def extract_report_data(xFilename, data, page_index, page_count=0):
xfield = data['x'] if 'x' in data else data[_X_FIELD]
# x, column_names, x_def, err
x_col = sdds_util.extract_sdds_column(xFilename, xfield, page_index)
if x_col['err']:
return x_col['err']
x = x_col['values']
if not _is_histogram_file(xFilename, x_col['column_names']):
# parameter plot
plots = []
filename = {
'y1': xFilename,
#TODO(pjm): y2Filename, y3Filename are not currently used. Would require rescaling x value across files.
'y2': xFilename,
'y3': xFilename,
}
for f in ('y1', 'y2', 'y3'):
if re.search(r'^none$', data[f], re.IGNORECASE) or data[f] == ' ':
continue
yfield = data[f]
y_col = sdds_util.extract_sdds_column(filename[f], yfield,
page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
plots.append({
'points': y,
'label': _field_label(yfield, y_col['column_def'][1]),
})
title = ''
if page_count > 1:
title = 'Plot {} of {}'.format(page_index + 1, page_count)
return {
'title': title,
'x_range': [min(x), max(x)],
'y_label': '',
'x_label': _field_label(xfield, x_col['column_def'][1]),
'x_points': x,
'plots': plots,
'y_range': template_common.compute_plot_color_and_range(plots),
}
yfield = data['y1'] if 'y1' in data else data['y']
y_col = sdds_util.extract_sdds_column(xFilename, yfield, page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
bins = data['histogramBins']
hist, edges = np.histogramdd([x, y], template_common.histogram_bins(bins))
return {
'x_range': [float(edges[0][0]),
float(edges[0][-1]),
len(hist)],
'y_range': [float(edges[1][0]),
float(edges[1][-1]),
len(hist[0])],
'x_label': _field_label(xfield, x_col['column_def'][1]),
'y_label': _field_label(yfield, y_col['column_def'][1]),
'title': _plot_title(xfield, yfield, page_index, page_count),
'z_matrix': hist.T.tolist(),
}
def _extract_evolution_plot(report, run_dir):
filename = str(run_dir.join(_BEAM_EVOLUTION_OUTPUT_FILENAME))
data = simulation_db.read_json(run_dir.join(template_common.INPUT_BASE_NAME))
x_col = sdds_util.extract_sdds_column(filename, _X_FIELD, 0)
if x_col['err']:
return x_col['err']
x = x_col['values']
plots = []
for f in ('y1', 'y2', 'y3'):
if report[f] == 'none':
continue
yfield = _map_field_name(report[f])
y_col = sdds_util.extract_sdds_column(filename, yfield, 0)
if y_col['err']:
return y_col['err']
plots.append({
'points': y_col['values'],
'label': '{}{}'.format(_field_label(yfield, y_col['column_def']), _field_description(yfield, data)),
})
return {
'title': '',
'x_range': [min(x), max(x)],
'y_label': '',
'x_label': _field_label(_X_FIELD, x_col['column_def']),
'x_points': x,
'plots': plots,
'y_range': template_common.compute_plot_color_and_range(plots),
}
def _extract_particle_plot(report, run_dir, page_index):
xfield = _map_field_name(report['x'])
yfield = _map_field_name(report['y'])
bins = report['histogramBins']
filename = _ion_files(run_dir)[page_index]
data = simulation_db.read_json(run_dir.join(template_common.INPUT_BASE_NAME))
settings = data.models.simulationSettings
time = settings.time / settings.step_number * settings.save_particle_interval * page_index
if time > settings.time:
time = settings.time
x_col = sdds_util.extract_sdds_column(filename, xfield, 0)
if x_col['err']:
return x_col['err']
x = x_col['values']
y_col = sdds_util.extract_sdds_column(filename, yfield, 0)
if y_col['err']:
return y_col['err']
y = y_col['values']
particle_animation = data.models.particleAnimation
range = None
if report['plotRangeType'] == 'fixed':
range = [_plot_range(report, 'horizontal'), _plot_range(report, 'vertical')]
elif report['plotRangeType'] == 'fit' and 'fieldRange' in particle_animation:
range = [particle_animation.fieldRange[xfield], particle_animation.fieldRange[yfield]]
hist, edges = np.histogramdd([x, y], template_common.histogram_bins(bins), range=range)
return {
'x_range': [float(edges[0][0]), float(edges[0][-1]), len(hist)],
'y_range': [float(edges[1][0]), float(edges[1][-1]), len(hist[0])],
'x_label': _field_label(xfield, x_col['column_def']),
'y_label': _field_label(yfield, y_col['column_def']),
'title': 'Ions at time {:.2f} [s]'.format(time),
'z_matrix': hist.T.tolist(),
}
def _extract_particle_plot(report, run_dir, page_index):
xfield = _map_field_name(report['x'])
yfield = _map_field_name(report['y'])
filename = _ion_files(run_dir)[page_index]
data = simulation_db.read_json(run_dir.join(template_common.INPUT_BASE_NAME))
settings = data.models.simulationSettings
time = settings.time / settings.step_number * settings.save_particle_interval * page_index
if time > settings.time:
time = settings.time
x_col = sdds_util.extract_sdds_column(filename, xfield, 0)
if x_col['err']:
return x_col['err']
x = x_col['values']
y_col = sdds_util.extract_sdds_column(filename, yfield, 0)
if y_col['err']:
return y_col['err']
y = y_col['values']
model = data.models.particleAnimation
model.update(report)
model['x'] = xfield
model['y'] = yfield
return template_common.heatmap([x, y], model, {
'x_label': _field_label(xfield, x_col['column_def']),
'y_label': _field_label(yfield, y_col['column_def']),
'title': 'Ions at time {:.2f} [s]'.format(time),
})
def sim_frame_particleAnimation(frame_args):
page_index = frame_args.frameIndex
xfield = _map_field_name(frame_args.x)
yfield = _map_field_name(frame_args.y)
filename = _ion_files(frame_args.run_dir)[page_index]
data = frame_args.sim_in
settings = data.models.simulationSettings
time = settings.time / settings.step_number * settings.save_particle_interval * page_index
if time > settings.time:
time = settings.time
x_col = sdds_util.extract_sdds_column(filename, xfield, 0)
if x_col['err']:
return x_col['err']
x = x_col['values']
y_col = sdds_util.extract_sdds_column(filename, yfield, 0)
if y_col['err']:
return y_col['err']
y = y_col['values']
model = data.models.particleAnimation
model.update(frame_args)
model['x'] = xfield
model['y'] = yfield
return template_common.heatmap(
[x, y], model, {
'x_label': _field_label(xfield, x_col['column_def']),
'y_label': _field_label(yfield, y_col['column_def']),
'title': 'Ions at time {:.2f} [s]'.format(time),
})
def sim_frame_beamEvolutionAnimation(frame_args):
filename = str(frame_args.run_dir.join(_BEAM_EVOLUTION_OUTPUT_FILENAME))
x_col = sdds_util.extract_sdds_column(filename, _X_FIELD, 0)
if x_col['err']:
return x_col['err']
x = x_col['values']
plots = []
for f in ('y1', 'y2', 'y3'):
if frame_args[f] == 'none':
continue
yfield = _map_field_name(frame_args[f])
y_col = sdds_util.extract_sdds_column(filename, yfield, 0)
if y_col['err']:
return y_col['err']
plots.append({
'points':
y_col['values'],
'label':
'{}{}'.format(
_field_label(yfield, y_col['column_def']),
_field_description(yfield, frame_args.sim_in),
),
})
return {
'title': '',
'x_range': [min(x), max(x)],
'y_label': '',
'x_label': _field_label(_X_FIELD, x_col['column_def']),
'x_points': x,
'plots': plots,
'y_range': template_common.compute_plot_color_and_range(plots),
}
def extract_report_data(xFilename, data, page_index, page_count=0):
xfield = data['x'] if 'x' in data else data[_X_FIELD]
# x, column_names, x_def, err
x_col = sdds_util.extract_sdds_column(xFilename, xfield, page_index)
if x_col['err']:
return x_col['err']
x = x_col['values']
if not _is_histogram_file(xFilename, x_col['column_names']):
# parameter plot
plots = []
filename = {
'y1': xFilename,
#TODO(pjm): y2Filename, y3Filename are not currently used. Would require rescaling x value across files.
'y2': xFilename,
'y3': xFilename,
}
for f in ('y1', 'y2', 'y3'):
if re.search(r'^none$', data[f], re.IGNORECASE) or data[f] == ' ':
continue
yfield = data[f]
y_col = sdds_util.extract_sdds_column(filename[f], yfield, page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
plots.append({
'points': y,
'label': _field_label(yfield, y_col['column_def'][1]),
})
title = ''
if page_count > 1:
title = 'Plot {} of {}'.format(page_index + 1, page_count)
return {
'title': title,
'x_range': [min(x), max(x)],
'y_label': '',
'x_label': _field_label(xfield, x_col['column_def'][1]),
'x_points': x,
'plots': plots,
'y_range': template_common.compute_plot_color_and_range(plots),
}
yfield = data['y1'] if 'y1' in data else data['y']
y_col = sdds_util.extract_sdds_column(xFilename, yfield, page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
bins = data['histogramBins']
hist, edges = np.histogramdd([x, y], template_common.histogram_bins(bins))
return {
'x_range': [float(edges[0][0]), float(edges[0][-1]), len(hist)],
'y_range': [float(edges[1][0]), float(edges[1][-1]), len(hist[0])],
'x_label': _field_label(xfield, x_col['column_def'][1]),
'y_label': _field_label(yfield, y_col['column_def'][1]),
'title': _plot_title(xfield, yfield, page_index, page_count),
'z_matrix': hist.T.tolist(),
}
def _extract_report_data(xFilename, frame_args, page_count=0):
page_index = frame_args.frameIndex
xfield = frame_args.x if 'x' in frame_args else frame_args[_X_FIELD]
# x, column_names, x_def, err
x_col = sdds_util.extract_sdds_column(xFilename, xfield, page_index)
if x_col['err']:
return x_col['err']
x = x_col['values']
if not _is_histogram_file(xFilename, x_col['column_names']):
# parameter plot
plots = []
filename = PKDict(
y1=xFilename,
#TODO(pjm): y2Filename, y3Filename are not currently used. Would require rescaling x value across files.
y2=xFilename,
y3=xFilename,
)
for f in ('y1', 'y2', 'y3'):
if re.search(r'^none$', frame_args[f],
re.IGNORECASE) or frame_args[f] == ' ':
continue
yfield = frame_args[f]
y_col = sdds_util.extract_sdds_column(filename[f], yfield,
page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
plots.append(
PKDict(
field=yfield,
points=y,
label=_field_label(yfield, y_col['column_def'][1]),
))
title = ''
if page_count > 1:
title = 'Plot {} of {}'.format(page_index + 1, page_count)
return template_common.parameter_plot(
x, plots, frame_args,
PKDict(
title=title,
y_label='',
x_label=_field_label(xfield, x_col['column_def'][1]),
))
yfield = frame_args['y1'] if 'y1' in frame_args else frame_args['y']
y_col = sdds_util.extract_sdds_column(xFilename, yfield, page_index)
if y_col['err']:
return y_col['err']
return template_common.heatmap(
[x, y_col['values']], frame_args,
PKDict(
x_label=_field_label(xfield, x_col['column_def'][1]),
y_label=_field_label(yfield, y_col['column_def'][1]),
title=_plot_title(xfield, yfield, page_index, page_count),
))
def extract_report_data(xFilename, data, page_index, page_count=0):
xfield = data['x'] if 'x' in data else data[_X_FIELD]
# x, column_names, x_def, err
x_col = sdds_util.extract_sdds_column(xFilename, xfield, page_index)
if x_col['err']:
return x_col['err']
x = x_col['values']
if not _is_histogram_file(xFilename, x_col['column_names']):
# parameter plot
plots = []
filename = {
'y1': xFilename,
#TODO(pjm): y2Filename, y3Filename are not currently used. Would require rescaling x value across files.
'y2': xFilename,
'y3': xFilename,
}
for f in ('y1', 'y2', 'y3'):
if re.search(r'^none$', data[f], re.IGNORECASE) or data[f] == ' ':
continue
yfield = data[f]
y_col = sdds_util.extract_sdds_column(filename[f], yfield,
page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
plots.append({
'field': yfield,
'points': y,
'label': _field_label(yfield, y_col['column_def'][1]),
})
title = ''
if page_count > 1:
title = 'Plot {} of {}'.format(page_index + 1, page_count)
return template_common.parameter_plot(
x, plots, data, {
'title': title,
'y_label': '',
'x_label': _field_label(xfield, x_col['column_def'][1]),
})
yfield = data['y1'] if 'y1' in data else data['y']
y_col = sdds_util.extract_sdds_column(xFilename, yfield, page_index)
if y_col['err']:
return y_col['err']
return template_common.heatmap(
[x, y_col['values']], data, {
'x_label': _field_label(xfield, x_col['column_def'][1]),
'y_label': _field_label(yfield, y_col['column_def'][1]),
'title': _plot_title(xfield, yfield, page_index, page_count),
})
def sim_frame_plot2Animation(frame_args):
x = None
plots = []
for f in ('x', 'y1', 'y2', 'y3'):
name = frame_args[f].replace(' ', '_')
if name == 'none':
continue
col = sdds_util.extract_sdds_column(
str(frame_args.run_dir.join(_OPAL_SDDS_FILE)), name, 0)
if col.err:
return col.err
field = PKDict(
points=col['values'],
label=frame_args[f],
)
_field_units(col.column_def[1], field)
if f == 'x':
x = field
else:
plots.append(field)
return template_common.parameter_plot(x.points, plots, {}, {
'title': '',
'y_label': '',
'x_label': x.label,
})
def sim_frame_plot2Animation(frame_args):
from sirepo.template import sdds_util
x = None
plots = []
for f in ('x', 'y1', 'y2', 'y3'):
name = frame_args[f].replace(' ', '_')
if name == 'none':
continue
col = sdds_util.extract_sdds_column(str(frame_args.run_dir.join(_OPAL_SDDS_FILE)), name, 0)
if col.err:
return col.err
field = PKDict(
points=col['values'],
label=frame_args[f],
)
_field_units(col.column_def[1], field)
if f == 'x':
x = field
else:
plots.append(field)
# independent reads of file may produce more columns, trim to match x length
for p in plots:
if len(x.points) < len(p.points):
p.points = p.points[:len(x.points)]
return template_common.parameter_plot(x.points, plots, {}, {
'title': '',
'y_label': '',
'x_label': x.label,
})
def _sdds_report(frame_args, filename, x_field):
xfield = _map_field_name(x_field)
x_col = sdds_util.extract_sdds_column(filename, xfield, 0)
if x_col.err:
return x_col.err
x = x_col['values']
if 'fieldRange' in frame_args.sim_in.models.particleAnimation:
frame_args.fieldRange = frame_args.sim_in.models.particleAnimation.fieldRange
plots = []
for f in ('y1', 'y2', 'y3'):
if f not in frame_args or frame_args[f] == 'none':
continue
yfield = _map_field_name(frame_args[f])
y_col = sdds_util.extract_sdds_column(filename, yfield, 0)
if y_col.err:
return y_col.err
y = y_col['values']
label_prefix = ''
#TODO(pjm): the forceScale feature makes the code unmanageable
# it might be simpler if this was done on the client
if 'forceScale' in frame_args \
and yfield in ('f_x', 'f_long') \
and frame_args.forceScale == 'negative':
y = [-v for v in y]
label_prefix = '-'
if 'fieldRange' in frame_args:
r = frame_args.fieldRange[frame_args[f]]
frame_args.fieldRange[frame_args[f]] = [-r[1], -r[0]]
plots.append(
PKDict(
field=frame_args[f],
points=y,
label='{}{}{}'.format(
label_prefix,
_field_label(yfield, y_col.column_def),
_field_description(yfield, frame_args.sim_in),
),
))
if xfield == 'V_trans':
x = _resort_vtrans(x, plots)
frame_args.x = x_field
return template_common.parameter_plot(
x, plots, frame_args,
PKDict(
y_label='',
x_label=_field_label(xfield, x_col.column_def),
))
def _beam_evolution_status(run_dir, settings, has_rates):
try:
filename = str(run_dir.join(_BEAM_EVOLUTION_OUTPUT_FILENAME))
col = sdds_util.extract_sdds_column(filename, 't', 0)
t_max = max(col['values'])
if t_max and settings.time > 0:
return {
# use current time as frameCount for uniqueness until simulation is completed
'frameCount': int(float(os.path.getmtime(filename))),
'percentComplete': 100.0 * t_max / settings.time,
'hasRates': has_rates,
}
except:
pass
return {
'frameCount': 0,
'percentComplete': 0,
}
def extract_report_data(xFilename, yFilename, data, page_index):
xfield = data['x'] if 'x' in data else data[_X_FIELD]
# x, column_names, x_def, err
x_col = sdds_util.extract_sdds_column(xFilename, xfield, page_index)
if x_col['err']:
return x_col['err']
x = x_col['values']
if 'y1' in data:
# parameter plot
y_range = None
plots = []
for f in ('y1', 'y2', 'y3'):
if data[f] == 'none':
continue
yfield = data[f]
y_col = sdds_util.extract_sdds_column(yFilename, yfield,
page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
if y_range:
y_range[0] = min(y_range[0], min(y))
y_range[1] = max(y_range[1], max(y))
else:
y_range = [min(y), max(y)]
plots.append({
'points': y,
'label': _field_label(yfield, y_col['column_def'][1]),
#TODO(pjm): refactor with template_common.compute_plot_color_and_range()
'color': _PLOT_LINE_COLOR[f],
})
return {
'title': '',
'x_range': [min(x), max(x)],
'y_label': '',
'x_label': _field_label(_X_FIELD, x_col['column_def'][1]),
'x_points': x,
'plots': plots,
'y_range': y_range,
}
yfield = data['y']
y_col = sdds_util.extract_sdds_column(yFilename, yfield, page_index)
if y_col['err']:
return y_col['err']
y = y_col['values']
if _is_2d_plot(x_col['column_names']):
# 2d plot
return {
'title': _plot_title(xfield, yfield, page_index),
'x_range': [np.min(x), np.max(x)],
'x_label': _field_label(xfield, x_col['column_def'][1]),
'y_label': _field_label(yfield, y_col['column_def'][1]),
'points': y,
'x_points': x,
}
bins = data['histogramBins']
hist, edges = np.histogramdd([x, y], template_common.histogram_bins(bins))
return {
'x_range': [float(edges[0][0]),
float(edges[0][-1]),
len(hist)],
'y_range': [float(edges[1][0]),
float(edges[1][-1]),
len(hist[0])],
'x_label': _field_label(xfield, x_col['column_def'][1]),
'y_label': _field_label(yfield, y_col['column_def'][1]),
'title': _plot_title(xfield, yfield, page_index),
'z_matrix': hist.T.tolist(),
}
