def plot_arai(self, component='m', show_std=True, out='show', plt_opt={}):
colors = get_colors()
components = {'x': 1, 'y': 2, 'z': 3, 'm': 4}
if not 'color' in plt_opt:
plt_opt.update({'color': colors[0]})
idx = components[component]
th_mean = self.get_data_mean(step='th')
ptrm_mean = self.get_data_mean(step='ptrm')
th_max = self.get_data_max(step='th')
ptrm_max = self.get_data_max(step='ptrm')
th_stdev = self.get_data_stdev(step='th')
ptrm_stdev = self.get_data_stdev(step='ptrm')
plt.plot(ptrm_mean[:, idx], th_mean[:, idx], '.-', **plt_opt)
if show_std:
plt.fill_between(ptrm_mean[:, idx], th_mean[:, idx] + th_stdev[:, idx], th_mean[:, idx] - th_stdev[:, idx],
color=colors[0], alpha=0.1, antialiased=True)
# plt.fill_betweenx(th_mean[:,idx]-th_stdev[:,idx], ptrm_mean[:,idx], ptrm_mean[:,idx]-ptrm_stdev[:,idx],
# where= th_stdev[:,idx]-th_stdev[:,idx] < th_stdev[:,idx],
# color=colors[1], alpha = 0.1, antialiased=True)
# plt.fill_betweenx(th_mean[:,idx]+th_stdev[:,idx], ptrm_mean[:,idx], ptrm_mean[:,idx]+ptrm_stdev[:,idx],
# where= th_stdev[:,idx]+th_stdev[:,idx] > th_stdev[:,idx],
# color=colors[1], alpha = 0.1, antialiased=True)
if out == 'show':
plt.xlabel(r'pTRM gained')
plt.ylabel(r'NRM remaining')
plt.show()
if out == 'rtn':
return
def plot_dunlop(self, component='m', show_std=True, out='show', plt_opt=None):
if not plt_opt: plt_opt = {}
colors = get_colors()
components = {'x': 1, 'y': 2, 'z': 3, 'm': 4}
idx = components[component]
th_mean = self.get_data_mean(step='th')
ptrm_mean = self.get_data_mean(step='ptrm')
sum_mean = np.c_[th_mean[:, 0], th_mean[:, 1:] + ptrm_mean[:, 1:]]
th_max = self.get_data_max(step='th')
ptrm_max = self.get_data_max(step='ptrm')
sum_max = self.get_data_max(step='sum')
th_stdev = self.get_data_stdev(step='th')
ptrm_stdev = self.get_data_stdev(step='ptrm')
sum_stdev = np.c_[th_stdev[:, 0], th_stdev[:, 1:] + ptrm_stdev[:, 1:]]
plt.plot(th_mean[:, 0], th_mean[:, idx], '.-', color=colors[1], **plt_opt)
plt.plot(ptrm_mean[:, 0], ptrm_mean[:, idx], '.-', color=colors[2], **plt_opt)
plt.plot(sum_mean[:, 0], sum_mean[:, idx], '.-', color=colors[0], **plt_opt)
if show_std:
plt.fill_between(th_mean[:, 0], th_mean[:, idx] - th_stdev[:, idx], th_mean[:, idx] + th_stdev[:, idx],
color=colors[1], alpha=0.1)
plt.fill_between(ptrm_mean[:, 0], ptrm_mean[:, idx] - ptrm_stdev[:, idx],
ptrm_mean[:, idx] + ptrm_stdev[:, idx], color=colors[2], alpha=0.1)
plt.fill_between(sum_mean[:, 0], sum_mean[:, idx] - sum_stdev[:, idx], sum_mean[:, idx] + sum_stdev[:, idx],
color=colors[0], alpha=0.1)
if out == 'show':
plt.xlabel(r'Temperature [$^\circ C$]')
plt.ylabel(r'Normalized Magnetic Moment')
plt.show()
if out == 'rtn':
return
def __init__(
self, sample_list, norm=None, log=None, plot="show", folder=None, name="output.pdf", plt_opt={}, **options
):
self.colors = helper.get_colors()
self.plot_marker = options.get("marker", True)
self.markers = helper.get_marker()
self.lines = ["-", "--", ":", "-."]
matplotlib.rcParams.update({"font.size": 10})
params = {
"backend": "ps",
"text.latex.preamble": [r"\usepackage{upgreek}", r"\usepackage[nice]{units}"],
"axes.labelsize": 12,
"text.fontsize": 12,
"legend.fontsize": 8,
"xtick.labelsize": 10,
"ytick.labelsize": 10,
# 'text.usetex': True,
"axes.unicode_minus": True,
"axes.color_cycle": self.colors,
}
plt.rcParams.update(params)
self.x_label = None
self.y_label = None
self.plot = plot
if not log:
self.log = logging.getLogger("RockPy.PLOTTING")
else:
self.log = logging.getLogger(log)
if type(sample_list) is not list:
self.log.debug("CONVERTING Sample Instance to Samples List")
sample_list = [sample_list]
self.name = name
if folder is None:
from os.path import expanduser
folder = expanduser("~") + "/Desktop/"
self.folder = folder
self.norm = norm
self.samples = [i for i in sample_list]
self.sample_list = self.samples
self.fig1 = options.get("fig", plt.figure(figsize=(8, 6), dpi=100))
self.ax = plt.subplot2grid((1, 1), (0, 0), colspan=1, rowspan=1)
self.plot_data = []
self.ax.xaxis.major.formatter._useMathText = True
self.ax.yaxis.major.formatter._useMathText = True
self.ax.ticklabel_format(style="sci", scilimits=(1, 4), axis="both")
# plt.rc('axes', color_cycle=['k', 'm', 'y', 'c'])
plt.rc("axes", color_cycle=self.colors)