def _create_plot(i, name, data, counter_two, display_plot=True):
# Step the color on all subplots no just on plots
# within the same axis/subplot
# this is to match the qcodes-pyqtplot behaviour.
title = "{} #{:03d}".format(CURRENT_EXPERIMENT["sample_name"],
data.location_provider.counter)
rasterized_note = " rasterized plot full data available in datafile"
color = 'C' + str(counter_two)
counter_two += 1
plot = MatPlot()
if issubclass(
i.__class__,
MultiChannelInstrumentParameter) or i._instrument is None:
inst_meas_name = name
else:
inst_meas_name = "{}_{}".format(i._instrument.name, name)
inst_meas_data = getattr(data, inst_meas_name)
try:
inst_meas_data = getattr(data, inst_meas_name)
except AttributeError:
inst_meas_name = "{}{}_0_0".format(i._instrument.name, name)
inst_meas_data = getattr(data, inst_meas_name)
inst_meta_data = __get_plot_type(inst_meas_data, plot)
if 'z' in inst_meta_data:
xlen, ylen = inst_meta_data['z'].shape
rasterized = xlen * ylen > 5000
po = plot.add(inst_meas_data, rasterized=rasterized)
auto_color_scale_from_config(po.colorbar, auto_color_scale,
inst_meta_data['z'],
cutoff_percentile)
else:
rasterized = False
plot.add(inst_meas_data, color=color)
plot.subplots[0].grid()
if rasterized:
plot.subplots[0].set_title(title + rasterized_note)
else:
plot.subplots[0].set_title(title)
title_list = plot.get_default_title().split(sep)
title_list.insert(-1, CURRENT_EXPERIMENT['pdf_subfolder'])
title = sep.join(title_list)
plot.rescale_axis()
plot.tight_layout()
plot.save("{}_{:03d}.pdf".format(title, counter_two))
if display_plot:
plot.fig.canvas.draw()
plt.show()
else:
plt.close(plot.fig)
def plot_dataset(dataset: DataSet, scanjob, save=True) -> None:
""" Plot a dataset to matplotlib figure window
Args:
dataset: DataSet to be plotted
scanjob: scanjob of the measurement
save: Select if you want to save the plots
"""
parameter_names = [
name for name in dataset.arrays.keys()
if not dataset.arrays[name].is_setpoint
]
default_array = dataset.default_parameter_array()
# Path for saving
base_loc = dataset.default_io.base_location
folder = '\\' + dataset.location + '\\'
label = str(scanjob.get('dataset_label'))
path = base_loc + folder + label
# 2D plots
if len(default_array.shape) >= 2:
for idx, parameter_name in enumerate(parameter_names):
plot_handle = MatPlot(dataset.arrays[parameter_name], num=idx)
plot_handle.rescale_axis()
if save == True:
plt.savefig(path + str(idx) + '.png')
# 1D plots
else:
for idx, parameter_name in enumerate(parameter_names):
plot_handle = MatPlot(dataset.arrays[parameter_name], num=idx)
plot_handle.rescale_axis()
if save == True:
plt.savefig(path + str(idx) + '.png')