def test_list_stdev_nonint(self):
L = []
for i in range(100):
L.append('A')
with self.assertRaises(ValueError) as ex:
math_lib.list_stdev(L)
self.assertEqual(str(ex.exception), 'Unsupported value in list.')
def test_list_stdev_parameters(self):
for i in range(1, 100):
stringlist = ["B", "x"]
for j in range(1, 100):
stringlist.append(random.randint(1, 100))
if (i % 2 == 0):
stringlist.append(False)
with self.assertRaises(Exception) as ex:
math_lib.list_stdev(stringlist)
def test_list_stdev_non_real_number_in_list(self):
"""test if list has bad inputs"""
L = []
for i in range(10):
L.append(random.randint(0, 100))
L.append('x')
with self.assertRaises(ValueError) as ex:
math_lib.list_stdev(L)
def test_list_stdev_non_num_in_list(self):
non_num_list = [random.random() for i in range(1000)]
non_num_list.append("non_num")
with self.assertRaises(TypeError) as ex:
math_lib.list_stdev(non_num_list)
self.assertEqual(str(ex.exception),
"List must only contain numeric values.")
def test_list_stdev_non_int_in_list(self):
L = []
for i in range(10):
L.append(rd.randint(0, 100))
L.append('X')
with self.assertRaises(ValueError) as ex:
math_lib.list_stdev(L)
self.assertEqual(
str(ex.exception),
'Mean and Stdev undefined.' + ' Unsupported value in L.')
def test_list_stdev_non_int_or_float(self):
L = []
for i in range(10):
L.append(random.randint(0, 100))
L.append('X')
for j in range(10):
L.append(random.uniform(0, 100))
with self.assertRaises(ValueError) as ex:
math_lib.list_stdev(L)
message = 'Unsupported value. List of ints and floats only'
self.assertEqual(str(ex.exception), message)
def combo(L, out_file_name):
"""
This function creates both a histogram and box plot displaying the data \
contained in the list of values and displays the mean and standard \
deviation of the data as the figure's title. It also saves \
the figure to a file.
Parameters:
- L(list): A list of numbers
- out_file_name(str): The name of the file we want to create
Returns:
- None, however, a file is saved.
"""
width = 3
height = 3
mean = list_mean(L)
std = list_stdev(L)
fig, axes = plt.subplots(2, 1)
axes[0].hist(L)
axes[0].set_xlabel("Value")
axes[0].set_ylabel("Frequency")
axes[0].set_title("Mean: " + str(mean) + "Standard Deviation: " + str(std),
loc="right")
axes[1].boxplot(L)
axes[1].set_xlabel("Array #1")
axes[1].set_ylabel("Value")
axes[1].set_title("Mean: " + str(mean) + "Standard Deviation: " + str(std),
loc="right")
plt.tight_layout()
plt.savefig(out_file_name)
def histogram(L, out_file_name):
file = pathlib.Path(out_file_name)
if file.exists():
return ('this file name is taken, choose another.')
else:
width = 3
height = 3
mean = ml.list_mean(L)
stdev = ml.list_stdev(L)
title = 'mean=' + str(mean) + ' stdev=' + str(stdev)
fig = plt.figure(figsize=(width, height), dpi=300)
ax = fig.add_subplot(1, 1, 1)
ax.set_title(title)
ax.set_xlabel('value')
ax.set_ylabel('frequency')
ax.hist(L, 3)
plt.savefig(out_file_name, bbox_inches='tight')
if not file.exists():
print('the plot did not save successfully.')
def histogram(L, out_file_name):
""" Histogram of numerical array and give specified name
Parameters
--------
L : Numerical array
Array contains list of integers or floats
out_file_name : file name
File name of the output file
Returns
--------
Generate file with specified name containing histogram
, tile and labeled axis.
Raises
--------
NameError
No output file name
SystemExit
File exits
"""
if out_file_name is None:
raise NameError('Out_file_name required')
if path.exists(out_file_name):
raise SystemExit('File already exits')
plt.hist(L)
plt.title(
str('Mean: ' + str(math_lib.list_mean(L)) + ' Stdev: ' +
str(math_lib.list_stdev(L))))
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.savefig(out_file_name, dpi=300)
pass
def boxplot(L, out_file_name):
""" Boxplot of numerical array and give specified name
Parameters
--------
L : Numerical array
Array contains list of integers or floats
out_file_name : file name
File name of the output file
Returns
--------
Generate file with specified name containing boxplot
, tile and labeled axist
Raises
--------
NameError
No output file name
SystemExit
File exits
"""
# Check input
if out_file_name is None:
raise NameError('Out_file_name required')
if path.exists(out_file_name):
raise SystemExit('File already exits')
plt.boxplot(L)
plt.title(
str('Mean: ' + str(math_lib.list_mean(L)) + ' Stdev: ' +
str(math_lib.list_stdev(L))))
plt.xlabel('Box')
plt.ylabel('Distribution')
plt.savefig(out_file_name, dpi=300)
pass
def test_list_stdev_rand(self):
rand_ary = []
for i in range(100):
rand_ary.append(random.random())
self.assertAlmostEqual(ml.list_stdev(rand_ary),
stats.stdev(rand_ary),
places=0)
def test_list_stdev_non_int_in_list(self):
L = []
for i in range(10):
L.append(random.randint(0, 100))
L.append('X')
r = math_lib.list_stdev(L)
self.assertRaises(TypeError, r)
def histogram(L, out_file_name):
# ensures correct input type
if L is None:
return None
if len(L) == 0:
return None
if not isinstance(L, list):
raise TypeError('Input must be list')
s = 0
for l in L:
if not isinstance(l, int) and not isinstance(l, float):
raise ValueError('Invalid type in list.')
if os.path.exists(out_file_name) is True:
print('This file name already exists')
return
out_file = out_file_name
plt.title('mean: ' + str(math_lib.list_mean(L)) + ' ' + 'stdev: ' +
str(math_lib.list_stdev(L)),
fontsize=20)
plt.xlabel('frequency')
plt.ylabel('values')
plt.hist(L)
plt.savefig(out_file, bbox_inches='tight')
def histogram(L, out_file_name='histogram.png'):
if L is None:
raise TypeError('histogram: No input to L')
if not isinstance(L,list):
raise TypeError('histogram: must pass a list to L')
valid_types = [isinstance(value,(int,float,complex)) for value in L]
if not any(valid_types):
raise TypeError("histogram: Invalid types in list")
if not isinstance(out_file_name,str):
raise TypeError("histogram: File name must be str")
fig = plt.figure(figsize=(3,3))
ax = fig.add_subplot(1, 1 ,1)
title = 'Mean: '+str(ml.list_mean(L))+ ', Stdev: ' + str(ml.list_stdev(L))
ax.title.set_text(title)
ax.set_ylabel('Values')
ax.set_xlabel('')
ax.hist(L)
try:
plt.savefig(out_file_name, bbox_inches='tight')
except ValueError:
raise ValueError
pass
def combo(L, out_file_name='combo.png'):
if L is None:
raise TypeError('combo: No input to L')
if not isinstance(L,list):
raise TypeError('combo: must pass a list to L')
valid_types = [isinstance(value,(int,float,complex)) for value in L]
if not any(valid_types):
raise TypeError("combo: Invalid types in list")
if not isinstance(out_file_name,str):
raise TypeError("combo: File name must be str")
fig,ax = plt.subplots(1,2,figsize=(10,5))
title = 'Mean: '+str(ml.list_mean(L))+ ', Stdev: ' + str(ml.list_stdev(L))
fig.suptitle(title)
#ax[0,1].set_ylabel('Values')
ax[1].hist(L)
ax[1].set_ylabel('Frequency')
ax[0].boxplot(L)
ax[0].set_ylabel('Values')
try:
plt.savefig(out_file_name, bbox_inches='tight')
except ValueError:
raise ValueError
pass
def test_list_stdev_randfloat(self):
F = []
for i in range(100):
F.append(random.uniform(-500, 1000))
stdev_liststdev = math_lib.list_stdev(F)
stdev_stat = statistics.pstdev(F)
self.assertEqual(round(stdev_liststdev, 4), round(stdev_stat, 4))
def histogram(L, out_file_name):
if path.exists(out_file_name):
raise OSError("File path already exists!")
sys.exit(1)
if L is None:
raise ValueError("Can't graph None!")
if L == []:
raise ValueError("Can't graph an empty list!")
try:
for line in L:
k = line[1]
except TypeError:
print("Can't plot 1D data!")
D = []
y = []
for l in L:
D.append(float(l[0]))
D.append(float(l[1]))
y.append(float(l[1]))
width = 3
height = 3
stat_mean = str(ml.list_mean(y))
stat_stdev = str(ml.list_stdev(y))
fig = plt.figure(figsize=(width, height), dpi=300)
ax = fig.add_subplot(1, 1, 1)
ax.hist(D)
plt.title("Mean: " + stat_mean + " " + "stdev: " + stat_stdev)
plt.ylabel('Frequency')
plt.savefig(out_file_name, bbox_inches='tight')
def combo(L, out_file_name):
"""
Draw one boxplot diagram and one histogram diagram in one figure
and save it as out_file_name.
Parameters:
L: A list of numbers in either integer or float type
out_file_name: The file name for the output figure
"""
if os.path.exists(out_file_name):
raise FileExistsError('File already exists.')
mean = math_lib.list_mean(L)
stdev = math_lib.list_stdev(L)
fig = plt.figure(dpi=300)
ax = fig.add_subplot(2, 1, 1)
plt.boxplot(L)
plt.title("mean: {} stdev: {}".format(mean, stdev))
plt.ylabel('Box')
plt.ylabel('Distribution')
plt.savefig(out_file_name)
ax = fig.add_subplot(2, 1, 2)
plt.hist(L)
plt.title("mean: {} stdev: {}".format(mean, stdev))
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.savefig(out_file_name)
def test_list_stdev_randint(self):
R = []
for i in range(100):
R.append(random.randint(0, 100))
stdev_liststdev = math_lib.list_stdev(R)
stdev_stat = statistics.pstdev(R)
self.assertEqual(round(stdev_liststdev, 4), round(stdev_stat, 4))
def test_list_stdev_random_float(self):
L = []
for i in range(100):
L.append(random.uniform(0, 100))
A = math_lib.list_stdev(L)
B = stats.stdev(L)
self.assertTrue(math.isclose(A, B))
def histogram(array, out_file_name):
"""
Creates and saves a histogram of the data given
in a 1D numeric list. Mean and standard deviation
are found and shown in the title.
Parameters
----------
array : list of ints or doubles
out_file_name : string name of file to save
Returns
----------
"""
# Make sure not to overwrite an existing file
if os.path.exists(out_file_name):
raise FileExistsError("That file name already exists.")
# Find mean and stdev using math_lib library
mean = ml.list_mean(array)
stdev = ml.list_stdev(array)
# Create and save the plot
plt.hist(array)
plt.title("mean: " + str(mean) + " stdev: " + str(stdev))
plt.xlabel("Value")
plt.ylabel("Frequency")
plt.savefig(out_file_name, bbox_inches="tight")
plt.close()
def combo(L, out_file_name):
out_file = out_file_name
X = []
Y = []
D = []
for l in sys.stdin:
A = l.rstrip().split()
X.append(float(A[0]))
Y.append(float(A[1]))
D.append(float(A[0]))
D.append(float(A[1]))
width = 5
height = 3
mean = math_lib.list_mean(L)
stdev = math_lib.list_stdev(L)
output = ('mean = ' + mean + 'stdev = ' + stdev)
fig = plt.figure(figsize=(width, height), dpi=300)
ax = fig.add_subplot(1, 2, 1)
ax.boxplot(L)
ax = fig.add_subplot(1, 2, 2)
ax.hist(D)
plt.savefig(out_file, bbox_inches='tight')
def combo(L, out_file_name):
# ensures correct input type
if L is None:
return None
if len(L) == 0:
return None
if not isinstance(L, list):
raise TypeError('Input must be list')
s = 0
for l in L:
if not isinstance(l, int) and not isinstance(l, float):
raise ValueError('Invalid type in list.')
if os.path.exists(out_file_name) is True:
print('This file name already exists')
return
out_file = out_file_name
width = 10
height = 5
fig = plt.figure(figsize=(width, height), dpi=300)
ax = fig.add_subplot(1, 2, 1)
ax.boxplot(L)
ax.set_xlabel('sample')
ax.set_ylabel('values')
ax = fig.add_subplot(1, 2, 2)
ax.hist(L)
ax.set_xlabel('frequency')
ax.set_ylabel('values')
fig.suptitle('mean: ' + str(math_lib.list_mean(L)) + ' ' + 'stdev: ' +
str(math_lib.list_stdev(L)),
fontsize=20)
plt.savefig(out_file, bbox_inches='tight')
def boxplot(L, out_file_name):
""" Make Boxplot in an output file from the data in a numerical array
Parameters
----------
L- Array of integers and/or floats to be plotted and analyzed
out_file_name - the name of the ouput file to which the plot,
mean and stdev will be given
Returns
----------
No return value except for datastream to output file
"""
if path.exists(out_file_name):
raise Exception("error, file already exists")
if (isinstance(out_file_name, str) is False):
raise Exception("file name must be alphanumeric(string)")
mean = math.list_mean(L)
stdev = math.list_stdev(L)
plt.boxplot(L)
plt.title("mean = " + str(mean) + ", stdev = " + str(stdev))
plt.ylabel("Located Values")
plt.xlabel("your entered list")
plt.savefig(out_file_name, dpi=300)
pass
def test_list_stdev_rand_ints(self):
L = []
for i in range(100):
for j in range(10):
L.append(random.randint(0, 100))
r = math_lib.list_stdev(L)
e = numpy.std(L)
self.assertTrue(math.isclose(e, r, rel_tol=1e-03))
def test_list_stdev_non_int(self):
L = []
for i in range(10):
L.append(random.randint(0, 100))
e = statistics.pstdev(L)
L.append('X')
r = math_lib.list_stdev(L)
self.assertAlmostEqual(e, r)
def test_list_stdev_rand_floats(self):
L = []
for i in range(100):
for j in range(10):
L.append(random.uniform(0, 100))
r = math_lib.list_stdev(L)
e = statistics.pstdev(L)
self.assertAlmostEqual(r, e)
def test_stdev_random_int_array(self):
for i in range(100):
A = []
for i in range(100):
A.append(random.randint(1, 100))
self.assertEqual(
round(math_lib.list_stdev(A), 5),
round(statistics.pstdev(A, statistics.mean(A)), 5))
def test_list_stdev_rand_floats_model(self):
L = []
for i in range(100):
for j in range(10):
L.append(random.uniform(0, 100))
r = math_lib.list_stdev(L)
e = statistics.stdev(L)
self.assertTrue(math.isclose(r, e))
def test_list_stdev_non_number_in_list(self):
L = []
for j in range(10):
L.append(random.uniform(0, 100))
stdev = statistics.stdev(L)
L.append('x')
random.shuffle(L)
self.assertAlmostEqual(ml.list_stdev(L), stdev)
