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Results: Refactoring '_export_time' method.
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parouby committed
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2 files changed
+101
-123
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@@ -826,7 +826,7 @@ class ProfileXYZ(Profile, SQLSubModel):
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return n_zones
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def froude(self, v, z):
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def froude(self, z, v):
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return v / np.sqrt(
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9.81 * (
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self.wet_area(z) / self.wet_width(z)
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+100
-122
@@ -937,6 +937,7 @@ class ResultsWindow(PamhyrWindow):
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my_dict = data["my_dict"]
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envelop = data["envelop"]
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id_ts = data["id_ts"]
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q = data["q"]
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my_dict["discharge"] = q[id_ts, :]
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@@ -949,6 +950,7 @@ class ResultsWindow(PamhyrWindow):
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my_dict = data["my_dict"]
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envelop = data["envelop"]
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id_ts = data["id_ts"]
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z = data["z"]
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my_dict["water_elevation"] = z[id_ts, :]
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@@ -961,6 +963,7 @@ class ResultsWindow(PamhyrWindow):
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my_dict = data["my_dict"]
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envelop = data["envelop"]
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id_ts = data["id_ts"]
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v = data["v"]
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my_dict["velocity"] = v[id_ts, :]
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@@ -974,6 +977,7 @@ class ResultsWindow(PamhyrWindow):
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envelop = data["envelop"]
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reach = data["reach"]
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id_ts = data["id_ts"]
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z = data["z"]
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my_dict["depth"] = list(
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@@ -995,6 +999,7 @@ class ResultsWindow(PamhyrWindow):
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my_dict = data["my_dict"]
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reach = data["reach"]
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id_ts = data["id_ts"]
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z = data["z"]
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my_dict["mean_depth"] = list(
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@@ -1010,14 +1015,15 @@ class ResultsWindow(PamhyrWindow):
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my_dict = data["my_dict"]
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reach = data["reach"]
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id_ts = data["id_ts"]
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z = data["z"]
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v = data["v"]
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my_dict["froude"] = list(
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map(
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lambda p: p.geometry.froude(
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v[id_ts, p.global_index],
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z[id_ts, p.global_index]
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z[id_ts, p.global_index],
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v[id_ts, p.global_index]
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),
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reach.profiles
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)
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@@ -1027,6 +1033,7 @@ class ResultsWindow(PamhyrWindow):
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my_dict = data["my_dict"]
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reach = data["reach"]
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id_ts = data["id_ts"]
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z = data["z"]
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my_dict["wet_area"] = list(
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@@ -1045,134 +1052,105 @@ class ResultsWindow(PamhyrWindow):
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dict_x = self._trad.get_dict("values_x")
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dict_y = self._trad.get_dict("values_y")
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my_dict = {}
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my_dict[dict_x["time"]] = self._timestamps
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table = results.get("table")
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ind = profile.global_index
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z = table["Z"][:, profile.global_index]
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q = table["Q"][:, profile.global_index]
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v = table["V"][:, profile.global_index]
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zfd = table["zfd"][:, profile.global_index]
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my_dict = {}
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data = {
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"z": table["Z"][:, ind],
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"q": table["Q"][:, ind],
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"v": table["V"][:, ind],
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"zfd": table["zfd"][:, ind],
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if self._current_results == 2:
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reach1 = self._results[0].river.reach(self._reach)
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reach2 = self._results[1].river.reach(self._reach)
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reach3 = self._results[2].river.reach(self._reach)
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profile1 = reach1.profile(self._profile)
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profile2 = reach2.profile(self._profile)
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# profile3 = reach3.profile(self._profile)
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"reach": reach,
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"profile": profile,
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"my_dict": my_dict,
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}
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z1 = table["Z"][:, profile1.global_index]
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q1 = table["Q"][:, profile1.global_index]
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v1 = table["V"][:, profile1.global_index]
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def set_dict(k, v):
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my_dict[k] = v
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z2 = table["Z"][:, profile2.global_index]
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q2 = table["Q"][:, profile2.global_index]
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v2 = table["V"][:, profile2.global_index]
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func = {
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"bed_elevation": self._export_time_compute_elevation,
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"discharge": lambda d: set_dict("discharge", d["q"]),
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"water_elevation": lambda d: set_dict("water_elevation", d["z"]),
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"velocity": lambda d: set_dict("velocity", d["v"]),
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"depth": self._export_time_compute_depth,
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"mean_depth": self._export_time_compute_mean_depth,
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"froude": self._export_time_compute_froude,
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"wet_area": self._export_time_compute_wet_area,
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}
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if "bed_elevation" in y:
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if reach.has_bedload():
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z_min = zfd
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else:
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z_min = [profile.geometry.z_min()] * len(self._timestamps)
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# Compute values
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for key in y:
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func[key](data)
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my_dict[dict_y["bed_elevation"]] = z_min
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if "discharge" in y:
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my_dict[dict_y["discharge"]] = q
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if "water_elevation" in y:
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my_dict[dict_y["water_elevation"]] = z
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if "velocity" in y:
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my_dict[dict_y["velocity"]] = v
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if "depth" in y:
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if self._current_results != 2:
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d = list(
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map(lambda x: profile.geometry.max_water_depth(x), z)
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)
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else:
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d1 = list(
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map(lambda x: profile1.geometry.max_water_depth(x), z1)
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)
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d2 = list(
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map(lambda x: profile2.geometry.max_water_depth(x), z2)
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)
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d = list(
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map(
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lambda x, y: x - y,
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d1, d2
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)
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)
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my_dict[dict_y["depth"]] = d
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if "mean_depth" in y:
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if self._current_results != 2:
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d = list(
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map(lambda x: profile.geometry.mean_water_depth(x), z)
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)
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else:
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d1 = list(
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map(lambda x: profile1.geometry.mean_water_depth(x), z1)
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)
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d2 = list(
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map(lambda x: profile2.geometry.mean_water_depth(x), z2)
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)
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d = list(map(
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lambda x, y: x - y,
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d1, d2
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))
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my_dict[dict_y["mean_depth"]] = d
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if "froude" in y:
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if self._current_results != 2:
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fr = my_dict[dict_y["froude"]] = list(
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map(lambda z, v:
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v / sqrt(9.81 * (
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profile.geometry.wet_area(z) /
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profile.geometry.wet_width(z))
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),
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z, v)
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)
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else:
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fr1 = list(
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map(lambda z, v:
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v /
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sqrt(9.81 * (
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profile1.geometry.wet_area(z) /
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profile1.geometry.wet_width(z))
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),
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z1, v1)
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)
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fr2 = list(
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map(lambda z, v:
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v /
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sqrt(9.81 * (
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profile2.geometry.wet_area(z) /
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profile2.geometry.wet_width(z))
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),
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z2, v2)
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)
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fr = list(map(
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lambda x, y: x - y,
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fr1, fr2
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))
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my_dict[dict_y["froude"]] = fr
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if "wet_area" in y:
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if self._current_results != 2:
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wa = list(
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map(lambda x: profile.geometry.wet_area(x), z)
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)
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else:
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wa1 = list(
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map(lambda x: profile1.geometry.wet_area(x), z1)
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)
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wa2 = list(
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map(lambda x: profile2.geometry.wet_area(x), z2)
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)
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wa = list(map(
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lambda x, y: x - y,
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wa1, wa2
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))
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my_dict[dict_y["wet_area"]] = wa
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# Translate dictionary keys
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translated_dict = {}
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for key in my_dict:
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translated_dict[dict_y[key]] = my_dict[key]
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return my_dict
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translated_dict[dict_x["time"]] = self._timestamps
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return translated_dict
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def _export_time_compute_elevation(self, data):
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my_dict = data["my_dict"]
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reach = data["reach"]
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if reach.has_bedload():
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z_min = data["zfd"]
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else:
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z_min = [profile.geometry.z_min()] * len(self._timestamps)
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my_dict["bed_elevation"] = z_min
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def _export_time_compute_depth(self, data):
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my_dict = data["my_dict"]
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profile = data["profile"]
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z = data["z"]
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my_dict["depth"] = list(
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map(lambda x: profile.geometry.max_water_depth(x), z)
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)
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def _export_time_compute_mean_depth(self, data):
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my_dict = data["my_dict"]
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profile = data["profile"]
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z = data["z"]
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my_dict["mean_depth"] = list(
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map(lambda x: profile.geometry.mean_water_depth(x), z)
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)
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def _export_time_compute_froude(self, data):
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my_dict = data["my_dict"]
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profile = data["profile"]
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z = data["z"]
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v = data["v"]
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my_dict["froude"] = list(
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map(
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lambda z, v: profile.geometry.froude(z, v),
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z, v
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)
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)
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def _export_time_compute_wet_area(self, data):
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my_dict = data["my_dict"]
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profile = data["profile"]
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z = data["z"]
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my_dict["wet_area"] = list(
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map(
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lambda x: profile.geometry.wet_area(x),
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z
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)
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)
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def get_timestamps(self):
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self._timestamps = sorted(list(self._results[0].get("timestamps")))
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