Thank you for the help!
Daπid wrote:
>
> On Sat, Jul 28, 2012 at 12:22 AM, surfcast23 wrote:
>> Am I reading (bins[1]-bins[0]) correctly as taking the difference
>> between
>> what is in the second and first bin?
>
> Yes. I am multipliying the width of the bins by their total height.
> Surely
On Sat, Jul 28, 2012 at 12:22 AM, surfcast23 wrote:
> Am I reading (bins[1]-bins[0]) correctly as taking the difference between
> what is in the second and first bin?
Yes. I am multipliying the width of the bins by their total height.
Surely there are cleaner and more general ways
(say, when the
That worked beautifully thank you!
Am I reading (bins[1]-bins[0]) correctly as taking the difference between
what is in the second and first bin?
Daπid wrote:
>
> I guess it is showing, but you have many data points, so the gaussian
> is too small down there. You have to increase its values t
I guess it is showing, but you have many data points, so the gaussian
is too small down there. You have to increase its values to make both
areas fit:
plt.plot(bins, N*(bins[1]-bins[0])*y, 'r--', linewidth=1)
And you will get a nice gaussian fitting your data.
On Fri, Jul 27, 2012 at 11:12 PM,
Thanks for catching that sigma was still a vector! I am no longer getting the
errors, but the best fit line is not showing up.Is there something else I am
missing ?
BTW thanks for the heads up on the np.mean and np.standard functions.
Khary
Daπid wrote:
>
> On Fri, Jul 27, 2012 at 9:57 PM, su
On Fri, Jul 27, 2012 at 9:57 PM, surfcast23 wrote:
> y = mlab.normpdf( nbins, avg, sigma)
> l = plt.plot(nbins, y, 'r--', linewidth=1)
> plt.show()
You should not change bins there, as you are evaluating the gaussian
function at different values.
Also, sigma is a vector, but it should be an scal
Just tried it with nbins set to 216 and I still get the error
surfcast23 wrote:
>
> Hi David,
>
>I tried your fix
> nbins = 20
> n, bins, patches = plt.hist(C, nbins, range=None, normed=False,
> weights=None, cumulative=False, bottom=None, histtype='bar', align='mid',
> orientation='v
Hi David,
I tried your fix
nbins = 20
n, bins, patches = plt.hist(C, nbins, range=None, normed=False,
weights=None, cumulative=False, bottom=None, histtype='bar', align='mid',
orientation='vertical', rwidth=None, log = False, color=None, label=None)
plt.title("")
plt.text(25,20,'M < -21.5' '\
In the example you provide, bins is returned by the hist command,
whereas in your code, bins is a number that you defined as 20. So,
change:
bins = 20
plt.hist(C, bins, ...
by:
nbins = 20
n, bins, patches = plt.hist(C, nbins, ...
As a side comment, your data loading is too complex, and fail pr
Hi
I have a code to plot a histogram and I am trying to add a best fit line
following this example
http://matplotlib.sourceforge.net/examples/pylab_examples/histogram_demo.html
but run into this error
Traceback (most recent call last):
File "/home/Astro/count_Histogram.py", line 54, in
On Sun, Mar 21, 2010 at 1:57 PM, AG wrote:
> Hi List
>
> I cannot figure out how to satisfy this issue to resolve the ValueError:
> x and y must have same first dimension.
>
>
> This is the relevant code:
> [code]
>
> for i in range( 0, time + 1 ):
>
>outflow = constant * quantity
>
>quant
Hi List
I cannot figure out how to satisfy this issue to resolve the ValueError:
x and y must have same first dimension.
This is the relevant code:
[code]
for i in range( 0, time + 1 ):
outflow = constant * quantity
quantityChange = inflow - outflow
changeList.append( quantityCh
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