def bin_test():
print('normal distribution, 3 bins')
out = audioplot.plot('histogram')
data = np.random.normal(size=1000000, loc=0, scale=1)
out.data(data)
out.bins(3)
out.play()
def duration_test():
print('testing shorter duration of 2 seconds')
out = audioplot.plot('line')
data_array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
out.data(data_array)
out.duration(2)
out.play()
def linear_range_test():
print('a linear line with adjusted audio range')
data_array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
out = audioplot.plot('line')
out.data(data_array)
out.audio_range(200, 250)
out.play()
def bar_test():
print('bar chart with default settings')
data_items = ['car','bicycle','bus']
data_values=[20,10,5]
out = audioplot.plot('bar')
out.data(data_values,data_items)
out.play()
def rate_test():
print('a bar chart with increased speaking rate')
data_items = ['car','bicycle','bus']
data_values=[20,10,5]
out = audioplot.plot('bar')
out.data(data_values,data_items)
out.rate('400' )
out.play()
def range_test():
print('normal distribution with adjusted frequencies')
out = audioplot.plot('histogram')
data = np.random.normal(size=1000000, loc=0, scale=1)
out.data(data)
out.bins(3)
out.audio_range(200, 350)
out.play()
def verbose_test():
print('a bar chart with verbose output')
data_items = ['car','bicycle','bus']
data_values=[20,10,5]
out = audioplot.plot('bar')
out.data(data_values,data_items)
out.verbosity(True)
out.title('A bar chart of the number of people that take different modes of transport')
out.play()
def verbose_test():
out = audioplot.plot('histogram')
print('normal distribution with verbose True')
data = np.random.normal(size=1000000, loc=0, scale=1)
out.data(data)
out.bins(3)
out.verbosity(True)
out.title('A normal distribution with 1,000,000 data points')
out.play()
def verbose_test():
print('testing verbose output')
out = audioplot.plot('line')
data_array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
out.data(data_array)
out.verbosity(True)
out.title('A linearly rising line')
out.xlabel('time period')
out.ylabel('amount of an item')
out.play()
def single_array_input_test():
out = audioplot.plot('line')
data_array = [1, 3]
out.data(data_array, smoothed=True)
out.play()
def linear_test():
print('a linear line with no smoothing')
data_array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
out = audioplot.plot('line')
out.data(data_array)
out.play()
def exponential_test():
print('an exponential line')
data_array = np.logspace(2, 9, dtype='int')
out = audioplot.plot('line')
out.data(data_array)
out.play()
def straight_test():
print('a straight line')
data_array = [1, 1, 1, 1, 1]
out = audioplot.plot('line')
out.data(data_array)
out.play()
def normal_test():
print('normal distribution, default settings')
out = audioplot.plot('histogram')
data = np.random.normal(size=1000000, loc=0, scale=1)
out.data(data)
out.play()