import numpy as np

example_array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
example_array

example_array[1, 1]

example_array[:, 0]

example_array[1, :]

example_array[1:3, 1:3]

array1 = np.array([1, 1, 1, 2, 2, 2, 1])
array2 = np.array([1, 2, 3, 4, 5, 6, 7])
array2[array1==1]

array3 = np.array(['a', 'a', 'a', 'b', 'b', 'b', 'b'])
array2[(array1==1) & (array3=='a')]

array1 = np.array([1, 1, 1, 2, 2, 2, 1])
array2 = np.array([1, 2, 3, 4, 5, 6, 7])

array1 * 2 + 1

array1 * array2

matrix1 = np.matrix([[1, 2, 3], [4, 5, 6]])
matrix2 = np.matrix([1, 2, 3])
matrix1 * matrix2.transpose()

data = np.genfromtxt('./data/examp_data.txt', delimiter=',', skip_header=1)
data

np.savetxt('./data/examp_output.txt', data, delimiter=',')

data = np.genfromtxt('./data/examp_data_species_mass.txt', dtype=None, names=True, delimiter=',')
data

def export_to_csv(data, filename):
    outputfile = open(filename, 'wb')
    datawriter = csv.writer(outputfile)
    datawriter.writerows(data)
    outputfile.close()

data = np.genfromtxt('./data/examp_data_species_mass.txt', dtype=None, names=True, delimiter=',')
print data
data['species']

data['mass'][data['species'] == 'DM']

data['mass'][(data['species'] == 'DM') & (data['site'] == 1)]

np.random.rand(3, 5)

np.random.randn(4, 2)

min = 10
max = 20
np.random.randint(min, max, [10, 2])