File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 23, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 20, in recsum
if n == 1:
RuntimeError: maximum recursion depth exceeded in cmp
In [11]: runfile('/Users/progprim/Desktop/factorial.py', wdir='/Users/progprim/Desktop')
In [12]: recsum(0.5)
Traceback (most recent call last):
File "<ipython-input-12-ef3a6ecd4510>", line 1, in <module>
recsum(0.5)
File "/Users/progprim/Desktop/factorial.py", line 21, in recsum
raise ValueError("n={}<1 -- don't know what to do.".format(n))
ValueError: n=0.5<1 -- don't know what to do.
In [13]: recsum(1.5)
Traceback (most recent call last):
File "<ipython-input-13-6bbc08a73508>", line 1, in <module>
recsum(1.5)
File "/Users/progprim/Desktop/factorial.py", line 25, in recsum
return n + recsum(n - 1)
File "/Users/progprim/Desktop/factorial.py", line 21, in recsum
raise ValueError("n={}<1 -- don't know what to do.".format(n))
ValueError: n=0.5<1 -- don't know what to do.
In [14]: import numpy
In [15]: a = numpy.array([1, 4 ,10])
In [16]: a
Out[16]: array([ 1, 4, 10])
In [17]: type(a)
Out[17]: numpy.ndarray
In [18]: a.shape
Out[18]: (3,)
In [19]: B = array([[0., 1.5], [10., 12]])
Traceback (most recent call last):
File "<ipython-input-19-fcd019bd5ab7>", line 1, in <module>
B = array([[0., 1.5], [10., 12]])
NameError: name 'array' is not defined
In [20]: B = numpy.array([[0., 1.5], [10., 12]])
In [21]: B
Out[21]:
array([[ 0. , 1.5],
[ 10. , 12. ]])
In [22]: B.shape
Out[22]: (2, 2)
In [23]: a.dtype
Out[23]: dtype('int64')
In [24]: a
Out[24]: array([ 1, 4, 10])
In [25]: B.dtype
Out[25]: dtype('float64')
In [26]: a
Out[26]: array([ 1, 4, 10])
In [27]: a * 10
Out[27]: array([ 10, 40, 100])
In [28]: numpy.array(range(5))
Out[28]: array([0, 1, 2, 3, 4])
In [29]: numpy.array(range(5))*2
Out[29]: array([0, 2, 4, 6, 8])
In [30]: numpy.arange(5)
Out[30]: array([0, 1, 2, 3, 4])
In [31]: numpy.arange(5, 15)
Out[31]: array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14])
In [32]: numpy.arange(5, 15, 2)
Out[32]: array([ 5, 7, 9, 11, 13])
In [33]: numpy.arange(5, 15, 0.5)
Out[33]:
array([ 5. , 5.5, 6. , 6.5, 7. , 7.5, 8. , 8.5, 9. ,
9.5, 10. , 10.5, 11. , 11.5, 12. , 12.5, 13. , 13.5,
14. , 14.5])
In [34]: range(10)
Out[34]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
In [35]: numpy.linspace(0, 15, 8)
Out[35]:
array([ 0. , 2.14285714, 4.28571429, 6.42857143,
8.57142857, 10.71428571, 12.85714286, 15. ])
In [36]: a
Out[36]: array([ 1, 4, 10])
In [37]: a * 100
Out[37]: array([ 100, 400, 1000])
In [38]: a + 42
Out[38]: array([43, 46, 52])
In [39]: a**2
Out[39]: array([ 1, 16, 100])
In [40]: numpy.sqrt(a)
Out[40]: array([ 1. , 2. , 3.16227766])
In [41]: import math
In [42]: math.sqrt(a)
Traceback (most recent call last):
File "<ipython-input-42-c7d50051514f>", line 1, in <module>
math.sqrt(a)
TypeError: only length-1 arrays can be converted to Python scalars
In [43]: a
Out[43]: array([ 1, 4, 10])
In [44]: a > 2
Out[44]: array([False, True, True], dtype=bool)
In [45]: a.size
Out[45]: 3
In [46]: a
Out[46]: array([ 1, 4, 10])
In [47]: B
Out[47]:
array([[ 0. , 1.5],
[ 10. , 12. ]])
In [48]: B.size
Out[48]: 4
In [49]: B.nbytes
Out[49]: 32
In [50]: a = numpy.array([1, 4 ,10.])
In [51]: a
Out[51]: array([ 1., 4., 10.])
In [52]: a = numpy.array([1, 4 ,10], numpy.float)
In [53]: a
Out[53]: array([ 1., 4., 10.])
In [54]: numpy.zeros((4, 3))
Out[54]:
array([[ 0., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.]])
In [55]: C = numpy.zeros((4, 3))
In [56]: C[1,0] = 100
In [57]: C
Out[57]:
array([[ 0., 0., 0.],
[ 100., 0., 0.],
[ 0., 0., 0.],
[ 0., 0., 0.]])
In [58]: D = numpy.ones((4, 3))
In [59]: D
Out[59]:
array([[ 1., 1., 1.],
[ 1., 1., 1.],
[ 1., 1., 1.],
[ 1., 1., 1.]])
In [60]: a
Out[60]: array([ 1., 4., 10.])
In [61]: a[:-1]
Out[61]: array([ 1., 4.])
In [62]: B
Out[62]:
array([[ 0. , 1.5],
[ 10. , 12. ]])
In [63]: B[:, 0]
Out[63]: array([ 0., 10.])
In [64]: B[:, 1]
Out[64]: array([ 1.5, 12. ])
In [65]: B[0, :]
Out[65]: array([ 0. , 1.5])
In [66]: xs = numpy.linspace(0, 10, 200)
In [67]: ys = numpy.sin(xs)
In [68]: xs
Out[68]:
array([ 0. , 0.05025126, 0.10050251, 0.15075377,
0.20100503, 0.25125628, 0.30150754, 0.35175879,
0.40201005, 0.45226131, 0.50251256, 0.55276382,
0.60301508, 0.65326633, 0.70351759, 0.75376884,
0.8040201 , 0.85427136, 0.90452261, 0.95477387,
1.00502513, 1.05527638, 1.10552764, 1.15577889,
1.20603015, 1.25628141, 1.30653266, 1.35678392,
1.40703518, 1.45728643, 1.50753769, 1.55778894,
1.6080402 , 1.65829146, 1.70854271, 1.75879397,
1.80904523, 1.85929648, 1.90954774, 1.95979899,
2.01005025, 2.06030151, 2.11055276, 2.16080402,
2.21105528, 2.26130653, 2.31155779, 2.36180905,
2.4120603 , 2.46231156, 2.51256281, 2.56281407,
2.61306533, 2.66331658, 2.71356784, 2.7638191 ,
2.81407035, 2.86432161, 2.91457286, 2.96482412,
3.01507538, 3.06532663, 3.11557789, 3.16582915,
3.2160804 , 3.26633166, 3.31658291, 3.36683417,
3.41708543, 3.46733668, 3.51758794, 3.5678392 ,
3.61809045, 3.66834171, 3.71859296, 3.76884422,
3.81909548, 3.86934673, 3.91959799, 3.96984925,
4.0201005 , 4.07035176, 4.12060302, 4.17085427,
4.22110553, 4.27135678, 4.32160804, 4.3718593 ,
4.42211055, 4.47236181, 4.52261307, 4.57286432,
4.62311558, 4.67336683, 4.72361809, 4.77386935,
4.8241206 , 4.87437186, 4.92462312, 4.97487437,
5.02512563, 5.07537688, 5.12562814, 5.1758794 ,
5.22613065, 5.27638191, 5.32663317, 5.37688442,
5.42713568, 5.47738693, 5.52763819, 5.57788945,
5.6281407 , 5.67839196, 5.72864322, 5.77889447,
5.82914573, 5.87939698, 5.92964824, 5.9798995 ,
6.03015075, 6.08040201, 6.13065327, 6.18090452,
6.23115578, 6.28140704, 6.33165829, 6.38190955,
6.4321608 , 6.48241206, 6.53266332, 6.58291457,
6.63316583, 6.68341709, 6.73366834, 6.7839196 ,
6.83417085, 6.88442211, 6.93467337, 6.98492462,
7.03517588, 7.08542714, 7.13567839, 7.18592965,
7.2361809 , 7.28643216, 7.33668342, 7.38693467,
7.43718593, 7.48743719, 7.53768844, 7.5879397 ,
7.63819095, 7.68844221, 7.73869347, 7.78894472,
7.83919598, 7.88944724, 7.93969849, 7.98994975,
8.04020101, 8.09045226, 8.14070352, 8.19095477,
8.24120603, 8.29145729, 8.34170854, 8.3919598 ,
8.44221106, 8.49246231, 8.54271357, 8.59296482,
8.64321608, 8.69346734, 8.74371859, 8.79396985,
8.84422111, 8.89447236, 8.94472362, 8.99497487,
9.04522613, 9.09547739, 9.14572864, 9.1959799 ,
9.24623116, 9.29648241, 9.34673367, 9.39698492,
9.44723618, 9.49748744, 9.54773869, 9.59798995,
9.64824121, 9.69849246, 9.74874372, 9.79899497,
9.84924623, 9.89949749, 9.94974874, 10. ])
In [69]: ys
Out[69]:
array([ 0. , 0.05023011, 0.10033341, 0.15018339, 0.19965422,
0.24862099, 0.29696008, 0.34454944, 0.39126893, 0.43700061,
0.481629 , 0.52504145, 0.56712835, 0.60778345, 0.6469041 ,
0.68439153, 0.72015112, 0.75409257, 0.78613019, 0.8161831 ,
0.84417544, 0.87003651, 0.89370105, 0.91510929, 0.9342072 ,
0.95094655, 0.96528509, 0.97718662, 0.98662108, 0.99356467,
0.99799984, 0.99991541, 0.99930653, 0.99617474, 0.99052796,
0.98238043, 0.97175273, 0.95867168, 0.94317032, 0.92528777,
0.90506919, 0.88256563, 0.85783388, 0.8309364 , 0.80194109,
0.77092115, 0.7379549 , 0.70312557, 0.66652108, 0.62823386,
0.58836056, 0.54700186, 0.50426216, 0.46024937, 0.41507461,
0.36885193, 0.32169803, 0.27373195, 0.22507478, 0.17584939,
0.12618003, 0.07619211, 0.02601183, -0.02423412, -0.07441889,
-0.12441577, -0.17409855, -0.22334179, -0.27202116, -0.32001378,
-0.36719847, -0.41345611, -0.45866992, -0.50272574, -0.54551235,
-0.58692173, -0.62684933, -0.66519435, -0.70185999, -0.73675367,
-0.7697873 , -0.80087747, -0.82994571, -0.85691862, -0.88172811,
-0.90431153, -0.92461187, -0.94257789, -0.95816422, -0.97133152,
-0.98204653, -0.99028221, -0.99601778, -0.99923873, -0.99993695,
-0.99811068, -0.99376451, -0.98690943, -0.97756275, -0.96574805,
-0.95149517, -0.93484009, -0.91582485, -0.89449748, -0.8709118 ,
-0.84512737, -0.81720929, -0.78722803, -0.75525929, -0.72138377,
-0.68568702, -0.64825913, -0.60919462, -0.56859209, -0.52655407,
-0.48318668, -0.4385994 , -0.39290482, -0.34621828, -0.29865766,
-0.25034303, -0.20139637, -0.15194126, -0.10210255, -0.05200606,
-0.00177827, 0.048454 , 0.09856395, 0.14842506, 0.19791144,
0.24689816, 0.29526155, 0.34287951, 0.38963181, 0.43540043,
0.48006981, 0.52352718, 0.56566282, 0.60637036, 0.64554701,
0.68309389, 0.71891618, 0.75292346, 0.78502987, 0.81515434,
0.84322083, 0.86915847, 0.89290179, 0.91439084, 0.93357136,
0.95039493, 0.96481908, 0.9768074 , 0.98632961, 0.99336168,
0.99788585, 0.99989069, 0.99937116, 0.99632856, 0.99077057,
0.98271122, 0.97217086, 0.95917611, 0.94375976, 0.92596075,
0.905824 , 0.88340035, 0.85874643, 0.83192446, 0.80300216,
0.77205257, 0.7391538 , 0.70438892, 0.66784571, 0.62961641,
0.58979754, 0.54848964, 0.50579699, 0.46182738, 0.41669181,
0.37050423, 0.32338126, 0.27544187, 0.22680707, 0.17759967,
0.12794389, 0.07796509, 0.02778946, -0.02245633, -0.07264543,
-0.12265112, -0.17234716, -0.22160808, -0.27030952, -0.31832851,
-0.36554384, -0.4118363 , -0.45708901, -0.50118772, -0.54402111])
In [70]: import pylab
In [71]: pylab.plot(xs, ys)
Out[71]: [<matplotlib.lines.Line2D at 0x10cd29e10>]
In [72]: pylab.plot(xs, ys, 'o')
Out[72]: [<matplotlib.lines.Line2D at 0x102a17e50>]
In [73]: pylab.savefig('myplot.pdf')
<matplotlib.figure.Figure at 0x10445c3d0>
In [74]: pylab.savefig('myplot.png')
<matplotlib.figure.Figure at 0x103b62d10>
In [75]: pylab.plot(xs, ys, 'o'); pylab.savefig('myplot.png')
In [76]: pylab.plot(xs, ys, 'o');
In [77]: %matplotlib qt
In [78]: pylab.plot(xs, ys, 'o');
In [79]: %matplotlib inline
In [80]: pylab.plot(xs, ys, 'o');
In [81]: