This file is indexed.

/usr/lib/python2.7/dist-packages/mpmath/visualization.py is in python-mpmath 0.19-3.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
"""
Plotting (requires matplotlib)
"""

from colorsys import hsv_to_rgb, hls_to_rgb
from .libmp import NoConvergence
from .libmp.backend import xrange

class VisualizationMethods(object):
    plot_ignore = (ValueError, ArithmeticError, ZeroDivisionError, NoConvergence)

def plot(ctx, f, xlim=[-5,5], ylim=None, points=200, file=None, dpi=None,
    singularities=[], axes=None):
    r"""
    Shows a simple 2D plot of a function `f(x)` or list of functions
    `[f_0(x), f_1(x), \ldots, f_n(x)]` over a given interval
    specified by *xlim*. Some examples::

        plot(lambda x: exp(x)*li(x), [1, 4])
        plot([cos, sin], [-4, 4])
        plot([fresnels, fresnelc], [-4, 4])
        plot([sqrt, cbrt], [-4, 4])
        plot(lambda t: zeta(0.5+t*j), [-20, 20])
        plot([floor, ceil, abs, sign], [-5, 5])

    Points where the function raises a numerical exception or
    returns an infinite value are removed from the graph.
    Singularities can also be excluded explicitly
    as follows (useful for removing erroneous vertical lines)::

        plot(cot, ylim=[-5, 5])   # bad
        plot(cot, ylim=[-5, 5], singularities=[-pi, 0, pi])  # good

    For parts where the function assumes complex values, the
    real part is plotted with dashes and the imaginary part
    is plotted with dots.

    .. note :: This function requires matplotlib (pylab).
    """
    if file:
        axes = None
    fig = None
    if not axes:
        import pylab
        fig = pylab.figure()
        axes = fig.add_subplot(111)
    if not isinstance(f, (tuple, list)):
        f = [f]
    a, b = xlim
    colors = ['b', 'r', 'g', 'm', 'k']
    for n, func in enumerate(f):
        x = ctx.arange(a, b, (b-a)/float(points))
        segments = []
        segment = []
        in_complex = False
        for i in xrange(len(x)):
            try:
                if i != 0:
                    for sing in singularities:
                        if x[i-1] <= sing and x[i] >= sing:
                            raise ValueError
                v = func(x[i])
                if ctx.isnan(v) or abs(v) > 1e300:
                    raise ValueError
                if hasattr(v, "imag") and v.imag:
                    re = float(v.real)
                    im = float(v.imag)
                    if not in_complex:
                        in_complex = True
                        segments.append(segment)
                        segment = []
                    segment.append((float(x[i]), re, im))
                else:
                    if in_complex:
                        in_complex = False
                        segments.append(segment)
                        segment = []
                    if hasattr(v, "real"):
                        v = v.real
                    segment.append((float(x[i]), v))
            except ctx.plot_ignore:
                if segment:
                    segments.append(segment)
                segment = []
        if segment:
            segments.append(segment)
        for segment in segments:
            x = [s[0] for s in segment]
            y = [s[1] for s in segment]
            if not x:
                continue
            c = colors[n % len(colors)]
            if len(segment[0]) == 3:
                z = [s[2] for s in segment]
                axes.plot(x, y, '--'+c, linewidth=3)
                axes.plot(x, z, ':'+c, linewidth=3)
            else:
                axes.plot(x, y, c, linewidth=3)
    axes.set_xlim([float(_) for _ in xlim])
    if ylim:
        axes.set_ylim([float(_) for _ in ylim])
    axes.set_xlabel('x')
    axes.set_ylabel('f(x)')
    axes.grid(True)
    if fig:
        if file:
            pylab.savefig(file, dpi=dpi)
        else:
            pylab.show()

def default_color_function(ctx, z):
    if ctx.isinf(z):
        return (1.0, 1.0, 1.0)
    if ctx.isnan(z):
        return (0.5, 0.5, 0.5)
    pi = 3.1415926535898
    a = (float(ctx.arg(z)) + ctx.pi) / (2*ctx.pi)
    a = (a + 0.5) % 1.0
    b = 1.0 - float(1/(1.0+abs(z)**0.3))
    return hls_to_rgb(a, b, 0.8)

def cplot(ctx, f, re=[-5,5], im=[-5,5], points=2000, color=None,
    verbose=False, file=None, dpi=None, axes=None):
    """
    Plots the given complex-valued function *f* over a rectangular part
    of the complex plane specified by the pairs of intervals *re* and *im*.
    For example::

        cplot(lambda z: z, [-2, 2], [-10, 10])
        cplot(exp)
        cplot(zeta, [0, 1], [0, 50])

    By default, the complex argument (phase) is shown as color (hue) and
    the magnitude is show as brightness. You can also supply a
    custom color function (*color*). This function should take a
    complex number as input and return an RGB 3-tuple containing
    floats in the range 0.0-1.0.

    To obtain a sharp image, the number of points may need to be
    increased to 100,000 or thereabout. Since evaluating the
    function that many times is likely to be slow, the 'verbose'
    option is useful to display progress.

    .. note :: This function requires matplotlib (pylab).
    """
    if color is None:
        color = ctx.default_color_function
    import pylab
    if file:
        axes = None
    fig = None
    if not axes:
        fig = pylab.figure()
        axes = fig.add_subplot(111)
    rea, reb = re
    ima, imb = im
    dre = reb - rea
    dim = imb - ima
    M = int(ctx.sqrt(points*dre/dim)+1)
    N = int(ctx.sqrt(points*dim/dre)+1)
    x = pylab.linspace(rea, reb, M)
    y = pylab.linspace(ima, imb, N)
    # Note: we have to be careful to get the right rotation.
    # Test with these plots:
    #   cplot(lambda z: z if z.real < 0 else 0)
    #   cplot(lambda z: z if z.imag < 0 else 0)
    w = pylab.zeros((N, M, 3))
    for n in xrange(N):
        for m in xrange(M):
            z = ctx.mpc(x[m], y[n])
            try:
                v = color(f(z))
            except ctx.plot_ignore:
                v = (0.5, 0.5, 0.5)
            w[n,m] = v
        if verbose:
            print(str(n) + ' of ' + str(N))
    rea, reb, ima, imb = [float(_) for _ in [rea, reb, ima, imb]]
    axes.imshow(w, extent=(rea, reb, ima, imb), origin='lower')
    axes.set_xlabel('Re(z)')
    axes.set_ylabel('Im(z)')
    if fig:
        if file:
            pylab.savefig(file, dpi=dpi)
        else:
            pylab.show()

def splot(ctx, f, u=[-5,5], v=[-5,5], points=100, keep_aspect=True, \
          wireframe=False, file=None, dpi=None, axes=None):
    """
    Plots the surface defined by `f`.

    If `f` returns a single component, then this plots the surface
    defined by `z = f(x,y)` over the rectangular domain with
    `x = u` and `y = v`.

    If `f` returns three components, then this plots the parametric
    surface `x, y, z = f(u,v)` over the pairs of intervals `u` and `v`.

    For example, to plot a simple function::

        >>> from mpmath import *
        >>> f = lambda x, y: sin(x+y)*cos(y)
        >>> splot(f, [-pi,pi], [-pi,pi])    # doctest: +SKIP

    Plotting a donut::

        >>> r, R = 1, 2.5
        >>> f = lambda u, v: [r*cos(u), (R+r*sin(u))*cos(v), (R+r*sin(u))*sin(v)]
        >>> splot(f, [0, 2*pi], [0, 2*pi])    # doctest: +SKIP

    .. note :: This function requires matplotlib (pylab) 0.98.5.3 or higher.
    """
    import pylab
    import mpl_toolkits.mplot3d as mplot3d
    if file:
        axes = None
    fig = None
    if not axes:
        fig = pylab.figure()
        axes = mplot3d.axes3d.Axes3D(fig)
    ua, ub = u
    va, vb = v
    du = ub - ua
    dv = vb - va
    if not isinstance(points, (list, tuple)):
        points = [points, points]
    M, N = points
    u = pylab.linspace(ua, ub, M)
    v = pylab.linspace(va, vb, N)
    x, y, z = [pylab.zeros((M, N)) for i in xrange(3)]
    xab, yab, zab = [[0, 0] for i in xrange(3)]
    for n in xrange(N):
        for m in xrange(M):
            fdata = f(ctx.convert(u[m]), ctx.convert(v[n]))
            try:
                x[m,n], y[m,n], z[m,n] = fdata
            except TypeError:
                x[m,n], y[m,n], z[m,n] = u[m], v[n], fdata
            for c, cab in [(x[m,n], xab), (y[m,n], yab), (z[m,n], zab)]:
                if c < cab[0]:
                    cab[0] = c
                if c > cab[1]:
                    cab[1] = c
    if wireframe:
        axes.plot_wireframe(x, y, z, rstride=4, cstride=4)
    else:
        axes.plot_surface(x, y, z, rstride=4, cstride=4)
    axes.set_xlabel('x')
    axes.set_ylabel('y')
    axes.set_zlabel('z')
    if keep_aspect:
        dx, dy, dz = [cab[1] - cab[0] for cab in [xab, yab, zab]]
        maxd = max(dx, dy, dz)
        if dx < maxd:
            delta = maxd - dx
            axes.set_xlim3d(xab[0] - delta / 2.0, xab[1] + delta / 2.0)
        if dy < maxd:
            delta = maxd - dy
            axes.set_ylim3d(yab[0] - delta / 2.0, yab[1] + delta / 2.0)
        if dz < maxd:
            delta = maxd - dz
            axes.set_zlim3d(zab[0] - delta / 2.0, zab[1] + delta / 2.0)
    if fig:
        if file:
            pylab.savefig(file, dpi=dpi)
        else:
            pylab.show()


VisualizationMethods.plot = plot
VisualizationMethods.default_color_function = default_color_function
VisualizationMethods.cplot = cplot
VisualizationMethods.splot = splot