modify advect option

Author: AntSimi

examples/06_grid_manipulation/pet_advect.py

@@ -73,7 +73,7 @@ def save(self, *args, **kwargs):
 # %%
 # Movie properties
 kwargs = dict(frames=arange(51), interval=100)
-kw_p = dict(nb_step=2, time_step=21600)
+kw_p = dict(u_name="u", v_name="v", nb_step=2, time_step=21600)
 frame_t = kw_p["nb_step"] * kw_p["time_step"] / 86400.0
 
 
@@ -102,21 +102,21 @@ def update(i_frame, t_step):
 # ^^^^^^^^^^^^^^^^
 # Draw 3 last position in one path for each particles.,
 # it could be run backward with `backward=True` option in filament method
-p = g.filament(x, y, "u", "v", **kw_p, filament_size=3)
+p = g.filament(x, y, **kw_p, filament_size=3)
 fig, txt, l, t = anim_ax(lw=0.5)
 _ = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))
 
 # %%
 # Particle forward
 # ^^^^^^^^^^^^^^^^^
 # Forward advection of particles
-p = g.advect(x, y, "u", "v", **kw_p)
+p = g.advect(x, y, **kw_p)
 fig, txt, l, t = anim_ax(ls="", marker=".", markersize=1)
 _ = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))
 
 # %%
 # We get last position and run backward until original position
-p = g.advect(x, y, "u", "v", **kw_p, backward=True)
+p = g.advect(x, y, **kw_p, backward=True)
 fig, txt, l, _ = anim_ax(ls="", marker=".", markersize=1)
 _ = VideoAnimation(fig, update, **kwargs, fargs=(-frame_t,))
 
@@ -139,9 +139,9 @@ def update(i_frame, t_step):
 )
 for time_step in (10800, 21600, 43200, 86400):
     x, y = x0.copy(), y0.copy()
-    kw_advect = dict(nb_step=int(50 * 86400 / time_step), time_step=time_step)
-    g.advect(x, y, "u", "v", **kw_advect).__next__()
-    g.advect(x, y, "u", "v", **kw_advect, backward=True).__next__()
+    kw_advect = dict(nb_step=int(50 * 86400 / time_step), time_step=time_step, u_name="u", v_name="v")
+    g.advect(x, y, **kw_advect).__next__()
+    g.advect(x, y, **kw_advect, backward=True).__next__()
     d = ((x - x0) ** 2 + (y - y0) ** 2) ** 0.5
     ax.hist(d, **kw, label=f"{86400. / time_step:.0f} time step by day")
 ax.set_xlim(0, 0.25), ax.set_ylim(0, 100), ax.legend(loc="lower right"), ax.grid()
@@ -158,9 +158,9 @@ def update(i_frame, t_step):
 time_step = 10800
 for duration in (5, 50, 100):
     x, y = x0.copy(), y0.copy()
-    kw_advect = dict(nb_step=int(duration * 86400 / time_step), time_step=time_step)
-    g.advect(x, y, "u", "v", **kw_advect).__next__()
-    g.advect(x, y, "u", "v", **kw_advect, backward=True).__next__()
+    kw_advect = dict(nb_step=int(duration * 86400 / time_step), time_step=time_step, u_name="u", v_name="v")
+    g.advect(x, y, **kw_advect).__next__()
+    g.advect(x, y, **kw_advect, backward=True).__next__()
     d = ((x - x0) ** 2 + (y - y0) ** 2) ** 0.5
     ax.hist(d, **kw, label=f"Time duration {duration} days")
 ax.set_xlim(0, 0.25), ax.set_ylim(0, 100), ax.legend(loc="lower right"), ax.grid()

examples/06_grid_manipulation/pet_lavd.py

@@ -110,9 +110,9 @@ def save(self, *args, **kwargs):
 step_by_day = 3
 # Compute step of advection every 4h
 nb_step = 2
-kw_p = dict(nb_step=nb_step, time_step=86400 / step_by_day / nb_step)
+kw_p = dict(nb_step=nb_step, time_step=86400 / step_by_day / nb_step, u_name="u", v_name="v")
 # Start a generator which at each iteration return new position at next time step
-particule = g.advect(x, y, "u", "v", **kw_p, rk4=True)
+particule = g.advect(x, y, **kw_p, rk4=True)
 
 # %%
 # LAVD

examples/07_cube_manipulation/pet_fsle_med.py

@@ -142,8 +142,8 @@ def build_triplet(x, y, step=0.02):
 used = zeros(x.shape[0], dtype="bool")
 
 # advection generator
-kw = dict(t_init=t0, nb_step=1, backward=backward, mask_particule=used)
-p = c.advect(x, y, "u", "v", time_step=86400 / time_step_by_days, **kw)
+kw = dict(t_init=t0, nb_step=1, backward=backward, mask_particule=used, u_name="u", v_name="v")
+p = c.advect(x, y, time_step=86400 / time_step_by_days, **kw)
 
 # We check at each step of advection if particle distance is over `dist_max`
 for i in range(time_step_by_days * nb_days):

examples/07_cube_manipulation/pet_lavd_detection.py

@@ -93,7 +93,7 @@ def update_axes(ax, mappable=None):
 # Time properties, for example with advection only 25 days
 nb_days, step_by_day = 25, 6
 nb_time = step_by_day * nb_days
-kw_p = dict(nb_step=1, time_step=86400 / step_by_day)
+kw_p = dict(nb_step=1, time_step=86400 / step_by_day, u_name="u", v_name="v")
 t0 = 20236
 t0_grid = c[t0]
 # Geographic properties, we use a coarser resolution for time consuming reasons
@@ -114,7 +114,7 @@ def update_axes(ax, mappable=None):
 # ----------------------------
 lavd = zeros(original_shape)
 lavd_ = lavd[m]
-p = c.advect(x0.copy(), y0.copy(), "u", "v", t_init=t0, **kw_p)
+p = c.advect(x0.copy(), y0.copy(), t_init=t0, **kw_p)
 for _ in range(nb_time):
     t, x, y = p.__next__()
     lavd_ += abs(c.interp("vort", t / 86400.0, x, y))
@@ -131,7 +131,7 @@ def update_axes(ax, mappable=None):
 # -----------------------------
 lavd = zeros(original_shape)
 lavd_ = lavd[m]
-p = c.advect(x0.copy(), y0.copy(), "u", "v", t_init=t0, backward=True, **kw_p)
+p = c.advect(x0.copy(), y0.copy(), t_init=t0, backward=True, **kw_p)
 for i in range(nb_time):
     t, x, y = p.__next__()
     lavd_ += abs(c.interp("vort", t / 86400.0, x, y))
@@ -148,7 +148,7 @@ def update_axes(ax, mappable=None):
 # ---------------------------
 lavd = zeros(original_shape)
 lavd_ = lavd[m]
-p = t0_grid.advect(x0.copy(), y0.copy(), "u", "v", **kw_p)
+p = t0_grid.advect(x0.copy(), y0.copy(), **kw_p)
 for _ in range(nb_time):
     x, y = p.__next__()
     lavd_ += abs(t0_grid.interp("vort", x, y))
@@ -165,7 +165,7 @@ def update_axes(ax, mappable=None):
 # ----------------------------
 lavd = zeros(original_shape)
 lavd_ = lavd[m]
-p = t0_grid.advect(x0.copy(), y0.copy(), "u", "v", backward=True, **kw_p)
+p = t0_grid.advect(x0.copy(), y0.copy(), backward=True, **kw_p)
 for i in range(nb_time):
     x, y = p.__next__()
     lavd_ += abs(t0_grid.interp("vort", x, y))

examples/16_network/pet_follow_particle.py

@@ -95,11 +95,11 @@ def save(self, *args, **kwargs):
 a.txt.set_position((25, 31))
 
 step = 0.25
-kw_p = dict(nb_step=2, time_step=86400 * step * 0.5, t_init=t_snapshot - 2 * step)
+kw_p = dict(nb_step=2, time_step=86400 * step * 0.5, t_init=t_snapshot - 2 * step, u_name="u", v_name="v")
 
 mappables = dict()
-particules = c.advect(x, y, "u", "v", **kw_p)
-filament = c.filament(x_f, y_f, "u", "v", **kw_p, filament_size=3)
+particules = c.advect(x, y, **kw_p)
+filament = c.filament(x_f, y_f, **kw_p, filament_size=3)
 kw = dict(ls="", marker=".", markersize=0.25)
 for k in index_:
     m = k == index