def display_on_map(self, map_name=None): color_scales = { "gimme_fluxes": [dict(type='min', color="yellow", size=20), dict(type='value', value=0, color="green", size=7), dict(type='max', color='blue', size=20)], "expression": [dict(type='value', value=log_plus_one(self.cutoff), color="green", size=10), dict(type='max', color='blue', size=20), dict(type='min', color='yellow', size=5)], "inconsistency_scores": [dict(type='value', value=0, color="yellow", size=10), dict(type='max', color='green', size=20)] } normalization_functions = { "gimme_fluxes": float, "expression": float, "inconsistency_scores": float } viewer = EscherViewer(self.data_frame, map_name, color_scales, normalization_functions) drop_down = Dropdown() drop_down.options = { "Fluxes": "gimme_fluxes", "Expression": "expression", "Inconsistency Score": "inconsistency_scores" } drop_down.default_value = "gimme_fluxes" drop_down.on_trait_change(lambda x: viewer(drop_down.get_state("value")["value"])) display(drop_down) viewer("gimme_fluxes")
def display_on_map(self, map_name): color_scales = { "fluxes_%s" % self._a_key: [dict(type='min', color="yellow", size=20), dict(type='value', value=0, color="blue", size=7), dict(type='max', color='green', size=20)], "fluxes_%s" % self._b_key: [dict(type='min', color="yellow", size=20), dict(type='value', value=0, color="blue", size=7), dict(type='max', color='green', size=20)], "manhattan_distance": [dict(type='min', color="yellow", size=20), dict(type='value', value=0, color="blue", size=7), dict(type='max', color='green', size=20)], "euclidean_distance": [dict(type='min', color="yellow", size=20), dict(type='value', value=0, color="blue", size=7), dict(type='max', color='green', size=20)], "activity_profile": [dict(type='value', value=-1, color="yellow", size=10), dict(type='value', value=0, color="green", size=10), dict(type='value', value=1, color='blue', size=10)], "fold_change": [dict(type='min', color="yellow", size=20), dict(type='value', value=0, color="blue", size=7), dict(type='max', color='green', size=20)] } normalization_functions = { "fluxes_%s" % self._a_key: float, "fluxes_%s" % self._b_key: float, "manhattan_distance": float, "euclidean_distance": float, "activity_profile": int, "fold_change": np.log2 } viewer = EscherViewer(self.data_frame, map_name, color_scales, normalization_functions) drop_down = Dropdown() drop_down.options = OrderedDict({ "Flux Distribution %s" % self._a_key: "fluxes_%s" % self._a_key, "Flux Distribution %s" % self._b_key: "fluxes_%s" % self._b_key, "Manhattan Distance": "manhattan_distance", "Euclidean Distance": "euclidean_distance", "Activity Profile": "activity_profile", "log2 Fold Change": "fold_change" }) drop_down.default_value = "fluxes_%s" % self._a_key drop_down.on_trait_change(lambda x: viewer(drop_down.get_state("value")["value"])) display(drop_down) viewer("fluxes_%s" % self._a_key)