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Various Julia plotting examples using PyPlot
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Plot_Examples.md

Plotting

Last Update: 12.12.2014
Offline Version

Contents

PyPlot

Translating

Translating PyPlot code from Python to Julia can be difficult so here are a few examples comparing Python code with its Julia equivalent.

# Python
ax.set_ylim([-30, 10])
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

Source: Axis Boundary Color

# Julia
ax[:set_ylim]([-30,10])
ax[:spines]["top"][:set_color]("none") # Remove the top axis boundary
ax[:spines]["right"][:set_color]("none") # Remove the right axis boundary

The above example looked at settings of plot components. The next example will call matplotlib itself.

# Python
from matplotlib.dates import MonthLocator, WeekdayLocator, DateFormatter
majorformatter = DateFormatter("%d.%m.%Y")
minorformatter = DateFormatter("%H:%M")
majorlocator = DayLocator(interval=1)
minorlocator = HourLocator(byhour=(8,16)) # Not sure about this one

Source: Modified from this forum post by Nat Wilson and this matplotlib example.

# Julia
majorformatter = matplotlib[:dates][:DateFormatter]("%d.%m.%Y")
minorformatter = matplotlib[:dates][:DateFormatter]("%H:%M")
majorlocator = matplotlib[:dates][:DayLocator](interval=1)
minorlocator = matplotlib[:dates][:HourLocator](byhour=(8, 16))

# After an axis exists
ax1[:xaxis][:set_major_formatter](majorformatter)
ax1[:xaxis][:set_minor_formatter](minorformatter)
ax1[:xaxis][:set_major_locator](majorlocator)
ax1[:xaxis][:set_minor_locator](minorlocator)

--

Basic Plot

Most of the basic commands in PyPlot are very similar to Matlab.

p = plot(x,y)
xlabel("X")
ylabel("Y")
title("Your Title Goes Here")
grid("on")

The first noticable change is in the plotting command when non-default values are used.

p = plot_date(x,y,linestyle="-",marker="None",label="Base Plot") # Basic line plot

Instead of "linesteyle","-" it uses linestyle="-" for parameters.

--

Plot Annotation

(IJulia, Code)

Annotation Examples

The following command will point an arrow at a point and label the arrow.

annotate("Look, data!",
	xy=[x;y,# Arrow tip
	xytext=[x+dx;y+dy], # Text offset from tip
	xycoords="data", # Coordinates in in "data" units
	arrowprops=["facecolor"=>"black"]) # Julia dictionary objects are automatically converted to Python object when they pass into a PyPlot function

It's important to note that in Python the arrowprops would look like this: arrowprops=dict(arrowstyle="->"). Dictionary definitions look like arrowprops=["facecolor"=>"black"] in Julia.

LaTeX can be used by putting an L in front of LaTeX code, L"$\int x = \frac{x^2}{2} + C$".

annotate(L"$\int x = \frac{x^2}{2} + C$",
	xy=[1;0],
	xycoords="axes fraction",
	xytext=[-10,10],
	textcoords="offset points",
	fontsize=30.0,
	ha="right",
	va="bottom")

--

Time Customization

(IJulia,Code)

The formatting preparation is accomplished by calling the formatters within Matplotlib.

majorformatter = matplotlib[:dates][:DateFormatter]("%d.%m.%Y")
minorformatter = matplotlib[:dates][:DateFormatter]("%H:%M")
majorlocator = matplotlib[:dates][:DayLocator](interval=1)
minorlocator = matplotlib[:dates][:HourLocator](byhour=(8, 16))

They are then applied to the specific axis, the handle of which is called ax1 in this case.

ax1[:xaxis][:set_major_formatter](majorformatter)
ax1[:xaxis][:set_minor_formatter](minorformatter)
ax1[:xaxis][:set_major_locator](majorlocator)
ax1[:xaxis][:set_minor_locator](minorlocator)

Custom Time

--

Subplots

(IJulia, Code)

subplot(YXN), Y = number of columns, X = number of rows, N = number of axis being created

The number, N, of a grid of axes starts in the upper left (1), and goes right then down. The second axis of a 2x2 grid is the upper right axis.

subplot(313) # Create the third plot of a 3x1 group of subplots

suptitle("3x1 Subplot") # Supe title, title for all subplots combined

2x2 Subplot

3x1 Subplot

3x1 Touching Subplots

--

Polar and Windrose Plot

(IJulia, Code)

ax = axes(polar="true") # Create a polar axis
# Do your plotting

# Optional changes
ax[:set_thetagrids]([0:dtheta:360-dtheta]) # Show grid lines from 0 to 360 in increments of dtheta
ax[:set_theta_zero_location]("N") # Set 0 degrees to the top of the plot
ax[:set_theta_direction](-1) # Switch to clockwise
fig[:canvas][:draw]() # Update the figure, required when doing additional modifications

Wind Rose - Bar Plot

Wind Rose - Line Plot

--

Histogram

(IJulia, Code)

h = PyPlot.plt.hist(x,nbins) # Histogram, PyPlot.plt required to differentiate with conflicting hist command

Histogram

--

Bar Plot

(IJulia, Code)

b = bar(x,y,color="#0f87bf",align="center",alpha=0.4)
b = barh(x,y,color="#0f87bf",align="center",alpha=0.4)

Bar Plots

--

Errorbar Plot

(IJulia, Code)

errorbar(x, # Original x data points, N values
	y, # Original y data points, N values
	yerr=errs, # Plus/minus error ranges, Nx2 values
	fmt="o") # Format

Erro Bar Plot

--

Inexact Plot

(IJulia, Code)

The IJulia example does not properly apply all the formatting as the terminal version does.

xkcd() # Set to XKCD mode, based on the comic (hand drawn)
# Plot everything

Inexact XKCD Plot

--

Pie Chart

(IJulia, Code)

p = pie(sizes,labels=labels,shadow=true,startangle=90,explode=explode,colors=colors,autopct="%1.1f%%")

Pie Chart

--

Scatter Plot

(IJulia, Code)

scatter(x,y,s=areas,alpha=0.5)

Scatter Plot

--

Box Plot

(IJulia, Code)

boxplot(data, # Each column/cell is one box
	notch=true, # Notched center
	whis=0.75, # Whisker length as a percent of inner quartile range
	widths=0.25, # Width of boxes
	vert=false, # Horizontal boxes
	sym="rs") # Symbol color and shape (rs = red square)

Box Plot

--

Major and Minor Ticks

(IJulia, Code)

###########################
#  Set the tick interval  #
###########################
Mx = matplotlib[:ticker][:MultipleLocator](20) # Define interval of major ticks
f = matplotlib[:ticker][:FormatStrFormatter]("%1.2f") # Define format of tick labels
ax[:xaxis][:set_major_locator](Mx) # Set interval of major ticks
ax[:xaxis][:set_major_formatter](f) # Set format of tick labels

mx = matplotlib[:ticker][:MultipleLocator](5) # Define interval of minor ticks
ax[:xaxis][:set_minor_locator](mx) # Set interval of minor ticks

My = matplotlib[:ticker][:MultipleLocator](0.5) # Define interval of major ticks
ax[:yaxis][:set_major_locator](My) # Set interval of major ticks

my = matplotlib[:ticker][:MultipleLocator](0.1) # Define interval of minor ticks
ax[:yaxis][:set_minor_locator](my) # Set interval of minor ticks

#########################
#  Set tick dimensions  #
#########################
ax[:xaxis][:set_tick_params](which="major",length=10,width=2)
ax[:xaxis][:set_tick_params](which="minor",length=5,width=2)

fig[:canvas][:draw]() # Update the figure

Major and Minor Ticks

--

Multi-axis Plot

(IJulia, Code)

################
#  Other Axes  #
################
new_position = [0.06,0.06,0.77,0.91] # Position Method 2
ax[:set_position](new_position) # Position Method 2: Change the size and position of the axis
#fig[:subplots_adjust](right=0.85) # Position Method 1

ax2 = ax[:twinx]() # Create another axis on top of the current axis
font2 = ["color"=>"purple"]
ylabel("Right Axis",fontdict=font2)
p = plot_date(x,y2,color="purple",linestyle="-",marker="o",label="Second") # Plot a basic line
ax2[:set_position](new_position) # Position Method 2
setp(ax2[:get_yticklabels](),color="purple") # Y Axis font formatting

ax3 = ax[:twinx]() # Create another axis on top of the current axis
ax3[:spines]["right"][:set_position](("axes",1.12)) # Offset the y-axis label from the axis itself so it doesn't overlap the second axis
font3 = ["color"=>"green"]
ylabel("Far Right Axis",fontdict=font3)
p = plot_date(x,y3,color="green",linestyle="-",marker="o",label="Third") # Plot a basic line
ax3[:set_position](new_position) # Position Method 2
setp(ax3[:get_yticklabels](),color="green") # Y Axis font formatting

axis("tight")

# Enable just the right part of the frame
ax3[:set_frame_on](true) # Make the entire frame visible
ax3[:patch][:set_visible](false) # Make the patch (background) invisible so it doesn't cover up the other axes' plots
ax3[:spines]["top"][:set_visible](false) # Hide the top edge of the axis
ax3[:spines]["bottom"][:set_visible](false) # Hide the bottom edge of the axis

fig[:canvas][:draw]() # Update the figure

Multi-axis Plot

--

Axis Placement

(IJulia, Code)

ax[:spines]["top"][:set_visible](false) # Hide the top edge of the axis
ax[:spines]["right"][:set_visible](false) # Hide the right edge of the axis
ax[:spines]["left"][:set_position]("center") # Move the right axis to the center
ax[:spines]["bottom"][:set_position]("center") # Most the bottom axis to the center
ax[:xaxis][:set_ticks_position]("bottom") # Set the x-ticks to only the bottom
ax[:yaxis][:set_ticks_position]("left") # Set the y-ticks to only the left
ax2[:spines]["top"][:set_visible](false) # Hide the top edge of the axis
ax2[:spines]["right"][:set_visible](false) # Hide the right edge of the axis
ax2[:xaxis][:set_ticks_position]("bottom")
ax2[:yaxis][:set_ticks_position]("left")
ax2[:spines]["left"][:set_position](("axes",-0.03)) # Offset the left scale from the axis
ax2[:spines]["bottom"][:set_position](("axes",-0.05)) # Offset the bottom scale from the axis

Axis Placement

--

Surface and Contour Plots

(IJulia, Code)

Thanks to Daniel Høegh for providing this example.

ax[:plot_surface](xgrid, ygrid, z, rstride=2,edgecolors="k", cstride=2,
   cmap=ColorMap("gray"), alpha=0.8, linewidth=0.25)
cp = ax[:contour](xgrid, ygrid, z, colors="black", linewidth=2.0)
ax[:clabel](cp, inline=1, fontsize=10)

Surface Plot

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