Dhananjay

2014-10-17 03:45:20 UTC

Hello,

This might be simple, but I guess I am missing something here.

I have data file as follows:

2.1576318858 -1.8651195165 4.2333428278

2.1681875208 -1.9229968780 4.1989176884

2.3387636157 -2.0376253255 2.4460899122

2.1696565965 -2.6186941271 4.4172007912

2.0848862071 -2.1708981985 3.3404520962

2.0824347942 -1.9142798955 3.3629290206

2.0281685821 -1.8103363482 2.5446721669

2.3309993378 -1.8721153619 2.7006893016

2.0957461483 -1.5379071451 4.5228264441

2.2761376261 -2.5935979811 3.9231744717

.

.

.

(total of 200 lines)

Columns 1,2,3 corresponds to x,y,z axis data points.

This is not a continuous data. I wish to make a plot as a 2D with 3rd

dimension (i.e z-axis data) as a color map with color bar on right hand

side.

As a beginner, I tried to follow tutorial with some modification as

follows:

http://matplotlib.org/examples/pylab_examples/tricontour_vs_griddata.html

# Read data from file:

fl1 = open('flooding-psiphi.dat','r').readlines()

xs = ys = zs = []

for line in fl1:

line = line.split()

xs.append(float(line[0]))

ys.append(float(line[1]))

zs.append(float(line[2]))

print xs[0], ys[0], zs[0]

xi = np.mgrid[-5.0:5.0:200j]

yi = np.mgrid[-5.0:5.0:200j]

zi = griddata((x, y), z, (xi, yi), method='cubic')

plt.subplot(221)

plt.contour(xi, yi, zi, 15, linewidths=0.5, colors='k')

plt.contourf(xi, yi, zi, 15, cmap=plt.cm.rainbow,

norm=plt.Normalize(vmax=abs(zi).max(), vmin=-abs(zi).max()))

plt.colorbar() # draw colorbar

plt.plot(x, y, 'ko', ms=3)

plt.xlim(-5, 5)

plt.ylim(-5, 5)

plt.title('griddata and contour (%d points, %d grid points)' %

(npts, ngridx*ngridy))

#print ('griddata and contour seconds: %f' % (time.clock() - start))

plt.gcf().set_size_inches(6, 6)

plt.show()

However, I failed and getting long error as follows:

QH6154 qhull precision error: initial facet 1 is coplanar with the interior

point

ERRONEOUS FACET:

- f1

- flags: bottom simplicial upperDelaunay flipped

- normal: 0.7071 -0.7071 0

- offset: -0

- vertices: p600(v2) p452(v1) p304(v0)

- neighboring facets: f2 f3 f4

While executing: | qhull d Qz Qbb Qt

Options selected for Qhull 2010.1 2010/01/14:

run-id 1531309415 delaunay Qz-infinity-point Qbbound-last Qtriangulate

_pre-merge _zero-centrum Pgood _max-width 8.8 Error-roundoff 1.2e-14

_one-merge 8.6e-14 _near-inside 4.3e-13 Visible-distance 2.5e-14

U-coplanar-distance 2.5e-14 Width-outside 4.9e-14 _wide-facet 1.5e-13

precision problems (corrected unless 'Q0' or an error)

2 flipped facets

The input to qhull appears to be less than 3 dimensional, or a

computation has overflowed.

Qhull could not construct a clearly convex simplex from points:

- p228(v3): 2.4 2.4 1.4

- p600(v2): 1.4 1.4 8.8

- p452(v1): 5.7 5.7 8

- p304(v0): -3.1 -3.1 2.4

The center point is coplanar with a facet, or a vertex is coplanar

with a neighboring facet. The maximum round off error for

computing distances is 1.2e-14. The center point, facets and distances

to the center point are as follows:

center point 1.595 1.595 5.173

facet p600 p452 p304 distance= 0

facet p228 p452 p304 distance= 0

facet p228 p600 p304 distance= 0

facet p228 p600 p452 distance= 0

These points either have a maximum or minimum x-coordinate, or

they maximize the determinant for k coordinates. Trial points

are first selected from points that maximize a coordinate.

The min and max coordinates for each dimension are:

0: -3.134 5.701 difference= 8.835

1: -3.134 5.701 difference= 8.835

2: -2.118e-22 8.835 difference= 8.835

If the input should be full dimensional, you have several options that

may determine an initial simplex:

- use 'QJ' to joggle the input and make it full dimensional

- use 'QbB' to scale the points to the unit cube

- use 'QR0' to randomly rotate the input for different maximum points

- use 'Qs' to search all points for the initial simplex

- use 'En' to specify a maximum roundoff error less than 1.2e-14.

- trace execution with 'T3' to see the determinant for each point.

If the input is lower dimensional:

- use 'QJ' to joggle the input and make it full dimensional

- use 'Qbk:0Bk:0' to delete coordinate k from the input. You should

pick the coordinate with the least range. The hull will have the

correct topology.

- determine the flat containing the points, rotate the points

into a coordinate plane, and delete the other coordinates.

- add one or more points to make the input full dimensional.

Traceback (most recent call last):

File "./scatter.py", line 43, in <module>

zi = griddata((x, y), z, (xi, yi), method='linear')

File "/usr/lib/python2.7/dist-packages/scipy/interpolate/ndgriddata.py",

line 183, in griddata

ip = LinearNDInterpolator(points, values, fill_value=fill_value)

File "interpnd.pyx", line 192, in

scipy.interpolate.interpnd.LinearNDInterpolator.__init__

(scipy/interpolate/interpnd.c:2598)

File "qhull.pyx", line 948, in scipy.spatial.qhull.Delaunay.__init__

(scipy/spatial/qhull.c:4121)

File "qhull.pyx", line 172, in scipy.spatial.qhull._construct_delaunay

(scipy/spatial/qhull.c:1314)

RuntimeError: Qhull error

Could anyone help me to point out what exactly I am missing here.

I just wish to plot 2D map with color bar for Z-axis.

Thank you in advance.

-- DJ

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This might be simple, but I guess I am missing something here.

I have data file as follows:

2.1576318858 -1.8651195165 4.2333428278

2.1681875208 -1.9229968780 4.1989176884

2.3387636157 -2.0376253255 2.4460899122

2.1696565965 -2.6186941271 4.4172007912

2.0848862071 -2.1708981985 3.3404520962

2.0824347942 -1.9142798955 3.3629290206

2.0281685821 -1.8103363482 2.5446721669

2.3309993378 -1.8721153619 2.7006893016

2.0957461483 -1.5379071451 4.5228264441

2.2761376261 -2.5935979811 3.9231744717

.

.

.

(total of 200 lines)

Columns 1,2,3 corresponds to x,y,z axis data points.

This is not a continuous data. I wish to make a plot as a 2D with 3rd

dimension (i.e z-axis data) as a color map with color bar on right hand

side.

As a beginner, I tried to follow tutorial with some modification as

follows:

http://matplotlib.org/examples/pylab_examples/tricontour_vs_griddata.html

# Read data from file:

fl1 = open('flooding-psiphi.dat','r').readlines()

xs = ys = zs = []

for line in fl1:

line = line.split()

xs.append(float(line[0]))

ys.append(float(line[1]))

zs.append(float(line[2]))

print xs[0], ys[0], zs[0]

xi = np.mgrid[-5.0:5.0:200j]

yi = np.mgrid[-5.0:5.0:200j]

zi = griddata((x, y), z, (xi, yi), method='cubic')

plt.subplot(221)

plt.contour(xi, yi, zi, 15, linewidths=0.5, colors='k')

plt.contourf(xi, yi, zi, 15, cmap=plt.cm.rainbow,

norm=plt.Normalize(vmax=abs(zi).max(), vmin=-abs(zi).max()))

plt.colorbar() # draw colorbar

plt.plot(x, y, 'ko', ms=3)

plt.xlim(-5, 5)

plt.ylim(-5, 5)

plt.title('griddata and contour (%d points, %d grid points)' %

(npts, ngridx*ngridy))

#print ('griddata and contour seconds: %f' % (time.clock() - start))

plt.gcf().set_size_inches(6, 6)

plt.show()

However, I failed and getting long error as follows:

QH6154 qhull precision error: initial facet 1 is coplanar with the interior

point

ERRONEOUS FACET:

- f1

- flags: bottom simplicial upperDelaunay flipped

- normal: 0.7071 -0.7071 0

- offset: -0

- vertices: p600(v2) p452(v1) p304(v0)

- neighboring facets: f2 f3 f4

While executing: | qhull d Qz Qbb Qt

Options selected for Qhull 2010.1 2010/01/14:

run-id 1531309415 delaunay Qz-infinity-point Qbbound-last Qtriangulate

_pre-merge _zero-centrum Pgood _max-width 8.8 Error-roundoff 1.2e-14

_one-merge 8.6e-14 _near-inside 4.3e-13 Visible-distance 2.5e-14

U-coplanar-distance 2.5e-14 Width-outside 4.9e-14 _wide-facet 1.5e-13

precision problems (corrected unless 'Q0' or an error)

2 flipped facets

The input to qhull appears to be less than 3 dimensional, or a

computation has overflowed.

Qhull could not construct a clearly convex simplex from points:

- p228(v3): 2.4 2.4 1.4

- p600(v2): 1.4 1.4 8.8

- p452(v1): 5.7 5.7 8

- p304(v0): -3.1 -3.1 2.4

The center point is coplanar with a facet, or a vertex is coplanar

with a neighboring facet. The maximum round off error for

computing distances is 1.2e-14. The center point, facets and distances

to the center point are as follows:

center point 1.595 1.595 5.173

facet p600 p452 p304 distance= 0

facet p228 p452 p304 distance= 0

facet p228 p600 p304 distance= 0

facet p228 p600 p452 distance= 0

These points either have a maximum or minimum x-coordinate, or

they maximize the determinant for k coordinates. Trial points

are first selected from points that maximize a coordinate.

The min and max coordinates for each dimension are:

0: -3.134 5.701 difference= 8.835

1: -3.134 5.701 difference= 8.835

2: -2.118e-22 8.835 difference= 8.835

If the input should be full dimensional, you have several options that

may determine an initial simplex:

- use 'QJ' to joggle the input and make it full dimensional

- use 'QbB' to scale the points to the unit cube

- use 'QR0' to randomly rotate the input for different maximum points

- use 'Qs' to search all points for the initial simplex

- use 'En' to specify a maximum roundoff error less than 1.2e-14.

- trace execution with 'T3' to see the determinant for each point.

If the input is lower dimensional:

- use 'QJ' to joggle the input and make it full dimensional

- use 'Qbk:0Bk:0' to delete coordinate k from the input. You should

pick the coordinate with the least range. The hull will have the

correct topology.

- determine the flat containing the points, rotate the points

into a coordinate plane, and delete the other coordinates.

- add one or more points to make the input full dimensional.

Traceback (most recent call last):

File "./scatter.py", line 43, in <module>

zi = griddata((x, y), z, (xi, yi), method='linear')

File "/usr/lib/python2.7/dist-packages/scipy/interpolate/ndgriddata.py",

line 183, in griddata

ip = LinearNDInterpolator(points, values, fill_value=fill_value)

File "interpnd.pyx", line 192, in

scipy.interpolate.interpnd.LinearNDInterpolator.__init__

(scipy/interpolate/interpnd.c:2598)

File "qhull.pyx", line 948, in scipy.spatial.qhull.Delaunay.__init__

(scipy/spatial/qhull.c:4121)

File "qhull.pyx", line 172, in scipy.spatial.qhull._construct_delaunay

(scipy/spatial/qhull.c:1314)

RuntimeError: Qhull error

Could anyone help me to point out what exactly I am missing here.

I just wish to plot 2D map with color bar for Z-axis.

Thank you in advance.

-- DJ

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