Python numpy.number方法代碼示例

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def revisitFilter(self,sInds,tmpCurrentTimeNorm):
        """Helper method for Overloading Revisit Filtering

        Args:
            sInds - indices of stars still in observation list
            tmpCurrentTimeNorm (MJD) - the simulation time after overhead was added in MJD form
        Returns:
            sInds - indices of stars still in observation list
        """

        tovisit = np.zeros(self.TargetList.nStars, dtype=bool)
        if len(sInds) > 0:
            tovisit[sInds] = ((self.starVisits[sInds] == min(self.starVisits[sInds])) \
                    & (self.starVisits[sInds] < self.nVisitsMax))#Checks that no star has exceeded the number of revisits and the indicies of all considered stars have minimum number of observations
            #The above condition should prevent revisits so long as all stars have not been observed
            if self.starRevisit.size != 0:
                dt_rev = np.abs(self.starRevisit[:,1]*u.day - tmpCurrentTimeNorm)
                ind_rev = [int(x) for x in self.starRevisit[dt_rev < self.dt_max,0] 
                        if x in sInds]
                tovisit[ind_rev] = (self.starVisits[ind_rev] < self.nVisitsMax)
            sInds = np.where(tovisit)[0]
        return sInds 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def one_from_two_pdm(two_pdm, nelec):
    '''Return a 1-rdm, given a 2-rdm to contract.

    Args:
        two_pdm : ndarray
            A (spin-free) 2-particle reduced density matrix.
        nelec: int
            The number of electrons contributing to the RDMs.

    Returns:
        one_pdm : ndarray
            The (spin-free) 1-particle reduced density matrix.
    '''

    # Last two indices refer to middle two second quantized operators in the 2RDM
    one_pdm = numpy.einsum('ikjj->ik', two_pdm)
    one_pdm /= (numpy.sum(nelec)-1)
    return one_pdm 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def kernel(self, h1e, eri, norb, nelec, ci0=None,
               tol=None, lindep=None, max_cycle=None, max_space=None,
               nroots=None, davidson_only=None, pspace_size=None,
               orbsym=None, wfnsym=None, ecore=0, **kwargs):
        if isinstance(nelec, (int, numpy.number)):
            nelecb = nelec//2
            neleca = nelec - nelecb
        else:
            neleca, nelecb = nelec
        link_indexa = cistring.gen_linkstr_index(range(norb), neleca)
        link_indexb = cistring.gen_linkstr_index(range(norb), nelecb)
        e, c = direct_spin1.kernel_ms1(self, h1e, eri, norb, nelec, ci0,
                                       (link_indexa,link_indexb),
                                       tol, lindep, max_cycle, max_space, nroots,
                                       davidson_only, pspace_size, ecore=ecore,
                                       **kwargs)
        self.eci, self.ci = e, c
        return e, c 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def reorder_eri(eri, norb, orbsym):
    if orbsym is None:
        return [eri], numpy.arange(norb), numpy.zeros(norb,dtype=numpy.int32)
# map irrep IDs of Dooh or Coov to D2h, C2v
# see symm.basis.linearmole_symm_descent
    orbsym = numpy.asarray(orbsym) % 10
# irrep of (ij| pair
    trilirrep = (orbsym[:,None]^orbsym)[numpy.tril_indices(norb)]
# and the number of occurence for each irrep
    dimirrep = numpy.asarray(numpy.bincount(trilirrep), dtype=numpy.int32)
# we sort the irreps of (ij| pair, to group the pairs which have same irreps
# "order" is irrep-id-sorted index. The (ij| paired is ordered that the
# pair-id given by order[0] comes first in the sorted pair
# "rank" is a sorted "order". Given nth (ij| pair, it returns the place(rank)
# of the sorted pair
    old_eri_irrep = numpy.asarray(trilirrep, dtype=numpy.int32)
    rank_in_irrep = numpy.empty_like(old_eri_irrep)
    p0 = 0
    eri_irs = [numpy.zeros((0,0))] * TOTIRREPS
    for ir, nnorb in enumerate(dimirrep):
        idx = numpy.asarray(numpy.where(trilirrep == ir)[0], dtype=numpy.int32)
        rank_in_irrep[idx] = numpy.arange(nnorb, dtype=numpy.int32)
        eri_irs[ir] = lib.take_2d(eri, idx, idx)
        p0 += nnorb
    return eri_irs, rank_in_irrep, old_eri_irrep 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def write_ci(fout, fcivec, norb, nelec, ncore=0):
    from pyscf import fci
    if isinstance(nelec, (int, numpy.number)):
        nelecb = nelec//2
        neleca = nelec - nelecb
    else:
        neleca, nelecb = nelec
    fout.write('NELACTIVE, NDETS, NORBCORE, NORBACTIVE\n')
    fout.write(' %5d %5d %5d %5d\n' % (neleca+nelecb, fcivec.size, ncore, norb))
    fout.write('COEFFICIENT/ OCCUPIED ACTIVE SPIN ORBITALS\n')

    nb = fci.cistring.num_strings(norb, nelecb)
    stringsa = fci.cistring.gen_strings4orblist(range(norb), neleca)
    stringsb = fci.cistring.gen_strings4orblist(range(norb), nelecb)
    def str2orbidx(string, ncore):
        bstring = bin(string)
        return [i+1+ncore for i,s in enumerate(bstring[::-1]) if s == '1']

    addrs = numpy.argsort(abs(fcivec.ravel()))
    for iaddr in reversed(addrs):
        addra, addrb = divmod(iaddr, nb)
        idxa = ['%3d' % x for x in str2orbidx(stringsa[addra], ncore)]
        idxb = ['%3d' % (-x) for x in str2orbidx(stringsb[addrb], ncore)]
        #TODO:add a cuttoff and a counter for ndets
        fout.write('%18.10E %s %s\n' % (fcivec[addra,addrb], ' '.join(idxa), ' '.join(idxb))) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def from_fcivec(ci0, norb, nelec, frozen=None):
    '''Extract CISD coefficients from FCI coefficients'''
    if not (frozen is None or frozen == 0):
        raise NotImplementedError

    if isinstance(nelec, (int, numpy.number)):
        nelecb = nelec//2
        neleca = nelec - nelecb
    else:
        neleca, nelecb = nelec
    nocc = neleca
    nvir = norb - nocc
    t1addr, t1sign = t1strs(norb, nocc)

    c0 = ci0[0,0]
    c1 = ci0[0,t1addr] * t1sign
    c2 = numpy.einsum('i,j,ij->ij', t1sign, t1sign, ci0[t1addr[:,None],t1addr])
    c1 = c1.reshape(nocc,nvir)
    c2 = c2.reshape(nocc,nvir,nocc,nvir).transpose(0,2,1,3)
    return amplitudes_to_cisdvec(c0, c1, c2) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def __rmul__(sys1, sys2):
        """Pre-multiply an input/output systems by a scalar/matrix"""
        if isinstance(sys2, (int, float, np.number)):
            # TODO: Scale the output
            raise NotImplemented("Scalar multiplication not yet implemented")
        elif isinstance(sys2, np.ndarray):
            # TODO: Post-multiply by a matrix
            raise NotImplemented("Matrix multiplication not yet implemented")
        elif isinstance(sys1, StateSpace) and isinstance(sys2, StateSpace):
            # Special case: maintain linear systems structure
            new_ss_sys = StateSpace.__rmul__(sys1, sys2)
            # TODO: set input and output names
            new_io_sys = LinearIOSystem(new_ss_sys)

            return new_io_sys
        elif not isinstance(sys2, InputOutputSystem):
            raise ValueError("Unknown I/O system object ", sys1)
        else:
            # Both systetms are InputOutputSystems => use __mul__
            return InputOutputSystem.__mul__(sys2, sys1) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def set_outputs(self, outputs, prefix='y'):
        """Set the number/names of the system outputs.

        Parameters
        ----------
        outputs : int, list of str, or None
            Description of the system outputs.  This can be given as an integer
            count or as a list of strings that name the individual signals.
            If an integer count is specified, the names of the signal will be
            of the form `u[i]` (where the prefix `u` can be changed using the
            optional prefix parameter).
        prefix : string, optional
            If `outputs` is an integer, create the names of the states using
            the given prefix (default = 'y').  The names of the input will be
            of the form `prefix[i]`.

        """
        self.noutputs, self.output_index = \
            self._process_signal_list(outputs, prefix=prefix) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def set_states(self, states, prefix='x'):
        """Set the number/names of the system states.

        Parameters
        ----------
        states : int, list of str, or None
            Description of the system states.  This can be given as an integer
            count or as a list of strings that name the individual signals.
            If an integer count is specified, the names of the signal will be
            of the form `u[i]` (where the prefix `u` can be changed using the
            optional prefix parameter).
        prefix : string, optional
            If `states` is an integer, create the names of the states using
            the given prefix (default = 'x').  The names of the input will be
            of the form `prefix[i]`.

        """
        self.nstates, self.state_index = \
            self._process_signal_list(states, prefix=prefix) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def set_input_map(self, input_map):
        """Set the input map for an interconnected I/O system.

        Parameters
        ----------
        input_map : 2D array
             Specify the matrix that will be used to multiply the vector of
             system inputs to obtain the vector of subsystem inputs.  These
             values are added to the inputs specified in the connection map.

        """
        # Figure out the number of internal inputs
        ninputs = sum(sys.ninputs for sys in self.syslist)

        # Make sure the input map is the right size
        if input_map.shape[0] != ninputs:
            ValueError("Input map is not the right shape")
        self.input_map = input_map
        self.ninputs = input_map.shape[1] 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def __truediv__(self, other):
        """Divide two LTI objects."""

        if isinstance(other, (int, float, complex, np.number)):
            return FRD(self.fresp * (1/other), self.omega,
                       smooth=(self.ifunc is not None))
        else:
            other = _convertToFRD(other, omega=self.omega)

        if (self.inputs > 1 or self.outputs > 1 or
            other.inputs > 1 or other.outputs > 1):
            raise NotImplementedError(
                "FRD.__truediv__ is currently only implemented for SISO "
                "systems.")

        return FRD(self.fresp/other.fresp, self.omega,
                   smooth=(self.ifunc is not None) and
                          (other.ifunc is not None))

    # TODO: Remove when transition to python3 complete 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def evalfr(self, omega):
        """Evaluate a transfer function at a single angular frequency.

        self._evalfr(omega) returns the value of the frequency response
        at frequency omega.

        Note that a "normal" FRD only returns values for which there is an
        entry in the omega vector. An interpolating FRD can return
        intermediate values.

        """
        warn("FRD.evalfr(omega) will be deprecated in a future release "
             "of python-control; use sys.eval(omega) instead",
             PendingDeprecationWarning)         # pragma: no coverage
        return self._evalfr(omega)

    # Define the `eval` function to evaluate an FRD at a given (real)
    # frequency.  Note that we choose to use `eval` instead of `evalfr` to
    # avoid confusion with :func:`evalfr`, which takes a complex number as its
    # argument.  Similarly, we don't use `__call__` to avoid confusion between
    # G(s) for a transfer function and G(omega) for an FRD object. 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def issiso(sys, strict=False):
    """
    Check to see if a system is single input, single output

    Parameters
    ----------
    sys : LTI system
        System to be checked
    strict: bool (default = False)
        If strict is True, do not treat scalars as SISO
    """
    if isinstance(sys, (int, float, complex, np.number)) and not strict:
        return True
    elif not isinstance(sys, LTI):
        raise ValueError("Object is not an LTI system")

    # Done with the tricky stuff...
    return sys.issiso()

# Return the timebase (with conversion if unspecified) 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def timebase(sys, strict=True):
    """Return the timebase for an LTI system

    dt = timebase(sys)

    returns the timebase for a system 'sys'.  If the strict option is
    set to False, dt = True will be returned as 1.
    """
    # System needs to be either a constant or an LTI system
    if isinstance(sys, (int, float, complex, np.number)):
        return None
    elif not isinstance(sys, LTI):
        raise ValueError("Timebase not defined")

    # Return the sample time, with converstion to float if strict is false
    if (sys.dt == None):
        return None
    elif (strict):
        return float(sys.dt)

    return sys.dt

# Check to see if two timebases are equal 

# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import number [as 別名]
def test_ticket_1539(self):
        dtypes = [x for x in np.typeDict.values()
                  if (issubclass(x, np.number)
                      and not issubclass(x, np.timedelta64))]
        a = np.array([], np.bool_)  # not x[0] because it is unordered
        failures = []

        for x in dtypes:
            b = a.astype(x)
            for y in dtypes:
                c = a.astype(y)
                try:
                    np.dot(b, c)
                except TypeError:
                    failures.append((x, y))
        if failures:
            raise AssertionError("Failures: %r" % failures)