def make_figure():
from scipy.optimize import curve_fit
from pyphare.pharesee.hierarchy import finest_field
rwT = Run("./withTagging")
rNoRef = Run("./noRefinement")
plot_time = 11
v = 2
BwT = rwT.GetB(plot_time)
BNoRef = rNoRef.GetB(plot_time)
JwT = rwT.GetJ(plot_time)
JNoRef = rNoRef.GetJ(plot_time)
bywT, xbywT = finest_field(BwT, "By")
byNoRef, xbyNoRef = finest_field(BNoRef, "By")
jzwT, xjzwT = finest_field(JwT, "Jz")
jzNoRef, xjzNoRef = finest_field(JNoRef, "Jz")
fig, axarr = plt.subplots(nrows=3, figsize=(8, 8))
def S(x, x0, l):
return 0.5 * (1 + np.tanh((x - x0) / l))
def by(x):
L = 200
v1 = -1
v2 = 1
return v1 + (v2 - v1) * (S(x, L * 0.25, 1) - S(x, L * 0.75, 1))
wT0 = 150.
ax0, ax1, ax2 = axarr
ax0.plot(xbywT, bywT)
ax0.plot(xbyNoRef, byNoRef, color="k", alpha=0.6)
ax0.plot(xbyNoRef, by(xbyNoRef), ls='--')
ax1.plot(xbywT, bywT)
ax1.plot(xbyNoRef, byNoRef, color='k')
ax1.set_xlim((wT0, 195))
ax1.set_ylim((-1.5, 2))
ax2.plot(xjzwT, jzwT)
ax2.plot(xjzNoRef, jzNoRef, color='k')
ax2.set_xlim((wT0, 195))
ax2.set_ylim((-1.5, 0.5))
# draw level patches
for ilvl, level in BwT.levels().items():
for patch in level.patches:
dx = patch.layout.dl[0]
x0 = patch.origin[0]
x1 = (patch.box.upper[0] + 1) * patch.layout.dl[0]
for ax in (ax1, ax2, ax0):
ax.axvspan(x0,
x1,
color='b',
ec='k',
alpha=0.2,
ymin=ilvl / 4,
ymax=(ilvl + 1) / 4)
from pyphare.pharesee.plotting import zoom_effect
zoom_effect(ax0, ax1, wT0, 195)
for ax in (ax0, ax1, ax2):
ax.axvline(wT0 + plot_time * v, color="r")
# select data around the rightward TD
idx = np.where((xbywT > 150) & (xbywT < 190))
xx = xbywT[idx]
bby = bywT[idx]
# now we will fit by_fit to the data
# and we expect to find x0=172 and L=1
# or close enough
def by_fit(x, x0, L):
v1 = 1
v2 = -1
return v1 + (v2 - v1) * S(x, x0, L)
popt, pcov = curve_fit(by_fit, xx, bby, p0=(150, 1))
x0, L = popt
if np.abs(L - 1) > 0.5:
raise RuntimeError(f"L (={L}) too far from 1.O")
if np.abs(x0 - (150 + plot_time * v)) > 0.5:
raise RuntimeError(f"x0 (={x0}) too far from 172")
def finest_field_plot(run_path, qty, **kwargs):
"""
plot the given quantity (qty) at 'run_path' with only the finest data
* run_path : the path of the run
* qty : ['Bx', 'By', 'Bz', 'Ex', 'Ey', 'Ez', 'Fx', 'Fy', 'Fz', 'Vx', 'Vy', 'Vz', 'rho']
kwargs:
* ax : the handle for the fig axes
* time : time (that should be in the time_stamps of the run)
* interp : the type of interpolation for the interpolator
* draw_style : steps-mid ou default... only for 1d
* title : (str) title of the plot
* xlabel, ylabel
* xlim, ylim
* filename : (str) if exists, save plot to figure under that name
return value : fig,ax
"""
import os
from pyphare.pharesee.hierarchy import get_times_from_h5
from pyphare.pharesee.run import Run
from mpl_toolkits.axes_grid1 import make_axes_locatable
import pyphare.core.gridlayout as gridlayout
r = Run(run_path)
time = kwargs.get("time", None)
dim = r.GetDl('finest', time).shape[0]
interp = kwargs.get("interp", "nearest")
domain = r.GetDomainSize()
if qty in ['Bx', 'By', 'Bz']:
file = os.path.join(run_path, "EM_B.h5")
if time is None:
times = get_times_from_h5(file)
time = times[0]
interpolator, finest_coords = r.GetB(time, merged=True,\
interp=interp)[qty]
elif qty in ['Ex', 'Ey', 'Ez']:
file = os.path.join(run_path, "EM_E.h5")
if time is None:
times = get_times_from_h5(file)
time = times[0]
interpolator, finest_coords = r.GetE(time, merged=True,\
interp=interp)[qty]
elif qty in ['Vx', 'Vy', 'Vz']:
file = os.path.join(run_path, "ions_bulkVelocity.h5")
if time is None:
times = get_times_from_h5(file)
time = times[0]
interpolator, finest_coords = r.GetVi(time, merged=True,\
interp=interp)[qty]
elif qty == 'rho':
file = os.path.join(run_path, "ions_density.h5")
if time is None:
times = get_times_from_h5(file)
time = times[0]
interpolator, finest_coords = r.GetNi(time, merged=True,\
interp=interp)[qty]
elif qty in ("Jx", "Jy", "Jz"):
file = os.path.join(run_path, "EM_B.h5")
if time is None:
times = get_times_from_h5(file)
time = times[0]
interpolator, finest_coords = r.GetJ(time, merged=True,\
interp=interp)[qty]
else:
# ___ TODO : should also include the files for a given population
raise ValueError(
"qty should be in ['Bx', 'By', 'Bz', 'Ex', 'Ey', 'Ez', 'Fx', 'Fy', 'Fz', 'Vx', 'Vy', 'Vz', 'rho']"
)
if "ax" not in kwargs:
fig, ax = plt.subplots()
else:
ax = kwargs["ax"]
fig = ax.figure
if dim == 1:
drawstyle = kwargs.get("drawstyle", "steps-mid")
ax.plot(finest_coords[0], interpolator(finest_coords[0]),\
drawstyle=drawstyle)
elif dim == 2:
x = finest_coords[0]
y = finest_coords[1]
dx = x[1] - x[0]
dy = y[1] - y[0]
# pcolormesh considers DATA_ij to be the center of the pixel
# and X,Y are the corners so XY need to be made 1 value larger
# and shifted around DATA_ij
x -= dx / 2
x = np.append(x, x[-1] + dx)
y -= dy / 2
y = np.append(y, y[-1] + dy)
X, Y = np.meshgrid(x, y)
DATA = interpolator(X, Y)
vmin = kwargs.get("vmin", np.nanmin(DATA))
vmax = kwargs.get("vmax", np.nanmax(DATA))
cmap = kwargs.get("cmap", 'Spectral_r')
im = ax.pcolormesh(x, y, DATA, cmap=cmap, vmin=vmin, vmax=vmax)
ax.set_aspect("equal")
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.08)
cb = plt.colorbar(im, ax=ax, cax=cax)
else:
raise ValueError("finest_field_plot not yet ready for 3d")
ax.set_title(kwargs.get("title", ""))
ax.set_xlabel(kwargs.get("xlabel", "$x c / \omega_p$"))
ax.set_ylabel(kwargs.get("ylabel", "$y c / \omega_p$"))
if "xlim" in kwargs:
ax.set_xlim(kwargs["xlim"])
if "ylim" in kwargs:
ax.set_ylim(kwargs["ylim"])
if "filename" in kwargs:
fig.savefig(kwargs["filename"])
return fig, ax