def curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y-x
def inv_tr(x,y):
x, y = np.asarray(x), np.asarray(y)
return x, y+x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
# ax1 will have a ticks and gridlines defined by the given
# transform (+ transData of the Axes). Note that the transform of
# the Axes itself (i.e., transData) is not affected by the given
# transform.
fig.add_subplot(ax1)
xx, yy = tr([3, 6], [5.0, 10.])
ax1.plot(xx, yy)
ax1.set_aspect(1.)
ax1.set_xlim(0, 10.)
ax1.set_ylim(0, 10.)
ax1.axis["t"]=ax1.new_floating_axis(0, 3.)
ax1.axis["t2"]=ax1.new_floating_axis(1, 7.)
ax1.grid(True)
def curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y - x
def inv_tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y + x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
# ax1 will have a ticks and gridlines defined by the given
# transform (+ transData of the Axes). Note that the transform of
# the Axes itself (i.e., transData) is not affected by the given
# transform.
fig.add_subplot(ax1)
xx, yy = tr([3, 6], [5.0, 10.])
ax1.plot(xx, yy)
ax1.set_aspect(1.)
ax1.set_xlim(0, 10.)
ax1.set_ylim(0, 10.)
ax1.grid(True)
def curvelinear_test1(fig):
"""
grid for custom transform.
"""
def tr(x, y):
x, y = np.asarray(x), np.asarray(y)
return x, y-x
def inv_tr(x,y):
x, y = np.asarray(x), np.asarray(y)
return x, y+x
grid_helper = GridHelperCurveLinear((tr, inv_tr))
ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
fig.add_subplot(ax1)
xx, yy = tr([3, 6], [5.0, 10.])
ax1.plot(xx, yy)
ax1.set_aspect(1.)
ax1.set_xlim(0, 10.)
ax1.set_ylim(0, 10.)
ax1.grid(True)
def generate_graph(chromosome, nearest_supers, FIELD_WIDTH, FIELD_HEIGHT,
graph_title, n):
chromosome = [int(i) for i in chromosome]
w = (FIELD_WIDTH) / 4.0
h = (FIELD_HEIGHT) / 4.0
fig = pylab.figure(figsize=(w + 1, h))
#fig = pylab.figure(figsize=(2.5,3))
#ax = pylab.subplot(111)
ax = Subplot(fig, 111)
fig.add_subplot(ax)
#ax.axis["right"].set_visible(False)
#ax.axis["top"].set_visible(False)
#ax.axis["bottom"].set_visible(False)
#ax.axis["left"].set_visible(False)
super_x = [
coords[i][0] for i in range(len(chromosome)) if (chromosome[i] == 1)
]
super_y = [
coords[i][1] for i in range(len(chromosome)) if chromosome[i] == 1
]
sensor_x = [
coords[i][0] for i in range(len(chromosome)) if chromosome[i] == 0
]
sensor_y = [
coords[i][1] for i in range(len(chromosome)) if chromosome[i] == 0
]
target_x = 0
target_y = 0
#pylab.grid(True)
for i, node in enumerate(chromosome):
if node == 1:
ax.plot([coords[i][0], 0], [coords[i][1], 0],
'--',
lw=.85,
color='red')
if not node and nearest_supers[i] >= 0:
ax.plot([coords[i][0], coords[nearest_supers[i]][0]],
[coords[i][1], coords[nearest_supers[i]][1]],
'-',
lw=.85,
color='blue')
ax.plot(sensor_x, sensor_y, 'go', label=r'sensor')
ax.plot(super_x, super_y, 'bo', label=r'super')
ax.plot(target_x, target_y, 'ro', label=r'target')
#add_ranges(ax, chromosome)
#draw_clusters(ax, chromosome, nearest_supers)
pylab.xticks(pylab.arange(0, FIELD_WIDTH + 1, 1), color='white')
pylab.yticks(pylab.arange(0, FIELD_HEIGHT + 1, 1), color='white')
#ax.set_xticklabels([])
#ax.set_yticklabels([])
#pylab.title(graph_title)
pylab.xlim((-1, FIELD_WIDTH + 1))
pylab.ylim((-1, FIELD_HEIGHT + 1))
ax.set_aspect(1)
#legend(loc='right', bbox_to_anchor=(2,1))
#box = ax.get_position()
#ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
#ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
#box = ax.get_position()
#ax.set_position([box.x0, box.y0 + box.height * 0.1,
# box.width, box.height * 0.9])
#ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05),
# fancybox=True, shadow=True, ncol=5,numpoints=1)
#LEGEND
#box = ax.get_position()
#ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
#ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), numpoints=1)
filename = "/home/milleraj/Desktop/genetic_graphs/chrom%d.pdf" % n
print filename
pylab.savefig(filename)
def generate_graph(chromosome, nearest_supers, FIELD_WIDTH, FIELD_HEIGHT,
graph_title, n):
chromosome = [ int(i) for i in chromosome ]
w = (FIELD_WIDTH)/4.0
h = (FIELD_HEIGHT)/4.0
fig = pylab.figure(figsize=(w+1,h))
#fig = pylab.figure(figsize=(2.5,3))
#ax = pylab.subplot(111)
ax = Subplot(fig, 111)
fig.add_subplot(ax)
#ax.axis["right"].set_visible(False)
#ax.axis["top"].set_visible(False)
#ax.axis["bottom"].set_visible(False)
#ax.axis["left"].set_visible(False)
super_x = [ coords[i][0] for i in range(len(chromosome))
if (chromosome[i] == 1) ]
super_y = [ coords[i][1] for i in range(len(chromosome))
if chromosome[i] == 1 ]
sensor_x = [ coords[i][0] for i in range(len(chromosome))
if chromosome[i] == 0 ]
sensor_y = [ coords[i][1] for i in range(len(chromosome))
if chromosome[i] == 0 ]
target_x = 0
target_y = 0
#pylab.grid(True)
for i, node in enumerate(chromosome):
if node == 1:
ax.plot([coords[i][0], 0], [coords[i][1], 0], '--',lw=.85,
color='red')
if not node and nearest_supers[i] >= 0:
ax.plot([coords[i][0],
coords[nearest_supers[i]][0]],
[coords[i][1],
coords[nearest_supers[i]][1]],
'-', lw=.85, color='blue')
ax.plot(sensor_x, sensor_y, 'go', label=r'sensor')
ax.plot(super_x, super_y, 'bo', label=r'super')
ax.plot(target_x, target_y, 'ro', label=r'target')
#add_ranges(ax, chromosome)
#draw_clusters(ax, chromosome, nearest_supers)
pylab.xticks(pylab.arange(0, FIELD_WIDTH+1, 1), color='white')
pylab.yticks(pylab.arange(0, FIELD_HEIGHT+1, 1), color='white')
#ax.set_xticklabels([])
#ax.set_yticklabels([])
#pylab.title(graph_title)
pylab.xlim((-1, FIELD_WIDTH+1))
pylab.ylim((-1, FIELD_HEIGHT+1))
ax.set_aspect(1)
#legend(loc='right', bbox_to_anchor=(2,1))
#box = ax.get_position()
#ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
#ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
#box = ax.get_position()
#ax.set_position([box.x0, box.y0 + box.height * 0.1,
# box.width, box.height * 0.9])
#ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05),
# fancybox=True, shadow=True, ncol=5,numpoints=1)
#LEGEND
#box = ax.get_position()
#ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
#ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), numpoints=1)
filename = "/home/milleraj/Desktop/genetic_graphs/chrom%d.pdf" % n
print filename
pylab.savefig(filename)
