def plot_palette(doc, palette_name):
# Create plots to compare the cmaps
plot = doc.new(
Plot(
plot_path=filepath,
plot_name=filename + '_' + palette_name,
lines='3pt',
height='6cm',
))
cmap = PREDEFINED_CMAPS[palette_name]
palette = PREDEFINED_PALETTES[palette_name]
# Numer of colors shown in the plot
n_colors = 25
interp_param = np.linspace(0, 1, n_colors + 1)
# Plot the hue(h)-lightness(J) space
for i, JCh_color in zip(range(n_colors), palette):
cmap.color_model = 'rgb' # Default JCh color model takes the hue mod 360 to be a valid color, but this makes the color map look non-continuous. The rgb color model does not process any of the components.
J1, C1, h1 = cmap(interp_param[i])
J2, C2, h2 = cmap(interp_param[i + 1])
cmap.color_model = 'JCh' # Resetting the color model to the original
plot.add_plot([h1, h2], [J1, J2], color=JCh_color, line_cap='round')
plot.x_label = 'Hue angle $h$'
plot.y_label = 'Lightness $J$'
plot.caption = f'The \\texttt{{{palette_name}}} color map'
# Show the generated colors in squares using TikZ.
for n_colors in [2, 3, 4, 5, 6, 9]:
doc += f'{n_colors} colors: \\hspace{{10pt}}'
tikzpicture = doc.new(
TexEnvironment('tikzpicture', options=['baseline=-.5ex']))
for i, color in zip(range(n_colors), palette):
tikzpicture += Node((i, 0), fill=color)
doc += ' '
x = [1, 2, 3, 4]
y1 = [32, 43, 45, 61]
y2 = [45, 51, 43, 34]
labels = ['Dataset 1', 'Dataset 2', 'Dataset 3', 'Dataset 4']
plot = Plot(
plot_path='./examples/',
plot_name='bar_chart_example',
as_float_env=False,
marks=False,
lines=False,
grid='none',
grid_style=('line width=.2pt', 'gray!50'),
ymajorgrids='true',
width='7cm',
height='6cm',
axis_line_style='{draw=none}',
legend_cell_align='{left}',
legend_style='{font=\\footnotesize, draw=none, fill=none}',
ylabel_style='{yshift=-3.5mm}',
bar_width='4mm',
ybar='0mm',
xticklabel_style='{font=\\footnotesize}',
xtick_style='{draw=none}',
ytick_style='{draw=none}',
)
plot.axis.options += (
'nodes near coords',
'every node near coord/.append style={font=\\scriptsize}',
)
from python2latex import Document, Plot import numpy as np # Document type 'standalone' will only show the plot, but does not support all tex environments. filepath = './examples/simple plot example/' filename = 'simple_plot_example' doc = Document(filename, doc_type='standalone', filepath=filepath) # Create the data X = np.linspace(0,2*np.pi,100) Y1 = np.sin(X) Y2 = np.cos(X) # Create a plot plot = doc.new(Plot(X, Y1, X, Y2, plot_path=filepath, as_float_env=False)) tex = doc.build()
], # Indigo
color_model='JCh',
color_transform=lambda c: tuple(JCh2rgb(c)))
cmap_def = r'\pgfplotsset{compat=1.14, colormap={bint}{' + '\n\t'.join(
f'rgb({i})={cmap(i)}' for i in np.linspace(0, 1, 25)) + '}}'
plot = Plot(
plot_path='./examples/',
plot_name='heatmap_example',
as_float_env=False,
lines=False,
grid=False,
width='7.5cm',
height='7.5cm',
axis_line_style='{draw=none}',
enlargelimits='false',
y_dir='reverse',
axis_x='top',
x_tick_label_style='{font=\\footnotesize}',
y_tick_label_style='{font=\\footnotesize}',
colorbar_style=
'{ylabel=Attention, ylabel style={rotate=180}, yticklabels={0.00,0.25,0.50,0.75,1.00}, ytick={0,0.25,0.5,0.75,1}}'
)
plot.add_matrix_plot(X, Y, Z)
for i, zz in enumerate(Z):
for j, z in enumerate(zz):
if z > .6:
plot.axis += f'\\node[white] at ({i},{j}) {{\\scriptsize {z:.2f} }};'
filename = 'simple_matrix_plot_example'
doc = Document(filename,
doc_type='standalone',
filepath=filepath,
border='1cm')
# Create the data
X = np.linspace(-3, 3, 11)
Y = np.linspace(-3, 3, 21)
# Create a plot
plot = doc.new(
Plot(plot_name=filename,
plot_path=filepath,
as_float_env=False,
grid=False,
lines=False,
enlargelimits='false',
width=r'.5\textwidth',
height=r'.5\textwidth'))
XX, YY = np.meshgrid(X, Y)
Z = np.exp(
-(XX**2 + YY**2) / 6
).T # Transpose is necessary because numpy puts the x dimension along columns and y dimension along rows, which is the opposite of a standard graph.
plot.add_matrix_plot(X, Y, Z)
# Adding titles and labels
plot.x_label = 'X axis'
plot.y_label = 'Y axis'
plot.title = 'Some title'
palette = Palette(colors=cmap, color_model='rgb')
pal = Palette(colors=cmap, n_colors=2)
# Create the data
X = np.linspace(-1, 1, 50)
Y = lambda c: np.exp(X * c) + c
# Let us compare the different color palettes generated for different number of line plots
for n_colors in [2, 3, 5, 10]:
# Create a plot
plot = doc.new(
Plot(
plot_name=filename + f'n_colors={n_colors}',
plot_path=filepath,
width='\\textwidth',
height='.21\\paperheight',
palette=palette,
))
for c in np.linspace(.5, 1.5, n_colors):
plot.add_plot(X, Y(c), label=f'\\footnotesize $c={c:.3f}$'
) # Add labels (default is at end of line plot)
plot.x_min = -1
plot.x_max = 1.3
doc += '\n'
tex = doc.build()
# Create the document
filepath = './examples/more complex plot example/'
filename = 'more_complex_plot_example'
doc = Document(filename, doc_type='article', filepath=filepath)
sec = doc.new_section('More complex plot')
sec.add_text(
'This section shows how to make a more complex plot integrated directly into a tex file.'
)
# Create the data
X = np.linspace(0, 2 * np.pi, 100)
Y1 = np.sin(X)
Y2 = np.cos(X)
# Create a plot
plot = sec.new(Plot(plot_name=filename, plot_path=filepath))
plot.caption = 'More complex plot'
nice_blue = Color(.07, .22, .29, color_name='nice_blue')
nice_orange = Color(.85, .33, .28, color_name='nice_orange')
plot.add_plot(X, Y1, nice_blue, 'dashed',
legend='sine') # Add colors and legend to the plot
plot.add_plot(X, Y2, nice_orange, line_width='3pt', legend='cosine')
plot.legend_position = 'south east' # Place the legend where you want
# Add a label to each axis
plot.x_label = 'Radians'
plot.y_label = 'Projection'
# Choose the limits of the axis
def heatmap_all_to_latex(self, experiment, sec, mean_metrics, x_label,
y_label, caption, file_path, file_name):
plot = sec.new(
Plot(plot_name=file_name,
plot_path=file_path,
grid=False,
lines=False,
enlargelimits='false',
width=r'.42\textwidth',
height=r'.42\textwidth',
position='th!',
label=file_name,
name='plot0'))
plot.caption = caption
kwargs_per_plot = {
1: {
'as_float_env': False,
'at': '(plot0.south east)',
'anchor': 'south west',
'xshift': r'.12\textwidth',
'name': 'plot1'
},
2: {
'as_float_env': False,
'at': '(plot0.south west)',
'anchor': 'north west',
'yshift': r'-0.07\textwidth',
'name': 'plot2'
},
3: {
'as_float_env': False,
'at': '(plot2.south east)',
'anchor': 'south west',
'xshift': r'.12\textwidth',
'name': 'plot3'
}
}
titles = {
'de': 'English-Deutsch',
'it': 'English-Italian',
'fi': 'English-Finnish',
'es': 'English-Spanish'
}
for i, language in enumerate(sorted(mean_metrics['accuracies'])):
if i == 0:
current_plot = plot
else:
current_plot = Plot(plot_name=file_name,
plot_path=file_path,
grid=False,
lines=False,
enlargelimits='false',
width=r'.42\textwidth',
height=r'.42\textwidth',
position='th!',
**kwargs_per_plot[i])
current_plot.tikzpicture.head = ''
current_plot.tikzpicture.tail = ''
x_values, y_values = sorted(
experiment.CHANGING_PARAMS[x_label]), sorted(
experiment.CHANGING_PARAMS[y_label])
z = np.zeros((len(x_values), len(y_values)), dtype=float)
for x_idx, x_value in enumerate(x_values):
for y_idx, y_value in enumerate(y_values):
z[x_idx, y_idx] = float(
mean_metrics['accuracies'][language][(str(y_value),
str(x_value))])
z = np.around(z, 2)
if i >= 2:
current_plot.x_label = r'$p_{factor}$'
current_plot.x_ticks_labels = [
'{:.1f}'.format(x) for x in x_values
]
else:
current_plot.x_ticks_labels = [r'\empty']
if i % 2 == 0:
current_plot.y_label = r'$p_0$'
current_plot.y_ticks_labels = [
'{:.2f}'.format(y) for y in y_values
]
else:
current_plot.y_ticks_labels = [r'\empty']
x_values = list(range(len(x_values)))
y_values = list(range(len(y_values)))
current_plot.x_ticks = x_values
current_plot.y_ticks = y_values
delta = z.max() - z.min()
point_min = z.min() - delta / 2
point_max = z.max() + delta / 2
current_plot.add_matrix_plot(x_values,
y_values,
z,
point_meta_min=point_min,
point_meta_max=point_max)
current_plot.axis.options += (
r'nodes near coords={\pgfmathprintnumber\pgfplotspointmeta}',
r'every node near coord/.append style={xshift=0pt,yshift=-7pt, black, font=\footnotesize}',
)
current_plot.axis.kwoptions[
'colorbar_style'] = '{{/pgf/number format/fixed zerofill, /pgf/number format/precision=1}}'
current_plot.title = titles[language]
current_plot.plot_name += '_en_{}'.format(language)
if i > 0:
plot.tikzpicture += current_plot
def plot_all_to_latex(self, sec, mean_metrics, std_metrics, caption,
file_path, file_name):
plot = sec.new(
Plot(plot_name=file_name,
plot_path=file_path,
position='th!',
width=r'.27\textwidth',
height=r'.25\textwidth',
label=file_name,
name='plot0',
xshift=r'-.115\textwidth'))
plot.caption = caption
kwargs_per_plot = {
1: {
'as_float_env': False,
'at': '(plot0.south east)',
'anchor': 'south west',
'xshift': r'-.04\textwidth',
'name': 'plot1'
},
2: {
'as_float_env': False,
'at': '(plot1.south east)',
'anchor': 'south west',
'xshift': r'0.035\textwidth',
'name': 'plot2'
},
3: {
'as_float_env': False,
'at': '(plot2.south east)',
'anchor': 'south west',
'xshift': r'.11\textwidth',
'name': 'plot3'
}
}
titles = {
'de': 'English-Deutsch',
'it': 'English-Italian',
'fi': 'English-Finnish',
'es': 'English-Spanish'
}
for i, language in enumerate(sorted(mean_metrics['accuracies'])):
if i == 0:
current_plot = plot
else:
current_plot = Plot(plot_name=file_name,
plot_path=file_path,
width=r'.27\textwidth',
height=r'.25\textwidth',
**kwargs_per_plot[i])
current_plot.tikzpicture.head = ''
current_plot.tikzpicture.tail = ''
x, y, std = np.array(
list(mean_metrics['accuracies'][language].keys())).astype(
int), np.array(
list(mean_metrics['accuracies']
[language].values())).astype(float), np.array(
list(std_metrics['accuracies']
[language].values())).astype(float)
sorting = x.argsort()
x, y, std = x[sorting], y[sorting], std[sorting]
current_plot.add_plot(x,
y,
'blue',
'ylabel near ticks',
mark='*',
line_width='1.2pt',
mark_size='.9pt')
current_plot.add_plot(x,
y + 1.96 * std,
name_path='upper',
draw='none')
current_plot.add_plot(x,
y - 1.96 * std,
name_path='lower',
draw='none')
current_plot.axis.append(
'\\addplot[fill=blue!10] fill between[of=upper and lower];')
current_plot.axis.kwoptions[
'y tick label style'] = '{/pgf/number format/fixed zerofill, /pgf/number format/precision=1}'
current_plot.x_min = np.floor(x.min())
current_plot.x_max = np.ceil(x.max())
y_max, y_min = (y + 1.96 * std).max(), (y - 1.96 * std).min()
delta = y.max() - y.min()
current_plot.y_min = y_min - delta / 2
current_plot.y_max = y_max + delta / 2
current_plot.title = titles[language]
current_plot.plot_name += '_en_{}'.format(language)
if i > 0:
plot.tikzpicture += current_plot
def f(x, a=1, b=1.5, c=400, d=8):
return np.clip((1 / (a * x)**4 - d / (a * x)**3) / c + b, -5, 6.3)
y1 = f(x)
y2 = f(x, .8, 2)
y3 = f(x, .65, 2.5)
y4 = f(x, .55, 3)
y5 = f(x, .5, 3.5)
plot = Plot(
plot_path='./examples/',
plot_name='lineplot_example',
as_float_env=False,
grid_style=('gray!35', 'ultra thin'),
width='7cm',
height='6cm',
ylabel_style='{yshift=-3.5mm}',
)
plot.add_plot(x * 1000, y1, label='\\scriptsize$p=10$')
plot.add_plot(x * 1000, y2, label='\\scriptsize$p=30$')
plot.add_plot(x * 1000, y3, label='\\scriptsize$p=50$')
plot.add_plot(x * 1000, y4, label='\\scriptsize$p=75$')
plot.add_plot(x * 1000, y5, label='\\scriptsize$p=100$')
plot.y_min = 0
plot.y_max = 6.2
plot.x_min = 0
plot.x_max = 900
x1 = np.random.normal(1, 1.4, 20)
x1 -= min(x1) - .5
y1 = x1 + np.random.normal(0, .7, 20)
x2 = np.random.normal(6, 2, 15)
y2 = x2 + np.random.normal(0, .5, 15)
plot = Plot(
plot_path='./examples/',
plot_name='scatterplot',
as_float_env=False,
marks=True,
lines=False,
grid_style=('gray!35', 'ultra thin'),
width='7cm',
height='6cm',
legend_cell_align='{left}',
legend_style='{font=\\footnotesize,draw=gray!50}',
ylabel_style='{yshift=-3.5mm}',
)
plot.add_plot(x1, y1+2, legend='Cercle indigo', fill_opacity=.5)
plot.add_plot(x2, y2+2, mark='triangle*', mark_size='2.5pt', legend='Triangle orange', fill_opacity=.5)
plot.legend_position = 'south east'
plot.y_min = 0
plot.x_min = 0
plot.x_ticks = (0,2,4,6,8)
# Adding necessary library to preamble for colormaps
doc.add_to_preamble(r'\usepgfplotslibrary{colorbrewer}')
doc.add_to_preamble(r'\pgfplotsset{compat=1.15, colormap/Blues-3}')
# Create the data
X = np.array([0.05, 0.1, 0.2])
Y = np.array([1.5, 2.0, 3.0, 4.0])
Z = np.random.random((3, 4))
# Create a plot
plot = sec.new(
Plot(plot_name=filename,
plot_path=filepath,
grid=False,
lines=False,
enlargelimits='false',
width=r'.6\textwidth',
height=r'.8\textwidth'))
plot.caption = 'Matrix plot of some random numbers as probabilities'
plot.add_matrix_plot(
range(len(X)), range(len(Y)), Z
) # Dummy values for x and y so that the region are all the same size, even though the values of X and Y are not linear.
# Adding more complex custom options to the axis (see PGFPlots documentation)
plot.axis.options += (
r'nodes near coords={\pgfmathprintnumber\pgfplotspointmeta\,\%}',
r'every node near coord/.append style={xshift=0pt,yshift=-7pt, black, font=\footnotesize}',
)
# Add a label to each axis
import matplotlib.pyplot as plt
iris = sns.load_dataset("iris")
features = ['petal_length', 'petal_width', 'sepal_length', 'sepal_width']
data = [iris[feature] for feature in features]
# Using seaborn to produce the violin plots
ax = sns.violinplot(data=data, cut=2.3, gridsize=200, bw=.2)
plot = Plot(
plot_path='./examples/',
plot_name='violin_plot_example',
as_float_env=False,
grid='none',
ymajorgrids='true',
grid_style=('gray!35', 'ultra thin'),
width='7cm',
height='6cm',
ylabel_style='{yshift=-4mm}',
xlabel_style='{yshift=-3.5mm}',
axis_line_style='{draw=none}',
x_tick_label_style='{align=center, font=\\scriptsize}',
xtick_style='{draw=none}',
ytick_style='{draw=none}',
)
palette = holi(4)
for i, feature in enumerate(features):
x, y = ax.collections[2 * i]._paths[
0]._vertices.T # Hacking into matplotlib objects to find the data defining the envelope
q25, q50, q75 = np.percentile(data[i], [25, 50, 75])
from python2latex import Template, Table, Plot filepath = './examples/templating an existing file' template = Template(filename='already_existing_file', filepath=filepath) table = Table((4, 3)) table[1:, 0:] = [[i for _ in range(3)] for i in range(3)] table[0] = 'Title' table[0].add_rule() table.caption = 'Here is a table caption.' template.anchors['some_table'] = table plot = Plot(plot_name='some_plot', plot_path=filepath) plot.add_plot(list(range(10)), list(range(10)), 'red') plot.caption = 'Here is a figure caption.' template.anchors['some_figure'] = plot template.render()
cmap_range=(0,1),
n_colors=n_colors,
color_transform=lambda color: (rgb2JCh(hsv_to_rgb(color))[0]/100,)
)
palette_hsb_gray = Palette(
cmap_hsb,
color_model='gray',
cmap_range=(0,1),
n_colors=n_colors,
color_transform=lambda color: (rgb2gray(hsv_to_rgb(color)),)
)
# Create plots to compare the cmaps
plot_color = doc.new(Plot(plot_path=filepath,
plot_name=filename+'_color',
lines='3pt',
height='6cm',
))
plot_lightness = doc.new(Plot(plot_path=filepath,
plot_name=filename+'_lightness',
lines='3pt',
height='6cm',
))
plot_gray = doc.new(Plot(plot_path=filepath,
plot_name=filename+'_gray',
lines='3pt',
height='6cm',
))
def unfold_hue(h):
"""Adds 360 degrees of hue when the hue value is less than the starting value to make sure the plots are continuous."""