#=============================================================================== # 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()