enhancing/fixing numpy and sympy examples

snippets_submenus_python/numpy.js

@@ -55,28 +55,31 @@ define([
  'x = np.linspace(0, 1, 7)',
  'y = np.linspace(0, 1, 11)',
  'xx, yy = np.meshgrid(x, y)',
+ 'xx, yy',
  ],
  },
  {
  'name' : 'Return views of the data, split into $N$ groups',
  'snippet' : [
  'x = np.arange(12)',
  'a,b,c = np.split(x, 3)',
+ 'a, b, c',
  ],
  },
  {
  'name' : 'Return views of the data, split at given indices along given axis',
  'snippet' : [
  'x = np.arange(27).reshape((3,9))',
  'a,b,c = np.split(x, [2,6], axis=1)',
+ 'a, b, c',
  ],
  },
  {
  'name' : 'Return copy of arrays, combined into one',
  'snippet' : [
  'a = np.arange(30).reshape((2,3,5))',
  'b = np.arange(42).reshape((2,3,7))',
- 'c = np.concatenate((a, b), axis=1)',
+ 'np.concatenate((a, b), axis=2)',
  ],
  },
  ],
@@ -109,15 +112,15 @@ define([
  'name' : 'View real array as complex',
  'snippet' : [
  'r = np.linspace(0, 10, num=100).reshape((25,4))',
- 'c = r.view(complex)',
+ 'r.view(complex)',
  ],
  },
  {
  'name' : 'View complex array as real with extra dimension',
  'snippet' : [
  'c = (np.linspace(0, 10, num=50) + 1j*np.linspace(0, 10, num=50))',
  'cv = c.view(float)',
- 'r = cv.reshape(c.shape + (2,))',
+ 'cv.reshape(c.shape + (2,))',
  ],
  },
  ],
@@ -151,21 +154,15 @@ define([
  'snippet' : [
  'x = np.arange(12)',
  'a,b,c = np.split(x, 3)',
+ 'a, b, c',
  ],
  },
  {
  'name' : 'Return views of the data, split at given indices along given axis',
  'snippet' : [
  'x = np.arange(27).reshape((3,9))',
  'a,b,c = np.split(x, [2,6], axis=1)',
- ],
- },
- {
- 'name' : 'Return copy of arrays, combined into one',
- 'snippet' : [
- 'a = np.arange(30).reshape((2,3,5))',
- 'b = np.arange(42).reshape((2,3,7))',
- 'c = np.concatenate((a, b), axis=1)',
+ 'a, b, c',
  ],
  },
  ],

snippets_submenus_python/numpy_polynomial.js

@@ -43,7 +43,7 @@ define({
  {
  'name' : 'Get coefficients (constant at index 0, higher indices for higher orders)',
  'snippet' : [
- 'poly.coeff',
+ 'poly.coef',
  ],
  },
  {
@@ -121,8 +121,8 @@ define({
  'np.random.seed(11)',
  'x = np.linspace(0, 2*np.pi, 20)',
  'y = np.sin(x) + np.random.normal(scale=.1, size=x.shape)',
- 'n = 5',
- 'p = T.fit(x, y, n)',
+ 'n = 5 # degree',
+ 'np.polyfit(x, y, n)',
  ],
  },
  ],

snippets_submenus_python/numpy_ufuncs.js

@@ -43,7 +43,8 @@ define({
  {
  'name' : 'trace: Return the sum along diagonals of the array.',
  'snippet' : [
- 'np.trace(a, axis1, axis2)',
+ 'data = np.array([[3, 0, 0], [7, -1, 0], [-1, 0, 1]])',
+ 'np.trace(data, axis1 = 0, axis2 = 1)',
  ],
  },
 
@@ -139,28 +140,34 @@ define({
  {
  'name' : 'gradient: Gradient of an N-dimensional array',
  'snippet' : [
- 'np.gradient(f, *varargs, **kwargs)',
+ 'xx = np.arange(0, 1, 0.1)',
+ 'yy = xx**2 + 1',
+ 'np.gradient(yy, 0.1)',
  ],
  },
 
  {
- 'name' : 'trapz: Integrate along the given axis using the composite trapezoidal rule',
+ 'name' : 'trapz: Integrate using the composite trapezoidal rule',
  'snippet' : [
- 'np.trapz(y, x, dx, axis)',
+ 'xx = np.linspace(0, np.pi, num=100)',
+ 'yy = np.sin(xx)',
+ 'np.trapz(yy, x=xx)',
  ],
  },
 
  {
  'name' : 'convolve: Discrete, linear convolution of two one-dimensional sequences',
  'snippet' : [
- 'np.convolve(a, v)',
+ 'np.convolve([1, 2, 3], [0, 1, 0.5])',
  ],
  },
 
  {
  'name' : 'interp: One-dimensional linear interpolation',
  'snippet' : [
- 'np.interp(x, xp, fp)',
+ 'xp = [-1, 2.5, 3, 8]',
+ 'fp = [0, 4, 4.1, 5]',
+ 'np.interp([0, 1, 2, 3, 4], xp, fp)',
  ],
  },
  ],
@@ -955,7 +962,7 @@ define({
  {
  'name' : 'cross: Cross product of two (arrays of) vectors',
  'snippet' : [
- 'np.cross(a, b)',
+ 'np.cross([1, -1, 1], [2, 3, -6])',
  ],
  },
  ],

snippets_submenus_python/scipy.js

@@ -191,7 +191,7 @@ define([
  'x = np.arange(0, 4.0, 0.01)',
  'y_0 = [-1.0 / 3**(1.0/3.0) / gamma(1.0/3.0), 1.0 / 3**(2.0/3.0) / gamma(2.0/3.0)]',
  'Ai, Aip, Bi, Bip = airy(x)',
- 'y = odeint(func, y_0, x, rtol=1e-12, atol=1e-12) # Exact answer: (Aip, Ai)',
+ 'y = integrate.odeint(func, y_0, x, rtol=1e-12, atol=1e-12) # Exact answer: (Aip, Ai)',
  ],
  },
  {
@@ -205,7 +205,7 @@ define([
  'x = np.arange(0, 4.0, 0.01)',
  'y_0 = [-1.0 / 3**(1.0/3.0) / gamma(1.0/3.0), 1.0 / 3**(2.0/3.0) / gamma(2.0/3.0)]',
  'Ai, Aip, Bi, Bip = airy(x)',
- 'y = odeint(func, y_0, x, rtol=1e-12, atol=1e-12, Dfun=gradient) # Exact answer: (Aip, Ai)',
+ 'y = integrate.odeint(func, y_0, x, rtol=1e-12, atol=1e-12, Dfun=gradient) # Exact answer: (Aip, Ai)',
  ],
  },
  {

snippets_submenus_python/sympy_functions.js

@@ -233,27 +233,27 @@ define({
  },
  {
  'name' : 'Stirling number of the second kind',
- 'snippet' : ['stirling(n, k)',],
+ 'snippet' : ['from sympy.functions.combinatorial.numbers import stirling', 'stirling(n, k)',],
  },
  {
  'name' : 'Stirling number of the first kind',
- 'snippet' : ['stirling(n, k, kind=1, signed=False)',],
+ 'snippet' : ['from sympy.functions.combinatorial.numbers import stirling', 'stirling(n, k, kind=1, signed=False)',],
  },
  {
  'name' : 'Reduced Stirling number of the second kind',
- 'snippet' : ['stirling(n, k, d)',],
+ 'snippet' : ['from sympy.functions.combinatorial.numbers import stirling', 'stirling(n, k, d)',],
  },
  {
  'name' : 'Number of combinations of length k among n items',
- 'snippet' : ['nC(n, k)',],
+ 'snippet' : ['from sympy.functions.combinatorial.numbers import nC', 'nC(n, k)',],
  },
  {
  'name' : 'Number of permutations of length k among n items',
- 'snippet' : ['nP(n, k)',],
+ 'snippet' : ['from sympy.functions.combinatorial.numbers import nP', 'nP(n, k)',],
  },
  {
  'name' : 'Number of partitions of length k among n items',
- 'snippet' : ['nT(n, k)',],
+ 'snippet' : ['from sympy.functions.combinatorial.numbers import nT', 'nT(n, k)',],
  },
  ],
  },
@@ -270,7 +270,7 @@ define({
  },
  {
  'name' : 'Heaviside function',
- 'snippet' : ['Heaviside(X)',],
+ 'snippet' : ['Heaviside(x)',],
  },
  {
  'name' : 'Gamma, Beta and related Functions',
@@ -484,7 +484,7 @@ define({
  },
  {
  'name' : 'Dirichlet eta function',
- 'snippet' : ['eta(s)',],
+ 'snippet' : ['dirichlet_eta(s)',],
  },
  {
  'name' : 'Polylogarithm function',