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Copy pathAnalyse_DMI.py
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Analyse_DMI.py
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import os
import numpy as np
import pandas as pd
import random
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
import matplotlib.colors as pltc
import re
import seaborn as sns
from bokeh.models import Range1d, FixedTicker, Label, LinearAxis, Legend, CategoricalAxis,ColumnDataSource
from latex_label import LatexLabel
from bokeh.plotting import figure, output_file, show, save
#from bokeh.io import show
from bokeh.models import HoverTool, LabelSet
from bokeh.util.compiler import TypeScript
from bokeh import palettes
from IPython.display import display, Latex
#handle_color = '#7D007D'
# version 0.3.0
chars = {"DW_field_creep":'o',
"DW_field_flow":'8',
"DW_current":'h',
"Domain_pattern":"v",
"Stripe_annihilation":"<",
"Nucleation": ">",
"BLS":'D',
'PSWS':'d',
'TR_MOKE' : "X",
'MASW' : "x",
"Spin_orbit_torque": 's'}
chars_bokeh = {"DW_field_creep":'circle',
"DW_field_flow":'circle_x',
"DW_current":'hex',
"Domain_pattern":"inverted_triangle",
"Stripe_annihilation":"square_cross",
"Nucleation": "square_dot",
"BLS":'diamond',
'PSWS':'diamond_cross',
'TR_MOKE' : "star",
'MASW' : "star_dot",
"Spin_orbit_torque": 'triangle_pin',
}
hatch_patterns = {"DW field creep":'/',
"DW field flow":'\\',
"DW current":'-',
"Domain pattern":"x",
"Stripe annihilation":"!",
"Nucleation": "dot",
"Stray field": '"',
"BLS":'@',
'PSWS':'o',
'TR MOKE' : "v",
'MASW' : ">",
"Spin orbit torque": '*',
}
redColors = {"DW field creep":'#8B0000', #DarkRed
"DW field flow":'#B22222', #FireBrick
"DW current":'#FF0000', #Red
"Domain pattern":"#DC143C", #Crimson
"Stripe annihilation":"#CD5C5C", #IndianRed
"Nucleation": "#F08080", #LightCoral
"Stray field": '#E9967A', #DarkSalmon
"BLS":'#8B008B', #DarkMagenta
'PSWS':'#800080', #Purple
'TR MOKE' : "#EE82EE", # Violet
'MASW' : "#FA8072", # Salmon
"Spin orbit torque": '#FFA07A', # LightSalmon
}
greenColors = {"DW field creep":'#006400', #DarkGreen
"DW field flow":'#2E8B57', #SeaGreen
"DW current":'#FF0000', #Green
"Domain pattern":"#3CB371", #MediumSeaGreen
"Stripe annihilation":"#6B8E23", #OliveDrab
"Nucleation": "#32CD32", #LimeGreen
"Stray field": '#00FF00', #Lime
"BLS":'#556B2F', #DarkOliveGreen
'PSWS':'#008080', #Teal
'TR MOKE' : "#EE82EE", # Violet
'MASW' : "#FA8072", # Salmon
"Spin orbit torque": '#FFA07A', # LightSalmon
}
methods_with_sign = ["DW field creep", "DW field flow",
"DW current", "Nucleation", "BLS", 'PSWS']
mm = list(greenColors.keys())
choice1 = ['rocket','mako']
choice2 = ['flare', 'crest']
choice3 = ['Blues', 'YlOrBr']
ch = choice3
# Method 1: Uniform colors (aka blues, oranges)
red_palette = sns.color_palette(ch[0], 3+len(methods_with_sign))[3:]
green_palette = sns.color_palette(ch[1], 3+len(methods_with_sign))[3:]
red_palette = red_palette[::-1]
green_palette = green_palette[::-1]
# Method 2: two colors (green+blu, orange+brown)
red_palette = red_palette[1:-1] + ['seagreen', '#96c5ab']
green_palette = green_palette[1:-1] + ['crimson', '#ed899d']
#['mediumvioletred', 'pink']
greenColors = {}
redColors = {}
for method, red, green in zip(methods_with_sign, red_palette, green_palette):
redColors[method] = pltc.to_hex(red)
greenColors[method] = pltc.to_hex(green)
# grayColors = {"DW field creep":'#808080',
# "Domain pattern": '#696969',
# "Stripe annihilation": '#A9A9A9',
# "Nucleation":'#C0C0C0',
# "Spin torque": '#D3D3D3',
# "BLS": '#DCDCDC'}
methods_no_sign = ["DW field creep",
"DW field flow",
"Domain pattern",
"Stripe annihilation",
"Nucleation",
"Spin orbit torque",
"BLS"]
gray_palette = sns.light_palette('gray', n_colors=len(methods_no_sign), reverse=True)
grayColors = {}
for method, gray in zip(methods_no_sign, gray_palette):
grayColors[method] = pltc.to_hex(gray)
fillstyle = {"DW_field_creep":['left', 'o'],
"DW_field_flow":['right', 'o'],
"DW_current":['bottom', 'o'],
"Domain_pattern": ["top", 's'],
"Stripe_annihilation": ["right", 's'],
"Nucleation": ["left", 's'],
#"BLS":['full','p'],
"BLS":['full','^'],
"PSWS":['full','v'],
'TR_MOKE' : ['full', "X"],
'MASW' : ['full', "x"],
"Spin_orbit_torque": ['full','>'],
}
colors = {1: "red", -1: "blue", 0: "black"}
marker_style = dict(linestyle='none', markerfacecoloralt='tab:grey')
#gray_methods = ['Domain_pattern', 'Stripe_annihilation', 'Nucleation', 'Spin_torque']
def get_string(s):
#s = str(s)
if s == int(s):
return str(int(s))
elif s*10 == int(s*10):
return "%.1f" % s
elif s*100 == int(s*100):
return "%.2f" % s
elif len(str(s)) > 4:
s = str(s)[:5]
while True:
if s[-1] == "0":
s = s[:-1]
else:
return s
TS_CODE = """
import * as p from "core/properties"
import {Label, LabelView} from "models/annotations/label"
declare const katex: any
export class LatexLabelView extends LabelView {
model: LatexLabel
render(): void {
//--- Start of copied section from ``Label.render`` implementation
// Here because AngleSpec does units tranform and label doesn't support specs
let angle: number
switch (this.model.angle_units) {
case "rad": {
angle = -this.model.angle
break
}
case "deg": {
angle = (-this.model.angle * Math.PI) / 180.0
break
}
default:
throw new Error("unreachable code")
}
const panel = this.layout ?? this.plot_view.layout.center_panel
let sx = this.model.x_units == "data" ? this.coordinates.x_scale.compute(this.model.x) : panel.xview.compute(this.model.x)
let sy = this.model.y_units == "data" ? this.coordinates.y_scale.compute(this.model.y) : panel.yview.compute(this.model.y)
sx += this.model.x_offset
sy -= this.model.y_offset
//--- End of copied section from ``Label.render`` implementation
// Must render as superpositioned div (not on canvas) so that KaTex
// css can properly style the text
this._css_text(this.layer.ctx, "", sx, sy, angle)
// ``katex`` is loaded into the global window at runtime
// katex.renderToString returns a html ``span`` element
katex.render(this.model.text, this.el, {displayMode: true})
}
}
export namespace LatexLabel {
export type Attrs = p.AttrsOf<Props>
export type Props = Label.Props
}
export interface LatexLabel extends LatexLabel.Attrs {}
export class LatexLabel extends Label {
properties: LatexLabel.Props
__view_type__: LatexLabelView
constructor(attrs?: Partial<LatexLabel.Attrs>) {
super(attrs)
}
static {
this.prototype.default_view = LatexLabelView
}
}
"""
class LatexLabel(Label):
"""A subclass of the Bokeh built-in `Label` that supports rendering
LaTex using the KaTex typesetting library.
Only the render method of LabelView is overloaded to perform the
text -> latex (via katex) conversion. Note: ``render_mode="canvas``
isn't supported and certain DOM manipulation happens in the Label
superclass implementation that requires explicitly setting
`render_mode='css'`).
"""
__javascript__ = ["https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.6.0/katex.min.js"]
__css__ = ["https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.6.0/katex.min.css"]
__implementation__ = TypeScript(TS_CODE)
class DMI:
def __init__(self, methods, filename="DMI.xlsx", papers="dmi_paper.xlsx", is_tofix=True):
self.figs = []
self.xl = pd.ExcelFile(filename, engine='openpyxl')
self.sheetnames = [sname for sname in methods if sname in self.xl.sheet_names]
self.is_tofix = is_tofix
self.fmats = []
self.k_factor = {"Ds": "p", "D": "m"}
self.n_experiments = {}
# Create the full data dataframe
all_data = None
for sname in self.sheetnames:
if all_data is None:
all_data = self.xl.parse(sname, dtype={"composition": str})
all_data['Method'] = len(all_data) * [sname]
else:
_data = self.xl.parse(sname, dtype={"composition": str})
if _data.empty:
continue
_data['Method'] = len(_data) * [sname]
all_data = pd.concat((all_data,_data), sort=False)
all_data = all_data.fillna("")
self.all_data_df = all_data.loc[:,'fm':'Method']
self.papers = pd.read_excel(papers, index_col=0)
self.set_authors()
def set_authors(self):
self.papers.Author
def print_most_popular_stacks(self, fm=None,nfirst=15):
data = self.all_data_df[self.all_data_df.Note!='To fix']
if fm == None:
q = data.groupby(['bottom','fm','top']).size().sort_values(ascending=False)[:nfirst]
else:
data = data[data.fm==fm]
#print(fm)
q = data.groupby(['bottom','top']).size().sort_values(ascending=False)[:nfirst]
q = q.to_frame()
q.columns = ['n']
display(q)
return q
def plotStack(self, stack, select_D="Ds",
size_factor=30, alpha=0.5,
figsizeX=8, marker_type='shapes',
marker_colors=colors, handle_color='gray',
set_axis=None, ndots=20,
visualization_library="mpl", is_XY_to_plot=False, is_anular_to_plot=True):
len_bottom, len_fm, len_top = [len(st) for st in stack]
try:
assert len_bottom==1 or len_top==1
except AssertionError:
print("At least top/bottom must be a single layer")
sys.exit()
if len_top + len_bottom == 2:
fig_out = self._plotTopBottom(stack, select_D,
size_factor, alpha, figsizeX,
marker_type, marker_colors, handle_color, set_axis,
ndots, visualization_library)
print("Plot Top Botttom")
if visualization_library == 'bokeh' and is_plot:
show(fig_out, notebook_handle=True)
return fig_out
else:
(fig_XY, fig_anular), df_annular = self._elementsVsThickness(stack, select_D,
size_factor, alpha,
figsizeX, marker_type, marker_colors, handle_color, set_axis,
ndots, visualization_library)
#print("Plot Element vs Thickness")
if visualization_library == 'bokeh' and is_XY_to_plot:
show(fig_XY, notebook_handle=True)
if fig_anular is not None:
show(fig_anular, notebook_handle=True)
return (fig_XY, fig_anular), df_annular
def _get_elements(self, stack):
bottom, fmats, top = stack
bottom_elements, bottom_thickness = self._get_thickness(bottom)
top_elements, top_thickness = self._get_thickness(top)
_fmats, _fmats_composition = [], []
for fmat in fmats:
fmat_composition = "".join(re.findall("[0-9]", fmat))
if len(fmat_composition):
fmat = "".join(re.findall("[a-zA-Z]", fmat))
_fmats.append(fmat)
_fmats_composition.append(fmat_composition)
out = [bottom_elements, bottom_thickness, _fmats, _fmats_composition,
top_elements, top_thickness]
return out
def _elementsVsThickness(self, stack, select_D="Ds",
size_factor=100, alpha=0.2,
figsizeX=8, marker_type='fillings',
marker_colors=colors, handle_color='gray',
set_axis=None, ndots=20,
visualization_library='mpl',
show_annular_plot=True):
"""
pass the stack to be analysed
([bottom elements], [top elements])
Example:
(['Hf', 'Ta', 'TaN','W', 'IrMn'], ['CoFeB'], ['MgO'])
It is possible to select a particular thickness in nm, like
(['Hf', 'Ta', 'TaN','W', 'IrMn'], ['MgO(2)'])
or give a range, or select some values
(['Hf(2,3)', 'Ta(1-3)', 'TaN','W', 'IrMn'], ['MgO(2)'])
marker_type: strings
shapes|fillings
"""
if isinstance(figsizeX, tuple):
figsize = figsizeX
else:
figsize = (figsizeX*2.2, figsizeX*1.2)
bottom, fmats, top = stack
out = self._get_elements(stack)
[bottom_elements, bottom_thickness, fmats, fmats_composition,
top_elements, top_thickness] = out
if len(top_elements) == 1:
fixed_layer_element = top_elements[0]
fixed_layer_thickness = top_thickness[0]
fixed_layer = "top"
fixed_tlayer = "ttop"
elements = bottom_elements[::-1]
telements = bottom_thickness[::-1]
layer = "bottom"
tlayer = "tbottom"
y_labels = bottom[::-1]
self.multiple_layer = 'bottom'
elif len(bottom_elements) == 1:
fixed_layer_element = bottom_elements[0]
fixed_layer_thickness = bottom_thickness[0]
fixed_layer = "bottom"
fixed_tlayer = "tbottom"
elements = top_elements[::-1]
telements = top_thickness[::-1]
layer = "top"
tlayer = "ttop"
y_labels = top[::-1]
self.multiple_layer = 'top'
else:
raise("Too many elements")
_elements = [r"${}$".format(elem.replace("x", "_x")) for elem in elements]
self.data = None
for fmat, fmat_composition in zip(fmats, fmats_composition):
if visualization_library == 'mpl':
fig, ax = plt.subplots(1,1,figsize=figsize)
ax.set_position([0.12,0.12,.65,.75])
n_data = 0
##################################################
self.dic_n_elements = {}
sheetnames_with_data = self.sheetnames.copy()
markers = []
methods = []
Ds_strings = []
for sname in self.sheetnames:
self.n_elements = []
data = self.xl.parse(sname)
data = data[data.fm == fmat]
data = data[data[fixed_layer]==fixed_layer_element]
#print(sname, data.shape)
if len(fixed_layer_thickness):
if "-" in fixed_layer_thickness:
v1, v2 = fixed_layer_thickness.split("-")
v1, v2 = float(v1), float(v2)
is_to_select = data[fixed_tlayer].between(v1, v2, inclusive=True)
else:
is_to_select = data[fixed_tlayer] == float(fixed_layer_thickness)
data = data[is_to_select]
if fmat_composition:
data = data[data.composition == int(fmat_composition)]
#print("********** %s ***********" % sname)
#print(data)
# Skip an empty dataframe
if data.size == 0:
sheetnames_with_data.remove(sname)
continue
for y, _e in enumerate(zip(elements, telements)):
element, t_element = _e
n_data = 0
is_to_select = data[layer] == element
sub_data = data[is_to_select]
if t_element != "":
if "-" in t_element:
v1, v2 = t_element.split("-")
v1, v2 = float(v1), float(v2)
is_to_select = sub_data[tlayer].between(v1, v2, inclusive=True)
else:
is_to_select = data[tlayer] == telement
sub_data = sub_data[is_to_select]
#print(sub_data)
if sub_data.size == 0:
self.n_elements.append(0)
continue
#else:
#print("*** %s ***" % element)
#print(sub_data)
if self.is_tofix:
_s = [str(d) for d in sub_data.Note]
is_to_select = [_ss != 'To fix' for _ss in _s]
sub_data = sub_data[is_to_select]
if self.data is None:
self.data = sub_data.copy()
else:
self.data = pd.concat((self.data,sub_data))
D_data = sub_data[select_D]
notes = sub_data.Note
#print(sname, _e)
for i in sub_data.index:
Ds = D_data.loc[i]
x = sub_data[tlayer].loc[i]
fill_color = marker_colors[np.sign(Ds)]
#print(x, y, Ds)
size = np.abs(Ds)**0.5 * size_factor
m = chars[sname]
markers.append(chars_bokeh[sname])
methods.append(sname.replace("_"," "))
if Ds:
if marker_type == 'shapes':
is_sign_given = sub_data.is_sign_given.loc[i]
#_filter1 = sname in ['Domain_pattern', 'Stripe_annihilation', 'Spin_torque']
# _filter2 = (sname == 'Nucleation') and (notes.loc[i] == 'Bubble')
if is_sign_given:
_c, _alpha, edgecolors = fill_color, alpha, 'face'
Ds_string = f"{Ds:.2f} pJ/m"
else:
_c, _alpha, edgecolors = 'lightgray', .5, 'black'
Ds_string = f"|{Ds:.2f}| pJ/m"
Ds_strings.append(Ds_string)
if visualization_library == 'mpl':
ax.scatter(x, y+1, c=_c, s=size**2, alpha=_alpha, marker=m,
edgecolors=edgecolors, linewidths=2)
elif marker_type == 'fillings':
color = "tab:%s" % fill_color
fstyle, marker = fillstyle[sname]
ax.plot(x, y+1, markersize=size, alpha=alpha, fillstyle=fstyle, marker=marker,
color=color, mew=2, **marker_style)
else:
if marker_type == 'shapes':
if visualization_library == 'mpl':
ax.scatter(x, y+1,c='black',s=10,alpha=alpha,marker=m)
else:
Ds_string = f"0 pJ/m"
Ds_strings.append(Ds_string)
elif marker_type == 'fillings':
ax.plot(x, y+1, markersize=size_factor, alpha=1, fillstyle='full', color='black', mew=2)
n_data += 1
self.n_elements.append(n_data)
self.dic_n_elements[sname] = self.n_elements
#print(dic_n_elements)
#print("Loop done")
#print("Full Loop done")
df = pd.DataFrame(self.dic_n_elements, index=elements)
if df.empty:
print("No data available")
continue
df.loc["Total"] = df.sum(axis=0)
stack_key = self._stack_as_string(stack)
self.n_experiments[stack_key] = df
self.fmats.append(fmat)
title = self._get_title_stack(fmat, fmat_composition, fixed_layer, fixed_layer_element, fixed_layer_thickness, select_D)
xlabel = "%s layer thickness (nm)" % layer
ylabel = "%s layer" % layer
if visualization_library == 'mpl':
if set_axis is not None:
ax.set_xlim(set_axis[:2])
ax.set_ylim(set_axis[2:])
else:
ax.set_ylim(0.2, len(elements)+0.8)
ax.set_yticks(range(1,len(elements)+1))
ax.set_yticklabels(_elements, size=20)
ax.set_xlabel(xlabel, size=20)
ax.set_ylabel(ylabel, size=20)
# Make the legends
self._print_legends(sheetnames_with_data, marker_type, marker_colors, select_D,
size_factor, alpha, handle_color, zero_point=False)
ax.set_title(title, size=20)
plt.show()
elif visualization_library == 'bokeh':
self.data = self.data.fillna("")
items = ['Author', 'Title', 'Journal', 'Volume', 'Pages', 'Year']
for item in items:
self.data.loc[:, item] = [self.papers.loc[ref][item] for ref in self.data.Ref]
# self.data[item] = [self.papers.loc[ref][item] for ref in self.data.Ref]
self.data.loc[:,'Author'] = self.get_authors_string(self.data['Author'])
self.data.loc[:,'size'] = np.abs(self.data.Ds)**0.5 * size_factor
self.data.loc[:,'alpha'] = [alpha if sign else 0.5 for sign in self.data.is_sign_given]
self.data.loc[:,'marker'] = markers
self.data.loc[:,'method'] = methods
_line_colors, _fill_colors = [], []
for sign, Ds in zip(self.data.is_sign_given, self.data.Ds):
if sign:
_c = marker_colors[np.sign(Ds)]
_line_colors.append(_c)
_fill_colors.append(_c)
else:
_line_colors.append('black')
_fill_colors.append('lightgray')
self.data.loc[:,'line_color'] = _line_colors
self.data.loc[:,'fill_color'] = _fill_colors
self.data.loc[:,'Ds_string'] = Ds_strings
stack_string = self.get_stack_string(self.data)
self.data.loc[:,'stack_string'] = stack_string
tooltips = [('Stack', '@stack_string'),
('D_s', '@Ds_string'),
('Method', '@method'),
('Authors', '@Author'),
('Tile', '@Title'),
('Ref', '@Journal, @Volume, @Pages (@Year)'),
('', 20*'-')]
fig = figure(plot_width=figsize[0], plot_height=figsize[1],
y_range=y_labels, tooltips=tooltips, toolbar_location='above')
fig.add_layout(CategoricalAxis(), 'right')
fig.add_layout(Legend(), 'right')
fig.scatter(f"t{layer}", layer, size='size', alpha='alpha', source=self.data,
line_color='line_color', fill_color='fill_color', marker='marker',
legend_group='method')
fig.xaxis.axis_label = xlabel
fig.xaxis.axis_label_text_font_size = "25px"
# yaxis
fig.yaxis.axis_label = ylabel
fig.yaxis.axis_label_text_font_size = "20px"
fig.yaxis.axis_label_text_font_style = "italic"
fig.yaxis.major_label_text_font_size = "25px"
fig.yaxis.major_label_text_font_style = "italic"
fig.add_layout(LinearAxis(), 'above')
#fig.extra_y_ranges = {"right": fig.y_range}
# if set_axis is not None:
# left, right, bottom, top = set_axis
# fig.x_range = Range1d(left, right)
# else:
# pass
#fig.y_range = Range1d(1, len(elements)+1)
#fig.xaxis.ticker = FixedTicker(ticks=list(range(1,len(elements)+1)))
#size=20
#ax.set_xlabel("%s layer thickness (nm)" % layer, size=20)
#ax.set_ylabel("%s layer" % layer, size=20)
# Make the legends
#self._print_legends(sheetnames_with_data, marker_type, marker_colors, select_D,
# size_factor, alpha, handle_color, zero_point=False)
fig.legend.title = 'Methods'
fig.legend.label_text_color = 'black'
title = title.replace("$","")
fig.title.text = title.replace("_","")
fig.title.text_font_size = "25px"
t0, t1 = title.split("-")
title_stack = t1
t1 = t1.replace("/", "_").strip()
t1 = f"{t1}.html"
#output_file(t1, title=t1)
if show_annular_plot:
fig_annular = self.plot_annular(self.data, elements, telements,
title=title_stack, xlabel=xlabel)
df_annular = self.df_annular[list(self.df_annular.columns[:23]) + ['method']]
return (fig, fig_annular), df_annular
return (fig, None), None
def plot_annular(self, df_data, elements, telements,
max_thickness=6, step_tickness=0.5, xlabel=None, title=None):
self.df_annular = df_data.copy()
self.df_annular = self.df_annular.sort_values('Ds', ascending=False, key=np.abs)
# Set the layer with different elements
tlayer = "t" + self.multiple_layer
self.df_annular = self.df_annular[self.df_annular[tlayer] < max_thickness]
type_elements = {
'metals': ['W', 'Pt', 'Ir', 'Au', 'Ta', 'Al', 'Gd', 'IrMn', 'Hf', 'TaN', 'Cu'],
'oxides': ['AlOx', 'GdO', 'MgO']
}
elements_color = dict([
#("metals", "#e69584"),
#("metals", "#f0f0f0"),
("metals", "#f5fffa"), #Mintcream
#("metals", "aliceblue"),
#("oxides", "#aeaeb8"),
#("oxides", "#fee8ca"),
("oxides", "cornsilk"),
])
metals_selected = False
oxides_selected = False
colors = []
for element in elements:
if element in type_elements['metals']:
colors.append(elements_color['metals'])
metals_selected = True
elif element in type_elements['oxides']:
colors.append(elements_color['oxides'])
oxides_selected = True
else:
print('Element %s non available' % element)
colors.append('#000000') #
methods_colors_red = [redColors[m] for m in methods_with_sign]
methods_colors_green = [greenColors[m] for m in methods_with_sign]
methods_colors_gray = [grayColors[m] for m in methods_no_sign]
clrs = []
for Ds, sign, method in zip(self.df_annular.Ds, self.df_annular.is_sign_given, self.df_annular.method):
if sign:
#i = methods.index(method)
if Ds > 0:
#c = greens[i]
c = greenColors[method]
elif Ds < 0:
#c = oranges[i]
c = redColors[method]
else:
c = grayColors[method]
clrs.append(c)
self.df_annular.loc[:,'fill_color'] = clrs
width, height, inner_radius, outer_radius, Y0 = 800, 800, 70, 270, 30
minr, maxr = 0, max(abs(self.df_annular.Ds))
a = (outer_radius - inner_radius) / (maxr - minr)
self.df_annular.loc[:,'rads'] = inner_radius + a * np.abs(self.df_annular.Ds)
rads = inner_radius + a * np.abs(self.df_annular.Ds)
n_sectors = len(elements)
print(f"{n_sectors} sectors to plot: {elements}")
big_angle = 2.0 * np.pi / (n_sectors + 1)
n_small_angle = max_thickness / step_tickness
small_angle = big_angle / n_small_angle
tooltips = [('Stack', '@stack_string'),
('D_s', '@Ds_string (@method)'),
('Paper', '@Author, @Title, @Journal @Volume, @Pages (@Year)'),
('', 20*'-')]
p = figure(width=width, height=height, title="",
x_axis_type=None, y_axis_type=None,
x_range=(-350, 350), y_range=(-350, 350),
min_border=0, outline_line_color="black",
#background_fill_color="#f0e1d2")
tooltips=tooltips,
tools=['pan', 'box_zoom', 'wheel_zoom', 'save',
'reset', 'hover'],
background_fill_color="#ffffff")
hover_tool = p.select(type=HoverTool)
hover_tool.names = ["DsValues"]
p.axis.visible = True
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
# annular wedges
n_sector = np.array([elements.index(e) for e in self.df_annular[self.multiple_layer]])
_angles = np.pi/2 - big_angle/2 - n_sector * big_angle
# Calculate the centers of the wedge in respect the sector
c0 = big_angle / max_thickness * self.df_annular[tlayer]
self.df_annular.loc[:,'angle0'] = _angles - c0 + small_angle/2
self.df_annular.loc[:,'angle1'] = self.df_annular['angle0'] - small_angle
angles = np.pi/2 - big_angle/2 - np.arange(n_sectors+1) * big_angle
p.annular_wedge(0, Y0, inner_radius, outer_radius*1.02, -big_angle+angles, angles, color=colors,
inner_radius_units='data', outer_radius_units='data')
# radial axes
p.annular_wedge(0, Y0, inner_radius-8, outer_radius+10,
-big_angle+angles, -big_angle+angles,
color="black", inner_radius_units='data', outer_radius_units='data')
ticks = big_angle / max_thickness * np.arange(1,max_thickness*(n_sectors+1))
ticks_angles = np.pi/2 - big_angle/2 - ticks
p.annular_wedge(0, Y0, inner_radius-5, inner_radius, ticks_angles, ticks_angles,
color="black",inner_radius_units='data', outer_radius_units='data')
R0 = inner_radius *.8
ticks_alpha = np.pi/2 + big_angle/2 - big_angle/max_thickness * np.arange(0,max_thickness+2,2)
ns = [str(n) for n in np.arange(0,max_thickness+2,2)]
# add other x_ticks if liked
if False:
_ticks_alpha = np.copy(ticks_alpha)
sector_numbers = [4,7]
ns = len(sector_numbers) * ns
for i in sector_numbers:
_alpha = _ticks_alpha + i * big_angle
ticks_alpha = np.concatenate((ticks_alpha, _alpha))
source_label = ColumnDataSource(data=dict(x=R0*np.cos(ticks_alpha),
y=R0*np.sin(ticks_alpha),
tick_angles = (-np.pi/2 + ticks_alpha),
ns = ns)
)
lbtk = LabelSet(x='x',y='y',y_offset=Y0,
text_font_size = "8px", text='ns', angle='tick_angles', source=source_label,
text_align='center')
p.add_layout(lbtk)
# small wedges
p.annular_wedge(0, Y0, inner_radius=inner_radius, outer_radius='rads',
start_angle='angle0', end_angle='angle1',
fill_color='fill_color',
line_color='black',
hatch_color=None,
name = "DsValues",
direction='clock',
source=self.df_annular,
inner_radius_units='data', outer_radius_units='data')
# circular axes and lables
n_radii = int(maxr / 0.5) + 1
labels = np.arange(n_radii) * 0.5
radii = inner_radius + a * labels
p.circle(0, Y0, radius=radii, fill_color=None, line_color="grey", radius_units='data')
p.arc(0, Y0,radius=outer_radius*1.02, start_angle = np.pi/2 + big_angle/2, end_angle = np.pi/2 - big_angle/2,
radius_units='data', color='black')
for i, r in enumerate(labels):
p.add_layout(Label(x=0, y=radii[i]+5*np.exp(-i/2), y_offset=Y0, text=str(r), x_units='data', y_units='data',
text_font_size="10px", text_align="center", text_baseline="bottom"))
# labels of elements
xr = 1.03 * outer_radius*np.cos(np.array(-big_angle/2 + angles[:-1]))
yr = 1.03 * outer_radius*np.sin(np.array(-big_angle/2 + angles)[:-1]) + Y0
#p.circle(xr, yr, radius=2, fill_color='gray', line_color="grey")
label_angle=np.array(-big_angle/2+angles[:-1])
selection = label_angle < -np.pi/2
i = np.argmax(selection)
label_angle[selection] += np.pi # easier to read labels on the left side
p.text(xr[:i], yr[:i], elements[:i], angle=label_angle[:i],
text_font_size="20px", text_align="left", text_baseline="middle")
p.text(xr[i:], yr[i:], elements[i:], angle=label_angle[i:],
text_font_size="20px", text_align="right", text_baseline="middle")
# Color patterns
h = outer_radius + 15
x0, y0, l0, dy = -h, -h-5, 15, 30
xs = x0 + l0 * np.arange(len(methods_with_sign))
ys = np.array(len(methods_with_sign) * [y0+l0])
p.rect(xs, ys, width=l0, height=l0, line_color='black',fill_color=methods_colors_red)
p.text(xs[-1] + 15, ys[-1], text=['Negative DMI'], text_font_size="14px",
text_align="left", text_baseline="middle")
ys = ys -l0
p.rect(xs, ys, width=l0, height=l0, line_color='black',fill_color=methods_colors_green)
p.text(xs[-1] + 15, ys[-1], text=['Positive DMI'], text_font_size="14px",
text_align="left", text_baseline="middle")
p.text(xs, ys[-1] + 2*l0, text=methods_with_sign, angle=np.pi/2, text_font_size="14px",
text_align="left", text_baseline="middle")
n_methods_no_sign = len(methods_no_sign)
xs = x0 + l0 * np.arange(len(methods_no_sign)) + 500
ys = np.array(n_methods_no_sign * [y0])
p.text(xs[0] - l0, ys[-1], text=['|DMI|'], text_font_size="14px",
text_align="right", text_baseline="middle")
p.rect(xs, ys, width=l0, height=l0, line_color='black',fill_color=methods_colors_gray[::-1])
p.text(xs, ys[-1] + l0, text=methods_no_sign[::-1], angle=np.pi/2, text_font_size="14px",
text_align="left", text_baseline="middle")
# # OK, these hand drawn legends are pretty clunky, will be improved in future release
x0 += 5
y0 = h - 10
if metals_selected:
p.rect(x0, y0, width=3*l0, height=l0,
color=elements_color['metals'], line_color='black')
lbm = Label(x=x0+2*l0, y=y0, text='Metals', text_font_size="16px",
text_align="left", text_baseline="middle")
p.add_layout(lbm)
# Add the stack at the top of the plot
if title:
lb_title = Label(x=0, y=y0+55, text=title, text_font_size="30px",
text_align="center", text_baseline="middle")
# lb_title = LatexLabel(x=0, y=y0+55, text=title, text_font_size="30px",
# x_units="data", y_units="data",
# render_mode = 'css', background_fill_alpha=0,
# text_align="center", text_baseline="middle")
p.add_layout(lb_title)
if oxides_selected:
x0 += 530
p.rect(x0, y0, width=3*l0, height=l0,
color=elements_color['oxides'], line_color='black')
lbo = Label(x=x0+2*l0, y=y0, text='Oxides', text_font_size="16px",
text_align="left", text_baseline="middle")
p.add_layout(lbo)
if xlabel:
self.write_curved_text(xlabel, p, R=inner_radius-25, y_offset=Y0)
return p
def write_curved_text(self, text, fig, white_spaces=0, R=60, y_offset=None, is_curved=False):
"""
is_curved: letter, word, None
"""
text = white_spaces * " " + text + white_spaces * " "
ltext = len(text)
if is_curved=='letter':
angles = np.pi * (1 - (np.arange(ltext) + 1.5)/ltext)
for i, angle in enumerate(angles):
if text[i]:
lb = Label(x=R*np.cos(angle), y=R*np.sin(angle),y_offset=y_offset,
text_font_size = "10px", text_font = 'helvetica',
text=text[i], angle=angle-np.pi/2)
fig.add_layout(lb)
elif is_curved == 'word':
split_text = text.strip().split(" ")
half_lens_text = [len(l)/2 for l in split_text]
for i in range(len(split_text)):
w = 2 * sum(half_lens_text[:i]) + half_lens_text[i] + i
angle = np.pi * ( 1 - w / len(text))
lb = Label(x=R*np.cos(angle), y=R*np.sin(angle),y_offset=y_offset,
text_font_size = "14px", text_font = 'times', text_font_style='italics',
text=split_text[i], angle=angle-np.pi/2,text_align="center")
fig.add_layout(lb)
else:
text = text.strip().split(" ")
t1 = " ".join(text[:2])
t2 = " ".join(text[2:])
x1, y1 = 0, 10
for tx in [t1,t2]:
lb = Label(x=x1, y=y1, y_offset=y_offset,
text_font_size = "20px", text_font = 'times', text_font_style='italic',
text=tx, text_align="center")
y1 += -20
fig.add_layout(lb)
def get_stack_string(self, data):
stack_string = []
for q in zip(data.bottom1,data.tbottom1,
data.bottom, data.tbottom,
data.fm, data.tfm,
data.top, data.ttop,
data.top1, data.ttop1, data.Repetitions):
b1,tb1,b,tb,_fm,_tfm,t,tt,t1,tt1, rep = q
rep = str(rep)
if len(rep) > 2:
_s = rep
else:
_s = ""
if b:
_s += "%s(%s)/" % (b, get_string(tb))
_s += "%s(%s)" % (_fm, get_string(_tfm))
if t:
_s += "/%s(%s)" % (t, get_string(tt))
if rep !="":
_s = "[%s]x%s" % (_s, rep)
if b1:
_s = "%s(%s)/" % (b1, get_string(tb1)) + _s
if t1:
_s += "/%s(%s)" % (t1, get_string(tt1))
stack_string.append(_s)
return stack_string
def get_authors_string(self, authors):
_auth = []
for auth in authors:
_authors = auth.split(";")
if len(_authors) > 3:
surname, name = _authors[0].split(",")
name = name.strip().capitalize()
_s = "%s, %s. et al." % (surname, name[0])
else:
_s = auth
_auth.append(_s)
return _auth
def _get_thickness(self, elements):
elements_name, elements_thickness = [], []
for element in elements:
thickness = re.findall("[(\-,0-9)]", element)
thickness = "".join(thickness[1:-1])
elements_thickness.append(thickness)
q = element.replace("(%s)" % thickness, "")
elements_name.append(q)
return elements_name, elements_thickness
def _print_legends(self, sheetnames_with_data, marker_type, marker_colors, select_D,
size_factor, alpha, handle_color, zero_point):
handles1, handles2 = self._get_handles(sheetnames_with_data, marker_type, marker_colors, select_D,
size_factor, alpha, handle_color, zero_point)
h_leg = self._h_leg(sheetnames_with_data)
leg2 = plt.legend(handles=handles2, bbox_to_anchor=(1.02, 1-h_leg), loc=2, borderaxespad=0.,
ncol=1, title=r"$\bf{DMI\ values}$", labelspacing=0.8)
leg = plt.legend(handles=handles1, bbox_to_anchor=(1.02, 1), loc=2, borderaxespad=0.,
ncol=1, title = r"$\bf{Methods}$")
plt.gca().add_artist(leg2)
#plt.draw()
# q = leg.get_window_extent()
# self.p = ax, leg
# print(q.height)
# h_leg = q.height/h
# plt.draw()
# self.leg = leg
# qq = leg.get_frame()
# h_leg = qq.get_bbox()
# print(h_leg)
def _get_handles(self, snames, marker_type, marker_colors, select_D,
size_factor, alpha, handle_color,zero_point=False):
handles1, handles2 = [], []
if marker_type == 'shapes':
for sname in snames:
h = mlines.Line2D([], [], color=handle_color, marker=chars[sname],
markersize=10, label=sname.replace("_", " "), ls="None", alpha=1)
handles1.append(h)
elif marker_type == 'fillings':
for sname in snames:
fstyle, marker = fillstyle[sname]
h = mlines.Line2D([], [], color=handle_color, markersize=10, marker=marker,
fillstyle=fstyle, label=sname.replace("_", " "), ls="None", alpha=alpha, **marker_style)
handles1.append(h)
for s in ["0.2", "0.5", "1"]:
dlabel = r"$%s$ = %s %sJ/m" % (select_D.replace("s", "_s"), s, self.k_factor[select_D])
size = float(s)**0.5*size_factor
size_max = plt.Line2D((0,1),(0,0), color=marker_colors[1], marker='o', alpha=alpha,
markersize=size, linestyle='', label=dlabel)
handles2.append(size_max)
for c, s in zip(marker_colors.values(), ['>','<', "="]):
dlabel = r"$%s$ %s 0" % (select_D.replace("s", "_s"), s)
if (s == "=") and (not zero_point):
dlabel = "No sign available"