def update(filename):
if verbose > 0:
print('Generating frame for file {}'.format(filename))
data = sdf.read(filename)
var = data.__dict__[varname]
vdata = var.data
grid = var.grid
i1 = 0
y = grid.data[i1]
ax = plt.gca()
im.set_array(vdata.ravel())
# Hack to change y axis for moving window. Change tick labels
# instead of changing the limits of axes. This plays better
# with pcolormesh.
ymult, ysym = get_si_prefix(np.max(y) - np.min(y))
curr_ticks = ax.get_yticks()
new_ticks = np.linspace(np.min(y), np.max(y), num=np.size(curr_ticks))
new_ticks = np.array(['{:.2f}'.format(x * ymult) for x in new_ticks])
ax.set_yticklabels(new_ticks)
ax.set_ylabel(grid.labels[i1] + ' $(' + ysym + grid.units[i1] + ')$')
plt.title('step={}, time={}'.format(data.Header['step'],
data.Header['time']))
return im,
def main():
path = "/Users/stephendiiorio/Documents/Research/1D_Sim/"
fnums = ["00056", "00060", "00070", "00088"]
fname = []
for n in fnums:
fname.append(path + n + ".sdf")
fig, axarr = plt.subplots(2, 2, sharex='col', sharey='row')
fig.set_facecolor("w")
txt = fig.suptitle('Electric Field Evolution', verticalalignment='bottom')
# only have a single file to plot, so we so this little hack since
# axarr does not come out in an array in this case
if not isinstance(axarr, np.ndarray):
axarr = np.array([axarr])
e_data = []
t_data = []
for i in range(len(fname)):
sdfdata = sdf.read(fname[i])
e_data.append(sdfdata.Electric_Field_Ex)
t_data.append(sdfdata.Header['time'])
x_axis = e_data[i].grid_mid.data[0]
tmult0, tsym0 = get_si_prefix(t_data[0])
tmult1, tsym1 = get_si_prefix(t_data[1])
tmult2, tsym2 = get_si_prefix(t_data[2])
tmult3, tsym3 = get_si_prefix(t_data[3])
axarr[0, 0].plot(x_axis, e_data[0].data, 'k')
axarr[0, 0].set_title(('t={0:.2f} $' + tsym0 + 's$').format(t_data[0] * tmult0))
axarr[0, 1].plot(x_axis, e_data[1].data, 'k')
axarr[0, 1].set_title(('t={0:.2f} $' + tsym1 + 's$').format(t_data[1] * tmult1))
axarr[1, 0].plot(x_axis, e_data[2].data, 'k')
axarr[1, 0].set_title(('t={0:.2f} $' + tsym2 + 's$').format(t_data[2] * tmult2))
axarr[1, 1].plot(x_axis, e_data[3].data, 'k')
axarr[1, 1].set_title(('t={0:.2f} $' + tsym3 + 's$').format(t_data[3] * tmult3))
xmin, xmax = get_var_range(x_axis)
xmult, xsym = get_si_prefix(xmax - xmin)
axarr[1, 0].xaxis.set_major_formatter(FuncFormatter(lambda x, y: '{0:g}'.format(x * xmult)))
axarr[1, 1].xaxis.set_major_formatter(FuncFormatter(lambda x, y: '{0:g}'.format(x * xmult)))
ymult1, ysym1 = get_si_prefix(e_data[0].data.max() - e_data[0].data.min())
ymult2, ysym2 = get_si_prefix(e_data[2].data.max() - e_data[2].data.min())
axarr[0, 0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult1)))
axarr[1, 0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult2)))
axarr[0, 0].set(ylabel='Electric Field' + ' $(' + ysym1 + 'V/m)$')
axarr[1, 0].set(xlabel='x' + ' $(' + xsym + 'm)$', ylabel='Electric Field' + ' $(' + ysym2 + 'V/m)$')
axarr[1, 1].set(xlabel='x' + ' $(' + xsym + 'm)$')
# Hide x labels and tick labels for top plots and y ticks for right plots.
for ax in axarr.flat:
ax.label_outer()
plt.savefig('efield.png', dpi=600, bbox_extra_artists=(txt,), bbox_inches = "tight")
def update(filename):
if verbose > 0:
print('Generating frame for file {}'.format(filename))
data = sdf.read(filename)
var = data.__dict__[varname]
vdata = var.data
im.set_ydata(vdata)
ax = plt.gca()
ticker.Locator.MAXTICKS = 2000
ax.xaxis.set_major_locator(ticker.MultipleLocator(5e-6))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.5e-6))
ax.yaxis.set_major_locator(ticker.MultipleLocator(1e9))
ax.yaxis.set_minor_locator(ticker.MultipleLocator(0.1e9))
ax.set_ylim(np.min(vdata), np.max(vdata))
ymult, ysym = get_si_prefix(np.max(vdata) - np.min(vdata))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
plt.ylabel(var.name + ' $(' + ysym + var.units + ')$')
plt.title('step={}, time={}'.format(data.Header['step'],
data.Header['time']))
return im,
def main():
path = "/scratch/lsa_flux/diiorios/Exp_Ar_32618/Full_smaller/"
fnums = ["00008", "00200"]
fname = []
for n in fnums:
fname.append(path + n + ".sdf")
fig, axarr = plt.subplots(1, 2, sharey='row')
plt.set_cmap(cm.coolwarm)
fig.set_facecolor("w")
# txt = fig.suptitle('Laser Focus and Initial Electric Field', verticalalignment='bottom')
# only have a single file to plot, so we so this little hack since
# axarr does not come out in an array in this case
if not isinstance(axarr, np.ndarray):
axarr = np.array([axarr])
x_data = []
y_data = []
e_data = []
t_data = []
i0 = 1
i1 = 0
for i in range(len(fname)):
sdfdata = sdf.read(fname[i])
e_data.append(sdfdata.Electric_Field_Ey)
x_data.append(e_data[i].grid.data[i0])
y_data.append(e_data[i].grid.data[i1])
t_data.append(sdfdata.Header['time'])
tmult0, tsym0 = get_si_prefix(t_data[0])
tmult1, tsym1 = get_si_prefix(t_data[1])
ymin1, ymax1 = get_var_range(y_data[0])
ymult1, ysym1 = get_si_prefix(ymax1 - ymin1)
ymin2, ymax2 = get_var_range(y_data[1])
ymult2, ysym2 = get_si_prefix(ymax2 - ymin2)
y_data[0] = np.add(y_data[0], 4.5/ymult1)
y_data[1] = np.add(y_data[1], 4.5/ymult2)
xmin1, xmax1 = get_var_range(x_data[0])
xmult1, xsym1 = get_si_prefix(xmax1 - xmin1)
xmin2, xmax2 = get_var_range(x_data[1])
xmult2, xsym2 = get_si_prefix(xmax2 - xmin2)
# calculate again because array was shifted
ymin1, ymax1 = get_var_range(y_data[0])
ymult1, ysym1 = get_si_prefix(ymax1 - ymin1)
ymin2, ymax2 = get_var_range(y_data[1])
ymult2, ysym2 = get_si_prefix(ymax2 - ymin2)
axarr[0].pcolormesh(x_data[0], y_data[0], e_data[0].data)
axarr[0].set_title(('t={0:.2f} $' + tsym0 + 's$').format(t_data[0] * tmult0))
im = axarr[1].pcolormesh(x_data[1], y_data[1], e_data[1].data)
axarr[1].set_title(('t={0:.2f} $' + tsym1 + 's$').format(t_data[1] * tmult1))
axarr[0].xaxis.set_major_formatter(FuncFormatter(lambda x, y: '{0:g}'.format(x * xmult1)))
axarr[1].xaxis.set_major_formatter(FuncFormatter(lambda x, y: '{0:g}'.format(x * xmult2)))
axarr[0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult1)))
axarr[0].set(xlabel='x' + ' $(' + xsym1 + 'm)$', ylabel='y' + ' $(' + ysym1 + 'm)$')
axarr[1].set(xlabel='x' + ' $(' + xsym2 + 'm)$')
axarr[0].set_ylim([-10e-6, 10e-6])
axarr[1].set_ylim([-10e-6, 10e-6])
axarr[0].get_xaxis().set_tick_params(direction='in')
axarr[1].get_xaxis().set_tick_params(direction='in')
axarr[0].get_yaxis().set_tick_params(direction='in')
axarr[1].get_yaxis().set_tick_params(direction='in')
plt.set_cmap(cm.coolwarm)
# divider = make_axes_locatable(axarr[1])
# cax = divider.append_axes("right", "5%", pad="15%")
cbar = fig.colorbar(im, ax=axarr.ravel().tolist(),#cax=cax, ax=axarr[1],
label='Electric Field ($E_{y}$) Direction',
ticks=[e_data[1].data.min(), e_data[1].data.max()])
cbar.ax.set_yticklabels(['$(-)$', '$(+)$'])
plt.savefig('2defield.png', dpi=600, # bbox_extra_artists=(txt,),
bbox_inches="tight")
def plot_figure(filename, varname, vmin=None, vmax=None, scale=False,
figsize=None, ax=None):
"""
Plot the given variable for each file from a simulation
"""
from matplotlib.ticker import FuncFormatter
global verbose, title_info
if verbose > 1:
print('Plotting {} from file {}'.format(varname, filename))
axis_type = 1 # 0 - off, 1 - left+bottom, 2 - all
if ax is not None:
fig = ax.get_figure()
elif figsize is None:
fig, ax = plt.subplots(1, 1, figsize=(8, 8))
else:
fig, ax = plt.subplots(1, 1, figsize=figsize)
if verbose > 1:
print('Adjusting subplot')
if axis_type == 0:
plt.subplots_adjust(left=0, right=0.9, bottom=0.05, top=0.92,
wspace=0, hspace=0)
else:
plt.subplots_adjust(left=0.1, right=0.9, bottom=0.1, top=0.92,
wspace=0, hspace=0)
plt.set_cmap(cm.coolwarm)
if verbose > 1:
print('Reading data')
# Draw initial plot
f = filename
data = sdf.read(f)
var = data.__dict__[varname]
grid = var.grid
num_x_axis_pts, num_y_axis_pts = grid.dims
vdata = var.data.reshape(num_x_axis_pts, num_y_axis_pts).T
print(vdata)
vscale = get_scale(filename, varname, scale)
i0 = 0
i1 = 1
if len(grid.dims) == 2:
x = grid.data[i0]
y = grid.data[i1]
else:
if (grid.dims[0] == 1):
orig = var.grid.name.replace('/', '_') + '_Orig'
grid = data.__dict__[orig]
i0 = 2
i1 = 1
x = grid.data[i0]
y = grid.data[i1]
elif (grid.dims[1] == 1):
i0 = 0
i1 = 1
x = grid.data[0][:, 0, :]
y = grid.data[1][:, 0, :]
else:
i0 = 0
i1 = 2
x = grid.data[0][:, :, 0]
y = grid.data[1][:, :, 0]
z = grid.data[2][:, :, 0]
x = np.sqrt(x * x + y * y)
y = z
if verbose > 1:
print('Scaling data')
vdata = vdata * vscale
if vmin is None:
vmin, vmax = get_var_range_from_sdf_files((filename,), varname, scale)
if verbose > 1:
print('Plotting data')
im = ax.pcolormesh(x, y, vdata, vmin=vmin, vmax=vmax)
if verbose > 1:
print('Plotting axes')
def fmt(x, pos):
return r'${}$'.format(x)
xmult, xsym = get_si_prefix(np.max(x) - np.min(x))
ymult, ysym = get_si_prefix(np.max(y) - np.min(y))
if verbose > 1:
print('Scale axis by {} ({}, {})'.format(xmult, np.min(x), np.max(x)))
ax.xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
ax.set_xlabel(grid.labels[i0] + ' $(' + xsym + grid.units[i0] + ')$')
ax.set_ylabel(grid.labels[i1] + ' $(' + ysym + grid.units[i1] + ')$')
ax.axis('image')
if axis_type == 0:
ax.axis('off')
elif axis_type == 1:
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.get_xaxis().tick_bottom()
ax.get_yaxis().tick_left()
# Add colorbar
mult, sym = get_si_prefix(vmax - vmin)
if verbose > 0 and plot_figure.first:
plot_figure.first = False
print('Scale colorbar by {} ({}, {})'.format(mult, vmin, vmax))
data_label = var.name + ' $(' + sym + var.units + ')$'
if title_info:
legend_label = ''
else:
legend_label = data_label
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", "5%", pad="15%")
cbar = fig.colorbar(im, cax=cax, ax=ax, label=legend_label,
format=FuncFormatter(lambda x, y: x * mult))
if title_info:
title_label = data_label + ', '
else:
title_label = ''
fig.fs = 'large'
fig.suptitle(title_label + 'step={}, time={}'.format(data.Header['step'],
data.Header['time']), fontsize=fig.fs, y=0.98)
fig.sca(ax)
fig.canvas.draw()
if verbose > 1:
print('Done plotting {} from file {}'.format(varname, filename))
return im, ax
def plot_first_figure(file_list, varname, vmin=None, vmax=None, scale=False):
global verbose, title_info
if verbose > 1:
print('Getting data range')
if vmin is None and vmax is None:
vmin, vmax = get_var_range_from_sdf_files(file_list, varname, scale)
elif vmin is None:
vmin = get_var_range_from_sdf_files(file_list, varname, scale)[0]
elif vmax is None:
vmax = get_var_range_from_sdf_files(file_list, varname, scale)[1]
if verbose > 1:
print('Found data range ({}, {})'.format(vmin, vmax))
filename = file_list[0]
im, ax = plot_figure(filename, varname, vmin, vmax, scale)
fig = ax.get_figure()
renderer = find_renderer(fig)
box_orig = fig.bbox_inches
box_raw = fig.get_tightbbox(renderer)
pp = box_raw.get_points()
figsize = (pp[1, 0] - pp[0, 0], pp[1, 1] - pp[0, 1])
ratio = figsize[0] / figsize[1]
if ratio > 1:
w = box_orig.width
h = w / ratio
h = round(10 * h) / 10.
figsize = (w, h)
else:
h = box_orig.height
w = h * ratio
w = round(10 * w) / 10.
figsize = (w, h)
im, ax = plot_figure(filename, varname, vmin, vmax, scale, figsize)
fig = ax.get_figure()
# Get positions of the title's step and time text fields so that they
# can be updated when animating
data = sdf.read(file_list[-1])
var = data.__dict__[varname]
mult, sym = get_si_prefix(vmax - vmin)
data_label = var.name + ' $(' + sym + var.units + ')$, '
if title_info:
title_label = data_label + ', '
title_label2 = data_label + ',_'
else:
title_label = ''
title_label2 = ''
fig._suptitle.set_text(title_label +
'step={}, time={}'.format(data.Header['step'],
data.Header['time']))
bbox = fig._suptitle.get_window_extent(renderer)
inv = fig.transFigure.inverted()
x0 = inv.transform(bbox)[0][0]
y = inv.transform(bbox)[0][1]
fig.y = y
tt = fig.text(x0, y, title_label2,
fontsize=fig.fs, ha='left', va='bottom')
bbox = tt.get_window_extent(renderer)
fig.x1 = inv.transform(bbox)[1][0]
fig.y = inv.transform(bbox)[0][1]
tt.set_text(title_label)
tt = fig.text(fig.x1, y, 'step={},_'.format(data.Header['step']),
fontsize=fig.fs, ha='left', va='bottom')
bbox = tt.get_window_extent(renderer)
fig.x2 = inv.transform(bbox)[1][0]
tt.set_visible(False)
fig._suptitle.set_visible(False)
return im, fig
def main():
filepath = "Ion_Results/10000fs/2Levels_N"
files = glob.glob(filepath + "/*.npz")
# print(files)
# print(len(files))
title = 'Nitrogen Ionization Last 2 Ionization Levels(10000fs), w BSI, wo Multiphoton'
# ion_energies = [13.59844]
#ion_energies = [24.58741, 54.41778]
ion_energies = [14.53414, 29.6013, 47.44924, 77.4735, 97.8902, 552.0718, 667.046]
e_nums = []
e_field = []
calc_intens = []
for f in files:
data = np.load(f)
e_nums.append(data['arr_0'][0])
e_field.append(data['arr_1'][0])
data.close()
e_field, e_nums = (list(t) for t in zip(*sorted(zip(e_field, e_nums))))
for i, val in enumerate(ion_energies):
calc_intens.append(ion_intens(val, i + 1))
# print(e_nums)
# print(e_field)
# print(calc_intens)
fig = plt.figure()
plt.title(title, y=1.12)
ax = fig.add_subplot(111)
l1, = ax.semilogx(e_field, e_nums, label='EPOCH Results')
ax.set_xlabel(r'Electric Field $(V/m)$')
ymult, ysym = get_si_prefix(np.max(e_nums) - np.min(e_nums))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
ax.set_ylabel(r'Derived Electron Number Density $(' + ysym + 'm^{-3})$')
left_lim, right_lim = ax.get_xlim()
scale_left_lim = np.power(left_lim, 2) * sc.speed_of_light * sc.epsilon_0 / 2.0
scale_right_lim = np.power(right_lim, 2) * sc.speed_of_light * sc.epsilon_0 / 2.0
ax2 = ax.twiny()
ax2.set_xscale('log')
ax2.set_xlim(scale_left_lim, scale_right_lim)
ax2.set_xlabel(r'Intensity $(W/m^2)$')
for val in calc_intens:
l2 = ax2.axvline(x=val, c='r', label='Calculated Intensities')
ax3 = ax.twinx()
ax3.set_ylim(0, len(ion_energies))
ax3.set_ylabel('Ionization per Atom')
ls = [l1, l2]
labels = [l.get_label() for l in ls]
ax.legend(ls, labels, loc=0)
plt.tight_layout()
plt.savefig(title + '.png')
return
def main():
absorb_key = 'Absorption_Fraction_of_Laser_Energy_Absorbed____'
inject_key = 'Absorption_Total_Laser_Energy_Injected__J_'
field_en_key = 'Total_Field_Energy_in_Simulation__J_'
part_en_key = 'Total_Particle_Energy_in_Simulation__J_'
filepath = "/scratch/lsa_flux/diiorios/Exp_81418/energy_test"
flist = get_files(wkdir=filepath)
flist = clean_file_list(flist, absorb_key)
flist = clean_file_list(flist, inject_key)
time = []
absorbed = []
injected = []
field = []
part = []
for f in flist:
data = sdf.read(f, mmap=0)
time.append(float(data.Header['time']))
absorbed.append(data.__dict__[absorb_key].data)
injected.append(data.__dict__[inject_key].data)
field.append(data.__dict__[field_en_key].data)
part.append(data.__dict__[part_en_key].data)
tmult, tsym = get_si_prefix(np.max(time) - np.min(time))
amult, asym = get_si_prefix(np.max(absorbed) - np.min(absorbed))
imult, isym = get_si_prefix(np.max(injected) - np.min(injected))
fmult, fsym = get_si_prefix(np.max(field) - np.min(field))
pmult, psym = get_si_prefix(np.max(part) - np.min(part))
fig = plt.figure()
ax = fig.add_subplot(111)
l1, = ax.plot(time, absorbed, 'k', label='Laser Energy Absorbed')
ax.xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * tmult)))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * amult)))
ax.set_xlabel('Time $(' + tsym + 's)$')
ax.set_ylabel('Absorption/Abs_frac')
ax2 = ax.twinx()
l2, = ax2.plot(time, injected, 'r', label='Laser Energy Injected')
ax2.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * imult)))
ax2.set_ylabel('Absorption/Laser_enTotal $(' + isym + 'J)$')
ax3 = ax.twinx()
ax3.spines['right'].set_position(('outward', 60))
l3, = ax3.plot(time, field, 'b', label='Total Field Energy')
ax3.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * fmult)))
ax3.set_ylabel('Total Field Energy $(' + fsym + 'J)$')
ax4 = ax.twinx()
ax4.spines['right'].set_position(('outward', 120))
l4, = ax4.plot(time, part, 'g', label='Total Particle Energy')
ax4.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * pmult)))
ax4.set_ylabel('Total Particle Energy $(' + psym + 'J)$')
ax.yaxis.label.set_color(l1.get_color())
ax2.yaxis.label.set_color(l2.get_color())
ax3.yaxis.label.set_color(l3.get_color())
ax4.yaxis.label.set_color(l4.get_color())
ls = [l1, l2, l3, l4]
labels = [l.get_label() for l in ls]
ax.legend(ls, labels, loc='best')
plt.tight_layout()
plt.savefig('Eng_Cons.png')
return
def plot_figure(filename, varname, vmin=None, vmax=None):
"""
Plot the given variable for each file from a simulation
"""
global verbose
if verbose > 1:
print('Plotting {} from file {}'.format(varname, filename))
fig = plt.figure()
if verbose > 1:
print('Reading data')
data = sdf.read(filename)
var = data.__dict__[varname]
grid = var.grid
num_x_axis_pts, num_y_axis_pts = grid.dims
vdata = var.data.reshape(num_x_axis_pts, num_y_axis_pts).T
x = grid.data[0]
y = np.copy(grid.data[1]) / (sc.value('electron volt') / sc.c)
# y = grid.data[1]
if verbose > 1:
print('Plotting data')
im = plt.pcolormesh(x, y, vdata, vmin=vmin, vmax=vmax)
plt.title('step={}, time={}'.format(data.Header['step'],
data.Header['time']))
plt.axis('tight')
# Get all labels for axes and data
mult, sym = get_si_prefix(vmax - vmin) # Data
data_label = var.name + ' $(' + sym + var.units + ')$'
xmult, xsym = get_si_prefix(np.max(x) - np.min(x)) # x axis
ymult, ysym = get_si_prefix(np.max(y) - np.min(y)) # y axis
if verbose > 1:
print('Plotting axes')
if verbose > 1:
print('Scale axis by {} ({}, {})'.format(xmult, np.min(x), np.max(x)))
ax = plt.gca()
ax.xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
plt.xlabel(grid.labels[0] + ' $(' + xsym + grid.units[0] + ')$')
plt.ylabel(grid.labels[1] + ' $(' + ysym + 'eV/c)$')
# plt.ylabel(grid.labels[1] + ' $(' + ysym + grid.units[1] + ')$')
# remove spines on right and top of plot
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
# only show ticks on left and bottom side for these axes
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
# point ticks outside of plot
ax.yaxis.set_tick_params(direction='out')
ax.xaxis.set_tick_params(direction='out')
if verbose > 1:
print('Plotting colorbar')
plt.colorbar(label=data_label,
format=FuncFormatter(lambda x, y: x * mult)).ax.tick_params(
axis='y', direction='out')
plt.set_cmap(cm.coolwarm)
if verbose > 1:
print('Done plotting {} from file {}'.format(varname, filename))
return im, fig
def main():
path = "/Users/stephendiiorio/Documents/Research/1D_Sim/"
fnums = ["00056", "00060", "00070", "00088"]
fname = []
for n in fnums:
fname.append(path + n + ".sdf")
fig, axarr = plt.subplots(2, 2, sharex='col', sharey='row')
fig.set_facecolor("w")
txt = fig.suptitle('Number Density Evolution', verticalalignment='bottom')
# only have a single file to plot, so we so this little hack since
# axarr does not come out in an array in this case
if not isinstance(axarr, np.ndarray):
axarr = np.array([axarr])
e_data = []
ar_data = []
ar8_data = []
t_data = []
for i in range(len(fname)):
sdfdata = sdf.read(fname[i])
e_data.append(sdfdata.Derived_Number_Density_Electron)
ar_data.append(sdfdata.Derived_Number_Density_Argon)
ar8_data.append(sdfdata.Derived_Number_Density_Argon8)
t_data.append(sdfdata.Header['time'])
x_axis = e_data[i].grid_mid.data[0]
tmult0, tsym0 = get_si_prefix(t_data[0])
tmult1, tsym1 = get_si_prefix(t_data[1])
tmult2, tsym2 = get_si_prefix(t_data[2])
tmult3, tsym3 = get_si_prefix(t_data[3])
l1, = axarr[0, 0].plot(x_axis, e_data[0].data, 'k', label='Electron')
l2, = axarr[0, 0].plot(x_axis, ar_data[0].data, 'r', label='Argon')
l3, = axarr[0, 0].plot(x_axis, ar8_data[0].data, 'b', label='Argon$^{+8}$')
axarr[0, 0].set_title(('t={0:.2f} $' + tsym0 + 's$').format(t_data[0] * tmult0))
axarr[0, 1].plot(x_axis, e_data[1].data, 'k')
axarr[0, 1].plot(x_axis, ar_data[1].data, 'r')
axarr[0, 1].plot(x_axis, ar8_data[0].data, 'b')
axarr[0, 1].set_title(('t={0:.2f} $' + tsym1 + 's$').format(t_data[1] * tmult1))
axarr[1, 0].plot(x_axis, e_data[2].data, 'k')
axarr[1, 0].plot(x_axis, ar_data[2].data, 'r')
axarr[1, 0].plot(x_axis, ar8_data[0].data, 'b')
axarr[1, 0].set_title(('t={0:.2f} $' + tsym2 + 's$').format(t_data[2] * tmult2))
axarr[1, 1].plot(x_axis, e_data[3].data, 'k')
axarr[1, 1].plot(x_axis, ar_data[3].data, 'r')
axarr[1, 1].plot(x_axis, ar8_data[0].data, 'b')
axarr[1, 1].set_title(('t={0:.2f} $' + tsym3 + 's$').format(t_data[3] * tmult3))
xmin, xmax = get_var_range(x_axis)
xmult, xsym = get_si_prefix(xmax - xmin)
axarr[1, 0].xaxis.set_major_formatter(FuncFormatter(lambda x, y: '{0:g}'.format(x * xmult)))
axarr[1, 1].xaxis.set_major_formatter(FuncFormatter(lambda x, y: '{0:g}'.format(x * xmult)))
ymult1, ysym1 = get_si_prefix(e_data[0].data.max() - e_data[0].data.min())
ymult2, ysym2 = get_si_prefix(e_data[2].data.max() - e_data[2].data.min())
axarr[0, 0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult1)))
axarr[1, 0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult2)))
axarr[0, 0].set(ylabel='Number Density' + ' $(' + ysym1 + 'm^{-3})$')
axarr[1, 0].set(xlabel='x' + ' $(' + xsym + 'm)$', ylabel='Number Density' + ' $(' + ysym2 + 'm^{-3})$')
axarr[1, 1].set(xlabel='x' + ' $(' + xsym + 'm)$')
# Hide x labels and tick labels for top plots and y ticks for right plots.
for ax in axarr.flat:
ax.label_outer()
ls = [l1, l2, l3]
labels = [l.get_label() for l in ls]
lgd = axarr[0, 1].legend(ls, labels, bbox_to_anchor=(1.0, 1.045), loc=2)#loc='upper right')
plt.savefig('numdens.png', dpi=600, bbox_extra_artists=(lgd,txt,), bbox_inches = "tight")
def main():
species = "Electron"
path = "/Users/stephendiiorio/Documents/Research/1D_Sim/"
fnums = ["00060", "00070", "00080"]
fname = []
for n in fnums:
fname.append(path + n + ".sdf")
x_axis_num = 0
# y_axis_num = 1
# z_axis_num = 2
fig, axarr = plt.subplots(len(fname), sharex=True) #, sharey=True)
fig.set_facecolor("w")
# only have a single file to plot, so we so this little hack since
# axarr does not come out in an array in this case
if not isinstance(axarr, np.ndarray):
axarr = np.array([axarr])
# axarr[0].set_title(species + " files " + str(fnums))
axarr[0].set_title('Contribution to E Field')
limit = 5E10
for i in range(len(fname)):
sdfdata = sdf.read(fname[i])
e_var = sdfdata.Electric_Field_Ex
# midpoint = int(len(e_var.data[0]) / 2)
temp_grid, temp_data = Temp_Field(sdfdata,
x_axis_num,
species='Electron')
res_mhd_grid, res_mhd_data = Resistive_MHD_Field(sdfdata, x_axis_num)
hall_grid, hall_data = Hall_Field(sdfdata, x_axis_num)
# ideal_mhd_grid, ideal_mhd_data = Ideal_MHD_Field(sdfdata,
# x_axis_num,
# species='Electron')
x_axis = e_var.grid_mid.data[0]
# fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True, sharey=True)
l1, = axarr[i].plot(
x_axis,
e_var.data, # [midpoint],
'k-',
label='Simulation')
# plt.plot(x_axis, e_var.data[midpoint], 'k-', label='Ey')
l2, = axarr[i].plot(
x_axis,
np.clip(
temp_data, # [midpoint],
-limit,
limit),
'r--',
label='Thermal')
# plt.plot(x_axis, temp_data[midpoint], 'r--', label='Temp_Ey')
l3, = axarr[i].plot(
x_axis,
np.clip(
res_mhd_data, # [midpoint],
-limit,
limit),
'b-.',
label='Resistive MHD')
# plt.plot(x_axis, temp_data[midpoint], 'r--', label='Temp_Ey')
l4, = axarr[i].plot(
x_axis,
np.clip(
hall_data, # [midpoint],
-limit,
limit),
'g:',
label='Hall Term')
# fig.legend([l1, l2, l3],
# ['Ey', 'Temp_Ey', 'Res_MHD_Ey'],
# loc='upper right')
ls = [l1, l2, l3, l4]
labels = [l.get_label() for l in ls]
lgd = fig.legend(ls, labels, bbox_to_anchor=(1.05, 1.0), loc=1)
fig.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
plt.xlim(-6.5e-6, 6.5e-6)
# plt.ylim(-limit, limit)
xmin, xmax = get_var_range(x_axis)
xmult, xsym = get_si_prefix(xmax - xmin)
axarr[0].xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
ymult, ysym = get_si_prefix(limit - (-limit))
axarr[0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
axarr[1].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
axarr[2].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
axarr[0].set_ylim([-limit, limit])
axarr[1].set_ylim([-limit, limit])
axarr[2].set_ylim([-0.5 * limit, 0.5 * limit])
plt.xlabel('x' + ' $(' + xsym + 'm)$')
axarr[1].set_ylabel('Electric Field' + ' $(' + ysym + 'V/m)$')
# plt.show()
plt.savefig('test.png',
dpi=600,
bbox_extra_artists=(lgd, ),
bbox_inches="tight",
pad_inches=0.2)
def plot_figure(filename, varname, vmin=None, vmax=None):
"""
Plot the given variable for each file from a simulation
"""
global verbose
if verbose > 1:
print('Plotting {} from file {}'.format(varname, filename))
fig = plt.figure()
if verbose > 1:
print('Reading data')
print(filename)
data = sdf.read(filename)
var = data.__dict__[varname]
vdata = var.data
grid = var.grid_mid
x = grid.data[0]
if verbose > 1:
print('Plotting data')
im, = plt.plot(x, vdata, 'k')
plt.title('step={}, time={}'.format(data.Header['step'],
data.Header['time']))
plt.axis('tight')
# Get all labels for axes and data
xmult, xsym = get_si_prefix(np.max(x) - np.min(x)) # x axis
ymult, ysym = get_si_prefix(np.max(vdata) - np.min(vdata)) # y axis
if verbose > 1:
print('Plotting axes')
if verbose > 1:
print('Scale axis by {} ({}, {})'.format(xmult, np.min(x), np.max(x)))
print('Scale axis by {} ({}, {})'.format(ymult, np.min(vdata),
np.max(vdata)))
ax = plt.gca()
ticker.Locator.MAXTICKS = 2000
ax.xaxis.set_major_locator(ticker.MultipleLocator(5e-6))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.5e-6))
ax.yaxis.set_major_locator(ticker.MultipleLocator(1e9))
ax.yaxis.set_minor_locator(ticker.MultipleLocator(0.1e9))
ax.xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
plt.xlabel(grid.labels[0] + ' $(' + xsym + grid.units[0] + ')$')
plt.ylabel(var.name + ' $(' + ysym + var.units + ')$')
# remove spines on right and top of plot
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
# only show ticks on left and bottom side for these axes
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
# point ticks outside of plot
ax.yaxis.set_tick_params(direction='out')
ax.xaxis.set_tick_params(direction='out')
if verbose > 1:
print('Done plotting {} from file {}'.format(varname, filename))
return im, fig
def main():
directory = '/scratch/lsa_flux/diiorios/2d_run/'
field = 'Electric_Field_Ex'
spec = 'Electron'
den = 'Derived_Number_Density_' + spec
file_list = get_files(wkdir=directory)
e_file_list = clean_file_list(file_list, field)
d_file_list = clean_file_list(file_list, den)
e_file_list.remove(directory + '0000.sdf')
e_file_list.remove(directory + '0002.sdf')
e_file_list.remove(directory + '0003.sdf')
e_file_list.remove(directory + '0004.sdf')
e_file_list.remove(directory + '0005.sdf')
e_file_list.remove(directory + '0006.sdf')
e_file_list.remove(directory + '0007.sdf')
e_file_list.remove(directory + '0008.sdf')
e_file_list.remove(directory + '0009.sdf')
e_file_list.remove(directory + '0011.sdf')
e_file_list.remove(directory + '0012.sdf')
e_file_list.remove(directory + '0013.sdf')
e_file_list.remove(directory + '0014.sdf')
e_file_list.remove(directory + '0015.sdf')
e_file_list.remove(directory + '0016.sdf')
e_file_list.remove(directory + '0017.sdf')
e_file_list.remove(directory + '0018.sdf')
e_file_list.remove(directory + '0019.sdf')
e_file_list.remove(directory + '0021.sdf')
e_file_list.remove(directory + '0022.sdf')
e_file_list.remove(directory + '0023.sdf')
e_file_list.remove(directory + '0024.sdf')
e_file_list.remove(directory + '0025.sdf')
e_file_list.remove(directory + '0026.sdf')
e_file_list.remove(directory + '0027.sdf')
e_file_list.remove(directory + '0028.sdf')
e_file_list.remove(directory + '0029.sdf')
e_file_list.remove(directory + '0031.sdf')
e_file_list.remove(directory + '0032.sdf')
e_file_list.remove(directory + '0033.sdf')
e_file_list.remove(directory + '0034.sdf')
e_file_list.remove(directory + '0035.sdf')
e_file_list.remove(directory + '0036.sdf')
e_file_list.remove(directory + '0037.sdf')
e_file_list.remove(directory + '0038.sdf')
e_file_list.remove(directory + '0039.sdf')
e_file_list.remove(directory + '0041.sdf')
e_file_list.remove(directory + '0042.sdf')
e_file_list.remove(directory + '0043.sdf')
e_file_list.remove(directory + '0044.sdf')
e_file_list.remove(directory + '0045.sdf')
e_file_list.remove(directory + '0046.sdf')
e_file_list.remove(directory + '0047.sdf')
e_file_list.remove(directory + '0048.sdf')
e_file_list.remove(directory + '0049.sdf')
e_file_list.remove(directory + '0051.sdf')
e_file_list.remove(directory + '0052.sdf')
e_file_list.remove(directory + '0053.sdf')
e_file_list.remove(directory + '0054.sdf')
e_file_list.remove(directory + '0055.sdf')
e_file_list.remove(directory + '0056.sdf')
e_file_list.remove(directory + '0057.sdf')
e_file_list.remove(directory + '0058.sdf')
e_file_list.remove(directory + '0059.sdf')
e_file_list.remove(directory + '0061.sdf')
e_file_list.remove(directory + '0062.sdf')
e_file_list.remove(directory + '0063.sdf')
e_file_list.remove(directory + '0064.sdf')
e_file_list.remove(directory + '0065.sdf')
e_file_list.remove(directory + '0066.sdf')
e_file_list.remove(directory + '0067.sdf')
e_file_list.remove(directory + '0068.sdf')
e_file_list.remove(directory + '0069.sdf')
e_file_list.remove(directory + '0071.sdf')
e_file_list.remove(directory + '0072.sdf')
e_file_list.remove(directory + '0073.sdf')
e_file_list.remove(directory + '0074.sdf')
e_file_list.remove(directory + '0075.sdf')
e_file_list.remove(directory + '0076.sdf')
e_file_list.remove(directory + '0077.sdf')
e_file_list.remove(directory + '0078.sdf')
e_file_list.remove(directory + '0079.sdf')
e_file_list.remove(directory + '0081.sdf')
e_file_list.remove(directory + '0082.sdf')
e_file_list.remove(directory + '0083.sdf')
e_file_list.remove(directory + '0084.sdf')
e_file_list.remove(directory + '0085.sdf')
e_file_list.remove(directory + '0086.sdf')
e_file_list.remove(directory + '0087.sdf')
e_file_list.remove(directory + '0088.sdf')
e_file_list.remove(directory + '0089.sdf')
e_file_list.remove(directory + '0091.sdf')
e_file_list.remove(directory + '0092.sdf')
e_file_list.remove(directory + '0093.sdf')
e_file_list.remove(directory + '0094.sdf')
e_file_list.remove(directory + '0095.sdf')
e_file_list.remove(directory + '0096.sdf')
e_file_list.remove(directory + '0097.sdf')
e_file_list.remove(directory + '0098.sdf')
e_file_list.remove(directory + '0099.sdf')
d_file_list.remove(directory + '0000.sdf')
d_file_list.remove(directory + '0002.sdf')
d_file_list.remove(directory + '0003.sdf')
d_file_list.remove(directory + '0004.sdf')
d_file_list.remove(directory + '0005.sdf')
d_file_list.remove(directory + '0006.sdf')
d_file_list.remove(directory + '0007.sdf')
d_file_list.remove(directory + '0008.sdf')
d_file_list.remove(directory + '0009.sdf')
d_file_list.remove(directory + '0011.sdf')
d_file_list.remove(directory + '0012.sdf')
d_file_list.remove(directory + '0013.sdf')
d_file_list.remove(directory + '0014.sdf')
d_file_list.remove(directory + '0015.sdf')
d_file_list.remove(directory + '0016.sdf')
d_file_list.remove(directory + '0017.sdf')
d_file_list.remove(directory + '0018.sdf')
d_file_list.remove(directory + '0019.sdf')
d_file_list.remove(directory + '0021.sdf')
d_file_list.remove(directory + '0022.sdf')
d_file_list.remove(directory + '0023.sdf')
d_file_list.remove(directory + '0024.sdf')
d_file_list.remove(directory + '0025.sdf')
d_file_list.remove(directory + '0026.sdf')
d_file_list.remove(directory + '0027.sdf')
d_file_list.remove(directory + '0028.sdf')
d_file_list.remove(directory + '0029.sdf')
d_file_list.remove(directory + '0031.sdf')
d_file_list.remove(directory + '0032.sdf')
d_file_list.remove(directory + '0033.sdf')
d_file_list.remove(directory + '0034.sdf')
d_file_list.remove(directory + '0035.sdf')
d_file_list.remove(directory + '0036.sdf')
d_file_list.remove(directory + '0037.sdf')
d_file_list.remove(directory + '0038.sdf')
d_file_list.remove(directory + '0039.sdf')
d_file_list.remove(directory + '0041.sdf')
d_file_list.remove(directory + '0042.sdf')
d_file_list.remove(directory + '0043.sdf')
d_file_list.remove(directory + '0044.sdf')
d_file_list.remove(directory + '0045.sdf')
d_file_list.remove(directory + '0046.sdf')
d_file_list.remove(directory + '0047.sdf')
d_file_list.remove(directory + '0048.sdf')
d_file_list.remove(directory + '0049.sdf')
d_file_list.remove(directory + '0051.sdf')
d_file_list.remove(directory + '0052.sdf')
d_file_list.remove(directory + '0053.sdf')
d_file_list.remove(directory + '0054.sdf')
d_file_list.remove(directory + '0055.sdf')
d_file_list.remove(directory + '0056.sdf')
d_file_list.remove(directory + '0057.sdf')
d_file_list.remove(directory + '0058.sdf')
d_file_list.remove(directory + '0059.sdf')
d_file_list.remove(directory + '0061.sdf')
d_file_list.remove(directory + '0062.sdf')
d_file_list.remove(directory + '0063.sdf')
d_file_list.remove(directory + '0064.sdf')
d_file_list.remove(directory + '0065.sdf')
d_file_list.remove(directory + '0066.sdf')
d_file_list.remove(directory + '0067.sdf')
d_file_list.remove(directory + '0068.sdf')
d_file_list.remove(directory + '0069.sdf')
d_file_list.remove(directory + '0071.sdf')
d_file_list.remove(directory + '0072.sdf')
d_file_list.remove(directory + '0073.sdf')
d_file_list.remove(directory + '0074.sdf')
d_file_list.remove(directory + '0075.sdf')
d_file_list.remove(directory + '0076.sdf')
d_file_list.remove(directory + '0077.sdf')
d_file_list.remove(directory + '0078.sdf')
d_file_list.remove(directory + '0079.sdf')
d_file_list.remove(directory + '0081.sdf')
d_file_list.remove(directory + '0082.sdf')
d_file_list.remove(directory + '0083.sdf')
d_file_list.remove(directory + '0084.sdf')
d_file_list.remove(directory + '0085.sdf')
d_file_list.remove(directory + '0086.sdf')
d_file_list.remove(directory + '0087.sdf')
d_file_list.remove(directory + '0088.sdf')
d_file_list.remove(directory + '0089.sdf')
d_file_list.remove(directory + '0091.sdf')
d_file_list.remove(directory + '0092.sdf')
d_file_list.remove(directory + '0093.sdf')
d_file_list.remove(directory + '0094.sdf')
d_file_list.remove(directory + '0095.sdf')
d_file_list.remove(directory + '0096.sdf')
d_file_list.remove(directory + '0097.sdf')
d_file_list.remove(directory + '0098.sdf')
d_file_list.remove(directory + '0099.sdf')
print('Found {} files to plot'.format(len(file_list)))
e_data = []
d_data = []
for f in e_file_list:
d = sdf.read(f)
avg, r, dummy_t = electric_radial_average(d)
e_data.append(avg)
for f in d_file_list:
d = sdf.read(f)
avg, r, dummy_t = density_radial_average(d, den)
d_data.append(avg)
e_var = d.__dict__[field] # for units later
d_var = d.__dict__[den] # for units later
e_data = np.asarray(e_data)
e_data = e_data.T
d_data = np.asarray(d_data)
d_data = d_data.T
tmin = sdf.read(e_file_list[0]).Header['time']
tmax = sdf.read(e_file_list[-1]).Header['time']
t_data = np.linspace(tmin, tmax, np.shape(e_data)[1])
rmin = np.min(r)
rmax = np.max(r)
r_data = np.linspace(rmin, rmax, np.shape(e_data)[0])
print(rmin, rmax)
rmult, rsym = get_si_prefix(rmax - rmin) # y axis
tmult, tsym = get_si_prefix(tmax - tmin) # x axis
emin, emax = get_var_range(e_data)
emax = 3e9
emult, esym = get_si_prefix(emax - emin)
dmin, dmax = get_var_range(d_data)
# dmin = max(d_data.min(), 0.1)
dmax = 0.5e23
dmult, dsym = get_si_prefix(dmax - dmin)
fig, axarr = plt.subplots(2, 1, sharex='col')
fig.set_facecolor("w")
e_im = axarr[0].pcolormesh(
t_data,
r_data,
e_data,
# norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03, vmin=emin, vmax=emax),
cmap=cm.coolwarm,
vmin=emin,
vmax=emax)
axarr[0].set_title('(a)', loc='left')
d_im = axarr[1].pcolormesh(
t_data,
r_data,
d_data,
# norm=colors.LogNorm(vmin=dmin, vmax=dmax),
cmap=cm.plasma,
vmin=dmin,
vmax=dmax)
axarr[1].set_title('(b)', loc='left')
e_label = '$E_{r}$ $(' + esym + e_var.units + ')$'
d_label = 'Radial $n_{e}$ $(' + dsym + d_var.units + ')$'
fig.colorbar(e_im,
ax=axarr[0],
label=e_label,
format=FuncFormatter(lambda x, y: x * emult))
fig.colorbar(d_im,
ax=axarr[1],
label=d_label,
format=FuncFormatter(lambda x, y: x * dmult))
axarr[1].xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * tmult)))
axarr[0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * rmult)))
axarr[1].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * rmult)))
axarr[0].set(ylabel='r $(' + rsym + 'm)$')
axarr[1].set(xlabel='t $(' + tsym + 's)$', ylabel='r $(' + rsym + 'm)$')
axarr[0].set_ylim([rmin, 40e-6])
axarr[1].set_ylim([rmin, 40e-6])
axarr[0].get_xaxis().set_tick_params(direction='in')
axarr[1].get_xaxis().set_tick_params(direction='in')
axarr[0].get_yaxis().set_tick_params(direction='in')
axarr[1].get_yaxis().set_tick_params(direction='in')
# plt.tight_layout()
plt.savefig('time_rad_evo.png', dpi=600, bbox_inches="tight")
def composite_field_plot(varname, vmin=None, vmax=None, directory='Data'):
global verbose, dpi
file_list = get_files(wkdir=directory)
file_list = clean_file_list(file_list, varname)
file_list.remove(directory + '0000.sdf')
file_list.remove(directory + '0002.sdf')
file_list.remove(directory + '0003.sdf')
file_list.remove(directory + '0004.sdf')
file_list.remove(directory + '0005.sdf')
file_list.remove(directory + '0006.sdf')
file_list.remove(directory + '0007.sdf')
file_list.remove(directory + '0008.sdf')
file_list.remove(directory + '0009.sdf')
file_list.remove(directory + '0011.sdf')
file_list.remove(directory + '0012.sdf')
file_list.remove(directory + '0013.sdf')
file_list.remove(directory + '0014.sdf')
file_list.remove(directory + '0015.sdf')
file_list.remove(directory + '0016.sdf')
file_list.remove(directory + '0017.sdf')
file_list.remove(directory + '0018.sdf')
file_list.remove(directory + '0019.sdf')
file_list.remove(directory + '0021.sdf')
file_list.remove(directory + '0022.sdf')
file_list.remove(directory + '0023.sdf')
file_list.remove(directory + '0024.sdf')
file_list.remove(directory + '0025.sdf')
file_list.remove(directory + '0026.sdf')
file_list.remove(directory + '0027.sdf')
file_list.remove(directory + '0028.sdf')
file_list.remove(directory + '0029.sdf')
file_list.remove(directory + '0031.sdf')
file_list.remove(directory + '0032.sdf')
file_list.remove(directory + '0033.sdf')
file_list.remove(directory + '0034.sdf')
file_list.remove(directory + '0035.sdf')
file_list.remove(directory + '0036.sdf')
file_list.remove(directory + '0037.sdf')
file_list.remove(directory + '0038.sdf')
file_list.remove(directory + '0039.sdf')
file_list.remove(directory + '0041.sdf')
file_list.remove(directory + '0042.sdf')
file_list.remove(directory + '0043.sdf')
file_list.remove(directory + '0044.sdf')
file_list.remove(directory + '0045.sdf')
file_list.remove(directory + '0046.sdf')
file_list.remove(directory + '0047.sdf')
file_list.remove(directory + '0048.sdf')
file_list.remove(directory + '0049.sdf')
file_list.remove(directory + '0051.sdf')
file_list.remove(directory + '0052.sdf')
file_list.remove(directory + '0053.sdf')
file_list.remove(directory + '0054.sdf')
file_list.remove(directory + '0055.sdf')
file_list.remove(directory + '0056.sdf')
file_list.remove(directory + '0057.sdf')
file_list.remove(directory + '0058.sdf')
file_list.remove(directory + '0059.sdf')
file_list.remove(directory + '0061.sdf')
file_list.remove(directory + '0062.sdf')
file_list.remove(directory + '0063.sdf')
file_list.remove(directory + '0064.sdf')
file_list.remove(directory + '0065.sdf')
file_list.remove(directory + '0066.sdf')
file_list.remove(directory + '0067.sdf')
file_list.remove(directory + '0068.sdf')
file_list.remove(directory + '0069.sdf')
file_list.remove(directory + '0071.sdf')
file_list.remove(directory + '0072.sdf')
file_list.remove(directory + '0073.sdf')
file_list.remove(directory + '0074.sdf')
file_list.remove(directory + '0075.sdf')
file_list.remove(directory + '0076.sdf')
file_list.remove(directory + '0077.sdf')
file_list.remove(directory + '0078.sdf')
file_list.remove(directory + '0079.sdf')
file_list.remove(directory + '0081.sdf')
file_list.remove(directory + '0082.sdf')
file_list.remove(directory + '0083.sdf')
file_list.remove(directory + '0084.sdf')
file_list.remove(directory + '0085.sdf')
file_list.remove(directory + '0086.sdf')
file_list.remove(directory + '0087.sdf')
file_list.remove(directory + '0088.sdf')
file_list.remove(directory + '0089.sdf')
file_list.remove(directory + '0091.sdf')
file_list.remove(directory + '0092.sdf')
file_list.remove(directory + '0093.sdf')
file_list.remove(directory + '0094.sdf')
file_list.remove(directory + '0095.sdf')
file_list.remove(directory + '0096.sdf')
file_list.remove(directory + '0097.sdf')
file_list.remove(directory + '0098.sdf')
file_list.remove(directory + '0099.sdf')
if verbose > 0:
print('Found {} files to plot'.format(len(file_list)))
data = []
for f in file_list:
d = sdf.read(f)
avg, r, t = density_radial_average(d, varname)
data.append(avg)
var = d.__dict__[varname] # for units later
data = np.asarray(data)
data = data.T
tmin = sdf.read(file_list[0]).Header['time']
tmax = sdf.read(file_list[-1]).Header['time']
rmin = np.min(r)
rmax = np.max(r)
print(rmin, rmax)
shape = data.shape
extent = [tmin, tmax, rmin, rmax]
rmult, rsym = get_si_prefix(rmax - rmin) # y axis
tmult, tsym = get_si_prefix(tmax - tmin) # x axis
if vmin is None and vmax is None:
vmin = np.min(data)
vmax = np.max(data)
elif vmin is None:
vmin = np.min(data)
elif vmax is None:
vmax = np.max(data)
mult, sym = get_si_prefix(vmax - vmin)
fig, ax = plt.subplots()
im = ax.imshow(data, extent=extent, aspect=calculate_aspect(shape, extent), interpolation='none', cmap=cm.coolwarm, vmin=vmin, vmax=vmax, origin='lower')
ax.xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * tmult)))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * rmult)))
plt.xlabel('t $(' + tsym + 's)$')
plt.ylabel('r $(' + rsym + 'm)$')
data_label = 'Radial ' + var.name + ' Distribution $(' + sym + var.units + ')$'
# data_label = 'Radial Electric Field $(' + sym + var.units + ')$'
plt.title('Radial Density Evolution')
cbar = fig.colorbar(im, label=data_label, format=FuncFormatter(lambda x, y: x * mult))
plt.tight_layout()
plt.savefig('test.png', dpi=600, bbox_inches="tight")
def main():
species = "Electron"
path = "/scratch/lsa_flux/diiorios/2d_run/"
fnums = ["0100", "0200", "0400"]
fname = []
for n in fnums:
fname.append(path + n + ".sdf")
x_axis_num = 0
y_axis_num = 1
# z_axis_num = 2
fig, axarr = plt.subplots(len(fname), sharex=True)#, sharey=True)
fig.set_facecolor("w")
# only have a single file to plot, so we so this little hack since
# axarr does not come out in an array in this case
if not isinstance(axarr, np.ndarray):
axarr = np.array([axarr])
# axarr[0].set_title(species + " files " + str(fnums))
# axarr[0].set_title('Contribution to E Field')
limit = 8E9
for i in range(len(fname)):
sdfdata = sdf.read(fname[i])
print(sdfdata.Header['time'])
e_var_x = sdfdata.Electric_Field_Ex
e_var_y = sdfdata.Electric_Field_Ey
x_grid = e_var_x.grid_mid.data[0]
y_grid = e_var_y.grid_mid.data[1]
x_grid_cent = e_var_x.grid.data[0]
y_grid_cent = e_var_y.grid.data[1]
e_avg, dummy_e_r, dummy_e_t = __radial_average(x_grid, y_grid, e_var_x.data, e_var_y.data)
dummy_temp_grid_x, temp_data_x = Temp_Field(sdfdata,
x_axis_num,
species='Electron')
dummy_temp_grid_y, temp_data_y = Temp_Field(sdfdata,
y_axis_num,
species='Electron')
temp_avg, dummy_temp_r, dummy_temp_t = __radial_average(x_grid, y_grid,
temp_data_x,
temp_data_y)
dummy_res_mhd_grid_x, res_mhd_data_x = Resistive_MHD_Field(sdfdata,
x_axis_num)
dummy_res_mhd_grid_y, res_mhd_data_y = Resistive_MHD_Field(sdfdata,
y_axis_num)
rmhd_avg, dummy_rmhd_r, dummy_rmhd_t = __radial_average(x_grid, y_grid,
res_mhd_data_x,
res_mhd_data_y)
dummy_hall_grid_x, hall_data_x = Hall_Field(sdfdata, x_axis_num)
dummy_hall_grid_y, hall_data_y = Hall_Field(sdfdata, y_axis_num)
hall_avg, dummy_hall_r, dummy_hall_t = __radial_average(x_grid, y_grid, hall_data_x, hall_data_y)
gen_data_x = Generalized_Ohm(sdfdata,
x_axis_num,
species='Electron')
gen_data_y = Generalized_Ohm(sdfdata,
y_axis_num,
species='Electron')
gen_avg, dummy_gen_r, dummy_gen_t = __radial_average(x_grid, y_grid, gen_data_x, gen_data_y)
gen_avg2 = Generalized_Ohm_radavg(sdfdata,
species='Electron')
high_order = higher_order(sdfdata, species='Electron')
cart_high_x = cart_higher_order_x(sdfdata, species='Electron')
cart_high_y = cart_higher_order_y(sdfdata, species='Electron')
cart_high_avg, dummy_high_r, dummy_high_t = __radial_average(x_grid_cent, y_grid_cent, cart_high_x, cart_high_y)
# ideal_mhd_grid_x, ideal_mhd_data_x = Ideal_MHD_Field(sdfdata,
# x_axis_num,
# species='Electron')
# ideal_mhd_grid_y, ideal_mhd_data_y = Ideal_MHD_Field(sdfdata,
# y_axis_num,
# species='Electron')
# imhd_avg, imhd_r, imhd_t = __radial_average(x_grid, y_grid, ideal_mhd_data_x, ideal_mhd_data_y)
l1, = axarr[i].plot(#e_r,
e_avg,
'k-',
label='Simulation')
l2, = axarr[i].plot(#temp_r,
np.clip(temp_avg, -limit, limit),
'r--',
label='Pressure Tensor Gradient')
# l3, = axarr[i].plot(#rmhd_r,
# np.clip(rmhd_avg, -limit, limit),
# 'b-.',
# label='Resistive MHD')
# l4, = axarr[i].plot(#hall_r,
# np.clip(hall_avg, -limit, limit),
# 'g:',
# label='Hall Term')
# l5, = axarr[i].plot(#imhd_r,
# np.clip(imhd_avg,
# -limit, limit),
# 'm-.',
# label='Ideal MHD Term')
# l6, = axarr[i].plot(np.clip(gen_avg, -limit, limit),
# 'm-.',
# label='Generalized Ohm',
# alpha=0.2)
l7, = axarr[i].plot(np.clip(gen_avg2, -limit, limit),
'b-.',
label='Ohm Law 1st Term')
l8, = axarr[i].plot(np.clip(high_order, -limit, limit),
'g:',
label='Ohm Law 2nd Term')
# l9, = axarr[i].plot(np.clip(cart_high_avg, -limit, limit),
# 'b:',
# label='Cart Higher Order')
ls = [l1, l2, l7, l8] #l3, l4, l5]
labels = [l.get_label() for l in ls]
lgd = fig.legend(ls, labels, bbox_to_anchor=(1.05, 1.0), loc=1)
fig.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
# plt.xlim(-6.5e-6, 6.5e-6)
# plt.ylim(-limit, limit)
# xmult, xsym = get_si_prefix(np.max(e_r) - np.min(e_r))
ymult, ysym = get_si_prefix(limit - (-limit))
# axarr[0].xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
axarr[0].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
axarr[1].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
axarr[2].yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * ymult)))
axarr[0].set_ylim([-limit, limit])
axarr[1].set_ylim([-limit, limit])
axarr[2].set_ylim([-limit, limit])
xmult, xsym = get_si_prefix(dummy_e_r.max() - dummy_e_r.min())
# axarr[2].xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
# axarr[2].set_xlim([dummy_e_r.min(), dummy_e_r.max()])
plt.xlabel('r' + ' $(' + xsym + 'm)$')
axarr[1].set_ylabel('$E_{r}$ $(' + ysym + 'V/m)$')
# plt.show()
axarr[0].get_yaxis().set_tick_params(direction='in')
axarr[1].get_yaxis().set_tick_params(direction='in')
axarr[2].get_yaxis().set_tick_params(direction='in')
axarr[2].get_xaxis().set_tick_params(direction='in')
plt.savefig('ohm_rad.png', dpi=600, bbox_extra_artists=(lgd,), bbox_inches = "tight", pad_inches=0.2)
plt.close(fig)
def composite_field_plot(varname, vmin=None, vmax=None, directory='Data'):
global verbose, dpi
file_list = get_files(wkdir=directory)
file_list = clean_file_list(file_list, varname)
file_list.remove(directory + '00000.sdf')
file_list.remove(directory + '00002.sdf')
file_list.remove(directory + '00003.sdf')
file_list.remove(directory + '00004.sdf')
file_list.remove(directory + '00005.sdf')
file_list.remove(directory + '00006.sdf')
file_list.remove(directory + '00007.sdf')
file_list.remove(directory + '00008.sdf')
file_list.remove(directory + '00009.sdf')
file_list.remove(directory + '00010.sdf')
file_list.remove(directory + '00011.sdf')
file_list.remove(directory + '00012.sdf')
file_list.remove(directory + '00013.sdf')
file_list.remove(directory + '00014.sdf')
file_list.remove(directory + '00015.sdf')
file_list.remove(directory + '00016.sdf')
file_list.remove(directory + '00017.sdf')
file_list.remove(directory + '00018.sdf')
file_list.remove(directory + '00019.sdf')
file_list.remove(directory + '00020.sdf')
file_list.remove(directory + '00021.sdf')
file_list.remove(directory + '00022.sdf')
file_list.remove(directory + '00023.sdf')
file_list.remove(directory + '00024.sdf')
file_list.remove(directory + '00025.sdf')
file_list.remove(directory + '00027.sdf')
file_list.remove(directory + '00028.sdf')
file_list.remove(directory + '00029.sdf')
file_list.remove(directory + '00030.sdf')
file_list.remove(directory + '00031.sdf')
file_list.remove(directory + '00032.sdf')
file_list.remove(directory + '00033.sdf')
file_list.remove(directory + '00034.sdf')
file_list.remove(directory + '00035.sdf')
file_list.remove(directory + '00037.sdf')
file_list.remove(directory + '00038.sdf')
file_list.remove(directory + '00039.sdf')
file_list.remove(directory + '00040.sdf')
file_list.remove(directory + '00041.sdf')
file_list.remove(directory + '00042.sdf')
file_list.remove(directory + '00043.sdf')
file_list.remove(directory + '00044.sdf')
file_list.remove(directory + '00045.sdf')
file_list.remove(directory + '00047.sdf')
file_list.remove(directory + '00048.sdf')
file_list.remove(directory + '00049.sdf')
file_list.remove(directory + '00050.sdf')
file_list.remove(directory + '00051.sdf')
file_list.remove(directory + '00052.sdf')
file_list.remove(directory + '00053.sdf')
file_list.remove(directory + '00054.sdf')
file_list.remove(directory + '00055.sdf')
if verbose > 0:
print('Found {} files to plot'.format(len(file_list)))
data = []
for f in file_list:
d = sdf.read(f)
var = d.__dict__[varname]
data.append(var.data)
data = np.asarray(data)
data = data.T
tmin = sdf.read(file_list[0]).Header['time']
tmax = sdf.read(file_list[-1]).Header['time']
grid = var.grid_mid
xmin = np.min(grid.data[0])
xmax = np.max(grid.data[0])
shape = data.shape
extent = [tmin, tmax, xmax, xmin]
xmult, xsym = get_si_prefix(xmax - xmin) # y axis
tmult, tsym = get_si_prefix(tmax - tmin) # x axis
if vmin is None and vmax is None:
vmin, vmax = get_var_range_from_sdf_files(file_list, varname)
elif vmin is None:
vmin = get_var_range_from_sdf_files(file_list, varname)[0]
elif vmax is None:
vmax = get_var_range_from_sdf_files(file_list, varname)[1]
mult, sym = get_si_prefix(vmax - vmin)
fig, ax = plt.subplots()
im = ax.imshow(data,
extent=extent,
aspect=calculate_aspect(shape, extent),
interpolation='none',
cmap=cm.plasma,
vmin=vmin,
vmax=vmax)
ax.xaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * tmult)))
ax.yaxis.set_major_formatter(FuncFormatter(lambda x, y: (x * xmult)))
plt.xlabel('t $(' + tsym + 's)$')
plt.ylabel(grid.labels[0] + ' $(' + xsym + grid.units[0] + ')$')
# data_label = var.name + ' $(' + sym + var.units + ')$'
data_label = 'Argon$^{+8}$ Number Density $(' + sym + var.units + ')$'
plt.title('Electron Density Evolution')
cbar = fig.colorbar(im,
label=data_label,
format=FuncFormatter(lambda x, y: x * mult))
plt.tight_layout()
plt.savefig('electron_comp_thermal_nocoll.png',
dpi=600,
bbox_inches="tight")