type error with python 3.2 and version 1.1.1 of matplotlib (numpy error)

The following Python code:

ax.fill_between(dates, lower, upper, facecolor=‘gray’, alpha=0.5)

Produces this error with Python 3.2:

Traceback (most recent call last):
File “scripts/audit_reports_weekly.py”, line 150, in

ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

File “/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py”, line 6741, in fill_between
y1 = ma.masked_invalid(self.convert_yunits(y1))

File “/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py”, line 2241, in masked_invalid
condition = ~(np.isfinite(a))
TypeError: ufunc ‘isfinite’ not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ‘‘safe’’

[Decimal(‘3619.900530366609820157812617’), …]

If I change the list from type Decimal to type float, then I don’t get the error. Likewise, if I use Python 2.7, I also don’t get an error.

After reading over the error message, I realize that this error really results because of numpy, not matplotlib. But I’ll go ahead and post this message, in case you are unaware of the problem.

Just a quick note, mpl v1.1.x is not officially supported for py3k. The upcoming release of v1.2.0 will be the first official release with such support.

That being said, it probably would be a good idea to make sure where the bug lies for this one (numpy or matplotlib). Which version of numpy are you using?

Ben Root

···

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremblay@…287…> wrote:

The following Python code:

ax.fill_between(dates, lower, upper, facecolor=‘gray’, alpha=0.5)

Produces this error with Python 3.2:

Traceback (most recent call last):
File “scripts/audit_reports_weekly.py”, line 150, in

ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

File “/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py”, line 6741, in fill_between
y1 = ma.masked_invalid(self.convert_yunits(y1))

File “/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py”, line 2241, in masked_invalid
condition = ~(np.isfinite(a))
TypeError: ufunc ‘isfinite’ not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ‘‘safe’’

[Decimal(‘3619.900530366609820157812617’), …]

If I change the list from type Decimal to type float, then I don’t get the error. Likewise, if I use Python 2.7, I also don’t get an error.

After reading over the error message, I realize that this error really results because of numpy, not matplotlib. But I’ll go ahead and post this message, in case you are unaware of the problem.

    The following Python code:

     >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

    Produces this error with Python 3.2:

    Traceback (most recent call last):
       File "scripts/audit_reports_weekly.py", line 150, in <module>
         ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
    line 6741, in fill_between
         y1 = ma.masked_invalid(self.convert_yunits(y1))
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
    line 2241, in masked_invalid
         condition = ~(np.isfinite(a))
    TypeError: ufunc 'isfinite' not supported for the input types, and
    the inputs could not be safely coerced to any supported types
    according to the casting rule ''safe''

    [Decimal('3619.900530366609820157812617'), .....]

    If I change the list from type Decimal to type float, then I don't
    get the error. Likewise, if I use Python 2.7, I also don't get an error.

    After reading over the error message, I realize that this error
    really results because of numpy, not matplotlib. But I'll go ahead
    and post this message, in case you are unaware of the problem.

Just a quick note, mpl v1.1.x is not officially supported for py3k. The
upcoming release of v1.2.0 will be the first official release with such
support.

That being said, it probably would be a good idea to make sure where the
bug lies for this one (numpy or matplotlib). Which version of numpy are
you using?

Should this be considered a bug? Or should we say that we don't support Decimal inputs? If we are going to support Decimal inputs, then we need to put in filters to force conversion to float. Do you want to have to check every entry in every list input to see if it Decimal?

Eric

···

On 2012/09/04 9:09 AM, Benjamin Root wrote:

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremblay@…287… > <mailto:paulhtremblay@…287…>> wrote:

Ben Root

Looking at the message, it is saying that the np.isfinite() function fails on Decimal inputs. From our perspective, a Decimal input should look just the same as integer and floats (following the duck-typing paradigm). Therefore, I think this problem lies squarely at the feet of numpy. However, I am doubtful of just how quickly to expect this issue to be solved by them.

Ben Root

···

On Tue, Sep 4, 2012 at 3:24 PM, Eric Firing <efiring@…202…> wrote:

On 2012/09/04 9:09 AM, Benjamin Root wrote:

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremblay@…287… > > mailto:paulhtremblay@...287...> wrote:

The following Python code:
 >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
Produces this error with Python 3.2:
Traceback (most recent call last):
   File "scripts/audit_reports_weekly.py", line 150, in <module>
     ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
   File
"/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
line 6741, in fill_between
     y1 = ma.masked_invalid(self.convert_yunits(y1))
   File
"/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
line 2241, in masked_invalid
     condition = ~(np.isfinite(a))
TypeError: ufunc 'isfinite' not supported for the input types, and
the inputs could not be safely coerced to any supported types
according to the casting rule ''safe''
[Decimal('3619.900530366609820157812617'), .....]
If I change the list from type Decimal to type float, then I don't
get the error. Likewise, if I use Python 2.7, I also don't get an error.
After reading over the error message, I realize that this error
really results because of numpy, not matplotlib. But I'll go ahead
and post this message, in case you are unaware of the problem.

Just a quick note, mpl v1.1.x is not officially supported for py3k. The

upcoming release of v1.2.0 will be the first official release with such

support.

That being said, it probably would be a good idea to make sure where the

bug lies for this one (numpy or matplotlib). Which version of numpy are

you using?

Should this be considered a bug? Or should we say that we don’t support

Decimal inputs? If we are going to support Decimal inputs, then we need

to put in filters to force conversion to float. Do you want to have to

check every entry in every list input to see if it Decimal?

Eric

    The following Python code:

     >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

    Produces this error with Python 3.2:

    Traceback (most recent call last):
       File "scripts/audit_reports_weekly.py", line 150, in <module>
         ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
    line 6741, in fill_between
         y1 = ma.masked_invalid(self.convert_yunits(y1))
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
    line 2241, in masked_invalid
         condition = ~(np.isfinite(a))
    TypeError: ufunc 'isfinite' not supported for the input types, and
    the inputs could not be safely coerced to any supported types
    according to the casting rule ''safe''

    [Decimal('3619.900530366609820157812617'), .....]

    If I change the list from type Decimal to type float, then I don't
    get the error. Likewise, if I use Python 2.7, I also don't get an error.

    After reading over the error message, I realize that this error
    really results because of numpy, not matplotlib. But I'll go ahead
    and post this message, in case you are unaware of the problem.

Just a quick note, mpl v1.1.x is not officially supported for py3k. The
upcoming release of v1.2.0 will be the first official release with such
support.

That being said, it probably would be a good idea to make sure where the
bug lies for this one (numpy or matplotlib). Which version of numpy are
you using?

To clarify my previous message: I think we will remain mostly at the mercy of numpy, which may change from version to version, to determine what we can handle. Apart from registered unit types, we fall back on numpy, typically masked_invalid, to handle inputs. If we really want to handle Decimal reliably, then it probably has to be done within the units framework.

Eric

···

On 2012/09/04 9:09 AM, Benjamin Root wrote:

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremblay@…287… > <mailto:paulhtremblay@…287…>> wrote:

Ben Root

Isn't that what the unit system is for? It allows users to use whatever objects they want and register conversions to/from MPL types. If Decimal is a common use-case, then perhaps MPL should provide those converters but the user would (and probably should) still need to activate them.

···

________________________________________
From: Eric Firing [efiring@...202...]
Sent: Tuesday, September 04, 2012 12:24 PM
To: matplotlib-users@lists.sourceforge.net
Subject: Re: [Matplotlib-users] type error with python 3.2 and version 1.1.1 of matplotlib (numpy error)

On 2012/09/04 9:09 AM, Benjamin Root wrote:

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremblay@…287… > <mailto:paulhtremblay@…287…>> wrote:

    The following Python code:

     >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

    Produces this error with Python 3.2:

    Traceback (most recent call last):
       File "scripts/audit_reports_weekly.py", line 150, in <module>
         ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
    line 6741, in fill_between
         y1 = ma.masked_invalid(self.convert_yunits(y1))
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
    line 2241, in masked_invalid
         condition = ~(np.isfinite(a))
    TypeError: ufunc 'isfinite' not supported for the input types, and
    the inputs could not be safely coerced to any supported types
    according to the casting rule ''safe''

    [Decimal('3619.900530366609820157812617'), .....]

    If I change the list from type Decimal to type float, then I don't
    get the error. Likewise, if I use Python 2.7, I also don't get an error.

    After reading over the error message, I realize that this error
    really results because of numpy, not matplotlib. But I'll go ahead
    and post this message, in case you are unaware of the problem.

Just a quick note, mpl v1.1.x is not officially supported for py3k. The
upcoming release of v1.2.0 will be the first official release with such
support.

That being said, it probably would be a good idea to make sure where the
bug lies for this one (numpy or matplotlib). Which version of numpy are
you using?

Should this be considered a bug? Or should we say that we don't support
Decimal inputs? If we are going to support Decimal inputs, then we need
to put in filters to force conversion to float. Do you want to have to
check every entry in every list input to see if it Decimal?

Eric

Ben Root

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I am using numpy 1.7, which I built myself (python3 setup.py build). I had a chance to look a bit deeper into matplotlib, which in turn forced me to learn a bit of numpy, and now I see that it probably makes more sense to use numpy arrays for my data. Since the default for an array is a float, most users won’t encounter the problems I did, but a warning in a FAQ might solve a few headaches, regardless of how the developers decided to go.

Thanks for your help.

Paul

···

On Tue, Sep 4, 2012 at 3:09 PM, Benjamin Root <ben.root@…1304…> wrote:

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay <paulhtremblay@…287…> wrote:

The following Python code:

ax.fill_between(dates, lower, upper, facecolor=‘gray’, alpha=0.5)

Produces this error with Python 3.2:

Traceback (most recent call last):
File “scripts/audit_reports_weekly.py”, line 150, in

ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

File “/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py”, line 6741, in fill_between
y1 = ma.masked_invalid(self.convert_yunits(y1))

File “/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py”, line 2241, in masked_invalid
condition = ~(np.isfinite(a))
TypeError: ufunc ‘isfinite’ not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ‘‘safe’’

[Decimal(‘3619.900530366609820157812617’), …]

If I change the list from type Decimal to type float, then I don’t get the error. Likewise, if I use Python 2.7, I also don’t get an error.

After reading over the error message, I realize that this error really results because of numpy, not matplotlib. But I’ll go ahead and post this message, in case you are unaware of the problem.

Just a quick note, mpl v1.1.x is not officially supported for py3k. The upcoming release of v1.2.0 will be the first official release with such support.

That being said, it probably would be a good idea to make sure where the bug lies for this one (numpy or matplotlib). Which version of numpy are you using?

Ben Root

I am using numpy 1.7, which I built myself (python3 setup.py build). I
had a chance to look a bit deeper into matplotlib, which in turn forced
me to learn a bit of numpy, and now I see that it probably makes more
sense to use numpy arrays for my data. Since the default for an array is
a float, most users won't encounter the problems I did, but a warning in
a FAQ might solve a few headaches, regardless of how the developers
decided to go.

Paul,

numpy 1.7 has a new datetime dtype which probably would be good for your use--except that mpl doesn't support it yet. That will be a project for mpl v1.3.

Eric

···

On 2012/09/05 4:04 PM, Paul Tremblay wrote:

Thanks for your help.

Paul

On Tue, Sep 4, 2012 at 3:09 PM, Benjamin Root <ben.root@…1304… > <mailto:ben.root@…1304…>> wrote:

    On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay > <paulhtremblay@…287… <mailto:paulhtremblay@…287…>> wrote:

        The following Python code:

         >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)

        Produces this error with Python 3.2:

        Traceback (most recent call last):
           File "scripts/audit_reports_weekly.py", line 150, in <module>
             ax.fill_between(dates, lower, upper, facecolor='gray',
        alpha=0.5)
           File
        "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
        line 6741, in fill_between
             y1 = ma.masked_invalid(self.convert_yunits(y1))
           File
        "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
        line 2241, in masked_invalid
             condition = ~(np.isfinite(a))
        TypeError: ufunc 'isfinite' not supported for the input types,
        and the inputs could not be safely coerced to any supported
        types according to the casting rule ''safe''

        [Decimal('3619.900530366609820157812617'), .....]

        If I change the list from type Decimal to type float, then I
        don't get the error. Likewise, if I use Python 2.7, I also don't
        get an error.

        After reading over the error message, I realize that this error
        really results because of numpy, not matplotlib. But I'll go
        ahead and post this message, in case you are unaware of the
        problem.

    Just a quick note, mpl v1.1.x is not officially supported for py3k.
    The upcoming release of v1.2.0 will be the first official release
    with such support.

    That being said, it probably would be a good idea to make sure where
    the bug lies for this one (numpy or matplotlib). Which version of
    numpy are you using?

    Ben Root

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_______________________________________________
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Hmm. I found that mpl handled my datetime objects just fine:

put the weeks on the x axis

dates are datetime.datetime

ax.plot(dates, defects)
ax.xaxis.set_major_formatter(
matplotlib.dates.DateFormatter(’%W’))

create an invisible line in order to

create a secondary x axis below

the first axis, which just has the month(s)

newax = fig.add_axes(ax.get_position())
newax.spines[‘bottom’].set_position((‘outward’, 25))
newax.patch.set_visible(False)
newax.yaxis.set_visible(False)

months are also datetime. However, I filtered out

all dates except the first date for each month

newax.plot_date(months, y, visible=False)
newax.xaxis.set_major_locator(
matplotlib.dates.MonthLocator()
)
newax.xaxis.set_major_formatter(
matplotlib.dates.DateFormatter(’%b’)
)

···

On Thu, Sep 6, 2012 at 12:02 AM, Eric Firing <efiring@…202…> wrote:

On 2012/09/05 4:04 PM, Paul Tremblay wrote:

I am using numpy 1.7, which I built myself (python3 setup.py build). I

had a chance to look a bit deeper into matplotlib, which in turn forced

me to learn a bit of numpy, and now I see that it probably makes more

sense to use numpy arrays for my data. Since the default for an array is

a float, most users won’t encounter the problems I did, but a warning in

a FAQ might solve a few headaches, regardless of how the developers

decided to go.

Paul,

numpy 1.7 has a new datetime dtype which probably would be good for your

use–except that mpl doesn’t support it yet. That will be a project for

mpl v1.3.

Eric

Thanks for your help.

Paul

On Tue, Sep 4, 2012 at 3:09 PM, Benjamin Root <ben.root@…1304… > > mailto:ben.root@...1304...> wrote:

On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay > >     <paulhtremblay@...287... <mailto:paulhtremblay@...287...>> wrote:
    The following Python code:
     >>ax.fill_between(dates, lower, upper, facecolor='gray', alpha=0.5)
    Produces this error with Python 3.2:
    Traceback (most recent call last):
       File "scripts/audit_reports_weekly.py", line 150, in <module>
         ax.fill_between(dates, lower, upper, facecolor='gray',
    alpha=0.5)
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
    line 6741, in fill_between
         y1 = ma.masked_invalid(self.convert_yunits(y1))
       File
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
    line 2241, in masked_invalid
         condition = ~(np.isfinite(a))
    TypeError: ufunc 'isfinite' not supported for the input types,
    and the inputs could not be safely coerced to any supported
    types according to the casting rule ''safe''
    [Decimal('3619.900530366609820157812617'), .....]
    If I change the list from type Decimal to type float, then I
    don't get the error. Likewise, if I use Python 2.7, I also don't
    get an error.
    After reading over the error message, I realize that this error
    really results because of numpy, not matplotlib. But I'll go
    ahead and post this message, in case you are unaware of the
    problem.
Just a quick note, mpl v1.1.x is not officially supported for py3k.
The upcoming release of v1.2.0 will be the first official release
with such support.
That being said, it probably would be a good idea to make sure where
the bug lies for this one (numpy or matplotlib).  Which version of
numpy are you using?
Ben Root

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threat landscape has changed and how IT managers can respond. Discussions

will include endpoint security, mobile security and the latest in malware

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will include endpoint security, mobile security and the latest in malware

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Hmm. I found that mpl handled my datetime objects just fine:

Right, mpl has handled python datetime objects for a long time, but the numpy array with a datetime dtype is a new and different object, and it will take a bit of work to support it properly.

Eric

···

On 2012/09/05 6:17 PM, Paul Tremblay wrote:

# put the weeks on the x axis
# dates are datetime.datetime
ax.plot(dates, defects)
ax.xaxis.set_major_formatter(
     matplotlib.dates.DateFormatter('%W'))

# create an invisible line in order to
# create a secondary x axis below
# the first axis, which just has the month(s)
newax = fig.add_axes(ax.get_position())
newax.spines['bottom'].set_position(('outward', 25))
newax.patch.set_visible(False)
newax.yaxis.set_visible(False)
# months are also datetime. However, I filtered out
# all dates except the first date for each month
newax.plot_date(months, y, visible=False)
newax.xaxis.set_major_locator(
     matplotlib.dates.MonthLocator()
)
newax.xaxis.set_major_formatter(
     matplotlib.dates.DateFormatter('%b')
)

On Thu, Sep 6, 2012 at 12:02 AM, Eric Firing <efiring@…202… > <mailto:efiring@…202…>> wrote:

    On 2012/09/05 4:04 PM, Paul Tremblay wrote:
     > I am using numpy 1.7, which I built myself (python3 setup.py
    build). I
     > had a chance to look a bit deeper into matplotlib, which in turn
    forced
     > me to learn a bit of numpy, and now I see that it probably makes more
     > sense to use numpy arrays for my data. Since the default for an
    array is
     > a float, most users won't encounter the problems I did, but a
    warning in
     > a FAQ might solve a few headaches, regardless of how the developers
     > decided to go.

    Paul,

    numpy 1.7 has a new datetime dtype which probably would be good for your
    use--except that mpl doesn't support it yet. That will be a project for
    mpl v1.3.

    Eric

     >
     > Thanks for your help.
     >
     > Paul
     >
     > On Tue, Sep 4, 2012 at 3:09 PM, Benjamin Root <ben.root@…1304… > <mailto:ben.root@…1304…> > > <mailto:ben.root@…1304…>> wrote:
     >
     > On Tue, Sep 4, 2012 at 2:20 PM, Paul Tremblay > > <paulhtremblay@…287… <mailto:paulhtremblay@…287…> > <mailto:paulhtremblay@…287…>> > wrote:
     >
     > The following Python code:
     >
     > >>ax.fill_between(dates, lower, upper, facecolor='gray',
    alpha=0.5)
     >
     > Produces this error with Python 3.2:
     >
     > Traceback (most recent call last):
     > File "scripts/audit_reports_weekly.py", line 150, in
    <module>
     > ax.fill_between(dates, lower, upper, facecolor='gray',
     > alpha=0.5)
     > File
     >
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/matplotlib/axes.py",
     > line 6741, in fill_between
     > y1 = ma.masked_invalid(self.convert_yunits(y1))
     > File
     >
    "/home/local/ANT/ptrembl/.local/lib/python3.2/site-packages/numpy/ma/core.py",
     > line 2241, in masked_invalid
     > condition = ~(np.isfinite(a))
     > TypeError: ufunc 'isfinite' not supported for the input
    types,
     > and the inputs could not be safely coerced to any supported
     > types according to the casting rule ''safe''
     >
     > [Decimal('3619.900530366609820157812617'), …]
     >
     > If I change the list from type Decimal to type float, then I
     > don't get the error. Likewise, if I use Python 2.7, I
    also don't
     > get an error.
     >
     > After reading over the error message, I realize that this
    error
     > really results because of numpy, not matplotlib. But I'll go
     > ahead and post this message, in case you are unaware of the
     > problem.
     >
     > Just a quick note, mpl v1.1.x is not officially supported for
    py3k.
     > The upcoming release of v1.2.0 will be the first official release
     > with such support.
     >
     > That being said, it probably would be a good idea to make
    sure where
     > the bug lies for this one (numpy or matplotlib). Which
    version of
     > numpy are you using?
     >
     > Ben Root
     >
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Pedantic: numpy’s datetime64 dtype, not datetime.

Ben Root

···

On Thu, Sep 6, 2012 at 2:24 AM, Eric Firing <efiring@…202…> wrote:

On 2012/09/05 6:17 PM, Paul Tremblay wrote:

Hmm. I found that mpl handled my datetime objects just fine:

Right, mpl has handled python datetime objects for a long time, but the

numpy array with a datetime dtype is a new and different object, and it

will take a bit of work to support it properly.

Eric