ggplot(mtcars, aes(x = mpg,
y = wt,
size = hp,
colour = as.factor(cyl))) +
geom_point() +
theme(legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "bottom")
gives me
How can I produce the legend in a way, where the cyl-label remains vertical and the hp categories are arranged horizontally?
You can individually control legends via guides(...):
ggplot(mtcars, aes(x = mpg,
y = wt,
size = hp,
colour = as.factor(cyl))) +
geom_point() +
theme(legend.direction = "vertical",
legend.box = "horizontal",
legend.position = "bottom") +
guides(size=guide_legend(direction='horizontal'))
Related
Is it possible to plot with ggplot2 3D surface which is presented as (x, y, z)-vector with labeled countour lines?
Desired result is presented below
Surface map with countour lines
This is exactly what the geomtextpath package was built for.
Example copied from ?geomtextpath::geom_textcontour
library(geomtextpath)
#> Loading required package: ggplot2
df <- expand.grid(x = seq(nrow(volcano)), y = seq(ncol(volcano)))
df$z <- as.vector(volcano)
ggplot(df, aes(x, y, z = z)) +
geom_contour_filled(bins = 6, alpha = 0.6) +
geom_textcontour(bins = 6, size = 2.5, padding = unit(0.05, "in")) +
scale_fill_manual(values = terrain.colors(11)) +
theme_classic() +
theme(legend.position = "none")
Created on 2023-01-26 with reprex v2.0.2
I've been trying to change the bars width and I'm using geom_bar (width) but it does not change the bars width, I need to make them more narrow
library(ggplot2)
library(tidyverse)
color_table <- tibble(
Land_cover = c("A", "B", "C", "D"),
Color = c("yellow", "darkgreen", "blue4", "maroon3")
)
df <- data.frame(
name=c("FM_BICEP","FM_NR","FM_TRICEP","FM_H_GRASP1","FM_CS_SPE","FM_MOS_SFL","FM_H_GRASP3*","FM_FS_RET","FM_W_SE3","FM_FS_ABD*","FM_MOS_SAB") ,
value=c(1.7,1.8,1.8,22.0,26.8,27.4,27.9,31.8,33.4,35.8,35.8),
group=c("A","A","A","C","D","A","C","A","B","A","A")
)
df$name <- factor(df$name, levels = df$name)
df$group <- factor(df$group, levels = color_table$Land_cover)
# Barplot
ggplot(df, aes(x=name, y=value,fill = group)) +
geom_bar(stat = "identity", aes(fill=group))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+
scale_fill_manual(values = color_table$Color) + geom_col(width = 0.4)
I recommend you to use geom_col() as you use both x and y axis. It's the same as geom_bar(scale = "identity").
Also, to width work, I moved it to inside the geom_bar() function.
library(ggplot2)
library(tidyverse)
color_table <- tibble(
Land_cover = c("A", "B", "C", "D"),
Color = c("yellow", "darkgreen", "blue4", "maroon3")
)
df <- data.frame(
name=c("FM_BICEP","FM_NR","FM_TRICEP","FM_H_GRASP1","FM_CS_SPE","FM_MOS_SFL","FM_H_GRASP3*","FM_FS_RET","FM_W_SE3","FM_FS_ABD*","FM_MOS_SAB") ,
value=c(1.7,1.8,1.8,22.0,26.8,27.4,27.9,31.8,33.4,35.8,35.8),
group=c("A","A","A","C","D","A","C","A","B","A","A")
)
df$name <- factor(df$name, levels = df$name)
df$group <- factor(df$group, levels = color_table$Land_cover)
# Barplot
ggplot(df, aes(x=name, y=value,fill = group)) +
geom_col(aes(fill=group),
width = 0.4)+
scale_fill_manual(values = color_table$Color)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
Created on 2022-11-19 with reprex v2.0.2
I am plotting pie charts with ggplot2 and succeeded in having the percentage-labels centered in each slice
library(dplyr)
library(ggplot2)
library(ggpubr)
library("readxl")
df <- read_excel("Radiocomp.xlsx")
df$Pattern <- factor(cc$Pattern)
str(cc)
GGO <- ggplot(data=df, aes(x = "", y = GGO, fill = Pattern)) +
geom_bar(stat="identity", color = "white") +
geom_text(aes(label = paste0(GGO, "%")), position = position_stack(vjust = 0.5)) +
coord_polar("y") +
theme_void()
GGO
Pie chart
I try to place the percent-label outside the pie for better readability
Any recommendation?
Thank you
This can be achieved by setting the x aesthetic inside geom_text, e.g. x = 1.6 will put the label just outside of the pie.
library(ggplot2)
library(dplyr)
# example data
mpg1 <- mpg %>%
count(class) %>%
mutate(pct = n / sum(n))
ggplot(mpg1, aes(x = "", y = pct, fill = class)) +
geom_bar(stat = "identity", color = "white") +
geom_text(aes(x = 1.6, label = scales::percent(pct, accuracy = .1)), position = position_stack(vjust = .5)) +
coord_polar("y") +
theme_void()
Created on 2020-06-03 by the reprex package (v0.3.0)
I am drawing different circles with Matplotlib. Each circle has a label, and each label has a colour. What can I do to have a colourmap legend for these different labels?
I have tried a lot of solutions online, including the most naive one by just adding plt.colorbar(), which I will get the error
RuntimeError('No mappable was found to use for colorbar')
Here is my complete code. It's a little bit long. Please note that the key part just starts from if labels is None:. I just include everything for completeness.
def plot_gaussian_circles(loc_list, scale_list, save_path=None, sigma_coe=3, num_to_plot=300, labels=None):
mu_x_max = -float('inf')
mu_y_max = -float('inf')
mu_x_min = float('inf')
mu_y_min = float('inf')
color_idx = 0
rvs = []
lim_loc_list = loc_list[:num_to_plot]
lim_scale_list = scale_list[:num_to_plot]
for a_mu_, a_sigma_ in zip(lim_loc_list, lim_scale_list):
a_mu = a_mu_.squeeze()
a_sigma_ = a_sigma_.squeeze()
if not type(a_sigma_) is np.ndarray:
a_sigma_ = a_sigma_.numpy()
radius = sigma_coe * np.max(a_sigma_)
a_mu_x = a_mu[0]
a_mu_y = a_mu[1]
if (a_mu_x + radius) >= mu_x_max:
mu_x_max = a_mu_x + radius
if (a_mu_x - radius) <= mu_x_min:
mu_x_min = a_mu_x - radius
if (a_mu_y + radius) >= mu_y_max:
mu_y_max = a_mu_y + radius
if (a_mu_y - radius) <= mu_y_min:
mu_y_min = a_mu_y - radius
if labels is None:
rv = plt.Circle(a_mu, radius, fill=False, clip_on=False)
else:
colors = cm.rainbow(np.linspace(0, 1, len(set(labels))))
rv = plt.Circle(a_mu, radius, color=colors[labels[color_idx]], fill=False, clip_on=False)
rvs.append(rv)
color_idx = (color_idx + 1)
fig, ax = plt.subplots()
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
axes = plt.gca()
axes.set_xlim([mu_x_min - 1, mu_x_max + 1])
axes.set_ylim([mu_y_min - 1, mu_y_max + 1])
for rv in rvs:
ax.add_artist(rv)
if not(labels is None):
# plt.legend(colors, list(range(len(set(labels)))))
plt.colorbar()
if save_path is None:
plt.plot()
plt.show()
# plt.savefig('plotcircles_test.png')
else:
plt.savefig(save_path, dpi=200)
The image here is currently what I am getting, while I wish to have a legend of the colormap.
I found doing this will have the colour for the circles. Thanks ImportanceOfBeingErnest's comment for suggesting PatchCollection.
p = PatchCollection(rvs, cmap=cm.jet, alpha=0.4)
p.set_array(labels)
ax.add_collection(p)
fig.colorbar(p, ax=ax)
I am adding a second x-axis to my plot like this:
ax2 = ax.twiny()
offset = 0, -25
new_axisline = ax2.get_grid_helper().new_fixed_axis
ax2.axis["bottom"] = new_axisline(loc="bottom", axes=ax2, offset=offset)
ax2.axis["top"].set_visible(False)
ax2.set_xticks(xticks)
ax2.xaxis.set_major_formatter(ticker.NullFormatter())
ax2.xaxis.set_minor_locator(ticker.FixedLocator(xticks))
ax2.xaxis.set_minor_formatter(ticker.FixedFormatter(xticks_labels))
the problem is I don't know how I can rotate the labels from there.
Also: If I add ticks to my first axis:
plt.xticks(xticks1, xticks1_labels, rotation='vertical')
the rotation argument gets ignored and I don't understand why either.
I have tried
ax2.set_xticklabels(ax2.xaxis.get_minorticklabels(), rotation=45)
but it also has no effect.
Any help would be appreciated.
You can take a look at the complete plotting logic below:
def event_plot(event_list, labels=None, figsize=(16, 9), padding=0.85, grid=False, title=None, colors=None):
fig = plt.figure(figsize=figsize)
ax = SubplotHost(fig, 111)
# ax = fig.add_subplot(111)
fig.add_subplot(ax)
ax.grid(grid)
if title is not None:
ax.set_title(title)
max_end = 0
for i, events in enumerate(event_list):
for event in events:
start = event[0]
end = event[1]
max_end = max(max_end, end)
y = (i, i + padding)
c = 'red' if colors is None else colors[i]
plt.fill_between([start, end], y[0], y2=y[1], color=c, alpha=0.35, linewidth=0.0)
plt.legend(['Recording data available for channel'], loc='upper center')
if labels is not None:
labels_ids = np.asarray(range(len(labels))) + 1
labels_y = labels_ids - 0.5 - (1 - padding) / 2.
plt.yticks(labels_y, labels)
for y in labels_y:
plt.axhline(y, alpha=0.125, color='k', linestyle='--')
return ax, fig
def plot_case_windows(all_records, case_windows, filename_title, filename=None):
channel_event_list = list()
labels = list()
for group_name, group in all_records.channel_groups.items():
[(labels.append(x[0]), channel_event_list.append(x[1])) for x in group.items()]
recording_time = all_records.end - all_records.start
title = 'File: {:s}, recording time: {:d} sec'.format(os.path.basename(filename_title), int(recording_time))
ax1, fig = event_plot(channel_event_list, title=title, labels=labels)
xticksmax = 0
xticksmin = float('Inf')
xticks1 = list()
xticks1_labels = list()
xticks2 = list()
xticks2_labels = list()
for case_win in case_windows:
xticks1.append(int(case_win.start + (case_win.end - case_win.start)/2.))
xticks2.append(case_win.start)
xticksmax = max(xticksmax, case_win.end)
xticksmin = min(xticksmin, case_win.start)
xticks1_labels.append(case_win.name)
xticks2_labels.append(str(case_win.start) + ' s')
plt.axvline(x=case_win.start, color='k', linestyle='--')
plt.axvline(x=case_win.end, color='k', linestyle='--')
xticks2 = (np.asarray(xticks2) - xticksmin) / (xticksmax - xticksmin)
plt.xlim([xticksmin, xticksmax])
ax1.set_xticks(xticks1)
ax1.xaxis.set_major_formatter(ticker.NullFormatter())
ax1.xaxis.set_minor_locator(ticker.FixedLocator(xticks1))
ax1.xaxis.set_minor_formatter(ticker.FixedFormatter(xticks1_labels))
ax2 = ax1.twiny()
offset = 0, -20
new_axisline = ax2.get_grid_helper().new_fixed_axis
ax2.axis["bottom"] = new_axisline(loc="bottom", axes=ax2, offset=offset)
ax2.axis["top"].set_visible(False)
ax2.set_xticks(xticks2)
ax2.xaxis.set_major_formatter(ticker.NullFormatter())
ax2.xaxis.set_minor_locator(ticker.FixedLocator(xticks2))
ax2.xaxis.set_minor_formatter(ticker.FixedFormatter(xticks2_labels))
plt.setp(ax2.xaxis.get_minorticklabels(), rotation=45)
# ax2.set_xticklabels(ax1.xaxis.get_minorticklabels(), rotation=45)
#plt.show()
plt.tight_layout()
if filename:
plt.savefig(filename)