def __init__(self, kdeType):
"""
Initialize the logger and ensure the requested KDE type exists.
This uses the `statsmodels.nonparametric.kernel_density` library
"""
LOG.info("Initialising KDEParameters")
kernels = kernel_switch.keys()
if kdeType in kernels:
LOG.debug("Using {0} to generate distribution".format(kdeType))
self.kdeType = kdeType
else:
LOG.error("Invalid kernel type: {0}".format(kdeType))
raise NotImplementedError(
"Invalid kernel type: {0}".format(kdeType))
def __init__(self, kdeType):
"""
Initialize the logger and ensure the requested KDE type exists.
This uses the `statsmodels.nonparametric.kernel_density` library
"""
LOG.info("Initialising KDEParameters")
kernels = kernel_switch.keys()
if kdeType in kernels:
LOG.debug(f"Using {kdeType} to generate distribution")
self.kdeType = kdeType
else:
msg = (f"Invalid kernel type: {kdeType} \n"
f"Valid kernels are {repr(kernels)}")
LOG.error(msg)
raise NotImplementedError(msg)
color='red',
zorder=20,
label='Data samples',
alpha=0.5)
ax.legend(loc='best')
ax.set_xlim([-3, 3])
ax.grid(True, zorder=-5)
# ## Comparing kernel functions
# In the example above, a Gaussian kernel was used. Several other kernels
# are also available.
from statsmodels.nonparametric.kde import kernel_switch
list(kernel_switch.keys())
# ### The available kernel functions
# Create a figure
fig = plt.figure(figsize=(12, 5))
# Enumerate every option for the kernel
for i, (ker_name, ker_class) in enumerate(kernel_switch.items()):
# Initialize the kernel object
kernel = ker_class()
# Sample from the domain
domain = kernel.domain or [-3, 3]
x_vals = np.linspace(*domain, num=2**10)
color='red',
zorder=20,
label='Data samples',
alpha=0.5)
ax.legend(loc='best')
ax.set_xlim([-3, 3])
ax.grid(True, zorder=-5)
# ## Comparing kernel functions
# In the example above, a Gaussian kernel was used. Several other kernels
# are also available.
from statsmodels.nonparametric.kde import kernel_switch
list(kernel_switch.keys())
# ### The available kernel functions
# Create a figure
fig = plt.figure(figsize=(12, 5))
# Enumerate every option for the kernel
for i, (ker_name, ker_class) in enumerate(kernel_switch.items()):
# Initialize the kernel object
kernel = ker_class()
# Sample from the domain
domain = kernel.domain or [-3, 3]
x_vals = np.linspace(*domain, num=2**10)