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20 | import sys
import pypgfplots
import numpy as np
np.random.seed( 0 )
x = np.arange( 0, 1, 0.1 )
y1 = np.random.randint( 0, 11, len(x) )
y2 = np.random.randint( 0, 11, len(x) )
# There are two y-series on one y-axis. User should make sure that y1 and y2 can
# be plotted together.
pypgfplots.standalone( (x, y1, y2 )
, outfile = '%s.tex' % sys.argv[0]
, xlabel = 'Index', ylabel = '$\frac{a}{b}$'
, title = "Plot with Index."
, legend = [ "Series A", "Series B" ]
, axis_attrib = 'legend pos=outer north east'
, label = r'\bf a.'
)
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25 | # Having multiple y-axis with 1 x-axis not very well tested. This is a corner
# case and should be avoided.
import sys
import pypgfplots
import numpy as np
np.random.seed( 1 )
x = np.arange( 0, 1, 0.1 )
y1 = np.random.randint( 0, 11, len(x) )
y2 = np.random.randint( 11, 101, len(x) )
# There are two y-series on two different y-axis. One will be on left and
# another will be on right.
# be plotted together.
pypgfplots.standalone( (x, y1), (x, y2)
, outfile = '%s.tex' % sys.argv[0]
, xlabel = 'Time'
, color = [ 'red', 'blue' ]
, ylabel = [ 'conc', 'N' ]
, title = "Plot with Index."
, legends = [ "Series A", "Series B" ]
, axis_attrib = 'legend pos=outer north east'
, label = r'\bf a.'
)
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16 | import sys
import pypgfplots
import numpy as np
np.random.seed( 10 )
mat = np.random.rand( 10, 10 )
pypgfplots.standalone(
matrix = mat
, outfile = '%s.tex' % sys.argv[0]
, title = 'Measurement matrix'
, xlabel = 'Index'
, ylabel = 'Index'
, label = r'\bf b.'
)
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17 | import sys
import pypgfplots
import numpy as np
np.random.seed( 0 )
# Genearte a random matrix.
mat = np.random.rand( 10, 10 )
pypgfplots.standalone( matrix = mat
, outfile = '%s.tex' % sys.argv[0]
, title = 'Measurement matrix'
, xlabel = 'Index'
, ylabel = 'Index'
# If indices are not given then we compute the tick location.
, ytick = [ (1,'c1'), (3,'c2'), (6,'c3') ]
, label = r'\bf b.'
)
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25 | # Plot subplot in grid.
import sys
import pypgfplots
import numpy as np
np.random.seed( 10 )
m1 = np.random.rand( 10, 10 )
m2 = np.random.rand( 10, 10 )
y1 = np.random.rand( 100 )
y2 = np.random.rand( 100 )
pypgfplots.standalone(
subplots = {
(0,0) : dict( matrix = m1, title = 'mat A', label = 'a.' )
, (0,1) : dict( xy = (np.arange(0, 100,1), y1), label = 'b.' )
, (1,0) : dict( histogram = y1, label = 'b.'
, xlabel = 'bins', ylabel = 'Count'
, plot_attrib='fill=blue!20')
, (1,1) : dict( matrix = m2, title = 'B', label = 'd.' )
}
, outfile = '%s.pdf' % sys.argv[0]
, title = 'Measurement matrix'
, label = r'\bf b.'
)
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19 | import sys
import pypgfplots
import numpy as np
np.random.seed( 10 )
# generate a very large matrix.
mat = np.random.rand( 1000, 1000 )
pypgfplots.standalone(
matrix = mat
, outfile = '%s.tex' % sys.argv[0]
, title = 'A very large matrix for pdflatex'
, shader = 'interp'
, xlabel = 'A(i)'
, ylabel = 'f(A(i))'
, every = (10,20) # Plot every 10th row and 20th column.
, label = r'\bf b.'
)
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25 | # Plot subplot in grid.
import sys
import pypgfplots
import numpy as np
np.random.seed( 10 )
m1 = np.random.rand( 10, 10 )
m2 = np.random.rand( 10, 10 )
y1 = np.random.rand( 100 )
y2 = np.random.rand( 100 )
pypgfplots.standalone(
subplots = {
(0,0) : dict( matrix = m1, title = 'mat A', label = 'a.' )
, (0,1) : dict( xy = (np.arange(0, 100,1), y1), label = 'b.' )
, (1,0) : dict( histogram = y1, label = 'b.'
, xlabel = 'bins', ylabel = 'Count'
, plot_attrib='fill=blue!20')
, (1,1) : dict( matrix = m2, title = 'B', label = 'd.' )
}
, outfile = '%s.tex' % sys.argv[0]
, title = 'Measurement matrix'
, label = r'\bf b.'
)
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