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<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="matplotlib.html"><font color="#ffffff">matplotlib</font></a>.numerix</strong></big></big></font></td
><td align=right valign=bottom
><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/usr/local/lib/python2.3/site-packages/matplotlib/numerix.py">/usr/local/lib/python2.3/site-packages/matplotlib/numerix.py</a></font></td></tr></table>
<p><tt>numerix imports either Numeric or numarray based on various selectors.<br>
<br>
0. If the value "--numarray" or "--Numeric" is specified on the<br>
command line, then numerix imports the specified array package.<br>
<br>
1. The value of numerix in ~/.matplotlibrc: either Numeric or numarray<br>
<br>
2. If the environment variable NUMERIX is defined as either "Numeric"<br>
or as "numarray", then numerix will import from the specified array package.<br>
<br>
3. If the file numerix or .numerix in the HOME directory of the current<br>
user contains a single line specifying either "Numeric" or "numarray",<br>
then the specified array package is imported.<br>
<br>
4. If none of the above is done, the default array package is Numeric.<br>
<br>
5. If the Numeric is selected and the import fails, numarray is tried.<br>
<br>
To summarize: the commandline is examined first, the rc file seconds,<br>
the environment third, the configuration file next, and the default<br>
array package is Numeric. If everything else fails, numarray is tried.</tt></p>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#aa55cc">
<td colspan=3 valign=bottom> <br>
<font color="#fffff" face="helvetica, arial"><big><strong>Modules</strong></big></font></td></tr>
<tr><td bgcolor="#aa55cc"><tt> </tt></td><td> </td>
<td width="100%"><table width="100%" summary="list"><tr><td width="25%" valign=top><a href="LinearAlgebra.html">LinearAlgebra</a><br>
<a href="MLab.html">MLab</a><br>
<a href="RandomArray.html">RandomArray</a><br>
</td><td width="25%" valign=top><a href="copy.html">copy</a><br>
<a href="copy_reg.html">copy_reg</a><br>
<a href="math.html">math</a><br>
</td><td width="25%" valign=top><a href="multiarray.html">multiarray</a><br>
<a href="os.html">os</a><br>
<a href="pickle.html">pickle</a><br>
</td><td width="25%" valign=top><a href="string.html">string</a><br>
<a href="sys.html">sys</a><br>
<a href="types.html">types</a><br>
</td></tr></table></td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
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<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Functions</strong></big></font></td></tr>
<tr><td bgcolor="#eeaa77"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt><a name="-arange"><strong>arange</strong></a>(...)</dt><dd><tt><a href="#-arange">arange</a>(start, stop=None, step=1, typecode=None)<br>
<br>
Just like range() except it returns an array whose type can be<br>
specified by the keyword argument typecode.</tt></dd></dl>
<dl><dt><a name="-array"><strong>array</strong></a>(...)</dt><dd><tt><a href="#-array">array</a>(sequence, typecode=None, copy=1, savespace=0) will return a new array formed from the given (potentially nested) sequence with type given by typecode. If no typecode is given, then the type will be determined as the minimum type required to hold the objects in sequence. If copy is zero and sequence is already an array, a reference will be returned. If savespace is nonzero, the new array will maintain its precision in operations.</tt></dd></dl>
<dl><dt><a name="-arrayrange"><strong>arrayrange</strong></a> = arange(...)</dt><dd><tt><a href="#-arange">arange</a>(start, stop=None, step=1, typecode=None)<br>
<br>
Just like range() except it returns an array whose type can be<br>
specified by the keyword argument typecode.</tt></dd></dl>
<dl><dt><a name="-choose"><strong>choose</strong></a>(...)</dt><dd><tt><a href="#-choose">choose</a>(a, (b1,b2,...))</tt></dd></dl>
<dl><dt><a name="-cross_correlate"><strong>cross_correlate</strong></a>(...)</dt><dd><tt><a href="#-cross_correlate">cross_correlate</a>(a,v, mode=0)</tt></dd></dl>
<dl><dt><a name="-fromstring"><strong>fromstring</strong></a>(...)</dt><dd><tt><a href="#-fromstring">fromstring</a>(string, typecode='l', count=-1) returns a new 1d array initialized from the raw binary data in string. If count is positive, the new array will have count elements, otherwise it's size is determined by the size of string.</tt></dd></dl>
<dl><dt><a name="-get_which"><strong>get_which</strong></a>(home, file)</dt></dl>
<dl><dt><a name="-reshape"><strong>reshape</strong></a>(...)</dt><dd><tt><a href="#-reshape">reshape</a>(a, (d1, d2, ..., dn)). Change the shape of a to be an n-dimensional array with dimensions given by d1...dn. Note: the size specified for the new array must be exactly equal to the size of the old one or an error will occur.</tt></dd></dl>
<dl><dt><a name="-searchsorted"><strong>searchsorted</strong></a> = binarysearch(...)</dt><dd><tt>binarysearch(a,v)</tt></dd></dl>
<dl><dt><a name="-take"><strong>take</strong></a>(...)</dt><dd><tt><a href="#-take">take</a>(a, indices, axis=0). Selects the elements in indices from array a along the given axis.</tt></dd></dl>
<dl><dt><a name="-zeros"><strong>zeros</strong></a>(...)</dt><dd><tt><a href="#-zeros">zeros</a>((d1,...,dn),typecode='l',savespace=0) will return a new array of shape (d1,...,dn) and type typecode with all it's entries initialized to zero. If savespace is nonzero the array will be a spacesaver array.</tt></dd></dl>
</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
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<font color="#ffffff" face="helvetica, arial"><big><strong>Data</strong></big></font></td></tr>
<tr><td bgcolor="#55aa55"><tt> </tt></td><td> </td>
<td width="100%"><strong>Character</strong> = 'c'<br>
<strong>Complex</strong> = 'D'<br>
<strong>Complex0</strong> = 'F'<br>
<strong>Complex16</strong> = 'F'<br>
<strong>Complex32</strong> = 'F'<br>
<strong>Complex64</strong> = 'D'<br>
<strong>Complex8</strong> = 'F'<br>
<strong>Float</strong> = 'd'<br>
<strong>Float0</strong> = 'f'<br>
<strong>Float16</strong> = 'f'<br>
<strong>Float32</strong> = 'f'<br>
<strong>Float64</strong> = 'd'<br>
<strong>Float8</strong> = 'f'<br>
<strong>Int</strong> = 'l'<br>
<strong>Int0</strong> = '1'<br>
<strong>Int16</strong> = 's'<br>
<strong>Int32</strong> = 'i'<br>
<strong>Int8</strong> = '1'<br>
<strong>LittleEndian</strong> = True<br>
<strong>NewAxis</strong> = None<br>
<strong>PrecisionError</strong> = 'PrecisionError'<br>
<strong>PyObject</strong> = 'O'<br>
<strong>UInt</strong> = 'u'<br>
<strong>UInt16</strong> = 'w'<br>
<strong>UInt32</strong> = 'u'<br>
<strong>UInt8</strong> = 'b'<br>
<strong>UnsignedInt16</strong> = 'w'<br>
<strong>UnsignedInt32</strong> = 'u'<br>
<strong>UnsignedInt8</strong> = 'b'<br>
<strong>UnsignedInteger</strong> = 'u'<br>
<strong>a</strong> = 'matplotlib.transforms'<br>
<strong>absolute</strong> = <ufunc 'absolute'><br>
<strong>add</strong> = <ufunc 'add'><br>
<strong>arccos</strong> = <ufunc 'arccos'><br>
<strong>arccosh</strong> = <ufunc 'arccosh'><br>
<strong>arcsin</strong> = <ufunc 'arcsin'><br>
<strong>arcsinh</strong> = <ufunc 'arcsinh'><br>
<strong>arctan</strong> = <ufunc 'arctan'><br>
<strong>arctan2</strong> = <ufunc 'arctan2'><br>
<strong>arctanh</strong> = <ufunc 'arctanh'><br>
<strong>bitwise_and</strong> = <ufunc 'bitwise_and'><br>
<strong>bitwise_or</strong> = <ufunc 'bitwise_or'><br>
<strong>bitwise_xor</strong> = <ufunc 'bitwise_xor'><br>
<strong>ceil</strong> = <ufunc 'ceil'><br>
<strong>conjugate</strong> = <ufunc 'conjugate'><br>
<strong>cos</strong> = <ufunc 'cos'><br>
<strong>cosh</strong> = <ufunc 'cosh'><br>
<strong>divide</strong> = <ufunc 'divide'><br>
<strong>divide_safe</strong> = <ufunc 'divide_safe'><br>
<strong>e</strong> = 2.7182818284590451<br>
<strong>equal</strong> = <ufunc 'equal'><br>
<strong>exp</strong> = <ufunc 'exp'><br>
<strong>fabs</strong> = <ufunc 'fabs'><br>
<strong>floor</strong> = <ufunc 'floor'><br>
<strong>floor_divide</strong> = <ufunc 'floor_divide'><br>
<strong>fmod</strong> = <ufunc 'fmod'><br>
<strong>greater</strong> = <ufunc 'greater'><br>
<strong>greater_equal</strong> = <ufunc 'greater_equal'><br>
<strong>hypot</strong> = <ufunc 'hypot'><br>
<strong>invert</strong> = <ufunc 'invert'><br>
<strong>left_shift</strong> = <ufunc 'left_shift'><br>
<strong>less</strong> = <ufunc 'less'><br>
<strong>less_equal</strong> = <ufunc 'less_equal'><br>
<strong>log</strong> = <ufunc 'log'><br>
<strong>log10</strong> = <ufunc 'log10'><br>
<strong>logical_and</strong> = <ufunc 'logical_and'><br>
<strong>logical_not</strong> = <ufunc 'logical_not'><br>
<strong>logical_or</strong> = <ufunc 'logical_or'><br>
<strong>logical_xor</strong> = <ufunc 'logical_xor'><br>
<strong>maximum</strong> = <ufunc 'maximum'><br>
<strong>minimum</strong> = <ufunc 'minimum'><br>
<strong>multiply</strong> = <ufunc 'multiply'><br>
<strong>negative</strong> = <ufunc 'negative'><br>
<strong>not_equal</strong> = <ufunc 'not_equal'><br>
<strong>pi</strong> = 3.1415926535897931<br>
<strong>power</strong> = <ufunc 'power'><br>
<strong>rcParams</strong> = {'axes.edgecolor': 'k', 'axes.facecolor': 'w', 'axes.grid': False, 'axes.labelcolor': 'k', 'axes.labelsize': 12.0, 'axes.linewidth': 0.5, 'axes.titlesize': 14.0, 'backend': 'GTKAgg', 'datapath': '/usr/local/share/matplotlib', 'figure.dpi': 80.0, ...}<br>
<strong>remainder</strong> = <ufunc 'remainder'><br>
<strong>right_shift</strong> = <ufunc 'right_shift'><br>
<strong>sin</strong> = <ufunc 'sin'><br>
<strong>sinh</strong> = <ufunc 'sinh'><br>
<strong>sqrt</strong> = <ufunc 'sqrt'><br>
<strong>subtract</strong> = <ufunc 'subtract'><br>
<strong>tan</strong> = <ufunc 'tan'><br>
<strong>tanh</strong> = <ufunc 'tanh'><br>
<strong>true_divide</strong> = <ufunc 'true_divide'><br>
<strong>typecodes</strong> = {'Character': 'c', 'Complex': 'FD', 'Float': 'fd', 'Integer': '1sil', 'UnsignedInteger': 'bwu'}<br>
<strong>which</strong> = ('numeric', 'rc')</td></tr></table>
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