python - Fully load raster into a numpy array?

I have been trying to check my filters on DEM raster for pattern recognition and it is always resulting in missing last rows and columns(like..20). I have tried with PIL library, image load. Then with numpy. The output is the same.

I thought, something is wrong with my loops, when checking values in array (just picking pixels with Identification in ArcCatalog) I realized that pixel values were not loaded into an array.

So, just simply opening, puting into array and saving the image from array:

a=numpy.array(Image.open(inraster)) #raster is .tif Float32, size 561x253
newIm=Image.new(Im.mode, Im.size)
Image.fromarray(a).save(outraster)

Results in cuting away the last rows and columns. Sorry, can#t post the image

Anyone could help to understand why? And advise some solution?

EDIT:

So, I succeeded loading small rasters into numpy array with a help of guys, but when having a bigger image I start getting errors. I suppose it's about the limits of numpy array, and so array is automatically reshaped or smth like that... So ex:

Traceback (most recent call last):
  File "", line 1, in 
    ima=numpy.array(inDs.GetRasterBand(1).ReadAsArray())
  File "C:\Python25\lib\site-packages\osgeo\gdal.py", line 835, in ReadAsArray
    buf_xsize, buf_ysize, buf_obj )
  File "C:\Python25\lib\site-packages\osgeo\gdal_array.py", line 140, in BandReadAsArray
    ar = numpy.reshape(ar, [buf_ysize,buf_xsize])
  File "C:\Python25\lib\site-packages\numpy\core\fromnumeric.py", line 108, in reshape

    return reshape(newshape, order=order)
ValueError: total size of new array must be unchanged

The point is I don't want to read block by block as I need filtering, several times with different filters, different sizes.. Is there any work around or I must learn rading by blocks :O

Answer

if you have python-gdal bindings:

import numpy as np
from osgeo import gdal
ds = gdal.Open("mypic.tif")
myarray = np.array(ds.GetRasterBand(1).ReadAsArray())

And you're done:

myarray.shape
(2610,4583)
myarray.size
11961630
myarray
array([[        nan,         nan,         nan, ...,  0.38068664,
     0.37952521,  0.14506227],
   [        nan,         nan,         nan, ...,  0.39791253,

            nan,         nan],
   [        nan,         nan,         nan, ...,         nan,
            nan,         nan],
   ..., 
   [ 0.33243281,  0.33221543,  0.33273876, ...,         nan,
            nan,         nan],
   [ 0.33308044,  0.3337177 ,  0.33416209, ...,         nan,
            nan,         nan],
   [ 0.09213851,  0.09242494,  0.09267616, ...,         nan,
            nan,         nan]], dtype=float32)