mirror of https://gitlab.com/pamhyr/pamhyr2
Ensemble: Results: Rename Z to z_mean and dont keep individual result.
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92990948ad
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d4d5e26a2b
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@ -1648,16 +1648,13 @@ class Mage8(Mage):
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res["q_max"] = np.maximum(q, res["q_max"])
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# Keep results min, mean and max
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res["res_z_min"].append((run_number, np.min(z, axis=0)))
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res["res_z_mean"].append((run_number, np.mean(z, axis=0)))
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res["res_z_max"].append((run_number, np.max(z, axis=0)))
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# res["res_z_min"].append((run_number, np.min(z, axis=0)))
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# res["res_z_mean"].append((run_number, np.mean(z, axis=0)))
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# res["res_z_max"].append((run_number, np.max(z, axis=0)))
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res["res_q_min"].append((run_number, np.min(q, axis=0)))
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res["res_q_mean"].append((run_number, np.mean(q, axis=0)))
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res["res_q_max"].append((run_number, np.max(q, axis=0)))
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# FIXME: Keep all results ?
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res["traces"].append((run_number, tables))
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# res["res_q_min"].append((run_number, np.min(q, axis=0)))
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# res["res_q_mean"].append((run_number, np.mean(q, axis=0)))
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# res["res_q_max"].append((run_number, np.max(q, axis=0)))
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@timer
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def results_ensemble(self, study, repertory,
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@ -155,7 +155,7 @@ class PlotRKCEnsemble(PamhyrPlot):
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colors = [
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("z_min", self.color_plot_ensemble_min),
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("Z", self.color_plot_ensemble_mean),
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("z_mean", self.color_plot_ensemble_mean),
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("z_max", self.color_plot_ensemble_max),
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]
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@ -263,7 +263,7 @@ class PlotRKCEnsemble(PamhyrPlot):
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reach = result.river.reach(self._current_reach_id)
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rk = reach.geometry.get_rk()
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z_min = reach.geometry.get_z_min()
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table = result.get("table")["Z"]
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table = result.get("table")["z_mean"]
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ts = result.get_timestamp_id(self._current_timestamp)
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gi_0, gi_1 = reach.global_index
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@ -271,7 +271,7 @@ class PlotRKCEnsemble(PamhyrPlot):
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colors = [
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(0, "z_min", self.color_plot_ensemble_min),
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(1, "Z", self.color_plot_ensemble_mean),
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(1, "z_mean", self.color_plot_ensemble_mean),
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(2, "z_max", self.color_plot_ensemble_max),
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]
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@ -537,17 +537,12 @@ class SolverLogEnsWindow(SolverLogWindow):
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table = {}
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table["Z"] = results.new_table_data("Z", tables["z_mean"])
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table["Q"] = results.new_table_data("Q", tables["q_mean"])
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table["z_min"] = results.new_table_data("z_min", tables["z_min"])
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table["q_min"] = results.new_table_data("q_min", tables["q_min"])
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table["z_max"] = results.new_table_data("z_max", tables["z_max"])
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table["q_max"] = results.new_table_data("q_max", tables["q_max"])
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for key in ["z", "q"]:
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for func in ["min", "mean", "max"]:
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name = f"res_{key}_{func}"
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name = f"{key}_{func}"
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table[name] = results.new_table_data(name, tables[name])
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name = f"res_{name}"
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table[name] = results.new_table_data(
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name,
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np.array(
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@ -555,10 +550,12 @@ class SolverLogEnsWindow(SolverLogWindow):
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)
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)
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for nb, data in tables["traces"]:
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name = f"{nb}_"
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table[name + "z"] = results.new_table_data(name + "z", data["Z"])
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table[name + "q"] = results.new_table_data(name + "q", data["Q"])
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# for nb, data in tables["traces"]:
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# name = f"{nb}_"
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# table[name + "z"] = results.new_table_data(name + "z",
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# data["Z"])
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# table[name + "q"] = results.new_table_data(name + "q",
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# data["Q"])
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table["samples"] = results.new_table_data(
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"samples", np.array(self._run_samples)
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