chelseatroy

    def nonzero(self):
        """nonzero indices

        Returns a tuple of arrays (row,col) containing the indices
        of the non-zero elements of the matrix.

        Examples
        --------
        >>> from scipy.sparse import csr_matrix
        >>> A = csr_matrix([[1,2,0],[0,0,3],[4,0,5]])

chelseatroy

class coo_1d(_data_matrix, ...):  
    ...
    def row(self):
        return np.zeros(self.col.shape[0])
    
    def nonzero(self):
        ...

        nz_mask = A.data != 0
        return (None, A.col[nz_mask])

chelseatroy

class coo_matrix(_data_matrix, _minmax_mixin):
    ...
    
    format = 'coo'

    def __init__(self, arg1, shape=None, dtype=None, copy=False):
        ...
            else:
                #dense argument
                

chelseatroy

import pandas as pd
import numpy as np
import itertool
from nltk import word_tokenize
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import MultinomialNB

df = pd.read_csv('my_data_with_text.csv')
df.columns #id, text, category

chelseatroy

class Bird(models.Model):
    species_choices = [
        ("Spix's Macaw", "Spix's Macaw"),
        ("Cockatiel", "Cockatiel"),
        ...
        ("Caique", "Caique"),
        ("Guam Kingfisher", "Guam Kingfisher")
    ]
    species = models.CharField(max_length=50, choices=species_choices)

chelseatroy

chelseatroy

/**begin repeat
 *
 * #name = BYTE, UBYTE, SHORT, USHORT, INT, UINT,
 * LONG, ULONG, LONGLONG, ULONGLONG,
 * FLOAT, DOUBLE, LONGDOUBLE,
 * DATETIME, TIMEDELTA#
 * #type = npy_byte, npy_ubyte, npy_short, npy_ushort, npy_int, npy_uint,
 * npy_long, npy_ulong, npy_longlong, npy_ulonglong,
 * npy_float, npy_double, npy_longdouble,
 * npy_datetime, npy_timedelta#

chelseatroy

import numpy as np

def cython_multiplication(a,b):
    product = np.ones(a.shape)

    for row_index in np.arange(a.shape[0]):
        for col_index in np.arange(a.shape[1]):
            product[row_index][col_index] = a[row_index][col_index] * b[row_index][col_index]

    return product

chelseatroy

import ctypes
import time
from _ctypes import Structure, POINTER, byref
from ctypes import c_int, c_float
import pyximport; pyximport.install()
import multiplication

import numpy as np

a = np.random.rand(2000,2000)

chelseatroy

import numpy as np

def cython_multiplication(double[:,:] a, double[:,:] b, double[:,:] out, int x_dims, int y_dims):
    cdef int i, j

    for i in range(x_dims):
        for j in range(y_dims):
            out[i, j] = a[i,j] * b[i,j]

    return np.asarray(out)