MMF Utils

Small set of utilities: containers and interfaces.

This package provides some utilities that I tend to rely on during development. Presently it includes some convenience containers, plotting tools, and a patch for including zope.interface documentation in a notebook.

(Note: If this file does not render properly, try viewing it through nbviewer.org)

Documentation: http://mmfutils.readthedocs.org

Source: https://bitbucket.org/mforbes/mmfutils

Issues: https://bitbucket.org/mforbes/mmfutils/issues

Build Status:

Main	Fork
mmfutils Build Status	mmfutils-fork Build Status

Table of Contents

Installing

This package can be installed from from the bitbucket project:

pip install hg+https://bitbucket.org/mforbes/mmfutils

Usage

Containers

Object

The Object object provides a base class to satisfy the following use-case.

Serialization and Deferred Initialization: Consider a problem where a class is defined through a few parameters, but requires extensive initialization before it can be properly used. An example is a numerical simulation where one passes the number of grid points N and a length L , but the initialization must generate large grids for efficient use later on. These grids should not be pickled when the object is serialized: instead, they should be generated at the end of initialization. By default, everything in __dict__ will be pickled, leading to bloated pickles. The solution here is to split initialization into two steps: __init__() should initialize everything that is picklable, then init() should do any further initialization, defining the grid points based on the values of the picklable attributes. To do this, the semantics of the __init__() method are changed slightly here. Object.__init__() registers all keys in __dict__ as self.picklable_attributes. These and only these attributes will be pickled (through the provided __getstate__ and __setstate__ methods).

The intended use is for subclasses to set and defined all attributes that should be pickled in the __init__() method, then call Object.__init__(self). Any additional initialization can be done after this call, or in the init() method (see below) and attributes defined after this point will be treated as temporary. Note, however, that unpickling an object will not call __init__() so any additional initialization required should be included in the init() method.

Deferred initialization via the ``init()`` method: The idea here is to defer any expensive initialization – especially that which creates large temporary data that should not be pickled – until later. This method is automatically called at the end of Object.__init__() and after restoring a pickle. A further use-case is to allow one to change many parameters, then reinitialize the object once with an explicit call to init().

Object Example

ROOTDIR = !hg root
ROOTDIR = ROOTDIR[0]
import sys;sys.path.insert(0, ROOTDIR)

import numpy as np

from mmfutils.containers import Object

class State(Object):
    def __init__(self, N, L=1.0):
        """This method should set all of the picklable
        parameters, in this case, N and L."""
        print("__init__() called")
        self.N = N
        self.L = L

        # Now register these and call init()
        Object.__init__(self)

    def init(self):
        """All additional initializations"""
        print("init() called")
        dx = self.L / self.N
        self.x = np.arange(self.N, dtype=float) * dx - self.L/2.0
        self.k = 2*np.pi * np.fft.fftfreq(self.N, dx)

        # Set highest momentum to zero if N is even to
        # avoid rapid oscillations
        if self.N % 2 == 0:
            self.k[self.N//2] = 0.0

    def compute_derivative(self, f):
        """Return the derivative of f."""
        return np.fft.ifft(self.k*1j*np.fft.fft(f)).real

s = State(256)
print s

__init__() called
init() called
State(L=1.0, N=256)

One feature is that a nice repr() of the object is produced. Now let’s do a calculation:

f = np.exp(3*np.cos(2*np.pi*s.x/s.L)) / 15
df = -2.*np.pi/5.*np.exp(3*np.cos(2*np.pi*s.x/s.L))*np.sin(2*np.pi*s.x/s.L)/s.L
np.allclose(s.compute_derivative(f), df)

True

Here we demonstrate pickling. Note that the pickle is very small, and when unpickled, init() is called to re-establish s.x and s.k.

import pickle
s_repr = pickle.dumps(s)
print(len(s_repr))
s1 = pickle.loads(s_repr)

169
init() called

Another use case applies when init() is expensive. If x and k were computed in __init__(), then using properties to change both N and L would trigger two updates. Here we do the updates, then call init(). Good practice is to call init() automatically before any serious calculation to ensure that the object is brought up to date before the computation.

s.N = 64
s.L = 2.0
s.init()

init() called

Finally, we demonstrate that Object instances can be archived using the persist package:

import persist.archive;reload(persist.archive)
a = persist.archive.Archive(check_on_insert=True)
a.insert(s=s)

d = {}
exec str(a) in d

d['s']

__init__() called
init() called

State(L=2.0, N=64)

Container

The Container object is a slight extension of Object that provides a simple container for storing data with attribute and iterative access. These implement some of the Collections Abstract Base Classes from the python standard library. The following containers are provided:

• Container: Bare-bones container extending the Sized, Iterable, and Container abstract ase classes (ABCs) from the standard containers library.
• ContainerList: Extension that acts like a tuple/list satisfying the Sequence ABC from the containers library (but not the MutableSequence ABC. Although we allow setting and deleting items, we do not provide a way for insertion, which breaks this interface.)
• ContainerDict: Extension that acts like a dict satisfying the MutableMapping ABC from the containers library.

These were designed with the following use cases in mind:

• Returning data from a function associating names with each data. The resulting ContainerList will act like a tuple, but will support attribute access. Note that the order will be lexicographic. One could use a dictionary, but attribute access with tab completion is much nicer in an interactive session. The containers.nametuple generator could also be used, but this is somewhat more complicated (though might be faster). Also, named tuples are immutable - here we provide a mutable object that is picklable etc. The choice between ContainerList and ContainerDict will depend on subsequent usage. Containers can be converted from one type to another.

Container Examples

from mmfutils.containers import Container

c = Container(a=1, c=2, b='Hi there')
print c
print tuple(c)

Container(a=1, b='Hi there', c=2)
(1, 'Hi there', 2)

# Attributes are mutable
c.b = 'Ho there'
print c

Container(a=1, b='Ho there', c=2)

# Other attributes can be used for temporary storage but will not be pickled.
import numpy as np

c.large_temporary_array = np.ones((256,256))
print c
print c.large_temporary_array

Container(a=1, b='Ho there', c=2)
[[ 1.  1.  1. ...,  1.  1.  1.]
 [ 1.  1.  1. ...,  1.  1.  1.]
 [ 1.  1.  1. ...,  1.  1.  1.]
 ...,
 [ 1.  1.  1. ...,  1.  1.  1.]
 [ 1.  1.  1. ...,  1.  1.  1.]
 [ 1.  1.  1. ...,  1.  1.  1.]]

import pickle
c1 = pickle.loads(pickle.dumps(c))
print c1
c1.large_temporary_array

Container(a=1, b='Ho there', c=2)

---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

<ipython-input-9-c6cad315ac19> in <module>()
      2 c1 = pickle.loads(pickle.dumps(c))
      3 print c1
----> 4 c1.large_temporary_array


AttributeError: 'Container' object has no attribute 'large_temporary_array'

Contexts

The mmfutils.contexts module provides two useful contexts:

NoInterrupt: This can be used to susspend KeyboardInterrupt exceptions until they can be dealt with at a point that is convenient. A typical use is when performing a series of calculations in a loop. By placing the loop in a NoInterrupt context, one can avoid an interrupt from ruining a calculation:

from mmfutils.contexts import NoInterrupt

complete = False
n = 0
with NoInterrupt() as interrupted:
    while not complete and not interrupted:
        n += 1
        if n > 10:
            complete = True

Note: One can nest NoInterrupt contexts so that outer loops are also interrupted.

Interfaces

The interfaces module collects some useful zope.interface tools for checking interface requirements. Interfaces provide a convenient way of communicating to a programmer what needs to be done to used your code. This can then be checked in tests.

from mmfutils.interface import Interface, Attribute, verifyClass, verifyObject, implements

class IAdder(Interface):
    """Interface for objects that support addition."""

    value = Attribute('value', "Current value of object")

    # No self here since this is the "user" interface
    def add(other):
        """Return self + other."""

Here is a broken implementation. We muck up the arguments to add:

class AdderBroken(object):
    implements(IAdder)

    def add(self, one, another):
        # There should only be one argument!
        return one + another

try:
    verifyClass(IAdder, AdderBroken)
except Exception, e:
    print("{0.__class__.__name__}: {0}".format(e))

BrokenMethodImplementation: The implementation of add violates its contract
        because implementation requires too many arguments.

Now we get add right, but forget to define value. This is only caught when we have an object since the attribute is supposed to be defined in __init__():

class AdderBroken(object):
    implements(IAdder)

    def add(self, other):
        return one + other

# The class validates...
verifyClass(IAdder, AdderBroken)

# ... but objects are missing the value Attribute
try:
    verifyObject(IAdder, AdderBroken())
except Exception, e:
    print("{0.__class__.__name__}: {0}".format(e))

BrokenImplementation: An object has failed to implement interface <InterfaceClass __main__.IAdder>

        The value attribute was not provided.

Finally, a working instance:

class Adder(object):
    implements(IAdder)
    def __init__(self, value=0):
        self.value = value
    def add(self, other):
        return one + other

verifyClass(IAdder, Adder) and verifyObject(IAdder, Adder())

True

Interface Documentation

We also monkeypatch zope.interface.documentation.asStructuredText() to provide a mechanism for documentating interfaces in a notebook.

from mmfutils.interface import describe_interface
describe_interface(IAdder)

Parallel

The mmfutils.parallel module provides some tools for launching and connecting to IPython clusters. The parallel.Cluster class represents and controls a cluster. The cluster is specified by the profile name, and can be started or stopped from this class:

import logging
logger = logging.getLogger()
logger.setLevel(logging.INFO)
import numpy as np
from mmfutils import parallel
cluster = parallel.Cluster(profile='default', n=3, sleep_time=1.0)
cluster.start()
cluster.wait()  # Instance of IPython.parallel.Client
view = cluster.load_balanced_view
x = np.linspace(-6,6, 100)
y = view.map(lambda x:x**2, x)
print np.allclose(y, x**2)
cluster.stop()

Waiting for connection file: ~/.ipython/profile_default/security/ipcontroller-client.json

INFO:root:Starting cluster: ipcluster start --daemonize --quiet --profile=default --n=3

Waiting for connection file: ~/.ipython/profile_default/security/ipcontroller-client.json

INFO:root:waiting for 3 engines
INFO:root:0 of 3 running
INFO:root:3 of 3 running
INFO:root:Stopping cluster: ipcluster stop --profile=default

True
Waiting for connection file: ~/.ipython/profile_default/security/ipcontroller-client.json

If you only need a cluster for a single task, it can be managed with a context. Be sure to wait for the result to be computed before exiting the context and shutting down the cluster!

with parallel.Cluster(profile='default', n=3, sleep_time=1.0) as client:
    view = client.load_balanced_view
    x = np.linspace(-6,6, 100)
    y = view.map(lambda x:x**2, x, block=True)  # Make sure to wait for the result!
print np.allclose(y, x**2)

Waiting for connection file: ~/.ipython/profile_default/security/ipcontroller-client.json

INFO:root:Starting cluster: ipcluster start --daemonize --quiet --profile=default --n=3

Waiting for connection file: ~/.ipython/profile_default/security/ipcontroller-client.json

INFO:root:waiting for 3 engines
INFO:root:0 of 3 running
INFO:root:3 of 3 running
INFO:root:Stopping cluster: ipcluster stop --profile=default

Waiting for connection file: ~/.ipython/profile_default/security/ipcontroller-client.json
True

If you just need to connect to a running cluster, you can use parallel.get_client().

Performance

The mmfutils.performance module provides some tools for high performance computing. Note: this module requires some additional packages including numexp, pyfftw, and the mkl package installed by anaconda. Some of these require building system libraries (i.e. the FFTW). However, the various components will not be imported by default.

Here is a brief description of the components:

• mmfutils.performance.blas: Provides an interface to a few of the scipy BLAS wrappers. Very incomplete (only things I currently need).
• mmfutils.performance.fft: Provides an interface to the FFTW using pyfftw if it is available. Also enables the planning cache and setting threads so you can better control your performance.
• mmfutils.performance.numexpr: Robustly imports numexpr and disabling the VML. (If you don’t do this carefully, it will crash your program so fast you won’t even get a traceback.)
• mmfutils.performance.threads: Provides some hooks for setting the maximum number of threads in a bunch of places including the MKL, numexpr, and fftw.

Plotting

Several tools are provided in mmfutils.plot:

Fast Filled Contour Plots

mmfutils.plot.imcontourf is similar to matplotlib’s plt.contourf function, but uses plt.imshow which is much faster. This is useful for animations and interactive work. It also supports my idea of saner array-shape processing (i.e. if x and y have different shapes, then it will match these to the shape of z). Matplotlib now provies plt.pcolourmesh which is similar, but has the same interface issues.

%matplotlib inline
from matplotlib import pyplot as plt
import time
import numpy as np
from mmfutils import plot as mmfplt
x = np.linspace(-1, 1, 100)[:, None]**3
y = np.linspace(-0.1, 0.1, 200)[None, :]**3
z = np.sin(10*x)*y**2
plt.figure(figsize=(12,3))
plt.subplot(141)
%time mmfplt.imcontourf(x, y, z, cmap='gist_heat')
plt.subplot(142)
%time plt.contourf(x.ravel(), y.ravel(), z.T, 50, cmap='gist_heat')
plt.subplot(143)
%time plt.pcolor(x.ravel(), y.ravel(), z.T, cmap='gist_heat')
plt.subplot(144)
%time plt.pcolormesh(x.ravel(), y.ravel(), z.T, cmap='gist_heat')

CPU times: user 9.77 ms, sys: 50 µs, total: 9.82 ms
Wall time: 9.86 ms
CPU times: user 43.5 ms, sys: 1.19 ms, total: 44.6 ms
Wall time: 44.7 ms
CPU times: user 426 ms, sys: 34.1 ms, total: 460 ms
Wall time: 450 ms
CPU times: user 2.39 ms, sys: 346 µs, total: 2.73 ms
Wall time: 2.74 ms

<matplotlib.collections.QuadMesh at 0x1209acd10>

Angular Variables

A couple of tools are provided to visualize angular fields, such as the phase of a complex wavefunction.

%matplotlib inline
from matplotlib import pyplot as plt
import time
import numpy as np
from mmfutils import plot as mmfplt;reload(mmfplt)
x = np.linspace(-1, 1, 100)[:, None]
y = np.linspace(-1, 1, 200)[None, :]
z = x + 1j*y

plt.figure(figsize=(9,2))
plt.subplot(131).set_aspect(1)
mmfplt.phase_contour(x, y, z, aspect=1, colors='k', linewidths=0.5)

# This is a little slow but allows you to vary the luminosity.
plt.subplot(132).set_aspect(1)
mmfplt.imcontourf(x, y, mmfplt.colors.color_complex(z), aspect=1)
mmfplt.phase_contour(x, y, z, aspect=1, linewidths=0.5)

# This is faster if you just want to show the phase and allows
# for a colorbar via a registered colormap
plt.subplot(133).set_aspect(1)
mmfplt.imcontourf(x, y, np.angle(z), cmap='huslp', aspect=1)
plt.colorbar()
mmfplt.phase_contour(x, y, z, aspect=1, linewidths=0.5)

(<matplotlib.contour.QuadContourSet at 0x11558d8d0>,
 <matplotlib.contour.QuadContourSet at 0x115630b10>)

Debugging

A couple of debugging tools are provided. The most useful is the debug decorator which will store the local variables of a function in a dictionary or in your global scope.

from mmfutils.debugging import debug

@debug(locals())
def f(x):
    y = x**1.5
    z = 2/x
    return z

print(f(2.0), x, y, z)

(1.0, 2.0, 2.8284271247461903, 1.0)

Mathematics

We include a few mathematical tools here too. In particular, numerical integration and differentiation. Check the API documentation for details.

Developer Instructions

If you are a developer of this package, there are a few things to be aware of.

1. If you modify the notebooks in docs/notebooks then you may need to regenerate some of the .rst files and commit them so they appear on bitbucket. This is done automatically by the pre-commit hook in .hgrc if you include this in your .hg/hgrc file with a line like:

   %include ../.hgrc
   

Security Warning: if you do this, be sure to inspect the .hgrc file carefully to make sure that no one inserts malicious code.

This runs the following code:

!cd $ROOTDIR; jupyter nbconvert --to=rst --output=README.rst doc/README.ipynb

[NbConvertApp] Converting notebook doc/README.ipynb to rst
[NbConvertApp] Support files will be in README_files/
[NbConvertApp] Making directory README_files
[NbConvertApp] Making directory README_files
[NbConvertApp] Writing 29492 bytes to README.rst

We also run a comprehensive set of tests, and the pre-commit hook will fail if any of these do not pass, or if we don’t have complete code coverage. This uses nosetests and flake8. To run individal tests do one of:

python setup.py nosetests
python setup.py flake8
python setup.py check
python setup.py test   # This runs them all using a custom command defined in setup.py

Here is an example:

!cd $ROOTDIR; python setup.py test

/data/apps/anaconda/envs/work/lib/python2.7/site-packages/setuptools-19.1.1-py2.7.egg/setuptools/dist.py:284: UserWarning: Normalizing '0.4.7dev' to '0.4.7.dev0'
running test
running nosetests
running egg_info
writing requirements to mmfutils.egg-info/requires.txt
writing mmfutils.egg-info/PKG-INFO
writing top-level names to mmfutils.egg-info/top_level.txt
writing dependency_links to mmfutils.egg-info/dependency_links.txt
reading manifest file 'mmfutils.egg-info/SOURCES.txt'
writing manifest file 'mmfutils.egg-info/SOURCES.txt'
nose.config: INFO: Set working dir to /Users/mforbes/work/mmfbb/mmfutils
nose.config: INFO: Ignoring files matching ['^\.', '^_', '^setup\.py$']
nose.plugins.cover: INFO: Coverage report will include only packages: ['mmfutils']
INFO:root:Patching zope.interface.document.asStructuredText to format code
INFO:root:Patching flake8 for issues 39 and 40
Doctest: mmfutils.containers.Container ... ok
Doctest: mmfutils.containers.ContainerDict ... ok
Doctest: mmfutils.containers.ContainerList ... ok
Doctest: mmfutils.containers.Object ... ok
Doctest: mmfutils.debugging.debug ... ok
Doctest: mmfutils.debugging.persistent_locals ... ok
Doctest: mmfutils.interface.describe_interface ... ok
Doctest: mmfutils.math.differentiate.differentiate ... ok
Doctest: mmfutils.math.differentiate.hessian ... ok
Test the Richardson extrapolation for the correct scaling behaviour. ... ok
Doctest: mmfutils.math.integrate.Richardson ... ok
Doctest: mmfutils.math.integrate.exact_add ... ok
Doctest: mmfutils.math.integrate.exact_sum ... ok
Doctest: mmfutils.math.integrate.mquad ... /Users/mforbes/work/mmfbb/mmfutils/mmfutils/math/integrate/__init__.py:1: RuntimeWarning: divide by zero encountered in double_scalars
  """Integration Utilities.
WARNING:root:mquad:MinStepSize: Minimum step size reached. (5.94368304574e-19 < 6.50521303491e-19) Singularity possible (err = 0.0).
WARNING:root:mquad:MinStepSize: Minimum step size reached. (5.94368304574e-19 < 6.50521303491e-19) Singularity possible (err = 1.98122768191e-19).
ok
Doctest: mmfutils.math.integrate.quad ... ok
Doctest: mmfutils.math.integrate.rsum ... ok
Doctest: mmfutils.math.integrate.ssum_inline ... ok
Doctest: mmfutils.math.integrate.ssum_python ... ok
Test directional first derivatives ... ok
Test directional second derivatives ... ok
Doctest: mmfutils.optimize.bracket_monotonic ... ok
Doctest: mmfutils.performance.fft.resample ... ok
Doctest: mmfutils.performance.numexpr ... ok
mmfutils.tests.test_containers.TestContainer.test_container_delattr ... ok
Test persistent representation of object class ... ok
Check that the order of attributes defined by ... ok
mmfutils.tests.test_containers.TestContainerConversion.test_conversions ... ok
mmfutils.tests.test_containers.TestContainerDict.test_container_del ... ok
mmfutils.tests.test_containers.TestContainerDict.test_container_setitem ... ok
mmfutils.tests.test_containers.TestContainerList.test_container_delitem ... ok
mmfutils.tests.test_containers.TestObject.test_empty_object ... ok
Test persistent representation of object class ... ok
mmfutils.tests.test_containers.TestPersist.test_archive ... ok
Doctest: mmfutils.tests.test_containers.Issue4 ... ok
mmfutils.tests.test_debugging.TestCoverage.test_coverage_1 ... ok
mmfutils.tests.test_debugging.TestCoverage.test_coverage_2 ... ok
mmfutils.tests.test_debugging.TestCoverage.test_coverage_3 ... ok
mmfutils.tests.test_debugging.TestCoverage.test_coverage_exception ... ok
Test 3rd order differentiation ... ok
mmfutils.tests.test_interface.TestInterfaces.test_verifyBrokenClass ... ok
mmfutils.tests.test_interface.TestInterfaces.test_verifyBrokenObject1 ... ok
mmfutils.tests.test_interface.TestInterfaces.test_verifyBrokenObject2 ... ok
mmfutils.tests.test_interface.TestInterfaces.test_verifyClass ... ok
mmfutils.tests.test_interface.TestInterfaces.test_verifyObject ... ok
Doctest: mmfutils.tests.test_interface.Doctests ... ok
mmfutils.tests.test_monkeypatchs.TestCoverage.test_cover_monkeypatchs ... INFO:root:Patching flake8 for issues 39 and 40
ok
mmfutils.tests.test_monkeypatchs.TestCoverage.test_flake8_patch_err ... INFO:root:Patching flake8 for issues 39 and 40
ok
[ProfileCreate] Generating default config file: u'/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A/profile_testing/ipython_config.py'
[ProfileCreate] Generating default config file: u'/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A/profile_testing/ipython_kernel_config.py'
[ProfileCreate] Generating default config file: u'/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A/profile_testing/ipcontroller_config.py'
[ProfileCreate] Generating default config file: u'/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A/profile_testing/ipengine_config.py'
[ProfileCreate] Generating default config file: u'/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A/profile_testing/ipcluster_config.py'
INFO:root:Starting cluster: ipcluster start --daemonize --quiet --profile=testing1 --n=7 --ipython-dir="/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A"
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
INFO:root:waiting for 1 engines
INFO:root:0 of 1 running
INFO:root:7 of 1 running
INFO:root:Starting cluster: ipcluster start --daemonize --quiet --profile=testing_pbs --n=3 --ipython-dir="/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A"
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
WARNING:root:No ipcontroller-client.json, waiting...
INFO:root:waiting for 1 engines
INFO:root:0 of 1 running
INFO:root:3 of 1 running
Simple test connecting to a cluster. ... INFO:root:waiting for 1 engines
INFO:root:7 of 1 running
ok
Test deleting of cluster objects ... ok
Test that starting a running cluster does nothing. ... ok
Test that the PBS_NODEFILE is used if defined ... INFO:root:waiting for 1 engines
INFO:root:3 of 1 running
INFO:root:waiting for 3 engines
INFO:root:3 of 3 running
INFO:root:Stopping cluster: ipcluster stop --profile=testing_pbs --ipython-dir="/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A"
2016-01-05 12:16:55.566 [IPClusterStop] Stopping cluster [pid=17497] with [signal=2]
ok
Test timeout (coverage) ... ok
mmfutils.tests.test_parallel.TestCluster.test_views ... DEBUG:root:Importing canning map
ok
INFO:root:Stopping cluster: ipcluster stop --profile=testing1 --ipython-dir="/var/folders/m7/dnr91tjs4gn58_t3k8zp_g000000gn/T/tmp9itx0A"
2016-01-05 12:16:56.330 [IPClusterStop] Stopping cluster [pid=17461] with [signal=2]
mmfutils.tests.test_performance_blas.Test_BLAS.test_daxpy ... ok
mmfutils.tests.test_performance_blas.Test_BLAS.test_ddot ... ok
mmfutils.tests.test_performance_blas.Test_BLAS.test_dnorm ... ok
mmfutils.tests.test_performance_blas.Test_BLAS.test_zaxpy ... ok
mmfutils.tests.test_performance_blas.Test_BLAS.test_zdotc ... ok
mmfutils.tests.test_performance_blas.Test_BLAS.test_znorm ... ok
mmfutils.tests.test_performance_fft.Test_FFT.test_fft ... ok
mmfutils.tests.test_performance_fft.Test_FFT.test_fftn ... ok
mmfutils.tests.test_performance_fft.Test_FFT_pyfftw.test_fft ... ok
mmfutils.tests.test_performance_fft.Test_FFT_pyfftw.test_fft_pyfftw ... ok
mmfutils.tests.test_performance_fft.Test_FFT_pyfftw.test_fftn ... ok
mmfutils.tests.test_performance_fft.Test_FFT_pyfftw.test_fftn_pyfftw ... ok
mmfutils.tests.test_performance_fft.Test_FFT_pyfftw.test_get_fft_pyfftw ... ok
mmfutils.tests.test_performance_fft.Test_FFT_pyfftw.test_get_fftn_pyfftw ... ok
mmfutils.tests.test_performance_threads.TestThreads.test_hook_mkl ... ok
mmfutils.tests.test_performance_threads.TestThreads.test_hooks_fft ... ok
mmfutils.tests.test_performance_threads.TestThreads.test_hooks_numexpr ... ok
mmfutils.tests.test_performance_threads.TestThreads.test_set_threads_fft ... ok
mmfutils.tests.test_performance_threads.TestThreads.test_set_threads_mkl ... ok
mmfutils.tests.test_performance_threads.TestThreads.test_set_threads_numexpr ... ok

Name                           Stmts   Miss  Cover   Missing
------------------------------------------------------------
mmfutils                           1      0   100%
mmfutils.containers               85      0   100%
mmfutils.debugging                47      0   100%
mmfutils.interface                70      0   100%
mmfutils.math                      0      0   100%
mmfutils.math.differentiate       61      0   100%
mmfutils.math.integrate          193      0   100%
mmfutils.monkeypatches            14      0   100%
mmfutils.optimize                 13      0   100%
mmfutils.parallel                124      2    98%   15-16
mmfutils.performance               0      0   100%
mmfutils.performance.blas         58      0   100%
mmfutils.performance.fft          61      0   100%
mmfutils.performance.numexpr      10      0   100%
mmfutils.performance.threads      10      0   100%
------------------------------------------------------------
TOTAL                            747      2    99%
----------------------------------------------------------------------
Ran 73 tests in 19.302s

OK

Complete code coverage information is provided in build/_coverage/index.html.

from IPython.display import HTML
with open(os.path.join(ROOTDIR, 'build/_coverage/index.html')) as f:
    coverage = f.read()
HTML(coverage)

Releases

We try to keep the repository clean with the following properties:

1. The default branch is stable: i.e. if someone runs hg clone, this will pull the latest stable release.
2. Each release has its own named branch so that e.g. hg up 0.4.6 will get the right thing. Note: this should update to the development branch, not the default branch so that any work committed will not pollute the development branch (which would violate the previous point).

To do this, we advocate the following proceedure.

1. ``hg up <version>``: Make sure this is the correct development branch, not the default branch. (Check by hg up default which should take you to the default branch.)

2. Work: Do your work, committing as required with messages as shown in the repository with the following keys:

   • DOC: Documentation changes.
   • API: Changes to the exising API. This could break old code.
   • EHN: Enhancement or new functionality. Without an API tag, these should not break existing codes.
   • BLD: Build system changes (setup.py, requirements.txt etc.)
   • TST: Update tests, code coverage, etc.
   • BUG: Address an issue as filed on the issue tracker.
   • BRN: Start a new branch (see below).
   • REL: Release (see below).
   • WIP: Work in progress. Do not depend on these! They will be stripped. This is useful when testing things like the rendering of documentation on bitbucket etc. where you need to push an incomplete set of files. Please collapse and strip these eventually when you get things working.
   • CHK: Checkpoints. These should not be pushed to bitbucket!

3. ``python setup.py test``: Make sure the tests pass. (hg com will do this automatically if you have linked the .hgrc file as discussed above.

4. Update Docs: Update the documentation if needed. To generate new documentation run:

   cd doc
   sphinx-apidoc -eTE ../mmfutils -o source
   rm source/mmfutis.tests.*
   

   Include any changes at the bottom of this file (doc/README.ipynb).

   Edit any new files created (titles often need to be added) and check that this looks good with

   make html
   open build/html/index.html
   

   Look especially for errors of the type WARNING: document isn't included in any toctree. This indicates that you probably need to add the module to an upper level .. toctree::. Also look for WARNING: toctree contains reference to document u'...' that doesn't have a title: no link will be generated. This indicates you need to add a title to a new file. For example, when I added the mmf.math.optimize module, I needed to update the following:

.. doc/source/mmfutils.rst
mmfutils
========

.. toctree::
    ...
    mmfutils.optimize
    ...

.. doc/source/mmfutils.optimize.rst
mmfutils.optimize
=================

.. automodule:: mmfutils.optimize
    :members:
    :undoc-members:
    :show-inheritance:

5. ``hg histedit``: (or hg rebase, or hg strip as needed) Clean up the repo before you push. Branches should generally be linear unless there is an exceptional reason to split development.

6. Release: First edit mmfutils/__init__.py and update the version number by removing the dev part of the version number. Commit only this change and then push only the branch you are working on:

   hg com -m "REL: <version>"
   hg push -b .
   

7. Create a pull request on the development fork from your branch to default on the release project bitbucket. Review it, fix anything, then accept the PR and close the branch.

8. Start new branch: On the same development branch (not default), increase the version number in mmfutils/__init__.py and add dev: i.e.:

   __version__ = '0.4.7dev'
   

Then create this branch and commit this:

hg branch "0.4.7"
hg com -m "BRN: Started branch 0.4.7"

9. Update MyPI index.
10. Optional: Update any setup.py files that depend on your new features/fixes etc.

Change Log

REL: 0.4.7

API changes:

• Added mmfutils.interface.describe_interface() for inserting interfaces into documentation.
• Added some DVR basis code to mmfutils.math.bases.
• Added a diverging colormap and some support in mmfutils.plot.
• Added a Wigner Ville distribution computation in mmfutils.math.wigner
• Added mmfutils.optimize.usolve and ubrentq for finding roots with `uncertanties <https://pythonhosted.org/uncertainties/>`__ support.

Issues:

• Resolve issue #8: Use `ipyparallel <https://github.com/ipython/ipyparallel>`__ now.
• Resolve issue #9: Use pytest rather than nose (which is no longer supported).
• Resolve issue #10: PYFFTW wrappers now support negative axis and axes arguments.
• Address issue #11: Preliminary version of some DVR basis classes.
• Resolve issue #12: Added solvers with `uncertanties <https://pythonhosted.org/uncertainties/>`__ support.