i have this several plots and want to correct the title name location. I want to make the Vertical Acceleration (y) on the middle left vertically and the Flare Time (x) on the middle bot horizontally also the Test Title on middle top. Basically I want to be able to move the label location.
Below is the code
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import NullFormatter
x = ip.RESULTS
y = Vert
xy = np.vstack([x,y])
z = gaussian_kde(xy)(xy)
idx = z.argsort()
x, y, z = x[idx], y[idx], z[idx]
nullfmt = NullFormatter() # no labels
# definitions for the axes
left, width = 0.1, 0.65
bottom, height = 0.1, 0.65
bottom_h = left_h = left + width + 0.02
rect_scatter = [left, bottom, width, height]
rect_histx = [left, bottom_h, width, 0.2]
rect_histy = [left_h, bottom, 0.2, height]
# start with a rectangular Figure
plt.figure(1, figsize=(8, 8))
axScatter = plt.axes(rect_scatter)
#plt.plot(np.unique(x), np.poly1d(np.polyfit(x, y, 1))(np.unique(x)))
#plt.plot(np.unique(x), np.poly1d(np.polyfit(x, y, 1))(np.unique(x)))
axHistx = plt.axes(rect_histx)
axHisty = plt.axes(rect_histy)
# no labels
axHistx.xaxis.set_major_formatter(nullfmt)
axHisty.yaxis.set_major_formatter(nullfmt)
# the scatter plot:
axScatter.scatter(x, y, c=z, s=50, edgecolor='')
# now determine nice limits by hand:
binwidth = 1
xymax = np.max([np.max(np.fabs(x)), np.max(np.fabs(y))])
lim = (int(xymax/binwidth) + 1) * binwidth
bins = np.arange(-lim, lim + binwidth, binwidth)
axHistx.hist(x)
axHisty.hist(y, orientation='horizontal')
plt.title('test title', fontsize=20)
axHisty.set_xlabel("Vertical Acceleration")
axHistx.set_xlabel("Flare Time")
and the results look like this. Any help would be appreciated
You have three Axes objects (plot rectangles to say it sloppy) in your graph: axScatter is your main chart in the bottom left. axHisty is the histogram on the right and axHistx is the histogram on the top. Your axis titles belong on the y- and x-axis of axScatter. So just do:
axScatter.set_ylabel('Vertical Acceleration')
axScatter.set_xlabel('Flare Time')
Based on your vague question I have no idea where you want the "test title", but just figure out which Axes object is best and give it an xlabel, ylabel or title.
When I make figure with 5 subplots and annotate the bars in each subplot, matplotlib appears to scale the figure so that the maximum from the largest y-axis scales to the smallest y-axis.
I can't describe the problem too well, but see this image:
where there's tons of white-space above where the figure should begin.
However, the figure would ideally look like this
When I set the 4 smallest axes to have the same upper y-limit as the largest axis, then the figure scales correctly, but for the purpose of the visualization, I would prefer not to do that.
Why does this happen? Is there anyway to control the figure so that it's not automatically scaled as in the first image? Or otherwise, a more appropriate way of plotting what I hope to achieve?
The code I'm using to generate the figure:
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.patches import Patch
from matplotlib import rcParams
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Arial']
department = ["100", "1,000", "10,000", \
"100,000", "1,000,000"]
quarter = ["Serial", "MPI", "CUDA", "Hybrid"]
budgets = np.array([[0.049979, 0.43584, 2.787366, 19.75062, 201.6935],\
[2.184624, 0.175213, 0.677837, 5.265575, 46.33678],\
[0.050294, 0.068537, 0.23739, 1.93778, 18.55734],\
[3.714284, 3.9917, 4.977599, 6.174967, 37.732232]])
budgets = np.transpose(budgets)
em = np.zeros((len(department), len(quarter)))
# set up barchart
x = np.arange(len(department)) # label locations
width = 0.8 # width of all the bars
# set up figure
fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots(1, 5)
axes = [ax1, ax2, ax3, ax4, ax5]
# generate bars
rects = []
color = ["tomato", "royalblue", "limegreen", "orange"]
n = len(quarter)
for i in range(n):
bar_x = x - width/2.0 + i/float(n)*width + width/(n*2)
m = len(budgets[:,i])
for j in range(m):
bar_x = x[j] - width/2.0 + i/float(n)*width + width/(n*2)
e = budgets[j,i]
#bar_x = x - width/2.0 + i/float(n)*width + width/(n*2)
rects.append(axes[j].bar(bar_x, e, width=width/float(n), \
label=quarter[i], color=color[i]))
# set figure properties
fig.set_size_inches(12, 2.5)
fig.tight_layout(rect=[0, 0.03, 1, 0.95])
nAx = len(axes)
for i in range(nAx):
#axes[i].set_aspect("auto")
axes[i].tick_params(axis='x', which='both', bottom=False, top=False,
labelbottom=False)
ax1.set_ylabel("Time (ms)")
for i in range(nAx):
axes[i].yaxis.grid(which="major", color="white", lw=0.75)
ax1.set_ylim([0, 4])
fig.suptitle("Time per iteration for differing dataset sizes") # title
for i in range(nAx):
axes[i].set_xlabel(department[i])
# annotate bars
for i in range(nAx):
for rect in rects:
j = 0;
for bar in rect:
y_bottom, y_top = axes[i].get_ylim() # axis limits
height = bar.get_height() # bar's height
va = 'bottom'
offset = 3
color = 'k'
fg = 'w'
# keep label within plot
if (y_top < 1.1 * height):
offset = -3
va = 'top'
color='w'
fg = 'k'
# annotate the bar
axes[i].annotate('{:.2f}'.format(height),
xy=(bar.get_x() + bar.get_width()/2, height),
xytext=(0,offset),
textcoords="offset points",
ha='center', va=va, color=color)
# set custom legend
legend_elements = [Patch(facecolor='tomato', label='Serial'),
Patch(facecolor='royalblue', label='MPI'),
Patch(facecolor='limegreen', label='CUDA'),
Patch(facecolor='orange', label='Hybrid')]
plt.legend(handles=legend_elements, loc="upper center", fancybox=False,
edgecolor='k', ncol=4, bbox_to_anchor=(-2, -0.1))
plt.show()
This is a partial answer.
This might be a bug, since I couldn't reproduce the problem until I switched to a Jupyter notebook in a Debian system (different hardware too). Your figure gets drawn correctly in my macOS Jupyter notebook, and in Debian when displayed from a .py script.
The problem appears to be with your annotations. If you make the tight_layout call after annotation, you might get a warning like this:
<ipython-input-80-f9f592f5efc5>:88: UserWarning: Tight layout not applied. The bottom and top margins cannot be made large enough to accommodate all axes decorations.
fig.tight_layout(rect=[0, 0.03, 1, 0.95])
It seems like the annotate function is calculating some totally wacky coordinates for your annotations, though the text ends up in the right spot. If you remove them, the white space disappears. You can try calculating the xy coordinates a for your annotations a different way. This might get you started:
axes[i].annotate('{:.2f}'.format(height),
xy=(bar.get_x() + bar.get_width()/2, height),
xytext=(0,offset),
textcoords="offset points",
xycoords="axes points", # change
ha='center', va=va, color=color)
Output:
To correctly calculate the points, you can try using the appropriate axis transformation, though again, I couldn't get it to work and it might be related to a bug.
try putting the fig.tight_layout(rect=[0, 0.03, 1, 0.95]) after all the plotting commands, as below.
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.patches import Patch
from matplotlib import rcParams
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Arial']
department = ["100", "1,000", "10,000", \
"100,000", "1,000,000"]
quarter = ["Serial", "MPI", "CUDA", "Hybrid"]
budgets = np.array([[0.049979, 0.43584, 2.787366, 19.75062, 201.6935],\
[2.184624, 0.175213, 0.677837, 5.265575, 46.33678],\
[0.050294, 0.068537, 0.23739, 1.93778, 18.55734],\
[3.714284, 3.9917, 4.977599, 6.174967, 37.732232]])
budgets = np.transpose(budgets)
em = np.zeros((len(department), len(quarter)))
# set up barchart
x = np.arange(len(department)) # label locations
width = 0.8 # width of all the bars
# set up figure
fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots(1, 5)
axes = [ax1, ax2, ax3, ax4, ax5]
# generate bars
rects = []
color = ["tomato", "royalblue", "limegreen", "orange"]
n = len(quarter)
for i in range(n):
bar_x = x - width/2.0 + i/float(n)*width + width/(n*2)
m = len(budgets[:,i])
for j in range(m):
bar_x = x[j] - width/2.0 + i/float(n)*width + width/(n*2)
e = budgets[j,i]
#bar_x = x - width/2.0 + i/float(n)*width + width/(n*2)
rects.append(axes[j].bar(bar_x, e, width=width/float(n), \
label=quarter[i], color=color[i]))
# set figure properties
fig.set_size_inches(12, 2.5)
#fig.tight_layout(rect=[0, 0.03, 1, 0.95])
nAx = len(axes)
for i in range(nAx):
#axes[i].set_aspect("auto")
axes[i].tick_params(axis='x', which='both', bottom=False, top=False,
labelbottom=False)
ax1.set_ylabel("Time (ms)")
for i in range(nAx):
axes[i].yaxis.grid(which="major", color="white", lw=0.75)
ax1.set_ylim([0, 4])
fig.suptitle("Time per iteration for differing dataset sizes") # title
for i in range(nAx):
axes[i].set_xlabel(department[i])
# annotate bars
for i in range(nAx):
for rect in rects:
j = 0;
for bar in rect:
y_bottom, y_top = axes[i].get_ylim() # axis limits
height = bar.get_height() # bar's height
va = 'bottom'
offset = 3
color = 'k'
fg = 'w'
# keep label within plot
if (y_top < 1.1 * height):
offset = -3
va = 'top'
color='w'
fg = 'k'
# annotate the bar
axes[i].annotate('{:.2f}'.format(height),
xy=(bar.get_x() + bar.get_width()/2, height),
xytext=(0,offset),
textcoords="offset points",
ha='center', va=va, color=color)
# set custom legend
legend_elements = [Patch(facecolor='tomato', label='Serial'),
Patch(facecolor='royalblue', label='MPI'),
Patch(facecolor='limegreen', label='CUDA'),
Patch(facecolor='orange', label='Hybrid')]
plt.legend(handles=legend_elements, loc="upper center", fancybox=False,
edgecolor='k', ncol=4, bbox_to_anchor=(-2, -0.1))
fig.tight_layout(rect=[0, 0.03, 1, 0.95])
plt.show()
Right now I can create a radarchart as follows. Note that I made it a function just so that I can simply insert the function into my larger scatterplot more cleanly.
Radar Chart
def radarChart(PlayerLastName):
playerdf = dg.loc[dg['Player Name'] == name].index.tolist()[0]
#print(playerdf)
labels=np.array(['SOG', 'SH', 'G', 'A'])
stats=dg.loc[playerdf,labels].values
#print(stats)
# Set the angle of polar axis.
# And here we need to use the np.concatenate to draw a closed plot in radar chart.
angles=np.linspace(0, 2*np.pi, len(labels), endpoint=False)
# close the plot
stats=np.concatenate((stats,[stats[0]]))
angles=np.concatenate((angles,[angles[0]]))
fig = plt.figure()
ax = fig.add_subplot(111, polar=True)
ax.plot(angles, stats, 'o-', linewidth=1)
ax.fill(angles, stats, alpha=0.3)
ax.set_thetagrids(angles * 180/np.pi, labels)
#plt.title(PlayerLastName + ' vs. ' + namegame)
ax.grid(True)
return
I then want to put this figure in the bottom right of my scatter plot I have elsewhere. This other article does not provide me with any way to do this since my plot is circular. Any help would be great!
When I call radarChart('someones name') I get
I would really like to not have to save it as an image first and then put it in the plot.
I am not sure, what your desired output is. You should always provide a Minimal, Complete, and Verifiable example. Apart from this, I don't know, why a polar plot would be different from any other plot to create an inset:
import matplotlib.pyplot as plt
import numpy as np
#function for the polar plot
def radarChart(Player = "SOG", left = .3, bottom = .6, width = .2, height = .2):
#labels and positions
labels = np.array(['SOG', 'SH', 'G', 'A'])
angles = np.linspace(0, 360, len(labels), endpoint = False)
#inset position
ax = plt.axes([left, bottom, width, height], facecolor = "lightblue", polar = True)
#label polar chart
ax.set_thetagrids(angles, labels)
#polar chart title
plt.title(Player, loc = "left")
return ax
#main figure
x = np.linspace (-3, 1, 1000)
y = 2 * np.exp(3 - x) - 1
plt.plot(x, y)
plt.xlabel("x values")
plt.ylabel("y values")
plt.title("figure with polar insets")
#inset 1
ax = radarChart(Player = "A")
plt.scatter(x[::50], y[::50])
#inset 2
ax = radarChart(left = .6, bottom = .4, width = .2, height = .2)
plt.plot(x, y)
plt.show()
Sample output:
This question already has answers here:
Aligning rotated xticklabels with their respective xticks
(5 answers)
Closed 4 months ago.
I am making a bar chart and I want to move the x-axis tick labels one position to left. Here is the code of the plot:
matplotlib.rcParams.update(matplotlib.rcParamsDefault)
plt.style.use(['seaborn-white', 'bmh'])
fig1, ax = plt.subplots()
palette = ['#2a5495', '#07a64c', '#e979ad', '#d88432', '#2a5495',
'#b7040e', '#82c5db', '#b9c09b', '#cd065d', '#4b117f']
x = np.array(df.index)
y = np.array(df.loc[:, 2015])
width = 1.0
lefts = [x * width for x, _ in enumerate(y)]
ax.bar(left = lefts, height = y, width = width, tick_label = x, color = palette, label = ranked_univs)
ax.axis(ymin = 0, ymax = 200, xmin = -0.5, xmax = 9.5)
ax.tick_params(axis='x', which='major', labelsize=8)
ax.set_xticklabels(ax.xaxis.get_majorticklabels(), rotation=45)
fig1.tight_layout()
plt.show()
And here is the bar chart:
Any clue?
Your labels are correctly positioned, as shown by the fact that if you were to rotate them 90°, they would be perfectly aligned with your bars.
fig1, ax = plt.subplots()
palette = ['#2a5495', '#07a64c', '#e979ad', '#d88432', '#2a5495',
'#b7040e', '#82c5db', '#b9c09b', '#cd065d', '#4b117f']
labels = ['Long misaligned label {}'.format(i) for i in range(10)]
x = range(10)
y = 100+100*np.random.random((10,))
width = 1.0
lefts = [x * width for x, _ in enumerate(y)]
ax.bar(left = lefts, height = y, width = width, tick_label = labels, color = palette)
ax.axis(ymin = 0, ymax = 200, xmin = -0.5, xmax = 9.5)
ax.tick_params(axis='x', which='major', labelsize=8)
ax.set_xticklabels(ax.xaxis.get_majorticklabels(), rotation=90)
fig1.tight_layout()
plt.show()
The problem is that the labels are centered horizontally, so when you rotate them 45°, they appear to be aligned with the wrong bar. To fix this, align the labels to the right, and they'll get back to their correct (visual) position.
plt.setp(ax.xaxis.get_majorticklabels(), ha='right')
Another (maybe simpler) option is to use the helper function Figure.autofmt_xdate(), which handles all of this for you.
See this question: How can I rotate xticklabels in matplotlib so that the spacing between each xticklabel is equal?
There the solution is to align the labels to their right side:
ax.set_xticklabels(xticklabels, rotation = 45, ha="right")