Another related question. is there some statistics function that
computes the mean, std. dev., min/max, etc. from a frequency distribution?
--
Wayne Watson (Watson Adventures, Prop., Nevada City, CA)
(121.015 Deg. W, 39.262 Deg. N) GMT-8 hr std. time)
Obz S
Thanks. Very good.
Pierre de Buyl wrote:
> bar does what you need.
>
> import numpy as np
> import matplotlib.pyplot as plt
>
> freq = np.array( [127516, 8548, 46797, 46648, 21085, 9084, 7466,
> 6534, 5801,
> 5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, 0, 0,
> 0, 0, 0, 0,
bar does what you need.
import numpy as np
import matplotlib.pyplot as plt
freq = np.array( [127516, 8548, 46797, 46648, 21085, 9084, 7466,
6534, 5801,
5051, 4655, 4168, 4343, 3105, 2508, 2082, 1200, 488, 121, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0] )
fig = plt.figure()
plt.bar(range(0,255,8),
That helped by using the original data of 256 elements. So all the
large values in the array beyond 120 would be tiny bars stretched out
to x of about 127516. OK, now with the original 256 elements I see
some problems.
Individually, they contain some high counts, so I guess they are going
I'm working with a Python program that produces freq below. There are 32
bins. The bins represent 0-7, 8-14, ..., 248 - 255 of a set of
frequencies (integer counts). 0 to 255 are the brightness pixel values
from a 640x480 frame of b/w pixels. I binned 8 into each of 32 bins. One
can easily see