记录一下我在安装，更新以及使用Python过程中遇到的问题

return list(map(_addcyclic,arr[:-1]) + [_addcyclic_lon(arr[-1])])
TypeError: unsupported operand type(s) for +: 'map' and 'list'

def addcyclic(arrin,lonsin):
	"""
	``arrout, lonsout = addcyclic(arrin, lonsin)``
	adds cyclic (wraparound) point in longitude to ``arrin`` and ``lonsin``,
	assumes longitude is the right-most dimension of ``arrin``.
	"""
	nlons = arrin.shape[-1]
	newshape = list(arrin.shape)
	newshape[-1] += 1
	if ma.isMA(arrin):
	    arrout  = ma.zeros(newshape,arrin.dtype)
	else:
	    arrout  = np.zeros(newshape,arrin.dtype)
	arrout[...,0:nlons] = arrin[:]
	arrout[...,nlons] = arrin[...,0]
	if ma.isMA(lonsin):
	    lonsout = ma.zeros(nlons+1,lonsin.dtype)
	else:
	    lonsout = np.zeros((nlons+1,1),lonsin.dtype)
	lonsout[0:nlons] = lonsin[:]
	lonsout[nlons]  = lonsin[-1] + lonsin[1]-lonsin[0]
	return arrout,lonsout

def addcyclic(*arr,**kwargs):
	"""  
	Adds cyclic (wraparound) points in longitude to one or several arrays,
	the last array being longitudes in degrees. e.g.
	     
	`data1out, data2out, lonsout = addcyclic(data1,data2,lons)``
	     
	==============   ====================================================
	Keywords         Description
	==============   ====================================================
	axis             the dimension representing longitude (default -1,
	                 or right-most)
	cyclic           width of periodic domain (default 360)
	==============   ====================================================
	"""  
	# get (default) keyword arguments
	axis = kwargs.get('axis',-1)
	cyclic = kwargs.get('cyclic',360)
	# define functions
	def _addcyclic(a):
	    """addcyclic function for a single data array"""
	    npsel = np.ma if np.ma.is_masked(a) else np
	    slicer = [slice(None)] * np.ndim(a)
	    try:
	        slicer[axis] = slice(0, 1)
	    except IndexError:
	        raise ValueError('The specified axis does not correspond to an '
	                'array dimension.')
	    return npsel.concatenate((a,a[slicer]),axis=axis)
	def _addcyclic_lon(a):
	    """addcyclic function for a single longitude array"""
	    # select the right numpy functions
	    npsel = np.ma if np.ma.is_masked(a) else np
	    # get cyclic longitudes
	    clon = (np.take(a,[0],axis=axis)
	            + cyclic * np.sign(np.diff(np.take(a,0,-1],axis=axis),axis=axis)))
	    # ensure the values do not exceed cyclic
	    clonmod = npsel.where(clon<=cyclic,clon,np.mod(clon,cyclic))
	    return npsel.concatenate((a,clonmod),axis=axis)
	# process array(s)
	if len(arr) == 1:
	    return _addcyclic_lon(arr[-1])
	else:
	    # return list(map(_addcyclic,arr[:-1]) + [_addcyclic_lon(arr[-1])])
	    return list(map(_addcyclic,arr[:-1])) + [_addcyclic_lon(arr[-1])]

>>> from mpl_toolkits.basemap import Basemap, addcyclic
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/dxl/anaconda3/lib/python3.8/site-packages/mpl_toolkits/basemap/__init__.py", line 50, in <module>
    from .proj import Proj
  File "/Users/dxl/anaconda3/lib/python3.8/site-packages/mpl_toolkits/basemap/proj.py", line 6, in <module>
    from matplotlib.cbook import dedent
ImportError: cannot import name 'dedent' from 'matplotlib.cbook' (/Users/dxl/anaconda3/lib/python3.8/site-packages/matplotlib/cbook/__init__.py)

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

import iris
from eofs.iris import Eof

# read a spatial-temporal field, time must be the first dimension
sst = iris.load_cube('sst_monthly.nc')

# create a solver class, taking advantage of built-in weighting
solver = Eof(sst, weights='coslat')

# retrieve the first two EOFs from the solver class
eofs = solver.eofs(neofs=2)