#!/usr/bin/env python
from matplotlib import matlab
data = ((3, 1000), (10, 3), (100, 30), (500, 800), (50, 1))
matlab.xlabel("FOO")
matlab.ylabel("FOO")
matlab.title("Testing")
matlab.gca().set_yscale('log')
dim = len(data[0])
w = 0.75
dimw = w / dim
x = matlab.arange(len(data))
for i in range(len(data[0])):
y = [d[i] for d in data]
b = matlab.bar(x + i * dimw, y, dimw, bottom=0.001)
matlab.gca().set_xticks(x + w / 2)
matlab.gca().set_ylim((0.001, 1000))
matlab.show()
#!/usr/bin/env python
from matplotlib import matlab
data = ((3,1000), (10,3), (100,30), (500, 800), (50,1))
matlab.xlabel("FOO")
matlab.ylabel("FOO")
matlab.title("Testing")
matlab.gca().set_yscale('log')
dim = len(data[0])
w = 0.75
dimw = w / dim
x = matlab.arange(len(data))
for i in range(len(data[0])) :
y = [d[i] for d in data]
b = matlab.bar(x + i * dimw, y, dimw, bottom=0.001)
matlab.gca().set_xticks(x + w / 2)
matlab.gca().set_ylim( (0.001,1000))
matlab.show()
"""Load Nicolet BMSI data."""
if tmin < 0: tmin = 0
fh = file(filename, 'rb')
indmin = Fs * tmin
numsamples = os.path.getsize(filename) / (channels * 2)
indmax = min(numsamples, Fs * tmax)
byte0 = int(indmin * channels * 2)
numbytes = int((indmax - indmin) * channels * 2)
fh.seek(byte0)
data = fromstring(fh.read(numbytes), Int16).astype(Float)
data.shape = -1, channels
t = (1 / Fs) * arange(indmin, indmax)
return t, data
t, data = read_nicolet(0, 10)
x = data[:, 5]
Pxx, freqs, t = specgram(x, NFFT=512, Fs=Fs, noverlap=412)
T, F = meshgrid(t, freqs)
pcolor(T, F, 10 * log10(Pxx), shading='flat')
set(gca(), 'ylim', [0, 100])
#print Pxx.shape, freqs.shape, t.shape
show()
indmax = min(numsamples, Fs*tmax)
byte0 = int(indmin*channels*2)
numbytes = int( (indmax-indmin)*channels*2 )
fh.seek(byte0)
data = fromstring(fh.read(numbytes), Int16).astype(Float)
data.shape = -1, channels
t = (1/Fs)*arange(indmin, indmax)
return t, data
t, data = read_nicolet(0,10)
x = data[:,5]
Pxx, freqs, t = specgram(x, NFFT=512, Fs=Fs, noverlap=412)
T, F = meshgrid(t,freqs)
pcolor(T, F, 10*log10(Pxx), shading='flat')
set(gca(), 'ylim', [0,100])
#print Pxx.shape, freqs.shape, t.shape
show()