"""
A collection of utility functions and classes.  Many (but not all)
from the Python Cookbook -- hence the name cbook
"""
from __future__ import generators
import re, os, errno, sys, StringIO, traceback, locale, threading, types
import time, datetime
import numpy as np
import numpy.ma as ma
from weakref import ref

major, minor1, minor2, s, tmp = sys.version_info


# on some systems, locale.getpreferredencoding returns None, which can break unicode
preferredencoding = locale.getpreferredencoding()

def unicode_safe(s):
    if preferredencoding is None: return unicode(s)
    else: return unicode(s, preferredencoding)

class converter:
    """
    Base class for handling string -> python type with support for
    missing values
    """
    def __init__(self, missing='Null', missingval=None):
        self.missing = missing
        self.missingval = missingval
    def __call__(self, s):
        if s==self.missing: return self.missingval
        return s

    def is_missing(self, s):
        return not s.strip() or s==self.missing

class tostr(converter):
    'convert to string or None'
    def __init__(self, missing='Null', missingval=''):
        converter.__init__(self, missing=missing, missingval=missingval)

class todatetime(converter):
    'convert to a datetime or None'
    def __init__(self, fmt='%Y-%m-%d', missing='Null', missingval=None):
        'use a :func:`time.strptime` format string for conversion'
        converter.__init__(self, missing, missingval)
        self.fmt = fmt

    def __call__(self, s):
        if self.is_missing(s): return self.missingval
        tup = time.strptime(s, self.fmt)
        return datetime.datetime(*tup[:6])



class todate(converter):
    'convert to a date or None'
    def __init__(self, fmt='%Y-%m-%d', missing='Null', missingval=None):
        'use a :func:`time.strptime` format string for conversion'
        converter.__init__(self, missing, missingval)
        self.fmt = fmt
    def __call__(self, s):
        if self.is_missing(s): return self.missingval
        tup = time.strptime(s, self.fmt)
        return datetime.date(*tup[:3])

class tofloat(converter):
    'convert to a float or None'
    def __init__(self, missing='Null', missingval=None):
        converter.__init__(self, missing)
        self.missingval = missingval
    def __call__(self, s):
        if self.is_missing(s): return self.missingval
        return float(s)


class toint(converter):
    'convert to an int or None'
    def __init__(self, missing='Null', missingval=None):
        converter.__init__(self, missing)

    def __call__(self, s):
        if self.is_missing(s): return self.missingval
        return int(s)

class CallbackRegistry:
    """
    Handle registering and disconnecting for a set of signals and
    callbacks::

       signals = 'eat', 'drink', 'be merry'

       def oneat(x):
           print 'eat', x

       def ondrink(x):
           print 'drink', x

       callbacks = CallbackRegistry(signals)

       ideat = callbacks.connect('eat', oneat)
       iddrink = callbacks.connect('drink', ondrink)

       #tmp = callbacks.connect('drunk', ondrink) # this will raise a ValueError

       callbacks.process('drink', 123)    # will call oneat
       callbacks.process('eat', 456)      # will call ondrink
       callbacks.process('be merry', 456) # nothing will be called
       callbacks.disconnect(ideat)        # disconnect oneat
       callbacks.process('eat', 456)      # nothing will be called

    """
    def __init__(self, signals):
        '*signals* is a sequence of valid signals'
        self.signals = set(signals)
        # callbacks is a dict mapping the signal to a dictionary
        # mapping callback id to the callback function
        self.callbacks = dict([(s, dict()) for s in signals])
        self._cid = 0

    def _check_signal(self, s):
        'make sure *s* is a valid signal or raise a ValueError'
        if s not in self.signals:
            signals = list(self.signals)
            signals.sort()
            raise ValueError('Unknown signal "%s"; valid signals are %s'%(s, signals))

    def connect(self, s, func):
        """
        register *func* to be called when a signal *s* is generated
        func will be called
        """
        self._check_signal(s)
        self._cid +=1
        self.callbacks[s][self._cid] = func
        return self._cid

    def disconnect(self, cid):
        """
        disconnect the callback registered with callback id *cid*
        """
        for eventname, callbackd in self.callbacks.items():
            try: del callbackd[cid]
            except KeyError: continue
            else: return

    def process(self, s, *args, **kwargs):
        """
        process signal *s*.  All of the functions registered to receive
        callbacks on *s* will be called with *\*args* and *\*\*kwargs*
        """
        self._check_signal(s)
        for func in self.callbacks[s].values():
            func(*args, **kwargs)


class Scheduler(threading.Thread):
    """
    Base class for timeout and idle scheduling
    """
    idlelock = threading.Lock()
    id = 0

    def __init__(self):
        threading.Thread.__init__(self)
        self.id = Scheduler.id
        self._stopped = False
        Scheduler.id += 1
        self._stopevent = threading.Event()

    def stop(self):
        if self._stopped: return
        self._stopevent.set()
        self.join()
        self._stopped = True

class Timeout(Scheduler):
    """
    Schedule recurring events with a wait time in seconds
    """
    def __init__(self, wait, func):
        Scheduler.__init__(self)
        self.wait = wait
        self.func = func

    def run(self):

        while not self._stopevent.isSet():
            self._stopevent.wait(self.wait)
            Scheduler.idlelock.acquire()
            b = self.func(self)
            Scheduler.idlelock.release()
            if not b: break

class Idle(Scheduler):
    """
    Schedule callbacks when scheduler is idle
    """
    # the prototype impl is a bit of a poor man's idle handler.  It
    # just implements a short wait time.  But it will provide a
    # placeholder for a proper impl ater
    waittime = 0.05
    def __init__(self, func):
        Scheduler.__init__(self)
        self.func = func

    def run(self):

        while not self._stopevent.isSet():
            self._stopevent.wait(Idle.waittime)
            Scheduler.idlelock.acquire()
            b = self.func(self)
            Scheduler.idlelock.release()
            if not b: break

class silent_list(list):
    """
    override repr when returning a list of matplotlib artists to
    prevent long, meaningless output.  This is meant to be used for a
    homogeneous list of a give type
    """
    def __init__(self, type, seq=None):
        self.type = type
        if seq is not None: self.extend(seq)

    def __repr__(self):
        return '<a list of %d %s objects>' % (len(self), self.type)

    def __str__(self):
        return '<a list of %d %s objects>' % (len(self), self.type)

def strip_math(s):
    'remove latex formatting from mathtext'
    remove = (r'\mathdefault', r'\rm', r'\cal', r'\tt', r'\it', '\\', '{', '}')
    s = s[1:-1]
    for r in remove:  s = s.replace(r,'')
    return s

class Bunch:
    """
    Often we want to just collect a bunch of stuff together, naming each
    item of the bunch; a dictionary's OK for that, but a small do- nothing
    class is even handier, and prettier to use.  Whenever you want to
    group a few variables:

      >>> point = Bunch(datum=2, squared=4, coord=12)
      >>> point.datum

      By: Alex Martelli
      From: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/52308
    """
    def __init__(self, **kwds):
        self.__dict__.update(kwds)


def unique(x):
    'Return a list of unique elements of *x*'
    return dict([ (val, 1) for val in x]).keys()

def iterable(obj):
    'return true if *obj* is iterable'
    try: len(obj)
    except: return 0
    return 1


def is_string_like(obj):
    'return true if *obj* looks like a string'
    if hasattr(obj, 'shape'): return 0
    try: obj + ''
    except (TypeError, ValueError): return 0
    return 1

def is_sequence_of_strings(obj):
    """
    Returns true if *obj* is iterable and contains strings
    """
    if not iterable(obj): return False
    if is_string_like(obj): return False
    for o in obj:
        if not is_string_like(o): return False
    return True

def is_writable_file_like(obj):
    'return true if *obj* looks like a file object with a *write* method'
    return hasattr(obj, 'write') and callable(obj.write)

def is_scalar(obj):
    'return true if *obj* is not string like and is not iterable'
    return not is_string_like(obj) and not iterable(obj)

def is_numlike(obj):
    'return true if *obj* looks like a number'
    try: obj+1
    except TypeError: return False
    else: return True

def to_filehandle(fname, flag='r', return_opened=False):
    """
    *fname* can be a filename or a file handle.  Support for gzipped
    files is automatic, if the filename ends in .gz.  *flag* is a
    read/write flag for :func:`file`
    """
    if is_string_like(fname):
        if fname.endswith('.gz'):
            import gzip
            fh = gzip.open(fname, flag)
        else:
            fh = file(fname, flag)
        opened = True
    elif hasattr(fname, 'seek'):
        fh = fname
        opened = False
    else:
        raise ValueError('fname must be a string or file handle')
    if return_opened:
        return fh, opened
    return fh

def flatten(seq, scalarp=is_scalar):
    """
    this generator flattens nested containers such as

    >>> l=( ('John', 'Hunter'), (1,23), [[[[42,(5,23)]]]])

    so that

    >>> for i in flatten(l): print i,
    John Hunter 1 23 42 5 23

    By: Composite of Holger Krekel and Luther Blissett
    From: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/121294
    and Recipe 1.12 in cookbook
    """
    for item in seq:
        if scalarp(item): yield item
        else:
            for subitem in flatten(item, scalarp):
                yield subitem



class Sorter:
    """

    Sort by attribute or item

    Example usage::

      sort = Sorter()

      list = [(1, 2), (4, 8), (0, 3)]
      dict = [{'a': 3, 'b': 4}, {'a': 5, 'b': 2}, {'a': 0, 'b': 0},
              {'a': 9, 'b': 9}]


      sort(list)       # default sort
      sort(list, 1)    # sort by index 1
      sort(dict, 'a')  # sort a list of dicts by key 'a'

    """

    def _helper(self, data, aux, inplace):
        aux.sort()
        result = [data[i] for junk, i in aux]
        if inplace: data[:] = result
        return result

    def byItem(self, data, itemindex=None, inplace=1):
        if itemindex is None:
            if inplace:
                data.sort()
                result = data
            else:
                result = data[:]
                result.sort()
            return result
        else:
            aux = [(data[i][itemindex], i) for i in range(len(data))]
            return self._helper(data, aux, inplace)

    def byAttribute(self, data, attributename, inplace=1):
        aux = [(getattr(data[i],attributename),i) for i in range(len(data))]
        return self._helper(data, aux, inplace)

    # a couple of handy synonyms
    sort = byItem
    __call__ = byItem





class Xlator(dict):
    """
    All-in-one multiple-string-substitution class

    Example usage::

      text = "Larry Wall is the creator of Perl"
      adict = {
      "Larry Wall" : "Guido van Rossum",
      "creator" : "Benevolent Dictator for Life",
      "Perl" : "Python",
      }

      print multiple_replace(adict, text)

      xlat = Xlator(adict)
      print xlat.xlat(text)
    """

    def _make_regex(self):
        """ Build re object based on the keys of the current dictionary """
        return re.compile("|".join(map(re.escape, self.keys())))

    def __call__(self, match):
        """ Handler invoked for each regex *match* """
        return self[match.group(0)]

    def xlat(self, text):
        """ Translate *text*, returns the modified text. """
        return self._make_regex().sub(self, text)



def soundex(name, len=4):
    """ soundex module conforming to Odell-Russell algorithm """

    # digits holds the soundex values for the alphabet
    soundex_digits = '01230120022455012623010202'
    sndx = ''
    fc = ''

    # Translate letters in name to soundex digits
    for c in name.upper():
        if c.isalpha():
            if not fc: fc = c   # Remember first letter
            d = soundex_digits[ord(c)-ord('A')]
            # Duplicate consecutive soundex digits are skipped
            if not sndx or (d != sndx[-1]):
                sndx += d

    # Replace first digit with first letter
    sndx = fc + sndx[1:]

    # Remove all 0s from the soundex code
    sndx = sndx.replace('0', '')

    # Return soundex code truncated or 0-padded to len characters
    return (sndx + (len * '0'))[:len]



class Null:
    """ Null objects always and reliably "do nothing." """

    def __init__(self, *args, **kwargs): pass
    def __call__(self, *args, **kwargs): return self
    def __str__(self): return "Null()"
    def __repr__(self): return "Null()"
    def __nonzero__(self): return 0

    def __getattr__(self, name): return self
    def __setattr__(self, name, value): return self
    def __delattr__(self, name): return self




def mkdirs(newdir, mode=0777):
    try: os.makedirs(newdir, mode)
    except OSError, err:
        # Reraise the error unless it's about an already existing directory
        if err.errno != errno.EEXIST or not os.path.isdir(newdir):
            raise


class GetRealpathAndStat:
    def __init__(self):
        self._cache = {}

    def __call__(self, path):
        result = self._cache.get(path)
        if result is None:
            realpath = os.path.realpath(path)
            if sys.platform == 'win32':
                stat_key = realpath
            else:
                stat = os.stat(realpath)
                stat_key = (stat.st_ino, stat.st_dev)
            result = realpath, stat_key
            self._cache[path] = result
        return result
get_realpath_and_stat = GetRealpathAndStat()

def dict_delall(d, keys):
    'delete all of the *keys* from the :class:`dict` *d*'
    for key in keys:
        try: del d[key]
        except KeyError: pass


class RingBuffer:
    """ class that implements a not-yet-full buffer """
    def __init__(self,size_max):
        self.max = size_max
        self.data = []

    class __Full:
        """ class that implements a full buffer """
        def append(self, x):
            """ Append an element overwriting the oldest one. """
            self.data[self.cur] = x
            self.cur = (self.cur+1) % self.max
        def get(self):
            """ return list of elements in correct order """
            return self.data[self.cur:]+self.data[:self.cur]

    def append(self,x):
        """append an element at the end of the buffer"""
        self.data.append(x)
        if len(self.data) == self.max:
            self.cur = 0
            # Permanently change self's class from non-full to full
            self.__class__ = __Full

    def get(self):
        """ Return a list of elements from the oldest to the newest. """
        return self.data

    def __get_item__(self, i):
        return self.data[i % len(self.data)]



def get_split_ind(seq, N):
    """
    *seq* is a list of words.  Return the index into seq such that::

        len(' '.join(seq[:ind])<=N

    """

    sLen = 0
    # todo: use Alex's xrange pattern from the cbook for efficiency
    for (word, ind) in zip(seq, range(len(seq))):
        sLen += len(word) + 1  # +1 to account for the len(' ')
        if sLen>=N: return ind
    return len(seq)


def wrap(prefix, text, cols):
    'wrap *text* with *prefix* at length *cols*'
    pad = ' '*len(prefix.expandtabs())
    available = cols - len(pad)

    seq = text.split(' ')
    Nseq = len(seq)
    ind = 0
    lines = []
    while ind<Nseq:
        lastInd = ind
        ind += get_split_ind(seq[ind:], available)
        lines.append(seq[lastInd:ind])

    # add the prefix to the first line, pad with spaces otherwise
    ret = prefix + ' '.join(lines[0]) + '\n'
    for line in lines[1:]:
        ret += pad + ' '.join(line) + '\n'
    return ret

# A regular expression used to determine the amount of space to
# remove.  It looks for the first sequence of spaces immediately
# following the first newline, or at the beginning of the string.
_find_dedent_regex = re.compile("(?:(?:\n\r?)|^)( *)\S")
# A cache to hold the regexs that actually remove the indent.
_dedent_regex = {}
def dedent(s):
    """
    Remove excess indentation from docstring *s*.

    Discards any leading blank lines, then removes up to n whitespace
    characters from each line, where n is the number of leading
    whitespace characters in the first line. It differs from
    textwrap.dedent in its deletion of leading blank lines and its use
    of the first non-blank line to determine the indentation.

    It is also faster in most cases.
    """
    # This implementation has a somewhat obtuse use of regular
    # expressions.  However, this function accounted for almost 30% of
    # matplotlib startup time, so it is worthy of optimization at all
    # costs.

    if not s:      # includes case of s is None
        return ''

    match = _find_dedent_regex.match(s)
    if match is None:
        return s

    # This is the number of spaces to remove from the left-hand side.
    nshift = match.end(1) - match.start(1)
    if nshift == 0:
        return s

    # Get a regex that will remove *up to* nshift spaces from the
    # beginning of each line.  If it isn't in the cache, generate it.
    unindent = _dedent_regex.get(nshift, None)
    if unindent is None:
        unindent = re.compile("\n\r? {0,%d}" % nshift)
        _dedent_regex[nshift] = unindent

    result = unindent.sub("\n", s).strip()
    return result


def listFiles(root, patterns='*', recurse=1, return_folders=0):
    """
    Recursively list files

    from Parmar and Martelli in the Python Cookbook
    """
    import os.path, fnmatch
    # Expand patterns from semicolon-separated string to list
    pattern_list = patterns.split(';')
    # Collect input and output arguments into one bunch
    class Bunch:
        def __init__(self, **kwds): self.__dict__.update(kwds)
    arg = Bunch(recurse=recurse, pattern_list=pattern_list,
        return_folders=return_folders, results=[])

    def visit(arg, dirname, files):
        # Append to arg.results all relevant files (and perhaps folders)
        for name in files:
            fullname = os.path.normpath(os.path.join(dirname, name))
            if arg.return_folders or os.path.isfile(fullname):
                for pattern in arg.pattern_list:
                    if fnmatch.fnmatch(name, pattern):
                        arg.results.append(fullname)
                        break
        # Block recursion if recursion was disallowed
        if not arg.recurse: files[:]=[]

    os.path.walk(root, visit, arg)

    return arg.results

def get_recursive_filelist(args):
    """
    Recurs all the files and dirs in *args* ignoring symbolic links
    and return the files as a list of strings
    """
    files = []

    for arg in args:
        if os.path.isfile(arg):
            files.append(arg)
            continue
        if os.path.isdir(arg):
            newfiles = listFiles(arg, recurse=1, return_folders=1)
            files.extend(newfiles)

    return [f for f in files if not os.path.islink(f)]



def pieces(seq, num=2):
    "Break up the *seq* into *num* tuples"
    start = 0
    while 1:
        item = seq[start:start+num]
        if not len(item): break
        yield item
        start += num

def exception_to_str(s = None):

    sh = StringIO.StringIO()
    if s is not None: print >>sh, s
    traceback.print_exc(file=sh)
    return sh.getvalue()


def allequal(seq):
    """
    Return *True* if all elements of *seq* compare equal.  If *seq* is
    0 or 1 length, return *True*
    """
    if len(seq)<2: return True
    val = seq[0]
    for i in xrange(1, len(seq)):
        thisval = seq[i]
        if thisval != val: return False
    return True

def alltrue(seq):
    """
    Return *True* if all elements of *seq* evaluate to *True*.  If
    *seq* is empty, return *False*.
    """
    if not len(seq): return False
    for val in seq:
        if not val: return False
    return True

def onetrue(seq):
    """
    Return *True* if one element of *seq* is *True*.  It *seq* is
    empty, return *False*.
    """
    if not len(seq): return False
    for val in seq:
        if val: return True
    return False

def allpairs(x):
    """
    return all possible pairs in sequence *x*

    Condensed by Alex Martelli from this thread_ on c.l.python

    .. _thread: http://groups.google.com/groups?q=all+pairs+group:*python*&hl=en&lr=&ie=UTF-8&selm=mailman.4028.1096403649.5135.python-list%40python.org&rnum=1
    """
    return [ (s, f) for i, f in enumerate(x) for s in x[i+1:] ]




# python 2.2 dicts don't have pop--but we don't support 2.2 any more
def popd(d, *args):
    """
    Should behave like python2.3 :meth:`dict.pop` method; *d* is a
    :class:`dict`::

      # returns value for key and deletes item; raises a KeyError if key
      # is not in dict
      val = popd(d, key)

      # returns value for key if key exists, else default.  Delete key,
      # val item if it exists.  Will not raise a KeyError
      val = popd(d, key, default)

    """
    warnings.warn("Use native python dict.pop method", DeprecationWarning)
    # warning added 2008/07/22
    if len(args)==1:
        key = args[0]
        val = d[key]
        del d[key]
    elif len(args)==2:
        key, default = args
        val = d.get(key, default)
        try: del d[key]
        except KeyError: pass
    return val


class maxdict(dict):
    """
    A dictionary with a maximum size; this doesn't override all the
    relevant methods to contrain size, just setitem, so use with
    caution
    """
    def __init__(self, maxsize):
        dict.__init__(self)
        self.maxsize = maxsize
        self._killkeys = []
    def __setitem__(self, k, v):
        if len(self)>=self.maxsize:
            del self[self._killkeys[0]]
            del self._killkeys[0]
        dict.__setitem__(self, k, v)
        self._killkeys.append(k)



class Stack:
    """
    Implement a stack where elements can be pushed on and you can move
    back and forth.  But no pop.  Should mimic home / back / forward
    in a browser
    """

    def __init__(self, default=None):
        self.clear()
        self._default = default

    def __call__(self):
        'return the current element, or None'
        if not len(self._elements): return self._default
        else: return self._elements[self._pos]

    def forward(self):
        'move the position forward and return the current element'
        N = len(self._elements)
        if self._pos<N-1: self._pos += 1
        return self()

    def back(self):
        'move the position back and return the current element'
        if self._pos>0: self._pos -= 1
        return self()

    def push(self, o):
        """
        push object onto stack at current position - all elements
        occurring later than the current position are discarded
        """
        self._elements = self._elements[:self._pos+1]
        self._elements.append(o)
        self._pos = len(self._elements)-1
        return self()

    def home(self):
        'push the first element onto the top of the stack'
        if not len(self._elements): return
        self.push(self._elements[0])
        return self()

    def empty(self):
        return len(self._elements)==0

    def clear(self):
        'empty the stack'
        self._pos = -1
        self._elements = []

    def bubble(self, o):
        """
        raise *o* to the top of the stack and return *o*.  *o* must be
        in the stack
        """

        if o not in self._elements:
            raise ValueError('Unknown element o')
        old = self._elements[:]
        self.clear()
        bubbles = []
        for thiso in old:
            if thiso==o: bubbles.append(thiso)
            else: self.push(thiso)
        for thiso in bubbles:
            self.push(o)
        return o

    def remove(self, o):
        'remove element *o* from the stack'
        if o not in self._elements:
            raise ValueError('Unknown element o')
        old = self._elements[:]
        self.clear()
        for thiso in old:
            if thiso==o: continue
            else: self.push(thiso)

def popall(seq):
    'empty a list'
    for i in xrange(len(seq)): seq.pop()

def finddir(o, match, case=False):
    """
    return all attributes of *o* which match string in match.  if case
    is True require an exact case match.
    """
    if case:
        names = [(name,name) for name in dir(o) if is_string_like(name)]
    else:
        names = [(name.lower(), name) for name in dir(o) if is_string_like(name)]
        match = match.lower()
    return [orig for name, orig in names if name.find(match)>=0]

def reverse_dict(d):
    'reverse the dictionary -- may lose data if values are not unique!'
    return dict([(v,k) for k,v in d.items()])


def report_memory(i=0):  # argument may go away
    'return the memory consumed by process'
    pid = os.getpid()
    if sys.platform=='sunos5':
        a2 = os.popen('ps -p %d -o osz' % pid).readlines()
        mem = int(a2[-1].strip())
    elif sys.platform.startswith('linux'):
        a2 = os.popen('ps -p %d -o rss,sz' % pid).readlines()
        mem = int(a2[1].split()[1])
    elif sys.platform.startswith('darwin'):
        a2 = os.popen('ps -p %d -o rss,vsz' % pid).readlines()
        mem = int(a2[1].split()[0])

    return mem

_safezip_msg = 'In safezip, len(args[0])=%d but len(args[%d])=%d'
def safezip(*args):
    'make sure *args* are equal len before zipping'
    Nx = len(args[0])
    for i, arg in enumerate(args[1:]):
        if len(arg) != Nx:
            raise ValueError(_safezip_msg % (Nx, i+1, len(arg)))
    return zip(*args)

def issubclass_safe(x, klass):
    'return issubclass(x, klass) and return False on a TypeError'

    try:
        return issubclass(x, klass)
    except TypeError:
        return False

class MemoryMonitor:
    def __init__(self, nmax=20000):
        self._nmax = nmax
        self._mem = np.zeros((self._nmax,), np.int32)
        self.clear()

    def clear(self):
        self._n = 0
        self._overflow = False

    def __call__(self):
        mem = report_memory()
        if self._n < self._nmax:
            self._mem[self._n] = mem
            self._n += 1
        else:
            self._overflow = True
        return mem

    def report(self, segments=4):
        n = self._n
        segments = min(n, segments)
        dn = int(n/segments)
        ii = range(0, n, dn)
        ii[-1] = n-1
        print
        print 'memory report: i, mem, dmem, dmem/nloops'
        print 0, self._mem[0]
        for i in range(1, len(ii)):
            di = ii[i] - ii[i-1]
            if di == 0:
                continue
            dm = self._mem[ii[i]] - self._mem[ii[i-1]]
            print '%5d %5d %3d %8.3f' % (ii[i], self._mem[ii[i]],
                                            dm, dm / float(di))
        if self._overflow:
            print "Warning: array size was too small for the number of calls."

    def xy(self, i0=0, isub=1):
        x = np.arange(i0, self._n, isub)
        return x, self._mem[i0:self._n:isub]

    def plot(self, i0=0, isub=1, fig=None):
        if fig is None:
            from pylab import figure, show
            fig = figure()

        ax = fig.add_subplot(111)
        ax.plot(*self.xy(i0, isub))
        fig.canvas.draw()


def print_cycles(objects, outstream=sys.stdout, show_progress=False):
    """
    *objects*
        A list of objects to find cycles in.  It is often useful to
        pass in gc.garbage to find the cycles that are preventing some
        objects from being garbage collected.

    *outstream*
        The stream for output.

    *show_progress*
        If True, print the number of objects reached as they are found.
    """
    import gc
    from types import FrameType

    def print_path(path):
        for i, step in enumerate(path):
            # next "wraps around"
            next = path[(i + 1) % len(path)]

            outstream.write("   %s -- " % str(type(step)))
            if isinstance(step, dict):
                for key, val in step.items():
                    if val is next:
                        outstream.write("[%s]" % repr(key))
                        break
                    if key is next:
                        outstream.write("[key] = %s" % repr(val))
                        break
            elif isinstance(step, list):
                outstream.write("[%d]" % step.index(next))
            elif isinstance(step, tuple):
                outstream.write("( tuple )")
            else:
                outstream.write(repr(step))
            outstream.write(" ->\n")
        outstream.write("\n")

    def recurse(obj, start, all, current_path):
        if show_progress:
            outstream.write("%d\r" % len(all))

        all[id(obj)] = None

        referents = gc.get_referents(obj)
        for referent in referents:
            # If we've found our way back to the start, this is
            # a cycle, so print it out
            if referent is start:
                print_path(current_path)

            # Don't go back through the original list of objects, or
            # through temporary references to the object, since those
            # are just an artifact of the cycle detector itself.
            elif referent is objects or isinstance(referent, FrameType):
                continue

            # We haven't seen this object before, so recurse
            elif id(referent) not in all:
                recurse(referent, start, all, current_path + [obj])

    for obj in objects:
        outstream.write("Examining: %r\n" % (obj,))
        recurse(obj, obj, { }, [])

class Grouper(object):
    """
    This class provides a lightweight way to group arbitrary objects
    together into disjoint sets when a full-blown graph data structure
    would be overkill.

    Objects can be joined using :meth:`join`, tested for connectedness
    using :meth:`joined`, and all disjoint sets can be retreived by
    using the object as an iterator.

    The objects being joined must be hashable.

    For example:

    >>> g = grouper.Grouper()
    >>> g.join('a', 'b')
    >>> g.join('b', 'c')
    >>> g.join('d', 'e')
    >>> list(g)
    [['a', 'b', 'c'], ['d', 'e']]
    >>> g.joined('a', 'b')
    True
    >>> g.joined('a', 'c')
    True
    >>> g.joined('a', 'd')
    False
    """
    def __init__(self, init=[]):
        mapping = self._mapping = {}
        for x in init:
            mapping[ref(x)] = [ref(x)]

    def __contains__(self, item):
        return ref(item) in self._mapping

    def clean(self):
        """
        Clean dead weak references from the dictionary
        """
        mapping = self._mapping
        for key, val in mapping.items():
            if key() is None:
                del mapping[key]
                val.remove(key)

    def join(self, a, *args):
        """
        Join given arguments into the same set.  Accepts one or more
        arguments.
        """
        mapping = self._mapping
        set_a = mapping.setdefault(ref(a), [ref(a)])

        for arg in args:
            set_b = mapping.get(ref(arg))
            if set_b is None:
                set_a.append(ref(arg))
                mapping[ref(arg)] = set_a
            elif set_b is not set_a:
                if len(set_b) > len(set_a):
                    set_a, set_b = set_b, set_a
                set_a.extend(set_b)
                for elem in set_b:
                    mapping[elem] = set_a

        self.clean()

    def joined(self, a, b):
        """
        Returns True if *a* and *b* are members of the same set.
        """
        self.clean()

        mapping = self._mapping
        try:
            return mapping[ref(a)] is mapping[ref(b)]
        except KeyError:
            return False

    def __iter__(self):
        """
        Iterate over each of the disjoint sets as a list.

        The iterator is invalid if interleaved with calls to join().
        """
        self.clean()

        class Token: pass
        token = Token()

        # Mark each group as we come across if by appending a token,
        # and don't yield it twice
        for group in self._mapping.itervalues():
            if not group[-1] is token:
                yield [x() for x in group]
                group.append(token)

        # Cleanup the tokens
        for group in self._mapping.itervalues():
            if group[-1] is token:
                del group[-1]

    def get_siblings(self, a):
        """
        Returns all of the items joined with *a*, including itself.
        """
        self.clean()

        siblings = self._mapping.get(ref(a), [ref(a)])
        return [x() for x in siblings]


def simple_linear_interpolation(a, steps):
    steps = np.floor(steps)
    new_length = ((len(a) - 1) * steps) + 1
    new_shape = list(a.shape)
    new_shape[0] = new_length
    result = np.zeros(new_shape, a.dtype)

    result[0] = a[0]
    a0 = a[0:-1]
    a1 = a[1:  ]
    delta = ((a1 - a0) / steps)

    for i in range(1, int(steps)):
        result[i::steps] = delta * i + a0
    result[steps::steps] = a1

    return result

def less_simple_linear_interpolation( x, y, xi, extrap=False ):
    """
    This function provides simple (but somewhat less so than
    simple_linear_interpolation) linear interpolation.
    simple_linear_interpolation will give a list of point between a
    start and an end, while this does true linear interpolation at an
    arbitrary set of points.

    This is very inefficient linear interpolation meant to be used
    only for a small number of points in relatively non-intensive use
    cases.
    """
    if is_scalar(xi): xi = [xi]

    x = np.asarray(x)
    y = np.asarray(y)
    xi = np.asarray(xi)

    s = list(y.shape)
    s[0] = len(xi)
    yi = np.tile( np.nan, s )

    for ii,xx in enumerate(xi):
        bb = x == xx
        if np.any(bb):
            jj, = np.nonzero(bb)
            yi[ii] = y[jj[0]]
        elif xx<x[0]:
            if extrap:
                yi[ii] = y[0]
        elif xx>x[-1]:
            if extrap:
                yi[ii] = y[-1]
        else:
            jj, = np.nonzero(x<xx)
            jj = max(jj)

            yi[ii] = y[jj] + (xx-x[jj])/(x[jj+1]-x[jj]) * (y[jj+1]-y[jj])

    return yi

def recursive_remove(path):
    if os.path.isdir(path):
        for fname in glob.glob(os.path.join(path, '*')) + glob.glob(os.path.join(path, '.*')):
            if os.path.isdir(fname):
                recursive_remove(fname)
                os.removedirs(fname)
            else:
                os.remove(fname)
        #os.removedirs(path)
    else:
        os.remove(path)

def delete_masked_points(*args):
    """
    Find all masked and/or non-finite points in a set of arguments,
    and return the arguments with only the unmasked points remaining.

    Arguments can be in any of 5 categories:

    1) 1-D masked arrays
    2) 1-D ndarrays
    3) ndarrays with more than one dimension
    4) other non-string iterables
    5) anything else

    The first argument must be in one of the first four categories;
    any argument with a length differing from that of the first
    argument (and hence anything in category 5) then will be
    passed through unchanged.

    Masks are obtained from all arguments of the correct length
    in categories 1, 2, and 4; a point is bad if masked in a masked
    array or if it is a nan or inf.  No attempt is made to
    extract a mask from categories 2, 3, and 4 if :meth:`np.isfinite`
    does not yield a Boolean array.

    All input arguments that are not passed unchanged are returned
    as ndarrays after removing the points or rows corresponding to
    masks in any of the arguments.

    A vastly simpler version of this function was originally
    written as a helper for Axes.scatter().

    """
    if not len(args):
        return ()
    if (is_string_like(args[0]) or not iterable(args[0])):
        raise ValueError("First argument must be a sequence")
    nrecs = len(args[0])
    margs = []
    seqlist = [False] * len(args)
    for i, x in enumerate(args):
        if (not is_string_like(x)) and iterable(x) and len(x) == nrecs:
            seqlist[i] = True
            if ma.isMA(x):
                if x.ndim > 1:
                    raise ValueError("Masked arrays must be 1-D")
            else:
                x = np.asarray(x)
        margs.append(x)
    masks = []    # list of masks that are True where good
    for i, x in enumerate(margs):
        if seqlist[i]:
            if x.ndim > 1:
                continue  # Don't try to get nan locations unless 1-D.
            if ma.isMA(x):
                masks.append(~ma.getmaskarray(x))  # invert the mask
                xd = x.data
            else:
                xd = x
            try:
                mask = np.isfinite(xd)
                if isinstance(mask, np.ndarray):
                    masks.append(mask)
            except: #Fixme: put in tuple of possible exceptions?
                pass
    if len(masks):
        mask = reduce(np.logical_and, masks)
        igood = mask.nonzero()[0]
        if len(igood) < nrecs:
            for i, x in enumerate(margs):
                if seqlist[i]:
                    margs[i] = x.take(igood, axis=0)
    for i, x in enumerate(margs):
        if seqlist[i] and ma.isMA(x):
            margs[i] = x.filled()
    return margs

def unmasked_index_ranges(mask, compressed = True):
    '''
    Find index ranges where *mask* is *False*.

    *mask* will be flattened if it is not already 1-D.

    Returns Nx2 :class:`numpy.ndarray` with each row the start and stop
    indices for slices of the compressed :class:`numpy.ndarray`
    corresponding to each of *N* uninterrupted runs of unmasked
    values.  If optional argument *compressed* is *False*, it returns
    the start and stop indices into the original :class:`numpy.ndarray`,
    not the compressed :class:`numpy.ndarray`.  Returns *None* if there
    are no unmasked values.

    Example::

      y = ma.array(np.arange(5), mask = [0,0,1,0,0])
      ii = unmasked_index_ranges(ma.getmaskarray(y))
      # returns array [[0,2,] [2,4,]]

      y.compressed()[ii[1,0]:ii[1,1]]
      # returns array [3,4,]

      ii = unmasked_index_ranges(ma.getmaskarray(y), compressed=False)
      # returns array [[0, 2], [3, 5]]

      y.filled()[ii[1,0]:ii[1,1]]
      # returns array [3,4,]

    Prior to the transforms refactoring, this was used to support
    masked arrays in Line2D.

    '''
    mask = mask.reshape(mask.size)
    m = np.concatenate(((1,), mask, (1,)))
    indices = np.arange(len(mask) + 1)
    mdif = m[1:] - m[:-1]
    i0 = np.compress(mdif == -1, indices)
    i1 = np.compress(mdif == 1, indices)
    assert len(i0) == len(i1)
    if len(i1) == 0:
        return None  # Maybe this should be np.zeros((0,2), dtype=int)
    if not compressed:
        return np.concatenate((i0[:, np.newaxis], i1[:, np.newaxis]), axis=1)
    seglengths = i1 - i0
    breakpoints = np.cumsum(seglengths)
    ic0 = np.concatenate(((0,), breakpoints[:-1]))
    ic1 = breakpoints
    return np.concatenate((ic0[:, np.newaxis], ic1[:, np.newaxis]), axis=1)

def isvector(X):
    """
    Like the Matlab (TM) function with the same name, returns true if
    the supplied numpy array or matrix looks like a vector, meaning it
    has a one non-singleton axis (i.e., it can have multiple axes, but
    all must have length 1, except for one of them).

    If you just want to see if the array has 1 axis, use X.ndim==1

    """
    return np.prod(X.shape)==np.max(X.shape)

def vector_lengths( X, P=2., axis=None ):
    """
    Finds the length of a set of vectors in n dimensions.  This is
    like the numpy norm function for vectors, but has the ability to
    work over a particular axis of the supplied array or matrix.

    Computes (sum((x_i)^P))^(1/P) for each {x_i} being the elements of X along
    the given axis.  If *axis* is *None*, compute over all elements of X.
    """
    X = np.asarray(X)
    return (np.sum(X**(P),axis=axis))**(1./P)

def distances_along_curve( X ):
    """
    Computes the distance between a set of successive points in N dimensions.

    where X is an MxN array or matrix.  The distances between successive rows
    is computed.  Distance is the standard Euclidean distance.
    """
    X = np.diff( X, axis=0 )
    return vector_lengths(X,axis=1)

def path_length(X):
    """
    Computes the distance travelled along a polygonal curve in N dimensions.


    where X is an MxN array or matrix.  Returns an array of length M consisting
    of the distance along the curve at each point (i.e., the rows of X).
    """
    X = distances_along_curve(X)
    return np.concatenate( (np.zeros(1), np.cumsum(X)) )

def is_closed_polygon(X):
    """
    Tests whether first and last object in a sequence are the same.  These are
    presumably coordinates on a polygonal curve, in which case this function
    tests if that curve is closed.

    """
    return np.all(X[0] == X[-1])

# a dict to cross-map linestyle arguments
_linestyles = [('-', 'solid'),
    ('--', 'dashed'),
    ('-.', 'dashdot'),
    (':',  'dotted')]

ls_mapper = dict(_linestyles)
ls_mapper.update([(ls[1], ls[0]) for ls in _linestyles])

if __name__=='__main__':
    assert( allequal([1,1,1]) )
    assert(not  allequal([1,1,0]) )
    assert( allequal([]) )
    assert( allequal(('a', 'a')))
    assert( not allequal(('a', 'b')))
