Python math.ceil函数代码示例

def is_converged(hartree_parameters, structure, return_values=False):
    filename = s_name(structure) + ".conv_res"
    to_return = {}
    try:
        f = open(filename, mode='r')
        conv_res = ast.literal_eval(f.read())
        f.close()
        converged = True if True in conv_res['control'].values() else False
    except (IOError, OSError, ValueError):
        if return_values:
            print('Inputfile ', filename, ' not found, the convergence calculation did not finish properly' \
                                          ' or was not parsed ...')
        converged = False
        return converged
    if return_values and converged:
        if hartree_parameters:
            try:
                conv_res['values']['ecut'] = 4 * math.ceil(conv_res['values']['ecut'] * eV_to_Ha / 4)
            except (KeyError, ArithmeticError, FloatingPointError, SyntaxError):
                pass
            try:
                conv_res['values']['ecuteps'] = 4 * math.ceil(conv_res['values']['ecuteps'] * eV_to_Ha / 4)
            except (KeyError, ArithmeticError, FloatingPointError, SyntaxError):
                pass
        for k in conv_res['values'].keys():
            if conv_res['values'][k] != 0 and conv_res['values'][k] != np.inf:
                to_return.update({k: conv_res['values'][k]})
        return to_return
    else:
        return converged

 def sharkeventkinshnavaw(self, a_ship, a_screen):
     randnum = random.randint(1, 10)
     if randnum < 10:
         self.mess = "What were you thinking? The king shark sees all in the seas, nothing escapes it's sight"
         self.mess += "What would you order your crew to do? The shark is still attacking."
         messobj = StrObj.render(self.mess[0:33], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 5))
         messobj = StrObj.render(self.mess[33:68], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 25))
         messobj = StrObj.render(self.mess[69:87], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 45))
         messobj = StrObj.render(self.mess[87:113], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 65))
         messobj = StrObj.render(self.mess[113:143], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 85))
         messobj = StrObj.render(self.mess[144:], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 105))
         randnum = random.randint(0, 9)
         a_ship.ShipHp -= int(math.ceil(randnum * .55))
         a_ship.CrewHp -= int(math.ceil(randnum * .45))
         self.MenuOp.initshkinafternavawf(170)
         self.MenuOp.drawmen(a_screen, 0)
     else:
         self.mess = "Impossible! The king shark did not see us! The fates must be asleep."
         messobj = StrObj.render(self.mess[0:35], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 5))
         messobj = StrObj.render(self.mess[35:], 1, (0, 0, 0))
         a_screen.blit(messobj, (self.xpos, 25))

def _download(url):
    """
    Do a wget: Download the file specified in url to the cwd.
    Return the filename.
    """
    filename = os.path.split(url)[1]
    req = requests.get(url, stream=True, headers={'User-Agent': 'PyBOMBS'})
    filesize = float(req.headers['content-length'])
    filesize_dl = 0
    with open(filename, "wb") as f:
        for buff in req.iter_content(chunk_size=8192):
            if buff:
                f.write(buff)
                filesize_dl += len(buff)
            # TODO wrap this into an output processor or at least
            # standardize the progress bars we use
            status = r"%05d kB / %05d kB (%03d%%)" % (
                    int(math.ceil(filesize_dl/1000.)),
                    int(math.ceil(filesize/1000.)),
                    int(math.ceil(filesize_dl*100.)/filesize)
            )
            status += chr(8)*(len(status)+1)
            sys.stdout.write(status)
    sys.stdout.write("\n")
    return filename

    def SetValue(self, value):
        """ Sets the FloatSpin value. """

        if not self._textctrl or not self.InRange(value):
            return

        if self._snapticks and self._increment != 0.0:

            finite, snap_value = self.IsFinite(value)

            if not finite: # FIXME What To Do About A Failure?

                if (snap_value - floor(snap_value) < ceil(snap_value) - snap_value):
                    value = self._defaultvalue + floor(snap_value)*self._increment
                else:
                    value = self._defaultvalue + ceil(snap_value)*self._increment

        strs = ("%100." + str(self._digits) + self._textformat[1])%value
        strs = strs.strip()
        strs = self.ReplaceDoubleZero(strs)

        if value != self._value or strs != self._textctrl.GetValue():

            self._textctrl.SetValue(strs)
            self._textctrl.DiscardEdits()
            self._value = value

    def __init__(self, n, n_iter=3, train_size=.5, test_size=None,
                 random_state=None, n_bootstraps=None):
        self.n = n
        if n_bootstraps is not None:  # pragma: no cover
            warnings.warn("n_bootstraps was renamed to n_iter and will "
                          "be removed in 0.16.", DeprecationWarning)
            n_iter = n_bootstraps
        self.n_iter = n_iter
        if (isinstance(train_size, numbers.Real) and train_size >= 0.0
                and train_size <= 1.0):
            self.train_size = int(ceil(train_size * n))
        elif isinstance(train_size, numbers.Integral):
            self.train_size = train_size
        else:
            raise ValueError("Invalid value for train_size: %r" %
                             train_size)
        if self.train_size > n:
            raise ValueError("train_size=%d should not be larger than n=%d" %
                             (self.train_size, n))

        if isinstance(test_size, numbers.Real) and 0.0 <= test_size <= 1.0:
            self.test_size = int(ceil(test_size * n))
        elif isinstance(test_size, numbers.Integral):
            self.test_size = test_size
        elif test_size is None:
            self.test_size = self.n - self.train_size
        else:
            raise ValueError("Invalid value for test_size: %r" % test_size)
        if self.test_size > n:
            raise ValueError("test_size=%d should not be larger than n=%d" %
                             (self.test_size, n))

        self.random_state = random_state

def NNI(dir):
    All  = os.listdir(dir)
    NumL = [int(I[0:-4]) for I in All]
    n = len(All)
    if n < 32:
        Ext = [int(math.ceil(x*32./n)) for x in NumL]
        for i in range(n):
            os.rename(os.path.join(dir, All[i]), os.path.join(dir,'__' + str(Ext[i]) + '.png'))
        for i in range(n):
            os.rename(os.path.join(dir, '__' + str(Ext[i]) + '.png'), os.path.join(dir, str(Ext[i]) + '.png'))
        Dif = list(set(range(1,33)).difference(set(Ext)))
        Dif.sort()
        Ext.sort()
        for i in Dif:
            item = [x>i for x in Ext].index(True)
            obj  = Ext[item]
            os.system('cp '+os.path.join(dir,str(obj)+'.png')+' '+os.path.join(dir,str(i)+'.png'))
    elif n > 32:
        Ext = [int(math.ceil(x*n/32.)) for x in range(1,33)]
        m = len(Ext)
        Dif = list(set(NumL).difference(set(Ext)))
        Dif.sort()
        Ext.sort()
        for i in Dif:
            os.remove(os.path.join(dir, str(i) + '.png'))
        for i in range(m):
            os.rename(os.path.join(dir, str(Ext[i]) + '.png'),os.path.join(dir, '__'+str(i+1) + '.png'))
        for i in range(m):
            os.rename(os.path.join(dir, '__'+str(i+1) + '.png'),os.path.join(dir, str(i+1) + '.png'))

 def setAppearance(self):
     """
     A setter for the appearance of the tower.
     """
     self.towerDiv = avg.DivNode(size=util.towerDivSize, pos=(self.pos.x - util.towerDivSize[0]//2, self.pos.y-util.towerDivSize[1]//2))
     
     #sets the explosion radius
     self.towerCircle = avg.CircleNode(fillopacity=0.3, strokewidth=0, fillcolor=self.team.color, r=self.towerDiv.size.x//2, pos=(self.towerDiv.size.x//2,self.towerDiv.size.y//2), parent=self.towerDiv)
     
     
     #sets the fancy snow balls
     
     for i in xrange(5):
         radius = self.towerDiv.size[0]//10
         xPos = random.randint(0 + math.floor(radius), math.ceil(self.towerDiv.size.x - radius))
         yPos = random.randint(0 + math.floor(radius), math.ceil(self.towerDiv.size.y - radius))
         
         snowball = avg.CircleNode(fillopacity=0.5, strokewidth=0, filltexhref=os.path.join(getMediaDir(__file__, "resources"), "snowflakes.png"), r=radius, pos=(xPos,yPos), parent=self.towerDiv)
         
         self.snowballAnim(xPos,yPos,snowball)
         
     
     self.tower = avg.RectNode(fillopacity=1, strokewidth=0, size=util.towerSize, pos=(self.pos.x  - util.towerSize[0] // 2, self.pos.y - util.towerSize[1] // 2))
     
     
     if self.team.name == "Team2":
         self.tower.filltexhref = os.path.join(getMediaDir(__file__, "resources"), "iceball.png")
     else:
         self.tower.filltexhref = os.path.join(getMediaDir(__file__, "resources"), "iceball.png")

    def testFloor(self):
        self.assertRaises(TypeError, math.floor)
        # These types will be int in py3k.
        self.assertEquals(float, type(math.floor(1)))
        self.assertEquals(float, type(math.floor(1L)))
        self.assertEquals(float, type(math.floor(1.0)))
        self.ftest('floor(0.5)', math.floor(0.5), 0)
        self.ftest('floor(1.0)', math.floor(1.0), 1)
        self.ftest('floor(1.5)', math.floor(1.5), 1)
        self.ftest('floor(-0.5)', math.floor(-0.5), -1)
        self.ftest('floor(-1.0)', math.floor(-1.0), -1)
        self.ftest('floor(-1.5)', math.floor(-1.5), -2)
        # pow() relies on floor() to check for integers
        # This fails on some platforms - so check it here
        self.ftest('floor(1.23e167)', math.floor(1.23e167), 1.23e167)
        self.ftest('floor(-1.23e167)', math.floor(-1.23e167), -1.23e167)
        self.assertEquals(math.ceil(INF), INF)
        self.assertEquals(math.ceil(NINF), NINF)
        self.assert_(math.isnan(math.floor(NAN)))

        class TestFloor(object):
            def __float__(self):
                return 42.3
        class TestNoFloor(object):
            pass
        self.ftest('floor(TestFloor())', math.floor(TestFloor()), 42)
        self.assertRaises(TypeError, math.floor, TestNoFloor())

        t = TestNoFloor()
        t.__floor__ = lambda *args: args
        self.assertRaises(TypeError, math.floor, t)
        self.assertRaises(TypeError, math.floor, t, 0)

 def readEgg(self,filename):
     """ reads the egg file and stores the info"""
     egg = EggData()
     egg.read(filename)
     for char in getAllEggGroup(egg):
         name = str(char.getName())
         
         image = Image()
         image.name = name
         self.images[name] = image 
         
         pos = char.getComponentVec3(0)
         
         for p in getAllType(char,EggPolygon):     
                  
             if p.getNumVertices() > 2:
                 v = p.getVertex(2)
                 vpos = v.getPos3()-pos
                 image.x = pos.getX()
                 image.y = pos.getZ()
                 image.w = vpos.getX()
                 image.h = vpos.getZ()
                 
             for l in getAllType(char,EggPoint):
                 extend = l.getVertex(0).getPos3()-pos
                 image.extend = math.ceil(extend.getX()),math.ceil(extend.getZ())

    def gaussian_smear(self, r):
        """
        Applies an isotropic Gaussian smear of width (standard deviation) r to the potential field. This is necessary to
        avoid finding paths through narrow minima or nodes that may exist in the field (although any potential or
        charge distribution generated from GGA should be relatively smooth anyway). The smearing obeys periodic
        boundary conditions at the edges of the cell.

        :param r - Smearing width in cartesian coordinates, in the same units as the structure lattice vectors
        """
        # Since scaling factor in fractional coords is not isotropic, have to have different radii in 3 directions
        a_lat = self.__s.lattice.a
        b_lat = self.__s.lattice.b
        c_lat = self.__s.lattice.c

        # Conversion factors for discretization of v
        v_dim = self.__v.shape
        r_frac = (r / a_lat, r / b_lat, r / c_lat)
        r_disc = (int(math.ceil(r_frac[0] * v_dim[0])), int(math.ceil(r_frac[1] * v_dim[1])),
                  int(math.ceil(r_frac[2] * v_dim[2])))

        # Apply smearing
        # Gaussian filter
        gauss_dist = np.zeros((r_disc[0] * 4 + 1, r_disc[1] * 4 + 1, r_disc[2] * 4 + 1))
        for g_a in np.arange(-2.0 * r_disc[0], 2.0 * r_disc[0] + 1, 1.0):
            for g_b in np.arange(-2.0 * r_disc[1], 2.0 * r_disc[1] + 1, 1.0):
                for g_c in np.arange(-2.0 * r_disc[2], 2.0 * r_disc[2] + 1, 1.0):
                    g = np.array([g_a / v_dim[0], g_b / v_dim[1], g_c / v_dim[2]]).T
                    gauss_dist[int(g_a + r_disc[0])][int(g_b + r_disc[1])][int(g_c + r_disc[2])] = la.norm(np.dot(self.__s.lattice.matrix, g))/r
        gauss = scipy.stats.norm.pdf(gauss_dist)
        gauss = gauss/np.sum(gauss, dtype=float)
        padded_v = np.pad(self.__v, ((r_disc[0], r_disc[0]), (r_disc[1], r_disc[1]), (r_disc[2], r_disc[2])), mode='wrap')
        smeared_v = scipy.signal.convolve(padded_v, gauss, mode='valid')
        self.__v = smeared_v

 def __setAccountsAttrs(self, isPremiumAccount, premiumExpiryTime = 0):
     disableTTHeader = ''
     disableTTBody = ''
     isNavigationEnabled = True
     if self.prbDispatcher:
         isNavigationEnabled = not self.prbDispatcher.getFunctionalState().isNavigationDisabled()
     if isPremiumAccount:
         if not premiumExpiryTime > 0:
             raise AssertionError
             deltaInSeconds = float(time_utils.getTimeDeltaFromNow(time_utils.makeLocalServerTime(premiumExpiryTime)))
             if deltaInSeconds > time_utils.ONE_DAY:
                 timeLeft = math.ceil(deltaInSeconds / time_utils.ONE_DAY)
                 timeMetric = i18n.makeString('#menu:header/account/premium/days')
             else:
                 timeLeft = math.ceil(deltaInSeconds / time_utils.ONE_HOUR)
                 timeMetric = i18n.makeString('#menu:header/account/premium/hours')
             buyPremiumLabel = i18n.makeString('#menu:headerButtons/doLabel/premium')
             premiumBtnLbl = makeHtmlString('html_templates:lobby/header', 'premium-account-label', {'timeMetric': timeMetric,
              'timeLeft': timeLeft})
             canUpdatePremium = deltaInSeconds < time_utils.ONE_YEAR
         else:
             canUpdatePremium = True
             premiumBtnLbl = makeHtmlString('html_templates:lobby/header', 'base-account-label')
             buyPremiumLabel = i18n.makeString('#menu:common/premiumBuy')
         if not canUpdatePremium:
             disableTTHeader = i18n.makeString(TOOLTIPS.LOBBY_HEADER_BUYPREMIUMACCOUNT_DISABLED_HEADER)
             disableTTBody = i18n.makeString(TOOLTIPS.LOBBY_HEADER_BUYPREMIUMACCOUNT_DISABLED_BODY, number=time_utils.ONE_YEAR / time_utils.ONE_DAY)
         self.as_doDisableHeaderButtonS(self.BUTTONS.PREM, canUpdatePremium and isNavigationEnabled)
         hasPersonalDiscount = len(g_itemsCache.items.shop.personalPremiumPacketsDiscounts) > 0
         tooltip = canUpdatePremium or {'header': disableTTHeader,
          'body': disableTTBody}
     else:
         tooltip = TOOLTIPS.HEADER_PREMIUM_EXTEND if isPremiumAccount else TOOLTIPS.HEADER_PREMIUM_BUY
     self.as_setPremiumParamsS(isPremiumAccount, premiumBtnLbl, buyPremiumLabel, canUpdatePremium, disableTTHeader, disableTTBody, hasPersonalDiscount, tooltip, TOOLTIP_TYPES.COMPLEX)

    def _max_min(self):
        """
        Calculate minimum and maximum for the axis adding some padding.
        There are always a maximum of ten units for the length of the axis.
        """
        value = length = self._max - self._min

        sign = value/value
        zoom = less_than_one(value) or 1
        value = value * zoom
        ab = abs(value)
        value = math.ceil(ab * 1.1) * sign

        # calculate tick
        l = math.log10(abs(value))
        exp = int(l)
        mant = l - exp
        unit = math.ceil(math.ceil(10**mant) * 10**(exp-1))
        # recalculate max
        value = math.ceil(value / unit) * unit
        unit = unit / zoom

        if value / unit > 9:
            # no more that 10 ticks
            unit *= 2
        self.unit = unit
        scale = value / length
        mini = math.floor(self._min * scale) / zoom
        maxi = math.ceil(self._max * scale) / zoom
        return mini, maxi

def getCtInfo(id):
    infos = {'description':'','ip':[],'hostname':'','ram':0}
    infos['vmStatus'] = VE_STOPPED
    #infos['ips'] = getCtIp(id)
    
    f = open(VPS_CONF_DIR+'/'+id+'.conf')
    for line in f:
      line = re.sub('#.*','',line).strip()
      if line != '':
        m = re.search('([A-Z_]*)="(.*)"', line)
        key = m.group(1)
        value = m.group(2).replace('\\"','"')
        if   key == 'HOSTNAME':
          infos['hostname'] = value
        elif key == 'DESCRIPTION':
          infos['description'] = unescape(value)
        elif key == 'PRIVVMPAGES':
          privvmpages = int(ceil(int(value.split(':')[0])/256.0))
        elif key == 'LOCKEDPAGES':
          infos['ram'] = int(ceil(int(value.split(':')[0])/256.0))
        elif key == 'IP_ADDRESS':
            infos['ip'] = re.sub('\s+',' ',value).strip().split(' ')
            
    infos['swap'] = privvmpages - infos['ram']
    
    return infos

def generate_shifts_2d(width, height, n_samples, with_hot=False):
    x_shifts = gpu_rng.gen_uniform((n_samples,), np.float32) * (width - 0.01)
    x_shifts = x_shifts.astype(np.uint32)

    y_shifts = gpu_rng.gen_uniform((n_samples,), np.float32) * (height - 0.01)
    y_shifts = y_shifts.astype(np.uint32)

    if with_hot:
        shifts_hot = gp.empty((width * height, n_samples), np.float32)
        threads_per_block = 32
        n_blocks = int(math.ceil(n_samples / threads_per_block))
        gpu_shift_to_hot_2d(x_shifts, y_shifts, shifts_hot,
                            np.uint32(shifts_hot.strides[0]/4),
                            np.uint32(shifts_hot.strides[1]/4),
                            np.uint32(width), np.uint32(height), np.uint32(n_samples),
                            block=(threads_per_block, 1, 1), grid=(n_blocks, 1))
        return x_shifts, y_shifts, shifts_hot
    else:
        shifts = gp.empty((2, n_samples), np.float32)
        threads_per_block = 32
        n_blocks = int(math.ceil(n_samples / threads_per_block))
        gpu_vstack(y_shifts, x_shifts, shifts,
                   np.uint32(shifts.strides[0]/4), np.uint32(shifts.strides[1]/4),
                   np.uint32(n_samples),
                   block=(threads_per_block, 1, 1), grid=(n_blocks, 1))
        return x_shifts, y_shifts, shifts

	def format(self, value, form, length=32):
		""" Format a number based on a format character and length
		"""
		# get current gdb radix setting
		radix = int(re.search("\d+", gdb.execute("show output-radix", True, True)).group(0))

		# override it if asked to
		if form == 'x' or form == 'a':
			radix = 16
		elif form == 'o':
			radix = 8
		elif form == 'b' or form == 't':
			radix = 2

		# format the output
		if radix == 16:
			# For addresses, probably best in hex too
			l = int(math.ceil(length/4.0))
			return "0x"+"{:X}".format(value).zfill(l)
		if radix == 8:
			l = int(math.ceil(length/3.0))
			return "0"+"{:o}".format(value).zfill(l)
		if radix == 2:
			return "0b"+"{:b}".format(value).zfill(length)
		# Default: Just return in decimal
		return str(value)