# Path: cotede/qctests/qctests.py
# def frozen_profile():
# def grey_list():
# def valid_speed():
# def gross_sensor_drift():
# def platform_identification():
# 
# Path: cotede/qctests/spike.py
# def spike(x):
#     """ Spike
#     """
#     if isinstance(x, ma.MaskedArray):
#         x[x.mask] = np.nan
#         x = x.data
# 
#     x = np.atleast_1d(x)
#     y = np.nan * x
#     y[1:-1] = np.abs(x[1:-1] - (x[:-2] + x[2:]) / 2.0) - np.abs((x[2:] - x[:-2]) / 2.0)
#     return y


import logging
import numpy as np
from numpy import ma
from .qctests import QCCheckVar
from .spike import spike
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst

"""

"""





module_logger = logging.getLogger(__name__)


class SpikeDepthConditional(QCCheckVar):
    def set_features(self):

# Path: cotede/qctests/qctests.py
# def frozen_profile():
# def grey_list():
# def valid_speed():
# def gross_sensor_drift():
# def platform_identification():
# 
# Path: cotede/qctests/spike.py
# def spike(x):
#     """ Spike
#     """
#     if isinstance(x, ma.MaskedArray):
#         x[x.mask] = np.nan
#         x = x.data
# 
#     x = np.atleast_1d(x)
#     y = np.nan * x
#     y[1:-1] = np.abs(x[1:-1] - (x[:-2] + x[2:]) / 2.0) - np.abs((x[2:] - x[:-2]) / 2.0)
#     return y


# Path: cotede/qctests/spike_depthconditional.py
import logging
import numpy as np
from numpy import ma
from .qctests import QCCheckVar
from .spike import spike

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst

"""

"""





module_logger = logging.getLogger(__name__)


class SpikeDepthConditional(QCCheckVar):
    def set_features(self):

        self.features = {"spike": spike(self.data[self.varname])}