How to create a compact horizontal gauge like for example a thermometer for temperature, barometer for pressure using Matplotlib. The scale of the gauge will be split into ranges; each range denoting high-high, high. low and low-low and a pointer reading the value? Is it possible to create such a gauge in matplotlib?
You could use a colorbar.
For example:
import matplotlib.pyplot as plt
import matplotlib as mpl
fig = plt.figure(figsize=(8, 2))
ax = fig.add_axes([0.1, 0.4, 0.8, 0.2])
bounds = [-20, -10, 0, 10, 20]
labels = ('low-low', 'low', 'high', 'high-high')
cmap = mpl.cm.coolwarm
norm = mpl.colors.Normalize(vmin=bounds[0], vmax=bounds[-1])
cb = mpl.colorbar.ColorbarBase(
ax,
cmap=cmap,
norm=norm,
orientation='horizontal',
boundaries=bounds,
label='temperature (degrees celcius)',
)
for i, label in enumerate(labels):
xpos = float((2*i + 1))/(2*len(labels))
ax.annotate(label, xy=(xpos, 0.5), xycoords='axes fraction', ha='center', va='center')
plt.show()
Which produces something like this:
For more info see these examples in the matplotlib docs.
Related
I am looking for a custom colormap that highlights the center (value of 1) and just has white color at the edges (values of 0 and 2). Ideally there should be a gradient from 1 to [0, 2].
Usual colormaps do the opposite: diverges from center (white at center).
Thanks for your help
You can use the from_list method from LinearSegmentedColormap for this from the matplotlib.colors module.
Here, we give 3 colors as a list (["white", "red", "white"]). This can easily be customised by changing any of those color names.
For example:
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
import numpy as np
cmap = LinearSegmentedColormap.from_list('wrw', ["white", "red", "white"], N=256)
a = np.arange(0, 2, 0.01).reshape(20, 10)
fig, ax = plt.subplots()
p = ax.pcolormesh(a, cmap=cmap, vmin=0, vmax=2)
fig.colorbar(p)
plt.show()
You can create based on availbale colormaps from matplotlib.
from matplotlib.colors import ListedColormap
def show_cmap(ax, cmap):
n = 256
ax.imshow(np.tile(np.arange(n), [int(n*0.20),1]),
cmap=cmap,
interpolation="nearest", aspect="auto")
ax.set_xticks([])
ax.set_yticks([])
ax.set_xticklabels([])
ax.set_yticklabels([])
c1 = plt.cm.Blues(range(0, 128))
c2 = c1[::-1]
c = np.vstack([c1, c2])
cmap = ListedColormap(c)
fig, ax = plt.subplots(1, 1, figsize=(7.2, 7.2))
show_cmap(ax, cmap)
I have
x = array([0., 0.08, 0.12, 0.18, 0.27, 0.42, 0.65])
y = array([0., 0.03758546, 0.06577713, 0.48786205, 0.28553257, 0.09909356, 0.02414922])
I then write
plt.ticklabel_format(useOffset=False)
plt.figure(figsize=(20,10))
plt.xlabel('D/Dmax')
plt.bar(x, y), align = 'edge', tick_label = x, color = 'red', edgecolor = "black")
And I get the following chart. Why is it like this, and how can I make the bars not overlap and distinct like every other bar chart?
As your bars don't have a constant width, you can calculate these widths as the difference between the x-values: np.diff(x). Note that there is one less difference than there are elements in x. To get a width for the last bar (which in theory could be infinite), you can either repeat the next-to-last width, or add an extra x-value to set the rightmost boundary.
from matplotlib import pyplot as plt
import numpy as np
x = np.array([0., 0.08, 0.12, 0.18, 0.27, 0.42, 0.65])
y = np.array([0., 0.03758546, 0.06577713, 0.48786205, 0.28553257, 0.09909356, 0.02414922])
widths = np.pad(np.diff(x), (0, 1), 'edge')
plt.figure(figsize=(20, 10))
plt.xlabel('D/Dmax')
plt.bar(x, y, width=widths, align='edge', tick_label=x, color='red', edgecolor="black")
plt.show()
In this case, a logical extension for x could be to include 1:
from matplotlib import pyplot as plt
import numpy as np
x = np.array([0., 0.08, 0.12, 0.18, 0.27, 0.42, 0.65])
x = np.concatenate([x, [1]])
y = np.array([0., 0.03758546, 0.06577713, 0.48786205, 0.28553257, 0.09909356, 0.02414922])
widths = np.diff(x)
plt.figure(figsize=(20, 10))
plt.xlabel('D/Dmax')
plt.bar(x[:-1], y, width=widths, align='edge', color='red', edgecolor="black")
plt.xticks(x)
plt.show()
Your real x-values are much smaller than the default bar width which makes the bars overlap. You need to use a smaller bar width, for ex. 0.02 which is of the order of your smaller x-value.
plt.bar(x, y, align='edge', tick_label=x, color='red', edgecolor="black",
width=0.02)
In an errorbar matplotlib plot, the main line, the markers and the errorbars of a same color overlap each other on their countour when I use the alpha parameter. Although my goal was to have a transparency between the two different colors, but not within the same color, as if same color lines, markers and errorbars were only one object. Is that possible?
import matplotlib.pyplot as plt
import numpy as np
Time = np.array([1, 2, 3])
Green = np.array([3, 5, 9])
Blue = np.array([4, 7, 13])
Green_StDev = np.array([0.6, 0.6, 0.7])
Blue_StDev = np.array([0.5, 0.5, 0.6])
plt.errorbar(Time, Green, Green_StDev, marker='o', c='green', alpha=0.5)
plt.errorbar(Time, Blue, Blue_StDev, marker='o', c='blue', alpha=0.5)
plt.show()
Like the example below, but with transparency only between different color objects, differently of the example above.
I think you cannot draw them as one single object since they (marker and error bar) are drawn individually. However, to make it more 'aesthetic', you could redraw a non-transparent marker:
import matplotlib.pyplot as plt
import numpy as np
Time = np.array([1, 2, 3])
Green = np.array([3, 5, 9])
Blue = np.array([4, 7, 13])
Green_StDev = np.array([0.6, 0.6, 0.7])
Blue_StDev = np.array([0.5, 0.5, 0.6])
plt.errorbar(Time, Green, Green_StDev, marker='o', c='green', alpha=0.5)
# Add additional marker
plt.scatter(Time, Green,marker='o', c='green')
plt.errorbar(Time, Blue, Blue_StDev, marker='o', c='blue', alpha=0.5)
# Add additional marker
plt.scatter(Time, Blue, marker='o', c='blue')
plt.show()
Dear stackoverflow users,
I want to plot some data labels with its coordinates in a x,y-plot. Around the labels I want to put a circle with a user-defined radius as I want to symbolize the magnitude of the data property by the radius of the circle.
An example dataset could look like the following:
point1 = ["label1", 0.5, 0.25, 1e0] # equals [label, x, y, radius]
point2 = ["label2", 0.5, 0.75, 1e1] # equals [label, x, y, radius]
I want to use a code silimar to the following one:
import matplotlib.pyplot as plt
plt.text(point1[1], point1[2], point1[0], bbox = dict(boxstyle="circle")) # here I want to alter the radius by passing point1[3]
plt.text(point2[1], point2[2], point2[0], bbox = dict(boxstyle="circle")) # here I want to alter the radius by passing point2[3]
plt.show()
Is this possible somehow or is the plt.add_patch variant the only possible way?
Regards
In principle, you can use the boxes' pad parameter to define the circle size. However this is then relative to the label. I.e. a small label would have a smaller circle around it for the same value of pad than a larger label. Also the units of pad are fontsize (i.e. if you have a fontsize of 10pt, a padding of 1 would correspond to 10pt).
import numpy as np
import matplotlib.pyplot as plt
points = [["A", 0.2, 0.25, 0], # zero radius
["long label", 0.4, 0.25, 0], # zero radius
["label1", 0.6, 0.25, 1]] # one radius
for point in points:
plt.text(point[1], point[2], point[0], ha="center", va="center",
bbox = dict(boxstyle=f"circle,pad={point[3]}", fc="lightgrey"))
plt.show()
I don't know in how far this is desired.
I guess usually you would rather create a scatterplot at the same positions as the text
import numpy as np
import matplotlib.pyplot as plt
points = [["A", 0.2, 0.25, 100], # 5 pt radius
["long label", 0.4, 0.25, 100], # 5 pt radius
["label1", 0.6, 0.25, 1600]] # 20 pt radius
data = np.array([l[1:] for l in points])
plt.scatter(data[:,0], data[:,1], s=data[:,2], facecolor="gold")
for point in points:
plt.text(point[1], point[2], point[0], ha="center", va="center")
plt.show()
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)