North Arrows

# Packages used by this tutorial
import geopandas # manipulating geographic data
import numpy # creating arrays
import pygris # easily acquiring shapefiles from the US Census
import matplotlib.pyplot # visualization

# Downloading the state-level dataset from pygris
states = pygris.states(cb=True, year=2022, cache=False).to_crs(3857)

# This is just a function to create a new, blank map with matplotlib, with our default settings
def new_map(rows=1, cols=1, figsize=(5,5), dpi=150, ticks=False):
    # Creating the plot(s)
    fig, ax = matplotlib.pyplot.subplots(rows,cols, figsize=figsize, dpi=dpi)
    # Turning off the x and y axis ticks
    if ticks==False:
        if rows > 1 or cols > 1:
            for a in ax.flatten():
                a.set_xticks([])
                a.set_yticks([])
        else:
            ax.set_xticks([])
            ax.set_yticks([])
    # Returning the fig and ax
    return fig, ax

# Importing the main package
from matplotlib_map_utils import NorthArrow, north_arrow

# Setting up a plot
fig, ax = new_map()

# Plotting a state (Georgia)
states.query("NAME=='Georgia'").plot(ax=ax)

# Adding a north arrow to the upper-right corner of the axis, without any rotation (see Rotation under Formatting Components for details)
north_arrow(ax=ax, location="upper right", rotation={"degrees":0})

# Setting up a plot
fig, ax = new_map()

# Plotting a state (Georgia)
states.query("NAME=='Georgia'").plot(ax=ax)

# Creating a NorthArrow object that we want to place in the upper-right corner of the axis, 
# without any rotation (see Rotation under Formatting Components for details)
# Note that here, we do not specify the axis
na = NorthArrow(location="upper right", rotation={"degrees":0})

# The NorthArrow can then be added using add_artist(), which calls its built-in draw() function:
ax.add_artist(na)

shapes = ["Texas","Georgia","California","Louisiana"]
labels = ["First","Second","Third","Fourth"]

# Creating the initial arrow
na = NorthArrow(location="upper right", rotation={"degrees":0})

# Creating four subplots
fig, axs = new_map(1,4, figsize=(20,5))

for ax,s,l in zip(axs.flatten(), shapes, labels):
    states.query(f"NAME=='{s}'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    na.label = {"text":l}
    ax.add_artist(na.copy())

shapes = ["Texas","Georgia","California","Louisiana"]
labels = ["First","Second","Third","Fourth"]

# Creating four subplots
fig, axs = new_map(1,4, figsize=(20,5))

for ax,s,l in zip(axs.flatten(), shapes, labels):
    states.query(f"NAME=='{s}'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", label={"text":l}, rotation={"degrees":0})

# Modifying specific elements
modifications = [
    {"facecolor":"cyan"}, # changing the color
    {"edgecolor":"red"}, # changing the color
    {"linewidth":6}, # changing the stroke
    False # hiding it entirely - note that the shadow is hidden here too, as it is dependent on the base artist for visibility
]

# Creating four subplots
fig, axs = new_map(1,4, figsize=(20,5))

for ax,m in zip(axs.flatten(), modifications):
    states.query(f"NAME=='Georgia'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", rotation={"degrees":0}, base=m)

# Modifying specific elements
modifications = [
    True, # normal patch
    {"coords":numpy.array([(0.50, 0.85), (0.35, 0.50), (0.50, 0.55), (0.65, 0.50), (0.50, 0.85)])}, # changing the shape
    {"facecolor":"blue"}, # changing the color
    False # hiding it entirely
]

# Creating four subplots
fig, axs = new_map(1,4, figsize=(20,5))

for ax,m in zip(axs.flatten(), modifications):
    states.query(f"NAME=='Georgia'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", rotation={"degrees":0}, fancy=m)

# Modifying specific elements
modifications = [
    {"text": "North"}, # changing the text
    {"position": "left"}, # changing the position
    {"fontsize": 30}, # changing the size
    {"fontfamily": "cursive"}, # changing the family
    {"color": "cyan"}, # changing the color of the text
    {"stroke_width": 5, "stroke_color": "red"}, # changing the stroke size and color
    {"rotation": 30}, # changing the rotation
    False # hiding it entirely
]

# Creating eight subplots
fig, axs = new_map(2,4, figsize=(20,10))

for ax,m in zip(axs.flatten(), modifications):
    states.query(f"NAME=='Georgia'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", rotation={"degrees":0}, label=m)

# Modifying specific elements
modifications = [
    {"offset": (4, -4)}, # changing the offset
    {"offset": (4, 4)}, # changing the offset
    {"offset": (-4, 4)}, # changing the offset
    {"offset": (-4, -4)}, # changing the offset
    {"alpha": 0.2}, # changing the transparency
    {"alpha": 0.8}, # changing the transparency
    {"shadow_rgbFace": "red"}, # changing the color
    False # hiding it entirely
]

# Creating eight subplots
fig, axs = new_map(2,4, figsize=(20,10))

for ax,m in zip(axs.flatten(), modifications):
    states.query(f"NAME=='Georgia'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", rotation={"degrees":0}, shadow=m)

# Modifying specific elements
modifications = [
    None, # default settings
    {"sep": 15}, # increased separation between items
    {"align": "left"}, # changing the alignment of items
    {"width": 100, "height": 200, "mode": "expand"}, # changing the mode, not a great example
]

# Creating four subplots
fig, axs = new_map(1,4, figsize=(20,5))

for ax,m in zip(axs.flatten(), modifications):
    states.query(f"NAME=='Georgia'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", rotation={"degrees":0}, pack=m)

# Modifying specific elements
modifications = [
    {"facecolor": "black"}, # different facecolor
    {"edgecolor": "red"}, # different edgecolor
    # these two show the difference between pad and borderpad
    {"edgecolor": "red", "pad": 3}, # increased pad
    {"edgecolor": "red", "borderpad": 3}, # increased borderpad
]

# Creating four subplots
fig, axs = new_map(1,4, figsize=(20,5))

for ax,m in zip(axs.flatten(), modifications):
    states.query(f"NAME=='Georgia'").plot(ax=ax)
    ax.set_aspect(1, adjustable="datalim")
    north_arrow(ax=ax, location="upper right", rotation={"degrees":0}, aob=m)

# Creating an empty plot - for reference, this is 10 inches x 5 inches
fig, ax = new_map(1,1, figsize=(10,5))

# Visualizing the different sizes at various positions
for l,s in zip([0.1, 0.2, 0.35, 0.55, 0.85], ["xs","sm","md","lg","xl"]):
    # Using the size parameter to set the size directly
    north_arrow(ax=ax, size=s, location="center", label={"text":s}, rotation={"degrees":0}, aob={"bbox_to_anchor":(l, 0.5), "bbox_transform":ax.transAxes})

fig, ax = new_map()

states.query("NAME=='Georgia'").plot(ax=ax)

north_arrow(ax=ax, size="sm", location="upper left", rotation={"degrees":0}, aob={"bbox_to_anchor":(1.05,1), "bbox_transform":ax.transAxes})