Hello, i've updated my published worksheet from above.
To clearify this, the polyfit is actually numpy's and the glm
(generalized linear model) is from R. Sage just enables you to use
both of them (more or less seamless). I don't know any chemical
problems, i've just some background in experimenta
Hi Jason:
Thanks for the help. I teach a MATLAB for engineers online course at the
local univ so I tend to use MATLAB syntax by habit. However, I'm interested
in swapping out and going to Sage/Python for the same type of early
programming class for engineers. Thanks for the input, that helps al
Hi Harald:
Thanks for the great example. The fit is much better. I've been working
problems from Cutlip and Shacham, "Problem Solving in Chemical Engineering
with Numerical Methods". They have worked 10 selected problems with
Polymath, MATLAB, Mathematica, Maple and Excel. I've been working th
Steve Yarbro wrote:
>
>
> On Sun, Jan 11, 2009 at 4:13 PM, mabshoff <> wrote:
>
>
> Hi Michael:
>
>
> Thanks for the help. The error is very likely my lack of skill with
> sage (an excellent piece of work BTW). I have put together an example
> as you suggested. The support for sage
On Jan 15, 5:41 am, "Steve Yarbro" wrote:
> Hi Michael:
>
> I published an example athttp://sagenb.org:8000/home/pub/156. Thanks.
Hello, aside from the actual problem, this fit looks quite wrong. I
played around a bit and fitted a logarithmic model in R. R is not very
well embedded and I forgot
Hi Michael:
I published an example at http://sagenb.org:8000/home/pub/156. Thanks.
Steve
On Wed, Jan 14, 2009 at 4:53 AM, mabshoff <
michael.absh...@mathematik.uni-dortmund.de> wrote:
>
>
>
> On Jan 11, 6:49 pm, "Steve Yarbro" wrote:
> > On Sun, Jan 11, 2009 at 4:13 PM, mabshoff <> wrote:
> >
On Jan 11, 6:49 pm, "Steve Yarbro" wrote:
> On Sun, Jan 11, 2009 at 4:13 PM, mabshoff <> wrote:
>
> > Hi Michael:
>
> Thanks for the help. The error is very likely my lack of skill with sage
> (an excellent piece of work BTW). I have put together an example as you
> suggested. The support fo
On Sun, Jan 11, 2009 at 4:13 PM, mabshoff <> wrote:
>
> Hi Michael:
Thanks for the help. The error is very likely my lack of skill with sage
(an excellent piece of work BTW). I have put together an example as you
suggested. The support for sage is very good. Thank you. The example URL
is h
On Jan 12, 12:04 am, "Steve Yarbro" wrote:
> My thanks to Harald S., this was an excellent example.
glad to help you, this example is just a working one, maybe there are
better ways to do the same thing... i.e. a more "sage"-way where you
use numpy's polyfit only implicitly.
> For example, usin
On Jan 11, 3:04 pm, "Steve Yarbro" wrote:
> Hi:
Hi Steve,
> My thanks to Harald S., this was an excellent example.
>
> This example worked great and solved another issue I was having using
> list_plot with the results. How do you figure out what object type is
> required for input to other f
Hi:
My thanks to Harald S., this was an excellent example.
This example worked great and solved another issue I was having using
list_plot with the results. How do you figure out what object type is
required for input to other functions? For example, using zip() to produce
a list to use with li
On Jan 11, 5:29 am, slybro wrote:
> I am having trouble using the polyfit function. ...
few days ago i did this quick example: http://sagenb.org/home/pub/141/
h
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Mike:
Outstanding! Thank you, I appreciate the help.
Regards,
slybro
On Sat, Jan 10, 2009 at 10:08 PM, Mike Hansen wrote:
>
> Hello,
>
> On Sat, Jan 10, 2009 at 8:29 PM, slybro wrote:
> >
> > I am having trouble using the polyfit function. Here are the
> > commands:
> >
> > import numpy as
slybro wrote:
> I am having trouble using the polyfit function. Here are the
> commands:
>
> import numpy as np
> import scipy as sc
>
> vp = np.array([1.0, 5.0, 10.0, 20.0, 40.0, 60.0, 100.0, 200.0, 400.0,
> 760.0])
>
> T = np.array([-36.7, -19.6, -11.5, -2.6, 7.6, 15.4, 26.1, 42.2, 60.6,
> 8
Hello,
On Sat, Jan 10, 2009 at 8:29 PM, slybro wrote:
>
> I am having trouble using the polyfit function. Here are the
> commands:
>
> import numpy as np
> import scipy as sc
>
> vp = np.array([1.0, 5.0, 10.0, 20.0, 40.0, 60.0, 100.0, 200.0, 400.0,
> 760.0])
>
> T = np.array([-36.7, -19.6, -11.
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