#===============================================================================
# Copyright 2011 Jake Ross
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#===============================================================================
from traits.etsconfig.etsconfig import ETSConfig
ETSConfig.toolkit = 'qt4'
from pychron.graph.regression_graph import RegressionGraph
import numpy as np
if __name__ == '__main__':
reg = RegressionGraph()
reg.new_plot()
# xs = np.linspace(0, 100, 100)
# ys = xs * 0.02 + np.random.random(100)
xs = [0, 1, 2, 3, 4, 5]
ys = [0, 3, 5, 6, 7, 5]
reg.new_series(xs, ys, fit='linear')
reg.configure_traits()
# ===============================================================================
# Copyright 2011 Jake Ross
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ===============================================================================
from traits.etsconfig.etsconfig import ETSConfig
ETSConfig.toolkit = 'qt4'
from pychron.graph.regression_graph import RegressionGraph
if __name__ == '__main__':
reg = RegressionGraph()
reg.new_plot()
# xs = np.linspace(0, 100, 100)
# ys = xs * 0.02 + np.random.random(100)
xs = [0, 1, 2, 3, 4, 5]
ys = [0, 3, 5, 6, 7, 5]
reg.new_series(xs, ys, fit='linear')
reg.configure_traits()