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import unittest 

import sqlite3 

import numpy as np 

import pandas as pd 

from navipy import database 

# from navipy.processing.tools import is_numeric_array 

import pkg_resources 

import tempfile 

from navipy.database import DataBase 

from navipy import unittestlogger 

 

 

class TestCase(unittest.TestCase): 

def setUp(self): 

unittestlogger() 

self.mydb_filename = pkg_resources.resource_filename( 

'navipy', 'resources/database2.db') 

self.mydb = DataBase(self.mydb_filename, mode='r') 

 

def test_DataBase_init_(self): 

""" 

this test checks the initialization of a DataBase works 

correctly. 

it checks if correct errors are raised for: 

- a database file with out .db ending is used for initialization 

- wrong types are passed for the database name 

i.e. integers, floats, none, nan 

""" 

# filename must end with .db 

with self.assertRaises(NameError): 

DataBase('test') 

# filename must be string 

for n in [2, 5.0, None, np.nan]: 

with self.assertRaises(TypeError): 

DataBase(n) 

 

# only works if testdb was created before e.g. with DataBase 

# with self.assertRaises(NameError): 

# DataBase('test') 

 

def test_DataBase_init_channel(self): 

""" 

this test checks the initialization of a DataBase works 

correctly. 

it checks if correct errors are raised for: 

- channels names, which are no strings or chars 

- channel name is None value or nan 

""" 

# channels must be strings or char 

for n in [3, 8.7, None, np.nan]: 

with self.assertRaises(TypeError): 

DataBase(self.mydb_filename, channels=n) 

with self.assertRaises(ValueError): 

DataBase(self.mydb_filename, channels=[None, 2]) 

 

def test_table_exist(self): 

""" 

this test checks if the function table_exists works correctly 

it checks if correct errors are raised for: 

- a database name that are not of type string or char 

i.e. integer, float, none, nan 

- Attention: in this test the check for a table that existed 

did not work correctly (False was returned) 

""" 

# self.assertFalse(self.mydb.table_exist('testblubb')) 

for n in [2, 7.0, None, np.nan]: 

with self.assertRaises(TypeError): 

self.assertFalse(self.mydb.table_exist(n)) 

# self.assertFalse(self.mydb.table_exist(self.mydb_filename)) 

 

def test_check_data_validity(self): 

""" 

this test checks the function data validity works 

correctly. It should return true if the database 

contains data in the row, that is checked for 

it checks if correct errors are raised for: 

- row numbers that are not integers. 

i.e. float non, nan (must be integer) 

- row is out of range; smaller or equal to 0 

- checks if true is returned for an exiting entry (row=1) 

""" 

for n in [7.0, None, np.nan]: 

with self.assertRaises(TypeError): 

self.mydb.check_data_validity(n) 

for n in [-1, 0]: 

with self.assertRaises(ValueError): 

self.mydb.check_data_validity(n) 

assert self.mydb.check_data_validity(1) 

 

def get_posid_test(self): 

""" 

this test checks the function get_posid works 

correctly. 

it checks if correct errors are raised for: 

- posorient is missing an entry (no 'x' column) 

- posorient contains nan or none values 

- posorient is of wrong type (dict instead of pd.series) 

""" 

conn = sqlite3.connect(self.mydb_filename) 

c = conn.cursor() 

c.execute(""" SELECT * FROM position_orientation WHERE (rowid=1) """) 

rows = c.fetchall()[0] 

# convention = rows[1] 

 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient = pd.Series(index=index) 

posorient['location']['x'] = rows[6] 

posorient['location']['y'] = rows[7] 

posorient['location']['z'] = rows[8] 

posorient['xyz']['alpha_0'] = rows[3] 

posorient['xyz']['alpha_1'] = rows[5] 

posorient['xyz']['alpha_2'] = rows[4] 

 

posid = self.mydb.get_posid(posorient) 

assert posid == 1 

 

# incorrect case missing column 

tuples = [('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

 

with self.assertRaises(Exception): 

posid = self.mydb.get_posid(posorient2) 

 

# incorrect case None 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(self.tuples, 

names=['position', 'orientation']) 

 

posorient3 = pd.Series(index=index) 

posorient3['location']['x'] = None 

posorient3['location']['y'] = rows[7] 

posorient3['location']['z'] = rows[8] 

posorient3['xyz']['alpha_0'] = rows[3] 

posorient3['xyz']['alpha_1'] = rows[5] 

posorient3['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

posid = self.mydb.get_posid(posorient2) 

 

# incorrect case nan 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(self.tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['x'] = np.nan 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

posid = self.mydb.get_posid(posorient2) 

 

# incorrect case no pandas series but dict 

posorient2 = {} 

posorient2['location']['x'] = rows[6] 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(TypeError): 

self.mydb.get_posid(posorient2) 

 

# not working case empty 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(self.tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

 

with self.assertRaises(Exception): 

self.mydb.get_posid(posorient2) 

 

def test_read_posorient(self): 

""" 

this test checks the function read_posorient works 

correctly. 

it checks if correct errors are raised for: 

- posorient is missing an entry (no 'x' column) 

- posorient contains nan or none values 

- posorient is of wrong type (dict instead of pd.series) 

""" 

conn = sqlite3.connect(self.mydb_filename) 

c = conn.cursor() 

c.execute(""" SELECT * FROM position_orientation WHERE (rowid=1) """) 

rows = c.fetchall()[0] 

# working case 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient = pd.Series(index=index) 

posorient['location']['x'] = rows[6] 

posorient['location']['y'] = rows[7] 

posorient['location']['z'] = rows[8] 

posorient['xyz']['alpha_0'] = rows[3] 

posorient['xyz']['alpha_1'] = rows[5] 

posorient['xyz']['alpha_2'] = rows[4] 

posid = self.mydb.read_posorient(posorient=posorient) 

# print(posid) 

assert posid['location']['x'] == posorient['location']['x'] 

 

# incorrect case missing column 

tuples = [('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

self.mydb.read_posorient(posorient=posorient2) 

 

# incorrect case None 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['x'] = None 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

self.mydb.read_posorient(posorient=posorient2) 

 

# incorrect case nan 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['x'] = np.nan 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

self.mydb.read_posorient(posorient=posorient2) 

 

# incorrect case no pandas series but dict 

posorient2 = {} 

posorient2['location'] = {} 

posorient2['xyz'] = {} 

posorient2['location']['x'] = rows[6] 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(TypeError): 

self.mydb.read_posorient(posorient=posorient2) 

 

# not working case empty 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

 

with self.assertRaises(Exception): 

self.mydb.read_posorient(posorient=posorient2) 

 

def test_read_posid_id(self): 

""" 

this test checks the function read_posorient works 

correctly. 

it checks if correct errors are raised for: 

- rowid is out of range (<=0) 

- rowid is of type char, none, nan, float 

and checks if the returned entry for rowid 1 is correct 

- that it all columns and correct values 

""" 

conn = sqlite3.connect(self.mydb_filename) 

c = conn.cursor() 

c.execute(""" SELECT * FROM position_orientation WHERE (rowid=1) """) 

rows = c.fetchall()[0] 

# working case 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient = pd.Series(index=index) 

posorient['location']['x'] = rows[6] 

posorient['location']['y'] = rows[7] 

posorient['location']['z'] = rows[8] 

posorient['xyz']['alpha_0'] = rows[3] 

posorient['xyz']['alpha_1'] = rows[5] 

posorient['xyz']['alpha_2'] = rows[4] 

for rowid in [0, -2]: 

with self.assertRaises(ValueError): 

# print("rowid",rowid) 

self.mydb.read_posorient(rowid=rowid) 

with self.assertRaises(TypeError): 

self.mydb.read_posorient(rowid='T') 

with self.assertRaises(Exception): 

self.mydb.read_posorient(rowid=None) 

with self.assertRaises(TypeError): 

self.mydb.read_posorient(rowid=np.nan) 

with self.assertRaises(TypeError): 

self.mydb.read_posorient(rowid=4.5) 

 

for rowid in [1]: 

posoriend2 = self.mydb.read_posorient(rowid=rowid) 

assert posoriend2['location']['x'] == posorient['location']['x'] 

assert posoriend2['location']['y'] == posorient['location']['y'] 

assert posoriend2['location']['z'] == posorient['location']['z'] 

assert (posoriend2['xyz']['alpha_0'] == 

posorient['xyz']['alpha_0']) 

assert (posoriend2['xyz']['alpha_1'] == 

posorient['xyz']['alpha_1']) 

assert (posoriend2['xyz']['alpha_2'] == 

posorient['xyz']['alpha_2']) 

 

def test_scene_id(self): 

""" 

this test checks the function scene works 

correctly. 

it checks if correct errors are raised for: 

- rowid is out of range (<=0) 

- rowid is of type char, none, nan, float 

 

and checks if the returned entry for different 

rows is correct 

- has correct shape 

- does not contain nans 

""" 

for rowid in [0, -2]: 

with self.assertRaises(ValueError): 

# print("rowid",rowid) 

self.mydb.scene(rowid=rowid) 

with self.assertRaises(TypeError): 

self.mydb.scene(rowid='T') 

with self.assertRaises(Exception): 

self.mydb.scene(rowid=None) 

with self.assertRaises(TypeError): 

self.mydb.scene(rowid=np.nan) 

with self.assertRaises(TypeError): 

self.mydb.scene(rowid=4.5) 

 

for rowid in [1, 2, 3, 4, 5]: 

image = self.mydb.scene(rowid=rowid) 

# image=np.array(image) 

self.assertIsNotNone(image) 

self.assertFalse(sum(image.shape) == 0) 

self.assertTrue(len(image.shape) == 4) 

self.assertFalse(np.any(np.isnan(image))) 

self.assertTrue(image.shape[3] == 1) 

self.assertTrue(image.shape[2] == 4) 

self.assertTrue(image.shape[0] > 0) 

self.assertTrue(image.shape[1] > 0) 

 

def test_scene_posorient(self): 

""" 

this test checks the function scene works 

correctly. 

it checks if correct errors are raised for: 

- posorient is missing an entry (no 'x' column) 

- posorient contains nan or none values 

- posorient is of wrong type (dict instead of pd.series) 

""" 

conn = sqlite3.connect(self.mydb_filename) 

c = conn.cursor() 

c.execute(""" SELECT * FROM position_orientation WHERE (rowid=1) """) 

rows = c.fetchall()[0] 

# working case 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

posorient = pd.Series(index=index) 

posorient['location']['x'] = rows[6] 

posorient['location']['y'] = rows[7] 

posorient['location']['z'] = rows[8] 

posorient['xyz']['alpha_0'] = rows[3] 

posorient['xyz']['alpha_1'] = rows[5] 

posorient['xyz']['alpha_2'] = rows[4] 

image = self.mydb.scene(posorient=posorient) 

self.assertIsNotNone(image) 

self.assertFalse(sum(image.shape) == 0) 

# print("shape",image.shape) 

self.assertTrue(len(image.shape) == 4) 

self.assertTrue(image.shape[3] == 1) 

 

# incorrect case missing column 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(Exception): 

image = self.mydb.scene(posorient=posorient2) 

 

# incorrect case None 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['x'] = None 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

image = self.mydb.scene(posorient=posorient2) 

 

# incorrect case nan 

tuples = [('location', 'x'), ('location', 'y'), 

('location', 'z'), ('xyz', 'alpha_0'), 

('xyz', 'alpha_1'), ('xyz', 'alpha_2')] 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

posorient2['location']['x'] = np.nan 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(ValueError): 

image = self.mydb.scene(posorient=posorient2) 

 

# incorrect case no pandas series but dict 

posorient2 = {} 

posorient2['location'] = {} 

posorient2['xyz'] = {} 

posorient2['location']['x'] = rows[6] 

posorient2['location']['y'] = rows[7] 

posorient2['location']['z'] = rows[8] 

posorient2['xyz']['alpha_0'] = rows[3] 

posorient2['xyz']['alpha_1'] = rows[5] 

posorient2['xyz']['alpha_2'] = rows[4] 

with self.assertRaises(TypeError): 

image = self.mydb.scene(posorient=posorient2) 

 

# not working case empty 

index = pd.MultiIndex.from_tuples(tuples, 

names=['position', 'orientation']) 

 

posorient2 = pd.Series(index=index) 

 

with self.assertRaises(Exception): 

image = self.mydb.scene(posorient=posorient2) 

 

def test_denormalise_image(self): 

""" 

this test checks the function denormalise_image works 

correctly. 

it checks if correct errors are raised for: 

- image has wrong type (list instead of np.ndarray) 

- image does not have enough dimensions 

- image contains nan values 

- image has to many dimensions 

- cminmax range is missing one channel 

- cminmax range is empty pd.series 

- cminmax range is dictionary 

- cminmax contains nans 

""" 

image = self.mydb.scene(rowid=1) 

image = np.squeeze(image) 

cminmaxrange = pd.Series(index=['R_min', 'R_max', 'R_range', 

'G_min', 'G_max', 'G_range', 

'B_min', 'B_max', 'B_range', 

'D_min', 'D_max', 'D_range']) 

cminmaxrange.R_min = 0 

cminmaxrange.R_max = 1 

cminmaxrange.R_range = 1 

cminmaxrange.G_min = 0 

cminmaxrange.G_max = 1 

cminmaxrange.G_range = 1 

cminmaxrange.B_min = 0 

cminmaxrange.B_max = 1 

cminmaxrange.B_range = 1 

cminmaxrange.D_min = 0 

cminmaxrange.D_max = 1 

cminmaxrange.D_range = 1 

imagecorrect = (image.copy() * 500).astype(int) 

self.mydb.denormalise_image(imagecorrect, cminmaxrange) 

 

# not working 

image2 = image.copy().tolist() 

with self.assertRaises(TypeError): 

self.mydb.denormalise_image(image2, cminmaxrange) 

 

image2 = image[:, :, 0].copy() 

with self.assertRaises(Exception): 

self.mydb.denormalise_image(image2, cminmaxrange) 

 

image2 = image.copy() 

image2[23, 34, 0] = np.nan 

with self.assertRaises(ValueError): 

self.mydb.denormalise_image(image2, cminmaxrange) 

 

# image2 = image 

# image2[23,34,0] = 'addsf' 

# with self.assertRaises(ValueError): 

# denormed=self.mydb.denormalise_image(image2,cminmaxrange) 

 

image2 = image[np.newaxis, :, :, :] 

with self.assertRaises(Exception): 

self.mydb.denormalise_image(image2, cminmaxrange) 

 

cminmaxrange2 = pd.Series(index=['R_min', 'R_max', 'R_range', 

'B_min', 'B_max', 'B_range', 

'D_min', 'D_max', 'D_range']) 

cminmaxrange2.R_min = 0 

cminmaxrange2.R_max = 1 

cminmaxrange2.R_range = 1 

cminmaxrange2.B_min = 0 

cminmaxrange2.B_max = 1 

cminmaxrange2.B_range = 1 

cminmaxrange2.D_min = 0 

cminmaxrange2.D_max = 1 

cminmaxrange2.D_range = 1 

imagecorrect = (image.copy() * 500).astype(int) 

with self.assertRaises(ValueError): 

self.mydb.denormalise_image(imagecorrect, cminmaxrange2) 

 

cminmaxrange3 = pd.Series(index=['R_min', 'R_max', 'R_range', 

'G_min', 'G_max', 'G_range', 

'B_min', 'B_max', 'B_range', 

'D_min', 'D_max', 'D_range']) 

# cminmaxrange3.R_min = [] 

# cminmaxrange3.R_max = [] 

# cminmaxrange3.R_range = [] 

# cminmaxrange3.G_min = [] 

# cminmaxrange3.G_max = [] 

# cminmaxrange3.G_range = [] 

# cminmaxrange3.B_min = [] 

# cminmaxrange3.B_max = [] 

# cminmaxrange3.B_range = [] 

# cminmaxrange3.D_min = [] 

# cminmaxrange3.D_max = [] 

# cminmaxrange3.D_range = [] 

 

with self.assertRaises(ValueError): 

self.mydb.denormalise_image(imagecorrect, cminmaxrange3) 

 

cminmaxrange3 = {} 

cminmaxrange3['R_min'] = 0 

cminmaxrange3['R_max'] = 1 

cminmaxrange3['R_range'] = 1 

cminmaxrange3['G_min'] = 0 

cminmaxrange3['G_max'] = 1 

cminmaxrange3['G_range'] = 1 

cminmaxrange3['B_min'] = 0 

cminmaxrange3['B_max'] = 1 

cminmaxrange3['B_range'] = 1 

cminmaxrange3['D_min'] = 0 

cminmaxrange3['D_max'] = 1 

cminmaxrange3['D_range'] = 1 

with self.assertRaises(TypeError): 

self.mydb.denormalise_image(imagecorrect, cminmaxrange3) 

 

cminmaxrange.R_min = np.nan 

with self.assertRaises(ValueError): 

self.mydb.denormalise_image(imagecorrect, cminmaxrange) 

 

def test_normalise_image(self): 

""" 

this test checks the function normalise_image works 

correctly. 

it checks if correct errors are raised for: 

- image is of wrong type (list) 

- image has wrong dimensionality (too big, too small) 

- image contains nan values 

""" 

image = self.mydb.scene(rowid=1) 

image = np.squeeze(image) 

with tempfile.TemporaryDirectory() as folder: 

testdb_filename = folder + '/testdatabase.db' 

loadDB = DataBase(testdb_filename, mode='w') 

loadDB.normalise_image(image) 

 

# not working 

image2 = image.tolist() 

with self.assertRaises(TypeError): 

loadDB.normalise_image(image2) 

 

image2 = image[:, :, 0].copy() 

with self.assertRaises(Exception): 

loadDB.normalise_image(image2) 

 

image2 = image.copy() 

image2[23, 34, 0] = np.nan 

with self.assertRaises(ValueError): 

loadDB.normalise_image(image2) 

 

"""image2 = image.copy() 

image2[23,34,0] = 'addsf' 

with self.assertRaises(ValueError): 

denormed=loadDB.normalise_image(image2)""" 

 

image2 = image[np.newaxis, :, :, :].copy() 

with self.assertRaises(Exception): 

loadDB.normalise_image(image2) 

 

def test_insert_replace(self): 

""" 

this test checks the function insert_replace works 

correctly. 

it checks if correct errors are raised for: 

- filename is of type integer, float, nan or none 

- filename does not exist in database/params are wrong 

""" 

params = {} 

params['hight'] = 1.7 

params['age'] = 20 

with tempfile.TemporaryDirectory() as folder: 

testdb_filename = folder + '/testdatabase.db' 

tmpmydb = database.DataBase(testdb_filename, mode='w') 

 

for name in [3, 7.5, np.nan, None]: 

with self.assertRaises(TypeError): 

tmpmydb.insert_replace(name, params) 

 

with self.assertRaises(sqlite3.OperationalError): 

tmpmydb.insert_replace('test', params) 

 

 

if __name__ == '__main__': 

unittest.main()