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# -*- coding: utf-8 -*- # # rtk.dao.RTKMatrix.py is part of The RTK Project # # All rights reserved. # Copyright 2007 - 2017 Andrew Rowland andrew.rowland <AT> reliaqual <DOT> com """ =============================================================================== The RTKMatrix Table =============================================================================== """ # pylint: disable=E0401 from sqlalchemy import Column, ForeignKey, Integer, String from sqlalchemy.orm import relationship # pylint: disable=E0401 # Import other RTK modules. from Utilities import none_to_default # pylint: disable=E0401 from dao.RTKCommonDB import RTK_BASE # pylint: disable=E0401 class RTKMatrix(RTK_BASE): """ Class to represent the rtk_matrix table in the RTK Program database. Matrix types are one of the following: +-------------+--------------+--------------+ | Row Table | Column Table | Matrix Type | +-------------+--------------+--------------+ | Function | Hardware | fnctn_hrdwr | +-------------+--------------+--------------+ | Function | Software | fnctn_sftwr | +-------------+--------------+--------------+ | Function | Validation | fnctn_vldtn | +-------------+--------------+--------------+ | Requirement | Hardware | rqrmnt_hrdwr | +-------------+--------------+--------------+ | Requirement | Software | rqrmnt_sftwr | +-------------+--------------+--------------+ | Requirement | Validation | rqrmnt_vldtn | +-------------+--------------+--------------+ | Hardware | Testing | hrdwr_tstng | +-------------+--------------+--------------+ | Hardware | Validation | hrdwr_vldtn | +-------------+--------------+--------------+ | Software | Risk | sftwr_rsk | +-------------+--------------+--------------+ | Software | Validation | sftwr_vldtn | +-------------+--------------+--------------+ The primary key for this table consists of the revision_id, matrix_id, column_item_id, and row_item_id. This table shares a Many-to-One relationship with rtk_revision. """ __tablename__ = 'rtk_matrix' __table_args__ = {'extend_existing': True} revision_id = Column( 'fld_revision_id', Integer, ForeignKey('rtk_revision.fld_revision_id'), primary_key=True, nullable=False) matrix_id = Column('fld_matrix_id', Integer, primary_key=True, default=0) column_id = Column('fld_column_id', Integer, default=0) column_item_id = Column( 'fld_column_item_id', Integer, primary_key=True, default=0) matrix_type = Column('fld_matrix_type', String(128), default='') parent_id = Column('fld_parent_id', Integer, default=0) row_id = Column('fld_row_id', Integer, default=0) row_item_id = Column( 'fld_row_item_id', Integer, primary_key=True, default=0) value = Column('fld_value', Integer, default=0) # Define the relationships to other tables in the RTK Program database. revision = relationship('RTKRevision', back_populates='matrix') def get_attributes(self): """ Retrieve the current values of the RTKMatrix data model attributes. :return: {revision_id, matrix_id, column_id, column_item_id, parent_id, row_id, row_item_id, type_id, value} pairs. :rtype: tuple """ _attributes = { 'revision_id': self.revision_id, 'matrix_id': self.matrix_id, 'column_id': self.column_id, 'column_item_id': self.column_item_id, 'matrix_type': self.matrix_type, 'parent_id': self.parent_id, 'row_id': self.row_id, 'row_item_id': self.row_item_id, 'value': self.value } return _attributes def set_attributes(self, values): """ Set the RTKMatrix data model attributes. :param tuple values: tuple of values to assign to the instance attributes. :return: (_code, _msg); the error code and error message. :rtype: tuple """ _error_code = 0 _msg = "RTK SUCCESS: Updating RTKMatrix {0:d} attributes.". \ format(self.matrix_id) try: self.column_id = int(none_to_default(values['column_id'], 0)) self.column_item_id = int( none_to_default(values['column_item_id'], 0)) self.matrix_type = str(none_to_default(values['matrix_type'], '')) self.parent_id = int(none_to_default(values['parent_id'], 0)) self.row_id = int(none_to_default(values['row_id'], 0)) self.row_item_id = int(none_to_default(values['row_item_id'], 0)) self.value = float(none_to_default(values['value'], 0.0)) except KeyError as _err: _error_code = 40 _msg = "RTK ERROR: Missing attribute {0:s} in attribute " \ "dictionary passed to " \ "RTKMatrix.set_attributes().".format(_err) return _error_code, _msg
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import os import shutil def pull_default(folder=None): cwd = os.getcwd() if None == folder: folder = cwd for path in os.listdir(folder): project_path = os.path.join(folder, path) if os.path.isdir(project_path): dot_git_folder = os.path.join(project_path, '.git') if os.path.isdir(dot_git_folder): print('[git pull start] {}'.format(project_path)) os.chdir(project_path) os.system('git pull') print('[git pull end] {}'.format(project_path)) os.chdir(cwd) pull_default() input('按回车结束')
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from django.conf.urls.defaults import * # Uncomment the next two lines to enable the admin: # from django.contrib import admin # admin.autodiscover() urlpatterns = patterns('', # Example: # (r'^pyogp_webbot/', include('pyogp_webbot.foo.urls')), # Uncomment the admin/doc line below and add 'django.contrib.admindocs' # to INSTALLED_APPS to enable admin documentation: # (r'^admin/doc/', include('django.contrib.admindocs.urls')), # Uncomment the next line to enable the admin: # (r'^admin/', include(admin.site.urls)), (r'^$', 'pyogp_webbot.login.views.index'), (r'^pyogp_webbot/$', 'pyogp_webbot.login.views.index'), (r'^pyogp_webbot/login/$', 'pyogp_webbot.login.views.login'), (r'^pyogp_webbot/login/login_request/$', 'pyogp_webbot.login.views.login_request'), )
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''' code emitters ''' import out, enums as e class s: ''' state ''' # long_len # arg_regs, arg_regs_n # regs # stack_regs pass def init (long_len): s.long_len = long_len if long_len == 8: s.arg_regs = ['%rdi', '%rsi', '%rdx', '%rcx', 'r8', 'r9'] s.arg_regs_n = len(s.arg_regs) s.regs = ['%rax', '%rbx', '%r10'] s.stack_regs = ['%rsp', '%rbp'] elif long_len == 4: s.arg_regs = [] s.arg_regs_n = 0 s.regs = ['%eax', '%ebx', '%ecx'] s.stack_regs = ['%esp', '%ebp'] else: out.error ('what year is this???') return False return True def emit (fn_cur, et, val, val2 = None): if et == e.EMIT_DEF: out.put ('.section .text', i_n = 0) out.put ('.globl ' + val, i_n = 0) out.put (val + ':', i_n = 0) out.put ('push ' + s.stack_regs [1]) out.put ('mov ' + s.stack_regs [0] + ', ' + s.stack_regs [1]) out.put ('xor ' + s.regs [0] + ', ' + s.regs [0]) elif et == e.EMIT_RET: if val: if not get_val (fn_cur, val, s.regs [0]): return False out.put ('pop ' + s.stack_regs [0]) out.put ('ret') elif et == e.EMIT_END: if not fn_cur.flow_ret_t: out.put ('pop ' + s.stack_regs [1]) out.put ('ret') if fn_cur.data_n: out.put ('.section .data', i_n = 0) for datum in fn_cur.data: if datum._type == e.DATA_LONG: out.put (datum.name_s + ': .zero ' + str(datum._len), i_n = 0) elif datum._type == e.DATA_LARRAY: out.put (datum.name_s + ': .zero ' + str(datum._len), i_n = 0) elif datum._type == e.DATA_STR: out.put (datum.name_s + ': .string ' + datum.val, i_n = 0) elif et == e.EMIT_CALL: arg_n = len (val2) for arg_i, arg in enumerate (val2): if arg_i < s.arg_regs_n: if not get_val (fn_cur, arg, s.arg_regs [arg_i]): return False else: if not get_val (fn_cur, arg, s.regs [0]): return False out.put ('push ' + s.regs [0]) out.put ('call ' + val) if arg_n > s.arg_regs_n: out.put ('add $' + str((arg_n - s.arg_regs_n) * s.long_len) +\ ', ' + s.stack_regs [0]) elif et == e.EMIT_PUSH: if not get_val (fn_cur, val, s.regs [0]): return False out.put ('push ' + s.regs [0]) elif et == e.EMIT_IF: if not get_val (fn_cur, val, s.regs [0]): return False out.put ('test ' + s.regs [0] + ', ' + s.regs [0]) out.put ('jz ' + fn_cur.name_s + '.else.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1])) elif et == e.EMIT_ELSE: out.put ('jmp ' + fn_cur.name_s + '.endif.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1])) out.put (fn_cur.name_s + '.else.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1]) + ':', i_n = 0) elif et == e.EMIT_ENDIF: out.put (fn_cur.name_s + '.endif.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1]) + ':', i_n = 0) elif et == e.EMIT_WHILE: out.put (fn_cur.name_s + '.while.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1]) + ':', i_n = 0) if not get_val (fn_cur, val, s.regs [0]): return False out.put ('test ' + s.regs [0] + ', ' + s.regs [0]) out.put ('jz ' + fn_cur.name_s + '.wend.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1])) elif et == e.EMIT_WEND: out.put ('jmp ' + fn_cur.name_s + '.while.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1])) out.put (fn_cur.name_s + '.wend.' +\ str(fn_cur.flow_cur [fn_cur.flow_n - 1][1]) + ':', i_n = 0) elif et == e.EMIT_ADD: if not get_val (fn_cur, val, s.regs [1]): return False out.put ('add ' + s.regs [1] + ', ' + s.regs [0]) elif et == e.EMIT_SUB: if not get_val (fn_cur, val, s.regs [1]): return False out.put ('sub ' + s.regs [1] + ', ' + s.regs [0]) elif et == e.EMIT_MUL: if not get_val (fn_cur, val, s.regs [1]): return False out.put ('imul ' + s.regs [1] + ', ' + s.regs [0]) elif et == e.EMIT_DIV: if not get_val (fn_cur, val, s.regs [1]): return False out.put ('cltd') out.put ('idiv ' + s.regs [1]) elif et == e.EMIT_RES: if not set_val (fn_cur, val): return False elif et == e.EMIT_SET: if not get_val (fn_cur, val2, s.regs [0]): return False if not set_val (fn_cur, val): return False elif et == e.EMIT_ADDTO: if not get_val (fn_cur, val2, s.regs [1]): return False if not get_val (fn_cur, val, s.regs [0]): return False out.put ('add ' + s.regs [1] + ', ' + s.regs [0]) if not set_val (fn_cur, val): return False elif et == e.EMIT_SUBFROM: if not get_val (fn_cur, val2, s.regs [1]): return False if not get_val (fn_cur, val, s.regs [0]): return False out.put ('sub ' + s.regs [1] + ', ' + s.regs [0]) if not set_val (fn_cur, val): return False elif et == e.EMIT_MULTO: if not get_val (fn_cur, val2, s.regs [1]): return False if not get_val (fn_cur, val, s.regs [0]): return False out.put ('imul ' + s.regs [1] + ', ' + s.regs [0]) if not set_val (fn_cur, val): return False elif et == e.EMIT_DIVFROM: if not get_val (fn_cur, val2, s.regs [1]): return False if not get_val (fn_cur, val, s.regs [0]): return False out.put ('cltd') out.put ('idiv ' + s.regs [1]) if not set_val (fn_cur, val): return False else: out.put ('uknown emit type') return False return True def get_val (fn_cur, val, reg): val_type = get_val_type (val) if not val_type: out.error ('unknown val type "' + val + '"') return False elif val_type == e.VAL_LARRAY: datum = fn_cur.def_data ('.l' + str(fn_cur.data_larray_n),\ e.DATA_LARRAY, val) out.put ('mov ' + '$' + datum.name_s + ', ' + reg) elif val_type == e.VAL_STR: datum = fn_cur.def_data ('.s' + str(fn_cur.data_str_n),\ e.DATA_STR, val) out.put ('mov ' + '$' + datum.name_s + ', ' + reg) elif val_type == e.VAL_LONG: out.put ('mov $' + val + ', ' + reg) elif val_type == e.VAL_VAR: arg_i = fn_cur.get_arg (val) if arg_i: arg_i -= 1 if arg_i < s.arg_regs_n: _s = s.arg_regs [arg_i] else: _s = str((arg_i + 1) * s.long_len) + '(' + s.stack_regs [1] +\ ')' out.put ('mov ' + _s + ', ' + reg) else: var = fn_cur.get_or_def_var (val) if not var: return False out.put ('mov ' + var.datum.name_s + ', ' + reg) elif val_type == e.VAL_VAR_DEREF: _n = val [1:] arg_i = fn_cur.get_arg (_n) if arg_i: # TODO support this out.error ('dereferencing arg') return False else: var = fn_cur.get_or_def_var (_n) if not var: return False out.put ('mov ' + var.datum.name_s + ', ' + reg) out.put ('mov (' + reg + '), ' + reg) return True def set_val (fn_cur, val): reg0 = s.regs [0] reg2 = s.regs [2] val_type = get_val_type (val) if \ val_type == e.VAL_STR or\ val_type == e.VAL_LARRAY or\ val_type == e.VAL_LONG: out.error ('can\'t assign to this type') return False elif val_type == e.VAL_VAR: arg_i = fn_cur.get_arg (val) if arg_i: arg_i -= 1 if arg_i < s.arg_regs_n: _s = s.arg_regs [arg_i] else: _s = str((arg_i + 1) * s.long_len) + '(' + s.stack_regs [1] +\ ')' out.put ('mov ' + reg0 + ', ' + _s) else: var = fn_cur.get_or_def_var (val) if not var: return False out.put ('mov ' + reg0 + ', ' + var.datum.name_s) elif val_type == e.VAL_VAR_DEREF: _n = val [1:] arg_i = fn_cur.get_arg (_n) if arg_i: out.error ('can\'t modify function arg') return False else: var = fn_cur.get_or_def_var (_n) if not var: return False out.put ('mov ' + var.datum.name_s + ', ' + reg2) out.put ('mov ' + reg0 + ', (' + reg2 + ')') return True def get_val_type (_s): if not _s: return e.VAL_NONE elif _s [0] == '-' or _s.isdigit () or _s [0] == "'": return e.VAL_LONG elif _s [0] == '[': return e.VAL_LARRAY elif _s [0] == '"': return e.VAL_STR elif _s [0] == '@': return e.VAL_VAR_DEREF else: return e.VAL_VAR
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""" GravMag: Classic 3D Euler deconvolution of magnetic data using an expanding window """ from fatiando import logger, mesher, gridder, utils, gravmag from fatiando.vis import mpl, myv log = logger.get() log.info(logger.header()) # Make a model bounds = [-5000, 5000, -5000, 5000, 0, 5000] model = [ mesher.Prism(-1500, -500, -1500, -500, 1000, 2000, {'magnetization':2}), mesher.Prism(500, 1500, 500, 2000, 1000, 2000, {'magnetization':2})] # Generate some data from the model shape = (100, 100) area = bounds[0:4] xp, yp, zp = gridder.regular(area, shape, z=-1) # Add a constant baselevel baselevel = 10 # Convert from nanoTesla to Tesla because euler and derivatives require things # in SI tf = (utils.nt2si(gravmag.prism.tf(xp, yp, zp, model, inc=-45, dec=0)) + baselevel) # Calculate the derivatives using FFT xderiv = gravmag.fourier.derivx(xp, yp, tf, shape) yderiv = gravmag.fourier.derivy(xp, yp, tf, shape) zderiv = gravmag.fourier.derivz(xp, yp, tf, shape) mpl.figure() titles = ['Total field', 'x derivative', 'y derivative', 'z derivative'] for i, f in enumerate([tf, xderiv, yderiv, zderiv]): mpl.subplot(2, 2, i + 1) mpl.title(titles[i]) mpl.axis('scaled') mpl.contourf(yp, xp, f, shape, 50) mpl.colorbar() mpl.m2km() mpl.show() # Pick the centers of the expanding windows # The number of final solutions will be the number of points picked mpl.figure() mpl.suptitle('Pick the centers of the expanding windows') mpl.axis('scaled') mpl.contourf(yp, xp, tf, shape, 50) mpl.colorbar() centers = mpl.pick_points(area, mpl.gca(), xy2ne=True) # Run the euler deconvolution on an expanding window # Structural index is 3 index = 3 results = [] for center in centers: results.append( gravmag.euler.expanding_window(xp, yp, zp, tf, xderiv, yderiv, zderiv, index, gravmag.euler.classic, center, 500, 5000)) print "Base level used: %g" % (baselevel) print "Estimated base level: %g" % (results[-1]['baselevel']) print "Estimated source location: %s" % (str(results[-1]['point'])) myv.figure() myv.points([r['point'] for r in results], size=300.) myv.prisms(model, opacity=0.5) axes = myv.axes(myv.outline(bounds), ranges=[b*0.001 for b in bounds]) myv.wall_bottom(bounds) myv.wall_north(bounds) myv.show()
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# Generated by Django 2.1.5 on 2019-01-22 09:39 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('popmemes', '0001_initial'), ] operations = [ migrations.RenameModel( old_name='Popmemes', new_name='PopImage', ), ]
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# Copyright 2019 The AmpliGraph Authors. All Rights Reserved. # # This file is Licensed under the Apache License, Version 2.0. # A copy of the Licence is available in LICENCE, or at: # # http://www.apache.org/licenses/LICENSE-2.0 # from ampligraph.datasets import load_wn18, load_fb15k, load_fb15k_237, load_yago3_10, load_wn18rr, load_wn11, load_fb13 from ampligraph.datasets.datasets import _clean_data import numpy as np def test_clean_data(): X = { 'train': np.array([['a', 'b', 'c'], ['d', 'e', 'f'], ['g', 'h', 'i'], ['j', 'k', 'l']]), 'valid': np.array([['a', 'b', 'c'], ['x', 'e', 'f'], ['g', 'a', 'i'], ['j', 'k', 'y']]), 'test': np.array([['a', 'b', 'c'], ['d', 'e', 'x'], ['g', 'b', 'i'], ['y', 'k', 'l']]), } clean_X, valid_idx, test_idx = _clean_data(X, return_idx=True) np.testing.assert_array_equal(clean_X['train'], X['train']) np.testing.assert_array_equal(clean_X['valid'], np.array([['a', 'b', 'c']])) np.testing.assert_array_equal(clean_X['test'], np.array([['a', 'b', 'c'], ['g', 'b', 'i']])) np.testing.assert_array_equal(valid_idx, np.array([True, False, False, False])) np.testing.assert_array_equal(test_idx, np.array([True, False, True, False])) def test_load_wn18(): wn18 = load_wn18() assert len(wn18['train']) == 141442 assert len(wn18['valid']) == 5000 assert len(wn18['test']) == 5000 ent_train = np.union1d(np.unique(wn18["train"][:, 0]), np.unique(wn18["train"][:, 2])) ent_valid = np.union1d(np.unique(wn18["valid"][:, 0]), np.unique(wn18["valid"][:, 2])) ent_test = np.union1d(np.unique(wn18["test"][:, 0]), np.unique(wn18["test"][:, 2])) distinct_ent = np.union1d(np.union1d(ent_train, ent_valid), ent_test) distinct_rel = np.union1d(np.union1d(np.unique(wn18["train"][:, 1]), np.unique(wn18["train"][:, 1])), np.unique(wn18["train"][:, 1])) assert len(distinct_ent) == 40943 assert len(distinct_rel) == 18 def test_load_fb15k(): fb15k = load_fb15k() assert len(fb15k['train']) == 483142 assert len(fb15k['valid']) == 50000 assert len(fb15k['test']) == 59071 # ent_train = np.union1d(np.unique(fb15k["train"][:,0]), np.unique(fb15k["train"][:,2])) # ent_valid = np.union1d(np.unique(fb15k["valid"][:,0]), np.unique(fb15k["valid"][:,2])) # ent_test = np.union1d(np.unique(fb15k["test"][:,0]), np.unique(fb15k["test"][:,2])) # distinct_ent = np.union1d(np.union1d(ent_train, ent_valid), ent_test) # distinct_rel = np.union1d(np.union1d(np.unique(fb15k["train"][:,1]), np.unique(fb15k["train"][:,1])), # np.unique(fb15k["train"][:,1])) # assert len(distinct_ent) == 14951 # assert len(distinct_rel) == 1345 def test_load_fb15k_237(): fb15k_237 = load_fb15k_237() assert len(fb15k_237['train']) == 272115 # - 9 because 9 triples containing unseen entities are removed assert len(fb15k_237['valid']) == 17535 - 9 # - 28 because 28 triples containing unseen entities are removed assert len(fb15k_237['test']) == 20466 - 28 def test_yago_3_10(): yago_3_10 = load_yago3_10() assert len(yago_3_10['train']) == 1079040 assert len(yago_3_10['valid']) == 5000 - 22 assert len(yago_3_10['test']) == 5000 - 18 # ent_train = np.union1d(np.unique(yago_3_10["train"][:,0]), np.unique(yago_3_10["train"][:,2])) # ent_valid = np.union1d(np.unique(yago_3_10["valid"][:,0]), np.unique(yago_3_10["valid"][:,2])) # ent_test = np.union1d(np.unique(yago_3_10["test"][:,0]), np.unique(yago_3_10["test"][:,2])) # assert len(set(ent_valid) - set(ent_train)) == 22 # assert len (set(ent_test) - ((set(ent_valid) & set(ent_train)) | set(ent_train))) == 18 # distinct_ent = np.union1d(np.union1d(ent_train, ent_valid), ent_test) # distinct_rel = np.union1d(np.union1d(np.unique(yago_3_10["train"][:,1]), np.unique(yago_3_10["train"][:,1])), # np.unique(yago_3_10["train"][:,1])) # assert len(distinct_ent) == 123182 # assert len(distinct_rel) == 37 def test_wn18rr(): wn18rr = load_wn18rr() ent_train = np.union1d(np.unique(wn18rr["train"][:, 0]), np.unique(wn18rr["train"][:, 2])) ent_valid = np.union1d(np.unique(wn18rr["valid"][:, 0]), np.unique(wn18rr["valid"][:, 2])) ent_test = np.union1d(np.unique(wn18rr["test"][:, 0]), np.unique(wn18rr["test"][:, 2])) distinct_ent = np.union1d(np.union1d(ent_train, ent_valid), ent_test) distinct_rel = np.union1d(np.union1d(np.unique(wn18rr["train"][:, 1]), np.unique(wn18rr["train"][:, 1])), np.unique(wn18rr["train"][:, 1])) assert len(wn18rr['train']) == 86835 # - 210 because 210 triples containing unseen entities are removed assert len(wn18rr['valid']) == 3034 - 210 # - 210 because 210 triples containing unseen entities are removed assert len(wn18rr['test']) == 3134 - 210 def test_wn11(): wn11 = load_wn11(clean_unseen=False) assert len(wn11['train']) == 110361 assert len(wn11['valid']) == 5215 assert len(wn11['test']) == 21035 assert len(wn11['valid_labels']) == 5215 assert len(wn11['test_labels']) == 21035 assert sum(wn11['valid_labels']) == 2606 assert sum(wn11['test_labels']) == 10493 wn11 = load_wn11(clean_unseen=True) assert len(wn11['train']) == 110361 assert len(wn11['valid']) == 5215 - 338 assert len(wn11['test']) == 21035 - 1329 assert len(wn11['valid_labels']) == 5215 - 338 assert len(wn11['test_labels']) == 21035 - 1329 assert sum(wn11['valid_labels']) == 2409 assert sum(wn11['test_labels']) == 9706 def test_fb13(): fb13 = load_fb13(clean_unseen=False) assert len(fb13['train']) == 316232 assert len(fb13['valid']) == 5908 + 5908 assert len(fb13['test']) == 23733 + 23731 assert len(fb13['valid_labels']) == 5908 + 5908 assert len(fb13['test_labels']) == 23733 + 23731 assert sum(fb13['valid_labels']) == 5908 assert sum(fb13['test_labels']) == 23733 fb13 = load_fb13(clean_unseen=True) assert len(fb13['train']) == 316232 assert len(fb13['valid']) == 5908 + 5908 assert len(fb13['test']) == 23733 + 23731 assert len(fb13['valid_labels']) == 5908 + 5908 assert len(fb13['test_labels']) == 23733 + 23731 assert sum(fb13['valid_labels']) == 5908 assert sum(fb13['test_labels']) == 23733
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from io import StringIO from math import atan2, ceil from typing import Literal, Union, overload from common import PI, Real, TWOPI, deg, real, reduce_angle from functions import qbezeir_svg_given_middle from .circle import CircleBase, FixedCircle from .point import PointBase, Polar def check_arc(value: float, /): if not (0 < value < TWOPI): raise ValueError(f'arc should be in range (0°, 360°), got {deg(value):.0g}°') class SectorBase: __slots__ = '_circle', '_arc', '_arm' def __init__(self, circle: FixedCircle, arc: float, arm: float, /): self._circle = circle self._arc = arc self._arm = arm @property def circle(self, /): return self._circle @property def arc(self, /): return self._arc @property def start_arm(self, /): return self._arm @property def end_arm(self, /): return self._arm - self._arc @property def end_arm_reduced(self, /): return reduce_angle(self.end_arm) def __repr__(self, /): return ( f'{self.__class__.__name__}(' f'{self.circle}, ' f'arc={deg(self.arc):.0f}°, ' f'start_arm={deg(self.start_arm):.0f}°' f')' ) def copy(self, /): return self.__class__(self.circle.copy(), self.arc, self.start_arm) def __getnewargs__(self, /): return self._circle, self._arc, self._arm def fix(self, /) -> 'FixedSector': raise NotImplementedError def unfix(self, /) -> 'MutableSector': raise NotImplementedError def __eq__(self, other, /): if isinstance(other, SectorBase): return self.arc == other.arc and self.start_arm == self.start_arm and self.circle == other.circle return NotImplemented def __ne__(self, other, /): if isinstance(other, SectorBase): return self.arc != other.arc or self.start_arm != self.start_arm or self.circle != other.circle return NotImplemented def is_angle_inside(self, fi: Real, /) -> bool: fi = reduce_angle(fi) start = self.start_arm end = self.end_arm_reduced if end > start: return end <= fi <= PI or -PI < fi <= start return end <= fi <= start def is_point_inside(self, p: PointBase, /) -> bool: # Another way https://stackoverflow.com/a/13675772 x = p.x - self.circle.center.x y = p.y - self.circle.center.y r2 = x * x + y * y if r2 == 0: return True if r2 > self.circle.r2: return False return self.is_angle_inside(atan2(y, x)) def __contains__(self, item, /): if isinstance(item, real): return self.is_angle_inside(item) if isinstance(item, PointBase): return self.is_point_inside(item) return False def as_plotly_shape(self, step_angle: Real = PI / 6, /) -> dict: # Simulate circle arc with quadratic Bezier curves center = self.circle.center r = self.circle.radius n = ceil(self.arc / step_angle) - 1 p0 = Polar(r, self.start_arm) + center path = StringIO() path.write( f'M {center.x} {center.y} ' f'L {p0.x} {p0.y} ' ) arm = self.start_arm for _ in range(n): pm = Polar(r, arm - step_angle / 2) + center arm -= step_angle p2 = Polar(r, arm) + center path.write(f'{qbezeir_svg_given_middle(p0, p2, pm)} ') p0 = p2 p2 = Polar(r, self.end_arm) + center pm = Polar(r, (arm + self.end_arm) / 2) + center path.write(f'{qbezeir_svg_given_middle(p0, p2, pm)} Z') return dict( type='path', path=path.getvalue() ) class FixedSector(SectorBase): __slots__ = '_hash', def __init__(self, circle: FixedCircle, arc: float, arm: float, /): super().__init__(circle, arc, arm) self._hash = hash(frozenset((circle, arc, arm))) def fix(self, /): return self def unfix(self, /): return MutableSector(self.circle, self.arc, self.start_arm) def __hash__(self, /): return self._hash class MutableSector(SectorBase): __slots__ = () # TODO: add circle changing @property def arc(self, /): return self._arc @arc.setter def arc(self, value: Real, /): check_arc(value) self._arc = float(value) @property def start_arm(self, /): return self._arm @start_arm.setter def start_arm(self, value: Real, /): self._arm = reduce_angle(float(value)) @property def end_arm(self, /): return self._arm - self._arc @end_arm.setter def end_arm(self, value: Real, /): self._arm = reduce_angle(value + self._arc) def fix(self, /): return FixedSector(self.circle, self.arc, self.start_arm) def unfix(self, /): return self def rotate(self, angle: Real, /): """ Rotates the sector by the given angle clockwise """ self.start_arm -= angle @overload def Sector(circle: CircleBase, arc: Real, start_arm: Real = PI, /) -> FixedSector: ... @overload def Sector(circle: CircleBase, arc: Real, start_arm: Real = PI, /, *, fix: Literal[True]) -> FixedSector: ... @overload def Sector(circle: CircleBase, arc: Real, start_arm: Real = PI, /, *, fix: Literal[False]) -> MutableSector: ... @overload def Sector(circle: CircleBase, arc: Real, start_arm: Real = PI, /, *, fix: bool) -> Union[FixedSector, MutableSector]: ... def Sector(circle: CircleBase, arc: Real, start_arm: Real = PI, /, *, fix: bool = True) -> SectorBase: check_arc(arc) arc = float(arc) start_arm = float(start_arm) if fix: return FixedSector(circle.fix(), arc, start_arm) return MutableSector(circle.fix(), arc, start_arm)
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import os COL_SEPARATOR = "\t" MULTI_SEPARATOR = "$" for neFile in os.listdir('data/'): neFile = 'data/' + neFile out_filename = neFile.replace('.tsv', "_mh.tsv") if os.path.isfile(out_filename) or '_mh' in neFile or os.path.isdir(neFile): continue out_f = open(out_filename, "w") with open(neFile, "r") as in_f: for line in in_f: if len(line) > 2: token_attrs = line.rstrip().split(COL_SEPARATOR) if (token_attrs[1] == "O") and (token_attrs[2] == "O"): new_label = "O" elif (token_attrs[1] != "O") and (token_attrs[2] == "O"): new_label = token_attrs[1] elif (token_attrs[1] == "O") and (token_attrs[2] != "O"): new_label = token_attrs[2] else: labels = [token_attrs[1], token_attrs[2]] labels.sort() new_label = labels[0] + MULTI_SEPARATOR + labels[1] out_f.write(token_attrs[0] + COL_SEPARATOR + new_label + "\n") else: out_f.write(line) out_f.close()
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import os import sys from pprint import pprint import click from pykechain.utils import temp_chdir from kecpkg.commands.utils import CONTEXT_SETTINGS from kecpkg.gpg import get_gpg, list_keys, hash_of_file from kecpkg.settings import SETTINGS_FILENAME, GNUPG_KECPKG_HOME, load_settings, DEFAULT_SETTINGS, ARTIFACTS_FILENAME, \ ARTIFACTS_SIG_FILENAME from kecpkg.utils import remove_path, echo_info, echo_success, echo_failure, get_package_dir, unzip_package @click.command(context_settings=CONTEXT_SETTINGS, short_help="Perform package signing and key management.") @click.argument('package', required=False) @click.option('--settings', '--config', '-s', 'settings_filename', help="path to the setting file (default `{}`".format(SETTINGS_FILENAME), type=click.Path(), default=SETTINGS_FILENAME) @click.option('--keyid', '--key-id', '-k', 'keyid', help="ID (name, email, KeyID) of the cryptographic key to do the operation with. ") # @click.option('--passphrase', '-p', 'sign_passphrase', hide_input=True, # help="Passphrase of the cryptographic key to sign the contents of the package. " # "Use in combination with `--sign` and `--keyid`") @click.option('--import-key', '--import', '-i', 'do_import', type=click.Path(exists=True), help="Import secret keyfile (in .asc) to the KECPKG keyring which will be used for signing. " "You can export a created key in gpg with `gpg -a --export-secret-key [keyID] > secret_key.asc`.") @click.option('--delete-key', '-d', 'do_delete_key', help="Delete key by its fingerprint permanently from the KECPKG keyring. To retrieve the full " "fingerprint of the key, use the `--list` option and look at the 'fingerprint' section.") @click.option('--create-key', '-c', 'do_create_key', is_flag=True, help="Create secret key and add it to the KECPKG keyring.") @click.option('--export-key', '--export', '-e', 'do_export_key', type=click.Path(), help="Export public key to filename with `--keyid KeyID` in .ASC format for public distribution.") @click.option('--clear-keyring', 'do_clear', is_flag=True, default=False, help="Clear all keys from the KECPKG keyring") @click.option('--list', '-l', 'do_list', is_flag=True, help="List all available keys in the KECPKG keyring") @click.option('--verify-kecpkg', 'do_verify_kecpkg', type=click.Path(exists=True), help="Verify contents and signature of an existing kecpkg.") @click.option('--yes', '-y', 'do_yes', is_flag=True, help="Don't ask questions, just do it.") @click.option('-v', '--verbose', help="Be more verbose", is_flag=True) def sign(package=None, **options): """Sign the package.""" # noinspection PyShadowingNames def _do_clear(options): echo_info("Clearing all keys from the KECPKG keyring") if not options.get('do_yes'): options['do_yes'] = click.confirm("Are you sure you want to clear the KECPKG keyring?", default=False) if options.get('do_yes'): remove_path(GNUPG_KECPKG_HOME) echo_success("Completed") sys.exit(0) else: echo_failure("Not removing the KECPKG keyring") sys.exit(1) def _do_list(gpg, explain=False): if explain: echo_info("Listing all keys from the KECPKG keyring") result = gpg.list_keys(secret=True) if len(result): from tabulate import tabulate print(tabulate(list_keys(gpg=gpg), headers=("Name", "Comment", "E-mail", "Expires", "Fingerprint"))) else: if explain: echo_info("No keys found in KECPKG keyring. Use `--import-key` or `--create-key` to add a " "secret key to the KECPKG keyring in order to sign KECPKG's.") sys.exit(1) # noinspection PyShadowingNames def _do_import(gpg, options): echo_info("Importing secret key into KECPKG keyring from '{}'".format(options.get('do_import'))) result = gpg.import_keys(open(os.path.abspath(options.get('do_import')), 'rb').read()) # pprint(result.__dict__) if result and result.sec_imported: echo_success("Succesfully imported secret key into the KECPKG keystore") _do_list(gpg=gpg) sys.exit(0) elif result and result.unchanged: echo_failure("Did not import the secret key into the KECPKG keystore. The key was already " "in place and was unchanged") _do_list(gpg=gpg) sys.exit(1) echo_failure("Did not import a secret key into the KECPKG keystore. Is something wrong " "with the file: '{}'? Are you sure it is a ASCII file containing a " "private key block?".format(options.get('do_import'))) sys.exit(1) # noinspection PyShadowingNames def _do_delete_key(gpg, options): echo_info("Deleting private key with ID '{}' from the KECPKG keyring".format(options.get('do_delete_key'))) # custom call to gpg using --delete-secret-and-public-key result = gpg.result_map['delete'](gpg) # noinspection PyProtectedMember p = gpg._open_subprocess(['--yes', '--delete-secret-and-public-key', options.get('do_delete_key')]) # noinspection PyProtectedMember gpg._collect_output(p, result, stdin=p.stdin) # result = gpg.delete_keys(fingerprints=options.get('do_delete_key'), # secret=True, # passphrase=options.get('sign_passphrase')) # pprint(result.__dict__) if result and result.stderr.find("failed") < 0: echo_success("Succesfully deleted key") _do_list(gpg=gpg) sys.exit(0) echo_failure("Could not delete key.") sys.exit(1) # noinspection PyShadowingNames def _do_create_key(gpg, options): echo_info("Will create a secret key and store it into the KECPKG keyring.") package_dir = get_package_dir(package_name=package, fail=False) settings = DEFAULT_SETTINGS if package_dir is not None: package_name = os.path.basename(package_dir) echo_info('Package `{}` has been selected'.format(package_name)) settings = load_settings(package_dir=package_dir, settings_filename=options.get('settings_filename')) key_info = {'name_real': click.prompt("Name", default=settings.get('name')), 'name_comment': click.prompt("Comment", default="KECPKG SIGNING KEY"), 'name_email': click.prompt("Email", default=settings.get('email')), 'expire_date': click.prompt("Expiration in months", default=12, value_proc=lambda i: "{}m".format(i)), 'key_type': 'RSA', 'key_length': 4096, 'key_usage': '', 'subkey_type': 'RSA', 'subkey_length': 4096, 'subkey_usage': 'encrypt,sign,auth', 'passphrase': ''} passphrase = click.prompt("Passphrase", hide_input=True) passphrase_confirmed = click.prompt("Confirm passphrase", hide_input=True) if passphrase == passphrase_confirmed: key_info['passphrase'] = passphrase else: raise ValueError("The passphrases did not match.") echo_info("Creating the secret key '{name_real} ({name_comment}) <{name_email}>'".format(**key_info)) echo_info("Please move around mouse or generate other activity to introduce sufficient entropy. " "This might take a minute...") result = gpg.gen_key(gpg.gen_key_input(**key_info)) pprint(result.__dict__) if result and result.stderr.find('KEY_CREATED'): echo_success("The key is succesfully created") _do_list(gpg=gpg) sys.exit(0) echo_failure("Could not generate the key due to an error: '{}'".format(result.stderr)) sys.exit(1) # noinspection PyShadowingNames def _do_export_key(gpg, options): """Export public key.""" echo_info("Exporting public key") if options.get('keyid') is None: _do_list(gpg=gpg) options['keyid'] = click.prompt("Provide KeyId (name, comment, email, fingerprint) of the key to export") result = gpg.export_keys(keyids=[options.get('keyid')], secret=False, armor=True) if result is not None: with open(options.get('do_export_key'), 'w') as fd: fd.write(result) echo_success("Sucessfully written public key to '{}'".format(options.get('do_export_key'))) sys.exit(0) echo_failure("Could not export key") sys.exit(1) # noinspection PyShadowingNames def _do_verify_kecpkg(gpg, options): """Verify the kecpkg.""" echo_info("Verify the contents of the KECPKG and if the KECPKG is signed with a valid signature.") current_working_directory = os.getcwd() with temp_chdir() as d: unzip_package(package_path=os.path.join(current_working_directory, options.get('do_verify_kecpkg')), target_path=d) verify_signature(d, artifacts_filename=ARTIFACTS_FILENAME, artifacts_sig_filename=ARTIFACTS_SIG_FILENAME) verify_artifacts_hashes(d, artifacts_filename=ARTIFACTS_FILENAME) sys.exit(0) # # Dispatcher to subfunctions # if options.get('do_clear'): _do_clear(options=options) elif options.get('do_list'): _do_list(gpg=get_gpg(), explain=True) elif options.get('do_import'): _do_import(gpg=get_gpg(), options=options) elif options.get('do_delete_key'): _do_delete_key(gpg=get_gpg(), options=options) elif options.get('do_create_key'): _do_create_key(gpg=get_gpg(), options=options) elif options.get('do_export_key'): _do_export_key(gpg=get_gpg(), options=options) elif options.get('do_verify_kecpkg'): _do_verify_kecpkg(gpg=get_gpg(), options=options) else: sys.exit(500) sys.exit(0) def verify_signature(package_dir, artifacts_filename, artifacts_sig_filename): """ Check signature of the package. :param package_dir: directory fullpath of the package :param artifacts_filename: path of the artifacts file :param artifacts_sig_filename: path of the artifacts signature file :return: None """ gpg = get_gpg() artifacts_fp = os.path.join(package_dir, artifacts_filename) artifacts_sig_fp = os.path.join(package_dir, artifacts_sig_filename) if not os.path.exists(artifacts_fp): echo_failure("Artifacts file does not exist: '{}'".format(artifacts_filename)) sys.exit(1) if not os.path.exists(artifacts_sig_fp): echo_failure("Artifacts signature file does not exist: '{}'. Is the package signed?". format(artifacts_filename)) sys.exit(1) with open(artifacts_sig_fp, 'rb') as sig_fd: results = gpg.verify_file(sig_fd, data_filename=artifacts_fp) if results.valid: echo_info("Verified the signature and the signature is valid") echo_info("Signed with: '{}'".format(results.username)) elif not results.valid: echo_failure("Signature of the package is invalid") echo_failure(pprint(results.__dict__)) sys.exit(1) def verify_artifacts_hashes(package_dir, artifacts_filename): """ Check the hashes of the artifacts in the package. :param package_dir: directory fullpath of the package :param artifacts_filename: filename of the artifacts file :return: """ artifacts_fp = os.path.join(package_dir, artifacts_filename) if not os.path.exists(artifacts_fp): echo_failure("Artifacts file does not exist: '{}'".format(artifacts_filename)) sys.exit(1) with open(artifacts_fp, 'r') as fd: artifacts = fd.readlines() # process the file contents # A line is "README.md,sha256=d831....ccf79a,336" # ^filename ^algo ^hash ^size in bytes fails = [] for af in artifacts: # noinspection PyShadowingBuiltins,PyShadowingBuiltins filename, hash, orig_size = af.split(',') algorithm, orig_hash = hash.split('=') fp = os.path.join(package_dir, filename) if os.path.exists(fp): found_hash = hash_of_file(fp, algorithm) found_size = os.stat(fp).st_size if found_hash != orig_hash.strip() or found_size != int(orig_size.strip()): fails.append("File '{}' is changed in the package.".format(filename)) fails.append("File '{}' original checksum: '{}', found: '{}'".format(filename, orig_hash, found_hash)) fails.append("File '{}' original size: {}, found: {}".format(filename, orig_size, found_size)) else: fails.append("File '{}' does not exist".format(filename)) if fails: echo_failure('The package has been changed after building the package.') for fail in fails: print(fail) sys.exit(1) else: echo_info("Package contents succesfully verified.")
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import argparse import random SIGNATURE = b'\xDE\xAD\xBE\xEF\xC0\xFF\xEE\xAA\xBB\xCC\xDD\xEE\xFF\x00\x11\x22\x33\x44\x55\x66\x77\x88\x99\xAA' # Generate data in chunks of 1024 bytes. def generate_random_data(size): data = bytearray() while len(data) <= size: data += random.randbytes(1024) return data def sign_data(data, signature): pos = random.randrange(0, len(data) - len(signature)) for (i, p) in enumerate(range(pos, pos + len(signature))): data[p] = signature[i] def write_data(data): with open("output.bin", 'wb') as f: f.write(data) def main(): parser = argparse.ArgumentParser(description="Generate some random data") parser.add_argument("--size", metavar="S", type=int, default=1024 * 1024 * 10, required=False) args = parser.parse_args() data = generate_random_data(args.size) sign_data(data, SIGNATURE) write_data(data) if __name__ == "__main__": main()
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import datetime import io import os import re import subprocess import warnings from collections import namedtuple from decimal import Decimal from pathlib import Path import six from PyPDF2 import PdfFileMerger from reportlab.pdfgen import canvas class DoctorUnicodeDecodeError(UnicodeDecodeError): def __init__(self, obj, *args): self.obj = obj UnicodeDecodeError.__init__(self, *args) def __str__(self): original = UnicodeDecodeError.__str__(self) return f"{original}. You passed in {self.obj!r} ({type(self.obj)})" def force_bytes(s, encoding="utf-8", strings_only=False, errors="strict"): """ Similar to smart_bytes, except that lazy instances are resolved to strings, rather than kept as lazy objects. If strings_only is True, don't convert (some) non-string-like objects. """ # Handle the common case first for performance reasons. if isinstance(s, bytes): if encoding == "utf-8": return s else: return s.decode("utf-8", errors).encode(encoding, errors) if strings_only and is_protected_type(s): return s if isinstance(s, six.memoryview): return bytes(s) if isinstance(s, Promise): return six.text_type(s).encode(encoding, errors) if not isinstance(s, six.string_types): try: if six.PY3: return six.text_type(s).encode(encoding) else: return bytes(s) except UnicodeEncodeError: if isinstance(s, Exception): # An Exception subclass containing non-ASCII data that doesn't # know how to print itself properly. We shouldn't raise a # further exception. return b" ".join( force_bytes(arg, encoding, strings_only, errors) for arg in s ) return six.text_type(s).encode(encoding, errors) else: return s.encode(encoding, errors) def force_text(s, encoding="utf-8", strings_only=False, errors="strict"): """ Similar to smart_text, except that lazy instances are resolved to strings, rather than kept as lazy objects. If strings_only is True, don't convert (some) non-string-like objects. """ # Handle the common case first for performance reasons. if issubclass(type(s), six.text_type): return s if strings_only and is_protected_type(s): return s try: if not issubclass(type(s), six.string_types): if six.PY3: if isinstance(s, bytes): s = six.text_type(s, encoding, errors) else: s = six.text_type(s) elif hasattr(s, "__unicode__"): s = six.text_type(s) else: s = six.text_type(bytes(s), encoding, errors) else: # Note: We use .decode() here, instead of six.text_type(s, encoding, # errors), so that if s is a SafeBytes, it ends up being a # SafeText at the end. s = s.decode(encoding, errors) except UnicodeDecodeError as e: if not isinstance(s, Exception): raise DoctorUnicodeDecodeError(s, *e.args) else: # If we get to here, the caller has passed in an Exception # subclass populated with non-ASCII bytestring data without a # working unicode method. Try to handle this without raising a # further exception by individually forcing the exception args # to unicode. s = " ".join(force_text(arg, encoding, strings_only, errors) for arg in s) return s def smart_text(s, encoding="utf-8", strings_only=False, errors="strict"): """ Returns a text object representing 's' -- unicode on Python 2 and str on Python 3. Treats bytestrings using the 'encoding' codec. If strings_only is True, don't convert (some) non-string-like objects. """ if isinstance(s, Promise): # The input is the result of a gettext_lazy() call. return s return force_text(s, encoding, strings_only, errors) class Promise(object): """ This is just a base class for the proxy class created in the closure of the lazy function. It can be used to recognize promises in code. """ pass _PROTECTED_TYPES = six.integer_types + ( type(None), float, Decimal, datetime.datetime, datetime.date, datetime.time, ) def is_protected_type(obj): """Determine if the object instance is of a protected type. Objects of protected types are preserved as-is when passed to force_text(strings_only=True). """ return isinstance(obj, _PROTECTED_TYPES) def audio_encoder(data): return namedtuple("AudioFile", data.keys())(*data.values()) def ignore_warnings(test_func): def do_test(self, *args, **kwargs): with warnings.catch_warnings(): warnings.simplefilter("ignore", ResourceWarning) warnings.simplefilter("ignore", DeprecationWarning) test_func(self, *args, **kwargs) return do_test def make_png_thumbnail_for_instance(filepath, max_dimension): """Abstract function for making a thumbnail for a PDF See helper functions below for how to use this in a simple way. :param filepath: The attr where the PDF is located on the item :param max_dimension: The longest you want any edge to be :param response: Flask response object """ command = [ "pdftoppm", "-singlefile", "-f", "1", "-scale-to", str(max_dimension), filepath, "-png", ] p = subprocess.Popen( command, close_fds=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE ) stdout, stderr = p.communicate() return stdout, stderr.decode("utf-8"), str(p.returncode) def make_png_thumbnails(filepath, max_dimension, pages, directory): """Abstract function for making a thumbnail for a PDF See helper functions below for how to use this in a simple way. :param filepath: The attr where the PDF is located on the item :param max_dimension: The longest you want any edge to be :param response: Flask response object """ for page in pages: command = [ "pdftoppm", "-singlefile", "-f", str(page), "-scale-to", str(max_dimension), filepath, "-png", f"{directory.name}/thumb-{page}", ] p = subprocess.Popen( command, close_fds=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE ) p.communicate() def pdf_bytes_from_image_array(image_list, output_path) -> None: """Make a pdf given an array of Image files :param image_list: List of images :type image_list: list :return: pdf_data :type pdf_data: PDF as bytes """ image_list[0].save( output_path, "PDF", resolution=100.0, save_all=True, append_images=image_list[1:], ) del image_list def strip_metadata_from_path(file_path): """Convert PDF file into PDF and remove metadata from it Stripping the metadata allows us to hash the PDFs :param pdf_bytes: PDF as binary content :return: PDF bytes with metadata removed. """ with open(file_path, "rb") as f: pdf_merger = PdfFileMerger() pdf_merger.append(io.BytesIO(f.read())) pdf_merger.addMetadata({"/CreationDate": "", "/ModDate": ""}) byte_writer = io.BytesIO() pdf_merger.write(byte_writer) return force_bytes(byte_writer.getvalue()) def strip_metadata_from_bytes(pdf_bytes): """Convert PDF bytes into PDF and remove metadata from it Stripping the metadata allows us to hash the PDFs :param pdf_bytes: PDF as binary content :return: PDF bytes with metadata removed. """ pdf_merger = PdfFileMerger() pdf_merger.append(io.BytesIO(pdf_bytes)) pdf_merger.addMetadata({"/CreationDate": "", "/ModDate": ""}) byte_writer = io.BytesIO() pdf_merger.write(byte_writer) return force_bytes(byte_writer.getvalue()) def cleanup_form(form): """Clean up a form object""" os.remove(form.cleaned_data["fp"]) def make_file(filename, dir=None): filepath = f"{Path.cwd()}/doctor/test_assets/{filename}" with open(filepath, "rb") as f: return {"file": (filename, f.read())} def make_buffer(filename, dir=None): filepath = f"{Path.cwd()}/doctor/test_assets/{filename}" with open(filepath, "rb") as f: return {"file": ("filename", f.read())} def pdf_has_images(path: str) -> bool: """Check raw PDF for embedded images. We need to check if a PDF contains any images. If a PDF contains images it likely has content that needs to be scanned. :param path: Location of PDF to process. :return: Does the PDF contain images? :type: bool """ with open(path, "rb") as pdf_file: pdf_bytes = pdf_file.read() return True if re.search(rb"/Image ?/", pdf_bytes) else False def ocr_needed(path: str, content: str) -> bool: """Check if OCR is needed on a PDF Check if images are in PDF or content is empty. :param path: The path to the PDF :param content: The content extracted from the PDF. :return: Whether OCR should be run on the document. """ if content.strip() == "" or pdf_has_images(path): return True return False def make_page_with_text(page, data, h, w): """Make a page with text :param page: :param data: :param h: :param w: :return: """ packet = io.BytesIO() can = canvas.Canvas(packet, pagesize=(w, h)) # Set to a standard size and font for now. can.setFont("Helvetica", 9) # Make the text transparent can.setFillAlpha(0) for i in range(len(data["level"])): try: letter, (x, y, ww, hh), pg = ( data["text"][i], (data["left"][i], data["top"][i], data["width"][i], data["height"][i]), data["page_num"][i], ) except: continue # Adjust the text to an 8.5 by 11 inch page sub = ((11 * 72) / h) * int(hh) x = ((8.5 * 72) / w) * int(x) y = ((11 * 72) / h) * int(y) yy = (11 * 72) - y if int(page) == int(pg): can.drawString(x, yy - sub, letter) can.showPage() can.save() packet.seek(0) return packet
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import gym import numpy as np import os import random import matplotlib.pyplot as plt from atariari.benchmark.wrapper import AtariARIWrapper # YarsRevenge # env_name = "DemonAttackDeterministic-v4" def print_labels(env_info): # extract raw features labels = env_info["labels"] print(labels) env = AtariARIWrapper(gym.make(env_name)) name = env.unwrapped.spec.id #ballgame = any(game in name for game in ["Pong", "Tennis"]) print(np.int16(3)) üsad n_actions = env.action_space.n _ = env.reset() obs, _, done, info = env.step(0) r = 0 for t in range(50000): plt.imshow(env.render(mode='rgb_array'), interpolation='none') plt.plot() plt.pause(0.0001) # pause a bit so that plots are updated action = random.randint(0, n_actions - 1) obs, reward, done, info = env.step(action) r += reward print(reward) print_labels(info) if(done): break print(r)
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# encoding: utf-8 from datetime import datetime class Table(object): def config_db(self,pkg): tbl=pkg.table('question', pkey='id', name_long='!![en]Question', name_plural='!![en]Questions',caption_field='question') self.sysFields(tbl, draftField=True) tbl.column('question',name_long='!![en]Question', validate_notnull=True) tbl.column('description', name_long='!![en]Description') tbl.column('details', name_long='!![en]Details') tbl.column('user_id',size='22', group='_', name_long='!![en]Inserted by' ).relation('adm.user.id', relation_name='myquestions', mode='foreignkey', onDelete='raise') tbl.column('approval_ts', dtype='DH', name_long='!![en]Approval TS') tbl.column('approved_by_user_id', size='22', group='_', name_long='!![en]Approved by' ).relation('adm.user.id', relation_name='approved_questions', mode='foreignkey', onDelete='raise') tbl.column('main_topic_id',size='22', group='_', name_long='!![en]Main topic' ).relation('topic.id', relation_name='questions', mode='foreignkey', onDelete='setnull') tbl.column('main_answer_id',size='22', group='_', name_long='!![en]Main answer' ).relation('answer.id', relation_name='questions', mode='foreignkey', onDelete='setnull') #tbl.formulaColumn('__protected_by_approval_ts',"""($approval_ts IS NOT NULL AND $approved_by_user_id!=:env_user_id)""",dtype='B') def defaultValues(self): user_id = self.db.currentEnv.get('user_id') #Se l'utente ha i giusti requisiti le sue domande e le sue risposte non nascono com ebozza if 'admin' in self.db.currentEnv['userTags']: #posso pensare ad una condizione migliore e più sofisticata return dict( __is_draft = False, approval_ts = datetime.now(), approved_by_user_id = user_id, user_id=user_id) return dict(__is_draft=True, user_id = user_id) def trigger_onUpdating(self, record, old_record): #Quando un record passa da bozza ad approvato metto utente approvatore e timestamp di approvazione if old_record['__is_draft'] and not record['__is_draft']: record['approval_ts'] = datetime.now() record['approved_by_user_id'] = self.db.currentEnv.get('user_id')
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import json import requests from os import path class OxfordAPI: def __init__(self, app_id, app_key, cache_path): self.app_id = app_id self.app_key = app_key self.cache_path = cache_path def __parse_sense(self, word, sense): for definition in sense.get('definitions', list()): word.definitions.append(definition) for example in sense.get('examples', list()): word.examples.append(example.get('text', None)) for synonym in sense.get('synonyms', list()): word.synonyms.append(synonym.get('text', None)) for subsense in sense.get('subsenses', list()): self.__parse_sense(word, subsense) def __parse_pronunciation(self, word, pronunciation): audioFile = pronunciation.get('audioFile', None) if audioFile is not None: word.audio_file = audioFile def __parse_entry(self, word, entry): for pronunciation in entry.get('pronunciations', list()): self.__parse_pronunciation(word, pronunciation) for sense in entry.get('senses', list()): self.__parse_sense(word, sense) def __parse_lexical_entry(self, word, lexical_entry): for entry in lexical_entry.get('entries', list()): self.__parse_entry(word, entry) def __parse_result(self, word, result): for lexical_entry in result.get('lexicalEntries', list()): self.__parse_lexical_entry(word, lexical_entry) def __parse_word(self, word, data): success = False if data.get('error') is None: for result in data.get('results', list()): self.__parse_result(word, result) success = True return success def __get_word_data(self, word): filepath = self.cache_path + word.text + '.json' with open(filepath, 'w') as file: url = "https://od-api.oxforddictionaries.com/api/v2/words/en-us?q=" + word.text r = requests.get(url, headers={"app_id": self.app_id, "app_key": self.app_key}) file.write(r.text) return r.json() def get_word(self, word): """ Populates the given word object with the relevant information from the Oxford Dictionary API. First, the word is looked for in the cache folder, if it exists, load that data. Otherwise, the information is requested from the OxfordAPI and stored in the cache folder. :param word: The word object to be populated. :return: A boolean indicating if the operation has been successful or not. """ success = False if path.exists(self.cache_path): filepath = self.cache_path + word.text + '.json' if path.exists(filepath): with open(filepath, 'r') as file: data = json.load(file) else: data = self.__get_word_data(word) success = self.__parse_word(word, data) else: print('OxfordAPI: Please provide a valid cache path.') return success
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class Node: def __init__(self, data=None): self.data = data self.next = None class LinkedListIndexError(IndexError): pass class LinkedList: def __init__(self): self.head = Node() def _get_last_node(self): pointer = self.head while pointer.next is not None: pointer = pointer.next return pointer def get_last_node(self): return self._get_last_node().data def append(self, data): new_node = Node(data=data) last = self._get_last_node() last.next = new_node def print(self): print(self.__str__()) def __str__(self): pointer = self.head idx = 0 ll_str = "" while pointer.next is not None: pointer = pointer.next ll_str += f"{idx}: {pointer.data}\n" idx += 1 return ll_str def length(self): pointer = self.head counter = 0 while pointer.next is not None: pointer = pointer.next counter += 1 return counter def _get(self, index): pointer = self.head counter = 0 if not(0 <= index < self.length()): raise LinkedListIndexError(f"Index '{index}' does not exist") while pointer.next is not None: pointer = pointer.next if counter == index: return pointer counter += 1 def get(self, index): return self._get(index=index).data def __getitem__(self, item): return self.get(index=item) def erase(self, index): if index == 0: prev = self.head else: prev = self._get(index=index - 1) to_del = prev.next prev.next = to_del.next data = to_del.data del to_del return data def set(self, index, new_data): node = self._get(index=index) node.data = new_data def __del__(self): length = self.length() while length != 0: self.erase(index=length - 1) length -= 1 del self.head if __name__ == '__main__': ll = LinkedList() ll.append(data="Fedor") ll.append(data="Julia") ll.append(data="Bentsi") ll.print() print("Length of the Linked list is: ", ll.length()) idx = 1 print(ll.get(index=idx)) print(f"Data at index {idx} is {ll[idx]}") print("Deleted: ", ll.erase(index=0)) ll.append(data="Fedor") ll.append(data="Bentsi") ll.set(index=3, new_data="Tim Peters") print(ll)
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# -*- coding: utf-8 -*- ''' Copyright (c) 2016, Virginia Tech All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. The views and conclusions contained in the software and documentation are those of the authors and should not be interpreted as representing official policies, either expressed or implied, of the FreeBSD Project. This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor Virginia Tech, nor any of their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, favoring by the United States Government or any agency thereof, or Virginia Tech - Advanced Research Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. VIRGINIA TECH – ADVANCED RESEARCH INSTITUTE under Contract DE-EE0006352 #__author__ = "BEMOSS Team" #__credits__ = "" #__version__ = "2.0" #__maintainer__ = "BEMOSS Team" #__email__ = "aribemoss@gmail.com" #__website__ = "www.bemoss.org" #__created__ = "2014-09-12 12:04:50" #__lastUpdated__ = "2016-03-14 11:23:33" ''' from django.shortcuts import render_to_response from django.contrib.auth import authenticate, login from django.template import RequestContext from django.http import HttpResponseRedirect from django.contrib import messages import logging logger = logging.getLogger("views") def login_user(request): print "inside login_user() method" # Like before, obtain the context for the user's request. context = RequestContext(request) if request.method == 'POST': # Gather the username and password provided by the user. # This information is obtained from the login form. username = request.POST['username'] password = request.POST['password'] # Use Django's machinery to attempt to see if the username/password # combination is valid - a User object is returned if it is. user = authenticate(username=username, password=password) # If we have a User object, the details are correct. # If None (Python's way of representing the absence of a value), no user # with matching credentials was found. if user is not None: # Is the account active? It could have been disabled. if user.is_active: # If the account is valid and active, we can log the user in. # We'll send the user back to the homepage. login(request, user) request.session['zipcode'] = '22204' logger.info("Login of user : %s", user.username) return HttpResponseRedirect('/home/') else: # An inactive account was used - no logging in! messages.error(request, 'This account has been disabled by the administrator.') else: # Bad login details were provided. So we can't log the user in. print "Invalid login details: {0}, {1}".format(username, password) messages.error(request, 'Your username/password information is incorrect.') #return HttpResponse("Invalid login details supplied.") return HttpResponseRedirect('/login/') #render_to_response('login/login.html', {}, context) else: # The request is not a HTTP POST, so display the login form. # This scenario would most likely be a HTTP GET. return render_to_response('login/login.html', {}, context)
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from html.parser import HTMLParser class CustomHTMLValidater(HTMLParser): __SINGLE_TAGS = [ 'area','base','br','col','embed', 'hr','img','input','keygen','link', 'meta','param','source','track','wbr' ] def __init__(self): HTMLParser.__init__(self) self.reset(True) def reset(self, tag_reset = False): HTMLParser.reset(self) self.__core = { 'status': 0, 'detail':'', 'detected_list':[] } if tag_reset: self.__allowed_tags = [] return def set_allowed_tags(self, __allowed_tags): self.__allowed_tags = __allowed_tags return def handle_starttag(self,tag,attrs): if self.__core['status'] == 0: if not tag in self.__allowed_tags: self.__core['status'] = -1 self.__core['detail'] = 'not_allowed_tag' else: for attr in attrs: if not attr[0] in self.__allowed_tags[tag]: self.__core['status'] = -1 self.__core['detail'] = 'not_allowed_attr' return detected = { 'tag': tag, 'attr': attrs, 'complete': False } self.__core['detected_list'].append(detected) return def handle_endtag(self,tag): if self.__core['status'] == 0: last_index = len(self.__core['detected_list']) - 1 for index in range(last_index, -1, -1): data = self.__core['detected_list'][index] if not data['complete']: if data['tag'] == tag: data['complete'] = True return elif data['tag'] in self.__SINGLE_TAGS: data['complete'] = True else: break self.__core['status'] = -1 self.__core['detail'] = 'Construction Error' return def close(self): HTMLParser.close(self) if self.__core['status'] == 0: errored = False for data in self.__core['detected_list']: if not data['complete']: if data['tag'] in self.__SINGLE_TAGS: data['complete'] = True continue self.__core['status'] = -1 self.__core['detail'] = 'Construction Error' errored = True break if not errored: self.__core['status'] = 1 self.__core['detail'] = 'ok' return self.__core
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import logging import os.path import bolt import bolt.about PROJECT_ROOT = os.path.abspath(os.path.dirname(__file__)) _src_dir = os.path.join(PROJECT_ROOT, 'bolt') _test_dir = os.path.join(PROJECT_ROOT, 'test') _output_dir = os.path.join(PROJECT_ROOT, 'output') _coverage_dir = os.path.join(_output_dir, 'coverage') config = { 'pip': { 'command': 'install', 'options': { 'r': './requirements.txt' } }, 'delete-pyc': { 'sourcedir': _src_dir, 'recursive': True, 'test-pyc': { 'sourcedir': _test_dir, } }, 'conttest' : { 'task': 'ut' }, 'mkdir': { 'directory': _output_dir, }, 'nose': { 'directory': _test_dir, 'ci': { 'options': { 'with-xunit': True, 'xunit-file': os.path.join(_output_dir, 'unit_tests_log.xml'), 'with-coverage': True, 'cover-erase': True, 'cover-package': 'bolt', 'cover-html': True, 'cover-html-dir': _coverage_dir, 'cover-branches': True, } } }, 'setup': { 'command': 'bdist_wheel', 'egg-info': { 'command': 'egg_info' } }, 'coverage': { 'task': 'nose', 'include': ['bolt'], 'output': os.path.join(_output_dir, 'ut_coverage') } } # Development tasks bolt.register_task('clear-pyc', ['delete-pyc', 'delete-pyc.test-pyc']) bolt.register_task('ut', ['clear-pyc', 'nose']) bolt.register_task('ct', ['conttest']) bolt.register_task('pack', ['setup', 'setup.egg-info']) # CI/CD tasks bolt.register_task('run-unit-tests', ['clear-pyc', 'mkdir', 'nose.ci']) # Default task (not final). bolt.register_task('default', ['pip', 'ut'])
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from enum import Enum from pyxedit.xedit.attribute import XEditAttribute from pyxedit.xedit.generic import XEditGenericObject class HeadPartTypes(Enum): Misc = 'Misc' Face = 'Face' Eyes = 'Eyes' Hair = 'Hair' FacialHair = 'Facial Hair' Scar = 'Scar' Eyebrows = 'Eyebrows' class XEditHeadPart(XEditGenericObject): SIGNATURE = 'HDPT' HeadPartTypes = HeadPartTypes full = full_name = XEditAttribute('FULL') modl = model_filename = XEditAttribute('Model\\MODL') data = flags = XEditAttribute('DATA') pnam = headpart_type = XEditAttribute('PNAM', enum=HeadPartTypes) hnam = extra_parts = XEditAttribute('HNAM') nam0 = parts = XEditAttribute('Parts') tnam = texture_set = base_texture = XEditAttribute('TNAM') cnam = color = XEditAttribute('CNAM') rnam = valid_races = resource_list = XEditAttribute('RNAM') @property def file_paths(self): files = ([f'Meshes\\{self.model_filename}'] + [f'Meshes\\{part["NAM1"].value}' for part in self.parts or []]) return sorted(set([file_ for file_ in files if file_]))
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#!/usr/bin/env python3 """ Author : Me <me@foo.com> Date : today Purpose: Rock the Casbah """ import argparse import io import os import sys # -------------------------------------------------- def get_args(): """Get command-line arguments""" parser = argparse.ArgumentParser( description='Rock the Casbah', formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('-n', '--num', help='Number of lines', metavar='int', type=int, default=10) parser.add_argument('file', help='Input File', type=argparse.FileType('r')) args = parser.parse_args() if not args.num > 0: parser.error(f'--num "{args.num}" must be greater than 0') return args # -------------------------------------------------- def main(): """Make a jazz noise here""" args = get_args() for fh in args.file: print(fh.name) num_line = 0 for line in fh: num_line += 1 print(line, end='') if num_line == args.num: break # -------------------------------------------------- if __name__ == '__main__': main()
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#!/usr/bin/env python import os import sys import unittest from collections import namedtuple sys.path = [ os.path.abspath(os.path.join(os.path.dirname(__file__), '../..')) ] + sys.path from pluckit import pluck class CornerCasesTest(unittest.TestCase): def test_null_handle(self): data = [1, 2, 3] self.assertEqual([ None, None, None ], pluck(data, None)) def test_empty(self): self.assertEqual([], pluck([], 'k')) self.assertEqual({}, pluck({}, 'k')) self.assertEqual(set(), pluck(set(), 'k')) def test_null(self): self.assertEqual(None, pluck(None, None)) self.assertEqual(None, pluck(None, 123)) def test_null_values(self): data = { None : [1, 2], 'b' : [3, 4], 'c' : [None, 5] } self.assertEqual( { None : 1, 'b' : 3, 'c' : None, }, pluck(data, 0) ) if __name__ == '__main__': unittest.main()
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from albumentations.core.transforms_interface import ImageOnlyTransform import albumentations.augmentations.functional as F import random class CrossDrop(ImageOnlyTransform): def __init__(self, max_h_cut=0.2, max_w_cut=0.2, fill_value=0, always_apply=False, p=0.5): super(CrossDrop, self).__init__(always_apply, p) self.max_h_cut = max_h_cut self.max_w_cut = max_w_cut self.fill_value = fill_value def apply(self, image, fill_value=0, holes=(), **params): return F.cutout(image, holes, fill_value) def get_params_dependent_on_targets(self, params): img = params["image"] height, width = img.shape[:2] y1 = int(random.random() * self.max_h_cut * height) x1 = int(random.random() * self.max_w_cut * width) y2 = int(random.random() * self.max_h_cut * height) x2 = int(random.random() * self.max_w_cut * width) y3 = int(random.random() * self.max_h_cut * height) x3 = int(random.random() * self.max_w_cut * width) y4 = int(random.random() * self.max_h_cut * height) x4 = int(random.random() * self.max_w_cut * width) return {"holes": [ (0, 0, x1, y1), (width-x2, 0, width, y2), (0, height-y3, x3, height), (width-x4, height-y4, width, height) ]} @property def targets_as_params(self): return ["image"] def get_transform_init_args_names(self): return ("max_h_cut", "max_w_cut")
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# -*- coding: utf-8 -*- from __future__ import unicode_literals import functools import six from django.utils.translation import ugettext_lazy as _ from django.template import TemplateDoesNotExist from django.template.loader import select_template from cms.plugin_base import CMSPluginBase, CMSPluginBaseMetaclass from cms.plugin_pool import plugin_pool from . import models, forms from .utils.urlmatch import urlmatch from .constants import ( HIDE_PROMO, HIDE_PROMO_ROLLOVER, HIDE_PROMO_VIDEO, HIDE_TWITTER, HIDE_COUNTERS, HIDE_RAWHTML, HIDE_GATED_CONTENT, HIDE_FLOAT, HIDE_LIGHTBOX, CUSTOM_PLUGINS, PROMO_CHILD_CLASSES, ) class LayoutMixin(): def get_layout(self, context, instance, placeholder): return instance.layout def get_render_template(self, context, instance, placeholder): layout = self.get_layout(context, instance, placeholder) if layout: template = self.TEMPLATE_NAME % layout try: select_template([template]) return template except TemplateDoesNotExist: pass return self.render_template def render(self, context, instance, placeholder): context.update({ 'instance': instance, 'placeholder': placeholder, }) return context class PromoUnitPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/promo_%s.html' name = _('Promo Unit') model = models.PromoUnit form = forms.PromoUnitForm render_template = 'js_components/promo.html' change_form_template = 'admin/js_components/float.html' allow_children = True if PROMO_CHILD_CLASSES else False child_classes = PROMO_CHILD_CLASSES main_fields = [ 'layout', 'alignment', 'title', 'subtitle', 'color', 'image', 'svg', 'icon', 'content', 'rollover_content', 'background_video', 'link_text', 'link_url', ('file_src', 'show_filesize'), 'open_in_new_window', 'full_height', ] if HIDE_PROMO_ROLLOVER: main_fields.remove('rollover_content') if HIDE_PROMO_VIDEO: main_fields.remove('background_video') fieldsets = [ (None, { 'fields': main_fields }), (_('Advanced settings'), { 'classes': ('collapse',), 'fields': ( 'modal_id', 'attributes', ) }), ] if not HIDE_PROMO: plugin_pool.register_plugin(PromoUnitPlugin) class TwitterFeedPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/twitter_%s.html' name = _('Twitter Feed') model = models.TwitterFeed form = forms.TwitterFeedForm render_template = 'js_components/twitter.html' if not HIDE_TWITTER: plugin_pool.register_plugin(TwitterFeedPlugin) class CountersContainerPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/counters_%s.html' name = _('Counters Container (DO NOT USE, NEED REMOVE)') model = models.CountersContainer form = forms.CountersContainerForm render_template = 'js_components/counters.html' allow_children = True child_classes = ['CounterPlugin'] parent_classes = ['Bootstrap4GridRowPlugin'] class CounterPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/counter_%s.html' name = _('Counter') model = models.Counter form = forms.CounterForm render_template = 'js_components/counter.html' if not HIDE_COUNTERS: plugin_pool.register_plugin(CountersContainerPlugin) plugin_pool.register_plugin(CounterPlugin) #if 'Bootstrap4GridRowPlugin' in plugin_pool.plugins: #plugin_pool.plugins['Bootstrap4GridRowPlugin'].child_classes.append('CountersContainerPlugin') class RawHTMLPlugin(CMSPluginBase): module = 'JumpSuite Componens' name = _('Raw HTML') model = models.RawHTML render_template = 'js_components/html.html' def render(self, context, instance, placeholder): context.update({ 'instance': instance, 'placeholder': placeholder, 'html': instance.body, }) return context class RawHTMLWithIDPlugin(CMSPluginBase): module = 'JumpSuite Componens' name = _('Raw HTML with ID') model = models.RawHTMLWithID render_template = 'js_components/html.html' def render(self, context, instance, placeholder): request = context['request'] html = instance.body for param in instance.parameters.split(','): param = param.strip() key = '[%s]' % param.upper() html = html.replace(key, request.GET.get(param) or request.POST.get(param, '')) context.update({ 'instance': instance, 'placeholder': placeholder, 'html': html, }) return context if not HIDE_RAWHTML: plugin_pool.register_plugin(RawHTMLPlugin) plugin_pool.register_plugin(RawHTMLWithIDPlugin) @plugin_pool.register_plugin class CustomPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/custom_%s.html' name = _('Custom') model = models.Custom form = forms.CustomForm render_template = 'js_components/custom.html' def get_form(self, request, obj=None, **kwargs): Form = super().get_form(request, obj=None, **kwargs) if self.name in CUSTOM_PLUGINS: Form.plugin_name=self.name return Form for name, parameters in CUSTOM_PLUGINS.items(): p = type( str(name.replace(' ', '') + 'Plugin'), (CustomPlugin,), {'name': name}, ) plugin_pool.register_plugin(p) class GatedContentPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/gated_content_%s.html' name = _('Gated Content') model = models.GatedContent form = forms.GatedContentForm render_template = 'js_components/gated_content.html' allow_children = True if not HIDE_GATED_CONTENT: plugin_pool.register_plugin(GatedContentPlugin) @plugin_pool.register_plugin class AnimatePlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/animate_%s.html' name = _('Animate') model = models.Animate form = forms.AnimateForm render_template = 'js_components/animate.html' allow_children = True @plugin_pool.register_plugin class JSFolderPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/folder_%s.html' name = _('Filer listing') model = models.Folder form = forms.FolderForm render_template = 'js_components/folder.html' def render(self, context, instance, placeholder): request = context['request'] files = [] if instance.folder: files = instance.folder.files.all() if instance.order_by: files = files.order_by(instance.order_by) context.update({ 'instance': instance, 'placeholder': placeholder, 'files': files, }) return context @plugin_pool.register_plugin class IncludeExcludeContainer(CMSPluginBase): module = 'JumpSuite Componens' name = _('Include/Exclude Container') model = models.IncludeExcludeContainer render_template = 'js_components/container.html' change_form_template = 'admin/js_components/change_form_container.html' allow_children = True cache = False def render(self, context, instance, placeholder): request = context['request'] url = '%s://%s%s' % (request.scheme, request.META['HTTP_HOST'], request.path) is_shown = urlmatch(','.join(instance.include.split('\n')), url) and not urlmatch(','.join(instance.exclude.split('\n')), url) context.update({ 'instance': instance, 'placeholder': placeholder, 'is_shown': is_shown, }) return context class FloatPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' name = _('Float Container') model = models.Float form = forms.FloatForm render_template = 'js_components/float.html' TEMPLATE_NAME = 'js_components/float_%s.html' #change_form_template = 'admin/js_components/float.html' allow_children = True def get_layout(self, context, instance, placeholder): return '' if instance.alignment in ['left', 'right', 'center'] else instance.alignment def render(self, context, instance, placeholder): context.update({ 'instance': instance, 'placeholder': placeholder, 'alignment': instance.alignment, }) return context if not HIDE_FLOAT: plugin_pool.register_plugin(FloatPlugin) class LightboxPlugin(LayoutMixin, CMSPluginBase): module = 'JumpSuite Componens' TEMPLATE_NAME = 'js_components/lightbox_%s.html' name = _('Lightbox') model = models.Lightbox form = forms.LightboxForm render_template = 'js_components/lightbox.html' allow_children = True child_classes = ['Bootstrap4PicturePlugin'] if not HIDE_LIGHTBOX: plugin_pool.register_plugin(LightboxPlugin)
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import pytest from julia.core import JuliaOptions # fmt: off @pytest.mark.parametrize("kwargs, args", [ ({}, []), (dict(compiled_modules=None), []), (dict(compiled_modules=False), ["--compiled-modules", "no"]), (dict(compiled_modules="no"), ["--compiled-modules", "no"]), (dict(depwarn="error"), ["--depwarn", "error"]), (dict(sysimage="PATH"), ["--sysimage", "PATH"]), (dict(bindir="PATH"), ["--home", "PATH"]), ]) # fmt: on def test_as_args(kwargs, args): assert JuliaOptions(**kwargs).as_args() == args @pytest.mark.parametrize("kwargs", [ dict(compiled_modules="invalid value"), dict(bindir=123456789), ]) def test_valueerror(kwargs): with pytest.raises(ValueError) as excinfo: JuliaOptions(**kwargs) assert "Option" in str(excinfo.value) assert "accept" in str(excinfo.value) # fmt: off @pytest.mark.parametrize("kwargs", [ dict(invalid_option=None), dict(invalid_option_1=None, invalid_option_2=None), ]) # fmt: on def test_unsupported(kwargs): with pytest.raises(TypeError) as excinfo: JuliaOptions(**kwargs) assert "Unsupported Julia option(s): " in str(excinfo.value) for key in kwargs: assert key in str(excinfo.value)
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import os import pathlib import typing import pytest from ext_argparse.parameter import Parameter from ext_argparse.param_enum import ParameterEnum from enum import Enum class RoofMaterial(Enum): SLATE = 0 METAL = 1 CONCRETE = 2 COMPOSITE = 3 SOLAR = 4 CLAY = 5 SYNTHETIC_BARREL = 6 SYNTHETIC_SLATE = 7 SYNTHETIC_CEDAR = 8 class HouseStyle(Enum): CRAFTSMAN_BUNGALO = 0 CAPE_COD = 1 RANCH = 2 CONTEMPORARY = 3 QUEEN_ANNE = 4 COLONIAL_REVIVAL = 5 TUDOR_REVIVAL = 6 TOWNHOUSE = 7 PRAIRIE = 8 MID_CENTURY_MODERN = 9 NEOCLASSICAL = 10 MEDITERRANEAN = 11 class HouseRoofSettings(ParameterEnum): year_changed = Parameter(arg_type=int, default=2010, arg_help="The last year when the roof tiles were changed.") roof_material: typing.Type[RoofMaterial] = Parameter(arg_type=RoofMaterial, default=RoofMaterial.SLATE, arg_help="Material of the roof tiles.") class HouseParameters(ParameterEnum): sturdiness = Parameter(arg_type=float, default=5.0, arg_help="Sturdiness of the house.", shorthand="stu") year_built = Parameter(arg_type=int, default=2000, arg_help="The year the house was built.") roof: typing.Type[HouseRoofSettings] = HouseRoofSettings style = Parameter(arg_type=HouseStyle, default=HouseStyle.CRAFTSMAN_BUNGALO, arg_help="Style of da house.", shorthand="sty") @pytest.fixture def test_data_dir(): return os.path.join(pathlib.Path(__file__).parent.resolve(), "test_data")
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#! /usr/local/bin/Python3.5 import urllib.request with open("images.csv", 'r') as csv: i = 0 for line in csv: line = line.split(',') if line[1] != '' and line[1] != "\n": urllib.request.urlretrieve(line[1].encode('utf-8'), ("img_" + str(i) + ".jpg").encode('utf-8')) print("Image saved".encode('utf-8')) i += 1 print("No result")
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''' API-related functions in one spot for convenience Created by NGnius 2019-06-15 ''' from flask import jsonify, request from threading import Semaphore, RLock def get_param(param, silent=False): if request.method == 'GET': return request.args.get(param) else: try: return request.get_json(force=True, silent=silent)[param] except KeyError: return None def error(status=500, reason=None): error_response = {'status':status} if reason is not None: error_response['reason'] = reason return jsonify(error_response), status single_semaphores = dict() resource_lock = RLock() def start_single(identifier): resource_lock.acquire() if identifier not in single_semaphores: resource_lock.release() single_semaphores[identifier] = Semaphore(1) else: resource_lock.release() single_semaphores[identifier].acquire() def end_single(identifier): resource_lock.acquire() single_semaphores[identifier].release()
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""" productporter ~~~~~~~~~~~~~~~~~~~~ helper for uwsgi :copyright: (c) 2014 by the ProductPorter Team. :license: BSD, see LICENSE for more details. """ from productporter.app import create_app from productporter.configs.production import ProductionConfig app = create_app(config=ProductionConfig())
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# BSD 3-Clause License # # Copyright (c) 2017 xxxx # All rights reserved. # Copyright 2021 Huawei Technologies Co., Ltd # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # * Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ============================================================================ import time import torch import torch.nn as nn import torch.backends.cudnn as cudnn import torchvision.models as models from torch.autograd import Variable class MobileNet(nn.Module): def __init__(self): super(MobileNet, self).__init__() def conv_bn(inp, oup, stride): return nn.Sequential( nn.Conv2d(inp, oup, 3, stride, 1, bias=False), nn.BatchNorm2d(oup), nn.ReLU(inplace=True) ) def conv_dw(inp, oup, stride): return nn.Sequential( nn.Conv2d(inp, inp, 3, stride, 1, groups=inp, bias=False), nn.BatchNorm2d(inp), nn.ReLU(inplace=True), nn.Conv2d(inp, oup, 1, 1, 0, bias=False), nn.BatchNorm2d(oup), nn.ReLU(inplace=True), ) self.model = nn.Sequential( conv_bn( 3, 32, 2), conv_dw( 32, 64, 1), conv_dw( 64, 128, 2), conv_dw(128, 128, 1), conv_dw(128, 256, 2), conv_dw(256, 256, 1), conv_dw(256, 512, 2), conv_dw(512, 512, 1), conv_dw(512, 512, 1), conv_dw(512, 512, 1), conv_dw(512, 512, 1), conv_dw(512, 512, 1), conv_dw(512, 1024, 2), conv_dw(1024, 1024, 1), nn.AvgPool2d(7), ) self.fc = nn.Linear(1024, 1000) def forward(self, x): x = self.model(x) x = x.view(-1, 1024) x = self.fc(x) return x def speed(model, name): t0 = time.time() input = torch.rand(1,3,224,224).npu() input = Variable(input, volatile = True) t1 = time.time() model(input) t2 = time.time() model(input) t3 = time.time() print('%10s : %f' % (name, t3 - t2)) if __name__ == '__main__': #cudnn.benchmark = True # This will make network slow ?? resnet18 = models.resnet18().npu() alexnet = models.alexnet().npu() vgg16 = models.vgg16().npu() squeezenet = models.squeezenet1_0().npu() mobilenet = MobileNet().npu() speed(resnet18, 'resnet18') speed(alexnet, 'alexnet') speed(vgg16, 'vgg16') speed(squeezenet, 'squeezenet') speed(mobilenet, 'mobilenet')
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from setuptools import setup, find_packages __version__ = '1.0.0' __author__ = 'Takumi Sueda' __author_email__ = 'puhitaku@gmail.com' __license__ = 'MIT License' __classifiers__ = ( 'Development Status :: 4 - Beta', 'License :: OSI Approved :: MIT License', 'Operating System :: OS Independent', 'Programming Language :: Python', 'Programming Language :: Python :: 3', ) with open('README.md', 'r') as f: readme = f.read() setup( name='tepracli', version=__version__, license=__license__, author=__author__, author_email=__author_email__, url='https://github.com/puhitaku/tepra-lite-esp32/tree/master/client', description='An example of tepra-lite-esp32 client / CLI', long_description=readme, long_description_content_type='text/markdown', classifiers=__classifiers__, packages=find_packages(), package_data={'': ['assets/ss3.ttf']}, include_package_data=True, install_requires=['click', 'pillow', 'qrcode[pil]', 'requests'], )
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# Como trabalhar com paths from os import path import time def dadosArquivo(): # Verificar se o arquivo existe arquivoExiste = path.exists("./03.Trabalhando_com_Arquivos/NovoArquivo.txt") # Verificar se é diretório ehDiretorio = path.isdir("./03.Trabalhando_com_Arquivos/NovoArquivo.txt") # Verificar o path desse arquivo pathArquivo = path.realpath("./03.Trabalhando_com_Arquivos/NovoArquivo.txt") # Verificar o path relativo pathRelativo = path.relpath("./03.Trabalhando_com_Arquivos/NovoArquivo.txt") # Verificar data criação desse arquivo dataCriacao = time.ctime(path.getctime("./03.Trabalhando_com_Arquivos/NovoArquivo.txt")) # Data de modificação dataModificacao = time.ctime(path.getmtime("./03.Trabalhando_com_Arquivos/NovoArquivo.txt")) print(arquivoExiste) print(ehDiretorio) print(pathArquivo) print(pathRelativo) print(dataCriacao) print(dataModificacao) dadosArquivo()
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#!/usr/bin/env python3 import os import colorsys import cv2 import numpy as np from scipy.stats import multivariate_normal from matplotlib import pyplot as plt from mpl_toolkits.mplot3d import Axes3D class ColorPredicate: def __init__(self, name, images_path, n_max=10): self.name = name self._total_pixel_count = 0 self.images = self.load_images(images_path, n_max) self.masks = [255 * np.ones(image.shape[:2], np.uint8) for image in self.images] self._histogram_channels = None self._histogram_color_space = None self._bins = None self._grid = None self._ch_indexes = None self._target_histogram = None self._background_histogram = None self._gaussian_smoothed_histogram = None self._color_predicate = None self.color_spaces = { 'hsv': cv2.COLOR_BGR2HSV } self.ch_ranges = { 'b': (0, 256), 'g': (0, 256), 'r': (0, 256), 'h': (0, 180), 's': (0, 256), 'v': (0, 256) } def load_images(self, path, n_max): """Load and return a list of up to `n_max` images from `path`.""" images_list = [] n_max = min(n_max, len(os.listdir(path))) for filename in sorted(os.listdir(path))[:n_max]: image = cv2.imread(os.path.join(path, filename)) if image is not None: images_list.append(image) self._total_pixel_count += image.shape[0] * image.shape[1] return images_list def load_masks(self, path): """Load and return a list of image masks from path.""" masks_list = [] n_images = len(self.images) n_masks = len(os.listdir(path)) if n_masks >= len(self.images): for filename in sorted(os.listdir(path))[:n_images]: mask_gray = cv2.imread(os.path.join(path, filename), 0) ret, mask = cv2.threshold(mask_gray, 127, 255, cv2.THRESH_BINARY) if mask is not None: masks_list.append(mask) self.masks = masks_list else: print(f'Directory must contain at least {n_images} image files, ' f'but only {n_masks} were provided. Masks will be ignored.') @staticmethod def sample_pixels(target_pixels, bg_pixels, target_sr, bg_rate): """Take a random sample of target and background pixels. Parameters ---------- target_pixels : numpy.ndarray Array of pixels from target region. bg_pixels : numpy.ndarray Array of pixels from background region. target_sr : int or float Target pixels sample rate (percentage of total target pixels). bg_rate : int or float Ratio of background to target pixels. A value of 1.0 means equivalent distribution. Returns ------- target_pixels_sample : numpy.ndarray Array of random samples from target region. bg_pixels_sample : numpy.ndarray Array of random samples from background region. """ n_target_pixels, n_bg_pixels = len(target_pixels), len(bg_pixels) target_samples = n_target_pixels * target_sr if n_bg_pixels > 0: n_bg_samples = target_samples * bg_rate target_bg_ratio = n_target_pixels / n_bg_pixels if n_bg_samples > n_bg_pixels: target_sr = n_bg_pixels / (n_target_pixels * bg_rate) bg_sr = target_bg_ratio * target_sr * bg_rate indexes_bg_samples = np.random.choice([0, 1], size=n_bg_pixels, p=[(1 - bg_sr), bg_sr]) bg_pixels_sample = bg_pixels[indexes_bg_samples == 1] else: bg_pixels_sample = bg_pixels indexes_target_samples = np.random.choice([0, 1], size=n_target_pixels, p=[1 - target_sr, target_sr]) target_pixels_sample = target_pixels[indexes_target_samples == 1] return target_pixels_sample, bg_pixels_sample def create_multidimensional_histogram(self, color_space='bgr', ch_indexes=(0, 1, 2), bins=(8, 8, 8), target_sr=1.0, bg_rate=1.0): """Create a multidimensional histogram of instance's images. Color space can be either RGB or HSV. Dimension is set according to `ch_indexes` length. Sampling can be specified. Parameters ---------- color_space : str, optional Histogram color space. Accepts `bgr` (default) or `hsv`. ch_indexes : tuple, optional Sequence of histogram channel indexes. Values refer to `color_space` string order. E.g, use (0, 2) to create a 2D histogram of channels b and r. bins : tuple, optional Sequence of histogram bins. Must be of same length of `ch_indexes`. target_sr : int or float Target pixels sample rate (percentage of total target pixels). bg_rate : int or float Ratio of background to target pixels. A value of 1.0 means equivalent distribution. Returns ------- self._target_histogram : numpy.ndarray 2D or 3D histogram of sampled target pixels self._bg_histogram : numpy.ndarray 2D or 3D histogram of samples background pixels """ print('Computing histogram...', end=' ') target_pixels_per_image, bg_pixels_per_image = [], [] if sorted(ch_indexes) in ([0, 1], [0, 2], [1, 2], [0, 1, 2]): self._histogram_channels = [color_space[i] for i in ch_indexes] hist_range = [self.ch_ranges[ch] for ch in self._histogram_channels] else: raise ValueError('Parameter "ch_indexes" must be a sequence ' 'of unique integers between 0 and 2') for image, mask in zip(self.images, self.masks): if color_space != 'bgr': image = cv2.cvtColor(image, self.color_spaces[color_space]) target_pixels_per_image.append(image[mask > 0]) bg_pixels_per_image.append(image[~mask > 0]) target_pixels = np.concatenate(target_pixels_per_image) bg_pixels = np.concatenate(bg_pixels_per_image) target_samples, bg_samples = self.sample_pixels(target_pixels, bg_pixels, target_sr, bg_rate) self._target_histogram, _ = np.histogramdd(target_samples[:, ch_indexes], bins=bins, range=hist_range) self._background_histogram, _ = np.histogramdd(bg_samples[:, ch_indexes], bins=bins, range=hist_range) self._bins = bins self._histogram_color_space = color_space self._ch_indexes = ch_indexes print('Done!') return self._target_histogram, self._background_histogram def pdf(self, mean, cov, domain): """Multidimensional probability density function.""" pdf = multivariate_normal.pdf(domain, mean=mean, cov=cov) pdf = pdf.reshape(self._bins) return pdf def create_gaussian_smoothed_histogram(self, t_amp=1.0, t_cov=0.05, bg_amp=1.0, bg_cov=0.025, threshold=0.01, norm=True): """Create a 2D or 3D gaussian-smoothed histogram. A gaussian-smoothed histogram is built from target and background pixels according to [1]: for each pixel in target region, a normal distribution centered at its position is added to the histogram; similarly, for each pixel at background, a normal distribution is subtracted. Finally, thresholding is applied: color frequencies below threshold times maximum frequency are set to zero. [1] `Finding skin in color images`, R. Kjeldsen and J. Kender. Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, 1996. DOI:10.1109/AFGR.1996.557283 Parameters ---------- t_amp : float, optional Amplitude of target's normal distribution. Default is 1.0. t_cov : float, optional Covariance of target's normal distribution. Default is 0.05. bg_amp : float, optional Amplitude of background's normal distribution. Default is 1.0. bg_cov : float, optional Covariance of background's normal distribution. Default is 0.025. threshold : float, optional Color frequencies below threshold times maximum frequency are set to zero. Default is 0.01. norm : bool, optional When True, histogram is normalized by maximum frequency. Default is True. Returns ------- self._gaussian_smoothed_histogram : numpy.ndarray 2D or 3D gaussian-smoothed histogram. """ print('Generating gaussian-smoothed histogram...', end=' ') self._grid = np.mgrid[tuple([slice(0, b) for b in self._bins])] domain = np.column_stack([axis.flat for axis in self._grid]) gauss_sum = np.zeros(self._bins, dtype=np.float32) t_cov = t_cov * min(self._bins) bg_cov = bg_cov * min(self._bins) t_hist = self._target_histogram bg_hist = self._background_histogram for pos in np.argwhere(t_hist): pdf = self.pdf(pos, t_cov, domain) * t_amp gauss_sum += pdf * t_hist[tuple(pos)] for pos in np.argwhere(bg_hist): pdf = - self.pdf(pos, bg_cov, domain) * bg_amp gauss_sum += pdf * bg_hist[tuple(pos)] gauss_sum[gauss_sum < threshold * np.max(gauss_sum)] = 0 if norm: gauss_sum = gauss_sum / np.max(gauss_sum) self._gaussian_smoothed_histogram = gauss_sum print('Done!') return self._gaussian_smoothed_histogram def create_color_predicate(self, threshold=0, save=False, filename='color_predicate'): """Create a color predicate from gaussian-smoothed histogram. Parameters ---------- threshold : int or float, optional Histogram frequencies above threshold are set to one; frequencies below threshold are set to zero. Default is 0. save : bool, optional If true, color predicate is saved as a numpy array. Default is False. filename : str, optional Color predicate file name. Default is `color_predicate` Returns ------- color_predicate : numpy.ndarray Color predicate with the same dimension as the histogram. """ color_predicate = self._gaussian_smoothed_histogram.copy() color_predicate[color_predicate > threshold] = 1 color_predicate[color_predicate <= threshold] = 0 if save: np.save(filename, color_predicate) return color_predicate def plot_gaussian_smoothed_histogram(self, figsize=(8, 8), dpi=75, save=False): """Plot a 2D or 3D gaussian-smoothed histogram. When 2D, creates a pseudocolor histogram; when 3D, each bin is represented by a circle with size proportional to its frequency. Parameters ---------- figsize : tuple, optional Matplotlib's `figsize` parameter. Default is (8, 8). dpi : int, optional Matplotlib's `dpi` parameter. Default is 75. save : bool, optional When true, saves the plot as a png file. """ print('Plotting gaussian smoothed histogram...', end=' ') grid = self._grid ranges = self.ch_ranges bins = self._bins channels = self._histogram_channels histogram = self._gaussian_smoothed_histogram color_space = self._histogram_color_space axis = [(ranges[ch][1] / bins[i]) * grid[i] + (ranges[ch][1] / bins[i]) / 2 for i, ch in enumerate(channels)] if histogram.ndim == 3: colors = np.vstack((axis[0].flatten() / ranges[channels[0]][1], axis[1].flatten() / ranges[channels[1]][1], axis[2].flatten() / ranges[channels[2]][1])).T colors = colors[:, tuple([channels.index(ch) for ch in color_space])] if color_space == 'hsv': colors = np.array([colorsys.hsv_to_rgb(color[0], color[1], color[2]) for color in colors]) elif color_space == 'bgr': colors = colors[:, ::-1] fig = plt.figure(figsize=figsize, dpi=dpi) ax = fig.add_subplot(111, projection='3d') ax.title.set_position([0.5, 1.1]) ax.set_title(f'3D Color Histogram - ' f'{channels[0].title()} x ' f'{channels[1].title()} x ' f'{channels[2].title()}', fontsize=16) ax.xaxis.set_tick_params(labelsize=8) ax.yaxis.set_tick_params(labelsize=8) ax.zaxis.set_tick_params(labelsize=8) ax.set_xlim(ranges[channels[0]][0], ranges[channels[0]][1]) ax.set_ylim(ranges[channels[1]][0], ranges[channels[1]][1]) ax.set_zlim(ranges[channels[2]][0], ranges[channels[2]][1]) ax.set_xlabel(channels[0].title(), fontsize=12) ax.set_ylabel(channels[1].title(), fontsize=12) ax.set_zlabel(channels[2].title(), fontsize=12) ax.view_init(azim=45) ax.scatter(axis[0], axis[1], axis[2], s=histogram * 1000, c=colors) if save: ch_str = channels[0] + channels[1] + channels[2] plt.savefig(f'{self.name}_3d_{ch_str}_histogram.png') plt.show() if self._gaussian_smoothed_histogram.ndim == 2: fig = plt.figure(figsize=figsize, dpi=dpi) ax = fig.add_subplot(111) ax.set_aspect('equal') ax.set_title(f'2D Color Histogram - ' f'{channels[0].title()} x ' f'{channels[1].title()}') ax.set_xlabel(channels[0].title(), fontsize=12) ax.set_ylabel(channels[1].title(), fontsize=12, rotation=0) h = ax.pcolormesh(axis[0], axis[1], histogram) fig.colorbar(h, ax=ax) if save: ch_str = channels[0] + channels[1] plt.savefig(f'{self.name}_2d_{ch_str}_histogram.png') plt.show() print('Done!') @property def total_pixel_count(self): return self._total_pixel_count @property def gaussian_smoothed_histogram(self): return self._gaussian_smoothed_histogram @property def true_pixels_histogram(self): return self._target_histogram @property def false_pixels_histogram(self): return self._background_histogram @property def color_predicate(self): return self._color_predicate def __str__(self): description = f''' {self.name.title()} color predicate. Images: {len(self.images)} Bins: {self._bins} Color Space: {self._histogram_color_space} Channels: {self._ch_indexes} ''' return description
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# -*- coding: utf-8 -*- # Generated by Django 1.11.13 on 2018-05-25 15:41 from __future__ import unicode_literals import app.utils from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('projects', '0001_initial'), ] operations = [ migrations.CreateModel( name='Environment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=2000)), ('created_date', models.DateTimeField(auto_now_add=True, verbose_name='DateCreated')), ('api_key', models.CharField(default=app.utils.create_hash, max_length=100, unique=True)), ('project', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='environments', to='projects.Project')), ], options={ 'ordering': ['id'], }, ), migrations.CreateModel( name='Identity', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('identifier', models.CharField(max_length=2000)), ('created_date', models.DateTimeField(auto_now_add=True, verbose_name='DateCreated')), ('environment', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='identities', to='environments.Environment')), ], options={ 'ordering': ['id'], 'verbose_name_plural': 'Identities', }, ), ]
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""" module: basic_train.py - Model fitting methods docs : https://docs.fast.ai/train.html """ import pytest, fastai from fastai.vision import * from utils.fakes import * from utils.text import * from utils.mem import * from fastai.utils.mem import * from math import isclose torch_preload_mem() @pytest.fixture(scope="module") def data(): path = untar_data(URLs.MNIST_TINY) data = ImageDataBunch.from_folder(path, ds_tfms=([], []), bs=2) return data # this is not a fixture on purpose - the memory measurement tests are very sensitive, so # they need to be able to get a fresh learn object and not one modified by other tests. def learn_large_unfit(data): learn = create_cnn(data, models.resnet18, metrics=accuracy) return learn @pytest.fixture(scope="module") def learn(data): return learn_large_unfit(data) def test_get_preds(): learn = fake_learner() with CaptureStdout() as cs: a = learn.get_preds() assert learn.data.batch_size == len(a[1]) def test_save_load(learn): name = 'mnist-tiny-test-save-load' # testing that all these various sequences don't break each other model_path = learn.save(name, return_path=True) learn.load(name, purge=True) learn.data.sanity_check() assert 709 == len(learn.data.train_ds) learn.purge() learn.load(name) learn.load(name) model_path = learn.save(name, return_path=True) learn.load(name, purge=True) # basic checks #assert learn.recorder assert learn.opt assert 709 == len(learn.data.train_ds) # XXX: could use more sanity checks if os.path.exists(model_path): os.remove(model_path) def check_mem_expected(used_exp, peaked_exp, mtrace, abs_tol=2, ctx=None): used_received, peaked_received = mtrace.data() ctx = f" ({ctx})" if ctx is not None else "" assert isclose(used_exp, used_received, abs_tol=abs_tol), f"used mem: expected={used_exp} received={used_received}{ctx}" assert isclose(peaked_exp, peaked_received, abs_tol=abs_tol), f"peaked mem: expected={peaked_exp} received={peaked_received}{ctx}" def report_mem_real(used_exp, peaked_exp, mtrace, abs_tol=2, ctx=None): ctx = f" ({ctx})" if ctx is not None else "" print(f"{mtrace}{ctx}") #check_mem_expected = report_mem_real #@pytest.mark.skip(reason="WIP") @pytest.mark.cuda def test_save_load_mem_leak(data): learn = learn_large_unfit(data) name = 'mnist-tiny-test-save-load' #learn.fit_one_cycle(1) # A big difficulty with measuring memory consumption is that it varies quite # wildly from one GPU model to another. # # Perhaps we need sets of different expected numbers per developer's GPUs? # override check_mem_expected above with report_mem_real to acquire a new set # # So for now just testing the specific card I have until a better way is found. dev_name = torch.cuda.get_device_name(None) if dev_name != 'GeForce GTX 1070 Ti': pytest.skip(f"currently only matched for mem usage on specific GPU models, {dev_name} is not one of them") # save should consume no extra used or peaked memory with GPUMemTrace() as mtrace: model_path = learn.save(name, return_path=True) check_mem_expected(used_exp=0, peaked_exp=0, mtrace=mtrace, abs_tol=10, ctx="save") # load w/ purge still leaks some the first time it's run with GPUMemTrace() as mtrace: learn.load(name, purge=True) # XXX: very different numbers if done w/o fit first 42 8, w/ fit 24 16 check_mem_expected(used_exp=42, peaked_exp=8, mtrace=mtrace, abs_tol=10, ctx="load") # subsequent multiple load w/o purge should consume no extra used memory with GPUMemTrace() as mtrace: learn.load(name, purge=False) learn.load(name, purge=False) check_mem_expected(used_exp=0, peaked_exp=20, mtrace=mtrace, abs_tol=10, ctx="load x 2") # subsequent multiple load w/ purge should consume no extra used memory with GPUMemTrace() as mtrace: learn.load(name, purge=True) learn.load(name, purge=True) check_mem_expected(used_exp=0, peaked_exp=20, mtrace=mtrace, abs_tol=10, ctx="load x 2 2nd time") # purge + load w/ default purge should consume no extra used memory with GPUMemTrace() as mtrace: learn.purge() learn.load(name) check_mem_expected(used_exp=0, peaked_exp=20, mtrace=mtrace, abs_tol=10, ctx="purge+load") if os.path.exists(model_path): os.remove(model_path)
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# return.none.py def func(): pass func() # the return of this call won't be collected. It's lost. a = func() # the return of this one instead is collected into `a` print(a) # prints: None
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# -*- coding: utf-8 -*- __author__ = """Tom Smith""" __email__ = 'tom@takeontom.com' __version__ = '0.2.0' from pyperi.pyperi import Peri # noqa from pyperi.pyperi import PyPeriConnectionError # noqa
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import numpy as np import scipy.sparse as sparse from scipy.integrate import ode from scipy.interpolate import interp1d import time import control import control.matlab import numpy.random import pandas as pd from ltisim import LinearStateSpaceSystem from pendulum_model import * from pyMPC.mpc import MPCController # Reference model default parameters k_def = 5.0 tau_def = 120e-3 Acl_c_def = np.array([[0,1,0], [0, 0, k_def], [0, 0, -1/tau_def]]) Bcl_c_def = np.array([[0], [k_def], [1/tau_def] ]) # PID default parameters Ts_PID = 1e-3 # Reference trajectory t_ref_vec = np.array([0.0, 5.0, 10.0, 20.0, 25.0, 30.0, 40.0, 100.0]) p_ref_vec = np.array([0.0, 0.0, 0.8, 0.8, 0.0, 0.0, 0.8, 0.8]) rp_fun = interp1d(t_ref_vec, p_ref_vec, kind='linear') def xref_cl_fun_def(t): return np.array([rp_fun(t), 0.0, 0.0]) # MPC parameters Ts_MPC_def = 10e-3 Qx_def = 1.0 * sparse.diags([1.0, 0, 10.0]) # Quadratic cost for states x0, x1, ..., x_N-1 QxN_def = Qx_def Qr_def = 0.0 * sparse.eye(1) # Quadratic cost for u0, u1, ...., u_N-1 QDr_def = 1e-1 / (Ts_MPC_def ** 2) * sparse.eye(1) # Quadratic cost for Du0, Du1, ...., Du_N-1 # Defaults DEFAULTS_PENDULUM_MPC = { 'xref_cl_fun': xref_cl_fun_def, 'uref': np.array([0.0]), # N 'std_npos': 0*0.001, # m 'std_nphi': 0*0.00005, # rad 'std_dF': 0.05, # N 'w_F':20, # rad 'len_sim': 40, #s 'Acl_c': Acl_c_def, 'Bcl_c': Bcl_c_def, 'Ts_MPC': Ts_MPC_def, 'Np': 100, 'Nc': 50, 'Qx': Qx_def, 'QxN': QxN_def, 'Qr': Qr_def, 'QDr': QDr_def, 'Q_kal': np.diag([0.1, 10, 0.1, 10]), 'R_kal': 1*np.eye(2), 'QP_eps_abs': 1e-3, 'QP_eps_rel': 1e-3, 'seed_val': None } def get_parameter(sim_options, par_name): return sim_options.get(par_name, DEFAULTS_PENDULUM_MPC[par_name]) def get_default_parameters(sim_options): """ Which parameters are left to default ??""" default_keys = [key for key in DEFAULTS_PENDULUM_MPC if key not in sim_options] return default_keys def simulate_pendulum_MPC(sim_options): seed_val = get_parameter(sim_options,'seed_val') if seed_val is not None: np.random.seed(seed_val) # In[Sample times] Ts_MPC = get_parameter(sim_options, 'Ts_MPC') ratio_Ts = int(Ts_MPC // Ts_PID) # In[Real System] Cc = np.array([[1., 0., 0., 0.], [0., 0., 1., 0.]]) Cd = np.copy(Cc) nx, nu = 4,1 ny = 2 # In[initialize simulation system] t0 = 0 phi0 = -0.0 * 2 * np.pi / 360 # initial angle x0 = np.array([0, 0, phi0, 0]) # initial state #system_dyn = ode(f_ODE_wrapped).set_integrator('vode', method='bdf') # dopri5 system_dyn = ode(f_ODE_wrapped).set_integrator('dopri5') # dopri5 # system_dyn = ode(f_ODE_wrapped).set_integrator('dopri5') system_dyn.set_initial_value(x0, t0) system_dyn.set_f_params(0.0) #In[MPC params --model] Acl_c = get_parameter(sim_options, 'Acl_c') Bcl_c = get_parameter(sim_options, 'Bcl_c') Ccl_c = np.array([[1., 0., 0], [0., 0., 1]]) Dcl_c = np.zeros((2, 1)) ncl_x, ncl_u = Bcl_c.shape # number of states and number or inputs #ncl_y = np.shape(Ccl_c)[0] #In[MPC matrices discretization] Acl_d = np.eye(ncl_x) + Acl_c*Ts_MPC Bcl_d = Bcl_c*Ts_MPC Ccl_d = Ccl_c Dcl_d = Dcl_c x0_cl = np.array([0,0,phi0]) M_cl = LinearStateSpaceSystem(A=Acl_d, B=Bcl_d, C=Ccl_d, D=Dcl_d, x0=x0_cl) # MPC parameters Np = get_parameter(sim_options, 'Np') Nc = get_parameter(sim_options, 'Nc') Qx = get_parameter(sim_options, 'Qx') QxN = get_parameter(sim_options, 'QxN') Qr = get_parameter(sim_options, 'Qr') QDr = get_parameter(sim_options, 'QDr') # Constraints #xmin = np.array([-1.5, -100, -100]) #xmax = np.array([1.5, 100.0, 100]) #umin = np.array([-10]) #umax = np.array([10]) #Dumin = np.array([-100 * Ts_MPC_def]) #Dumax = np.array([100 * Ts_MPC_def]) QP_eps_rel = get_parameter(sim_options, 'QP_eps_rel') QP_eps_abs = get_parameter(sim_options, 'QP_eps_abs') # Emergency exit conditions EMERGENCY_STOP = False EMERGENCY_POS = 2.0 EMERGENCY_ANGLE = 30 * DEG_TO_RAD # Reference input and states xref_cl_fun = get_parameter(sim_options, 'xref_cl_fun') # reference state xref_cl_fun_v = np.vectorize(xref_cl_fun, signature='()->(n)') t0 = 0 xref_MPC = xref_cl_fun(t0) uref = get_parameter(sim_options, 'uref') uminus1 = np.array([0.0]) # input at time step negative one - used to penalize the first delta u at time instant 0. Could be the same as uref. kMPC = MPCController(Acl_d, Bcl_d, Np=Np, Nc=Nc, x0=x0_cl, xref=xref_MPC, uminus1=uminus1, Qx=Qx, QxN=QxN, Qu=Qr, QDu=QDr, eps_feas=1e3, eps_rel=QP_eps_rel, eps_abs=QP_eps_abs) try: kMPC.setup(solve=True) # setup initial problem and also solve it except: EMERGENCY_STOP = True if not EMERGENCY_STOP: if kMPC.res.info.status != 'solved': EMERGENCY_STOP = True # In[initialize PID] # Default controller parameters - P = -100.0 I = -1 D = -20 N = 100.0 kP = control.tf(P,1, Ts_PID) kI = I*Ts_PID*control.tf([0, 1], [1,-1], Ts_PID) kD = D*control.tf([N, -N], [1.0, Ts_PID*N - 1], Ts_PID) PID_tf = kP + kD + kI PID_ss = control.ss(PID_tf) k_PID = LinearStateSpaceSystem(A=PID_ss.A, B=PID_ss.B, C=PID_ss.C, D=PID_ss.D) # In[initialize noise] # Standard deviation of the measurement noise on position and angle std_npos = get_parameter(sim_options, 'std_npos') std_nphi = get_parameter(sim_options, 'std_nphi') # Force disturbance std_dF = get_parameter(sim_options, 'std_dF') # Disturbance power spectrum w_F = get_parameter(sim_options, 'w_F') # bandwidth of the force disturbance tau_F = 1 / w_F Hu = control.TransferFunction([1], [1 / w_F, 1]) Hu = Hu * Hu Hud = control.matlab.c2d(Hu, Ts_PID) N_sim_imp = tau_F / Ts_PID * 20 t_imp = np.arange(N_sim_imp) * Ts_PID t, y = control.impulse_response(Hud, t_imp) y = y[0] std_tmp = np.sqrt(np.sum(y ** 2)) # np.sqrt(trapz(y**2,t)) Hu = Hu / (std_tmp) * std_dF N_skip = int(20 * tau_F // Ts_PID) # skip initial samples to get a regime sample of d t_sim_d = get_parameter(sim_options, 'len_sim') # simulation length (s) N_sim_d = int(t_sim_d // Ts_PID) N_sim_d = N_sim_d + N_skip + 1 e = np.random.randn(N_sim_d) te = np.arange(N_sim_d) * Ts_PID _, d, _ = control.forced_response(Hu, te, e) d = d.ravel() # Simulate in closed loop len_sim = get_parameter(sim_options, 'len_sim') # simulation length (s) nsim = int(len_sim // Ts_MPC) #int(np.ceil(len_sim / Ts_MPC)) # simulation length(timesteps) # watch out! +1 added, is it correct? t_vec = np.zeros((nsim, 1)) status_vec = np.zeros((nsim,1)) x_vec = np.zeros((nsim, nx)) x_ref_vec = np.zeros((nsim, ncl_x)) y_vec = np.zeros((nsim, ny)) y_meas_vec = np.zeros((nsim, ny)) u_vec = np.zeros((nsim, nu)) x_model_vec = np.zeros((nsim,3)) nsim_fast = int(len_sim // Ts_PID) t_vec_fast = np.zeros((nsim_fast, 1)) x_vec_fast = np.zeros((nsim_fast, nx)) # finer integration grid for performance evaluation ref_phi_vec_fast = np.zeros((nsim_fast, 1)) y_meas_vec_fast = np.zeros((nsim_fast, ny)) x_ref_vec_fast = np.zeros((nsim_fast, nx)) # finer integration grid for performance evaluatio u_vec_fast = np.zeros((nsim_fast, nu)) # finer integration grid for performance evaluatio Fd_vec_fast = np.zeros((nsim_fast, nu)) # t_int_vec_fast = np.zeros((nsim_fast, 1)) emergency_vec_fast = np.zeros((nsim_fast, 1)) # t_step = t0 x_step = x0 u_PID = None t_pred_all = t0 + np.arange(nsim + Np + 1) * Ts_MPC Xref_MPC_all = xref_cl_fun_v(t_pred_all) for idx_fast in range(nsim_fast): ## Determine step type: fast simulation only or MPC step idx_MPC = idx_fast // ratio_Ts run_MPC_controller = (idx_fast % ratio_Ts) == 0 y_step = Cd.dot(x_step) # y[i] from the system ymeas_step = np.copy(y_step) ymeas_step[0] += std_npos * np.random.randn() ymeas_step[1] += std_nphi * np.random.randn() y_meas_vec_fast[idx_fast,:] = ymeas_step # Output for step i # Ts_MPC outputs if run_MPC_controller: # it is also a step of the simulation at rate Ts_MPC if idx_MPC < nsim: t_vec[idx_MPC, :] = t_step y_vec[idx_MPC,:] = y_step y_meas_vec[idx_MPC,:] = ymeas_step u_vec[idx_MPC, :] = u_PID x_model_vec[idx_MPC, :] = M_cl.x.ravel() xref_MPC = xref_cl_fun(t_step) x_ref_vec[idx_MPC,:] = xref_MPC.ravel() if not EMERGENCY_STOP: phi_ref_MPC, info_MPC = kMPC.output(return_status=True) # u[i] = k(\hat x[i]) possibly computed at time instant -1 else: phi_ref_MPC = np.zeros(nu) # PID angle CONTROLLER ref_phi = phi_ref_MPC.ravel() error_phi = ref_phi - ymeas_step[1] u_PID = k_PID.output(error_phi) u_PID[u_PID > 10.0] = 10.0 u_PID[u_PID < -10.0] = -10.0 u_TOT = u_PID # Ts_fast outputs t_vec_fast[idx_fast,:] = t_step x_vec_fast[idx_fast, :] = x_step #system_dyn.y u_vec_fast[idx_fast,:] = u_TOT Fd_vec_fast[idx_fast,:] = 0.0 ref_phi_vec_fast[idx_fast,:] = ref_phi ## Update to step i+1 k_PID.update(error_phi) # Controller simulation step at rate Ts_MPC if run_MPC_controller: M_cl.update(ref_phi) if not EMERGENCY_STOP: x_cl = np.array([x_step[0], x_step[1], x_step[2]]) Xref_MPC = Xref_MPC_all[idx_MPC:idx_MPC + Np + 1] xref_MPC = Xref_MPC_all[idx_MPC] kMPC.update(x_cl, phi_ref_MPC, xref=xref_MPC) # update with measurement and reference # System simulation step at rate Ts_fast time_integrate_start = time.perf_counter() system_dyn.set_f_params(u_TOT) system_dyn.integrate(t_step + Ts_PID) x_step = system_dyn.y t_int_vec_fast[idx_fast,:] = time.perf_counter() - time_integrate_start # Time update t_step += Ts_PID simout = {'t': t_vec, 'x': x_vec, 'u': u_vec, 'y': y_vec, 'y_meas': y_meas_vec, 'x_ref': x_ref_vec, 'status': status_vec, 'Fd_fast': Fd_vec_fast, 't_fast': t_vec_fast, 'x_fast': x_vec_fast, 'x_ref_fast': x_ref_vec_fast, 'u_fast': u_vec_fast, 'y_meas_fast': y_meas_vec_fast, 'emergency_fast': emergency_vec_fast, 'PID_tf': PID_tf, 'Ts_MPC': Ts_MPC, 'ref_phi_fast': ref_phi_vec_fast, 'x_model': x_model_vec, 't_int_fast': t_int_vec_fast } return simout if __name__ == '__main__': import matplotlib.pyplot as plt import matplotlib plt.close('all') simopt = DEFAULTS_PENDULUM_MPC time_sim_start = time.perf_counter() simout = simulate_pendulum_MPC(simopt) time_sim = time.perf_counter() - time_sim_start t = simout['t'] x = simout['x'] u = simout['u'] y = simout['y'] y_meas = simout['y_meas'] x_ref = simout['x_ref'] x_fast = simout['x_fast'] y_meas_fast = simout['y_meas_fast'] u_fast = simout['u_fast'] x_model = simout['x_model'] t_fast = simout['t_fast'] x_ref_fast = simout['x_ref_fast'] F_input = simout['Fd_fast'] status = simout['status'] ref_phi_fast = simout['ref_phi_fast'] uref = get_parameter(simopt, 'uref') nsim = len(t) nx = x.shape[1] ny = y.shape[1] y_ref = x_ref[:, [0, 2]] fig,axes = plt.subplots(4,1, figsize=(10,10), sharex=True) axes[0].plot(t, y_meas[:, 0], "b", label='p_meas') axes[0].plot(t_fast, x_fast[:, 0], "k", label='p') axes[0].plot(t, x_model[:, 0], "r", label='p model') axes[0].plot(t, x_ref[:, 0], "k--", label='p reference') axes[0].set_ylim(-2.0,2.0) axes[0].set_title("Position (m)") axes[1].plot(t_fast, x_fast[:, 1], "k", label='v') axes[1].plot(t, x_model[:, 1], "r", label='v model') axes[1].set_ylim(-3,3.0) axes[1].set_title("Speed (m/s)") axes[2].plot(t, y_meas[:, 1]*RAD_TO_DEG, "b", label='phi_meas') axes[2].plot(t_fast, x_fast[:, 2]*RAD_TO_DEG, 'k', label="phi") axes[2].plot(t, x_model[:, 2]*RAD_TO_DEG, "r", label='phi model') axes[2].plot(t_fast, ref_phi_fast[:,0]*RAD_TO_DEG, "k--", label="phi_ref") axes[2].set_ylim(-20,20) axes[2].set_title("Angle (deg)") axes[3].plot(t, u[:,0], label="F") axes[3].plot(t_fast, F_input, "k", label="Fd") axes[3].plot(t, uref*np.ones(np.shape(t)), "r--", label="F_ref") axes[3].set_ylim(-20,20) axes[3].set_title("Force (N)") for ax in axes: ax.grid(True) ax.legend() X = np.hstack((t_fast, x_fast, u_fast, y_meas_fast, F_input)) COL_T = ['time'] COL_X = ['p', 'v', 'theta', 'omega'] COL_U = ['u'] COL_D = ['d'] COL_Y = ['p_meas', 'theta_meas'] COL = COL_T + COL_X + COL_U + COL_Y + COL_D df_X = pd.DataFrame(X, columns=COL) df_X.to_csv("pendulum_data_PID.csv", index=False)
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from flask import Blueprint, current_app main = Blueprint('main', __name__) @main.route('/') def home(): return current_app.send_static_file('index.html')
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from enum import Enum from .dev import Dev class Collab(Enum): UNKNOWN = -1 NONE = 0 RAGNAROK_ONLINE = 1 TAIKO_NO_TATSUJIN = 2 EMIL_CHRONICLE_ONLINE = 3 GUNMA_NO_YABOU = 5 CRYSTAL_DEFENDER = 6 FAMITSU = 7 PRINCESS_PUNT_SWEET = 8 ANDROID = 9 SHINRABANSHO_CHOCO = 10 CAPYBARA_SAN = 11 FREAK_TOWER = 12 SENGOKU_TENKA_TRIGGER = 13 EVANGELION = 14 SEVEN_ELEVEN = 15 CLASH_OF_CLANS = 16 GROOVE_COASTER = 17 RAGNAROK_ODYSSEY_ACE = 18 DRAGONS_DOGMA_QUEST = 19 TAKAOKA_CITY = 20 MONSTER_HUNTER_4G = 21 BATMAN = 22 THIRTY_ONE_ICECREAM = 23 ANGRY_BIRDS = 24 PUZZLE_AND_DRAGONS_Z = 25 HUNTER_X_HUNTER = 26 SANRIO_CHARACTERS = 27 PAD_BATTLE_TOURNAMENT = 28 BEAMS = 29 DRAGON_BALL = 30 SAINT_SEIYA = 31 ROAD_TO_DRAGON = 32 DIVINE_GATE = 33 SUMMONS_BOARD = 34 PICOTTO_KINGDOM = 35 BIKKURIMAN = 36 ANGRY_BIRDS_EPIC = 37 DC_UNIVERSE = 38 CHIBI_1 = 39 # first round chibis - three kingdoms series FIST_OF_THE_NORTH_STAR = 40 CHIBI_2 = 41 # second round chibis CHIBI_3 = 44 # third round chibis FINAL_FANTASY = 45 GHOST_IN_THE_SHELL = 46 DUEL_MASTERS = 47 ATTACK_ON_TITAN = 48 NINJA_HATTORI_KUN = 49 SHONEN_SUNDAY = 50 CROWS_X_WORST = 51 # TODO VERIFY NO OVERLAP WITH VOLTRON BLEACH = 52 ACE_ATTORNEY = 55 RUROUNI_KENSHIN = 56 PEPPER = 57 KINNIKUMAN = 58 HIRUNE_HIME = 59 MAGAZINE = 60 MONSTER_HUNTER = 61 KAIBUTSU_KUN = 62 VOLTRON = 63 # TODO VERIFY NO OVERLAP WITH CROW X WORST FULLMETAL_ALCHEMIST = 65 KING_OF_FIGHTERS = 66 YU_YU_HAKUSHO = 67 PERSONA = 68 COCA_COLA = 69 MAGIC_THE_GATHERING = 70 CHRONO_MAGIA = 71 SEVENTH_REBIRTH = 72 CALCIO_FANTASISTA = 73 POWER_PROS = 74 GINTAMA = 75 SWORD_ART_ONLINE = 76 KAMEN_RIDER = 77 YOKAI_WATCH_W = 78 FATE_STAY_NIGHT = 79 STREET_FIGHTER_V = 80 UMAIBOU = 81 MC_DONALDS = 82 SHAMAN_KING = 83 ERROR_999 = 999 DRAGONBOUNDS_AND_DRAGON_CALLERS = 10001 @classmethod def _missing_(cls, value): Dev.log(f'Unknown collab: {value}') return Collab.UNKNOWN
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import pandas as pd from matplotlib.colors import LinearSegmentedColormap # Dataset data = pd.read_csv("./hr.csv") entries = len(data) bins = 10 # Data analysis analysis = { "bins": 10, "balance_threshold": 0.1 } # Plot labels labels = ["satisfaction_level", "average_montly_hours", "last_evaluation", "time_spend_company", "number_project", "Work_accident", "left", "promotion_last_5years", "sales", "salary"] pretty_prints = ["Self-reported satisfaction", "AVG Monthly hours", "Time since last valuation, in years", "Time in company, in years", "Projects", "Accidents", "Left", "Promoted (last 5 years)", "Department", "Salary"] short_pretty_prints = ["Injuries", "Work hours", "Last evaluation", "Left", "Projects", "Promotion", "Wage", "Satisfaction", "Years in company", "Dpt."] departments_pretty_prints = ["Information Technology", "R&D", "Accounting", "Human Resources", "Management", "Marketing", "Product Management", "Sales", "Support", "Technical"] labels_pretty_print = {k: v for k, v in zip(labels, pretty_prints)} short_labels_pretty_print = {k: v for k, v in zip(labels, short_pretty_prints)} labels_pretty_print["salary_int"] = "Salary" continuous_labels = labels[0:2] discrete_labels = labels[2:5] categorical_labels = labels[5:-1] ordinal_labels = labels[-1:] correlated_labels = continuous_labels + discrete_labels + ["salary_int"] categorical_labels_pretty_prints = { "Work_accident": ("Not Injured", "Injured"), "left": ("Stayed", "Left"), "promotion_last_5years": ("Not promoted", "Promoted"), "sales": tuple(departments_pretty_prints) } ordinal_labels_pretty_prints = { "salary": ("Low", "Medium", "High"), } ordered_ordinal_vars = { "salary": ["low", "medium", "high"] } departments = set(data["sales"]) # Scatter plot scatter = { "sampling_size": 100, # size of each sample "samples": 5, # number of samples to extract "edge_bins": 1, # edge bins possibly containing outliers "bins": 10, "replace": True } clusetering_types = ["normal", "discrete", "raw"] # Graphs palette = { "main": "#FE4365", "complementary": "#FC9D9A", "pr_complementary": "#F9CDAD", "sc_complementary": "#C8C8A9", "secondary": "#83AF9B" } round_palette = { "main": palette["secondary"], "secondary": palette["complementary"], "pr_complementary": palette["sc_complementary"], "sc_complementary": palette["secondary"] } large_palette = { "navy": "#001f3f", "blue": "#0074D9", "green": "#2ECC40", "olive": "#3D9970", "orange": "#FF851B", "yellow": "#FFDC00", "red": "#FF4136", "maroon": "#85144b", "black": "#111111", "grey": "#AAAAAA" } large_palette_full = { "navy": "#001f3f", "blue": "#0074D9", "aqua": "#7FDBFF", "teal": "#39CCCC", "olive": "#3D9970", "green": "#2ECC40", "lime": "#01FF70", "yellow": "#FFDC00", "orange": "#FF851B", "red": "#FF4136", "maroon": "#85144b", "fuchsia": "#F012BE", "purple": "#B10DC9", "black": "#111111", "grey": "#AAAAAA", "silver": "#DDDDDD" } large_palette_stacked = { "navy": "#001f3f", "blue": "#0074D9", "olive": "#3D9970", "orange": "#FF851B", "green": "#2ECC40", "yellow": "#FFDC00", "red": "#FF4136", "maroon": "#85144b", "black": "#111111", "grey": "#AAAAAA", "stack": large_palette["orange"] } cmap_pale_pink = LinearSegmentedColormap.from_list("Pale pink", [palette["pr_complementary"], palette["main"]], N=1000000) cmap_pale_pink_and_green = LinearSegmentedColormap.from_list("Pale pink&green", [palette["main"], palette["complementary"], palette["pr_complementary"], palette["sc_complementary"], palette["secondary"]], N=1000000)
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# Author: Vishal Gaur # Created: 17-01-2021 20:31:34 # function to find GCD using Basic Euclidean Algorithm def gcdEuclid(a, b): if a == 0: return b else: return gcdEuclid(b % a, a) # Driver Code to test above function a = 14 b = 35 g = gcdEuclid(a, b) print("GCD of", a, "&", b, "is: ", g) a = 56 b = 125 g = gcdEuclid(a, b) print("GCD of", a, "&", b, "is: ", g)
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# modules/InterpolationLayer.py from torch.nn import Module from functions.MotionSymmetryLayer import MotionSymmetryLayer class MotionSymmetryModule(Module): def __init__(self): super(MotionSymmetryModule, self).__init__() self.f = MotionSymmetryLayer() def forward(self, input1, input2): return self.f(input1, input2) #we actually dont need to write the backward code for a module, since we have
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import numpy from steer2HarmMtx import steer2HarmMtx def steer(*args): ''' Steer BASIS to the specfied ANGLE. function res = steer(basis,angle,harmonics,steermtx) BASIS should be a matrix whose columns are vectorized rotated copies of a steerable function, or the responses of a set of steerable filters. ANGLE can be a scalar, or a column vector the size of the basis. HARMONICS (optional, default is N even or odd low frequencies, as for derivative filters) should be a list of harmonic numbers indicating the angular harmonic content of the basis. STEERMTX (optional, default assumes cosine phase harmonic components, and filter positions at 2pi*n/N) should be a matrix which maps the filters onto Fourier series components (ordered [cos0 cos1 sin1 cos2 sin2 ... sinN]). See steer2HarmMtx.m Eero Simoncelli, 7/96. Ported to Python by Rob Young, 5/14. ''' if len(args) < 2: print 'Error: input parameters basis and angle are required!' return basis = args[0] num = basis.shape[1] angle = args[1] if isinstance(angle, (int, long, float)): angle = numpy.array([angle]) else: if angle.shape[0] != basis.shape[0] or angle.shape[1] != 1: print 'ANGLE must be a scalar, or a column vector the size of the basis elements' return # If HARMONICS are not passed, assume derivatives. if len(args) < 3: if num%2 == 0: harmonics = numpy.array(range(num/2))*2+1 else: harmonics = numpy.array(range((15+1)/2))*2 else: harmonics = args[2] if len(harmonics.shape) == 1 or harmonics.shape[0] == 1: # reshape to column matrix harmonics = harmonics.reshape(harmonics.shape[0], 1) elif harmonics.shape[0] != 1 and harmonics.shape[1] != 1: print 'Error: input parameter HARMONICS must be 1D!' return if 2*harmonics.shape[0] - (harmonics == 0).sum() != num: print 'harmonics list is incompatible with basis size!' return # If STEERMTX not passed, assume evenly distributed cosine-phase filters: if len(args) < 4: steermtx = steer2HarmMtx(harmonics, numpy.pi*numpy.array(range(num))/num, 'even') else: steermtx = args[3] steervect = numpy.zeros((angle.shape[0], num)) arg = angle * harmonics[numpy.nonzero(harmonics)[0]].T if all(harmonics): steervect[:, range(0,num,2)] = numpy.cos(arg) steervect[:, range(1,num,2)] = numpy.sin(arg) else: steervect[:, 1] = numpy.ones((arg.shape[0],1)) steervect[:, range(0,num,2)] = numpy.cos(arg) steervect[:, range(1,num,2)] = numpy.sin(arg) steervect = numpy.dot(steervect,steermtx) if steervect.shape[0] > 1: tmp = numpy.dot(basis, steervect) res = sum(tmp).T else: res = numpy.dot(basis, steervect.T) return res
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import aiohttp import asyncio import os import zipfile from pydest.api import API from pydest.manifest import Manifest class Pydest: def __init__(self, api_key, loop=None, client_id=None, client_secret=None): """Base class for Pydest Args: api_key (str): Bungie.net API key loop [optional]: AsyncIO event loop, if not passed one will be created client_id (str) [optional]: Bungie.net application client id client_secret (str) [optional]: Bungie.net application client id """ headers = {'X-API-KEY': api_key} self._loop = asyncio.get_event_loop() if loop is None else loop self._session = aiohttp.ClientSession(loop=self._loop, headers=headers) self.api = API(self._session, client_id, client_secret) self._manifest = Manifest(self.api) async def decode_hash(self, hash_id, definition, language='en'): """Get the corresponding static info for an item given it's hash value from the Manifest Args: hash_id (str): The unique identifier of the entity to decode definition (str): The type of entity to be decoded (ex. 'DestinyClassDefinition') language (str): The language to use when retrieving results from the Manifest Returns: json (dict) Raises: PydestException """ return await self._manifest.decode_hash(hash_id, definition, language) async def update_manifest(self, language='en'): """Update the manifest if there is a newer version available Args: language (str) [optional]: The language corresponding to the manifest to update """ await self._manifest.update_manifest(language) async def close(self): await self._session.close() class PydestException(Exception): pass class PydestTokenException(Exception): pass
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# Generated by Django 3.2.1 on 2021-05-06 22:30 import django.contrib.gis.db.models.fields from django.db import migrations class Migration(migrations.Migration): dependencies = [ ("core", "0119_populate_source_location_point"), ] operations = [ migrations.AlterField( model_name="location", name="point", field=django.contrib.gis.db.models.fields.PointField( blank=True, geography=True, null=True, srid=4326 ), ), migrations.AlterField( model_name="sourcelocation", name="point", field=django.contrib.gis.db.models.fields.GeometryField( blank=True, geography=True, null=True, srid=4326 ), ), ]
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#!/usr/bin/python # -*- coding: utf8 -*- import os import re import textwrap import requests import unicodedata from datetime import datetime, timedelta from flask import Flask, g, request, render_template, abort, make_response from flask_babel import Babel, gettext from jinja2 import evalcontextfilter, Markup app = Flask(__name__, static_url_path='/static') app.config['BABEL_DEFAULT_LOCALE'] = 'sk' app.jinja_options = {'extensions': ['jinja2.ext.with_', 'jinja2.ext.i18n']} babel = Babel(app) EVENT = gettext('PyCon SK 2018') DOMAIN = 'https://2018.pycon.sk' API_DOMAIN = 'https://api.pycon.sk' LANGS = ('en', 'sk') TIME_FORMAT = '%Y-%m-%dT%H:%M:%S+00:00' NOW = datetime.utcnow().strftime(TIME_FORMAT) SRC_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__))) LOGO_PYCON = 'logo/pycon_logo_square.svg' LDJSON_SPY = { "@type": "Organization", "name": "SPy o. z.", "url": "https://spy.pycon.sk", "logo": "https://spy.pycon.sk/img/logo/spy-logo.png", "sameAs": [ "https://facebook.com/pyconsk", "https://twitter.com/pyconsk", "https://www.linkedin.com/company/spy-o--z-", "https://github.com/pyconsk", ] } LDJSON_PYCON = { "@context": "http://schema.org", "@type": "Event", "name": EVENT, "description": gettext("PyCon will be back at Slovakia in 2018 again. PyCon SK is a community-organized conference " "for the Python programming language."), "startDate": "2018-03-09T9:00:00+01:00", "endDate": "2018-03-11T18:00:00+01:00", "image": DOMAIN + "/static/img/logo/pycon_long_2018.png", "location": { "@type": "Place", "name": "FIIT STU", "address": { "@type": "PostalAddress", "streetAddress": "Ilkovičova 2", "addressLocality": "Bratislava 4", "postalCode": "842 16", "addressCountry": gettext("Slovak Republic") }, }, "url": DOMAIN, "workPerformed": { "@type": "CreativeWork", "name": EVENT, "creator": LDJSON_SPY } } # calendar settings ICAL_LEN = 70 # length of a calendar (ical) line ICAL_NL = '\\n\n' # calendar newline IGNORE_TALKS = ['Break', 'Coffee Break'] TYPE = { 'talk': gettext('Talk'), 'workshop': gettext('Workshop'), } TAGS = { 'ai': gettext('Machine Learning / AI'), 'community': gettext('Community / Diversity / Social'), 'data': gettext('Data Science'), 'devops': 'DevOps', 'docs': gettext('Documentation'), 'edu': gettext('Education'), 'generic': gettext('Python General'), 'security': gettext('Security'), 'softskills': gettext('Soft Skills'), 'hardware': gettext('Hardware'), 'web': gettext('Web Development'), 'other': gettext('Other'), } FRIDAY_START = datetime(2018, 3, 9, hour=9) SATURDAY_START = datetime(2018, 3, 10, hour=9) SUNDAY_START = datetime(2018, 3, 11, hour=10, minute=15) FRIDAY_TRACK1 = ( {"pause": 5, 'title': gettext("Conference Opening"), 'duration': 25, 'flag': 'other', 'type': 'talk'}, {"pause": 15, 'title': gettext("FaaS and Furious - Zero to Serverless in 60 seconds - Anywhere")}, {"pause": 15, 'title': gettext("Docs or it didn't happen")}, {"pause": 5, 'title': gettext("GraphQL is the new black")}, {"pause": 60, 'title': gettext("To the Google in 80 Days")}, {"pause": 5, 'title': gettext("Unsafe at Any Speed")}, {"pause": 15, 'title': gettext("Protecting Privacy and Security — For Yourself and Your Community")}, {"pause": 5, 'title': gettext("ZODB: The Graph database for Python Developers.")}, {"pause": 15, 'title': gettext("Differentiable programming in Python and Gluon for (not only medical) image analysis")}, {"pause": 5, 'title': gettext("Vim your Python, Python your Vim")}, ) FRIDAY_TRACK2 = ( {"pause": 5, 'title': gettext("Conference Opening in Kiwi.com Hall"), 'duration': 25}, {"pause": 5, 'title': gettext("Python Days in Martin and follow-up activities")}, {"pause": 15, 'title': gettext("Python programming till graduation")}, {"pause": 5, 'title': gettext("Open educational resources for learning Python")}, {"pause": 60, 'title': gettext("About Ninjas and Mentors: CoderDojo in Slovakia")}, {"pause": 5, 'title': gettext("Community based courses")}, {"pause": 15, 'title': gettext("How do we struggle with Python in Martin?")}, {"pause": 5, 'title': gettext("Why hardware attracts kids and adults to IT")}, {"pause": 5, 'title': gettext("Panel discussion: Teaching IT in Slovakia - where is it heading?")}, {"pause": 5, 'title': gettext("EDU Talks"), 'duration': 30, 'language': 'SK', 'flag': 'edu', 'type': 'talk'}, ) FRIDAY_WORKSHOPS1 = ( {"pause": 10, 'title': gettext("How to create interactive maps in Python / R")}, {"pause": 60, 'title': gettext("Working with XML")}, {"pause": 5, 'title': gettext("Managing high-available applications in production")}, ) FRIDAY_WORKSHOPS2 = ( {"pause": 40, 'title': gettext("Workshop: An Introduction to Ansible")}, {"pause": 5, 'title': gettext("Introduction to Machine Learning with Python")}, ) FRIDAY_HALLWAY = ( {"pause": 0, 'title': gettext("OpenPGP key-signing party"), 'duration': 30, 'link': 'https://github.com/pyconsk/2018.pycon.sk/tree/master/openpgp-key-signing-party', 'flag': 'security'}, ) SATURDAY_TRACK1 = ( {"pause": 5, 'title': gettext("Conference Opening"), 'duration': 25, 'flag': 'other', 'type': 'talk'}, {"pause": 5, 'title': gettext("Solutions Reviews")}, {"pause": 15, 'title': gettext("Campaign Automation & Abusing Celery Properly")}, {"pause": 5, 'title': gettext("The Truth about Mastering Big Data")}, {"pause": 5, 'title': gettext("Industrial Machine Learning: Building scalable distributed machine learning pipelines with Python")}, {"pause": 25, 'title': gettext("Programming contest Semi finale"), 'duration': 30, 'flag': 'other', 'link': 'https://app.pycon.sk'}, {"pause": 5, 'title': gettext("Pythonic code, by example")}, {"pause": 15, 'title': gettext("Our DevOps journey, is SRE the next stop?")}, {"pause": 5, 'title': gettext("Implementing distributed systems with Consul")}, {"pause": 15, 'title': gettext("Designing fast and scalable Python MicroServices with django")}, {"pause": 5, 'title': gettext("When your wetware has too many threads - Tips from an ADHDer on how to improve your focus")}, {"pause": 5, 'title': gettext("Programming Python as performance: live coding with FoxDot")}, {"pause": 5, 'title': gettext("Programming Contest Grand Finale"), 'duration': 30, 'flag': 'other', 'type': 'talk', 'language': 'EN'}, {"pause": 5, 'title': gettext("Lightning Talks"), 'duration': 45, 'flag': 'other', 'type': 'talk'}, ) SATURDAY_TRACK2 = ( {"pause": 5, 'title': gettext("Conference Opening in Kiwi.com Hall"), 'duration': 25}, {"pause": 5, 'title': gettext("Meteo data in Python. Effectively.")}, {"pause": 15, 'title': gettext("Around the World in 30 minutes")}, {"pause": 5, 'title': gettext("LOCKED SHIELDS: What a good cyber testing looks like")}, {"pause": 60, 'title': gettext("Kiwi.com in ZOO")}, {"pause": 5, 'title': gettext("Keynote in Kiwi.com Hall"), 'duration': 30, 'flag': 'generic', 'type': 'talk'}, {"pause": 15, 'title': gettext("Skynet your Infrastructure with QUADS")}, {"pause": 5, 'title': gettext("Automated network OS testing")}, {"pause": 15, 'title': gettext("Tools to interact with Bitcoin and Ethereum")}, {"pause": 5, 'title': gettext("7 Steps to a Clean Issue Tracker")}, {"pause": 5, 'title': gettext("The Concierge Paradigm")}, ) SATURDAY_WORKSHOPS1 = ( {"pause": 55, 'title': gettext("Effectively running python applications in Kubernetes/OpenShift")}, {"pause": 5, 'title': gettext("Roboworkshop")}, ) SATURDAY_WORKSHOPS2 = ( {"pause": 55, 'title': gettext("Microbit:Slovakia")}, {"pause": 5, 'title': gettext("Coding in Python: A high-school programming lesson")}, ) SATURDAY_HALLWAY1 = ( {"pause": 0, 'title': gettext("Pandas documentation sprint"), 'duration': 360, 'link': 'https://python-sprints.github.io/pandas/', 'flag': 'docs'}, ) SATURDAY_HALLWAY2 = ( {"pause": 145, 'title': gettext("Programming contest"), 'duration': 95, 'flag': 'other', 'link': 'https://app.pycon.sk'}, {"pause": 5, 'title': gettext("Conference organizers meetup"), 'duration': 30, 'flag': 'community'}, ) SUNDAY_TRACK1 = ( {"pause": 5, 'title': gettext("Charon and the way out from a pickle hell")}, {"pause": 15, 'title': gettext("Making Python Behave")}, {"pause": 5, 'title': gettext("“Secret” information about the code we write")}, {"pause": 60, 'title': gettext("How to connect objects with each other in different situations with Pythonic ways - association, aggregation, composition and etc.")}, {"pause": 5, 'title': gettext("APIs: Gateway to world's data")}, {"pause": 15, 'title': gettext("Getting started with HDF5 and PyTables")}, {"pause": 5, 'title': gettext("Real-time personalized recommendations using embeddings")}, {"pause": 5, 'title': gettext("Quiz"), 'duration': 30, 'flag': 'other', 'type': 'talk'}, ) SUNDAY_WORKSHOPS1 = ( {"pause": 40, 'title': gettext("Real-time transcription and sentiment analysis of audio streams; on the phone and in the browser")}, {"pause": 5, 'title': gettext("Learn MongoDB by modeling PyPI in a document database")}, ) SUNDAY_WORKSHOPS2 = ( {"pause": 15, 'title': gettext("Testing Essentials for Scientists and Engineers")}, {"pause": 5, 'title': gettext("Cython: Speed up your code without going insane")}, ) SUNDAY_WORKSHOPS3 = ( {"pause": 15, 'title': gettext("Meet the pandas")}, {"pause": 5, 'title': gettext("Serverless with OpenFaaS and Python")}, ) SUNDAY_WORKSHOPS4 = ( {"pause": 5, 'title': gettext("Django Girls"), 'duration': 540, 'flag': 'web', 'type': 'workshop'}, ) SUNDAY_HALLWAY = ( {"pause": 5, 'title': gettext("Documentation clinic/helpdesk")}, ) AULA1 = { 'name': gettext('Kiwi.com Hall'), 'number': '-1.61', } AULA2 = { 'name': gettext('Python Software Foundation Hall'), 'number': '-1.65', } AULA3 = { 'name': gettext('SPy - Hall A'), 'number': '-1.57', } AULA4 = { 'name': gettext('SPy - Hall B'), 'number': '-1.57', } AULA5 = { 'name': gettext('Django Girls Auditorium'), 'number': '+1.31', } HALLWAY = { 'name': gettext('Hallway'), 'number': '', } def get_conference_data(url='', filters=''): """Connect to API and get public talks and speakers data.""" url = API_DOMAIN + url if filters: url = url + '&' + filters r = requests.get(url) return r.json() API_DATA_SPEAKERS = get_conference_data(url='/event/2018/speakers/') API_DATA_TALKS = get_conference_data(url='/event/2018/talks/') @app.before_request def before(): if request.view_args and 'lang_code' in request.view_args: g.current_lang = request.view_args['lang_code'] if request.view_args['lang_code'] not in LANGS: return abort(404) request.view_args.pop('lang_code') @babel.localeselector def get_locale(): # try to guess the language from the user accept # header the browser transmits. The best match wins. # return request.accept_languages.best_match(['de', 'sk', 'en']) return g.get('current_lang', app.config['BABEL_DEFAULT_LOCALE']) @app.template_filter() @evalcontextfilter def linebreaks(eval_ctx, value): """Converts newlines into <p> and <br />s.""" value = re.sub(r'\r\n|\r|\n', '\n', value) # normalize newlines paras = re.split('\n{2,}', value) paras = [u'<p>%s</p>' % p.replace('\n', '<br />') for p in paras] paras = u'\n\n'.join(paras) return Markup(paras) @app.template_filter() @evalcontextfilter def linebreaksbr(eval_ctx, value): """Converts newlines into <p> and <br />s.""" value = re.sub(r'\r\n|\r|\n', '\n', value) # normalize newlines paras = re.split('\n{2,}', value) paras = [u'%s' % p.replace('\n', '<br />') for p in paras] paras = u'\n\n'.join(paras) return Markup(paras) @app.template_filter() @evalcontextfilter def strip_accents(eval_ctx, value): """Strip non ASCII characters and convert them to ASCII.""" return unicodedata.normalize('NFKD', value).encode('ascii', 'ignore').decode("utf-8") def _get_template_variables(**kwargs): """Collect variables for template that repeats, e.g. are in body.html template""" lang = get_locale() variables = { 'title': EVENT, 'logo': LOGO_PYCON, # TODO: Do we need this? 'ld_json': LDJSON_PYCON } variables['ld_json']['url'] = DOMAIN + '/' + lang + '/' variables.update(kwargs) if 'current_lang' in g: variables['lang_code'] = g.current_lang else: variables['lang_code'] = app.config['BABEL_DEFAULT_LOCALE'] return variables def generate_track(api_data, track_data, start, flag=None): """Helper function to mix'n'match API data, with schedule order defined here, to generate schedule dict""" template_track_data = [] for talk in track_data: # Check if talk is in API talk_api_data = next((item for item in api_data if item['title'] == talk['title']), None) # If talk is not in API data we'll use text from track_data dict == same structure for template generation if not talk_api_data: talk_api_data = talk if not flag or ('flag' in talk_api_data and flag == talk_api_data['flag']): # Store data to be displayed in template template_track_data.append({ "start": start, "talk": talk_api_data }) start = start + timedelta(minutes=talk_api_data.get('duration', 0)) # start = start + timedelta(minutes=talk_api_data['duration']) if not flag: # Generate break break_name = gettext('Break') if talk['pause'] in (40, 60): break_name = gettext('Lunch 🍱') if talk['pause'] in (15, 20): break_name = gettext('Coffee Break ☕') template_track_data.append({ 'start': start, 'talk': {'title': break_name}, 'css': 'break' }) start = start + timedelta(minutes=talk['pause']) # break time does not comes from API always defined in track return template_track_data def generate_schedule(api_data, flag=None): return [ { 'room': AULA1, 'start': FRIDAY_START, 'schedule': generate_track(api_data, FRIDAY_TRACK1, FRIDAY_START, flag=flag), 'day': 'friday', 'block_start': True, }, { 'room': AULA2, 'start': FRIDAY_START, 'schedule': generate_track(api_data, FRIDAY_TRACK2, FRIDAY_START, flag=flag), 'day': 'friday' }, { 'room': AULA3, 'start': FRIDAY_START, 'schedule': generate_track(api_data, FRIDAY_WORKSHOPS1, FRIDAY_START+timedelta(minutes=30), flag=flag), 'day': 'friday' }, { 'room': AULA4, 'start': FRIDAY_START, 'schedule': generate_track(api_data, FRIDAY_WORKSHOPS2, FRIDAY_START+timedelta(minutes=30), flag=flag), 'day': 'friday', }, { 'room': HALLWAY, 'start': FRIDAY_START+timedelta(minutes=395), 'schedule': generate_track(api_data, FRIDAY_HALLWAY, FRIDAY_START+timedelta(minutes=395), flag=flag), 'day': 'saturday', 'block_end': True, }, { 'room': AULA1, 'start': SATURDAY_START, 'schedule': generate_track(api_data, SATURDAY_TRACK1, SATURDAY_START, flag=flag), 'day': 'saturday', 'block_start': True, }, { 'room': AULA2, 'start': SATURDAY_START, 'schedule': generate_track(api_data, SATURDAY_TRACK2, SATURDAY_START, flag=flag), 'day': 'saturday' }, { 'room': AULA3, 'start': SATURDAY_START, 'schedule': generate_track(api_data, SATURDAY_WORKSHOPS1, SATURDAY_START+timedelta(minutes=30), flag=flag), 'day': 'saturday' }, { 'room': AULA4, 'start': SATURDAY_START, 'schedule': generate_track(api_data, SATURDAY_WORKSHOPS2, SATURDAY_START+timedelta(minutes=30), flag=flag), 'day': 'saturday' }, { 'room': HALLWAY, 'start': SATURDAY_START+timedelta(minutes=60), 'schedule': generate_track(api_data, SATURDAY_HALLWAY1, SATURDAY_START+timedelta(minutes=60), flag=flag), 'day': 'saturday', }, { 'room': HALLWAY, 'start': SATURDAY_START+timedelta(minutes=30), 'schedule': generate_track(api_data, SATURDAY_HALLWAY2, SATURDAY_START+timedelta(minutes=30), flag=flag), 'day': 'saturday', 'block_end': True, }, { 'room': AULA1, 'start': SUNDAY_START, 'schedule': generate_track(api_data, SUNDAY_TRACK1, SUNDAY_START, flag=flag), 'day': 'sunday', 'block_start': True, }, { 'room': AULA2, 'start': SUNDAY_START, 'schedule': generate_track(api_data, SUNDAY_WORKSHOPS1, SUNDAY_START, flag=flag), 'day': 'sunday' }, { 'room': AULA3, 'start': SUNDAY_START, 'schedule': generate_track(api_data, SUNDAY_WORKSHOPS2, SUNDAY_START, flag=flag), 'day': 'sunday' }, { 'room': AULA4, 'start': SUNDAY_START, 'schedule': generate_track(api_data, SUNDAY_WORKSHOPS3, SUNDAY_START, flag=flag), 'day': 'sunday' }, { 'room': AULA5, 'start': SUNDAY_START, 'schedule': generate_track(api_data, SUNDAY_WORKSHOPS4, SUNDAY_START-timedelta(minutes=135), flag=flag), 'day': 'sunday', }, { 'room': HALLWAY, 'start': SUNDAY_START, 'schedule': generate_track(api_data, SUNDAY_HALLWAY, SUNDAY_START+timedelta(minutes=45), flag=flag), 'day': 'sunday', 'block_end': True, }, ] def _timestamp(dt=None): if dt is None: dt = datetime.now() fmt = '%Y%m%dT%H%M%S' return dt.strftime(fmt) def _ignore_talk(title, names=IGNORE_TALKS): # yes, we can paste unicode symbols, but if we change the symbol this test will still work max_appended_symbols = 2 return any((title == name or title[:-(_len+1)] == name) for _len in range(max_appended_symbols) for name in names) def _hash_event(track, slot): room = track.get('room') name = room.get('name') ts = _timestamp(slot.get('start')) _hash = str(hash('{name}:{ts}'.format(name=name, ts=ts))) _hash = _hash.replace('-', '*') return '-'.join(_hash[i*5:(i+1)*5] for i in range(4)) def _normalize(text, tag=None, subsequent_indent=' ', **kwargs): # tag must be always included to determine amount of space left in the first line if tag: max_width = ICAL_LEN - len(tag) - 1 else: max_width = ICAL_LEN text = text.strip().replace('\n', ICAL_NL) return '\n'.join(textwrap.wrap(text, width=max_width, subsequent_indent=subsequent_indent, **kwargs)) # CALENDAR FUNCTIONS def generate_event(track, slot): room = track.get('room') location = '{name} ({number})'.format(**room) talk = slot.get('talk') summary = talk.get('title', 'N/A') transp = 'OPAQUE' if _ignore_talk(summary): # skip breaks # alternatively we can include breaks into talks (duration=duration+pause) return {} summary = _normalize(summary, 'SUMMARY') start = slot.get('start') duration = talk.get('duration', 0) # TODO add missing duration handling (nonzero default duration? title based dictionary? dtend = _timestamp(start + timedelta(minutes=duration)) dtstart = _timestamp(start) dtstamp = created = modified = _timestamp() # event_uuid caused the event not to be imported to calendar # this creates hash of name:start and split with dashes by 5 uid = _hash_event(track, slot) author = '' main_description = '' tags = '' speaker = talk.get('primary_speaker') if speaker: name = ' '.join([speaker.get(n, '') for n in ['first_name', 'last_name']]) author = '{name}{nl} {nl}'.format(name=name, nl=ICAL_NL) # this is to determine how many chars do we have in the first line # if author is used we start at position 1, otherwise it will be prefixed with tag: desc_tag = 'DESCRIPTION' if not author else '' abstract = talk.get('abstract', '') if abstract: main_description = _normalize(abstract, desc_tag, initial_indent=' ') + ICAL_NL if 'flag' in talk: tags = ' {nl} TAGS: {flag}'.format(nl=ICAL_NL, **talk) description = author + main_description + tags status = 'CONFIRMED' sequence = 0 # number of revisions, we will use default zero even if event changed return {'dtstart': dtstart, 'dtend': dtend, 'dtstamp': dtstamp, 'created': created, 'last-modified': modified, 'uid': uid, 'location': location, 'sequence': sequence, 'description': description, 'status': status, 'summary': summary, 'transp': transp, } @app.route('/<lang_code>/calendar.ics') def generate_ics(): # https://tools.ietf.org/html/rfc5545#section-2.1 # https://en.wikipedia.org/wiki/ICalendar#Technical_specifications omni_schedule = generate_schedule(API_DATA_TALKS) events = [] uids = set() for track in omni_schedule: schedule = track.get('schedule') for slot in schedule: evt = generate_event(track, slot) if evt and evt.get('uid') not in uids: events.append(evt) uids.update([evt.get('uid')]) calendar_ics = render_template('calendar.ics', events=events) response = make_response(calendar_ics.replace('\n', '\r\n')) response.headers["Content-Type"] = "text/calendar" return response @app.route('/<lang_code>/index.html') def index(): return render_template('index.html', **_get_template_variables(li_index='active')) @app.route('/<lang_code>/tickets.html') def tickets(): return render_template('tickets.html', **_get_template_variables(li_tickets='active')) @app.route('/<lang_code>/<flag>/<day>/schedule.html') def schedule_day_filter(flag, day): variables = _get_template_variables(li_schedule_nav='active', li_schedule='active') variables['flag'] = flag variables['day'] = day variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} variables['data'] = api_data = API_DATA_TALKS variables['schedule'] = generate_schedule(api_data, flag=flag) return render_template('schedule.html', **variables) @app.route('/<lang_code>/<filter>/schedule.html') def schedule_filter(filter): variables = _get_template_variables(li_schedule_nav='active', li_schedule='active') if filter in ('friday', 'saturday', 'sunday'): variables['day'] = filter variables['flag'] = None else: variables['flag'] = filter variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} variables['data'] = api_data = API_DATA_TALKS variables['schedule'] = generate_schedule(api_data, flag=variables['flag']) return render_template('schedule.html', **variables) @app.route('/<lang_code>/schedule.html') def schedule(): variables = _get_template_variables(li_schedule_nav='active', li_schedule='active') variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} variables['data'] = api_data = API_DATA_TALKS variables['schedule'] = generate_schedule(api_data) variables['disable_last'] = True return render_template('schedule.html', **variables) @app.route('/<lang_code>/<flag>/talks.html') def talks_filter(flag): variables = _get_template_variables(li_schedule_nav='active', li_talks='active') variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} variables['data'] = get_conference_data(url='/event/2018/talks/?flag=' + flag) return render_template('talks.html', **variables) @app.route('/<lang_code>/talks.html') def talks(): variables = _get_template_variables(li_schedule_nav='active', li_talks='active') variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} variables['data'] = API_DATA_TALKS return render_template('talks.html', **variables) @app.route('/<lang_code>/speakers.html') def speakers(): variables = _get_template_variables(li_schedule_nav='active', li_speakers='active') variables['data'] = API_DATA_SPEAKERS variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} return render_template('speakers.html', **variables) @app.route('/<lang_code>/speakers/<last_name>.html') def profile(last_name): variables = _get_template_variables(li_schedule_nav='active') variables['tags'] = TAGS variables['all'] = {**TYPE, **TAGS} for speaker in API_DATA_SPEAKERS: if speaker['last_name'] == last_name: variables['speaker'] = speaker break variables['talks'] = [] for track in generate_schedule(API_DATA_TALKS): for talk in track['schedule']: if ('primary_speaker' in talk['talk'] or 'secondary_speaker' in talk['talk']) and \ talk['talk']['primary_speaker']['last_name'] == variables['speaker']['last_name'] or ( 'secondary_speaker' in talk['talk'] and talk['talk']['secondary_speaker']['last_name'] == variables['speaker']['last_name']): variables['talks'].append((track, talk)) break return render_template('profile.html', **variables) @app.route('/<lang_code>/cfp.html') def cfp(): return render_template('cfp.html', **_get_template_variables(li_cfp='active')) @app.route('/<lang_code>/coc.html') def coc(): return render_template('coc.html', **_get_template_variables(li_coc='active')) @app.route('/<lang_code>/hall-of-fame.html') def hall_of_fame(): return render_template('hall-of-fame.html', **_get_template_variables(li_hall_of_fame='active')) @app.route('/<lang_code>/venue.html') def venue(): return render_template('venue.html', **_get_template_variables(li_venue='active')) @app.route('/<lang_code>/sponsoring.html') def sponsoring(): return render_template('sponsoring.html', **_get_template_variables(li_sponsoring='active')) def get_mtime(filename): """Get last modification time from file""" mtime = datetime.fromtimestamp(os.path.getmtime(filename)) return mtime.strftime(TIME_FORMAT) SITEMAP_DEFAULT = {'prio': '0.1', 'freq': 'weekly'} SITEMAP = { 'sitemap.xml': {'prio': '0.9', 'freq': 'daily', 'lastmod': get_mtime(__file__)}, 'index.html': {'prio': '1', 'freq': 'daily'}, 'schedule.html': {'prio': '0.9', 'freq': 'daily'}, 'speakers.html': {'prio': '0.9', 'freq': 'daily'}, 'hall_of_fame.html': {'prio': '0.5', 'freq': 'weekly'}, 'tickets.html': {'prio': '0.5', 'freq': 'weekly'}, } def get_lastmod(route, sitemap_entry): """Used by sitemap() below""" if 'lastmod' in sitemap_entry: return sitemap_entry['lastmod'] template = route.rule.split('/')[-1] template_file = os.path.join(SRC_DIR, 'templates', template) if os.path.exists(template_file): return get_mtime(template_file) return NOW @app.route('/sitemap.xml', methods=['GET']) def sitemap(): """Generate sitemap.xml. Makes a list of urls and date modified.""" pages = [] # static pages for rule in app.url_map.iter_rules(): if "GET" in rule.methods: if len(rule.arguments) == 0: indx = rule.rule.replace('/', '') sitemap_data = SITEMAP.get(indx, SITEMAP_DEFAULT) pages.append({ 'loc': DOMAIN + rule.rule, 'lastmod': get_lastmod(rule, sitemap_data), 'freq': sitemap_data['freq'], 'prio': sitemap_data['prio'], }) elif 'lang_code' in rule.arguments: indx = rule.rule.replace('/<lang_code>/', '') for lang in LANGS: alternate = [] for alt_lang in LANGS: if alt_lang != lang: alternate.append({ 'lang': alt_lang, 'url': DOMAIN + rule.rule.replace('<lang_code>', alt_lang) }) sitemap_data = SITEMAP.get(indx, SITEMAP_DEFAULT) pages.append({ 'loc': DOMAIN + rule.rule.replace('<lang_code>', lang), 'alternate': alternate, 'lastmod': get_lastmod(rule, sitemap_data), 'freq': sitemap_data['freq'], 'prio': sitemap_data['prio'], }) sitemap_xml = render_template('sitemap_template.xml', pages=pages) response = make_response(sitemap_xml) response.headers["Content-Type"] = "text/xml" return response if __name__ == "__main__": app.run(debug=True, host=os.environ.get('FLASK_HOST', '127.0.0.1'), port=int(os.environ.get('FLASK_PORT', 5000)), use_reloader=True)
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations from django.conf import settings class Migration(migrations.Migration): dependencies = [ ('group', '0001_initial'), migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('community', '0001_initial'), ('doc', '0001_initial'), ] operations = [ migrations.AddField( model_name='rule', name='cached_ids', field=models.ManyToManyField(to='doc.Document'), preserve_default=True, ), migrations.AddField( model_name='rule', name='community_list', field=models.ForeignKey(to='community.CommunityList'), preserve_default=True, ), migrations.AlterUniqueTogether( name='rule', unique_together=set([('community_list', 'rule_type', 'value')]), ), migrations.AddField( model_name='listnotification', name='event', field=models.ForeignKey(to='doc.DocEvent'), preserve_default=True, ), migrations.AddField( model_name='expectedchange', name='community_list', field=models.ForeignKey(to='community.CommunityList'), preserve_default=True, ), migrations.AddField( model_name='expectedchange', name='document', field=models.ForeignKey(to='doc.Document'), preserve_default=True, ), migrations.AddField( model_name='emailsubscription', name='community_list', field=models.ForeignKey(to='community.CommunityList'), preserve_default=True, ), migrations.AddField( model_name='documentchangedates', name='document', field=models.ForeignKey(to='doc.Document'), preserve_default=True, ), migrations.AddField( model_name='displayconfiguration', name='community_list', field=models.ForeignKey(to='community.CommunityList'), preserve_default=True, ), migrations.AddField( model_name='communitylist', name='added_ids', field=models.ManyToManyField(to='doc.Document'), preserve_default=True, ), migrations.AddField( model_name='communitylist', name='group', field=models.ForeignKey(blank=True, to='group.Group', null=True), preserve_default=True, ), migrations.AddField( model_name='communitylist', name='user', field=models.ForeignKey(blank=True, to=settings.AUTH_USER_MODEL, null=True), preserve_default=True, ), ]
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#!/usr/bin/env python import argparse import fishact if __name__ == '__main__': parser = argparse.ArgumentParser( description='Validate data files.') parser.add_argument('activity_fname', metavar='activity_file', type=str, help='Name of activity file.') parser.add_argument('gtype_fname', metavar='genotype_file', type=str, help='Name of genotype file.') args = parser.parse_args() print('------------------------------------------------') print('Checking genotype file...') fishact.validate.test_genotype_file(args.gtype_fname) print('------------------------------------------------\n\n\n') print('------------------------------------------------') print('Checking activity file...') fishact.validate.test_activity_file(args.activity_fname, args.gtype_fname) print('------------------------------------------------')
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#!/usr/bin/env python3 from sys import stdout,stderr,exit from optparse import OptionParser from newick_parser import parse_tree_iterator, Branch from tree_span import calculateSpan from copy import deepcopy def rescale_absolute(tree, max_length): span = calculateSpan(tree) s = max_length/float(span) return rescale(tree, s) def rescale(tree, scale_factor): res = deepcopy(tree) stack = list() stack.append(res.subtree) while stack: x = stack.pop() if x.length: x.length *= scale_factor if type(x) == Branch: stack.extend(x.subtrees) return res if __name__ == '__main__': usage = 'usage: %prog [options] <NEWICK FILE>' parser = OptionParser(usage=usage) parser.add_option('-s', '--scale_factor', dest='scale_factor', help='Scale factor of distances in tree', type=float, default=0, metavar='FLOAT') parser.add_option('-a', '--absolute_length', dest='absolute', help='Absolute length of maximal distance in tree', type=float, default=0, metavar='FLOAT') (options, args) = parser.parse_args() if len(args) != 1: parser.print_help() exit(1) if not ((options.absolute > 0) ^ (options.scale_factor > 0)): print('!! Specify either scale factor or absolute length with ' + \ 'strictly positive number', file = stderr) exit(1) for tree in parse_tree_iterator(open(args[0])): if options.absolute > 0: print(rescale_absolute(tree, options.absolute), file = stdout) else: print(rescale(tree, options.scale_factor), file = stdout)
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from stable_baselines3 import PPO import os from setup_gym_env import SnakeEnv import time #models_dir = "./models/1644408901/" + "40000" #models_dir = "./models/1644462865/" + "120000" #models_dir = "./models/1644466638/" + "100000" models_dir = "./models/1644485414/" + "100000" env = SnakeEnv() env.reset() model = PPO.load(models_dir) episodes = 10 # snake doesn't known where itself for episode in range(episodes): done = False obs = env.reset() #while True:#not done: while not done: action, _states = model.predict(obs) #print("action",action) obs, reward, done, info = env.step(action) #print('reward',reward) if done == True: print(done) env.render()
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#!/usr/bin/env python3 import yoda, sys import h5py import numpy as np def chunkIt(seq, num): avg = len(seq) / float(num) out = [] last = 0.0 while last < len(seq): out.append(seq[int(last):int(last + avg)]) last += avg # Fix size, sometimes there is spillover # TODO: replace with while if problem persists if len(out) > num: out[-2].extend(out[-1]) out = out[0:-1] if len(out) != num: raise Exception("something went wrong in chunkIt, the target size differs from the actual size") return out def createDatasets(f, binids, variations, depth=1, compression=4): """ Create data sets in the HDF5 file. """ nbins=len(binids) nvars=len(variations) # The fundamental moments/elements of yoda objecs floats = [ "sumw", "sumw2", "sumwx", "sumwx2", "sumwy", "sumwy2", "sumwxy", "numEntries", "xval", "xerr-", "xerr+", "yval", "yerr-", "yerr+", "xmin", "xmax", "ymin", "ymax" ] # The datasets have 3 axes: binid, weight variation, point in parameter space for df in floats: f.create_dataset(df, (nbins,nvars,depth), maxshape=(None,None,None), dtype='f' , chunks=True, compression=compression) # Lookups --- helps when reading data and reconstucting YODA objects f.create_group("Histo1D") f.create_group("Histo2D") f.create_group("Profile1D") f.create_group("Counter") f.create_group("Scatter1D") f.create_group("Scatter2D") # This is the one that works well with hdf5 when reading std::string in C++ dt = h5py.special_dtype(vlen=str) # We use these simple lists as lookup tables to associate the elements of the datasets ^^^ with # the actual YODA Analysis objects import numpy as np f.create_dataset("binids", data=np.array(binids, dtype=dt)) f.create_dataset("variations", data=np.array(variations, dtype=dt)) def dbn0ToArray(dbn): return np.array([dbn.sumW(), dbn.sumW2(), dbn.numEntries()]) def dbn1ToArray(dbn): """ The try except block deals with the underflow things not having xmin, xmax """ try: return np.array([dbn.sumW(), dbn.sumW2(), dbn.sumWX(), dbn.sumWX2(), dbn.numEntries(), dbn.xMin(), dbn.xMax()]) except: return np.array([dbn.sumW(), dbn.sumW2(), dbn.sumWX(), dbn.sumWX2(), dbn.numEntries(), 0, 0]) def H2dbn2ToArray(dbn): """ The try except block deals with the underflow things not having xmin, xmax """ try: return np.array([dbn.sumW(), dbn.sumW2(), dbn.sumWX(), dbn.sumWX2(), dbn.sumWY(), dbn.sumWY2(), dbn.sumWXY(), dbn.numEntries(), dbn.xMin(), dbn.xMax(), dbn.yMin(), dbn.yMax()]) except: return np.array([dbn.sumW(), dbn.sumW2(), dbn.sumWX(), dbn.sumWX2(), dbn.sumWY(), dbn.sumWY2(), dbn.sumWXY(), dbn.numEntries(), 0, 0, 0, 0]) def dbn2ToArray(dbn): try: return np.array([dbn.sumW(), dbn.sumW2(), dbn.sumWX(), dbn.sumWX2(), dbn.sumWY(), dbn.sumWY2(), dbn.numEntries(), dbn.xMin(), dbn.xMax()]) except: return np.array([dbn.sumW(), dbn.sumW2(), dbn.sumWX(), dbn.sumWX2(), dbn.sumWY(), dbn.sumWY2(), dbn.numEntries(), 0, 0]) def point2DToArray(pnt): return np.array([pnt.val(1), pnt.errMinus(1), pnt.errPlus(1), pnt.val(2), pnt.errMinus(2), pnt.errPlus(2)]) def point1DToArray(pnt): return np.array([pnt.val(1), pnt.errMinus(1), pnt.errPlus(1)]) def mkSafeHname(hname): return hname.replace("/","|") def mkBinids(hdict): binids= [] for num, hname in enumerate(sorted(list(hdict.keys()))): if hname.endswith("]"): continue ao = hdict[hname] base = ao.path().split("[")[0].replace("/","|") if ao.type()=="Scatter1D" or ao.type()=="Scatter2D": temp = ["{}#{}".format(base, i) for i in range(len(ao))] elif ao.type()=="Counter": temp = ["{}#{}".format(base, 0)] else: suffixes = ["T", "O", "U"] if ao.type() == "Counter": suffixes.append(0) else: suffixes.extend([i for i in range(len(ao))]) temp = ["{}#{}".format(base, s) for s in suffixes] binids.extend(temp) return binids def mkIndexDict(datadict, allbinids): ret = {'Histo1D':{}, 'Histo2D':{}, 'Profile1D':{}, 'Scatter1D':{}, 'Scatter2D':{}, 'Counter':{}} for hname, v in datadict.items(): _hname=mkSafeHname(hname) try: ret[datadict[hname].type()][_hname] = [num for num, binid in enumerate(allbinids) if binid.startswith("{}#".format(_hname))] except Exception as e: print("oops: ", e) return ret def createIndexDS(f, d_idx): for dtype, objects in d_idx.items(): for _hname, binIdx in objects.items(): f.create_dataset("{}/{}".format(dtype, _hname), data=binIdx , chunks=True) def fillDatasets(f, binIdx, variations, ddict, hname, depth=0): if len(binIdx) ==0: print("Warning, no matching binid for {} --- is this one of the raw ratios maybe???".format(hname)) return if ddict[hname].type()=='Histo1D': nFields=7 fdbn = dbn1ToArray elif ddict[hname].type()=='Histo2D': nFields=12 fdbn = H2dbn2ToArray elif ddict[hname].type()=='Profile1D': fdbn = dbn2ToArray nFields=9 elif ddict[hname].type()=='Scatter2D': fdbn = point2DToArray nFields=6 elif ddict[hname].type()=='Scatter1D': fdbn = point1DToArray nFields=3 elif ddict[hname].type()=='Counter': nFields=3 else: raise Exception("type {} Not implemented".format(ddict[hname].type())) # Empty array to be filled and written to datasets temp = np.zeros((len(binIdx), len(variations), nFields)) hids = [hname] for v in variations[1:]: hids.append("{}[{}]".format(hname, v)) # Iterate over variations for col, hn in enumerate(hids): # Iterate over bins H=ddict[hn] if H.type() == "Counter": temp[0][col] = np.array([H.sumW(), H.sumW2(), H.numEntries()]) # Things with under/overflow first elif H.type() not in ["Scatter1D", "Scatter2D", "Histo2D"]: temp[0][col] = fdbn(H.totalDbn()) temp[1][col] = fdbn(H.overflow()) temp[2][col] = fdbn(H.underflow()) for i in range(len(binIdx)-3): temp[3+i][col] = fdbn(H.bin(i)) elif H.type() =="Histo2D": temp[0][col] = fdbn(H.totalDbn()) temp[1][col] = 0.0 # Future proofing temp[2][col] = 0.0 # for i in range(len(binIdx)-3): temp[3+i][col] = fdbn(H.bin(i)) else: for i in range(len(binIdx)): temp[i][col] = fdbn(H.point(i)) if ddict[hname].type()=='Histo1D': f["sumw"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,0] f["sumw2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,1] f["sumwx"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,2] f["sumwx2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,3] f["numEntries"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,4] f["xmin"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,5] f["xmax"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,6] # elif ddict[hname].type()=='Histo2D': # f["sumw"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,0] # f["sumw2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,1] # f["sumwx"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,2] # f["sumwx2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,3] # f["sumwy"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,4] # f["sumwy2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,5] # f["sumwxy"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,6] # f["numEntries"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,7] # f["xmin"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,8] # f["xmax"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,9] # f["ymin"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,10] # f["ymax"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,11] # elif ddict[hname].type()=='Profile1D': # f["sumw"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,0] # f["sumw2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,1] # f["sumwx"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,2] # f["sumwx2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,3] # f["sumwy"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,4] # f["sumwy2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,5] # f["numEntries"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,6] # f["xmin"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,7] # f["xmax"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,8] # elif ddict[hname].type()=='Scatter1D': # f["xval"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,0] # f["xerr-"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,1] # f["xerr+"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,2] # elif ddict[hname].type()=='Scatter2D': # f["xval"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,0] # f["xerr-"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,1] # f["xerr+"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,2] # f["yval"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,3] # f["yerr-"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,4] # f["yerr+"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,5] # elif ddict[hname].type()=='Counter': # f["sumw"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,0] # f["sumw2"][ binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,1] # f["numEntries"][binIdx[0]:binIdx[-1]+1,:,depth] = temp[:,:,2] # else: # raise Exception("yikes") if __name__=="__main__": import sys import optparse, os, sys op = optparse.OptionParser(usage=__doc__) op.add_option("-v", "--debug", dest="DEBUG", action="store_true", default=False, help="Turn on some debug messages") op.add_option("-o", dest="OUTPUT", default="analysisobjects.h5", help="Output HDF5 file (default: %default)") opts, args = op.parse_args() YODAFILES = args from mpi4py import MPI comm = MPI.COMM_WORLD size = comm.Get_size() rank = comm.Get_rank() binids, VVV, aix, aix_flat, central = None, None, None, None, None if rank==0: # TODO if len(args)==1 and os.path.isdir(args[0]) --- hierarchical reading with pnames finding etc # Let's assume they are all consistent TODO add robustness DATA0 = yoda.readYODA(args[0]) L = sorted(list(DATA0.keys())) names = [x for x in L ]# if not "/RAW" in x] central = [x for x in names if not x.endswith("]")] variations = [x for x in names if x.endswith("]")] # TODO In principle one probably should check that all variations are always the # same, we assume this is the case here var = [] for c in central: var.append([x for x in variations if x.startswith(c+"[")]) ## Thats the weight and weight variation order we store the data in VVV = ["CentralWeight"] import re p=re.compile("\[(.*?)\]") for x in var[0]: try: VVV.append(p.findall(x)[0]) except Exception as e: print(x, e) binids = mkBinids(DATA0) # Hierarchical, i.e. top layer is the AnalysisObject type aix = mkIndexDict(DATA0, binids) # Object name as keys and lists of indices as values aix_flat = {} for k, v in aix.items(): aix_flat.update(v) binids = comm.bcast(binids, root=0) VVV = comm.bcast(VVV, root=0) aix = comm.bcast(aix, root=0) aix_flat = comm.bcast(aix_flat, root=0) central = comm.bcast(central, root=0) # NOTE dataset operations are collective # This require h5py to use and H5 that is build with MPI try: f = h5py.File(opts.OUTPUT, "w", driver='mpio', comm=MPI.COMM_WORLD) except: f = h5py.File(opts.OUTPUT, "w") createDatasets(f, binids, VVV, depth=len(YODAFILES)) createIndexDS(f, aix) rankwork = chunkIt([i for i in range(len(YODAFILES))], size) if rank==0 else None rankwork = comm.scatter(rankwork, root=0) # This part is MPI trivial for num, findex in enumerate(rankwork): DATA = yoda.readYODA(YODAFILES[findex]) for hname in central: _hname=mkSafeHname(hname) fillDatasets(f, aix_flat[_hname], VVV, DATA, hname, depth=findex) if rank==0: print("[{}] --- {}/{} complete".format(rank, num, len(rankwork))) sys.stdout.flush() f.close()
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import zipfile import os import glob import sys # Actual directory that we could find somewhere class Folder: def __init__(self, path): self.path = path print("Current working folder is: " + self.path) self.checkForZippedFile() self.checkForDirectories() def checkForZippedFile(self): self.filesToUnzip = list() self.filesToUnzip = glob.glob(os.path.join(self.path,'*.zip'), recursive=True) # If we find a .zip file in the current directory for fileToUnzip in self.filesToUnzip: print("new ZipFile found at: " + fileToUnzip) zip_ref = zipfile.ZipFile(fileToUnzip, 'r') # We prepare to unzip zipFilePath = fileToUnzip.split('.zip')[0] # Reformating the path to remove the .zip at the end print("Current zip is at: " + zipFilePath) zip_ref.extractall(zipFilePath) # Extracting .zip content zip_ref.close() # Closing extraction flow os.remove(zipFilePath + '.zip') # Removing the zip files Folder(zipFilePath) # Calling Folder again def checkForDirectories(self): with os.scandir(self.path) as listOfDirectories: for entry in listOfDirectories: # We check if the actual file is a directory and if it isn't the .git one if not entry.is_file() and entry.name != '.git': entry = Folder(os.path.join(self.path, entry.name)) # Reading the first arg written in the console (program name not included) fileTest = Folder(sys.argv[1])
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from functools import partial from airflow.operators.python_operator import ShortCircuitOperator def make_control_flow(is_dummy_operator_short_circuit, dag): control_flow = ShortCircuitOperator( task_id="dummy-control-flow", dag=dag, provide_context=True, python_callable=partial(eval_control_flow, is_dummy_operator_short_circuit), ) return control_flow def eval_control_flow(is_dummy_operator_short_circuit, **kwargs): True if not is_dummy_operator_short_circuit: return True if kwargs["task_instance"].next_try_number > 2: return True return False
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# Imports import pandas as pd import pickle from keras.models import load_model from preprocess import preprocess from preprocess import prep_text #Logging import logging logging.getLogger().setLevel(logging.INFO) logging.info('Loading comments to classify...') # Enter comment to be classified below comment_to_classify = '' def return_label(predicted_probs): """ Function that takes in a list of 7 class probabilities and returns the labels with probabilities over a certain threshold. """ threshold = 0.4 labels = [] classes = ['clean', 'toxic', 'severe toxic', 'obscene', 'threat', 'insult', 'identity hate'] i = 0 while i < len(classes): if predicted_probs[i] > threshold: labels.append(classes[i]) i += 1 return (labels) def predict_label(comment_str): """ Function that takes in a comment in string form and returns the predicted class labels: not toxic, toxic, severe toxic, obscene, threat, insults, identity hate. May output multiple labels. """ data = pd.DataFrame(data=[comment_str], columns=['comment_text']) logging.info('Comments loaded.') # Preprocess text X_to_predict = preprocess(data) # Identify data to make predictions from X_to_predict = X_to_predict['model_text'] # Format data properly X_to_predict = prep_text(X_to_predict) logging.info('Loading model...') # Load CNN from disk cnn = load_model('model/CNN/binarycrossentropy_adam/model-04-0.9781.hdf5') logging.info('Model loaded.') logging.info('Making prediction(s)...') # Make predictions preds = cnn.predict(X_to_predict) for each_comment, prob in zip(data['comment_text'], preds): print('COMMENT:') print(each_comment) print() print('PREDICTION:') print(return_label(prob)) print() logging.info('Finished.') predict_label(comment_to_classify)
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class Solution(object): def getHint(self, secret, guess): """ :type secret: str :type guess: str :rtype: str """ dic = {} countA = 0 setA = set() for i in range(len(secret)): if secret[i] == guess[i]: countA += 1 setA.add(i) elif secret[i] not in dic: dic[secret[i]] = 1 else: dic[secret[i]] += 1 countB = 0 for i in range(len(guess)): if i not in setA: if guess[i] in dic: countB += 1 dic[guess[i]] -= 1 if dic[guess[i]] == 0: del dic[guess[i]] return str(countA)+"A"+str(countB)+"B"
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from .efficientdet import EfficientDet def get_efficientdet(num_layers, cfg): model = EfficientDet(intermediate_channels=cfg.MODEL.INTERMEDIATE_CHANNEL) return model
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import json import logging import boto3 from box import Box from crhelper import CfnResource from schema import Optional import codesmith.common.naming as naming from codesmith.common.cfn import resource_properties from codesmith.common.schema import encoded_bool, non_empty_string, tolerant_schema from codesmith.common.ssm import put_string_parameter, silent_delete_parameter_from_event helper = CfnResource() logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) properties_schema = tolerant_schema({ 'UserPoolId': non_empty_string, 'UserPoolClientId': non_empty_string, Optional('All', default=False): encoded_bool, Optional('Domains', default=[]): [str], Optional('Emails', default=[]): [str] }) ssm = boto3.client('ssm') def validate_properties(props): return Box(properties_schema.validate(props), camel_killer_box=True) @helper.create @helper.update def create(event, _): p = validate_properties(resource_properties(event)) parameter_name = naming.cog_cond_pre_auth_parameter_name(p.user_pool_id, p.user_pool_client_id) parameter_value = json.dumps({'All': p.all, 'Domains': p.domains, 'Emails': p.emails}) put_string_parameter(ssm, parameter_name, value=parameter_value, description='Forge Cognito Pre Auth Settings Parameter') return parameter_name @helper.delete def delete(event, _): return silent_delete_parameter_from_event(ssm, event) def handler(event, context): logger.info('event: %s', event) helper(event, context)
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n = int(input('Digite um número: ')) print('Seu número é {}. O antecessor é {} e seu sucessor é {}'.format(n, n - 1, n + 1))
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# Given two binary trees, check if the first tree is subtree of the second one. # A subtree of a tree T is a tree S consisting of a node in T and all of its descendants in T. # The subtree corresponding to the root node is the entire tree; the subtree corresponding to any other node is called a proper subtree. class Node: # Constructor to create a new node def __init__(self, data): self.data = data self.left = None self.right = None def are_identical(root1, root2): if root1 is None and root2 is None: return True if root1 is None or root2 is None: return False return (root1.data == root2.data and are_identical(root1.left, root2.left) and are_identical(root1.right, root2.right)) def is_subtree(t, s): if t == None or s == None: return True if(are_identical(t, s)): return True return (is_subtree(t.left, s) or is_subtree(t.right, s)) # Driver program to test above function """ TREE 1 Construct the following tree 26 / \ 10 3 / \ \ 4 6 3 \ 30 """ T = Node(26) T.right = Node(3) T.right.right = Node(3) T.left = Node(10) T.left.left = Node(4) T.left.left.right = Node(30) T.left.right = Node(6) """ TREE 2 Construct the following tree 10 / \ 4 6 \ 30 """ S = Node(10) S.right = Node(6) S.left = Node(4) S.left.right = Node(30) if is_subtree(T, S): print "Tree 2 is subtree of Tree 1" else : print "Tree 2 is not a subtree of Tree 1"
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from typing import List, Optional from papi_sdk.models.search.base_affiliate_response import ( BaseAffiliateSearchData, BaseAffiliateSearchResponse, BaseHotel, BaseRate, ) from papi_sdk.models.search.base_request import BaseAffiliateRequest class AffiliateHotelPageRequest(BaseAffiliateRequest): id: str class Rate(BaseRate): book_hash: str class Hotel(BaseHotel): rates: List[Rate] class HotelPageAffiliateSearchData(BaseAffiliateSearchData): hotels: List[Hotel] class AffiliateHotelPageResponse(BaseAffiliateSearchResponse): data: Optional[HotelPageAffiliateSearchData]
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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2019-01-02 16:44 # @Author : zhangzhen # @Site : # @File : torch_neural_networks.py # @Software: PyCharm import torch import torch.nn as nn import torch.nn.functional as F class Net(nn.Module): def __init__(self): super(Net, self).__init__() # 1 input image channel, 6 output channels, 5 * 5 square convolution # kernel self.conv1 = nn.Conv2d(in_channels=1, out_channels=6, kernel_size=5) self.conv2 = nn.Conv2d(in_channels=6, out_channels=16, kernel_size=5) # an affine operation: y = Wx + b self.fc1 = nn.Linear(16 * 5 * 5, 120) self.fc2 = nn.Linear(120, 84) self.fc3 = nn.Linear(84, 10) def forward(self, *input): # Max pooling over a (2, 2) window x = F.max_pool2d(F.relu(self.conv1(input[0])), (2, 2)) # if the size is a square you can only specify a single number x = F.max_pool2d(F.relu(self.conv2(x)), (2, 2)) x = x.view(-1, self.num_flat_features(x)) x = F.relu(self.fc1(x)) x = F.relu(self.fc2(x)) x = self.fc3(x) return x def num_flat_features(self, x): size = x.size()[1:] num_features = 1 for s in size: num_features *= s return num_features if __name__ == '__main__': net = Net() criterion = nn.MSELoss() print(net) params = list(net.parameters()) print("参数个数:", len(params)) for param in params: print(param.size()) input = torch.randn(1, 1, 32, 32) target = torch.randn(10) out = net(input) loss = criterion(out, target) print(100 * "=") print(out, target) print("Loss:", loss) print(loss.grad_fn) # MSELoss print(loss.grad_fn.next_functions[0][0]) # Linear print(loss.grad_fn.next_functions[0][0].next_functions[0][0]) # ReLU net.zero_grad() print('conv1.bias.grad before backward') print(net.conv1.bias.grad) loss.backward() print('conv1.bias.grad after backward') print(net.conv1.bias.grad)
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from bottle import route, run, template gitdict = {'po2go':{'https://github.com/cadamswaite/po2go.git:master':'https://github.com/cadamswaite/po2go.git:gh-pages'}} # Handle http requests to the root address @route('/') def index(): return 'Go away.' @route('/build/<name>') def greet(name): if name in gitdict: return 'Building ' + name else: return name + 'not found in gitdict' run(host='0.0.0.0', port=80)
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""" Leonard always DRIVES Sheldon (this module is the __main__ driver for Sheldon) """ import argparse import sys import os try: from cooper import Sheldon except: from .cooper import Sheldon # Extensions for python source files EXTENSIONS = [".py", ".mpy"] def parse_commandline(): parser = argparse.ArgumentParser( description="Find divisions in Python code") parser.add_argument("-u", "--human_readable", help="Display friendlier output", action="store_true") parser.add_argument("-r", "--recursive", help="Scan subdirectories recursively", action="store_true") parser.add_argument("path", type=str, help="Path to the target file or directory") return parser.parse_args() def process_files(files, divs_found, readable, path=""): for filename in files: fname = os.path.join(path, filename) with open(fname) as f: pysource = f.read() s = Sheldon(pysource) try: s.analyze() except SyntaxError: exc_type, exc_obj, exc_tb = sys.exc_info() print(f"{fname} {exc_tb.tb_lineno} SyntaxError") continue divs_found += len(s.divisions) s.printdivs(fname, s.divisions, readable) return divs_found def main(): args = parse_commandline() if args.human_readable: def readableprint(*args, **kwargs): print(*args, **kwargs) else: readableprint = lambda *a, **k: None # do - nothing function files_checked = 0 divs_found = 0 # Directory path if os.path.isdir(args.path): for path, dirs, files in os.walk(args.path): files = [f for f in os.listdir(path) if f.endswith(tuple(EXTENSIONS))] files_checked += len(files) divs_found = process_files(files, divs_found, args.human_readable, path=path) if not args.recursive: exit(0) readableprint(f"{files_checked} files checked") readableprint(f"{divs_found} divisions found") # File path elif os.path.isfile(args.path): files =[f for f in [args.path] if args.path.endswith(tuple(EXTENSIONS))] divs_found = process_files(files, divs_found, args.human_readable) readableprint(f"{divs_found} divisions found") # Error else: sys.exit(f"{args.path} doesn't exist!") if __name__ == "__main__": main()
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# -*- coding: utf-8 -*- def test_001(settings, finder): result = finder.change_extension("foo.scss", 'css') assert result == "foo.css" def test_002(settings, finder): result = finder.change_extension("foo.backup.scss", 'css') assert result == "foo.backup.css" def test_003(settings, finder): result = finder.change_extension("bar/foo.scss", 'css') assert result == "bar/foo.css" def test_004(settings, finder): result = finder.change_extension("/home/bar/foo.scss", 'css') assert result == "/home/bar/foo.css" def test_005(settings, finder): result = finder.change_extension("/home/bar/foo.backup.scss", 'css') assert result == "/home/bar/foo.backup.css"
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"""Basic tests for the CherryPy core: request handling.""" from cherrypy.test import test test.prefer_parent_path() import cherrypy from cherrypy import _cptools, tools from cherrypy.lib import http, static import types import os localDir = os.path.dirname(__file__) log_file = os.path.join(localDir, "test.log") log_access_file = os.path.join(localDir, "access.log") favicon_path = os.path.join(os.getcwd(), localDir, "../favicon.ico") defined_http_methods = ("OPTIONS", "GET", "HEAD", "POST", "PUT", "DELETE", "TRACE", "CONNECT", "PROPFIND") def setup_server(): class Root: def index(self): return "hello" index.exposed = True favicon_ico = tools.staticfile.handler(filename=favicon_path) def andnow(self): return "the larch" andnow.exposed = True def global_(self): pass global_.exposed = True def delglobal(self): del self.__class__.__dict__['global_'] delglobal.exposed = True def defct(self, newct): newct = "text/%s" % newct cherrypy.config.update({'tools.response_headers.on': True, 'tools.response_headers.headers': [('Content-Type', newct)]}) defct.exposed = True def upload(self, file): return "Size: %s" % len(file.file.read()) upload.exposed = True root = Root() class TestType(type): """Metaclass which automatically exposes all functions in each subclass, and adds an instance of the subclass as an attribute of root. """ def __init__(cls, name, bases, dct): type.__init__(name, bases, dct) for value in dct.itervalues(): if isinstance(value, types.FunctionType): value.exposed = True setattr(root, name.lower(), cls()) class Test(object): __metaclass__ = TestType class URL(Test): _cp_config = {'tools.trailing_slash.on': False} def index(self, path_info, relative=None): return cherrypy.url(path_info, relative=bool(relative)) def leaf(self, path_info, relative=None): return cherrypy.url(path_info, relative=bool(relative)) class Params(Test): def index(self, thing): return repr(thing) def ismap(self, x, y): return "Coordinates: %s, %s" % (x, y) def default(self, *args, **kwargs): return "args: %s kwargs: %s" % (args, kwargs) class Status(Test): def index(self): return "normal" def blank(self): cherrypy.response.status = "" # According to RFC 2616, new status codes are OK as long as they # are between 100 and 599. # Here is an illegal code... def illegal(self): cherrypy.response.status = 781 return "oops" # ...and here is an unknown but legal code. def unknown(self): cherrypy.response.status = "431 My custom error" return "funky" # Non-numeric code def bad(self): cherrypy.response.status = "error" return "bad news" class Redirect(Test): class Error: _cp_config = {"tools.err_redirect.on": True, "tools.err_redirect.url": "/errpage", "tools.err_redirect.internal": False, } def index(self): raise NameError("redirect_test") index.exposed = True error = Error() def index(self): return "child" def by_code(self, code): raise cherrypy.HTTPRedirect("somewhere else", code) by_code._cp_config = {'tools.trailing_slash.extra': True} def nomodify(self): raise cherrypy.HTTPRedirect("", 304) def proxy(self): raise cherrypy.HTTPRedirect("proxy", 305) def stringify(self): return str(cherrypy.HTTPRedirect("/")) def fragment(self, frag): raise cherrypy.HTTPRedirect("/some/url#%s" % frag) def login_redir(): if not getattr(cherrypy.request, "login", None): raise cherrypy.InternalRedirect("/internalredirect/login") tools.login_redir = _cptools.Tool('before_handler', login_redir) def redir_custom(): raise cherrypy.InternalRedirect("/internalredirect/custom_err") class InternalRedirect(Test): def index(self): raise cherrypy.InternalRedirect("/") def relative(self, a, b): raise cherrypy.InternalRedirect("cousin?t=6") def cousin(self, t): assert cherrypy.request.prev.closed return cherrypy.request.prev.query_string def petshop(self, user_id): if user_id == "parrot": # Trade it for a slug when redirecting raise cherrypy.InternalRedirect('/image/getImagesByUser?user_id=slug') elif user_id == "terrier": # Trade it for a fish when redirecting raise cherrypy.InternalRedirect('/image/getImagesByUser?user_id=fish') else: # This should pass the user_id through to getImagesByUser raise cherrypy.InternalRedirect('/image/getImagesByUser?user_id=%s' % user_id) # We support Python 2.3, but the @-deco syntax would look like this: # @tools.login_redir() def secure(self): return "Welcome!" secure = tools.login_redir()(secure) # Since calling the tool returns the same function you pass in, # you could skip binding the return value, and just write: # tools.login_redir()(secure) def login(self): return "Please log in" login._cp_config = {'hooks.before_error_response': redir_custom} def custom_err(self): return "Something went horribly wrong." def early_ir(self, arg): return "whatever" early_ir._cp_config = {'hooks.before_request_body': redir_custom} class Image(Test): def getImagesByUser(self, user_id): return "0 images for %s" % user_id class Flatten(Test): def as_string(self): return "content" def as_list(self): return ["con", "tent"] def as_yield(self): yield "content" def as_dblyield(self): yield self.as_yield() as_dblyield._cp_config = {'tools.flatten.on': True} def as_refyield(self): for chunk in self.as_yield(): yield chunk class Error(Test): _cp_config = {'tools.log_tracebacks.on': True, } def custom(self): raise cherrypy.HTTPError(404, "No, <b>really</b>, not found!") custom._cp_config = {'error_page.404': os.path.join(localDir, "static/index.html")} def noexist(self): raise cherrypy.HTTPError(404, "No, <b>really</b>, not found!") noexist._cp_config = {'error_page.404': "nonexistent.html"} def page_method(self): raise ValueError() def page_yield(self): yield "howdy" raise ValueError() def page_streamed(self): yield "word up" raise ValueError() yield "very oops" page_streamed._cp_config = {"response.stream": True} def cause_err_in_finalize(self): # Since status must start with an int, this should error. cherrypy.response.status = "ZOO OK" cause_err_in_finalize._cp_config = {'request.show_tracebacks': False} def rethrow(self): """Test that an error raised here will be thrown out to the server.""" raise ValueError() rethrow._cp_config = {'request.throw_errors': True} class Ranges(Test): def get_ranges(self, bytes): return repr(http.get_ranges('bytes=%s' % bytes, 8)) def slice_file(self): path = os.path.join(os.getcwd(), os.path.dirname(__file__)) return static.serve_file(os.path.join(path, "static/index.html")) class Expect(Test): def expectation_failed(self): expect = cherrypy.request.headers.elements("Expect") if expect and expect[0].value != '100-continue': raise cherrypy.HTTPError(400) raise cherrypy.HTTPError(417, 'Expectation Failed') class Headers(Test): def default(self, headername): """Spit back out the value for the requested header.""" return cherrypy.request.headers[headername] def doubledheaders(self): # From http://www.cherrypy.org/ticket/165: # "header field names should not be case sensitive sayes the rfc. # if i set a headerfield in complete lowercase i end up with two # header fields, one in lowercase, the other in mixed-case." # Set the most common headers hMap = cherrypy.response.headers hMap['content-type'] = "text/html" hMap['content-length'] = 18 hMap['server'] = 'CherryPy headertest' hMap['location'] = ('%s://%s:%s/headers/' % (cherrypy.request.local.ip, cherrypy.request.local.port, cherrypy.request.scheme)) # Set a rare header for fun hMap['Expires'] = 'Thu, 01 Dec 2194 16:00:00 GMT' return "double header test" def ifmatch(self): val = cherrypy.request.headers['If-Match'] cherrypy.response.headers['ETag'] = val return repr(val) class HeaderElements(Test): def get_elements(self, headername): e = cherrypy.request.headers.elements(headername) return "\n".join([unicode(x) for x in e]) class Method(Test): def index(self): m = cherrypy.request.method if m in defined_http_methods: return m if m == "LINK": raise cherrypy.HTTPError(405) else: raise cherrypy.HTTPError(501) def parameterized(self, data): return data def request_body(self): # This should be a file object (temp file), # which CP will just pipe back out if we tell it to. return cherrypy.request.body def reachable(self): return "success" class Divorce: """HTTP Method handlers shouldn't collide with normal method names. For example, a GET-handler shouldn't collide with a method named 'get'. If you build HTTP method dispatching into CherryPy, rewrite this class to use your new dispatch mechanism and make sure that: "GET /divorce HTTP/1.1" maps to divorce.index() and "GET /divorce/get?ID=13 HTTP/1.1" maps to divorce.get() """ documents = {} def index(self): yield "<h1>Choose your document</h1>\n" yield "<ul>\n" for id, contents in self.documents.iteritems(): yield (" <li><a href='/divorce/get?ID=%s'>%s</a>: %s</li>\n" % (id, id, contents)) yield "</ul>" index.exposed = True def get(self, ID): return ("Divorce document %s: %s" % (ID, self.documents.get(ID, "empty"))) get.exposed = True root.divorce = Divorce() class Cookies(Test): def single(self, name): cookie = cherrypy.request.cookie[name] cherrypy.response.cookie[name] = cookie.value def multiple(self, names): for name in names: cookie = cherrypy.request.cookie[name] cherrypy.response.cookie[name] = cookie.value class ThreadLocal(Test): def index(self): existing = repr(getattr(cherrypy.request, "asdf", None)) cherrypy.request.asdf = "rassfrassin" return existing cherrypy.config.update({ 'log.error_file': log_file, 'environment': 'test_suite', 'server.max_request_body_size': 200, 'server.max_request_header_size': 500, }) appconf = { '/': {'log.access_file': log_access_file}, '/method': {'request.methods_with_bodies': ("POST", "PUT", "PROPFIND")}, } cherrypy.tree.mount(root, config=appconf) # Client-side code # from cherrypy.test import helper class CoreRequestHandlingTest(helper.CPWebCase): def testParams(self): self.getPage("/params/?thing=a") self.assertBody("'a'") self.getPage("/params/?thing=a&thing=b&thing=c") self.assertBody("['a', 'b', 'c']") # Test friendly error message when given params are not accepted. ignore = helper.webtest.ignored_exceptions ignore.append(TypeError) try: self.getPage("/params/?notathing=meeting") self.assertInBody("index() got an unexpected keyword argument 'notathing'") finally: ignore.pop() # Test "% HEX HEX"-encoded URL, param keys, and values self.getPage("/params/%d4%20%e3/cheese?Gruy%E8re=Bulgn%e9ville") self.assertBody(r"args: ('\xd4 \xe3', 'cheese') " r"kwargs: {'Gruy\xe8re': 'Bulgn\xe9ville'}") # Make sure that encoded = and & get parsed correctly self.getPage("/params/code?url=http%3A//cherrypy.org/index%3Fa%3D1%26b%3D2") self.assertBody(r"args: ('code',) " r"kwargs: {'url': 'http://cherrypy.org/index?a=1&b=2'}") # Test coordinates sent by <img ismap> self.getPage("/params/ismap?223,114") self.assertBody("Coordinates: 223, 114") def testStatus(self): self.getPage("/status/") self.assertBody('normal') self.assertStatus(200) self.getPage("/status/blank") self.assertBody('') self.assertStatus(200) self.getPage("/status/illegal") self.assertStatus(500) msg = "Illegal response status from server (781 is out of range)." self.assertErrorPage(500, msg) self.getPage("/status/unknown") self.assertBody('funky') self.assertStatus(431) self.getPage("/status/bad") self.assertStatus(500) msg = "Illegal response status from server ('error' is non-numeric)." self.assertErrorPage(500, msg) def testLogging(self): f = open(log_access_file, "wb") f.write("") f.close() f = open(log_file, "wb") f.write("") f.close() self.getPage("/flatten/as_string") self.assertBody('content') self.assertStatus(200) self.getPage("/flatten/as_yield") self.assertBody('content') self.assertStatus(200) data = open(log_access_file, "rb").readlines() host = self.HOST if not host: # The empty string signifies INADDR_ANY, # which should respond on localhost. host = "127.0.0.1" intro = '%s - - [' % host if not data[0].startswith(intro): self.fail("%r doesn't start with %r" % (data[0], intro)) haslength = False for k, v in self.headers: if k.lower() == 'content-length': haslength = True line = data[-2].strip() if haslength: if not line.endswith('] "GET %s/flatten/as_string HTTP/1.1" 200 7 "" ""' % self.prefix()): self.fail(line) else: if not line.endswith('] "GET %s/flatten/as_string HTTP/1.1" 200 - "" ""' % self.prefix()): self.fail(line) if not data[-1].startswith(intro): self.fail("%r doesn't start with %r" % (data[-1], intro)) haslength = False for k, v in self.headers: if k.lower() == 'content-length': haslength = True line = data[-1].strip() if haslength: self.assert_(line.endswith('] "GET %s/flatten/as_yield HTTP/1.1" 200 7 "" ""' % self.prefix())) else: self.assert_(line.endswith('] "GET %s/flatten/as_yield HTTP/1.1" 200 - "" ""' % self.prefix())) ignore = helper.webtest.ignored_exceptions ignore.append(ValueError) try: # Test that tracebacks get written to the error log. self.getPage("/error/page_method") self.assertInBody("raise ValueError()") data = open(log_file, "rb").readlines() self.assertEqual(data[0].strip().endswith('HTTP Traceback (most recent call last):'), True) self.assertEqual(data[-3].strip().endswith('raise ValueError()'), True) finally: ignore.pop() def testSlashes(self): # Test that requests for index methods without a trailing slash # get redirected to the same URI path with a trailing slash. # Make sure GET params are preserved. self.getPage("/redirect?id=3") self.assertStatus(('302 Found', '303 See Other')) self.assertInBody("<a href='%s/redirect/?id=3'>" "%s/redirect/?id=3</a>" % (self.base(), self.base())) if self.prefix(): # Corner case: the "trailing slash" redirect could be tricky if # we're using a virtual root and the URI is "/vroot" (no slash). self.getPage("") self.assertStatus(('302 Found', '303 See Other')) self.assertInBody("<a href='%s/'>%s/</a>" % (self.base(), self.base())) # Test that requests for NON-index methods WITH a trailing slash # get redirected to the same URI path WITHOUT a trailing slash. # Make sure GET params are preserved. self.getPage("/redirect/by_code/?code=307") self.assertStatus(('302 Found', '303 See Other')) self.assertInBody("<a href='%s/redirect/by_code?code=307'>" "%s/redirect/by_code?code=307</a>" % (self.base(), self.base())) # If the trailing_slash tool is off, CP should just continue # as if the slashes were correct. But it needs some help # inside cherrypy.url to form correct output. self.getPage('/url?path_info=page1') self.assertBody('%s/url/page1' % self.base()) self.getPage('/url/leaf/?path_info=page1') self.assertBody('%s/url/page1' % self.base()) def testRedirect(self): self.getPage("/redirect/") self.assertBody('child') self.assertStatus(200) self.getPage("/redirect/by_code?code=300") self.assertMatchesBody(r"<a href='(.*)somewhere else'>\1somewhere else</a>") self.assertStatus(300) self.getPage("/redirect/by_code?code=301") self.assertMatchesBody(r"<a href='(.*)somewhere else'>\1somewhere else</a>") self.assertStatus(301) self.getPage("/redirect/by_code?code=302") self.assertMatchesBody(r"<a href='(.*)somewhere else'>\1somewhere else</a>") self.assertStatus(302) self.getPage("/redirect/by_code?code=303") self.assertMatchesBody(r"<a href='(.*)somewhere else'>\1somewhere else</a>") self.assertStatus(303) self.getPage("/redirect/by_code?code=307") self.assertMatchesBody(r"<a href='(.*)somewhere else'>\1somewhere else</a>") self.assertStatus(307) self.getPage("/redirect/nomodify") self.assertBody('') self.assertStatus(304) self.getPage("/redirect/proxy") self.assertBody('') self.assertStatus(305) # HTTPRedirect on error self.getPage("/redirect/error/") self.assertStatus(('302 Found', '303 See Other')) self.assertInBody('/errpage') # Make sure str(HTTPRedirect()) works. self.getPage("/redirect/stringify", protocol="HTTP/1.0") self.assertStatus(200) self.assertBody("(['%s/'], 302)" % self.base()) if cherrypy.server.protocol_version == "HTTP/1.1": self.getPage("/redirect/stringify", protocol="HTTP/1.1") self.assertStatus(200) self.assertBody("(['%s/'], 303)" % self.base()) # check that #fragments are handled properly # http://skrb.org/ietf/http_errata.html#location-fragments frag = "foo" self.getPage("/redirect/fragment/%s" % frag) self.assertMatchesBody(r"<a href='(.*)\/some\/url\#%s'>\1\/some\/url\#%s</a>" % (frag, frag)) loc = self.assertHeader('Location') assert loc.endswith("#%s" % frag) self.assertStatus(('302 Found', '303 See Other')) def test_InternalRedirect(self): # InternalRedirect self.getPage("/internalredirect/") self.assertBody('hello') self.assertStatus(200) # Test passthrough self.getPage("/internalredirect/petshop?user_id=Sir-not-appearing-in-this-film") self.assertBody('0 images for Sir-not-appearing-in-this-film') self.assertStatus(200) # Test args self.getPage("/internalredirect/petshop?user_id=parrot") self.assertBody('0 images for slug') self.assertStatus(200) # Test POST self.getPage("/internalredirect/petshop", method="POST", body="user_id=terrier") self.assertBody('0 images for fish') self.assertStatus(200) # Test ir before body read self.getPage("/internalredirect/early_ir", method="POST", body="arg=aha!") self.assertBody("Something went horribly wrong.") self.assertStatus(200) self.getPage("/internalredirect/secure") self.assertBody('Please log in') self.assertStatus(200) # Relative path in InternalRedirect. # Also tests request.prev. self.getPage("/internalredirect/relative?a=3&b=5") self.assertBody("a=3&b=5") self.assertStatus(200) # InternalRedirect on error self.getPage("/internalredirect/login/illegal/extra/vpath/atoms") self.assertStatus(200) self.assertBody("Something went horribly wrong.") def testFlatten(self): for url in ["/flatten/as_string", "/flatten/as_list", "/flatten/as_yield", "/flatten/as_dblyield", "/flatten/as_refyield"]: self.getPage(url) self.assertBody('content') def testErrorHandling(self): self.getPage("/error/missing") self.assertStatus(404) self.assertErrorPage(404, "The path '/error/missing' was not found.") ignore = helper.webtest.ignored_exceptions ignore.append(ValueError) try: valerr = '\n raise ValueError()\nValueError' self.getPage("/error/page_method") self.assertErrorPage(500, pattern=valerr) self.getPage("/error/page_yield") self.assertErrorPage(500, pattern=valerr) self.getPage("/error/page_streamed") # Because this error is raised after the response body has # started, the status should not change to an error status. self.assertStatus(200) self.assertBody("word upUnrecoverable error in the server.") # No traceback should be present self.getPage("/error/cause_err_in_finalize") msg = "Illegal response status from server ('ZOO' is non-numeric)." self.assertErrorPage(500, msg, None) finally: ignore.pop() # Test custom error page. self.getPage("/error/custom") self.assertStatus(404) self.assertBody("Hello, world\r\n" + (" " * 499)) # Test error in custom error page (ticket #305). # Note that the message is escaped for HTML (ticket #310). self.getPage("/error/noexist") self.assertStatus(404) msg = ("No, &lt;b&gt;really&lt;/b&gt;, not found!<br />" "In addition, the custom error page failed:\n<br />" "[Errno 2] No such file or directory: 'nonexistent.html'") self.assertInBody(msg) if (hasattr(self, 'harness') and "modpython" in self.harness.__class__.__name__.lower()): pass else: # Test throw_errors (ticket #186). self.getPage("/error/rethrow") self.assertInBody("raise ValueError()") def testRanges(self): self.getPage("/ranges/get_ranges?bytes=3-6") self.assertBody("[(3, 7)]") # Test multiple ranges and a suffix-byte-range-spec, for good measure. self.getPage("/ranges/get_ranges?bytes=2-4,-1") self.assertBody("[(2, 5), (7, 8)]") # Get a partial file. if cherrypy.server.protocol_version == "HTTP/1.1": self.getPage("/ranges/slice_file", [('Range', 'bytes=2-5')]) self.assertStatus(206) self.assertHeader("Content-Type", "text/html") self.assertHeader("Content-Range", "bytes 2-5/14") self.assertBody("llo,") # What happens with overlapping ranges (and out of order, too)? self.getPage("/ranges/slice_file", [('Range', 'bytes=4-6,2-5')]) self.assertStatus(206) ct = self.assertHeader("Content-Type") expected_type = "multipart/byteranges; boundary=" self.assert_(ct.startswith(expected_type)) boundary = ct[len(expected_type):] expected_body = ("\r\n--%s\r\n" "Content-type: text/html\r\n" "Content-range: bytes 4-6/14\r\n" "\r\n" "o, \r\n" "--%s\r\n" "Content-type: text/html\r\n" "Content-range: bytes 2-5/14\r\n" "\r\n" "llo,\r\n" "--%s--\r\n" % (boundary, boundary, boundary)) self.assertBody(expected_body) self.assertHeader("Content-Length") # Test "416 Requested Range Not Satisfiable" self.getPage("/ranges/slice_file", [('Range', 'bytes=2300-2900')]) self.assertStatus(416) # "When this status code is returned for a byte-range request, # the response SHOULD include a Content-Range entity-header # field specifying the current length of the selected resource" self.assertHeader("Content-Range", "bytes */14") elif cherrypy.server.protocol_version == "HTTP/1.0": # Test Range behavior with HTTP/1.0 request self.getPage("/ranges/slice_file", [('Range', 'bytes=2-5')]) self.assertStatus(200) self.assertBody("Hello, world\r\n") def testExpect(self): e = ('Expect', '100-continue') self.getPage("/headerelements/get_elements?headername=Expect", [e]) self.assertBody('100-continue') self.getPage("/expect/expectation_failed", [('Content-Length', '200'), e]) self.assertStatus(417) def testHeaderElements(self): # Accept-* header elements should be sorted, with most preferred first. h = [('Accept', 'audio/*; q=0.2, audio/basic')] self.getPage("/headerelements/get_elements?headername=Accept", h) self.assertStatus(200) self.assertBody("audio/basic\n" "audio/*;q=0.2") h = [('Accept', 'text/plain; q=0.5, text/html, text/x-dvi; q=0.8, text/x-c')] self.getPage("/headerelements/get_elements?headername=Accept", h) self.assertStatus(200) self.assertBody("text/x-c\n" "text/html\n" "text/x-dvi;q=0.8\n" "text/plain;q=0.5") # Test that more specific media ranges get priority. h = [('Accept', 'text/*, text/html, text/html;level=1, */*')] self.getPage("/headerelements/get_elements?headername=Accept", h) self.assertStatus(200) self.assertBody("text/html;level=1\n" "text/html\n" "text/*\n" "*/*") # Test Accept-Charset h = [('Accept-Charset', 'iso-8859-5, unicode-1-1;q=0.8')] self.getPage("/headerelements/get_elements?headername=Accept-Charset", h) self.assertStatus("200 OK") self.assertBody("iso-8859-5\n" "unicode-1-1;q=0.8") # Test Accept-Encoding h = [('Accept-Encoding', 'gzip;q=1.0, identity; q=0.5, *;q=0')] self.getPage("/headerelements/get_elements?headername=Accept-Encoding", h) self.assertStatus("200 OK") self.assertBody("gzip;q=1.0\n" "identity;q=0.5\n" "*;q=0") # Test Accept-Language h = [('Accept-Language', 'da, en-gb;q=0.8, en;q=0.7')] self.getPage("/headerelements/get_elements?headername=Accept-Language", h) self.assertStatus("200 OK") self.assertBody("da\n" "en-gb;q=0.8\n" "en;q=0.7") def testHeaders(self): # Tests that each header only appears once, regardless of case. self.getPage("/headers/doubledheaders") self.assertBody("double header test") hnames = [name.title() for name, val in self.headers] for key in ['Content-Length', 'Content-Type', 'Date', 'Expires', 'Location', 'Server']: self.assertEqual(hnames.count(key), 1) if cherrypy.server.protocol_version == "HTTP/1.1": # Test RFC-2047-encoded request and response header values c = "=E2=84=ABngstr=C3=B6m" self.getPage("/headers/ifmatch", [('If-Match', '=?utf-8?q?%s?=' % c)]) self.assertBody("u'\\u212bngstr\\xf6m'") self.assertHeader("ETag", '=?utf-8?b?4oSrbmdzdHLDtm0=?=') # Test a *LONG* RFC-2047-encoded request and response header value self.getPage("/headers/ifmatch", [('If-Match', '=?utf-8?q?%s?=' % (c * 10))]) self.assertBody("u'%s'" % ('\\u212bngstr\\xf6m' * 10)) self.assertHeader("ETag", '=?utf-8?b?4oSrbmdzdHLDtm3ihKtuZ3N0csO2beKEq25nc3Ryw7Zt4oSrbmdzdHLDtm0=?=' '=?utf-8?b?4oSrbmdzdHLDtm3ihKtuZ3N0csO2beKEq25nc3Ryw7Zt4oSrbmdzdHLDtm0=?=' '=?utf-8?b?4oSrbmdzdHLDtm3ihKtuZ3N0csO2bQ==?=') # Test that two request headers are collapsed into one. # See http://www.cherrypy.org/ticket/542. self.getPage("/headers/Accept-Charset", headers=[("Accept-Charset", "iso-8859-5"), ("Accept-Charset", "unicode-1-1;q=0.8")]) self.assertBody("iso-8859-5, unicode-1-1;q=0.8") # If we don't pass a Content-Type header, it should not be present # in cherrypy.request.headers self.getPage("/headers/Content-Type", headers=[]) self.assertStatus(500) # If Content-Type is present in the request, it should be present in # cherrypy.request.headers self.getPage("/headers/Content-Type", headers=[("Content-type", "application/json")]) self.assertBody("application/json") def testHTTPMethods(self): helper.webtest.methods_with_bodies = ("POST", "PUT", "PROPFIND") # Test that all defined HTTP methods work. for m in defined_http_methods: self.getPage("/method/", method=m) # HEAD requests should not return any body. if m == "HEAD": self.assertBody("") elif m == "TRACE": # Some HTTP servers (like modpy) have their own TRACE support self.assertEqual(self.body[:5], "TRACE") else: self.assertBody(m) # Request a PUT method with a form-urlencoded body self.getPage("/method/parameterized", method="PUT", body="data=on+top+of+other+things") self.assertBody("on top of other things") # Request a PUT method with a file body b = "one thing on top of another" h = [("Content-Type", "text/plain"), ("Content-Length", str(len(b)))] self.getPage("/method/request_body", headers=h, method="PUT", body=b) self.assertStatus(200) self.assertBody(b) # Request a PUT method with no body whatsoever (not an empty one). # See http://www.cherrypy.org/ticket/650. # Provide a C-T or webtest will provide one (and a C-L) for us. h = [("Content-Type", "text/plain")] self.getPage("/method/reachable", headers=h, method="PUT") self.assertBody("success") # Request a custom method with a request body b = ('<?xml version="1.0" encoding="utf-8" ?>\n\n' '<propfind xmlns="DAV:"><prop><getlastmodified/>' '</prop></propfind>') h = [('Content-Type', 'text/xml'), ('Content-Length', str(len(b)))] self.getPage("/method/request_body", headers=h, method="PROPFIND", body=b) self.assertStatus(200) self.assertBody(b) # Request a disallowed method self.getPage("/method/", method="LINK") self.assertStatus(405) # Request an unknown method self.getPage("/method/", method="SEARCH") self.assertStatus(501) # For method dispatchers: make sure that an HTTP method doesn't # collide with a virtual path atom. If you build HTTP-method # dispatching into the core, rewrite these handlers to use # your dispatch idioms. self.getPage("/divorce/get?ID=13") self.assertBody('Divorce document 13: empty') self.assertStatus(200) self.getPage("/divorce/", method="GET") self.assertBody('<h1>Choose your document</h1>\n<ul>\n</ul>') self.assertStatus(200) def testFavicon(self): # favicon.ico is served by staticfile. icofilename = os.path.join(localDir, "../favicon.ico") icofile = open(icofilename, "rb") data = icofile.read() icofile.close() self.getPage("/favicon.ico") self.assertBody(data) def testCookies(self): import sys if sys.version_info >= (2, 5): self.getPage("/cookies/single?name=First", [('Cookie', 'First=Dinsdale;')]) self.assertHeader('Set-Cookie', 'First=Dinsdale') self.getPage("/cookies/multiple?names=First&names=Last", [('Cookie', 'First=Dinsdale; Last=Piranha;'), ]) self.assertHeader('Set-Cookie', 'First=Dinsdale') self.assertHeader('Set-Cookie', 'Last=Piranha') else: self.getPage("/cookies/single?name=First", [('Cookie', 'First=Dinsdale;')]) self.assertHeader('Set-Cookie', 'First=Dinsdale;') self.getPage("/cookies/multiple?names=First&names=Last", [('Cookie', 'First=Dinsdale; Last=Piranha;'), ]) self.assertHeader('Set-Cookie', 'First=Dinsdale;') self.assertHeader('Set-Cookie', 'Last=Piranha;') def testMaxRequestSize(self): self.getPage("/", headers=[('From', "x" * 500)]) self.assertStatus(413) # Test for http://www.cherrypy.org/ticket/421 # (Incorrect border condition in readline of SizeCheckWrapper). # This hangs in rev 891 and earlier. lines256 = "x" * 248 self.getPage("/", headers=[('Host', '%s:%s' % (self.HOST, self.PORT)), ('From', lines256)]) # Test upload body = """--x Content-Disposition: form-data; name="file"; filename="hello.txt" Content-Type: text/plain %s --x-- """ b = body % ("x" * 96) h = [("Content-type", "multipart/form-data; boundary=x"), ("Content-Length", len(b))] self.getPage('/upload', h, "POST", b) self.assertBody('Size: 96') b = body % ("x" * 200) h = [("Content-type", "multipart/form-data; boundary=x"), ("Content-Length", len(b))] self.getPage('/upload', h, "POST", b) self.assertStatus(413) def testEmptyThreadlocals(self): results = [] for x in xrange(20): self.getPage("/threadlocal/") results.append(self.body) self.assertEqual(results, ["None"] * 20) def testDefaultContentType(self): self.getPage('/') self.assertHeader('Content-Type', 'text/html') self.getPage('/defct/plain') self.getPage('/') self.assertHeader('Content-Type', 'text/plain') self.getPage('/defct/html') def test_cherrypy_url(self): # Input relative to current self.getPage('/url/leaf?path_info=page1') self.assertBody('%s/url/page1' % self.base()) self.getPage('/url/?path_info=page1') self.assertBody('%s/url/page1' % self.base()) # Input is 'absolute'; that is, relative to script_name self.getPage('/url/leaf?path_info=/page1') self.assertBody('%s/page1' % self.base()) self.getPage('/url/?path_info=/page1') self.assertBody('%s/page1' % self.base()) # Single dots self.getPage('/url/leaf?path_info=./page1') self.assertBody('%s/url/page1' % self.base()) self.getPage('/url/leaf?path_info=other/./page1') self.assertBody('%s/url/other/page1' % self.base()) self.getPage('/url/?path_info=/other/./page1') self.assertBody('%s/other/page1' % self.base()) # Double dots self.getPage('/url/leaf?path_info=../page1') self.assertBody('%s/page1' % self.base()) self.getPage('/url/leaf?path_info=other/../page1') self.assertBody('%s/url/page1' % self.base()) self.getPage('/url/leaf?path_info=/other/../page1') self.assertBody('%s/page1' % self.base()) # Output relative to current path or script_name self.getPage('/url/?path_info=page1&relative=True') self.assertBody('page1') self.getPage('/url/leaf?path_info=/page1&relative=True') self.assertBody('../page1') self.getPage('/url/leaf?path_info=../page1&relative=True') self.assertBody('../page1') self.getPage('/url/?path_info=other/../page1&relative=True') self.assertBody('page1') if __name__ == '__main__': setup_server() helper.testmain()
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# Solution 1 def readInputFile(filename): f = open(filename, "r") inputString = f.read() f.close() return inputString input = readInputFile("input.txt").strip() print(input) lowest = input.split("-")[0] highest = input.split("-")[1] current = int(input.split("-")[0]) print(lowest) print(highest) def checkNeverDecreaseRule(n): n = str(n) l = len(n) i = 0 while i < l - 1: # print("comparing " + n[i] + " with " + n[i + 1] + "...") if int(n[i]) > int(n[i + 1]): return False i += 1 return True def checkHasAdjacentSame(n): n = str(n) l = len(n) i = 0 adjCount = 0 while i < l - 1: # print("comparing " + n[i] + " with " + n[i + 1] + "...") if n[i] == n[i + 1]: adjCount += 1 i += 1 if adjCount >= 1: return True else: return False resultArr = [] while current <= int(highest): if checkNeverDecreaseRule(current) and checkHasAdjacentSame(current): resultArr.append(current) #print(checkNeverDecreaseRule(lowest)) #print(checkHasAdjacentSame(lowest)) current += 1 print(len(resultArr))
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#Transactions classes. from e2e.Classes.Transactions.Transaction import Transaction from e2e.Classes.Transactions.Transactions import Transactions #TestError Exception. from e2e.Tests.Errors import TestError #RPC class. from e2e.Meros.RPC import RPC #Sleep standard function. from time import sleep #Verify a Transaction. def verifyTransaction( rpc: RPC, tx: Transaction ) -> None: if rpc.call("transactions", "getTransaction", [tx.hash.hex()]) != tx.toJSON(): raise TestError("Transaction doesn't match.") #Verify the Transactions. def verifyTransactions( rpc: RPC, transactions: Transactions ) -> None: #Sleep to ensure data races aren't a problem. sleep(2) for tx in transactions.txs: verifyTransaction(rpc, transactions.txs[tx])
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import pygame from graphics.component import Component class GameComponent(Component): def __init__(self) -> None: super().__init__()
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import json import os.path import logging import csv from random import randint logger = logging.getLogger() logger.setLevel(logging.INFO) def get_quote(file): if os.path.exists(file): with open(file) as csvfile: quotes = list(csv.reader(csvfile, delimiter=';')) max_quotes = len(quotes) - 1 rand_quotes_idx = randint(0, max_quotes) logger.debug(quotes[rand_quotes_idx]) return quotes[rand_quotes_idx] else: logger.info(file + " not found") def lambda_handler(event, context): # logger.debug(context.aws_request_id) quote_entry = get_quote("quotes.csv") logger.debug(quote_entry) quote = "" author = "" if quote_entry is not None: quote = quote_entry[0] author = quote_entry[1] return { "statusCode": 200, "body": json.dumps({ "quote": quote, "author": author }), }
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from pathlib import Path import cv2 import json import math import numpy as np from argparse import ArgumentParser def distance(p1, p2): return math.sqrt((p2[0] - p1[0])**2 + (p2[1] - p1[1])**2) def order_points(points): pts = {} for x1, y1 in points: count_x_larger = 0 count_x_smaller = 0 count_y_larger = 0 count_y_smaller = 0 for x2, y2 in points: if x1 > x2: count_x_larger += 1 elif x1 < x2: count_x_smaller += 1 if y1 > y2: count_y_larger += 1 elif y1 < y2: count_y_smaller += 1 p = (x1, y1) if count_x_larger >= 2 and count_y_larger >= 2: pts['br'] = p elif count_x_smaller >= 2 and count_y_larger >= 2: pts['bl'] = p elif count_y_smaller >= 2 and count_x_smaller >= 2: pts['tl'] = p else: pts['tr'] = p return [pts['tl'], pts['tr'], pts['br'], pts['bl']] def get_padding_box(points, x_factor, y_factor): tl, tr, br, bl = points width = int(np.round(max([distance(tl, tr), distance(bl, br)]))) height = int(np.round(max([distance(tl, bl), distance(tr, br)]))) padding_x = x_factor * width padding_y = y_factor * height points2 = [ [tl[0] - padding_x, tl[1] - padding_y], [tr[0] + padding_x, tr[1] - padding_y], [br[0] + padding_x, br[1] + padding_y], [bl[0] - padding_x, bl[1] + padding_y], ] return points2 if __name__ == "__main__": parser = ArgumentParser() parser.add_argument('input_dir', type=str, help='Directory where the frame image and the json label be') parser.add_argument('output_dir', type=str, help='Directory where the textline would be extracted to') parser.add_argument('--ext', type=str, default='png') args = parser.parse_args() input_dir = Path(args.input_dir) output_dir = Path(args.output_dir) output_dir.mkdir(parents=True, exist_ok=True) jsons = list(input_dir.glob('*.json')) json_path: Path for json_path in jsons: label_dict = json.load(open(json_path, 'rt')) if len(label_dict['shapes']) == 0: continue frame = cv2.imread(str(json_path.with_suffix(f'.{args.ext}'))) for i, shape in enumerate(label_dict['shapes']): points = order_points(shape['points']) tl, tr, br, bl = points width = int(np.round(max([distance(tl, tr), distance(bl, br)]))) height = int(np.round(max([distance(tl, bl), distance(tr, br)]))) dst = np.array([[0, 0], [width - 1, 0], [width - 1, height - 1], [0, height - 1]], dtype=np.float32) M = cv2.getPerspectiveTransform(np.array(points, dtype=np.float32), dst) warp = cv2.warpPerspective(frame, M, (width, height)) output_path = output_dir.joinpath(json_path.stem + f'.{args.ext}') cv2.imwrite(str(output_path), warp)
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# ***** BEGIN GPL LICENSE BLOCK ***** # # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software Foundation, # Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # ***** END GPL LICENCE BLOCK ***** import bpy import os def find_index(objekti): luku = 0 for tex in objekti.active_material.texture_slots: if(not(hasattr(tex,'texture'))): break luku = luku +1 return luku def gettex(mat_list, objekti, scene,export): coat3D = bpy.context.scene.coat3D coa = objekti.coat3D if(bpy.context.scene.render.engine == 'VRAY_RENDER' or bpy.context.scene.render.engine == 'VRAY_RENDER_PREVIEW'): vray = True else: vray = False take_color = 0 take_spec = 0 take_normal = 0 take_disp = 0 bring_color = 1 bring_spec = 1 bring_normal = 1 bring_disp = 1 texcoat = {} texcoat['color'] = [] texcoat['specular'] = [] texcoat['nmap'] = [] texcoat['disp'] = [] texu = [] if(export): objekti.coat3D.objpath = export nimi = os.path.split(export)[1] osoite = os.path.dirname(export) + os.sep #pitaa ehka muuttaa for mate in objekti.material_slots: for tex_slot in mate.material.texture_slots: if(hasattr(tex_slot,'texture')): if(tex_slot.texture.type == 'IMAGE'): if tex_slot.texture.image is not None: tex_slot.texture.image.reload() else: if(os.sys.platform == 'win32'): osoite = os.path.expanduser("~") + os.sep + 'Documents' + os.sep + '3DC2Blender' + os.sep + 'Textures' + os.sep else: osoite = os.path.expanduser("~") + os.sep + '3DC2Blender' + os.sep + 'Textures' + os.sep ki = os.path.split(coa.applink_name)[1] ko = os.path.splitext(ki)[0] just_nimi = ko + '_' just_nimi_len = len(just_nimi) print('terve:' + coa.applink_name) if(len(objekti.material_slots) != 0): for obj_tex in objekti.active_material.texture_slots: if(hasattr(obj_tex,'texture')): if(obj_tex.texture.type == 'IMAGE'): if(obj_tex.use_map_color_diffuse): bring_color = 0; if(obj_tex.use_map_specular): bring_spec = 0; if(obj_tex.use_map_normal): bring_normal = 0; if(obj_tex.use_map_displacement): bring_disp = 0; files = os.listdir(osoite) for i in files: tui = i[:just_nimi_len] if(tui == just_nimi): texu.append(i) for yy in texu: minimi = (yy.rfind('_'))+1 maksimi = (yy.rfind('.')) tex_name = yy[minimi:maksimi] koko = '' koko += osoite koko += yy texcoat[tex_name].append(koko) if((texcoat['color'] or texcoat['nmap'] or texcoat['disp'] or texcoat['specular']) and (len(objekti.material_slots)) == 0): materials_old = bpy.data.materials.keys() bpy.ops.material.new() materials_new = bpy.data.materials.keys() new_ma = list(set(materials_new).difference(set(materials_old))) new_mat = new_ma[0] ki = bpy.data.materials[new_mat] objekti.data.materials.append(ki) if(bring_color == 1 and texcoat['color']): index = find_index(objekti) tex = bpy.ops.Texture objekti.active_material.texture_slots.create(index) total_mat = len(objekti.active_material.texture_slots.items()) useold = '' for seekco in bpy.data.textures: if((seekco.name[:5] == 'Color') and (seekco.users_material == ())): useold = seekco if(useold == ''): textures_old = bpy.data.textures.keys() bpy.data.textures.new('Color',type='IMAGE') textures_new = bpy.data.textures.keys() name_te = list(set(textures_new).difference(set(textures_old))) name_tex = name_te[0] bpy.ops.image.new(name=name_tex) bpy.data.images[name_tex].filepath = texcoat['color'][0] bpy.data.images[name_tex].source = 'FILE' objekti.active_material.texture_slots[index].texture = bpy.data.textures[name_tex] objekti.active_material.texture_slots[index].texture.image = bpy.data.images[name_tex] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].texture.image.reload() elif(useold != ''): objekti.active_material.texture_slots[index].texture = useold objekti.active_material.texture_slots[index].texture.image = bpy.data.images[useold.name] objekti.active_material.texture_slots[index].texture.image.filepath = texcoat['color'][0] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name if(bring_normal == 1 and texcoat['nmap']): index = find_index(objekti) tex = bpy.ops.Texture objekti.active_material.texture_slots.create(index) total_mat = len(objekti.active_material.texture_slots.items()) useold = '' for seekco in bpy.data.textures: if((seekco.name[:6] == 'Normal') and (seekco.users_material == ())): useold = seekco if(useold == ''): textures_old = bpy.data.textures.keys() bpy.data.textures.new('Normal',type='IMAGE') textures_new = bpy.data.textures.keys() name_te = list(set(textures_new).difference(set(textures_old))) name_tex = name_te[0] bpy.ops.image.new(name=name_tex) bpy.data.images[name_tex].filepath = texcoat['nmap'][0] bpy.data.images[name_tex].source = 'FILE' objekti.active_material.texture_slots[index].texture = bpy.data.textures[name_tex] objekti.active_material.texture_slots[index].texture.image = bpy.data.images[name_tex] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].use_map_color_diffuse = False objekti.active_material.texture_slots[index].use_map_normal = True objekti.active_material.texture_slots[index].texture.image.reload() if(vray): bpy.data.textures[name_tex].vray_slot.BRDFBump.map_type = 'TANGENT' else: bpy.data.textures[name_tex].use_normal_map = True objekti.active_material.texture_slots[index].normal_map_space = 'TANGENT' objekti.active_material.texture_slots[index].normal_factor = 1 elif(useold != ''): objekti.active_material.texture_slots[index].texture = useold objekti.active_material.texture_slots[index].texture.image = bpy.data.images[useold.name] objekti.active_material.texture_slots[index].texture.image.filepath = texcoat['nmap'][0] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].use_map_color_diffuse = False objekti.active_material.texture_slots[index].use_map_normal = True objekti.active_material.texture_slots[index].normal_factor = 1 if(bring_spec == 1 and texcoat['specular']): index = find_index(objekti) objekti.active_material.texture_slots.create(index) useold = '' for seekco in bpy.data.textures: if((seekco.name[:8] == 'Specular') and (seekco.users_material == ())): useold = seekco if(useold == ''): textures_old = bpy.data.textures.keys() bpy.data.textures.new('Specular',type='IMAGE') textures_new = bpy.data.textures.keys() name_te = list(set(textures_new).difference(set(textures_old))) name_tex = name_te[0] bpy.ops.image.new(name=name_tex) bpy.data.images[name_tex].filepath = texcoat['specular'][0] bpy.data.images[name_tex].source = 'FILE' objekti.active_material.texture_slots[index].texture = bpy.data.textures[name_tex] objekti.active_material.texture_slots[index].texture.image = bpy.data.images[name_tex] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].use_map_color_diffuse = False objekti.active_material.texture_slots[index].use_map_specular = True objekti.active_material.texture_slots[index].texture.image.reload() elif(useold != ''): objekti.active_material.texture_slots[index].texture = useold objekti.active_material.texture_slots[index].texture.image = bpy.data.images[useold.name] objekti.active_material.texture_slots[index].texture.image.filepath = texcoat['specular'][0] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].use_map_color_diffuse = False objekti.active_material.texture_slots[index].use_map_specular = True if(bring_disp == 1 and texcoat['disp']): index = find_index(objekti) objekti.active_material.texture_slots.create(index) useold = '' for seekco in bpy.data.textures: if((seekco.name[:12] == 'Displacement') and (seekco.users_material == ())): useold = seekco if useold == "": textures_old = bpy.data.textures.keys() bpy.data.textures.new('Displacement',type='IMAGE') textures_new = bpy.data.textures.keys() name_te = list(set(textures_new).difference(set(textures_old))) name_tex = name_te[0] bpy.ops.image.new(name=name_tex) bpy.data.images[name_tex].filepath = texcoat['disp'][0] bpy.data.images[name_tex].source = 'FILE' objekti.active_material.texture_slots[index].texture = bpy.data.textures[name_tex] objekti.active_material.texture_slots[index].texture.image = bpy.data.images[name_tex] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].use_map_color_diffuse = False objekti.active_material.texture_slots[index].use_map_displacement = True objekti.active_material.texture_slots[index].texture.image.reload() elif(useold != ''): objekti.active_material.texture_slots[index].texture = useold objekti.active_material.texture_slots[index].texture.image = bpy.data.images[useold.name] objekti.active_material.texture_slots[index].texture.image.filepath = texcoat['disp'][0] if(objekti.data.uv_textures.active): objekti.active_material.texture_slots[index].texture_coords = 'UV' objekti.active_material.texture_slots[index].uv_layer = objekti.data.uv_textures.active.name objekti.active_material.texture_slots[index].use_map_color_diffuse = False objekti.active_material.texture_slots[index].use_map_displacement = True if(vray): objekti.active_material.texture_slots[index].texture.use_interpolation = False objekti.active_material.texture_slots[index].displacement_factor = 0.05 else: disp_modi = '' for seek_modi in objekti.modifiers: if(seek_modi.type == 'DISPLACE'): disp_modi = seek_modi break if(disp_modi): disp_modi.texture = objekti.active_material.texture_slots[index].texture if(objekti.data.uv_textures.active): disp_modi.texture_coords = 'UV' disp_modi.uv_layer = objekti.data.uv_textures.active.name else: objekti.modifiers.new('Displace',type='DISPLACE') objekti.modifiers['Displace'].texture = objekti.active_material.texture_slots[index].texture if(objekti.data.uv_textures.active): objekti.modifiers['Displace'].texture_coords = 'UV' objekti.modifiers['Displace'].uv_layer = objekti.data.uv_textures.active.name return('FINISHED')
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#!/usr/bin/env python3 # # Proxy alerts generated by Prometheus Alertmanager turning them into # nagios passive alert information. # # Copyright 2019-2020, PostgreSQL Infrastructure Team # Author: Magnus Hagander # import argparse import http.server import json import time import sys missed_alerts = 0 def send_nagios_alert(status, alertname, hostname, info, severity): global args if status == 'firing': if severity == 'CRITICAL': alertlevel = 2 elif severity == 'WARNING': alertlevel = 1 else: # Actively specified to something that's not warning or critical, # so we're just going to map it to critical. alertlevel = 2 elif status == 'resolved': alertlevel = 0 info = "" else: raise Exception("Unknown alert status {0}".format(status)) if args.hostsuffix: hostname = "{0}.{1}".format(hostname, args.hostsuffix) out = "[{0}] PROCESS_SERVICE_CHECK_RESULT;{1};{2};{3};{4}\n".format( int(time.time()), hostname, alertname, alertlevel, info ) with open(args.nagioscmd, 'w') as f: f.write(out) class NotificationHandler(http.server.BaseHTTPRequestHandler): def do_GET(self): if self.path == '/ping': global missed_alerts if missed_alerts: self.send_and_end(500, 'Missed {0} alerts!'.format( missed_alerts).encode('utf8')) return self.send_response(200) self.send_header('Content-type', 'text/plain') self.end_headers() self.wfile.write(b'OK') return self.send_and_end(404, 'Not found') def do_POST(self): if self.path == '/alert': if self.headers['Content-Type'] != 'application/json': self.send_and_end(415, b'Must be json') return j = json.loads(self.rfile.read( int(self.headers['Content-Length']) ).decode('utf8')) try: for a in j['alerts']: status = a['status'] alertname = a['labels']['alertname'] hostname = a['labels']['name'] info = a['annotations']['summary'] severity = a['labels'].get('severity', 'CRITICAL').upper() send_nagios_alert(status, alertname, hostname, info, severity) except Exception as e: print("MISSED ALERT: %s" % e) global missed_alerts missed_alerts += 1 self.send_and_end(200, b"OK") def send_and_end(self, code, msg): self.send_response(code) self.end_headers() self.wfile.write(msg) if __name__ == "__main__": global args parser = argparse.ArgumentParser( description="Create nagios alerts from prometheus monitors" ) parser.add_argument('--hostsuffix', help='Suffix to add to hostnamees') parser.add_argument('--port', help='TCP port to bind to') parser.add_argument('--nagioscmd', help='Path to nagios command file') args = parser.parse_args() if not args.port: print("Port must be specified") sys.exit(1) if not args.nagioscmd: print("Nagios command path must be specified") sys.exit(1) server_address = ('localhost', int(args.port)) httpd = http.server.HTTPServer(server_address, NotificationHandler) httpd.serve_forever()
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#!/usr/bin/env python # -*- coding: utf-8 -*- # # __init__.py # @Author : wanhanwan (wanshuai_shufe@163.com) # @Date : 2019/11/25 下午1:20:12 from .filter import llt_filter
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def get_n_params(model): pp=0 for p in list(model.parameters()): nn=1 for s in list(p.size()): nn = nn*s pp += nn return pp
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import socket import sys import os import optparse from threading import * def createServer(ip, port): # create a TCP socket sck = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # bind the socket to the port server_address = (ip, port) print("starting up on {} port {}".format(*server_address)) sck.bind(server_address) # put the socket into server mode sck.listen(5) return sck def clientHandler(sck, conn, client, logs): # initialise user name = conn.recv(2014) # receive data while True: try: data = conn.recv(1024) message = name.decode() + ': ' + data.decode() + '\n' print(message) updateClients(message) logs.write(message) except: message = name.decode() + " closed the connection.\n" logs.write(message) print(message) break conn.close() def updateClients(message): for client in clients: client.send(bytes(message, 'ASCII')) def main(): # option to set port when launching the server parser = optparse.OptionParser("Usage: python3 server.py -h <server ip> -p <server port>") parser.add_option('-p', dest='port', type='int', help="specify server port") parser.add_option('-h', dest='ip', type='string', help="specify server ip") (options, args) = parser.parse_args() port = options.port ip = options.ip if port == None: print(parser.usage) exit(0) logs = open('./logs.txt', 'a+') sck = createServer(ip, port) while True: # wait for connection conn, client = sck.accept() clients.append(conn) # log connection message = client[0] + " connected.\n" print(message) logs.write(message) # start thread t = Thread(target=clientHandler, args=(sck, conn, client, logs)) t.start() clients = [] if __name__ == '__main__': main()
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#!/usr/bin/python # -*- coding: ascii -*- """ Byte utilities testing. :date: 2021 :author: Christian Wiche :contact: cwichel@gmail.com :license: The MIT License (MIT) """ import unittest from embutils.utils import bitmask, reverse_bits, reverse_bytes # -->> Definitions <<------------------ # -->> Test API <<--------------------- class TestBytes(unittest.TestCase): """ Test byte utilities. """ def test_01_bitmask(self): """ Test bitmask generation. """ # Test bitmask fill mask = bitmask(bit=7, fill=True) assert mask == 0b11111111 # Test bitmask mask = bitmask(bit=7) assert mask == 0b10000000 def test_02_reverse_bits(self): """ Test bit reverse functionality """ # Test using fixed size rev_bits = reverse_bits(value=0b00101011, size=8) assert rev_bits == 0b11010100 # Test using minimum size rev_bits = reverse_bits(value=0b00101011) assert rev_bits == 0b110101 def test_03_reverse_bytes(self): """ Test byte reverse functionality. """ # Test using fixed size rev_bytes = reverse_bytes(value=0x00020304, size=4) assert rev_bytes == 0x04030200 # Test using minimum size rev_bytes = reverse_bytes(value=0x00020304) assert rev_bytes == 0x040302 # -->> Test Execution <<--------------- if __name__ == '__main__': unittest.main()
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# Generated by Django 2.0 on 2018-03-24 02:55 import datetime import django.db.models.deletion from django.db import migrations, models import mptt.fields class Migration(migrations.Migration): dependencies = [("events", "0019_add_org_slug")] operations = [ migrations.CreateModel( name="EventComment", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ("body", models.TextField()), ( "created_time", models.DateTimeField(db_index=True, default=datetime.datetime.now), ), ( "status", models.SmallIntegerField( choices=[(-1, "Removed"), (0, "Pending"), (1, "Approved")], db_index=True, default=1, ), ), ("lft", models.PositiveIntegerField(db_index=True, editable=False)), ("rght", models.PositiveIntegerField(db_index=True, editable=False)), ("tree_id", models.PositiveIntegerField(db_index=True, editable=False)), ("level", models.PositiveIntegerField(db_index=True, editable=False)), ], options={"abstract": False}, ), migrations.AddField( model_name="eventcomment", name="author", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="events.UserProfile" ), ), migrations.AddField( model_name="eventcomment", name="event", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="events.Event" ), ), migrations.AddField( model_name="eventcomment", name="parent", field=mptt.fields.TreeForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="children", to="events.EventComment", ), ), ]
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# -*- coding: utf-8 -*- """Ant_Algorithm.ipynb Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1Zjt1SInhoaFEqSmsPjEfWQE7jhugAvZA # **ANT ALGORITHM BY KELOMPOK 9** 1. Heri Khariono - 18081010002 2. Devan Cakra Mudra Wijaya - 18081010013 3. Ika Nur Habibah - 18081010033 4. Trisa Pratiwi - 18081010036 5. Rifky Akhmad Fernanda - 18081010126 # **1. Import Libraries** """ #**********************************IMPORT LIBRARIES******************************* #Library untuk operasi matematika import math #Library untuk membentuk dan memanipulasi segala bentuk graf dan jaringan import networkx as nx #Library untuk visualisasi grafik from matplotlib import pyplot as plt import matplotlib.patches as mpatches from pylab import * #Library untuk mendukung komputasi numerik import numpy as np #Library untuk analisis dan manipulasi data tingkat tinggi import pandas as pn #Library untuk untuk mengukur waktu eksekusi from time import time """# **2. Read Data**""" read_jarak_antarkota = pn.read_excel('https://raw.githubusercontent.com/devancakra/Ant-Algorithm-Pencarian-Rute-Tercepat/master/jarak_antarkota.xlsx') read_kota = pn.read_excel('https://raw.githubusercontent.com/devancakra/Ant-Algorithm-Pencarian-Rute-Tercepat/master/kota.xlsx') arr_kota = np.array(read_kota) arr_jarak_antarkota = np.array(read_jarak_antarkota) #Grafik Map def Grafik_Map(simpul,sudut): plt.style.use('ggplot') fig = plt.figure(figsize=(25.200,15)) x = simpul[:,0] y = simpul[:,1] #Mencetak garis plt.plot( x, y, '--',x, y, 'p',color='#FF8000',#Warna garis markersize=35, #Ukuran objek linewidth=2, markerfacecolor='#00E4B6',#Warna objek markeredgecolor='#00FF00',#Warna tepi objek markeredgewidth=2)#Ketebalan tepi titik plt.title("KOTA") legend(("Jalur","Kota"), prop = {'size': 30}, loc='lower right') plt.grid(True) #plt.tight_layout() for i in range (len(simpul)): #Pengidentifikasi kota (nomor setiap kota) plt.annotate("Kota"+str(i+1), size=8, xy=simpul[i], horizontalalignment='center', verticalalignment='center') #Kotak dalam anotasi bbox = dict (facecolor = 'none', edgecolor = 'black', boxstyle = 'round, pad = 1') Grafik_Map(arr_kota,arr_jarak_antarkota) """# **3. Implementasi Algoritma Ant** 1. Transisi status, Pembaruan Feromon Lokal, Pembaruan Feromon Global """ import random class Rute_Cepat_ACO: #Sub class Tepi = objek tepi yang menyimpan simpul a, simpul b, jarak antara ab, dan feromon koneksi class Tepi: def __init__(self, a, b, jarak_ab, feromon_koneksi): self.a = a self.b = b self.jarak_ab = jarak_ab self.feromon_koneksi = feromon_koneksi #Sub class Semut class Semut: def __init__(self, alpha, beta, num_simpul, tepi): self.alpha = alpha self.beta = beta self.num_simpul = num_simpul self.tepi = tepi self.survei = None self.jarak_tempuh = 0.0 #Metode untuk memilih simpul berikutnya yang akan dikunjungi, memvalidasi bahwa node tersebut belum pernah dikunjungi. def _select_simpul(self): persebaran = 0.0 #mulai persebaran dari nol,lalu pilih jalur secara acak k_simpul_sepi = [node for node in range(self.num_simpul) if node not in self.jalur] #Simpul Sepi heuristic_total = 0.0 #Peningkatan jarak jalan for simpul_sepi in k_simpul_sepi: heuristic_total += self.tepi[self.jalur[-1]][simpul_sepi].jarak_ab for simpul_sepi in k_simpul_sepi: persebaran += pow(self.tepi[self.jalur[-1]][simpul_sepi].feromon_koneksi, self.alpha) * \ pow((heuristic_total / self.tepi[self.jalur[-1]][simpul_sepi].jarak_ab), self.beta) nilai_random = random.uniform(0.0, persebaran) pos_sebar = 0.0 for simpul_sepi in k_simpul_sepi: pos_sebar += pow(self.tepi[self.jalur[-1]][simpul_sepi].feromon_koneksi, self.alpha) * \ pow((heuristic_total / self.tepi[self.jalur[-1]][simpul_sepi].jarak_ab), self.beta) if pos_sebar >= nilai_random: return simpul_sepi #Metode untuk menemukan cara untuk memilih jalur def survei_jalur(self): self.jalur = [random.randint(0, self.num_simpul - 1)] while len(self.jalur) < self.num_simpul: self.jalur.append(self._select_simpul()) return self.jalur #Jarak antara satu simpul dengan simpul lainnya def get_jarak_tempuh(self): self.jarak_tempuh = 0.0 for i in range(self.num_simpul): self.jarak_tempuh += self.tepi[self.jalur[i]][self.jalur[(i + 1) % self.num_simpul]].jarak_ab return self.jarak_tempuh # Definisi atribut untuk objek kelas Rute_Cepat_ACO def __init__(self, mode='ACS', jumlah_semut=10, alpha=1.0, beta=3.0, rho=0.1, feromon_tersimpan=1.0, feromon_koneksi=1.0, langkah=100, v_simpul=None, m_jarak=None, posting=None): self.mode = mode self.jumlah_semut = jumlah_semut self.rho = rho self.feromon_tersimpan = feromon_tersimpan self.langkah = langkah self.num_simpul = len(v_simpul) self.v_simpul = v_simpul if posting is not None: self.posting = posting else: self.posting = range(1, self.num_simpul + 1) #Deklarasi list tepi kosong self.tepi = [[None] * self.num_simpul for _ in range(self.num_simpul)] #Membuat objek tepi untuk setiap tuple i = a j = b dan menyimpannya di list tepi, pada akhirnya array n*n dibuat, dengan n = jumlah simpul for i in range(self.num_simpul): for j in range(self.num_simpul): self.tepi[i][j] = self.tepi[j][i] = self.Tepi(i, j, m_jarak[i][j],feromon_koneksi) #Simpan objek bertipe Endge di list tepi self.semut = [self.Semut(alpha, beta, self.num_simpul, self.tepi) for _ in range(self.jumlah_semut)] #Buat semut dalam array yang terdiri dari objek kelas Semut self.jalur_terbaik = None #Atribut jalan terbaik self.jarak_terbaik = float("inf") #Atribut untuk jarak minimum #Metode yang menambahkan feromon ke jalan def _add_feromon(self, jalur, jarak_ab, weight=1.0): add_feromon = self.feromon_tersimpan / jarak_ab for i in range(self.num_simpul): self.tepi[jalur[i]][jalur[(i + 1) % self.num_simpul]].feromon_koneksi += jarak_ab * add_feromon #Siklus perutean setiap semut def _acs(self): for k_langkah in range(self.langkah): for k_semut in self.semut: self._add_feromon(k_semut.survei_jalur(), k_semut.get_jarak_tempuh()) if k_semut.jarak_tempuh < self.jarak_terbaik: self.jalur_terbaik = k_semut.jalur self.jarak_terbaik = k_semut.jarak_tempuh for i in range(self.num_simpul): for j in range(i + 1, self.num_simpul): self.tepi[i][j].feromon_koneksi *= (1.0 - self.rho) #Metode yang dimuat saat menjalankan kelas def run(self): self._acs() #Membuat grafik hasil def plot(self, line_width=1, point_radius=math.sqrt(2.0), annotation_size=10, dpi=120, save=True, name=None): fig = plt.figure(figsize=(25.200,15)) x = [self.v_simpul[i][0] for i in self.jalur_terbaik] x.append(x[0]) y = [self.v_simpul[i][1] for i in self.jalur_terbaik] y.append(y[0]) #Mencetak garis plt.plot( x, y, '--',x, y, 'p',color='#FF8000',#Warna garis markersize=35, #Ukuran objek linewidth=2, markerfacecolor='#00E4B6',#Warna objek markeredgecolor='#00FF00',#Warna tepi objek markeredgewidth=2)#Ketebalan tepi titik #Membuat tambalan untuk diletakkan di kanan atas gambar handle1 = mpatches.Patch(color='white', label='Semut: '+str(self.jumlah_semut)) handle2 = mpatches.Patch(color='white', label='Langkah: '+str(self.langkah)) handle3 = mpatches.Patch(color='white', label='Rho: '+str(self.rho)) ax = plt.gca().add_artist(plt.legend(handles=[handle1,handle2,handle3],prop = {'size': 12})) #Hasil handle4 = mpatches.Patch(color='white', label='Jarak tempuh: '+str(round(self.jarak_terbaik, 2))) ax = plt.gca().add_artist(plt.legend(handles=[handle4],prop = {'size': 12},loc='lower left')) #Data grafik plt.title(" Perutean ACS - "+self.mode) legend(("Jalur","Kota"), prop = {'size': 30}, loc='lower right') plt.grid(True) #Pengenal kota (nomor tiap kota) for i in self.jalur_terbaik: plt.annotate("Kota"+str(i+1), size=8, xy=self.v_simpul[i], horizontalalignment='center', verticalalignment='center') #Kotak dalam anotasi bbox = dict (facecolor = 'none', edgecolor = 'black', boxstyle = 'round, pad = 1') plt.show() return self.jarak_terbaik """2. Konfigurasi perutean""" #Mendefinisikan fungsi untuk mengirim konfigurasi yang berbeda secara teratur def config(tipe, ts, lg, t_evap): acs = Rute_Cepat_ACO(mode=tipe, jumlah_semut=ts, langkah=lg, v_simpul=arr_kota, m_jarak=arr_jarak_antarkota, rho=t_evap) acs.run() jarak_jalur_akhir = acs.plot() return jarak_jalur_akhir #Konfigurasi yang berbeda didefinisikan txt_config = [] #Teks konfigurasi jumlah_semut = [] #Ukuran koloni langkah = [] #Jumlah langkah total rho = [] #Tingkat penguapan fermones ANTARA 0 dan 1 txt_config.append('Konfigurasi 1'); jumlah_semut.append(50); langkah.append(10); rho.append(0.1); txt_config.append('Konfigurasi 2'); jumlah_semut.append(100); langkah.append(10); rho.append(0.1); txt_config.append('Konfigurasi 3'); jumlah_semut.append(250); langkah.append(10); rho.append(0.1); txt_config.append('Konfigurasi 4'); jumlah_semut.append(50); langkah.append(30); rho.append(0.5); txt_config.append('Konfigurasi 5'); jumlah_semut.append(90); langkah.append(40); rho.append(0.5); txt_config.append('Konfigurasi 6'); jumlah_semut.append(150); langkah.append(30); rho.append(0.5); txt_config.append('Konfigurasi 7'); jumlah_semut.append(50); langkah.append(50); rho.append(0.1); txt_config.append('Konfigurasi 8'); jumlah_semut.append(200); langkah.append(90); rho.append(0.1); txt_config.append('Konfigurasi 9'); jumlah_semut.append(150); langkah.append(50); rho.append(0.1); txt_config.append('Konfigurasi 10'); jumlah_semut.append(80); langkah.append(100); rho.append(0.5); txt_config.append('Konfigurasi 11'); jumlah_semut.append(100); langkah.append(100); rho.append(0.5); txt_config.append('Konfigurasi 12'); jumlah_semut.append(150); langkah.append(100); rho.append(0.5); jarak_ab = [] #Vektor perpindahan akhir di setiap konfigurasi tempo = [] #Vektor waktu eksekusi algoritma di setiap konfigurasi for i in range(len(txt_config)): start_time = time() jarak_ab.append(config(txt_config[i], jumlah_semut[i], langkah[i], rho[i])) tempo.append(time()-start_time) """3. Pemilihan Hasil Terbaik""" #Grafik hasil tiga rute terbaik berdasarkan jarak index1=jarak_ab.index(sorted(jarak_ab,reverse=False)[0]) index2=jarak_ab.index(sorted(jarak_ab,reverse=False)[1]) index3=jarak_ab.index(sorted(jarak_ab,reverse=False)[2]) if index2==index1: index2=index2+1 if index2==index3: index3=index3+1 plt.style.use('ggplot') fig = plt.figure(figsize=(10.80,5)) plt.bar(range(3),sorted(jarak_ab,reverse=False)[0:3], edgecolor='#93329F', color='#5D87B6') plt.xticks(range(3),(txt_config[index1],txt_config[index2],txt_config[index3]), rotation=70) plt.ylim(min(jarak_ab[index1],jarak_ab[index2],jarak_ab[index3])-1, max(jarak_ab[index1],jarak_ab[index2],jarak_ab[index3])+1) plt.title("Hasil konfigurasi terbaik berdasarkan jarak") plt.ylabel('Jarak tempuh') plt.xlabel('Konfigurasi rute yang digunakan (jarak)\n\n') plt.show() #Grafik hasil tiga rute terbaik berdasarkan waktu plt.style.use('ggplot') fig = plt.figure(figsize=(10.80,5)) plt.bar(range(3),(tempo[index1],tempo[index2],tempo[index3]), edgecolor='#282623', color='#138d90') plt.xticks(range(3),(txt_config[index1],txt_config[index2],txt_config[index3]), rotation=70) plt.ylim(min(tempo[index1],tempo[index2],tempo[index3])-1, max(tempo[index1],tempo[index2],tempo[index3])+10) plt.title("Hasil konfigurasi terbaik berdasarkan waktu") plt.ylabel('Waktu tempuh') plt.xlabel('Konfigurasi rute yang digunakan (waktu)\n\n') plt.show() #Grafik hasil tiga rute terbaik berdasarkan jalur plt.style.use('ggplot') fig = plt.figure(figsize=(10.80,5)) plt.bar(range(3),(langkah[index1],langkah[index2],langkah[index3]), edgecolor='#F387FF', color='#0D3E00') plt.xticks(range(3),(txt_config[index1],txt_config[index2],txt_config[index3]), rotation=70) plt.ylim(min(langkah[index1],langkah[index2],langkah[index3])-1, max(langkah[index1],langkah[index2],langkah[index3])+1) plt.title("Hasil konfigurasi terbaik berdasarkan jalur") plt.ylabel('Jalur tempuh') plt.xlabel('Konfigurasi rute yang digunakan (jalur)\n\n') plt.show()
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import numpy as np from scipy.ndimage import maximum_filter class AttrDict(dict): __setattr__ = dict.__setitem__ __getattr__ = dict.__getitem__ def signal2noise(r_map): """ Compute the signal-to-noise ratio of correlation plane. w*h*c""" r = r_map.copy() max_r = maximum_filter(r_map, (5,5,1)) ind = max_r> (r_map+1e-3) r[ind] = 0.05 r = np.reshape(r, (-1, r.shape[-1])) r = np.sort(r,axis=0) ratio = r[-1,:]/r[-2,:] return ratio def main(): r = np.random.randn(5,5,3) signal2noise(r) if __name__=='__main__': main()
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import os import time import argparse from tqdm import tqdm import torch from torch import optim from torch import nn from fastNLP import BucketSampler from fastNLP import logger from fastNLP import DataSetIter from fastNLP import Tester from fastNLP import cache_results from bjtunlp.models import BertParser from bjtunlp.models.metrics import SegAppCharParseF1Metric, CWSPOSMetric, ParserMetric from bjtunlp.modules.trianglelr import TriangleLR from bjtunlp.modules.chart import save_table from bjtunlp.modules.pipe import CTBxJointPipe from bjtunlp.modules.word_batch import BatchSampler from bjtunlp.modules.embedding import ElectraEmbedding def main(): parser = argparse.ArgumentParser() parser.add_argument('--model_type', type=str, help=r'Whether to use the first-order model or the second-order model, LOC represents the first-order model CRF2 stands for second-order model. default:LOC', choices=['LOC', 'CRF2'], default='LOC') parser.add_argument('--output', type=str, help=r'The path where the output model is stored. default:./output', default=r'output') parser.add_argument('--dataset', type=str, help=r'The data set required for training the joint model, which must include the training set, test set and development set, and the data format is CoNLL format. default:./ctb7', default=r'G:\真正联合\bjtunlp\data\ctb7') parser.add_argument('--pretraining', type=str, help='Pre-trained language models Electra downloaded from huggingface. default:./discriminator', default=r'H:\预训练语言模型\哈工大20G语料-Electra\base\discriminator') parser.add_argument('--epochs', type=int, help='Number of epoch to train the model. default:15', default=15) parser.add_argument('--lr', type=float, help='Learning rate setting. default:2e-5', default=2e-5) parser.add_argument('--batch_size', type=int, help='The number of words fed to the model at a time. default:1000', default=1000) parser.add_argument('--clip', type=float, help='Value for gradient clipping nn.utils.clip_grad_value_. default:5.0', default=5.0) parser.add_argument('--weight_decay', type=float, help='L2 regularization. default:1e-2', default=1e-2) parser.add_argument('--device', type=int, help='Whether to use GPU for training, 0 means cuda:0, -1 means cpu. default:0', default=0) parser.add_argument('--dropout', type=float, help='dropout. default:0.5', default=0.5) parser.add_argument('--arc_mlp_size', type=int, help='The hidden dimensions of predicting the dependency arc. default:500', default=500) parser.add_argument('--label_mlp_size', type=int, help='The hidden dimensions of predicting the dependency label. default:100', default=300) args = parser.parse_args() print(args) context_path = os.getcwd() save_path = os.path.join(context_path, args.output) if not os.path.exists(context_path): os.makedirs(context_path) model_type = args.model_type data_name = args.dataset pretraining = args.pretraining epochs = args.epochs lr = args.lr # 0.01~0.001 batch_size = args.batch_size # 1000 clip = args.clip weight_decay = args.weight_decay device = torch.device("cuda:%d" % args.device if (torch.cuda.is_available()) else "cpu") dropout = args.dropout # 0.3~0.6 arc_mlp_size = args.arc_mlp_size # 200, 300 label_mlp_size = args.label_mlp_size logger.add_file(save_path + '/joint' + time.strftime('%Y-%m-%d-%H-%M-%S', time.localtime(time.time())) + '.log', level='INFO') # 将超参数保存的日志中 logger.info(f'model_type:{model_type}') logger.info(f'data_name:{data_name}') logger.info(f'pretraining:{pretraining}') logger.info(f'epochs:{epochs}') logger.info(f'lr:{lr}') logger.info(f'batch_size:{batch_size}') logger.info(f'clip:{clip}') logger.info(f'weight_decay:{weight_decay}') logger.info(f'device:{device}') logger.info(f'dropout:{dropout}') logger.info(f'arc_mlp_size:{arc_mlp_size}') logger.info(f'label_mlp_size:{label_mlp_size}') cache_name = os.path.split(data_name)[-1] @cache_results(save_path + '/caches/{}.pkl'.format(cache_name), _refresh=False) def get_data(data_name, pretraining): data, special_root = CTBxJointPipe().process_from_file(data_name) data.delete_field('bigrams') data.delete_field('trigrams') data.delete_field('chars') data.rename_field('pre_chars', 'chars') data.delete_field('pre_bigrams') data.delete_field('pre_trigrams') embed = ElectraEmbedding(data.get_vocab('chars'), pretraining) return data, embed, special_root data, embed, special_root = get_data(data_name, pretraining) print(data) model = BertParser(embed=embed, char_label_vocab=data.get_vocab('char_labels'), num_pos_label=len(data.get_vocab('char_pos')), arc_mlp_size=arc_mlp_size, label_mlp_size=label_mlp_size, dropout=dropout, model=model_type, special_root=special_root, use_greedy_infer=False, ) metric1 = SegAppCharParseF1Metric(data.get_vocab('char_labels')) metric2 = CWSPOSMetric(data.get_vocab('char_labels'), data.get_vocab('char_pos')) metric3 = ParserMetric(data.get_vocab('char_labels')) metrics = [metric1, metric2, metric3] optimizer = optim.AdamW([param for param in model.parameters() if param.requires_grad], lr=lr, weight_decay=weight_decay) sampler = BucketSampler(batch_size=4, seq_len_field_name='seq_lens') train_batch = DataSetIter(batch_size=4, dataset=data.get_dataset('train'), sampler=sampler, batch_sampler=BatchSampler(data.get_dataset('train'), batch_size, 'seq_lens')) scheduler = TriangleLR(optimizer, len(train_batch) * epochs, schedule='linear') best_score = 0. best_epoch = 0 table = [] model = model.to(device) for i in range(epochs): for batch_x, batch_y in tqdm(train_batch, desc='Epoch: %3d' % i): optimizer.zero_grad() if args.device >= 0: batch_x['chars'] = batch_x['chars'].to(device) batch_y['char_heads'] = batch_y['char_heads'].to(device) batch_y['char_labels'] = batch_y['char_labels'].to(device) batch_y['char_pos'] = batch_y['char_pos'].to(device) batch_y['sibs'] = batch_y['sibs'].to(device) output = model(batch_x['chars'], batch_y['char_heads'], batch_y['char_labels'], batch_y['sibs']) loss = output['loss'] loss.backward() nn.utils.clip_grad_value_(model.parameters(), clip) optimizer.step() scheduler.step() dev_tester = Tester(data.get_dataset('dev'), model, batch_size=8, metrics=metrics, device=device, verbose=0) dev_res = dev_tester.test() logger.info('Epoch:%3d Dev' % i + dev_tester._format_eval_results(dev_res)) print('Epoch:%3d Dev' % i + dev_tester._format_eval_results(dev_res)) test_tester = Tester(data.get_dataset('test'), model, batch_size=8, metrics=metrics, device=device, verbose=0) test_res = test_tester.test() logger.info('Epoch:%3d Test' % i + test_tester._format_eval_results(test_res)) print('Epoch:%3d Test' % i + test_tester._format_eval_results(test_res)) if dev_res['SegAppCharParseF1Metric']['u_f1'] > best_score: best_score = dev_res['SegAppCharParseF1Metric']['u_f1'] best_epoch = i torch.save(model, save_path + '/joint.model') table.append([dev_res, test_res]) print('best performance on test dataset Related to the development set %d' % best_epoch) print('Save the model in this directory :%s' % save_path) logger.info('best performance on test dataset Related to the development set %d' % best_epoch) logger.info('Save the model in this directory :%s' % save_path) logger.info(str(table[best_epoch])) save_table(table, save_path + '/results.csv') if __name__ == '__main__': main()
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import time import torch from torch.autograd import Variable from torch.utils.data.sampler import SubsetRandomSampler from archived.elasticache import redis_init from archived.s3.get_object import get_object from archived.old_model import LogisticRegression from data_loader.libsvm_dataset import DenseDatasetWithLines # lambda setting redis_location = "test.fifamc.ng.0001.euc1.cache.amazonaws.com" grad_bucket = "tmp-grads" model_bucket = "tmp-updates" local_dir = "/tmp" w_prefix = "w_" b_prefix = "b_" w_grad_prefix = "w_grad_" b_grad_prefix = "b_grad_" # algorithm setting learning_rate = 0.1 batch_size = 100 num_epochs = 2 validation_ratio = .2 shuffle_dataset = True random_seed = 42 endpoint = redis_init(redis_location) def handler(event, context): start_time = time.time() bucket = event['bucket'] key = event['name'] num_features = event['num_features'] num_classes = event['num_classes'] print('bucket = {}'.format(bucket)) print('key = {}'.format(key)) key_splits = key.split("_") worker_index = int(key_splits[0]) num_worker = int(key_splits[1]) # read file(dataset) from s3 file = get_object(bucket, key).read().decode('utf-8').split("\n") print("read data cost {} s".format(time.time() - start_time)) parse_start = time.time() dataset = DenseDatasetWithLines(file, num_features) preprocess_start = time.time() print("libsvm operation cost {}s".format(parse_start - preprocess_start)) # Creating data indices for training and validation splits: dataset_size = len(dataset) print("dataset size = {}".format(dataset_size)) indices = list(range(dataset_size)) split = int(np.floor(validation_ratio * dataset_size)) if shuffle_dataset: np.random.seed(random_seed) np.random.shuffle(indices) train_indices, val_indices = indices[split:], indices[:split] # Creating PT data samplers and loaders: train_sampler = SubsetRandomSampler(train_indices) valid_sampler = SubsetRandomSampler(val_indices) train_loader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, sampler=train_sampler) validation_loader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, sampler=valid_sampler) print("preprocess data cost {} s".format(time.time() - preprocess_start)) model = LogisticRegression(num_features, num_classes) # Loss and Optimizer # Softmax is internally computed. # Set parameters to be updated. criterion = torch.nn.CrossEntropyLoss() optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate) # Training the Model for epoch in range(num_epochs): for batch_index, (items, labels) in enumerate(train_loader): print("------worker {} epoch {} batch {}------".format(worker_index, epoch, batch_index)) batch_start = time.time() items = Variable(items.view(-1, num_features)) labels = Variable(labels) # Forward + Backward + Optimize optimizer.zero_grad() outputs = model(items) loss = criterion(outputs, labels) loss.backward() print("forward and backward cost {} s".format(time.time()-batch_start)) w_grad = model.linear.weight.grad.data.numpy() b_grad = model.linear.bias.grad.data.numpy() print("w_grad before merge = {}".format(w_grad[0][0:5])) print("b_grad before merge = {}".format(b_grad)) #synchronization starts from that every worker writes their gradients of this batch and epoch sync_start = time.time() hset_object(endpoint, grad_bucket, w_grad_prefix + str(worker_index), w_grad.tobytes()) hset_object(endpoint, grad_bucket, b_grad_prefix + str(worker_index), b_grad.tobytes()) #merge gradients among files merge_start = time.time() file_postfix = "{}_{}".format(epoch, batch_index) if worker_index == 0: merge_start = time.time() w_grad_merge, b_grad_merge = \ merge_w_b_grads(endpoint, grad_bucket, num_worker, w_grad.dtype, w_grad.shape, b_grad.shape, w_grad_prefix, b_grad_prefix) print("model average time = {}".format(time.time()-merge_start)) #possible rewrite the file before being accessed. wait until anyone finishes accessing. put_merged_w_b_grads(endpoint, model_bucket, w_grad_merge, b_grad_merge, w_grad_prefix, b_grad_prefix) hset_object(endpoint, model_bucket, "epoch", epoch) hset_object(endpoint, model_bucket, "index", batch_index) #delete_expired_w_b(endpoint, # model_bucket, epoch, batch_index, w_grad_prefix, b_grad_prefix) model.linear.weight.grad = Variable(torch.from_numpy(w_grad_merge)) model.linear.bias.grad = Variable(torch.from_numpy(b_grad_merge)) else: # wait for flag to access while hget_object(endpoint, model_bucket, "epoch") != None: if int(hget_object(endpoint, model_bucket, "epoch")) == epoch \ and int(hget_object(endpoint, model_bucket, "index")) == batch_index: break time.sleep(0.01) w_grad_merge, b_grad_merge = get_merged_w_b_grads(endpoint,model_bucket, w_grad.dtype, w_grad.shape, b_grad.shape, w_grad_prefix, b_grad_prefix) hcounter(endpoint, model_bucket, "counter") #flag it if it's accessed. print("number of access at this time = {}".format(int(hget_object(endpoint, model_bucket, "counter")))) model.linear.weight.grad = Variable(torch.from_numpy(w_grad_merge)) model.linear.bias.grad = Variable(torch.from_numpy(b_grad_merge)) print("w_grad after merge = {}".format(model.linear.weight.grad.data.numpy()[0][:5])) print("b_grad after merge = {}".format(model.linear.bias.grad.data.numpy())) print("synchronization cost {} s".format(time.time() - sync_start)) optimizer.step() print("batch cost {} s".format(time.time() - batch_start)) if (batch_index + 1) % 10 == 0: print('Epoch: [%d/%d], Step: [%d/%d], Loss: %.4f' % (epoch + 1, num_epochs, batch_index + 1, len(train_indices) / batch_size, loss.data)) """ if worker_index == 0: while sync_counter(endpoint, bucket, num_workers): time.sleep(0.001) clear_bucket(endpoint, model_bucket) clear_bucket(endpoint, grad_bucket) """ # Test the Model correct = 0 total = 0 for items, labels in validation_loader: items = Variable(items.view(-1, num_features)) outputs = model(items) _, predicted = torch.max(outputs.data, 1) total += labels.size(0) correct += (predicted == labels).sum() print('Accuracy of the model on the %d test samples: %d %%' % (len(val_indices), 100 * correct / total)) end_time = time.time() print("elapsed time = {} s".format(end_time - start_time))
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from enum import Enum class NeuronTypes(Enum): """ Enum class containing neuron types: excitatory and inhibitory. """ EX = "excitatory" IN = "inhibitory"
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from typing import List from backend.common.cache_clearing import get_affected_queries from backend.common.manipulators.manipulator_base import ManipulatorBase from backend.common.models.cached_model import TAffectedReferences from backend.common.models.team import Team class TeamManipulator(ManipulatorBase[Team]): """ Handle Team database writes. """ @classmethod def getCacheKeysAndQueries( cls, affected_refs: TAffectedReferences ) -> List[get_affected_queries.TCacheKeyAndQuery]: return get_affected_queries.team_updated(affected_refs) """ @classmethod def postDeleteHook(cls, teams): # To run after the team has been deleted. for team in teams: SearchHelper.remove_team_location_index(team) @classmethod def postUpdateHook(cls, teams, updated_attr_list, is_new_list): # To run after models have been updated for (team, updated_attrs) in zip(teams, updated_attr_list): if 'city' in updated_attrs or 'state_prov' in updated_attrs or \ 'country' in updated_attrs or 'postalcode' in updated_attrs: try: LocationHelper.update_team_location(team) except Exception, e: logging.error("update_team_location for {} errored!".format(team.key.id())) logging.exception(e) try: SearchHelper.update_team_location_index(team) except Exception, e: logging.error("update_team_location_index for {} errored!".format(team.key.id())) logging.exception(e) cls.createOrUpdate(teams, run_post_update_hook=False) """ @classmethod def updateMerge( cls, new_model: Team, old_model: Team, auto_union: bool = True ) -> Team: cls._update_attrs(new_model, old_model, auto_union) # Take the new tpid and tpid_year iff the year is newer than or equal to the old one if ( new_model.first_tpid_year is not None and new_model.first_tpid_year >= old_model.first_tpid_year ): old_model.first_tpid_year = new_model.first_tpid_year old_model.first_tpid = new_model.first_tpid old_model._dirty = True return old_model
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from django.conf import settings INFUSIONSOFT_COMPANY = getattr(settings, 'INFUSIONSOFT_COMPANY_ID', None) INFUSIONSOFT_API_KEY = getattr(settings, 'INFUSIONSOFT_API_KEY', None)
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# MIT License # # Copyright (c) 2020 HENSOLDT # # 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. # Python implementation of the under/over-exposure measure. We focus on simplicity and readability rather than efficiency. # # This code is related to the paper # M. Teutsch, S. Sedelmaier, S. Moosbauer, G. Eilertsen, T. Walter, # "An Evaluation of Objective Image Quality Assessment for Thermal Infrared Video Tone Mapping", IEEE CVPR Workshops, 2020. # # Please cite the paper if you use the code for your evaluations. # This measure was originally proposed here: # G. Eilertsen, R. Mantiuk, J. Unger, "A comparative review of tone-mapping algorithms for high dynamic range video", Eurographics, 2017. import numpy as np import cv2 ## Calcuate the over- and under-exposure measure (number of over- and under-exposed pixels) for one given tone mapped LDR image. # @param image_ldr Low Definition Range image (processed image after tone mapping). def number_of_over_and_under_exposures_pixels(image_ldr): # calculate exposure measure for one given frame # calculate histogram of the image hist, bins = np.histogram(image_ldr, 256, [0, 255]) # fraction of under-exposed pixels under_exp_pix = sum(hist[0:int(255 * 0.02)])/sum(hist) * 100 # fraction of over-exposed pixels over_exp_pix = sum(hist[int(255 * 0.95):])/sum(hist) * 100 return over_exp_pix, under_exp_pix ## Calculate over- and under-exposure measure for all (already tone mapped) images in given path. # @param images_ldr_path Directory path that contains the tone mapped images of one sequence. def calculate_over_and_under_exposure_measure(images_ldr_path): sequence_length = len(images_ldr_path) if sequence_length == 0: raise ValueError('List of LDR image paths must not be empty.') under_exp_pix = 0 over_exp_pix = 0 for image_ldr_path in images_ldr_path: print(".", end = '', flush = True) # show progress # read tone mapped (TM) image as grayscale image image_ldr = cv2.imread(str(image_ldr_path), cv2.IMREAD_GRAYSCALE) curr_over_exp_pix, curr_under_exp_pix = number_of_over_and_under_exposures_pixels(image_ldr) # fraction of under-exposed pixels under_exp_pix += curr_under_exp_pix # fraction of over-exposed pixels over_exp_pix += curr_over_exp_pix # calculate average of over- and under-exposed pixels for this sequence over_exposure = over_exp_pix / sequence_length under_exposure = under_exp_pix / sequence_length print() # newline after progress dots return over_exposure, under_exposure
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from pilco.models.pilco import PILCO import jax.numpy as jnp import numpy as np import objax import os import oct2py import logging oc = oct2py.Oct2Py(logger=oct2py.get_log()) oc.logger = oct2py.get_log("new_log") oc.logger.setLevel(logging.INFO) dir_path = os.path.dirname(os.path.realpath("__file__")) + "/tests/Matlab Code" oc.addpath(dir_path) def test_cascade(): objax.random.Generator(0) d = 2 # State dimenstion k = 1 # Controller's output dimension b = 100 horizon = 10 e = jnp.array( [[10.0]] ) # Max control input. Set too low can lead to Cholesky failures. # Training Dataset X0 = objax.random.uniform((b, d + k)) A = objax.random.uniform((d + k, d)) Y0 = jnp.sin(X0).dot(A) + 1e-3 * (objax.random.uniform((b, d)) - 0.5) pilco = PILCO((X0, Y0)) pilco.controller.max_action = e pilco.optimize_models(restarts=5) pilco.optimize_policy(restarts=5) # Generate input m = objax.random.uniform((1, d)) s = objax.random.uniform((d, d)) s = s.dot(s.T) # Make s positive semidefinite M, S, reward = pilco.predict(m, s, horizon) # convert data to the struct expected by the MATLAB implementation policy = oct2py.io.Struct() policy.p = oct2py.io.Struct() policy.p.w = np.array(pilco.controller.W) policy.p.b = np.array(pilco.controller.b).T policy.maxU = e # convert data to the struct expected by the MATLAB implementation lengthscales = np.stack( [np.array(model.kernel.lengthscale) for model in pilco.mgpr.models] ) variance = np.stack( [np.array(model.kernel.variance) for model in pilco.mgpr.models] ) noise = np.stack( [np.array(model.likelihood.variance) for model in pilco.mgpr.models] ) hyp = np.log( np.hstack((lengthscales, np.sqrt(variance[:, None]), np.sqrt(noise[:, None]))) ).T dynmodel = oct2py.io.Struct() dynmodel.hyp = hyp dynmodel.inputs = X0 dynmodel.targets = Y0 plant = oct2py.io.Struct() plant.angi = np.zeros(0) plant.angi = np.zeros(0) plant.poli = np.arange(d) + 1 plant.dyni = np.arange(d) + 1 plant.difi = np.arange(d) + 1 # Call function in octave M_mat, S_mat = oc.pred( policy, plant, dynmodel, m.T, s, horizon, nout=2, verbose=True ) # Extract only last element of the horizon M_mat = M_mat[:, -1] S_mat = S_mat[:, :, -1] assert jnp.allclose(M[0], M_mat, rtol=1e-2) assert jnp.allclose(S, S_mat, rtol=1e-2) if __name__ == "__main__": test_cascade()
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from flask import Blueprint, redirect, url_for from server.utils.core_utils import logger # Create Blueprint main = Blueprint("main", __name__) # redirect when you visit / @main.route("/") def index(): logger.info("Base redirect") return redirect(url_for('keys'))
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# Generated by Django 3.1.7 on 2021-03-07 06:43 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('api', '0002_auto_20210306_1136'), ] operations = [ migrations.AddField( model_name='group', name='post', field=models.ForeignKey(default=None, on_delete=django.db.models.deletion.CASCADE, related_name='group', to='api.post'), preserve_default=False, ), ]
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from .odefunc import (ODEnet, ODEfunc) from .cnf import CNF from .diffeq_layers import *
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import urllib, urllib2, json, time, os username = "username" #CHANGE password = "password" #CHANGE replicaURL = "feature service url/FeatureServer/createReplica" #CHANGE replicaLayers = [0] #CHANGE replicaName = "replicaTest" #CHANGE def sendRequest(request): response = urllib2.urlopen(request) readResponse = response.read() jsonResponse = json.loads(readResponse) return jsonResponse print("Generating token") url = "https://arcgis.com/sharing/rest/generateToken" data = {'username': username, 'password': password, 'referer': "https://www.arcgis.com", 'f': 'json'} request = urllib2.Request(url, urllib.urlencode(data)) jsonResponse = sendRequest(request) token = jsonResponse['token'] print("Creating the replica") data = {'f' : 'json', 'replicaName' : replicaName, 'layers' : replicaLayers, 'returnAttachments' : 'true', 'returnAttachmentsDatabyURL' : 'false', 'syncModel' : 'none', 'dataFormat' : 'filegdb', 'async' : 'true', 'token': token} request = urllib2.Request(replicaURL, urllib.urlencode(data)) jsonResponse = sendRequest(request) print(jsonResponse) print("Pinging the server") responseUrl = jsonResponse['statusUrl'] url = "{}?f=json&token={}".format(responseUrl, token) request = urllib2.Request(url) jsonResponse = sendRequest(request) while not jsonResponse.get("status") == "Completed": time.sleep(5) request = urllib2.Request(url) jsonResponse = sendRequest(request) userDownloads = os.environ['USERPROFILE'] + "\\Downloads" print("Downloading the replica. In case this fails note that the replica URL is: \n") jres = jsonResponse['resultUrl'] url = "{0}?token={1}".format(jres, token) print(url) f = urllib2.urlopen(url) with open(userDownloads + "\\" + os.path.basename(jres), "wb") as local_file: local_file.write(f.read()) print("\n Finished!")
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import re import textwrap import yaml from osc_trino_acl_dsl.dsl2rules import dsl_to_rules class Table(object): def __init__(self, catalog: str, schema: str, table: str): self.catalog: str = str(catalog) self.schema: str = str(schema) self.table: str = str(table) class User(object): def __init__(self, user: str, group): self.user = str(user) if type(group) == set: self.groups = set([str(e) for e in list(group)]) elif type(group) == list: self.groups = set([str(e) for e in group]) else: self.groups = set([str(group)]) def rule_matches(rule: dict, table: Table, user: User) -> bool: """emulates trino rule matching semantics""" if ("catalog" in rule) and (not re.fullmatch(rule["catalog"], table.catalog)): return False if ("schema" in rule) and (not re.fullmatch(rule["schema"], table.schema)): return False if ("table" in rule) and (not re.fullmatch(rule["table"], table.table)): return False if ("user" in rule) and (not re.fullmatch(rule["user"], user.user)): return False if "group" in rule: x = [e for e in list(user.groups) if re.fullmatch(rule["group"], e)] if len(x) == 0: return False return True def first_matching_rule(user: User, table: Table, rules: list) -> dict: for rule in rules: if rule_matches(rule, table, user): return rule return None def rule_permissions(user: User, table: Table, rules: dict) -> tuple: assert type(rules) == dict assert "catalogs" in rules assert "schemas" in rules assert "tables" in rules crule = first_matching_rule(user, table, rules["catalogs"]) assert type(crule) == dict assert "allow" in crule allow = crule["allow"] srule = first_matching_rule(user, table, rules["schemas"]) assert type(srule) == dict assert "owner" in srule owner = srule["owner"] trule = first_matching_rule(user, table, rules["tables"]) assert type(trule) == dict assert "privileges" in trule privs = trule["privileges"] return (allow, owner, privs) _admin = ["SELECT", "INSERT", "DELETE", "OWNERSHIP"] _public = ["SELECT"] def test_dsl_minimal(): # a minimal schema: declares one admin group, defaults public, and no other rules dsl = yaml.load( textwrap.dedent( """ admin: - group: admins public: true catalogs: [] schemas: [] tables: [] """ ), yaml.SafeLoader, ) rules = dsl_to_rules(dsl, validate=True) # test permissions of the admin group perms = rule_permissions(User("x", "admins"), Table("x", "x", "x"), rules) assert perms == ("all", True, _admin) # test permissions of generic user perms = rule_permissions(User("x", []), Table("x", "x", "x"), rules) assert perms == ("read-only", False, _public) def test_dsl_catalog(): dsl = yaml.load( textwrap.dedent( """ admin: - group: admins public: true catalogs: - catalog: dev public: false schemas: [] tables: [] """ ), yaml.SafeLoader, ) rules = dsl_to_rules(dsl, validate=True) # test permissions of the admin group perms = rule_permissions(User("x", "admins"), Table("x", "x", "x"), rules) assert perms == ("all", True, _admin) # test permissions of generic user and non-dev catalog (global default) perms = rule_permissions(User("x", []), Table("x", "x", "x"), rules) assert perms == ("read-only", False, _public) perms = rule_permissions(User("x", []), Table("dev", "x", "x"), rules) assert perms == ("read-only", False, []) def test_dsl_schema(): dsl = yaml.load( textwrap.dedent( """ admin: - group: admins public: true catalogs: - catalog: dev public: false schemas: - catalog: dev schema: proj1 admin: - group: devs - user: usery public: true tables: [] """ ), yaml.SafeLoader, ) rules = dsl_to_rules(dsl, validate=True) # test permissions of the admin group perms = rule_permissions(User("x", "admins"), Table("x", "x", "x"), rules) assert perms == ("all", True, _admin) # test permissions of generic user and non-dev catalog (global default) perms = rule_permissions(User("x", []), Table("x", "x", "x"), rules) assert perms == ("read-only", False, _public) # test permissions of the dev group on the dev catalog perms = rule_permissions(User("x", "devs"), Table("dev", "x", "x"), rules) assert perms == ("all", False, []) # devs have admin in proj1 schema for all tables perms = rule_permissions(User("x", "devs"), Table("dev", "proj1", "x"), rules) assert perms == ("all", True, _admin) perms = rule_permissions(User("usery", []), Table("dev", "proj1", "x"), rules) assert perms == ("all", True, _admin) # dev-catalog default is non-public (no privs) perms = rule_permissions(User("x", "nondev"), Table("dev", "x", "x"), rules) assert perms == ("read-only", False, []) # inside dev.proj1 schema tables default to public perms = rule_permissions(User("x", []), Table("dev", "proj1", "x"), rules) assert perms == ("read-only", False, _public) def test_dsl_table(): dsl = yaml.load( textwrap.dedent( """ admin: - group: admins public: true catalogs: - catalog: dev public: false schemas: - catalog: dev schema: proj1 admin: - group: devs - user: usery public: true tables: - catalog: dev schema: proj1 table: priv1 admin: - user: userz public: false """ ), yaml.SafeLoader, ) rules = dsl_to_rules(dsl, validate=True) # test permissions of the admin group perms = rule_permissions(User("x", "admins"), Table("x", "x", "x"), rules) assert perms == ("all", True, _admin) # global default should be readable perms = rule_permissions(User("x", []), Table("x", "x", "x"), rules) assert perms == ("read-only", False, _public) # dev catalog default should be non-public perms = rule_permissions(User("x", []), Table("dev", "x", "x"), rules) assert perms == ("read-only", False, []) # dev.proj1 schema default should be readable perms = rule_permissions(User("x", []), Table("dev", "proj1", "x"), rules) assert perms == ("read-only", False, _public) # dev.proj1.priv1 should default to non-public perms = rule_permissions(User("x", []), Table("dev", "proj1", "priv1"), rules) assert perms == ("read-only", False, []) # "usery" and "devs" group have schema admin: perms = rule_permissions(User("x", "devs"), Table("dev", "proj1", "x"), rules) assert perms == ("all", True, _admin) perms = rule_permissions(User("usery", []), Table("dev", "proj1", "x"), rules) assert perms == ("all", True, _admin) # userz added as table admin for priv1 perms = rule_permissions(User("userz", []), Table("dev", "proj1", "priv1"), rules) assert perms == ("all", False, _admin) # but userz is not admin for any other table in proj1 perms = rule_permissions(User("userz", []), Table("dev", "proj1", "x"), rules) assert perms == ("all", False, _public) def test_dsl_table_acl(): dsl = yaml.load( textwrap.dedent( """ admin: - group: admins public: true catalogs: - catalog: dev public: false schemas: - catalog: dev schema: proj1 admin: - group: devs - user: usery public: true tables: - catalog: dev schema: proj1 table: priv1 public: filter: - "population < 1000" hide: - column3 acl: - id: - user: usera - user: userb filter: - "country = 'london'" - "year < 2061" hide: - column1 - column2 """ ), yaml.SafeLoader, ) rules = dsl_to_rules(dsl, validate=True) # test permissions of the admin group perms = rule_permissions(User("x", "admins"), Table("x", "x", "x"), rules) assert perms == ("all", True, _admin) # global default should be readable perms = rule_permissions(User("x", []), Table("x", "x", "x"), rules) assert perms == ("read-only", False, _public) # dev catalog default should be non-public perms = rule_permissions(User("x", []), Table("dev", "x", "x"), rules) assert perms == ("read-only", False, []) # dev.proj1 schema default should be readable perms = rule_permissions(User("x", []), Table("dev", "proj1", "x"), rules) assert perms == ("read-only", False, _public) # "usery" and "devs" group have schema admin: perms = rule_permissions(User("x", "devs"), Table("dev", "proj1", "x"), rules) assert perms == ("all", True, _admin) perms = rule_permissions(User("usery", []), Table("dev", "proj1", "x"), rules) assert perms == ("all", True, _admin) for u in ["usera", "userb"]: perms = rule_permissions(User(u, []), Table("dev", "proj1", "priv1"), rules) assert perms == ("read-only", False, _public) r = first_matching_rule(User(u, []), Table("dev", "proj1", "priv1"), rules["tables"]) assert "filter" in r assert r["filter"] == "(country = 'london') and (year < 2061)" assert "columns" in r assert r["columns"] == [{"name": "column1", "allow": False}, {"name": "column2", "allow": False}] # dev.proj1.priv1 should default to public # but with additional row and column acl settings perms = rule_permissions(User("x", []), Table("dev", "proj1", "priv1"), rules) assert perms == ("read-only", False, _public) r = first_matching_rule(User("x", []), Table("dev", "proj1", "priv1"), rules["tables"]) assert "filter" in r assert r["filter"] == "(country = 'london') and (population < 1000) and (year < 2061)" assert "columns" in r assert r["columns"] == [ {"name": "column1", "allow": False}, {"name": "column2", "allow": False}, {"name": "column3", "allow": False}, ]
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import os from distutils.command.build import build from django.core import management from setuptools import find_packages, setup try: with open(os.path.join(os.path.dirname(__file__), 'README.rst'), encoding='utf-8') as f: long_description = f.read() except: long_description = '' class CustomBuild(build): def run(self): management.call_command('compilemessages', verbosity=1) build.run(self) cmdclass = { 'build': CustomBuild } setup( name='byro-cnss', version='0.0.1', description='Byro plugin for CNSS (Clausewitz-Netzwerk für Strategische Studien e.V.)', long_description=long_description, url='https://github.com/henryk/byro-cnss', author='Henryk Plötz', author_email='henryk@ploetzli.ch', license='Apache Software License', install_requires=[], packages=find_packages(exclude=['tests', 'tests.*']), include_package_data=True, cmdclass=cmdclass, entry_points=""" [byro.plugin] byro_cnss=byro_cnss:ByroPluginMeta """, )
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# Copyright 2018, The TensorFlow Federated Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np import tensorflow as tf from utils import tensor_utils class TensorUtilsTest(tf.test.TestCase): def test_zero_all_if_any_non_finite(self): def expect_ok(structure): with tf.Graph().as_default(): result, error = tensor_utils.zero_all_if_any_non_finite(structure) with self.session() as sess: result, error = sess.run((result, error)) try: tf.nest.map_structure(np.testing.assert_allclose, result, structure) except AssertionError: self.fail('Expected to get input {} back, but instead got {}'.format( structure, result)) self.assertEqual(error, 0) expect_ok([]) expect_ok([(), {}]) expect_ok(1.1) expect_ok([1.0, 0.0]) expect_ok([1.0, 2.0, {'a': 0.0, 'b': -3.0}]) def expect_zeros(structure, expected): with tf.Graph().as_default(): result, error = tensor_utils.zero_all_if_any_non_finite(structure) with self.session() as sess: result, error = sess.run((result, error)) try: tf.nest.map_structure(np.testing.assert_allclose, result, expected) except AssertionError: self.fail('Expected to get zeros, but instead got {}'.format(result)) self.assertEqual(error, 1) expect_zeros(np.inf, 0.0) expect_zeros((1.0, (2.0, np.nan)), (0.0, (0.0, 0.0))) expect_zeros((1.0, (2.0, { 'a': 3.0, 'b': [[np.inf], [np.nan]] })), (0.0, (0.0, { 'a': 0.0, 'b': [[0.0], [0.0]] }))) if __name__ == '__main__': tf.test.main()
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#!/usr/bin/env python3 import logging.handlers import sys from sys import argv, modules from os.path import join from autonmap import cron_scheduler from autonmap import launch_client from autonmap import launch_server from autonmap.server import server_config as sconfig """ This module allows autonmap to interact with the server and client process to preform the tasks each is assigned. """ LOG_FILE = "/tmp/autonmap.log" LOGGING_LEVEL = logging.INFO logger = logging.getLogger(__name__) logger.setLevel(LOGGING_LEVEL) handler = logging.handlers.TimedRotatingFileHandler(LOG_FILE, when='midnight', backupCount=3) formatter = logging.Formatter('%(asctime)s %(levelname)-8s %(message)s') handler.setFormatter(formatter) logger.addHandler(handler) class Log(object): def __init__(self, log, level): self.logger = log self.level = level def write(self, message): if message.rstrip() != "": self.logger.log(self.level, message.rstrip()) def flush(self): pass def main(): """ Main routine :return: None """ if len(argv) > 1: print("Automated nMap Server/Client Manager") if argv[1] == 'cron': cron_scheduler.main() elif argv[1] == "update": if len(argv) == 3: file_location = join(sconfig.get_base(), "work.txt") if str(argv[2]).lower() == "delete": with open(file_location, "w") as file: pass # This empties the file of all contents else: with open(argv[2], "r") as infile: with open(file_location, "w+") as outfile: subnets = set() for in_line in infile: subnets.add(in_line) for out_line in outfile: subnets.add(out_line) outfile.seek(0) outfile.truncate() for item in subnets: outfile.write("{}\n".format(item)) elif len(argv) == 3: if argv[2] in ['start', 'stop', 'update', 'report']: if argv[1] == 'server': sys.stdout = Log(log=logger, level=logging.INFO) sys.stderr = Log(log=logger, level=logging.ERROR) launch_server.main(argv[2]) elif argv[1] == 'client': sys.stdout = Log(log=logger, level=logging.INFO) sys.stderr = Log(log=logger, level=logging.ERROR) launch_client.main(argv[2]) else: print("Invalid arguments") else: print("Invalid arguments") else: print("Usage: {} {} {}".format("python3 -m autonmap", "client|server|update", "start<client>|stop|report|update|" "location<update>|delete<update>")) print("Usage: {} {}".format("python3 -m autonmap", "cron")) print("\t{} {}".format("python3 -m autonmap", "update ~/workfile.txt")) print("Client script is located at: \n\t\t{}".format(modules[launch_client.__name__])) print("The log is located in /tmp/autonmap.log") if __name__ == "__main__": main()
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# import random # from typing import List, Dict import numpy as np # import matplotlib.pyplot as plt def get_info() -> dict: """ This controls your Battlesnake appearance and author permissions. For customization options, see https://docs.battlesnake.com/references/personalization TIP: If you open your Battlesnake URL in browser you should see this data. """ return { "apiversion": "1", "author": "Mex", # TODO: Your Battlesnake Username "color": "#888889", # TODO: Personalize "head": "silly", # TODO: Personalize "tail": "curled", # TODO: Personalize } # Globals food_weight = 9 snake_weight = -9 snake_head_weight = -2 wall_weight = -9 board_centre = 1 board_x = None board_y = None def gkern(l=10, scale=4): """\ creates gaussian kernel with side length `l` and a sigma of `sig` """ sig = (l-1)/3 ax = np.linspace(-(l - 1) / 2., (l - 1) / 2., l) gauss = np.exp(-0.5 * np.square(ax) / np.square(sig)) kernel = np.outer(gauss, gauss) return scale * kernel / np.max(kernel) def centre_grad(data: dict) -> np.array: board_w = data["board"]["width"] board_h = data["board"]["height"] gradient_board = gkern(max(board_w, board_h), board_centre) return gradient_board def populate_food(board: np.array, data: dict): for food in data['board']['food']: food_x, food_y = food['x'], food['y'] kern_size = max(board.shape[0], board.shape[1]) kernel = gkern(kern_size*2 + 1, 1) mid = kern_size + 1 x_min = mid - food_x x_max = mid + board.shape[0] - food_x y_min = mid - food_y y_max = mid + board.shape[0] - food_y board += kernel[x_min:x_max, y_min:y_max]*food_weight def populate_other_snakes(board: np.array, data: dict): for snake in data['board']['snakes']: snake_body = snake['body'] for ele in snake_body: if ele == snake['head']: if ele == data['you']['head']: board[ele['x'], ele['y']] = snake_weight elif snake['length'] < data['you']['length']: continue else: board[ele['x'], ele['y']] = snake_weight # direction snake head can go are dangerous board[ele['x'] + 1, ele['y']] += snake_head_weight board[ele['x'] - 1, ele['y']] += snake_head_weight board[ele['x'], ele['y'] + 1] += snake_head_weight board[ele['x'], ele['y'] - 1] += snake_head_weight else: board[ele['x'], ele['y']] = snake_weight def follow_global_max(head: dict, board: np.array) -> str: global_max = np.unravel_index(np.argmax(board), board.shape) directions = { "up": (0,1), "down": (0,-1), "left": (-1,0), "right": (1,0) } direction = "" distance = 10000 for item in directions.items(): curr_dist = (head['x'] + item[1][0] - global_max[0])**2 + (head['y'] + item[1][1] - global_max[1])**2 print(curr_dist, item[0]) if curr_dist < distance: distance = curr_dist direction = item[0] return direction def follow_grad(head: dict, board: np.array) -> str: directions = { "up": (0,1), "down": (0,-1), "left": (-1,0), "right": (1,0) } direction = "" max_score = 0 for item in directions.items(): curr_score = board[head['x'] + item[1][0] + 1, head['y'] + item[1][1] + 1] if curr_score > max_score: max_score = curr_score direction = item[0] return direction def choose_move(data: dict) -> str: board_y = data['board']['height'] board_x = data['board']['width'] board = centre_grad(data) # print(f'GRADIENT ARRAY: {array_of_arrays}') populate_other_snakes(board, data) board = np.pad(board, 1, 'constant', constant_values=wall_weight) populate_food(board, data) direction = follow_global_max(data['you']['head'], board) # direction = follow_grad(array_of_arrays) print(f'GOING THIS DIRECTION: {direction}') return direction data = { "turn": 14, "board": { "height": 11, "width": 11, "food": [ {"x": 5, "y": 5}, {"x": 9, "y": 0}, {"x": 2, "y": 6} ], "hazards": [ {"x": 3, "y": 2} ], "snakes": [ { "id": "snake-508e96ac-94ad-11ea-bb37", "name": "My Snake", "health": 54, "body": [ {"x": 0, "y": 0}, {"x": 1, "y": 0}, {"x": 2, "y": 0} ], "latency": "111", "head": {"x": 0, "y": 0}, "length": 3, "shout": "why are we shouting??", "squad": "", "customizations":{ "color":"#FF0000", "head":"pixel", "tail":"pixel" } }, { "id": "snake-b67f4906-94ae-11ea-bb37", "name": "Another Snake", "health": 16, "body": [ {"x": 5, "y": 4}, {"x": 5, "y": 3}, {"x": 6, "y": 3}, {"x": 6, "y": 2} ], "latency": "222", "head": {"x": 5, "y": 4}, "length": 4, "shout": "I'm not really sure...", "squad": "", "customizations":{ "color":"#26CF04", "head":"silly", "tail":"curled" } } ] }, "you": { "id": "snake-508e96ac-94ad-11ea-bb37", "name": "My Snake", "health": 54, "body": [ {"x": 0, "y": 0}, {"x": 1, "y": 0}, {"x": 2, "y": 0} ], "latency": "111", "head": {"x": 0, "y": 0}, "length": 3, "shout": "why are we shouting??", "squad": "", "customizations":{ "color":"#FF0000", "head":"pixel", "tail":"pixel" } } } if False: board = centre_grad(data) board_x, board_y = 11, 11 populate_other_snakes(board, data) populate_food(board, data) board = np.pad(board, 1, 'constant', constant_values=snake_weight) # plt.imshow(np.rot90(np.fliplr(board)), interpolation='none', origin="lower") # plt.show()
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import os import sys from dataclasses import dataclass, field from typing import List, Set, Optional from nuclear.builder.rule import PrimaryOptionRule, ParameterRule, FlagRule, CliRule, SubcommandRule, \ PositionalArgumentRule, ManyArgumentsRule, DictionaryRule, ValueRule from nuclear.parser.context import RunContext from nuclear.parser.keyword import format_var_names, format_var_name from nuclear.parser.parser import Parser from nuclear.parser.transform import filter_rules from nuclear.parser.value import generate_value_choices from nuclear.version import __version__ @dataclass class _OptionHelp(object): cmd: str help: str parent: '_OptionHelp' = None rule: SubcommandRule = None subrules: List[CliRule] = field(default_factory=lambda: []) internal_options = {'--autocomplete', '--install-bash', '--install-autocomplete'} def print_help(rules: List[CliRule], app_name: str, version: str, help: str, subargs: List[str], hide_internal: bool): helps = generate_help(rules, app_name, version, help, subargs, hide_internal) print('\n'.join(helps)) def print_usage(rules: List[CliRule]): all_rules, available_subcommands, precommands = help_context(rules, []) pos_arguments = filter_rules(all_rules, PositionalArgumentRule) many_args = filter_rules(all_rules, ManyArgumentsRule) has_commands = bool(filter_rules(available_subcommands, SubcommandRule)) command_name = shell_command_name() app_bin_prefix = ' '.join([command_name] + precommands) usage = generate_usage(app_bin_prefix, has_commands, have_rules_options(all_rules), many_args, pos_arguments) how_to_help = f'Run "{command_name} --help" for more information.' print('\n'.join([f'Usage: {usage}', how_to_help])) def generate_help(rules: List[CliRule], app_name: str, version: str, help: str, subargs: List[str], hide_internal: bool) -> List[str]: all_rules, available_subcommands, precommands = help_context(rules, subargs) return generate_subcommand_help(all_rules, app_name, version, help, precommands, available_subcommands, hide_internal) def help_context(rules, subargs): available_subcommands = filter_rules(rules, SubcommandRule) run_context: Optional[RunContext] = Parser(rules, dry=True).parse_args(subargs) all_rules: List[CliRule] = run_context.active_rules active_subcommands: List[SubcommandRule] = run_context.active_subcommands precommands: List[str] = [_subcommand_short_name(rule) for rule in active_subcommands] if active_subcommands: available_subcommands = filter_rules(active_subcommands[-1].subrules, SubcommandRule) return all_rules, available_subcommands, precommands def generate_subcommand_help( all_rules: List[CliRule], app_name: str, version: str, help: str, precommands: List[str], subcommands: List[SubcommandRule], hide_internal: bool, ) -> List[str]: pos_arguments = filter_rules(all_rules, PositionalArgumentRule) many_args = filter_rules(all_rules, ManyArgumentsRule) pos_args_helps: List[_OptionHelp] = _generate_pos_args_helps(pos_arguments, many_args) options: List[_OptionHelp] = _generate_options_helps(all_rules, hide_internal) commands: List[_OptionHelp] = _generate_commands_helps(subcommands) out = [] app_info = app_help_info(app_name, help, version) if app_info: out.append(app_info + '\n') app_bin_prefix = ' '.join([shell_command_name()] + precommands) out.append('Usage:') out.append(generate_usage(app_bin_prefix, bool(commands), have_rules_options(all_rules), many_args, pos_arguments)) if pos_args_helps: out.append('\nArguments:') __helpers_output(pos_args_helps, out) if options: out.append('\nOptions:') __helpers_output(options, out) if commands: out.append('\nCommands:') __helpers_output(commands, out) out.append(f'\nRun "{app_bin_prefix} COMMAND --help" for more information on a command.') return out def app_help_info(app_name: str, help: str, version: str) -> Optional[str]: info = app_name_version(app_name, version) return ' - '.join(filter(bool, [info, help])) def app_name_version(app_name, version): infos = [] if app_name: infos += [app_name] if version: version = _normalized_version(version) infos += [version] if infos: infos += [f'(nuclear v{__version__})'] return ' '.join(infos) def generate_usage(app_bin_prefix, has_commands: bool, has_options: bool, many_args, pos_arguments) -> str: usage_syntax: str = app_bin_prefix if has_commands: usage_syntax += ' [COMMAND]' if has_options: usage_syntax += ' [OPTIONS]' usage_syntax += usage_positional_arguments(pos_arguments) usage_syntax += usage_many_arguments(many_args) return usage_syntax def __helpers_output(commands, out): padding = _max_name_width(commands) for helper in commands: name_padded = helper.cmd.ljust(padding) if helper.help: for idx, line in enumerate(helper.help.splitlines()): if idx == 0: out.append(f' {name_padded} - {line}') else: out.append(' ' * (2 + padding + 3) + line) else: out.append(f' {name_padded}') def print_version(app_name: str, version: str): print(app_name_version(app_name, version)) def _normalized_version(version: str) -> str: if version.startswith('v'): return version return f'v{version}' def _max_name_width(helps: List[_OptionHelp]) -> int: return max(map(lambda h: len(h.cmd), helps)) def _generate_pos_args_helps( pos_arguments: List[PositionalArgumentRule], many_args: List[ManyArgumentsRule] ) -> List[_OptionHelp]: return [_pos_arg_help(rule) for rule in pos_arguments] + \ [_many_args_help(rule) for rule in many_args] def _generate_options_helps(rules: List[CliRule], hide_internal: bool) -> List[_OptionHelp]: # filter non-empty return list(filter(lambda o: o, [_generate_option_help(rule, hide_internal) for rule in rules])) def _generate_option_help(rule: CliRule, hide_internal: bool) -> Optional[_OptionHelp]: if isinstance(rule, PrimaryOptionRule): return _primary_option_help(rule, hide_internal) elif isinstance(rule, FlagRule): return _flag_help(rule) elif isinstance(rule, ParameterRule): return _parameter_help(rule) elif isinstance(rule, DictionaryRule): return _dictionary_help(rule) return None def _generate_commands_helps(rules: List[CliRule], parent: _OptionHelp = None, subrules: List[CliRule] = None ) -> List[_OptionHelp]: commands: List[_OptionHelp] = [] for rule in filter_rules(rules, SubcommandRule): subsubrules = (subrules or []) + rule.subrules helper = _subcommand_help(rule, parent, subsubrules) if rule.run or rule.help: commands.append(helper) commands.extend(_generate_commands_helps(rule.subrules, helper, subsubrules)) return commands def _subcommand_help(rule: SubcommandRule, parent: _OptionHelp, subrules: List[CliRule]) -> _OptionHelp: pos_args = filter_rules(subrules, PositionalArgumentRule) many_args = filter_rules(subrules, ManyArgumentsRule) cmd = _subcommand_prefix(parent) + '|'.join(sorted_keywords(rule.keywords)) cmd += usage_positional_arguments(pos_args) cmd += usage_many_arguments(many_args) return _OptionHelp(cmd, rule.help, parent=parent, rule=rule, subrules=subrules) def _subcommand_prefix(helper: _OptionHelp) -> str: if not helper: return '' return _subcommand_prefix(helper.parent) + '|'.join(sorted_keywords(helper.rule.keywords)) + ' ' def _primary_option_help(rule: PrimaryOptionRule, hide_internal: bool) -> Optional[_OptionHelp]: if hide_internal: for keyword in rule.keywords: if keyword in internal_options: return None cmd = ', '.join(sorted_keywords(rule.keywords)) pos_args = filter_rules(rule.subrules, PositionalArgumentRule) all_args = filter_rules(rule.subrules, ManyArgumentsRule) cmd += usage_positional_arguments(pos_args) cmd += usage_many_arguments(all_args) return _OptionHelp(cmd, rule.help) def _flag_help(rule: FlagRule) -> _OptionHelp: cmd = ', '.join(sorted_keywords(rule.keywords)) return _OptionHelp(cmd, rule.help) def _parameter_help(rule: ParameterRule) -> _OptionHelp: cmd = ', '.join(sorted_keywords(rule.keywords)) + ' ' + _param_display_name(rule) default_value = display_default_value(rule.default) choices_help = display_choices_help(rule) help_text = join_nonempty_lines(rule.help, default_value, choices_help) return _OptionHelp(cmd, help_text) def _dictionary_help(rule: DictionaryRule) -> _OptionHelp: cmd = ', '.join(sorted_keywords(rule.keywords)) + ' KEY VALUE' return _OptionHelp(cmd, rule.help) def _pos_arg_help(rule: PositionalArgumentRule) -> _OptionHelp: cmd = display_positional_argument(rule) default_value = display_default_value(rule.default) choices_help = display_choices_help(rule) help_text = join_nonempty_lines(rule.help, default_value, choices_help) return _OptionHelp(cmd, help_text) def _many_args_help(rule: ManyArgumentsRule) -> _OptionHelp: cmd = display_many_arguments(rule) choices_help = display_choices_help(rule) help_text = join_nonempty_lines(rule.help, choices_help) return _OptionHelp(cmd, help_text) def _param_display_name(rule: ParameterRule) -> str: if rule.name: return format_var_name(rule.name).upper() else: # get name from the longest keyword names: Set[str] = format_var_names(rule.keywords) return max(names, key=lambda n: len(n)).upper() def _argument_var_name(rule: PositionalArgumentRule) -> str: return format_var_name(rule.name).upper() def _subcommand_short_name(rule: SubcommandRule) -> str: return next(iter(rule.keywords)) def sorted_keywords(keywords: Set[str]) -> List[str]: # shortest keywords first, then alphabetically return sorted(keywords, key=lambda k: (len(k), k)) def display_positional_argument(rule: PositionalArgumentRule) -> str: var_name = _argument_var_name(rule) if rule.required: return f' {var_name}' else: return f' [{var_name}]' def display_many_arguments(rule: ManyArgumentsRule) -> str: arg_name = rule.name.upper() if rule.count_min(): return f' {arg_name}...' else: return f' [{arg_name}...]' def usage_positional_arguments(rules: List[PositionalArgumentRule]) -> str: return ''.join([display_positional_argument(rule) for rule in rules]) def usage_many_arguments(rules: List[ManyArgumentsRule]) -> str: return ''.join([display_many_arguments(rule) for rule in rules]) def shell_command_name(): _, command = os.path.split(sys.argv[0]) if command == '__main__.py': return sys.modules['__main__'].__package__ return command def have_rules_options(rules: List[CliRule]) -> bool: return bool(filter_rules(rules, FlagRule, ParameterRule, DictionaryRule, PrimaryOptionRule)) def display_default_value(default) -> Optional[str]: if default is None: return None return 'Default: ' + str(default) def display_choices_help(rule: ValueRule) -> Optional[str]: choices = generate_value_choices(rule) if not choices or not rule.strict_choices: return None return 'Choices: ' + ', '.join(choices) def join_nonempty_lines(*lines: str) -> str: return '\n'.join(filter(lambda t: t is not None, lines))
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#The MIT License (MIT) # #Copyright (c) 2015 Geoffroy Givry # #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. import nuke LookAtName = "LookAt" def panelLookAt(): p = nuke.Panel("Look At Panel") p.addSingleLineInput("LookAt Name:", LookAtName) p.addButton("Cancel") p.addButton("OK") result = p.show() nameLookAt = p.value("LookAt Name:") EXpX = 'degrees(atan2(%s.translate.y-translate.y,sqrt(pow(%s.translate.x-translate.x,2)+pow(%s.translate.z-translate.z,2))))' % (nameLookAt, nameLookAt, nameLookAt) EXpY = '%s.translate.z-this.translate.z >= 0 ? 180+degrees(atan2(%s.translate.x-translate.x,%s.translate.z-translate.z)):180+degrees(atan2(%s.translate.x-translate.x,%s.translate.z-translate.z))' % (nameLookAt, nameLookAt, nameLookAt, nameLookAt, nameLookAt) nuke.nodes.Axis(name=nameLookAt) for n in nuke.selectedNodes(): n['rotate'].setExpression(EXpX, 0) n['rotate'].setExpression(EXpY, 1)
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""" `main` is the top level module where AppEngine gets access to your Flask application. """ from app import create_app from config import config from os import environ if environ['SERVER_SOFTWARE'].startswith('Development'): app_config = config['development'] else: app_config = config['production'] app = create_app(app_config) # Note: We don't need to call run() since our application is # embedded within the App Engine WSGI application server.
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