def test_load_csv(): csv = loader.load_csv('boat.csv') assert csv is None csv = loader.load_csv('data/boat.csv') assert csv.shape == (100, 4)
def _load(self, file_path): """Loads and parses a dataframe from a file. Args: file_path (str): File to be loaded. Returns: Arrays holding the features and labels. """ # Getting file extension extension = file_path.split('.')[-1] if extension == 'csv': data = loader.load_csv(file_path) elif extension == 'txt': data = loader.load_txt(file_path) elif extension == 'json': data = loader.load_json(file_path) else: raise e.ArgumentError( 'File extension not recognized. It should be `.csv`, `.json` or `.txt`' ) X, Y = p.parse_loader(data) return X, Y
def _read_distances(self, file_name): """Reads the distance between nodes from a pre-defined file. Args: file_name (str): File to be loaded. """ logger.debug('Running private method: read_distances().') # Getting file extension extension = file_name.split('.')[-1] if extension == 'csv': distances = loader.load_csv(file_name) elif extension == 'txt': distances = loader.load_txt(file_name) else: # Raises an ArgumentError exception raise e.ArgumentError('File extension not recognized. It should be either `.csv` or .txt`') # Check if distances have been properly loaded if distances is None: raise e.ValueError('Pre-computed distances could not been properly loaded') # Apply the distances matrix to the property self.pre_distances = distances
def test_parse_loader(): X, Y = parser.parse_loader([]) assert X is None assert Y is None try: data = np.ones((4, 4)) X, Y = parser.parse_loader(data) except: try: data = np.ones((4, 4)) data[3, 1] = 3 X, Y = parser.parse_loader(data) except: csv = loader.load_csv('data/boat.csv') X, Y = parser.parse_loader(csv) assert X.shape == (100, 2) assert Y.shape == (100, )
def _load(self, file_path): """Loads and parses a dataframe from a file. Args: file_path (str): File to be loaded. Returns: Arrays holding the features and labels. """ # Getting file extension extension = file_path.split('.')[-1] # Check if extension is .csv if extension == 'csv': # If yes, call the method that actually loads csv data = loader.load_csv(file_path) # Check if extension is .txt elif extension == 'txt': # If yes, call the method that actually loads txt data = loader.load_txt(file_path) # Check if extension is .json elif extension == 'json': # If yes, call the method that actually loads json data = loader.load_json(file_path) # If extension is not recognized else: # Raises an ArgumentError exception raise e.ArgumentError( 'File extension not recognized. It should be `.csv`, `.json` or `.txt`' ) # Parsing array X, Y = p.parse_loader(data) return X, Y
def _read_distances(self, file_path): """Reads the distance between nodes from a pre-defined file. Args: file_path (str): File to be loaded. Returns: A matrix with pre-computed distances. """ logger.debug('Running private method: read_distances().') # Getting file extension extension = file_path.split('.')[-1] # Check if extension is .csv if extension == 'csv': # If yes, call the method that actually loads csv distances = loader.load_csv(file_path) # Check if extension is .txt elif extension == 'txt': # If yes, call the method that actually loads txt distances = loader.load_txt(file_path) # If extension is not recognized else: # Raises an ArgumentError exception raise e.ArgumentError( 'File extension not recognized. It should be either `.csv` or .txt`' ) # Check if distances have been properly loaded if distances is None: # If not, raises a ValueError raise e.ValueError( 'Pre-computed distances could not been properly loaded') return distances
import numpy as np import pytest from opfython.math import distance from opfython.stream import loader, parser from opfython.subgraphs import knn csv = loader.load_csv('data/boat.csv') X, Y = parser.parse_loader(csv) def test_knn_subgraph_n_clusters(): subgraph = knn.KNNSubgraph(X, Y) assert subgraph.n_clusters == 0 def test_knn_subgraph_n_clusters_setter(): subgraph = knn.KNNSubgraph(X, Y) try: subgraph.n_clusters = 0.5 except: subgraph.n_clusters = 1 assert subgraph.n_clusters == 1 try: subgraph.n_clusters = -1 except: subgraph.n_clusters = 1
import opfython.stream.loader as l # Loading a .csv file csv = l.load_csv('data/sample.csv') # Loading a .txt file txt = l.load_txt('data/sample.txt') # Loading a .json file json = l.load_json('data/sample.json')
import opfython.stream.loader as l # Loading a .csv file csv = l.load_csv('data/boat.csv') # Loading a .txt file txt = l.load_txt('data/boat.txt') # Loading a .json file json = l.load_json('data/boat.json')