diff --git a/PCP_07_exp.html b/PCP_07_exp.html index 33e184b..b69aed6 100644 --- a/PCP_07_exp.html +++ b/PCP_07_exp.html @@ -13137,7 +13137,7 @@

Power Series
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import numpy as np
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Power Series
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Exponentiation Identity and

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from matplotlib import ticker 
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Exponentiation Identity and
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/tmp/ipykernel_277743/1914264468.py:4: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed two minor releases later. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap(obj)`` instead.
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Differential Equations
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def exp_approx_Euler(x_min=0, x_max=2, x_delta=0.01, f_0=1):
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Differential Equations
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Roots of Unity
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from math import gcd
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Roots of Unity
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Exercises and Results
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import libpcp.exp
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Exercises and Results
 

 

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#<solution>
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Exercises and Results
 

 

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libpcp.exp.exercise_approx_exp(show_result=show_result)
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Exercises and Results
 

 

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Input argument z = 1
+N =   1, Numpy = 2.7182818285, Approx1 = 2.0000000000, Approx2 = 2.0000000000
+N =   2, Numpy = 2.7182818285, Approx1 = 2.5000000000, Approx2 = 2.2500000000
+N =   4, Numpy = 2.7182818285, Approx1 = 2.7083333333, Approx2 = 2.4414062500
+N =   8, Numpy = 2.7182818285, Approx1 = 2.7182787698, Approx2 = 2.5657845140
+N =  16, Numpy = 2.7182818285, Approx1 = 2.7182818285, Approx2 = 2.6379284974
+N =  32, Numpy = 2.7182818285, Approx1 = 2.7182818285, Approx2 = 2.6769901294
+Input argument z = (2.0, 0.7)
+N =   1, Numpy = (5.651462, 4.760161), Approx1 = (3.000000, 0.700000), Approx2 = (3.000000, 0.700000)
+N =   2, Numpy = (5.651462, 4.760161), Approx1 = (4.755000, 2.100000), Approx2 = (3.877500, 1.400000)
+N =   4, Numpy = (5.651462, 4.760161), Approx1 = (5.785004, 4.261833), Approx2 = (4.650000, 2.330344)
+N =   8, Numpy = (5.651462, 4.760161), Approx1 = (5.654404, 4.760077), Approx2 = (5.152687, 3.223932)
+N =  16, Numpy = (5.651462, 4.760161), Approx1 = (5.651462, 4.760161), Approx2 = (5.415734, 3.881969)
+N =  32, Numpy = (5.651462, 4.760161), Approx1 = (5.651462, 4.760161), Approx2 = (5.540143, 4.288473)
+N =  64, Numpy = (5.651462, 4.760161), Approx1 = (5.651462, 4.760161), Approx2 = (5.597987, 4.515429)
+N = 128, Numpy = (5.651462, 4.760161), Approx1 = (5.651462, 4.760161), Approx2 = (5.625352, 4.635473)
+N = 256, Numpy = (5.651462, 4.760161), Approx1 = (5.651462, 4.760161), Approx2 = (5.638575, 4.697223)
+N = 512, Numpy = (5.651462, 4.760161), Approx1 = (5.651462, 4.760161), Approx2 = (5.645062, 4.728542)
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Exercises and Results
 

 

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#<solution>
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Exercises and Results
 

 

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libpcp.exp.exercise_gaussian(show_result=show_result)
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Exercises and Results
 

 

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Exercises and Results
 

 

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#<solution>
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Exercises and Results
 

 

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libpcp.exp.exercise_spiral(show_result=show_result)
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Exercises and Results
 

 

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