Hi guys..
I seem to have a problems with converting my plot to a numpy ndarray -
Such that if I made a imshow of the numpy ndarray i would see am image similar to the lmage i created..
librosa.display.specshow(static.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)
plt.title("log mel power spectrum of " + name)
plt.colorbar(format='%+02.0f dB')
plt.tight_layout()
plt.savefig(plot+"/"+name+"_plot_static_conv.png")
plt.show()
This will show an image such as:
But if i try to store it as a numpy ndarray and then trying to plot it using this code
convert = plt.get_cmap(cm.jet)
numpy_output_static = convert(static.T)
plt.imshow(numpy_output_static)
plt.show()
raw_input("sadas")
I see something like this
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I made this tiny example code for reproducing the output:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from PIL import Image
import librosa
import librosa.display
from matplotlib import cm
fig = plt.figure(figsize=(12,4))
min = -1.828067
max = 22.70058
data = np.random.uniform(low=min, high=max, size=(474,40))
librosa.display.specshow(data.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)
plt.show()
raw_input("sadas")
convert = plt.get_cmap(cm.jet)
numpy_output_static = convert(data.T)
plt.imshow(numpy_output_static, aspect = 'auto')
plt.show()
raw_input("asds")
Which gives two different images, a random plot in first one, and a red plot in the second one.
···
Den 13. maj 2017 kl. 11.50 skrev Carlton Banks <noflaco at gmail.com>:
Hi guys..
I seem to have a problems with converting my plot to a numpy ndarray -
Such that if I made a imshow of the numpy ndarray i would see am image similar to the lmage i created..
librosa.display.specshow(static.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)
plt.title("log mel power spectrum of " + name)
plt.colorbar(format='%+02.0f dB')
plt.tight_layout()
plt.savefig(plot+"/"+name+"_plot_static_conv.png")
plt.show()
This will show an image such as:
<JPR6G.png>
But if i try to store it as a numpy ndarray and then trying to plot it using this code
convert = plt.get_cmap(cm.jet)
numpy_output_static = convert(static.T)
plt.imshow(numpy_output_static)
plt.show()
raw_input("sadas")
I see something like this <2WGgJ.png>
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Hi,
I think the problem is that you do not actually retrieve the plotted array data
with `matplotlib.pyplot.get_cmap` but the `matplotlib.colormap.Colormap`
instance instead (i.e. just the color <-> value mapping).
Please see the following code snippet to achieve something that looks like you
want if I understood correctly your wish.
import matplotlib.pyplot as plt
import numpy as np
original_data = np.arange(600).reshape((200, -1))
im_opts = {'aspect': 'auto', 'cmap': 'viridis'}
fig, (ax0, ax1) = plt.subplots(ncols=2)
ax0.set_title('From Original Data')
im0 = ax0.imshow(original_data, **im_opts)
# NB: ``get_array`` returns a masked array from `numpy.ma`. More information:
# https://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html
masked_data = im0.get_array()
np.save('recorded_array.npy', masked_data.data) # NB: use the mask if needed
reloaded_data = np.load('recorded_array.npy')
ax1.set_title('From Recorded Data')
im1 = ax1.imshow(reloaded_data, **im_opts)
# just to be sure :)
np.testing.assert_allclose(original_data, reloaded_data)
plt.show()
Best regards,
Adrien V.
Le 13/05/2017 ? 13:52, Carlton Banks a ?crit :
···
I made this tiny example code for reproducing the output:
>importnumpy asnp importmatplotlib.pyplot asplt importmatplotlib fromPIL
importImageimportlibrosa importlibrosa.display frommatplotlib importcm fig
=plt.figure(figsize=(12,4))min =-1.828067max =22.70058data
=np.random.uniform(low=min,high=max,size=(474,40))librosa.display.specshow(data.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)plt.show()raw_input("sadas")convert
=plt.get_cmap(cm.jet)numpy_output_static
=convert(data.T)plt.imshow(numpy_output_static,aspect
='auto')plt.show()raw_input("asds")|
Which gives two different images, a random plot in first one, and a red plot in
the second one.
Den 13. maj 2017 kl. 11.50 skrev Carlton Banks <noflaco at gmail.com
<mailto:noflaco at gmail.com>>:
Hi guys..
I seem to have a problems with converting my plot to a numpy ndarray -
Such that if I made a imshow of the numpy ndarray i would see am image similar
to the lmage i created..
>librosa.display.specshow(static.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)plt.title("log
mel power spectrum of "+name)plt.colorbar(format='%+02.0f
dB')plt.tight_layout()plt.savefig(plot+"/"+name+"_plot_static_conv.png")plt.show()|
This will show an image such as:
<JPR6G.png>
But if i try to store it as a numpy ndarray and then trying to plot it using
this code
>convert =plt.get_cmap(cm.jet)numpy_output_static
=convert(static.T)plt.imshow(numpy_output_static)plt.show()raw_input("sadas")|
I see something like this <2WGgJ.png>
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
Matplotlib-users Info Page
I am not an expert in Numpy masked array, but if I am correct, you can access
the data array of a masked array `m_arr` with no masking through the
`m_arr.data` attribute, the boolean mask through the `m_arr.mask` one and the
masked array through something like `m_arr[~m_arr.mask]`. This way, you can
retrieve the data that is actually displayed by imshow, can't you?
If you absolutely need to save the mask too with Numpy, I would suggest to use
`numpy.savez` (note the ending z) to record both the data array and the boolean
mask. With similar notations as in the previous code snippet, this may looks like:
masked_data = im0.get_array()
np.savez('full_data.npz', data=masked_data.data, mask=masked_data.mask)
with np.load('test.npz') as f:
reloaded_data = f['data']
reloaded_mask = f['mask']
reloaded_ma = np.ma.MaskedArray(reloaded_data, mask=reloaded_mask)
ax1.imshow(reloaded_ma, **im_opts)
Best,
Adrien V.
Le 13/05/2017 ? 13:52, Carlton Banks a ?crit :
···
I made this tiny example code for reproducing the output:
>importnumpy asnp importmatplotlib.pyplot asplt importmatplotlib fromPIL
importImageimportlibrosa importlibrosa.display frommatplotlib importcm fig
=plt.figure(figsize=(12,4))min =-1.828067max =22.70058data
=np.random.uniform(low=min,high=max,size=(474,40))librosa.display.specshow(data.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)plt.show()raw_input("sadas")convert
=plt.get_cmap(cm.jet)numpy_output_static
=convert(data.T)plt.imshow(numpy_output_static,aspect
='auto')plt.show()raw_input("asds")|
Which gives two different images, a random plot in first one, and a red plot in
the second one.
Den 13. maj 2017 kl. 11.50 skrev Carlton Banks <noflaco at gmail.com
<mailto:noflaco at gmail.com>>:
Hi guys..
I seem to have a problems with converting my plot to a numpy ndarray -
Such that if I made a imshow of the numpy ndarray i would see am image similar
to the lmage i created..
>librosa.display.specshow(static.T,sr=16000,x_axis='frames',y_axis='mel',hop_length=160,cmap=cm.jet)plt.title("log
mel power spectrum of "+name)plt.colorbar(format='%+02.0f
dB')plt.tight_layout()plt.savefig(plot+"/"+name+"_plot_static_conv.png")plt.show()|
This will show an image such as:
<JPR6G.png>
But if i try to store it as a numpy ndarray and then trying to plot it using
this code
>convert =plt.get_cmap(cm.jet)numpy_output_static
=convert(static.T)plt.imshow(numpy_output_static)plt.show()raw_input("sadas")|
I see something like this <2WGgJ.png>
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users at python.org
Matplotlib-users Info Page
