " cl, al" elif bytes[counter1+1]=="C2": after_instruction = " dl, al" elif bytes[counter1+1]=="C3": after_instruction = " bl, al" elif bytes[counter1+1]=="C4": after_instruction = " ah, al" elif bytes[counter1+1]=="C5": after_instruction = " ch, al" elif bytes[counter1+1]=="C6": after_instruction = " dh, al" elif bytes[counter1+1]=="C7": after_instruction = " bh, al" elif bytes[counter1+1]=="C8": after_instruction = " al, cl" elif bytes[counter1+1]=="C9": after_instruction = " cl, cl" elif bytes[counter1+1]=="CA": after_instruction = " dl, cl" elif bytes[counter1+1]=="CB": after_instruction = " bl, cl" elif bytes[counter1+1]=="CC": after_instruction = " ah, cl" elif bytes[counter1+1]=="CD": after_instruction = " ch, cl" elif bytes[counter1+1]=="CE": after_instruction = " dh, cl" elif bytes[counter1+1]=="CF": after_instruction = " bh, cl" elif bytes[counter1+1]=="D0": after_instruction = " al, dl" elif bytes[counter1+1]=="D1": after_instruction = " cl, dl" elif bytes[counter1+1]=="D2": after_instruction = " dl, dl" elif bytes[counter1+1]=="D3": after_instruction = " bl, dl" elif bytes[counter1+1]=="D4": after_instruction = " ah, dl" elif bytes[counter1+1]=="D5": after_instruction = " ch, dl" elif bytes[counter1+1]=="D6": after_instruction = " dh, dl" elif bytes[counter1+1]=="D7": after_instruction = " bh, dl" elif bytes[counter1+1]=="D8": after_instruction = " al, bl" elif bytes[counter1+1]=="D9": after_instruction = " cl, bl" elif bytes[counter1+1]=="DA": after_instruction = " dl, bl" elif bytes[counter1+1]=="DB": after_instruction = " bl, bl" elif bytes[counter1+1]=="DC": after_instruction = " ah, bl" elif bytes[counter1+1]=="DD": after_instruction = " ch, bl" elif bytes[counter1+1]=="DE": after_instruction = " dh, bl" elif bytes[counter1+1]=="DF": after_instruction = " bh, bl" elif bytes[counter1+1]=="E0": after_instruction = " al, ah" elif bytes[counter1+1]=="E1": after_instruction = " cl, ah" elif bytes[counter1+1]=="E2": after_instruction = " dl, ah" elif bytes[counter1+1]=="E3": after_instruction = " bl, ah" elif bytes[counter1+1]=="E4": after_instruction = " ah, ah" elif bytes[counter1+1]=="E5": after_instruction = " ch, ah" elif bytes[counter1+1]=="E6": after_instruction = " dh, ah" elif bytes[counter1+1]=="E7": after_instruction = " bh, ah" elif bytes[counter1+1]=="E8": after_instruction = " al, ch" elif bytes[counter1+1]=="E9": after_instruction = " cl, ch" elif bytes[counter1+1]=="EA": after_instruction = " dl, ch" elif bytes[counter1+1]=="EB": after_instruction = " bl, ch" elif bytes[counter1+1]=="EC": after_instruction = " ah, ch" elif bytes[counter1+1]=="ED": after_instruction = " ch, ch" elif bytes[counter1+1]=="EE": after_instruction = " dh, ch" elif bytes[counter1+1]=="EF": after_instruction = " bh, ch" elif bytes[counter1+1]=="F0": after_instruction = " al, dh" elif bytes[counter1+1]=="F1": after_instruction = " cl, dh" elif bytes[counter1+1]=="F2": after_instruction = " dl, dh" elif bytes[counter1+1]=="F3": after_instruction = " bl, dh" elif bytes[counter1+1]=="F4": after_instruction = " ah, dh" elif bytes[counter1+1]=="F5": after_instruction = " ch, dh" elif bytes[counter1+1]=="F6": after_instruction = " dh, dh" elif bytes[counter1+1]=="F7": after_instruction = " bh, dh" elif bytes[counter1+1]=="F8": after_instruction = " al, bh" elif bytes[counter1+1]=="F9": after_instruction = " cl, bh" elif bytes[counter1+1]=="FA": after_instruction = " dl, bh" elif bytes[counter1+1]=="FB": after_instruction = " bl, bh" elif bytes[counter1+1]=="FC": after_instruction = " ah, bh" elif bytes[counter1+1]=="FD": after_instruction = " ch, bh" elif bytes[counter1+1]=="FE": after_instruction = " dh, bh" elif bytes[counter1+1]=="FF": after_instruction = " bh, bh" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "85": # TEST after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="C0": after_instruction = " eax, eax" elif bytes[counter1+1]=="C1": after_instruction = " ecx, eax" elif bytes[counter1+1]=="C2": after_instruction = " edx, eax" elif bytes[counter1+1]=="C3": after_instruction = " ebx, eax" elif bytes[counter1+1]=="C4": after_instruction = " esp, eax" elif bytes[counter1+1]=="C5": after_instruction = " ebp, eax" elif bytes[counter1+1]=="C6": after_instruction = " esi, eax" elif bytes[counter1+1]=="C7": after_instruction = " edi, eax" elif bytes[counter1+1]=="C8": after_instruction = " eax, ecx" elif bytes[counter1+1]=="C9": after_instruction = " ecx, ecx" elif bytes[counter1+1]=="CA": after_instruction = " edx, ecx" elif bytes[counter1+1]=="CB": after_instruction = " ebx, ecx" elif bytes[counter1+1]=="CC": after_instruction = " esp, ecx" elif bytes[counter1+1]=="CD": after_instruction = " ebp, ecx" elif bytes[counter1+1]=="CE": after_instruction = " esi, ecx" elif bytes[counter1+1]=="CF": after_instruction = " edi, ecx" elif bytes[counter1+1]=="D0": after_instruction = " eax, edx" elif bytes[counter1+1]=="D1": after_instruction = " ecx, edx" elif bytes[counter1+1]=="D2": after_instruction = " edx, edx" elif bytes[counter1+1]=="D3": after_instruction = " ebx, edx" elif bytes[counter1+1]=="D4": after_instruction = " esp, edx" elif bytes[counter1+1]=="D5": after_instruction = " ebp, edx" elif bytes[counter1+1]=="D6": after_instruction = " esi, edx" elif bytes[counter1+1]=="D7": after_instruction = " edi, edx" elif bytes[counter1+1]=="D8": after_instruction = " eax, ebx" elif bytes[counter1+1]=="D9": after_instruction = " ecx, ebx" elif bytes[counter1+1]=="DA": after_instruction = " edx, ebx" elif bytes[counter1+1]=="DB": after_instruction = " ebx, ebx" elif bytes[counter1+1]=="DC": after_instruction = " esp, ebx" elif bytes[counter1+1]=="DD": after_instruction = " ebp, ebx" elif bytes[counter1+1]=="DE": after_instruction = " esi, ebx" elif bytes[counter1+1]=="DF": after_instruction = " edi, ebx" elif bytes[counter1+1]=="E0": after_instruction = " eax, esp" elif bytes[counter1+1]=="E1": after_instruction = " ecx, esp" elif bytes[counter1+1]=="E2": after_instruction = " edx, esp" elif bytes[counter1+1]=="E3": after_instruction = " ebx, esp" elif bytes[counter1+1]=="E4": after_instruction = " esp, esp" elif bytes[counter1+1]=="E5": after_instruction = " ebp, esp" elif bytes[counter1+1]=="E6": after_instruction = " esi, esp" elif bytes[counter1+1]=="E7": after_instruction = " edi, esp" elif bytes[counter1+1]=="E8": after_instruction = " eax, ebp" elif bytes[counter1+1]=="E9": after_instruction = " ecx, ebp" elif bytes[counter1+1]=="EA": after_instruction = " edx, ebp" elif bytes[counter1+1]=="EB": after_instruction = " ebx, ebp" elif bytes[counter1+1]=="EC": after_instruction = " esp, ebp" elif bytes[counter1+1]=="ED": after_instruction = " ebp, ebp" elif bytes[counter1+1]=="EE": after_instruction = " esi, ebp" elif bytes[counter1+1]=="EF": after_instruction = " edi, ebp" elif bytes[counter1+1]=="F0": after_instruction = " eax, esi" elif bytes[counter1+1]=="F1": after_instruction = " ecx, esi" elif bytes[counter1+1]=="F2": after_instruction = " edx, esi" elif bytes[counter1+1]=="F3": after_instruction = " ebx, esi" elif bytes[counter1+1]=="F4": after_instruction = " esp, esi" elif bytes[counter1+1]=="F5": after_instruction = " ebp, esi" elif bytes[counter1+1]=="F6": after_instruction = " esi, esi" elif bytes[counter1+1]=="F7": after_instruction = " edi, esi" elif bytes[counter1+1]=="F8": after_instruction = " eax, edi" elif bytes[counter1+1]=="F9": after_instruction = " ecx, edi" elif bytes[counter1+1]=="FA": after_instruction = " edx, edi" elif bytes[counter1+1]=="FB": after_instruction = " ebx, edi" elif bytes[counter1+1]=="FC": after_instruction = " esp, edi" elif bytes[counter1+1]=="FD": after_instruction = " ebp, edi" elif bytes[counter1+1]=="FE": after_instruction = " esi, edi" elif bytes[counter1+1]=="FF": after_instruction = " edi, edi" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "89": # MOV after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="C0": after_instruction = " eax, eax" elif bytes[counter1+1]=="C1": after_instruction = " ecx, eax" elif bytes[counter1+1]=="C2": after_instruction = " edx, eax" elif bytes[counter1+1]=="C3": after_instruction = " ebx, eax" elif bytes[counter1+1]=="C4": after_instruction = " esp, eax" elif bytes[counter1+1]=="C5": after_instruction = " ebp, eax" elif bytes[counter1+1]=="C6": after_instruction = " esi, eax" elif bytes[counter1+1]=="C7": after_instruction = " edi, eax" elif bytes[counter1+1]=="C8": after_instruction = " eax, ecx" elif bytes[counter1+1]=="C9": after_instruction = " ecx, ecx" elif bytes[counter1+1]=="CA": after_instruction = " edx, ecx" elif bytes[counter1+1]=="CB": after_instruction = " ebx, ecx" elif bytes[counter1+1]=="CC": after_instruction = " esp, ecx" elif bytes[counter1+1]=="CD": after_instruction = " ebp, ecx" elif bytes[counter1+1]=="CE": after_instruction = " esi, ecx" elif bytes[counter1+1]=="CF": after_instruction = " edi, ecx" elif bytes[counter1+1]=="D0": after_instruction = " eax, edx" elif bytes[counter1+1]=="D1": after_instruction = " ecx, edx" elif bytes[counter1+1]=="D2": after_instruction = " edx, edx" elif bytes[counter1+1]=="D3": after_instruction = " ebx, edx" elif bytes[counter1+1]=="D4": after_instruction = " esp, edx" elif bytes[counter1+1]=="D5": after_instruction = " ebp, edx" elif bytes[counter1+1]=="D6": after_instruction = " esi, edx" elif bytes[counter1+1]=="D7": after_instruction = " edi, edx" elif bytes[counter1+1]=="D8": after_instruction = " eax, ebx" elif bytes[counter1+1]=="D9": after_instruction = " ecx, ebx" elif bytes[counter1+1]=="DA": after_instruction = " edx, ebx" elif bytes[counter1+1]=="DB": after_instruction = " ebx, ebx" elif bytes[counter1+1]=="DC": after_instruction = " esp, ebx" elif bytes[counter1+1]=="DD": after_instruction = " ebp, ebx" elif bytes[counter1+1]=="DE": after_instruction = " esi, ebx" elif bytes[counter1+1]=="DF": after_instruction = " edi, ebx" elif bytes[counter1+1]=="E0": after_instruction = " eax, esp" elif bytes[counter1+1]=="E1": after_instruction = " ecx, esp" elif bytes[counter1+1]=="E2": after_instruction = " edx, esp" elif bytes[counter1+1]=="E3": after_instruction = " ebx, esp" elif bytes[counter1+1]=="E4": after_instruction = " esp, esp" elif bytes[counter1+1]=="E5": after_instruction = " ebp, esp" elif bytes[counter1+1]=="E6": after_instruction = " esi, esp" elif bytes[counter1+1]=="E7": after_instruction = " edi, esp" elif bytes[counter1+1]=="E8": after_instruction = " eax, ebp" elif bytes[counter1+1]=="E9": after_instruction = " ecx, ebp" elif bytes[counter1+1]=="EA": after_instruction = " edx, ebp" elif bytes[counter1+1]=="EB": after_instruction = " ebx, ebp" elif bytes[counter1+1]=="EC": after_instruction = " esp, ebp" elif bytes[counter1+1]=="ED": after_instruction = " ebp, ebp" elif bytes[counter1+1]=="EE": after_instruction = " esi, ebp" elif bytes[counter1+1]=="EF": after_instruction = " edi, ebp" elif bytes[counter1+1]=="F0": after_instruction = " eax, esi" elif bytes[counter1+1]=="F1": after_instruction = " ecx, esi" elif bytes[counter1+1]=="F2": after_instruction = " edx, esi" elif bytes[counter1+1]=="F3": after_instruction = " ebx, esi" elif bytes[counter1+1]=="F4": after_instruction = " esp, esi" elif bytes[counter1+1]=="F5": after_instruction = " ebp, esi" elif bytes[counter1+1]=="F6": after_instruction = " esi, esi" elif bytes[counter1+1]=="F7": after_instruction = " edi, esi" elif bytes[counter1+1]=="F8": after_instruction = " eax, edi" elif bytes[counter1+1]=="F9": after_instruction = " ecx, edi" elif bytes[counter1+1]=="FA": after_instruction = " edx, edi" elif bytes[counter1+1]=="FB": after_instruction = " ebx, edi" elif bytes[counter1+1]=="FC": after_instruction = " esp, edi" elif bytes[counter1+1]=="FD": after_instruction = " ebp, edi" elif bytes[counter1+1]=="FE": after_instruction = " esi, edi" elif bytes[counter1+1]=="FF": after_instruction = " edi, edi" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "8B": # MOV after_byte = " "+bytes[counter1+1] TEMPvar = 1 if bytes[counter1+1]=="1C": if bytes[counter1+2]=="24": after_instruction = " ebx, dword [esp]" after_byte += " "+bytes[counter1+2] TEMPvar += 1 elif bytes[counter1+1]=="10": after_instruction = " edx, dword [eax]" elif bytes[counter1+1]=="55": after_instruction = " edx, dword [var_4h]" elif bytes[counter1+1]=="45": after_instruction = " eax, dword [arg_8h]" elif bytes[counter1+1]=="4D": after_instruction = " ecx, dword [var_4h]" elif bytes[counter1+1]=="00": after_instruction = " eax, dword [eax]" elif bytes[counter1+1]=="6C": after_instruction = " ebp, dword [arg_4h]" elif bytes[counter1+1]=="43": TEMPvar2 = str(bytes[counter1+2]) if str(bytes[counter1+2][0])=="0": TEMPvar2 = str(bytes[counter1+2][1]) after_instruction = " eax, dword [ebx + "+str(TEMPvar2)+"]" TEMPvar = 2 else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(TEMPvar) elif i == "BA": # MOV edx, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " edx, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "E4": # IN al, <value> after_byte = " "+bytes[counter1+1] TEMPvar = bytes[counter1+1] if bytes[counter1+1][0]=="0": TEMPvar = bytes[counter1+1][1] after_instruction = " al, "+"0x"+str(TEMPvar.lower()) lenWholeOpcode = len(instruction)+len(after_instruction) if isClean: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+"; "+str(int(TEMPvar,16)) else: after_instruction = after_instruction+" "*(32-lenWholeOpcode)+f"{bcolors.OKGREEN}; "+str(int(TEMPvar,16)) check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" print(check1) after_byte = "" after_instruction = "" cancle_function_iteration(1) elif i == "F3": # RET after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="C3": pass else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "F6": # NOT, NEG, IDIV, DIV, IMUL, MUL after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="FF": instruction = "IDIV" after_instruction = " bh" elif bytes[counter1+1]=="FE": instruction = "IDIV" after_instruction = " dh" elif bytes[counter1+1]=="FD": instruction = "IDIV" after_instruction = " ch" elif bytes[counter1+1]=="FC": instruction = "IDIV" after_instruction = " ah" elif bytes[counter1+1]=="FB": instruction = "IDIV" after_instruction = " bl" elif bytes[counter1+1]=="FA": instruction = "IDIV" after_instruction = " dl" elif bytes[counter1+1]=="F9": instruction = "IDIV" after_instruction = " cl" elif bytes[counter1+1]=="F8": instruction = "IDIV" after_instruction = " al" elif bytes[counter1+1]=="F7": instruction = "DIV" after_instruction = " bh" elif bytes[counter1+1]=="F6": instruction = "DIV" after_instruction = " dh" elif bytes[counter1+1]=="F5": instruction = "DIV" after_instruction = " ch" elif bytes[counter1+1]=="F4": instruction = "DIV" after_instruction = " ah" elif bytes[counter1+1]=="F3": instruction = "DIV" after_instruction = " bl" elif bytes[counter1+1]=="F2": instruction = "DIV" after_instruction = " dl" elif bytes[counter1+1]=="F1": instruction = "DIV" after_instruction = " cl" elif bytes[counter1+1]=="F0": instruction = "DIV" after_instruction = " al" elif bytes[counter1+1]=="EF": instruction = "IMUL" after_instruction = " bh" elif bytes[counter1+1]=="EE": instruction = "IMUL" after_instruction = " dh" elif bytes[counter1+1]=="ED": instruction = "IMUL" after_instruction = " ch" elif bytes[counter1+1]=="EC": instruction = "IMUL" after_instruction = " ah" elif bytes[counter1+1]=="EB": instruction = "IMUL" after_instruction = " bl" elif bytes[counter1+1]=="EA": instruction = "IMUL" after_instruction = " dl" elif bytes[counter1+1]=="E9": instruction = "IMUL" after_instruction = " cl" elif bytes[counter1+1]=="E8": instruction = "IMUL" after_instruction = " al" elif bytes[counter1+1]=="E7": instruction = "MUL" after_instruction = " bh" elif bytes[counter1+1]=="E6": instruction = "MUL" after_instruction = " dh" elif bytes[counter1+1]=="E5": instruction = "MUL" after_instruction = " ch" elif bytes[counter1+1]=="E4": instruction = "MUL" after_instruction = " ah" elif bytes[counter1+1]=="E3": instruction = "MUL" after_instruction = " bl" elif bytes[counter1+1]=="E2": instruction = "MUL" after_instruction = " dl" elif bytes[counter1+1]=="E1": instruction = "MUL" after_instruction = " cl" elif bytes[counter1+1]=="E0": instruction = "MUL" after_instruction = " al" elif bytes[counter1+1]=="DF": instruction = "NEG" after_instruction = " bh" elif bytes[counter1+1]=="DE": instruction = "NEG" after_instruction = " dh" elif bytes[counter1+1]=="DD": instruction = "NEG" after_instruction = " ch" elif bytes[counter1+1]=="DC": instruction = "NEG" after_instruction = " ah" elif bytes[counter1+1]=="DB": instruction = "NEG" after_instruction = " bl" elif bytes[counter1+1]=="DA": instruction = "NEG" after_instruction = " dl" elif bytes[counter1+1]=="D9": instruction = "NEG" after_instruction = " cl" elif bytes[counter1+1]=="D8": instruction = "NEG" after_instruction = " al" elif bytes[counter1+1]=="D7": instruction = "NOT" after_instruction = " bh" elif bytes[counter1+1]=="D6": instruction = "NOT" after_instruction = " dh" elif bytes[counter1+1]=="D5": instruction = "NOT" after_instruction = " ch" elif bytes[counter1+1]=="D4": instruction = "NOT" after_instruction = " ah" elif bytes[counter1+1]=="D3": instruction = "NOT" after_instruction = " bl" elif bytes[counter1+1]=="D2": instruction = "NOT" after_instruction = " dl" elif bytes[counter1+1]=="D1": instruction = "NOT" after_instruction = " cl" elif bytes[counter1+1]=="D0": instruction = "NOT" after_instruction = " al" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "F7": # NOT, NEG, IDIV, DIV, IMUL, MUL after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="FF": instruction = "IDIV" after_instruction = " edi" elif bytes[counter1+1]=="FE": instruction = "IDIV" after_instruction = " esi" elif bytes[counter1+1]=="FD": instruction = "IDIV" after_instruction = " ebp" elif bytes[counter1+1]=="FC": instruction = "IDIV" after_instruction = " esp" elif bytes[counter1+1]=="FB": instruction = "IDIV" after_instruction = " ebx" elif bytes[counter1+1]=="FA": instruction = "IDIV" after_instruction = " edx" elif bytes[counter1+1]=="F9": instruction = "IDIV" after_instruction = " ecx" elif bytes[counter1+1]=="F8": instruction = "IDIV" after_instruction = " eax" elif bytes[counter1+1]=="F7": instruction = "DIV" after_instruction = " edi" elif bytes[counter1+1]=="F6": instruction = "DIV" after_instruction = " esi" elif bytes[counter1+1]=="F5": instruction = "DIV" after_instruction = " ebp" elif bytes[counter1+1]=="F4": instruction = "DIV" after_instruction = " esp" elif bytes[counter1+1]=="F3": instruction = "DIV" after_instruction = " ebx" elif bytes[counter1+1]=="F2": instruction = "DIV" after_instruction = " edx" elif bytes[counter1+1]=="F1": instruction = "DIV" after_instruction = " ecx" elif bytes[counter1+1]=="F0": instruction = "DIV" after_instruction = " eax" elif bytes[counter1+1]=="EF": instruction = "IMUL" after_instruction = " edi" elif bytes[counter1+1]=="EE": instruction = "IMUL" after_instruction = " esi" elif bytes[counter1+1]=="ED": instruction = "IMUL" after_instruction = " ebp" elif bytes[counter1+1]=="EC": instruction = "IMUL" after_instruction = " esp" elif bytes[counter1+1]=="EB": instruction = "IMUL" after_instruction = " ebx" elif bytes[counter1+1]=="EA": instruction = "IMUL" after_instruction = " edx" elif bytes[counter1+1]=="E9": instruction = "IMUL" after_instruction = " ecx" elif bytes[counter1+1]=="E8": instruction = "IMUL" after_instruction = " eax" elif bytes[counter1+1]=="E7": instruction = "MUL" after_instruction = " edi" elif bytes[counter1+1]=="E6": instruction = "MUL" after_instruction = " esi" elif bytes[counter1+1]=="E5": instruction = "MUL" after_instruction = " ebp" elif bytes[counter1+1]=="E4": instruction = "MUL" after_instruction = " esp" elif bytes[counter1+1]=="E3": instruction = "MUL" after_instruction = " ebx" elif bytes[counter1+1]=="E2": instruction = "MUL" after_instruction = " edx" elif bytes[counter1+1]=="E1": instruction = "MUL" after_instruction = " ecx" elif bytes[counter1+1]=="E0": instruction = "MUL" after_instruction = " eax" elif bytes[counter1+1]=="DF": instruction = "NEG" after_instruction = " edi" elif bytes[counter1+1]=="DE": instruction = "NEG" after_instruction = " esi" elif bytes[counter1+1]=="DD": instruction = "NEG" after_instruction = " ebp" elif bytes[counter1+1]=="DC": instruction = "NEG" after_instruction = " esp" elif bytes[counter1+1]=="DB": instruction = "NEG" after_instruction = " ebx" elif bytes[counter1+1]=="DA": instruction = "NEG" after_instruction = " edx" elif bytes[counter1+1]=="D9": instruction = "NEG" after_instruction = " ecx" elif bytes[counter1+1]=="D8": instruction = "NEG" after_instruction = " eax" elif bytes[counter1+1]=="D7": instruction = "NOT" after_instruction = " edi" elif bytes[counter1+1]=="D6": instruction = "NOT" after_instruction = " esi" elif bytes[counter1+1]=="D5": instruction = "NOT" after_instruction = " ebp" elif bytes[counter1+1]=="D4": instruction = "NOT" after_instruction = " esp" elif bytes[counter1+1]=="D3": instruction = "NOT" after_instruction = " ebx" elif bytes[counter1+1]=="D2": instruction = "NOT" after_instruction = " edx" elif bytes[counter1+1]=="D1": instruction = "NOT" after_instruction = " ecx" elif bytes[counter1+1]=="D0": instruction = "NOT" after_instruction = " eax" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "FF": # CALL after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="D0": after_instruction = " eax" elif bytes[counter1+1]=="D1": after_instruction = " ecx" elif bytes[counter1+1]=="D2": after_instruction = " edx" elif bytes[counter1+1]=="D3": after_instruction = " ebx" elif bytes[counter1+1]=="D4": after_instruction = " esp" elif bytes[counter1+1]=="D5": after_instruction = " ebp" elif bytes[counter1+1]=="D6": after_instruction = " esi" elif bytes[counter1+1]=="D7": after_instruction = " edi" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(1) elif i == "0F": # PUSH fs, PUSH gs, POP fs, POP gs, ... TEMPvar = 1 after_byte = " "+bytes[counter1+1] if bytes[counter1+1]=="A0": instruction = "PUSH" after_instruction = " fs" elif bytes[counter1+1]=="A1": instruction = "POP" after_instruction = " fs" elif bytes[counter1+1]=="A8": instruction = "PUSH" after_instruction = " gs" elif bytes[counter1+1]=="A9": instruction = "POP" after_instruction = " gs" else: should_print = False check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.WARNING}"+instruction+after_instruction+f"{bcolors.RESET}" intruction_len_for_check = 51+len(instruction)+len(after_instruction) if len(check1) < intruction_len_for_check: for _ in range(intruction_len_for_check-len(check1)): after_byte += " " if isClean: bcolors = colors try: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+" "+f"{bcolors.WARNING}"+instruction.split(" ")[1]+after_instruction+f"{bcolors.RESET}" except: check1 = f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+after_byte+f"{bcolors.OKGREEN}"+instruction.split(" ")[0]+f"{bcolors.WARNING}"+after_instruction+f"{bcolors.RESET}" if should_print: print(check1) after_byte = "" after_instruction = "" if should_print: cancle_function_iteration(TEMPvar) else: pass #bcolors = colors #print(f"{bcolors.OKBLUE}"+str(hex(offset1))+" "+f"{bcolors.FAIL}"+to_display+" "+f"{bcolors.WARNING}"+"???"+f"{bcolors.RESET}") else: times -= 1 offset1 += 1 counter1 += 1 return True

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88165805b526770855010a689c896688df331c0c

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py

Python

ucloud/services/uddb/schemas/apis.py

ucloud/ucloud-sdk-python3

b96a079a5e747228049129d83f03a8067a05e881

[ "Apache-2.0" ]

37

2019-06-19T09:41:34.000Z

2022-02-18T08:06:00.000Z

ucloud/services/uddb/schemas/apis.py

ucloud/ucloud-sdk-python3

b96a079a5e747228049129d83f03a8067a05e881

[ "Apache-2.0" ]

90

2019-08-09T09:27:33.000Z

2022-03-30T15:54:55.000Z

ucloud/services/uddb/schemas/apis.py

ucloud/ucloud-sdk-python3

b96a079a5e747228049129d83f03a8067a05e881

[ "Apache-2.0" ]

19

2019-06-13T02:46:01.000Z

2021-11-01T07:22:18.000Z

""" Code is generated by ucloud-model, DO NOT EDIT IT. """ from ucloud.core.typesystem import schema, fields from ucloud.services.uddb.schemas import models """ UDDB API Schema """ """ API: ChangeUDDBInstanceName 修改分布式数据库中间件名称 """ class ChangeUDDBInstanceNameRequestSchema(schema.RequestSchema): """ChangeUDDBInstanceName - 修改分布式数据库中间件名称""" fields = { "NewName": fields.Str(required=True, dump_to="NewName"), "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class ChangeUDDBInstanceNameResponseSchema(schema.ResponseSchema): """ChangeUDDBInstanceName - 修改分布式数据库中间件名称""" fields = {} """ API: ChangeUDDBSlaveCount 改变分布式数据库数据节点的只读实例个数每一个UDDB的数据节点负责处理所有的写入请求。与此同时，每一个数据节点可以配置若干个该节点的只读实例。当主节点的数据写入完毕后，只读实例把这次的写入操作进行更新，从而和数据节点保持一致。只读实例可以使得数据由多份复制，在数据节点和只读实例之间，可以做请求的读写分离, 也就是说, 主节点写入数据之后, 数据的读操作可以由数据只读实例进行分担, 这样减少主节点的压力, 增加性能当改变了数据节点的只读实例个数之后，对于现有的和以后的每一个数据节点都采用这个配置。如果UDDB实例有现有的数据节点, 那么它会根据新配置的参数，自动创建或删除数据节点的只读实例如下状态的UDDB实例可以进行这个操作: Running: 系统正常运行中当请求返回成功之后，UDDB实例的状态变成"ChangingSlaveCount"; 如果返回失败, UDDB实例状态保持不变当UDDB更改数据分区的只读实例个数成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果更改过程中出现异常, 状态变成"Abnormal"(异常运行中)或者"Error"(运行错误) """ class ChangeUDDBSlaveCountRequestSchema(schema.RequestSchema): """ChangeUDDBSlaveCount - 改变分布式数据库数据节点的只读实例个数每一个UDDB的数据节点负责处理所有的写入请求。与此同时，每一个数据节点可以配置若干个该节点的只读实例。当主节点的数据写入完毕后，只读实例把这次的写入操作进行更新，从而和数据节点保持一致。只读实例可以使得数据由多份复制，在数据节点和只读实例之间，可以做请求的读写分离, 也就是说, 主节点写入数据之后, 数据的读操作可以由数据只读实例进行分担, 这样减少主节点的压力, 增加性能当改变了数据节点的只读实例个数之后，对于现有的和以后的每一个数据节点都采用这个配置。如果UDDB实例有现有的数据节点, 那么它会根据新配置的参数，自动创建或删除数据节点的只读实例如下状态的UDDB实例可以进行这个操作: Running: 系统正常运行中当请求返回成功之后，UDDB实例的状态变成"ChangingSlaveCount"; 如果返回失败, UDDB实例状态保持不变当UDDB更改数据分区的只读实例个数成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果更改过程中出现异常, 状态变成"Abnormal"(异常运行中)或者"Error"(运行错误) """ fields = { "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "SlaveCount": fields.Str(required=True, dump_to="SlaveCount"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class ChangeUDDBSlaveCountResponseSchema(schema.ResponseSchema): """ChangeUDDBSlaveCount - 改变分布式数据库数据节点的只读实例个数每一个UDDB的数据节点负责处理所有的写入请求。与此同时，每一个数据节点可以配置若干个该节点的只读实例。当主节点的数据写入完毕后，只读实例把这次的写入操作进行更新，从而和数据节点保持一致。只读实例可以使得数据由多份复制，在数据节点和只读实例之间，可以做请求的读写分离, 也就是说, 主节点写入数据之后, 数据的读操作可以由数据只读实例进行分担, 这样减少主节点的压力, 增加性能当改变了数据节点的只读实例个数之后，对于现有的和以后的每一个数据节点都采用这个配置。如果UDDB实例有现有的数据节点, 那么它会根据新配置的参数，自动创建或删除数据节点的只读实例如下状态的UDDB实例可以进行这个操作: Running: 系统正常运行中当请求返回成功之后，UDDB实例的状态变成"ChangingSlaveCount"; 如果返回失败, UDDB实例状态保持不变当UDDB更改数据分区的只读实例个数成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果更改过程中出现异常, 状态变成"Abnormal"(异常运行中)或者"Error"(运行错误) """ fields = {} """ API: CreateUDDBInstance 创建创建分布式数据库UDDB实例, 简称UDDB实例。 """ class CreateUDDBInstanceRequestSchema(schema.RequestSchema): """CreateUDDBInstance - 创建创建分布式数据库UDDB实例, 简称UDDB实例。""" fields = { "AdminPassword": fields.Str(required=True, dump_to="AdminPassword"), "AdminUser": fields.Str(required=False, dump_to="AdminUser"), "ChargeType": fields.Str(required=False, dump_to="ChargeType"), "CouponId": fields.Str(required=False, dump_to="CouponId"), "DBTypeId": fields.Str(required=True, dump_to="DBTypeId"), "DataNodeCount": fields.Int(required=True, dump_to="DataNodeCount"), "DataNodeDiskSpace": fields.Int( required=True, dump_to="DataNodeDiskSpace" ), "DataNodeMemory": fields.Int(required=True, dump_to="DataNodeMemory"), "DataNodeSlaveCount": fields.Int( required=False, dump_to="DataNodeSlaveCount" ), "InstanceMode": fields.Str(required=False, dump_to="InstanceMode"), "InstanceType": fields.Str(required=False, dump_to="InstanceType"), "Name": fields.Str(required=True, dump_to="Name"), "Port": fields.Int(required=False, dump_to="Port"), "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Quantity": fields.Int(required=False, dump_to="Quantity"), "Region": fields.Str(required=True, dump_to="Region"), "RouterNodeNum": fields.Int(required=True, dump_to="RouterNodeNum"), "RouterVersion": fields.Str(required=True, dump_to="RouterVersion"), "SubnetId": fields.Str(required=False, dump_to="SubnetId"), "VPCId": fields.Str(required=False, dump_to="VPCId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class CreateUDDBInstanceResponseSchema(schema.ResponseSchema): """CreateUDDBInstance - 创建创建分布式数据库UDDB实例, 简称UDDB实例。""" fields = { "Message": fields.Str(required=False, load_from="Message"), "UDDBId": fields.Str(required=False, load_from="UDDBId"), } """ API: DeleteUDDBInstance 删除UDDB实例。如下状态的UDDB实例可以进行这个操作: InitFail: 初始化失败 Shutoff: 已关闭当请求返回成功之后，UDDB实例就已经被删除, 列表上看不到对应的UDDB实例 """ class DeleteUDDBInstanceRequestSchema(schema.RequestSchema): """DeleteUDDBInstance - 删除UDDB实例。如下状态的UDDB实例可以进行这个操作: InitFail: 初始化失败 Shutoff: 已关闭当请求返回成功之后，UDDB实例就已经被删除, 列表上看不到对应的UDDB实例 """ fields = { "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class DeleteUDDBInstanceResponseSchema(schema.ResponseSchema): """DeleteUDDBInstance - 删除UDDB实例。如下状态的UDDB实例可以进行这个操作: InitFail: 初始化失败 Shutoff: 已关闭当请求返回成功之后，UDDB实例就已经被删除, 列表上看不到对应的UDDB实例 """ fields = { "Message": fields.Str(required=True, load_from="Message"), } """ API: DescribeUDDBInstance 获取分布式数据库UDDB的详细信息 """ class DescribeUDDBInstanceRequestSchema(schema.RequestSchema): """DescribeUDDBInstance - 获取分布式数据库UDDB的详细信息""" fields = { "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class DescribeUDDBInstanceResponseSchema(schema.ResponseSchema): """DescribeUDDBInstance - 获取分布式数据库UDDB的详细信息""" fields = { "DataSet": fields.List( models.DataSetUDDBSchema(), required=False, load_from="DataSet" ), "Message": fields.Str(required=False, load_from="Message"), } """ API: DescribeUDDBInstancePrice 获取分布式数据库UDDB价格 """ class DescribeUDDBInstancePriceRequestSchema(schema.RequestSchema): """DescribeUDDBInstancePrice - 获取分布式数据库UDDB价格""" fields = { "ChargeType": fields.Str(required=False, dump_to="ChargeType"), "DataNodeCount": fields.Int(required=True, dump_to="DataNodeCount"), "DataNodeDiskSpace": fields.Int( required=True, dump_to="DataNodeDiskSpace" ), "DataNodeMemory": fields.Str(required=True, dump_to="DataNodeMemory"), "DataNodeSlaveCount": fields.Int( required=False, dump_to="DataNodeSlaveCount" ), "InstanceMode": fields.Str(required=False, dump_to="InstanceMode"), "InstanceType": fields.Str(required=False, dump_to="InstanceType"), "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Quantity": fields.Int(required=False, dump_to="Quantity"), "Region": fields.Str(required=True, dump_to="Region"), "RouterNodeNum": fields.Int(required=True, dump_to="RouterNodeNum"), "RouterVersion": fields.Str(required=True, dump_to="RouterVersion"), "Zone": fields.Str(required=True, dump_to="Zone"), } class DescribeUDDBInstancePriceResponseSchema(schema.ResponseSchema): """DescribeUDDBInstancePrice - 获取分布式数据库UDDB价格""" fields = { "Message": fields.Str(required=False, load_from="Message"), "PriceInfo": models.PriceDetailInfoSchema(), } """ API: DescribeUDDBInstanceUpgradePrice 升级UDDB时，获取升级后的价格 """ class DescribeUDDBInstanceUpgradePriceRequestSchema(schema.RequestSchema): """DescribeUDDBInstanceUpgradePrice - 升级UDDB时，获取升级后的价格""" fields = { "DataNodeCount": fields.Int(required=False, dump_to="DataNodeCount"), "DataNodeDiskSpace": fields.Int( required=False, dump_to="DataNodeDiskSpace" ), "DataNodeMemory": fields.Int(required=False, dump_to="DataNodeMemory"), "DataNodeSlaveCount": fields.Int( required=False, dump_to="DataNodeSlaveCount" ), "InstanceMode": fields.Str(required=False, dump_to="InstanceMode"), "InstanceType": fields.Str(required=False, dump_to="InstanceType"), "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "RouterNodeNum": fields.Int(required=True, dump_to="RouterNodeNum"), "RouterVersion": fields.Str(required=True, dump_to="RouterVersion"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class DescribeUDDBInstanceUpgradePriceResponseSchema(schema.ResponseSchema): """DescribeUDDBInstanceUpgradePrice - 升级UDDB时，获取升级后的价格""" fields = { "Message": fields.Str(required=False, load_from="Message"), "PriceInfo": models.PriceInfoSchema(), } """ API: RestartUDDBInstance 重启UDDB实例，开始提供服务。如下状态的UDDB实例可以进行这个操作: Running: 正常运行中 Abnormal: 异常运行中当请求返回成功之后，UDDB实例的状态变成"Starting"(启动中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在重启过程中, 当UDDB实例启动成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果启动过程中出现异常, 状态变成"Abnormal"(异常运行中), 或者"Shutoff"(已关闭 """ class RestartUDDBInstanceRequestSchema(schema.RequestSchema): """RestartUDDBInstance - 重启UDDB实例，开始提供服务。如下状态的UDDB实例可以进行这个操作: Running: 正常运行中 Abnormal: 异常运行中当请求返回成功之后，UDDB实例的状态变成"Starting"(启动中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在重启过程中, 当UDDB实例启动成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果启动过程中出现异常, 状态变成"Abnormal"(异常运行中), 或者"Shutoff"(已关闭 """ fields = { "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class RestartUDDBInstanceResponseSchema(schema.ResponseSchema): """RestartUDDBInstance - 重启UDDB实例，开始提供服务。如下状态的UDDB实例可以进行这个操作: Running: 正常运行中 Abnormal: 异常运行中当请求返回成功之后，UDDB实例的状态变成"Starting"(启动中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在重启过程中, 当UDDB实例启动成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果启动过程中出现异常, 状态变成"Abnormal"(异常运行中), 或者"Shutoff"(已关闭 """ fields = { "Message": fields.Str(required=True, load_from="Message"), } """ API: StartUDDBInstance 启动UDDB实例，开始提供服务。如下状态的UDDB实例可以进行这个操作: Shutoff: 已关闭当请求返回成功之后，UDDB实例的状态变成"Starting"(启动中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在启动过程中, 当UDDB实例启动成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果启动过程中出现异常, 状态变成"Abnormal"(异常运行中), 或者"Shutoff"(已关闭) """ class StartUDDBInstanceRequestSchema(schema.RequestSchema): """StartUDDBInstance - 启动UDDB实例，开始提供服务。如下状态的UDDB实例可以进行这个操作: Shutoff: 已关闭当请求返回成功之后，UDDB实例的状态变成"Starting"(启动中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在启动过程中, 当UDDB实例启动成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果启动过程中出现异常, 状态变成"Abnormal"(异常运行中), 或者"Shutoff"(已关闭) """ fields = { "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class StartUDDBInstanceResponseSchema(schema.ResponseSchema): """StartUDDBInstance - 启动UDDB实例，开始提供服务。如下状态的UDDB实例可以进行这个操作: Shutoff: 已关闭当请求返回成功之后，UDDB实例的状态变成"Starting"(启动中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在启动过程中, 当UDDB实例启动成功之后, UDDB实例的状态变成"Running"(正常运行中); 如果启动过程中出现异常, 状态变成"Abnormal"(异常运行中), 或者"Shutoff"(已关闭) """ fields = { "Message": fields.Str(required=True, load_from="Message"), } """ API: StopUDDBInstance 关闭UDDB实例，停止提供服务。如下状态的UDDB实例可以进行这个操作: Running: 正常运行中 Abnormal: 异常运行中当请求返回成功之后，UDDB实例的状态变成"Shutdown"(关闭中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在关闭过程中, 当UDDB实例关闭成功之后, UDDB实例的状态变成"Shutoff"(已关闭); 如果关闭过程中出现异常, 根据UDDB实例的情况, 状态变成"Abnormal"(异常运行中), 或者"Running"(正常运行中) """ class StopUDDBInstanceRequestSchema(schema.RequestSchema): """StopUDDBInstance - 关闭UDDB实例，停止提供服务。如下状态的UDDB实例可以进行这个操作: Running: 正常运行中 Abnormal: 异常运行中当请求返回成功之后，UDDB实例的状态变成"Shutdown"(关闭中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在关闭过程中, 当UDDB实例关闭成功之后, UDDB实例的状态变成"Shutoff"(已关闭); 如果关闭过程中出现异常, 根据UDDB实例的情况, 状态变成"Abnormal"(异常运行中), 或者"Running"(正常运行中) """ fields = { "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=True, dump_to="Zone"), } class StopUDDBInstanceResponseSchema(schema.ResponseSchema): """StopUDDBInstance - 关闭UDDB实例，停止提供服务。如下状态的UDDB实例可以进行这个操作: Running: 正常运行中 Abnormal: 异常运行中当请求返回成功之后，UDDB实例的状态变成"Shutdown"(关闭中); 如果返回失败, UDDB实例状态保持不变 UDDB实例在关闭过程中, 当UDDB实例关闭成功之后, UDDB实例的状态变成"Shutoff"(已关闭); 如果关闭过程中出现异常, 根据UDDB实例的情况, 状态变成"Abnormal"(异常运行中), 或者"Running"(正常运行中) """ fields = { "Message": fields.Str(required=True, load_from="Message"), } """ API: UpgradeUDDBDataNode 升降级分布式数据库数据节点的配置, 提高/降低数据节点的数据容量和内存所有数据节点以及其所挂载的只读实例的配置都受到影响升降级数据节点的配置之后之后, 会按照数据节点新的磁盘和内存大小重新计费如下状态的数据节点实例可以进行这个操作: Shutoff: 已关闭当请求返回成功之后，UDDB实例的状态变成"UpgradingDataNode"，相关数据节点的状态变成"Upgrading"; 如果返回失败, UDDB实例状态保持不变当UDDB实例升级结束之后, UDDB实例的状态变成"Shutoff" """ class UpgradeUDDBDataNodeRequestSchema(schema.RequestSchema): """UpgradeUDDBDataNode - 升降级分布式数据库数据节点的配置, 提高/降低数据节点的数据容量和内存所有数据节点以及其所挂载的只读实例的配置都受到影响升降级数据节点的配置之后之后, 会按照数据节点新的磁盘和内存大小重新计费如下状态的数据节点实例可以进行这个操作: Shutoff: 已关闭当请求返回成功之后，UDDB实例的状态变成"UpgradingDataNode"，相关数据节点的状态变成"Upgrading"; 如果返回失败, UDDB实例状态保持不变当UDDB实例升级结束之后, UDDB实例的状态变成"Shutoff" """ fields = { "CouponId": fields.Str(required=False, dump_to="CouponId"), "DataNodeDiskSpace": fields.Int( required=True, dump_to="DataNodeDiskSpace" ), "DataNodeMemory": fields.Int(required=True, dump_to="DataNodeMemory"), "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=False, dump_to="Zone"), } class UpgradeUDDBDataNodeResponseSchema(schema.ResponseSchema): """UpgradeUDDBDataNode - 升降级分布式数据库数据节点的配置, 提高/降低数据节点的数据容量和内存所有数据节点以及其所挂载的只读实例的配置都受到影响升降级数据节点的配置之后之后, 会按照数据节点新的磁盘和内存大小重新计费如下状态的数据节点实例可以进行这个操作: Shutoff: 已关闭当请求返回成功之后，UDDB实例的状态变成"UpgradingDataNode"，相关数据节点的状态变成"Upgrading"; 如果返回失败, UDDB实例状态保持不变当UDDB实例升级结束之后, UDDB实例的状态变成"Shutoff" """ fields = { "Message": fields.Str(required=True, load_from="Message"), } """ API: UpgradeUDDBInstance 升降级分布式数据库中间件的配置, 提高/降低请求处理的并发性修改请求处理节点个数之后, 按照所有请求处理节点的总内存容量和CPU核数重新计费如下状态的UDDB实例可以进行这个操作: Running: 系统正常运行中当请求返回成功之后，UDDB实例的状态变成"UpgradingUDDB"; 如果返回失败, UDDB实例状态保持不变当UDDB实例升级成功之后, UDDB实例的状态变成"Running"; 如果更改过程中出现异常, 状态变成"Abnormal", 或者"Error" """ class UpgradeUDDBInstanceRequestSchema(schema.RequestSchema): """UpgradeUDDBInstance - 升降级分布式数据库中间件的配置, 提高/降低请求处理的并发性修改请求处理节点个数之后, 按照所有请求处理节点的总内存容量和CPU核数重新计费如下状态的UDDB实例可以进行这个操作: Running: 系统正常运行中当请求返回成功之后，UDDB实例的状态变成"UpgradingUDDB"; 如果返回失败, UDDB实例状态保持不变当UDDB实例升级成功之后, UDDB实例的状态变成"Running"; 如果更改过程中出现异常, 状态变成"Abnormal", 或者"Error" """ fields = { "CouponId": fields.Str(required=False, dump_to="CouponId"), "ProjectId": fields.Str(required=True, dump_to="ProjectId"), "Region": fields.Str(required=True, dump_to="Region"), "RouterNodeNum": fields.Int(required=True, dump_to="RouterNodeNum"), "RouterVersion": fields.Str(required=True, dump_to="RouterVersion"), "UDDBId": fields.Str(required=True, dump_to="UDDBId"), "Zone": fields.Str(required=False, dump_to="Zone"), } class UpgradeUDDBInstanceResponseSchema(schema.ResponseSchema): """UpgradeUDDBInstance - 升降级分布式数据库中间件的配置, 提高/降低请求处理的并发性修改请求处理节点个数之后, 按照所有请求处理节点的总内存容量和CPU核数重新计费如下状态的UDDB实例可以进行这个操作: Running: 系统正常运行中当请求返回成功之后，UDDB实例的状态变成"UpgradingUDDB"; 如果返回失败, UDDB实例状态保持不变当UDDB实例升级成功之后, UDDB实例的状态变成"Running"; 如果更改过程中出现异常, 状态变成"Abnormal", 或者"Error" """ fields = { "Message": fields.Str(required=True, load_from="Message"), }

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888169dfc6c081359c25cb16582871351d932fa4

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Python

resources/test_cases/python/M2Crypto/python-code-test.py

stg-tud/licma

b899e6e682f7716d19e79d6ce7b73c28c6efd4cf

[ "MIT" ]

5

2021-09-13T11:24:13.000Z

2022-03-18T21:56:58.000Z

resources/test_cases/python/M2Crypto/python-code-test.py

stg-tud/licma

b899e6e682f7716d19e79d6ce7b73c28c6efd4cf

[ "MIT" ]

null

resources/test_cases/python/M2Crypto/python-code-test.py

stg-tud/licma

b899e6e682f7716d19e79d6ce7b73c28c6efd4cf

[ "MIT" ]

1

2021-09-13T06:02:20.000Z

from M2Crypto.EVP import Cipher from M2Crypto.EVP import pbkdf2 import TestRule1 import TestRule2 import TestRule3 import TestRule4 import TestRule5 encryption_mode = 1 decryption_mode = 0 key = b"12345678123456781234567812345678" iv_ecb = b"0000000000000000" iv_cbc = b"1234567812345678" password = b"12345678" salt = b"12345678" iter_eq_1000 = 1000 iter_eq_999 = 999 algorithm = "aes_256_ecb" plaintext = b"abcdefghijklmnop" def decrypt_aes_ecb(key, data): cipher = Cipher("aes_256_ecb", key, iv_ecb, decryption_mode) cipher_text = cipher.update(data) + cipher.final() return cipher_text def decrypt_aes_cbc(key, iv, data): cipher = Cipher("aes_256_cbc", key, iv, decryption_mode) cipher_text = cipher.update(data) + cipher.final() return cipher_text def get_pbk(salt, iter): key = pbkdf2(password, salt, iter, 32) return key if __name__ == '__main__': # TestRule1 code print("M2Crypto -> rule1 -> p_example1_hard_coded1:", decrypt_aes_ecb(key, TestRule1.p_example1_hard_coded(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example2_local_variable1:", decrypt_aes_ecb(key, TestRule1.p_example2_local_variable(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example3_nested_local_variable1:", decrypt_aes_ecb(key, TestRule1.p_example3_nested_local_variable(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example4_direct_method_call1:", decrypt_aes_ecb(key, TestRule1.p_example4_direct_method_call(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example5_nested_method_call1:", decrypt_aes_ecb(key, TestRule1.p_example5_nested_method_call(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example6_direct_g_variable_access1:", decrypt_aes_ecb(key, TestRule1.p_example6_direct_g_variable_access(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example7_indirect_g_variable_access1:", decrypt_aes_ecb(key, TestRule1.p_example7_indirect_g_variable_access(key, plaintext)) == plaintext) print("M2Crypto -> rule1 -> p_example8_warning_parameter_not_resolvable:", decrypt_aes_ecb(key, TestRule1.p_example8_warning_parameter_not_resolvable(key, plaintext, algorithm)) == plaintext) print("M2Crypto -> rule1 -> n_example1_cbc:", TestRule1.n_example1_cbc(key, iv_cbc, plaintext)) # TestRule2 code print("M2Crypto -> rule2 -> p_example1_hard_coded1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example1_hard_coded1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example2_hard_coded2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example2_hard_coded2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example3_local_variable1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example3_local_variable1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example4_local_variable2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example4_local_variable2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example5_nested_local_variable1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example5_nested_local_variable1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example6_nested_local_variable2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example6_nested_local_variable2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example7_direct_method_call1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example7_direct_method_call1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example8_direct_method_call2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example8_direct_method_call2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example9_nested_method_call1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example9_nested_method_call1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example10_nested_method_call2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example10_nested_method_call2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example11_direct_g_variable_access1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example11_direct_g_variable_access1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example12_direct_g_variable_access2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example12_direct_g_variable_access2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example13_indirect_g_variable_access1:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example13_indirect_g_variable_access1(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example14_indirect_g_variable_access2:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example14_indirect_g_variable_access2(key, plaintext)) == plaintext) print("M2Crypto -> rule2 -> p_example15_warning_parameter_not_resolvable:", decrypt_aes_cbc(key, iv_cbc, TestRule2.p_example15_warning_parameter_not_resolvable(key, iv_cbc, plaintext)) == plaintext) print("M2Crypto -> rule2 -> n_example1_secrets_system_random:", TestRule2.n_example1_secrets_system_random(key, plaintext)) # TestRule3 code print("M2Crypto -> rule3 -> p_example1_hard_coded1:", decrypt_aes_ecb(key, TestRule3.p_example1_hard_coded1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example2_hard_coded2:", decrypt_aes_ecb(key, TestRule3.p_example2_hard_coded2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example3_local_variable1:", decrypt_aes_ecb(key, TestRule3.p_example3_local_variable1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example4_local_variable2:", decrypt_aes_ecb(key, TestRule3.p_example4_local_variable2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example5_nested_local_variable1:", decrypt_aes_ecb(key, TestRule3.p_example5_nested_local_variable1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example6_nested_local_variable2:", decrypt_aes_ecb(key, TestRule3.p_example6_nested_local_variable2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example7_direct_method_call1:", decrypt_aes_ecb(key, TestRule3.p_example7_direct_method_call1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example8_direct_method_call2:", decrypt_aes_ecb(key, TestRule3.p_example8_direct_method_call2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example9_nested_method_call1:", decrypt_aes_ecb(key, TestRule3.p_example9_nested_method_call1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example10_nested_method_call2:", decrypt_aes_ecb(key, TestRule3.p_example10_nested_method_call2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example11_direct_g_variable_access1:", decrypt_aes_ecb(key, TestRule3.p_example11_direct_g_variable_access1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example12_direct_g_variable_access2:", decrypt_aes_ecb(key, TestRule3.p_example12_direct_g_variable_access2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example13_indirect_g_variable_access1:", decrypt_aes_ecb(key, TestRule3.p_example13_indirect_g_variable_access1(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example14_indirect_g_variable_access2:", decrypt_aes_ecb(key, TestRule3.p_example14_indirect_g_variable_access2(plaintext)) == plaintext) print("M2Crypto -> rule3 -> p_example15_warning_parameter_not_resolvable:", decrypt_aes_ecb(key, TestRule3.p_example15_warning_parameter_not_resolvable(key, plaintext)) == plaintext) print("M2Crypto -> rule3 -> n_example1_random_key:", TestRule3.n_example1_random_key(plaintext)) # TestRule4 code print("M2Crypto -> rule4 -> p_example1_hard_coded1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example1_hard_coded1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example2_hard_coded2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example2_hard_coded2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example3_local_variable1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example3_local_variable1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example4_local_variable2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example4_local_variable2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example5_nested_local_variable1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example5_nested_local_variable1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example6_nested_local_variable2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example6_nested_local_variable2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example7_direct_method_call1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example7_direct_method_call1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example8_direct_method_call2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example8_direct_method_call2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example9_nested_method_call1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example9_nested_method_call1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example10_nested_method_call2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example10_nested_method_call2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example11_direct_g_variable_access1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example11_direct_g_variable_access1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example12_direct_g_variable_access2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example12_direct_g_variable_access2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example13_indirect_g_variable_access1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example13_indirect_g_variable_access1(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example14_indirect_g_variable_access2:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example14_indirect_g_variable_access2(password, plaintext)) == plaintext) print("M2Crypto -> rule4 -> p_example15_warning_parameter_not_resolvable:", decrypt_aes_ecb(get_pbk(salt, iter_eq_1000), TestRule4.p_example15_warning_parameter_not_resolvable(password, salt, plaintext)) == plaintext) print("M2Crypto -> rule4 -> n_example1_random_salt:", TestRule4.n_example1_random_salt(password, plaintext)) # TestRule5 code print("M2Crypto -> rule5 -> p_example1_hard_coded1:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example1_hard_coded(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example2_local_variable:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example2_local_variable(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example3_nested_local_variable:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example3_nested_local_variable(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example4_direct_method_call:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example4_direct_method_call(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example5_nested_method_call:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example5_nested_method_call(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example6_direct_g_variable_access:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example6_direct_g_variable_access(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example7_indirect_g_variable_access:", decrypt_aes_ecb(get_pbk(salt, iter_eq_999), TestRule5.p_example7_indirect_g_variable_access(password, plaintext)) == plaintext) print("M2Crypto -> rule5 -> p_example8_warning_parameter_not_resolvable:", decrypt_aes_ecb(get_pbk(salt, 1000), TestRule5.p_example8_warning_parameter_not_resolvable(password, iter_eq_1000, plaintext)) == plaintext) print("M2Crypto -> rule5 -> n_example1_iterations_eq_1000:", TestRule5.n_example1_iterations_eq_1000(password, plaintext))

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88b6746a1cf99beaf1faf0dfc28adddc1b47eaff

10,819

py

Python

analysis/webservice/algorithms/colortables.py

tloubrieu-jpl/incubator-sdap-nexus

5bf903f04f12eb27f25ea2aa738c617ca404a87b

[ "Apache-2.0" ]

17

2017-11-16T07:36:33.000Z

2021-11-07T00:02:20.000Z

analysis/webservice/algorithms/colortables.py

ifenty/incubator-sdap-nexus

3059c66f53d3f3d24c74d557c7632bdcc7f1eeec

[ "Apache-2.0" ]

35

2018-01-11T00:50:20.000Z

2022-03-17T23:08:07.000Z

analysis/webservice/algorithms/colortables.py

ifenty/incubator-sdap-nexus

3059c66f53d3f3d24c74d557c7632bdcc7f1eeec

[ "Apache-2.0" ]

25

2017-11-16T07:36:38.000Z

2022-02-03T20:48:46.000Z

# 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. grayscale = [ [0, 0, 0], [255, 255, 255] ] oceanography = [ [2, 3, 206], [143, 226, 255], [255, 255, 255], [255, 241, 27], [253, 0, 0] ] rainbow = [ [125, 0, 255], [0, 0, 255], [0, 255, 0], [255, 255, 0], [255, 125, 0], [255, 0, 0] ] anomaly = [ [129, 31, 240], [124, 30, 240], [119, 29, 241], [114, 27, 242], [108, 26, 242], [103, 24, 243], [97, 23, 244], [91, 21, 245], [86, 20, 245], [80, 18, 246], [73, 17, 247], [67, 15, 247], [61, 14, 248], [55, 12, 249], [48, 11, 250], [42, 9, 250], [35, 7, 251], [28, 6, 252], [21, 4, 252], [14, 3, 253], [7, 1, 254], [0, 0, 255], [3, 6, 253], [6, 12, 252], [10, 18, 250], [13, 24, 249], [17, 30, 247], [20, 36, 246], [23, 42, 245], [26, 47, 243], [29, 52, 242], [33, 57, 240], [36, 62, 239], [39, 67, 237], [42, 72, 236], [45, 76, 235], [48, 81, 233], [51, 85, 232], [53, 89, 230], [56, 93, 229], [59, 97, 227], [62, 101, 226], [65, 105, 225], [63, 106, 226], [62, 107, 227], [60, 108, 229], [59, 110, 230], [57, 111, 232], [56, 113, 233], [54, 115, 235], [52, 116, 236], [51, 118, 237], [49, 120, 239], [47, 122, 240], [46, 123, 242], [44, 125, 243], [42, 127, 245], [41, 130, 246], [39, 132, 247], [37, 134, 249], [35, 136, 250], [33, 139, 252], [31, 141, 253], [29, 144, 255], [28, 145, 255], [27, 147, 255], [25, 149, 255], [24, 151, 255], [22, 153, 255], [21, 155, 255], [19, 158, 255], [18, 160, 255], [17, 162, 255], [15, 164, 255], [14, 166, 255], [12, 169, 255], [11, 171, 255], [9, 173, 255], [8, 176, 255], [7, 178, 255], [5, 180, 255], [4, 183, 255], [2, 185, 255], [1, 188, 255], [0, 191, 255], [7, 191, 254], [14, 191, 253], [21, 191, 252], [28, 191, 251], [35, 192, 251], [41, 192, 250], [48, 193, 249], [55, 193, 248], [62, 194, 248], [69, 194, 247], [75, 195, 246], [82, 196, 245], [88, 196, 245], [95, 197, 244], [101, 198, 243], [108, 199, 242], [114, 200, 242], [121, 201, 241], [127, 202, 240], [133, 203, 239], [140, 205, 239], [143, 206, 239], [146, 208, 239], [149, 209, 240], [152, 211, 240], [155, 212, 241], [158, 214, 241], [161, 215, 242], [164, 217, 242], [168, 218, 243], [171, 220, 243], [174, 221, 244], [177, 222, 244], [180, 224, 245], [184, 225, 245], [187, 227, 246], [190, 228, 246], [193, 230, 247], [197, 231, 247], [200, 233, 248], [203, 234, 248], [207, 236, 249], [255, 255, 200], [255, 254, 192], [255, 254, 185], [255, 253, 178], [255, 252, 171], [255, 251, 164], [255, 250, 157], [255, 249, 149], [255, 248, 142], [255, 247, 135], [255, 246, 128], [255, 244, 121], [255, 243, 114], [255, 241, 107], [255, 239, 99], [255, 238, 92], [255, 236, 85], [255, 234, 78], [255, 231, 71], [255, 229, 64], [255, 227, 57], [255, 225, 49], [255, 222, 47], [255, 220, 45], [255, 218, 42], [255, 215, 40], [255, 213, 38], [255, 211, 35], [255, 208, 33], [255, 206, 30], [255, 203, 28], [255, 201, 26], [255, 198, 23], [255, 195, 21], [255, 193, 19], [255, 190, 16], [255, 187, 14], [255, 184, 11], [255, 181, 9], [255, 179, 7], [255, 176, 4], [255, 173, 2], [255, 170, 0], [255, 167, 0], [255, 164, 0], [255, 161, 0], [255, 158, 0], [255, 155, 0], [255, 152, 0], [255, 149, 0], [255, 147, 0], [255, 144, 0], [255, 141, 0], [255, 138, 0], [255, 135, 0], [255, 132, 0], [255, 129, 0], [255, 127, 0], [255, 124, 0], [255, 121, 0], [255, 118, 0], [255, 115, 0], [255, 112, 0], [255, 110, 0], [255, 104, 0], [255, 99, 0], [255, 94, 0], [255, 89, 0], [255, 83, 0], [255, 78, 0], [255, 73, 0], [255, 68, 0], [255, 62, 0], [255, 57, 0], [255, 52, 0], [255, 47, 0], [255, 41, 0], [255, 36, 0], [255, 31, 0], [255, 26, 0], [255, 20, 0], [255, 15, 0], [255, 10, 0], [255, 5, 0], [255, 0, 0], [252, 0, 0], [249, 0, 0], [247, 0, 0], [244, 0, 0], [241, 0, 0], [239, 0, 0], [236, 0, 0], [234, 0, 0], [231, 0, 0], [228, 0, 0], [226, 0, 0], [223, 0, 0], [220, 0, 0], [218, 0, 0], [215, 0, 0], [213, 0, 0], [210, 0, 0], [207, 0, 0], [205, 0, 0], [202, 0, 0], [200, 0, 0], [202, 6, 6], [205, 13, 13], [207, 20, 20], [210, 27, 27], [213, 35, 35], [215, 43, 43], [218, 50, 50], [220, 58, 58], [223, 66, 66], [226, 75, 75], [228, 83, 83], [231, 92, 92], [234, 101, 101], [236, 110, 110], [239, 119, 119], [241, 128, 128], [244, 138, 138], [247, 147, 147], [249, 157, 157], [252, 167, 167], [255, 178, 178] ] hottemp = [ [255, 255, 255], [255, 255, 0], [255, 0, 0], [0, 0, 0], [0, 0, 0] ] anomaly2 = [ [129, 31, 240], [124, 30, 240], [119, 29, 241], [114, 27, 242], [108, 26, 242], [103, 24, 243], [97, 23, 244], [91, 21, 245], [86, 20, 245], [80, 18, 246], [73, 17, 247], [67, 15, 247], [61, 14, 248], [55, 12, 249], [48, 11, 250], [42, 9, 250], [35, 7, 251], [28, 6, 252], [21, 4, 252], [14, 3, 253], [7, 1, 254], [0, 0, 255], [3, 6, 253], [6, 12, 252], [10, 18, 250], [13, 24, 249], [17, 30, 247], [20, 36, 246], [23, 42, 245], [26, 47, 243], [29, 52, 242], [33, 57, 240], [36, 62, 239], [39, 67, 237], [42, 72, 236], [45, 76, 235], [48, 81, 233], [51, 85, 232], [53, 89, 230], [56, 93, 229], [59, 97, 227], [62, 101, 226], [65, 105, 225], [63, 106, 226], [62, 107, 227], [60, 108, 229], [59, 110, 230], [57, 111, 232], [56, 113, 233], [54, 115, 235], [52, 116, 236], [51, 118, 237], [49, 120, 239], [47, 122, 240], [46, 123, 242], [44, 125, 243], [42, 127, 245], [41, 130, 246], [39, 132, 247], [37, 134, 249], [35, 136, 250], [33, 139, 252], [31, 141, 253], [29, 144, 255], [28, 145, 255], [27, 147, 255], [25, 149, 255], [24, 151, 255], [22, 153, 255], [21, 155, 255], [19, 158, 255], [18, 160, 255], [17, 162, 255], [15, 164, 255], [14, 166, 255], [12, 169, 255], [11, 171, 255], [9, 173, 255], [8, 176, 255], [7, 178, 255], [5, 180, 255], [4, 183, 255], [2, 185, 255], [1, 188, 255], [0, 191, 255], [7, 191, 254], [14, 191, 253], [21, 191, 252], [28, 191, 251], [35, 192, 251], [41, 192, 250], [48, 193, 249], [55, 193, 248], [62, 194, 248], [69, 194, 247], [75, 195, 246], [82, 196, 245], [88, 196, 245], [95, 197, 244], [101, 198, 243], [108, 199, 242], [114, 200, 242], [121, 201, 241], [127, 202, 240], [133, 203, 239], [140, 205, 239], [143, 206, 239], [146, 208, 239], [149, 209, 240], [152, 211, 240], [155, 212, 241], [158, 214, 241], [161, 215, 242], [164, 217, 242], [168, 218, 243], [171, 220, 243], [174, 221, 244], [177, 222, 244], [180, 224, 245], [184, 225, 245], [187, 227, 246], [190, 228, 246], [193, 230, 247], [197, 231, 247], [200, 233, 248], [203, 234, 248], [207, 236, 249], [255, 255, 255], [255, 255, 255], [255, 255, 200], [255, 254, 192], [255, 254, 185], [255, 253, 178], [255, 252, 171], [255, 251, 164], [255, 250, 157], [255, 249, 149], [255, 248, 142], [255, 247, 135], [255, 246, 128], [255, 244, 121], [255, 243, 114], [255, 241, 107], [255, 239, 99], [255, 238, 92], [255, 236, 85], [255, 234, 78], [255, 231, 71], [255, 229, 64], [255, 227, 57], [255, 225, 49], [255, 222, 47], [255, 220, 45], [255, 218, 42], [255, 215, 40], [255, 213, 38], [255, 211, 35], [255, 208, 33], [255, 206, 30], [255, 203, 28], [255, 201, 26], [255, 198, 23], [255, 195, 21], [255, 193, 19], [255, 190, 16], [255, 187, 14], [255, 184, 11], [255, 181, 9], [255, 179, 7], [255, 176, 4], [255, 173, 2], [255, 170, 0], [255, 167, 0], [255, 164, 0], [255, 161, 0], [255, 158, 0], [255, 155, 0], [255, 152, 0], [255, 149, 0], [255, 147, 0], [255, 144, 0], [255, 141, 0], [255, 138, 0], [255, 135, 0], [255, 132, 0], [255, 129, 0], [255, 127, 0], [255, 124, 0], [255, 121, 0], [255, 118, 0], [255, 115, 0], [255, 112, 0], [255, 110, 0], [255, 104, 0], [255, 99, 0], [255, 94, 0], [255, 89, 0], [255, 83, 0], [255, 78, 0], [255, 73, 0], [255, 68, 0], [255, 62, 0], [255, 57, 0], [255, 52, 0], [255, 47, 0], [255, 41, 0], [255, 36, 0], [255, 31, 0], [255, 26, 0], [255, 20, 0], [255, 15, 0], [255, 10, 0], [255, 5, 0], [255, 0, 0], [252, 0, 0], [249, 0, 0], [247, 0, 0], [244, 0, 0], [241, 0, 0], [239, 0, 0], [236, 0, 0], [234, 0, 0], [231, 0, 0], [228, 0, 0], [226, 0, 0], [223, 0, 0], [220, 0, 0], [218, 0, 0], [215, 0, 0], [213, 0, 0], [210, 0, 0], [207, 0, 0], [205, 0, 0], [202, 0, 0], [200, 0, 0], [200, 6, 6] ] smap = [ [125, 0, 255], [0, 0, 255], [0, 255, 0], [255, 255, 0], [255, 125, 0], [255, 0, 0] ]

19.670909

74

0.409465

1,669

10,819

2.654284

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9

31f34959f00117c9ae66f7b76ce0b28d6b7863d1

7,283

py

Python

block_ciphers.py

DatJezdziec/block_ciphers

4d7541c592ed6b6cb78d07970a334c9d3417eec9

[ "MIT" ]

null

block_ciphers.py

DatJezdziec/block_ciphers

4d7541c592ed6b6cb78d07970a334c9d3417eec9

[ "MIT" ]

null

block_ciphers.py

DatJezdziec/block_ciphers

4d7541c592ed6b6cb78d07970a334c9d3417eec9

[ "MIT" ]

null

from Crypto.Cipher import AES from Crypto.Random import get_random_bytes from Crypto.Util.Padding import pad, unpad from base64 import b64encode,b64decode from Crypto.Util import Counter import binascii from hashlib import md5 import os import time import json password="0987654321" key="1234567890abcdef" key = md5(key.encode('utf8')).digest() files_to_encrypt = ['1m.txt', '64m.txt', '128m.txt'] def ctre(): for file_to_encrypt in files_to_encrypt: input_file = open(file_to_encrypt, "rb") output_file = open('encrypted' + file_to_encrypt, 'w') startd = time.time() buffer_size = os.stat(file_to_encrypt).st_size data = input_file.read(buffer_size) cipher = AES.new(key, AES.MODE_CTR) ct_bytes = cipher.encrypt(data) nonce = b64encode(cipher.nonce).decode('utf-8') ct = b64encode(ct_bytes).decode('utf-8') result = json.dumps({'nonce':nonce, 'ct':ct}) output_file.write(result) print("CTR encrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def ctrd(): for file_to_encrypt in files_to_encrypt: input_file = open('encrypted' + file_to_encrypt, 'rb') output_file = open('decrypted' + file_to_encrypt, 'wb') startd = time.time() buffer_size = os.stat('encrypted' + file_to_encrypt).st_size json_input = input_file.read(buffer_size) b64 = json.loads(json_input) nonce = b64decode(b64['nonce']) ct = b64decode(b64['ct']) cipher = AES.new(key, AES.MODE_CTR, nonce=nonce) pt = cipher.decrypt(ct) output_file.write(pt) print("CTR decrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def cbce(): for file_to_encrypt in files_to_encrypt: input_file = open(file_to_encrypt, "rb") output_file = open('encrypted' + file_to_encrypt, 'w') startd = time.time() buffer_size = os.stat(file_to_encrypt).st_size data = input_file.read(buffer_size) cipher = AES.new(key, AES.MODE_CBC) ct_bytes = cipher.encrypt(pad(data, AES.block_size)) iv = b64encode(cipher.iv).decode('utf-8') ct = b64encode(ct_bytes).decode('utf-8') result = json.dumps({'iv':iv, 'ct':ct}) output_file.write(result) print("CBC encrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def cbcd(): for file_to_encrypt in files_to_encrypt: input_file = open('encrypted' + file_to_encrypt, 'rb') output_file = open('decrypted' + file_to_encrypt, 'wb') startd = time.time() buffer_size = os.stat('encrypted' + file_to_encrypt).st_size json_input = input_file.read(buffer_size) b64 = json.loads(json_input) iv = b64decode(b64['iv']) ct = b64decode(b64['ct']) cipher = AES.new(key, AES.MODE_CBC, iv) pt = unpad(cipher.decrypt(ct), AES.block_size) output_file.write(pt) print("CBC decrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def cfbe(): for file_to_encrypt in files_to_encrypt: input_file = open(file_to_encrypt, "rb") output_file = open('encrypted' + file_to_encrypt, 'w') startd = time.time() buffer_size = os.stat(file_to_encrypt).st_size data = input_file.read(buffer_size) cipher = AES.new(key, AES.MODE_CFB) ct_bytes = cipher.encrypt(data) iv = b64encode(cipher.iv).decode('utf-8') ct = b64encode(ct_bytes).decode('utf-8') result = json.dumps({'iv': iv, 'ciphertext': ct}) output_file.write(result) print("CFB encrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def cfbd(): for file_to_encrypt in files_to_encrypt: input_file = open('encrypted' + file_to_encrypt, 'rb') output_file = open('decrypted' + file_to_encrypt, 'wb') startd = time.time() buffer_size = os.stat('encrypted' + file_to_encrypt).st_size json_input = input_file.read(buffer_size) b64 = json.loads(json_input) iv = b64decode(b64['iv']) ct = b64decode(b64['ciphertext']) cipher = AES.new(key, AES.MODE_CFB, iv=iv) pt = cipher.decrypt(ct) output_file.write(pt) print("CFB decrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def ofbe(): for file_to_encrypt in files_to_encrypt: input_file = open(file_to_encrypt, "rb") output_file = open('encrypted' + file_to_encrypt, 'w') startd = time.time() buffer_size = os.stat(file_to_encrypt).st_size data = input_file.read(buffer_size) cipher = AES.new(key, AES.MODE_OFB) ct_bytes = cipher.encrypt(data) iv = b64encode(cipher.iv).decode('utf-8') ct = b64encode(ct_bytes).decode('utf-8') result = json.dumps({'iv': iv, 'ciphertext': ct}) output_file.write(result) print("OFB encrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def ofbd(): for file_to_encrypt in files_to_encrypt: input_file = open('encrypted' + file_to_encrypt, 'rb') output_file = open('decrypted' + file_to_encrypt, 'wb') startd = time.time() buffer_size = os.stat('encrypted' + file_to_encrypt).st_size json_input = input_file.read(buffer_size) b64 = json.loads(json_input) iv = b64decode(b64['iv']) ct = b64decode(b64['ciphertext']) cipher = AES.new(key, AES.MODE_OFB, iv=iv) pt = cipher.decrypt(ct) output_file.write(pt) print("OFB decrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def ecbe(): for file_to_encrypt in files_to_encrypt: input_file = open(file_to_encrypt, "rb") output_file = open('encrypted' + file_to_encrypt, 'w') startd = time.time() buffer_size = os.stat(file_to_encrypt).st_size data = input_file.read(buffer_size) cipher = AES.new(key, AES.MODE_ECB) ct_bytes = cipher.encrypt(pad(data, AES.block_size)) ct = b64encode(ct_bytes).decode('utf-8') result = json.dumps({'ct':ct}) output_file.write(result) print("ECB encrypt time " + file_to_encrypt) endd = time.time() print(endd - startd) def ecbd(): for file_to_encrypt in files_to_encrypt: input_file = open('encrypted' + file_to_encrypt, 'rb') output_file = open('decrypted' + file_to_encrypt, 'wb') startd = time.time() buffer_size = os.stat('encrypted' + file_to_encrypt).st_size json_input = input_file.read(buffer_size) b64 = json.loads(json_input) ct = b64decode(b64['ct']) cipher = AES.new(key, AES.MODE_ECB) pt = unpad(cipher.decrypt(ct), AES.block_size) output_file.write(pt) print("ECB decrypt time " + file_to_encrypt) endd = time.time() print(endd - startd)

40.016484

69

0.610463

970

7,283

4.348454

0.091753

0.130156

0.154101

0.078236

0.892129

0.886439

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0.267335

7,283

181

70

40.237569

0.77024

0

0.726744

0

0.078158

0

1

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false

0.005814

0.05814

0

0.116279

0

null

0

1

0

1

0

null

0

7

ee3ef671726c79b4b6d16f15e24083cf16a57f07

30,140

py

Python

server/models/inception_resnet/inception_resnet.py

Mobile-and-Ubiquitous-Computing-2020-1/team1

a3a5b4916a012ee0cd98cb186046a1957872b550

[ "MIT" ]

3

2020-03-23T10:32:43.000Z

2020-06-25T03:36:06.000Z

server/models/inception_resnet/inception_resnet.py

Mobile-and-Ubiquitous-Computing-2020-1/team1

a3a5b4916a012ee0cd98cb186046a1957872b550

[ "MIT" ]

4

2020-05-11T13:50:00.000Z

2022-02-10T01:58:08.000Z

server/models/inception_resnet/inception_resnet.py

Mobile-and-Ubiquitous-Computing-2020-1/team1

a3a5b4916a012ee0cd98cb186046a1957872b550

[ "MIT" ]

1

2020-08-13T00:01:01.000Z

""" Model code for FaceNet updated version (compatible with TF 2.x) of https://github.com/davidsandberg/facenet/blob/master/src/models/inception_resnet_v1.py """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf from tensorflow.python import keras from tensorflow.python.keras import layers from tensorflow.python.keras import initializers from tensorflow.python.keras import regularizers class CenterLoss(layers.Layer): """center loss calculation (this is stateful)""" def __init__(self, num_classes, embed_dim=512): super(CenterLoss, self).__init__() self.num_classes = num_classes self.embed_dim = embed_dim def build(self, input_shape): self.center_var = self.add_weight('center_var', shape=(self.num_classes, self.embed_dim), dtype=tf.float32, initializer=initializers.zeros, trainable=False) self.built = True def call(self, features, labels): labels = tf.reshape(labels, [-1]) centers_batch = tf.gather(self.center_var, labels) diff = (1 - 0.95) * (centers_batch - features) with tf.control_dependencies( [self.center_var.scatter_nd_sub(labels, diff)]): loss = tf.reduce_mean(tf.square(features - centers_batch)) return loss class BaseConvBlock(keras.Model): """Base Convolution Module""" def __init__(self, output_channels, kernel_size, strides=(1, 1), padding='valid', weight_decay=5e-4, kernel_initializer=initializers.glorot_uniform, batch_norm_decay=0.995, batch_norm_epsilon=0.001, name=None): super(BaseConvBlock, self).__init__() self.conv = layers.Conv2D(filters=output_channels, kernel_size=kernel_size, strides=strides, padding=padding, kernel_initializer=kernel_initializer, kernel_regularizer=regularizers.l2(weight_decay) \ if weight_decay > 0 else None, use_bias=False, name=name) self.norm = layers.BatchNormalization(axis=-1, momentum=batch_norm_decay, epsilon=batch_norm_epsilon, name=name) self.activation = layers.ReLU() def call(self, x, training=False): x = self.conv(x) x = self.norm(x, training=training) x = self.activation(x) return x class Block35(keras.Model): """Block35 module""" def __init__(self, filters, scale=1.0, activation_fn=tf.nn.relu): super(Block35, self).__init__() # branch 0 self.tower_conv = BaseConvBlock(32, (1, 1), padding='same', name='Conv2d_1x1') # branch 1 self.tower_conv1_0 = BaseConvBlock(32, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv1_1 = BaseConvBlock(32, (3, 3), padding='same', name='Conv2d_0b_3x3') # branch 2 self.tower_conv2_0 = BaseConvBlock(32, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv2_1 = BaseConvBlock(32, (3, 3), padding='same', name='Conv2d_0b_3x3') self.tower_conv2_2 = BaseConvBlock(32, (3, 3), padding='same', name='Conv2d_0c_3x3') # filters 256 self.up_conv = layers.Conv2D(filters, (1, 1), name='Conv2d_1x1') self.scale = scale self.activation_fn = activation_fn def call(self, x, training=False): inputs = x branch1 = self.tower_conv(x, training=training) branch2 = self.tower_conv1_0(x, training=training) branch2 = self.tower_conv1_1(branch2, training=training) branch3 = self.tower_conv2_0(x, training=training) branch3 = self.tower_conv2_1(branch3, training=training) branch3 = self.tower_conv2_2(branch3, training=training) mixed = tf.concat([branch1, branch2, branch3], axis=3) # 32 * 3 == 96 x = self.up_conv(mixed, training=training) # 96 => 256 x = inputs + self.scale * x if self.activation_fn is not None: x = self.activation_fn(x) return x class Block17(keras.Model): def __init__(self, filters, scale=1.0, activation_fn=tf.nn.relu): super(Block17, self).__init__() # branch 0 self.tower_conv = BaseConvBlock(128, (1, 1), padding='same', name='Conv2d_1x1') # branch 1 self.tower_conv1_0 = BaseConvBlock(128, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv1_1 = BaseConvBlock(128, (1, 7), padding='same', name='Conv2d_0b_1x7') self.tower_conv1_2 = BaseConvBlock(128, (7, 1), padding='same', name='Conv2d_0c_7x1') self.up_conv = layers.Conv2D(filters, (1, 1), name='Conv2d_1x1') self.scale = scale self.activation_fn = activation_fn def call(self, x, training=False): inputs = x branch1 = self.tower_conv(x, training=training) branch2 = self.tower_conv1_0(x, training=training) branch2 = self.tower_conv1_1(branch2, training=training) branch2 = self.tower_conv1_2(branch2, training=training) mixed = tf.concat([branch1, branch2], axis=3) x = self.up_conv(mixed, training=training) x = inputs + self.scale * x if self.activation_fn is not None: x = self.activation_fn(x) return x class Block8(keras.Model): def __init__(self, filters, scale=1.0, activation_fn=tf.nn.relu): super(Block8, self).__init__() # branch 0 self.tower_conv = BaseConvBlock(192, (1, 1), padding='same', name='Conv2d_1x1') # branch 1 self.tower_conv1_0 = BaseConvBlock(192, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv1_1 = BaseConvBlock(192, (1, 3), padding='same', name='Conv2d_0b_1x3') self.tower_conv1_2 = BaseConvBlock(192, (3, 1), padding='same', name='Conv2d_0c_3x1') self.up_conv = layers.Conv2D(filters, (1, 1), name='Conv2d_1x1') self.scale = scale self.activation_fn = activation_fn def call(self, x, training=False): inputs = x branch1 = self.tower_conv(x, training=training) branch2 = self.tower_conv1_0(x, training=training) branch2 = self.tower_conv1_1(branch2, training=training) branch2 = self.tower_conv1_2(branch2, training=training) mixed = tf.concat([branch1, branch2], axis=3) x = self.up_conv(mixed, training=training) x = inputs + self.scale * x if self.activation_fn is not None: x = self.activation_fn(x) return x class ReductionA(keras.Model): def __init__(self, k, l, m, n): super(ReductionA, self).__init__() # branch 0 self.tower_conv = BaseConvBlock(n, (3, 3), (2, 2), padding='valid', name='Conv2d_1a_3x3') # branch 1 self.tower_conv1_0 = BaseConvBlock(k, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv1_1 = BaseConvBlock(l, (3, 3), padding='same', name='Conv2d_0b_3x3') self.tower_conv1_2 = BaseConvBlock(m, (3, 3), (2, 2), padding='valid', name='Conv2d_1a_3x3') # branch 2 self.tower_pool = layers.MaxPooling2D((3, 3), (2, 2), padding='valid', name='MaxPool_1a_3x3') def call(self, x, training=False): branch0 = self.tower_conv(x, training=training) # n branch1 = self.tower_conv1_0(x, training=training) branch1 = self.tower_conv1_1(branch1, training=training) branch1 = self.tower_conv1_2(branch1, training=training) # l branch2 = self.tower_pool(x) # x x = tf.concat([branch0, branch1, branch2], axis=3) # n + l + x return x class ReductionB(keras.Model): def __init__(self): super(ReductionB, self).__init__() # branch 0 self.tower_conv = BaseConvBlock(256, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv_1 = BaseConvBlock(384, (3, 3), strides=(2, 2), padding='valid', name='Conv2d_1a_3x3') # branch 1 self.tower_conv1 = BaseConvBlock(256, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv1_1 = BaseConvBlock(256, (3, 3), strides=(2, 2), padding='valid', name='Conv2d_1a_3x3') # branch 2 self.tower_conv2 = BaseConvBlock(256, (1, 1), padding='same', name='Conv2d_0a_1x1') self.tower_conv2_1 = BaseConvBlock(256, (3, 3), padding='same', name='Conv2d_0b_3x3') self.tower_conv2_2 = BaseConvBlock(256, (3, 3), strides=(2, 2), padding='valid', name='Conv2d_1a_3x3') self.tower_pool = layers.MaxPooling2D((3, 3), strides=(2, 2), padding='valid', name='MaxPool_1a_3x3') def call(self, x, training=False): inputs = x branch0 = self.tower_conv(x, training=training) branch0 = self.tower_conv_1(branch0, training=training) branch1 = self.tower_conv1(x, training=training) branch1 = self.tower_conv1_1(branch1, training=training) branch2 = self.tower_conv2(x, training=training) branch2 = self.tower_conv2_1(branch2, training=training) branch2 = self.tower_conv2_2(branch2, training=training) branch3 = self.tower_pool(x) x = tf.concat([branch0, branch1, branch2, branch3], axis=3) return x class InceptionResNetV1(keras.Model): def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(InceptionResNetV1, self).__init__() self.conv1 = BaseConvBlock(32, (3, 3), strides=(2, 2), padding='valid', name='Conv2d_1a_3x3') self.conv2 = BaseConvBlock(32, (3, 3), padding='valid', name='Conv2d_2a_3x3') self.conv3 = BaseConvBlock(64, (3, 3), padding='same', name='Conv2d_2b_3x3') self.pool = layers.MaxPooling2D((3, 3), strides=(2, 2), padding='valid', name='MaxPool_3a_3x3') self.conv4 = BaseConvBlock(80, (1, 1), padding='valid', name='Conv2d_3b_1x1') self.conv5 = BaseConvBlock(192, (3, 3), padding='valid', name='Conv2d_4a_3x3') self.conv6 = BaseConvBlock(256, (3, 3), strides=(2, 2), padding='valid', name='Conv2d_4b_3x3') self.block35 = [Block35(256, scale=0.17) for _ in range(5)] self.reduction_a = ReductionA(192, 192, 256, 384) # 256 + 256 + 384 self.block17 = [Block17(256 + 256 + 384, scale=0.10) for _ in range(10)] self.reduction_b = ReductionB() self.block8 = [Block8(1792, scale=0.20, activation_fn=tf.nn.relu \ if i < 5 else None) for i in range(6)] self.avg_pool = layers.GlobalAveragePooling2D(name='AvgPool_1a_global') self.flatten = layers.Flatten() self.dropout = layers.Dropout(1 - dropout_keep_prob) self.embedding = layers.Dense(bottleneck_layer_size, name='Bottleneck', use_bias=False) self.last_bn = layers.BatchNormalization() # pylint: disable=line-too-long self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(InceptionResNetV1, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): if len(x.shape) == 4: x = self.conv1(x, training=training) x = self.conv2(x, training=training) x = self.conv3(x, training=training) x = self.pool(x, training=training) x = self.conv4(x, training=training) x = self.conv5(x, training=training) x = self.conv6(x, training=training) for block in self.block35: x = block(x, training=training) x = self.reduction_a(x, training=training) for block in self.block17: x = block(x, training=training) x = self.reduction_b(x, training=training) for block in self.block8: x = block(x, training=training) x = self.avg_pool(x) x = self.flatten(x) x = self.dropout(x, training=training) prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=training) else: assert len(x.shape) == 2 prelogits = x x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits def feature_extract(self, x): """just feature extraction without training flag""" x = self.conv1(x, training=False) x = self.conv2(x, training=False) x = self.conv3(x, training=False) x = self.pool(x, training=False) x = self.conv4(x, training=False) x = self.conv5(x, training=False) x = self.conv6(x, training=False) for block in self.block35: x = block(x, training=False) x = self.reduction_a(x, training=False) for block in self.block17: x = block(x, training=False) x = self.reduction_b(x, training=False) for block in self.block8: x = block(x, training=False) x = self.avg_pool(x) x = self.flatten(x) x = self.dropout(x, training=False) prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=False) return prelogits class ThawedModel1(keras.Model): """ assume only first three layers are fixed input size should be 38 x 38 x 64 """ def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(ThawedModel1, self).__init__() self.conv4 = BaseConvBlock(80, (1, 1), padding='valid', name='Conv2d_3b_1x1') self.conv5 = BaseConvBlock(192, (3, 3), padding='valid', name='Conv2d_4a_3x3') self.conv6 = BaseConvBlock(256, (3, 3), strides=(2, 2), padding='valid', name='Conv2d_4b_3x3') self.block35 = [Block35(256, scale=0.17) for _ in range(5)] self.reduction_a = ReductionA(192, 192, 256, 384) # 256 + 256 + 384 self.block17 = [Block17(256 + 256 + 384, scale=0.10) for _ in range(10)] self.reduction_b = ReductionB() self.block8 = [Block8(1792, scale=0.20, activation_fn=tf.nn.relu \ if i < 5 else None) for i in range(6)] self.avg_pool = layers.GlobalAveragePooling2D(name='AvgPool_1a_global') self.flatten = layers.Flatten() self.dropout = layers.Dropout(1 - dropout_keep_prob) self.embedding = layers.Dense(bottleneck_layer_size, name='Bottleneck', use_bias=False) self.last_bn = layers.BatchNormalization() # pylint: disable=line-too-long self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(ThawedModel1, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): x = self.conv4(x, training=training) x = self.conv5(x, training=training) x = self.conv6(x, training=training) for block in self.block35: x = block(x, training=training) x = self.reduction_a(x, training=training) for block in self.block17: x = block(x, training=training) x = self.reduction_b(x, training=training) for block in self.block8: x = block(x, training=training) x = self.avg_pool(x) x = self.flatten(x) x = self.dropout(x, training=training) prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=training) x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits class ThawedModel2(keras.Model): """ input size should be 17 x 17 x 256 """ def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(ThawedModel2, self).__init__() self.block35 = [Block35(256, scale=0.17) for _ in range(5)] self.reduction_a = ReductionA(192, 192, 256, 384) # 256 + 256 + 384 self.block17 = [Block17(256 + 256 + 384, scale=0.10) for _ in range(10)] self.reduction_b = ReductionB() self.block8 = [Block8(1792, scale=0.20, activation_fn=tf.nn.relu \ if i < 5 else None) for i in range(6)] self.avg_pool = layers.GlobalAveragePooling2D(name='AvgPool_1a_global') self.flatten = layers.Flatten() self.dropout = layers.Dropout(1 - dropout_keep_prob) self.embedding = layers.Dense(bottleneck_layer_size, name='Bottleneck', use_bias=False) self.last_bn = layers.BatchNormalization() # pylint: disable=line-too-long self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(ThawedModel2, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): for block in self.block35: x = block(x, training=training) x = self.reduction_a(x, training=training) for block in self.block17: x = block(x, training=training) x = self.reduction_b(x, training=training) for block in self.block8: x = block(x, training=training) x = self.avg_pool(x) x = self.flatten(x) x = self.dropout(x, training=training) prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=training) x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits class ThawedModel3(keras.Model): """ input size should be 17 x 17 x 256 """ def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(ThawedModel3, self).__init__() self.reduction_a = ReductionA(192, 192, 256, 384) # 256 + 256 + 384 self.block17 = [Block17(256 + 256 + 384, scale=0.10) for _ in range(10)] self.reduction_b = ReductionB() self.block8 = [Block8(1792, scale=0.20, activation_fn=tf.nn.relu \ if i < 5 else None) for i in range(6)] self.avg_pool = layers.GlobalAveragePooling2D(name='AvgPool_1a_global') self.flatten = layers.Flatten() self.dropout = layers.Dropout(1 - dropout_keep_prob) self.embedding = layers.Dense(bottleneck_layer_size, name='Bottleneck', use_bias=False) self.last_bn = layers.BatchNormalization() # pylint: disable=line-too-long self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(ThawedModel3, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): x = self.reduction_a(x, training=training) for block in self.block17: x = block(x, training=training) x = self.reduction_b(x, training=training) for block in self.block8: x = block(x, training=training) x = self.avg_pool(x) x = self.flatten(x) x = self.dropout(x, training=training) prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=training) x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits class ThawedModel4(keras.Model): """ input size should be 8 x 8 x 896 """ def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(ThawedModel4, self).__init__() self.reduction_b = ReductionB() self.block8 = [Block8(1792, scale=0.20, activation_fn=tf.nn.relu \ if i < 5 else None) for i in range(6)] self.avg_pool = layers.GlobalAveragePooling2D(name='AvgPool_1a_global') self.flatten = layers.Flatten() self.dropout = layers.Dropout(1 - dropout_keep_prob) self.embedding = layers.Dense(bottleneck_layer_size, name='Bottleneck', use_bias=False) self.last_bn = layers.BatchNormalization() # pylint: disable=line-too-long self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(ThawedModel4, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): x = self.reduction_b(x, training=training) for block in self.block8: x = block(x, training=training) x = self.avg_pool(x) x = self.flatten(x) x = self.dropout(x, training=training) prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=training) x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits class ThawedModel5(keras.Model): """ input size should be 1792 """ def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(ThawedModel5, self).__init__() self.embedding = layers.Dense(bottleneck_layer_size, name='Bottleneck', use_bias=False) self.last_bn = layers.BatchNormalization() # pylint: disable=line-too-long self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(ThawedModel5, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): prelogits = self.embedding(x) prelogits = self.last_bn(prelogits, training=training) x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits class ThawedModel6(keras.Model): """ input size should be 512 """ def __init__(self, dropout_keep_prob=0.4, bottleneck_layer_size=512, use_center_loss=False, num_classes=8631): super(ThawedModel6, self).__init__() self.classifier = layers.Dense(num_classes, kernel_initializer=initializers.glorot_uniform, kernel_regularizer=regularizers.l2(5e-4), name='Logits') self.activation = layers.Activation('softmax') self.use_center_loss = use_center_loss if use_center_loss: self.center_loss = CenterLoss(num_classes, 512) def build(self, input_shape): if self.use_center_loss: self.center_loss.build(input_shape) super(ThawedModel6, self).build(input_shape) def calculate_embedding(self, prelogits): # https://github.com/tamerthamoqa/facenet-pytorch-vggface2/blob/master/models/resnet.py x = tf.nn.l2_normalize(prelogits, axis=1, epsilon=1e-10) x = x * 10. return x def calculate_center_loss(self, features, labels): assert self.use_center_loss return self.center_loss(features, labels) def call(self, x, training=False): prelogits = x x = self.calculate_embedding(prelogits) x = self.classifier(x) x = self.activation(x) return x, prelogits

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Python

dfirtrack_main/tests/os/test_os_views.py

blackhatethicalhacking/dfirtrack

9c2e13015291f2981d14d63c9683e7c447e91f3a

[ "MIT" ]

4

2020-03-06T17:37:09.000Z

2020-03-17T07:50:55.000Z

dfirtrack_main/tests/os/test_os_views.py

blackhatethicalhacking/dfirtrack

9c2e13015291f2981d14d63c9683e7c447e91f3a

[ "MIT" ]

null

dfirtrack_main/tests/os/test_os_views.py

blackhatethicalhacking/dfirtrack

9c2e13015291f2981d14d63c9683e7c447e91f3a

[ "MIT" ]

1

2020-03-06T20:54:52.000Z

from django.contrib.auth.models import User from django.test import TestCase from dfirtrack_main.models import Os import urllib.parse class OsViewTestCase(TestCase): """ os view tests """ @classmethod def setUpTestData(cls): # create object Os.objects.create(os_name='os_1') # create user test_user = User.objects.create_user(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') def test_oss_list_not_logged_in(self): """ test list view """ # create url destination = '/login/?next=' + urllib.parse.quote('/oss/', safe='') # get response response = self.client.get('/oss/', follow=True) # compare self.assertRedirects(response, destination, status_code=302, target_status_code=200) def test_oss_list_logged_in(self): """ test list view """ # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/') # compare self.assertEqual(response.status_code, 200) def test_oss_list_template(self): """ test list view """ # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/') # compare self.assertTemplateUsed(response, 'dfirtrack_main/os/oss_list.html') def test_oss_list_get_user_context(self): """ test list view """ # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/') # compare self.assertEqual(str(response.context['user']), 'testuser_os') def test_oss_detail_not_logged_in(self): """ test detail view """ # get object os_1 = Os.objects.get(os_name='os_1') # create url destination = '/login/?next=' + urllib.parse.quote('/oss/' + str(os_1.os_id), safe='') # get response response = self.client.get('/oss/' + str(os_1.os_id), follow=True) # compare self.assertRedirects(response, destination, status_code=302, target_status_code=200) def test_oss_detail_logged_in(self): """ test detail view """ # get object os_1 = Os.objects.get(os_name='os_1') # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/' + str(os_1.os_id)) # compare self.assertEqual(response.status_code, 200) def test_oss_detail_template(self): """ test detail view """ # get object os_1 = Os.objects.get(os_name='os_1') # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/' + str(os_1.os_id)) # compare self.assertTemplateUsed(response, 'dfirtrack_main/os/oss_detail.html') def test_oss_detail_get_user_context(self): """ test detail view """ # get object os_1 = Os.objects.get(os_name='os_1') # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/' + str(os_1.os_id)) # compare self.assertEqual(str(response.context['user']), 'testuser_os') def test_oss_add_not_logged_in(self): """ test add view """ # create url destination = '/login/?next=' + urllib.parse.quote('/oss/add/', safe='') # get response response = self.client.get('/oss/add/', follow=True) # compare self.assertRedirects(response, destination, status_code=302, target_status_code=200) def test_oss_add_logged_in(self): """ test add view """ # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/add/') # compare self.assertEqual(response.status_code, 200) def test_oss_add_template(self): """ test add view """ # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/add/') # compare self.assertTemplateUsed(response, 'dfirtrack_main/os/oss_add.html') def test_oss_add_get_user_context(self): """ test add view """ # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/add/') # compare self.assertEqual(str(response.context['user']), 'testuser_os') def test_oss_edit_not_logged_in(self): """ test edit view """ # get object os_1 = Os.objects.get(os_name='os_1') # create url destination = '/login/?next=' + urllib.parse.quote('/oss/' + str(os_1.os_id) + '/edit/', safe='') # get response response = self.client.get('/oss/' + str(os_1.os_id) + '/edit/', follow=True) # compare self.assertRedirects(response, destination, status_code=302, target_status_code=200) def test_oss_edit_logged_in(self): """ test edit view """ # get object os_1 = Os.objects.get(os_name='os_1') # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/' + str(os_1.os_id) + '/edit/') # compare self.assertEqual(response.status_code, 200) def test_oss_edit_template(self): """ test edit view """ # get object os_1 = Os.objects.get(os_name='os_1') # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/' + str(os_1.os_id) + '/edit/') # compare self.assertTemplateUsed(response, 'dfirtrack_main/os/oss_edit.html') def test_oss_edit_get_user_context(self): """ test edit view """ # get object os_1 = Os.objects.get(os_name='os_1') # login testuser login = self.client.login(username='testuser_os', password='n7hIWBsrGsG0n4mSjbfw') # get response response = self.client.get('/oss/' + str(os_1.os_id) + '/edit/') # compare self.assertEqual(str(response.context['user']), 'testuser_os')

35.364583

105

0.620913

809

6,790

5.016069

0.080346

0.069

0.022178

0.090685

0.903154

0.871365

0.857812

0.848448

0.785116

0.77723

0

0.019977

0.248012

6,790

191

106

35.549738

0.774775

0.139764

0

0.54321

0

0.145397

0.022003

0

0.197531

1

0.209877

false

0.160494

0.049383

0

0.271605

0

null

0

1

0

null

0

1

0

1

0

8

4ea129f6fb6686b442d2238251ed35e2a4eded4d

1,235

py

Python

exception.py

kebrick/pyucallerapi

90e099bb206e5def916927228006bcf7e755926a

[ "MIT" ]

null

exception.py

kebrick/pyucallerapi

90e099bb206e5def916927228006bcf7e755926a

[ "MIT" ]

null

exception.py

kebrick/pyucallerapi

90e099bb206e5def916927228006bcf7e755926a

[ "MIT" ]

null

class uCallerException(Exception): pass class GetException(uCallerException): """Basic exception for errors thrown on get request.""" def __init__(self, name_class, name_method, message): super().__init__(f"Class \"{name_class}\": Method \"{name_method}\" - {message}") class SetSession(uCallerException): """Base exception for errors caused within a get couriers.""" def __init__(self, name_class, name_method, message): super().__init__(f"Class {name_class}: Method - {name_method} - {message}") class SetServiceId(uCallerException): """Base exception for errors caused within a get couriers.""" def __init__(self, name_class, name_method, message): super().__init__(f"Class {name_class}: Method - {name_method} - {message}") class SetKey(uCallerException): """Base exception for errors caused within a get couriers.""" def __init__(self, name_class, name_method, message, exit_now: int = None): super().__init__(f"Class {name_class}: Method - {name_method} - {message}") if exit_now is not None: exit(exit_now) class ParamSetException(uCallerException): """""" def __init__(self, name_class, name_method, message): super().__init__(f"Class {name_class}: Method - {name_method} - {message}")

30.875

83

0.729555

157

1,235

5.33758

0.229299

0.107399

0.202864

0.089499

0.74105

0

0.128745

1,235

39

84

31.666667

0.77881

0.175709

0

0.421053

0

0.247225

0

1

0.263158

false

0.052632

0

0.578947

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

9

4ebc120943cb4a46be36712c48ecd451e0f09888

99

py

Python

libconform/base.py

jofas/conform

9f8dd3c7c607269529bf4d62a729ed2ca1880baa

[ "MIT" ]

5

2020-02-10T13:30:06.000Z

2021-12-22T16:08:02.000Z

libconform/base.py

jofas/conform

9f8dd3c7c607269529bf4d62a729ed2ca1880baa

[ "MIT" ]

1

2019-07-04T14:12:13.000Z

2020-06-16T16:05:02.000Z

libconform/base.py

jofas/conform

9f8dd3c7c607269529bf4d62a729ed2ca1880baa

[ "MIT" ]

null

class NCMBase: def fit(self, X, y): pass def scores(self, X, y, cp): pass

14.142857

31

0.494949

15

99

3.266667

0.666667

0.204082

0.244898

0

0.383838

99

6

32

16.5

0.803279

0

0.4

0

1

0.4

false

0.4

0

0.6

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

4ec15c7e6207984f5322a06ca6c503c76940eb52

6,940

py

Python

tp_gst.py

lightbooster/TP-GST-BERT-Tacotron2

aa07e81c1ea3ace02bec5ac70f25a545d1ff0eb1

[ "BSD-3-Clause" ]

null

tp_gst.py

lightbooster/TP-GST-BERT-Tacotron2

aa07e81c1ea3ace02bec5ac70f25a545d1ff0eb1

[ "BSD-3-Clause" ]

null

tp_gst.py

lightbooster/TP-GST-BERT-Tacotron2

aa07e81c1ea3ace02bec5ac70f25a545d1ff0eb1

[ "BSD-3-Clause" ]

1

2021-05-25T20:08:56.000Z

import torch from torch import nn from torch.nn import functional as F from layers import LinearNorm class TPCW(nn.Module): """ Text-Predicting Combination Weights of GST """ def __init__(self, hparams): """ constructs TPCW model :param hparams: hyper parameters object """ super().__init__() self.hidden_state_dim = hparams.tpcw_gru_hidden_state_dim self.encoder_embedding_dim = hparams.encoder_embedding_dim + \ (hparams.bert_encoder_dim if hparams.tp_gst_use_bert else 0) self.attention_heads_num = hparams.num_heads self.token_num = hparams.token_num self.gru = nn.GRU(input_size=self.encoder_embedding_dim, hidden_size=self.hidden_state_dim, num_layers=1, batch_first=True) self.fc_layer = LinearNorm(in_dim=self.hidden_state_dim, out_dim=int(self.token_num * self.attention_heads_num)) self.soft_max_layer = nn.Softmax(dim=2) def forward(self, inputs): """ forwarding through the model layers :param inputs: encoder output shape of (batch_size, max_seq_len, embedding_dim) :return: combination weights tensor shape of (batch_size, attention_heads_num, token_num) """ self.gru.flatten_parameters() _, hidden_state_n = self.gru(inputs) # hidden_state_n - tensor shape of (1, batch_size, hidden_state_dim) # bring to shape (batch_size, hidden_state_dim) hidden_state_n = hidden_state_n.squeeze(dim=0) fc_output = self.fc_layer(hidden_state_n) # fc_output - tensor shape of (batch_size, token_num * attention_heads_num) # reshape to (batch_size, attention_heads_num, token_num) fc_output = fc_output.reshape(-1, self.attention_heads_num, self.token_num) w_combination = self.soft_max_layer(fc_output) return w_combination def inference(self, inputs): """ perform inference :param inputs: encoder output shape of (batch_size, max_seq_len, embedding_dim) :return: combination weights tensor shape of (batch_size, token_num) """ pass class TPSE(nn.Module): """ Text-Predicting Style Embedding """ def __init__(self, hparams): super().__init__() self.hidden_state_dim = hparams.tpse_gru_hidden_state_dim self.encoder_embedding_dim = hparams.encoder_embedding_dim + \ (hparams.bert_encoder_dim if hparams.tp_gst_use_bert else 0) self.fc_layers = hparams.tpse_fc_layers self.fc_layers_dim = hparams.tpse_fc_layer_dim self.token_dim = hparams.token_embedding_size self.gru = nn.GRU(input_size=self.encoder_embedding_dim, hidden_size=self.hidden_state_dim, num_layers=1, batch_first=True) self.fc_layers_model = None if self.fc_layers < 1: raise ValueError('hparams.fc_layers must be 1 or greater') elif self.fc_layers == 1: self.fc_layers_model = nn.Sequential(LinearNorm(self.hidden_state_dim, self.token_dim), nn.Tanh()) else: fc_layers_list = [] # input layer fc_layers_list.append(LinearNorm(self.hidden_state_dim, self.fc_layers_dim)) fc_layers_list.append(nn.ReLU()) # hidden layers for i in range(self.fc_layers - 2): fc_layers_list.append(LinearNorm(self.fc_layers_dim, self.fc_layers_dim)) fc_layers_list.append(nn.ReLU()) # output layer fc_layers_list.append(LinearNorm(self.fc_layers_dim, self.token_dim)) fc_layers_list.append(nn.Tanh()) self.fc_layers_model = nn.Sequential(*fc_layers_list) def forward(self, inputs): """ forwarding through the model layers :param inputs: encoder output shape of (batch_size, max_seq_len, embedding_dim) :return: style token tensor shape of (batch_size, token_dim) """ self.gru.flatten_parameters() _, hidden_state_n = self.gru(inputs) # hidden_state_n - tensor shape of (1, batch_size, hidden_state_dim) # bring to shape (batch_size, hidden_state_dim) hidden_state_n = hidden_state_n.squeeze(dim=0) fc_output = self.fc_layers_model(hidden_state_n) return fc_output def inference(self, inputs): """ perform inference :param inputs: encoder output shape of (batch_size, max_seq_len, embedding_dim) :return: style token tensor shape of (batch_size, token_dim) """ pass class TPSELinear(nn.Module): """ Text-Predicting Style Embedding (without rnn layer) """ def __init__(self, hparams): super().__init__() self.encoder_embedding_dim = hparams.encoder_embedding_dim + \ (hparams.bert_encoder_dim if hparams.tp_gst_use_bert else 0) self.fc_layers = hparams.tpse_linear_fc_layers self.fc_layers_dim = hparams.tpse_linear_fc_layer_dim self.token_dim = hparams.token_embedding_size self.fc_layers_model = None if self.fc_layers < 1: raise ValueError('hparams.fc_layers must be 1 or greater') elif self.fc_layers == 1: self.fc_layers_model = nn.Sequential(LinearNorm(self.encoder_embedding_dim, self.token_dim), nn.Tanh()) else: fc_layers_list = [] # input layer fc_layers_list.append(LinearNorm(self.encoder_embedding_dim, self.fc_layers_dim)) fc_layers_list.append(nn.ReLU()) # hidden layers for i in range(self.fc_layers - 2): fc_layers_list.append(LinearNorm(self.fc_layers_dim, self.fc_layers_dim)) fc_layers_list.append(nn.ReLU()) # output layer fc_layers_list.append(LinearNorm(self.fc_layers_dim, self.token_dim)) fc_layers_list.append(nn.Tanh()) self.fc_layers_model = nn.Sequential(*fc_layers_list) def forward(self, inputs): """ forwarding through the model layers :param inputs: encoder output shape of (batch_size, max_seq_len, embedding_dim) :return: style token tensor shape of (batch_size, token_dim) """ fc_output = self.fc_layers_model(inputs) return fc_output def inference(self, inputs): """ perform inference :param inputs: encoder output shape of (batch_size, max_seq_len, embedding_dim) :return: style token tensor shape of (batch_size, token_dim) """ pass

39.431818

104

0.62781

875

6,940

4.635429

0.117714

0.09073

0.076923

0.051282

0.859714

0.847387

0.807446

0.755671

0.738905

0

0.003863

0.29121

6,940

175

105

39.657143

0.820695

0.240346

0

0.705263

0

0.015354

0

1

0.094737

false

0.031579

0.042105

0

0.2

0

null

0

1

0

1

0

null

0

7

14f4e20f4bf8aa610dde7ba4000361be275fdb25

190

py

Python

project_2/interpreter/app/token.py

jelic98/raf_pp

7fcee2745bf3c47971a93d71fe5195d3bf29ea2d

[ "Apache-2.0" ]

1

2020-10-14T14:35:41.000Z

project_2/interpreter/app/token.py

jelic98/raf_pp

7fcee2745bf3c47971a93d71fe5195d3bf29ea2d

[ "Apache-2.0" ]

null

project_2/interpreter/app/token.py

jelic98/raf_pp

7fcee2745bf3c47971a93d71fe5195d3bf29ea2d

[ "Apache-2.0" ]

null

class Token(): def __init__(self, token_type, value): self.token_type = token_type self.value = value def __str__(self): return "<{} {}>".format(self.token_type, self.value)

23.75

55

0.668421

26

190

4.423077

0.384615

0.313043

0.33913

0.313043

0

0.178947

190

7

56

27.142857

0.737179

0

0.038251

0

1

0.333333

false

0

0.166667

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

0914aec0a5b481fe72e5b016c37f835f45d0c080

4,016

py

Python

userbot/modules/salam.py

oxyda-fox/XBot-Remix

3d97bea5395b223fc89a8cc6cb699cc624ccc967

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

userbot/modules/salam.py

oxyda-fox/XBot-Remix

3d97bea5395b223fc89a8cc6cb699cc624ccc967

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

userbot/modules/salam.py

oxyda-fox/XBot-Remix

3d97bea5395b223fc89a8cc6cb699cc624ccc967

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

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13

0928d94875922df6c3a71123f407279263b86046

9,439

py

Python

compiler/front_end/write_inference_test.py

chloeyutianyi/emboss

ec9b566848d322e0afd598327a6e81a8c7953008

[ "ECL-2.0", "Apache-2.0" ]

null

compiler/front_end/write_inference_test.py

chloeyutianyi/emboss

ec9b566848d322e0afd598327a6e81a8c7953008

[ "ECL-2.0", "Apache-2.0" ]

null

compiler/front_end/write_inference_test.py

chloeyutianyi/emboss

ec9b566848d322e0afd598327a6e81a8c7953008

[ "ECL-2.0", "Apache-2.0" ]

null

# Copyright 2019 Google LLC # # 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 # # https://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. """Tests for ...emboss.front_end.write_inference.""" import unittest from compiler.front_end import glue from compiler.front_end import test_util from compiler.front_end import write_inference from compiler.util import ir_pb2 class WriteInferenceTest(unittest.TestCase): def _make_ir(self, emb_text): ir, unused_debug_info, errors = glue.parse_emboss_file( "m.emb", test_util.dict_file_reader({"m.emb": emb_text}), stop_before_step="set_write_methods") assert not errors, errors return ir def test_adds_physical_write_method(self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n") self.assertEqual([], write_inference.set_write_methods(ir)) self.assertTrue( ir.module[0].type[0].structure.field[0].write_method.physical) def test_adds_read_only_write_method_to_non_alias_virtual(self): ir = self._make_ir("struct Foo:\n" " let x = 5\n") self.assertEqual([], write_inference.set_write_methods(ir)) self.assertTrue( ir.module[0].type[0].structure.field[0].write_method.read_only) def test_adds_alias_write_method_to_alias_of_physical_field(self): ir = self._make_ir("struct Foo:\n" " let x = y\n" " 0 [+1] UInt y\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[0] self.assertTrue(field.write_method.HasField("alias")) self.assertEqual( "y", field.write_method.alias.path[0].canonical_name.object_path[-1]) def test_adds_alias_write_method_to_alias_of_alias_of_physical_field(self): ir = self._make_ir("struct Foo:\n" " let x = z\n" " let z = y\n" " 0 [+1] UInt y\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[0] self.assertTrue(field.write_method.HasField("alias")) self.assertEqual( "z", field.write_method.alias.path[0].canonical_name.object_path[-1]) def test_adds_read_only_write_method_to_alias_of_read_only(self): ir = self._make_ir("struct Foo:\n" " let x = y\n" " let y = 5\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[0] self.assertTrue(field.write_method.read_only) def test_adds_read_only_write_method_to_alias_of_alias_of_read_only(self): ir = self._make_ir("struct Foo:\n" " let x = z\n" " let z = y\n" " let y = 5\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[0] self.assertTrue(field.write_method.read_only) def test_adds_read_only_write_method_to_alias_of_parameter(self): ir = self._make_ir("struct Foo(x: UInt:8):\n" " let y = x\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[0] self.assertTrue(field.write_method.read_only) def test_adds_transform_write_method_to_base_value_field(self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n" " let y = x + 50\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[1] transform = field.write_method.transform self.assertTrue(transform) self.assertEqual( "x", transform.destination.path[0].canonical_name.object_path[-1]) self.assertEqual(ir_pb2.Function.SUBTRACTION, transform.function_body.function.function) arg0, arg1 = transform.function_body.function.args self.assertEqual("$logical_value", arg0.builtin_reference.canonical_name.object_path[0]) self.assertEqual("50", arg1.constant.value) def test_adds_transform_write_method_to_negative_base_value_field(self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n" " let y = x - 50\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[1] transform = field.write_method.transform self.assertTrue(transform) self.assertEqual( "x", transform.destination.path[0].canonical_name.object_path[-1]) self.assertEqual(ir_pb2.Function.ADDITION, transform.function_body.function.function) arg0, arg1 = transform.function_body.function.args self.assertEqual("$logical_value", arg0.builtin_reference.canonical_name.object_path[0]) self.assertEqual("50", arg1.constant.value) def test_adds_transform_write_method_to_reversed_base_value_field(self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n" " let y = 50 + x\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[1] transform = field.write_method.transform self.assertTrue(transform) self.assertEqual( "x", transform.destination.path[0].canonical_name.object_path[-1]) self.assertEqual(ir_pb2.Function.SUBTRACTION, transform.function_body.function.function) arg0, arg1 = transform.function_body.function.args self.assertEqual("$logical_value", arg0.builtin_reference.canonical_name.object_path[0]) self.assertEqual("50", arg1.constant.value) def test_adds_transform_write_method_to_reversed_negative_base_value_field( self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n" " let y = 50 - x\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[1] transform = field.write_method.transform self.assertTrue(transform) self.assertEqual( "x", transform.destination.path[0].canonical_name.object_path[-1]) self.assertEqual(ir_pb2.Function.SUBTRACTION, transform.function_body.function.function) arg0, arg1 = transform.function_body.function.args self.assertEqual("50", arg0.constant.value) self.assertEqual("$logical_value", arg1.builtin_reference.canonical_name.object_path[0]) def test_adds_transform_write_method_to_nested_invertible_field(self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n" " let y = 30 + (50 - x)\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[1] transform = field.write_method.transform self.assertTrue(transform) self.assertEqual( "x", transform.destination.path[0].canonical_name.object_path[-1]) self.assertEqual(ir_pb2.Function.SUBTRACTION, transform.function_body.function.function) arg0, arg1 = transform.function_body.function.args self.assertEqual("50", arg0.constant.value) self.assertEqual(ir_pb2.Function.SUBTRACTION, arg1.function.function) arg10, arg11 = arg1.function.args self.assertEqual("$logical_value", arg10.builtin_reference.canonical_name.object_path[0]) self.assertEqual("30", arg11.constant.value) def test_does_not_add_transform_write_method_for_parameter_target(self): ir = self._make_ir("struct Foo(x: UInt:8):\n" " let y = 50 + x\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[0] self.assertEqual("read_only", field.write_method.WhichOneof("method")) def test_adds_transform_write_method_with_complex_auxiliary_subexpression( self): ir = self._make_ir("struct Foo:\n" " 0 [+1] UInt x\n" " let y = x - $max(Foo.$size_in_bytes, Foo.z)\n" " let z = 500\n") self.assertEqual([], write_inference.set_write_methods(ir)) field = ir.module[0].type[0].structure.field[1] transform = field.write_method.transform self.assertTrue(transform) self.assertEqual( "x", transform.destination.path[0].canonical_name.object_path[-1]) self.assertEqual(ir_pb2.Function.ADDITION, transform.function_body.function.function) args = transform.function_body.function.args self.assertEqual("$logical_value", args[0].builtin_reference.canonical_name.object_path[0]) self.assertEqual(field.read_transform.function.args[1], args[1]) if __name__ == "__main__": unittest.main()

43.497696

77

0.658968

1,253

9,439

4.717478

0.134078

0.109119

0.038065

0.033159

0.808831

0.795635

0.779733

0.762308

0.756894

0.718998

0

0.022352

0.222693

9,439

216

78

43.699074

0.78329

0.063142

0

0.718232

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0.00272

0

0.314917

1

0.082873

false

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0.121547

0

null

0

1

0

1

0

null

0

7

119ce26edc610780942723b4145c63843f36af4e

106

py

Python

tools/Polygraphy/polygraphy/backend/pyt/__init__.py

martellz/TensorRT

f182e83b30b5d45aaa3f9a041ff8b3ce83e366f4

[ "Apache-2.0" ]

4

2021-04-16T13:49:38.000Z

2022-01-16T08:58:07.000Z

tools/Polygraphy/polygraphy/backend/pyt/__init__.py

martellz/TensorRT

f182e83b30b5d45aaa3f9a041ff8b3ce83e366f4

[ "Apache-2.0" ]

null

tools/Polygraphy/polygraphy/backend/pyt/__init__.py

martellz/TensorRT

f182e83b30b5d45aaa3f9a041ff8b3ce83e366f4

[ "Apache-2.0" ]

2

2021-02-04T14:46:10.000Z

2021-02-04T14:56:08.000Z

from polygraphy.backend.pyt.loader import BaseLoadPyt from polygraphy.backend.pyt.runner import PytRunner

35.333333

53

0.867925

14

106

6.571429

0.642857

0.304348

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8

119ea49519131a0ad71bb974356c388970cedac9

4,888

py

Python

picbackend/views/v2/case_management_module_views/individual_cm_step_views/default_enrollment_step_2_views/tools/create_update_delete.py

bbcawodu/careadvisors-backend

5ebd3c0fc189b2486cea92b2a13c0bd8a0ee3838

[ "MIT" ]

null

picbackend/views/v2/case_management_module_views/individual_cm_step_views/default_enrollment_step_2_views/tools/create_update_delete.py

bbcawodu/careadvisors-backend

5ebd3c0fc189b2486cea92b2a13c0bd8a0ee3838

[ "MIT" ]

null

picbackend/views/v2/case_management_module_views/individual_cm_step_views/default_enrollment_step_2_views/tools/create_update_delete.py

bbcawodu/careadvisors-backend

5ebd3c0fc189b2486cea92b2a13c0bd8a0ee3838

[ "MIT" ]

null

import datetime import pytz from picbackend.views.utils import clean_int_value_from_dict_object from picbackend.views.utils import clean_string_value_from_dict_object def validate_put_rqst_params(rqst_body, rqst_errors): validated_params = { 'rqst_action': clean_string_value_from_dict_object(rqst_body, "root", "db_action", rqst_errors) } rqst_action = validated_params['rqst_action'] if rqst_action == 'create': validate_create_row_params(rqst_body, validated_params, rqst_errors) elif rqst_action == 'update': validated_params['id'] = clean_int_value_from_dict_object(rqst_body, "root", "id", rqst_errors) validate_update_row_params(rqst_body, validated_params, rqst_errors) elif rqst_action == 'delete': validated_params['id'] = clean_int_value_from_dict_object(rqst_body, "root", "id", rqst_errors) return validated_params def validate_create_row_params(rqst_body, validated_params, rqst_errors): validated_params['consumer_id'] = clean_int_value_from_dict_object( rqst_body, "root", "consumer_id", rqst_errors ) validated_params['navigator_id'] = clean_int_value_from_dict_object( rqst_body, "root", "navigator_id", rqst_errors ) validated_params['cm_client_id'] = clean_int_value_from_dict_object( rqst_body, "root", "cm_client_id", rqst_errors, none_allowed=True ) validated_params['cm_sequence_id'] = clean_int_value_from_dict_object( rqst_body, "root", "cm_sequence_id", rqst_errors, none_allowed=True ) if 'notes' in rqst_body: validated_params['notes'] = clean_string_value_from_dict_object( rqst_body, "root", "notes", rqst_errors, empty_string_allowed=True, none_allowed=True ) if "datetime_completed" in rqst_body: datetime_completed = clean_string_value_from_dict_object( rqst_body, "root", "datetime_completed", rqst_errors, none_allowed=True ) validated_datetime_completed = None if datetime_completed: try: validated_datetime_completed = datetime.datetime.strptime(datetime_completed, "%Y-%m-%dT%H:%M:%S").replace(tzinfo=pytz.UTC) except ValueError: rqst_errors.append( 'datetime_completed must be a properly formatted datetime string in UTC, eg. YYYY-MM-DDTHH:MM:SS. Value is : {}'.format( datetime_completed) ) validated_params['datetime_completed'] = validated_datetime_completed def validate_update_row_params(rqst_body, validated_params, rqst_errors): if 'consumer_id' in rqst_body: validated_params['consumer_id'] = clean_int_value_from_dict_object( rqst_body, "root", "consumer_id", rqst_errors ) if 'navigator_id' in rqst_body: validated_params['navigator_id'] = clean_int_value_from_dict_object( rqst_body, "root", "navigator_id", rqst_errors ) if 'cm_client_id' in rqst_body: validated_params['cm_client_id'] = clean_int_value_from_dict_object( rqst_body, "root", "cm_client_id", rqst_errors, none_allowed=True ) if "cm_sequence_id" in rqst_body: validated_params['cm_sequence_id'] = clean_int_value_from_dict_object( rqst_body, "root", "cm_sequence_id", rqst_errors, none_allowed=True ) if 'notes' in rqst_body: validated_params['notes'] = clean_string_value_from_dict_object( rqst_body, "root", "notes", rqst_errors, empty_string_allowed=True, none_allowed=True ) if "datetime_completed" in rqst_body: datetime_completed = clean_string_value_from_dict_object( rqst_body, "root", "datetime_completed", rqst_errors, none_allowed=True ) validated_datetime_completed = None if datetime_completed: try: validated_datetime_completed = datetime.datetime.strptime(datetime_completed, "%Y-%m-%dT%H:%M:%S").replace(tzinfo=pytz.UTC) except ValueError: rqst_errors.append( 'datetime_completed must be a properly formatted datetime string in UTC, eg. YYYY-MM-DDTHH:MM:SS. Value is : {}'.format( datetime_completed) ) validated_params['datetime_completed'] = validated_datetime_completed

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4,888

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141

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null

0

1

0

1

0

null

0

7

11b8a76b644d8e8508d75241bb55c6197f6b6bb5

3,506

py

Python

tests/unit/test_profiler.py

ylathouris/bio

8261f6a730b46e783d54b562d6acc674b5b828ce

[ "MIT" ]

null

tests/unit/test_profiler.py

ylathouris/bio

8261f6a730b46e783d54b562d6acc674b5b828ce

[ "MIT" ]

1

2019-11-28T17:23:13.000Z

2020-07-31T21:19:16.000Z

tests/unit/test_profiler.py

ylathouris/bio

8261f6a730b46e783d54b562d6acc674b5b828ce

[ "MIT" ]

null

from unittest import mock import cProfile import bio def do_something(): sum([1, 1]) @mock.patch.object(cProfile.Profile, "dump_stats") @mock.patch.object(cProfile.Profile, "print_stats") def test_profiler_context_manager(mock_print, mock_dump): """ Test profiler context manager (with defaults). This test demonstrates how to profile your code using the `profiler` context manager. When used without any arguments, the output will be written/printed to stdout. """ with bio.profiler(): do_something() mock_print.assert_called_once() mock_dump.assert_not_called() @mock.patch.object(cProfile.Profile, "dump_stats") @mock.patch.object(cProfile.Profile, "print_stats") def test_profiler_context_manager_with_output_file(mock_print, mock_dump): """ Test profiler context manager with output file. This test demonstrates how to use the `profiler` context manager. In this case we're providing a file location for storing the output data. """ path = "path/to/file.prof" with bio.profiler(path): do_something() mock_print.assert_called_once() mock_dump.assert_called_once_with(path) @mock.patch.object(cProfile.Profile, "dump_stats") @mock.patch.object(cProfile.Profile, "print_stats") def test_profiler_context_manager_with_no_stdout(mock_print, mock_dump): """ Test profiler context manager with output file. This test demonstrates how to use the `profiler` context manager. In this case we're providing the `quiet=True` option to prevent the output from being written to stdout (i.e. the console). """ path = "path/to/file.prof" with bio.profiler(path, quiet=True): do_something() mock_print.assert_not_called() mock_dump.assert_called_once_with(path) @mock.patch.object(cProfile.Profile, "dump_stats") @mock.patch.object(cProfile.Profile, "print_stats") def test_profiler_decorator(mock_print, mock_dump): """ Test profiler decorator. This test demonstrates how to profile code using the `profile` function decorator. """ @bio.profile() def do_something(): sum([1, 1]) do_something() mock_print.assert_called_once() mock_dump.assert_not_called() @mock.patch.object(cProfile.Profile, "dump_stats") @mock.patch.object(cProfile.Profile, "print_stats") def test_profiler_decorator_with_output_file(mock_print, mock_dump): """ Test profiler decorator witth output file. This test demonstrates how to profile code using the `profile` function decorator. In this case we're providing a file location for storing the output data. """ path = "path/to/file.prof" @bio.profile(path) def do_something(): sum([1, 1]) do_something() mock_print.assert_called_once() mock_dump.assert_called_once_with(path) @mock.patch.object(cProfile.Profile, "dump_stats") @mock.patch.object(cProfile.Profile, "print_stats") def test_profiler_decorator_with_no_stdout(mock_print, mock_dump): """ Test profiler decorator with output file. This test demonstrates how to use the `profiler` decorator. In this case we're providing the `quiet=True` option to prevent the output from being written to stdout (i.e. the console). """ path = "path/to/file.prof" @bio.profile(path, quiet=True) def do_something(): sum([1, 1]) do_something() mock_print.assert_not_called() mock_dump.assert_called_once_with(path)

27.825397

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0.146939

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0.074411

0.114097

0.916081

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0.863993

0.852418

0.778421

0

0.002786

0.181118

3,506

125

75

28.048

0.839777

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0

null

0

1

0

1

0

null

0

7

eed4f52505f07451403ae784d9ad203682f862f3

182

py

Python

postcodeapi/utils.py

roedesh/postcodeapi

53a6a5578d9dbf0566ae0712ed33c596b2dc6e64

[ "MIT" ]

null

postcodeapi/utils.py

roedesh/postcodeapi

53a6a5578d9dbf0566ae0712ed33c596b2dc6e64

[ "MIT" ]

7

2018-11-23T15:00:55.000Z

2019-04-21T19:47:51.000Z

postcodeapi/utils.py

roedesh/postcodeapi

53a6a5578d9dbf0566ae0712ed33c596b2dc6e64

[ "MIT" ]

null

import re DUTCH_POSTAL_CODE_REGEX = re.compile("^[1-9][0-9]{3}\s?[a-zA-Z]{2}$") def is_valid_postal_code(postal_code): return bool(DUTCH_POSTAL_CODE_REGEX.match(postal_code))

22.75

69

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34

182

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0.325203

0

0.036145

0.087912

182

7

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1

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null

0

1

0

1

0

8

e113067abb06fd2a23cd03c15e8ce879b9635f78

10,919

py

Python

LAMARCK_ML/nn_framework/nn_framework_test.py

JonasDHomburg/LAMARCK

0e372c908ff59effc6fd68e6477d04c4d89e6c26

[ "Apache-2.0", "BSD-3-Clause" ]

3

2019-09-20T08:03:47.000Z

2021-05-10T11:02:09.000Z

LAMARCK_ML/nn_framework/nn_framework_test.py

JonasDHomburg/LAMARCK_ML

0e372c908ff59effc6fd68e6477d04c4d89e6c26

[ "Apache-2.0", "BSD-3-Clause" ]

null

LAMARCK_ML/nn_framework/nn_framework_test.py

JonasDHomburg/LAMARCK_ML

0e372c908ff59effc6fd68e6477d04c4d89e6c26

[ "Apache-2.0", "BSD-3-Clause" ]

null

import unittest import os import numpy as np import tensorflow as tf from sklearn.datasets import make_classification from LAMARCK_ML.data_util import TypeShape, IOLabel, DFloat, Shape, DimNames from LAMARCK_ML.datasets import UncorrelatedSupervised from LAMARCK_ML.individuals import ClassifierIndividualACDG, ClassifierIndividualOPACDG if tf.__version__ == '1.12.0': from LAMARCK_ML.nn_framework.nvidia_tensorflow_1_12_0 import NVIDIATensorFlow else: from LAMARCK_ML.nn_framework.nvidia_tensorflow import NVIDIATensorFlow from LAMARCK_ML.architectures.functions import * @unittest.skipIf((os.environ.get('test_fast', False) in {'True','true', '1'}), 'time consuming') class TestNVIDIATensorFlowFramework(unittest.TestCase): @unittest.skipIf((os.environ.get('test_fast', False) in {'True', 'true', '1'}), 'time consuming') def test_MLP_Dense_Merge(self): train_samples = 1000 data_X, data_Y = make_classification(n_samples=train_samples, n_features=20, n_classes=5, n_informative=4, ) data_Y = tf.keras.utils.to_categorical(data_Y) data_X, data_Y = np.asarray(data_X), np.asarray(data_Y) train_X, test_X = data_X[:int(train_samples * .9), :], data_X[int(train_samples * .9):, :] train_Y, test_Y = data_Y[:int(train_samples * .9), :], data_Y[int(train_samples * .9):, :] batch = None dataset = UncorrelatedSupervised(train_X=train_X, train_Y=train_Y, test_X=test_X, test_Y=test_Y, batch=batch, typeShapes={IOLabel.DATA: TypeShape(DFloat, Shape((DimNames.UNITS, 20))), IOLabel.TARGET: TypeShape(DFloat, Shape((DimNames.UNITS, 5)))}, name='Dataset') ci = ClassifierIndividualACDG(**{ ClassifierIndividualACDG.arg_DATA_NTS: dict( [(label, (nts, dataset.id_name)) for label, nts in dataset.outputs.items()]), ClassifierIndividualACDG.arg_NN_FUNCTIONS: [Dense, Merge], }) NN = ci.network f_ids = dict([(_id, None) for _, _id in NN.inputs.values()]) for _f in NN.functions: f_ids[_f.id_name] = _f for _f in NN.functions: for _f_input, (other_output, other_id) in _f.inputs.items(): if other_id not in f_ids: self.assertTrue(False) stack = [f_id for _, f_id in NN.output_mapping.values()] required_ids = set() while stack: f_id = stack.pop() required_ids.add(f_id) f_ = f_ids.get(f_id) if f_ is not None: stack.extend([f_id for _, f_id in f_.inputs.values()]) self.assertSetEqual(required_ids, set(f_ids.keys())) framework = NVIDIATensorFlow(**{ NVIDIATensorFlow.arg_DATA_SETS: [dataset], }) ci.build_instance(framework) framework.accuracy(ci) framework.time() framework.memory() # framework.flops_per_sample() # framework.parameters() framework.reset() @unittest.skipIf((os.environ.get('test_fast', False) in {'True', 'true', '1'}), 'time consuming') def test_MLP_Dense_Merge_mutate(self): train_samples = 1000 data_X, data_Y = make_classification(n_samples=train_samples, n_features=20, n_classes=5, n_informative=4, ) data_Y = tf.keras.utils.to_categorical(data_Y) data_X, data_Y = np.asarray(data_X), np.asarray(data_Y) train_X, test_X = data_X[:int(train_samples * .9), :], data_X[int(train_samples * .9):, :] train_Y, test_Y = data_Y[:int(train_samples * .9), :], data_Y[int(train_samples * .9):, :] batch = None dataset = UncorrelatedSupervised(train_X=train_X, train_Y=train_Y, test_X=test_X, test_Y=test_Y, batch=batch, typeShapes={IOLabel.DATA: TypeShape(DFloat, Shape((DimNames.UNITS, 20))), IOLabel.TARGET: TypeShape(DFloat, Shape((DimNames.UNITS, 5)))}, name='Dataset') ci = ClassifierIndividualACDG(**{ ClassifierIndividualACDG.arg_DATA_NTS: dict( [(label, (nts, dataset.id_name)) for label, nts in dataset.outputs.items()]), ClassifierIndividualACDG.arg_NN_FUNCTIONS: [Dense, Merge], }) ci = ci.mutate(1)[0] NN = ci.network f_ids = dict([(_id, None) for _, _id in NN.inputs.values()]) for _f in NN.functions: f_ids[_f.id_name] = _f for _f in NN.functions: for _f_input, (other_output, other_id) in _f.inputs.items(): if other_id not in f_ids: self.assertTrue(False) stack = [f_id for _, f_id in NN.output_mapping.values()] required_ids = set() while stack: f_id = stack.pop() required_ids.add(f_id) f_ = f_ids.get(f_id) if f_ is not None: stack.extend([f_id for _, f_id in f_.inputs.values()]) self.assertSetEqual(required_ids, set(f_ids.keys())) framework = NVIDIATensorFlow(**{ NVIDIATensorFlow.arg_DATA_SETS: [dataset], }) ci.build_instance(framework) framework.accuracy(ci) framework.time() framework.memory() # framework.flops_per_sample() # framework.parameters() framework.reset() @unittest.skipIf((os.environ.get('test_fast', False) in {'True', 'true', '1'}), 'time consuming') def test_Conv_Flatten_Pool_Dense_Merge(self): train_samples = 1000 data_X, data_Y = make_classification(n_samples=train_samples, n_features=3072, n_classes=5, n_informative=4, ) data_X = data_X.reshape((train_samples, 32, 32, 3)) data_Y = tf.keras.utils.to_categorical(data_Y) data_X, data_Y = np.asarray(data_X), np.asarray(data_Y) train_X, test_X = data_X[:int(train_samples * .9), :], data_X[int(train_samples * .9):, :] train_Y, test_Y = data_Y[:int(train_samples * .9), :], data_Y[int(train_samples * .9):, :] batch = None dataset = UncorrelatedSupervised(train_X=train_X, train_Y=train_Y, test_X=test_X, test_Y=test_Y, batch=batch, typeShapes={IOLabel.DATA: TypeShape(DFloat, Shape((DimNames.HEIGHT, 32), (DimNames.WIDTH, 32), (DimNames.CHANNEL, 3))), IOLabel.TARGET: TypeShape(DFloat, Shape((DimNames.UNITS, 5)))}, name='Dataset') ci = ClassifierIndividualACDG(**{ ClassifierIndividualACDG.arg_DATA_NTS: dict( [(label, (nts, dataset.id_name)) for label, nts in dataset.outputs.items()]), ClassifierIndividualACDG.arg_NN_FUNCTIONS: [Conv2D, Flatten, Dense, Merge], ClassifierIndividualACDG.arg_MAX_NN_DEPTH: 10, }) framework = NVIDIATensorFlow(**{ NVIDIATensorFlow.arg_DATA_SETS: [dataset], }) ci.build_instance(framework) framework.accuracy(ci) framework.time() framework.memory() # framework.flops_per_sample() # framework.parameters() framework.reset() @unittest.skipIf((os.environ.get('test_fast', False) in {'True', 'true', '1'}), 'time consuming') def test_Conv_Flatten_Pool_Dense_Merge_mutate_recombine(self): train_samples = 1000 data_X, data_Y = make_classification(n_samples=train_samples, n_features=3072, n_classes=5, n_informative=4, ) data_X = data_X.reshape((train_samples, 32, 32, 3)) data_Y = tf.keras.utils.to_categorical(data_Y) data_X, data_Y = np.asarray(data_X), np.asarray(data_Y) train_X, test_X = data_X[:int(train_samples * .9), :], data_X[int(train_samples * .9):, :] train_Y, test_Y = data_Y[:int(train_samples * .9), :], data_Y[int(train_samples * .9):, :] batch = None dataset = UncorrelatedSupervised(train_X=train_X, train_Y=train_Y, test_X=test_X, test_Y=test_Y, batch=batch, typeShapes={IOLabel.DATA: TypeShape(DFloat, Shape((DimNames.HEIGHT, 32), (DimNames.WIDTH, 32), (DimNames.CHANNEL, 3))), IOLabel.TARGET: TypeShape(DFloat, Shape((DimNames.UNITS, 5)))}, name='Dataset') ci = ClassifierIndividualACDG(**{ ClassifierIndividualACDG.arg_DATA_NTS: dict( [(label, (nts, dataset.id_name)) for label, nts in dataset.outputs.items()]), ClassifierIndividualACDG.arg_NN_FUNCTIONS: [Conv2D, Pooling2D, Flatten, Dense, Merge], ClassifierIndividualACDG.arg_MAX_NN_DEPTH: 10, }) ci = ci.mutate(1)[0] framework = NVIDIATensorFlow(**{ NVIDIATensorFlow.arg_DATA_SETS: [dataset], }) ci.build_instance(framework) state = ci.train_instance(framework) ci.update_state(**state) self.assertTrue(isinstance(framework.accuracy(None), float)) self.assertTrue(isinstance(framework.time(), float)) self.assertTrue(isinstance(framework.memory(), float)) # self.assertTrue(isinstance(framework.flops_per_sample(), float)) # self.assertTrue(isinstance(framework.parameters(), float)) framework.reset() self.assertGreater(len(ci.network.variable_pool), 0) ci2 = ClassifierIndividualACDG(**{ ClassifierIndividualACDG.arg_DATA_NTS: dict( [(label, (nts, dataset.id_name)) for label, nts in dataset.outputs.items()]), ClassifierIndividualACDG.arg_NN_FUNCTIONS: [Conv2D, Pooling2D, Flatten, Dense, Merge], ClassifierIndividualACDG.arg_MAX_NN_DEPTH: 10, }) ci.build_instance(framework) framework.reset() ci_rec = ci.recombine(ci2)[0] self.assertGreater(len(ci_rec.network.variable_pool), 0)

43.501992

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0

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0

1

0

1

0

null

0

7

0145743b1ed2a13da7c4bd03d3420606ebed67e4

105

py

Python

backend/beedare/user_information/__init__.py

gijs3ntius/BeeDare

9ad5a93dad9b531b332aeb58f9b97e98585bc1ac

[ "Apache-2.0" ]

null

backend/beedare/user_information/__init__.py

gijs3ntius/BeeDare

9ad5a93dad9b531b332aeb58f9b97e98585bc1ac

[ "Apache-2.0" ]

17

2020-06-05T18:27:11.000Z

2022-03-11T23:24:50.000Z

backend/beedare/user_information/__init__.py

gijsentius/BeeDare

9ad5a93dad9b531b332aeb58f9b97e98585bc1ac

[ "Apache-2.0" ]

null

from flask import Blueprint user_info_blueprint = Blueprint('user_info', __name__) from . import views

17.5

54

0.8

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105

5.5

0.571429

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105

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1

0

1

0

null

0

1

0

1

0

7

6d728c8728d85b92bd38bf9c9aa4625485c03e1f

92

py

Python

parameters_8020.py

AnujBrandy/AdsIdeaInQBO

561b096a0e5db3acddbf9f1fc57d29ac8fe1791d

[ "BSD-3-Clause" ]

2

2015-07-05T12:25:08.000Z

2015-07-05T15:39:32.000Z

parameters_8020.py

AnujBrandy/AdsIdeaInQBO

561b096a0e5db3acddbf9f1fc57d29ac8fe1791d

[ "BSD-3-Clause" ]

null

parameters_8020.py

AnujBrandy/AdsIdeaInQBO

561b096a0e5db3acddbf9f1fc57d29ac8fe1791d

[ "BSD-3-Clause" ]

null

password="pbkdf2(1000,20,sha512)$a652e2e1499cdf8c$3eb3c6d91c3eb578ef19cebe65b13866f70da95b"

46

91

0.891304

7

92

11.714286

1

0

0.450549

0.01087

92

1

92

0.450549

0

0.869565

0

1

0

false

1

0

1

0

1

null

0

1

0

1

0

1

0

1

null

0

1

0

8

0996bc8cb8466dd2c8911b023022afa3ba529f98

3,967

py

Python

worker/tests/unit/tasks/test_auth.py

wattlecloud/foundation-server

e1467d192a7729fa4f116c80dcd001bfd58662e8

[ "Apache-2.0" ]

null

worker/tests/unit/tasks/test_auth.py

wattlecloud/foundation-server

e1467d192a7729fa4f116c80dcd001bfd58662e8

[ "Apache-2.0" ]

1

2021-07-20T00:28:27.000Z

worker/tests/unit/tasks/test_auth.py

wattlecloud/foundation-server

e1467d192a7729fa4f116c80dcd001bfd58662e8

[ "Apache-2.0" ]

null

import base64 import json from unittest.mock import ANY from wattle.core.models.db.user import User from wattle.worker.config import config as worker_config from wattle.worker.tasks.auth import email_password_reset, email_verify def test_email_verify_user_does_not_exist(mocker, monkeypatch): session = mocker.patch("wattle.worker.tasks.auth.session_scope") session.return_value.__enter__.return_value = "session" mocker.patch.object(User, "get_by_email") User.get_by_email.return_value = None mock_create_verify_token = mocker.patch( "wattle.worker.tasks.auth.create_verify_token" ) email_verify("test@test.com") User.get_by_email.assert_called_with("session", "test@test.com") mock_create_verify_token.assert_not_called() def test_email_verify(mocker, monkeypatch): session = mocker.patch("wattle.worker.tasks.auth.session_scope") session.return_value.__enter__.return_value = "session" mocker.patch.object(User, "get_by_email") user = User(email="test@test.com", id="user-id") User.get_by_email.return_value = user mock_create_verify_token = mocker.patch( "wattle.worker.tasks.auth.create_verify_token" ) mock_create_verify_token.return_value = "token" mock_create_message = mocker.patch( "wattle.worker.tasks.auth.create_message" ) mock_create_message.return_value = "an_email" mock_send_email = mocker.patch( "wattle.worker.tasks.auth.send_email" ) email_verify("test@test.com") User.get_by_email.assert_called_with("session", "test@test.com") mock_create_verify_token.assert_called_with(id=user.id) # TODO: Properly test messages when templating in implemented mock_create_message.assert_called_with( f"{worker_config.FROM_EMAIL_NAME} <{worker_config.FROM_EMAIL}>", user.email, "Wattle - Verification", ANY, ANY ) mock_send_email.assert_called_with(user.email, mock_create_message.return_value) def test_email_password_reset_user_does_not_exist(mocker, monkeypatch): session = mocker.patch("wattle.worker.tasks.auth.session_scope") session.return_value.__enter__.return_value = "session" mocker.patch.object(User, "get_by_email") User.get_by_email.return_value = None mock_create_password_reset_token = mocker.patch( "wattle.worker.tasks.auth.create_password_reset_token" ) email_password_reset("test@test.com") User.get_by_email.assert_called_with("session", "test@test.com") mock_create_password_reset_token.assert_not_called() def test_email_password_reset(mocker, monkeypatch): session = mocker.patch("wattle.worker.tasks.auth.session_scope") session.return_value.__enter__.return_value = "session" mocker.patch.object(User, "get_by_email") user = User( id="user-id", email="test@test.com", hashed_password="hashed-pass" ) User.get_by_email.return_value = user mock_create_password_reset_token = mocker.patch( "wattle.worker.tasks.auth.create_password_reset_token" ) mock_create_password_reset_token.return_value = "token" mock_create_message = mocker.patch( "wattle.worker.tasks.auth.create_message" ) mock_create_message.return_value = "an_email" mock_send_email = mocker.patch( "wattle.worker.tasks.auth.send_email" ) email_password_reset("test@test.com") User.get_by_email.assert_called_with("session", "test@test.com") mock_create_password_reset_token.assert_called_with( id=user.id, hashed_password="hashed-pass" ) # TODO: Properly test messages when templating in implemented mock_create_message.assert_called_with( f"{worker_config.FROM_EMAIL_NAME} <{worker_config.FROM_EMAIL}>", user.email, "Wattle - Password Reset", ANY, ANY ) mock_send_email.assert_called_with(user.email, mock_create_message.return_value)

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5.082243

0.11215

0.072821

0.08128

0.100405

0.870541

0.848106

0.819419

0.798088

0

0.000602

0.161835

3,967

124

85

31.991935

0.817143

0.029997

0

0.613636

0

0.247594

0.158648

0

0.008065

0.136364

1

0.045455

false

0.170455

0.068182

0

0.113636

0

null

0

1

0

null

0

1

0

7

09d7238b67b1a62451ddf3e03c3d506c818b2f9c

74,545

py

Python

fhir/resources/STU3/tests/test_plandefinition.py

mmabey/fhir.resources

cc73718e9762c04726cd7de240c8f2dd5313cbe1

[ "BSD-3-Clause" ]

null

fhir/resources/STU3/tests/test_plandefinition.py

mmabey/fhir.resources

cc73718e9762c04726cd7de240c8f2dd5313cbe1

[ "BSD-3-Clause" ]

null

fhir/resources/STU3/tests/test_plandefinition.py

mmabey/fhir.resources

cc73718e9762c04726cd7de240c8f2dd5313cbe1

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ Profile: http://hl7.org/fhir/StructureDefinition/PlanDefinition Release: STU3 Version: 3.0.2 Revision: 11917 Last updated: 2019-10-24T11:53:00+11:00 """ import io import json import os import unittest import pytest from .. import plandefinition from ..fhirdate import FHIRDate from .fixtures import force_bytes @pytest.mark.usefixtures("base_settings") class PlanDefinitionTests(unittest.TestCase): def instantiate_from(self, filename): datadir = os.environ.get("FHIR_UNITTEST_DATADIR") or "" with io.open(os.path.join(datadir, filename), "r", encoding="utf-8") as handle: js = json.load(handle) self.assertEqual("PlanDefinition", js["resourceType"]) return plandefinition.PlanDefinition(js) def testPlanDefinition1(self): inst = self.instantiate_from("plandefinition-example-kdn5-simplified.json") self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition1(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition1(inst2) def implPlanDefinition1(self, inst): self.assertEqual( force_bytes( inst.action[0] .action[0] .action[0] .action[0] .action[0] .extension[0] .extension[0] .url ), force_bytes("day"), ) self.assertEqual( inst.action[0] .action[0] .action[0] .action[0] .action[0] .extension[0] .extension[0] .valueInteger, 1, ) self.assertEqual( force_bytes( inst.action[0] .action[0] .action[0] .action[0] .action[0] .extension[0] .extension[1] .url ), force_bytes("day"), ) self.assertEqual( inst.action[0] .action[0] .action[0] .action[0] .action[0] .extension[0] .extension[1] .valueInteger, 8, ) self.assertEqual( force_bytes( inst.action[0].action[0].action[0].action[0].action[0].extension[0].url ), force_bytes("http://hl7.org/fhir/StructureDefinition/timing-daysOfCycle"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].action[0].action[0].id), force_bytes("action-1"), ) self.assertEqual( force_bytes( inst.action[0].action[0].action[0].action[0].action[0].textEquivalent ), force_bytes("Gemcitabine 1250 mg/m² IV over 30 minutes on days 1 and 8"), ) self.assertEqual( force_bytes( inst.action[0] .action[0] .action[0] .action[0] .action[1] .extension[0] .extension[0] .url ), force_bytes("day"), ) self.assertEqual( inst.action[0] .action[0] .action[0] .action[0] .action[1] .extension[0] .extension[0] .valueInteger, 1, ) self.assertEqual( force_bytes( inst.action[0].action[0].action[0].action[0].action[1].extension[0].url ), force_bytes("http://hl7.org/fhir/StructureDefinition/timing-daysOfCycle"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].action[0].action[1].id), force_bytes("action-2"), ) self.assertEqual( force_bytes( inst.action[0] .action[0] .action[0] .action[0] .action[1] .relatedAction[0] .actionId ), force_bytes("action-1"), ) self.assertEqual( force_bytes( inst.action[0] .action[0] .action[0] .action[0] .action[1] .relatedAction[0] .relationship ), force_bytes("concurrent-with-start"), ) self.assertEqual( force_bytes( inst.action[0].action[0].action[0].action[0].action[1].textEquivalent ), force_bytes("CARBOplatin AUC 5 IV over 30 minutes on Day 1"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].action[0].id), force_bytes("cycle-definition-1"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].action[0].textEquivalent), force_bytes("21-day cycle for 6 cycles"), ) self.assertEqual( inst.action[0].action[0].action[0].action[0].timingTiming.repeat.count, 6 ) self.assertEqual( inst.action[0].action[0].action[0].action[0].timingTiming.repeat.duration, 21, ) self.assertEqual( force_bytes( inst.action[0] .action[0] .action[0] .action[0] .timingTiming.repeat.durationUnit ), force_bytes("d"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].groupingBehavior), force_bytes("sentence-group"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].selectionBehavior), force_bytes("exactly-one"), ) self.assertEqual( force_bytes(inst.action[0].action[0].selectionBehavior), force_bytes("all") ) self.assertEqual( force_bytes(inst.action[0].selectionBehavior), force_bytes("exactly-one") ) self.assertEqual(inst.approvalDate.date, FHIRDate("2016-07-27").date) self.assertEqual(inst.approvalDate.as_json(), "2016-07-27") self.assertEqual(force_bytes(inst.contained[0].id), force_bytes("1111")) self.assertEqual(force_bytes(inst.contained[1].id), force_bytes("2222")) self.assertEqual( force_bytes(inst.contributor[0].name), force_bytes("Lee Surprenant") ) self.assertEqual(force_bytes(inst.contributor[0].type), force_bytes("author")) self.assertEqual( force_bytes(inst.copyright), force_bytes("All rights reserved.") ) self.assertTrue(inst.experimental) self.assertEqual(force_bytes(inst.id), force_bytes("KDN5")) self.assertEqual( force_bytes(inst.identifier[0].system), force_bytes("http://example.org/ordertemplates"), ) self.assertEqual(force_bytes(inst.identifier[0].value), force_bytes("KDN5")) self.assertEqual(inst.lastReviewDate.date, FHIRDate("2016-07-27").date) self.assertEqual(inst.lastReviewDate.as_json(), "2016-07-27") self.assertEqual( force_bytes(inst.publisher), force_bytes("National Comprehensive Cancer Network, Inc."), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].display), force_bytes("NCCN Guidelines for Kidney Cancer. V.2.2016"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual( force_bytes(inst.relatedArtifact[0].url), force_bytes( "http://www.example.org/professionals/physician_gls/PDF/kidney.pdf" ), ) self.assertEqual( force_bytes(inst.relatedArtifact[1].citation), force_bytes("Oudard S, et al. J Urol. 2007;177(5):1698-702"), ) self.assertEqual( force_bytes(inst.relatedArtifact[1].type), force_bytes("citation") ) self.assertEqual( force_bytes(inst.relatedArtifact[1].url), force_bytes("http://www.ncbi.nlm.nih.gov/pubmed/17437788"), ) self.assertEqual(force_bytes(inst.status), force_bytes("draft")) self.assertEqual(force_bytes(inst.text.status), force_bytes("additional")) self.assertEqual( force_bytes(inst.title), force_bytes("Gemcitabine/CARBOplatin") ) self.assertEqual( force_bytes(inst.type.text), force_bytes("Chemotherapy Order Template") ) self.assertEqual( force_bytes(inst.useContext[0].code.code), force_bytes("treamentSetting-or-diseaseStatus"), ) self.assertEqual( force_bytes(inst.useContext[0].code.system), force_bytes("http://example.org/fhir/CodeSystem/indications"), ) self.assertEqual( force_bytes(inst.useContext[0].extension[0].url), force_bytes("http://hl7.org/fhir/StructureDefinition/usagecontext-group"), ) self.assertEqual( force_bytes(inst.useContext[0].extension[0].valueString), force_bytes("A") ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.text), force_bytes("Metastatic"), ) self.assertEqual( force_bytes(inst.useContext[1].code.code), force_bytes("disease-or-histology"), ) self.assertEqual( force_bytes(inst.useContext[1].code.system), force_bytes("http://example.org/fhir/CodeSystem/indications"), ) self.assertEqual( force_bytes(inst.useContext[1].extension[0].url), force_bytes("http://hl7.org/fhir/StructureDefinition/usagecontext-group"), ) self.assertEqual( force_bytes(inst.useContext[1].extension[0].valueString), force_bytes("A") ) self.assertEqual( force_bytes(inst.useContext[1].valueCodeableConcept.text), force_bytes("Collecting Duct/Medullary Subtypes"), ) self.assertEqual( force_bytes(inst.useContext[2].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[2].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[2].extension[0].url), force_bytes("http://hl7.org/fhir/StructureDefinition/usagecontext-group"), ) self.assertEqual( force_bytes(inst.useContext[2].extension[0].valueString), force_bytes("A") ) self.assertEqual( force_bytes(inst.useContext[2].valueCodeableConcept.text), force_bytes("Kidney Cancer"), ) self.assertEqual( force_bytes(inst.useContext[3].code.code), force_bytes("treatmentSetting-or-diseaseStatus"), ) self.assertEqual( force_bytes(inst.useContext[3].code.system), force_bytes("http://example.org/fhir/CodeSystem/indications"), ) self.assertEqual( force_bytes(inst.useContext[3].extension[0].url), force_bytes("http://hl7.org/fhir/StructureDefinition/usagecontext-group"), ) self.assertEqual( force_bytes(inst.useContext[3].extension[0].valueString), force_bytes("B") ) self.assertEqual( force_bytes(inst.useContext[3].valueCodeableConcept.text), force_bytes("Relapsed"), ) self.assertEqual( force_bytes(inst.useContext[4].code.code), force_bytes("disease-or-histology"), ) self.assertEqual( force_bytes(inst.useContext[4].code.system), force_bytes("http://example.org/fhir/CodeSystem/indications"), ) self.assertEqual( force_bytes(inst.useContext[4].extension[0].url), force_bytes("http://hl7.org/fhir/StructureDefinition/usagecontext-group"), ) self.assertEqual( force_bytes(inst.useContext[4].extension[0].valueString), force_bytes("B") ) self.assertEqual( force_bytes(inst.useContext[4].valueCodeableConcept.text), force_bytes("Collecting Duct/Medullary Subtypes"), ) self.assertEqual( force_bytes(inst.useContext[5].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[5].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[5].extension[0].url), force_bytes("http://hl7.org/fhir/StructureDefinition/usagecontext-group"), ) self.assertEqual( force_bytes(inst.useContext[5].extension[0].valueString), force_bytes("B") ) self.assertEqual( force_bytes(inst.useContext[5].valueCodeableConcept.text), force_bytes( "Kidney Cancer – Collecting Duct/Medullary Subtypes - Metastatic" ), ) self.assertEqual(force_bytes(inst.version), force_bytes("1")) def testPlanDefinition2(self): inst = self.instantiate_from("plandefinition-options-example.json") self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition2(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition2(inst2) def implPlanDefinition2(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].id), force_bytes("medication-action-1") ) self.assertEqual( force_bytes(inst.action[0].action[0].title), force_bytes("Administer Medication 1"), ) self.assertEqual( force_bytes(inst.action[0].action[1].id), force_bytes("medication-action-2") ) self.assertEqual( force_bytes(inst.action[0].action[1].relatedAction[0].actionId), force_bytes("medication-action-1"), ) self.assertEqual( force_bytes(inst.action[0].action[1].relatedAction[0].offsetDuration.unit), force_bytes("h"), ) self.assertEqual( inst.action[0].action[1].relatedAction[0].offsetDuration.value, 1 ) self.assertEqual( force_bytes(inst.action[0].action[1].relatedAction[0].relationship), force_bytes("after-end"), ) self.assertEqual( force_bytes(inst.action[0].action[1].title), force_bytes("Administer Medication 2"), ) self.assertEqual( force_bytes(inst.action[0].groupingBehavior), force_bytes("logical-group") ) self.assertEqual( force_bytes(inst.action[0].selectionBehavior), force_bytes("all") ) self.assertEqual( force_bytes(inst.contained[0].id), force_bytes("activitydefinition-medicationrequest-1"), ) self.assertEqual( force_bytes(inst.contained[1].id), force_bytes("activitydefinition-medicationrequest-2"), ) self.assertEqual(force_bytes(inst.id), force_bytes("options-example")) self.assertEqual(force_bytes(inst.status), force_bytes("draft")) self.assertEqual( force_bytes(inst.text.div), force_bytes( '<div xmlns="http://www.w3.org/1999/xhtml">[Put rendering here]</div>' ), ) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("This example illustrates relationships between actions."), ) def testPlanDefinition3(self): inst = self.instantiate_from( "plandefinition-exclusive-breastfeeding-intervention-02.json" ) self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition3(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition3(inst2) def implPlanDefinition3(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].dynamicValue[0].expression), force_bytes("Communication Request to Provider"), ) self.assertEqual( force_bytes(inst.action[0].action[0].dynamicValue[0].path), force_bytes("/") ) self.assertEqual( force_bytes(inst.action[0].action[0].textEquivalent), force_bytes( "A Breastfeeding Readiness Assessment is recommended, please authorize or reject the order." ), ) self.assertEqual( force_bytes(inst.action[0].action[0].title), force_bytes("Notify the provider to sign the order."), ) self.assertEqual( force_bytes(inst.action[0].action[0].type.code), force_bytes("create") ) self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes("Should Notify Provider to Sign Assessment Order"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes( "Mother should be administered a breastfeeding readiness assessment." ), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].eventName), force_bytes("Admission"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[1].eventName), force_bytes("Birth"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[1].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[2].eventName), force_bytes("Infant Transfer to Recovery"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[2].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[3].eventName), force_bytes("Transfer to Post-Partum"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[3].type), force_bytes("named-event"), ) self.assertEqual(inst.date.date, FHIRDate("2015-03-08").date) self.assertEqual(inst.date.as_json(), "2015-03-08") self.assertEqual( force_bytes(inst.id), force_bytes("exclusive-breastfeeding-intervention-02") ) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("exclusive-breastfeeding-intervention-02"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual(force_bytes(inst.status), force_bytes("active")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Exclusive Breastfeeding Intervention-02"), ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Exclusive Breastfeeding") ) self.assertEqual(force_bytes(inst.version), force_bytes("1.0.0")) def testPlanDefinition4(self): inst = self.instantiate_from( "plandefinition-exclusive-breastfeeding-intervention-03.json" ) self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition4(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition4(inst2) def implPlanDefinition4(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].dynamicValue[0].expression), force_bytes("Communication Request to Charge Nurse"), ) self.assertEqual( force_bytes(inst.action[0].action[0].dynamicValue[0].path), force_bytes("/") ) self.assertEqual( force_bytes(inst.action[0].action[0].textEquivalent), force_bytes( "A Breastfeeding Readiness Assessment is recommended, please administer the assessment." ), ) self.assertEqual( force_bytes(inst.action[0].action[0].title), force_bytes("Notify the charge nurse to perform the assessment."), ) self.assertEqual( force_bytes(inst.action[0].action[0].type.code), force_bytes("create") ) self.assertEqual( force_bytes(inst.action[0].action[1].dynamicValue[0].expression), force_bytes("Communication Request to Bedside Nurse"), ) self.assertEqual( force_bytes(inst.action[0].action[1].dynamicValue[0].path), force_bytes("/") ) self.assertEqual( force_bytes(inst.action[0].action[1].textEquivalent), force_bytes( "A Breastfeeding Readiness Assessment is recommended, please administer the assessment." ), ) self.assertEqual( force_bytes(inst.action[0].action[1].title), force_bytes("Notify the bedside nurse to perform the assessment."), ) self.assertEqual( force_bytes(inst.action[0].action[1].type.code), force_bytes("create") ) self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes("Should Notify Nurse to Perform Assessment"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes( "Mother should be administered a breastfeeding readiness assessment." ), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].eventName), force_bytes("Admission"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[1].eventName), force_bytes("Birth"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[1].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[2].eventName), force_bytes("Infant Transfer to Recovery"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[2].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[3].eventName), force_bytes("Transfer to Post-Partum"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[3].type), force_bytes("named-event"), ) self.assertEqual(inst.date.date, FHIRDate("2015-03-08").date) self.assertEqual(inst.date.as_json(), "2015-03-08") self.assertEqual( force_bytes(inst.id), force_bytes("exclusive-breastfeeding-intervention-03") ) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("exclusive-breastfeeding-intervention-03"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual(force_bytes(inst.status), force_bytes("active")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Exclusive Breastfeeding Intervention-03"), ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Exclusive Breastfeeding") ) self.assertEqual(force_bytes(inst.version), force_bytes("1.0.0")) def testPlanDefinition5(self): inst = self.instantiate_from("plandefinition-protocol-example.json") self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition5(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition5(inst2) def implPlanDefinition5(self, inst): self.assertEqual( force_bytes(inst.action[0].cardinalityBehavior), force_bytes("single") ) self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes( "exists ([Condition: Obesity]) or not exists ([Observation: BMI] O where O.effectiveDateTime 2 years or less before Today())" ), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].condition[0].language), force_bytes("text/cql") ) self.assertEqual( force_bytes(inst.action[0].goalId[0]), force_bytes("reduce-bmi-ratio") ) self.assertEqual(force_bytes(inst.action[0].label), force_bytes("Measure BMI")) self.assertEqual( force_bytes(inst.action[0].requiredBehavior), force_bytes("must-unless-documented"), ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes("Measure, Weight, Height, Waist, Circumference; Calculate BMI"), ) self.assertEqual(force_bytes(inst.contained[0].id), force_bytes("procedure")) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[0].system), force_bytes("url"), ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[0].value), force_bytes("https://www.nhlbi.nih.gov/health-pro/guidelines"), ) self.assertEqual( force_bytes(inst.contributor[0].name), force_bytes("National Heart, Lung, and Blood Institute"), ) self.assertEqual(force_bytes(inst.contributor[0].type), force_bytes("author")) self.assertEqual( force_bytes(inst.goal[0].addresses[0].coding[0].code), force_bytes("414916001"), ) self.assertEqual( force_bytes(inst.goal[0].addresses[0].coding[0].display), force_bytes("Obesity (disorder)"), ) self.assertEqual( force_bytes(inst.goal[0].addresses[0].coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual( force_bytes(inst.goal[0].category.text), force_bytes("Treatment") ) self.assertEqual( force_bytes(inst.goal[0].description.text), force_bytes("Reduce BMI to below 25"), ) self.assertEqual( force_bytes(inst.goal[0].documentation[0].display), force_bytes("Evaluation and Treatment Strategy"), ) self.assertEqual( force_bytes(inst.goal[0].documentation[0].type), force_bytes("justification"), ) self.assertEqual( force_bytes(inst.goal[0].documentation[0].url), force_bytes( "https://www.nhlbi.nih.gov/health-pro/guidelines/current/obesity-guidelines/e_textbook/txgd/42.htm" ), ) self.assertEqual(force_bytes(inst.goal[0].id), force_bytes("reduce-bmi-ratio")) self.assertEqual( force_bytes(inst.goal[0].priority.text), force_bytes("medium-priority") ) self.assertEqual( force_bytes(inst.goal[0].start.text), force_bytes("When the patient's BMI Ratio is at or above 25"), ) self.assertEqual( force_bytes(inst.goal[0].target[0].detailRange.high.unit), force_bytes("kg/m2"), ) self.assertEqual(inst.goal[0].target[0].detailRange.high.value, 24.9) self.assertEqual(force_bytes(inst.goal[0].target[0].due.unit), force_bytes("a")) self.assertEqual(inst.goal[0].target[0].due.value, 1) self.assertEqual( force_bytes(inst.goal[0].target[0].measure.coding[0].code), force_bytes("39156-5"), ) self.assertEqual( force_bytes(inst.goal[0].target[0].measure.coding[0].display), force_bytes("Body mass index (BMI) [Ratio]"), ) self.assertEqual( force_bytes(inst.goal[0].target[0].measure.coding[0].system), force_bytes("http://loinc.org"), ) self.assertEqual(force_bytes(inst.id), force_bytes("protocol-example")) self.assertEqual( force_bytes(inst.identifier[0].system), force_bytes("http://acme.org") ) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("example-1") ) self.assertEqual( force_bytes(inst.purpose), force_bytes( "Example of A medical algorithm for assessment and treatment of overweight and obesity" ), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].display), force_bytes("Overweight and Obesity Treatment Guidelines"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual( force_bytes(inst.relatedArtifact[0].url), force_bytes( "http://www.nhlbi.nih.gov/health-pro/guidelines/current/obesity-guidelines/e_textbook/txgd/algorthm/algorthm.htm" ), ) self.assertEqual(force_bytes(inst.status), force_bytes("draft")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Obesity Assessment Protocol") ) self.assertEqual(force_bytes(inst.type.coding[0].code), force_bytes("protocol")) self.assertEqual( force_bytes(inst.useContext[0].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.coding[0].code), force_bytes("414916001"), ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.coding[0].display), force_bytes("Obesity (disorder)"), ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) def testPlanDefinition6(self): inst = self.instantiate_from("plandefinition-example.json") self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition6(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition6(inst2) def implPlanDefinition6(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[0].expression), force_bytes("Now()"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[0].path), force_bytes("timing.event"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[1].expression), force_bytes( "Code '261QM0850X' from SuicideRiskLogic.\"NUCC Provider Taxonomy\" display 'Adult Mental Health'" ), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[1].path), force_bytes("specialty"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[2].expression), force_bytes("SuicideRiskLogic.ReferralRequestFulfillmentTime"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[2].path), force_bytes("occurrenceDateTime"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[3].expression), force_bytes("SuicideRiskLogic.Patient"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[3].path), force_bytes("subject"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[4].expression), force_bytes("SuicideRiskLogic.Practitioner"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[4].path), force_bytes("requester.agent"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[5].expression), force_bytes("SuicideRiskLogic.RiskAssessmentScore"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[5].path), force_bytes("reasonCode"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[6].expression), force_bytes("SuicideRiskLogic.RiskAssessment"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].dynamicValue[6].path), force_bytes("reasonReference"), ) self.assertEqual( force_bytes(inst.action[0].action[0].action[0].textEquivalent), force_bytes( "Refer to outpatient mental health program for evaluation and treatment of mental health conditions now" ), ) self.assertEqual( force_bytes(inst.action[0].action[0].groupingBehavior), force_bytes("logical-group"), ) self.assertEqual( force_bytes(inst.action[0].action[0].selectionBehavior), force_bytes("any") ) self.assertEqual( force_bytes(inst.action[0].action[0].title), force_bytes("Consults and Referrals"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[0] .expression ), force_bytes("'draft'"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[0] .path ), force_bytes("status"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[1] .expression ), force_bytes("SuicideRiskLogic.Patient"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[1] .path ), force_bytes("patient"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[2] .expression ), force_bytes("SuicideRiskLogic.Practitioner"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[2] .path ), force_bytes("prescriber"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[3] .expression ), force_bytes("SuicideRiskLogic.RiskAssessmentScore"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[3] .path ), force_bytes("reasonCode"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[4] .expression ), force_bytes("SuicideRiskLogic.RiskAssessment"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .action[0] .dynamicValue[4] .path ), force_bytes("reasonReference"), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].action[0].action[0].textEquivalent ), force_bytes( "citalopram 20 mg tablet 1 tablet oral 1 time daily now (30 table; 3 refills)" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].action[0].action[1].textEquivalent ), force_bytes( "escitalopram 10 mg tablet 1 tablet oral 1 time daily now (30 tablet; 3 refills)" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].action[0].action[2].textEquivalent ), force_bytes( "fluoxetine 20 mg capsule 1 capsule oral 1 time daily now (30 tablet; 3 refills)" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].action[0].action[3].textEquivalent ), force_bytes( "paroxetine 20 mg tablet 1 tablet oral 1 time daily now (30 tablet; 3 refills)" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].action[0].action[4].textEquivalent ), force_bytes( "sertraline 50 mg tablet 1 tablet oral 1 time daily now (30 tablet; 3 refills)" ), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .documentation[0] .document.contentType ), force_bytes("text/html"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .documentation[0] .document.title ), force_bytes( "National Library of Medicine. DailyMed website. CITALOPRAM- citalopram hydrobromide tablet, film coated." ), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .action[0] .documentation[0] .document.url ), force_bytes( "http://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=6daeb45c-451d-b135-bf8f-2d6dff4b6b01" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].action[0].documentation[0].type ), force_bytes("citation"), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].action[0].groupingBehavior), force_bytes("logical-group"), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].action[0].selectionBehavior), force_bytes("at-most-one"), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].action[0].title), force_bytes( "Selective Serotonin Reuptake Inhibitors (Choose a mazimum of one or document reasons for exception)" ), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].action[1].textEquivalent), force_bytes( "Dopamine Norepinephrine Reuptake Inhibitors (Choose a maximum of one or document reasons for exception)" ), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].action[2].textEquivalent), force_bytes( "Serotonin Norepinephrine Reuptake Inhibitors (Choose a maximum of one or doument reasons for exception)" ), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].action[3].textEquivalent), force_bytes( "Norepinephrine-Serotonin Modulators (Choose a maximum of one or document reasons for exception)" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].documentation[0].document.contentType ), force_bytes("text/html"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .documentation[0] .document.extension[0] .url ), force_bytes( "http://hl7.org/fhir/StructureDefinition/cqif-qualityOfEvidence" ), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .documentation[0] .document.extension[0] .valueCodeableConcept.coding[0] .code ), force_bytes("high"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .documentation[0] .document.extension[0] .valueCodeableConcept.coding[0] .system ), force_bytes("http://hl7.org/fhir/evidence-quality"), ) self.assertEqual( force_bytes( inst.action[0] .action[1] .action[0] .documentation[0] .document.extension[0] .valueCodeableConcept.text ), force_bytes("High Quality"), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].documentation[0].document.title ), force_bytes( "Practice Guideline for the Treatment of Patients with Major Depressive Disorder" ), ) self.assertEqual( force_bytes( inst.action[0].action[1].action[0].documentation[0].document.url ), force_bytes( "http://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf" ), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].documentation[0].type), force_bytes("citation"), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].groupingBehavior), force_bytes("logical-group"), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].selectionBehavior), force_bytes("at-most-one"), ) self.assertEqual( force_bytes(inst.action[0].action[1].action[0].title), force_bytes("First-Line Antidepressants"), ) self.assertEqual( force_bytes(inst.action[0].action[1].groupingBehavior), force_bytes("logical-group"), ) self.assertEqual( force_bytes(inst.action[0].action[1].selectionBehavior), force_bytes("at-most-one"), ) self.assertEqual( force_bytes(inst.action[0].action[1].title), force_bytes("Medications") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes("Suicide Risk Assessment and Outpatient Management"), ) self.assertEqual(inst.approvalDate.date, FHIRDate("2016-03-12").date) self.assertEqual(inst.approvalDate.as_json(), "2016-03-12") self.assertEqual( force_bytes(inst.contact[0].telecom[0].system), force_bytes("phone") ) self.assertEqual( force_bytes(inst.contact[0].telecom[0].use), force_bytes("work") ) self.assertEqual( force_bytes(inst.contact[0].telecom[0].value), force_bytes("415-362-4007") ) self.assertEqual( force_bytes(inst.contact[0].telecom[1].system), force_bytes("email") ) self.assertEqual( force_bytes(inst.contact[0].telecom[1].use), force_bytes("work") ) self.assertEqual( force_bytes(inst.contact[0].telecom[1].value), force_bytes("info@motivemi.com"), ) self.assertEqual( force_bytes(inst.contained[0].id), force_bytes("referralToMentalHealthCare") ) self.assertEqual( force_bytes(inst.contained[1].id), force_bytes("citalopramPrescription") ) self.assertEqual( force_bytes(inst.contained[2].id), force_bytes("citalopramMedication") ) self.assertEqual( force_bytes(inst.contained[3].id), force_bytes("citalopramSubstance") ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[0].system), force_bytes("phone"), ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[0].use), force_bytes("work"), ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[0].value), force_bytes("415-362-4007"), ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[1].system), force_bytes("email"), ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[1].use), force_bytes("work"), ) self.assertEqual( force_bytes(inst.contributor[0].contact[0].telecom[1].value), force_bytes("info@motivemi.com"), ) self.assertEqual( force_bytes(inst.contributor[0].name), force_bytes("Motive Medical Intelligence"), ) self.assertEqual(force_bytes(inst.contributor[0].type), force_bytes("author")) self.assertEqual( force_bytes(inst.copyright), force_bytes( "© Copyright 2016 Motive Medical Intelligence. All rights reserved." ), ) self.assertEqual(inst.date.date, FHIRDate("2015-08-15").date) self.assertEqual(inst.date.as_json(), "2015-08-15") self.assertEqual( force_bytes(inst.description), force_bytes( "Orders to be applied to a patient characterized as low suicide risk." ), ) self.assertEqual(inst.effectivePeriod.end.date, FHIRDate("2017-12-31").date) self.assertEqual(inst.effectivePeriod.end.as_json(), "2017-12-31") self.assertEqual(inst.effectivePeriod.start.date, FHIRDate("2016-01-01").date) self.assertEqual(inst.effectivePeriod.start.as_json(), "2016-01-01") self.assertTrue(inst.experimental) self.assertEqual( force_bytes(inst.id), force_bytes("low-suicide-risk-order-set") ) self.assertEqual( force_bytes(inst.identifier[0].system), force_bytes("http://motivemi.com/artifacts"), ) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("mmi:low-suicide-risk-order-set"), ) self.assertEqual( force_bytes(inst.jurisdiction[0].coding[0].code), force_bytes("US") ) self.assertEqual( force_bytes(inst.jurisdiction[0].coding[0].system), force_bytes("urn:iso:std:iso:3166"), ) self.assertEqual(inst.lastReviewDate.date, FHIRDate("2016-08-15").date) self.assertEqual(inst.lastReviewDate.as_json(), "2016-08-15") self.assertEqual(force_bytes(inst.name), force_bytes("LowSuicideRiskOrderSet")) self.assertEqual( force_bytes(inst.publisher), force_bytes("Motive Medical Intelligence") ) self.assertEqual( force_bytes(inst.purpose), force_bytes( "This order set helps ensure consistent application of appropriate orders for the care of low suicide risk patients." ), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].display), force_bytes( "Practice Guideline for the Treatment of Patients with Major Depressive Disorder" ), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual( force_bytes(inst.relatedArtifact[0].url), force_bytes( "http://psychiatryonline.org/pb/assets/raw/sitewide/practice_guidelines/guidelines/mdd.pdf" ), ) self.assertEqual( force_bytes(inst.relatedArtifact[1].type), force_bytes("composed-of") ) self.assertEqual( force_bytes(inst.relatedArtifact[2].type), force_bytes("composed-of") ) self.assertEqual(force_bytes(inst.status), force_bytes("active")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Low Suicide Risk Order Set") ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Suicide risk assessment") ) self.assertEqual( force_bytes(inst.url), force_bytes( "http://motivemi.com/artifacts/PlanDefinition/low-suicide-risk-order-set" ), ) self.assertEqual( force_bytes(inst.usage), force_bytes( "This order set should be applied after assessing a patient for suicide risk, when the findings of that assessment indicate the patient has low suicide risk." ), ) self.assertEqual(force_bytes(inst.useContext[0].code.code), force_bytes("age")) self.assertEqual( force_bytes(inst.useContext[0].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.coding[0].code), force_bytes("D000328"), ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.coding[0].display), force_bytes("Adult"), ) self.assertEqual( force_bytes(inst.useContext[0].valueCodeableConcept.coding[0].system), force_bytes("https://meshb.nlm.nih.gov"), ) self.assertEqual( force_bytes(inst.useContext[1].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[1].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[1].valueCodeableConcept.coding[0].code), force_bytes("87512008"), ) self.assertEqual( force_bytes(inst.useContext[1].valueCodeableConcept.coding[0].display), force_bytes("Mild major depression"), ) self.assertEqual( force_bytes(inst.useContext[1].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual( force_bytes(inst.useContext[2].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[2].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[2].valueCodeableConcept.coding[0].code), force_bytes("40379007"), ) self.assertEqual( force_bytes(inst.useContext[2].valueCodeableConcept.coding[0].display), force_bytes("Major depression, recurrent, mild"), ) self.assertEqual( force_bytes(inst.useContext[2].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual( force_bytes(inst.useContext[3].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[3].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[3].valueCodeableConcept.coding[0].code), force_bytes("394687007"), ) self.assertEqual( force_bytes(inst.useContext[3].valueCodeableConcept.coding[0].display), force_bytes("Low suicide risk"), ) self.assertEqual( force_bytes(inst.useContext[3].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual( force_bytes(inst.useContext[4].code.code), force_bytes("focus") ) self.assertEqual( force_bytes(inst.useContext[4].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[4].valueCodeableConcept.coding[0].code), force_bytes("225337009"), ) self.assertEqual( force_bytes(inst.useContext[4].valueCodeableConcept.coding[0].display), force_bytes("Suicide risk assessment"), ) self.assertEqual( force_bytes(inst.useContext[4].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual(force_bytes(inst.useContext[5].code.code), force_bytes("user")) self.assertEqual( force_bytes(inst.useContext[5].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[5].valueCodeableConcept.coding[0].code), force_bytes("309343006"), ) self.assertEqual( force_bytes(inst.useContext[5].valueCodeableConcept.coding[0].display), force_bytes("Physician"), ) self.assertEqual( force_bytes(inst.useContext[5].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual( force_bytes(inst.useContext[6].code.code), force_bytes("venue") ) self.assertEqual( force_bytes(inst.useContext[6].code.system), force_bytes("http://hl7.org/fhir/usage-context-type"), ) self.assertEqual( force_bytes(inst.useContext[6].valueCodeableConcept.coding[0].code), force_bytes("440655000"), ) self.assertEqual( force_bytes(inst.useContext[6].valueCodeableConcept.coding[0].display), force_bytes("Outpatient environment"), ) self.assertEqual( force_bytes(inst.useContext[6].valueCodeableConcept.coding[0].system), force_bytes("http://snomed.info/sct"), ) self.assertEqual(force_bytes(inst.version), force_bytes("1.0.0")) def testPlanDefinition7(self): inst = self.instantiate_from( "plandefinition-exclusive-breastfeeding-intervention-04.json" ) self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition7(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition7(inst2) def implPlanDefinition7(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].dynamicValue[0].expression), force_bytes("Create Lactation Consult Request"), ) self.assertEqual( force_bytes(inst.action[0].action[0].dynamicValue[0].path), force_bytes("/") ) self.assertEqual( force_bytes(inst.action[0].action[0].textEquivalent), force_bytes("Create a lactation consult request"), ) self.assertEqual( force_bytes(inst.action[0].action[0].title), force_bytes("Create a lactation consult request."), ) self.assertEqual( force_bytes(inst.action[0].action[0].type.code), force_bytes("create") ) self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes("Should Create Lactation Consult"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes( "Mother should be referred to a lactation specialist for consultation." ), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].eventName), force_bytes("Admission"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[1].eventName), force_bytes("Birth"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[1].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[2].eventName), force_bytes("Infant Transfer to Recovery"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[2].type), force_bytes("named-event"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[3].eventName), force_bytes("Transfer to Post-Partum"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[3].type), force_bytes("named-event"), ) self.assertEqual(inst.date.date, FHIRDate("2015-03-08").date) self.assertEqual(inst.date.as_json(), "2015-03-08") self.assertEqual( force_bytes(inst.description), force_bytes( "Exclusive breastfeeding intervention intended to improve outcomes for exclusive breastmilk feeding of newborns by creating a lactation consult for the mother if appropriate." ), ) self.assertEqual( force_bytes(inst.id), force_bytes("exclusive-breastfeeding-intervention-04") ) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("exclusive-breastfeeding-intervention-04"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual(force_bytes(inst.status), force_bytes("active")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Exclusive Breastfeeding Intervention-04"), ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Exclusive Breastfeeding") ) self.assertEqual(force_bytes(inst.version), force_bytes("1.0.0")) def testPlanDefinition8(self): inst = self.instantiate_from("plandefinition-predecessor-example.json") self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition8(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition8(inst2) def implPlanDefinition8(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].condition[0].expression), force_bytes("Should Administer Zika Virus Exposure Assessment"), ) self.assertEqual( force_bytes(inst.action[0].action[0].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[1].condition[0].expression), force_bytes("Should Order Serum + Urine rRT-PCR Test"), ) self.assertEqual( force_bytes(inst.action[0].action[1].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[2].condition[0].expression), force_bytes("Should Order Serum Zika Virus IgM + Dengue Virus IgM"), ) self.assertEqual( force_bytes(inst.action[0].action[2].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[3].condition[0].expression), force_bytes("Should Consider IgM Antibody Testing"), ) self.assertEqual( force_bytes(inst.action[0].action[3].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[4].condition[0].expression), force_bytes("Should Provide Mosquito Prevention and Contraception Advice"), ) self.assertEqual( force_bytes(inst.action[0].action[4].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes("Is Patient Pregnant"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes("Zika Virus Assessment") ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].eventName), force_bytes("patient-view"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].type), force_bytes("named-event"), ) self.assertEqual(inst.date.date, FHIRDate("2016-11-14").date) self.assertEqual(inst.date.as_json(), "2016-11-14") self.assertEqual( force_bytes(inst.description), force_bytes( "Zika Virus Management intervention describing the CDC Guidelines for Zika Virus Reporting and Management." ), ) self.assertEqual( force_bytes(inst.id), force_bytes("zika-virus-intervention-initial") ) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("zika-virus-intervention"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual( force_bytes(inst.relatedArtifact[0].url), force_bytes( "https://www.cdc.gov/mmwr/volumes/65/wr/mm6539e1.htm?s_cid=mm6539e1_w" ), ) self.assertEqual( force_bytes(inst.relatedArtifact[1].type), force_bytes("successor") ) self.assertEqual(force_bytes(inst.status), force_bytes("active")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Example Zika Virus Intervention") ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Zika Virus Management") ) self.assertEqual( force_bytes(inst.url), force_bytes("http://example.org/PlanDefinition/zika-virus-intervention"), ) self.assertEqual(force_bytes(inst.version), force_bytes("1.0.0")) def testPlanDefinition9(self): inst = self.instantiate_from("plandefinition-zika-virus-intervention.json") self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition9(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition9(inst2) def implPlanDefinition9(self, inst): self.assertEqual( force_bytes(inst.action[0].action[0].condition[0].expression), force_bytes("Should Administer Zika Virus Exposure Assessment"), ) self.assertEqual( force_bytes(inst.action[0].action[0].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[1].condition[0].expression), force_bytes("Should Order Serum + Urine rRT-PCR Test"), ) self.assertEqual( force_bytes(inst.action[0].action[1].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[2].condition[0].expression), force_bytes("Should Order Serum Zika Virus IgM + Dengue Virus IgM"), ) self.assertEqual( force_bytes(inst.action[0].action[2].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[3].condition[0].expression), force_bytes("Should Consider IgM Antibody Testing"), ) self.assertEqual( force_bytes(inst.action[0].action[3].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].action[4].condition[0].expression), force_bytes("Should Provide Mosquito Prevention and Contraception Advice"), ) self.assertEqual( force_bytes(inst.action[0].action[4].condition[0].kind), force_bytes("applicability"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes("Is Patient Pregnant"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes("Zika Virus Assessment") ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].eventName), force_bytes("patient-view"), ) self.assertEqual( force_bytes(inst.action[0].triggerDefinition[0].type), force_bytes("named-event"), ) self.assertEqual(inst.date.date, FHIRDate("2017-01-12").date) self.assertEqual(inst.date.as_json(), "2017-01-12") self.assertEqual( force_bytes(inst.description), force_bytes( "Zika Virus Management intervention describing the CDC Guidelines for Zika Virus Reporting and Management." ), ) self.assertEqual(force_bytes(inst.id), force_bytes("zika-virus-intervention")) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("zika-virus-intervention"), ) self.assertEqual( force_bytes(inst.relatedArtifact[0].type), force_bytes("derived-from") ) self.assertEqual( force_bytes(inst.relatedArtifact[0].url), force_bytes( "https://www.cdc.gov/mmwr/volumes/65/wr/mm6539e1.htm?s_cid=mm6539e1_w" ), ) self.assertEqual( force_bytes(inst.relatedArtifact[1].type), force_bytes("predecessor") ) self.assertEqual(force_bytes(inst.status), force_bytes("active")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Example Zika Virus Intervention") ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Zika Virus Management") ) self.assertEqual( force_bytes(inst.url), force_bytes("http://example.org/PlanDefinition/zika-virus-intervention"), ) self.assertEqual(force_bytes(inst.version), force_bytes("2.0.0")) def testPlanDefinition10(self): inst = self.instantiate_from( "plandefinition-chlamydia-screening-intervention.json" ) self.assertIsNotNone(inst, "Must have instantiated a PlanDefinition instance") self.implPlanDefinition10(inst) js = inst.as_json() self.assertEqual("PlanDefinition", js["resourceType"]) inst2 = plandefinition.PlanDefinition(js) self.implPlanDefinition10(inst2) def implPlanDefinition10(self, inst): self.assertEqual( force_bytes(inst.action[0].condition[0].expression), force_bytes("NoScreening"), ) self.assertEqual( force_bytes(inst.action[0].condition[0].kind), force_bytes("applicability") ) self.assertEqual( force_bytes(inst.action[0].dynamicValue[0].expression), force_bytes("ChlamydiaScreeningRequest"), ) self.assertEqual( force_bytes(inst.action[0].dynamicValue[0].path), force_bytes("~") ) self.assertEqual( force_bytes(inst.action[0].title), force_bytes( "Patient has not had chlamydia screening within the recommended timeframe..." ), ) self.assertEqual(inst.date.date, FHIRDate("2015-07-22").date) self.assertEqual(inst.date.as_json(), "2015-07-22") self.assertEqual( force_bytes(inst.description), force_bytes("Chlamydia Screening CDS Example Using Common"), ) self.assertEqual( force_bytes(inst.id), force_bytes("chlamydia-screening-intervention") ) self.assertEqual(force_bytes(inst.identifier[0].use), force_bytes("official")) self.assertEqual( force_bytes(inst.identifier[0].value), force_bytes("ChlamydiaScreening_CDS_UsingCommon"), ) self.assertEqual(force_bytes(inst.status), force_bytes("draft")) self.assertEqual(force_bytes(inst.text.status), force_bytes("generated")) self.assertEqual( force_bytes(inst.title), force_bytes("Chalmydia Screening CDS Example Using Common"), ) self.assertEqual( force_bytes(inst.topic[0].text), force_bytes("Chlamydia Screeening") ) self.assertEqual(force_bytes(inst.version), force_bytes("2.0.0"))

38.78512

191

0.576041

7,510

74,545

5.601598

0.08229

0.196586

0.196349

0.245436

0.883783

0.86857

0.849054

0.826329

0.803009

0.773201

0

0.028669

0.301871

74,545

1,921

192

38.80531

0.77964

0.002294

0

0.576145

0

0.005857

0.166716

0.020735

0

0.250266

1

0.011182

false

0

0.00426

0

0.016507

0

null

0

1

0

null

0

8

09f6b804d27a26cc465a31702f0cb60abd7a7de6

80

py

Python

Chapter02/checkargs.py

Mehdi-Soltanmoradi/Python-Network-Programming

984bc9cbb0d42a86ec2076d72a6b9ef82fd3ada0

[ "MIT" ]

36

2019-01-28T07:19:09.000Z

2022-01-13T04:44:38.000Z

Chapter02/checkargs.py

larisk8ter/Practical-Network-Automation

fa0e7e81869162fe578cf85166fdccca2acdd418

[ "MIT" ]

null

Chapter02/checkargs.py

larisk8ter/Practical-Network-Automation

fa0e7e81869162fe578cf85166fdccca2acdd418

[ "MIT" ]

37

2019-01-26T09:50:19.000Z

2022-02-28T22:16:36.000Z

import sys print ("Total output is ") print (int(sys.argv[1])+int(sys.argv[2]))

20

41

0.675

15

80

3.6

0.666667

0.222222

0.37037

0

0.028169

0.1125

80

3

42

26.666667

0.732394

0

0.2

0

1

0

true

0

0.333333

0

0.333333

0.666667

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

09fe489efa28b32f1c8a145b061bded7329ea938

783

py

Python

tests/integration/test_sec.py

mhadam/holdingsparser

c2f58acf6414e417ff435bb01ecbb8c37be50d77

[ "MIT" ]

9

2018-04-23T23:35:21.000Z

2021-11-03T04:34:09.000Z

tests/integration/test_sec.py

mhadam/holdingsparser

c2f58acf6414e417ff435bb01ecbb8c37be50d77

[ "MIT" ]

2

2021-05-06T14:38:14.000Z

2021-05-08T01:17:33.000Z

tests/integration/test_sec.py

mhadam/holdingsparser

c2f58acf6414e417ff435bb01ecbb8c37be50d77

[ "MIT" ]

4

2018-08-18T18:09:06.000Z

2021-06-21T02:02:07.000Z

from holdingsparser.sec import get_holdings_document_url def test_get_holdings_document_url_new(): documents_url = "https://www.sec.gov/Archives/edgar/data/1166559/000110465921021959/0001104659-21-021959-index.htm" result = get_holdings_document_url(documents_url) expected = "https://www.sec.gov/Archives/edgar/data/1166559/000110465921021959/a21-6498_1informationtable.xml" assert result == expected def test_get_holdings_document_url(): documents_url = "https://www.sec.gov/Archives/edgar/data/1166559/000110465921021959/0001104659-21-021959-index.htm" result = get_holdings_document_url(documents_url) expected = "https://www.sec.gov/Archives/edgar/data/1166559/000110465921021959/a21-6498_1informationtable.xml" assert result == expected

39.15

119

0.796935

101

783

5.940594

0.316832

0.091667

0.158333

0.183333

0.913333

0.816667

0

0.211566

0.094508

783

19

120

41.210526

0.634697

0

0.727273

0

0.363636

0.49553

0

0.181818

1

0.181818

false

0

0.090909

0

0.272727

0

null

0

1

0

1

0

1

0

1

0

null

0

10

61ce356895da46963f90bea4da737f5968938b7b

1,802

py

Python

dpm/criterion/adversarial_loss/gan_loss.py

nextBillyonair/DPM

840ffaafe15c208b200b74094ffa8fe493b4c975

[ "MIT" ]

1

2021-07-20T14:02:55.000Z

dpm/criterion/adversarial_loss/gan_loss.py

nextBillyonair/DPM

840ffaafe15c208b200b74094ffa8fe493b4c975

[ "MIT" ]

null

dpm/criterion/adversarial_loss/gan_loss.py

nextBillyonair/DPM

840ffaafe15c208b200b74094ffa8fe493b4c975

[ "MIT" ]

null

from .adversarial_loss import AdversarialLoss from torch.nn import BCEWithLogitsLoss, MSELoss import torch # Also NSGAN class GANLoss(AdversarialLoss): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.bce_loss = BCEWithLogitsLoss() def discriminator_loss(self, p_values, q_values): p_loss = self.bce_loss(p_values, torch.ones_like(p_values)) q_loss = self.bce_loss(q_values, torch.zeros_like(q_values)) return p_loss + q_loss def generator_loss(self, q_values): return self.bce_loss(q_values, torch.ones_like(q_values)) class MMGANLoss(AdversarialLoss): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.bce_loss = BCEWithLogitsLoss() def discriminator_loss(self, p_values, q_values): p_loss = self.bce_loss(p_values, torch.ones_like(p_values)) q_loss = self.bce_loss(q_values, torch.zeros_like(q_values)) return p_loss + q_loss def generator_loss(self, q_values): return -self.bce_loss(q_values, torch.zeros_like(q_values)) class WGANLoss(AdversarialLoss): def discriminator_loss(self, p_values, q_values): return p_values.mean() - q_values.mean() def generator_loss(self, q_values): return q_values.mean() class LSGANLoss(AdversarialLoss): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.mse_loss = MSELoss() def discriminator_loss(self, p_values, q_values): p_loss = self.mse_loss(p_values, torch.ones_like(p_values)) q_loss = self.mse_loss(q_values, torch.zeros_like(q_values)) return p_loss + q_loss def generator_loss(self, q_values): return self.mse_loss(q_values, torch.ones_like(q_values))

31.068966

68

0.695893

253

1,802

4.565217

0.134387

0.133333

0.07619

0.083117

0.805195

0.8

0.771429

0.698701

0

0.194229

1,802

57

69

31.614035

0.795455

0.005549

0

0.605263

0

1

0.289474

false

0

0.078947

0.131579

0.684211

0

null

0

1

0

1

0

null

0

1

0

1

0

8

feec0ac10deeb4539d48ca91a99bef04691e5437

1,376

py

Python

ika_web/app/test/test_endpoints.py

Harisonm/ika

243ceab532007ee4fb05b205e1125fab5d3d325b

[ "Apache-2.0" ]

6

2020-11-17T19:41:26.000Z

2021-01-13T14:55:56.000Z

ika_web/app/test/test_endpoints.py

Harisonm/ika

243ceab532007ee4fb05b205e1125fab5d3d325b

[ "Apache-2.0" ]

3

2020-11-16T19:51:17.000Z

2020-11-16T19:51:36.000Z

ika_web/app/test/test_endpoints.py

Harisonm/Ika

243ceab532007ee4fb05b205e1125fab5d3d325b

[ "Apache-2.0" ]

null

# import os # import requests # def test_credentials_test(api_v1_host): # endpoint = os.path.join(api_v1_host, 'credentials', 'test') # response = requests.get(endpoint) # assert response.status_code == 200 # json = response.json() # assert 'msg' in json # assert json['msg'] == "I'm the test endpoint from credentials." # def test_blueprint_y_test(api_v1_host): # endpoint = os.path.join(api_v1_host, 'path_for_blueprint_y', 'test') # response = requests.get(endpoint) # assert response.status_code == 200 # json = response.json() # assert 'msg' in json # assert json['msg'] == "I'm the test endpoint from blueprint_y." # def test_blueprint_x_plus(api_v1_host): # endpoint = os.path.join(api_v1_host, 'path_for_blueprint_x', 'plus') # payload = {'number': 5} # response = requests.post(endpoint, json=payload) # assert response.status_code == 200 # json = response.json() # assert 'msg' in json # assert json['msg'] == "Your result is: '10'" # def test_blueprint_x_minus(api_v1_host): # endpoint = os.path.join(api_v1_host, 'path_for_blueprint_y', 'minus') # payload = {'number': 1000} # response = requests.post(endpoint, json=payload) # assert response.status_code == 200 # json = response.json() # assert 'msg' in json # assert json['msg'] == "Your result is: '0'"

38.222222

75

0.66061

189

1,376

4.592593

0.216931

0.046083

0.082949

0.078341

0.797235

0

0.025294

0.195494

1,376

36

76

38.222222

0.758808

0.950581

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

1

0

null

0

1

0

7

28bf7455f1f00cf8a2e2c5779a408dca3b607561

171

py

Python

katas/kyu_7/all_unique.py

the-zebulan/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

40

2016-03-09T12:26:20.000Z

2022-03-23T08:44:51.000Z

katas/kyu_7/all_unique.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

null

katas/kyu_7/all_unique.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

36

2016-11-07T19:59:58.000Z

2022-03-31T11:18:27.000Z

from collections import Counter def has_unique_chars(s): return Counter(s).most_common(1)[0][1] == 1 # def has_unique_chars(s): # return len(s) == len(set(s))

17.1

47

0.666667

29

171

3.758621

0.551724

0.110092

0.220183

0.311927

0.440367

0

0.028369

0.175439

171

9

48

19

0.744681

0.333333

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

28e94a85f2ee42d44587a1a08b3845f9045fb7b2

3,249

py

Python

CursoemVideoPython/Desafio 33.py

Beebruna/Python

bdbe10ea76acca1b417f5960db0aae8be44e0af3

[ "MIT" ]

null

CursoemVideoPython/Desafio 33.py

Beebruna/Python

bdbe10ea76acca1b417f5960db0aae8be44e0af3

[ "MIT" ]

null

CursoemVideoPython/Desafio 33.py

Beebruna/Python

bdbe10ea76acca1b417f5960db0aae8be44e0af3

[ "MIT" ]

null

''' Faça um programa que leia três números e mostre qual é o maior e qual é o menor. ''' num1 = int(input('Digite o primeiro número: ')) num2 = int(input('Digite o segundo número: ')) num3 = int(input('Digite o terceiro número: ')) ''' if num1 == num2 and num1 == num3 and num2 == num3: print('\nOs números são todos iguais!') else: if num1 == num2 and num1 > num3: print(f'\nO número {num1} é o maior de todos!') print(f'O número {num3} é o menor de todos!') else: if num1 == num2 and num1 < num3: print(f'\nO número {num3} é o maior de todos!') print(f'O número {num1} é o menor de todos!') else: if num1 == num3 and num1 > num2: print(f'\nO número {num1} é o maior de todos!') print(f'O número {num2} é o menor de todos!') else: if num1 == num3 and num1 < num2: print(f'\nO número {num2} é o maior de todos!') print(f'O número {num1} é o menor de todos!') else: if num2 == num3 and num2 > num1: print(f'\nO número {num2} é o maior de todos!') print(f'O número {num1} é o menor de todos!') else: if num2 == num3 and num2 < num1: print(f'\nO número {num1} é o maior de todos!') print(f'O número {num2} é o menor de todos!') else: if num1 > num2 and num1 > num3: print(f'\nO número {num1} é o maior de todos!') if num2 < num3: print(f'O número {num2} é o menor de todos!') else: print(f'O número {num3} é o menor de todos!') else: if num2 > num1 and num2 > num3: print(f'\nO número {num2} é o maior de todos!') if num1 < num3: print(f'O número {num1} é o menor de todos!') else: print(f'O número {num3} é o menor de todos!') else: print(f'\nO número {num3} é o maior de todos!') if num1 < num2: print(f'O número {num1} é o menor de todos!') else: print(f'O número {num2} é o menor de todos!') ''' #Correção if num1 == num2 and num1 == num3 and num2 == num3: print('\nOs números são todos iguais!') else: menor = num1 if num2 < num1 and num2 < num3: menor = num2 else: if num3 < num1 and num3 < num2: menor = num3 maior = num1 if num2 > num1 and num2 > num3: maior = num2 else: if num3 > num1 and num3 > num2: maior = num3 print(f'\n{menor} é o menor número.') print(f'{maior} é o maior número.')

39.621951

85

0.429363

403

3,249

3.461538

0.091811

0.035842

0.070251

0.111828

0.81147

0.805735

0.793548

0.749104

0.70466

0

0.056504

0.47707

3,249

81

86

40.111111

0.764567

0.027393

0

0.15

0

0.251185

0

0.271605

0

1

0

false

0

0.15

0

null

0

1

0

null

0

1

0

7

e9361a6466e1f10368eca262f0fbe84a0a13ac8e

18,425

py

Python

train_semisupervised/models.py

zdx3578/self-driving-truck

0d6870ea8d00eb5daa89deee2ce0b8fe4d04783b

[ "MIT" ]

373

2017-06-02T22:32:15.000Z

2022-03-27T12:23:03.000Z

train_semisupervised/models.py

zdx3578/self-driving-truck

0d6870ea8d00eb5daa89deee2ce0b8fe4d04783b

[ "MIT" ]

10

2017-07-19T12:18:30.000Z

2020-10-07T23:08:58.000Z

train_semisupervised/models.py

Bill-ME/self-driving-truck

0d6870ea8d00eb5daa89deee2ce0b8fe4d04783b

[ "MIT" ]

106

2017-06-08T05:12:58.000Z

2022-03-30T12:37:01.000Z

from __future__ import print_function, division import sys import os sys.path.append(os.path.join(os.path.dirname(__file__), '..')) import train from lib import actions from lib.util import to_cuda, to_variable from config import Config import torch import torch.nn as nn import torch.nn.functional as F from torch.autograd.function import InplaceFunction import torch.optim as optim from torch.autograd import Variable import numpy as np import imgaug as ia import random import math import cv2 class Predictor(nn.Module): def __init__(self): super(Predictor, self).__init__() def identity(_): return lambda x: x #bn2d = nn.BatchNorm2d #bn1d = nn.BatchNorm1d bn2d = nn.InstanceNorm2d bn1d = nn.InstanceNorm1d #bn2d = identity #bn1d = identity #bn2d = InstanceNormalization self.nb_previous_images = 2 self.emb_c1_curr = nn.Conv2d(3, 128, kernel_size=7, padding=3, stride=2) self.emb_c1_bn_curr = bn2d(128) self.emb_c1_sd_curr = nn.Dropout2d(0.0) self.emb_c2_curr = nn.Conv2d(128, 128, kernel_size=3, padding=1, stride=1) self.emb_c2_bn_curr = bn2d(128) self.emb_c2_sd_curr = nn.Dropout2d(0.0) self.emb_c3_curr = nn.Conv2d(128, 256, kernel_size=3, padding=1, stride=1) self.emb_c3_bn_curr = bn2d(256) self.emb_c3_sd_curr = nn.Dropout2d(0.0) self.emb_c1_prev = nn.Conv2d(self.nb_previous_images, 64, kernel_size=3, padding=1, stride=1) self.emb_c1_bn_prev = bn2d(64) self.emb_c1_sd_prev = nn.Dropout2d(0.0) self.emb_c2_prev = nn.Conv2d(64, 128, kernel_size=3, padding=1, stride=1) self.emb_c2_bn_prev = bn2d(128) self.emb_c2_sd_prev = nn.Dropout2d(0.0) self.emb_c4 = nn.Conv2d(256+128+4, 256, kernel_size=5, padding=2, stride=2) self.emb_c4_bn = bn2d(256) self.emb_c4_sd = nn.Dropout2d(0.0) self.emb_c5 = nn.Conv2d(256, 256, kernel_size=5, padding=2, stride=2) self.emb_c5_bn = bn2d(256) self.emb_c5_sd = nn.Dropout2d(0.0) self.emb_c6 = nn.Conv2d(256, 512, kernel_size=3, padding=1, stride=2) self.emb_c6_bn = bn2d(512) self.emb_c6_sd = nn.Dropout2d(0.0) self.emb_c7 = nn.Conv2d(512, 512, kernel_size=3, padding=1, stride=1) self.emb_c7_bn = bn2d(512) self.emb_c7_sd = nn.Dropout2d(0.0) self.maps_c1 = nn.Conv2d(512, 256, kernel_size=5, padding=2) self.maps_c1_bn = bn2d(256) self.maps_c2 = nn.Conv2d(256, 256, kernel_size=5, padding=(0, 2)) self.maps_c2_bn = bn2d(256) self.maps_c3 = nn.Conv2d(256, 8+3+self.nb_previous_images+1+1, kernel_size=5, padding=2) # 8 grids, 3 for RGB AE, N prev for N grayscale AE, 1 flow, 1 canny # road_type: 10 # intersection: 7 # direction: 3 # lane count: 5 # curve: 8 # space-front: 4 # space-left: 4 # space-right: 4 # offroad: 3 atts_size = 10 + 7 + 3 + 5 + 8 + 4 + 4 + 4 + 3 ma_size = 9 + 9 + 9 + 9 flipped_size = self.nb_previous_images self.vec_fc1 = nn.Linear(512*3*5, atts_size+ma_size+flipped_size, bias=False) for m in self.modules(): classname = m.__class__.__name__ if classname.find('Conv') != -1: n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels m.weight.data.normal_(0, math.sqrt(2. / n)) elif classname.find('Linear') != -1: m.weight.data.normal_(0, 0.02) elif classname.find('BatchNorm') != -1: m.weight.data.fill_(1) m.bias.data.zero_() #m.weight.data.normal_(1.0, 0.02) #m.bias.data.fill_(0) def downscale(self, img): return ia.imresize_single_image(img, (train.MODEL_HEIGHT, train.MODEL_WIDTH), interpolation="cubic") def downscale_prev(self, img): return ia.imresize_single_image(img, (train.MODEL_PREV_HEIGHT, train.MODEL_PREV_WIDTH), interpolation="cubic") def embed_state(self, previous_states, state, volatile=False, requires_grad=True, gpu=-1): prev_scrs = [self.downscale_prev(s.screenshot_rs) for s in previous_states] prev_scrs_y = [cv2.cvtColor(scr, cv2.COLOR_RGB2GRAY) for scr in prev_scrs] #inputs = np.dstack([self.downscale(state.screenshot_rs)] + list(reversed(prev_scrs_y))) inputs = np.array(self.downscale(state.screenshot_rs), dtype=np.float32) inputs = inputs / 255.0 inputs = inputs.transpose((2, 0, 1)) inputs = inputs[np.newaxis, ...] inputs = to_cuda(to_variable(inputs, volatile=volatile, requires_grad=requires_grad), gpu) inputs_prev = np.dstack(prev_scrs_y) inputs_prev = inputs_prev.astype(np.float32) / 255.0 inputs_prev = inputs_prev.transpose((2, 0, 1)) inputs_prev = inputs_prev[np.newaxis, ...] inputs_prev = to_cuda(to_variable(inputs_prev, volatile=volatile, requires_grad=requires_grad), gpu) return self.embed(inputs, inputs_prev) def embed(self, inputs, inputs_prev): return self.forward(inputs, inputs_prev, only_embed=True) def forward(self, inputs, inputs_prev, only_embed=False): def act(x): return F.relu(x, inplace=True) def lrelu(x, negative_slope=0.2): return F.leaky_relu(x, negative_slope=negative_slope, inplace=True) def up(x, f=2): m = nn.UpsamplingNearest2d(scale_factor=f) return m(x) def maxp(x): return F.max_pool2d(x, 2) B = inputs.size(0) pos_x = np.tile(np.linspace(0, 1, 40).astype(np.float32).reshape(1, 1, 40), (B, 1, 23, 1)) pos_x = np.concatenate([pos_x, np.fliplr(pos_x)], axis=1) pos_y = np.tile(np.linspace(0, 1, 23).astype(np.float32).reshape(1, 23, 1), (B, 1, 1, 40)) pos_y = np.concatenate([pos_y, np.flipud(pos_y)], axis=1) """ print(pos_x_curr[0, 0, 0, 0]) print(pos_x_curr[0, 0, 0, int(MODEL_WIDTH*(1/4))-1]) print(pos_x_curr[0, 0, 0, int(MODEL_WIDTH*(2/4))-1]) print(pos_x_curr[0, 0, 0, int(MODEL_WIDTH*(3/4))-1]) print(pos_x_curr[0, 0, 0, int(MODEL_WIDTH*(4/4))-1]) from scipy import misc misc.imshow( np.vstack([ np.squeeze(pos_x_curr[0].transpose((1, 2, 0))) * 255, np.squeeze(pos_y_curr[0].transpose((1, 2, 0))) * 255 ]) ) """ pos_x = to_cuda(to_variable(pos_x, volatile=inputs.volatile, requires_grad=inputs.requires_grad), Config.GPU) pos_y = to_cuda(to_variable(pos_y, volatile=inputs.volatile, requires_grad=inputs.requires_grad), Config.GPU) x_emb0_curr = inputs # 3x90x160 x_emb1_curr = lrelu(self.emb_c1_sd_curr(self.emb_c1_bn_curr(self.emb_c1_curr(x_emb0_curr)))) # 45x80 x_emb2_curr = lrelu(self.emb_c2_sd_curr(self.emb_c2_bn_curr(self.emb_c2_curr(x_emb1_curr)))) # 45x80 x_emb2_curr = F.pad(x_emb2_curr, (0, 0, 1, 0)) # 45x80 -> 46x80 x_emb2_curr = maxp(x_emb2_curr) # 23x40 x_emb3_curr = lrelu(self.emb_c3_sd_curr(self.emb_c3_bn_curr(self.emb_c3_curr(x_emb2_curr)))) # 23x40 x_emb0_prev = inputs_prev # 2x45x80 x_emb1_prev = lrelu(self.emb_c1_sd_prev(self.emb_c1_bn_prev(self.emb_c1_prev(x_emb0_prev)))) # 45x80 x_emb1_prev = F.pad(x_emb1_prev, (0, 0, 1, 0)) # 45x80 -> 46x80 x_emb1_prev = maxp(x_emb1_prev) # 23x40 x_emb2_prev = lrelu(self.emb_c2_sd_prev(self.emb_c2_bn_prev(self.emb_c2_prev(x_emb1_prev)))) # 23x40 x_emb3 = torch.cat([x_emb3_curr, x_emb2_prev, pos_x, pos_y], 1) x_emb3 = F.pad(x_emb3, (0, 0, 1, 0)) # 23x40 -> 24x40 x_emb4 = lrelu(self.emb_c4_sd(self.emb_c4_bn(self.emb_c4(x_emb3)))) # 12x20 x_emb5 = lrelu(self.emb_c5_sd(self.emb_c5_bn(self.emb_c5(x_emb4)))) # 6x10 x_emb6 = lrelu(self.emb_c6_sd(self.emb_c6_bn(self.emb_c6(x_emb5)))) # 3x5 x_emb7 = lrelu(self.emb_c7_sd(self.emb_c7_bn(self.emb_c7(x_emb6)))) # 3x5 x_emb = x_emb7 if only_embed: return x_emb else: x_maps = x_emb # 3x5 x_maps = up(x_maps, 4) # 12x20 x_maps = lrelu(self.maps_c1_bn(self.maps_c1(x_maps))) # 12x20 x_maps = up(x_maps, 4) # 48x80 x_maps = lrelu(self.maps_c2_bn(self.maps_c2(x_maps))) # 48x80 -> 44x80 x_maps = F.pad(x_maps, (0, 0, 1, 0)) # 45x80 x_maps = up(x_maps) # 90x160 x_maps = F.sigmoid(self.maps_c3(x_maps)) # 90x160 ae_size = 3 + self.nb_previous_images x_grids = x_maps[:, 0:8, ...] x_ae = x_maps[:, 8:8+ae_size, ...] x_flow = x_maps[:, 8+ae_size:8+ae_size+1, ...] x_canny = x_maps[:, 8+ae_size+1:8+ae_size+2, ...] x_vec = x_emb x_vec = x_vec.view(-1, 512*3*5) x_vec = F.dropout(x_vec, p=0.5, training=self.training) x_vec = F.sigmoid(self.vec_fc1(x_vec)) atts_size = 10 + 7 + 3 + 5 + 8 + 4 + 4 + 4 + 3 ma_size = 9 + 9 + 9 + 9 x_atts = x_vec[:, 0:atts_size] x_ma = x_vec[:, atts_size:atts_size+ma_size] x_flipped = x_vec[:, atts_size+ma_size:] return x_ae, x_grids, x_atts, x_ma, x_flow, x_canny, x_flipped, x_emb def predict_grids(self, inputs, inputs_prev): x_ae, x_grids, x_atts, x_ma, x_flow, x_canny, x_flipped, x_emb = self.forward(inputs, inputs_prev) return x_grids class PredictorWithShortcuts(nn.Module): def __init__(self): super(PredictorWithShortcuts, self).__init__() def identity(_): return lambda x: x #bn2d = nn.BatchNorm2d #bn1d = nn.BatchNorm1d bn2d = nn.InstanceNorm2d bn1d = nn.InstanceNorm1d #bn2d = identity #bn1d = identity #bn2d = InstanceNormalization self.nb_previous_images = 2 self.emb_c1_curr = nn.Conv2d(3, 128, kernel_size=7, padding=3, stride=2) self.emb_c1_bn_curr = bn2d(128) self.emb_c1_sd_curr = nn.Dropout2d(0.0) self.emb_c2_curr = nn.Conv2d(128, 128, kernel_size=3, padding=1, stride=1) self.emb_c2_bn_curr = bn2d(128) self.emb_c2_sd_curr = nn.Dropout2d(0.0) self.emb_c3_curr = nn.Conv2d(128, 256, kernel_size=3, padding=1, stride=1) self.emb_c3_bn_curr = bn2d(256) self.emb_c3_sd_curr = nn.Dropout2d(0.0) self.emb_c1_prev = nn.Conv2d(self.nb_previous_images, 64, kernel_size=3, padding=1, stride=1) self.emb_c1_bn_prev = bn2d(64) self.emb_c1_sd_prev = nn.Dropout2d(0.0) self.emb_c2_prev = nn.Conv2d(64, 128, kernel_size=3, padding=1, stride=1) self.emb_c2_bn_prev = bn2d(128) self.emb_c2_sd_prev = nn.Dropout2d(0.0) self.emb_c4 = nn.Conv2d(256+128+4, 256, kernel_size=5, padding=2, stride=2) self.emb_c4_bn = bn2d(256) self.emb_c4_sd = nn.Dropout2d(0.0) self.emb_c5 = nn.Conv2d(256, 256, kernel_size=5, padding=2, stride=2) self.emb_c5_bn = bn2d(256) self.emb_c5_sd = nn.Dropout2d(0.0) self.emb_c6 = nn.Conv2d(256, 512, kernel_size=3, padding=1, stride=2) self.emb_c6_bn = bn2d(512) self.emb_c6_sd = nn.Dropout2d(0.0) self.emb_c7 = nn.Conv2d(512, 512, kernel_size=3, padding=1, stride=1) self.emb_c7_bn = bn2d(512) self.emb_c7_sd = nn.Dropout2d(0.0) self.maps_c1 = nn.Conv2d(512+256, 256, kernel_size=5, padding=2) self.maps_c1_bn = bn2d(256) self.maps_c2 = nn.Conv2d(256+128, 256, kernel_size=5, padding=(0, 2)) self.maps_c2_bn = bn2d(256) self.maps_c3 = nn.Conv2d(256+3, 8+3+self.nb_previous_images+1+1, kernel_size=5, padding=2) # 8 grids, 3 for RGB AE, N prev for N grayscale AE, 1 flow, 1 canny # road_type: 10 # intersection: 7 # direction: 3 # lane count: 5 # curve: 8 # space-front: 4 # space-left: 4 # space-right: 4 # offroad: 3 atts_size = 10 + 7 + 3 + 5 + 8 + 4 + 4 + 4 + 3 ma_size = 9 + 9 + 9 + 9 flipped_size = self.nb_previous_images self.vec_fc1 = nn.Linear(512*3*5, atts_size+ma_size+flipped_size, bias=False) for m in self.modules(): classname = m.__class__.__name__ if classname.find('Conv') != -1: n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels m.weight.data.normal_(0, math.sqrt(2. / n)) elif classname.find('Linear') != -1: m.weight.data.normal_(0, 0.02) elif classname.find('BatchNorm') != -1: m.weight.data.fill_(1) m.bias.data.zero_() #m.weight.data.normal_(1.0, 0.02) #m.bias.data.fill_(0) def downscale(self, img): return ia.imresize_single_image(img, (train.MODEL_HEIGHT, train.MODEL_WIDTH), interpolation="cubic") def downscale_prev(self, img): return ia.imresize_single_image(img, (train.MODEL_PREV_HEIGHT, train.MODEL_PREV_WIDTH), interpolation="cubic") def embed_state(self, previous_states, state, volatile=False, requires_grad=True, gpu=-1): prev_scrs = [self.downscale_prev(s.screenshot_rs) for s in previous_states] prev_scrs_y = [cv2.cvtColor(scr, cv2.COLOR_RGB2GRAY) for scr in prev_scrs] #inputs = np.dstack([self.downscale(state.screenshot_rs)] + list(reversed(prev_scrs_y))) inputs = np.array(self.downscale(state.screenshot_rs), dtype=np.float32) inputs = inputs / 255.0 inputs = inputs.transpose((2, 0, 1)) inputs = inputs[np.newaxis, ...] inputs = to_cuda(to_variable(inputs, volatile=volatile, requires_grad=requires_grad), gpu) inputs_prev = np.dstack(prev_scrs_y) inputs_prev = inputs_prev.astype(np.float32) / 255.0 inputs_prev = inputs_prev.transpose((2, 0, 1)) inputs_prev = inputs_prev[np.newaxis, ...] inputs_prev = to_cuda(to_variable(inputs_prev, volatile=volatile, requires_grad=requires_grad), gpu) return self.embed(inputs, inputs_prev) def embed(self, inputs, inputs_prev): return self.forward(inputs, inputs_prev, only_embed=True) def forward(self, inputs, inputs_prev, only_embed=False): def act(x): return F.relu(x, inplace=True) def lrelu(x, negative_slope=0.2): return F.leaky_relu(x, negative_slope=negative_slope, inplace=True) def up(x, f=2): m = nn.UpsamplingNearest2d(scale_factor=f) return m(x) def maxp(x): return F.max_pool2d(x, 2) B = inputs.size(0) pos_x = np.tile(np.linspace(0, 1, 40).astype(np.float32).reshape(1, 1, 40), (B, 1, 23, 1)) pos_x = np.concatenate([pos_x, np.fliplr(pos_x)], axis=1) pos_y = np.tile(np.linspace(0, 1, 23).astype(np.float32).reshape(1, 23, 1), (B, 1, 1, 40)) pos_y = np.concatenate([pos_y, np.flipud(pos_y)], axis=1) pos_x = to_cuda(to_variable(pos_x, volatile=inputs.volatile, requires_grad=inputs.requires_grad), Config.GPU) pos_y = to_cuda(to_variable(pos_y, volatile=inputs.volatile, requires_grad=inputs.requires_grad), Config.GPU) x_emb0_curr = inputs # 3x90x160 x_emb1_curr = lrelu(self.emb_c1_sd_curr(self.emb_c1_bn_curr(self.emb_c1_curr(x_emb0_curr)))) # 45x80 x_emb2_curr = lrelu(self.emb_c2_sd_curr(self.emb_c2_bn_curr(self.emb_c2_curr(x_emb1_curr)))) # 45x80 x_emb2_curr = F.pad(x_emb2_curr, (0, 0, 1, 0)) # 45x80 -> 46x80 x_emb2_curr_pool = maxp(x_emb2_curr) # 23x40 x_emb3_curr = lrelu(self.emb_c3_sd_curr(self.emb_c3_bn_curr(self.emb_c3_curr(x_emb2_curr_pool)))) # 23x40 x_emb0_prev = inputs_prev # 2x45x80 x_emb1_prev = lrelu(self.emb_c1_sd_prev(self.emb_c1_bn_prev(self.emb_c1_prev(x_emb0_prev)))) # 45x80 x_emb1_prev = F.pad(x_emb1_prev, (0, 0, 1, 0)) # 45x80 -> 46x80 x_emb1_prev = maxp(x_emb1_prev) # 23x40 x_emb2_prev = lrelu(self.emb_c2_sd_prev(self.emb_c2_bn_prev(self.emb_c2_prev(x_emb1_prev)))) # 23x40 x_emb3 = torch.cat([x_emb3_curr, x_emb2_prev, pos_x, pos_y], 1) x_emb3 = F.pad(x_emb3, (0, 0, 1, 0)) # 23x40 -> 24x40 x_emb4 = lrelu(self.emb_c4_sd(self.emb_c4_bn(self.emb_c4(x_emb3)))) # 12x20 x_emb5 = lrelu(self.emb_c5_sd(self.emb_c5_bn(self.emb_c5(x_emb4)))) # 6x10 x_emb6 = lrelu(self.emb_c6_sd(self.emb_c6_bn(self.emb_c6(x_emb5)))) # 3x5 x_emb7 = lrelu(self.emb_c7_sd(self.emb_c7_bn(self.emb_c7(x_emb6)))) # 3x5 x_emb = x_emb7 if only_embed: return x_emb else: x_maps = x_emb # 3x5 x_maps = up(x_maps, 4) # 12x20 x_maps = lrelu(self.maps_c1_bn(self.maps_c1( torch.cat([x_maps, x_emb4], 1) ))) # 12x20 x_maps = up(x_maps, 4) # 48x80 x_maps = lrelu(self.maps_c2_bn(self.maps_c2( torch.cat([x_maps, F.pad(x_emb2_curr, (0, 0, 1, 1))], 1) ))) # 48x80 -> 44x80 x_maps = F.pad(x_maps, (0, 0, 1, 0)) # 45x80 x_maps = up(x_maps) # 90x160 x_maps = F.sigmoid(self.maps_c3( torch.cat([x_maps, inputs], 1) )) # 90x160 ae_size = 3 + self.nb_previous_images x_grids = x_maps[:, 0:8, ...] x_ae = x_maps[:, 8:8+ae_size, ...] x_flow = x_maps[:, 8+ae_size:8+ae_size+1, ...] x_canny = x_maps[:, 8+ae_size+1:8+ae_size+2, ...] x_vec = x_emb x_vec = x_vec.view(-1, 512*3*5) x_vec = F.dropout(x_vec, p=0.5, training=self.training) x_vec = F.sigmoid(self.vec_fc1(x_vec)) atts_size = 10 + 7 + 3 + 5 + 8 + 4 + 4 + 4 + 3 ma_size = 9 + 9 + 9 + 9 x_atts = x_vec[:, 0:atts_size] x_ma = x_vec[:, atts_size:atts_size+ma_size] x_flipped = x_vec[:, atts_size+ma_size:] return x_ae, x_grids, x_atts, x_ma, x_flow, x_canny, x_flipped, x_emb def predict_grids(self, inputs, inputs_prev): x_ae, x_grids, x_atts, x_ma, x_flow, x_canny, x_flipped, x_emb = self.forward(inputs, inputs_prev) return x_grids

43.049065

166

0.614383

2,981

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null

0

1

0

1

0

null

0

7

3a63a44318c3f788a7357416beed8f13234ef4af

14,101

py

Python

qa327_test/frontend/test_sell.py

CanonAY/Highedge-Co.

aced31e287b3dd4d6fb444825aa5b553166deff9

[ "MIT" ]

null

qa327_test/frontend/test_sell.py

CanonAY/Highedge-Co.

aced31e287b3dd4d6fb444825aa5b553166deff9

[ "MIT" ]

null

qa327_test/frontend/test_sell.py

CanonAY/Highedge-Co.

aced31e287b3dd4d6fb444825aa5b553166deff9

[ "MIT" ]

2

2021-02-23T06:18:42.000Z

2021-04-17T07:07:52.000Z

import pytest from seleniumbase import BaseCase from selenium.webdriver.common.keys import Keys from qa327_test.conftest import base_url from unittest.mock import patch from qa327.models import db, User from werkzeug.security import generate_password_hash, check_password_hash """ This file defines all unit tests for the frontend login page. """ # Moch a sample user test_user = User( email='test_sell@test.com', name='test_sell', password=generate_password_hash('TEST_frontend') ) class FrontEndSellTest(BaseCase): # Login to the profile for the purpose of testing functionality of sell form. def login_to_profile(self): # invalid any existing session self.open(base_url + '/logout') self.open(base_url + '/login') # enter test user email and password self.type("#email", "test_sell@test.com") self.type("#password", "TEST_frontend") # click enter button self.click('input[type="submit"]') # R4.1 The name of the ticket has to be alphanumeric-only, and space allowed only if it is not the first or the last character. @patch('qa327.backend.get_user', return_value=test_user) def test_name_format(self, *_): # login to the profile self.login_to_profile() """ NEGATIVE """ # enter invalid name and valid quantity, price and date self.type("#sell-name", " TESTticket") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT, "31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid name and valid quantity, price and date self.type("#sell-name", "TESTticket ") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid name and valid quantity, price and date self.type("#sell-name", "TE_STticket") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) """ POSITIVE """ # enter valid name, quantity, price and date self.type("#sell-name", "TESTticket") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit succeed self.assert_element("#message") self.assert_text("Ticket successfully posted", "#message") self.open(base_url) # R4.2 The name of the ticket is no longer than 60 characters # R4.8 (optional) The name of the tickets has to contain at least 6 characters @patch('qa327.backend.get_user', return_value=test_user) def test_name_length(self, *_): # login to the profile self.login_to_profile() """ NEGATIVE """ # enter invalid name and valid quantity, price and date self.type("#sell-name", 6*"TESTticket1") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid name and valid quantity, price and date self.type("#sell-name", "TEST1") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) """ POSITIVE """ # enter valid name, quantity, price and date self.type("#sell-name", "TESTticket1") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit succeed self.assert_element("#message") self.assert_text("Ticket successfully posted", "#message") self.open(base_url) # R4.3 The quantity of the tickets has to be more than 0, and less than or equal to 100. @patch('qa327.backend.get_user', return_value=test_user) def test_quantity(self, *_): # login to the profile self.login_to_profile() """ NEGATIVE """ # enter invalid quantity and valid name, price and date self.type("#sell-name", "TESTticket2") self.type("#sell-quantity", "0") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid quantity and valid name, price and date self.type("#sell-name", "TESTticket2") self.type("#sell-quantity", "102") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) """ POSITIVE """ # enter valid name, quantity, price and date self.type("#sell-name", "TESTticket2") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit succeed self.assert_element("#message") self.assert_text("Ticket successfully posted", "#message") self.open(base_url) # R4.4 Price has to be of range [10, 100] @patch('qa327.backend.get_user', return_value=test_user) def test_price(self, *_): # login to the profile self.login_to_profile() """ NEGATIVE """ # enter invalid price and valid name, quantity and date self.type("#sell-name", "TESTticket3") self.type("#sell-quantity", "50") self.type("#sell-price", "0") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid price and valid name, quantity and date self.type("#sell-name", "TESTticket3") self.type("#sell-quantity", "50") self.type("#sell-price", "102") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) """ POSITIVE """ # enter valid name, quantity, price and date self.type("#sell-name", "TESTticket3") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit succeed self.assert_element("#message") self.assert_text("Ticket successfully posted", "#message") self.open(base_url) # R4.5 Date must be given in the format YYYYMMDD (e.g. 20200901) @patch('qa327.backend.get_user', return_value=test_user) def test_date(self, *_): # login to the profile self.login_to_profile() """ NEGATIVE """ # enter invalid date and valid name, price and quantity self.type("#sell-name", "TESTticket4") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("201202", "12", "31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) """ POSITIVE """ # enter valid name, quantity, price and date self.type("#sell-name", "TESTticket4") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit succeed self.assert_element("#message") self.assert_text("Ticket successfully posted", "#message") self.open(base_url) # R4.6 For any errors, redirect back to / and show an error message @patch('qa327.backend.get_user', return_value=test_user) def test_redirect(self, *_): # login to the profile self.login_to_profile() # enter invalid name and valid date, price and quantity self.type("#sell-name", "TEST_ticket5") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_title("Profile") self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid quantity and valid date, price and name self.type("#sell-name", "TEST_ticket5") self.type("#sell-quantity", "0") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_title("Profile") self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid price and valid name, quantity and date self.type("#sell-name", "TESTticket5") self.type("#sell-quantity", "50") self.type("#sell-price", "0") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_title("Profile") self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # enter invalid date and valid name, price and quantity self.type("#sell-name", "TESTticket5") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("201202", "12", "31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit failed self.assert_title("Profile") self.assert_element("#message_s") self.assert_text("Ticket format invalid", "#message_s") self.open(base_url) # R4.7 The added new ticket information will be posted on the user profile page @patch('qa327.backend.get_user', return_value=test_user) def test_post_ticket(self, *_): # login to the profile self.login_to_profile() # enter valid name, quantity, price and date self.type("#sell-name", "TESTticket6") self.type("#sell-quantity", "50") self.type("#sell-price", "50") date = self.find_element("#sell-date") date.send_keys("2020", Keys.ARROW_RIGHT, "12", Keys.ARROW_RIGHT,"31") self.click('input[value="Submit Selling Ticket"]') # assert ticket submit succeed self.assert_element("#message") self.assert_text("Ticket successfully posted", "#message") self.open(base_url) # assert the ticket posted on profile page self.assert_text("TESTticket6")

39.946176

131

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1,814

14,101

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0.094818

0.058018

0.08422

0.038601

0.864546

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null

0

7

3ab9cd8cbe494c909c3d2d08361fabcb98fac9d0

24,557

py

Python

tests/test_validate_network_bgp.py

Cray-HPE/canu

3a92ce1e9b63f35aa30b9135afaa734e61909407

[ "MIT" ]

6

2021-09-16T22:02:48.000Z

2022-02-04T18:08:57.000Z

tests/test_validate_network_bgp.py

Cray-HPE/canu

3a92ce1e9b63f35aa30b9135afaa734e61909407

[ "MIT" ]

57

2021-09-17T17:15:59.000Z

2022-03-31T20:56:21.000Z

tests/test_validate_network_bgp.py

Cray-HPE/canu

3a92ce1e9b63f35aa30b9135afaa734e61909407

[ "MIT" ]

4

2022-01-06T17:09:02.000Z

2022-02-04T18:09:33.000Z

# MIT License # # (C) Copyright [2022] Hewlett Packard Enterprise Development LP # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included # in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR # OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, # ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR # OTHER DEALINGS IN THE SOFTWARE. """Test CANU validate network bgp commands.""" from unittest.mock import patch from click import testing import requests import responses from canu.cli import cli username = "admin" password = "admin" ip = "192.168.1.1" asn = 65533 sls_cache = { "HMN_IPs": { "sw-spine-001": "192.168.1.1", "sw-spine-002": "192.168.1.2", }, "SWITCH_ASN": asn, } cache_minutes = 0 sls_address = "api-gw-service-nmn.local" runner = testing.CliRunner() @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_aruba(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs and returns PASS.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache for name, ip in sls_cache["HMN_IPs"].items(): responses.add( responses.POST, f"https://{ip}/rest/v10.04/login", ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system/vrfs/default/bgp_routers/{asn}/bgp_neighbors?depth=2", json=all_established, ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system/vrfs/Customer/bgp_routers/{asn}/bgp_neighbors?depth=2", json=all_established, ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system?attributes=platform_name,hostname", json={"hostname": name, "platform_name": "X86-64"}, ) responses.add( responses.POST, f"https://{ip}/rest/v10.04/logout", ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "PASS - IP: 192.168.1.1 Hostname: sw-spine-001" in str(result.output) assert "PASS - IP: 192.168.1.2 Hostname: sw-spine-002" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_verbose(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs and returns PASS.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache for name, ip_address in sls_cache["HMN_IPs"].items(): responses.add( responses.POST, f"https://{ip_address}/rest/v10.04/login", ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system/vrfs/default/bgp_routers/{asn}/bgp_neighbors?depth=2", json=all_established, ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system/vrfs/Customer/bgp_routers/{asn}/bgp_neighbors?depth=2", json=all_established_cmn, ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system?attributes=platform_name,hostname", json={"hostname": name, "platform_name": "X86-64"}, ) responses.add( responses.POST, f"https://{ip_address}/rest/v10.04/logout", ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, "--verbose", ], ) assert result.exit_code == 0 assert "Switch: sw-spine-001 (192.168.1.1) " in str(result.output) assert "sw-spine-001 ===> 192.168.1.2: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.1.3: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.1.4: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.10.2: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.10.3: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.10.4: Established" in str(result.output) assert "Switch: sw-spine-002 (192.168.1.2) " in str(result.output) assert "sw-spine-002 ===> 192.168.1.2: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.1.3: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.1.4: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.10.2: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.10.3: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.10.4: Established" in str(result.output) assert "PASS - IP: 192.168.1.1 Hostname: sw-spine-001" in str(result.output) assert "PASS - IP: 192.168.1.2 Hostname: sw-spine-002" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_nmn(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs and returns PASS.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache for name, ip_address in sls_cache["HMN_IPs"].items(): responses.add( responses.POST, f"https://{ip_address}/rest/v10.04/login", ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system/vrfs/default/bgp_routers/{asn}/bgp_neighbors?depth=2", json=all_established, ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system?attributes=platform_name,hostname", json={"hostname": name, "platform_name": "X86-64"}, ) responses.add( responses.POST, f"https://{ip_address}/rest/v10.04/logout", ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, "--verbose", "--network", "nmn", ], ) assert result.exit_code == 0 assert "Switch: sw-spine-001 (192.168.1.1) " in str(result.output) assert "sw-spine-001 ===> 192.168.1.2: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.1.3: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.1.4: Established" in str(result.output) assert "Switch: sw-spine-002 (192.168.1.2) " in str(result.output) assert "sw-spine-002 ===> 192.168.1.2: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.1.3: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.1.4: Established" in str(result.output) assert "PASS - IP: 192.168.1.1 Hostname: sw-spine-001" in str(result.output) assert "PASS - IP: 192.168.1.2 Hostname: sw-spine-002" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_cmn(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs and returns PASS.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache for name, ip_address in sls_cache["HMN_IPs"].items(): responses.add( responses.POST, f"https://{ip_address}/rest/v10.04/login", ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system/vrfs/Customer/bgp_routers/{asn}/bgp_neighbors?depth=2", json=all_established_cmn, ) responses.add( responses.GET, f"https://{ip_address}/rest/v10.04/system?attributes=platform_name,hostname", json={"hostname": name, "platform_name": "X86-64"}, ) responses.add( responses.POST, f"https://{ip_address}/rest/v10.04/logout", ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, "--verbose", "--network", "cmn", ], ) assert result.exit_code == 0 assert "Switch: sw-spine-001 (192.168.1.1) " in str(result.output) assert "sw-spine-001 ===> 192.168.10.2: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.10.3: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.10.4: Established" in str(result.output) assert "Switch: sw-spine-002 (192.168.1.2) " in str(result.output) assert "sw-spine-002 ===> 192.168.10.2: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.10.3: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.10.4: Established" in str(result.output) assert "PASS - IP: 192.168.1.1 Hostname: sw-spine-001" in str(result.output) assert "PASS - IP: 192.168.1.2 Hostname: sw-spine-002" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_bad_password(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command errors on bad credentials.""" bad_password = "foo" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache responses.add( responses.POST, f"https://{ip}/rest/v10.04/login", body=requests.exceptions.HTTPError("Client Error: Unauthorized for url"), ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", bad_password, ], ) assert result.exit_code == 0 assert ( "Error connecting to switch 192.168.1.1, check the username or password" in str(result.output) ) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_fail(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs and returns PASS.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache for name, ip in sls_cache["HMN_IPs"].items(): responses.add( responses.POST, f"https://{ip}/rest/v10.04/login", ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system/vrfs/default/bgp_routers/{asn}/bgp_neighbors?depth=2", json=one_idle, ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system/vrfs/Customer/bgp_routers/{asn}/bgp_neighbors?depth=2", json=one_idle, ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system?attributes=platform_name,hostname", json={"hostname": name, "platform_name": "X86-64"}, ) responses.add( responses.POST, f"https://{ip}/rest/v10.04/logout", ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "FAIL - IP: 192.168.1.1 Hostname: sw-spine-001" in str(result.output) assert "FAIL - IP: 192.168.1.2 Hostname: sw-spine-002" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_fail_verbose(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs and returns PASS.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache for name, ip in sls_cache["HMN_IPs"].items(): responses.add( responses.POST, f"https://{ip}/rest/v10.04/login", ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system/vrfs/default/bgp_routers/{asn}/bgp_neighbors?depth=2", json=one_idle, ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system/vrfs/Customer/bgp_routers/{asn}/bgp_neighbors?depth=2", json=one_idle, ) responses.add( responses.GET, f"https://{ip}/rest/v10.04/system?attributes=platform_name,hostname", json={"hostname": name, "platform_name": "X86-64"}, ) responses.add( responses.POST, f"https://{ip}/rest/v10.04/logout", ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, "--verbose", ], ) assert result.exit_code == 0 assert "Switch: sw-spine-001 (192.168.1.1) " in str(result.output) assert "sw-spine-001 ===> 192.168.1.2: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.1.3: Established" in str(result.output) assert "sw-spine-001 ===> 192.168.1.4: Idle" in str(result.output) assert "Switch: sw-spine-002 (192.168.1.2) " in str(result.output) assert "sw-spine-002 ===> 192.168.1.2: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.1.3: Established" in str(result.output) assert "sw-spine-002 ===> 192.168.1.4: Idle" in str(result.output) assert "FAIL - IP: 192.168.1.1 Hostname: sw-spine-001" in str(result.output) assert "FAIL - IP: 192.168.1.2 Hostname: sw-spine-002" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_vendor_error(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command errors on 'None' vendor.""" with runner.isolated_filesystem(): switch_vendor.return_value = None pull_sls_networks.return_value = sls_cache result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "192.168.1.1 - Connection Error" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @patch("canu.validate.network.bgp.bgp.get_bgp_neighbors_aruba") @responses.activate def test_validate_bgp_exception( get_bgp_neighbors_aruba, pull_sls_networks, switch_vendor, ): """Test that the `canu validate network bgp` command errors on exception.""" with runner.isolated_filesystem(): switch_vendor.return_value = "aruba" pull_sls_networks.return_value = sls_cache get_bgp_neighbors_aruba.side_effect = requests.exceptions.HTTPError result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "192.168.1.1 - Connection Error" in str(result.output) # Mellanox @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_mellanox(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command runs with Mellanox switch.""" with runner.isolated_filesystem(): switch_vendor.return_value = "mellanox" pull_sls_networks.return_value = sls_cache responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", json={"status": "OK", "status_msg": "Successfully logged-in"}, ) responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", json=bgp_status_mellanox, ) responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", json={"data": [{"Hostname": "sw-spine-mellanox"}]}, ) responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", json={"data": {"value": ["MSN2100"]}}, ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "PASS - IP: 192.168.1.1 Hostname: sw-spine-mellanox" in str( result.output, ) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_mellanox_connection_error(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command errors with Mellanox switch connection error.""" with runner.isolated_filesystem(): switch_vendor.return_value = "mellanox" pull_sls_networks.return_value = sls_cache responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", status=404, ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "192.168.1.1 - Connection Error" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_mellanox_bad_login(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command errors with Mellanox switch bad login.""" with runner.isolated_filesystem(): switch_vendor.return_value = "mellanox" pull_sls_networks.return_value = sls_cache responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", json={"status": "ERROR", "status_msg": "Invalid username or password"}, ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "192.168.1.1 - Connection Error" in str(result.output) @patch("canu.validate.network.bgp.bgp.switch_vendor") @patch("canu.validate.network.bgp.bgp.pull_sls_networks") @responses.activate def test_validate_bgp_mellanox_exception(pull_sls_networks, switch_vendor): """Test that the `canu validate network bgp` command errors with Mellanox switch exception.""" with runner.isolated_filesystem(): switch_vendor.return_value = "mellanox" pull_sls_networks.return_value = sls_cache responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", json={"status": "OK", "status_msg": "Successfully logged-in"}, ) responses.add( responses.POST, f"https://{ip}/admin/launch?script=rh&template=json-request&action=json-login", body=requests.exceptions.HTTPError(), ) result = runner.invoke( cli, [ "validate", "network", "bgp", "--username", username, "--password", password, ], ) assert result.exit_code == 0 assert "192.168.1.1 - Connection Error" in str(result.output) all_established = { "192.168.1.2": { "status": {"bgp_peer_state": "Established"}, }, "192.168.1.3": { "status": {"bgp_peer_state": "Established"}, }, "192.168.1.4": { "status": {"bgp_peer_state": "Established"}, }, } all_established_cmn = { "192.168.10.2": { "status": {"bgp_peer_state": "Established"}, }, "192.168.10.3": { "status": {"bgp_peer_state": "Established"}, }, "192.168.10.4": { "status": {"bgp_peer_state": "Established"}, }, } one_idle = { "192.168.1.2": { "status": {"bgp_peer_state": "Established"}, }, "192.168.1.3": { "status": {"bgp_peer_state": "Established"}, }, "192.168.1.4": { "status": {"bgp_peer_state": "Idle"}, }, } dell_firmware_mock = { "dell-system-software:sw-version": { "sw-version": "10.5.1.4", "sw-platform": "S4048T-ON", }, } dell_hostname_mock = {"dell-system:hostname": "test-dell"} bgp_status_mellanox = { "status": "OK", "executed_command": "show ip bgp summary", "status_message": "", "data": [ { "VRF name": "default", }, { "192.168.1.9": [ { "State/PfxRcd": "ESTABLISHED/13", }, ], }, ], }

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4.755074

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0

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0

1

0

null

0

1

0

8

3ac2862bd592576f2ad893877b0fe9b5151232be

41

py

Python

validate_passcode.py

kimsappi/laundry_reservation_flask

5668df956d899934db4ad4ec26fb7b4e6e5770f4

[ "Unlicense" ]

null

validate_passcode.py

kimsappi/laundry_reservation_flask

5668df956d899934db4ad4ec26fb7b4e6e5770f4

[ "Unlicense" ]

null

validate_passcode.py

kimsappi/laundry_reservation_flask

5668df956d899934db4ad4ec26fb7b4e6e5770f4

[ "Unlicense" ]

null

def validate_passcode(data): return True

20.5

28

0.829268

6

41

5.5

1

0

0.097561

41

2

29

20.5

0.891892

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0.5

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0.5

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0

null

0

1

0

1

0

1

0

7

3acea938f6ce580c6754da7a0d20e9034741125d

21,223

py

Python

pyban/tickets/tests.py

abderrahmen-hadjadj-aoul/pyban

82fe3f0bcf36880b710bbf617f2a7e6b1097f80c

[ "MIT" ]

null

pyban/tickets/tests.py

abderrahmen-hadjadj-aoul/pyban

82fe3f0bcf36880b710bbf617f2a7e6b1097f80c

[ "MIT" ]

null

pyban/tickets/tests.py

abderrahmen-hadjadj-aoul/pyban

82fe3f0bcf36880b710bbf617f2a7e6b1097f80c

[ "MIT" ]

null

from django.test import TestCase, Client from django.urls import reverse import json class GeneralTests(TestCase): def setUp(self): self.client = Client() # HELPERS def create_user(self, username, password): payload = { "username": username, "password": password, } response = self.client.post(reverse("tickets:users"), json.dumps(payload), content_type="application/json") user = json.loads(response.content) return (response, user) def get_user(self, id): response = self.client.get( reverse("tickets:user", kwargs={"user_id": id})) user = json.loads(response.content) return (response, user) def get_users(self): response = self.client.get(reverse("tickets:users")) data = json.loads(response.content) return (response, data) def get_token(self, username, password): payload = { "username": username, "password": password, } response = self.client.post(reverse("tickets:api_token_auth"), json.dumps(payload), follow=True, content_type="application/json") data = json.loads(response.content) return (response, data) # USERS def test_create_user(self): """ A user should be created """ username = "Tom" password = "123" (response, user) = self.create_user(username, password) self.assertIs(response.status_code, 201) self.assertEqual(user['username'], username) def test_create_user_witout_username(self): """ A user created without username should return an error """ username = "" password = "123" (response, data) = self.create_user(username, password) self.assertEqual(response.status_code, 400) self.assertEqual(data['message'], "Username must be set") def test_create_user_twice(self): """ A user created twice should return an error """ username = "Tom" password = "123" (response, user) = self.create_user(username, password) self.assertIs(response.status_code, 201) self.assertEqual(user['username'], username) (response, data) = self.create_user(username, password) self.assertEqual(data['message'], "User already exists") def test_create_then_get_user(self): """ A user should be created then get """ username = "Tom2" password = "1232" (response, created_user) = self.create_user(username, password) id = created_user['id'] (response, user) = self.get_user(id) self.assertEqual(response.status_code, 200) self.assertEqual(user['username'], username) def test_get_user_not_exist(self): """ An error should be returned """ id = 123456789 (response, user) = self.get_user(id) self.assertEqual(response.status_code, 404) def test_get_users(self): """ Should get users """ username = "Tom3" password = "1233" (response, created_user) = self.create_user(username, password) (response, data) = self.get_users() self.assertEqual(response.status_code, 200) self.assertEqual(len(data['users']), 1) self.assertEqual(data['users'][0]['username'], username) def test_get_token(self): """ Should log properly with right credentials """ username = "Tom3" password = "1233" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) self.assertEqual(response.status_code, 200) self.assertIn("token", data) def test_login_wrong_username(self): """ Should return an error for wrong credentials """ username = "Tom3" password = "1233" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username + "0", password) self.assertEqual(response.status_code, 400) def test_login_wrong_password(self): """ Should return an error for wrong credentials """ username = "Tom3" password = "1233" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password + "0") self.assertEqual(response.status_code, 400) # BOARD def create_board(self, name, headers={}): payload = { "name": name, "columns": [], } response = self.client.post(reverse("tickets:boards"), json.dumps(payload), content_type="application/json", **headers) board = json.loads(response.content) boardid = board["id"] payload = { "title": "TODO", } response = self.client.post(reverse("tickets:board_columns", kwargs={"pk": boardid}), json.dumps(payload), content_type="application/json", **headers) column = json.loads(response.content) board["columns"].append(column["id"]) return (response, board, column) def get_board(self, board_id, headers={}): response = self.client.get( reverse("tickets:board", kwargs={"pk": board_id}), **headers) board = {} try: board = json.loads(response.content) except Exception: pass return (response, board) def test_board_create(self): """ Should create a board """ username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) name = "Board Name" (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} (response, created_board, created_column) = self.create_board(name, headers=headers) self.assertEqual(response.status_code, 201) self.assertEqual(created_board["name"], name) def test_board_create_then_get_it(self): """ Should get the created board """ # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) # Get token (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create board name = "Board Name" (response, created_board, created_column) = self.create_board(name, headers=headers) self.assertEqual(response.status_code, 201) boardid = created_board["id"] # Get board (response, board) = self.get_board(boardid, headers=headers) self.assertEqual(board["id"], boardid) self.assertEqual(board["name"], name) def test_board_get_not_exist(self): """ Should return error for board that does not exist """ username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} boardid = 12346789 (response, board) = self.get_board(boardid, headers=headers) self.assertEqual(response.status_code, 404) def test_board_permission(self): """ Should return error for no permission of board """ # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) username2 = "Tom--" password2 = "123--" (response, created_user2) = self.create_user(username2, password2) # Get token (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} (response2, data2) = self.get_token(username2, password2) token2 = data2["token"] headers2 = {"HTTP_AUTHORIZATION": "Token " + token2} # Create board name = "Board Name" (response, created_board, created_column) = self.create_board(name, headers=headers) self.assertEqual(response.status_code, 201) boardid = created_board["id"] # Get board (response, board) = self.get_board(boardid, headers=headers2) self.assertEqual(response.status_code, 401) def test_get_board_list(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) # Get token (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create boards created_boards = [] number_of_boards = 5 for n in range(number_of_boards): name = "Board Name" + str(n) (response, created_board, created_column) = self.create_board(name, headers=headers) created_boards.append((response, created_board)) response = self.client.get(reverse("tickets:boards"), **headers) boards = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(len(boards), 5) for n in range(number_of_boards): self.assertIn(created_boards[n][1], boards) def test_get_board_list_without_other_users_boards(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) username2 = "Tom--" password2 = "123--" (response2, created_user2) = self.create_user(username2, password2) # Get token (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} (response2, data2) = self.get_token(username2, password2) token2 = data2["token"] headers2 = {"HTTP_AUTHORIZATION": "Token " + token2} # Create boards created_boards = [] number_of_boards = 5 for n in range(number_of_boards): name = "Board Name" + str(n) (response, created_board, created_column) = self.create_board(name, headers=headers) created_boards.append((response, created_board)) name = "Board Name Other" + str(n) (response, created_board, created_column) = self.create_board(name, headers=headers2) response = self.client.get(reverse("tickets:boards"), **headers) boards = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(len(boards), 5) for n in range(number_of_boards): self.assertIn(created_boards[n][1], boards) # TICKETS def test_create_ticket(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create board name = "Board Name for tickets" (response, created_board, created_column) = self.create_board(name, headers=headers) self.assertEqual(response.status_code, 201) columnid = created_column["id"] # Create ticket payload = { "title": "Ticket Title", "description": "Ticket Description", "column": columnid, } response = self.client.post(reverse("tickets:tickets"), json.dumps(payload), content_type="application/json", **headers) ticket = json.loads(response.content) ticketid = ticket["id"] self.assertEqual(response.status_code, 201) self.assertEqual(ticket["title"], payload["title"]) self.assertEqual(ticket["description"], payload["description"]) # Get Ticket response = self.client.get( reverse("tickets:ticket", kwargs={"pk": ticketid}), **headers) ticket = json.loads(response.content) self.assertEqual(ticket["title"], payload["title"]) self.assertEqual(ticket["description"], payload["description"]) def test_create_ticket_wrong_board(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} username2 = "Tom--" password2 = "123" (response, created_user) = self.create_user(username2, password2) (response, data) = self.get_token(username2, password2) token2 = data["token"] headers2 = {"HTTP_AUTHORIZATION": "Token " + token2} # Create board name = "Board Name for tickets" (response, created_board, created_column) = self.create_board(name, headers=headers) self.assertEqual(response.status_code, 201) # Create ticket payload = { "title": "Ticket Title", "description": "Ticket Description", "column": created_column["id"], } response = self.client.post(reverse("tickets:tickets"), json.dumps(payload), content_type="application/json", **headers2) error = json.loads(response.content) self.assertEqual(response.status_code, 401) self.assertEqual(error["error"], "You don't have access to the board") def test_create_and_ticket_list(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) # Get token (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create board name = "Board Name for tickets" (response, created_board, created_column) = self.create_board(name, headers=headers) self.assertEqual(response.status_code, 201) boardid = created_board["id"] # Create ticket created_tickets = [] number_of_tickets = 5 for n in range(number_of_tickets): payload = { "title": "Ticket Title" + str(n), "description": "Ticket Description" + str(n), "column": created_column["id"], } response = self.client.post(reverse("tickets:tickets"), json.dumps(payload), content_type="application/json", **headers) ticket_created = json.loads(response.content) created_tickets.append((response, ticket_created)) url = reverse("tickets:tickets") + "?boardid=" + str(boardid) response = self.client.get(url, **headers) tickets = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(len(tickets), number_of_tickets) for n in range(number_of_tickets): self.assertIn(created_tickets[n][1], tickets) def test_update_ticket(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create board name = "Board Name for tickets" (response, created_board, created_column) = self.create_board(name, headers=headers) # Create ticket payload = { "title": "Ticket Title", "description": "Ticket Description", "column": created_column["id"], } response = self.client.post(reverse("tickets:tickets"), json.dumps(payload), content_type="application/json", **headers) ticket = json.loads(response.content) ticketid = ticket["id"] # Update Ticket newTitle = "New title" newDescription = "New description" payload = { "title": newTitle, "description": newDescription, } response = self.client.patch(reverse("tickets:ticket", kwargs={"pk": ticketid}), payload, content_type="application/json", **headers) ticket = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(ticket["title"], payload["title"]) self.assertEqual(ticket["description"], payload["description"]) # Get Ticket response = self.client.get( reverse("tickets:ticket", kwargs={"pk": ticketid}), **headers) ticket = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(ticket["title"], payload["title"]) self.assertEqual(ticket["description"], payload["description"]) def test_delete_ticket(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create board name = "Board Name for tickets" (response, created_board, created_column) = self.create_board(name, headers=headers) # Create ticket payload = { "title": "Ticket Title", "description": "Ticket Description", "column": created_column["id"], } response = self.client.post(reverse("tickets:tickets"), json.dumps(payload), content_type="application/json", **headers) ticket = json.loads(response.content) ticketid = ticket["id"] # Delete Ticket response = self.client.delete( reverse("tickets:ticket", kwargs={"pk": ticketid}), **headers) ticket = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(ticket["title"], payload["title"]) self.assertEqual(ticket["description"], payload["description"]) # Get Ticket response = self.client.get( reverse("tickets:ticket", kwargs={"pk": ticketid}), **headers) ticket = json.loads(response.content) self.assertEqual(response.status_code, 404) def test_column_create(self): # Create user username = "Tom" password = "123" (response, created_user) = self.create_user(username, password) (response, data) = self.get_token(username, password) token = data["token"] headers = {"HTTP_AUTHORIZATION": "Token " + token} # Create board name = "Board Name for tickets" (response, created_board, created_column) = self.create_board(name, headers=headers) boardid = created_board["id"] payload = { "title": "In progress", } # Create column url = reverse("tickets:board_columns", kwargs={"pk": boardid}) response = self.client.post(url, json.dumps(payload), content_type="application/json", **headers) self.assertEqual(response.status_code, 201) # Get column response = self.client.get( reverse("tickets:board_columns", kwargs={"pk": boardid}), **headers) columns = json.loads(response.content) self.assertEqual(response.status_code, 200) self.assertEqual(columns[1]["title"], payload["title"])

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0.772847

0.726603

0.692301

0.673245

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0.01596

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21,223

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79

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0.796299

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null

0

1

0

7

c9233b0f41114fc18617e0e6148267e3cc4b9e7e

64

py

Python

The Core/01 - addTwoDigits.py

lucasalme1da/codesignal

faff1ae635d04a33a1b59e6f751d266fabca5e71

[ "MIT" ]

2

2020-04-15T00:15:03.000Z

2021-02-17T18:43:08.000Z

The Core/01 - addTwoDigits.py

lucasalme1da/codesignal

faff1ae635d04a33a1b59e6f751d266fabca5e71

[ "MIT" ]

null

The Core/01 - addTwoDigits.py

lucasalme1da/codesignal

faff1ae635d04a33a1b59e6f751d266fabca5e71

[ "MIT" ]

null

def addTwoDigits(n): return int(str(n)[0]) + int(str(n)[1])

21.333333

42

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64

3.166667

0.666667

0.315789

0.368421

0

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1

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null

0

1

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1

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7

c9287aead3165b47fba22a664aab50ec4fa3458e

7,786

py

Python

Scripts/Examples/FL6-Font-Drop Anchors.py

twardoch/TypeRig

121838d98ed41160dbebf575d0a5623def0ce256

[ "BSD-3-Clause" ]

1

2020-07-11T06:18:49.000Z

Scripts/Examples/FL6-Font-Drop Anchors.py

twardoch/TypeRig

121838d98ed41160dbebf575d0a5623def0ce256

[ "BSD-3-Clause" ]

null

Scripts/Examples/FL6-Font-Drop Anchors.py

twardoch/TypeRig

121838d98ed41160dbebf575d0a5623def0ce256

[ "BSD-3-Clause" ]

null

#FLM: Font: Auto Anchors Drop # VER: 1.0 #---------------------------------- # Foundry: Borges Type # Typeface: Future Tense # Date: 22.10.2018 #---------------------------------- # - Dependancies import fontlab as fl6 from typerig.proxy import pFont from typerig.glyph import eGlyph # - Init ------------------------------------------------ font = pFont() clear_anchors = True work_layer = None # -- Diacritic creation pattern (config dictionary) diac_cfg_all = { 'A':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'C':[('top', work_layer, (0, 800), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'D':[('top', work_layer, (0, 800), ('A', None), 5, False, False) ], 'E':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'G':[('top', work_layer, (0, 800), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'H':[('top', work_layer, (0, 800), ('AT', None), 5, False, False) ], 'I':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'J':[('top', work_layer, (0, 800), ('AT', None), 5, False, False) ], 'K':[('top', work_layer, (-30, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (-10, 0), ('C', None), 5, False, False)], 'L':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'N':[('top', work_layer, (0, 800), ('A', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'O':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'R':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'S':[('top', work_layer, (0, 800), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'T':[('top', work_layer, (0, 800), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'U':[('top', work_layer, (0, 800), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'W':[('top', work_layer, (0, 800), ('A', None), 5, False, False) ], 'Y':[('top', work_layer, (0, 800), ('C', None), 5, False, False) ], 'Z':[('top', work_layer, (0, 800), ('AT', None), 5, False, False) ], 'a':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'c':[('top', work_layer, (0, 695), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'd':[('top', work_layer, (0, 695), ('A', None), 5, False, False) ], 'e':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'g':[('top', work_layer, (0, 695), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'h':[('top', work_layer, (0, 695), ('AT', None), 5, False, False) ], 'i':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'j':[('top', work_layer, (0, 695), ('AT', None), 5, False, False) ], 'k':[('top', work_layer, (-20, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (-10, 0), ('C', None), 5, False, False)], 'l':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'n':[('top', work_layer, (0, 695), ('A', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'o':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'r':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 's':[('top', work_layer, (0, 695), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 't':[('top', work_layer, (0, 695), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'u':[('top', work_layer, (0, 695), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'w':[('top', work_layer, (0, 695), ('A', None), 5, False, False) ], 'y':[('top', work_layer, (0, 695), ('C', None), 5, False, False) ], 'z':[('top', work_layer, (0, 695), ('AT', None), 5, False, False) ] } diac_cfg_smcp = { 'a':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'c':[('top', work_layer, (0, 625), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'd':[('top', work_layer, (0, 625), ('A', None), 5, False, False) ], 'e':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'g':[('top', work_layer, (0, 625), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'h':[('top', work_layer, (0, 625), ('AT', None), 5, False, False) ], 'i':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('R', None), 5, False, False)], 'j':[('top', work_layer, (0, 625), ('AT', None), 5, False, False) ], 'k':[('top', work_layer, (-20, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (-10, 0), ('C', None), 5, False, False)], 'l':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'n':[('top', work_layer, (0, 625), ('A', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'o':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'r':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 's':[('top', work_layer, (0, 625), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 't':[('top', work_layer, (0, 625), ('AT', None), 5, False, False), ('bottom', work_layer, (0, 0), ('A', None), 5, False, False)], 'u':[('top', work_layer, (0, 625), ('C', None), 5, False, False), ('bottom', work_layer, (0, 0), ('C', None), 5, False, False)], 'w':[('top', work_layer, (0, 625), ('A', None), 5, False, False) ], 'y':[('top', work_layer, (0, 625), ('C', None), 5, False, False) ], 'z':[('top', work_layer, (0, 625), ('AT', None), 5, False, False) ] } # - Procedures --------------------------------------------- def dropAnchors(glyph, control): # - Init work_name = glyph.name.split('.')[0] # - Process if work_name in control.keys(): work_glyph = eGlyph(font.fg, glyph) #work_glyph.clearAnchors(work_layer) for ctr_tuple in control[work_name]: work_glyph.dropAnchor(*ctr_tuple) work_glyph.update() work_glyph.updateObject(work_glyph.fl, 'Drop anchors: %s.' %work_glyph.name) # - Process ------------------------------------------------ for glyph in font.glyphs(): if 'smcp' not in glyph.name: dropAnchors(glyph, diac_cfg_all) if 'smcp' in glyph.name: dropAnchors(glyph, diac_cfg_smcp) # - Finish font.update() print 'DONE.'

68.902655

137

0.514642

1,159

7,786

3.354616

0.083693

0.226852

0.246914

0.37037

0.841821

0.841049

0.82356

0.817901

0

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0.17159

7,786

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68.902655

0.537674

0.060108

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0

null

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0

null

1

0

null

0

1

0

10

c93a91a3b01d7e3dd65d9c4574395812a29410c8

230

py

Python

pants-plugins/experimental/mypyc/register.py

lilatomic/pants-plugins

0757fcf52325fa5809211f7a7a25081a134333a5

[ "Apache-2.0" ]

4

2022-02-14T23:14:21.000Z

2022-03-29T12:39:26.000Z

pants-plugins/experimental/mypyc/register.py

lilatomic/pants-plugins

0757fcf52325fa5809211f7a7a25081a134333a5

[ "Apache-2.0" ]

36

2022-02-02T05:01:04.000Z

2022-03-31T16:46:34.000Z

pants-plugins/experimental/mypyc/register.py

lilatomic/pants-plugins

0757fcf52325fa5809211f7a7a25081a134333a5

[ "Apache-2.0" ]

2

2022-02-14T04:16:19.000Z

2022-03-02T11:22:37.000Z

from experimental.mypyc.rules import rules as mypyc_rules from experimental.mypyc.target_types import MyPycPythonDistribution def rules(): return (*mypyc_rules(),) def target_types(): return (MyPycPythonDistribution,)

20.909091

67

0.786957

26

230

6.807692

0.423077

0.169492

0.237288

0

0.130435

230

10

68

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1

0.333333

true

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

a31cf33d8480498361f7aa3e7174b19a227c9765

1,327

py

Python

main.py

statsu1990/kaggle_ion_switching

487025284cdfc79741a744e73f77b4bf86490e30

[ "MIT" ]

null

main.py

statsu1990/kaggle_ion_switching

487025284cdfc79741a744e73f77b4bf86490e30

[ "MIT" ]

null

main.py

statsu1990/kaggle_ion_switching

487025284cdfc79741a744e73f77b4bf86490e30

[ "MIT" ]

null

import make_model as mm #mm.Model_v5_0_0().train_model() #mm.Model_v5_0_1().train_model() #mm.Model_v5_0_2().train_model() #mm.Model_v5_0_3().train_model() #mm.Model_v5_0_4().train_model() #mm.Model_v5_0_5().train_model() #mm.Model_v5_0_11().train_model() #mm.Model_v5_0_10().train_model() #mm.Model_v5_0_9().train_model() #mm.Model_v5_0_8().train_model() #mm.Model_v5_0_8_1().pred_test() #mm.Model_v5_0_7().train_model() #mm.Model_v5_0_6().train_model() #mm.Model_v5_0_5_1().train_model() #mm.Model_v5_0_5_2().train_model() #mm.Model_v5_0_5_3().train_model() #mm.Model_v5_0_5_4().train_model() #mm.Model_v5_0_5_5().train_model() #mm.Model_v5_0_5_6().train_model() #mm.Model_v5_0_5_7().train_model() #mm.Model_v5_0_5_8().train_model() #mm.Model_v5_0_5_9().train_model() #mm.Model_v5_0_12().train_model() #mm.Model_v5_1_0().train_model() #mm.Model_v5_1_1().train_model() #mm.Model_v5_2_0_0().train_model() #mm.Model_v5_2_0_1().train_model() #mm.Model_v5_3_0().train_model() #mm.Model_v5_3_1().train_model() #mm.Model_v5_3_2().train_model() #mm.Model_v6_0_0().train_model() #mm.Model_v6_0_1().train_model() #mm.Model_v6_0_2().train_model() #mm.Model_v6_0_3().train_model() #mm.Model_v6_1_0().train_model() mm.Model_v6_1_1().train_model() #mm.Model_v6_1_2().train_model()

27.081633

35

0.730972

276

1,327

2.931159

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8

a33ea9a2e20e6c1aff15ddddf949d51f44be754e

16,088

py

Python

scripts/options.py

edwardoughton/ictp4d

0e36b3c4515e57cc9210bd22f2ab761f2aa750d6

[ "MIT" ]

4

2021-02-07T19:36:57.000Z

2021-05-20T16:46:02.000Z

scripts/options.py

edwardoughton/ictp4d

0e36b3c4515e57cc9210bd22f2ab761f2aa750d6

[ "MIT" ]

null

scripts/options.py

edwardoughton/ictp4d

0e36b3c4515e57cc9210bd22f2ab761f2aa750d6

[ "MIT" ]

null

""" Options consisting of scenarios and strategies. Country parameters consist of those parameters which are specific to each country. Written by Ed Oughton January 2020 #strategy is defined based on generation_core_backhaul_sharing_networks_spectrum_tax generation: technology generation, so 3G or 4G core: type of core data transport network, eg. evolved packet core (4G) backhaul: type of backhaul, so fiber or wireless sharing: the type of infrastructure sharing, active, passive etc.. network: relates to the number of networks, as defined in country parameters spectrum: type of spectrum strategy, so baseline, high or low tax: type of taxation strategy, so baseline, high or low integration: option to undertake regional integration """ OPTIONS = { 'technology_options': [ { 'scenario': 'low_10_10_10', 'strategy': '3G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_10_10_10', 'strategy': '3G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_10_10_10', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_10_10_10', 'strategy': '4G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '3G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '3G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '4G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '3G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '3G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '4G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '3G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '3G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '4G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '3G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '3G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '4G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '3G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '3G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '4G_epc_fiber_baseline_baseline_baseline_baseline_baseline', }, ], 'business_model_options': [ { 'scenario': 'low_10_10_10', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_10_10_10', 'strategy': '4G_epc_wireless_psb_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_10_10_10', 'strategy': '4G_epc_wireless_moran_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_10_10_10', 'strategy': '4G_epc_wireless_srn_srn_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '4G_epc_wireless_psb_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '4G_epc_wireless_moran_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_10_10_10', 'strategy': '4G_epc_wireless_srn_srn_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '4G_epc_wireless_psb_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '4G_epc_wireless_moran_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_10_10_10', 'strategy': '4G_epc_wireless_srn_srn_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '4G_epc_wireless_psb_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '4G_epc_wireless_moran_baseline_baseline_baseline_baseline', }, { 'scenario': 'low_2_2_2', 'strategy': '4G_epc_wireless_srn_srn_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '4G_epc_wireless_psb_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '4G_epc_wireless_moran_baseline_baseline_baseline_baseline', }, { 'scenario': 'baseline_2_2_2', 'strategy': '4G_epc_wireless_srn_srn_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '4G_epc_wireless_baseline_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '4G_epc_wireless_psb_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '4G_epc_wireless_moran_baseline_baseline_baseline_baseline', }, { 'scenario': 'high_2_2_2', 'strategy': '4G_epc_wireless_srn_srn_baseline_baseline_baseline', }, ], } COUNTRY_PARAMETERS = { 'CIV': { 'luminosity': { 'high': 5, 'medium': 1, }, 'arpu': { 'high': 8, 'medium': 6, 'low': 2, }, 'networks': { 'baseline_urban': 3, 'baseline_suburban': 3, 'baseline_rural': 3, 'srn_urban': 3, 'srn_suburban': 3, 'srn_rural': 1, }, 'frequencies': { '3G': [ { 'frequency': 1800, 'bandwidth': '2x10', }, { 'frequency': 2100, 'bandwidth': '2x10', }, ], '4G': [ { 'frequency': 800, 'bandwidth': '2x10', }, { 'frequency': 1800, 'bandwidth': '2x10', }, ], }, 'financials': { 'wacc': 15, 'profit_margin': 10, 'spectrum_coverage_baseline_usd_mhz_pop': 0.04, 'spectrum_capacity_baseline_usd_mhz_pop': 0.03, 'tax_low': 10, 'tax_baseline': 25, 'tax_high': 40, 'administration_percentage_of_network_cost': 10, }, }, 'MLI': { 'luminosity': { 'high': 5, 'medium': 1, }, 'arpu': { 'high': 8, 'medium': 6, 'low': 2, }, 'networks': { 'baseline_urban': 2, 'baseline_suburban': 2, 'baseline_rural': 2, 'srn_urban': 2, 'srn_suburban': 2, 'srn_rural': 1, }, 'frequencies': { '3G': [ { 'frequency': 1800, 'bandwidth': '2x10', }, { 'frequency': 2100, 'bandwidth': '2x10', }, ], '4G': [ { 'frequency': 700, 'bandwidth': '2x10', }, { 'frequency': 1800, 'bandwidth': '2x10', }, ], }, 'financials': { 'wacc': 15, 'profit_margin': 10, 'spectrum_coverage_baseline_usd_mhz_pop': 0.04, 'spectrum_capacity_baseline_usd_mhz_pop': 0.03, 'tax_low': 10, 'tax_baseline': 30, 'tax_high': 40, 'administration_percentage_of_network_cost': 10, }, }, 'SEN': { 'luminosity': { 'high': 5, 'medium': 1, }, 'arpu': { 'high': 8, 'medium': 6, 'low': 2, }, 'networks': { 'baseline_urban': 3, 'baseline_suburban': 3, 'baseline_rural': 3, 'srn_urban': 3, 'srn_suburban': 3, 'srn_rural': 1, }, 'frequencies': { '3G': [ { 'frequency': 1800, 'bandwidth': '2x10', }, { 'frequency': 2100, 'bandwidth': '2x10', }, ], '4G': [ { 'frequency': 800, 'bandwidth': '2x10', }, { 'frequency': 1800, 'bandwidth': '2x10', }, ], }, 'financials': { 'wacc': 15, 'profit_margin': 10, 'spectrum_coverage_baseline_usd_mhz_pop': 0.04, 'spectrum_capacity_baseline_usd_mhz_pop': 0.03, 'tax_low': 10, 'tax_baseline': 30, 'tax_high': 40, 'administration_percentage_of_network_cost': 10, }, }, 'KEN': { 'luminosity': { 'high': 5, 'medium': 1, }, 'arpu': { 'high': 8, 'medium': 6, 'low': 2, }, 'networks': { 'baseline_urban': 3, 'baseline_suburban': 3, 'baseline_rural': 3, 'srn_urban': 3, 'srn_suburban': 3, 'srn_rural': 1, }, 'frequencies': { '3G': [ { 'frequency': 1800, 'bandwidth': '2x10', }, { 'frequency': 2100, 'bandwidth': '2x10', }, ], '4G': [ { 'frequency': 700, 'bandwidth': '2x10', }, { 'frequency': 800, 'bandwidth': '2x10', }, ], }, 'financials': { 'wacc': 15, 'profit_margin': 10, 'spectrum_coverage_baseline_usd_mhz_pop': 0.1, 'spectrum_capacity_baseline_usd_mhz_pop': 0.08, 'tax_low': 10, 'tax_baseline': 30, 'tax_high': 40, 'administration_percentage_of_network_cost': 10, }, }, 'TZA': { 'luminosity': { 'high': 5, 'medium': 1, }, 'arpu': { 'high': 8, 'medium': 3, 'low': 2, }, 'networks': { 'baseline_urban': 3, 'baseline_suburban': 3, 'baseline_rural': 3, 'srn_urban': 3, 'srn_suburban': 3, 'srn_rural': 1, }, 'frequencies': { '3G': [ { 'frequency': 1800, 'bandwidth': '2x10', }, { 'frequency': 2100, 'bandwidth': '2x10', }, ], '4G': [ { 'frequency': 700, 'bandwidth': '2x10', }, { 'frequency': 1800, 'bandwidth': '2x10', }, ], }, 'financials': { 'wacc': 15, 'profit_margin': 10, 'spectrum_coverage_baseline_usd_mhz_pop': 0.1, 'spectrum_capacity_baseline_usd_mhz_pop': 0.08, 'tax_low': 10, 'tax_baseline': 30, 'tax_high': 40, 'administration_percentage_of_network_cost': 10, }, }, 'UGA': { 'luminosity': { 'high': 5, 'medium': 1, }, 'arpu': { 'high': 8, 'medium': 3, 'low': 2, }, 'networks': { 'baseline_urban': 3, 'baseline_suburban': 3, 'baseline_rural': 3, 'srn_urban': 3, 'srn_suburban': 3, 'srn_rural': 1, }, 'frequencies': { '3G': [ { 'frequency': 1800, 'bandwidth': '2x10', }, { 'frequency': 2100, 'bandwidth': '2x10', }, ], '4G': [ { 'frequency': 800, 'bandwidth': '2x10', }, { 'frequency': 1800, 'bandwidth': '2x10', }, ], }, 'financials': { 'wacc': 15, 'profit_margin': 10, 'spectrum_coverage_baseline_usd_mhz_pop': 0.1, 'spectrum_capacity_baseline_usd_mhz_pop': 0.08, 'tax_low': 10, 'tax_baseline': 30, 'tax_high': 40, 'administration_percentage_of_network_cost': 10, }, }, }

30.240602

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9

a346661106836df18572fe6396ffa0e8a37e0707

69

py

Python

server/ferret/pnw/export/pnw.py

Lyrositor/pnw-ferret

3eacd2f56e9811c1ccc9c5dafdcb4738ca767193

[ "CC0-1.0" ]

2

2019-11-02T22:40:13.000Z

2019-11-07T23:02:35.000Z

server/ferret/pnw/export/pnw.py

Lyrositor/pnw-ferret

3eacd2f56e9811c1ccc9c5dafdcb4738ca767193

[ "CC0-1.0" ]

null

server/ferret/pnw/export/pnw.py

Lyrositor/pnw-ferret

3eacd2f56e9811c1ccc9c5dafdcb4738ca767193

[ "CC0-1.0" ]

null

from ferret.pnw.constants import * from ferret.pnw.formulas import *

23

34

0.797101

10

69

5.5

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0.472727

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69

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true

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null

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0

1

0

1

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7

a36d0ec395c69e356042f2685212ab64465c76e1

47,662

py

Python

report/customer_vendor_statement.py

alconor/partner_statement

4aead85436a065b3d8608aef06d8ec7a9169e973

[ "Unlicense" ]

null

report/customer_vendor_statement.py

alconor/partner_statement

4aead85436a065b3d8608aef06d8ec7a9169e973

[ "Unlicense" ]

null

report/customer_vendor_statement.py

alconor/partner_statement

4aead85436a065b3d8608aef06d8ec7a9169e973

[ "Unlicense" ]

null

# -*- coding: utf-8 -*- # Copyright 2017 Eficent Business and IT Consulting Services S.L. # (http://www.eficent.com) # License AGPL-3.0 or later (https://www.gnu.org/licenses/agpl.html). from datetime import datetime, timedelta from openerp.tools import DEFAULT_SERVER_DATE_FORMAT from openerp import api, fields, models class CustomerVendorStatement(models.AbstractModel): """Model of Customer Activity Statement""" _name = 'report.customer_vendor_statement.statement' def _format_date_to_partner_lang(self, str_date, partner_id): lang_code = self.env['res.partner'].browse(partner_id).lang lang_id = self.env['res.lang']._lang_get(lang_code) lang = self.env['res.lang'].browse(lang_id) date = datetime.strptime(str_date, DEFAULT_SERVER_DATE_FORMAT).date() return date.strftime(lang_id.date_format) def _initial_balance_sql_q1(self, partners, date_start): return """ SELECT l.partner_id, l.currency_id, l.company_id, CASE WHEN l.currency_id is not null AND l.amount_currency > 0.0 THEN sum(l.amount_currency) ELSE sum(l.debit) END as debit, CASE WHEN l.currency_id is not null AND l.amount_currency < 0.0 THEN sum(l.amount_currency * (-1)) ELSE sum(l.credit) END as credit FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) WHERE l.partner_id IN (%s) AND at.type = 'receivable' AND l.date <= '%s' AND not l.blocked GROUP BY l.partner_id, l.currency_id, l.amount_currency, l.company_id """ % (partners, date_start) def _initial_balance_sql_q1_payable(self, partners, date_start): return """ SELECT l.partner_id, l.currency_id, l.company_id, CASE WHEN l.currency_id is not null AND l.amount_currency > 0.0 THEN sum(l.amount_currency) ELSE sum(l.debit) END as debit, CASE WHEN l.currency_id is not null AND l.amount_currency < 0.0 THEN sum(l.amount_currency * (-1)) ELSE sum(l.credit) END as credit FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) WHERE l.partner_id IN (%s) AND at.type = 'payable' AND l.date <= '%s' AND not l.blocked GROUP BY l.partner_id, l.currency_id, l.amount_currency, l.company_id """ % (partners, date_start) def _initial_balance_sql_q1_receivable_and_payable(self, partners, date_start): return """ SELECT l.partner_id, l.currency_id, l.company_id, CASE WHEN l.currency_id is not null AND l.amount_currency > 0.0 THEN sum(l.amount_currency) ELSE sum(l.debit) END as debit, CASE WHEN l.currency_id is not null AND l.amount_currency < 0.0 THEN sum(l.amount_currency * (-1)) ELSE sum(l.credit) END as credit FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) WHERE l.partner_id IN (%s) AND (at.type = 'payable' OR at.type = 'receivable') AND l.date <= '%s' AND not l.blocked GROUP BY l.partner_id, l.currency_id, l.amount_currency, l.company_id """ % (partners, date_start) def _initial_balance_sql_q2(self, company_id): return """ SELECT Q1.partner_id, debit-credit AS balance, COALESCE(Q1.currency_id, c.currency_id) AS currency_id FROM Q1 JOIN res_company c ON (c.id = Q1.company_id) WHERE c.id = %s """ % company_id def _initial_balance_sql_q2_payable(self, company_id): return """ SELECT Q1.partner_id, debit-credit AS balance, COALESCE(Q1.currency_id, c.currency_id) AS currency_id FROM Q1 JOIN res_company c ON (c.id = Q1.company_id) WHERE c.id = %s """ % company_id def _initial_balance_sql_q2_receivable_and_payable(self, company_id): return """ SELECT Q1.partner_id, debit-credit AS balance, COALESCE(Q1.currency_id, c.currency_id) AS currency_id FROM Q1 JOIN res_company c ON (c.id = Q1.company_id) WHERE c.id = %s """ % company_id def _get_account_initial_balance(self, company_id, partner_ids, date_start): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_start = datetime.strptime( date_start, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s) SELECT partner_id, currency_id, balance FROM Q2""" % (self._initial_balance_sql_q1(partners, date_start), self._initial_balance_sql_q2(company_id))) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _get_account_initial_balance_payable(self, company_id, partner_ids, date_start): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_start = datetime.strptime( date_start, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s) SELECT partner_id, currency_id, balance FROM Q2""" % (self._initial_balance_sql_q1_payable(partners, date_start), self._initial_balance_sql_q2_payable(company_id))) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _get_account_initial_balance_receivable_and_payable(self, company_id, partner_ids, date_start): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_start = datetime.strptime( date_start, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s) SELECT partner_id, currency_id, balance FROM Q2""" % (self._initial_balance_sql_q1_receivable_and_payable(partners, date_start), self._initial_balance_sql_q2_receivable_and_payable(company_id))) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _display_lines_sql_q1(self, partners, date_start, date_end): return """ SELECT m.name AS move_id, l.partner_id, l.date, l.name, l.ref, l.blocked, l.currency_id, l.company_id, CASE WHEN (l.currency_id is not null AND l.amount_currency > 0.0) THEN sum(l.amount_currency) ELSE sum(l.debit) END as debit, CASE WHEN (l.currency_id is not null AND l.amount_currency < 0.0) THEN sum(l.amount_currency * (-1)) ELSE sum(l.credit) END as credit, CASE WHEN l.date_maturity is null THEN l.date ELSE l.date_maturity END as date_maturity FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) WHERE l.partner_id IN (%s) AND at.type = 'receivable' AND '%s' < l.date AND l.date <= '%s' GROUP BY l.partner_id, m.name, l.date, l.date_maturity, l.name, l.ref, l.blocked, l.currency_id, l.amount_currency, l.company_id """ % (partners, date_start, date_end) def _display_lines_sql_q1_payable(self, partners, date_start, date_end): return """ SELECT m.name AS move_id, l.partner_id, l.date, l.name, l.ref, l.blocked, l.currency_id, l.company_id, CASE WHEN (l.currency_id is not null AND l.amount_currency > 0.0) THEN sum(l.amount_currency) ELSE sum(l.debit) END as debit, CASE WHEN (l.currency_id is not null AND l.amount_currency < 0.0) THEN sum(l.amount_currency * (-1)) ELSE sum(l.credit) END as credit, CASE WHEN l.date_maturity is null THEN l.date ELSE l.date_maturity END as date_maturity FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) WHERE l.partner_id IN (%s) AND at.type = 'payable' AND '%s' < l.date AND l.date <= '%s' GROUP BY l.partner_id, m.name, l.date, l.date_maturity, l.name, l.ref, l.blocked, l.currency_id, l.amount_currency, l.company_id """ % (partners, date_start, date_end) def _display_lines_sql_q1_receivable_and_payable(self, partners, date_start, date_end): return """ SELECT m.name AS move_id, l.partner_id, l.date, l.name, l.ref, l.blocked, l.currency_id, l.company_id, CASE WHEN (l.currency_id is not null AND l.amount_currency > 0.0) THEN sum(l.amount_currency) ELSE sum(l.debit) END as debit, CASE WHEN (l.currency_id is not null AND l.amount_currency < 0.0) THEN sum(l.amount_currency * (-1)) ELSE sum(l.credit) END as credit, CASE WHEN l.date_maturity is null THEN l.date ELSE l.date_maturity END as date_maturity FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) WHERE l.partner_id IN (%s) AND (at.type = 'payable' OR at.type = 'receivable') AND '%s' < l.date AND l.date <= '%s' GROUP BY l.partner_id, m.name, l.date, l.date_maturity, l.name, l.ref, l.blocked, l.currency_id, l.amount_currency, l.company_id """ % (partners, date_start, date_end) def _display_lines_sql_q2(self, company_id): return """ SELECT Q1.partner_id, move_id, date, date_maturity, Q1.name, ref, debit, credit, debit-credit as amount, blocked, COALESCE(Q1.currency_id, c.currency_id) AS currency_id FROM Q1 JOIN res_company c ON (c.id = Q1.company_id) WHERE c.id = %s """ % company_id def _display_lines_sql_q2_payable(self, company_id): return """ SELECT Q1.partner_id, move_id, date, date_maturity, Q1.name, ref, debit, credit, debit-credit as amount, blocked, COALESCE(Q1.currency_id, c.currency_id) AS currency_id FROM Q1 JOIN res_company c ON (c.id = Q1.company_id) WHERE c.id = %s """ % company_id def _display_lines_sql_q2_receivable_and_payable(self, company_id): return """ SELECT Q1.partner_id, move_id, date, date_maturity, Q1.name, ref, debit, credit, debit-credit as amount, blocked, COALESCE(Q1.currency_id, c.currency_id) AS currency_id FROM Q1 JOIN res_company c ON (c.id = Q1.company_id) WHERE c.id = %s """ % company_id def _get_account_display_lines(self, company_id, partner_ids, date_start, date_end): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_start = datetime.strptime( date_start, DEFAULT_SERVER_DATE_FORMAT).date() date_end = datetime.strptime( date_end, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s) SELECT partner_id, move_id, date, date_maturity, name, ref, debit, credit, amount, blocked, currency_id FROM Q2 ORDER BY date, date_maturity, move_id""" % ( self._display_lines_sql_q1(partners, date_start, date_end), self._display_lines_sql_q2(company_id))) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _get_account_display_lines_payable(self, company_id, partner_ids, date_start, date_end): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_start = datetime.strptime( date_start, DEFAULT_SERVER_DATE_FORMAT).date() date_end = datetime.strptime( date_end, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s) SELECT partner_id, move_id, date, date_maturity, name, ref, debit, credit, amount, blocked, currency_id FROM Q2 ORDER BY date, date_maturity, move_id""" % ( self._display_lines_sql_q1_payable(partners, date_start, date_end), self._display_lines_sql_q2_payable(company_id))) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _get_account_display_lines_receivable_and_payable(self, company_id, partner_ids, date_start, date_end): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_start = datetime.strptime( date_start, DEFAULT_SERVER_DATE_FORMAT).date() date_end = datetime.strptime( date_end, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s) SELECT partner_id, move_id, date, date_maturity, name, ref, debit, credit, amount, blocked, currency_id FROM Q2 ORDER BY date, date_maturity, move_id""" % ( self._display_lines_sql_q1_receivable_and_payable(partners, date_start, date_end), self._display_lines_sql_q2_receivable_and_payable(company_id))) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _show_buckets_sql_q1(self, partners, date_end): return """ SELECT l.partner_id, l.currency_id, l.company_id, l.move_id, CASE WHEN l.balance > 0.0 THEN l.balance - sum(coalesce(pd.amount, 0.0)) ELSE l.balance + sum(coalesce(pc.amount, 0.0)) END AS open_due, CASE WHEN l.balance > 0.0 THEN l.amount_currency - sum(coalesce(pd.amount_currency, 0.0)) ELSE l.amount_currency + sum(coalesce(pc.amount_currency, 0.0)) END AS open_due_currency, CASE WHEN l.date_maturity is null THEN l.date ELSE l.date_maturity END as date_maturity FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) LEFT JOIN (SELECT pr.* FROM account_partial_reconcile pr INNER JOIN account_move_line l2 ON pr.credit_move_id = l2.id WHERE l2.date <= '%s' ) as pd ON pd.debit_move_id = l.id LEFT JOIN (SELECT pr.* FROM account_partial_reconcile pr INNER JOIN account_move_line l2 ON pr.debit_move_id = l2.id WHERE l2.date <= '%s' ) as pc ON pc.credit_move_id = l.id WHERE l.partner_id IN (%s) AND at.type = 'receivable' AND not l.reconciled AND not l.blocked GROUP BY l.partner_id, l.currency_id, l.date, l.date_maturity, l.amount_currency, l.balance, l.move_id, l.company_id """ % (date_end, date_end, partners) def _show_buckets_sql_q1_payable(self, partners, date_end): return """ SELECT l.partner_id, l.currency_id, l.company_id, l.move_id, CASE WHEN l.balance > 0.0 THEN l.balance - sum(coalesce(pd.amount, 0.0)) ELSE l.balance + sum(coalesce(pc.amount, 0.0)) END AS open_due, CASE WHEN l.balance > 0.0 THEN l.amount_currency - sum(coalesce(pd.amount_currency, 0.0)) ELSE l.amount_currency + sum(coalesce(pc.amount_currency, 0.0)) END AS open_due_currency, CASE WHEN l.date_maturity is null THEN l.date ELSE l.date_maturity END as date_maturity FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) LEFT JOIN (SELECT pr.* FROM account_partial_reconcile pr INNER JOIN account_move_line l2 ON pr.credit_move_id = l2.id WHERE l2.date <= '%s' ) as pd ON pd.debit_move_id = l.id LEFT JOIN (SELECT pr.* FROM account_partial_reconcile pr INNER JOIN account_move_line l2 ON pr.debit_move_id = l2.id WHERE l2.date <= '%s' ) as pc ON pc.credit_move_id = l.id WHERE l.partner_id IN (%s) AND at.type = 'payable' AND not l.reconciled AND not l.blocked GROUP BY l.partner_id, l.currency_id, l.date, l.date_maturity, l.amount_currency, l.balance, l.move_id, l.company_id """ % (date_end, date_end, partners) def _show_buckets_sql_q1_receivable_and_payable(self, partners, date_end): return """ SELECT l.partner_id, l.currency_id, l.company_id, l.move_id, CASE WHEN l.balance > 0.0 THEN l.balance - sum(coalesce(pd.amount, 0.0)) ELSE l.balance + sum(coalesce(pc.amount, 0.0)) END AS open_due, CASE WHEN l.balance > 0.0 THEN l.amount_currency - sum(coalesce(pd.amount_currency, 0.0)) ELSE l.amount_currency + sum(coalesce(pc.amount_currency, 0.0)) END AS open_due_currency, CASE WHEN l.date_maturity is null THEN l.date ELSE l.date_maturity END as date_maturity FROM account_move_line l JOIN account_account_type at ON (at.id = l.user_type_id) JOIN account_move m ON (l.move_id = m.id) LEFT JOIN (SELECT pr.* FROM account_partial_reconcile pr INNER JOIN account_move_line l2 ON pr.credit_move_id = l2.id WHERE l2.date <= '%s' ) as pd ON pd.debit_move_id = l.id LEFT JOIN (SELECT pr.* FROM account_partial_reconcile pr INNER JOIN account_move_line l2 ON pr.debit_move_id = l2.id WHERE l2.date <= '%s' ) as pc ON pc.credit_move_id = l.id WHERE l.partner_id IN (%s) AND (at.type = 'payable' OR at.type = 'receivable') AND not l.reconciled AND not l.blocked GROUP BY l.partner_id, l.currency_id, l.date, l.date_maturity, l.amount_currency, l.balance, l.move_id, l.company_id """ % (date_end, date_end, partners) def _show_buckets_sql_q2(self, today, minus_30, minus_60, minus_90, minus_120): return """ SELECT partner_id, currency_id, date_maturity, open_due, open_due_currency, move_id, company_id, CASE WHEN '%s' <= date_maturity AND currency_id is null THEN open_due WHEN '%s' <= date_maturity AND currency_id is not null THEN open_due_currency ELSE 0.0 END as current, CASE WHEN '%s' < date_maturity AND date_maturity < '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity < '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_1_30, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_30_60, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_60_90, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_90_120, CASE WHEN date_maturity <= '%s' AND currency_id is null THEN open_due WHEN date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_over_120 FROM Q1 GROUP BY partner_id, currency_id, date_maturity, open_due, open_due_currency, move_id, company_id """ % (today, today, minus_30, today, minus_30, today, minus_60, minus_30, minus_60, minus_30, minus_90, minus_60, minus_90, minus_60, minus_120, minus_90, minus_120, minus_90, minus_120, minus_120) def _show_buckets_sql_q2_payable(self, today, minus_30, minus_60, minus_90, minus_120): return """ SELECT partner_id, currency_id, date_maturity, open_due, open_due_currency, move_id, company_id, CASE WHEN '%s' <= date_maturity AND currency_id is null THEN open_due WHEN '%s' <= date_maturity AND currency_id is not null THEN open_due_currency ELSE 0.0 END as current, CASE WHEN '%s' < date_maturity AND date_maturity < '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity < '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_1_30, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_30_60, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_60_90, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_90_120, CASE WHEN date_maturity <= '%s' AND currency_id is null THEN open_due WHEN date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_over_120 FROM Q1 GROUP BY partner_id, currency_id, date_maturity, open_due, open_due_currency, move_id, company_id """ % (today, today, minus_30, today, minus_30, today, minus_60, minus_30, minus_60, minus_30, minus_90, minus_60, minus_90, minus_60, minus_120, minus_90, minus_120, minus_90, minus_120, minus_120) def _show_buckets_sql_q2_receivable_and_payable(self, today, minus_30, minus_60, minus_90, minus_120): return """ SELECT partner_id, currency_id, date_maturity, open_due, open_due_currency, move_id, company_id, CASE WHEN '%s' <= date_maturity AND currency_id is null THEN open_due WHEN '%s' <= date_maturity AND currency_id is not null THEN open_due_currency ELSE 0.0 END as current, CASE WHEN '%s' < date_maturity AND date_maturity < '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity < '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_1_30, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_30_60, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_60_90, CASE WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is null THEN open_due WHEN '%s' < date_maturity AND date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_90_120, CASE WHEN date_maturity <= '%s' AND currency_id is null THEN open_due WHEN date_maturity <= '%s' AND currency_id is not null THEN open_due_currency ELSE 0.0 END as b_over_120 FROM Q1 GROUP BY partner_id, currency_id, date_maturity, open_due, open_due_currency, move_id, company_id """ % (today, today, minus_30, today, minus_30, today, minus_60, minus_30, minus_60, minus_30, minus_90, minus_60, minus_90, minus_60, minus_120, minus_90, minus_120, minus_90, minus_120, minus_120) def _show_buckets_sql_q3(self, company_id): return """ SELECT Q2.partner_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120, COALESCE(Q2.currency_id, c.currency_id) AS currency_id FROM Q2 JOIN res_company c ON (c.id = Q2.company_id) WHERE c.id = %s """ % company_id def _show_buckets_sql_q3_payable(self, company_id): return """ SELECT Q2.partner_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120, COALESCE(Q2.currency_id, c.currency_id) AS currency_id FROM Q2 JOIN res_company c ON (c.id = Q2.company_id) WHERE c.id = %s """ % company_id def _show_buckets_sql_q3_receivable_and_payable(self, company_id): return """ SELECT Q2.partner_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120, COALESCE(Q2.currency_id, c.currency_id) AS currency_id FROM Q2 JOIN res_company c ON (c.id = Q2.company_id) WHERE c.id = %s """ % company_id def _show_buckets_sql_q4(self): return """ SELECT partner_id, currency_id, sum(current) as current, sum(b_1_30) as b_1_30, sum(b_30_60) as b_30_60, sum(b_60_90) as b_60_90, sum(b_90_120) as b_90_120, sum(b_over_120) as b_over_120 FROM Q3 GROUP BY partner_id, currency_id """ def _show_buckets_sql_q4_payable(self): return """ SELECT partner_id, currency_id, sum(current) as current, sum(b_1_30) as b_1_30, sum(b_30_60) as b_30_60, sum(b_60_90) as b_60_90, sum(b_90_120) as b_90_120, sum(b_over_120) as b_over_120 FROM Q3 GROUP BY partner_id, currency_id """ def _show_buckets_sql_q4_receivable_and_payable(self): return """ SELECT partner_id, currency_id, sum(current) as current, sum(b_1_30) as b_1_30, sum(b_30_60) as b_30_60, sum(b_60_90) as b_60_90, sum(b_90_120) as b_90_120, sum(b_over_120) as b_over_120 FROM Q3 GROUP BY partner_id, currency_id """ _bucket_dates = { 'today': fields.date.today(), 'minus_30': fields.date.today() - timedelta(days=30), 'minus_60': fields.date.today() - timedelta(days=60), 'minus_90': fields.date.today() - timedelta(days=90), 'minus_120': fields.date.today() - timedelta(days=120), } def _get_account_show_buckets(self, company_id, partner_ids, date_end): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_end = datetime.strptime( date_end, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s), Q3 AS (%s), Q4 AS (%s) SELECT partner_id, currency_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120, current+b_1_30+b_30_60+b_60_90+b_90_120+b_over_120 AS balance FROM Q4 GROUP BY partner_id, currency_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120""" % ( self._show_buckets_sql_q1(partners, date_end), self._show_buckets_sql_q2( self._bucket_dates['today'], self._bucket_dates['minus_30'], self._bucket_dates['minus_60'], self._bucket_dates['minus_90'], self._bucket_dates['minus_120']), self._show_buckets_sql_q3(company_id), self._show_buckets_sql_q4())) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _get_account_show_buckets_payable(self, company_id, partner_ids, date_end): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_end = datetime.strptime( date_end, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s), Q3 AS (%s), Q4 AS (%s) SELECT partner_id, currency_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120, current+b_1_30+b_30_60+b_60_90+b_90_120+b_over_120 AS balance FROM Q4 GROUP BY partner_id, currency_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120""" % ( self._show_buckets_sql_q1_payable(partners, date_end), self._show_buckets_sql_q2_payable( self._bucket_dates['today'], self._bucket_dates['minus_30'], self._bucket_dates['minus_60'], self._bucket_dates['minus_90'], self._bucket_dates['minus_120']), self._show_buckets_sql_q3_payable(company_id), self._show_buckets_sql_q4_payable())) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res def _get_account_show_buckets_receivable_and_payable(self, company_id, partner_ids, date_end): res = dict(map(lambda x: (x, []), partner_ids)) partners = ', '.join([str(i) for i in partner_ids]) date_end = datetime.strptime( date_end, DEFAULT_SERVER_DATE_FORMAT).date() self.env.cr.execute("""WITH Q1 AS (%s), Q2 AS (%s), Q3 AS (%s), Q4 AS (%s) SELECT partner_id, currency_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120, current+b_1_30+b_30_60+b_60_90+b_90_120+b_over_120 AS balance FROM Q4 GROUP BY partner_id, currency_id, current, b_1_30, b_30_60, b_60_90, b_90_120, b_over_120""" % ( self._show_buckets_sql_q1_receivable_and_payable(partners, date_end), self._show_buckets_sql_q2_receivable_and_payable( self._bucket_dates['today'], self._bucket_dates['minus_30'], self._bucket_dates['minus_60'], self._bucket_dates['minus_90'], self._bucket_dates['minus_120']), self._show_buckets_sql_q3_receivable_and_payable(company_id), self._show_buckets_sql_q4_receivable_and_payable())) for row in self.env.cr.dictfetchall(): res[row.pop('partner_id')].append(row) return res @api.multi def render_html(self, docids,data=None): model = self.env.context.get('active_model') docs = self.env[model].browse(self.env.context.get('active_id')) company_id = data['company_id'] partner_ids = data['partner_ids'] date_start = data['date_start'] date_end = data['date_end'] today = fields.Date.today() if data['report_type'] == 'receivable': balance_start_to_display, buckets_to_display = {}, {} lines_to_display, amount_due = {}, {} currency_to_display = {} today_display, date_start_display, date_end_display = {}, {}, {} balance_start = self._get_account_initial_balance( company_id, partner_ids, date_start) for partner_id in partner_ids: balance_start_to_display[partner_id] = {} for line in balance_start[partner_id]: currency = self.env['res.currency'].browse(line['currency_id']) if currency not in balance_start_to_display[partner_id]: balance_start_to_display[partner_id][currency] = [] balance_start_to_display[partner_id][currency] = \ line['balance'] lines = self._get_account_display_lines( company_id, partner_ids, date_start, date_end) for partner_id in partner_ids: lines_to_display[partner_id], amount_due[partner_id] = {}, {} currency_to_display[partner_id] = {} today_display[partner_id] = self._format_date_to_partner_lang( today, partner_id) date_start_display[partner_id] = self._format_date_to_partner_lang( date_start, partner_id) date_end_display[partner_id] = self._format_date_to_partner_lang( date_end, partner_id) for line in lines[partner_id]: currency = self.env['res.currency'].browse(line['currency_id']) if currency not in lines_to_display[partner_id]: lines_to_display[partner_id][currency] = [] currency_to_display[partner_id][currency] = currency if currency in balance_start_to_display[partner_id]: amount_due[partner_id][currency] = \ balance_start_to_display[partner_id][currency] else: amount_due[partner_id][currency] = 0.0 if not line['blocked']: amount_due[partner_id][currency] += line['amount'] line['balance'] = amount_due[partner_id][currency] line['date'] = self._format_date_to_partner_lang( line['date'], partner_id) line['date_maturity'] = self._format_date_to_partner_lang( line['date_maturity'], partner_id) lines_to_display[partner_id][currency].append(line) if data['show_aging_buckets']: buckets = self._get_account_show_buckets( company_id, partner_ids, date_end) for partner_id in partner_ids: buckets_to_display[partner_id] = {} for line in buckets[partner_id]: currency = self.env['res.currency'].browse( line['currency_id']) if currency not in buckets_to_display[partner_id]: buckets_to_display[partner_id][currency] = [] buckets_to_display[partner_id][currency] = line if data['report_type'] == 'payable': balance_start_to_display, buckets_to_display = {}, {} lines_to_display, amount_due = {}, {} currency_to_display = {} today_display, date_start_display, date_end_display = {}, {}, {} balance_start = self._get_account_initial_balance_payable( company_id, partner_ids, date_start) for partner_id in partner_ids: balance_start_to_display[partner_id] = {} for line in balance_start[partner_id]: currency = self.env['res.currency'].browse(line['currency_id']) if currency not in balance_start_to_display[partner_id]: balance_start_to_display[partner_id][currency] = [] balance_start_to_display[partner_id][currency] = \ line['balance'] lines = self._get_account_display_lines_payable( company_id, partner_ids, date_start, date_end) for partner_id in partner_ids: lines_to_display[partner_id], amount_due[partner_id] = {}, {} currency_to_display[partner_id] = {} today_display[partner_id] = self._format_date_to_partner_lang( today, partner_id) date_start_display[partner_id] = self._format_date_to_partner_lang( date_start, partner_id) date_end_display[partner_id] = self._format_date_to_partner_lang( date_end, partner_id) for line in lines[partner_id]: currency = self.env['res.currency'].browse(line['currency_id']) if currency not in lines_to_display[partner_id]: lines_to_display[partner_id][currency] = [] currency_to_display[partner_id][currency] = currency if currency in balance_start_to_display[partner_id]: amount_due[partner_id][currency] = \ balance_start_to_display[partner_id][currency] else: amount_due[partner_id][currency] = 0.0 if not line['blocked']: amount_due[partner_id][currency] += line['amount'] line['balance'] = amount_due[partner_id][currency] line['date'] = self._format_date_to_partner_lang( line['date'], partner_id) line['date_maturity'] = self._format_date_to_partner_lang( line['date_maturity'], partner_id) lines_to_display[partner_id][currency].append(line) if data['show_aging_buckets']: buckets = self._get_account_show_buckets_payable( company_id, partner_ids, date_end) for partner_id in partner_ids: buckets_to_display[partner_id] = {} for line in buckets[partner_id]: currency = self.env['res.currency'].browse( line['currency_id']) if currency not in buckets_to_display[partner_id]: buckets_to_display[partner_id][currency] = [] buckets_to_display[partner_id][currency] = line if data['report_type'] == 'receivable_and_payable': balance_start_to_display, buckets_to_display = {}, {} lines_to_display, amount_due = {}, {} currency_to_display = {} today_display, date_start_display, date_end_display = {}, {}, {} balance_start = self._get_account_initial_balance_receivable_and_payable( company_id, partner_ids, date_start) for partner_id in partner_ids: balance_start_to_display[partner_id] = {} for line in balance_start[partner_id]: currency = self.env['res.currency'].browse(line['currency_id']) if currency not in balance_start_to_display[partner_id]: balance_start_to_display[partner_id][currency] = [] balance_start_to_display[partner_id][currency] = \ line['balance'] lines = self._get_account_display_lines_receivable_and_payable( company_id, partner_ids, date_start, date_end) for partner_id in partner_ids: lines_to_display[partner_id], amount_due[partner_id] = {}, {} currency_to_display[partner_id] = {} today_display[partner_id] = self._format_date_to_partner_lang( today, partner_id) date_start_display[partner_id] = self._format_date_to_partner_lang( date_start, partner_id) date_end_display[partner_id] = self._format_date_to_partner_lang( date_end, partner_id) for line in lines[partner_id]: currency = self.env['res.currency'].browse(line['currency_id']) if currency not in lines_to_display[partner_id]: lines_to_display[partner_id][currency] = [] currency_to_display[partner_id][currency] = currency if currency in balance_start_to_display[partner_id]: amount_due[partner_id][currency] = \ balance_start_to_display[partner_id][currency] else: amount_due[partner_id][currency] = 0.0 if not line['blocked']: amount_due[partner_id][currency] += line['amount'] line['balance'] = amount_due[partner_id][currency] line['date'] = self._format_date_to_partner_lang( line['date'], partner_id) line['date_maturity'] = self._format_date_to_partner_lang( line['date_maturity'], partner_id) lines_to_display[partner_id][currency].append(line) if data['show_aging_buckets']: buckets = self._get_account_show_buckets_receivable_and_payable( company_id, partner_ids, date_end) for partner_id in partner_ids: buckets_to_display[partner_id] = {} for line in buckets[partner_id]: currency = self.env['res.currency'].browse( line['currency_id']) if currency not in buckets_to_display[partner_id]: buckets_to_display[partner_id][currency] = [] buckets_to_display[partner_id][currency] = line docargs = { 'doc_ids': partner_ids, 'doc_model': 'res.partner', 'docs': self.env['res.partner'].browse(partner_ids), 'Amount_Due': amount_due, 'Balance_forward': balance_start_to_display, 'Lines': lines_to_display, 'Buckets': buckets_to_display, 'Currencies': currency_to_display, 'Show_Buckets': data['show_aging_buckets'], 'Filter_non_due_partners': data['filter_partners_non_due'], 'Date_start': date_start_display, 'Date_end': date_end_display, 'Date': today_display, } return self.env['report'].render( 'customer_vendor_statement.statement', values=docargs)

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null

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7

a3810e0eeb7f7786b4f409fd221396b7804d6a94

138

py

Python

entitylinking/mlearning/models/__init__.py

debayan/starsem2018-entity-linking

6a25ebe5b0a488af400f4c37dadf9cb50aaca1a5

[ "Apache-2.0" ]

56

2018-04-17T08:44:26.000Z

2022-03-28T00:47:45.000Z

entitylinking/mlearning/models/__init__.py

debayan/starsem2018-entity-linking

6a25ebe5b0a488af400f4c37dadf9cb50aaca1a5

[ "Apache-2.0" ]

12

2019-01-26T08:37:16.000Z

2020-12-08T16:14:19.000Z

entitylinking/mlearning/models/__init__.py

debayan/starsem2018-entity-linking

6a25ebe5b0a488af400f4c37dadf9cb50aaca1a5

[ "Apache-2.0" ]

16

2018-05-01T12:07:17.000Z

2021-02-06T09:01:45.000Z

from entitylinking.mlearning.models.feature_model import FeatureModel from entitylinking.mlearning.models.vector_model import VectorModel

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a38e81f05874cc2664de2ca13c20682533256cf0

10,426

py

Python

download_and_create_reference_datasets/v01/hail_scripts/write_gnomad_coverage_vds.py

NLSVTN/hail-elasticsearch-pipelines

8b895a2e46a33d347dd2a1024101a6d515027a03

[ "MIT" ]

null

download_and_create_reference_datasets/v01/hail_scripts/write_gnomad_coverage_vds.py

NLSVTN/hail-elasticsearch-pipelines

8b895a2e46a33d347dd2a1024101a6d515027a03

[ "MIT" ]

null

download_and_create_reference_datasets/v01/hail_scripts/write_gnomad_coverage_vds.py

NLSVTN/hail-elasticsearch-pipelines

8b895a2e46a33d347dd2a1024101a6d515027a03

[ "MIT" ]

null

import argparse import hail from hail.expr import TInt, TDouble, TString import time p = argparse.ArgumentParser() p.add_argument("-b", "--output-bucket", help="Google Storage output bucket", default="seqr-reference-datasets") args = p.parse_args() hc = hail.HailContext(log="./hail_{}.log".format(time.strftime("%y%m%d_%H%M%S"))) COVERAGE_TSV_PATHS = { "grch37_exomes": { "input_paths": [ "gs://gnomad-browser/exomes/coverage/exacv2.chr1.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr10.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr11.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr12.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr13.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr14.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr15.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr16.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr17.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr18.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr19.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr2.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr20.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr21.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr22.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr3.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr4.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr5.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr6.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr7.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr8.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chr9.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chrY.cov.txt.gz", "gs://gnomad-browser/exomes/coverage/exacv2.chrX.cov.txt.gz", ], "output_path": "gs://%(output_bucket)s/GRCh37/gnomad/exomes.coverage.vds" % args.__dict__, }, "grch37_genomes": { "input_paths": [ "gs://gnomad-browser/genomes/coverage/Panel.chr1.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr10.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr11.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr12.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr13.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr14.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr15.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr16.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr17.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr18.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr19.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr2.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr20.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr21.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr22.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr3.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr4.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr5.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr6.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr7.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr8.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chr9.genome.coverage.txt.gz", "gs://gnomad-browser/genomes/coverage/Panel.chrX.genome.coverage.txt.gz", ], "output_path": "gs://%(output_bucket)s/GRCh37/gnomad/genomes.coverage.vds" % args.__dict__, }, "grch38_exomes": { "input_paths": [ "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr1.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr10.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr11.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr12.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr13.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr14.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr15.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr16.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr17.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr18.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr19.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr2.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr20.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr21.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr22.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr3.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr4.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr5.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr6.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr7.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr8.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chr9.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chrX.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/exacv2.chrY.cov.liftover.GRCh38.txt.gz", ], "output_path": "gs://%(output_bucket)s/GRCh38/gnomad/exomes.coverage.vds" % args.__dict__, }, "grch38_genomes": { "input_paths": [ "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr1.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr10.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr11.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr12.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr13.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr14.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr15.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr16.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr17.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr18.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr19.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr2.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr20.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr21.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr22.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr3.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr4.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr5.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr6.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr7.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr8.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chr9.cov.liftover.GRCh38.txt.gz", "gs://seqr-reference-data/GRCh38/gnomad/coverage/gnomad.chrX.cov.liftover.GRCh38.txt.gz", ], "output_path": "gs://%(output_bucket)s/GRCh38/gnomad/genomes.coverage.vds" % args.__dict__, }, } field_types = { '#chrom': TString(), 'pos': TInt(), 'mean': TDouble(), 'median': TDouble(), '1': TDouble(), '5': TDouble(), '10': TDouble(), '15': TDouble(), '20': TDouble(), '25': TDouble(), '30': TDouble(), '50': TDouble(), '100': TDouble(), } for label, data_paths in COVERAGE_TSV_PATHS.items(): kt = hc.import_table(data_paths["input_paths"], types=field_types).rename({ '#chrom': 'chrom', '1': 'x1', '5': 'x5', '10': 'x10', '15': 'x15', '20': 'x20', '25': 'x25', '30': 'x30', '50': 'x50', '100': 'x100', }) output_path = data_paths["output_path"] print("\n\n==> writing out {}".format(output_path)) kt.write(output_path, overwrite=True)

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null

0

9

6e79c833fa4c5a7a5600376bd5654c036e7e525b

14,649

py

Python

idm/trainers.py

xmy0916/IDM

ab29fbd6d3d8c4650f3dbe41a7d21f745d6167ee

[ "MIT" ]

68

2021-07-25T11:56:30.000Z

2022-03-29T07:33:02.000Z

idm/trainers.py

xmy0916/IDM

ab29fbd6d3d8c4650f3dbe41a7d21f745d6167ee

[ "MIT" ]

11

2021-08-08T09:33:17.000Z

2022-01-17T06:29:05.000Z

idm/trainers.py

xmy0916/IDM

ab29fbd6d3d8c4650f3dbe41a7d21f745d6167ee

[ "MIT" ]

10

2021-08-13T02:39:55.000Z

2022-03-22T07:55:13.000Z

from __future__ import print_function, absolute_import import time import torch from .utils.meters import AverageMeter from .evaluation_metrics import accuracy from .loss import TripletLoss, CrossEntropyLabelSmooth, TripletLossXBM, DivLoss, BridgeFeatLoss, BridgeProbLoss class Baseline_Trainer(object): def __init__(self, model, xbm, num_classes, margin=None): super(Baseline_Trainer, self).__init__() self.model = model self.xbm = xbm self.num_classes = num_classes self.criterion_ce = CrossEntropyLabelSmooth(num_classes).cuda() self.criterion_tri = TripletLoss(margin=margin).cuda() self.criterion_tri_xbm = TripletLossXBM(margin=margin) def train(self, epoch, data_loader_source, data_loader_target, source_classes, target_classes, optimizer, print_freq=50, train_iters=400, use_xbm=False): self.criterion_ce = CrossEntropyLabelSmooth(source_classes + target_classes).cuda() self.model.train() batch_time = AverageMeter() data_time = AverageMeter() losses = AverageMeter() losses_ce = AverageMeter() losses_tri = AverageMeter() losses_xbm = AverageMeter() precisions_s = AverageMeter() precisions_t = AverageMeter() end = time.time() for i in range(train_iters): # load data source_inputs = data_loader_source.next() target_inputs = data_loader_target.next() data_time.update(time.time() - end) # process inputs s_inputs, s_targets, _ = self._parse_data(source_inputs) t_inputs, t_targets, t_indexes = self._parse_data(target_inputs) # arrange batch for domain-specific BN device_num = torch.cuda.device_count() B, C, H, W = s_inputs.size() def reshape(inputs): return inputs.view(device_num, -1, C, H, W) s_inputs, t_inputs = reshape(s_inputs), reshape(t_inputs) inputs = torch.cat((s_inputs, t_inputs), 1).view(-1, C, H, W) targets = torch.cat((s_targets.view(device_num, -1), t_targets.view(device_num, -1)), 1) targets = targets.view(-1) # forward prob, feats = self._forward(inputs) prob = prob[:, 0:source_classes + target_classes] # split feats ori_feats = feats.view(device_num, -1, feats.size(-1)) feats_s, feats_t = ori_feats.split(ori_feats.size(1) // 2, dim=1) ori_feats = torch.cat((feats_s, feats_t), 1).view(-1, ori_feats.size(-1)) # classification+triplet loss_ce = self.criterion_ce(prob, targets) loss_tri = self.criterion_tri(ori_feats, targets) # enqueue and dequeue for xbm if use_xbm: self.xbm.enqueue_dequeue(ori_feats.detach(), targets.detach()) xbm_feats, xbm_targets = self.xbm.get() loss_xbm = self.criterion_tri_xbm(ori_feats, targets, xbm_feats, xbm_targets) losses_xbm.update(loss_xbm.item()) loss = loss_ce + loss_tri + loss_xbm else: loss = loss_ce + loss_tri optimizer.zero_grad() loss.backward() optimizer.step() ori_prob = prob.view(device_num, -1, prob.size(-1)) prob_s, prob_t = ori_prob.split(ori_prob.size(1) // 2, dim=1) prob_s, prob_t = prob_s.contiguous(), prob_t.contiguous() prec_s, = accuracy(prob_s.view(-1, prob_s.size(-1)).data, s_targets.data) prec_t, = accuracy(prob_t.view(-1, prob_s.size(-1)).data, t_targets.data) losses.update(loss.item()) losses_ce.update(loss_ce.item()) losses_tri.update(loss_tri.item()) precisions_s.update(prec_s[0]) precisions_t.update(prec_t[0]) # print log batch_time.update(time.time() - end) end = time.time() if (i + 1) % print_freq == 0: if use_xbm: print('Epoch: [{}][{}/{}]\t' 'Time {:.3f} ({:.3f}) ' 'Data {:.3f} ({:.3f}) ' 'Loss {:.3f} ({:.3f}) ' 'Loss_ce {:.3f} ({:.3f}) ' 'Loss_tri {:.3f} ({:.3f}) ' 'Loss_xbm {:.3f} ({:.3f}) ' 'Prec_s {:.2%} ({:.2%}) ' 'Prec_t {:.2%} ({:.2%}) ' .format(epoch, i + 1, len(data_loader_target), batch_time.val, batch_time.avg, data_time.val, data_time.avg, losses.val, losses.avg, losses_ce.val, losses_ce.avg, losses_tri.val, losses_tri.avg, losses_xbm.val, losses_xbm.avg, precisions_s.val, precisions_s.avg, precisions_t.val, precisions_t.avg )) else: print('Epoch: [{}][{}/{}]\t' 'Time {:.3f} ({:.3f}) ' 'Data {:.3f} ({:.3f}) ' 'Loss {:.3f} ({:.3f}) ' 'Loss_ce {:.3f} ({:.3f}) ' 'Loss_tri {:.3f} ({:.3f}) ' 'Prec_s {:.2%} ({:.2%}) ' 'Prec_t {:.2%} ({:.2%}) ' .format(epoch, i + 1, len(data_loader_target), batch_time.val, batch_time.avg, data_time.val, data_time.avg, losses.val, losses.avg, losses_ce.val, losses_ce.avg, losses_tri.val, losses_tri.avg, precisions_s.val, precisions_s.avg, precisions_t.val, precisions_t.avg )) def _parse_data(self, inputs): imgs, _, pids, _, indexes = inputs return imgs.cuda(), pids.cuda(), indexes.cuda() def _forward(self, inputs): return self.model(inputs) class IDM_Trainer(object): def __init__(self, model, xbm, num_classes, margin=None, mu1=1.0, mu2=1.0, mu3=1.0): super(IDM_Trainer, self).__init__() self.model = model self.xbm = xbm self.mu1 = mu1 self.mu2 = mu2 self.mu3 = mu3 self.num_classes = num_classes self.criterion_ce = BridgeProbLoss(num_classes).cuda() self.criterion_tri = TripletLoss(margin=margin).cuda() self.criterion_tri_xbm = TripletLossXBM(margin=margin) self.criterion_bridge_feat = BridgeFeatLoss() self.criterion_diverse = DivLoss() def train(self, epoch, data_loader_source, data_loader_target, source_classes, target_classes, optimizer, print_freq=50, train_iters=400, use_xbm=False, stage=0): self.criterion_ce = BridgeProbLoss(source_classes + target_classes).cuda() self.model.train() batch_time = AverageMeter() data_time = AverageMeter() losses = AverageMeter() losses_ce = AverageMeter() losses_tri = AverageMeter() losses_xbm = AverageMeter() losses_bridge_prob = AverageMeter() losses_bridge_feat = AverageMeter() losses_diverse = AverageMeter() precisions_s = AverageMeter() precisions_t = AverageMeter() end = time.time() for i in range(train_iters): # load data source_inputs = data_loader_source.next() target_inputs = data_loader_target.next() data_time.update(time.time() - end) # process inputs s_inputs, s_targets, _ = self._parse_data(source_inputs) t_inputs, t_targets, t_indexes = self._parse_data(target_inputs) # arrange batch for domain-specific BN device_num = torch.cuda.device_count() B, C, H, W = s_inputs.size() def reshape(inputs): return inputs.view(device_num, -1, C, H, W) s_inputs, t_inputs = reshape(s_inputs), reshape(t_inputs) inputs = torch.cat((s_inputs, t_inputs), 1).view(-1, C, H, W) targets = torch.cat((s_targets.view(device_num, -1), t_targets.view(device_num, -1)), 1) targets = targets.view(-1) # forward prob, feats, attention_lam= self._forward(inputs, stage) # attention_lam: [B, 2] prob = prob[:, 0:source_classes + target_classes] # split feats ori_feats = feats.view(device_num, -1, feats.size(-1)) feats_s, feats_t, feats_mixed = ori_feats.split(ori_feats.size(1) // 3, dim=1) ori_feats = torch.cat((feats_s, feats_t), 1).view(-1, ori_feats.size(-1)) # classification+triplet loss_ce, loss_bridge_prob = self.criterion_ce(prob, targets, attention_lam[:,0].detach()) loss_tri = self.criterion_tri(ori_feats, targets) loss_diverse = self.criterion_diverse(attention_lam) feats_s = feats_s.contiguous().view(-1, feats.size(-1)) feats_t = feats_t.contiguous().view(-1, feats.size(-1)) feats_mixed = feats_mixed.contiguous().view(-1, feats.size(-1)) loss_bridge_feat = self.criterion_bridge_feat(feats_s, feats_t, feats_mixed, attention_lam) # enqueue and dequeue for xbm if use_xbm: self.xbm.enqueue_dequeue(ori_feats.detach(), targets.detach()) xbm_feats, xbm_targets = self.xbm.get() loss_xbm = self.criterion_tri_xbm(ori_feats, targets, xbm_feats, xbm_targets) losses_xbm.update(loss_xbm.item()) loss = (1.-self.mu1) * loss_ce + loss_tri + loss_xbm + \ self.mu1 * loss_bridge_prob + self.mu2 * loss_bridge_feat + self.mu3 * loss_diverse else: loss = (1.-self.mu1) * loss_ce + loss_tri + \ self.mu1 * loss_bridge_prob + self.mu2 * loss_bridge_feat + self.mu3 * loss_diverse optimizer.zero_grad() loss.backward() optimizer.step() ori_prob = prob.view(device_num, -1, prob.size(-1)) prob_s, prob_t, _ = ori_prob.split(ori_prob.size(1) // 3, dim=1) prob_s, prob_t = prob_s.contiguous(), prob_t.contiguous() prec_s, = accuracy(prob_s.view(-1, prob_s.size(-1)).data, s_targets.data) prec_t, = accuracy(prob_t.view(-1, prob_s.size(-1)).data, t_targets.data) losses.update(loss.item()) losses_ce.update(loss_ce.item()) losses_tri.update(loss_tri.item()) losses_bridge_prob.update(loss_bridge_prob.item()) losses_bridge_feat.update(loss_bridge_feat.item()) losses_diverse.update(loss_diverse.item()) precisions_s.update(prec_s[0]) precisions_t.update(prec_t[0]) # print log batch_time.update(time.time() - end) end = time.time() if (i + 1) % print_freq == 0: if use_xbm: print('Epoch: [{}][{}/{}]\t' 'Time {:.3f} ({:.3f}) ' 'Data {:.3f} ({:.3f}) ' 'Loss {:.3f} ({:.3f}) ' 'Loss_ce {:.3f} ({:.3f}) ' 'Loss_tri {:.3f} ({:.3f}) ' 'Loss_xbm {:.3f} ({:.3f}) ' 'Loss_bridge_prob {:.3f} ({:.3f}) ' 'Loss_bridge_feat {:.3f} ({:.3f}) ' 'Loss_diverse {:.3f} ({:.3f}) ' 'Prec_s {:.2%} ({:.2%}) ' 'Prec_t {:.2%} ({:.2%}) ' .format(epoch, i + 1, len(data_loader_target), batch_time.val, batch_time.avg, data_time.val, data_time.avg, losses.val, losses.avg, losses_ce.val, losses_ce.avg, losses_tri.val, losses_tri.avg, losses_xbm.val, losses_xbm.avg, losses_bridge_prob.val, losses_bridge_prob.avg, losses_bridge_feat.val, losses_bridge_feat.avg, losses_diverse.val, losses_diverse.avg, precisions_s.val, precisions_s.avg, precisions_t.val, precisions_t.avg )) else: print('Epoch: [{}][{}/{}]\t' 'Time {:.3f} ({:.3f}) ' 'Data {:.3f} ({:.3f}) ' 'Loss {:.3f} ({:.3f}) ' 'Loss_ce {:.3f} ({:.3f}) ' 'Loss_tri {:.3f} ({:.3f}) ' 'Loss_bridge_prob {:.3f} ({:.3f}) ' 'Loss_bridge_feat {:.3f} ({:.3f}) ' 'Loss_diverse {:.3f} ({:.3f}) ' 'Prec_s {:.2%} ({:.2%}) ' 'Prec_t {:.2%} ({:.2%}) ' .format(epoch, i + 1, len(data_loader_target), batch_time.val, batch_time.avg, data_time.val, data_time.avg, losses.val, losses.avg, losses_ce.val, losses_ce.avg, losses_tri.val, losses_tri.avg, losses_bridge_prob.val, losses_bridge_prob.avg, losses_bridge_feat.val, losses_bridge_feat.avg, losses_diverse.val, losses_diverse.avg, precisions_s.val, precisions_s.avg, precisions_t.val, precisions_t.avg )) def _parse_data(self, inputs): imgs, _, pids, _, indexes = inputs return imgs.cuda(), pids.cuda(), indexes.cuda() def _forward(self, inputs, stage): return self.model(inputs, stage=stage)

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6ea7d1960c847c1c0aa183f58e5d8241c710d5d8

14,034

py

Python

test/firmware_test/firmware_test.py

Createcafe3d/YXE-firmware-flash

4c03fceeedafd9f3c801111d8ee9a8d614e53ae0

[ "MIT" ]

1

2017-03-08T02:47:17.000Z

test/firmware_test/firmware_test.py

Createcafe3d/YXE-firmware-flash

4c03fceeedafd9f3c801111d8ee9a8d614e53ae0

[ "MIT" ]

null

test/firmware_test/firmware_test.py

Createcafe3d/YXE-firmware-flash

4c03fceeedafd9f3c801111d8ee9a8d614e53ae0

[ "MIT" ]

8

2016-05-11T11:38:59.000Z

2020-02-15T09:55:39.000Z

import sys import os from mock import patch, MagicMock import unittest from subprocess import PIPE # sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..')) sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'src')) import firmware from firmware.firmware import FirmwareUpdater, MacFirmwareUpdater, LinuxFirmwareUpdater, WindowsFirmwareUpdater @patch('firmware.sys') class TestFirmwareInit(unittest.TestCase): def test_correct_class_for_mac_platform_is_provided(self, mock_sys): mock_sys.platform = 'darwin' result = firmware.get_firmware_updater() self.assertEquals(MacFirmwareUpdater, type(result)) def test_correct_class_for_win32_platform_is_provided(self, mock_sys): mock_sys.platform = 'win32' result = firmware.get_firmware_updater() self.assertEquals(WindowsFirmwareUpdater, type(result)) def test_correct_class_for_win64_platform_is_provided(self, mock_sys): mock_sys.platform = 'winamd64' result = firmware.get_firmware_updater() self.assertEquals(WindowsFirmwareUpdater, type(result)) def test_correct_class_for_linux_platform_is_provided(self, mock_sys): mock_sys.platform = 'linux' result = firmware.get_firmware_updater() self.assertEquals(LinuxFirmwareUpdater, type(result)) def test_exception_raised_if_not_supported(self, mock_sys): mock_sys.platform = 'sun' with self.assertRaises(Exception): firmware.get_firmware_updater() @patch('firmware.firmware.Popen') @patch('firmware.os.path.isfile') @patch('firmware.os.stat') @patch('firmware.os.chmod') class TestLinuxFirmwareUpdater(unittest.TestCase): BOOTLOADER_IDVENDOR = 0x0483 BOOTLOADER_IDPRODUCT = 0xdf11 PEACHY_IDVENDOR = 0x16d0 PEACHY_IDPRODUCT = 0x0af3 def setUp(self): self.bin_path = os.path.join('some','binary', 'path') self.firmware_path = os.path.join('some', 'firmware', 'path.bin') def test_update_should_return_true_if_update_successfull(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_isfile.return_value = True mock_Popen.return_value.communicate.return_value = ('err', 'out') mock_Popen.return_value.wait.return_value = 0 usb_addess = '{}:{}'.format('0483', 'df11') expected_command = [os.path.join(self.bin_path, 'dfu-util'), '-a', '0', '--dfuse-address', '0x08000000', '-D', self.firmware_path, '-d', usb_addess] l_fw_up = LinuxFirmwareUpdater(self.bin_path, self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = l_fw_up.update(self.firmware_path) self.assertTrue(result) mock_Popen.assert_called_with(expected_command, stdout=PIPE, stderr=PIPE) mock_Popen.return_value.wait.assert_called_with() def test_update_should_return_false_if_update_not_successfull(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_isfile.return_value = True mock_Popen.return_value.communicate.return_value = ('err', 'out') mock_Popen.return_value.wait.return_value = 34 usb_addess = '{}:{}'.format('0483', 'df11') expected_command = [os.path.join(self.bin_path, 'dfu-util'), '-a', '0', '--dfuse-address', '0x08000000', '-D', self.firmware_path, '-d', usb_addess] l_fw_up = LinuxFirmwareUpdater(self.bin_path, self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = l_fw_up.update(self.firmware_path) self.assertFalse(result) mock_Popen.assert_called_with(expected_command, stdout=PIPE, stderr=PIPE) mock_Popen.return_value.wait.assert_called_with() def test_check_ready_should_return_true_if_1_bootloader(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('{:04x}:{:04x}'.format(self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = LinuxFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = fw_up.check_ready() self.assertTrue(result) mock_Popen.assert_called_with(['lsusb'], stdout=PIPE, stderr=PIPE) def test_check_ready_should_return_False_if_no_results(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('', '') mock_Popen.return_value.wait.return_value = 0 fw_up = LinuxFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = fw_up.check_ready() self.assertFalse(result) mock_Popen.assert_called_with(['lsusb'], stdout=PIPE, stderr=PIPE) def test_check_ready_should_return_False_if_only_peachy_results(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('{:04x}:{:04x}'.format(self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = LinuxFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = fw_up.check_ready() self.assertFalse(result) mock_Popen.assert_called_with(['lsusb'], stdout=PIPE, stderr=PIPE) def test_check_ready_should_raise_exception_if_peachy_and_bootloader(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('{:04x}:{:04x}\n{:04x}:{:04x}'.format(self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT, self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = LinuxFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) with self.assertRaises(Exception): fw_up.check_ready() mock_Popen.assert_called_with(['lsusb'], stdout=PIPE, stderr=PIPE) def test_check_ready_should_raise_exception_if_multipule_peachys(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('{0:04x}:{1:04x}\n{0:04x}:{1:04x}'.format(self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = LinuxFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) with self.assertRaises(Exception): fw_up.check_ready() mock_Popen.assert_called_with(['lsusb'], stdout=PIPE, stderr=PIPE) def test_check_ready_should_raise_exception_if_multipule_bootloaders(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('{0:04x}:{1:04x}\n{0:04x}:{1:04x}'.format(self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = LinuxFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) with self.assertRaises(Exception): fw_up.check_ready() mock_Popen.assert_called_with(['lsusb'], stdout=PIPE, stderr=PIPE) @patch('firmware.firmware.Popen') @patch('firmware.os.path.isfile') @patch('firmware.os.stat') @patch('firmware.os.chmod') class TestWindowsFirmwareUpdater(unittest.TestCase): BOOTLOADER_IDVENDOR = 0x0483 BOOTLOADER_IDPRODUCT = 0xdf11 PEACHY_IDVENDOR = 0x16d0 PEACHY_IDPRODUCT = 0x0af3 def setUp(self): self.bin_path = os.path.join('some','binary', 'path') self.firmware_path = os.path.join('some', 'firmware', 'path.bin') # def test_update_should_return_true_if_update_successfull(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): # mock_isfile.return_value = True # mock_Popen.return_value.communicate.return_value = ('err', 'out') # mock_Popen.return_value.wait.return_value = 0 # usb_addess = '{}:{}'.format('0483', 'df11') # expected_command = [os.path.join(self.bin_path, 'dfu-util'), '-a', '0', '--dfuse-address', '0x08000000', '-D', self.firmware_path, '-d', usb_addess] # l_fw_up = LinuxFirmwareUpdater(self.bin_path, self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) # result = l_fw_up.update(self.firmware_path) # self.assertTrue(result) # mock_Popen.assert_called_with(expected_command, stdout=PIPE, stderr=PIPE) # mock_Popen.return_value.wait.assert_called_with() # def test_update_should_return_false_if_update_not_successfull(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): # mock_isfile.return_value = True # mock_Popen.return_value.communicate.return_value = ('err', 'out') # mock_Popen.return_value.wait.return_value = 34 # usb_addess = '{}:{}'.format('0483', 'df11') # expected_command = [os.path.join(self.bin_path, 'dfu-util'), '-a', '0', '--dfuse-address', '0x08000000', '-D', self.firmware_path, '-d', usb_addess] # l_fw_up = LinuxFirmwareUpdater(self.bin_path, self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) # result = l_fw_up.update(self.firmware_path) # self.assertFalse(result) # mock_Popen.assert_called_with(expected_command, stdout=PIPE, stderr=PIPE) # mock_Popen.return_value.wait.assert_called_with() def test_check_ready_should_return_true_if_1_bootloader(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('"USB\VID_{:04X}&PID_{:04X}"'.format(self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = WindowsFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = fw_up.check_ready() self.assertTrue(result) mock_Popen.assert_called_with('''wmic.exe path WIN32_PnPEntity where "DeviceID like 'USB\\\\VID_%'" get HardwareID''', stdout=PIPE, stderr=PIPE) def test_check_ready_should_return_False_if_no_results(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('', '') mock_Popen.return_value.wait.return_value = 0 fw_up = WindowsFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = fw_up.check_ready() self.assertFalse(result) mock_Popen.assert_called_with('''wmic.exe path WIN32_PnPEntity where "DeviceID like 'USB\\\\VID_%'" get HardwareID''', stdout=PIPE, stderr=PIPE) def test_check_ready_should_return_False_if_only_peachy_results(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('"USB\VID_{:04X}&PID_{:04X}"'.format(self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = WindowsFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) result = fw_up.check_ready() self.assertFalse(result) mock_Popen.assert_called_with('''wmic.exe path WIN32_PnPEntity where "DeviceID like 'USB\\\\VID_%'" get HardwareID''', stdout=PIPE, stderr=PIPE) def test_check_ready_should_raise_exception_if_peachy_and_bootloader(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('"USB\VID_{:04X}&PID_{:04X}"\n"USB\VID_{:04X}&PID_{:04X}"'.format(self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT, self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = WindowsFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) with self.assertRaises(Exception): fw_up.check_ready() mock_Popen.assert_called_with('''wmic.exe path WIN32_PnPEntity where "DeviceID like 'USB\\\\VID_%'" get HardwareID''', stdout=PIPE, stderr=PIPE) def test_check_ready_should_raise_exception_if_multipule_peachys(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('"USB\VID_{0:04X}&PID_{1:04X}"\n"USB\VID_{0:04X}&PID_{1:04X}"'.format(self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = WindowsFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) with self.assertRaises(Exception): fw_up.check_ready() mock_Popen.assert_called_with('''wmic.exe path WIN32_PnPEntity where "DeviceID like 'USB\\\\VID_%'" get HardwareID''', stdout=PIPE, stderr=PIPE) def test_check_ready_should_raise_exception_if_multipule_bootloaders(self, mock_chmod, mock_stat, mock_isfile, mock_Popen): mock_Popen.return_value.communicate.return_value = ('"USB\VID_{0:04X}&PID_{1:04X}"\n"USB\VID_{0:04X}&PID_{1:04X}"'.format(self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT), '') mock_Popen.return_value.wait.return_value = 0 fw_up = WindowsFirmwareUpdater('somepath', self.BOOTLOADER_IDVENDOR, self.BOOTLOADER_IDPRODUCT, self.PEACHY_IDVENDOR, self.PEACHY_IDPRODUCT) with self.assertRaises(Exception): fw_up.check_ready() mock_Popen.assert_called_with('''wmic.exe path WIN32_PnPEntity where "DeviceID like 'USB\\\\VID_%'" get HardwareID''', stdout=PIPE, stderr=PIPE) if __name__ == '__main__': unittest.main()

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42e451a9820c75d1c5187a731488067714a5351c

204

py

Python

docassemble_demo/docassemble/demo/change_suffix.py

knod/docassemble

bd052b557743d098138a5f2129a9d3c2f68090a6

[ "MIT" ]

568

2016-01-08T19:05:06.000Z

2022-03-30T19:44:47.000Z

docassemble_demo/docassemble/demo/change_suffix.py

knod/docassemble

bd052b557743d098138a5f2129a9d3c2f68090a6

[ "MIT" ]

348

2016-01-25T02:17:36.000Z

2022-03-27T21:22:43.000Z

docassemble_demo/docassemble/demo/change_suffix.py

knod/docassemble

bd052b557743d098138a5f2129a9d3c2f68090a6

[ "MIT" ]

262

2016-01-14T23:09:50.000Z

2022-03-23T15:06:08.000Z

import docassemble.base.functions def my_name_suffix(): return ['Jr', 'Sr', 'II', 'III', 'IV', 'Esq', 'PhD'] docassemble.base.functions.update_language_function('en', 'name_suffix', my_name_suffix)

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16,506

py

Python

sinkhorn_barycenters.py

hichamjanati/debiased-ot-barycenters

632adefbc6c9e98ea237ac86feab921dc8d00778

[ "BSD-3-Clause" ]

15

2020-06-06T02:56:58.000Z

2021-12-06T05:09:22.000Z

sinkhorn_barycenters.py

hichamjanati/debiased-ot-barycenters

632adefbc6c9e98ea237ac86feab921dc8d00778

[ "BSD-3-Clause" ]

1

2021-09-10T12:04:48.000Z

2021-09-10T14:49:55.000Z

sinkhorn_barycenters.py

hichamjanati/debiased-ot-barycenters

632adefbc6c9e98ea237ac86feab921dc8d00778

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ Debiased Sinkhorn barycenters. """ # # License: MIT License import torch import numpy as np import warnings def convol_imgs(imgs, K): kx = torch.einsum("...ij,kjl->kil", K, imgs) kxy = torch.einsum("...ij,klj->kli", K, kx) return kxy def convol_3d(cloud, K): kx = torch.einsum("ij,rjlk->rilk", K, cloud) kxy = torch.einsum("ij,rkjl->rkil", K, kx) kxyz = torch.einsum("ij,rlkj->rlki", K, kxy) return kxyz def barycenter_3d(P, K, Kb=None, c=None, maxiter=1000, tol=1e-7, debiased=False, weights=None, return_log=False): """Compute the Wasserstein divergence barycenter between histograms. """ n_hists, width, _, _ = P.shape b = torch.ones_like(P, requires_grad=False) q = torch.ones((width, width, width), device=P.device, dtype=P.dtype) if Kb is None: Kb = convol_3d(b, K) if c is None: c = q.clone() log = {'err': [], 'a': [], 'b': [], 'q': []} err = 10 if weights is None: weights = torch.ones(n_hists, device=P.device, dtype=P.dtype) / n_hists for ii in range(maxiter): if torch.isnan(q).any(): break qold = q.clone() a = P / Kb Ka = convol_3d(a, K.t()) q = c * torch.prod((Ka) ** weights[:, None, None, None], dim=0) if debiased: Kc = convol_3d(c[None, :], K).squeeze() c = (c * q / Kc) ** 0.5 Q = q[None, :] b = Q / Ka Kb = convol_3d(b, K) err = abs(q - qold).max() if err < tol and ii > 10: break print("Barycenter 3d | err = ", err) if return_log: log["err"].append(err) log["a"] = a log["q"] = q log["b"] = b if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def barycenter_debiased_1d(P, K, maxiter=5000, tol=1e-5, weights=None, return_log=False): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape bold = torch.ones_like(P, device=P.device) b = bold.clone() c, q = torch.ones((2, dim), dtype=P.dtype, device=P.device) Kb = K.mm(b) log = {'err': [], 'a': [], 'b': [], 'c': [], 'q': []} err = 10 if weights is None: weights = torch.ones(n_hists, dtype=P.dtype, device=P.device) / n_hists for ii in range(maxiter): qold = q.clone() a = P / Kb Ka = K.t().mm(a) q = c * torch.prod((Ka) ** weights[None, :], dim=1) c = (c * q / K.mv(c)) ** 0.5 Q = q[:, None] b = Q / Ka Kb = K.mm(b) # err = abs(a * Kb - P).mean() err = abs(q - qold).max() if return_log: log["err"].append(err) log["a"].append(a) log["q"].append(q) log["c"].append(c) log["b"].append(b) if err < tol and ii > 10: break if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def ot_diag_2d(q, K, maxiter=100, tol=1e-5): """Computes Auto-correlation potential for 2d distributions.""" c = torch.ones_like(q) for ii in range(maxiter): Kc = K.t().mm(K.mm(c).t()).t() c_new = (c * q / Kc) ** 0.5 err = abs(c - c_new).max() err /= max(c.max(), c_new.max(), 1.) c = c_new.clone() if err < tol and ii > 3: break if ii == maxiter - 1: warnings.warn("*** Auto-correlation potential " "did not converge ! err = {} ***".format(err)) return c def ot_diag_1d(c, q, K, maxiter=100, tol=1e-5): """Computes Auto-correlation potential for 2d distributions.""" c = torch.ones_like(q) for ii in range(maxiter): Kc = K.mv(c) c_new = (c * q / Kc) ** 0.5 err = abs(c - c_new).max() err /= max(c.max(), c_new.max(), 1.) c = c_new.clone() if err < tol and ii > 3: break if ii == maxiter - 1: warnings.warn("*** Auto-correlation potential " "did not converge ! err = {} ***".format(err)) return c def ot_diag_2d_np(c, q, K, maxiter=100, tol=1e-5): """Computes Auto-correlation potential for 2d distributions.""" for ii in range(maxiter): Kc = K.T.dot(K.dot(c).T).T c_new = (c * q / Kc) ** 0.5 err = abs(c - c_new).max() err /= max(c.max(), c_new.max(), 1.) c = c_new.copy() if err < tol and ii > 3: break if ii == maxiter - 1: warnings.warn("*** Auto-correlation potential " "did not converge ! err = {} ***".format(err)) return c def ot_diag_1d_np(q, K, maxiter=100, tol=1e-5): """Computes Auto-correlation potential for 2d distributions.""" c = np.ones_like(q) for ii in range(maxiter): c_new = (c * q / K.dot(c)) ** 0.5 err = abs(c - c_new).max() err /= max(c.max(), c_new.max(), 1.) c = c_new.copy() if err < tol and ii > 3: break if ii == maxiter - 1: warnings.warn("*** Auto-correlation potential " "did not converge ! err = {} ***".format(err)) return c def barycenter_1d(P, K, maxiter=5000, tol=1e-5, weights=None, return_log=False): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape b = torch.ones_like(P, device=P.device) q = torch.ones(dim, dtype=P.dtype, device=P.device) Kb = K.mm(b) err = 1 log = {'err': [err], 'a': [], 'b': [], 'c': [], 'q': []} if weights is None: weights = torch.ones(n_hists, dtype=P.dtype, device=P.device) / n_hists for ii in range(maxiter): qold = q.clone() a = P / Kb Ka = K.t().mm(a) q = torch.prod((b * Ka) ** weights[None, :], dim=1) Q = q[:, None] b = Q / Ka Kb = K.mm(b) # err = abs(a * Kb - P).mean() err = abs(q - qold).max() if err < tol and ii > 10: break if return_log: log["err"].append(err) log["a"].append(a) log["q"].append(q) log["b"].append(b) if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def barycenter_debiased_2d(P, K, Kb=None, c=None, maxiter=5000, tol=1e-5, weights=None, return_log=False): """Compute the Wasserstein divergence barycenter between histograms. """ n_hists, width, _ = P.shape b = torch.ones_like(P, requires_grad=False) q = torch.ones((width, width), dtype=P.dtype, device=P.device) if Kb is None: Kb = convol_imgs(b, K) if c is None: c = q.clone() log = {'err': [], 'a': [], 'b': [], 'q': []} err = 10 if weights is None: weights = torch.ones(n_hists, dtype=P.dtype, device=P.device) / n_hists for ii in range(maxiter): qold = q.clone() a = P / Kb Ka = convol_imgs(a, K.t()) q = c * torch.prod((Ka) ** weights[:, None, None], dim=0) for kk in range(10): Kc = K.t().mm(K.mm(c).t()).t() c = (c * q / Kc) ** 0.5 Q = q[None, :, :] b = Q / Ka Kb = convol_imgs(b, K) # err = abs(a * Kb - P).mean() err = abs(q - qold).max() if err < tol and ii > 10: break if return_log: log["err"].append(err) log["a"] = a log["q"] = q log["b"] = b if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def barycenter_2d(P, K, Kb=None, maxiter=5000, tol=1e-5, weights=None, return_log=False): """Compute the Wasserstein divergence barycenter between histograms. """ n_hists, width, _ = P.shape b = torch.ones_like(P, requires_grad=False) q = torch.ones((width, width), dtype=P.dtype, device=P.device) if Kb is None: Kb = convol_imgs(b, K) log = {'err': [], 'a': [], 'b': [], 'q': []} err = 10 if weights is None: weights = torch.ones(n_hists, dtype=P.dtype, device=P.device) / n_hists for ii in range(maxiter): qold = q.clone() a = P / Kb Ka = convol_imgs(a, K.t()) q = torch.prod((b * Ka) ** weights[:, None, None], dim=0) Q = q[None, :, :] b = Q / Ka Kb = convol_imgs(b, K) err = abs(q - qold).max() if err < tol and ii > 10: break if return_log: log["err"].append(err) log["a"] = a log["q"] = q log["b"] = b if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def barycenter(P, K, reference="debiased", **kwargs): """Compute OT barycenter.""" ndim = P.ndimension() if ndim > 3 or ndim <= 1: raise ValueError("Data dimension must be 2 for 1d distributions" " or 3 for 2d distributions.") if reference == "debiased": if ndim == 2: func = barycenter_debiased_1d elif ndim == 3: func = barycenter_debiased_2d elif reference == "uniform": if ndim == 2: func = barycenter_1d elif ndim == 3: func = barycenter_2d elif reference == "product": if ndim == 2: func = barycenter_ref_1d else: func = barycenter_ref_2d return func(P, K, **kwargs) def barycenter_np_debiased_1d(P, K, maxiter=5000, tol=1e-5, weights=None, return_log=True): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape bold = np.ones_like(P) b = bold.copy() q, c = np.ones((2, dim)) Kb = K.dot(b) log = {'err': [], 'a': [], 'b': [], 'c': [], 'q': []} err = 10 if weights is None: weights = np.ones(n_hists) / n_hists for ii in range(maxiter): qold = q.copy() a = P / Kb Ka = K.T.dot(a) q = c * np.prod(Ka ** weights[None, :], axis=1) Q = q[:, None] b = Q / Ka Kb = K.dot(b) c = (c * q / K.dot(c)) ** 0.5 err = abs(q - qold).max() if return_log: log["err"].append(err) log["a"].append(a) log["q"].append(q) log["c"].append(c) log["b"].append(b) if err < tol and ii > 10: break if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def barycenter_np_1d(P, K, maxiter=5000, tol=1e-5, weights=None, return_log=True): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape bold = np.ones_like(P) b = bold.copy() q = np.ones(dim) Kb = K.dot(b) log = {'err': [], 'a': [], 'b': [], 'c': [], 'q': []} err = 10 if weights is None: weights = np.ones(n_hists) / n_hists for ii in range(maxiter): qold = q.copy() a = P / Kb Ka = K.T.dot(a) q = np.prod((b * Ka) ** weights[None, :], axis=1) Q = q[:, None] # err = abs(Ka * b).std(axis=1).mean() b = Q / Ka Kb = K.dot(b) err = abs(q - qold).max() if return_log: log["err"].append(err) log["a"].append(a) log["q"].append(q) log["b"].append(b) if err < tol and ii > 10: break if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) if return_log: return q, log return q def _barycenter_inner_1d_np(P, K, qold=None, bold=None, maxiter=1000, tol=1e-5, weights=None): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape if bold is None: bold = np.ones_like(P) b = bold.copy() if qold is None: qold = np.ones(dim) / dim Kb = K.dot(b) err = 10 if weights is None: weights = np.ones(n_hists) / n_hists for ii in range(maxiter): a = P / Kb Ka = K.T.dot(a) q = qold * np.prod((Ka) ** weights[None, :], axis=1) Q = q[:, None] err = abs(Ka * b).std(axis=1).mean() b = Q / Ka Kb = K.dot(b) if err < tol and ii > 10: break if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) return q, b def _barycenter_inner_1d(P, K, qold=None, bold=None, maxiter=1000, tol=1e-4, weights=None): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape if bold is None: bold = torch.ones_like(P) b = bold.clone() if qold is None: qold = torch.ones(dim) / dim Kb = K.mm(b) err = 10 if weights is None: weights = torch.ones(n_hists) / n_hists q = qold.clone() for ii in range(maxiter): qold_inner = q.clone() a = P / Kb Ka = K.t().mm(a) q = qold * torch.prod((Ka) ** weights[None, :], dim=1) Q = q[:, None] b = Q / Ka Kb = K.mm(b) err = abs(q - qold_inner).max() if err < tol and ii > 10: break if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) return q, b def _barycenter_inner_2d(P, K, qold=None, bold=None, maxiter=1000, tol=1e-4, weights=None): """Compute the Wasserstein divergence barycenter between histograms. """ n_hists, width, _ = P.shape if bold is None: bold = torch.ones_like(P, requires_grad=False) b = bold.clone() Kb = convol_imgs(b, K) if weights is None: weights = torch.ones(n_hists, dtype=P.dtype, device=P.device) / n_hists if qold is None: qold = torch.ones_like(P[0]) / (width ** 2) q = qold.clone() for ii in range(maxiter): qlocal = q.clone() a = P / Kb Ka = convol_imgs(a, K.t()) q = qold * torch.prod(Ka ** weights[:, None, None], dim=0) Q = q[None, :, :] b = Q / Ka Kb = convol_imgs(b, K) err = abs(q - qlocal).max() if err < tol and ii > 10: break if ii == maxiter - 1: warnings.warn("*** Maxiter reached ! err = {} ***".format(err)) return q, b def barycenter_ref_1d(P, K, maxiter=500, tol=1e-5, weights=None, return_log=True): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape q = torch.ones(dim) / dim b = torch.ones_like(P) for ii in range(maxiter): qold = q.clone() q, b = _barycenter_inner_1d(P, K, qold=q, bold=b) err = abs(q - qold).max() if err < tol: break return q def barycenter_ref_2d(P, K, maxiter=500, tol=1e-5, weights=None, return_log=True): """Compute the Wasserstein divergence barycenter between histograms. """ n_hists, width, _ = P.shape q = torch.ones((width, width), device=P.device, dtype=P.dtype) b = torch.ones_like(P) for ii in range(maxiter): qold = q.clone() q, b = _barycenter_inner_2d(P, K, qold=q, bold=b) err = abs(q - qold).max() if err < tol: break return q def barycenter_ref_1d_np(P, K, maxiter=500, tol=1e-5, weights=None, return_log=True): """Compute the Wasserstein divergence barycenter between histograms. """ dim, n_hists = P.shape q = np.ones(dim) / dim b = np.ones_like(P) for ii in range(maxiter): qold = q.copy() q, b = _barycenter_inner_1d_np(P, K, qold=q, bold=b) err = abs(q - qold).max() if err < tol: break return q def barycenter_np(P, K, debiased=True, **kwargs): if debiased: func = barycenter_np_debiased_1d else: func = barycenter_np_1d return func(P, K, **kwargs)

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null

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281a1ca4add71229dc7b87ab2e0255bb29ff30bd

175

py

Python

apps/general/views.py

cspatgithub/Bloggy

1ce62811cc24e0a108cb6b7b445f50f0c123aeb2

[ "MIT" ]

null

apps/general/views.py

cspatgithub/Bloggy

1ce62811cc24e0a108cb6b7b445f50f0c123aeb2

[ "MIT" ]

6

2021-03-19T02:38:48.000Z

2021-09-22T18:57:13.000Z

apps/general/views.py

cspatgithub/Bloggy

1ce62811cc24e0a108cb6b7b445f50f0c123aeb2

[ "MIT" ]

null

from django.shortcuts import render def Home(request): return render(request, 'general/home.html') def About(request): return render(request, 'general/about.html')

19.444444

48

0.737143

23

175

5.608696

0.521739

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0.403101

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0

0.142857

175

9

48

19.444444

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1

0

1

0

null

0

1

0

1

0

8

284be3a20d5345d9e1ad61f64e009548c796680b

176

py

Python

descarteslabs/workflows/execution/__init__.py

descarteslabs/descarteslabs-python

efc874d6062603dc424c9646287a9b1f8636e7ac

[ "Apache-2.0" ]

167

2017-03-23T22:16:58.000Z

2022-03-08T09:19:30.000Z

descarteslabs/workflows/execution/__init__.py

descarteslabs/descarteslabs-python

efc874d6062603dc424c9646287a9b1f8636e7ac

[ "Apache-2.0" ]

93

2017-03-23T22:11:40.000Z

2021-12-13T18:38:53.000Z

descarteslabs/workflows/execution/__init__.py

descarteslabs/descarteslabs-python

efc874d6062603dc424c9646287a9b1f8636e7ac

[ "Apache-2.0" ]

46

2017-03-25T19:12:14.000Z

2021-08-15T18:04:29.000Z

from .arguments import arguments_to_grafts, promote_arguments from .to_computable import to_computable __all__ = ["arguments_to_grafts", "promote_arguments", "to_computable"]

35.2

71

0.835227

22

176

6.090909

0.363636

0.246269

0.253731

0.358209

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0

0.085227

176

4

72

44

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0

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null

0

1

0

1

0

7

2886d18cb9b0df3bd118dd252967071d9df3ba65

145

py

Python

semantic-python/test/fixtures/3-01-empty-class-definition.py

Temurson/semantic

2e9cd2c006cec9a0328791e47d8c6d60af6d5a1b

[ "MIT" ]

8,844

2019-05-31T15:47:12.000Z

2022-03-31T18:33:51.000Z

semantic-python/test/fixtures/3-01-empty-class-definition.py

Qanora/semantic

b0eda9a61bbc690a342fb177cfc12eec8c1c001c

[ "MIT" ]

401

2019-05-31T18:30:26.000Z

2022-03-31T16:32:29.000Z

semantic-python/test/fixtures/3-01-empty-class-definition.py

Qanora/semantic

b0eda9a61bbc690a342fb177cfc12eec8c1c001c

[ "MIT" ]

504

2019-05-31T17:55:03.000Z

2022-03-30T04:15:04.000Z

# CHECK-TREE: { Foo <- rec Foo = __semantic_prelude.type "Foo" __semantic_prelude.object #record {}; #record { Foo: Foo }} class Foo(): pass

36.25

122

0.668966

19

145

4.789474

0.578947

0.241758

0.395604

0

0.172414

145

3

123

48.333333

0.758333

0.813793

0

1

0

true

0.5

0

0.5

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0

1

0

1

0

null

0

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0

7

953f4fda908710036f4aca3782c38572b035d1f8

66,411

py

Python

atom/nucleus/python/nucleus_api/api/insurance_api.py

sumit4-ttn/SDK

b3ae385e5415e47ac70abd0b3fdeeaeee9aa7cff

[ "Apache-2.0" ]

null

atom/nucleus/python/nucleus_api/api/insurance_api.py

sumit4-ttn/SDK

b3ae385e5415e47ac70abd0b3fdeeaeee9aa7cff

[ "Apache-2.0" ]

null

atom/nucleus/python/nucleus_api/api/insurance_api.py

sumit4-ttn/SDK

b3ae385e5415e47ac70abd0b3fdeeaeee9aa7cff

[ "Apache-2.0" ]

null

# coding: utf-8 """ Hydrogen Atom API The Hydrogen Atom API # noqa: E501 OpenAPI spec version: 1.7.0 Contact: info@hydrogenplatform.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from nucleus_api.api_client import ApiClient class InsuranceApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def create_insurance_coverage_using_post(self, insurance_coverage, **kwargs): # noqa: E501 """Create a insurance coverage request # noqa: E501 Create a new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_insurance_coverage_using_post(insurance_coverage, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceCoverage insurance_coverage: insuranceCoverage (required) :return: InsuranceCoverage If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_insurance_coverage_using_post_with_http_info(insurance_coverage, **kwargs) # noqa: E501 else: (data) = self.create_insurance_coverage_using_post_with_http_info(insurance_coverage, **kwargs) # noqa: E501 return data def create_insurance_coverage_using_post_with_http_info(self, insurance_coverage, **kwargs): # noqa: E501 """Create a insurance coverage request # noqa: E501 Create a new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_insurance_coverage_using_post_with_http_info(insurance_coverage, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceCoverage insurance_coverage: insuranceCoverage (required) :return: InsuranceCoverage If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_coverage'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_insurance_coverage_using_post" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_coverage' is set if ('insurance_coverage' not in params or params['insurance_coverage'] is None): raise ValueError("Missing the required parameter `insurance_coverage` when calling `create_insurance_coverage_using_post`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'insurance_coverage' in params: body_params = params['insurance_coverage'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_coverage', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceCoverage', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_insurance_discount_using_post(self, insurance_discount, **kwargs): # noqa: E501 """Create a insurance discount request # noqa: E501 Create a new insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_insurance_discount_using_post(insurance_discount, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceDiscount insurance_discount: insuranceDiscount (required) :return: InsuranceDiscount If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_insurance_discount_using_post_with_http_info(insurance_discount, **kwargs) # noqa: E501 else: (data) = self.create_insurance_discount_using_post_with_http_info(insurance_discount, **kwargs) # noqa: E501 return data def create_insurance_discount_using_post_with_http_info(self, insurance_discount, **kwargs): # noqa: E501 """Create a insurance discount request # noqa: E501 Create a new insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_insurance_discount_using_post_with_http_info(insurance_discount, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceDiscount insurance_discount: insuranceDiscount (required) :return: InsuranceDiscount If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_discount'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_insurance_discount_using_post" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_discount' is set if ('insurance_discount' not in params or params['insurance_discount'] is None): raise ValueError("Missing the required parameter `insurance_discount` when calling `create_insurance_discount_using_post`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'insurance_discount' in params: body_params = params['insurance_discount'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_discount', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceDiscount', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def create_insurance_quote_using_post(self, insurance_quote, **kwargs): # noqa: E501 """Create a insuranceQuote request # noqa: E501 Create a new insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_insurance_quote_using_post(insurance_quote, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceQuote insurance_quote: insuranceQuote (required) :return: InsuranceQuote If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_insurance_quote_using_post_with_http_info(insurance_quote, **kwargs) # noqa: E501 else: (data) = self.create_insurance_quote_using_post_with_http_info(insurance_quote, **kwargs) # noqa: E501 return data def create_insurance_quote_using_post_with_http_info(self, insurance_quote, **kwargs): # noqa: E501 """Create a insuranceQuote request # noqa: E501 Create a new insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_insurance_quote_using_post_with_http_info(insurance_quote, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceQuote insurance_quote: insuranceQuote (required) :return: InsuranceQuote If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_quote'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method create_insurance_quote_using_post" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_quote' is set if ('insurance_quote' not in params or params['insurance_quote'] is None): raise ValueError("Missing the required parameter `insurance_quote` when calling `create_insurance_quote_using_post`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'insurance_quote' in params: body_params = params['insurance_quote'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_quote', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceQuote', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_insurance_coverage_using_delete(self, insurance_coverage_id, **kwargs): # noqa: E501 """Delete an insurance coverage request # noqa: E501 Delete an insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_insurance_coverage_using_delete(insurance_coverage_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_coverage_id: UUID insurance_coverage_id (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_insurance_coverage_using_delete_with_http_info(insurance_coverage_id, **kwargs) # noqa: E501 else: (data) = self.delete_insurance_coverage_using_delete_with_http_info(insurance_coverage_id, **kwargs) # noqa: E501 return data def delete_insurance_coverage_using_delete_with_http_info(self, insurance_coverage_id, **kwargs): # noqa: E501 """Delete an insurance coverage request # noqa: E501 Delete an insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_insurance_coverage_using_delete_with_http_info(insurance_coverage_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_coverage_id: UUID insurance_coverage_id (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_coverage_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_insurance_coverage_using_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_coverage_id' is set if ('insurance_coverage_id' not in params or params['insurance_coverage_id'] is None): raise ValueError("Missing the required parameter `insurance_coverage_id` when calling `delete_insurance_coverage_using_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_coverage_id' in params: path_params['insurance_coverage_id'] = params['insurance_coverage_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_coverage/{insurance_coverage_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_insurance_discount_using_delete(self, insurance_discount_id, **kwargs): # noqa: E501 """Delete an insurance discount request # noqa: E501 Delete an insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_insurance_discount_using_delete(insurance_discount_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_discount_id: UUID insurance_discount_id (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_insurance_discount_using_delete_with_http_info(insurance_discount_id, **kwargs) # noqa: E501 else: (data) = self.delete_insurance_discount_using_delete_with_http_info(insurance_discount_id, **kwargs) # noqa: E501 return data def delete_insurance_discount_using_delete_with_http_info(self, insurance_discount_id, **kwargs): # noqa: E501 """Delete an insurance discount request # noqa: E501 Delete an insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_insurance_discount_using_delete_with_http_info(insurance_discount_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_discount_id: UUID insurance_discount_id (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_discount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_insurance_discount_using_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_discount_id' is set if ('insurance_discount_id' not in params or params['insurance_discount_id'] is None): raise ValueError("Missing the required parameter `insurance_discount_id` when calling `delete_insurance_discount_using_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_discount_id' in params: path_params['insurance_discount_id'] = params['insurance_discount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_discount/{insurance_discount_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def delete_insurance_quote_using_delete(self, insurance_quote, insurance_quote_id, **kwargs): # noqa: E501 """Delete a insuranceQuote request # noqa: E501 Permanently delete a insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_insurance_quote_using_delete(insurance_quote, insurance_quote_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_quote: UUID insurance_quote_id (required) :param str insurance_quote_id: insurance_quote_id (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_insurance_quote_using_delete_with_http_info(insurance_quote, insurance_quote_id, **kwargs) # noqa: E501 else: (data) = self.delete_insurance_quote_using_delete_with_http_info(insurance_quote, insurance_quote_id, **kwargs) # noqa: E501 return data def delete_insurance_quote_using_delete_with_http_info(self, insurance_quote, insurance_quote_id, **kwargs): # noqa: E501 """Delete a insuranceQuote request # noqa: E501 Permanently delete a insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_insurance_quote_using_delete_with_http_info(insurance_quote, insurance_quote_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_quote: UUID insurance_quote_id (required) :param str insurance_quote_id: insurance_quote_id (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_quote', 'insurance_quote_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method delete_insurance_quote_using_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_quote' is set if ('insurance_quote' not in params or params['insurance_quote'] is None): raise ValueError("Missing the required parameter `insurance_quote` when calling `delete_insurance_quote_using_delete`") # noqa: E501 # verify the required parameter 'insurance_quote_id' is set if ('insurance_quote_id' not in params or params['insurance_quote_id'] is None): raise ValueError("Missing the required parameter `insurance_quote_id` when calling `delete_insurance_quote_using_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_quote' in params: path_params['insurance_quote'] = params['insurance_quote'] # noqa: E501 if 'insurance_quote_id' in params: path_params['insurance_quote_id'] = params['insurance_quote_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_quote/{insurance_quote_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_insurance_coverage_all_using_get(self, **kwargs): # noqa: E501 """Get all insurance coverage request # noqa: E501 Get all new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_coverage_all_using_get(async_req=True) >>> result = thread.get() :param async_req bool :param bool ascending: ascending :param str filter: filter :param str order_by: order_by :param int page: page :param int size: size :return: PageInsuranceCoverage If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_insurance_coverage_all_using_get_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_insurance_coverage_all_using_get_with_http_info(**kwargs) # noqa: E501 return data def get_insurance_coverage_all_using_get_with_http_info(self, **kwargs): # noqa: E501 """Get all insurance coverage request # noqa: E501 Get all new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_coverage_all_using_get_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param bool ascending: ascending :param str filter: filter :param str order_by: order_by :param int page: page :param int size: size :return: PageInsuranceCoverage If the method is called asynchronously, returns the request thread. """ all_params = ['ascending', 'filter', 'order_by', 'page', 'size'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_insurance_coverage_all_using_get" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'ascending' in params: query_params.append(('ascending', params['ascending'])) # noqa: E501 if 'filter' in params: query_params.append(('filter', params['filter'])) # noqa: E501 if 'order_by' in params: query_params.append(('order_by', params['order_by'])) # noqa: E501 if 'page' in params: query_params.append(('page', params['page'])) # noqa: E501 if 'size' in params: query_params.append(('size', params['size'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_coverage', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PageInsuranceCoverage', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_insurance_coverage_using_get(self, insurance_coverage_id, **kwargs): # noqa: E501 """Get a insurance coverage request # noqa: E501 Get a new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_coverage_using_get(insurance_coverage_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_coverage_id: UUID insurance_coverage_id (required) :return: InsuranceCoverage If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_insurance_coverage_using_get_with_http_info(insurance_coverage_id, **kwargs) # noqa: E501 else: (data) = self.get_insurance_coverage_using_get_with_http_info(insurance_coverage_id, **kwargs) # noqa: E501 return data def get_insurance_coverage_using_get_with_http_info(self, insurance_coverage_id, **kwargs): # noqa: E501 """Get a insurance coverage request # noqa: E501 Get a new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_coverage_using_get_with_http_info(insurance_coverage_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_coverage_id: UUID insurance_coverage_id (required) :return: InsuranceCoverage If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_coverage_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_insurance_coverage_using_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_coverage_id' is set if ('insurance_coverage_id' not in params or params['insurance_coverage_id'] is None): raise ValueError("Missing the required parameter `insurance_coverage_id` when calling `get_insurance_coverage_using_get`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_coverage_id' in params: path_params['insurance_coverage_id'] = params['insurance_coverage_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_coverage/{insurance_coverage_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceCoverage', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_insurance_discount_all_using_get(self, **kwargs): # noqa: E501 """Get all insurance discount request # noqa: E501 Get all new insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_discount_all_using_get(async_req=True) >>> result = thread.get() :param async_req bool :param bool ascending: ascending :param str filter: filter :param str order_by: order_by :param int page: page :param int size: size :return: PageInsuranceDiscount If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_insurance_discount_all_using_get_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_insurance_discount_all_using_get_with_http_info(**kwargs) # noqa: E501 return data def get_insurance_discount_all_using_get_with_http_info(self, **kwargs): # noqa: E501 """Get all insurance discount request # noqa: E501 Get all new insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_discount_all_using_get_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param bool ascending: ascending :param str filter: filter :param str order_by: order_by :param int page: page :param int size: size :return: PageInsuranceDiscount If the method is called asynchronously, returns the request thread. """ all_params = ['ascending', 'filter', 'order_by', 'page', 'size'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_insurance_discount_all_using_get" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'ascending' in params: query_params.append(('ascending', params['ascending'])) # noqa: E501 if 'filter' in params: query_params.append(('filter', params['filter'])) # noqa: E501 if 'order_by' in params: query_params.append(('order_by', params['order_by'])) # noqa: E501 if 'page' in params: query_params.append(('page', params['page'])) # noqa: E501 if 'size' in params: query_params.append(('size', params['size'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_discount', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PageInsuranceDiscount', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_insurance_discount_using_get(self, insurance_discount_id, **kwargs): # noqa: E501 """Get a insurance discount request # noqa: E501 Get a new insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_discount_using_get(insurance_discount_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_discount_id: UUID insurance_discount_id (required) :return: InsuranceDiscount If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_insurance_discount_using_get_with_http_info(insurance_discount_id, **kwargs) # noqa: E501 else: (data) = self.get_insurance_discount_using_get_with_http_info(insurance_discount_id, **kwargs) # noqa: E501 return data def get_insurance_discount_using_get_with_http_info(self, insurance_discount_id, **kwargs): # noqa: E501 """Get a insurance discount request # noqa: E501 Get a new insurance discount. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_discount_using_get_with_http_info(insurance_discount_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_discount_id: UUID insurance_discount_id (required) :return: InsuranceDiscount If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_discount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_insurance_discount_using_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_discount_id' is set if ('insurance_discount_id' not in params or params['insurance_discount_id'] is None): raise ValueError("Missing the required parameter `insurance_discount_id` when calling `get_insurance_discount_using_get`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_discount_id' in params: path_params['insurance_discount_id'] = params['insurance_discount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_discount/{insurance_discount_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceDiscount', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_insurance_quote_all_using_get(self, **kwargs): # noqa: E501 """List all insuranceQuote requests # noqa: E501 Get the information for all insuranceQuote requests. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_quote_all_using_get(async_req=True) >>> result = thread.get() :param async_req bool :param bool ascending: ascending :param str filter: filter :param str order_by: order_by :param int page: page :param int size: size :return: PageInsuranceQuote If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_insurance_quote_all_using_get_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_insurance_quote_all_using_get_with_http_info(**kwargs) # noqa: E501 return data def get_insurance_quote_all_using_get_with_http_info(self, **kwargs): # noqa: E501 """List all insuranceQuote requests # noqa: E501 Get the information for all insuranceQuote requests. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_quote_all_using_get_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param bool ascending: ascending :param str filter: filter :param str order_by: order_by :param int page: page :param int size: size :return: PageInsuranceQuote If the method is called asynchronously, returns the request thread. """ all_params = ['ascending', 'filter', 'order_by', 'page', 'size'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_insurance_quote_all_using_get" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] if 'ascending' in params: query_params.append(('ascending', params['ascending'])) # noqa: E501 if 'filter' in params: query_params.append(('filter', params['filter'])) # noqa: E501 if 'order_by' in params: query_params.append(('order_by', params['order_by'])) # noqa: E501 if 'page' in params: query_params.append(('page', params['page'])) # noqa: E501 if 'size' in params: query_params.append(('size', params['size'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_quote', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='PageInsuranceQuote', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def get_insurance_quote_using_get(self, insurance_quote, insurance_quote_id, **kwargs): # noqa: E501 """Retrieve a insuranceQuote request # noqa: E501 Retrieve the information for a insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_quote_using_get(insurance_quote, insurance_quote_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_quote: UUID insurance_quote_id (required) :param str insurance_quote_id: insurance_quote_id (required) :return: InsuranceQuote If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_insurance_quote_using_get_with_http_info(insurance_quote, insurance_quote_id, **kwargs) # noqa: E501 else: (data) = self.get_insurance_quote_using_get_with_http_info(insurance_quote, insurance_quote_id, **kwargs) # noqa: E501 return data def get_insurance_quote_using_get_with_http_info(self, insurance_quote, insurance_quote_id, **kwargs): # noqa: E501 """Retrieve a insuranceQuote request # noqa: E501 Retrieve the information for a insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_insurance_quote_using_get_with_http_info(insurance_quote, insurance_quote_id, async_req=True) >>> result = thread.get() :param async_req bool :param str insurance_quote: UUID insurance_quote_id (required) :param str insurance_quote_id: insurance_quote_id (required) :return: InsuranceQuote If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_quote', 'insurance_quote_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method get_insurance_quote_using_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_quote' is set if ('insurance_quote' not in params or params['insurance_quote'] is None): raise ValueError("Missing the required parameter `insurance_quote` when calling `get_insurance_quote_using_get`") # noqa: E501 # verify the required parameter 'insurance_quote_id' is set if ('insurance_quote_id' not in params or params['insurance_quote_id'] is None): raise ValueError("Missing the required parameter `insurance_quote_id` when calling `get_insurance_quote_using_get`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_quote' in params: path_params['insurance_quote'] = params['insurance_quote'] # noqa: E501 if 'insurance_quote_id' in params: path_params['insurance_quote_id'] = params['insurance_quote_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_quote/{insurance_quote_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceQuote', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_insurance_coverage_using_put(self, insurance_coverage, insurance_coverage_id, **kwargs): # noqa: E501 """Update a insurance coverage request # noqa: E501 Update a new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_insurance_coverage_using_put(insurance_coverage, insurance_coverage_id, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceCoverage insurance_coverage: insurance_coverage (required) :param str insurance_coverage_id: UUID insurance_coverage_id (required) :return: InsuranceCoverage If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.update_insurance_coverage_using_put_with_http_info(insurance_coverage, insurance_coverage_id, **kwargs) # noqa: E501 else: (data) = self.update_insurance_coverage_using_put_with_http_info(insurance_coverage, insurance_coverage_id, **kwargs) # noqa: E501 return data def update_insurance_coverage_using_put_with_http_info(self, insurance_coverage, insurance_coverage_id, **kwargs): # noqa: E501 """Update a insurance coverage request # noqa: E501 Update a new insurance coverage. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_insurance_coverage_using_put_with_http_info(insurance_coverage, insurance_coverage_id, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceCoverage insurance_coverage: insurance_coverage (required) :param str insurance_coverage_id: UUID insurance_coverage_id (required) :return: InsuranceCoverage If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_coverage', 'insurance_coverage_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_insurance_coverage_using_put" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_coverage' is set if ('insurance_coverage' not in params or params['insurance_coverage'] is None): raise ValueError("Missing the required parameter `insurance_coverage` when calling `update_insurance_coverage_using_put`") # noqa: E501 # verify the required parameter 'insurance_coverage_id' is set if ('insurance_coverage_id' not in params or params['insurance_coverage_id'] is None): raise ValueError("Missing the required parameter `insurance_coverage_id` when calling `update_insurance_coverage_using_put`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_coverage_id' in params: path_params['insurance_coverage_id'] = params['insurance_coverage_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'insurance_coverage' in params: body_params = params['insurance_coverage'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_coverage/{insurance_coverage_id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceCoverage', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_insurance_discount_using_put(self, insurance_discount, insurance_discount_id, **kwargs): # noqa: E501 """Update an insurance discount # noqa: E501 Update an new insurance . # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_insurance_discount_using_put(insurance_discount, insurance_discount_id, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceDiscount insurance_discount: insurance_discount (required) :param str insurance_discount_id: UUID insurance_discount_id (required) :return: InsuranceDiscount If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.update_insurance_discount_using_put_with_http_info(insurance_discount, insurance_discount_id, **kwargs) # noqa: E501 else: (data) = self.update_insurance_discount_using_put_with_http_info(insurance_discount, insurance_discount_id, **kwargs) # noqa: E501 return data def update_insurance_discount_using_put_with_http_info(self, insurance_discount, insurance_discount_id, **kwargs): # noqa: E501 """Update an insurance discount # noqa: E501 Update an new insurance . # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_insurance_discount_using_put_with_http_info(insurance_discount, insurance_discount_id, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceDiscount insurance_discount: insurance_discount (required) :param str insurance_discount_id: UUID insurance_discount_id (required) :return: InsuranceDiscount If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_discount', 'insurance_discount_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_insurance_discount_using_put" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_discount' is set if ('insurance_discount' not in params or params['insurance_discount'] is None): raise ValueError("Missing the required parameter `insurance_discount` when calling `update_insurance_discount_using_put`") # noqa: E501 # verify the required parameter 'insurance_discount_id' is set if ('insurance_discount_id' not in params or params['insurance_discount_id'] is None): raise ValueError("Missing the required parameter `insurance_discount_id` when calling `update_insurance_discount_using_put`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_discount_id' in params: path_params['insurance_discount_id'] = params['insurance_discount_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'insurance_discount' in params: body_params = params['insurance_discount'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_discount/{insurance_discount_id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceDiscount', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def update_insurance_quote_using_put(self, insurance_quote, insurance_quote_id, **kwargs): # noqa: E501 """Update a insuranceQuote request # noqa: E501 Update the information for a insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_insurance_quote_using_put(insurance_quote, insurance_quote_id, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceQuote insurance_quote: insurance_quote (required) :param str insurance_quote_id: UUID insurance_quote_id (required) :return: InsuranceQuote If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.update_insurance_quote_using_put_with_http_info(insurance_quote, insurance_quote_id, **kwargs) # noqa: E501 else: (data) = self.update_insurance_quote_using_put_with_http_info(insurance_quote, insurance_quote_id, **kwargs) # noqa: E501 return data def update_insurance_quote_using_put_with_http_info(self, insurance_quote, insurance_quote_id, **kwargs): # noqa: E501 """Update a insuranceQuote request # noqa: E501 Update the information for a insuranceQuote request. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.update_insurance_quote_using_put_with_http_info(insurance_quote, insurance_quote_id, async_req=True) >>> result = thread.get() :param async_req bool :param InsuranceQuote insurance_quote: insurance_quote (required) :param str insurance_quote_id: UUID insurance_quote_id (required) :return: InsuranceQuote If the method is called asynchronously, returns the request thread. """ all_params = ['insurance_quote', 'insurance_quote_id'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method update_insurance_quote_using_put" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'insurance_quote' is set if ('insurance_quote' not in params or params['insurance_quote'] is None): raise ValueError("Missing the required parameter `insurance_quote` when calling `update_insurance_quote_using_put`") # noqa: E501 # verify the required parameter 'insurance_quote_id' is set if ('insurance_quote_id' not in params or params['insurance_quote_id'] is None): raise ValueError("Missing the required parameter `insurance_quote_id` when calling `update_insurance_quote_using_put`") # noqa: E501 collection_formats = {} path_params = {} if 'insurance_quote_id' in params: path_params['insurance_quote_id'] = params['insurance_quote_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'insurance_quote' in params: body_params = params['insurance_quote'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['*/*']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['oauth2'] # noqa: E501 return self.api_client.call_api( '/insurance_quote/{insurance_quote_id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='InsuranceQuote', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

42.571154

154

0.637545

7,524

66,411

5.313131

0.023126

0.047228

0.024415

0.027016

0.987543

0.982164

0.977436

0.97526

0.96678

0.954898

0

0.015288

0.279005

66,411

1,559

155

42.598461

0.819598

0.326934

0

0.834721

1

0

0.212818

0.082795

0

1

0.036861

false

0

0.004756

0

0.096314

0

null

0

1

0

1

0

null

0

8

958d1e3cedfbb52632717dd0096fa6230ab0d676

2,014

py

Python

src/uselessfacts/main.py

Jakeisbored/uselessfacts

a79e2ba0d99959ef20dff734d7a98697f0157c53

[ "Apache-2.0" ]

null

src/uselessfacts/main.py

Jakeisbored/uselessfacts

a79e2ba0d99959ef20dff734d7a98697f0157c53

[ "Apache-2.0" ]

null

src/uselessfacts/main.py

Jakeisbored/uselessfacts

a79e2ba0d99959ef20dff734d7a98697f0157c53

[ "Apache-2.0" ]

null

import requests formats = ['html' , 'md' , 'txt' , 'json'] languages = ['en','de'] def random_fact(format=None,language=None): if(format == None) : format = 'json' if(not formats.__contains__(format)): raise Exception(f'Invaid format , should be one of {str(formats)}') else: if(language == None) : language = 'en' else: if(not languages.__contains__(language)): raise Exception(f'Invalid language , should be one of {str(languages)}') else: language = language try: r = requests.get('https://uselessfacts.jsph.pl/random.{}?language={}'.format(format,language)) return { 'status_code' : r.status_code, 'response' : r.json() if format == 'json' else r.text } except Exception as error: raise error def daily_fact(format=None,language=None): if(format == None) : format = 'json' if(not formats.__contains__(format)): raise Exception(f'Invaid format , should be one of {str(formats)}') else: if(language == None) : language = 'en' else: if(not languages.__contains__(language)): raise Exception(f'Invalid language , should be one of {str(languages)}') else: language = language try: r = requests.get('https://uselessfacts.jsph.pl/today.{}?language={}'.format(format,language)) return { 'status_code' : r.status_code, 'response' : r.json() if format == 'json' else r.text } except Exception as error: raise error def get_fact(id=None , format=None): if(id == None): raise Exception('You must provide an id') if(format == None) : format = 'json' if(not formats.__contains__(format)): raise Exception(f'Invaid format , should be one of {str(formats)}') try: r = requests.get('https://uselessfacts.jsph.pl/{}.{}'.format(id,format)) return { 'status_code' : r.status_code, 'response' : r.json() if format == 'json' else r.text } except Exception as error: raise Exception('Fact not found fool')

32.483871

98

0.632075

260

2,014

4.784615

0.207692

0.078778

0.060289

0.052251

0.860129

0.829582

0

0.217478

2,014

61

99

33.016393

0.78934

0

0.75

0

0.258689

0

1

0.05

false

0

0.016667

0

0.116667

0

null

0

1

0

1

0

null

0

7

95cd88b7a4d70b7dee36b3146e5819bdc87f669b

9,892

py

Python

dotmotif/executors/test_grandisoexecutor.py

aplbrain/dotmotif

db093ddad7308756e9cf7ee01199f0dca1369872

[ "Apache-2.0" ]

28

2020-06-12T20:46:15.000Z

2022-02-05T18:33:46.000Z

dotmotif/executors/test_grandisoexecutor.py

aplbrain/dotmotif

db093ddad7308756e9cf7ee01199f0dca1369872

[ "Apache-2.0" ]

26

2020-06-09T20:09:32.000Z

2022-02-01T18:22:20.000Z

dotmotif/executors/test_grandisoexecutor.py

aplbrain/dotmotif

db093ddad7308756e9cf7ee01199f0dca1369872

[ "Apache-2.0" ]

4

2021-03-08T02:47:49.000Z

2021-09-13T19:16:29.000Z

import unittest import dotmotif from dotmotif import Motif from dotmotif.executors import GrandIsoExecutor from dotmotif.executors.NetworkXExecutor import ( _edge_satisfies_constraints, _node_satisfies_constraints, ) from dotmotif.parsers.v2 import ParserV2 import networkx as nx class TestSmallMotifs(unittest.TestCase): def test_edgecount_motif(self): dm = Motif("""A->B""") H = nx.DiGraph() H.add_edge("x", "y") self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 1) H.add_edge("x", "y") self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 1) H.add_edge("x", "z") self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 2) def test_fullyconnected_triangle_motif(self): dm = Motif( """ A->B B->C C->A """ ) H = nx.DiGraph() H.add_edge("x", "y") self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 0) H.add_edge("y", "z") self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 0) H.add_edge("z", "x") self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 3) def test_edge_attribute_equality(self): dm = Motif( """ A->B [weight==10, area==4] """ ) H = nx.DiGraph() H.add_edge("z", "x", weight=10, area=4) H.add_edge("x", "y") H.add_edge("y", "z", weight=5) self.assertEqual(len(GrandIsoExecutor(graph=H).find(dm)), 1) def test_one_instance(self): H = nx.DiGraph() H.add_edge("x", "y", weight=1) H.add_edge("y", "z", weight=10) H.add_edge("z", "x", weight=5) motif = dotmotif.Motif( """ A -> B [weight>=11] """.strip() ) self.assertEqual(len(GrandIsoExecutor(graph=H).find(motif)), 0) def test_two_instance(self): H = nx.DiGraph() H.add_edge("x", "y", weight=1) H.add_edge("y", "z", weight=10) H.add_edge("z", "x", weight=5) H.add_edge("z", "a", weight=5) H.add_edge("a", "b", weight=1) H.add_edge("b", "c", weight=10) H.add_edge("c", "a", weight=5) motif = dotmotif.Motif( """ A -> B [weight>=7] """.strip() ) self.assertEqual(len(GrandIsoExecutor(graph=H).find(motif)), 2) def test_triangle_two_instance(self): H = nx.DiGraph() H.add_edge("x", "y", weight=1) H.add_edge("y", "z", weight=10) H.add_edge("z", "x", weight=5) H.add_edge("z", "a", weight=5) H.add_edge("a", "b", weight=1) H.add_edge("b", "c", weight=10) H.add_edge("c", "a", weight=5) motif = dotmotif.Motif( """ A -> B [weight>=7] B -> C C -> A """.strip() ) self.assertEqual(len(GrandIsoExecutor(graph=H).find(motif)), 2) def test_mini_example(self): H = nx.DiGraph() H.add_edge("y", "x", ATTRIBUTE=7) H.add_edge("y", "z", ATTRIBUTE=7) motif = dotmotif.Motif( """ A -> B [ATTRIBUTE>=7] """.strip() ) self.assertEqual(len(GrandIsoExecutor(graph=H).find(motif)), 2) def test_node_and_edge_full_example(self): H = nx.DiGraph() H.add_edge("X", "Y", weight=10) H.add_edge("Y", "Z", weight=9) H.add_edge("Z", "X", weight=8) motif = dotmotif.Motif( """ A -> B [weight>=7] """.strip() ) res = GrandIsoExecutor(graph=H).find(motif) self.assertEqual(len(res), 3) H.add_edge("Z", "C", weight=7) res = GrandIsoExecutor(graph=H).find(motif) self.assertEqual(len(res), 4) H.add_edge("Z", "D", weight="no") res = GrandIsoExecutor(graph=H).find(motif) self.assertEqual(len(res), 4) H.add_edge("y", "a") self.assertEqual(len(GrandIsoExecutor(graph=H).find(motif)), 4) H.add_edge("y", "a", other_weight=7, weight=8) self.assertEqual(len(GrandIsoExecutor(graph=H).find(motif)), 5) def test_automorphism_reduction(self): G = nx.DiGraph() G.add_edge("X", "Z") G.add_edge("Y", "Z") motif = dotmotif.Motif( """ A -> C B -> C A === B """ ) res = GrandIsoExecutor(graph=G).find(motif) self.assertEqual(len(res), 2) motif = dotmotif.Motif(exclude_automorphisms=True).from_motif( """ A -> C B -> C A === B """ ) res = GrandIsoExecutor(graph=G).find(motif) self.assertEqual(len(res), 1) def test_automorphism_auto(self): G = nx.DiGraph() G.add_edge("X", "Z") G.add_edge("Y", "Z") motif = dotmotif.Motif(exclude_automorphisms=True).from_motif( """ A -> C B -> C """ ) res = GrandIsoExecutor(graph=G).find(motif) self.assertEqual(len(res), 1) def test_automorphism_notauto(self): G = nx.DiGraph() G.add_edge("X", "Z") G.add_edge("Y", "Z") motif = dotmotif.Motif( """ A -> C B -> C """ ) res = GrandIsoExecutor(graph=G).find(motif) self.assertEqual(len(res), 2) def test_automorphism_flag_triangle(self): G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") motif = dotmotif.Motif( """ A -> B B -> C C -> A """ ) res = GrandIsoExecutor(graph=G).find(motif) self.assertEqual(len(res), 3) motif = dotmotif.Motif(exclude_automorphisms=True).from_motif( """ A -> B B -> C C -> A """ ) res = GrandIsoExecutor(graph=G).find(motif) self.assertEqual(len(res), 1) class TestDynamicNodeConstraints(unittest.TestCase): def test_dynamic_constraints_zero_results(self): """ Test that comparisons may be made between variables, e.g.: A.type != B.type """ G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") G.add_node("A", radius=5) G.add_node("B", radius=10) exp = """\ A -> B A.radius > B.radius """ dm = dotmotif.Motif(parser=ParserV2) res = GrandIsoExecutor(graph=G).find(dm.from_motif(exp)) self.assertEqual(len(res), 0) def test_dynamic_constraints_one_result(self): """ Test that comparisons may be made between variables, e.g.: A.type != B.type """ G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") G.add_node("A", radius=25) G.add_node("B", radius=10) exp = """\ A -> B A.radius > B.radius """ dm = dotmotif.Motif(parser=ParserV2) res = GrandIsoExecutor(graph=G).find(dm.from_motif(exp)) self.assertEqual(len(res), 1) def test_dynamic_constraints_two_results(self): """ Test that comparisons may be made between variables, e.g.: A.type != B.type """ G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") G.add_node("A", radius=25) G.add_node("B", radius=10) G.add_node("C", radius=5) exp = """\ A -> B A.radius > B.radius """ dm = dotmotif.Motif(parser=ParserV2) res = GrandIsoExecutor(graph=G).find(dm.from_motif(exp)) self.assertEqual(len(res), 2) def test_dynamic_constraints_in_macros_zero_results(self): """ Test that comparisons may be made between variables, e.g.: A.type != B.type """ G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") G.add_node("A", radius=5) G.add_node("B", radius=10) exp = """\ macro(A, B) { A.radius > B.radius } macro(A, B) A -> B """ dm = dotmotif.Motif(parser=ParserV2) res = GrandIsoExecutor(graph=G).find(dm.from_motif(exp)) self.assertEqual(len(res), 0) def test_dynamic_constraints_in_macros_one_result(self): """ Test that comparisons may be made between variables, e.g.: A.type != B.type """ G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") G.add_node("A", radius=15) G.add_node("B", radius=10) exp = """\ macro(A, B) { A.radius > B.radius } macro(A, B) A -> B """ dm = dotmotif.Motif(parser=ParserV2) res = GrandIsoExecutor(graph=G).find(dm.from_motif(exp)) self.assertEqual(len(res), 1) def test_dynamic_constraints_in_macros_two_result(self): """ Test that comparisons may be made between variables, e.g.: A.type != B.type """ G = nx.DiGraph() G.add_edge("A", "B") G.add_edge("B", "C") G.add_edge("C", "A") G.add_node("A", radius=15) G.add_node("B", radius=10) G.add_node("C", radius=10) exp = """\ macro(A, B) { A.radius >= B.radius } macro(A, B) A -> B """ dm = dotmotif.Motif(parser=ParserV2) res = GrandIsoExecutor(graph=G).find(dm.from_motif(exp)) self.assertEqual(len(res), 2)

26.449198

71

0.503134

1,267

9,892

3.805051

0.078137

0.090023

0.058079

0.086289

0.870774

0.851898

0.819125

0.812694

0.763327

0.722879

0

0.015887

0.331884

9,892

373

72

26.520107

0.713572

0.046603

0

0.710084

0

0.074551

0

0.117647

1

0.07563

false

0

0.029412

0

0.113445

0

null

0

1

0

1

0

null

0

7

667fdb0824d7d709028cb1c834695fba8cb0946e

24,515

py

Python

baoming/webapp/controller/search/administrator.py

hanxiaoshun/RegistrationSystem

2f7310508fc1725e96fe941b1062ce7f26f265a4

[ "Apache-2.0" ]

null

baoming/webapp/controller/search/administrator.py

hanxiaoshun/RegistrationSystem

2f7310508fc1725e96fe941b1062ce7f26f265a4

[ "Apache-2.0" ]

14

2020-06-06T01:24:24.000Z

2022-03-12T00:17:22.000Z

baoming/webapp/controller/search/administrator.py

hanxiaoshun/RegistrationSystem

2f7310508fc1725e96fe941b1062ce7f26f265a4

[ "Apache-2.0" ]

null

import json from django.core.paginator import Paginator from ..renderUtil import render_result from .search_common import * from .search_param_deal import search_return, search_parameter from webapp.utils.date_encoder import * sys_msg = '报名系统' result = {'status': True, 'message': ''} def administrator_search_chemical(request): """ 化工类待条件查询 :param request: :return: """ title_msg = '化工类学员' param_result = search_parameter(request) if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main,'report_skill':report_skill} if param_result: return render_result(request, "page_main_controller/administrator/reporter_chemical.html", page_result) def administrator_search_chemical_not(request): """ (非化工类)化工类待条件查询 :param request: :return: """ title_msg = "学员报名资料(非化工)" param_result = search_parameter(request) if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main,'report_skill':report_skill} if param_result: return render_result(request, "page_main_controller/administrator/reporter_chemical_not.html", page_result) def administrator_search_all_student(request): """ 所有学员的条件查询 :param request: :return: """ title_msg = '查询所有学员' param_result = search_parameter(request, 'all_student') if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main,'report_skill':report_skill,'no_term': True} if param_result: return render_result(request, "page_main_controller/administrator/all_student_base_info.html", page_result) def administrator_search_wait_confirm(request): """ 待确认学生信息列表 :param request: :return: """ title_msg = '学生填报信息待确认列表' param_result = search_parameter(request, 'wait_confirm') if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main, 'report_skill':report_skill, 'no_term': True} if param_result: return render_result(request, "page_main_controller/administrator/report_student_info_list_admin.html", page_result) def administrator_reporter_electronic_communication(request): """ 电子通信类 :param request: :return: """ param_result = search_parameter(request, 'electronic_communication') if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] title_msg = "电子通信类导入模板" page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main,'report_skill':report_skill} if param_result: return render_result(request, "page_main_controller/administrator/reporter_electronic_communication.html", page_result) def administrator_reporter_spin(request): """ 纺织类 :param request: :return: """ title_msg = '查询所有纺织大类学员' param_result = search_parameter(request, 'spin') if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main,'report_skill':report_skill} if param_result: return render_result(request, "page_main_controller/administrator/reporter_spin.html", page_result) def administrator_worker_years_6(request): """ 工作满6年（含）以上人员名单 :param request: :return: """ title_msg = '工作满6年（含）以上人员名单' param_result = search_parameter(request, '') if 'school_term' in param_result: if param_result['school_term'] is None: message = '尚未添加->报考学期->信息，请->管理员->添加相关信息' return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'user_search_error_class' in param_result: if param_result['user_search_error_class'] is not None: print(param_result['user_search_error_class'], param_result['user_search_errors']) message = '系统提示：参数传输错误：' + param_result['user_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) elif 'student_search_error_class' in param_result: if param_result['student_search_error_class'] is not None: print(param_result['student_search_error_class'], param_result['student_search_errors']) message = '系统提示：获取当前用户信息失败：' + param_result['student_search_errors'] return render_result(request, "page_main_controller/message.html", {'title_msg': title_msg, 'message': message}) else: report_skill_main_list = param_result['report_skill_main_list'] report_skill_list = param_result['report_skill_list'] tmp_list = param_result['tmp_list'] last_school_term = param_result['last_school_term'] student_info = param_result['student_info'] contacts = param_result['contacts'] teacher_infos = param_result['teacher_infos'] school_terms = param_result['school_terms'] school_term = param_result['school_term'] teacher_info = param_result['teacher_info'] identification_level = param_result['identification_level'] report_skill_main = param_result['report_skill_main'] report_skill = param_result['report_skill'] page_result = {'title_msg': title_msg, 'need_login': False, 'report_skill_main_list':report_skill_main_list, 'report_skill_list':report_skill_list, 'tmp_list': json.dumps(tmp_list, ensure_ascii=False), 'last_school_term': last_school_term, 'student_info': student_info, 'contacts': contacts, 'teacher_infos': teacher_infos, 'school_terms': school_terms, 'school_term': school_term, 'teacher_info': teacher_info, 'identification_level': identification_level, 'report_skill_main':report_skill_main,'report_skill':report_skill} if param_result: return render_result(request, "page_main_controller/administrator/reporter_worker_years_6.html", page_result)

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null

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1

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null

0

7

dd71b0fb8d569e7cf2ee675f50d1aa265788903f

146

py

Python

netbox_graphql/tests/utils.py

ninech/django-netbox-graphql

8383570bdf3a8ce8d9d912c5b8f7b053b31c7363

[ "MIT" ]

17

2017-08-17T02:38:09.000Z

2022-01-05T15:36:20.000Z

netbox_graphql/tests/utils.py

ninech/django-netbox-graphql

8383570bdf3a8ce8d9d912c5b8f7b053b31c7363

[ "MIT" ]

2

2017-09-13T14:53:56.000Z

2018-02-08T14:06:54.000Z

netbox_graphql/tests/utils.py

ninech/django-netbox-graphql

8383570bdf3a8ce8d9d912c5b8f7b053b31c7363

[ "MIT" ]

2

2020-03-04T11:51:10.000Z

2021-03-11T19:24:37.000Z

from graphql_relay.node.node import from_global_id, to_global_id def obj_to_global_id(obj): return to_global_id(type(obj).__name__, obj.id)

24.333333

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null

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0

8

06e442cf2393ab3f5c198839ce7144b9e59bfe3b

232

py

Python

{{cookiecutter.repository_name}}/{{cookiecutter.package_name}}/model/__init__.py

Aiwizo/pytorch-lantern-template

cc20b82ac91d0291c0c981f4afc87ca4c6422207

[ "Apache-2.0" ]

1

2021-04-13T14:13:16.000Z

{{cookiecutter.repository_name}}/{{cookiecutter.package_name}}/model/__init__.py

Aiwizo/pytorch-lantern-template

cc20b82ac91d0291c0c981f4afc87ca4c6422207

[ "Apache-2.0" ]

10

2020-12-17T07:26:29.000Z

2021-08-13T07:43:17.000Z

{{cookiecutter.repository_name}}/{{cookiecutter.package_name}}/model/__init__.py

Aiwizo/pytorch-lantern-template

cc20b82ac91d0291c0c981f4afc87ca4c6422207

[ "Apache-2.0" ]

null

from {{cookiecutter.package_name}}.model.standardized_image import StandardizedImage from {{cookiecutter.package_name}}.model.prediction import Prediction, PredictionBatch from {{cookiecutter.package_name}}.model.model import Model

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1

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null

0

1

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1

0

7

66131fa66c1183d21a56009eb259eb3983959979

34,923

py

Python

pytest/testPyTX.py

Manny27nyc/BitcoinArmory

1d02a6640d6257ab0c37013e5cd4b99681a5cfc3

[ "MIT" ]

505

2016-02-04T15:54:46.000Z

2022-03-27T18:43:01.000Z

pytest/testPyTX.py

jimmysong/BitcoinArmory

1c7190176897a2e0f3e4e198ab2f199059bb2402

[ "MIT" ]

528

2016-02-06T19:50:12.000Z

2022-01-15T10:21:16.000Z

pytest/testPyTX.py

jimmysong/BitcoinArmory

1c7190176897a2e0f3e4e198ab2f199059bb2402

[ "MIT" ]

208

2015-01-02T10:31:40.000Z

2021-12-14T07:37:36.000Z

''' Created on Aug 4, 2013 @author: Andy ''' import sys sys.path.append('..') import unittest from pytest.Tiab import TiabTest # Do not put any other imports before TiabTest ################ from armoryengine.ArmoryUtils import hex_to_binary, binary_to_hex, hex_to_int, \ ONE_BTC from armoryengine.BinaryUnpacker import BinaryUnpacker from armoryengine.Block import PyBlock from armoryengine.PyBtcAddress import PyBtcAddress from armoryengine.Script import PyScriptProcessor from armoryengine.Transaction import PyTx, PyTxIn, PyOutPoint, PyTxOut, \ PyCreateAndSignTx, getMultisigScriptInfo, BlockComponent,\ PyCreateAndSignTx_old # Unserialize an reserialize tx1raw = hex_to_binary( \ '01000000016290dce984203b6a5032e543e9e272d8bce934c7de4d15fa0fe44d' 'd49ae4ece9010000008b48304502204f2fa458d439f957308bca264689aa175e' '3b7c5f78a901cb450ebd20936b2c500221008ea3883a5b80128e55c9c6070aa6' '264e1e0ce3d18b7cd7e85108ce3d18b7419a0141044202550a5a6d3bb81549c4' 'a7803b1ad59cdbba4770439a4923624a8acfc7d34900beb54a24188f7f0a4068' '9d905d4847cc7d6c8d808a457d833c2d44ef83f76bffffffff0242582c0a0000' '00001976a914c1b4695d53b6ee57a28647ce63e45665df6762c288ac80d1f008' '000000001976a9140e0aec36fe2545fb31a41164fb6954adcd96b34288ac00000000') tx2raw = hex_to_binary( \ '0100000001f658dbc28e703d86ee17c9a2d3b167a8508b082fa0745f55be5144' 'a4369873aa010000008c49304602210041e1186ca9a41fdfe1569d5d807ca7ff' '6c5ffd19d2ad1be42f7f2a20cdc8f1cc0221003366b5d64fe81e53910e156914' '091d12646bc0d1d662b7a65ead3ebe4ab8f6c40141048d103d81ac9691cf13f3' 'fc94e44968ef67b27f58b27372c13108552d24a6ee04785838f34624b294afee' '83749b64478bb8480c20b242c376e77eea2b3dc48b4bffffffff0200e1f50500' '0000001976a9141b00a2f6899335366f04b277e19d777559c35bc888ac40aeeb' '02000000001976a9140e0aec36fe2545fb31a41164fb6954adcd96b34288ac00000000') multiTx1raw = hex_to_binary( \ '0100000004a14fd232f045f0c9f28c6848a22fee393152e901eaa61a9f18438b3ba05c6035010000008a47304402201b19808aa145dbebf775ed11a15d763eaa2' 'b5df92b20f9835f62c72404918b1b02205aea3e816ac6ac7545254b9c34a00c37f20024793bbe0a64958934343f3c577b014104c0f3d0a4920bb6825769dd6ae1' 'e36b0ac36581639d605241cdd548c4ef5d46cda5ac21723d478041a63118f192fdb730c4cf76106789824cd68879a7afeb5288ffffffffa14fd232f045f0c9f28' 'c6848a22fee393152e901eaa61a9f18438b3ba05c6035000000008b4830450220796307d9787b892c8b1ada8511d99e855ea3099e1a76ce0f7aa783ed352a6e59' '022100fc38d05d7dfbe51e28c36d854dd0dcc938d60a3e406573c3dc39253694d14a12014104630aaf9d5c8d757cb5759428d4075911a2b2ff13dd7208ad7ea1d' '1682738a7138be93ee526c9d774e0dea03fa2a5fbb68043259ddfb942c0763f9b636b40c43fffffffffa14fd232f045f0c9f28c6848a22fee393152e901eaa61a' '9f18438b3ba05c6035020000008c493046022100cb423b63197ef3cdbfaed69f61aac59755f0025bd6d7a9d3c78024d897ebcf94022100f3ad14804a3c8042387' 'eca9b9053abe99e12651a795cae7f546b08e1c08c6464014104649694df12dcd7fdb5a8c54c376b904bd7337891d865b8d306beb5d2e5d8fdf2a537d6f9df65ff' '44eb0b6042ebfdf9e338bff7f4afacb359dd6c71aea7b9b92dffffffffa14fd232f045f0c9f28c6848a22fee393152e901eaa61a9f18438b3ba05c60350300000' '08b483045022100fb9f4ddc68497a266362d489abf05184909a2b99aa64803061c88597b725877802207f39cf5a90a305aee45f365cf9e2d258e37cab4da6c123' 'aa287635cd1fd40dd001410438252055130f3dd242201684931550c4065efc1b87c48192f75868f747e2a9df9a700fed7e90068bd395c58680bd593780c8119e7' '981dae08c345588f120fcb4ffffffff02e069f902000000001976a914ad00cf2b893e132c33a79a22ae938d6309c780a488ac80f0fa02000000001976a9143155' '18b646ea65ad148ee1e2f0360233617447e288ac00000000') multiTx2raw = hex_to_binary( \ '0100000004a14fd232f045f0c9f28c6848a22fee393152e901eaa61a9f18438b3ba05c6035010000008a47304402201b19808aa145dbebf775ed11a15d763eaa2' 'b5df92b20f9835f62c72404918b1b02205aea3e816ac6ac7545254b9c34a00c37f20024793bbe0a64958934343f3c577b014104c0f3d0a4920bb6825769dd6ae1' 'e36b0ac36581639d605241cdd548c4ef5d46cda5ac21723d478041a63118f192fdb730c4cf76106789824cd68879a7afeb5288ffffffffa14fd232f045f0c9f28' 'c6848a22fee393152e901eaa61a9f18438b3ba05c6035000000008b4830450220796307d9787b892c8b1ada8511d99e855ea3099e1a76ce0f7aa783ed352a6e59' '022100fc38d05d7dfbe51e28c36d854dd0dcc938d60a3e406573c3dc39253694d14a12014104630aaf9d5c8d757cb5759428d4075911a2b2ff13dd7208ad7ea1d' '1682738a7138be93ee526c9d774e0dea03fa2a5fbb68043259ddfb942c0763f9b636b40c43fffffffffa14fd232f045f0c9f28c6848a22fee393152e901eaa61a' '9f18438b3ba05c6035020000008c493046022100cb423b63197ef3cdbfaed69f61aac59755f0025bd6d7a9d3c78024d897ebcf94022100f3ad14804a3c8042387' 'eca9b9053abe99e12651a795cae7f546b08e1c08c6464014104649694df12dcd7fdb5a8c54c376b904bd7337891d865b8d306beb5d2e5d8fdf2a537d6f9df65ff' '44eb0b6042ebfdf9e338bff7f4afacb359dd6c71aea7b9b92dffffffffa14fd232f045f0c9f28c6848a22fee393152e901eaa61a9f18438b3ba05c60350300000' '08c49304602220000fb9f4ddc68497a266362d489abf05184909a2b99aa64803061c88597b725877802207f39cf5a90a305aee45f365cf9e2d258e37cab4da6c123' 'aa287635cd1fd40dd001410438252055130f3dd242201684931550c4065efc1b87c48192f75868f747e2a9df9a700fed7e90068bd395c58680bd593780c8119e7' '981dae08c345588f120fcb4ffffffff02e069f902000000001976a914ad00cf2b893e132c33a79a22ae938d6309c780a488ac80f0fa02000000001976a9143155' '18b646ea65ad148ee1e2f0360233617447e288ac00000000') # has both Multi-SigmultiSig2of3 bare and P2SH # First input is bare, and 2nd and 3rd are P2SH multiSig2of3 = hex_to_binary(( '01000000 036bceb0 631853d2 e9d8597c f91b7339 7e1ad838 fa1f1396 275c5ad3' '32ea0c16 15010000 00920048 30450221 00909e02 1f8d9482 04773a1e e953459f' '96b42247 7e0f11ba b54a4bb8 d1fadea8 0d02202d 1b79dcbc 8e3a2b36 3cc971ae' 'f7cacb42 3bef200e ebcbb680 fce6c475 f9175801 47304402 20326f53 d77c049b' '7627fd52 25cf0542 f16e5d84 99714b68 2aa11e9e e389605f 31022007 b9bfac66' '886efdca eef17581 21646c0d 97fbf7f5 639538e0 06aee09e 3c471101 ffffffff' 'fdba3759 bac4d06b 9a16e669 96a986fc 13108842 ebbe87fc eadf4752 4b4809dd' '00000000 fd5c0100 47304402 2055c491 84845c1d 92c81ad8 f0085b80 8e00fc58' '6c8c8332 6177213a 5778a35d 2302200d 2bd241fd 8f8c77db 0b12517d 4edbeaed' '47dd21d7 ffd46729 4992fe33 fb1c4201 47304402 201ff20a ce41831b b7902f0c' 'a5ecd6cb 3f681f23 47d89cd3 ba2e5cce 1e2e9cc4 f302204d fab13267 729f0290' 'a1b22e39 ce951b91 c3102b82 99dc6bb7 4aed7de5 83045a01 4cc95241 04390ad0' '36732b60 991854df d75f2a69 f9c66f05 05d031dd 7883be1d 411dea29 a97c1cb3' 'c172344d eea11050 e21d4dd5 647241de f6cdfb30 db27aad5 f63817b7 ac410466' 'f9270b58 4c3e0418 277b8bd6 046b609d 77eac38b 6be4384e 589f3335 1976884b' '8944b03d 0f6f6bcd 08aba612 4cae1af1 34514e0e 958064ae 9eaef831 055d6441' '04cfaa15 4390a4fa 244fd064 ec8e61ac 0c3e9ccf 94a4a7f4 d89ac946 b7005080' '82f5a63b 2f25fdfc 3621c94b ead1c378 2793c53f 0734cc18 08ed3b79 5ce94a40' '4c53aeff ffffff2c 94040fe5 d781fb35 d779cf0c 88bae45b d1bd03b5 761bae32' 'f8cf4d4c 3c31c400 000000fd 5e010048 30450221 00824183 2fd85b99 4bc54168' '8db9daf5 fb90244c 5f0eb9d5 4142b092 c8dce878 cc022049 67a455d9 852afaea' '15c9f788 7f31db72 368a8393 f6b4b34c 9488b765 618c3b01 48304502 2100b050' '78411f13 42d10495 cb8bc7bd 1ede6748 c327c68f c5e90310 fe11dd7e 2d4c0220' '410346b8 d40c54ed 237f0864 eeee0eb5 fa259026 6a5f1909 21ec973f 13a5bdb4' '014cc952 4104390a d036732b 60991854 dfd75f2a 69f9c66f 0505d031 dd7883be' '1d411dea 29a97c1c b3c17234 4deea110 50e21d4d d5647241 def6cdfb 30db27aa' 'd5f63817 b7ac4104 66f9270b 584c3e04 18277b8b d6046b60 9d77eac3 8b6be438' '4e589f33 35197688 4b8944b0 3d0f6f6b cd08aba6 124cae1a f134514e 0e958064' 'ae9eaef8 31055d64 4104cfaa 154390a4 fa244fd0 64ec8e61 ac0c3e9c cf94a4a7' 'f4d89ac9 46b70050 8082f5a6 3b2f25fd fc3621c9 4bead1c3 782793c5 3f0734cc' '1808ed3b 795ce94a 404c53ae ffffffff 01cfb8a2 09000000 00c95241 04390ad0' '36732b60 991854df d75f2a69 f9c66f05 05d031dd 7883be1d 411dea29 a97c1cb3' 'c172344d eea11050 e21d4dd5 647241de f6cdfb30 db27aad5 f63817b7 ac410466' 'f9270b58 4c3e0418 277b8bd6 046b609d 77eac38b 6be4384e 589f3335 1976884b' '8944b03d 0f6f6bcd 08aba612 4cae1af1 34514e0e 958064ae 9eaef831 055d6441' '04cfaa15 4390a4fa 244fd064 ec8e61ac 0c3e9ccf 94a4a7f4 d89ac946 b7005080' '82f5a63b 2f25fdfc 3621c94b ead1c378 2793c53f 0734cc18 08ed3b79 5ce94a40' '4c53ae00 000000 ').replace(' ','')) # has both Multi-Sig bare and P2SH # First input is ... multiSig7of7 = hex_to_binary(( '01000000 02827c86 94a5c3c3 698fee0c 30d8b1e8 7880f47e 4a99e1c5 7a060ffb' 'b09ad4ac ad000000 00fdfd01 00473044 02201a85 dde4134c f8491241 f5c33821' '6a0c2771 1b519ef3 122429d7 e0016b21 4e960220 711ae401 457d3aa9 e6fa684f' 'e5238cee 54ff7b38 c754a722 2ab32b1d 5a6710d7 01483045 022100ca fad36ad8' '79cd5c7e 3b3a5864 03e6f30d 8bfb8b3c 60c42c3b c3ee1ec1 41639f02 2074e0b8' '2df54cf3 dc966351 4ccbc743 52cda16c f6e9181f 5c9bcbae 4b589d88 36014830' '45022100 bbb047a8 6c75b089 df24b650 1e466db7 7a83cdcd e6a6c29a 7bf7349d' '6a986ffd 02200806 86406105 0c05e797 e5f46b1a 3e0a28bb 65b86617 af2ea010' 'b58a1e46 63a20147 30440220 5da1823d e450841b 96f44d15 48ec6165 49dbecd1' 'defad45e ea767b88 6665291a 02201e4a 4b5139e3 34200c3f 171ab22c 4fac6e16' '9011c17e cc473750 4c1d3bdb b09f0147 30440220 32a970ec 0d3fd10a e6e47aa3' '388817e6 9c4a40e9 ef37d71c 935106d1 bf5a5f96 02201124 237ce7c9 eef01f1c' 'cb6f4c3f 8069b826 a97e999a 5efa150d 2149fe67 fc9f0148 30450221 00d799e6' '2819bba2 691461a8 a5e0bd55 48df3f97 8091760b 437aec57 863ca5b5 9402202c' '791d8949 93ee88f1 c3de2363 fa1c6200 005f2e41 85ed1a49 9a7cd174 1aeb8d01' '48304502 21008f59 02bd3487 1bc920ad e293e08f b57bbdbb bd2127d5 14551866' 'b14befef ff620220 35eafa7e 653bffaf e681af7d b1cb86c0 4096f17f ac2edbce' 'e654e4b5 7b86e86d 01ffffff ff827c86 94a5c3c3 698fee0c 30d8b1e8 7880f47e' '4a99e1c5 7a060ffb b09ad4ac ad010000 00fdd303 00483045 022100f9 c1bea188' '7991f50e 78c7c67d 4ca5d6db 69254b94 089ec3dc 848e682d 1eb79502 200e564d' 'bf74024d e2a89439 726d8efe 522dfc01 587b749c 34a8c22e 98943e81 29014830' '45022100 ebdd6a9a 45ac4be7 0f982a53 c79b9903 68635f0a 9dcb29ec 46845686' '712e9459 02203c77 968795bb 8c360a5c 616c9695 26a56846 17c44635 b85c458a' '76155ca7 528b0148 30450221 00eec14d 4d6cb1da 92e43c93 a3a088a1 7799696f' 'f7aa64b7 6e06207b b400b0db a0022068 df74f129 42681229 f5a99c34 f6cbf7bc' 'df10e8ff 3da0432a ead01fc6 523cda01 48304502 2100e7f4 c88fd69b 7a00255b' '3e6d48bf 2d6249c0 8669fbc5 cfdd395e 76b0e5c1 cfb10220 27665a72 a75d1762' '7c14589e d6d9f3c7 9b3c1f62 e5ab35cc 18e957b4 fcaa0e43 01483045 022100c6' '73b28b2c 6f5be2dd c04395e3 aaf3d7ba f148e679 8629603c 5dfd7e01 f5b27d02' '203db74e ebd0ebd2 dfb30912 316d0f0c 39e54431 0c2948b8 f1534f9b d31ae4fb' 'de014830 45022100 e484209f e5298481 3d6b3c74 ace64bc7 caaedc5e eccc4fb3' '6026c6af 0851b50e 02207a26 d23168b7 31b8d3e8 ac351e17 370eeb33 69c1f684' '6200fee0 5786fdb1 bfe50147 30440220 3636c311 c249013f f55d1987 3c70d003' 'eae19ae1 03bc60b6 44173865 2d882c9a 022069a9 c2a30200 d9c62116 ba6e5cb0' '3a6772fc 01687225 dd87127a 87776de6 a2ef014d d1015741 0434fba0 192f2030' '5e3d4c62 0efea962 6d0f9a90 9d2890dc 4101e945 89ea4e68 22b67efc eed5fbab' 'c1d994db 8abf9a86 fcc44606 ab76b6a5 d38a9930 0072208d 7e410446 cb30b98f' '7d162fa6 5f8b34f7 6ebb0e46 4903b64d 93eac48a 021db98d 80a1416e 848af76e' '0a2c79dd 2fda9616 2314db83 7863d8d8 1a956949 26cd8e58 2ccb8d41 0449ff69' '21e263ec 2880c9fa 1620f42a 0c2cebf3 bfb78c51 bb462c50 852f0cd3 ab31470a' 'f0dc234a c9167da2 d962a25e fde71bb2 0ef53d6d 446c053f b8458399 d1410450' 'abee229f 06ca4ed9 cbff65e5 4cfdb562 6c4a707e aa5d40cb a181e56d 59ef36d3' '638c7704 8cb0fbcd 3bf0cf78 39e668df 5401d89a f9075710 9da190c8 f67eec41' '0452f588 273dda31 649aab7b f825c2e2 706962c2 0c17e738 7b3698de 06f7af09' 'c8d18a76 1162d510 915a8097 e29dcd5f f3d4de9d cac226da f2e3c61b 81b064be' '82410461 9c4390ca 53825a15 a07ebf6d e2979bc9 c42c4de0 f57f3e83 cd7b5007' '6a413799 6403ec86 2fd5c1d4 13b63683 36c6a2b6 c88bcb61 beb1009e 3a691572' 'c2799841 04bbee46 8827e700 4a9c535d c699e33e cf01a521 471738fa 2a25c432' '58d13be5 f0654189 ca5c1a56 880791a6 1039fb65 de1d9056 836a0a7f 139369b2' '46a42b94 ed57aeff ffffff02 007e5603 00000000 17a914ee 5ae7effc dc259821' '70b8a822 978338c1 c3b3c987 e0ba3c00 00000000 17a914ee 5ae7effc dc259821' '70b8a822 978338c1 c3b3c987 00000000 ').replace(' ','')) # Here's a full block, which we should be able to parse and process hexBlock = ( \ '01000000eb10c9a996a2340a4d74eaab41421ed8664aa49d18538bab59010000000000005a2f06efa9f2bd804f17877537f2080030cadbfa1eb50e02338117cc' '604d91b9b7541a4ecfbb0a1a64f1ade70301000000010000000000000000000000000000000000000000000000000000000000000000ffffffff0804cfbb0a1a' '02360affffffff0100f2052a01000000434104c2239c4eedb3beb26785753463be3ec62b82f6acd62efb65f452f8806f2ede0b338e31d1f69b1ce449558d7061' 'aa1648ddc2bf680834d3986624006a272dc21cac000000000100000003e8caa12bcb2e7e86499c9de49c45c5a1c6167ea4b894c8c83aebba1b6100f343010000' '008c493046022100e2f5af5329d1244807f8347a2c8d9acc55a21a5db769e9274e7e7ba0bb605b26022100c34ca3350df5089f3415d8af82364d7f567a6a297f' 'cc2c1d2034865633238b8c014104129e422ac490ddfcb7b1c405ab9fb42441246c4bca578de4f27b230de08408c64cad03af71ee8a3140b40408a7058a1984a9' 'f246492386113764c1ac132990d1ffffffff5b55c18864e16c08ef9989d31c7a343e34c27c30cd7caa759651b0e08cae0106000000008c4930460221009ec9aa' '3e0caf7caa321723dea561e232603e00686d4bfadf46c5c7352b07eb00022100a4f18d937d1e2354b2e69e02b18d11620a6a9332d563e9e2bbcb01cee559680a' '014104411b35dd963028300e36e82ee8cf1b0c8d5bf1fc4273e970469f5cb931ee07759a2de5fef638961726d04bd5eb4e5072330b9b371e479733c942964bb8' '6e2b22ffffffff3de0c1e913e6271769d8c0172cea2f00d6d3240afc3a20f9fa247ce58af30d2a010000008c493046022100b610e169fd15ac9f60fe2b507529' '281cf2267673f4690ba428cbb2ba3c3811fd022100ffbe9e3d71b21977a8e97fde4c3ba47b896d08bc09ecb9d086bb59175b5b9f03014104ff07a1833fd8098b' '25f48c66dcf8fde34cbdbcc0f5f21a8c2005b160406cbf34cc432842c6b37b2590d16b165b36a3efc9908d65fb0e605314c9b278f40f3e1affffffff0240420f' '00000000001976a914adfa66f57ded1b655eb4ccd96ee07ca62bc1ddfd88ac007d6a7d040000001976a914981a0c9ae61fa8f8c96ae6f8e383d6e07e77133e88' 'ac00000000010000000138e7586e0784280df58bd3dc5e3d350c9036b1ec4107951378f45881799c92a4000000008a47304402207c945ae0bbdaf9dadba07bdf' '23faa676485a53817af975ddf85a104f764fb93b02201ac6af32ddf597e610b4002e41f2de46664587a379a0161323a85389b4f82dda014104ec8883d3e4f7a3' '9d75c9f5bb9fd581dc9fb1b7cdf7d6b5a665e4db1fdb09281a74ab138a2dba25248b5be38bf80249601ae688c90c6e0ac8811cdb740fcec31dffffffff022f66' 'ac61050000001976a914964642290c194e3bfab661c1085e47d67786d2d388ac2f77e200000000001976a9141486a7046affd935919a3cb4b50a8a0c233c286c' '88ac00000000') # I made these two tx in a fake blockchain... but they should still work tx1Fake = PyTx().unserialize(hex_to_binary( ( '01000000 0163451d 1002611c 1388d5ba 4ddfdf99 196a86b5 990fb5b0 dc786207' '4fdcb8ee d2000000 004a4930 46022100 cb02fb5a 910e7554 85e3578e 6e9be315' 'a161540a 73f84ee6 f5d68641 925c59ac 0221007e 530a1826 30b50e2c 12dd09cd' 'ebfd809f 038be982 bdc2c7e9 d4cbf634 9e088d01 ffffffff 0200ca9a 3b000000' '001976a9 14cb2abd e8bccacc 32e893df 3a054b9e f7f227a4 ce88ac00 286bee00' '00000019 76a914ee 26c56fc1 d942be8d 7a24b2a1 001dd894 69398088 ac000000' '00' ).replace(' ',''))) tx2Fake = PyTx().unserialize(hex_to_binary( ( '01000000 01a5b837 da38b64a 6297862c ba8210d0 21ac59e1 2b7c6d7e 70c355f6' '972ee7a8 6e010000 008c4930 46022100 89e47100 d88d5f8c 8f62a796 dac3afb8' 'f090c6fc 2eb0c4af ac7b7567 3a364c01 0221002b f40e554d ae51264b 0a86df17' '3e45756a 89bbd302 4f166cc4 2cfd1874 13636901 41046868 0737c76d abb801cb' '2204f57d be4e4579 e4f710cd 67dc1b42 27592c81 e9b5cf02 b5ac9e8b 4c9f49be' '5251056b 6a6d011e 4c37f6b6 d17ede6b 55faa235 19e2ffff ffff0100 286bee00' '00000019 76a914c5 22664fb0 e55cdc5c 0cea73b4 aad97ec8 34323288 ac000000' '00' ).replace(' ',''))) expectedMultiTxInput1 = hex_to_binary( ( '47304402 20796307 d9787b89 2c8b1ada 8511d99e 855ea309 9e1a76ce 0f7aa783' 'ed352a6e 59022003 c72fa282 041ae1d7 3c927ab2 2f233581 d8d2a86e e32c77e3' '9939563b 64f72f01 4104630a af9d5c8d 757cb575 9428d407 5911a2b2 ff13dd72' '08ad7ea1 d1682738 a7138be9 3ee526c9 d774e0de a03fa2a5 fbb68043 259ddfb9' '42c0763f 9b636b40 c43f').replace(' ','')) expectedMultiTxInput2 = hex_to_binary( ( '48304502 2100cb42 3b63197e f3cdbfae d69f61aa c59755f0 025bd6d7 a9d3c780' '24d897eb cf940220 0c52eb7f b5c37fbd c7813564 6fac5415 1c9c77cc 35ebf1bc' '6b6755ab 0fa9dcdd 01410464 9694df12 dcd7fdb5 a8c54c37 6b904bd7 337891d8' '65b8d306 beb5d2e5 d8fdf2a5 37d6f9df 65ff44eb 0b6042eb fdf9e338 bff7f4af' 'acb359dd 6c71aea7 b9b92d ').replace(' ','')) txInput0 = hex_to_binary( ( '47304402 204f2fa4 58d439f9 57308bca 264689aa 175e3b7c 5f78a901 cb450ebd' '20936b2c 50022071 5c77c5a4 7fed71aa 3639f8f5 59d9b09c a1f91523 cbc8536e' 'c9904fb7 7effa701 41044202 550a5a6d 3bb81549 c4a7803b 1ad59cdb ba477043' '9a492362 4a8acfc7 d34900be b54a2418 8f7f0a40 689d905d 4847cc7d 6c8d808a' '457d833c 2d44ef83 f76b').replace(' ','')) multiSigTx2of3Input0 = hex_to_binary( ( '00483045 02210090 9e021f8d 94820477 3a1ee953 459f96b4 22477e0f 11bab54a' '4bb8d1fa dea80d02 202d1b79 dcbc8e3a 2b363cc9 71aef7ca cb423bef 200eebcb' 'b680fce6 c475f917 58014730 44022032 6f53d77c 049b7627 fd5225cf 0542f16e' '5d849971 4b682aa1 1e9ee389 605f3102 2007b9bf ac66886e fdcaeef1 75812164' '6c0d97fb f7f56395 38e006ae e09e3c47 1101').replace(' ','')) multiSigTx2of3Input1 = hex_to_binary( ( '00473044 022055c4 9184845c 1d92c81a d8f0085b 808e00fc 586c8c83 32617721' '3a5778a3 5d230220 0d2bd241 fd8f8c77 db0b1251 7d4edbea ed47dd21 d7ffd467' '294992fe 33fb1c42 01473044 02201ff2 0ace4183 1bb7902f 0ca5ecd6 cb3f681f' '2347d89c d3ba2e5c ce1e2e9c c4f30220 4dfab132 67729f02 90a1b22e 39ce951b' '91c3102b 8299dc6b b74aed7d e583045a 014cc952 4104390a d036732b 60991854' 'dfd75f2a 69f9c66f 0505d031 dd7883be 1d411dea 29a97c1c b3c17234 4deea110' '50e21d4d d5647241 def6cdfb 30db27aa d5f63817 b7ac4104 66f9270b 584c3e04' '18277b8b d6046b60 9d77eac3 8b6be438 4e589f33 35197688 4b8944b0 3d0f6f6b' 'cd08aba6 124cae1a f134514e 0e958064 ae9eaef8 31055d64 4104cfaa 154390a4' 'fa244fd0 64ec8e61 ac0c3e9c cf94a4a7 f4d89ac9 46b70050 8082f5a6 3b2f25fd' 'fc3621c9 4bead1c3 782793c5 3f0734cc 1808ed3b 795ce94a 404c53ae').replace(' ','')) multiSigTx7of7Input0 = hex_to_binary( ( '00473044 02201a85 dde4134c f8491241 f5c33821 6a0c2771 1b519ef3 122429d7' 'e0016b21 4e960220 711ae401 457d3aa9 e6fa684f e5238cee 54ff7b38 c754a722' '2ab32b1d 5a6710d7 01483045 022100ca fad36ad8 79cd5c7e 3b3a5864 03e6f30d' '8bfb8b3c 60c42c3b c3ee1ec1 41639f02 2074e0b8 2df54cf3 dc966351 4ccbc743' '52cda16c f6e9181f 5c9bcbae 4b589d88 36014830 45022100 bbb047a8 6c75b089' 'df24b650 1e466db7 7a83cdcd e6a6c29a 7bf7349d 6a986ffd 02200806 86406105' '0c05e797 e5f46b1a 3e0a28bb 65b86617 af2ea010 b58a1e46 63a20147 30440220' '5da1823d e450841b 96f44d15 48ec6165 49dbecd1 defad45e ea767b88 6665291a' '02201e4a 4b5139e3 34200c3f 171ab22c 4fac6e16 9011c17e cc473750 4c1d3bdb' 'b09f0147 30440220 32a970ec 0d3fd10a e6e47aa3 388817e6 9c4a40e9 ef37d71c' '935106d1 bf5a5f96 02201124 237ce7c9 eef01f1c cb6f4c3f 8069b826 a97e999a' '5efa150d 2149fe67 fc9f0148 30450221 00d799e6 2819bba2 691461a8 a5e0bd55' '48df3f97 8091760b 437aec57 863ca5b5 9402202c 791d8949 93ee88f1 c3de2363' 'fa1c6200 005f2e41 85ed1a49 9a7cd174 1aeb8d01 48304502 21008f59 02bd3487' '1bc920ad e293e08f b57bbdbb bd2127d5 14551866 b14befef ff620220 35eafa7e' '653bffaf e681af7d b1cb86c0 4096f17f ac2edbce e654e4b5 7b86e86d 01').replace(' ','')) multiSigTx7of7Input1 = hex_to_binary( ( '00483045 022100f9 c1bea188 7991f50e 78c7c67d 4ca5d6db 69254b94 089ec3dc' '848e682d 1eb79502 200e564d bf74024d e2a89439 726d8efe 522dfc01 587b749c' '34a8c22e 98943e81 29014830 45022100 ebdd6a9a 45ac4be7 0f982a53 c79b9903' '68635f0a 9dcb29ec 46845686 712e9459 02203c77 968795bb 8c360a5c 616c9695' '26a56846 17c44635 b85c458a 76155ca7 528b0148 30450221 00eec14d 4d6cb1da' '92e43c93 a3a088a1 7799696f f7aa64b7 6e06207b b400b0db a0022068 df74f129' '42681229 f5a99c34 f6cbf7bc df10e8ff 3da0432a ead01fc6 523cda01 48304502' '2100e7f4 c88fd69b 7a00255b 3e6d48bf 2d6249c0 8669fbc5 cfdd395e 76b0e5c1' 'cfb10220 27665a72 a75d1762 7c14589e d6d9f3c7 9b3c1f62 e5ab35cc 18e957b4' 'fcaa0e43 01483045 022100c6 73b28b2c 6f5be2dd c04395e3 aaf3d7ba f148e679' '8629603c 5dfd7e01 f5b27d02 203db74e ebd0ebd2 dfb30912 316d0f0c 39e54431' '0c2948b8 f1534f9b d31ae4fb de014830 45022100 e484209f e5298481 3d6b3c74' 'ace64bc7 caaedc5e eccc4fb3 6026c6af 0851b50e 02207a26 d23168b7 31b8d3e8' 'ac351e17 370eeb33 69c1f684 6200fee0 5786fdb1 bfe50147 30440220 3636c311' 'c249013f f55d1987 3c70d003 eae19ae1 03bc60b6 44173865 2d882c9a 022069a9' 'c2a30200 d9c62116 ba6e5cb0 3a6772fc 01687225 dd87127a 87776de6 a2ef014d' 'd1015741 0434fba0 192f2030 5e3d4c62 0efea962 6d0f9a90 9d2890dc 4101e945' '89ea4e68 22b67efc eed5fbab c1d994db 8abf9a86 fcc44606 ab76b6a5 d38a9930' '0072208d 7e410446 cb30b98f 7d162fa6 5f8b34f7 6ebb0e46 4903b64d 93eac48a' '021db98d 80a1416e 848af76e 0a2c79dd 2fda9616 2314db83 7863d8d8 1a956949' '26cd8e58 2ccb8d41 0449ff69 21e263ec 2880c9fa 1620f42a 0c2cebf3 bfb78c51' 'bb462c50 852f0cd3 ab31470a f0dc234a c9167da2 d962a25e fde71bb2 0ef53d6d' '446c053f b8458399 d1410450 abee229f 06ca4ed9 cbff65e5 4cfdb562 6c4a707e' 'aa5d40cb a181e56d 59ef36d3 638c7704 8cb0fbcd 3bf0cf78 39e668df 5401d89a' 'f9075710 9da190c8 f67eec41 0452f588 273dda31 649aab7b f825c2e2 706962c2' '0c17e738 7b3698de 06f7af09 c8d18a76 1162d510 915a8097 e29dcd5f f3d4de9d' 'cac226da f2e3c61b 81b064be 82410461 9c4390ca 53825a15 a07ebf6d e2979bc9' 'c42c4de0 f57f3e83 cd7b5007 6a413799 6403ec86 2fd5c1d4 13b63683 36c6a2b6' 'c88bcb61 beb1009e 3a691572 c2799841 04bbee46 8827e700 4a9c535d c699e33e' 'cf01a521 471738fa 2a25c432 58d13be5 f0654189 ca5c1a56 880791a6 1039fb65' 'de1d9056 836a0a7f 139369b2 46a42b94 ed57ae ').replace(' ','')) ALL_ZERO_OUTPOINT = hex_to_binary('00' * 36) class PyTXTest(TiabTest): def testSerializeUnserialize(self): tx1 = PyTx().unserialize(tx1raw) tx2 = PyTx().unserialize(BinaryUnpacker(tx2raw)) tx1again = tx1.serialize() tx2again = tx2.serialize() self.assertEqual(tx1again, tx1raw) self.assertEqual(tx2again, tx2raw) blk = PyBlock().unserialize( hex_to_binary(hexBlock) ) blockReHex = binary_to_hex(blk.serialize()) self.assertEqual(hexBlock, blockReHex) binRoot = blk.blockData.getMerkleRoot() self.assertEqual(blk.blockHeader.merkleRoot, blk.blockData.merkleRoot) def testCreateTx(self): addrA = PyBtcAddress().createFromPrivateKey(hex_to_int('aa' * 32)) addrB = PyBtcAddress().createFromPrivateKey(hex_to_int('bb' * 32)) # This TxIn will be completely ignored, so it can contain garbage txinA = PyTxIn() txinA.outpoint = PyOutPoint().unserialize(hex_to_binary('00'*36)) txinA.binScript = hex_to_binary('99'*4) txinA.intSeq = hex_to_int('ff'*4) # test binary unpacker in unserialize testTxIn = PyTxIn().unserialize(txinA.serialize()) self.assertEqual(txinA.getScript(), testTxIn.getScript()) self.assertEqual(txinA.intSeq, testTxIn.intSeq) self.assertEqual(txinA.outpoint.txHash, testTxIn.outpoint.txHash) txoutA = PyTxOut() txoutA.value = 50 * ONE_BTC txoutA.binScript = '\x76\xa9\x14' + addrA.getAddr160() + '\x88\xac' # Test pprint print '\nTest pretty print PyTxIn, expect PrevTXHash all 0s' testTxIn.pprint() # test binary unpacker in unserialize testTxOut = PyTxOut().unserialize(txoutA.serialize()) self.assertEqual(txoutA.getScript(), testTxOut.getScript()) self.assertEqual(txoutA.value, testTxOut.getValue()) # Test pprint print '\nTest pretty print PyTxOut' testTxOut.pprint() tx1 = PyTx() tx1.version = 1 tx1.numInputs = 1 tx1.inputs = [txinA] tx1.numOutputs = 1 tx1.outputs = [txoutA] tx1.locktime = 0 tx1hash = tx1.getHash() recipientList = tx1.makeRecipientsList() self.assertEqual(len(recipientList), 1) self.assertEqual(recipientList[0][0], 0) self.assertEqual(recipientList[0][1], 50 * ONE_BTC) self.assertEqual(tx1.getHashHex(), binary_to_hex(tx1hash)) # Creating transaction to send coins from A to B tx2 = PyCreateAndSignTx_old( [[ addrA, tx1, 0 ]], [[addrB, 50*ONE_BTC]]) psp = PyScriptProcessor() psp.setTxObjects(tx1, tx2, 0) self.assertTrue(psp.verifyTransactionValid()) def testVerifyTxFromFakeBlockChain(self): psp = PyScriptProcessor() psp.setTxObjects(tx1Fake, tx2Fake, 0) self.assertTrue(psp.verifyTransactionValid()) def test2of2MultiSigTx(self): tx1 = PyTx().unserialize(hex_to_binary('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')) tx2 = PyTx().unserialize(hex_to_binary('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')) # Verify 2-of-2 tx from Testnet psp = PyScriptProcessor() psp.setTxObjects(tx1, tx2, 0) self.assertTrue(psp.verifyTransactionValid()) def test2of3MultiSigTx(self): tx1 = PyTx().unserialize(hex_to_binary('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')) tx2 = PyTx().unserialize(hex_to_binary('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')) # Verify 2-of-3 tx from Testnet psp = PyScriptProcessor() psp.setTxObjects(tx1, tx2, 0) self.assertTrue(psp.verifyTransactionValid()) def testMultiSig(self): tx1 = PyTx().unserialize(hex_to_binary('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')) tx2 = PyTx().unserialize(hex_to_binary('0100000001bb664ff716b9dfc831bcc666c1767f362ad467fcfbaf4961de92e45547daab8701000000fd190100493046022100d73f633f114e0e0b324d87d38d34f22966a03b072803afa99c9408201f6d6dc6022100900e85be52ad2278d24e7edbb7269367f5f2d6f1bd338d017ca460008776614401473044022071fef8ac0aa6318817dbd242bf51fb5b75be312aa31ecb44a0afe7b49fcf840302204c223179a383bb6fcb80312ac66e473345065f7d9136f9662d867acf96c12a42015241048c006ff0d2cfde86455086af5a25b88c2b81858aab67f6a3132c885a2cb9ec38e700576fd46c7d72d7d22555eee3a14e2876c643cd70b1b0a77fbf46e62331ac4104b68ef7d8f24d45e1771101e269c0aacf8d3ed7ebe12b65521712bba768ef53e1e84fff3afbee360acea0d1f461c013557f71d426ac17a293c5eebf06e468253e00ffffffff0280969800000000001976a9140817482d2e97e4be877efe59f4bae108564549f188ac7015a7000000000062537a7652a269537a829178a91480677c5392220db736455533477d0bc2fba65502879b69537a829178a91402d7aa2e76d9066fb2b3c41ff8839a5c81bdca19879b69537a829178a91410039ce4fdb5d4ee56148fe3935b9bfbbe4ecc89879b6953ae00000000')) # OP_CHECKMULTISIG from Testnet psp = PyScriptProcessor() psp.setTxObjects(tx1, tx2, 0) self.assertTrue(psp.verifyTransactionValid()) ''' def testMultiSigAddrExtraction(self): script1 = hex_to_binary('4104b54b5fc1917945fff64785d4baaca66a9704e9ed26002f51f53763499643321fbc047683a62be16e114e25404ce6ffdcf625a928002403402bf9f01e5cbd5f3dad4104f576e534f9bbf6d7c5f186ff4c6e0c5442c2755314bdee62fbc656f94d6cbf32c5eb3522da21cf9f954133000ffccb20dbfec030737640cc3315ce09619210d0ac') expectedBtcAddrList1 = ['1KmV9FdKJEFFCHydZUZGdBL9uKq2T9JUm8','13maaQeK5qSPjHwnHhwNUtNKruK3qYLwvv'] self.verifyMultiSigAddrExtraction(script1, expectedBtcAddrList1) script2 = hex_to_binary('537a7652a269537a829178a91480677c5392220db736455533477d0bc2fba65502879b69537a829178a91402d7aa2e76d9066fb2b3c41ff8839a5c81bdca19879b69537a829178a91410039ce4fdb5d4ee56148fe3935b9bfbbe4ecc89879b6953ae') expectedBtcAddrList2 = ['1ChwTs5Dmh6y9iDh4pjWyu2X6nAhjre7SV','1G2i31fxRqaoXBfYMuE4YKb9x96uYcHeQ','12Tg96ZPSYc3P2g5c9c4znFFH2whriN9NQ'] self.verifyMultiSigAddrExtraction(script2, expectedBtcAddrList2) script3 = hex_to_binary('527a7651a269527a829178a914731cdb75c88a01cbb96729888f726b3b9f29277a879b69527a829178a914e9b4261c6122f8957683636548923acc069e8141879b6952ae') expectedBtcAddrList3 = ['1BVfH6iKT1s8fYEVSj39QkJrPqCKN4hv2m','1NJiFfFPZ177Pv96Yt4FCNZFEumyL2eKmt'] self.verifyMultiSigAddrExtraction(script3, expectedBtcAddrList3) ''' def verifyMultiSigAddrExtraction(self, scr, expectedBtcAddrList): addrList = getMultisigScriptInfo(scr)[2] btcAddrList = [] for a in addrList: btcAddrList.append(PyBtcAddress().createFromPublicKeyHash160(a).getAddrStr()) self.assertEqual(btcAddrList, expectedBtcAddrList) def testUnpackUnserializePyOutPoint(self): outpoint = PyOutPoint().unserialize(BinaryUnpacker(ALL_ZERO_OUTPOINT)) self.assertEqual(outpoint.txHash, hex_to_binary('00'*32)) self.assertEqual(outpoint.txOutIndex, 0) def testCopyPyOutPoint(self): outpoint = PyOutPoint().unserialize(BinaryUnpacker(ALL_ZERO_OUTPOINT)) outpointCopy = outpoint.copy() self.assertEqual(outpoint.txHash, outpointCopy.txHash) self.assertEqual(outpoint.txOutIndex, outpointCopy.txOutIndex) def testPPrintPyOutPoint(self): # No return value - Should just print 0s outpoint = PyOutPoint().unserialize(BinaryUnpacker(ALL_ZERO_OUTPOINT)) print "PyOutPoint PPrint Test. Expect all 0s: " outpoint.pprint() ''' Does not pass because fromCpp is missing def testCreateCppFromCppPyOutPoint(self): outpoint = PyOutPoint().unserialize(BinaryUnpacker(ALL_ZERO_OUTPOINT)) outpointFromCpp = PyOutPoint().fromCpp(outpoint.createCpp()) self.assertEqual(outpoint.txHash, outpointFromCpp.txHash) self.assertEqual(outpoint.txOutIndex, outpointFromCpp.txOutIndex) ''' def testBogusBlockComponent(self): class TestBlockComponent(BlockComponent): pass testBlkComp = TestBlockComponent() self.assertRaises(NotImplementedError, testBlkComp.serialize) self.assertRaises(NotImplementedError, testBlkComp.unserialize) # TODO: Add some tests for the OP_CHECKMULTISIG support in TxDP # Running tests with "python <module name>" will NOT work for any Armory tests # You must run tests with "python -m unittest <module name>" or run all tests with "python -m unittest discover" # if __name__ == "__main__": # unittest.main()

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1

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7

b0c73abe7d6c4c20a371f847f449694a60b9f43c

137

py

Python

Lesson17_FunctionArguments/record_library.py

StyvenSoft/degree-python

644953608948f341f5a20ceb9a02976a128b472b

[ "MIT" ]

null

Lesson17_FunctionArguments/record_library.py

StyvenSoft/degree-python

644953608948f341f5a20ceb9a02976a128b472b

[ "MIT" ]

null

Lesson17_FunctionArguments/record_library.py

StyvenSoft/degree-python

644953608948f341f5a20ceb9a02976a128b472b

[ "MIT" ]

null

def place_record(album): return def rotate_record(album): return def drop_needle(album): print("Playing album {}".format(album))

15.222222

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7

b0ccc33c2e84e0017efc6e320749123bbc92dc31

13,441

py

Python

networks/network_dynamics.py

enflujo/COVID_schools_dashboard

702c9c3c91938e514e56f4cf6f325ed954d7bc3e

[ "Apache-2.0" ]

null

networks/network_dynamics.py

enflujo/COVID_schools_dashboard

702c9c3c91938e514e56f4cf6f325ed954d7bc3e

[ "Apache-2.0" ]

null

networks/network_dynamics.py

enflujo/COVID_schools_dashboard

702c9c3c91938e514e56f4cf6f325ed954d7bc3e

[ "Apache-2.0" ]

null

import jax.numpy as np import numpy as np2 from jax import random # Intervention functions def morning_set_intervention(Graphs_matrix, intervention_eff, hh_occupation=0.9): # load networks matrix_household = Graphs_matrix[0] # matrix_household[2] = [val.values[0] for val in matrix_household[2]] hh_row = np.asarray(np2.asarray(matrix_household[0])) hh_col = np.asarray(np2.asarray(matrix_household[1])) hh_data = np.asarray(np2.asarray(matrix_household[2])) matrix_preschool = Graphs_matrix[1] # matrix_preschool[2] = [val.values[0] for val in matrix_preschool[2]] preschl_row = np.asarray(np2.asarray(matrix_preschool[0])) preschl_col = np.asarray(np2.asarray(matrix_preschool[1])) preschl_data = np.asarray(np2.asarray(matrix_preschool[2])) matrix_primary = Graphs_matrix[2] # matrix_primary[2] = [val.values[0] for val in matrix_primary[2]] primary_row = np.asarray(np2.asarray(matrix_primary[0])) primary_col = np.asarray(np2.asarray(matrix_primary[1])) primary_data = np.asarray(np2.asarray(matrix_primary[2])) matrix_highschool = Graphs_matrix[3] # matrix_highschool[2] = [val.values[0] for val in matrix_highschool[2]] highschl_row = np.asarray(np2.asarray(matrix_highschool[0])) highschl_col = np.asarray(np2.asarray(matrix_highschool[1])) highschl_data = np.asarray(np2.asarray(matrix_highschool[2])) matrix_work = Graphs_matrix[4] # matrix_work[2] = [val.values[0] for val in matrix_work[2]] work_row = np.asarray(np2.asarray(matrix_work[0])) work_col = np.asarray(np2.asarray(matrix_work[1])) work_data = np.asarray(np2.asarray(matrix_work[2])) matrix_community = Graphs_matrix[5] # matrix_community[2] = [val.values[0] for val in matrix_community[2]] comm_row = np.asarray(np2.asarray(matrix_community[0])) comm_col = np.asarray(np2.asarray(matrix_community[1])) comm_data = np.asarray(np2.asarray(matrix_community[2])) # turn off school and work layers preschl_data_set = 0 * preschl_data primary_data_set = 0 * primary_data highschl_data_set = 0 * highschl_data work_data_set = 0 * work_data # turn on portions of households and community hh_occupation_intervention = hh_occupation * (1 - intervention_eff) comm_occupation = 1 - hh_occupation comm_occupation_intervention = comm_occupation * (1 - intervention_eff) length = int(hh_data.shape[0] / 2) hh_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(hh_occupation_intervention), shape=(length,)), 2) hh_data_set = hh_data_select.reshape(hh_data_select.shape[0], 1) * hh_data length = int(comm_data.shape[0] / 2) comm_data_select = np.repeat( random.bernoulli(random.PRNGKey(0), p=(comm_occupation_intervention), shape=(length,)), 2 ) comm_data_set = comm_data_select.reshape(comm_data_select.shape[0], 1) * comm_data # create conections args_ps = (hh_data_set, preschl_data_set, primary_data_set, highschl_data_set, work_data_set, comm_data_set) ps = np.concatenate(args_ps) ps = ps.reshape( ps.shape[0], ) args_rows = (hh_row, preschl_row, primary_row, highschl_row, work_row, comm_row) rows = np.concatenate(args_rows) args_cols = (hh_col, preschl_col, primary_col, highschl_col, work_col, comm_col) cols = np.concatenate(args_cols) w = [rows.astype(np.int32), cols.astype(np.int32), ps] return w def day_set_intervention( Graphs_matrix, intervention_eff, schl_occupation, work_occupation, schl_altern=False, hh_occupation=0.3 ): # load networks matrix_household = Graphs_matrix[0] # matrix_household[2] = [val.values[0] for val in matrix_household[2]] hh_row = np.asarray(np2.asarray(matrix_household[0])) hh_col = np.asarray(np2.asarray(matrix_household[1])) hh_data = np.asarray(np2.asarray(matrix_household[2])) matrix_preschool = Graphs_matrix[1] # matrix_preschool[2] = [val.values[0] for val in matrix_preschool[2]] preschl_row = np.asarray(np2.asarray(matrix_preschool[0])) preschl_col = np.asarray(np2.asarray(matrix_preschool[1])) preschl_data = np.asarray(np2.asarray(matrix_preschool[2])) matrix_primary = Graphs_matrix[2] # matrix_primary[2] = [val.values[0] for val in matrix_primary[2]] primary_row = np.asarray(np2.asarray(matrix_primary[0])) primary_col = np.asarray(np2.asarray(matrix_primary[1])) primary_data = np.asarray(np2.asarray(matrix_primary[2])) matrix_highschool = Graphs_matrix[3] # matrix_highschool[2] = [val.values[0] for val in matrix_highschool[2]] highschl_row = np.asarray(np2.asarray(matrix_highschool[0])) highschl_col = np.asarray(np2.asarray(matrix_highschool[1])) highschl_data = np.asarray(np2.asarray(matrix_highschool[2])) matrix_work = Graphs_matrix[4] # matrix_work[2] = [val.values[0] for val in matrix_work[2]] work_row = np.asarray(np2.asarray(matrix_work[0])) work_col = np.asarray(np2.asarray(matrix_work[1])) work_data = np.asarray(np2.asarray(matrix_work[2])) matrix_community = Graphs_matrix[5] # matrix_community[2] = [val.values[0] for val in matrix_community[2]] comm_row = np.asarray(np2.asarray(matrix_community[0])) comm_col = np.asarray(np2.asarray(matrix_community[1])) comm_data = np.asarray(np2.asarray(matrix_community[2])) # turn off portions of households and community hh_occupation_intervention = hh_occupation * (1 - intervention_eff) comm_occupation = 1 - hh_occupation comm_occupation_intervention = comm_occupation * (1 - intervention_eff) length = int(hh_data.shape[0] / 2) hh_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(hh_occupation_intervention), shape=(length,)), 2) hh_data_set = hh_data_select.reshape(hh_data_select.shape[0], 1) * hh_data length = int(comm_data.shape[0] / 2) comm_data_select = np.repeat( random.bernoulli(random.PRNGKey(0), p=(comm_occupation_intervention), shape=(length,)), 2 ) comm_data_set = comm_data_select.reshape(comm_data_select.shape[0], 1) * comm_data # turn off portions of school and work layers if schl_occupation == 0: preschl_data_set = 0 * preschl_data primary_data_set = 0 * primary_data highschl_data_set = 0 * highschl_data elif schl_occupation == 1.0: preschl_data_set = preschl_data primary_data_set = primary_data highschl_data_set = highschl_data else: length = int(preschl_data.shape[0] / 2) preschl_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(schl_occupation), shape=(length,)), 2) preschl_data_set = preschl_data_select.reshape(preschl_data_select.shape[0], 1) * preschl_data length = int(primary_data.shape[0] / 2) primary_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(schl_occupation), shape=(length,)), 2) primary_data_set = primary_data_select.reshape(primary_data_select.shape[0], 1) * primary_data length = int(highschl_data.shape[0] / 2) highschl_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(schl_occupation), shape=(length,)), 2) highschl_data_set = highschl_data_select.reshape(highschl_data_select.shape[0], 1) * highschl_data # work_occuption_intervention = 1-intervention_eff length = int(work_data.shape[0] / 2) work_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(work_occupation), shape=(length,)), 2) work_data_set = work_data_select.reshape(work_data_select.shape[0], 1) * work_data if work_occupation == 0: work_data_set = 0 * work_data # if work offices are fully closed # create conections args_ps = (hh_data_set, preschl_data_set, primary_data_set, highschl_data_set, work_data_set, comm_data_set) ps = np.concatenate(args_ps) ps = ps.reshape( ps.shape[0], ) args_rows = (hh_row, preschl_row, primary_row, highschl_row, work_row, comm_row) rows = np.concatenate(args_rows) args_cols = (hh_col, preschl_col, primary_col, highschl_col, work_col, comm_col) cols = np.concatenate(args_cols) w = [rows.astype(np.int32), cols.astype(np.int32), ps] return w def night_set_intervention(Graphs_matrix, intervention_eff, hh_occupation=0.7): # load networks matrix_household = Graphs_matrix[0] # matrix_household[2] = [val.values[0] for val in matrix_household[2]] hh_row = np.asarray(np2.asarray(matrix_household[0])) hh_col = np.asarray(np2.asarray(matrix_household[1])) hh_data = np.asarray(np2.asarray(matrix_household[2])) matrix_preschool = Graphs_matrix[1] # matrix_preschool[2] = [val.values[0] for val in matrix_preschool[2]] preschl_row = np.asarray(np2.asarray(matrix_preschool[0])) preschl_col = np.asarray(np2.asarray(matrix_preschool[1])) preschl_data = np.asarray(np2.asarray(matrix_preschool[2])) matrix_primary = Graphs_matrix[2] # matrix_primary[2] = [val.values[0] for val in matrix_primary[2]] primary_row = np.asarray(np2.asarray(matrix_primary[0])) primary_col = np.asarray(np2.asarray(matrix_primary[1])) primary_data = np.asarray(np2.asarray(matrix_primary[2])) matrix_highschool = Graphs_matrix[3] # matrix_highschool[2] = [val.values[0] for val in matrix_highschool[2]] highschl_row = np.asarray(np2.asarray(matrix_highschool[0])) highschl_col = np.asarray(np2.asarray(matrix_highschool[1])) highschl_data = np.asarray(np2.asarray(matrix_highschool[2])) matrix_work = Graphs_matrix[4] # matrix_work[2] = [val.values[0] for val in matrix_work[2]] work_row = np.asarray(np2.asarray(matrix_work[0])) work_col = np.asarray(np2.asarray(matrix_work[1])) work_data = np.asarray(np2.asarray(matrix_work[2])) matrix_community = Graphs_matrix[5] # matrix_community[2] = [val.values[0] for val in matrix_community[2]] comm_row = np.asarray(np2.asarray(matrix_community[0])) comm_col = np.asarray(np2.asarray(matrix_community[1])) comm_data = np.asarray(np2.asarray(matrix_community[2])) # turn off school and work layers preschl_data_set = 0 * preschl_data primary_data_set = 0 * primary_data highschl_data_set = 0 * highschl_data work_data_set = 0 * work_data # turn on portions of households and community hh_occupation_intervention = hh_occupation * (1 - intervention_eff) comm_occupation = 1 - hh_occupation comm_occupation_intervention = comm_occupation * (1 - intervention_eff) length = int(hh_data.shape[0] / 2) hh_data_select = np.repeat(random.bernoulli(random.PRNGKey(0), p=(hh_occupation_intervention), shape=(length,)), 2) hh_data_set = hh_data_select.reshape(hh_data_select.shape[0], 1) * hh_data length = int(comm_data.shape[0] / 2) comm_data_select = np.repeat( random.bernoulli(random.PRNGKey(0), p=(comm_occupation_intervention), shape=(length,)), 2 ) comm_data_set = comm_data_select.reshape(comm_data_select.shape[0], 1) * comm_data # create conections args_ps = (hh_data_set, preschl_data_set, primary_data_set, highschl_data_set, work_data_set, comm_data_set) ps = np.concatenate(args_ps) ps = ps.reshape( ps.shape[0], ) args_rows = (hh_row, preschl_row, primary_row, highschl_row, work_row, comm_row) rows = np.concatenate(args_rows) args_cols = (hh_col, preschl_col, primary_col, highschl_col, work_col, comm_col) cols = np.concatenate(args_cols) w = [rows.astype(np.int32), cols.astype(np.int32), ps] return w def create_day_intervention_dynamics( Graphs_matrix, Tmax, total_steps, schools_day_open, interv_glob, schl_occupation, work_occupation ): """ A day is devided in 3 partitions with consists of sets of hours over a day partition[0] -> morning: only a % of households and community is activated partition[1] -> evening: only work and school layers are activated partition[2] -> night: only a % of households and community is activated delta_t -> steps over a day """ # Hours distribution in a day partitions = [8, 8, 8] steps_per_days = int(total_steps / Tmax) m_day = int(steps_per_days * (partitions[0] / 24)) e_day = int(steps_per_days * (partitions[1] / 24)) n_day = int(steps_per_days * (partitions[2] / 24)) days_intervals = [m_day, e_day, n_day] m_w_interv = morning_set_intervention(Graphs_matrix, interv_glob) e_w_interv_schl_close = day_set_intervention( Graphs_matrix, interv_glob, schl_occupation=0, work_occupation=work_occupation ) e_w_interv_schl_open = day_set_intervention( Graphs_matrix, interv_glob, schl_occupation=schl_occupation, work_occupation=work_occupation ) n_w_interv = night_set_intervention(Graphs_matrix, interv_glob) w_interv_intervals_schl_close = [m_w_interv, e_w_interv_schl_close, n_w_interv] w_interv_intervals_schl_open = [m_w_interv, e_w_interv_schl_open, n_w_interv] sim_intervals = [] # iterations per network set w sim_ws = [] # networks per iteration for d in range(Tmax): if d < schools_day_open: sim_intervals.extend(days_intervals) sim_ws.extend(w_interv_intervals_schl_close) else: sim_intervals.extend(days_intervals) sim_ws.extend(w_interv_intervals_schl_open) return sim_intervals, sim_ws

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null

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7

b0f1157d9b25ddd968a718280f245c843c89f5ba

14,026

py

Python

tests/grammar/factory/control/test_group.py

orenyodfat/CWR-DataApi

f3b6ba8308c901b6ab87073c155c08e30692333c

[ "MIT" ]

37

2015-04-21T15:33:53.000Z

2022-02-07T00:02:29.000Z

tests/grammar/factory/control/test_group.py

orenyodfat/CWR-DataApi

f3b6ba8308c901b6ab87073c155c08e30692333c

[ "MIT" ]

86

2015-02-01T22:26:02.000Z

2021-07-09T08:49:36.000Z

tests/grammar/factory/control/test_group.py

orenyodfat/CWR-DataApi

f3b6ba8308c901b6ab87073c155c08e30692333c

[ "MIT" ]

27

2015-01-26T16:01:09.000Z

2021-11-08T23:53:55.000Z

# -*- coding: utf-8 -*- import unittest from pyparsing import ParseException from tests.utils.grammar import get_record_grammar """ CWR Administrator Information grammar tests. The following cases are tested: """ __author__ = 'Bernardo Martínez Garrido' __license__ = 'MIT' __status__ = 'Development' class TestGroupInformationGrammar(unittest.TestCase): def setUp(self): self.grammar = self.grammar = get_record_grammar('group_info') def test_agreement_min(self): header = 'GRHAGR0000102.100130400001 ' trailer = 'GRT012340123456701234567 ' record = header + '\n' + _agreement_short() + '\n' + trailer result = self.grammar.parseString(record)[0] self.assertEqual('GRH', result.group_header.record_type) self.assertEqual('GRT', result.group_trailer.record_type) transaction = result.transactions[0] self.assertEqual('AGR', transaction[0].record_type) def test_agreement_short(self): header = 'GRHAGR0000102.100130400001 ' trailer = 'GRT012340123456701234567' record = header + '\n' + _agreement_short() + '\n' + trailer result = self.grammar.parseString(record)[0] self.assertEqual('GRH', result.group_header.record_type) self.assertEqual('GRT', result.group_trailer.record_type) transaction = result.transactions[0] self.assertEqual('AGR', transaction[0].record_type) def test_agreement_short_b(self): header = 'GRHAGR0123402.100123456789 ' trailer = 'GRT012340123456701234567' agreement_record_1 = _agreement_record_big() agreement_record_2 = _agreement_record_big() record = header + '\n' + agreement_record_1 + '\n' + agreement_record_2 + '\n' + trailer result = self.grammar.parseString(record)[0] self.assertEqual('GRH', result.group_header.record_type) self.assertEqual('GRT', result.group_trailer.record_type) transactions = result.transactions self.assertEqual(2, len(transactions)) transaction = transactions[0] self.assertEqual(21, len(transaction)) self.assertEqual('AGR', transaction[0].record_type) self.assertEqual('TER', transaction[1].record_type) self.assertEqual('TER', transaction[2].record_type) self.assertEqual('IPA', transaction[3].record_type) self.assertEqual('NPA', transaction[4].record_type) self.assertEqual('IPA', transaction[5].record_type) self.assertEqual('NPA', transaction[6].record_type) self.assertEqual('IPA', transaction[7].record_type) self.assertEqual('NPA', transaction[8].record_type) self.assertEqual('IPA', transaction[9].record_type) self.assertEqual('NPA', transaction[10].record_type) self.assertEqual('TER', transaction[11].record_type) self.assertEqual('TER', transaction[12].record_type) self.assertEqual('IPA', transaction[13].record_type) self.assertEqual('NPA', transaction[14].record_type) self.assertEqual('IPA', transaction[15].record_type) self.assertEqual('NPA', transaction[16].record_type) self.assertEqual('IPA', transaction[17].record_type) self.assertEqual('NPA', transaction[18].record_type) self.assertEqual('IPA', transaction[19].record_type) def test_agreement_small_pair(self): header = 'GRHAGR0000102.100130400001 ' trailer = 'GRT000010000017900000719 0000000000' record = header + '\n' + _agreement_short() + '\n' + _agreement_short() + '\n' + trailer result = self.grammar.parseString(record)[0] self.assertEqual('GRH', result.group_header.record_type) self.assertEqual('GRT', result.group_trailer.record_type) transaction = result.transactions[0] self.assertEqual('AGR', transaction[0].record_type) def test_agreement_full(self): header = 'GRHAGR0123402.100123456789 ' trailer = 'GRT012340123456701234567 ' agreement_record_1 = _agreement_record_big() agreement_record_2 = _agreement_record_big() record = header + '\n' + agreement_record_1 + '\n' + agreement_record_2 + '\n' + trailer result = self.grammar.parseString(record)[0] self.assertEqual('GRH', result.group_header.record_type) self.assertEqual('GRT', result.group_trailer.record_type) transactions = result.transactions self.assertEqual(2, len(transactions)) transaction = transactions[0] self.assertEqual(21, len(transaction)) self.assertEqual('AGR', transaction[0].record_type) self.assertEqual('TER', transaction[1].record_type) self.assertEqual('TER', transaction[2].record_type) self.assertEqual('IPA', transaction[3].record_type) self.assertEqual('NPA', transaction[4].record_type) self.assertEqual('IPA', transaction[5].record_type) self.assertEqual('NPA', transaction[6].record_type) self.assertEqual('IPA', transaction[7].record_type) self.assertEqual('NPA', transaction[8].record_type) self.assertEqual('IPA', transaction[9].record_type) self.assertEqual('NPA', transaction[10].record_type) self.assertEqual('TER', transaction[11].record_type) self.assertEqual('TER', transaction[12].record_type) self.assertEqual('IPA', transaction[13].record_type) self.assertEqual('NPA', transaction[14].record_type) self.assertEqual('IPA', transaction[15].record_type) self.assertEqual('NPA', transaction[16].record_type) self.assertEqual('IPA', transaction[17].record_type) self.assertEqual('NPA', transaction[18].record_type) self.assertEqual('IPA', transaction[19].record_type) self.assertEqual('NPA', transaction[20].record_type) class TestGroupInformationGrammarException(unittest.TestCase): def setUp(self): self.grammar = self.grammar = get_record_grammar('group_info') def test_empty(self): record = '' self.assertRaises(ParseException, self.grammar.parseString, record) def test_invalid(self): record = 'This is an invalid string' self.assertRaises(ParseException, self.grammar.parseString, record) def _work_big(): return 'NWR0000019900000000WORK NAME 1450455 00000000 UNC000000YMTX ORI ORIORI N00000000000U Y' + '\n' + \ 'SPU0000019900000702014271370 MUSIC SOCIETY E 005101734040102328568410061 0500061 1000061 10000 0000000000000 OS ' + '\n' + \ 'SPU00000199000007030166 ANOTHER SOCIETY AM 002501650060477617137010061 0000061 0000061 00000 0000000000000 PS ' + '\n' + \ 'SPU00000199000007040170 YET ANOTHER SOCIETY SE 002261445930035870006610059 00000 00000 00000 0000000000000 PG ' + '\n' + \ 'SPT000001990000070570 050000500005000I0484Y001' + '\n' + \ 'SWR00000199000007061185684 A NAME YET ANOTHER NAME C 0026058307861 0500061 0000061 00000 0000260582865 ' + '\n' + \ 'SWT00000199000007071185684 050000500005000I0484Y001' + '\n' + \ 'PWR00000199000007084271370 MUSIC SOCIETY 01023285684100 1185684 ' + '\n' + \ 'PER0000019900000709A NAME 000000000000000000000000' + '\n' + \ 'REC000001990000071019980101 000300 A COMPILATION P A I _AR_ 33002 U ' def _agreement_record_big(): agreement = 'AGR0000123400000023C1234567890123D1234567890123OG201201022013020320140304D20100405D201605062017060701234MYY0123456789012A' territory_1 = 'TER0000123400000023I0020' territory_2 = 'TER0000123400000023I0020' ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' assignor_1 = ipa + '\n' + npa ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' assignor_2 = ipa + '\n' + npa ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' acquirer_1 = ipa + '\n' + npa ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' acquirer_2 = ipa + '\n' + npa agr_territory_1 = territory_1 + '\n' + territory_2 + '\n' + assignor_1 + '\n' + assignor_2 + '\n' + acquirer_1 + '\n' + acquirer_2 territory_1 = 'TER0000123400000023I0020' territory_2 = 'TER0000123400000023I0020' ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' assignor_1 = ipa + '\n' + npa ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' assignor_2 = ipa + '\n' + npa ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' acquirer_1 = ipa + '\n' + npa ipa = 'IPA0000123400000023AC01234567890I-000000229-7A12345678LAST NAME FIRST NAME 009020500100300001102312' npa = 'NPA0000123400000023012345678PARTY NAME PARTY WRITER NAME ES' acquirer_2 = ipa + '\n' + npa agr_territory_2 = territory_1 + '\n' + territory_2 + '\n' + assignor_1 + '\n' + assignor_2 + '\n' + acquirer_1 + '\n' + acquirer_2 return agreement + '\n' + agr_territory_1 + '\n' + agr_territory_2 def _agreement_short(): agr_1 = 'AGR000000000000000000023683606100 OS200311182013111820131118N D20131118 00009SYY ' ter_1_1 = 'TER0000000000000000I2136' ipa_1_1 = 'IPA0000000000000001AS0026166137500000000000001183606 ITALIAN GILBERTI DUANTE 61 0500061 0000061 00000' ipa_1_2 = 'IPA0000000000000002AC00250165006000000000000066 SOCIETY MUSIC 61 0500061 1000061 10000' return agr_1 + '\n' + ter_1_1 + '\n' + ipa_1_1 + '\n' + ipa_1_2

51.189781

362

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1,047

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0.403821

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false

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7

9fe7a6103019700f5924a45bc7f5b5267ff68577

1,549

py

Python

stayhome/geodata/migrations/0009_auto_20200319_1439.py

pavax/stayhomech

e661e042f2976bf380dc71a42f99930ce009f724

[ "MIT" ]

3

2020-03-20T11:01:57.000Z

2020-03-20T16:29:12.000Z

stayhome/geodata/migrations/0009_auto_20200319_1439.py

pavax/stayhomech

e661e042f2976bf380dc71a42f99930ce009f724

[ "MIT" ]

74

2020-03-23T21:35:07.000Z

2020-04-27T12:55:50.000Z

stayhome/geodata/migrations/0009_auto_20200319_1439.py

pavax/stayhomech

e661e042f2976bf380dc71a42f99930ce009f724

[ "MIT" ]

3

2020-03-20T11:02:35.000Z

2020-03-20T16:29:23.000Z

# Generated by Django 3.0.4 on 2020-03-19 13:39 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('geodata', '0008_auto_20200315_1940'), ] operations = [ migrations.AddField( model_name='municipality', name='name_de', field=models.CharField(max_length=30, null=True), ), migrations.AddField( model_name='municipality', name='name_en', field=models.CharField(max_length=30, null=True), ), migrations.AddField( model_name='municipality', name='name_fr', field=models.CharField(max_length=30, null=True), ), migrations.AddField( model_name='municipality', name='name_it', field=models.CharField(max_length=30, null=True), ), migrations.AddField( model_name='npa', name='name_de', field=models.CharField(max_length=27, null=True), ), migrations.AddField( model_name='npa', name='name_en', field=models.CharField(max_length=27, null=True), ), migrations.AddField( model_name='npa', name='name_fr', field=models.CharField(max_length=27, null=True), ), migrations.AddField( model_name='npa', name='name_it', field=models.CharField(max_length=27, null=True), ), ]

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0.545513

157

1,549

5.210191

0.273885

0.176039

0.224939

0.264059

0.816626

0.768949

0.691932

0.678484

0

0.045587

0.334409

1,549

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0.747818

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1

0

1

0

null

0

9

b00857fe1f229782497c52b5af1cef1a9c427432

13,256

py

Python

findfile/find.py

yangheng95/findfile

38d2e0c0ec4234bc1664b84cb2532b4f920bd46c

[ "MIT" ]

4

2021-11-12T09:41:42.000Z

2022-03-23T03:32:51.000Z

findfile/find.py

yangheng95/findfile

38d2e0c0ec4234bc1664b84cb2532b4f920bd46c

[ "MIT" ]

null

findfile/find.py

yangheng95/findfile

38d2e0c0ec4234bc1664b84cb2532b4f920bd46c

[ "MIT" ]

null

# -*- coding: utf-8 -*- # file: find.py # time: 2021/8/4 # author: yangheng <yangheng@m.scnu.edu.cn> # github: https://github.com/yangheng95 # Copyright (C) 2021. All Rights Reserved. import os import re from functools import reduce def accessible(search_path): try: os.listdir(search_path) except OSError: return False return True def covert_path_sep(key_list): new_key_list = [] for key in key_list: new_key_list.append(key.replace('/', os.sep)) return new_key_list def find_files(search_path: str, key='', exclude_key=None, use_regex=False, recursive=True, return_relative_path=True) -> list: ''' 'search_path': path to search 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path :return the files whose path contains the key(s) ''' if not use_regex: key = covert_path_sep(key) if not search_path: search_path = os.getcwd() res = [] if not exclude_key: exclude_key = [] if isinstance(exclude_key, str): exclude_key = [exclude_key] if isinstance(key, str): key = [key] if os.path.isfile(search_path): has_key = True for k in key: try: if use_regex: if not re.findall(k.lower(), search_path.lower()): has_key = False break else: if not k.lower() in search_path.lower(): has_key = False break except re.error: print('Regex pattern error, using string-based search') if not k.lower() in search_path.lower(): has_key = False break if has_key: if exclude_key: has_exclude_key = False for ex_key in exclude_key: try: if use_regex: if re.findall(ex_key.lower(), search_path.lower()): has_exclude_key = True break else: if ex_key.lower() in search_path.lower(): has_exclude_key = True break except re.error: print('Regex pattern error, using string-based search') if ex_key.lower() in search_path.lower(): has_exclude_key = True break if not has_exclude_key: res.append(search_path.replace(os.getcwd() + os.sep, '') if return_relative_path else search_path) else: res.append(search_path.replace(os.getcwd() + os.sep, '') if return_relative_path else search_path) if os.path.isdir(search_path) and accessible(search_path): items = os.listdir(search_path) for file in items: if recursive: res += find_files(os.path.join(search_path, file), key, exclude_key, use_regex=use_regex, recursive=recursive) return res def find_file(search_path: str, key='', exclude_key=None, use_regex=False, recursive=True, return_relative_path=True, return_deepest_path=False, disable_alert=False) -> str: ''' 'search_path': path to search 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path 'return_deepest_path' True/False to return the deepest/shortest path if multiple targets found 'disable_alert' no alert if multiple targets found :return the file whose path contains the key(s) ''' res = find_files(search_path=search_path, key=key, exclude_key=exclude_key, use_regex=use_regex, recursive=recursive, return_relative_path=return_relative_path) if len(res) > 1 and not disable_alert: print('FindFile Warning: multiple targets {} found but return the {} path'.format(res, 'deepest' if return_deepest_path else 'shortest')) if not return_deepest_path: return reduce(lambda x, y: x if len(x) < len(y) else y, res) if res else None else: return reduce(lambda x, y: x if len(x) > len(y) else y, res) if res else None def find_dirs(search_path: str, key='', exclude_key=None, use_regex=False, recursive=True, return_relative_path=True) -> list: ''' 'search_path': path to search 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path :return the dirs whose path contains the key(s) ''' if not use_regex: key = covert_path_sep(key) if not search_path: search_path = os.getcwd() res = [] if not exclude_key: exclude_key = [] if isinstance(exclude_key, str): exclude_key = [exclude_key] if isinstance(key, str): key = [key] if os.path.isdir(search_path): has_key = True for k in key: try: if use_regex: if not re.findall(k.lower(), search_path.lower()): has_key = False break else: if not k.lower() in search_path.lower(): has_key = False break except re.error: print('Regex pattern error, using string-based search') if not k.lower() in search_path.lower(): has_key = False break if has_key: if exclude_key: has_exclude_key = False for ex_key in exclude_key: try: if use_regex: if re.findall(ex_key.lower(), search_path.lower()): has_exclude_key = True break else: if ex_key.lower() in search_path.lower(): has_exclude_key = True break except re.error: print('Regex pattern error, using string-based search') if ex_key.lower() in search_path.lower(): has_exclude_key = True break if not has_exclude_key: res.append(search_path.replace(os.getcwd() + os.sep, '') if return_relative_path else search_path) else: res.append(search_path.replace(os.getcwd() + os.sep, '') if return_relative_path else search_path) if os.path.isdir(search_path) and accessible(search_path): items = os.listdir(search_path) for file in items: if recursive: res += find_dirs(os.path.join(search_path, file), key, exclude_key, use_regex, recursive) return res def find_dir(search_path: str, key='', exclude_key=None, use_regex=False, recursive=True, return_relative_path=True, return_deepest_path=False, disable_alert=False) -> str: ''' 'search_path': path to search 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path 'return_deepest_path' True/False to return the deepest/shortest path if multiple targets found 'disable_alert' no alert if multiple targets found :return the dir path ''' res = find_dirs(search_path=search_path, key=key, exclude_key=exclude_key, use_regex=use_regex, recursive=recursive, return_relative_path=return_relative_path) if len(res) > 1 and not disable_alert: print('FindFile Warning: multiple targets {} found but return the {} path'.format(res, 'deepest' if return_deepest_path else 'shortest')) if not return_deepest_path: return reduce(lambda x, y: x if len(x) < len(y) else y, res) if res else None else: return reduce(lambda x, y: x if len(x) > len(y) else y, res) if res else None def find_cwd_file(key='', use_regex=False, exclude_key=None, recursive=True, return_relative_path=True, return_deepest_path=False, disable_alert=False): ''' 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path 'return_deepest_path' True/False to return the deepest/shortest path if multiple targets found 'disable_alert' no alert if multiple targets found :return the target file path in current working directory ''' return find_file(search_path=os.getcwd(), key=key, use_regex=use_regex, exclude_key=exclude_key, recursive=recursive, return_relative_path=return_relative_path, return_deepest_path=return_deepest_path, disable_alert=disable_alert) def find_cwd_files(key='', use_regex=False, exclude_key=None, recursive=True, return_relative_path=True): ''' 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path :return the target files' path in current working directory ''' return find_files(search_path=os.getcwd(), key=key, exclude_key=exclude_key, use_regex=use_regex, recursive=recursive, return_relative_path=return_relative_path) def find_cwd_dir(key='', use_regex=False, exclude_key=None, recursive=True, return_relative_path=True, return_deepest_path=False, disable_alert=False): ''' 'key': find a set of files/dirs whose absolute path contain the 'key', 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path 'return_deepest_path' True/False to return the deepest/shortest path if multiple targets found 'disable_alert' no alert if multiple targets found :return the target dir path in current working directory ''' return find_dir(search_path=os.getcwd(), key=key, use_regex=use_regex, exclude_key=exclude_key, recursive=recursive, return_relative_path=return_relative_path, return_deepest_path=return_deepest_path, disable_alert=disable_alert) def find_cwd_dirs(key='', exclude_key=None, use_regex=False, recursive=True, return_relative_path=True): ''' 'key': find a set of files/dirs whose absolute path contain the 'key' 'exclude_key': file whose absolute path contains 'exclude_key' will be ignored 'recursive' recursive search in dir_path 'return_relative_path' return the relative path instead of absolute path :return the target dirs' path in current working directory ''' return find_dirs(search_path=os.getcwd(), key=key, exclude_key=exclude_key, use_regex=use_regex, recursive=recursive, return_relative_path=return_relative_path)

37.659091

145

0.570081

1,585

13,256

4.564038

0.075079

0.085706

0.079624

0.053083

0.938347

0.928808

0.9248

0.903235

0

0.00176

0.357121

13,256

351

146

37.766382

0.847102

0.255658

0

0.865217

0

0.036278

0

1

0.043478

false

0

0.013043

0

0.113043

0.026087

0

null

0

1

0

1

0

null

0

7

c6f7ab392868016be881d157d5be90fc093a9add

101

py

Python

common_utils/__init__.py

drsh4rky/python-hacking

798c2cddd8cb7a89ed310fbdb2c63ed9467c4048

[ "MIT" ]

32

2019-08-11T12:48:06.000Z

2022-02-24T03:07:12.000Z

common_utils/__init__.py

drsh4rky/python-hacking

798c2cddd8cb7a89ed310fbdb2c63ed9467c4048

[ "MIT" ]

null

common_utils/__init__.py

drsh4rky/python-hacking

798c2cddd8cb7a89ed310fbdb2c63ed9467c4048

[ "MIT" ]

8

2019-12-28T07:45:07.000Z

2022-02-25T09:28:08.000Z

from . import file_utils, menu_utils, var_utils __all__ = ["file_utils", "menu_utils", "var_utils"]

25.25

51

0.742574

15

101

4.333333

0.466667

0.276923

0.4

0.553846

0.8

0

0.118812

101

3

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33.666667

0.730337

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false

0

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0

null

1

0

1

0

1

0

null

0

1

0

7

af0b7f62849a36a656c6212a003b95896e4fed58

71,048

py

Python

loss.py

vanyoleyang/llll

ca2b880e1056af66a69d8c46c2f15c63904055f2

[ "MIT" ]

null

loss.py

vanyoleyang/llll

ca2b880e1056af66a69d8c46c2f15c63904055f2

[ "MIT" ]

null

loss.py

vanyoleyang/llll

ca2b880e1056af66a69d8c46c2f15c63904055f2

[ "MIT" ]

null

import torch import torch.nn as nn import numpy as np from utils import displayImage, displayMask class FHADLoss(nn.Module): def __init__(self, args): super(FHADLoss, self).__init__() # Initialize Parameters self.args = args self.alpha_2d = 2 self.alpha_3d = 10 #100 self.alpha_mask = 10 # 100 self.alpha_reg = 0#10 self.alpha_beta = 0#10000 self.alpha_camera = 1 self.img_size = 224 def forward(self, epoch, mask, predictions, targets, train=True): x2d_pred, x3d_pred, _, theta, beta = predictions joint_2d_targ, joint_3d_targ, _, _, _ = targets # Initialize Variables batch_size, seq_size, _ = x2d_pred.size() joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) # out2[:, :21, :] joint_3d_pred, pred_min, pred_max = self.normalize_joints_scale(joint_3d_pred) joint_3d_targ, targ_min, targ_max = self.normalize_joints_scale(joint_3d_targ) _, _, maxp = self.normalize_joints_scale(joint_3d_pred) _, _, maxt = self.normalize_joints_scale(joint_3d_targ) joint_3d_pred = self.center_joints_scale(joint_3d_pred, maxp) joint_3d_targ = self.center_joints_scale(joint_3d_targ, maxt) joint_3d_pred, joint_3d_targ = joint_3d_pred[:, -1, :, :], joint_3d_targ[:, -1, :, :] joint_2d_pred = torch.stack((x2d_pred[:, -1, :42:2], x2d_pred[:, -1, 1:42:2]), dim=2) # x_hat joint_2d_targ = joint_2d_targ[:, -1, :, :] loss_2d = torch.abs((joint_2d_pred.view(batch_size, -1) / self.img_size - joint_2d_targ.view(batch_size, -1) / self.img_size)).sum(1).mean() loss_2d = self.alpha_2d * loss_2d diff_2d = joint_2d_pred.view(batch_size, -1, 2) - joint_2d_targ.view(batch_size, -1,2) diff_3d = joint_3d_pred.view(batch_size, -1, 3) - joint_3d_targ.view(batch_size, -1,3) loss_3d = torch.pow(diff_3d.view(batch_size, -1), 2).sum(1).mean() diff_3d = diff_3d * (pred_max - pred_min).repeat(1, 1, 21, 1)[:, -1, :, :].view(batch_size, -1, 3) loss_3d = self.alpha_3d * loss_3d theta_prev = torch.cat((theta[:, 0, :].unsqueeze(1), theta[:, :-1, :]), 1) beta_prev = torch.cat((beta[:, 0, :].unsqueeze(1), beta[:, :-1, :]), 1) pose_temp_loss = torch.pow(theta_prev.view(batch_size * seq_size, -1) - theta.view(batch_size * seq_size, -1), 2).sum(1).mean() shape_temp_loss = torch.pow(beta_prev.view(batch_size * seq_size, -1) - beta.view(batch_size * seq_size, -1), 2).sum(1).mean() loss_temp = 0.0005 * ( 0.1 * pose_temp_loss + 1. * shape_temp_loss) loss_mask = torch.zeros(1).to(self.args.device) loss_reg = torch.zeros(1).to(self.args.device) loss_camera = torch.zeros(1).to(self.args.device) loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(self.args.n_kps): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.detach().cpu().numpy()), axis=2)) for i in range(self.args.n_kps): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_temp.item(), loss_reg.item(), loss_camera.item(), avg_distance_2d, avg_distance_3d] def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=2, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=2, keepdim=True) hand_joints[:, :, :, 0] = (hand_joints[:, :, :, 0] - min_joints[:, :, :, 0]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 1] = (hand_joints[:, :, :, 1] - min_joints[:, :, :, 1]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 2] = (hand_joints[:, :, :, 2] - min_joints[:, :, :, 2]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, :, :, 0] = hand_joints[:, :, :, 0] - max_joints[:, :, :, 0] hand_joints[:, :, :, 1] = hand_joints[:, :, :, 1] -max_joints[:, :, :, 1] hand_joints[:, :, :, 2] = hand_joints[:, :, :, 2] - max_joints[:, :, :, 2] return hand_joints class Hand3DLoss_wKLD(nn.Module): def __init__(self, args, pretrain=False): super(Hand3DLoss_wKLD, self).__init__() # Initialize Parameters self.args = args self.alpha_2d = 5 self.alpha_3d = 10 #100 self.alpha_mask = 10 # 100 self.alpha_reg = 0#10 self.alpha_beta = 0#10000 self.alpha_camera = 1 self.alpha_kld = 0.00001 self.n_meshes = 778 self.img_size = 224 def forward(self, epoch, mask, predictions, targets): # Initialize predictions x2d_pred, x3d_pred, camera_param_pred, theta, beta, mu, logvar = predictions # Initialize targets joint_2d_target, joint_3d_target, verts_3d_target, camera_param_target, dataset_type = targets # Initialize Variables batch_size, seq_size, _ = x2d_pred.size() # Get Vectors joint_2d_pred = torch.stack((x2d_pred[:, :, :42:2], x2d_pred[:, :, 1:42:2]), dim=3) # x_hat y_hat = x2d_pred[:, :, 42:].view(batch_size, seq_size, 778, 2) joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) # out2[:, :21, :] # KLD loss loss_kld = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp()) loss_kld = self.alpha_kld * loss_kld # Calculate the Losses - 2D joint re-projection loss loss_2d = torch.abs((joint_2d_pred.view(batch_size*seq_size, -1) / self.img_size - joint_2d_target.view(batch_size*seq_size, -1) / self.img_size)).sum(1).mean() loss_2d = self.alpha_2d * loss_2d # Calculate the Losses - 3D joint loss (Only the STEREO dataset) # print(joint_3d_pred[0, 0, 0, :], joint_3d_target[0, 0, 0, :]) joint_3d_pred, pred_min, pred_max = self.normalize_joints_scale(joint_3d_pred) joint_3d_target, targ_min, targ_max = self.normalize_joints_scale(joint_3d_target) _, _, maxp = self.normalize_joints_scale(joint_3d_pred) _, _, maxt = self.normalize_joints_scale(joint_3d_target) joint_3d_pred = self.center_joints_scale(joint_3d_pred, maxp) joint_3d_target = self.center_joints_scale(joint_3d_target,maxt ) # self.draw_3d_mano_pose(joint_3d_pred[0, 0, :, :], joint_3d_target[0, 0, :, :]) diff_3d = joint_3d_pred.view(batch_size * seq_size, -1, 3) - joint_3d_target.view(batch_size * seq_size, -1, 3) loss_3d = torch.pow(diff_3d.view(batch_size * seq_size, -1), 2).sum(1).mean() diff_3d = diff_3d * (pred_max - pred_min).repeat(1, 1, 21, 1).view(batch_size * seq_size, -1, 3) loss_3d = self.alpha_3d * loss_3d theta_prev = torch.cat((theta[:, 0, :].unsqueeze(1), theta[:, :-1, :]), 1) beta_prev = torch.cat((beta[:, 0, :].unsqueeze(1), beta[:, :-1, :]), 1) pose_temp_loss = torch.pow(theta_prev.view(batch_size * seq_size, -1) - theta.view(batch_size * seq_size, -1), 2).sum(1).mean() shape_temp_loss = torch.pow(beta_prev.view(batch_size * seq_size, -1) - beta.view(batch_size * seq_size, -1), 2).sum(1).mean() # print('theta_temp loss', pose_temp_loss, 'beta_temp_loss', shape_temp_loss) if 'ConvLSTM' in self.args.model_name : loss_temp = ( 0.05*pose_temp_loss + 100. * shape_temp_loss) # loss_temp *= 0. else : loss_temp = torch.zeros(1).cuda() # Calculate the Losses - Hand mask loss loss_mask = self.getHandMask(y_hat, mask) loss_mask = self.alpha_mask * loss_mask # Calculate the Losses - Regularization loss loss_reg = torch.zeros(1).cuda() # Calculate the Losses - Camera Parameter Loss if camera_param_target.sum().abs().item() > 0: if dataset_type[0] == 7 : loss_camera = torch.nn.functional.mse_loss( camera_param_pred[:, :, 16:26].view(batch_size * seq_size, -1), camera_param_target[:, :, 16:26].view(batch_size * seq_size, -1)) else : loss_camera_scale = torch.nn.functional.mse_loss(camera_param_pred[:, :, 0:1].view(batch_size*seq_size, -1), camera_param_target[:, :, 0:1].view(batch_size*seq_size, -1)) loss_camera_trans = torch.nn.functional.mse_loss(camera_param_pred[:, :, 1:3].view(batch_size*seq_size, -1), camera_param_target[:, :, 1:3].view(batch_size*seq_size, -1)) loss_camera_rot = torch.nn.functional.mse_loss(camera_param_pred[:, :, 3:6].view(batch_size*seq_size, -1), camera_param_target[:, :, 3:6].view(batch_size*seq_size, -1)) loss_camera_theta = torch.nn.functional.mse_loss(camera_param_pred[:, :, 6:16].view(batch_size*seq_size, -1), camera_param_target[:, :, 6:16].view(batch_size*seq_size, -1)) loss_camera_beta = torch.nn.functional.mse_loss(camera_param_pred[:, :, 16:26].view(batch_size*seq_size, -1), camera_param_target[:, :, 16:26].view(batch_size*seq_size, -1)) loss_camera = loss_camera_scale + loss_camera_trans + loss_camera_rot + loss_camera_theta + loss_camera_beta theta_dif = np.sum(np.square((camera_param_pred[:, :, 6:16].view(batch_size, seq_size, -1) - camera_param_target[:, :, 6:16].view(batch_size, seq_size, -1) ).detach().cpu().numpy()), axis=0) beta_dif = np.sum(np.square((camera_param_pred[:, :, 16:26].view(batch_size, seq_size, -1) - camera_param_target[:, :, 16:26].view(batch_size, seq_size, -1) ).detach().cpu().numpy()), axis=0) print('theta ', theta_dif,'\n', 'beta ', beta_dif) loss_camera = self.alpha_camera * loss_camera else: loss_camera = torch.zeros(1).cuda() # Weighted sum loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp + loss_kld # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(self.args.n_kps): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance diff_2d = joint_2d_pred.view(batch_size*seq_size, -1, 2) - joint_2d_target.view(batch_size*seq_size, -1, 2) euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.detach().cpu().numpy()), axis=2)) for i in range(self.args.n_kps): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_mask.item(), loss_kld.item() , loss_camera.item(), avg_distance_2d, avg_distance_3d] def getHandMask(self, y_hat, mask): batch_size, seq_size, _, h, w = mask.size() loss_mask = torch.ones(batch_size, seq_size, 1).cuda() y_hat = y_hat.round().long() y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] >= w, torch.tensor(w-1, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] >= h, torch.tensor(h-1, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) for i_batch in range(batch_size): for i_seq in range(seq_size): loss_mask[i_batch, i_seq] = loss_mask[i_batch, i_seq] - mask[i_batch, i_seq, 0, y_hat[i_batch, i_seq, :, 1], y_hat[i_batch, i_seq, :, 0]].sum()/self.n_meshes return loss_mask.mean() def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=2, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=2, keepdim=True) hand_joints[:, :, :, 0] = (hand_joints[:, :, :, 0] - min_joints[:, :, :, 0]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 1] = (hand_joints[:, :, :, 1] - min_joints[:, :, :, 1]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 2] = (hand_joints[:, :, :, 2] - min_joints[:, :, :, 2]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, :, :, 0] = hand_joints[:, :, :, 0] - max_joints[:, :, :, 0] hand_joints[:, :, :, 1] = hand_joints[:, :, :, 1] -max_joints[:, :, :, 1] hand_joints[:, :, :, 2] = hand_joints[:, :, :, 2] - max_joints[:, :, :, 2] return hand_joints class Hand3DLoss(nn.Module): def __init__(self, args, pretrain=False): super(Hand3DLoss, self).__init__() # Initialize Parameters self.args = args self.pretrain = pretrain if self.pretrain: self.alpha_2d = 0 self.alpha_3d = 0 self.alpha_mask = 0 self.alpha_reg = 0 self.alpha_beta = 0 self.alpha_camera = 1 else: self.alpha_2d = 5 self.alpha_3d = 100 #100 self.alpha_mask = 10 # 100 self.alpha_reg = 0#10 self.alpha_beta = 0#10000 self.alpha_camera = 1 self.n_meshes = 778 self.img_size = 224 def getRampUpScale(self, epoch): if self.pretrain: return torch.ones(1).cuda() else: return torch.ones(1).cuda() # return torch.FloatTensor([(epoch+1) / self.args.max_epochs_ramp_up]).cuda() def forward(self, epoch, mask, predictions, targets): # Initialize RampUp Scale rampup_scale = self.getRampUpScale(epoch) # Initialize predictions x2d_pred, x3d_pred, camera_param_pred, theta, beta = predictions # Initialize targets joint_2d_target, joint_3d_target, verts_3d_target, camera_param_target, dataset_type = targets # Initialize Variables batch_size, seq_size, _ = x2d_pred.size() # Get Vectors joint_2d_pred = torch.stack((x2d_pred[:, :, :42:2], x2d_pred[:, :, 1:42:2]), dim=3) # x_hat y_hat = x2d_pred[:, :, 42:].view(batch_size, seq_size, 778, 2) joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) # out2[:, :21, :] # Calculate the Losses - 2D joint re-projection loss loss_2d = torch.abs((joint_2d_pred.view(batch_size*seq_size, -1) / self.img_size - joint_2d_target.view(batch_size*seq_size, -1) / self.img_size)).sum(1).mean() loss_2d = rampup_scale * self.alpha_2d * loss_2d # Calculate the Losses - 3D joint loss (Only the STEREO dataset) # print(joint_3d_pred[0, 0, 0, :], joint_3d_target[0, 0, 0, :]) # joint_3d_pred, pred_min, pred_max = self.normalize_joints_scale(joint_3d_pred) # joint_3d_target, targ_min, targ_max = self.normalize_joints_scale(joint_3d_target) # _, _, maxp = self.normalize_joints_scale(joint_3d_pred) # _, _, maxt = self.normalize_joints_scale(joint_3d_target) # joint_3d_pred = self.center_joints_scale(joint_3d_pred, maxp) # joint_3d_target = self.center_joints_scale(joint_3d_target,maxt ) # self.draw_3d_mano_pose(joint_3d_pred[0, 0, :, :], joint_3d_target[0, 0, :, :]) diff_3d = joint_3d_pred.view(batch_size * seq_size, -1, 3) - joint_3d_target.view(batch_size * seq_size, -1, 3) loss_3d = torch.pow(diff_3d.view(batch_size * seq_size, -1), 2).sum(1).mean() #diff_3d = diff_3d * (pred_max - pred_min).repeat(1, 1, 21, 1).view(batch_size * seq_size, -1, 3) loss_3d = rampup_scale * self.alpha_3d * loss_3d theta_prev = torch.cat((theta[:, 0, :].unsqueeze(1), theta[:, :-1, :]), 1) beta_prev = torch.cat((beta[:, 0, :].unsqueeze(1), beta[:, :-1, :]), 1) pose_temp_loss = torch.pow(theta_prev.view(batch_size * seq_size, -1) - theta.view(batch_size * seq_size, -1), 2).sum(1).mean() shape_temp_loss = torch.pow(beta_prev.view(batch_size * seq_size, -1) - beta.view(batch_size * seq_size, -1), 2).sum(1).mean() # print('theta_temp loss', pose_temp_loss, 'beta_temp_loss', shape_temp_loss) if 'ConvLSTM' in self.args.model_name : loss_temp = 0.*( 0.05 * pose_temp_loss + 1. * shape_temp_loss) # loss_temp *= 0. else : loss_temp = torch.zeros(1).cuda() # Calculate the Losses - Hand mask loss loss_mask = self.getHandMask(y_hat, mask) loss_mask = rampup_scale * self.alpha_mask * loss_mask # Calculate the Losses - Regularization loss loss_reg = torch.zeros(1).cuda() # Calculate the Losses - Camera Parameter Loss if camera_param_target.sum().abs().item() > 0: if dataset_type[0] == 7 : loss_camera = torch.nn.functional.mse_loss( camera_param_pred[:, :, 16:26].view(batch_size * seq_size, -1), camera_param_target[:, :, 16:26].view(batch_size * seq_size, -1)) else : loss_camera_scale = torch.nn.functional.mse_loss(camera_param_pred[:, :, 0:1].view(batch_size*seq_size, -1), camera_param_target[:, :, 0:1].view(batch_size*seq_size, -1)) loss_camera_trans = torch.nn.functional.mse_loss(camera_param_pred[:, :, 1:3].view(batch_size*seq_size, -1), camera_param_target[:, :, 1:3].view(batch_size*seq_size, -1)) loss_camera_rot = torch.nn.functional.mse_loss(camera_param_pred[:, :, 3:6].view(batch_size*seq_size, -1), camera_param_target[:, :, 3:6].view(batch_size*seq_size, -1)) loss_camera_theta = torch.nn.functional.mse_loss(camera_param_pred[:, :, 6:16].view(batch_size*seq_size, -1), camera_param_target[:, :, 6:16].view(batch_size*seq_size, -1)) loss_camera_beta = torch.nn.functional.mse_loss(camera_param_pred[:, :, 16:26].view(batch_size*seq_size, -1), camera_param_target[:, :, 16:26].view(batch_size*seq_size, -1)) loss_camera = loss_camera_scale + loss_camera_trans + loss_camera_rot + loss_camera_theta + loss_camera_beta theta_dif = np.sum(np.square((camera_param_pred[:, :, 6:16].view(batch_size, seq_size, -1) - camera_param_target[:, :, 6:16].view(batch_size, seq_size, -1) ).detach().cpu().numpy()), axis=0) beta_dif = np.sum(np.square((camera_param_pred[:, :, 16:26].view(batch_size, seq_size, -1) - camera_param_target[:, :, 16:26].view(batch_size, seq_size, -1) ).detach().cpu().numpy()), axis=0) print(theta_dif, beta_dif) loss_camera = self.alpha_camera * loss_camera else: loss_camera = torch.zeros(1).cuda() # Weighted sum loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(self.args.n_kps): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance diff_2d = joint_2d_pred.view(batch_size*seq_size, -1, 2) - joint_2d_target.view(batch_size*seq_size, -1, 2) euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.detach().cpu().numpy()), axis=2)) for i in range(self.args.n_kps): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_mask.item(), loss_reg.item(), loss_camera.item(), avg_distance_2d, avg_distance_3d] def getHandMask(self, y_hat, mask): batch_size, seq_size, _, h, w = mask.size() loss_mask = torch.ones(batch_size, seq_size, 1).cuda() y_hat = y_hat.round().long() y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] >= w, torch.tensor(w-1, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] >= h, torch.tensor(h-1, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) for i_batch in range(batch_size): for i_seq in range(seq_size): loss_mask[i_batch, i_seq] = loss_mask[i_batch, i_seq] - mask[i_batch, i_seq, 0, y_hat[i_batch, i_seq, :, 1], y_hat[i_batch, i_seq, :, 0]].sum()/self.n_meshes return loss_mask.mean() def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=2, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=2, keepdim=True) hand_joints[:, :, :, 0] = (hand_joints[:, :, :, 0] - min_joints[:, :, :, 0]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 1] = (hand_joints[:, :, :, 1] - min_joints[:, :, :, 1]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 2] = (hand_joints[:, :, :, 2] - min_joints[:, :, :, 2]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, :, :, 0] = hand_joints[:, :, :, 0] - max_joints[:, :, :, 0] hand_joints[:, :, :, 1] = hand_joints[:, :, :, 1] -max_joints[:, :, :, 1] hand_joints[:, :, :, 2] = hand_joints[:, :, :, 2] - max_joints[:, :, :, 2] return hand_joints def draw_3d_mano_pose(self, pose_3d, pose_3d2, color='black', color2 ='red'): pose_3d = pose_3d.reshape(21, 3) pose_3d2 = pose_3d2.reshape(21, 3) # print(pose_3d[0][0], pose_3d[0][1], pose_3d[0][2]) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') b = color # or 'red' ax.plot([pose_3d2[0][0], pose_3d2[1][0]], [pose_3d2[0][1], pose_3d2[1][1]], zs=[pose_3d2[0][2], pose_3d2[1][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[5][0]], [pose_3d2[0][1], pose_3d2[5][1]], zs=[pose_3d2[0][2], pose_3d2[5][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[9][0]], [pose_3d2[0][1], pose_3d2[9][1]], zs=[pose_3d2[0][2], pose_3d2[9][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[13][0]], [pose_3d2[0][1], pose_3d2[13][1]], zs=[pose_3d2[0][2], pose_3d2[13][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[17][0]], [pose_3d2[0][1], pose_3d2[17][1]], zs=[pose_3d2[0][2], pose_3d2[17][2]], linewidth=3, color=color2) ax.plot([pose_3d2[1][0], pose_3d2[2][0]], [pose_3d2[1][1], pose_3d2[2][1]], zs=[pose_3d2[1][2], pose_3d2[2][2]], linewidth=3, color=color2) ax.plot([pose_3d2[2][0], pose_3d2[3][0]], [pose_3d2[2][1], pose_3d2[3][1]], zs=[pose_3d2[2][2], pose_3d2[3][2]], linewidth=3, color=color2) ax.plot([pose_3d2[3][0], pose_3d2[4][0]], [pose_3d2[3][1], pose_3d2[4][1]], zs=[pose_3d2[3][2], pose_3d2[4][2]], linewidth=3, color=color2) ax.plot([pose_3d2[5][0], pose_3d2[6][0]], [pose_3d2[5][1], pose_3d2[6][1]], zs=[pose_3d2[5][2], pose_3d2[6][2]], linewidth=3, color=color2) ax.plot([pose_3d2[6][0], pose_3d2[7][0]], [pose_3d2[6][1], pose_3d2[7][1]], zs=[pose_3d2[6][2], pose_3d2[7][2]], linewidth=3, color=color2) ax.plot([pose_3d2[7][0], pose_3d2[8][0]], [pose_3d2[7][1], pose_3d2[8][1]], zs=[pose_3d2[7][2], pose_3d2[8][2]], linewidth=3, color=color2) ax.plot([pose_3d2[9][0], pose_3d2[10][0]], [pose_3d2[9][1], pose_3d2[10][1]], zs=[pose_3d2[9][2], pose_3d2[10][2]], linewidth=3, color=color2) ax.plot([pose_3d2[10][0], pose_3d2[11][0]], [pose_3d2[10][1], pose_3d2[11][1]], zs=[pose_3d2[10][2], pose_3d2[11][2]], linewidth=3, color=color2) ax.plot([pose_3d2[11][0], pose_3d2[12][0]], [pose_3d2[11][1], pose_3d2[12][1]], zs=[pose_3d2[11][2], pose_3d2[12][2]], linewidth=3, color=color2) ax.plot([pose_3d2[13][0], pose_3d2[14][0]], [pose_3d2[13][1], pose_3d2[14][1]], zs=[pose_3d2[13][2], pose_3d2[14][2]], linewidth=3, color=color2) ax.plot([pose_3d2[14][0], pose_3d2[15][0]], [pose_3d2[14][1], pose_3d2[15][1]], zs=[pose_3d2[14][2], pose_3d2[15][2]], linewidth=3, color=color2) ax.plot([pose_3d2[15][0], pose_3d2[16][0]], [pose_3d2[15][1], pose_3d2[16][1]], zs=[pose_3d2[15][2], pose_3d2[16][2]], linewidth=3, color=color2) ax.plot([pose_3d2[17][0], pose_3d2[18][0]], [pose_3d2[17][1], pose_3d2[18][1]], zs=[pose_3d2[17][2], pose_3d2[18][2]], linewidth=3, color=color2) ax.plot([pose_3d2[18][0], pose_3d2[19][0]], [pose_3d2[18][1], pose_3d2[19][1]], zs=[pose_3d2[18][2], pose_3d2[19][2]], linewidth=3, color=color2) ax.plot([pose_3d2[19][0], pose_3d2[20][0]], [pose_3d2[19][1], pose_3d2[20][1]], zs=[pose_3d2[19][2], pose_3d2[20][2]], linewidth=3, color=color2) ax.plot([pose_3d[0][0], pose_3d[1][0]], [pose_3d[0][1], pose_3d[1][1]], zs=[pose_3d[0][2], pose_3d[1][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[5][0]], [pose_3d[0][1], pose_3d[5][1]], zs=[pose_3d[0][2], pose_3d[5][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[9][0]], [pose_3d[0][1], pose_3d[9][1]], zs=[pose_3d[0][2], pose_3d[9][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[13][0]], [pose_3d[0][1], pose_3d[13][1]], zs=[pose_3d[0][2], pose_3d[13][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[17][0]], [pose_3d[0][1], pose_3d[17][1]], zs=[pose_3d[0][2], pose_3d[17][2]], linewidth=3, color=b) ax.plot([pose_3d[1][0], pose_3d[2][0]], [pose_3d[1][1], pose_3d[2][1]], zs=[pose_3d[1][2], pose_3d[2][2]], linewidth=3, color=b) ax.plot([pose_3d[2][0], pose_3d[3][0]], [pose_3d[2][1], pose_3d[3][1]], zs=[pose_3d[2][2], pose_3d[3][2]], linewidth=3, color=b) ax.plot([pose_3d[3][0], pose_3d[4][0]], [pose_3d[3][1], pose_3d[4][1]], zs=[pose_3d[3][2], pose_3d[4][2]], linewidth=3, color=b) ax.plot([pose_3d[5][0], pose_3d[6][0]], [pose_3d[5][1], pose_3d[6][1]], zs=[pose_3d[5][2], pose_3d[6][2]], linewidth=3, color=b) ax.plot([pose_3d[6][0], pose_3d[7][0]], [pose_3d[6][1], pose_3d[7][1]], zs=[pose_3d[6][2], pose_3d[7][2]], linewidth=3, color=b) ax.plot([pose_3d[7][0], pose_3d[8][0]], [pose_3d[7][1], pose_3d[8][1]], zs=[pose_3d[7][2], pose_3d[8][2]], linewidth=3, color=b) ax.plot([pose_3d[9][0], pose_3d[10][0]], [pose_3d[9][1], pose_3d[10][1]], zs=[pose_3d[9][2], pose_3d[10][2]], linewidth=3, color=b) ax.plot([pose_3d[10][0], pose_3d[11][0]], [pose_3d[10][1], pose_3d[11][1]], zs=[pose_3d[10][2], pose_3d[11][2]], linewidth=3, color=b) ax.plot([pose_3d[11][0], pose_3d[12][0]], [pose_3d[11][1], pose_3d[12][1]], zs=[pose_3d[11][2], pose_3d[12][2]], linewidth=3, color=b) ax.plot([pose_3d[13][0], pose_3d[14][0]], [pose_3d[13][1], pose_3d[14][1]], zs=[pose_3d[13][2], pose_3d[14][2]], linewidth=3, color=b) ax.plot([pose_3d[14][0], pose_3d[15][0]], [pose_3d[14][1], pose_3d[15][1]], zs=[pose_3d[14][2], pose_3d[15][2]], linewidth=3, color=b) ax.plot([pose_3d[15][0], pose_3d[16][0]], [pose_3d[15][1], pose_3d[16][1]], zs=[pose_3d[15][2], pose_3d[16][2]], linewidth=3, color=b) ax.plot([pose_3d[17][0], pose_3d[18][0]], [pose_3d[17][1], pose_3d[18][1]], zs=[pose_3d[17][2], pose_3d[18][2]], linewidth=3, color=b) ax.plot([pose_3d[18][0], pose_3d[19][0]], [pose_3d[18][1], pose_3d[19][1]], zs=[pose_3d[18][2], pose_3d[19][2]], linewidth=3, color=b) ax.plot([pose_3d[19][0], pose_3d[20][0]], [pose_3d[19][1], pose_3d[20][1]], zs=[pose_3d[19][2], pose_3d[20][2]], linewidth=3, color=b) plt.show() return ax def getHandMask(y_hat, mask): batch_size, seq_size, _, h, w = mask.size() loss_mask = torch.ones(batch_size, seq_size, 1).cuda() y_hat = y_hat.round().long() y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] >= w, torch.tensor(w-1, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] >= h, torch.tensor(h-1, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) for i_batch in range(batch_size): for i_seq in range(seq_size): loss_mask[i_batch, i_seq] = loss_mask[i_batch, i_seq] - mask[i_batch, i_seq, 0, y_hat[i_batch, i_seq, :, 1], y_hat[i_batch, i_seq, :, 0]].sum()/778 return loss_mask.mean() def getHandMask(y_hat, mask): batch_size, seq_size, _, h, w = mask.size() loss_mask = torch.ones(batch_size, seq_size, 1).cuda() y_hat = y_hat.round().long() y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] >= w, torch.tensor(w-1, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] >= h, torch.tensor(h-1, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) for i_batch in range(batch_size): for i_seq in range(seq_size): loss_mask[i_batch, i_seq] = loss_mask[i_batch, i_seq] - mask[i_batch, i_seq, 0, y_hat[i_batch, i_seq, :, 1], y_hat[i_batch, i_seq, :, 0]].sum()/778 return loss_mask.mean() import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D class STBLoss(nn.Module): def __init__(self, args, pretrain=False): super(STBLoss, self).__init__() # Initialize Parameters self.args = args self.pretrain = pretrain self.alpha_2d = 1 self.alpha_3d = 10 #100 self.alpha_mask = 5 # 100 self.alpha_reg = 0#10 self.alpha_beta = 0#10000 self.alpha_camera = 1 self.n_meshes = 778 self.img_size = 224 def getRampUpScale(self, epoch): if self.pretrain: return torch.ones(1).cuda() else: return torch.ones(1).cuda() # return torch.FloatTensor([(epoch+1) / self.args.max_epochs_ramp_up]).cuda() def forward(self, epoch, mask, predictions, targets): # Initialize predictions x2d_pred, x3d_pred, camera_param_pred, theta, beta = predictions # Initialize targets joint_2d_target, joint_3d_target, verts_3d_target, camera_param_target, dataset_type = targets # Initialize Variables batch_size, seq_size, _ = x2d_pred.size() # Get Vectors joint_2d_pred = torch.stack((x2d_pred[:, :, :42:2], x2d_pred[:, :, 1:42:2]), dim=3) # x_hat y_hat = x2d_pred[:, :, 42:].view(batch_size, seq_size, 778, 2) joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) verts_3d_pred = torch.stack((x3d_pred[:, :, 63::3], x3d_pred[:, :, 64::3], x3d_pred[:, :, 65::3]), dim=3) # Calculate the Losses - 2D joint re-projection loss loss_2d = torch.abs((joint_2d_pred.view(batch_size*seq_size, -1) / self.img_size - joint_2d_target.view(batch_size*seq_size, -1) / self.img_size)).sum(1).mean() loss_2d = self.alpha_2d * loss_2d # Calculate the Losses - Temporal loss loss_temp = torch.zeros(1).cuda() # theta_prev = torch.cat((theta[:, 0, :].unsqueeze(1), theta[:, :-1, :]), 1) # beta_prev = torch.cat((beta[:, 0, :].unsqueeze(1), beta[:, :-1:]), 1) # pose_temp_loss = torch.pow(theta_prev.view(batch_size * seq_size, -1) - theta.view(batch_size * seq_size, -1), # 2).sum(1).mean() # shape_temp_loss = torch.pow(beta_prev.view(batch_size * seq_size, -1) - beta.view(batch_size * seq_size, -1), # 2).sum(1).mean() # loss_temp = 0.1 * pose_temp_loss + 1. * shape_temp_loss # Calculate the Losses - Hand mask loss loss_mask = self.alpha_mask * getHandMask(y_hat, mask) # Calculate the Losses - Camera loss loss_camera = torch.zeros(1).cuda() # Calculate the Losses - Regularization loss loss_reg = torch.zeros(1).cuda() # Calculate the Losses - 3D joint loss (Only the STEREO dataset) # diff_3d = joint_3d_pred.view(batch_size * seq_size, -1, 3) - joint_3d_target.view(batch_size * seq_size, -1, 3) ## normalize joint_3d_pred, pred_min, pred_max = self.normalize_joints_scale(joint_3d_pred) joint_3d_target, targ_min, targ_max = self.normalize_joints_scale(joint_3d_target) verts_3d_pred, _, pred_max_v = self.normalize_joints_scale(verts_3d_pred) _, _, maxp = self.normalize_joints_scale(joint_3d_pred) _, _, maxt = self.normalize_joints_scale(joint_3d_target) _, _, maxv = self.normalize_joints_scale(verts_3d_pred) # _, pred_mean, pred_std = self.normalize_joints(norm_scaled_joint3d_pred) # # verts_3d_pred, _, _ = self.normalize_joints(verts_3d_pred) # joint_3d_target, _, _ = self.normalize_joints(joint_3d_target) # print(pred_max.size(), pred_mean.size()) # joint_3d_target = self.denormalize_joints_scale(joint_3d_target, pred_min, pred_max) joint_3d_pred = self.center_joints_scale(joint_3d_pred, maxp) joint_3d_target = self.center_joints_scale(joint_3d_target,maxt ) verts_3d_pred = self.center_joints_scale(verts_3d_pred, maxv) # ax = self.draw_3d_mano_pose(joint_3d_pred[0][0], joint_3d_target[0][0], 'black', 'red') # ax.scatter(xs=verts_3d_pred[0,0,:, 0].cpu().numpy(), ys=verts_3d_pred[0,0,:, 1].cpu().numpy(), zs=verts_3d_pred[0, 0, :, 2].cpu().numpy()) # plt.show() palm_cent_pred = 0.5 * verts_3d_pred[:, :, 17, :] + 0.5 * verts_3d_pred[:, :, 67, :] palm_cent_targ = joint_3d_target[:, :, 0, :] diff_3d_pc = palm_cent_pred.view(batch_size * seq_size, 3) - palm_cent_targ.view(batch_size * seq_size, 3) diff_3d_ot = joint_3d_pred[:, :, 1:, :].view(batch_size * seq_size, -1, 3) - joint_3d_target[:, :, 1:, :].view(batch_size * seq_size, -1, 3) diff_3d = torch.cat((diff_3d_pc.unsqueeze(1), diff_3d_ot), 1) loss_3d = self.alpha_3d * torch.pow(diff_3d.view(batch_size * seq_size, -1), 2).sum(1).mean() diff_3d = diff_3d * (pred_max - pred_min).repeat(1,1,21,1).view(batch_size * seq_size, -1, 3) # Weighted sum loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(self.args.n_kps): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance diff_2d = joint_2d_pred.view(batch_size*seq_size, -1, 2) - joint_2d_target.view(batch_size*seq_size, -1, 2) euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.detach().cpu().numpy()), axis=2)) for i in range(self.args.n_kps): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_mask.item(), loss_reg.item(), loss_camera.item(), avg_distance_2d, avg_distance_3d] def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=2, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=2, keepdim=True) hand_joints[:, :, :, 0] = (hand_joints[:, :, :, 0] - min_joints[:, :, :, 0]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 1] = (hand_joints[:, :, :, 1] - min_joints[:, :, :, 1]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 2] = (hand_joints[:, :, :, 2] - min_joints[:, :, :, 2]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, :, :, 0] = hand_joints[:, :, :, 0] - max_joints[:, :, :, 0] hand_joints[:, :, :, 1] = hand_joints[:, :, :, 1] -max_joints[:, :, :, 1] hand_joints[:, :, :, 2] = hand_joints[:, :, :, 2] - max_joints[:, :, :, 2] return hand_joints def draw_3d_mano_pose(self, pose_3d, pose_3d2, color='black', color2 ='red'): pose_3d = pose_3d.reshape(21, 3) pose_3d2 = pose_3d2.reshape(21, 3) # print(pose_3d[0][0], pose_3d[0][1], pose_3d[0][2]) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') b = color # or 'red' ax.plot([pose_3d2[0][0], pose_3d2[1][0]], [pose_3d2[0][1], pose_3d2[1][1]], zs=[pose_3d2[0][2], pose_3d2[1][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[5][0]], [pose_3d2[0][1], pose_3d2[5][1]], zs=[pose_3d2[0][2], pose_3d2[5][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[9][0]], [pose_3d2[0][1], pose_3d2[9][1]], zs=[pose_3d2[0][2], pose_3d2[9][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[13][0]], [pose_3d2[0][1], pose_3d2[13][1]], zs=[pose_3d2[0][2], pose_3d2[13][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[17][0]], [pose_3d2[0][1], pose_3d2[17][1]], zs=[pose_3d2[0][2], pose_3d2[17][2]], linewidth=3, color=color2) ax.plot([pose_3d2[1][0], pose_3d2[2][0]], [pose_3d2[1][1], pose_3d2[2][1]], zs=[pose_3d2[1][2], pose_3d2[2][2]], linewidth=3, color=color2) ax.plot([pose_3d2[2][0], pose_3d2[3][0]], [pose_3d2[2][1], pose_3d2[3][1]], zs=[pose_3d2[2][2], pose_3d2[3][2]], linewidth=3, color=color2) ax.plot([pose_3d2[3][0], pose_3d2[4][0]], [pose_3d2[3][1], pose_3d2[4][1]], zs=[pose_3d2[3][2], pose_3d2[4][2]], linewidth=3, color=color2) ax.plot([pose_3d2[5][0], pose_3d2[6][0]], [pose_3d2[5][1], pose_3d2[6][1]], zs=[pose_3d2[5][2], pose_3d2[6][2]], linewidth=3, color=color2) ax.plot([pose_3d2[6][0], pose_3d2[7][0]], [pose_3d2[6][1], pose_3d2[7][1]], zs=[pose_3d2[6][2], pose_3d2[7][2]], linewidth=3, color=color2) ax.plot([pose_3d2[7][0], pose_3d2[8][0]], [pose_3d2[7][1], pose_3d2[8][1]], zs=[pose_3d2[7][2], pose_3d2[8][2]], linewidth=3, color=color2) ax.plot([pose_3d2[9][0], pose_3d2[10][0]], [pose_3d2[9][1], pose_3d2[10][1]], zs=[pose_3d2[9][2], pose_3d2[10][2]], linewidth=3, color=color2) ax.plot([pose_3d2[10][0], pose_3d2[11][0]], [pose_3d2[10][1], pose_3d2[11][1]], zs=[pose_3d2[10][2], pose_3d2[11][2]], linewidth=3, color=color2) ax.plot([pose_3d2[11][0], pose_3d2[12][0]], [pose_3d2[11][1], pose_3d2[12][1]], zs=[pose_3d2[11][2], pose_3d2[12][2]], linewidth=3, color=color2) ax.plot([pose_3d2[13][0], pose_3d2[14][0]], [pose_3d2[13][1], pose_3d2[14][1]], zs=[pose_3d2[13][2], pose_3d2[14][2]], linewidth=3, color=color2) ax.plot([pose_3d2[14][0], pose_3d2[15][0]], [pose_3d2[14][1], pose_3d2[15][1]], zs=[pose_3d2[14][2], pose_3d2[15][2]], linewidth=3, color=color2) ax.plot([pose_3d2[15][0], pose_3d2[16][0]], [pose_3d2[15][1], pose_3d2[16][1]], zs=[pose_3d2[15][2], pose_3d2[16][2]], linewidth=3, color=color2) ax.plot([pose_3d2[17][0], pose_3d2[18][0]], [pose_3d2[17][1], pose_3d2[18][1]], zs=[pose_3d2[17][2], pose_3d2[18][2]], linewidth=3, color=color2) ax.plot([pose_3d2[18][0], pose_3d2[19][0]], [pose_3d2[18][1], pose_3d2[19][1]], zs=[pose_3d2[18][2], pose_3d2[19][2]], linewidth=3, color=color2) ax.plot([pose_3d2[19][0], pose_3d2[20][0]], [pose_3d2[19][1], pose_3d2[20][1]], zs=[pose_3d2[19][2], pose_3d2[20][2]], linewidth=3, color=color2) ax.plot([pose_3d[0][0], pose_3d[1][0]], [pose_3d[0][1], pose_3d[1][1]], zs=[pose_3d[0][2], pose_3d[1][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[5][0]], [pose_3d[0][1], pose_3d[5][1]], zs=[pose_3d[0][2], pose_3d[5][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[9][0]], [pose_3d[0][1], pose_3d[9][1]], zs=[pose_3d[0][2], pose_3d[9][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[13][0]], [pose_3d[0][1], pose_3d[13][1]], zs=[pose_3d[0][2], pose_3d[13][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[17][0]], [pose_3d[0][1], pose_3d[17][1]], zs=[pose_3d[0][2], pose_3d[17][2]], linewidth=3, color=b) ax.plot([pose_3d[1][0], pose_3d[2][0]], [pose_3d[1][1], pose_3d[2][1]], zs=[pose_3d[1][2], pose_3d[2][2]], linewidth=3, color=b) ax.plot([pose_3d[2][0], pose_3d[3][0]], [pose_3d[2][1], pose_3d[3][1]], zs=[pose_3d[2][2], pose_3d[3][2]], linewidth=3, color=b) ax.plot([pose_3d[3][0], pose_3d[4][0]], [pose_3d[3][1], pose_3d[4][1]], zs=[pose_3d[3][2], pose_3d[4][2]], linewidth=3, color=b) ax.plot([pose_3d[5][0], pose_3d[6][0]], [pose_3d[5][1], pose_3d[6][1]], zs=[pose_3d[5][2], pose_3d[6][2]], linewidth=3, color=b) ax.plot([pose_3d[6][0], pose_3d[7][0]], [pose_3d[6][1], pose_3d[7][1]], zs=[pose_3d[6][2], pose_3d[7][2]], linewidth=3, color=b) ax.plot([pose_3d[7][0], pose_3d[8][0]], [pose_3d[7][1], pose_3d[8][1]], zs=[pose_3d[7][2], pose_3d[8][2]], linewidth=3, color=b) ax.plot([pose_3d[9][0], pose_3d[10][0]], [pose_3d[9][1], pose_3d[10][1]], zs=[pose_3d[9][2], pose_3d[10][2]], linewidth=3, color=b) ax.plot([pose_3d[10][0], pose_3d[11][0]], [pose_3d[10][1], pose_3d[11][1]], zs=[pose_3d[10][2], pose_3d[11][2]], linewidth=3, color=b) ax.plot([pose_3d[11][0], pose_3d[12][0]], [pose_3d[11][1], pose_3d[12][1]], zs=[pose_3d[11][2], pose_3d[12][2]], linewidth=3, color=b) ax.plot([pose_3d[13][0], pose_3d[14][0]], [pose_3d[13][1], pose_3d[14][1]], zs=[pose_3d[13][2], pose_3d[14][2]], linewidth=3, color=b) ax.plot([pose_3d[14][0], pose_3d[15][0]], [pose_3d[14][1], pose_3d[15][1]], zs=[pose_3d[14][2], pose_3d[15][2]], linewidth=3, color=b) ax.plot([pose_3d[15][0], pose_3d[16][0]], [pose_3d[15][1], pose_3d[16][1]], zs=[pose_3d[15][2], pose_3d[16][2]], linewidth=3, color=b) ax.plot([pose_3d[17][0], pose_3d[18][0]], [pose_3d[17][1], pose_3d[18][1]], zs=[pose_3d[17][2], pose_3d[18][2]], linewidth=3, color=b) ax.plot([pose_3d[18][0], pose_3d[19][0]], [pose_3d[18][1], pose_3d[19][1]], zs=[pose_3d[18][2], pose_3d[19][2]], linewidth=3, color=b) ax.plot([pose_3d[19][0], pose_3d[20][0]], [pose_3d[19][1], pose_3d[20][1]], zs=[pose_3d[19][2], pose_3d[20][2]], linewidth=3, color=b) return ax class RWorldLoss(nn.Module): def __init__(self, args, pretrain=False): super(RWorldLoss, self).__init__() # Initialize Parameters self.args = args self.pretrain = pretrain if self.pretrain: self.alpha_2d = 0 self.alpha_3d = 0 self.alpha_mask = 0 self.alpha_reg = 0 self.alpha_beta = 0 self.alpha_camera = 1 else: self.alpha_2d = 5 self.alpha_3d = 100 self.alpha_mask = 0 self.alpha_reg = 0 self.alpha_beta = 0 self.alpha_camera = 0 self.n_meshes = 778 self.img_size = 224 def getRampUpScale(self, epoch): if self.pretrain: return torch.ones(1).cuda() else: return torch.ones(1).cuda() # return torch.FloatTensor([(epoch+1) / self.args.max_epochs_ramp_up]).cuda() def forward(self, epoch, mask, predictions, targets): # Initialize predictions x2d_pred, x3d_pred, camera_param_pred, theta, beta = predictions # Initialize targets joint_2d_target, joint_3d_target, verts_3d_target, camera_param_target, dataset_type = targets # print(joint_3d_target, x3d_pred) batch_size, seq_size, _ = x2d_pred.size() # Get Vectors joint_2d_pred = torch.stack((x2d_pred[:, :, :42:2], x2d_pred[:, :, 1:42:2]), dim=3) # x_hat y_hat = x2d_pred[:, :, 42:].view(batch_size, seq_size, 778, 2) # No loss for Camera param vert3d loss, joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) # out2[:, :21, :] joint_3d_pred, pred_min, pred_max = self.normalize_joints_scale(joint_3d_pred) joint_3d_target, targ_min, targ_max = self.normalize_joints_scale(joint_3d_target) _, _, maxp = self.normalize_joints_scale(joint_3d_pred) _, _, maxt = self.normalize_joints_scale(joint_3d_target) joint_3d_pred = self.center_joints_scale(joint_3d_pred, maxp) joint_3d_target = self.center_joints_scale(joint_3d_target, maxt) diff_3d = joint_3d_pred.view(batch_size * seq_size, -1, 3) - joint_3d_target.view(batch_size * seq_size, -1, 3) loss_3d = self.alpha_3d * torch.pow(diff_3d.view(batch_size * seq_size, -1), 2).sum(1).mean() diff_3d = diff_3d * (pred_max - pred_min).repeat(1, 1, 21, 1).view(batch_size * seq_size, -1, 3) # Weighted sum loss_2d = torch.abs((joint_2d_pred.view(batch_size * seq_size, -1) / self.img_size - joint_2d_target.view( batch_size * seq_size, -1) / self.img_size)).sum(1).mean() loss_2d = self.alpha_2d * loss_2d loss_temp = torch.zeros(1).cuda() loss_mask = self.alpha_mask * getHandMask(y_hat, mask) loss_camera = torch.zeros(1).cuda() loss_reg = torch.zeros(1).cuda() loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(self.args.n_kps): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance diff_2d = joint_2d_pred.view(batch_size * seq_size, -1, 2) - joint_2d_target.view(batch_size * seq_size, -1, 2) euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.detach().cpu().numpy()), axis=2)) for i in range(self.args.n_kps): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_mask.item(), loss_reg.item(), loss_camera.item(), avg_distance_2d, avg_distance_3d] def getHandMask(self, y_hat, mask): batch_size, seq_size, _, h, w = mask.size() loss_mask = torch.ones(batch_size, seq_size, 1).cuda() y_hat = y_hat.round().long() y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] >= w, torch.tensor(w-1, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] >= h, torch.tensor(h-1, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) y_hat[:, :, :, 0] = torch.where(y_hat[:, :, :, 0] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 0]) y_hat[:, :, :, 1] = torch.where(y_hat[:, :, :, 1] < 0, torch.tensor(0, dtype=torch.long).cuda(), y_hat[:, :, :, 1]) for i_batch in range(batch_size): for i_seq in range(seq_size): loss_mask[i_batch, i_seq] = loss_mask[i_batch, i_seq] - mask[i_batch, i_seq, 0, y_hat[i_batch, i_seq, :, 1], y_hat[i_batch, i_seq, :, 0]].sum()/self.n_meshes return loss_mask.mean() def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=2, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=2, keepdim=True) hand_joints[:, :, :, 0] = (hand_joints[:, :, :, 0] - min_joints[:, :, :, 0]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 1] = (hand_joints[:, :, :, 1] - min_joints[:, :, :, 1]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) hand_joints[:, :, :, 2] = (hand_joints[:, :, :, 2] - min_joints[:, :, :, 2]) / (max_joints[:, :, :, 0] - min_joints[:, :, :, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, :, :, 0] = hand_joints[:, :, :, 0] - max_joints[:, :, :, 0] hand_joints[:, :, :, 1] = hand_joints[:, :, :, 1] -max_joints[:, :, :, 1] hand_joints[:, :, :, 2] = hand_joints[:, :, :, 2] - max_joints[:, :, :, 2] return hand_joints def draw_3d_mano_pose(self, pose_3d, pose_3d2, color='black', color2 ='red'): pose_3d = pose_3d.reshape(21, 3) pose_3d2 = pose_3d2.reshape(21, 3) # print(pose_3d[0][0], pose_3d[0][1], pose_3d[0][2]) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') b = color # or 'red' ax.plot([pose_3d2[0][0], pose_3d2[1][0]], [pose_3d2[0][1], pose_3d2[1][1]], zs=[pose_3d2[0][2], pose_3d2[1][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[5][0]], [pose_3d2[0][1], pose_3d2[5][1]], zs=[pose_3d2[0][2], pose_3d2[5][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[9][0]], [pose_3d2[0][1], pose_3d2[9][1]], zs=[pose_3d2[0][2], pose_3d2[9][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[13][0]], [pose_3d2[0][1], pose_3d2[13][1]], zs=[pose_3d2[0][2], pose_3d2[13][2]], linewidth=3, color=color2) ax.plot([pose_3d2[0][0], pose_3d2[17][0]], [pose_3d2[0][1], pose_3d2[17][1]], zs=[pose_3d2[0][2], pose_3d2[17][2]], linewidth=3, color=color2) ax.plot([pose_3d2[1][0], pose_3d2[2][0]], [pose_3d2[1][1], pose_3d2[2][1]], zs=[pose_3d2[1][2], pose_3d2[2][2]], linewidth=3, color=color2) ax.plot([pose_3d2[2][0], pose_3d2[3][0]], [pose_3d2[2][1], pose_3d2[3][1]], zs=[pose_3d2[2][2], pose_3d2[3][2]], linewidth=3, color=color2) ax.plot([pose_3d2[3][0], pose_3d2[4][0]], [pose_3d2[3][1], pose_3d2[4][1]], zs=[pose_3d2[3][2], pose_3d2[4][2]], linewidth=3, color=color2) ax.plot([pose_3d2[5][0], pose_3d2[6][0]], [pose_3d2[5][1], pose_3d2[6][1]], zs=[pose_3d2[5][2], pose_3d2[6][2]], linewidth=3, color=color2) ax.plot([pose_3d2[6][0], pose_3d2[7][0]], [pose_3d2[6][1], pose_3d2[7][1]], zs=[pose_3d2[6][2], pose_3d2[7][2]], linewidth=3, color=color2) ax.plot([pose_3d2[7][0], pose_3d2[8][0]], [pose_3d2[7][1], pose_3d2[8][1]], zs=[pose_3d2[7][2], pose_3d2[8][2]], linewidth=3, color=color2) ax.plot([pose_3d2[9][0], pose_3d2[10][0]], [pose_3d2[9][1], pose_3d2[10][1]], zs=[pose_3d2[9][2], pose_3d2[10][2]], linewidth=3, color=color2) ax.plot([pose_3d2[10][0], pose_3d2[11][0]], [pose_3d2[10][1], pose_3d2[11][1]], zs=[pose_3d2[10][2], pose_3d2[11][2]], linewidth=3, color=color2) ax.plot([pose_3d2[11][0], pose_3d2[12][0]], [pose_3d2[11][1], pose_3d2[12][1]], zs=[pose_3d2[11][2], pose_3d2[12][2]], linewidth=3, color=color2) ax.plot([pose_3d2[13][0], pose_3d2[14][0]], [pose_3d2[13][1], pose_3d2[14][1]], zs=[pose_3d2[13][2], pose_3d2[14][2]], linewidth=3, color=color2) ax.plot([pose_3d2[14][0], pose_3d2[15][0]], [pose_3d2[14][1], pose_3d2[15][1]], zs=[pose_3d2[14][2], pose_3d2[15][2]], linewidth=3, color=color2) ax.plot([pose_3d2[15][0], pose_3d2[16][0]], [pose_3d2[15][1], pose_3d2[16][1]], zs=[pose_3d2[15][2], pose_3d2[16][2]], linewidth=3, color=color2) ax.plot([pose_3d2[17][0], pose_3d2[18][0]], [pose_3d2[17][1], pose_3d2[18][1]], zs=[pose_3d2[17][2], pose_3d2[18][2]], linewidth=3, color=color2) ax.plot([pose_3d2[18][0], pose_3d2[19][0]], [pose_3d2[18][1], pose_3d2[19][1]], zs=[pose_3d2[18][2], pose_3d2[19][2]], linewidth=3, color=color2) ax.plot([pose_3d2[19][0], pose_3d2[20][0]], [pose_3d2[19][1], pose_3d2[20][1]], zs=[pose_3d2[19][2], pose_3d2[20][2]], linewidth=3, color=color2) ax.plot([pose_3d[0][0], pose_3d[1][0]], [pose_3d[0][1], pose_3d[1][1]], zs=[pose_3d[0][2], pose_3d[1][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[5][0]], [pose_3d[0][1], pose_3d[5][1]], zs=[pose_3d[0][2], pose_3d[5][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[9][0]], [pose_3d[0][1], pose_3d[9][1]], zs=[pose_3d[0][2], pose_3d[9][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[13][0]], [pose_3d[0][1], pose_3d[13][1]], zs=[pose_3d[0][2], pose_3d[13][2]], linewidth=3, color=b) ax.plot([pose_3d[0][0], pose_3d[17][0]], [pose_3d[0][1], pose_3d[17][1]], zs=[pose_3d[0][2], pose_3d[17][2]], linewidth=3, color=b) ax.plot([pose_3d[1][0], pose_3d[2][0]], [pose_3d[1][1], pose_3d[2][1]], zs=[pose_3d[1][2], pose_3d[2][2]], linewidth=3, color=b) ax.plot([pose_3d[2][0], pose_3d[3][0]], [pose_3d[2][1], pose_3d[3][1]], zs=[pose_3d[2][2], pose_3d[3][2]], linewidth=3, color=b) ax.plot([pose_3d[3][0], pose_3d[4][0]], [pose_3d[3][1], pose_3d[4][1]], zs=[pose_3d[3][2], pose_3d[4][2]], linewidth=3, color=b) ax.plot([pose_3d[5][0], pose_3d[6][0]], [pose_3d[5][1], pose_3d[6][1]], zs=[pose_3d[5][2], pose_3d[6][2]], linewidth=3, color=b) ax.plot([pose_3d[6][0], pose_3d[7][0]], [pose_3d[6][1], pose_3d[7][1]], zs=[pose_3d[6][2], pose_3d[7][2]], linewidth=3, color=b) ax.plot([pose_3d[7][0], pose_3d[8][0]], [pose_3d[7][1], pose_3d[8][1]], zs=[pose_3d[7][2], pose_3d[8][2]], linewidth=3, color=b) ax.plot([pose_3d[9][0], pose_3d[10][0]], [pose_3d[9][1], pose_3d[10][1]], zs=[pose_3d[9][2], pose_3d[10][2]], linewidth=3, color=b) ax.plot([pose_3d[10][0], pose_3d[11][0]], [pose_3d[10][1], pose_3d[11][1]], zs=[pose_3d[10][2], pose_3d[11][2]], linewidth=3, color=b) ax.plot([pose_3d[11][0], pose_3d[12][0]], [pose_3d[11][1], pose_3d[12][1]], zs=[pose_3d[11][2], pose_3d[12][2]], linewidth=3, color=b) ax.plot([pose_3d[13][0], pose_3d[14][0]], [pose_3d[13][1], pose_3d[14][1]], zs=[pose_3d[13][2], pose_3d[14][2]], linewidth=3, color=b) ax.plot([pose_3d[14][0], pose_3d[15][0]], [pose_3d[14][1], pose_3d[15][1]], zs=[pose_3d[14][2], pose_3d[15][2]], linewidth=3, color=b) ax.plot([pose_3d[15][0], pose_3d[16][0]], [pose_3d[15][1], pose_3d[16][1]], zs=[pose_3d[15][2], pose_3d[16][2]], linewidth=3, color=b) ax.plot([pose_3d[17][0], pose_3d[18][0]], [pose_3d[17][1], pose_3d[18][1]], zs=[pose_3d[17][2], pose_3d[18][2]], linewidth=3, color=b) ax.plot([pose_3d[18][0], pose_3d[19][0]], [pose_3d[18][1], pose_3d[19][1]], zs=[pose_3d[18][2], pose_3d[19][2]], linewidth=3, color=b) ax.plot([pose_3d[19][0], pose_3d[20][0]], [pose_3d[19][1], pose_3d[20][1]], zs=[pose_3d[19][2], pose_3d[20][2]], linewidth=3, color=b) return ax class EgoDexLoss(nn.Module): def __init__(self, args, pretrain=False): super(EgoDexLoss, self).__init__() # Initialize Parameters self.args = args self.pretrain = pretrain self.alpha_2d = 5. self.alpha_3d = 100 #100 self.alpha_mask = 0. # 100 self.alpha_reg = 0#10 self.alpha_beta = 0#10000 self.alpha_camera = 1 self.n_meshes = 778 self.img_size = 224 def getRampUpScale(self, epoch): if self.pretrain: return torch.ones(1).cuda() else: return torch.ones(1).cuda() # return torch.FloatTensor([(epoch+1) / self.args.max_epochs_ramp_up]).cuda() def forward(self, epoch, mask, predictions, targets): # Initialize predictions x2d_pred, x3d_pred, camera_param_pred, theta, beta = predictions # Initialize targets joint_2d_target, joint_3d_target, verts_3d_target, camera_param_target, dataset_type = targets # Initialize Variables batch_size, seq_size, _ = x2d_pred.size() # Get Vectors joint_2d_pred = torch.stack((x2d_pred[:, :, :42:2], x2d_pred[:, :, 1:42:2]), dim=3) # x_hat y_hat = x2d_pred[:, :, 42:].view(batch_size, seq_size, 778, 2) joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) verts_3d_pred = torch.stack((x3d_pred[:, :, 63::3], x3d_pred[:, :, 64::3], x3d_pred[:, :, 65::3]), dim=3) # Calculate the Losses - 2D joint re-projection loss loss_2d = torch.abs((joint_2d_pred[:, -1, [4, 8, 12, 16, 20], :].view(batch_size, -1) / self.img_size - joint_2d_target[:, -1, :, :].view(batch_size, -1) / self.img_size)).sum(1).mean() loss_2d = self.alpha_2d * loss_2d # Calculate the Losses - Temporal loss loss_temp = torch.zeros(1).cuda() # Calculate the Losses - Hand mask loss loss_mask = torch.zeros(1).cuda() # Calculate the Losses - Camera loss loss_camera = torch.zeros(1).cuda() # Calculate the Losses - Regularization loss loss_reg = torch.zeros(1).cuda() # Calculate the Losses - 3D joint loss (Only the STEREO dataset) diff_3d = torch.zeros(batch_size, 1, 5, 3).cuda() # last frame only joint3d_pred = joint_3d_pred[:, -1, [4, 8, 12, 16, 20], :] # last frame joint3d_targ = joint_3d_target[:, -1, :, :] # joint2d_pred = joint_2d_pred[:, -1, [4, 8, 12, 16, 20], :] # last frame # joint2d_targ = joint_2d_target[:, -1, :, :] #loop over batch for b in range(batch_size): targs3d = joint3d_targ[b, :] # 5, 3 preds3d = joint3d_pred[b, :] preds3d[joint3d_targ[b, :] == 0.] = 0. visible_indice = (joint3d_targ[b, :] != 0.).nonzero() visible_indice_mask = joint3d_targ[b, :] != 0. ## normalize preds3d, pred_min, pred_max = self.normalize_joints_scale(preds3d.clone()) targs3d, targ_min, targ_max = self.normalize_joints_scale(targs3d.clone()) maxp, _ = torch.max(preds3d.clone(), dim=0, keepdim=True) maxt, _ = torch.max(targs3d.clone(), dim=0, keepdim=True) preds3d = self.center_joints_scale(preds3d.clone(), maxp) targs3d = self.center_joints_scale(targs3d.clone(), maxt) # plt.figure() # ax = plt.axes(projection='3d') # ax.scatter3D(xs=preds3d[:, 0].clone().detach().cpu().numpy(), # ys=preds3d[:, 1].clone().detach().cpu().numpy(), # zs=preds3d[:, 2].clone().detach().cpu().numpy(), # c='blue') # ax.scatter3D(xs=targs3d[:, 0].clone().detach().cpu().numpy(), # ys=targs3d[:, 1].clone().detach().cpu().numpy(), # zs=targs3d[:, 2].clone().detach().cpu().numpy(), # c='red') # plt.show() targs3d = targs3d[visible_indice_mask].view(torch.unique(visible_indice[:, 0]).size()[0], 3) # joint, coord preds3d = preds3d[visible_indice_mask].view(torch.unique(visible_indice[:, 0]).size()[0], 3) # joint, coord diff_3d_ego = (targs3d - preds3d) * (pred_max - pred_min).repeat(torch.unique(visible_indice[:, 0]).size()[0],1) diff_3d[b, 0, visible_indice_mask] = diff_3d_ego.view(torch.unique(visible_indice[:, 0]).size()[0] * 3) loss_3d = self.alpha_3d * torch.pow(diff_3d.view(batch_size, -1), 2).sum(1).mean().cuda() # Weighted sum loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(5): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance diff_2d = joint_2d_pred[:, -1, [4, 8, 12, 16, 20], :].view(batch_size, -1, 2) - joint_2d_target[:, -1, :, :].view(batch_size, -1, 2) euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.squeeze(1).detach().cpu().numpy()), axis=2)) * 0.7 for i in range(5): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_mask.item(), loss_reg.item(), loss_camera.item(), avg_distance_2d, avg_distance_3d] def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=0, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=0, keepdim=True) hand_joints[:, 0] = (hand_joints[:, 0] - min_joints[:, 0]) / (max_joints[:, 0] - min_joints[:, 0]) hand_joints[:, 1] = (hand_joints[:, 1] - min_joints[:, 1]) / (max_joints[:, 0] - min_joints[:, 0]) hand_joints[:, 2] = (hand_joints[:, 2] - min_joints[:, 2]) / (max_joints[:, 0] - min_joints[:, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, 0] = hand_joints[:, 0] - max_joints[:, 0] hand_joints[:, 1] = hand_joints[:, 1] - max_joints[:, 1] hand_joints[:, 2] = hand_joints[:, 2] - max_joints[:, 2] return hand_joints class DexterObjLoss(nn.Module): def __init__(self, args, pretrain=False): super(DexterObjLoss, self).__init__() # Initialize Parameters self.args = args self.pretrain = pretrain self.alpha_2d = 1 self.alpha_3d = 100 #100 self.alpha_mask = 0. # 100 self.alpha_reg = 0#10 self.alpha_beta = 0#10000 self.alpha_camera = 1 self.n_meshes = 778 self.img_size = 224 def getRampUpScale(self, epoch): if self.pretrain: return torch.ones(1).cuda() else: return torch.ones(1).cuda() # return torch.FloatTensor([(epoch+1) / self.args.max_epochs_ramp_up]).cuda() def forward(self, epoch, mask, predictions, targets): # Initialize predictions x2d_pred, x3d_pred, camera_param_pred, theta, beta = predictions # Initialize targets joint_2d_target, joint_3d_target, verts_3d_target, camera_param_target, dataset_type = targets # Initialize Variables batch_size, seq_size, _ = x2d_pred.size() # Get Vectors joint_2d_pred = torch.stack((x2d_pred[:, :, :42:2], x2d_pred[:, :, 1:42:2]), dim=3) # x_hat y_hat = x2d_pred[:, :, 42:].view(batch_size, seq_size, 778, 2) joint_3d_pred = torch.stack((x3d_pred[:, :, :63:3], x3d_pred[:, :, 1:63:3], x3d_pred[:, :, 2:63:3]), dim=3) verts_3d_pred = torch.stack((x3d_pred[:, :, 63::3], x3d_pred[:, :, 64::3], x3d_pred[:, :, 65::3]), dim=3) # Calculate the Losses - 2D joint re-projection loss loss_2d = torch.abs((joint_2d_pred[:, -1, [4, 8, 12, 16, 20], :].view(batch_size, -1) / self.img_size - joint_2d_target[:, -1, :, :].view(batch_size, -1) / self.img_size)).sum(1).mean() loss_2d = self.alpha_2d * loss_2d # Calculate the Losses - Temporal loss loss_temp = torch.zeros(1).cuda() # Calculate the Losses - Hand mask loss loss_mask = torch.zeros(1).cuda() # Calculate the Losses - Camera loss loss_camera = torch.zeros(1).cuda() # Calculate the Losses - Regularization loss loss_reg = torch.zeros(1).cuda() # Calculate the Losses - 3D joint loss (Only the STEREO dataset) diff_3d = torch.zeros(batch_size, 1, 5, 3).cuda() # last frame only joint3d_pred = joint_3d_pred[:, -1, [4, 8, 12, 16, 20], :] # last frame joint3d_targ = joint_3d_target[:, -1, :, :] # joint2d_pred = joint_2d_pred[:, -1, [4, 8, 12, 16, 20], :] # last frame # joint2d_targ = joint_2d_target[:, -1, :, :] #loop over batch for b in range(batch_size): targs3d = joint3d_targ[b, :] # 5, 3 preds3d = joint3d_pred[b, :] targs3d[joint3d_targ[b, :, 2] == 32001, :] = 0. preds3d[joint3d_targ[b, :, 2] == 32001, :] = 0. visible_indice = (joint3d_targ[b, :, 2] != 32001).nonzero() visible_indice_mask = joint3d_targ[b, :, 2] != 32001 ## normalize preds3d, pred_min, pred_max = self.normalize_joints_scale(preds3d.clone()) targs3d, targ_min, targ_max = self.normalize_joints_scale(targs3d.clone()) maxp, _ = torch.max(preds3d.clone(), dim=0, keepdim=True) maxt, _ = torch.max(targs3d.clone(), dim=0, keepdim=True) preds3d = self.center_joints_scale(preds3d.clone(), maxp) targs3d = self.center_joints_scale(targs3d.clone(), maxt) targs3d = targs3d[visible_indice_mask, :] preds3d = preds3d[visible_indice_mask, :] # plt.figure() # ax = plt.axes(projection='3d') # ax.scatter3D(xs=preds3d[:, 0].clone().detach().cpu().numpy(), # ys=preds3d[:, 1].clone().detach().cpu().numpy(), # zs=preds3d[:, 2].clone().detach().cpu().numpy(), # c='blue') # ax.scatter3D(xs=targs3d[:, 0].clone().detach().cpu().numpy(), # ys=targs3d[:, 1].clone().detach().cpu().numpy(), # zs=targs3d[:, 2].clone().detach().cpu().numpy(), # c='red') # plt.show() targs3d = targs3d[visible_indice_mask].view(torch.unique(visible_indice[:, 0]).size()[0], 3) # joint, coord preds3d = preds3d[visible_indice_mask].view(torch.unique(visible_indice[:, 0]).size()[0], 3) # joint, coord diff_3d_dex = (targs3d - preds3d) * (pred_max - pred_min).repeat(torch.unique(visible_indice[:, 0]).size()[0],1) diff_3d[b, 0, visible_indice_mask, :] = diff_3d_dex.view(visible_indice.size()[0], 3) loss_3d = self.alpha_3d * torch.pow(diff_3d.view(batch_size, -1), 2).sum(1).mean().cuda() # Weighted sum loss = loss_2d + loss_3d + loss_mask + loss_reg + loss_camera + loss_temp # Initialize Average Distance Storage avg_distance_2d = list() avg_distance_3d = list() for _ in range(5): avg_distance_2d.append(None) avg_distance_3d.append(None) # Calculate euclidean distance diff_2d = joint_2d_pred[:, -1, [4, 8, 12, 16, 20], :].view(batch_size, -1, 2)\ - joint_2d_target[:, -1, :, :].view(batch_size, -1, 2) euclidean_dist_2d = np.sqrt(np.sum(np.square(diff_2d.detach().cpu().numpy()), axis=2)) euclidean_dist_3d = np.sqrt(np.sum(np.square(diff_3d.squeeze(1).detach().cpu().numpy()), axis=2)) for i in range(5): avg_distance_2d[i] = euclidean_dist_2d[:, i] avg_distance_3d[i] = euclidean_dist_3d[:, i] return loss, [loss_2d.item(), loss_3d.item(), loss_mask.item(), loss_reg.item(), loss_camera.item(), avg_distance_2d, avg_distance_3d] def normalize_joints_scale(self, hand_joints): min_joints, _ = torch.min(hand_joints, dim=0, keepdim=True) max_joints, _ = torch.max(hand_joints, dim=0, keepdim=True) hand_joints[:, 0] = (hand_joints[:, 0] - min_joints[:, 0]) / (max_joints[:, 0] - min_joints[:, 0]) hand_joints[:, 1] = (hand_joints[:, 1] - min_joints[:, 1]) / (max_joints[:, 0] - min_joints[:, 0]) hand_joints[:, 2] = (hand_joints[:, 2] - min_joints[:, 2]) / (max_joints[:, 0] - min_joints[:, 0]) return hand_joints, min_joints, max_joints def center_joints_scale(self, hand_joints, max_joints): hand_joints[:, 0] = hand_joints[:, 0] - max_joints[:, 0] hand_joints[:, 1] = hand_joints[:, 1] - max_joints[:, 1] hand_joints[:, 2] = hand_joints[:, 2] - max_joints[:, 2] return hand_joints

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af58affa0f475b2ef0d48347e97c938d2d4c8569

5,414

py

Python

tests/chainer_tests/functions_tests/normalization_tests/test_batch_normalization.py

Teppei-Kanayama/myChainer

6ffbfd8479768ca8b580c98788c5b1ba1fd3aee8

[ "MIT" ]

null

tests/chainer_tests/functions_tests/normalization_tests/test_batch_normalization.py

Teppei-Kanayama/myChainer

6ffbfd8479768ca8b580c98788c5b1ba1fd3aee8

[ "MIT" ]

null

tests/chainer_tests/functions_tests/normalization_tests/test_batch_normalization.py

Teppei-Kanayama/myChainer

6ffbfd8479768ca8b580c98788c5b1ba1fd3aee8

[ "MIT" ]

null

import unittest import numpy import six import chainer from chainer import cuda from chainer import functions from chainer.functions.normalization import batch_normalization from chainer import gradient_check from chainer import testing from chainer.testing import attr from chainer.testing import condition def _batch_normalization(expander, gamma, beta, x, mean, var): mean = mean[expander] std = numpy.sqrt(var)[expander] y_expect = (gamma[expander] * (x - mean) / std + beta[expander]) return y_expect @testing.parameterize(*testing.product({ 'ndim': [0, 1, 2, 3], 'dtype': [numpy.float16, numpy.float32, numpy.float64], })) class TestBatchNormalization(unittest.TestCase): def setUp(self): self.expander = (None, Ellipsis) + (None,) * self.ndim self.aggr_axes = (0,) + tuple(six.moves.range(2, self.ndim + 2)) self.eps = 1e-5 self.gamma = numpy.random.uniform(.5, 1, (3,)).astype(self.dtype) self.beta = numpy.random.uniform(-1, 1, (3,)).astype(self.dtype) shape = (7, 3) + (2,) * self.ndim self.x = numpy.random.uniform(-1, 1, shape).astype(self.dtype) self.gy = numpy.random.uniform(-1, 1, shape).astype(self.dtype) self.args = [self.x, self.gamma, self.beta] self.mean = self.x.mean(axis=self.aggr_axes) self.var = self.x.var(axis=self.aggr_axes) + self.eps self.check_forward_optionss = {'atol': 1e-4, 'rtol': 1e-3} self.check_backward_optionss = { 'eps': 1e-2, 'atol': 1e-4, 'rtol': 1e-3} if self.dtype == numpy.float16: self.check_forward_optionss = {'atol': 1e-3, 'rtol': 1e-2} self.check_backward_optionss = { 'eps': 2 ** -3, 'atol': 5e-2, 'rtol': 1e-1} def check_forward(self, args): y = functions.batch_normalization( *[chainer.Variable(i) for i in args], eps=self.eps) self.assertEqual(y.data.dtype, self.dtype) y_expect = _batch_normalization( self.expander, self.gamma, self.beta, self.x, self.mean, self.var) gradient_check.assert_allclose( y_expect, y.data, **self.check_forward_optionss) @condition.retry(3) def test_forward_cpu(self): self.check_forward(self.args) @attr.gpu @condition.retry(3) def test_forward_gpu(self): self.check_forward([cuda.to_gpu(i) for i in self.args]) def check_backward(self, args, y_grad): gradient_check.check_backward( batch_normalization.BatchNormalizationFunction(eps=self.eps), args, y_grad, **self.check_backward_optionss) @condition.retry(10) def test_backward_cpu(self): self.check_backward(self.args, self.gy) @attr.gpu @condition.retry(10) def test_backward_gpu(self): self.check_backward( [cuda.to_gpu(i) for i in self.args], cuda.to_gpu(self.gy)) @testing.parameterize(*testing.product({ 'ndim': [0, 1, 2, 3], 'dtype': [numpy.float16, numpy.float32, numpy.float64], })) class TestFixedBatchNormalization(unittest.TestCase): def setUp(self): self.gamma = numpy.random.uniform(.5, 1, (3,)).astype(self.dtype) self.beta = numpy.random.uniform(-1, 1, (3,)).astype(self.dtype) self.expander = (None, Ellipsis) + (None,) * self.ndim shape = (7, 3) + (2,) * self.ndim self.x = numpy.random.uniform(-1, 1, shape).astype(self.dtype) self.gy = numpy.random.uniform(-1, 1, shape).astype(self.dtype) self.eps = 1e-5 self.aggr_axes = (0,) + tuple(six.moves.range(2, self.ndim + 2)) self.mean = numpy.random.uniform(-1, 1, (3,)).astype(self.dtype) self.var = numpy.random.uniform( 0.5, 1, (3,)).astype(self.dtype) self.args = [self.x, self.gamma, self.beta, self.mean, self.var] self.check_forward_optionss = {'atol': 1e-4, 'rtol': 1e-3} self.check_backward_optionss = { 'eps': 1e-2, 'atol': 1e-4, 'rtol': 1e-3} if self.dtype == numpy.float16: self.check_forward_optionss = {'atol': 1e-3, 'rtol': 1e-2} self.check_backward_optionss = { 'eps': 2 ** -5, 'atol': 1e-2, 'rtol': 1e-1} def check_forward(self, args): y = functions.fixed_batch_normalization( *[chainer.Variable(i) for i in args], eps=self.eps) self.assertEqual(y.data.dtype, self.dtype) y_expect = _batch_normalization( self.expander, self.gamma, self.beta, self.x, self.mean, self.var) gradient_check.assert_allclose( y_expect, y.data, **self.check_forward_optionss) @condition.retry(3) def test_forward_cpu(self): self.check_forward(self.args) @attr.gpu @condition.retry(3) def test_forward_gpu(self): self.check_forward([cuda.to_gpu(i) for i in self.args]) def check_backward(self, args, y_grad): gradient_check.check_backward( batch_normalization.BatchNormalizationFunction(eps=self.eps), args, y_grad, **self.check_backward_optionss) @condition.retry(10) def test_backward_cpu(self): self.check_backward(self.args, self.gy) @attr.gpu @condition.retry(10) def test_backward_gpu(self): self.check_backward( [cuda.to_gpu(i) for i in self.args], cuda.to_gpu(self.gy)) testing.run_module(__name__, __file__)

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7

af9a58ff491811d18db56a8534c2c7b9bd3586a7

63

py

Python

v0.9.2/walletrpc/__init__.py

lncm/lnd-proto

8caa6558efe043413560f807ef44b11699901d76

[ "MIT" ]

2

2020-02-10T09:46:06.000Z

2020-04-09T19:30:30.000Z

v0.9.2/walletrpc/__init__.py

lncm/lnd-rpc

8caa6558efe043413560f807ef44b11699901d76

[ "MIT" ]

1

2020-02-04T16:34:35.000Z

v0.9.2/walletrpc/__init__.py

lncm/lnd-proto

8caa6558efe043413560f807ef44b11699901d76

[ "MIT" ]

null

from .walletkit_pb2 import * from .walletkit_pb2_grpc import *

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1

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1

0

7

afc2268887de87d035e6977c31d4865240e57c1a

8,281

py

Python

tests/grep_test.py

wojdatto/pyzet

4d737e7b3bd38879da37ffe6336962fb9f82e611

[ "Apache-2.0" ]

2

2022-01-23T21:23:04.000Z

2022-01-24T00:21:24.000Z

tests/grep_test.py

wojdatto/pyzet

4d737e7b3bd38879da37ffe6336962fb9f82e611

[ "Apache-2.0" ]

12

2022-01-24T21:19:05.000Z

2022-02-18T21:10:05.000Z

tests/grep_test.py

wojdatto/pyzet

4d737e7b3bd38879da37ffe6336962fb9f82e611

[ "Apache-2.0" ]

null

import pytest import pyzet.constants as C from pyzet.main import main GREP_CMD = ("--config", f"testing/{C.CONFIG_FILE}", "grep") def test_grep(capfd): main([*GREP_CMD, "zet"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md # Another zet test entry """ assert out.replace("\r", "") == expected assert err == "" def test_grep_ignore_case(capfd): main([*GREP_CMD, "--ignore-case", "zet"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md # Zet test entry 20211016223643/README.md # Another zet test entry 20220101220852/README.md # Zettel with UTF-8 """ assert out.replace("\r", "") == expected assert err == "" def test_grep_title(capfd): main([*GREP_CMD, "--title", "Hello"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md # Zet test entry Hello there! 20211016223643/README.md # Another zet test entry Hello everyone """ assert out.replace("\r", "") == expected assert err == "" def test_grep_line_number(capfd): main([*GREP_CMD, "--line-number", "Hello"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md 3:Hello there! 20211016223643/README.md 3:Hello everyone """ assert out.replace("\r", "") == expected assert err == "" def test_grep_title_and_line_number(capfd): main([*GREP_CMD, "--title", "--line-number", "Hello"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md 1:# Zet test entry 3:Hello there! 20211016223643/README.md 1:# Another zet test entry 3:Hello everyone """ assert out.replace("\r", "") == expected assert err == "" def test_grep_multiple_matches_in_file(capfd): main([*GREP_CMD, "test"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md # Zet test entry #test-tag #another-tag #tag-after-two-spaces 20211016223643/README.md # Another zet test entry #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_multiple_matches_in_file_title(capfd): # Title matches searched pattern, so --title doesn't make a difference. main([*GREP_CMD, "--title", "test"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md # Zet test entry #test-tag #another-tag #tag-after-two-spaces 20211016223643/README.md # Another zet test entry #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_multiple_matches_in_file_line_number(capfd): main([*GREP_CMD, "--line-number", "test"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md 1:# Zet test entry 7: #test-tag #another-tag #tag-after-two-spaces 20211016223643/README.md 1:# Another zet test entry 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_multiple_matches_in_file_title_and_line_number(capfd): # Title matches searched pattern, so --title doesn't make a difference. main([*GREP_CMD, "--title", "--line-number", "test"]) out, err = capfd.readouterr() expected = """\ 20211016205158/README.md 1:# Zet test entry 7: #test-tag #another-tag #tag-after-two-spaces 20211016223643/README.md 1:# Another zet test entry 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_two_patterns(capfd): main([*GREP_CMD, "everyone", "test-tag"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md Hello everyone #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_three_patterns(capfd): main([*GREP_CMD, "everyone", "test-tag", "zet"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md # Another zet test entry Hello everyone #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_three_patterns_verbose(capfd): main([*GREP_CMD, "everyone", "test-tag", "--", "--or", "-e", "zet"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md # Another zet test entry Hello everyone #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_two_patterns_line_number(capfd): main([*GREP_CMD, "--line-number", "everyone", "test-tag"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_two_patterns_line_number_last(capfd): main([*GREP_CMD, "everyone", "test-tag", "--line-number"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_two_patterns_error_argparse(capfd): with pytest.raises(SystemExit): main([*GREP_CMD, "everyone", "--line-number", "test-tag"]) out, err = capfd.readouterr() assert out == "" assert err.endswith("pyzet: error: unrecognized arguments: test-tag\n") def test_grep_two_patterns_error_argparse_weird(capfd): # I'm not sure why it fails, but it does, so this test confirms it. with pytest.raises(SystemExit): main([*GREP_CMD, "everyone", "test-tag", "--line-number", "--", "--no-color"]) out, err = capfd.readouterr() assert out == "" assert err.endswith("pyzet: error: unrecognized arguments: -- --no-color\n") def test_grep_title_with_options_error_weird(capfd): # I'm not sure why it fails, but it does, so this test confirms it. # # The only difference between this one and test_grep_title_with_options() # is the order of arguments. with pytest.raises(SystemExit): main([*GREP_CMD, "everyone", "--title", "--", "--or", "-e", "test-tag"]) out, err = capfd.readouterr() assert out == "" assert err.endswith("pyzet: error: unrecognized arguments: -- --or -e test-tag\n") def test_grep_two_patterns_line_number_verbose(capfd): main([*GREP_CMD, "everyone", "test-tag", "--", "--line-number"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_multiple_patterns_line_number(capfd): main( [*GREP_CMD, "everyone", "test-tag", "--", "--line-number", "--or", "-e", "zet"] ) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 1:# Another zet test entry 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_multiple_patterns_line_number_different_order(capfd): main( [*GREP_CMD, "everyone", "test-tag", "--", "--or", "-e", "zet", "--line-number"] ) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 1:# Another zet test entry 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_with_option_and_pattern(capfd): # --and means that matching line should always have its pattern main([*GREP_CMD, "--title", "--ignore-case", "zet", "--", "--and", "-e", "another"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md # Another zet test entry """ assert out.replace("\r", "") == expected assert err == "" def test_grep_line_number_with_options(capfd): main([*GREP_CMD, "--line-number", "everyone", "--", "--or", "-e", "test-tag"]) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == "" def test_grep_title_and_line_number_with_options(capfd): main( [ *GREP_CMD, "--title", "--line-number", "everyone", "--", "--or", "-e", "test-tag", ] ) out, err = capfd.readouterr() expected = """\ 20211016223643/README.md 1:# Another zet test entry 3:Hello everyone 7: #test-tag """ assert out.replace("\r", "") == expected assert err == ""

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null

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7

afc51a596e729b75216dd1523e4f746e733f823e

10,656

py

Python

src/MiniJavaListener.py

simonwangao/MiniJava_Compiler

32086af4e984d06301272744e6e755bbaef195bc

[ "Apache-2.0" ]

null

src/MiniJavaListener.py

simonwangao/MiniJava_Compiler

32086af4e984d06301272744e6e755bbaef195bc

[ "Apache-2.0" ]

null

src/MiniJavaListener.py

simonwangao/MiniJava_Compiler

32086af4e984d06301272744e6e755bbaef195bc

[ "Apache-2.0" ]

3

2020-01-14T12:12:35.000Z

2020-10-04T06:07:46.000Z

# Generated from MiniJava.g4 by ANTLR 4.7.2 from antlr4 import * if __name__ is not None and "." in __name__: from .MiniJavaParser import MiniJavaParser else: from MiniJavaParser import MiniJavaParser # This class defines a complete listener for a parse tree produced by MiniJavaParser. class MiniJavaListener(ParseTreeListener): # Enter a parse tree produced by MiniJavaParser#goal. def enterGoal(self, ctx:MiniJavaParser.GoalContext): pass # Exit a parse tree produced by MiniJavaParser#goal. def exitGoal(self, ctx:MiniJavaParser.GoalContext): pass # Enter a parse tree produced by MiniJavaParser#mainclass. def enterMainclass(self, ctx:MiniJavaParser.MainclassContext): pass # Exit a parse tree produced by MiniJavaParser#mainclass. def exitMainclass(self, ctx:MiniJavaParser.MainclassContext): pass # Enter a parse tree produced by MiniJavaParser#dec_class. def enterDec_class(self, ctx:MiniJavaParser.Dec_classContext): pass # Exit a parse tree produced by MiniJavaParser#dec_class. def exitDec_class(self, ctx:MiniJavaParser.Dec_classContext): pass # Enter a parse tree produced by MiniJavaParser#dec_var. def enterDec_var(self, ctx:MiniJavaParser.Dec_varContext): pass # Exit a parse tree produced by MiniJavaParser#dec_var. def exitDec_var(self, ctx:MiniJavaParser.Dec_varContext): pass # Enter a parse tree produced by MiniJavaParser#dec_method. def enterDec_method(self, ctx:MiniJavaParser.Dec_methodContext): pass # Exit a parse tree produced by MiniJavaParser#dec_method. def exitDec_method(self, ctx:MiniJavaParser.Dec_methodContext): pass # Enter a parse tree produced by MiniJavaParser#mtype. def enterMtype(self, ctx:MiniJavaParser.MtypeContext): pass # Exit a parse tree produced by MiniJavaParser#mtype. def exitMtype(self, ctx:MiniJavaParser.MtypeContext): pass # Enter a parse tree produced by MiniJavaParser#state_lrparents. def enterState_lrparents(self, ctx:MiniJavaParser.State_lrparentsContext): pass # Exit a parse tree produced by MiniJavaParser#state_lrparents. def exitState_lrparents(self, ctx:MiniJavaParser.State_lrparentsContext): pass # Enter a parse tree produced by MiniJavaParser#state_if. def enterState_if(self, ctx:MiniJavaParser.State_ifContext): pass # Exit a parse tree produced by MiniJavaParser#state_if. def exitState_if(self, ctx:MiniJavaParser.State_ifContext): pass # Enter a parse tree produced by MiniJavaParser#state_while. def enterState_while(self, ctx:MiniJavaParser.State_whileContext): pass # Exit a parse tree produced by MiniJavaParser#state_while. def exitState_while(self, ctx:MiniJavaParser.State_whileContext): pass # Enter a parse tree produced by MiniJavaParser#state_print. def enterState_print(self, ctx:MiniJavaParser.State_printContext): pass # Exit a parse tree produced by MiniJavaParser#state_print. def exitState_print(self, ctx:MiniJavaParser.State_printContext): pass # Enter a parse tree produced by MiniJavaParser#state_assign. def enterState_assign(self, ctx:MiniJavaParser.State_assignContext): pass # Exit a parse tree produced by MiniJavaParser#state_assign. def exitState_assign(self, ctx:MiniJavaParser.State_assignContext): pass # Enter a parse tree produced by MiniJavaParser#state_array_assign. def enterState_array_assign(self, ctx:MiniJavaParser.State_array_assignContext): pass # Exit a parse tree produced by MiniJavaParser#state_array_assign. def exitState_array_assign(self, ctx:MiniJavaParser.State_array_assignContext): pass # Enter a parse tree produced by MiniJavaParser#err_miss_RHS. def enterErr_miss_RHS(self, ctx:MiniJavaParser.Err_miss_RHSContext): pass # Exit a parse tree produced by MiniJavaParser#err_miss_RHS. def exitErr_miss_RHS(self, ctx:MiniJavaParser.Err_miss_RHSContext): pass # Enter a parse tree produced by MiniJavaParser#err_lparent_closing. def enterErr_lparent_closing(self, ctx:MiniJavaParser.Err_lparent_closingContext): pass # Exit a parse tree produced by MiniJavaParser#err_lparent_closing. def exitErr_lparent_closing(self, ctx:MiniJavaParser.Err_lparent_closingContext): pass # Enter a parse tree produced by MiniJavaParser#expr_this. def enterExpr_this(self, ctx:MiniJavaParser.Expr_thisContext): pass # Exit a parse tree produced by MiniJavaParser#expr_this. def exitExpr_this(self, ctx:MiniJavaParser.Expr_thisContext): pass # Enter a parse tree produced by MiniJavaParser#err_many_lparents. def enterErr_many_lparents(self, ctx:MiniJavaParser.Err_many_lparentsContext): pass # Exit a parse tree produced by MiniJavaParser#err_many_lparents. def exitErr_many_lparents(self, ctx:MiniJavaParser.Err_many_lparentsContext): pass # Enter a parse tree produced by MiniJavaParser#expr_op_multi. def enterExpr_op_multi(self, ctx:MiniJavaParser.Expr_op_multiContext): pass # Exit a parse tree produced by MiniJavaParser#expr_op_multi. def exitExpr_op_multi(self, ctx:MiniJavaParser.Expr_op_multiContext): pass # Enter a parse tree produced by MiniJavaParser#expr_bool. def enterExpr_bool(self, ctx:MiniJavaParser.Expr_boolContext): pass # Exit a parse tree produced by MiniJavaParser#expr_bool. def exitExpr_bool(self, ctx:MiniJavaParser.Expr_boolContext): pass # Enter a parse tree produced by MiniJavaParser#expr_length. def enterExpr_length(self, ctx:MiniJavaParser.Expr_lengthContext): pass # Exit a parse tree produced by MiniJavaParser#expr_length. def exitExpr_length(self, ctx:MiniJavaParser.Expr_lengthContext): pass # Enter a parse tree produced by MiniJavaParser#err_rparent_closing. def enterErr_rparent_closing(self, ctx:MiniJavaParser.Err_rparent_closingContext): pass # Exit a parse tree produced by MiniJavaParser#err_rparent_closing. def exitErr_rparent_closing(self, ctx:MiniJavaParser.Err_rparent_closingContext): pass # Enter a parse tree produced by MiniJavaParser#expr_op_and. def enterExpr_op_and(self, ctx:MiniJavaParser.Expr_op_andContext): pass # Exit a parse tree produced by MiniJavaParser#expr_op_and. def exitExpr_op_and(self, ctx:MiniJavaParser.Expr_op_andContext): pass # Enter a parse tree produced by MiniJavaParser#expr_lrparents. def enterExpr_lrparents(self, ctx:MiniJavaParser.Expr_lrparentsContext): pass # Exit a parse tree produced by MiniJavaParser#expr_lrparents. def exitExpr_lrparents(self, ctx:MiniJavaParser.Expr_lrparentsContext): pass # Enter a parse tree produced by MiniJavaParser#err_many_rparents. def enterErr_many_rparents(self, ctx:MiniJavaParser.Err_many_rparentsContext): pass # Exit a parse tree produced by MiniJavaParser#err_many_rparents. def exitErr_many_rparents(self, ctx:MiniJavaParser.Err_many_rparentsContext): pass # Enter a parse tree produced by MiniJavaParser#expr_array. def enterExpr_array(self, ctx:MiniJavaParser.Expr_arrayContext): pass # Exit a parse tree produced by MiniJavaParser#expr_array. def exitExpr_array(self, ctx:MiniJavaParser.Expr_arrayContext): pass # Enter a parse tree produced by MiniJavaParser#expr_int. def enterExpr_int(self, ctx:MiniJavaParser.Expr_intContext): pass # Exit a parse tree produced by MiniJavaParser#expr_int. def exitExpr_int(self, ctx:MiniJavaParser.Expr_intContext): pass # Enter a parse tree produced by MiniJavaParser#expr_int_array. def enterExpr_int_array(self, ctx:MiniJavaParser.Expr_int_arrayContext): pass # Exit a parse tree produced by MiniJavaParser#expr_int_array. def exitExpr_int_array(self, ctx:MiniJavaParser.Expr_int_arrayContext): pass # Enter a parse tree produced by MiniJavaParser#expr_op_minus. def enterExpr_op_minus(self, ctx:MiniJavaParser.Expr_op_minusContext): pass # Exit a parse tree produced by MiniJavaParser#expr_op_minus. def exitExpr_op_minus(self, ctx:MiniJavaParser.Expr_op_minusContext): pass # Enter a parse tree produced by MiniJavaParser#expr_op_plus. def enterExpr_op_plus(self, ctx:MiniJavaParser.Expr_op_plusContext): pass # Exit a parse tree produced by MiniJavaParser#expr_op_plus. def exitExpr_op_plus(self, ctx:MiniJavaParser.Expr_op_plusContext): pass # Enter a parse tree produced by MiniJavaParser#expr_new_array. def enterExpr_new_array(self, ctx:MiniJavaParser.Expr_new_arrayContext): pass # Exit a parse tree produced by MiniJavaParser#expr_new_array. def exitExpr_new_array(self, ctx:MiniJavaParser.Expr_new_arrayContext): pass # Enter a parse tree produced by MiniJavaParser#expr_op_less. def enterExpr_op_less(self, ctx:MiniJavaParser.Expr_op_lessContext): pass # Exit a parse tree produced by MiniJavaParser#expr_op_less. def exitExpr_op_less(self, ctx:MiniJavaParser.Expr_op_lessContext): pass # Enter a parse tree produced by MiniJavaParser#err_miss_LHS. def enterErr_miss_LHS(self, ctx:MiniJavaParser.Err_miss_LHSContext): pass # Exit a parse tree produced by MiniJavaParser#err_miss_LHS. def exitErr_miss_LHS(self, ctx:MiniJavaParser.Err_miss_LHSContext): pass # Enter a parse tree produced by MiniJavaParser#expr_method_calling. def enterExpr_method_calling(self, ctx:MiniJavaParser.Expr_method_callingContext): pass # Exit a parse tree produced by MiniJavaParser#expr_method_calling. def exitExpr_method_calling(self, ctx:MiniJavaParser.Expr_method_callingContext): pass # Enter a parse tree produced by MiniJavaParser#expr_not. def enterExpr_not(self, ctx:MiniJavaParser.Expr_notContext): pass # Exit a parse tree produced by MiniJavaParser#expr_not. def exitExpr_not(self, ctx:MiniJavaParser.Expr_notContext): pass # Enter a parse tree produced by MiniJavaParser#expr_id. def enterExpr_id(self, ctx:MiniJavaParser.Expr_idContext): pass # Exit a parse tree produced by MiniJavaParser#expr_id. def exitExpr_id(self, ctx:MiniJavaParser.Expr_idContext): pass

33.615142

86

0.747654

1,341

10,656

5.729306

0.085757

0.053885

0.089809

0.161656

0.894442

0.86789

0.863465

0.703241

0.664194

0.271899

0

0.000582

0.193412

10,656

316

87

33.721519

0.89331

0.383352

0

0.478873

1

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0.000156

0

1

0.478873

false

0.478873

0.021127

0

0.507042

0.014085

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null

0

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0

null

0

1

0

1

0

1

0

9

bb7389b9a85690df40129293a98c4485cec8a41e

5,940

py

Python

tests/orbit/models/test_ktrlite.py

pochoi/orbit

2d5728ccb032a28e4f8cef3dd40b85d2f0d90e35

[ "Apache-2.0" ]

1

2021-08-17T06:52:43.000Z

tests/orbit/models/test_ktrlite.py

pochoi/orbit

2d5728ccb032a28e4f8cef3dd40b85d2f0d90e35

[ "Apache-2.0" ]

null

tests/orbit/models/test_ktrlite.py

pochoi/orbit

2d5728ccb032a28e4f8cef3dd40b85d2f0d90e35

[ "Apache-2.0" ]

null

import pytest import numpy as np import pandas as pd from orbit.estimators.stan_estimator import StanEstimatorMAP from orbit.models.ktrlite import BaseKTRLite, KTRLiteMAP from orbit.diagnostics.metrics import smape @pytest.mark.parametrize("estimator_type", [StanEstimatorMAP]) def test_ktrlite_single_seas(make_daily_data, estimator_type): train_df, test_df, coef = make_daily_data ktrlite = KTRLiteMAP( response_col='response', date_col='date', seasonality=[365.25], seasonality_fs_order=[5], estimator_type=estimator_type ) ktrlite.fit(train_df) predict_df = ktrlite.predict(test_df) expected_columns = ['date', 'prediction_5', 'prediction', 'prediction_95'] expected_shape = (364, len(expected_columns)) expected_num_parameters = 6 assert predict_df.shape == expected_shape assert predict_df.columns.tolist() == expected_columns assert len(ktrlite._posterior_samples) == expected_num_parameters assert smape(test_df['response'].values, predict_df['prediction'].values) <= 0.5 @pytest.mark.parametrize("estimator_type", [StanEstimatorMAP]) def test_ktrlite_dual_seas(make_daily_data, estimator_type): train_df, test_df, coef = make_daily_data ktrlite = KTRLiteMAP( response_col='response', date_col='date', seasonality=[7, 365.25], seasonality_fs_order=[2, 5], estimator_type=estimator_type ) ktrlite.fit(train_df) predict_df = ktrlite.predict(test_df) expected_columns = ['date', 'prediction_5', 'prediction', 'prediction_95'] expected_shape = (364, len(expected_columns)) expected_num_parameters = 6 assert predict_df.shape == expected_shape assert predict_df.columns.tolist() == expected_columns assert len(ktrlite._posterior_samples) == expected_num_parameters assert smape(test_df['response'].values, predict_df['prediction'].values) <= 0.5 @pytest.mark.parametrize("level_knot_dates", [pd.date_range(start='2016-03-01', end='2019-01-01', freq='3M'), pd.date_range(start='2016-03-01', end='2019-01-01', freq='6M')]) def test_ktrlite_level_knot_dates(make_daily_data, level_knot_dates): train_df, test_df, coef = make_daily_data ktrlite = KTRLiteMAP( response_col='response', date_col='date', seasonality=[7, 365.25], seasonality_fs_order=[2, 5], level_knot_dates=level_knot_dates, estimator_type=StanEstimatorMAP ) ktrlite.fit(train_df) predict_df = ktrlite.predict(test_df) expected_columns = ['date', 'prediction_5', 'prediction', 'prediction_95'] expected_shape = (364, len(expected_columns)) expected_num_parameters = 6 assert predict_df.shape == expected_shape assert predict_df.columns.tolist() == expected_columns assert len(ktrlite._posterior_samples) == expected_num_parameters assert smape(test_df['response'].values, predict_df['prediction'].values) <= 0.5 @pytest.mark.parametrize("level_knot_length", [90, 120]) def test_ktrlite_level_knot_distance(make_daily_data, level_knot_length): train_df, test_df, coef = make_daily_data ktrlite = KTRLiteMAP( response_col='response', date_col='date', seasonality=[7, 365.25], seasonality_fs_order=[2, 5], level_knot_length=level_knot_length, estimator_type=StanEstimatorMAP ) ktrlite.fit(train_df) predict_df = ktrlite.predict(test_df) expected_columns = ['date', 'prediction_5', 'prediction', 'prediction_95'] expected_shape = (364, len(expected_columns)) expected_num_parameters = 6 assert predict_df.shape == expected_shape assert predict_df.columns.tolist() == expected_columns assert len(ktrlite._posterior_samples) == expected_num_parameters assert smape(test_df['response'].values, predict_df['prediction'].values) <= 0.5 @pytest.mark.parametrize("coefficients_knot_length", [90, 120]) def test_ktrlite_level_knot_distance(make_daily_data, coefficients_knot_length): train_df, test_df, coef = make_daily_data ktrlite = KTRLiteMAP( response_col='response', date_col='date', seasonality=[7, 365.25], seasonality_fs_order=[2, 5], coefficients_knot_length=coefficients_knot_length, estimator_type=StanEstimatorMAP ) ktrlite.fit(train_df) predict_df = ktrlite.predict(test_df) expected_columns = ['date', 'prediction_5', 'prediction', 'prediction_95'] expected_shape = (364, len(expected_columns)) expected_num_parameters = 6 assert predict_df.shape == expected_shape assert predict_df.columns.tolist() == expected_columns assert len(ktrlite._posterior_samples) == expected_num_parameters assert smape(test_df['response'].values, predict_df['prediction'].values) <= 0.5 def test_ktrlite_predict_decompose(make_daily_data): train_df, test_df, coef = make_daily_data ktrlite = KTRLiteMAP( response_col='response', date_col='date', seasonality=[7, 365.25], seasonality_fs_order=[2, 5], estimator_type=StanEstimatorMAP ) ktrlite.fit(train_df) predict_df = ktrlite.predict(test_df, decompose=True) expected_columns = ['date', 'prediction_5', 'prediction', 'prediction_95', 'trend_5', 'trend', 'trend_95', 'seasonality_7_5', 'seasonality_7', 'seasonality_7_95', 'seasonality_365.25_5', 'seasonality_365.25', 'seasonality_365.25_95'] expected_shape = (364, len(expected_columns)) expected_num_parameters = 6 assert predict_df.shape == expected_shape assert predict_df.columns.tolist() == expected_columns assert len(ktrlite._posterior_samples) == expected_num_parameters assert smape(test_df['response'].values, predict_df['prediction'].values) <= 0.5

36.219512

110

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732

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0

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5,940

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0

null

0

1

0

1

0

null

0

7

bb7b4927ceac387e33925c9d21eb61fc8eb64933

104

py

Python

plugin/sqlite/__init__.py

lisugar/ray_build_tools

a304c8fc30ce9f61cbdc566d8dc193945f14883d

[ "MIT" ]

null

plugin/sqlite/__init__.py

lisugar/ray_build_tools

a304c8fc30ce9f61cbdc566d8dc193945f14883d

[ "MIT" ]

null

plugin/sqlite/__init__.py

lisugar/ray_build_tools

a304c8fc30ce9f61cbdc566d8dc193945f14883d

[ "MIT" ]

null

from build_tools.plugin.sqlite import executor def get_plugin_class(): return executor.SqlitePlugin

26

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104

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0.115385

104

4

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0

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null

0

1

0

null

0

1

0

1

0

7

bb8123ad7bdfebe54f3ce6fa20aa97cc971458ad

15,977

py

Python

tests/test_api/test_user.py

cipherboy/modern-paste

ecc4168bda2a9e5981d495f9e0538258d9f727a2

[ "MIT" ]

271

2016-02-03T03:09:25.000Z

2021-12-12T02:21:03.000Z

tests/test_api/test_user.py

cipherboy/modern-paste

ecc4168bda2a9e5981d495f9e0538258d9f727a2

[ "MIT" ]

65

2016-02-03T07:20:16.000Z

2019-01-09T00:10:10.000Z

tests/test_api/test_user.py

cipherboy/modern-paste

ecc4168bda2a9e5981d495f9e0538258d9f727a2

[ "MIT" ]

64

2016-02-03T17:08:32.000Z

2021-05-23T08:48:22.000Z

import json import mock from sqlalchemy.exc import SQLAlchemyError import config import constants.api import database.user import util.testing from uri.user import * from uri.authentication import * class TestPaste(util.testing.DatabaseTestCase): def test_create_new_user_invalid_data(self): resp = self.client.post( UserCreateURI.uri(), data=json.dumps({}), content_type='application/json', ) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE, json.loads(resp.data)) def test_create_new_user_invalid_username(self): util.testing.UserFactory.generate(username='username') resp = self.client.post( UserCreateURI.uri(), data=json.dumps({ 'username': 'username', 'password': 'password', }), content_type='application/json', ) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE_CODE, resp.status_code) self.assertEqual('username_not_available_failure', json.loads(resp.data)['failure']) def test_create_new_user_invalid_email(self): resp = self.client.post( UserCreateURI.uri(), data=json.dumps({ 'username': 'username', 'password': 'password', 'email': 'invalid', }), content_type='application/json', ) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE_CODE, resp.status_code) self.assertEqual('invalid_email_failure', json.loads(resp.data)['failure']) def test_create_new_user_disabled(self): config.ENABLE_USER_REGISTRATION = False resp = self.client.post( UserCreateURI.uri(), data=json.dumps({ 'username': 'username', 'password': 'password', }), content_type='application/json', ) self.assertEqual(constants.api.USER_REGISTRATION_DISABLED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.USER_REGISTRATION_DISABLED_FAILURE, json.loads(resp.data)) def test_create_new_user_valid(self): resp = self.client.post( UserCreateURI.uri(), data=json.dumps({ 'username': 'username', 'password': 'password', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) resp = self.client.post( UserCreateURI.uri(), data=json.dumps({ 'username': 'other_username', 'password': 'password', 'name': 'name', 'email': 'test@test.com', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) def test_create_new_user_server_error(self): with mock.patch.object(database.user, 'create_new_user', side_effect=SQLAlchemyError): resp = self.client.post( UserCreateURI.uri(), data=json.dumps({ 'username': 'username', 'password': 'password', }), content_type='application/json', ) self.assertEqual(constants.api.UNDEFINED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.UNDEFINED_FAILURE, json.loads(resp.data)) def test_update_user_details(self): user = util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserUpdateDetailsURI.uri(), data=json.dumps({ 'name': 'name', 'email': 'email@email.com', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertEqual('name', database.user.get_user_by_id(user.user_id).name) self.assertEqual('email@email.com', database.user.get_user_by_id(user.user_id).email) self.assertTrue(database.user.authenticate_user('username', 'password')) def test_update_user_password(self): util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserUpdateDetailsURI.uri(), data=json.dumps({ 'current_password': 'password', 'new_password': 'new_password', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertFalse(database.user.authenticate_user('username', 'password')) self.assertTrue(database.user.authenticate_user('username', 'new_password')) def test_update_user_details_invalid_email(self): util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserUpdateDetailsURI.uri(), data=json.dumps({ 'name': 'name', 'email': 'email', }), content_type='application/json', ) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE_CODE, resp.status_code) self.assertEqual('invalid_email_failure', json.loads(resp.data)['failure']) def test_update_user_details_wrong_current_password(self): util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserUpdateDetailsURI.uri(), data=json.dumps({ 'current_password': 'invalid', 'new_password': 'new_password', }), content_type='application/json', ) self.assertEqual(constants.api.AUTH_FAILURE_CODE, resp.status_code) self.assertTrue(database.user.authenticate_user('username', 'password')) self.assertFalse(database.user.authenticate_user('username', 'invalid')) def test_remove_user_details(self): user = util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserUpdateDetailsURI.uri(), data=json.dumps({ 'name': None, 'email': None, 'new_password': None, }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertIsNone(database.user.get_user_by_id(user.user_id).name) self.assertIsNone(database.user.get_user_by_id(user.user_id).email) self.assertTrue(database.user.authenticate_user('username', 'password')) def test_update_user_details_server_error(self): with mock.patch.object(database.user, 'update_user_details', side_effect=SQLAlchemyError): util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserUpdateDetailsURI.uri(), data=json.dumps({ 'name': None, 'email': None, 'new_password': None, }), content_type='application/json', ) self.assertEqual(constants.api.UNDEFINED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.UNDEFINED_FAILURE, json.loads(resp.data)) def test_deactivate_user_not_logged_in(self): util.testing.UserFactory.generate() resp = self.client.post( UserDeactivateURI.uri(), data=json.dumps({}), content_type='application/json', ) self.assertEqual(constants.api.AUTH_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.AUTH_FAILURE, json.loads(resp.data)) def test_deactivate_user_logged_in(self): user = util.testing.UserFactory.generate(username='username', password='password') resp = self.client.post( LoginUserURI.uri(), data=json.dumps({ 'username': 'username', 'password': 'password', }), content_type='application/json', ) self.assertEqual(resp.status_code, constants.api.SUCCESS_CODE) resp = self.client.post( UserDeactivateURI.uri(), data=json.dumps({}), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertFalse(database.user.get_user_by_id(user.user_id).is_active) def test_deactivate_user_api_key(self): user = util.testing.UserFactory.generate() resp = self.client.post( UserDeactivateURI.uri(), data=json.dumps({ 'api_key': 'invalid', }), content_type='application/json', ) self.assertEqual(constants.api.AUTH_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.AUTH_FAILURE, json.loads(resp.data)) resp = self.client.post( UserDeactivateURI.uri(), data=json.dumps({ 'api_key': user.api_key, }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertFalse(database.user.get_user_by_id(user.user_id).is_active) def test_deactivate_user_server_error(self): with mock.patch.object(database.user, 'deactivate_user', side_effect=SQLAlchemyError): user = util.testing.UserFactory.generate() resp = self.client.post( UserDeactivateURI.uri(), data=json.dumps({ 'api_key': user.api_key, }), content_type='application/json', ) self.assertEqual(constants.api.UNDEFINED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.UNDEFINED_FAILURE, json.loads(resp.data)) def test_api_key_regenerate(self): old_api_key = util.testing.UserFactory.generate(username='username', password='password').api_key self.api_login_user('username', 'password') resp = self.client.post( UserAPIKeyRegenerateURI.uri(), data=json.dumps({}), content_type='application/json', ) new_key = json.loads(resp.data)['api_key'] self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertEqual(64, len(new_key)) self.assertNotEqual(old_api_key, new_key) def test_api_key_regenerate_server_error(self): with mock.patch.object(database.user, 'generate_new_api_key', side_effect=SQLAlchemyError): util.testing.UserFactory.generate(username='username', password='password') self.api_login_user('username', 'password') resp = self.client.post( UserAPIKeyRegenerateURI.uri(), data=json.dumps({}), content_type='application/json', ) self.assertEqual(constants.api.UNDEFINED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.UNDEFINED_FAILURE, json.loads(resp.data)) def test_check_username_availability_invalid_data(self): resp = self.client.post( CheckUsernameAvailabilityURI.uri(), data=json.dumps({}), content_type='application/json', ) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE, json.loads(resp.data)) def test_check_username_availability_available(self): resp = self.client.post( CheckUsernameAvailabilityURI.uri(), data=json.dumps({ 'username': 'username', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertTrue(json.loads(resp.data)['is_available']) def test_check_username_availability_unavailable(self): util.testing.UserFactory.generate(username='username') resp = self.client.post( CheckUsernameAvailabilityURI.uri(), data=json.dumps({ 'username': 'username', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertFalse(json.loads(resp.data)['is_available']) # Case-insensitivity resp = self.client.post( CheckUsernameAvailabilityURI.uri(), data=json.dumps({ 'username': 'useRNaME', }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertFalse(json.loads(resp.data)['is_available']) def test_check_username_availability_server_error(self): with mock.patch.object(database.user, 'is_username_available', side_effect=SQLAlchemyError): resp = self.client.post( CheckUsernameAvailabilityURI.uri(), data=json.dumps({ 'username': 'username', }), content_type='application/json', ) self.assertEqual(constants.api.UNDEFINED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.UNDEFINED_FAILURE, json.loads(resp.data)) def test_validate_email_address_invalid_data(self): resp = self.client.post( ValidateEmailAddressURI.uri(), data=json.dumps({}), content_type='application/json', ) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.INCOMPLETE_PARAMS_FAILURE, json.loads(resp.data)) def test_validate_email_address_valid(self): for email in ['test@test.com', 'test@test.co.uk', 'test.test.test@test.a.b.s']: resp = self.client.post( ValidateEmailAddressURI.uri(), data=json.dumps({ 'email': email, }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertTrue(json.loads(resp.data)['is_valid']) def test_validate_email_address_invalid(self): for email in ['invalid', 'test@', 'test@', '@test.com', 'spaces in@address.com']: resp = self.client.post( ValidateEmailAddressURI.uri(), data=json.dumps({ 'email': email, }), content_type='application/json', ) self.assertEqual(constants.api.SUCCESS_CODE, resp.status_code) self.assertFalse(json.loads(resp.data)['is_valid']) def test_validate_email_address_server_error(self): with mock.patch.object(database.user, 'is_email_address_valid', side_effect=SQLAlchemyError): resp = self.client.post( ValidateEmailAddressURI.uri(), data=json.dumps({ 'email': 'test@test.com', }), content_type='application/json', ) self.assertEqual(constants.api.UNDEFINED_FAILURE_CODE, resp.status_code) self.assertEqual(constants.api.UNDEFINED_FAILURE, json.loads(resp.data))

42.155673

105

0.612881

1,620

15,977

5.828395

0.068519

0.076255

0.104215

0.117242

0.910718

0.897691

0.888795

0.862847

0.845478

0.820695

0

0.000172

0.270702

15,977

378

106

42.267196

0.810161

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false

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1

0

1

0

null

0

1

0

8

bbe08c1cf2489a7c1206a95bdf8d590d6c368a31

5,675

py

Python

914.x-of-a-kind-in-a-deck-of-cards.py

windard/leeeeee

0107a5f95746592ca4fe78d2b5875cf65b1910e7

[ "MIT" ]

null

914.x-of-a-kind-in-a-deck-of-cards.py

windard/leeeeee

0107a5f95746592ca4fe78d2b5875cf65b1910e7

[ "MIT" ]

null

914.x-of-a-kind-in-a-deck-of-cards.py

windard/leeeeee

0107a5f95746592ca4fe78d2b5875cf65b1910e7

[ "MIT" ]

null

# coding=utf-8 # # @lc app=leetcode id=914 lang=python # # [914] X of a Kind in a Deck of Cards # # https://leetcode.com/problems/x-of-a-kind-in-a-deck-of-cards/description/ # # algorithms # Easy (33.91%) # Likes: 256 # Dislikes: 64 # Total Accepted: 21.8K # Total Submissions: 64.4K # Testcase Example: '[1,2,3,4,4,3,2,1]' # # In a deck of cards, each card has an integer written on it. # # Return true if and only if you can choose X >= 2 such that it is possible to # split the entire deck into 1 or more groups of cards, where: # # # Each group has exactly X cards. # All the cards in each group have the same integer. # # # # # Example 1: # # # Input: [1,2,3,4,4,3,2,1] # Output: true # Explanation: Possible partition [1,1],[2,2],[3,3],[4,4] # # # # Example 2: # # # Input: [1,1,1,2,2,2,3,3] # Output: false # Explanation: No possible partition. # # # # Example 3: # # # Input: [1] # Output: false # Explanation: No possible partition. # # # # Example 4: # # # Input: [1,1] # Output: true # Explanation: Possible partition [1,1] # # # # Example 5: # # # Input: [1,1,2,2,2,2] # Output: true # Explanation: Possible partition [1,1],[2,2],[2,2] # # # # # # # # Note: # # # 1 <= deck.length <= 10000 # 0 <= deck[i] < 10000 # # # # # # # # # # # # # class Solution(object): def _hasGroupsSizeX(self, deck): """ :type deck: List[int] :rtype: bool """ # Wrong Answer # [1,1,2,2,2,2] # 可以是最小因子的倍数 data = {} for d in deck: data[d] = data.get(d, 0) + 1 return len(set(data.values())) == 1 and data.values()[0] > 1 def __hasGroupsSizeX(self, deck): """ :type deck: List[int] :rtype: bool """ # Still Wrong # [1,1,1,1,2,2,2,2,2,2] # 可以有最小公因数 # too complex data = {} for d in deck: data[d] = data.get(d, 0) + 1 min_factor = None values = data.values() if not values: return False if values: if min(values) < 2: return False for i in range(len(values)-1): factor = self.gcd(values[i], values[i+1]) if factor < 2: return False if not min_factor: min_factor = factor else: if min_factor < factor: if factor % min_factor: return False elif min_factor > factor: if min_factor % factor: return False else: min_factor = factor return True def hasGroupsSizeX(self, deck): """ :type deck: List[int] :rtype: bool """ data = {} for d in deck: data[d] = data.get(d, 0) + 1 min_value = min(data.values()) for value in data.values(): if self.gcd(value, min_value) < 2: return False return True def gcd(self, a, b): while b: a, b = b, a % b return a # if __name__ == '__main__': # s = Solution() # print s.hasGroupsSizeX([0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,8,8,8,8,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,11,11,11,11,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,13,13,13,13,13,13,13,13,14,14,14,14,14,14,14,14,15,15,15,15,15,15,15,15,15,15,15,15,16,16,16,16,17,17,17,17,18,18,18,18,19,19,19,19]) # print s.hasGroupsSizeX([1,2,3,4,4,3,2,1]) # print s.hasGroupsSizeX([1,1,2,2,2,2]) # print s.hasGroupsSizeX([2,2]) # print s.hasGroupsSizeX([1]) # print s.hasGroupsSizeX([1,1,1,1,2,2,2,2,2,2]) # print s.gcd(1, 3) # print s.gcd(2, 3) # print s.gcd(3, 6) # print s.gcd(6, 8) # print s.gcd(6, 6)

30.842391

2,123

0.506256

1,497

5,675

1.905144

0.09352

0.329593

0.482819

0.638149

0.605891

0.587658

0.559958

0.512272

0.489481

0.4446

0

0.283799

0.224493

5,675

183

2,124

31.010929

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7

a5727c78c1aef8d3315ce7b20e7a57a2fa112b3e

183

py

Python

tests/sat/Models/s3-10.UNSAT.dimacs.test.py

bernardocuteri/wasp

05c8f961776dbdbf7afbf905ee00fc262eba51ad

[ "Apache-2.0" ]

19

2015-12-03T08:53:45.000Z

2022-03-31T02:09:43.000Z

tests/sat/Models/s3-10.UNSAT.dimacs.test.py

bernardocuteri/wasp

05c8f961776dbdbf7afbf905ee00fc262eba51ad

[ "Apache-2.0" ]

80

2017-11-25T07:57:32.000Z

2018-06-10T19:03:30.000Z

tests/sat/Models/s3-10.UNSAT.dimacs.test.py

bernardocuteri/wasp

05c8f961776dbdbf7afbf905ee00fc262eba51ad

[ "Apache-2.0" ]

6

2015-01-15T07:51:48.000Z

2020-06-18T14:47:48.000Z

input = """ p cnf 4 14 -4 2 1 0 -2 -3 4 0 1 -2 -4 0 -2 3 -4 0 1 2 3 0 1 2 -3 0 1 -2 3 0 1 -2 -3 0 -1 2 3 0 -1 2 -3 0 -1 -2 3 0 -1 -2 -3 0 1 2 4 0 -2 3 4 0 """ output = """ unsat """

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0.431694

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183

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0.379747

0.405063

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1

0

1

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null

0

7

a57c6ff9520a6d273a8f6334abeee2710d672394

136

py

Python

src/main/resources/docs/tests/E1304.py

h314to/codacy-pylint

9d31567db6188e1b31ce0e1567998f64946502df

[ "Apache-2.0" ]

null

src/main/resources/docs/tests/E1304.py

h314to/codacy-pylint

9d31567db6188e1b31ce0e1567998f64946502df

[ "Apache-2.0" ]

null

src/main/resources/docs/tests/E1304.py

h314to/codacy-pylint

9d31567db6188e1b31ce0e1567998f64946502df

[ "Apache-2.0" ]

null

##Patterns: E1304 ##Err: E1304 print "%(arg1)s %(arg2)s" % {"arg1":"wrong"} print "%(arg1)s %(arg2)s" % {"arg1":"this is", "arg2":"ok"}

27.2

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0.558824

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136

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0.263158

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null

0

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7

3c5710a59ac5f2263e31311a973afded6acdaaa6

86

py

Python

create_user.py

abdelinho24/flask-shop

ef030e6f2f015c74aa0bb00eccd6c88787606290

[ "BSD-2-Clause" ]

1

2015-10-10T01:21:58.000Z

create_user.py

abdelinho24/flask-shop

ef030e6f2f015c74aa0bb00eccd6c88787606290

[ "BSD-2-Clause" ]

null

create_user.py

abdelinho24/flask-shop

ef030e6f2f015c74aa0bb00eccd6c88787606290

[ "BSD-2-Clause" ]

1

2019-02-22T18:31:45.000Z

from flask_shop.flask_shop import app, bcrypt from flask_shop.models import User, db

21.5

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0.382353

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null

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7

3c6570bbc51fa5338331adda338511884d4c7d8e

7,149

py

Python

chaosLib/litmus/pod_delete/lib/pod_delete.py

prateekdegaons1991/experiment-loadtest

b53c70fac5b2f7d37df77844b26f79741c74c1b6

[ "Apache-2.0" ]

8

2020-04-17T06:34:30.000Z

2021-12-18T10:54:50.000Z

chaosLib/litmus/pod_delete/lib/pod_delete.py

oumkale/test-python

1f3d3e42ffbe1bf5ed9df8a0c6038e50129b2c4d

[ "Apache-2.0" ]

15

2020-04-18T06:01:53.000Z

2022-02-15T08:56:25.000Z

chaosLib/litmus/pod_delete/lib/pod_delete.py

oumkale/test-python

1f3d3e42ffbe1bf5ed9df8a0c6038e50129b2c4d

[ "Apache-2.0" ]

12

2020-04-17T05:14:27.000Z

2022-03-29T19:24:20.000Z

import pkg.types.types as types import pkg.events.events as events import logging import pkg.utils.common.common as common import pkg.utils.common.pods as pods from datetime import datetime import pkg.status.application as status import pkg.maths.maths as maths #PreparePodDelete contains the prepration steps before chaos injection def PreparePodDelete(experimentsDetails , resultDetails, eventsDetails, chaosDetails, clients): #Waiting for the ramp time before chaos injection if experimentsDetails.RampTime != 0 : logging.info("[Ramp]: Waiting for the %s ramp time before injecting chaos",experimentsDetails.RampTime) common.WaitForDuration(experimentsDetails.RampTime) # mode for chaos injection if experimentsDetails.Sequence.lower() == "serial": err = injectChaosInSerialMode(experimentsDetails, chaosDetails, eventsDetails, resultDetails, clients) if err != None: return err elif experimentsDetails.Sequence.lower() == "parallel": err = injectChaosInParallelMode(experimentsDetails, chaosDetails, eventsDetails, resultDetails, clients) if err != None: return err else: return ValueError("{} sequence is not supported".format(experimentsDetails.Sequence)) #Waiting for the ramp time after chaos injection if experimentsDetails.RampTime != 0 : logging.info("[Ramp]: Waiting for the %s ramp time after injecting chaos",experimentsDetails.RampTime) common.WaitForDuration(experimentsDetails.RampTime) return None # injectChaosInSerialMode delete the target application pods serial mode(one by one) def injectChaosInSerialMode(experimentsDetails , chaosDetails , eventsDetails , resultDetails, clients): #Initialising GracePeriod GracePeriod = 0 #ChaosStartTimeStamp contains the start timestamp, when the chaos injection begin ChaosStartTimeStamp = datetime.now() duration = (datetime.now() - ChaosStartTimeStamp).seconds while duration < experimentsDetails.ChaosDuration: # Get the target pod details for the chaos execution # if the target pod is not defined it will derive the random target pod list using pod affected percentage if experimentsDetails.TargetPods == "" and chaosDetails.AppDetail.Label == "" : return ValueError("Please provide one of the appLabel or TARGET_PODS") targetPodList, err = pods.Pods().GetPodList(experimentsDetails.TargetPods, experimentsDetails.PodsAffectedPerc, chaosDetails, clients) if err != None: return err podNames = [] for pod in targetPodList.items: podNames.append(pod.metadata.name) logging.info("[Info]: Target pods list, %s", podNames) if experimentsDetails.EngineName != "" : msg = "Injecting " + experimentsDetails.ExperimentName + " chaos on application pod" types.SetEngineEventAttributes(eventsDetails, types.ChaosInject, msg, "Normal", chaosDetails) events.GenerateEvents(eventsDetails, chaosDetails, "ChaosEngine", clients) #Deleting the application pod for pod in targetPodList.items : logging.info("[Info]: Killing the following pods, PodName : %s", pod.metadata.name) try: if experimentsDetails.Force: clients.clientCoreV1.delete_namespaced_pod(pod.metadata.name, experimentsDetails.AppNS, grace_period_seconds=GracePeriod) else: clients.clientCoreV1.delete_namespaced_pod(pod.metadata.name, experimentsDetails.AppNS) except Exception as exp: return exp if chaosDetails.Randomness: err = common.RandomInterval(experimentsDetails.ChaosInterval) if err != None: return err else: #Waiting for the chaos interval after chaos injection if experimentsDetails.ChaosInterval != "": logging.info("[Wait]: Wait for the chaos interval %s",(experimentsDetails.ChaosInterval)) waitTime = maths.atoi(experimentsDetails.ChaosInterval) common.WaitForDuration(waitTime) #Verify the status of pod after the chaos injection logging.info("[Status]: Verification for the recreation of application pod") err = status.Application().CheckApplicationStatus(experimentsDetails.AppNS, experimentsDetails.AppLabel, experimentsDetails.Timeout, experimentsDetails.Delay,clients) if err != None: return err duration = (datetime.now() - ChaosStartTimeStamp).seconds logging.info("[Completion]: %s chaos is done",(experimentsDetails.ExperimentName)) return None # injectChaosInParallelMode delete the target application pods in parallel mode (all at once) def injectChaosInParallelMode(experimentsDetails , chaosDetails , eventsDetails , resultDetails, clients): #Initialising GracePeriod GracePeriod = 0 #ChaosStartTimeStamp contains the start timestamp, when the chaos injection begin ChaosStartTimeStamp = datetime.now() duration = (datetime.now() - ChaosStartTimeStamp).seconds while duration < experimentsDetails.ChaosDuration: # Get the target pod details for the chaos execution # if the target pod is not defined it will derive the random target pod list using pod affected percentage if experimentsDetails.TargetPods == "" and chaosDetails.AppDetail.Label == "" : return ValueError("Please provide one of the appLabel or TARGET_PODS") targetPodList, err = pods.Pods().GetPodList(experimentsDetails.TargetPods, experimentsDetails.PodsAffectedPerc, chaosDetails, clients) if err != None: return err podNames = [] for pod in targetPodList.items: podNames.append(str(pod.metadata.name)) logging.info("[Info]: Target pods list for chaos, %s",(podNames)) if experimentsDetails.EngineName != "" : msg = "Injecting " + experimentsDetails.ExperimentName + " chaos on application pod" types.SetEngineEventAttributes(eventsDetails, types.ChaosInject, msg, "Normal", chaosDetails) events.GenerateEvents(eventsDetails, chaosDetails, "ChaosEngine",clients) #Deleting the application pod for pod in targetPodList.items: logging.info("[Info]: Killing the following pods, PodName : %s", pod.metadata.name) try: if experimentsDetails.Force: clients.clientCoreV1.delete_namespaced_pod(pod.metadata.name, experimentsDetails.AppNS, grace_period_seconds=GracePeriod) else: clients.clientCoreV1.delete_namespaced_pod(pod.metadata.name, experimentsDetails.AppNS) except Exception as err: return err if chaosDetails.Randomness: err = common.RandomInterval(experimentsDetails.ChaosInterval) if err != None: return err else: #Waiting for the chaos interval after chaos injection if experimentsDetails.ChaosInterval != "" : logging.info("[Wait]: Wait for the chaos interval %s", experimentsDetails.ChaosInterval) waitTime = maths.atoi(experimentsDetails.ChaosInterval) common.WaitForDuration(waitTime) #Verify the status of pod after the chaos injection logging.info("[Status]: Verification for the recreation of application pod") err = status.Application().CheckApplicationStatus(experimentsDetails.AppNS, experimentsDetails.AppLabel, experimentsDetails.Timeout, experimentsDetails.Delay, clients) if err != None: return err duration = (datetime.now() - ChaosStartTimeStamp).seconds logging.info("[Completion]: %s chaos is done",(experimentsDetails.ExperimentName)) return None

43.066265

169

0.773115

779

7,149

7.077022

0.18742

0.01306

0.021767

0.87339

0.853982

0.835843

0.804281

0.788319

0

0.001306

0.142957

7,149

165

170

43.327273

0.898482

0.160022

0

0.758929

0

0.13018

0

1

0.026786

false

0

0.071429

0

0.241071

0

null

0

1

0

1

0

null

0

7

5902687127ce3500229b5afdc67749d445fae75d

8,799

py

Python

funcChan.py

Lyle-zhang/kinetic_schemes

dc572bd1eedfddb871767573724cadddc57db76d

[ "MIT" ]

1

2021-12-27T11:14:58.000Z

funcChan.py

Lyle-zhang/kinetic_schemes

dc572bd1eedfddb871767573724cadddc57db76d

[ "MIT" ]

null

funcChan.py

Lyle-zhang/kinetic_schemes

dc572bd1eedfddb871767573724cadddc57db76d

[ "MIT" ]

1

2021-08-14T13:40:24.000Z

""" Functions based on Chan 1985 kinetic reaction scheme for biomass pyrolysis. Reactions evaluated at some temperature. Functions: chan1 - primary reactions only chan2 - primary reactions without moisture chan3 - primary and secondary reactions chan4 - primary and secondary reactions without moisture Reference: Chan, Kelbon, Krieger, 1985. Fuel, 64(11), pp.1505–1513. """ # Modules # ----------------------------------------------------------------------------- import numpy as np # Function - primary kinetic reactions from Table 2 # ----------------------------------------------------------------------------- def chan1(rhow, mc, T, dt, nt): """ rhow = wood density, kg/m^3 mc = moisture content, % T = temperature, K dt = time step, s nt = total number of time steps """ # vector for initial wood concentration, kg/m^3 pw = np.ones(nt)*rhow # vector for initial moisture content concentration, kg/m^3 pm = pw*(mc/100) # vectors to store product concentrations, kg/m^3 pg = np.zeros(nt) # gas pt = np.zeros(nt) # tar pc = np.zeros(nt) # char pv = np.zeros(nt) # water vapor R = 0.008314 # universal gas constant, kJ/mol*K # A = pre-factor (1/s) and E = activation energy (kJ/mol) A1 = 1.3e8; E1 = 140 # wood -> gas A2 = 2e8; E2 = 133 # wood -> tar A3 = 1.08e7; E3 = 121 # wood -> char A4 = 5.13e6; E4 = 87.9 # moisture -> water vapor # reaction rate constant for each reaction, 1/s K1 = A1 * np.exp(-E1 / (R * T)) # wood -> gas K2 = A2 * np.exp(-E2 / (R * T)) # wood -> tar K3 = A3 * np.exp(-E3 / (R * T)) # wood -> char K4 = A4 * np.exp(-E4 / (R * T)) # moisture -> water vapor # concentrations at each time step for each product, kg/m^3 # reaction rate as r, rho/s # concentration as density p, kg/m^3 for i in range(1, nt): rww = -(K1+K2+K3) * pw[i-1] # wood rate rwg = K1 * pw[i-1] # wood -> gas rate rwt = K2 * pw[i-1] # wood -> tar rate rwc = K3 * pw[i-1] # wood -> char rate rmw = K4 * pm[i-1] # moisture -> water vapor rate pw[i] = pw[i-1] + rww*dt # wood pg[i] = pg[i-1] + rwg*dt # gas pt[i] = pt[i-1] + rwt*dt # tar pc[i] = pc[i-1] + rwc*dt # char pm[i] = pm[i-1] - rmw*dt # moisture pv[i] = pv[i-1] + rmw*dt # water vapor # return the wood, gas, tar, char, moisture, water vapor concentrations # as a density, kg/m^3 return pw, pg, pt, pc, pm, pv # Function - primary kinetic reactions w/o moisture from Table 2 # ----------------------------------------------------------------------------- def chan2(rhow, T, dt, nt): """ rhow = wood density, kg/m^3 T = temperature, K dt = time step, s nt = total number of time steps """ # vector for initial wood concentration, kg/m^3 pw = np.ones(nt)*rhow # vectors to store product concentrations, kg/m^3 pg = np.zeros(nt) # gas pt = np.zeros(nt) # tar pc = np.zeros(nt) # char R = 0.008314 # universal gas constant, kJ/mol*K # A = pre-factor (1/s) and E = activation energy (kJ/mol) A1 = 1.3e8; E1 = 140 # wood -> gas A2 = 2e8; E2 = 133 # wood -> tar A3 = 1.08e7; E3 = 121 # wood -> char # reaction rate constant for each reaction, 1/s K1 = A1 * np.exp(-E1 / (R * T)) # wood -> gas K2 = A2 * np.exp(-E2 / (R * T)) # wood -> tar K3 = A3 * np.exp(-E3 / (R * T)) # wood -> char # concentrations at each time step for each product, kg/m^3 # reaction rate as r, rho/s # concentration as density p, kg/m^3 for i in range(1, nt): rww = -(K1+K2+K3) * pw[i-1] # wood rate rwg = K1 * pw[i-1] # wood -> gas rate rwt = K2 * pw[i-1] # wood -> tar rate rwc = K3 * pw[i-1] # wood -> char rate pw[i] = pw[i-1] + rww*dt # wood pg[i] = pg[i-1] + rwg*dt # gas pt[i] = pt[i-1] + rwt*dt # tar pc[i] = pc[i-1] + rwc*dt # char # return the wood, gas, tar, char, moisture, water vapor concentrations # as a density, kg/m^3 return pw, pg, pt, pc # Function - primary and secondary reactions from Table 2 # ----------------------------------------------------------------------------- def chan3(rhow, mc, T, dt, nt): """ rhow = wood density, kg/m^3 mc = moisture content, % T = temperature, K dt = time step, s nt = total number of time steps """ # vector for initial wood concentration, kg/m^3 pw = np.ones(nt)*rhow # vector for initial moisture content concentration, kg/m^3 pm = pw*(mc/100) # vectors to store product concentrations, kg/m^3 pg = np.zeros(nt) # gas pt = np.zeros(nt) # tar pc = np.zeros(nt) # char pv = np.zeros(nt) # water vapor R = 0.008314 # universal gas constant, kJ/mol*K # A = pre-factor (1/s) and E = activation energy (kJ/mol) A1 = 1.3e8; E1 = 140 # wood -> gas1 A2 = 2e8; E2 = 133 # wood -> tar1 A3 = 1.08e7; E3 = 121 # wood -> char A4 = 5.13e6; E4 = 87.9 # moisture -> water vapor A5 = 1.48e6; E5 = 144 # tar -> gas2 + tar2 # reaction rate constant for each reaction, 1/s K1 = A1 * np.exp(-E1 / (R * T)) # wood -> gas1 K2 = A2 * np.exp(-E2 / (R * T)) # wood -> tar1 K3 = A3 * np.exp(-E3 / (R * T)) # wood -> char K4 = A4 * np.exp(-E4 / (R * T)) # moisture -> water vapor K5 = A5 * np.exp(-E5 / (R * T)) # tar -> gas2 + tar2 # concentrations at each time step for each product, kg/m^3 # reaction rate as r, rho/s # concentration as density p, kg/m^3 for i in range(1, nt): rww = -(K1+K2+K3) * pw[i-1] # wood rate rwg = K1 * pw[i-1] # wood -> gas rate rwt = K2 * pw[i-1] # wood -> tar rate rwc = K3 * pw[i-1] # wood -> char rate rmw = K4 * pm[i-1] # moisture -> water vapor rate rtt = K5 * pt[i-1] # tar -> gas2 + tar2 rate pw[i] = pw[i-1] + rww*dt # wood pg[i] = pg[i-1] + (rwg + 0.9*rtt)*dt # gas pt[i] = pt[i-1] + (rwt + 0.1*rtt)*dt # tar pc[i] = pc[i-1] + rwc*dt # char pm[i] = pm[i-1] - rmw*dt # moisture pv[i] = pv[i-1] + rmw*dt # water vapor # return the wood, gas, tar, char, moisture, water vapor concentrations # as a density, kg/m^3 return pw, pg, pt, pc, pm, pv # Function - primary and secondary reactions w/o moisture from Table 2 # ----------------------------------------------------------------------------- def chan4(rhow, T, dt, nt): """ rhow = wood density, kg/m^3 T = temperature, K dt = time step, s nt = total number of time steps """ # vector for initial wood concentration, kg/m^3 pw = np.ones(nt)*rhow # vectors to store product concentrations, kg/m^3 pg = np.zeros(nt) # gas pt = np.zeros(nt) # tar pc = np.zeros(nt) # char R = 0.008314 # universal gas constant, kJ/mol*K # A = pre-factor (1/s) and E = activation energy (kJ/mol) A1 = 1.3e8; E1 = 140 # wood -> gas1 A2 = 2e8; E2 = 133 # wood -> tar1 A3 = 1.08e7; E3 = 121 # wood -> char A5 = 1.48e6; E5 = 144 # tar -> gas2 + tar2 # reaction rate constant for each reaction, 1/s K1 = A1 * np.exp(-E1 / (R * T)) # wood -> gas1 K2 = A2 * np.exp(-E2 / (R * T)) # wood -> tar1 K3 = A3 * np.exp(-E3 / (R * T)) # wood -> char K5 = A5 * np.exp(-E5 / (R * T)) # tar -> gas2 + tar2 # concentrations at each time step for each product, kg/m^3 # reaction rate as r, rho/s # concentration as density p, kg/m^3 for i in range(1, nt): rww = -(K1+K2+K3) * pw[i-1] # wood rate rwg = K1 * pw[i-1] # wood -> gas rate rwt = K2 * pw[i-1] # wood -> tar rate rwc = K3 * pw[i-1] # wood -> char rate rtt = K5 * pt[i-1] # tar -> gas2 + tar2 rate pw[i] = pw[i-1] + rww*dt # wood pg[i] = pg[i-1] + (rwg + 0.9*rtt)*dt # gas pt[i] = pt[i-1] + (rwt + 0.1*rtt)*dt # tar pc[i] = pc[i-1] + rwc*dt # char # return the wood, gas, tar, char, moisture, water vapor concentrations # as a density, kg/m^3 return pw, pg, pt, pc

36.510373

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1,305

8,799

3.257471

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0

7

59162871e6b1f9a1db64babef53c52a27c8e2a78

44

py

Python

vis/__init__.py

joeaortiz/gbp

5670a498950bfa948da502b2381899ab46f61021

[ "MIT" ]

50

2020-03-10T08:49:45.000Z

2022-03-24T01:50:24.000Z

vis/__init__.py

joeaortiz/gbp

5670a498950bfa948da502b2381899ab46f61021

[ "MIT" ]

1

2022-03-21T02:36:36.000Z

2022-03-21T03:03:38.000Z

vis/__init__.py

joeaortiz/gbp

5670a498950bfa948da502b2381899ab46f61021

[ "MIT" ]

11

2020-04-24T16:29:48.000Z

2022-03-09T07:39:30.000Z

from . import vis_scene from . import ba_vis

22

23

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8

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0

7

591f1f51426c00f086ae91a427aa67db3d54457d

22,381

py

Python

sdk/python/pulumi_alicloud/bastionhost/host_account.py

pulumi/pulumi-alicloud

9c34d84b4588a7c885c6bec1f03b5016e5a41683

[ "ECL-2.0", "Apache-2.0" ]

42

2019-03-18T06:34:37.000Z

2022-03-24T07:08:57.000Z

sdk/python/pulumi_alicloud/bastionhost/host_account.py

pulumi/pulumi-alicloud

9c34d84b4588a7c885c6bec1f03b5016e5a41683

[ "ECL-2.0", "Apache-2.0" ]

152

2019-04-15T21:03:44.000Z

2022-03-29T18:00:57.000Z

sdk/python/pulumi_alicloud/bastionhost/host_account.py

pulumi/pulumi-alicloud

9c34d84b4588a7c885c6bec1f03b5016e5a41683

[ "ECL-2.0", "Apache-2.0" ]

3

2020-08-26T17:30:07.000Z

2021-07-05T01:37:45.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities __all__ = ['HostAccountArgs', 'HostAccount'] @pulumi.input_type class HostAccountArgs: def __init__(__self__, *, host_account_name: pulumi.Input[str], host_id: pulumi.Input[str], instance_id: pulumi.Input[str], protocol_name: pulumi.Input[str], pass_phrase: Optional[pulumi.Input[str]] = None, password: Optional[pulumi.Input[str]] = None, private_key: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a HostAccount resource. :param pulumi.Input[str] host_account_name: The name of the host account. The name can be up to 128 characters in length. :param pulumi.Input[str] host_id: The ID of the host for which you want to create an account. :param pulumi.Input[str] instance_id: The ID of the Bastionhost instance where you want to create an account for the host. :param pulumi.Input[str] protocol_name: The protocol used by the host account. Valid values: SSH,RDP :param pulumi.Input[str] pass_phrase: The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. :param pulumi.Input[str] password: The password of the host account. :param pulumi.Input[str] private_key: The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` """ pulumi.set(__self__, "host_account_name", host_account_name) pulumi.set(__self__, "host_id", host_id) pulumi.set(__self__, "instance_id", instance_id) pulumi.set(__self__, "protocol_name", protocol_name) if pass_phrase is not None: pulumi.set(__self__, "pass_phrase", pass_phrase) if password is not None: pulumi.set(__self__, "password", password) if private_key is not None: pulumi.set(__self__, "private_key", private_key) @property @pulumi.getter(name="hostAccountName") def host_account_name(self) -> pulumi.Input[str]: """ The name of the host account. The name can be up to 128 characters in length. """ return pulumi.get(self, "host_account_name") @host_account_name.setter def host_account_name(self, value: pulumi.Input[str]): pulumi.set(self, "host_account_name", value) @property @pulumi.getter(name="hostId") def host_id(self) -> pulumi.Input[str]: """ The ID of the host for which you want to create an account. """ return pulumi.get(self, "host_id") @host_id.setter def host_id(self, value: pulumi.Input[str]): pulumi.set(self, "host_id", value) @property @pulumi.getter(name="instanceId") def instance_id(self) -> pulumi.Input[str]: """ The ID of the Bastionhost instance where you want to create an account for the host. """ return pulumi.get(self, "instance_id") @instance_id.setter def instance_id(self, value: pulumi.Input[str]): pulumi.set(self, "instance_id", value) @property @pulumi.getter(name="protocolName") def protocol_name(self) -> pulumi.Input[str]: """ The protocol used by the host account. Valid values: SSH,RDP """ return pulumi.get(self, "protocol_name") @protocol_name.setter def protocol_name(self, value: pulumi.Input[str]): pulumi.set(self, "protocol_name", value) @property @pulumi.getter(name="passPhrase") def pass_phrase(self) -> Optional[pulumi.Input[str]]: """ The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. """ return pulumi.get(self, "pass_phrase") @pass_phrase.setter def pass_phrase(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "pass_phrase", value) @property @pulumi.getter def password(self) -> Optional[pulumi.Input[str]]: """ The password of the host account. """ return pulumi.get(self, "password") @password.setter def password(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "password", value) @property @pulumi.getter(name="privateKey") def private_key(self) -> Optional[pulumi.Input[str]]: """ The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` """ return pulumi.get(self, "private_key") @private_key.setter def private_key(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "private_key", value) @pulumi.input_type class _HostAccountState: def __init__(__self__, *, host_account_id: Optional[pulumi.Input[str]] = None, host_account_name: Optional[pulumi.Input[str]] = None, host_id: Optional[pulumi.Input[str]] = None, instance_id: Optional[pulumi.Input[str]] = None, pass_phrase: Optional[pulumi.Input[str]] = None, password: Optional[pulumi.Input[str]] = None, private_key: Optional[pulumi.Input[str]] = None, protocol_name: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering HostAccount resources. :param pulumi.Input[str] host_account_id: Hosting account ID. :param pulumi.Input[str] host_account_name: The name of the host account. The name can be up to 128 characters in length. :param pulumi.Input[str] host_id: The ID of the host for which you want to create an account. :param pulumi.Input[str] instance_id: The ID of the Bastionhost instance where you want to create an account for the host. :param pulumi.Input[str] pass_phrase: The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. :param pulumi.Input[str] password: The password of the host account. :param pulumi.Input[str] private_key: The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` :param pulumi.Input[str] protocol_name: The protocol used by the host account. Valid values: SSH,RDP """ if host_account_id is not None: pulumi.set(__self__, "host_account_id", host_account_id) if host_account_name is not None: pulumi.set(__self__, "host_account_name", host_account_name) if host_id is not None: pulumi.set(__self__, "host_id", host_id) if instance_id is not None: pulumi.set(__self__, "instance_id", instance_id) if pass_phrase is not None: pulumi.set(__self__, "pass_phrase", pass_phrase) if password is not None: pulumi.set(__self__, "password", password) if private_key is not None: pulumi.set(__self__, "private_key", private_key) if protocol_name is not None: pulumi.set(__self__, "protocol_name", protocol_name) @property @pulumi.getter(name="hostAccountId") def host_account_id(self) -> Optional[pulumi.Input[str]]: """ Hosting account ID. """ return pulumi.get(self, "host_account_id") @host_account_id.setter def host_account_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "host_account_id", value) @property @pulumi.getter(name="hostAccountName") def host_account_name(self) -> Optional[pulumi.Input[str]]: """ The name of the host account. The name can be up to 128 characters in length. """ return pulumi.get(self, "host_account_name") @host_account_name.setter def host_account_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "host_account_name", value) @property @pulumi.getter(name="hostId") def host_id(self) -> Optional[pulumi.Input[str]]: """ The ID of the host for which you want to create an account. """ return pulumi.get(self, "host_id") @host_id.setter def host_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "host_id", value) @property @pulumi.getter(name="instanceId") def instance_id(self) -> Optional[pulumi.Input[str]]: """ The ID of the Bastionhost instance where you want to create an account for the host. """ return pulumi.get(self, "instance_id") @instance_id.setter def instance_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "instance_id", value) @property @pulumi.getter(name="passPhrase") def pass_phrase(self) -> Optional[pulumi.Input[str]]: """ The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. """ return pulumi.get(self, "pass_phrase") @pass_phrase.setter def pass_phrase(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "pass_phrase", value) @property @pulumi.getter def password(self) -> Optional[pulumi.Input[str]]: """ The password of the host account. """ return pulumi.get(self, "password") @password.setter def password(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "password", value) @property @pulumi.getter(name="privateKey") def private_key(self) -> Optional[pulumi.Input[str]]: """ The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` """ return pulumi.get(self, "private_key") @private_key.setter def private_key(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "private_key", value) @property @pulumi.getter(name="protocolName") def protocol_name(self) -> Optional[pulumi.Input[str]]: """ The protocol used by the host account. Valid values: SSH,RDP """ return pulumi.get(self, "protocol_name") @protocol_name.setter def protocol_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "protocol_name", value) class HostAccount(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, host_account_name: Optional[pulumi.Input[str]] = None, host_id: Optional[pulumi.Input[str]] = None, instance_id: Optional[pulumi.Input[str]] = None, pass_phrase: Optional[pulumi.Input[str]] = None, password: Optional[pulumi.Input[str]] = None, private_key: Optional[pulumi.Input[str]] = None, protocol_name: Optional[pulumi.Input[str]] = None, __props__=None): """ Provides a Bastion Host Host Account resource. For information about Bastion Host Host Account and how to use it, see [What is Host Account](https://www.alibabacloud.com/help/en/doc-detail/204377.htm). > **NOTE:** Available in v1.135.0+. ## Example Usage Basic Usage ```python import pulumi import pulumi_alicloud as alicloud example = alicloud.bastionhost.HostAccount("example", host_account_name="example_value", host_id="15", instance_id="bastionhost-cn-tl32bh0no30", password="YourPassword12345", protocol_name="SSH") ``` ## Import Bastion Host Host Account can be imported using the id, e.g. ```sh $ pulumi import alicloud:bastionhost/hostAccount:HostAccount example <instance_id>:<host_account_id> ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] host_account_name: The name of the host account. The name can be up to 128 characters in length. :param pulumi.Input[str] host_id: The ID of the host for which you want to create an account. :param pulumi.Input[str] instance_id: The ID of the Bastionhost instance where you want to create an account for the host. :param pulumi.Input[str] pass_phrase: The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. :param pulumi.Input[str] password: The password of the host account. :param pulumi.Input[str] private_key: The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` :param pulumi.Input[str] protocol_name: The protocol used by the host account. Valid values: SSH,RDP """ ... @overload def __init__(__self__, resource_name: str, args: HostAccountArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Provides a Bastion Host Host Account resource. For information about Bastion Host Host Account and how to use it, see [What is Host Account](https://www.alibabacloud.com/help/en/doc-detail/204377.htm). > **NOTE:** Available in v1.135.0+. ## Example Usage Basic Usage ```python import pulumi import pulumi_alicloud as alicloud example = alicloud.bastionhost.HostAccount("example", host_account_name="example_value", host_id="15", instance_id="bastionhost-cn-tl32bh0no30", password="YourPassword12345", protocol_name="SSH") ``` ## Import Bastion Host Host Account can be imported using the id, e.g. ```sh $ pulumi import alicloud:bastionhost/hostAccount:HostAccount example <instance_id>:<host_account_id> ``` :param str resource_name: The name of the resource. :param HostAccountArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(HostAccountArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, host_account_name: Optional[pulumi.Input[str]] = None, host_id: Optional[pulumi.Input[str]] = None, instance_id: Optional[pulumi.Input[str]] = None, pass_phrase: Optional[pulumi.Input[str]] = None, password: Optional[pulumi.Input[str]] = None, private_key: Optional[pulumi.Input[str]] = None, protocol_name: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = HostAccountArgs.__new__(HostAccountArgs) if host_account_name is None and not opts.urn: raise TypeError("Missing required property 'host_account_name'") __props__.__dict__["host_account_name"] = host_account_name if host_id is None and not opts.urn: raise TypeError("Missing required property 'host_id'") __props__.__dict__["host_id"] = host_id if instance_id is None and not opts.urn: raise TypeError("Missing required property 'instance_id'") __props__.__dict__["instance_id"] = instance_id __props__.__dict__["pass_phrase"] = pass_phrase __props__.__dict__["password"] = password __props__.__dict__["private_key"] = private_key if protocol_name is None and not opts.urn: raise TypeError("Missing required property 'protocol_name'") __props__.__dict__["protocol_name"] = protocol_name __props__.__dict__["host_account_id"] = None super(HostAccount, __self__).__init__( 'alicloud:bastionhost/hostAccount:HostAccount', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, host_account_id: Optional[pulumi.Input[str]] = None, host_account_name: Optional[pulumi.Input[str]] = None, host_id: Optional[pulumi.Input[str]] = None, instance_id: Optional[pulumi.Input[str]] = None, pass_phrase: Optional[pulumi.Input[str]] = None, password: Optional[pulumi.Input[str]] = None, private_key: Optional[pulumi.Input[str]] = None, protocol_name: Optional[pulumi.Input[str]] = None) -> 'HostAccount': """ Get an existing HostAccount resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] host_account_id: Hosting account ID. :param pulumi.Input[str] host_account_name: The name of the host account. The name can be up to 128 characters in length. :param pulumi.Input[str] host_id: The ID of the host for which you want to create an account. :param pulumi.Input[str] instance_id: The ID of the Bastionhost instance where you want to create an account for the host. :param pulumi.Input[str] pass_phrase: The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. :param pulumi.Input[str] password: The password of the host account. :param pulumi.Input[str] private_key: The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` :param pulumi.Input[str] protocol_name: The protocol used by the host account. Valid values: SSH,RDP """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _HostAccountState.__new__(_HostAccountState) __props__.__dict__["host_account_id"] = host_account_id __props__.__dict__["host_account_name"] = host_account_name __props__.__dict__["host_id"] = host_id __props__.__dict__["instance_id"] = instance_id __props__.__dict__["pass_phrase"] = pass_phrase __props__.__dict__["password"] = password __props__.__dict__["private_key"] = private_key __props__.__dict__["protocol_name"] = protocol_name return HostAccount(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="hostAccountId") def host_account_id(self) -> pulumi.Output[str]: """ Hosting account ID. """ return pulumi.get(self, "host_account_id") @property @pulumi.getter(name="hostAccountName") def host_account_name(self) -> pulumi.Output[str]: """ The name of the host account. The name can be up to 128 characters in length. """ return pulumi.get(self, "host_account_name") @property @pulumi.getter(name="hostId") def host_id(self) -> pulumi.Output[str]: """ The ID of the host for which you want to create an account. """ return pulumi.get(self, "host_id") @property @pulumi.getter(name="instanceId") def instance_id(self) -> pulumi.Output[str]: """ The ID of the Bastionhost instance where you want to create an account for the host. """ return pulumi.get(self, "instance_id") @property @pulumi.getter(name="passPhrase") def pass_phrase(self) -> pulumi.Output[Optional[str]]: """ The passphrase of the private key for the host account. **NOTE:** It is valid when the attribute `protocol_name` is `SSH`. """ return pulumi.get(self, "pass_phrase") @property @pulumi.getter def password(self) -> pulumi.Output[Optional[str]]: """ The password of the host account. """ return pulumi.get(self, "password") @property @pulumi.getter(name="privateKey") def private_key(self) -> pulumi.Output[Optional[str]]: """ The private key of the host account. The value is a Base64-encoded string. **NOTE:** It is valid when the attribute `protocol_name` is `SSH` """ return pulumi.get(self, "private_key") @property @pulumi.getter(name="protocolName") def protocol_name(self) -> pulumi.Output[str]: """ The protocol used by the host account. Valid values: SSH,RDP """ return pulumi.get(self, "protocol_name")

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8

5921d77484b0ffde79d1ca9631e163656b37d5f3

114

py

Python

WebEx_Teams/tools/api_key_webex.py

insidus341/devnet

8d44119b54051dcbc2b894f394e9a2b2d0fee7d8

[ "MIT" ]

null

WebEx_Teams/tools/api_key_webex.py

insidus341/devnet

8d44119b54051dcbc2b894f394e9a2b2d0fee7d8

[ "MIT" ]

null

WebEx_Teams/tools/api_key_webex.py

insidus341/devnet

8d44119b54051dcbc2b894f394e9a2b2d0fee7d8

[ "MIT" ]

null

key = 'Nzk1M2FkODEtY2NiMi00MWJjLWJjZDgtNzMxY2FlZTg2ZGNkZDM0MWMxN2QtOTdh_PF84_1eb65fdf-9643-417f-9974-ad72cae0e10f'

114

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8

114

12.875

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0.017544

114

1

114

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1

null

1

0

8

a72e685d91510e37333feb3ab1262dd5d440df2b

2,309

py

Python

tests/lib/database.py

cloud-gov/legacy-domain-certificate-renewer

6b008fdc8e1277cfe4449626e6c488d11fc4857c

[ "CC0-1.0" ]

1

2021-11-16T17:25:21.000Z

tests/lib/database.py

cloud-gov/legacy-domain-certificate-renewer

6b008fdc8e1277cfe4449626e6c488d11fc4857c

[ "CC0-1.0" ]

1

2021-12-22T19:04:34.000Z

tests/lib/database.py

cloud-gov/legacy-domain-certificate-renewer

6b008fdc8e1277cfe4449626e6c488d11fc4857c

[ "CC0-1.0" ]

null

import pytest from renewer.db import SessionHandler, cdn_engine, domain_engine @pytest.fixture(scope="function") def clean_db(): with SessionHandler() as session: session.execute("TRUNCATE TABLE user_data", bind=cdn_engine) session.execute("TRUNCATE TABLE routes CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE operations CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE certificates CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE challenges CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE acme_user_v2 CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE user_data", bind=domain_engine) session.execute("TRUNCATE TABLE routes CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE operations CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE certificates CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE challenges CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE acme_user_v2 CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE alb_proxies", bind=domain_engine) session.commit() session.close() yield session session.execute("TRUNCATE TABLE user_data", bind=cdn_engine) session.execute("TRUNCATE TABLE routes CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE operations CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE certificates CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE challenges CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE acme_user_v2 CASCADE", bind=cdn_engine) session.execute("TRUNCATE TABLE user_data", bind=domain_engine) session.execute("TRUNCATE TABLE routes CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE operations CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE certificates CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE challenges CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE acme_user_v2 CASCADE", bind=domain_engine) session.execute("TRUNCATE TABLE alb_proxies", bind=domain_engine) session.commit() session.close()

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0.423657

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0.172802

2,309

38

83

60.763158

0.865445

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0

0.3534

0

1

0.027778

true

0

0.055556

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0.083333

0

null

1

0

1

0

null

0

1

0

11

59817d58d6a13765508d6591888faafa9de5fb0d

85

py

Python

IPython/external/jsonschema/__init__.py

breisfeld/ipython

70e2c414014f3323d8a52fbcc94ee9e3a92d5d5f

[ "BSD-3-Clause-Clear" ]

26

2018-02-14T23:52:58.000Z

2021-08-16T13:50:03.000Z

IPython/external/jsonschema/__init__.py

breisfeld/ipython

70e2c414014f3323d8a52fbcc94ee9e3a92d5d5f

[ "BSD-3-Clause-Clear" ]

null

IPython/external/jsonschema/__init__.py

breisfeld/ipython

70e2c414014f3323d8a52fbcc94ee9e3a92d5d5f

[ "BSD-3-Clause-Clear" ]

10

2018-08-13T19:38:39.000Z

2020-04-19T03:02:00.000Z

try: from jsonschema import * except ImportError : from _jsonschema import *

17

29

0.717647

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85

6.666667

0.666667

0.466667

0.666667

0

0.235294

85

4

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1

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1

0

null

0

1

0

1

0

1

0

7

ab904ba0feba4770c518889ea6646d5d40c4b969

143

py

Python

deploy.py

gaetanV/python

6f5b38b918c5df2644a3f72606765904980fc2b8

[ "MIT" ]

null

deploy.py

gaetanV/python

6f5b38b918c5df2644a3f72606765904980fc2b8

[ "MIT" ]

null

deploy.py

gaetanV/python

6f5b38b918c5df2644a3f72606765904980fc2b8

[ "MIT" ]

null

import subprocess subprocess.call("gcc ./resolve/horse.c -o ./resolve/horse.exe") subprocess.call("gcc ./resolve/down.c -o ./resolve/down.exe")

47.666667

63

0.741259

22

143

4.818182

0.454545

0.264151

0.320755

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0

0.062937

143

3

64

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e6028103c590624651b0e182f176a34685c87460

3,801

py

Python

nfv/nfv-vim/nfv_vim/database/model/_instance_type.py

SidneyAn/nfv

5f0262a5b6ea4be59f977b9c587c483cbe0e373d

[ "Apache-2.0" ]

2

2020-02-07T19:01:36.000Z

2022-02-23T01:41:46.000Z

nfv/nfv-vim/nfv_vim/database/model/_instance_type.py

SidneyAn/nfv

5f0262a5b6ea4be59f977b9c587c483cbe0e373d

[ "Apache-2.0" ]

1

2021-01-14T12:02:25.000Z

nfv/nfv-vim/nfv_vim/database/model/_instance_type.py

SidneyAn/nfv

5f0262a5b6ea4be59f977b9c587c483cbe0e373d

[ "Apache-2.0" ]

2

2021-01-13T08:39:21.000Z

2022-02-09T00:21:55.000Z

# # Copyright (c) 2015-2016 Wind River Systems, Inc. # # SPDX-License-Identifier: Apache-2.0 # from sqlalchemy import Boolean from sqlalchemy import Column from sqlalchemy import Integer from sqlalchemy import String from nfv_vim.database.model._base import AsDictMixin from nfv_vim.database.model._base import Base class InstanceType_v5(AsDictMixin, Base): """ Instance Type Database Table """ __tablename__ = 'instance_types_v5' uuid = Column(String(64), nullable=False, primary_key=True) name = Column(String(64), nullable=False) have_details = Column(Boolean, nullable=False) vcpus = Column(Integer, nullable=False) mem_mb = Column(Integer, nullable=False) disk_gb = Column(Integer, nullable=False) ephemeral_gb = Column(Integer, nullable=False) swap_gb = Column(Integer, nullable=False) guest_services = Column(String(2048), nullable=False) auto_recovery = Column(Boolean, nullable=True) live_migration_timeout = Column(Integer, nullable=True) live_migration_max_downtime = Column(Integer, nullable=True) def __init__(self): """ Default some of the settings of the flavor """ self.have_details = False self.vcpus = 0 self.mem_mb = 0 self.disk_gb = 0 self.ephemeral_gb = 0 self.swap_gb = 0 self.guest_services = "{}" self.auto_recovery = None self.live_migration_timeout = None self.live_migration_max_downtime = None def __repr__(self): if self.have_details: return ("<Instance Type(%r, %r, %r, %r, %r, %r, %r, %r, %r, %r, %r )>" % (self.uuid, self.name, self.vcpus, self.mem_mb, self.disk_gb, self.ephemeral_gb, self.swap_gb, self.guest_services, self.auto_recovery, self.live_migration_timeout, self.live_migration_max_downtime)) return "<Instance Type(%r, %r)>" % (self.uuid, self.name) class InstanceType(AsDictMixin, Base): """ Instance Type Database Table """ __tablename__ = 'instance_types_v4' uuid = Column(String(64), nullable=False, primary_key=True) name = Column(String(64), nullable=False) have_details = Column(Boolean, nullable=False) vcpus = Column(Integer, nullable=False) mem_mb = Column(Integer, nullable=False) disk_gb = Column(Integer, nullable=False) ephemeral_gb = Column(Integer, nullable=False) swap_gb = Column(Integer, nullable=False) guest_services = Column(String(2048), nullable=False) auto_recovery = Column(Boolean, nullable=True) live_migration_timeout = Column(Integer, nullable=True) live_migration_max_downtime = Column(Integer, nullable=True) storage_type = Column(String(128), nullable=True) def __init__(self): """ Default some of the settings of the flavor """ self.have_details = False self.vcpus = 0 self.mem_mb = 0 self.disk_gb = 0 self.ephemeral_gb = 0 self.swap_gb = 0 self.guest_services = "{}" self.auto_recovery = None self.live_migration_timeout = None self.live_migration_max_downtime = None self.storage_Type = None def __repr__(self): if self.have_details: return ("<Instance Type(%r, %r, %r, %r, %r, %r, %r, %r, %r, %r, %r )>" % (self.uuid, self.name, self.vcpus, self.mem_mb, self.disk_gb, self.ephemeral_gb, self.swap_gb, self.guest_services, self.auto_recovery, self.live_migration_timeout, self.live_migration_max_downtime)) return "<Instance Type(%r, %r)>" % (self.uuid, self.name)

36.2

82

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468

3,801

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0.168803

0.019064

0.023397

0.02773

0.883882

0.855286

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0

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0.257827

3,801

104

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36.548077

0.803261

0.060247

0

0.842105

0

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1

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1

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null

0

1

0

8

05102942b27eae37630aaaeb0329a8ea114d6b6a

74,401

py

Python

lib/kb_muscle/kb_muscleImpl.py

dcchivian/kb_muscle

7740e2f273e0c59a0a550708092afa8666d0cb1e

[ "MIT" ]

1

2020-01-13T19:39:17.000Z

lib/kb_muscle/kb_muscleImpl.py

dcchivian/kb_muscle

7740e2f273e0c59a0a550708092afa8666d0cb1e

[ "MIT" ]

9

2017-11-09T16:54:17.000Z

2021-06-23T21:11:55.000Z

lib/kb_muscle/kb_muscleImpl.py

dcchivian/kb_muscle

7740e2f273e0c59a0a550708092afa8666d0cb1e

[ "MIT" ]

5

2017-06-25T02:42:55.000Z

2019-05-13T13:15:47.000Z

-*- coding: utf-8 -*- #BEGIN_HEADER import gzip import os import re import subprocess import sys import traceback import uuid import json from datetime import datetime from pprint import pformat import requests from Bio import SeqIO from Bio.Seq import Seq from Bio.SeqRecord import SeqRecord from requests_toolbelt import MultipartEncoder from installed_clients.AbstractHandleClient import AbstractHandle as HandleService from installed_clients.DataFileUtilClient import DataFileUtil as DFUClient from installed_clients.KBaseReportClient import KBaseReport from installed_clients.WorkspaceClient import Workspace as workspaceService from installed_clients.SetAPIServiceClient import SetAPI from installed_clients.AssemblyUtilClient import AssemblyUtil from installed_clients.kb_ObjectUtilitiesClient import kb_ObjectUtilities #END_HEADER class kb_muscle: ''' Module Name: kb_muscle Module Description: ** A KBase module: kb_muscle ** ** This module runs MUSCLE to make MSAs of either DNA or PROTEIN sequences. "MUSCLE nuc" will build nucleotide alignments, even for protein coding genes. "MUSCLE prot" will build protein sequence alignments, and will ignore any features that do not code for proteins. ** ''' ######## WARNING FOR GEVENT USERS ####### noqa # Since asynchronous IO can lead to methods - even the same method - # interrupting each other, you must be *very* careful when using global # state. A method could easily clobber the state set by another while # the latter method is running. ######################################### noqa VERSION = "1.1.1" GIT_URL = "https://github.com/kbaseapps/kb_muscle" GIT_COMMIT_HASH = "d25d4d112be6c3fce5d879734dabdf5cc524ea2f" #BEGIN_CLASS_HEADER workspaceURL = None shockURL = None handleURL = None serviceWizardURL = None callbackURL = None scratch = None MUSCLE_bin = '/kb/module/muscle/bin/muscle' # target is a list for collecting log messages def log(self, target, message): # we should do something better here... if target is not None: target.append(message) print(message) sys.stdout.flush() def get_single_end_read_library(self, ws_data, ws_info, forward): pass def get_feature_set_seqs(self, ws_data, ws_info): pass def KBase_data2file_GenomeAnnotation2Fasta(self, ws_data, ws_info): pass def get_genome_set_feature_seqs(self, ws_data, ws_info): pass # Translation def TranslateNucToProtSeq(self, ctx, params): if 'nuc_seq' not in params or params['nuc_seq'] == None or params['nuc_seq'] == '': raise ValueError('Method TranslateNucToProtSeq() requires nuc_seq parameter') if 'genetic_code' not in params or params['genetic_code'] == None or params['genetic_code'] == '': params['genetic_code'] = '11' if params['genetic_code'] != '11': raise ValueError('Method TranslateNucToProtSeq() only knows genetic code 11') nuc_seq = params['nuc_seq'].upper() prot_seq = '' genetic_code = params['genetic_code'] genetic_code_table = dict() genetic_code_table['11'] = { 'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M', 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T', 'AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K', 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R', 'CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L', 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P', 'CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q', 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R', 'GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V', 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A', 'GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E', 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G', 'TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S', 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L', 'TAC':'Y', 'TAT':'Y', 'TAA':'_', 'TAG':'_', 'TGC':'C', 'TGT':'C', 'TGA':'_', 'TGG':'W' } if genetic_code not in genetic_code_table: raise ValueError ("genetic code '"+str(genetic_code)+"' not configured in genetic_code_table") prot_seq = ''.join([genetic_code_table[genetic_code].get(nuc_seq[3*i:3*i+3],'X') for i in range(len(nuc_seq)//3)]) if prot_seq.endswith('_'): prot_seq = prot_seq.rstrip('_') return prot_seq # AMA_METHODS #def _get_ama_features_as_json (self, features_handle_ref, gff_handle_ref, protein_handle_ref): def _get_ama_features_as_json (self, features_handle_ref): this_id = str(uuid.uuid4()) this_scratch_dir = os.path.join (self.scratch, this_id) json_features_file_path = os.path.join (this_scratch_dir, 'features.json') #gff_file_path = os.path.join (this_scratch_dir, 'genes.gff') #protein_file_path = os.path.join (this_scratch_dir, 'protein.fasta') try: dfu = DFUClient (self.callbackURL) except Exception as e: raise ValueError('Unable to connect to DFU: ' + str(e)) try: dfu.shock_to_file({'handle_id': features_handle_ref, 'file_path': json_features_file_path+'.gz', 'unpack': 'uncompress' }) except Exception as e: raise ValueError('Unable to fetch AnnotatedMetagenomeAssembly features from SHOCK: ' + str(e)) """ try: dfu.shock_to_file({'handle_id': gff_handle_ref, 'file_path': gff_file_path+'.gz', 'unpack': 'uncompress' }) except Exception as e: raise ValueError('Unable to fetch AnnotatedMetagenomeAssembly gffs from SHOCK: ' + str(e)) try: dfu.shock_to_file({'handle_id': protein_handle_ref, 'file_path': protein_file_path+'.gz', 'unpack': 'uncompress' }) except Exception as e: raise ValueError('Unable to fetch AnnotatedMetagenomeAssembly protein FASTA from SHOCK: ' + str(e)) """ # DEBUG """ print ("SCRATCH CONTENTS") sys.stdout.flush() for this_file in os.listdir (this_scratch_dir): print ("\t"+this_file) sys.stdout.flush() buf = [] #with open(json_features_file_path, 'r') as f: with open(protein_file_path, 'r') as f: for line in f.readlines(): buf.append (line) #features_json = json.load(f) print ("FEATURES_JSON:\n"+"\n".join(buf)) sys.stdout.flush() """ with open(json_features_file_path, 'r') as f: features_json = json.load(f) os.remove(json_features_file_path+'.gz') os.remove(json_features_file_path) #os.remove(gff_file_path+'.gz') #os.remove(gff_file_path) #os.remove(protein_file_path+'.gz') #os.remove(protein_file_path) return features_json def _get_features_from_AnnotatedMetagenomeAssembly(self, ctx, ama_ref): # get ama object try: ws = workspaceService(self.workspaceURL, token=ctx['token']) ama_object = ws.get_objects2({'objects':[{'ref':ama_ref}]})['data'][0] ama_object_data = ama_object['data'] ama_object_info = ama_object['info'] except Exception as e: raise ValueError('Unable to fetch AnnotatedMetagenomeAssembly object from workspace: ' + str(e)) #to get the full stack trace: traceback.format_exc() # get features from json features_handle_ref = ama_object_data['features_handle_ref'] #gff_handle_ref = ama_object_data['gff_handle_ref'] #protein_handle_ref = ama_object_data['protein_handle_ref'] #features_json = self._get_ama_features_as_json (features_handle_ref, gff_handle_ref, protein_handle_ref) features_json = self._get_ama_features_as_json (features_handle_ref) return features_json #END_CLASS_HEADER # config contains contents of config file in a hash or None if it couldn't # be found def __init__(self, config): #BEGIN_CONSTRUCTOR self.workspaceURL = config['workspace-url'] self.shockURL = config['shock-url'] self.handleURL = config['handle-service-url'] self.serviceWizardURL = config['srv-wiz-url'] self.callbackURL = os.environ.get('SDK_CALLBACK_URL') if self.callbackURL == None: raise ValueError ("SDK_CALLBACK_URL not set in environment") self.scratch = os.path.abspath(config['scratch']) # HACK!! temporary hack for issue where megahit fails on mac because of silent named pipe error #self.host_scratch = self.scratch #self.scratch = os.path.join('/kb','module','local_scratch') # end hack if not os.path.exists(self.scratch): os.makedirs(self.scratch) #END_CONSTRUCTOR pass def MUSCLE_nuc(self, ctx, params): """ Methods for MSA building of either DNA or PROTEIN sequences ** ** overloading as follows: ** input_ref: SingleEndLibrary (just MUSCLE_nuc), FeatureSet (both) ** output_name: MSA :param params: instance of type "MUSCLE_Params" (MUSCLE Input Params ** ** MUSCLE_prot(): input_ref must be FeatureSet ** MUSCLE_nuc(): input_ref must be FeatureSet, SingleEndLibrary, or AssemblySet) -> structure: parameter "workspace_name" of type "workspace_name" (** The workspace object refs are of form: ** ** objects = ws.get_objects([{'ref': params['workspace_id']+'/'+params['obj_name']}]) ** ** "ref" means the entire name combining the workspace id and the object name ** "id" is a numerical identifier of the workspace or object, and should just be used for workspace ** "name" is a string identifier of a workspace or object. This is received from Narrative.), parameter "desc" of String, parameter "input_ref" of type "data_obj_ref", parameter "output_name" of type "data_obj_name", parameter "genome_disp_name_config" of String, parameter "maxiters" of Long, parameter "maxhours" of Double :returns: instance of type "MUSCLE_Output" (MUSCLE Output) -> structure: parameter "report_name" of type "data_obj_name", parameter "report_ref" of type "data_obj_ref" """ # ctx is the context object # return variables are: returnVal #BEGIN MUSCLE_nuc console = [] invalid_msgs = [] self.log(console,'Running MUSCLE_nuc with params=') self.log(console, "\n"+pformat(params)) report = '' # report = 'Running MUSCLE_nuc with params=' # report += "\n"+pformat(params) [OBJID_I, NAME_I, TYPE_I, SAVE_DATE_I, VERSION_I, SAVED_BY_I, WSID_I, WORKSPACE_I, CHSUM_I, SIZE_I, META_I] = range(11) # object_info tuple row_labels = {} #### do some basic checks # if 'workspace_name' not in params: raise ValueError('workspace_name parameter is required') if 'input_ref' not in params: raise ValueError('input_ref parameter is required') if 'output_name' not in params: raise ValueError('output_name parameter is required') #### Get the input_ref object ## input_forward_reads_file_compression = None sequencing_tech = 'N/A' try: ws = workspaceService(self.workspaceURL, token=ctx['token']) objects = ws.get_objects([{'ref': params['input_ref']}]) data = objects[0]['data'] info = objects[0]['info'] input_name = info[1] input_type_name = info[2].split('.')[1].split('-')[0] if input_type_name == 'SingleEndLibrary': input_type_namespace = info[2].split('.')[0] if input_type_namespace == 'KBaseAssembly': file_name = data['handle']['file_name'] elif input_type_namespace == 'KBaseFile': file_name = data['lib']['file']['file_name'] else: raise ValueError('bad data type namespace: '+input_type_namespace) #self.log(console, 'INPUT_FILENAME: '+file_name) # DEBUG if file_name[-3:] == ".gz": input_forward_reads_file_compression = 'gz' if 'sequencing_tech' in data: sequencing_tech = data['sequencing_tech'] except Exception as e: traceback.format_exc() raise ValueError('Unable to fetch input_ref object from workspace: ' + str(e)) # Handle overloading (input_ref can be SingleEndLibrary or FeatureSet) # if input_type_name == 'SingleEndLibrary': # DEBUG #for k in data: # self.log(console,"SingleEndLibrary ["+k+"]: "+str(data[k])) try: if 'lib' in data: input_forward_reads = data['lib']['file'] elif 'handle' in data: input_forward_reads = data['handle'] else: self.log(console,"bad structure for 'input_forward_reads'") raise ValueError("bad structure for 'input_forward_reads'") ### NOTE: this section is what could be replaced by the transform services input_forward_reads_file_path = os.path.join(self.scratch,input_forward_reads['file_name']) input_forward_reads_file_handle = open(input_forward_reads_file_path, 'w') self.log(console, 'downloading reads file: '+str(input_forward_reads_file_path)) headers = {'Authorization': 'OAuth '+ctx['token']} r = requests.get(input_forward_reads['url']+'/node/'+input_forward_reads['id']+'?download', stream=True, headers=headers) for chunk in r.iter_content(1024): input_forward_reads_file_handle.write(chunk) input_forward_reads_file_handle.close(); self.log(console, 'done') ### END NOTE # remove carriage returns new_file_path = input_forward_reads_file_path+"-CRfree" new_file_handle = open(new_file_path, 'w') input_forward_reads_file_handle = open(input_forward_reads_file_path, 'r') for line in input_forward_reads_file_handle: line = re.sub("\r","",line) new_file_handle.write(line) input_forward_reads_file_handle.close(); new_file_handle.close() input_forward_reads_file_path = new_file_path # convert FASTQ to FASTA (if necessary) new_file_path = input_forward_reads_file_path+".fna" new_file_handle = open(new_file_path, 'w') if input_forward_reads_file_compression == 'gz': input_forward_reads_file_handle = gzip.open(input_forward_reads_file_path, 'r') else: input_forward_reads_file_handle = open(input_forward_reads_file_path, 'r') header = None last_header = None last_seq_buf = None last_line_was_header = False was_fastq = False for line in input_forward_reads_file_handle: if line.startswith('>'): break elif line.startswith('@'): was_fastq = True header = line[1:] if last_header != None: new_file_handle.write('>'+last_header) new_file_handle.write(last_seq_buf) last_seq_buf = None last_header = header last_line_was_header = True elif last_line_was_header: last_seq_buf = line last_line_was_header = False else: continue if last_header != None: new_file_handle.write('>'+last_header) new_file_handle.write(last_seq_buf) new_file_handle.close() input_forward_reads_file_handle.close() if was_fastq: input_forward_reads_file_path = new_file_path except Exception as e: print(traceback.format_exc()) raise ValueError('Unable to download single-end read library files: ' + str(e)) # FeatureSet # elif input_type_name == 'FeatureSet': genome_id_feature_id_delim = '.f:' # retrieve sequences for features input_featureSet = data genomeObjName = {} genomeObjVer = {} genomeSciName = {} genome2Features = {} new_id = {} featureSet_elements = input_featureSet['elements'] if 'element_ordering' in input_featureSet and input_featureSet['element_ordering']: feature_order = input_featureSet['element_ordering'] else: feature_order = sorted(featureSet_elements.keys()) for fId in feature_order: genomeRef = featureSet_elements[fId][0] if genomeRef not in genome2Features: genome2Features[genomeRef] = [] new_id[genomeRef] = {} if genome_id_feature_id_delim in fId: [genome_id, feature_id] = fId.split(genome_id_feature_id_delim) else: feature_id = fId genome2Features[genomeRef].append(feature_id) this_id = genomeRef + genome_id_feature_id_delim + feature_id new_id[genomeRef][fId] = this_id # export features to FASTA file input_forward_reads_file_path = os.path.join(self.scratch, input_name+".fasta") self.log(console, 'writing fasta file: '+input_forward_reads_file_path) records_by_fid = dict() for genomeRef in genome2Features: genome_obj = ws.get_objects([{'ref':genomeRef}])[0] genome_type = re.sub('-[0-9]+\.[0-9]+$', "", genome_obj['info'][TYPE_I]) genomeObjName[genomeRef] = genome_obj['info'][NAME_I] genomeObjVer[genomeRef] = genome_obj['info'][VERSION_I] these_genomeFeatureIds = genome2Features[genomeRef] # Genome if genome_type == 'KBaseGenomes.Genome': genome = genome_obj['data'] genomeSciName[genomeRef] = genome['scientific_name'] for feature in genome['features']: if feature['id'] in these_genomeFeatureIds: #self.log(console,"kbase_id: '"+feature['id']+"'") # DEBUG this_id = genomeRef + genome_id_feature_id_delim + feature['id'] short_feature_id = re.sub("^.*\.([^\.]+)\.([^\.]+)$", r"\1.\2", feature['id']) genome_disp_name = '' if 'obj_name' in params.get('genome_disp_name_config'): genome_disp_name += genomeObjName[genomeRef] if 'ver' in params.get('genome_disp_name_config'): genome_disp_name += '.v'+str(genomeObjVer[genomeRef]) if genome_type == "KBaseGenomes.Genome" and \ 'sci_name' in params.get('genome_disp_name_config'): genome_disp_name += ': '+genomeSciName[genomeRef] else: genome_disp_name = genomeObjName[genomeRef] row_labels[this_id] = genome_disp_name+' - '+short_feature_id #record = SeqRecord(Seq(feature['dna_sequence']), id=feature['id'], description=genome['id']) record = SeqRecord(Seq(feature['dna_sequence']), id=this_id, description=genome['id']) records_by_fid[this_id] = record # AnnotatedMetagenomeAssembly elif genome_type == 'KBaseMetagenomes.AnnotatedMetagenomeAssembly': ama_features = self._get_features_from_AnnotatedMetagenomeAssembly (ctx, genomeRef) for feature in ama_features: if feature['id'] in these_genomeFeatureIds: if not feature.get('dna_sequence'): raise ValueError("bad feature "+feature['id']+": No dna_sequence field.") this_id = genomeRef + genome_id_feature_id_delim + feature['id'] short_feature_id = re.sub("^.*\.([^\.]+)\.([^\.]+)$", r"\1.\2", feature['id']) genome_disp_name = genomeObjName[genomeRef] row_labels[this_id] = genome_disp_name+' - '+short_feature_id record = SeqRecord(Seq(feature['dna_sequence']), id=this_id, description=genomeObjName[genomeRef]) records_by_fid[this_id] = record else: raise ValueError ("unable to handle feature from object type: "+genome_type) records = [] for fId in feature_order: genomeRef = featureSet_elements[fId][0] records.append(records_by_fid[new_id[genomeRef][fId]]) SeqIO.write(records, input_forward_reads_file_path, "fasta") # Missing proper input_input_type # else: raise ValueError('Cannot yet handle input_ref type of: '+input_type_name) """ # AssemblySet # elif input_type_name == 'AssemblySet': try: SetAPI_Client = SetAPI(self.serviceWizardURL, token=ctx['token']) except Exception as e: raise ValueError ("unable to instantiate SetAPI Client") try: auClient = AssemblyUtil(self.callbackURL, token=ctx['token']) except Exception as e: raise ValueError ("unable to instantiate AssemblyUtil Client") # HERE """ ### Construct the command # # e.g. muscle -in <fasta_in> -out <fasta_out> -maxiters <n> -haxours <h> # muscle_cmd = [self.MUSCLE_bin] # check for necessary files if not os.path.isfile(self.MUSCLE_bin): raise ValueError("no such file '"+self.MUSCLE_bin+"'") if not os.path.isfile(input_forward_reads_file_path): raise ValueError("no such file '"+input_forward_reads_file_path+"'") elif not os.path.getsize(input_forward_reads_file_path) > 0: raise ValueError("empty file '"+input_forward_reads_file_path+"'") # set the output path timestamp = int((datetime.utcnow() - datetime.utcfromtimestamp(0)).total_seconds()*1000) output_dir = os.path.join(self.scratch,'output.'+str(timestamp)) if not os.path.exists(output_dir): os.makedirs(output_dir) output_aln_file_path = os.path.join(output_dir, params['output_name']+'-MSA.fasta'); file_extension = '' muscle_cmd.append('-in') muscle_cmd.append(input_forward_reads_file_path) muscle_cmd.append('-out') muscle_cmd.append(output_aln_file_path) # options if 'maxiters' in params and params['maxiters'] != None: muscle_cmd.append('-maxiters') muscle_cmd.append(str(params['maxiters'])) if 'maxhours' in params and params['maxhours'] != None: muscle_cmd.append('-maxhours') muscle_cmd.append(str(params['maxhours'])) # Run MUSCLE, capture output as it happens # self.log(console, 'RUNNING MUSCLE:') self.log(console, ' '+' '.join(muscle_cmd)) # report += "\n"+'running MUSCLE:'+"\n" # report += ' '+' '.join(muscle_cmd)+"\n" p = subprocess.Popen(muscle_cmd, \ cwd = self.scratch, \ stdout = subprocess.PIPE, \ stderr = subprocess.STDOUT, \ shell = False) while True: line = p.stdout.readline().decode() if not line: break self.log(console, line.replace('\n', '')) p.stdout.close() p.wait() self.log(console, 'return code: ' + str(p.returncode)) if p.returncode != 0: raise ValueError('Error running MUSCLE, return code: '+str(p.returncode) + '\n\n'+ '\n'.join(console)) # Parse the FASTA MSA output and replace id for txt upload # self.log(console, 'PARSING MUSCLE MSA FASTA OUTPUT') if not os.path.isfile(output_aln_file_path): raise ValueError("failed to create MUSCLE output: "+output_aln_file_path) elif not os.path.getsize(output_aln_file_path) > 0: raise ValueError("created empty file for MUSCLE output: "+output_aln_file_path) output_aln_file_handle = open (output_aln_file_path, 'r') output_fasta_buf = [] row_order = [] alignment = {} alignment_length = None last_header = None header = None last_seq = '' leading_chars_pattern = re.compile("^\S+") for line in output_aln_file_handle: line = line.rstrip('\n') if line.startswith('>'): header = line[1:] if row_labels: this_id = leading_chars_pattern.findall(header)[0] this_row_label = re.sub ('\s', '_', row_labels[this_id]) output_fasta_buf.append('>'+this_row_label) else: output_fasta_buf.append(line) if last_header != None: last_id = leading_chars_pattern.findall(last_header)[0] row_order.append(last_id) #self.log(console,"ID: '"+last_id+"'\nALN: '"+last_seq+"'") # DEBUG #report += last_id+"\t"+last_seq+"\n" alignment[last_id] = last_seq if alignment_length == None: alignment_length = len(last_seq) elif alignment_length != len(last_seq): raise ValueError ("unequal alignment row for "+last_header+": '"+last_seq+"'") last_header = header last_seq = '' else: last_seq += line output_fasta_buf.append(line) if last_header != None: last_id = leading_chars_pattern.findall(last_header)[0] row_order.append(last_id) #self.log(console,"ID: '"+last_id+"'\nALN: '"+last_seq+"'") # DEBUG #report += last_id+"\t"+last_seq+"\n" alignment[last_id] = last_seq if alignment_length == None: alignment_length = len(last_seq) elif alignment_length != len(last_seq): raise ValueError ("unequal alignment row for "+last_header+": '"+last_seq+"'") output_aln_file_handle.close() # write remapped ids with open(output_aln_file_path, 'w') as output_aln_file_handle: output_aln_file_handle.write("\n".join(output_fasta_buf)+"\n") # load the method provenance from the context object # self.log(console,"SETTING PROVENANCE") # DEBUG provenance = [{}] if 'provenance' in ctx: provenance = ctx['provenance'] # add additional info to provenance here, in this case the input data object reference provenance[0]['input_ws_objects'] = [] provenance[0]['input_ws_objects'].append(params['input_ref']) provenance[0]['service'] = 'kb_muscle' provenance[0]['method'] = 'MUSCLE_nuc' # Upload results # if len(invalid_msgs) == 0: self.log(console,"UPLOADING RESULTS") # DEBUG MSA_name = params['output_name'] MSA_description = params['desc'] sequence_type = 'dna' ws_refs = None # may add these later from FeatureSet kb_refs = None #alignment_length # already have #row_order # already have #alignment # already have # NO trim_info # NO alignment_attributes # NO default_row_labels # NO parent_msa_ref # if input_type_name == 'FeatureSet': # features = featureSet['elements'] # genome2Features = {} # for fId in row_order: # genomeRef = features[fId][0] # if genomeRef not in genome2Features: # genome2Features[genomeRef] = [] # genome2Features[genomeRef].append(fId) # # for genomeRef in genome2Features: # genome = ws.get_objects([{'ref':genomeRef}])[0]['data'] # these_genomeFeatureIds = genome2Features[genomeRef] # for feature in genome['features']: # if feature['id'] in these_genomeFeatureIds: output_MSA = { 'name': MSA_name, 'description': MSA_description, 'sequence_type': sequence_type, 'alignment_length': alignment_length, 'row_order': row_order, 'alignment': alignment } if row_labels: output_MSA['default_row_labels'] = row_labels new_obj_info = ws.save_objects({ 'workspace': params['workspace_name'], 'objects':[{ 'type': 'KBaseTrees.MSA', 'data': output_MSA, 'name': params['output_name'], 'meta': {}, 'provenance': provenance }] }) # create CLW formatted output file max_row_width = 60 id_aln_gap_width = 1 gap_chars = '' for sp_i in range(id_aln_gap_width): gap_chars += ' ' # DNA strong_groups = { 'AG': True, 'CTU': True } weak_groups = None # PROTEINS # strong_groups = { 'AST': True, # 'EKNQ': True, # 'HKNQ': True, # 'DENQ': True, # 'HKQR': True, # 'ILMV': True, # 'FILM': True, # 'HY': True, # 'FWY': True # } # weak_groups = { 'ACS': True, # 'ATV': True, # 'AGS': True, # 'KNST': True, # 'APST': True, # 'DGNS': True, # 'DEKNQS': True, # 'DEHKNQ': True, # 'EHKNQR': True, # 'FILMV': True, # 'FHY': True # } clw_buf = [] clw_buf.append ('CLUSTALW format of MUSCLE alignment '+MSA_name+': '+MSA_description) clw_buf.append ('') long_id_len = 0 aln_pos_by_id = dict() for row_id in row_order: aln_pos_by_id[row_id] = 0 if row_labels: row_id_disp = row_labels[row_id] else: row_id_disp = row_id if long_id_len < len(row_id_disp): long_id_len = len(row_id_disp) full_row_cnt = alignment_length // max_row_width if alignment_length % max_row_width == 0: full_row_cnt -= 1 for chunk_i in range (full_row_cnt + 1): for row_id in row_order: if row_labels: row_id_disp = re.sub('\s', '_', row_labels[row_id]) else: row_id_disp = row_id for sp_i in range (long_id_len-len(row_id_disp)): row_id_disp += ' ' aln_chunk_upper_bound = (chunk_i+1)*max_row_width if aln_chunk_upper_bound > alignment_length: aln_chunk_upper_bound = alignment_length aln_chunk = alignment[row_id][chunk_i*max_row_width:aln_chunk_upper_bound] for c in aln_chunk: if c != '-': aln_pos_by_id[row_id] += 1 clw_buf.append (row_id_disp+gap_chars+aln_chunk+' '+str(aln_pos_by_id[row_id])) # conservation line cons_line = '' for pos_i in range(chunk_i*max_row_width, aln_chunk_upper_bound): col_chars = dict() seq_cnt = 0 for row_id in row_order: char = alignment[row_id][pos_i] if char != '-': seq_cnt += 1 col_chars[char] = True if seq_cnt <= 1: cons_char = ' ' elif len(col_chars.keys()) == 1: cons_char = '*' else: strong = False for strong_group in strong_groups.keys(): this_strong_group = True for seen_char in col_chars.keys(): if seen_char not in strong_group: this_strong_group = False break if this_strong_group: strong = True break if not strong: weak = False if weak_groups is not None: for weak_group in weak_groups.keys(): this_weak_group = True for seen_char in col_chars.keys(): if seen_char not in weak_group: this_strong_group = False break if this_weak_group: weak = True if strong: cons_char = ':' elif weak: cons_char = '.' else: cons_char = ' ' cons_line += cons_char lead_space = '' for sp_i in range(long_id_len): lead_space += ' ' lead_space += gap_chars clw_buf.append(lead_space+cons_line) clw_buf.append('') # write clw to file clw_buf_str = "\n".join(clw_buf)+"\n" output_clw_file_path = os.path.join(output_dir, input_name+'-MSA.clw') with open (output_clw_file_path, 'w') as output_clw_file_handle: output_clw_file_handle.write(clw_buf_str) # upload MUSCLE FASTA output to SHOCK for file_links dfu = DFUClient(self.callbackURL) try: output_upload_ret = dfu.file_to_shock({'file_path': output_aln_file_path, # DEBUG # 'make_handle': 0, # 'pack': 'zip'}) 'make_handle': 0}) except: raise ValueError ('error loading aln_out file to shock') # upload MUSCLE CLW output to SHOCK for file_links try: output_clw_upload_ret = dfu.file_to_shock({'file_path': output_clw_file_path, # DEBUG # 'make_handle': 0, # 'pack': 'zip'}) 'make_handle': 0}) except: raise ValueError ('error loading clw_out file to shock') # make HTML reports # # HERE # build output report object # self.log(console,"BUILDING REPORT") # DEBUG reportName = 'muscle_report_'+str(uuid.uuid4()) reportObj = { 'objects_created':[{'ref':params['workspace_name']+'/'+params['output_name'], 'description':'MUSCLE_nuc MSA'}], #'message': '', 'message': clw_buf_str, 'file_links': [], 'workspace_name': params['workspace_name'], 'report_object_name': reportName } reportObj['file_links'] = [{'shock_id': output_upload_ret['shock_id'], 'name': params['output_name']+'-MUSCLE_nuc.FASTA', 'label': 'MUSCLE_nuc FASTA' }, {'shock_id': output_clw_upload_ret['shock_id'], 'name': params['output_name']+'-MUSCLE_nuc.CLW', 'label': 'MUSCLE_nuc CLUSTALW' }] # save report object # SERVICE_VER = 'release' reportClient = KBaseReport(self.callbackURL, token=ctx['token'], service_ver=SERVICE_VER) #report_info = report.create({'report':reportObj, 'workspace_name':params['workspace_name']}) report_info = reportClient.create_extended_report(reportObj) else: # len(invalid_msgs) > 0 reportName = 'muscle_report_'+str(uuid.uuid4()) report += "FAILURE:\n\n"+"\n".join(invalid_msgs)+"\n" reportObj = { 'objects_created':[], 'text_message':report } ws = workspaceService(self.workspaceURL, token=ctx['token']) report_obj_info = ws.save_objects({ #'id':info[6], 'workspace':params['workspace_name'], 'objects':[ { 'type':'KBaseReport.Report', 'data':reportObj, 'name':reportName, 'meta':{}, 'hidden':1, 'provenance':provenance } ] })[0] report_info = dict() report_info['name'] = report_obj_info[1] report_info['ref'] = str(report_obj_info[6])+'/'+str(report_obj_info[0])+'/'+str(report_obj_info[4]) # done returnVal = { 'report_name': report_info['name'], 'report_ref': report_info['ref'] } self.log(console,"MUSCLE_nuc DONE") #END MUSCLE_nuc # At some point might do deeper type checking... if not isinstance(returnVal, dict): raise ValueError('Method MUSCLE_nuc return value ' + 'returnVal is not type dict as required.') # return the results return [returnVal] def MUSCLE_prot(self, ctx, params): """ :param params: instance of type "MUSCLE_Params" (MUSCLE Input Params ** ** MUSCLE_prot(): input_ref must be FeatureSet ** MUSCLE_nuc(): input_ref must be FeatureSet, SingleEndLibrary, or AssemblySet) -> structure: parameter "workspace_name" of type "workspace_name" (** The workspace object refs are of form: ** ** objects = ws.get_objects([{'ref': params['workspace_id']+'/'+params['obj_name']}]) ** ** "ref" means the entire name combining the workspace id and the object name ** "id" is a numerical identifier of the workspace or object, and should just be used for workspace ** "name" is a string identifier of a workspace or object. This is received from Narrative.), parameter "desc" of String, parameter "input_ref" of type "data_obj_ref", parameter "output_name" of type "data_obj_name", parameter "genome_disp_name_config" of String, parameter "maxiters" of Long, parameter "maxhours" of Double :returns: instance of type "MUSCLE_Output" (MUSCLE Output) -> structure: parameter "report_name" of type "data_obj_name", parameter "report_ref" of type "data_obj_ref" """ # ctx is the context object # return variables are: returnVal #BEGIN MUSCLE_prot console = [] invalid_msgs = [] self.log(console,'Running MUSCLE_prot with params=') self.log(console, "\n"+pformat(params)) report = '' # report = 'Running MUSCLE_prot with params=' # report += "\n"+pformat(params) [OBJID_I, NAME_I, TYPE_I, SAVE_DATE_I, VERSION_I, SAVED_BY_I, WSID_I, WORKSPACE_I, CHSUM_I, SIZE_I, META_I] = range(11) # object_info tuple row_labels = {} #### do some basic checks # if 'workspace_name' not in params: raise ValueError('workspace_name parameter is required') if 'input_ref' not in params: raise ValueError('input_ref parameter is required') if 'output_name' not in params: raise ValueError('output_name parameter is required') #### Get the input_ref object ## # input_forward_reads_file_compression = None # sequencing_tech = 'N/A' try: ws = workspaceService(self.workspaceURL, token=ctx['token']) objects = ws.get_objects([{'ref': params['input_ref']}]) data = objects[0]['data'] info = objects[0]['info'] input_name = info[1] input_type_name = info[2].split('.')[1].split('-')[0] # if input_type_name == 'SingleEndLibrary': # input_type_namespace = info[2].split('.')[0] # if input_type_namespace == 'KBaseAssembly': # file_name = data['handle']['file_name'] # elif input_type_namespace == 'KBaseFile': # file_name = data['lib']['file']['file_name'] # else: # raise ValueError('bad data type namespace: '+input_type_namespace) # #self.log(console, 'INPUT_FILENAME: '+file_name) # DEBUG # if file_name[-3:] == ".gz": # input_forward_reads_file_compression = 'gz' # if 'sequencing_tech' in data: # sequencing_tech = data['sequencing_tech'] except Exception as e: traceback.format_exc() raise ValueError('Unable to fetch input_ref object from workspace: ' + str(e)) # Handle overloading (input_name can be SingleEndLibrary or FeatureSet) # """ if input_type_name == 'SingleEndLibrary': # DEBUG #for k in data: # self.log(console,"SingleEndLibrary ["+k+"]: "+str(data[k])) try: if 'lib' in data: input_forward_reads = data['lib']['file'] elif 'handle' in data: input_forward_reads = data['handle'] else: self.log(console,"bad structure for 'input_forward_reads'") raise ValueError("bad structure for 'input_forward_reads'") ### NOTE: this section is what could be replaced by the transform services input_forward_reads_file_path = os.path.join(self.scratch,input_forward_reads['file_name']) input_forward_reads_file_handle = open(input_forward_reads_file_path, 'w') self.log(console, 'downloading reads file: '+str(input_forward_reads_file_path)) headers = {'Authorization': 'OAuth '+ctx['token']} r = requests.get(input_forward_reads['url']+'/node/'+input_forward_reads['id']+'?download', stream=True, headers=headers) for chunk in r.iter_content(1024): input_forward_reads_file_handle.write(chunk) input_forward_reads_file_handle.close() self.log(console, 'done') ### END NOTE # remove carriage returns new_file_path = input_forward_reads_file_path+"-CRfree" new_file_handle = open(new_file_path, 'w') input_forward_reads_file_handle = open(input_forward_reads_file_path, 'r') for line in input_forward_reads_file_handle: line = re.sub("\r","",line) new_file_handle.write(line) input_forward_reads_file_handle.close() new_file_handle.close() input_forward_reads_file_path = new_file_path # convert FASTQ to FASTA (if necessary) new_file_path = input_forward_reads_file_path+".fna" new_file_handle = open(new_file_path, 'w') if input_forward_reads_file_compression == 'gz': input_forward_reads_file_handle = gzip.open(input_forward_reads_file_path, 'r') else: input_forward_reads_file_handle = open(input_forward_reads_file_path, 'r') header = None last_header = None last_seq_buf = None last_line_was_header = False was_fastq = False for line in input_forward_reads_file_handle: if line.startswith('>'): break elif line.startswith('@'): was_fastq = True header = line[1:] if last_header != None: new_file_handle.write('>'+last_header) new_file_handle.write(last_seq_buf) last_seq_buf = None last_header = header last_line_was_header = True elif last_line_was_header: last_seq_buf = line last_line_was_header = False else: continue if last_header != None: new_file_handle.write('>'+last_header) new_file_handle.write(last_seq_buf) new_file_handle.close() input_forward_reads_file_handle.close() if was_fastq: input_forward_reads_file_path = new_file_path except Exception as e: print(traceback.format_exc()) raise ValueError('Unable to download single-end read library files: ' + str(e)) """ # FeatureSet # # elif input_type_name == 'FeatureSet': if input_type_name == 'FeatureSet': genome_id_feature_id_delim = '.f:' # retrieve sequences for features input_featureSet = data genomeObjName = {} genomeObjVer = {} genomeSciName = {} genome2Features = {} new_id = {} featureSet_elements = input_featureSet['elements'] if 'element_ordering' in input_featureSet and input_featureSet['element_ordering']: feature_order = input_featureSet['element_ordering'] else: feature_order = sorted(featureSet_elements.keys()) for fId in feature_order: genomeRef = featureSet_elements[fId][0] if genomeRef not in genome2Features: genome2Features[genomeRef] = [] new_id[genomeRef] = {} if genome_id_feature_id_delim in fId: [genome_id, feature_id] = fId.split(genome_id_feature_id_delim) else: feature_id = fId genome2Features[genomeRef].append(feature_id) this_id = genomeRef + genome_id_feature_id_delim + feature_id new_id[genomeRef][fId] = this_id # export features to FASTA file input_forward_reads_file_path = os.path.join(self.scratch, input_name+".fasta") self.log(console, 'writing fasta file: '+input_forward_reads_file_path) records_by_fid = dict() proteins_found = 0 for genomeRef in genome2Features: genome_obj = ws.get_objects([{'ref':genomeRef}])[0] genome_type = re.sub('-[0-9]+\.[0-9]+$', "", genome_obj['info'][TYPE_I]) genomeObjName[genomeRef] = genome_obj['info'][NAME_I] genomeObjVer[genomeRef] = genome_obj['info'][VERSION_I] these_genomeFeatureIds = genome2Features[genomeRef] # Genome if genome_type == 'KBaseGenomes.Genome': genome = genome_obj['data'] genomeSciName[genomeRef] = genome['scientific_name'] for feature in genome['features']: if feature['id'] in these_genomeFeatureIds: if 'protein_translation' not in feature or feature['protein_translation'] == None: self.log(invalid_msgs,"bad CDS Feature "+feature['id']+": no protein_translation found") continue else: #self.log(console,"kbase_id: '"+feature['id']+"'") # DEBUG this_id = genomeRef + genome_id_feature_id_delim + feature['id'] this_id = re.sub ('\s', '_', this_id) short_feature_id = re.sub("^.*\.([^\.]+)\.([^\.]+)$", r"\1.\2", feature['id']) genome_disp_name = '' if 'obj_name' in params.get('genome_disp_name_config'): genome_disp_name += genomeObjName[genomeRef] if 'ver' in params.get('genome_disp_name_config'): genome_disp_name += '.v'+str(genomeObjVer[genomeRef]) if genome_type == "KBaseGenomes.Genome" and \ 'sci_name' in params.get('genome_disp_name_config'): genome_disp_name += ': '+genomeSciName[genomeRef] else: genome_disp_name = genomeObjName[genomeRef] row_labels[this_id] = genome_disp_name+' - '+short_feature_id #record = SeqRecord(Seq(feature['protein_translation']), id=feature['id'], description=genome['id']) record = SeqRecord(Seq(feature['protein_translation']), id=this_id, description=genome['id']) proteins_found += 1 records_by_fid[this_id] = record # AnnotatedMetagenomeAssembly elif genome_type == 'KBaseMetagenomes.AnnotatedMetagenomeAssembly': ama_features = self._get_features_from_AnnotatedMetagenomeAssembly (ctx, genomeRef) for feature in ama_features: if feature['id'] in these_genomeFeatureIds: if not feature.get('type'): raise ValueError ("No type for AMA feature "+feature['id']) if feature['type'] != 'CDS': self.log ("skipping non-CDS AMA feature "+feature['id']) continue if not feature.get('protein_translatkon'): self.log(console,"AMA CDS Feature "+feature['id']+": no protein_translation found. Auto-translatiing from dna_sequence") prot_translation = self.TranslateNucToProtSeq(ctx, {'nuc_seq': feature['dna_sequence'], 'genetic_code': '11'}) else: prot_translation = feature['protein_translation'] this_id = genomeRef + genome_id_feature_id_delim + feature['id'] short_feature_id = re.sub("^.*\.([^\.]+)\.([^\.]+)$", r"\1.\2", feature['id']) genome_disp_name = genomeObjName[genomeRef] row_labels[this_id] = genome_disp_name+' - '+short_feature_id record = SeqRecord(Seq(prot_translation), id=this_id, description=genomeObjName[genomeRef]) proteins_found += 1 records_by_fid[this_id] = record if proteins_found < 2: self.log(invalid_msgs,"Less than 2 protein Features (CDS) found. exiting...") else: records = [] for fId in feature_order: genomeRef = featureSet_elements[fId][0] records.append(records_by_fid[new_id[genomeRef][fId]]) SeqIO.write(records, input_forward_reads_file_path, "fasta") # Missing proper input_input_type # else: raise ValueError('Cannot yet handle input_ref type of: '+input_type_name) ### Construct the command # # e.g. muscle -in <fasta_in> -out <fasta_out> -maxiters <n> -haxours <h> # if len(invalid_msgs) == 0: muscle_cmd = [self.MUSCLE_bin] # check for necessary files if not os.path.isfile(self.MUSCLE_bin): raise ValueError("no such file '"+self.MUSCLE_bin+"'") if not os.path.isfile(input_forward_reads_file_path): raise ValueError("no such file '"+input_forward_reads_file_path+"'") elif not os.path.getsize(input_forward_reads_file_path) > 0: raise ValueError("empty file '"+input_forward_reads_file_path+"'. May have not provided any protein coding genes?") # set the output path timestamp = int((datetime.utcnow() - datetime.utcfromtimestamp(0)).total_seconds()*1000) output_dir = os.path.join(self.scratch,'output.'+str(timestamp)) if not os.path.exists(output_dir): os.makedirs(output_dir) output_aln_file_path = os.path.join(output_dir, params['output_name']+'-MSA.fasta') file_extension = '' muscle_cmd.append('-in') muscle_cmd.append(input_forward_reads_file_path) muscle_cmd.append('-out') muscle_cmd.append(output_aln_file_path) # options if 'maxiters' in params and params['maxiters'] != None: muscle_cmd.append('-maxiters') muscle_cmd.append(str(params['maxiters'])) if 'maxhours' in params and params['maxhours'] != None: muscle_cmd.append('-maxhours') muscle_cmd.append(str(params['maxhours'])) # Run MUSCLE, capture output as it happens # self.log(console, 'RUNNING MUSCLE:') self.log(console, ' '+' '.join(muscle_cmd)) # report += "\n"+'running MUSCLE:'+"\n" # report += ' '+' '.join(muscle_cmd)+"\n" p = subprocess.Popen(muscle_cmd, \ cwd = self.scratch, \ stdout = subprocess.PIPE, \ stderr = subprocess.STDOUT, \ shell = False) while True: line = p.stdout.readline().decode() if not line: break self.log(console, line.replace('\n', '')) p.stdout.close() p.wait() self.log(console, 'return code: ' + str(p.returncode)) if p.returncode != 0: raise ValueError('Error running MUSCLE, return code: '+str(p.returncode) + '\n\n'+ '\n'.join(console)) # Parse the FASTA MSA output # self.log(console, 'PARSING MUSCLE MSA FASTA OUTPUT') if not os.path.isfile(output_aln_file_path): raise ValueError("failed to create MUSCLE output: "+output_aln_file_path) elif not os.path.getsize(output_aln_file_path) > 0: raise ValueError("created empty file for MUSCLE output: "+output_aln_file_path) output_aln_file_handle = open (output_aln_file_path, 'r') output_fasta_buf = [] row_order = [] alignment = {} alignment_length = None last_header = None header = None last_seq = '' leading_chars_pattern = re.compile("^\S+") for line in output_aln_file_handle: line = line.rstrip('\n') if line.startswith('>'): header = line[1:] if row_labels: this_id = leading_chars_pattern.findall(header)[0] this_row_label = re.sub ('\s', '_', row_labels[this_id]) output_fasta_buf.append('>'+this_row_label) else: output_fasta_buf.append(line) if last_header != None: last_id = leading_chars_pattern.findall(last_header)[0] row_order.append(last_id) #self.log(console,"ID: '"+last_id+"'\nALN: '"+last_seq+"'") # DEBUG #report += last_id+"\t"+last_seq+"\n" alignment[last_id] = last_seq if alignment_length == None: alignment_length = len(last_seq) elif alignment_length != len(last_seq): raise ValueError ("unequal alignment row for "+last_header+": '"+last_seq+"'") last_header = header last_seq = '' else: last_seq += line output_fasta_buf.append(line) if last_header != None: last_id = leading_chars_pattern.findall(last_header)[0] row_order.append(last_id) #self.log(console,"ID: '"+last_id+"'\nALN: '"+last_seq+"'") # DEBUG #report += last_id+"\t"+last_seq+"\n" alignment[last_id] = last_seq if alignment_length == None: alignment_length = len(last_seq) elif alignment_length != len(last_seq): raise ValueError ("unequal alignment row for "+last_header+": '"+last_seq+"'") output_aln_file_handle.close() # write remapped ids with open(output_aln_file_path, 'w') as output_aln_file_handle: output_aln_file_handle.write("\n".join(output_fasta_buf)+"\n") # load the method provenance from the context object # self.log(console,"SETTING PROVENANCE") # DEBUG provenance = [{}] if 'provenance' in ctx: provenance = ctx['provenance'] # add additional info to provenance here, in this case the input data object reference provenance[0]['input_ws_objects'] = [] provenance[0]['input_ws_objects'].append(params['input_ref']) provenance[0]['service'] = 'kb_muscle' provenance[0]['method'] = 'MUSCLE_prot' # Upload results # if len(invalid_msgs) == 0: self.log(console,"UPLOADING RESULTS") # DEBUG MSA_name = params['output_name'] MSA_description = params['desc'] sequence_type = 'protein' ws_refs = None # may add these later from FeatureSet kb_refs = None # alignment_length # already have # row_order # already have # alignment # already have # NO trim_info # NO alignment_attributes # NO default_row_labels # NO parent_msa_ref # if input_type_name == 'FeatureSet': # features = featureSet['elements'] # genome2Features = {} # for fId in row_order: # genomeRef = features[fId][0] # if genomeRef not in genome2Features: # genome2Features[genomeRef] = [] # genome2Features[genomeRef].append(fId) # # for genomeRef in genome2Features: # genome = ws.get_objects([{'ref':genomeRef}])[0]['data'] # these_genomeFeatureIds = genome2Features[genomeRef] # for feature in genome['features']: # if feature['id'] in these_genomeFeatureIds: output_MSA = { 'name': MSA_name, 'description': MSA_description, 'sequence_type': sequence_type, 'alignment_length': alignment_length, 'row_order': row_order, 'alignment': alignment } if row_labels: output_MSA['default_row_labels'] = row_labels new_obj_info = ws.save_objects({ 'workspace': params['workspace_name'], 'objects':[{ 'type': 'KBaseTrees.MSA', 'data': output_MSA, 'name': params['output_name'], 'meta': {}, 'provenance': provenance }] }) # create CLW formatted output file max_row_width = 60 id_aln_gap_width = 1 gap_chars = '' for sp_i in range(id_aln_gap_width): gap_chars += ' ' # DNA # strong_groups = { 'AG': True, # 'CTU': True # } # weak_groups = None # PROTEINS strong_groups = { 'AST': True, 'EKNQ': True, 'HKNQ': True, 'DENQ': True, 'HKQR': True, 'ILMV': True, 'FILM': True, 'HY': True, 'FWY': True } weak_groups = { 'ACS': True, 'ATV': True, 'AGS': True, 'KNST': True, 'APST': True, 'DGNS': True, 'DEKNQS': True, 'DEHKNQ': True, 'EHKNQR': True, 'FILMV': True, 'FHY': True } clw_buf = [] clw_buf.append ('CLUSTALW format of MUSCLE alignment '+MSA_name+': '+MSA_description) clw_buf.append ('') long_id_len = 0 aln_pos_by_id = dict() for row_id in row_order: aln_pos_by_id[row_id] = 0 if row_labels: row_id_disp = row_labels[row_id] else: row_id_disp = row_id if long_id_len < len(row_id_disp): long_id_len = len(row_id_disp) full_row_cnt = alignment_length // max_row_width if alignment_length % max_row_width == 0: full_row_cnt -= 1 for chunk_i in range (full_row_cnt + 1): for row_id in row_order: if row_labels: row_id_disp = re.sub('\s', '_', row_labels[row_id]) else: row_id_disp = row_id for sp_i in range (long_id_len-len(row_id_disp)): row_id_disp += ' ' aln_chunk_upper_bound = (chunk_i+1)*max_row_width if aln_chunk_upper_bound > alignment_length: aln_chunk_upper_bound = alignment_length aln_chunk = alignment[row_id][chunk_i*max_row_width:aln_chunk_upper_bound] for c in aln_chunk: if c != '-': aln_pos_by_id[row_id] += 1 clw_buf.append (row_id_disp+gap_chars+aln_chunk+' '+str(aln_pos_by_id[row_id])) # conservation line cons_line = '' for pos_i in range(chunk_i*max_row_width, aln_chunk_upper_bound): col_chars = dict() seq_cnt = 0 for row_id in row_order: char = alignment[row_id][pos_i] if char != '-': seq_cnt += 1 col_chars[char] = True if seq_cnt <= 1: cons_char = ' ' elif len(col_chars.keys()) == 1: cons_char = '*' else: strong = False for strong_group in strong_groups.keys(): this_strong_group = True for seen_char in col_chars.keys(): if seen_char not in strong_group: this_strong_group = False break if this_strong_group: strong = True break if not strong: weak = False if weak_groups is not None: for weak_group in weak_groups.keys(): this_weak_group = True for seen_char in col_chars.keys(): if seen_char not in weak_group: this_strong_group = False break if this_weak_group: weak = True if strong: cons_char = ':' elif weak: cons_char = '.' else: cons_char = ' ' cons_line += cons_char lead_space = '' for sp_i in range(long_id_len): lead_space += ' ' lead_space += gap_chars clw_buf.append(lead_space+cons_line) clw_buf.append('') # write clw to file clw_buf_str = "\n".join(clw_buf)+"\n" output_clw_file_path = os.path.join(output_dir, input_name+'-MSA.clw') with open (output_clw_file_path, 'w') as output_clw_file_handle: output_clw_file_handle.write(clw_buf_str) # upload MUSCLE FASTA output to SHOCK for file_links dfu = DFUClient(self.callbackURL) try: output_upload_ret = dfu.file_to_shock({'file_path': output_aln_file_path, # DEBUG # 'make_handle': 0, # 'pack': 'zip'}) 'make_handle': 0}) except: raise ValueError ('error loading aln_out file to shock') # upload MUSCLE CLW output to SHOCK for file_links try: output_clw_upload_ret = dfu.file_to_shock({'file_path': output_clw_file_path, # DEBUG # 'make_handle': 0, # 'pack': 'zip'}) 'make_handle': 0}) except: raise ValueError ('error loading clw_out file to shock') # make HTML reports # # HERE # build output report object # self.log(console,"BUILDING REPORT") # DEBUG reportName = 'muscle_report_'+str(uuid.uuid4()) reportObj = { 'objects_created':[{'ref':params['workspace_name']+'/'+params['output_name'], 'description':'MUSCLE_prot MSA'}], #'message': '', 'message': clw_buf_str, 'file_links': [], 'workspace_name': params['workspace_name'], 'report_object_name': reportName } reportObj['file_links'] = [{'shock_id': output_upload_ret['shock_id'], 'name': params['output_name']+'-MUSCLE_prot.FASTA', 'label': 'MUSCLE_prot FASTA' }, {'shock_id': output_clw_upload_ret['shock_id'], 'name': params['output_name']+'-MUSCLE_prot.CLW', 'label': 'MUSCLE_prot CLUSTALW' }] # save report object # SERVICE_VER = 'release' reportClient = KBaseReport(self.callbackURL, token=ctx['token'], service_ver=SERVICE_VER) #report_info = report.create({'report':reportObj, 'workspace_name':params['workspace_name']}) report_info = reportClient.create_extended_report(reportObj) else: # len(invalid_msgs) > 0 reportName = 'muscle_report_'+str(uuid.uuid4()) report += "FAILURE:\n\n"+"\n".join(invalid_msgs)+"\n" reportObj = { 'objects_created':[], 'text_message':report } ws = workspaceService(self.workspaceURL, token=ctx['token']) report_obj_info = ws.save_objects({ #'id':info[6], 'workspace':params['workspace_name'], 'objects':[ { 'type':'KBaseReport.Report', 'data':reportObj, 'name':reportName, 'meta':{}, 'hidden':1, 'provenance':provenance } ] })[0] report_info = dict() report_info['name'] = report_obj_info[1] report_info['ref'] = str(report_obj_info[6])+'/'+str(report_obj_info[0])+'/'+str(report_obj_info[4]) # done returnVal = { 'report_name': report_info['name'], 'report_ref': report_info['ref'] } self.log(console,"MUSCLE_prot DONE") #END MUSCLE_prot # At some point might do deeper type checking... if not isinstance(returnVal, dict): raise ValueError('Method MUSCLE_prot return value ' + 'returnVal is not type dict as required.') # return the results return [returnVal] def status(self, ctx): #BEGIN_STATUS returnVal = {'state': "OK", 'message': "", 'version': self.VERSION, 'git_url': self.GIT_URL, 'git_commit_hash': self.GIT_COMMIT_HASH} #END_STATUS return [returnVal]

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Python

tests/test_PIHandlerODBC.py

g-parki/tagreader-python

dba867d0ac1e05166e5b0cc3e42557264280727f

[ "MIT" ]

23

2020-04-16T17:23:33.000Z

2022-03-31T21:44:10.000Z

tests/test_PIHandlerODBC.py

g-parki/tagreader-python

dba867d0ac1e05166e5b0cc3e42557264280727f

[ "MIT" ]

62

2020-05-27T11:25:23.000Z

2022-03-11T07:03:48.000Z

tests/test_PIHandlerODBC.py

g-parki/tagreader-python

dba867d0ac1e05166e5b0cc3e42557264280727f

[ "MIT" ]

10

2020-08-18T08:24:27.000Z

2022-03-08T20:53:59.000Z

import pytest import pandas as pd from tagreader import utils from tagreader.utils import ReaderType START_TIME = "2018-01-17 16:00:00" STOP_TIME = "2018-01-17 17:00:00" SAMPLE_TIME = 60 @pytest.fixture(scope="module") def PIHandler(): from tagreader.odbc_handlers import PIHandlerODBC yield PIHandlerODBC( "thehostname.statoil.net", 1234, options={"das_server": "the_das_server"} ) def test_generate_connection_string(PIHandler): res = PIHandler.generate_connection_string() expected = ( "DRIVER={PI ODBC Driver};Server=the_das_server;Trusted_Connection=Yes;" "Command Timeout=1800;Provider Type=PIOLEDB;" "Provider String={Data source=thehostname;Integrated_Security=SSPI;" "Time Zone=UTC};" ) assert expected == res @pytest.mark.parametrize( "read_type", [ "RAW", # pytest.param( # "SHAPEPRESERVING", marks=pytest.mark.skip(reason="Not implemented") # ), "INT", "MIN", "MAX", "RNG", "AVG", "STD", "VAR", # pytest.param("COUNT", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("GOOD", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("BAD", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("TOTAL", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("SUM", marks=pytest.mark.skip(reason="Not implemented")), "SNAPSHOT", ], ) def test_generate_tag_read_query(PIHandler, read_type): starttime = utils.ensure_datetime_with_tz(START_TIME) stoptime = utils.ensure_datetime_with_tz(STOP_TIME) ts = pd.Timedelta(SAMPLE_TIME, unit="s") if read_type == "SNAPSHOT": res = PIHandler.generate_read_query( "thetag", None, None, None, getattr(ReaderType, read_type) ) else: res = PIHandler.generate_read_query( "thetag", starttime, stoptime, ts, getattr(ReaderType, read_type) ) expected = { "RAW": ( "SELECT TOP 100000 CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[picomp2] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "ORDER BY time" ), "INT": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[piinterp2] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "MIN": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[pimin] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "MAX": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[pimax] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "RNG": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[pirange] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "AVG": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[piavg] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "STD": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[pistd] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "VAR": ( "SELECT POWER(CAST(value as FLOAT32), 2) AS value, time " "FROM [piarchive]..[pistd] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "SNAPSHOT": ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[pisnapshot] WHERE tag='thetag'" ), } assert expected[read_type] == res @pytest.mark.parametrize( "read_type", [ "RAW", # pytest.param( # "SHAPEPRESERVING", marks=pytest.mark.skip(reason="Not implemented") # ), "INT", "MIN", "MAX", "RNG", "AVG", "STD", "VAR", # pytest.param("COUNT", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("GOOD", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("BAD", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("TOTAL", marks=pytest.mark.skip(reason="Not implemented")), # pytest.param("SUM", marks=pytest.mark.skip(reason="Not implemented")), "SNAPSHOT", ], ) def test_generate_tag_read_query_with_status(PIHandler, read_type): starttime = utils.ensure_datetime_with_tz(START_TIME) stoptime = utils.ensure_datetime_with_tz(STOP_TIME) ts = pd.Timedelta(SAMPLE_TIME, unit="s") if read_type == "SNAPSHOT": res = PIHandler.generate_read_query( "thetag", None, None, None, getattr(ReaderType, read_type), get_status=True ) else: res = PIHandler.generate_read_query( "thetag", starttime, stoptime, ts, getattr(ReaderType, read_type), get_status=True, ) expected = { "RAW": ( "SELECT TOP 100000 CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[picomp2] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "ORDER BY time" ), "INT": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[piinterp2] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "MIN": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[pimin] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "MAX": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[pimax] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "RNG": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[pirange] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "AVG": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[piavg] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "STD": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[pistd] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "VAR": ( "SELECT POWER(CAST(value as FLOAT32), 2) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[pistd] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '60s') ORDER BY time" ), "SNAPSHOT": ( "SELECT CAST(value as FLOAT32) AS value, " "status, questionable, substituted, time " "FROM [piarchive]..[pisnapshot] WHERE tag='thetag'" ), } assert expected[read_type] == res def test_genreadquery_long_sampletime(PIHandler): starttime = utils.ensure_datetime_with_tz(START_TIME) stoptime = utils.ensure_datetime_with_tz(STOP_TIME) ts = pd.Timedelta(86401, unit="s") res = PIHandler.generate_read_query( "thetag", starttime, stoptime, ts, ReaderType.INT ) expected = ( "SELECT CAST(value as FLOAT32) AS value, time " "FROM [piarchive]..[piinterp2] WHERE tag='thetag' " "AND (time BETWEEN '17-Jan-18 15:00:00' AND '17-Jan-18 16:00:00') " "AND (timestep = '86401s') ORDER BY time" ) assert expected == res

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