I have been following the example provided in:
https://matplotlib.org/examples/api/barchart_demo.html
My problem is that I want to add edges to the bars. But when I set the
linewidth=1, edgecolor='black'
parameters, the edges are only applied to the first pair of bars, leaving the remaining pairs unchanged.
"""
========
Barchart
========
A bar plot with errorbars and height labels on individual bars
"""
import numpy as np
import matplotlib.pyplot as plt
N = 5
men_means = (20, 35, 30, 35, 27)
men_std = (2, 3, 4, 1, 2)
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars
fig, ax = plt.subplots()
rects1 = ax.bar(ind, men_means, width, color='r', yerr=men_std,linewidth=1, edgecolor='black')
women_means = (25, 32, 34, 20, 25)
women_std = (3, 5, 2, 3, 3)
rects2 = ax.bar(ind + width, women_means, width, color='y', yerr=women_std, linewidth=1, edgecolor='black')
# add some text for labels, title and axes ticks
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind + width / 2)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))
ax.legend((rects1[0], rects2[0]), ('Men', 'Women'))
def autolabel(rects):
"""
Attach a text label above each bar displaying its height
"""
for rect in rects:
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
'%d' % int(height),
ha='center', va='bottom')
autolabel(rects1)
autolabel(rects2)
plt.show()
Thanks for your help.
David.
Related
I need to set the dimension of a chart exactly. I tried this, but the result is not what I expected (both if I set px and cm). In addiction, I would like to know how to export correctly the image.
import numpy as np
plt.rcParams['figure.dpi']=100
# create data
x = ['A', 'B', 'C', 'D']
y1 = np.array([10, 20, 10, 30])
y2 = np.array([20, 25, 15, 25])
y3 = np.array([12, 15, 19, 6])
y4 = np.array([10, 29, 13, 19])
# plot bars in stack manner
cm = 1/2.54 # centimeters in inches
px = 1/plt.rcParams['figure.dpi'] # pixel in inches
plt.figure(figsize=(800*px,1000*px))
plt.bar(x, y1, color='r')
plt.bar(x, y2, bottom=y1, color='b')
plt.bar(x, y3, bottom=y1+y2, color='y')
plt.bar(x, y4, bottom=y1+y2+y3, color='g')
plt.xlabel("Teams")
plt.ylabel("Score")
plt.legend(["Round 1", "Round 2", "Round 3", "Round 4"])
plt.title("Scores by Teams in 4 Rounds")
plt.show()
Dimensions expected: 800px x 1000 px, dpi= 100
I attach here a screenshot from Photoshop of the exported image
Not correct dimensions!
The Figure constructor accepts a tuple (numbers in inches) with a default of 80 dpi. You'll want to pass a dpi argument to change this
from matplotlib.figure import Figure
fig = Figure(figsize=(5, 4), dpi=80)
The above is 5 inches by 4 inches at 80dpi, which is 400px by 320px
if you want 800 by 1000 you can do
fig = Figure(figsize=(8, 10), dpi=100)
Exporting an image is as simple as
fig.savefig("MatPlotLib_Graph.png", dpi = 100)
I want to have multiple pie charts in a grid.
Each pie chart will have a different number of wedges, values, and labels.
The code below shows multiple labels in one pie chart.
Is there a way to label each wedge of pie-charts in this grid?
import matplotlib.pyplot as plt
import numpy as np
def heatmap_with_circles(data_array,row_labels,column_labels,ax=None, cmap=None, norm=None, cbar_kw={}, cbarlabel="", **kwargs):
for row_index, row in enumerate(row_labels,0):
for column_index, column in enumerate(column_labels,0):
print('row_index: %d column_index: %d' %(row_index,column_index))
if row_index==0 and column_index==0:
colors=['indianred','orange','gray']
values=[10,20,30]
else:
values=[45,20,38]
colors=['pink','violet','green']
wedges, text = plt.pie(values,labels=['0', '2', '3'],labeldistance = 0.25,colors=colors)
print('len(wedges):%d wedges: %s, text: %s' %(len(wedges), wedges, text))
radius = 0.45
[w.set_center((column_index,row_index)) for w in wedges]
[w.set_radius(radius) for w in wedges]
# We want to show all ticks...
ax.set_xticks(np.arange(data_array.shape[1]))
ax.set_yticks(np.arange(data_array.shape[0]))
fontsize=10
ax.set_xticklabels(column_labels, fontsize=fontsize)
ax.set_yticklabels(row_labels, fontsize=fontsize)
#X axis labels at top
ax.tick_params(top=True, bottom=False,labeltop=True, labelbottom=False,pad=5)
plt.setp(ax.get_xticklabels(), rotation=55, ha="left", rotation_mode="anchor")
# We want to show all ticks...
ax.set_xticks(np.arange(data_array.shape[1]+1)-.5, minor=True)
ax.set_yticks(np.arange(data_array.shape[0]+1)-.5, minor=True)
ax.grid(which="minor", color="black", linestyle='-', linewidth=2)
ax.tick_params(which="minor", bottom=False, left=False)
data_array=np.random.rand(3,4)
row_labels=['Row1', 'Row2', 'Row3']
column_labels=['Column1', 'Column2', 'Column3','Column4']
fig, ax = plt.subplots(figsize=(1.9*len(column_labels),1.2*len(row_labels)))
ax.set_aspect(1.0)
ax.set_facecolor('white')
heatmap_with_circles(data_array,row_labels,column_labels, ax=ax)
plt.tight_layout()
plt.show()
After updating heatmap_with_circles
def heatmap_with_circles(data_array,row_labels,column_labels,ax=None, cmap=None, norm=None, cbar_kw={}, cbarlabel="", **kwargs):
labels = ['x', 'y', 'z']
for row_index, row in enumerate(row_labels,0):
for column_index, column in enumerate(column_labels,0):
print('row_index: %d column_index: %d' %(row_index,column_index))
if row_index==0 and column_index==0:
colors=['indianred','orange','gray']
values=[10,20,30]
else:
values=[45,20,38]
colors=['pink','violet','green']
# wedges, texts = plt.pie(values,labels=['0', '2', '3'],labeldistance = 0.45,colors=colors)
wedges, texts = plt.pie(values,labeldistance = 0.25,colors=colors)
print('text:%s len(wedges):%d wedges: %s' %(texts, len(wedges), wedges))
radius = 0.45
[w.set_center((column_index,row_index)) for w in wedges]
[w.set_radius(radius) for w in wedges]
[text.set_position((text.get_position()[0]+column_index,text.get_position()[1]+row_index)) for text in texts]
[text.set_text(labels[text_index]) for text_index, text in enumerate(texts,0)]
I got the following image :)
You could loop through the texts of each pie, get its xy position, add column_index and row_index, and set that as new position.
Some small changes to the existing code:
ax.grid(which="minor", ..., clip_on=False) to make sure the thick lines are shown completely, also near the border
ax.set_xlim(xmin=-0.5) to set the limits
import matplotlib.pyplot as plt
import numpy as np
def heatmap_with_circles(data_array, row_labels, column_labels, ax=None):
ax = ax or plt.gca()
for row_index, row in enumerate(row_labels, 0):
for column_index, column in enumerate(column_labels, 0):
colors = np.random.choice(['indianred', 'orange', 'gray', 'pink', 'violet', 'green'], 3, replace=False)
values = np.random.randint(10, 41, 3)
wedges, text = plt.pie(values, labels=['1', '2', '3'], labeldistance=0.25, colors=colors)
radius = 0.45
for w in wedges:
w.set_center((column_index, row_index))
w.set_radius(radius)
w.set_edgecolor('white')
# w.set_linewidth(1)
for t in text:
x, y = t.get_position()
t.set_position((x + column_index, y + row_index))
# We want to show all ticks...
ax.set_xticks(np.arange(data_array.shape[1]))
ax.set_yticks(np.arange(data_array.shape[0]))
fontsize = 10
ax.set_xticklabels(column_labels, fontsize=fontsize)
ax.set_yticklabels(row_labels, fontsize=fontsize)
# X axis labels at top
ax.tick_params(top=True, bottom=False, labeltop=True, labelbottom=False, pad=5)
plt.setp(ax.get_xticklabels(), rotation=55, ha="left", rotation_mode="anchor")
# We want to show all minor ticks...
ax.set_xticks(np.arange(data_array.shape[1] + 1) - .5, minor=True)
ax.set_yticks(np.arange(data_array.shape[0] + 1) - .5, minor=True)
ax.set_xlim(xmin=-.5)
ax.set_ylim(ymin=-.5)
ax.grid(which="minor", color="black", linestyle='-', linewidth=2, clip_on=False)
ax.tick_params(axis="both", which="both", length=0) # hide tick marks
data_array = np.random.rand(3, 4)
row_labels = ['Row1', 'Row2', 'Row3']
column_labels = ['Column1', 'Column2', 'Column3', 'Column4']
fig, ax = plt.subplots(figsize=(1.9 * len(column_labels), 1.2 * len(row_labels)))
ax.set_aspect(1.0)
ax.set_facecolor('white')
heatmap_with_circles(data_array, row_labels, column_labels, ax=ax)
plt.tight_layout()
plt.show()
I am applying this strategy to place legend outside plot. The main difference here is that there are ax1 and ax2 twin axes.
The x value in bbox_to_anchor is set to 0.89 in the following MWE.
As can be seen, the legend box does not display the entire string labels for each color:
MWE:
import matplotlib.pyplot as plt
import numpy as np
suptitle_label = "rrrrrrrr # ttttt yyyyyyy. uuuuuuuuuuuuuuuuuu\n$[$Xx$_{2}$Yy$_{7}]^{-}$ + $[$XxYy$_{2}$(cccc)$_{2}]^{+}$ JjYy model"
# Plotting
fig, ax1 = plt.subplots()
ax1.set_xlabel('Time')
ax1.set_ylabel('y1label')
new_time = np.linspace(1, 8, 100)
j_data = [np.linspace(1, 4, 100), np.linspace(1, 5, 100), np.linspace(1, 6, 100), np.linspace(1, 7, 100)]
sorted_new_LABELS_fmt = ['$[$XxYy$_{2}$(cc)$_{2}]^{+}$', '$[$Xx$_{2}$Yy$_{7}]^{-}$', '$[$XxYy$_{4}]^{-}$', '$[$Xx$_{2}$Yy$_{5}$(cc)$_{2}]^{+}$']
sorted_new_LABELS_colors = ['green', 'red', 'blue', 'orange']
for j,k,c in zip(j_data, sorted_new_LABELS_fmt, sorted_new_LABELS_colors):
ax1.plot(new_time, j, label='%s' % k, color='%s' %c)
All_e_chunks_n = np.linspace(-850, -860, 100)
ax2 = ax1.twinx()
ax2.set_ylabel('y2label')
ax2.plot(new_time, All_e_chunks_n, 'grey', alpha=0.6, linewidth=2.5, label='y2')
# Shrink cccrent axis
box = ax1.get_position()
ax1.set_position([box.x0, box.y0, box.width * 0.9, box.height])
# Put the legend:
fig.legend(loc='center left', bbox_to_anchor=(0.89, 0.5))
fig.suptitle(suptitle_label, fontsize=15)
fig.savefig('mwe.pdf', bbox_inches='tight')
Decreasing this x value and commenting out thebbox_inches='tight' part, yields the following:
For bbox_to_anchor=(0.85, 0.5), this is the result:
For bbox_to_anchor=(0.80, 0.5), this is the result:
For bbox_to_anchor=(0.7, 0.5), this is the result:
I have a subplot and its tick labels overlap with the data. I would like to set the x-tick labels to have a background colour (e.g. white). Currently I have only been able to find how to change the label's colour, but not the background. I know how to get the effect using a text object as shown below. (NB - I don't want the whole subplot's margin to be coloured, but just the tick label).
MWE
import matplotlib as mpl
rc_fonts = {
"text.usetex": True,
'text.latex.preview': True,
"font.size": 50,
'mathtext.default': 'regular',
'axes.titlesize': 55,
"axes.labelsize": 55,
"legend.fontsize": 50,
"xtick.labelsize": 50,
"ytick.labelsize": 50,
'figure.titlesize': 55,
'figure.figsize': (10, 6.5), # 15, 9.3
'text.latex.preamble': [
r"""\usepackage{lmodern,amsmath,amssymb,bm,physics,mathtools,nicefrac,letltxmacro,fixcmex}
"""],
"font.family": "serif",
"font.serif": "computer modern roman",
}
mpl.rcParams.update(rc_fonts)
import matplotlib.pylab as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes, InsetPosition, mark_inset
from numpy import linspace, sin
x = linspace(0, 1, 100)
plt.clf()
ax1 = plt.gca()
ax2 = plt.axes([0, 0, 1, 1], label=str(2))
ip = InsetPosition(ax1, [0.08, 0.63, 0.45, 0.3])
ax2.set_axes_locator(ip)
ax1.plot(x, x)
ax1.plot(x, x + 0.3)
ax1.set_xlim(0, 1)
ax1.set_ylim(0, 1)
ax2.xaxis.set_tick_params(labelcolor='r')
ax1.text(0.3, 0.3, '$1$', transform=ax1.transAxes, horizontalalignment='center', verticalalignment='center', color='black', backgroundcolor='white')
To set a label's background color you may use the same property as for a text, essentially because a label is a text.
plt.setp(ax2.get_xticklabels(), backgroundcolor="limegreen")
For more sophisticated backgrounds, you could also use the bbox property.
bbox = dict(boxstyle="round", ec="limegreen", fc="limegreen", alpha=0.5)
plt.setp(ax2.get_xticklabels(), bbox=bbox)
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()
ax.plot(np.linspace(0, 1, 5), np.random.rand(5))
# set xticklabels
xtl = []
for x in ax.get_xticks():
xtl += ['lbl: {:.1f}'.format(x)]
ax.set_xticklabels(xtl)
# modify labels
for tl in ax.get_xticklabels():
txt = tl.get_text()
if txt == 'lbl: 1.0':
txt += ' (!)'
tl.set_backgroundcolor('C3')
tl.set_text(txt)
I have a pyplot code.
Since I want to group multiple bars, I am trying to write text in the graph using plt.annotate.
However, as you can see in the picture, the word 'Something' in left bottom gets cropped. Does anyone know How I can fix this?
Here is my code
#!/usr/bin/python
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import operator as o
import numpy as np
n_groups = 5
means_men = (20, 35, 30, 35, 27)
std_men = (2, 3, 4, 1, 2)
means_women = (25, 32, 34, 20, 25)
std_women = (3, 5, 2, 3, 3)
fig, ax = plt.subplots()
index = np.arange(n_groups)
bar_width = 0.35
opacity = 0.4
error_config = {'ecolor': '0.3'}
rects1 = plt.bar(index, means_men, bar_width, alpha=opacity, color='b', yerr=std_men, error_kw=error_config, label='Men')
rects2 = plt.bar(index + bar_width, means_women, bar_width,
alpha=opacity,
color='r',
yerr=std_women,
error_kw=error_config,
label='Women')
#plt.xlabel('Group')
plt.ylabel('Scores')
plt.title('Scores by group and gender')
plt.annotate('Something', (0,0), (50,-40), xycoords = 'axes fraction', textcoords='offset points', va='top');
plt.annotate('Something', (0,0), (200,-20), xycoords = 'axes fraction', textcoords='offset points', va='top');
plt.xticks(index + bar_width, ('A', 'B', 'C', 'D', 'E'))
plt.legend()
plt.savefig('barchart_3.png')
For some reason, matplotlib sometimes clips too aggressively. If you add bbox_inches='tight' to save fig this should include the figure correctly,
plt.savefig('barchart_3.png', bbox_inches='tight')
More generally, you can adjust your main figure with something like,
plt.subplots_adjust(bottom=0.1)