I'm trying to draw a box on a map in relative coordinates (i.e. 0 to 1). The reason is I have a colorbar on my map, but cannot see it clearly. I want a transparent box behind it. I've looked at adding patch Rectangles (see Draw rectangle (add_patch) in pylab mode), but that is in data coordinates, which is not easy to determine on this map. I also found axhspan, which uses relative coordinates for the x span, but data coordinates for the y span.
Is there a way to draw a box in a matplotlib axes object using relative coordinates?
Here's a way to add a boxed text to a relative coordinates:
#!/usr/bin/python3
from matplotlib import pyplot as plt
x = range(5)
y = range(5)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y)
ax.text(0.5, 0.5,
"Relative coords!",
horizontalalignment = 'center',
backgroundcolor = "white",
verticalalignment = 'center',
bbox=dict(facecolor='white', edgecolor='green', alpha=0.65),
transform = ax.transAxes,
)
fig.savefig("mwe.png")
Result:
Edit:
To draw just a box given it's relative coordinates/dimensions with no text in it:
#!/usr/bin/python3
from matplotlib import pyplot as plt
from matplotlib.patches import Rectangle
x = range(5)
y = range(5)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y, zorder=1)
plt.gca().add_patch(Rectangle(
(0.4, 0.4), # lower left point of rectangle
0.2, 0.2, # width/height of rectangle
transform=ax.transAxes,
facecolor="white",
edgecolor='green',
alpha=0.65,
zorder=2,
))
fig.savefig("mwe.png")
Result:
Related
Question background: In python, I am working on a task in which I have to project the nodes of geometry (X and Y coordinates). I have plotted a graph which shows Geometry and a circle around the geometry as shown in picture below using below code.
from matplotlib import pyplot as plt, patches
plt.rcParams["figure.figsize"] = [9.00, 6.50]
plt.rcParams["figure.autolayout"] = True
fig = plt.figure()
ax = fig.add_subplot()
# other plt.scatter or plt.plot here
plt.scatter(x_new, y_new) # x_new and y_new is a list of coordinates
circle1 = plt.Circle((0, 0), radius=4, fill = False) # (0, 0) is a centre of circle with radius 4
ax.add_patch(circle1)
ax.axis('equal')
plt.show()
My Question: I have to divide the circle into 36 pixels. I do not have clue at the moment what code I should write to do this. I want my result like in the picture below. Kindly help me on this.
Is it possible to set ax.grid in such a way that lines will go just to bars?
Below the regular output("before") and expected("after"):
My code:
fig, ax = plt.subplots(figsize=(15,6))
ax.set_axisbelow(True)
ax = data_test.bar(fontsize=15, zorder=1, color=(174/255, 199/255, 232/255)) # 'zorder' is bar layaut order
for p in ax.patches:
ax.annotate(s=p.get_height(),
xy=(p.get_x()+p.get_width()/2., p.get_height()),
ha='center',
va='center',
xytext=(0, 10),
textcoords='offset points')
ax.spines["right"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.spines["top"].set_visible(False)
ax.spines["bottom"].set_visible(False)
ax.set_xticklabels(
data_test.index,
rotation=34.56789,
fontsize='xx-large'
) # We will set xticklabels in angle to be easier to read)
# The labels are centred horizontally, so when we rotate them 34.56789°
ax.grid(axis='y', zorder=0) # 'zorder' is bar layaut order
plt.ylim([4500, 5300])
plt.show()
You could draw horizontal lines instead of using grid lines.
You forgot to add test data, making it quite unclear of what type data_test could be.
The code below supposes data_test is a pandas dataframe, and that data_test.plot.bar() is called to draw a bar plot. Note that since matplotlib 3.4 you can use ax.bar_label to label bars.
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
data_test = pd.DataFrame({'height': np.random.randint(1000, 2000, 7).cumsum()},
index=['Alkaid', 'Mizar', 'Alioth', 'Megrez', 'Phecda', 'Merak', 'Dubhe'])
fig, ax = plt.subplots(figsize=(15, 6))
ax.set_axisbelow(True)
data_test.plot.bar(fontsize=15, zorder=1, color=(174 / 255, 199 / 255, 232 / 255), ax=ax)
for container in ax.containers:
ax.bar_label(container, fmt='%.0f', fontsize=15)
for spine in ax.spines.values():
spine.set_visible(False)
ax.set_xticklabels(data_test.index, rotation=34.56789, fontsize='xx-large')
ax.tick_params(length=0) # remove tick marks
xmin, xmax = ax.get_xlim()
ticks = ax.get_yticks()
tick_extends = [xmax] * len(ticks)
# loop through the bars and the ticks; shorten the lines whenever a bar crosses it
for bar in ax.patches:
for j, tick in enumerate(ticks):
if tick <= bar.get_height():
tick_extends[j] = min(tick_extends[j], bar.get_x())
ax.hlines(ticks, xmin, tick_extends, color='grey', lw=0.8, ls=':', zorder=0)
plt.tight_layout()
plt.show()
I need to know how can I move the rectangle patch when I click anywhere with the mouse ?
in the code below the rectangle is fixed I just need to move it every time I click with the mouse somewhere ,
import matplotlib.pyplot as plt
import matplotlib.patches as patches
x=y=0.1
fig1 = plt.figure()
ax1 = fig1.add_subplot(111, aspect='equal')
patch= ax1.add_patch(patches.Rectangle((x, y), 0.5, 0.5,
alpha=1, fill=None,label='Label'))
plt.show()
maybe i need to use "motion_notify_event" to connect mouse to rectangle but id'ont know how i can use this function !
my second question is how to get this type of rectangle "selection icon" on the image with matplotlib or if possible to customize the rectangle patch !
thank you in advance
To move the rectangle around you can use a simple function that connects to a "button press event" via fig.canvas.mpl_connect('button_press_event', <function_name>) and re-defines the x, y origin coordinates of the rectangle. I have shifted those by half the width and height of the rectangle, so that the point you click on will be in its centre.
import matplotlib.pyplot as plt
import matplotlib.patches as patches
def on_press(event):
xpress, ypress = event.xdata, event.ydata
w = rect.get_width()
h = rect.get_height()
rect.set_xy((xpress-w/2, ypress-h/2))
ax.lines = []
ax.axvline(xpress, c='r')
ax.axhline(ypress, c='r')
fig.canvas.draw()
x = y = 0.1
fig = plt.figure()
ax = fig.add_subplot(111, aspect='equal')
fig.canvas.mpl_connect('button_press_event', on_press)
rect = patches.Rectangle((x, y), 0.1, 0.1, alpha=1, fill=None, label='Label')
ax.add_patch(rect)
plt.show()
As for the prettyfying of the rectangle, have a look at the
matplotlib patches or the gallery and see if you find something suitable. I have added a crosshair with red lines as an alternative.
I have a subplot with a single legend entry. I am placing the legend at the bottom of the figure and using mode='expand'; however, the single legend entry is placed to the very left of the legend box. To my understanding, changing kwargs such as bbox_to_anchor changes the legend box parameters but not the parameters of the symbols/text within. Below is an example to reproduce my issue.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-10, 10, 21)
y = np.exp(x)
z = x **2
fig, axes = plt.subplots(nrows=1, ncols=2)
axes[0].plot(x, y, color='r', label='exponential')
axes[1].plot(x, z, color='b')
# handles, labels = axes[0].get_legend_handles_labels()
plt.subplots_adjust(bottom=0.125)
fig.legend(mode='expand', loc='lower center')
plt.show()
plt.close(fig)
This code produces . How can I change the position of the symbol and text such that they are centered in the legend box?
PS: I am aware that exponential is a bad label for this subplot since it only describes the first subfigure. But, this is just for examples-sake so that I can apply it to my actual use-case.
The legend entries are placed using a HPacker object. This does not allow to be centered. The behaviour is rather that those HPackers are "justified" (similar to the "justify" option in common word processing software).
A workaround would be to create three (or any odd number of) legend entries, such that the desired entry is in the middle. This would be accomplished via the ncol argument and the use of "dummy" entries (which might be transparent and have no associated label).
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-10, 10, 21)
y = np.exp(x)
z = x **2
fig, axes = plt.subplots(nrows=1, ncols=2)
fig.subplots_adjust(bottom=0.125)
l1, = axes[0].plot(x, y, color='r', label='exponential')
axes[1].plot(x, z, color='b')
dummy = plt.Line2D([],[], alpha=0)
fig.legend(handles=[dummy, l1, dummy],
mode='expand', loc='lower center', ncol=3)
plt.show()
I am trying to plot a scatter plot on a background using basemap. But it's overwriting the background. How do I retain the background?
I am using this code
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
m = Basemap(projection='merc',llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180,lat_ts=20,resolution='c')
m.bluemarble()
x, y = m(list(longitude), list(latitude))
plt.scatter(x,y,1,marker='o',color='Red')
plt.show()
But as soon as I run the scatter plot, its overwriting background image. How can I overlay the scatter plot on the image.
This is how to plot a series of points on top of a raster map. Note that the bluemarble image is huge, so a full scale (1.0 or default) plot of it should be avoided. The code is based on yours.
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
# make up some data for scatter plot
lats = np.random.randint(-75, 75, size=20)
lons = np.random.randint(-179, 179, size=20)
fig = plt.gcf()
fig.set_size_inches(8, 6.5)
m = Basemap(projection='merc', \
llcrnrlat=-80, urcrnrlat=80, \
llcrnrlon=-180, urcrnrlon=180, \
lat_ts=20, \
resolution='c')
m.bluemarble(scale=0.2) # full scale will be overkill
m.drawcoastlines(color='white', linewidth=0.2) # add coastlines
x, y = m(lons, lats) # transform coordinates
plt.scatter(x, y, 10, marker='o', color='Red')
plt.show()
The resulting plot:
I realize it's an old question but in case anyone comes here with the same problem as I did.
The trick is to give a higher zorder for the scatter plot than for the .bluemarble().
m.scatter(x, y, 10, marker='o', color='Red', zorder=3)
More info here: https://matplotlib.org/3.1.0/gallery/misc/zorder_demo.html
I'm not entirely sure what you mean by "overwriting the background". When you use plt.scatter(), it will plot the points over the map, so it will display the points over the background.
Just based off the code provided, I think you're issue here is m(list(longitude), list(latitude)).
If you have multiple points in a list, you want to loop over them.
lats = [32, 38, 35]
lons = [-98, -79, -94]
x, y = m(lons, lats)
for i in range(len(lats)):
plt.scatter(x, y, marker = 'o')
If it's only one single point,
lat, lon = 32, -92
x, y = m(lon, lat)
plt.scatter(x, y, marker = 'o')
The styling of the points can be found in the matplotlib documentation.