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import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mcstasscript.helper.plot_helper import _fmt
from mcstasscript.helper.plot_helper import _find_min_max_I
from mcstasscript.helper.plot_helper import _plot_fig_ax
from mcstasscript.helper.plot_helper import _handle_kwargs
def make_plot(data_list, **kwargs):
"""
make_plot plots contents of McStasData objects given in list
Here a new figure is used for each dataset
Plotting is controlled through options assosciated with the
McStasData objects. If a list is given, the plots appear in one
subplot.
"""
data_list = _handle_kwargs(data_list, **kwargs)
if "figsize" in kwargs:
figsize = kwargs["figsize"]
if isinstance(figsize, list):
figsize = (figsize[0], figsize[1])
else:
figsize = (13, 7)
for data in data_list:
fig, ax0 = plt.subplots(figsize=figsize, tight_layout=True)
_plot_fig_ax(data, fig, ax0, **kwargs)
if "filename" in kwargs:
fig.tight_layout()
fig.savefig(kwargs["filename"])
else:
plt.show()
def make_sub_plot(data_list, **kwargs):
"""
make_sub_plot plots contents of McStasData objects given in list
It is fit into one big figure, each data set as a subplot.
Plotting is controlled through options assosciated with the
McStasData objects. If a list is given, the plots appear in one
subplot.
"""
data_list = _handle_kwargs(data_list, **kwargs)
number_of_plots = len(data_list)
if number_of_plots == 0:
print("No data to plot")
return
# Find reasonable grid size for the number of plots
special_cases = {
1: (1, 1),
4: (2, 2),
}
if number_of_plots in special_cases:
dim1 = special_cases[number_of_plots][0]
dim2 = special_cases[number_of_plots][0]
else:
if number_of_plots < 3:
dim2 = number_of_plots
dim1 = 1
else:
dim2 = 3
dim1 = math.ceil(number_of_plots / dim2)
if "figsize" in kwargs:
figsize = kwargs["figsize"]
if isinstance(figsize, list):
figsize = (figsize[0], figsize[1])
else:
# Adjust figure size after number of plots
figsize = (1 + dim2*4, 0.5 + 3.0*dim1)
if dim1 == 1 and dim2 == 1:
# Single plots can be a bit larger
figsize = (7, 5)
fig, axs = plt.subplots(dim1, dim2, figsize=figsize, tight_layout=True)
axs = np.array(axs)
ax = axs.reshape(-1)
for data, ax0 in zip(data_list, ax):
_plot_fig_ax(data, fig, ax0, **kwargs)
fig.tight_layout()
if "filename" in kwargs:
fig.tight_layout()
fig.savefig(kwargs["filename"])
plt.close(fig)
else:
plt.show()
def make_animation(data_list, **kwargs):
"""
Creates an animation from list of McStasData objects
Parameters
----------
data_list : list of McStasData
List of McStasData objects for animation
Keyword arguments
-----------------
filename : str
Filename for saving the gif
fps : float
Number of frames per second
"""
data_list = _handle_kwargs(data_list, **kwargs)
if "figsize" in kwargs:
figsize = kwargs["figsize"]
if isinstance(figsize, list):
figsize = (figsize[0], figsize[1])
else:
figsize = (13, 7)
if "fps" in kwargs:
period_in_ms = 1000 / kwargs["fps"]
else:
period_in_ms = 200
# find limits for entire dataset
maximum_values = []
minimum_values = []
is_1D = False
is_2D = False
for data in data_list:
if isinstance(data.metadata.dimension, int):
is_1D = True
elif len(data.metadata.dimension) == 2:
is_2D = True
min_value, max_value = _find_min_max_I(data)
# When data empty, min and max value is 0, skip
if not (min_value == 0 and max_value == 0):
minimum_values.append(min_value)
maximum_values.append(max_value)
if is_1D and is_2D:
raise ValueError(
"Both 1D and 2D data in animation, only one allowed.")
if len(minimum_values) == 0:
raise ValueError(
"No data found for animation!")
maximum_value = np.array(maximum_values).max()
minimum_value = np.array(minimum_values).min()
if "orders_of_mag" in kwargs:
orders_of_mag = kwargs["orders_of_mag"]
mag_diff = np.log10(maximum_value) - np.log10(minimum_value)
if mag_diff > orders_of_mag:
minimum_value_log10 = np.log10(maximum_value) - orders_of_mag
minimum_value = 10**(minimum_value_log10)
kwargs["fixed_minimum_value"] = minimum_value
kwargs["fixed_maximum_value"] = maximum_value
fig, ax0 = plt.subplots(figsize=figsize, tight_layout=True)
im = _plot_fig_ax(data_list[0], fig, ax0, **kwargs)
def animate_2D(index):
data = data_list[index]
intensity = data.Intensity
im.set_array(intensity.ravel())
return im,
anim = animation.FuncAnimation(fig, animate_2D,
frames=len(data_list),
interval=period_in_ms,
blit=False, repeat=True)
plt.show()
# The animation doesn't play unless it is saved. Bug.
if "filename" in kwargs:
filename = kwargs["filename"]
if not filename.endswith(".gif"):
filename = filename + ".gif"
# check if imagemagick available?
print("Saving animation with filename : \"" + filename + "\"")
anim.save(filename, writer="imagemagick")
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