Matplotlib wraps the graph

Hello everyone! I have a problem with matplotlib: If the

    > input data has values larger than 130, the graph wraps
    > around. Is this a known problem?

    > I am using matplotlib 0.87.3 on fedora core 5. -- Trond
    > Danielsen

I've never seen this before. Can you provide a free-standing,
complete example?

JDH

Could this be a data type issue?

from numpy import arange
arange(120, 130, dtype=Int8)

Out: array([ 120, 121, 122, 123, 124, 125, 126, 127, -128, -127],
dtype=int8)

···

On Wednesday 25 October 2006 09:51, John Hunter wrote:

    > Hello everyone! I have a problem with matplotlib: If the
    > input data has values larger than 130, the graph wraps
    > around. Is this a known problem?

    > I am using matplotlib 0.87.3 on fedora core 5. -- Trond
    > Danielsen

I've never seen this before. Can you provide a free-standing,
complete example?

JDH

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--
Darren S. Dale, Ph.D.
Staff Scientist
Cornell High Energy Synchrotron Source
Cornell University
275 Wilson Lab
Rt. 366 & Pine Tree Road
Ithaca, NY 14853

dd55@...163...
office: (607) 255-3819
fax: (607) 255-9001
http://www.chess.cornell.edu

2006/10/25, Darren Dale <dd55@...163...>:

Could this be a data type issue?

from numpy import arange
arange(120, 130, dtype=Int8)

Out: array([ 120, 121, 122, 123, 124, 125, 126, 127, -128, -127],
dtype=int8)

I will have to check this, but I do not think that is the problem. The
data is used in another algorithm which locates the correlation
maximum between two sliding windows (to detect the start of a data
msg), and the algorithm returns the correct result, only the plot is
wrong.

···

--
Trond Danielsen

2006/10/26, Trond Danielsen <trond.danielsen@...287...>:

I will have to check this, but I do not think that is the problem. The
data is used in another algorithm which locates the correlation
maximum between two sliding windows (to detect the start of a data
msg), and the algorithm returns the correct result, only the plot is
wrong.

I tried this again on Fedora Core 6, and the problem seems to be solved.

···

--
Trond Danielsen