def plot_recurrence_plots(x,
dimension=1,
epsilon=None,
percentage=10,
cmap='Greys',
output_file=None):
# Check parameters
if not isinstance(dimension, int):
raise TypeError("'dimension' must be an integer.")
if dimension <= 0:
raise ValueError("'dimension' must be greater than or equal to 1.")
if (epsilon is not None) and \
(epsilon not in ['percentage_points', 'percentage_distance']) and \
(not isinstance(epsilon, (int, float))):
raise TypeError("'epsilon' must be either None, 'percentage_points', "
"'percentage_distance', a float or an integer.")
if (isinstance(epsilon, (int, float))) and (epsilon < 0):
raise ValueError("if 'epsilon' is a float or an integer,"
"'epsilon' must be greater than or equal to 0.")
if not isinstance(percentage, (int, float)):
raise TypeError("'percentage' must be a float or an integer.")
if (percentage < 0) or (percentage > 100):
raise ValueError("'percentage' must be between 0 and 100.")
rp = recurrence_plot(x, dimension, epsilon, percentage)
plt.imshow(rp, origin='lower', cmap=cmap)
plt.axis('off')
if output_file is not None:
plt.savefig(output_file)
# Show plot
plt.show()
def test_recurrence_plot():
"""Testing 'recurrence_plot'"""
# Parameter
size = 9
X = np.linspace(-1, 1, size)
# Test 1
arr_actual = recurrence_plot(X, dimension=1, epsilon=None, percentage=10)
arr_desired = np.empty((size, size))
for i in range(size):
for j in range(size):
arr_desired[i, j] = abs(X[i] - X[j])
np.testing.assert_allclose(arr_actual, arr_desired, atol=1e-5, rtol=0.)
# Test 2
percentage = 50
epsilon = 'percentage_distance'
arr_actual = recurrence_plot(X,
dimension=1,
epsilon=epsilon,
percentage=percentage)
arr_desired = np.empty((size, size))
for i in range(size):
for j in range(size):
arr_desired[i,
j] = abs(X[i] -
X[j]) < percentage * (X.max() - X.min()) / 100
np.testing.assert_allclose(arr_actual, arr_desired, atol=1e-5, rtol=0.)
# Test 3
percentage = 50
epsilon = 'percentage_points'
arr_actual = recurrence_plot(X,
dimension=1,
epsilon=epsilon,
percentage=percentage)
arr_desired = np.empty((size, size))
for i in range(size):
for j in range(size):
arr_desired[i, j] = abs(X[i] - X[j])
arr_desired = arr_desired < np.percentile(arr_desired, q=50)
np.testing.assert_allclose(arr_actual, arr_desired, atol=1e-5, rtol=0.)
def plot_recurrence_plots(ts,
dimension=1,
epsilon=None,
percentage=10,
cmap='Greys',
output_file=None,
interpolation=None):
"""Plot the image obtained after Recurrence plots transformation.
Parameters
----------
ts : np.array, shape = [n_features]
time series to plot
dimension : int (default = 1)
dimension of the trajectory.
epsilon : None or 'percentage_points' or 'percentage_distance'
or float (default = None)
threshold for the minimum distance
percentage : float (default = 10)
percentage of black points if epsilon == 'percentage_points'
or percentage of maximum distance for threshold if
epsilon == 'percentage_distance'.
cmap : str (default = 'Greys')
color map from matplotlib.pyplot
output_file : str or None (default = None)
if str, save the figure.
interpolation : str or None (default = None)
'interpolation' parameter for matplotlib.pyplot.imshow
"""
# Check parameters
if not isinstance(dimension, int):
raise TypeError("'dimension' must be an integer.")
if dimension <= 0:
raise ValueError("'dimension' must be greater than or equal to 1.")
if (epsilon is not None) and \
(epsilon not in ['percentage_points', 'percentage_distance']) and \
(not isinstance(epsilon, (int, float))):
raise TypeError("'epsilon' must be either None, 'percentage_points', "
"'percentage_distance', a float or an integer.")
if (isinstance(epsilon, (int, float))) and (epsilon < 0):
raise ValueError("if 'epsilon' is a float or an integer,"
"'epsilon' must be greater than or equal to 0.")
if not isinstance(percentage, (int, float)):
raise TypeError("'percentage' must be a float or an integer.")
if (percentage < 0) or (percentage > 100):
raise ValueError("'percentage' must be between 0 and 100.")
rp = recurrence_plot(ts, dimension, epsilon, percentage)
plt.imshow(rp, origin='lower', cmap=cmap, interpolation=interpolation)
plt.axis('off')
if output_file is not None:
plt.savefig(output_file)
# Show plot
plt.show()