layer2img.py with arrowplots
Motiejus Jakštys
parent
3053799975
commit
b92ac92c90
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@ -5,8 +5,7 @@ fname=${1:-mj-msc-all.pdf}
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echo "Extracting $fname to $dir/" && pdfdetach -saveall -o "$dir" "$fname"
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echo "Generating $dir/$fname ..."
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make -j $(nproc) -C "$dir" "$fname" &> "$dir/make.log" || {
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echo "Generation failed. Here are the last 20 log lines:"
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tail -20 "$dir/make.log"
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echo "Generation failed. Log extract:" && tail -20 "$dir/make.log"
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exit 1
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}
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echo "Opening $dir/$fname ..." && xdg-open "$dir/$fname"
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@ -0,0 +1,181 @@
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#!/usr/bin/python3
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import argparse
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import geopandas
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import psycopg2
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import rc
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INCH = 25.4 # mm
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BOUNDS = ('xmin', 'ymin', 'xmax', 'ymax')
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GREEN, ORANGE, PURPLE = '#1b9e77', '#d95f02', '#7570b3'
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PSQL_CREDS="host=127.0.0.1 dbname=osm user=osm password=osm"
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def arrowplot(axes, x, y, narrs=30, dspace=0.5, direc='pos', \
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hl=0.3, hw=3, c='black'):
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''' narrs : Number of arrows that will be drawn along the curve
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dspace : Shift the position of the arrows along the curve.
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Should be between 0. and 1.
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direc : can be 'pos' or 'neg' to select direction of the arrows
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hl : length of the arrow head
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hw : width of the arrow head
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c : color of the edge and face of the arrow head
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https://stackoverflow.com/questions/8247973
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'''
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# r is the distance spanned between pairs of points
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r = [0]
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for i in range(1,len(x)):
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dx = x[i]-x[i-1]
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dy = y[i]-y[i-1]
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r.append(np.sqrt(dx*dx+dy*dy))
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r = np.array(r)
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# rtot is a cumulative sum of r, it's used to save time
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rtot = []
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for i in range(len(r)):
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rtot.append(r[0:i].sum())
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rtot.append(r.sum())
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# based on narrs set the arrow spacing
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aspace = r.sum() / narrs
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if direc is 'neg':
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dspace = -1.*abs(dspace)
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else:
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dspace = abs(dspace)
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arrowData = [] # will hold tuples of x,y,theta for each arrow
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arrowPos = aspace*(dspace) # current point on walk along data
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# could set arrowPos to 0 if you want
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# an arrow at the beginning of the curve
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ndrawn = 0
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rcount = 1
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while arrowPos < r.sum() and ndrawn < narrs:
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x1,x2 = x[rcount-1],x[rcount]
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y1,y2 = y[rcount-1],y[rcount]
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da = arrowPos-rtot[rcount]
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theta = np.arctan2((x2-x1),(y2-y1))
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ax = np.sin(theta)*da+x1
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ay = np.cos(theta)*da+y1
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arrowData.append((ax,ay,theta))
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ndrawn += 1
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arrowPos+=aspace
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while arrowPos > rtot[rcount+1]:
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rcount+=1
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if arrowPos > rtot[-1]:
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break
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# could be done in above block if you want
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for ax,ay,theta in arrowData:
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# use aspace as a guide for size and length of things
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# scaling factors were chosen by experimenting a bit
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dx0 = np.sin(theta)*hl/2. + ax
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dy0 = np.cos(theta)*hl/2. + ay
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dx1 = -1.*np.sin(theta)*hl/2. + ax
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dy1 = -1.*np.cos(theta)*hl/2. + ay
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if direc is 'neg' :
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ax0 = dx0
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ay0 = dy0
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ax1 = dx1
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ay1 = dy1
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else:
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ax0 = dx1
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ay0 = dy1
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ax1 = dx0
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ay1 = dy0
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axes.annotate('', xy=(ax0, ay0), xycoords='data',
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xytext=(ax1, ay1), textcoords='data',
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arrowprops=dict( headwidth=hw, frac=1., ec=c, fc=c))
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def plt_size(string):
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if not string:
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return None
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try:
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w, h = string.split("x")
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return float(w) / INCH, float(h) / INCH
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except Exception as e:
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raise argparse.ArgumentTypeError from e
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def parse_args():
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parser = argparse.ArgumentParser(
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description='Convert geopackage to an image')
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group1 = parser.add_mutually_exclusive_group()
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group1.add_argument('--group1-infile')
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group1.add_argument('--group1-table')
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parser.add_argument('-o', '--outfile', metavar='<file>')
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parser.add_argument(
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'--size', type=plt_size, help='Figure size in mm (WWxHH)')
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parser.add_argument( '--clip', type=float, nargs=4, metavar=BOUNDS)
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group2 = parser.add_mutually_exclusive_group()
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group2.add_argument('--group2-infile', type=str)
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group2.add_argument('--group2-table', type=str)
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group3 = parser.add_mutually_exclusive_group()
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group3.add_argument('--group3-infile', type=str)
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group3.add_argument('--group3-table', type=str)
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return parser.parse_args()
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def read_layer(maybe_table, maybe_file):
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if maybe_table:
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conn = psycopg2.connect(PSQL_CREDS)
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sql = "SELECT way FROM %s" % maybe_table
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return geopandas.read_postgis(sql, con=conn, geom_col='way')
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elif maybe_file:
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return geopandas.read_file(maybe_file)
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def add_lines(ax, group):
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for g in group.to_dict()['way'].values():
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for geom in getattr(g, 'geoms', [g]):
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x, y = zip(*geom.coords)
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narrs = geom.length / 16
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arrowplot(ax, np.array(x), np.array(y), narrs=narrs)
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def main():
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args = parse_args()
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group1 = read_layer(args.group1_table, args.group1_infile)
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group2 = read_layer(args.group2_table, args.group2_infile)
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group3 = read_layer(args.group3_table, args.group3_infile)
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rc('text', usetex=True)
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fig, ax = plt.subplots()
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if args.size:
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fig.set_size_inches(args.size)
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if c := args.clip:
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ax.set_xlim(left=c[0], right=c[2])
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ax.set_ylim(bottom=c[1], top=c[3])
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if group1 is not None:
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group1.plot(ax=ax, color=PURPLE)
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add_lines(ax, group1)
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if group2 is not None:
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group2.plot(ax=ax, color=ORANGE)
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add_lines(ax, group2)
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if group3 is not None:
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group3.plot(ax=ax, color=GREEN)
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add_lines(ax, group3)
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ax.axis('off')
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ax.margins(0, 0)
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#fig.tight_layout(0)
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if args.outfile:
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fig.savefig(args.outfile, bbox_inches=0, dpi=600)
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else:
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plt.show()
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if __name__ == '__main__':
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main()
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@ -244,10 +244,9 @@ unexpected regressions have been added while modifying the algorithm.
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We strongly believe in the ability to reproduce the results is critical for any
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scientific work. To make it possible for this paper, all source files and
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accompanying scripts have been attached to the PDF. To preview the code
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listings and re-generate this document (also, re-generate the included
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graphics), run this script (assuming name of this document is {\tt
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mj-msc-all.pdf}):
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accompanying scripts have been attached to the PDF. To re-generate this
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document and its accompanying graphics, run this script (assuming name of
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this document is {\tt mj-msc-all.pdf}):
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\inputminted[fontsize=\small]{bash}{extract-and-generate}
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