What behavior is unexpected?  For the (256, 256) images, matplotlib applies its default colormap to the grayscale (v1.5 and previous, that is jet, +v2.0, that will be viridis). The numpy array as loaded from PIL will never carry any additional information that came from the TIFF.

As for PIL, it will return an RGB[A] array if there is colormap data in the TIFF. If there is no colormap specified in the TIFF, it'll give you a simple 2D array. Now, maybe you'd like it to always return an RGB[A] array, but without a colormap in the TIFF, it makes sense to return the data as-is. This makes sense for people treating the TIFF as a data format rather than a visualization data format.

Ben Root


On Fri, Apr 29, 2016 at 12:47 PM, Henrique Almeida <hdante.lnls@gmail.com> wrote:
 I think in any case, the result is unexpected, PIL is loading garbage
from memory when loading black and white images because it sends the
wrong buffer size, and matplotlib correctly loads the black and white
image, but stores it in a 3D array.

2016-04-29 13:43 GMT-03:00 Henrique Almeida <hdante.lnls@gmail.com>:
>  For 1 bit images, the resulting array has shape (256, 256, 4). For
> grayscale images, the shape is (256, 256). So the image seems to have
> been loaded as a color image.
>
> 2016-04-29 13:38 GMT-03:00 Benjamin Root <ben.v.root@gmail.com>:
>> What kind of array is "img"? What is its dtype and shape?
>>
>> plt.imshow() will use the default colormap for matplotlib if the given array
>> is just 2D. But if it is 3D (a 2D array of RGB[A] channels), then it will
>> forego the colormap and utilize that for the colors. It knows nothing of the
>> colormap contained in the TIFF.
>>
>> Ben Root
>>
>>
>> On Fri, Apr 29, 2016 at 12:31 PM, Henrique Almeida <hdante.lnls@gmail.com>
>> wrote:
>>>
>>>  Paul, yes, imread() worked for reading the black and white TIFF. The
>>> situation improved, but now, there seems to be some problem with the
>>> color map. Example code:
>>>
>>> #!/usr/bin/env python3
>>> import numpy
>>> from matplotlib import pyplot, cm
>>>
>>> img = pyplot.imread('oi-00.tiff')
>>> pyplot.imshow(img)
>>> pyplot.colorbar()
>>> pyplot.show()
>>>
>>>  The code can open both 1-bit and 8-bit images, but only with 8 bits
>>> the image is shown with the colormap colors. The 1 bit image is shown
>>> as black and white.
>>>
>>>  The questions:
>>>  1) Should Image.open() behave like pyplot.imread() ? Is this a bug in PIL
>>> ?
>>>  2) Why isn't the colormap working with black and white images ?
>>>
>>> 2016-04-29 13:06 GMT-03:00 Paul Hobson <pmhobson@gmail.com>:
>>> > Does using pyplot.imgread work?
>>> >
>>> > On Fri, Apr 29, 2016 at 8:27 AM, Henrique Almeida
>>> > <hdante.lnls@gmail.com>
>>> > wrote:
>>> >>
>>> >>  Any help with this problem ?
>>> >>
>>> >> 2016-04-27 11:35 GMT-03:00 Henrique Almeida <hdante.lnls@gmail.com>:
>>> >> >  Hello, what's the current status on numpy for loading bit-arrays ?
>>> >> >
>>> >> > I'm currently unable to correctly load black and white (1-bit) TIFF
>>> >> > images. Code example follows:
>>> >> >
>>> >> > from PIL import Image
>>> >> > import numpy
>>> >> > from matplotlib import pyplot
>>> >> >
>>> >> > img = Image.open('oi-00.tiff')
>>> >> > a = numpy.array(img)
>>> >> >
>>> >> > ^ does not work for 1-bit TIFF images
>>> >> >
>>> >> > PIL source shows that it incorrectly uses typestr == '|b1'. I tried
>>> >> > to
>>> >> > change this to '|t1', but I get :
>>> >> >
>>> >> > TypeError: data type "|t1" not understood
>>> >> >
>>> >> > My goal is to make the above code to work for black and white TIFF
>>> >> > images the same way it works for grayscale images. Any help ?
>>> >> _______________________________________________
>>> >> NumPy-Discussion mailing list
>>> >> NumPy-Discussion@scipy.org
>>> >> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>> >
>>> >
>>> >
>>> > _______________________________________________
>>> > NumPy-Discussion mailing list
>>> > NumPy-Discussion@scipy.org
>>> > https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>> >
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion@scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
https://mail.scipy.org/mailman/listinfo/numpy-discussion