# Path: pygesture/pipeline.py
# class Pipeline(object):
# class PipelineBlock(object):
# class Windower(PipelineBlock):
# class Conditioner(PipelineBlock):
# class BandpassFilter(PipelineBlock):
# class Classifier(PipelineBlock):
#     def __init__(self, blocks):
#     def process(self, data):
#     def clear(self):
# def _call_block(fname, block, data=None):
# def _call_list(fname, block, data):
# def _call_tuple(fname, block, data):
#     def process(self, data):
#     def clear(self):
#     def __repr__(self):
#     def __init__(self, length, overlap=0):
#     def clear(self):
#     def process(self, data):
#     def _preallocate(self, cols):
#     def __repr__(self):
#     def __init__(self, order, f_cut, f_samp, f_down=None, overlap=0):
#     def process(self, data):
#     def clear(self):
#     def __repr__(self):
#     def __init__(self, order, f_cut, f_samp, overlap=0):
#     def _build_filter(self):
#     def clear(self):
#     def process(self, data):
#     def __repr__(self):
#     def __init__(self, clf):
#     def fit(self, X, y):
#     def process(self, data):
#             K = max(len(self.a)-1, len(self.b)-1)


import numpy as np
from numpy.testing import (assert_equal, assert_array_equal,
                           assert_array_almost_equal)
from pygesture import pipeline


np.random.seed(12345)

rand_data_1d = np.random.rand(100, 1)
rand_data_2d = np.random.rand(100, 5)


class _AddOneBlock(pipeline.PipelineBlock):

    def process(self, data):
        return data + 1



# Path: pygesture/pipeline.py
# class Pipeline(object):
# class PipelineBlock(object):
# class Windower(PipelineBlock):
# class Conditioner(PipelineBlock):
# class BandpassFilter(PipelineBlock):
# class Classifier(PipelineBlock):
#     def __init__(self, blocks):
#     def process(self, data):
#     def clear(self):
# def _call_block(fname, block, data=None):
# def _call_list(fname, block, data):
# def _call_tuple(fname, block, data):
#     def process(self, data):
#     def clear(self):
#     def __repr__(self):
#     def __init__(self, length, overlap=0):
#     def clear(self):
#     def process(self, data):
#     def _preallocate(self, cols):
#     def __repr__(self):
#     def __init__(self, order, f_cut, f_samp, f_down=None, overlap=0):
#     def process(self, data):
#     def clear(self):
#     def __repr__(self):
#     def __init__(self, order, f_cut, f_samp, overlap=0):
#     def _build_filter(self):
#     def clear(self):
#     def process(self, data):
#     def __repr__(self):
#     def __init__(self, clf):
#     def fit(self, X, y):
#     def process(self, data):
#             K = max(len(self.a)-1, len(self.b)-1)


# Path: pygesture/tests/test_pipeline.py
import numpy as np
from numpy.testing import (assert_equal, assert_array_equal,
                           assert_array_almost_equal)
from pygesture import pipeline



np.random.seed(12345)

rand_data_1d = np.random.rand(100, 1)
rand_data_2d = np.random.rand(100, 5)


class _AddOneBlock(pipeline.PipelineBlock):

    def process(self, data):
        return data + 1



class _TwoInputBlock(pipeline.PipelineBlock):