How to use e.findAt for similar geometrical models? - scripting
I used Abaqus macro recording when defining a set: by edge (20 deg). My end goal is to run the script for different .STEP models/geometries which are identical in every aspect except for a few parametric values. For each model I am using the same procedure for selecting the highlighted edges: create a set from edge-by-angle-20.
However, when I run it for other geometric models, it selects an entirely different e.getSequenceFromMask or as I should say entirely different sets for e.findAt after running the commands for the similar edge.
session.journalOptions.replayGeometry
session.journalOptions.setValues(replayGeometry=INDEX)
I am aware that the program has restrictions over findAt :
findAt initially uses the ACIS tolerance of 1E-6. As a result, findAt returns any edge that is at the arbitrary point specified or at a distance of less than 1E-6 from the arbitrary point.
Edge to be selected in all models which are similar with a few variations in dimensions
I would appreciate it if anyone can suggest how to ensure the same edges are selected for different geometries when using the e.findAt command.
My code:
#Sample for the same edges selected from different dimensioned CAD models
#CAD Model_1
edges = e.getSequenceFromMask(mask=(
'[#63002104 #88110 #10000480 #20402 #480c802 #10420070 #c4411',
' #70104842 #10022000 #1e2002 #30 #80820010 #20003 #18144186',
' #b000 ]',), )
p.Set(edges=edges, name='Set-2')
#Set 2:
mdb.models['Model-1'].parts['Circular_knit - 2, 3, 10'].edges.findAt(((2.808153, 3.86272, -0.231317),),((3.959929, 2.669325, -0.231317),),((3.581888, 1.932068, -0.134932),),((1.501975, 3.782442, -0.134931),),((2.094736, 4.291667, -0.231317),),((2.135971, 3.464163, -0.134931),),((2.705066, 3.040627, -0.134931),),((3.436245, 3.316406, -0.231317),),((3.19197, 2.524704, -0.134932),),((4.363292, 1.941137, -0.231317),),((3.862971, 1.280728, -0.134932),),((-0.318814, 3.68708, 0.0),),((1.317672, 4.590214, -0.231317),),((4.764061, 0.331739, -0.231318),),((4.74929, -0.500571, -0.231318),),((4.590214, -1.317672, -0.231317),),((4.634078, 1.15397, -0.231318),),((-0.590217, 4.023581, -0.132766),),((-0.331245, 4.765369, -0.229231),),((0.822343, 3.985795, -0.134932),),((0.500571, 4.74929, -0.231318),),((4.02668, 0.590473, -0.134933),),((4.068041, -0.117724, -0.134933),),((4.291667, -2.094736, -0.231317),),((3.464163, -2.135971, -0.134931),),((3.86272, -2.808153, -0.231317),),((1.932068, -3.581888, -0.134932),),((1.280728, -3.862971, -0.134932),),((1.15397, -4.634078, -0.231318),),((0.590473, -4.02668, -0.134933),),((-0.117724, -4.068041, -0.134933),),((3.985795, -0.822343, -0.134932),),((0.117724, 4.068041, -0.134933),),((-1.15397, 4.634078, -0.231318),),((-1.280728, 3.862971, -0.134932),),((-2.524704, 3.19197, -0.134932),),((-2.669325, 3.959929, -0.231317),),((-1.941137, 4.363292, -0.231317),),((-1.932068, 3.581888, -0.134932),),((3.782442, -1.501975, -0.134931),),((3.040627, -2.705066, -0.134931),),((3.316406, -3.436245, -0.231317),),((2.524704, -3.19197, -0.134932),),((2.669325, -3.959929, -0.231317),),((1.941137, -4.363292, -0.231317),),((0.331739, -4.764061, -0.231318),),((-0.500571, -4.74929, -0.231318),),((-3.464163, 2.135971, -0.134931),),((-4.291667, 2.094736, -0.231317),),((-3.316406, 3.436245, -0.231317),),((-3.040627, 2.705066, -0.134931),),((-3.86272, 2.808153, -0.231317),),((-1.317672, -4.590214, -0.231317),),((-0.822343, -3.985795, -0.134932),),((-4.764061, -0.331739, -0.231318),),((-3.959929, -2.669325, -0.231317),),((-3.862971, -1.280728, -0.134932),),((-3.782442, 1.501975, -0.134931),),((-4.590214, 1.317672, -0.231317),),((-3.985795, 0.822343, -0.134932),),((-2.135971, -3.464163, -0.134931),),((-4.74929, 0.500571, -0.231318),),((-4.068041, 0.117724, -0.134933),),((-4.02668, -0.590473, -0.134933),),((-4.634078, -1.15397, -0.231318),),((-4.363292, -1.941137, -0.231317),),((-3.581888, -1.932068, -0.134932),),((-3.19197, -2.524704, -0.134932),),((-3.436245, -3.316406, -0.231317),),((-2.705066, -3.040627, -0.134931),),((-2.094736, -4.291667, -0.231317),),((-1.501975, -3.782442, -0.134931),),((-2.808153, -3.86272, -0.231317),),)
#CAD Model_2
edges = e.getSequenceFromMask(mask=('[#ffffffff:12 #3fffff ]', ), )
p.Set(edges=edges, name='Set-2')
#Set_2:
mdb.models['Model-1'].parts['Circular_knit - 2, 3, 9'].edges.findAt(((3.609683, 0.972388, 1e-06),),((3.573439, 0.962676, 0.012491),),((3.76173, 1.266747, -0.034239),),((4.345677, 1.895909, -0.106922),),((3.369331, 1.576662, 0.046191),),((3.59632, 1.879201, -0.101049),),((4.017677, 2.705061, -0.092682),),((3.044359, 2.137787, 0.046191),),((3.950435, 2.621725, -0.106922),),((4.319341, 2.493773, 0.001066),),((3.51041, 1.897727, -0.09198),),((4.38626, 1.924207, -0.137251),),((3.786618, 1.25932, -0.091981),),((4.653757, 1.133308, -0.137251),),((3.94777, 0.582649, -0.091981),),((4.779853, 0.307975, -0.137252),),((4.987546, 0.0, 0.001066),),((3.968123, -0.096234, -0.034239),),((3.706257, -0.319236, 0.046191),),((4.054105, -0.170725, -0.101049),),((4.831941, 0.333813, -0.092682),),((3.705386, 0.329198, 0.046191),),((3.686317, 0.32753, 0.012491),),((3.591928, 0.967631, 0.046191),),((4.608877, 1.112487, -0.106922),),((3.924549, 0.594285, -0.034239),),((4.732039, 0.295263, -0.106922),),((4.68676, 1.705841, 0.001066),),((3.351983, 1.568572, 0.012491),),((3.38599, 1.58443, 1e-06),),((4.426368, 1.966302, -0.092682),),((3.868004, 1.226157, -0.101049),),((4.700566, 1.167799, -0.092682),),((4.02216, 0.535857, -0.101049),),((3.723697, 0.3308, 1e-06),),((4.332897, 2.501599, 0.037363),),((3.215364, 2.475146, -0.101049),),((3.059416, 2.14833, 1e-06),),((3.028679, 2.126808, 0.012491),),((3.101617, 2.476941, -0.034239),),((3.435161, 3.267881, -0.106922),),((2.613351, 2.620422, 0.012491),),((2.649644, 2.983909, -0.091979),),((2.83651, 3.859543, -0.137251),),((2.134748, 3.057453, 1e-06),),((2.14551, 3.072822, 2e-06),),((2.850196, 3.916052, -0.092682),),((3.215994, 3.832672, 0.037363),),((3.205932, 3.820682, 0.001066),),((2.815512, 3.814744, -0.106922),),((2.129595, 3.050095, 0.046191),),((2.174904, 3.425595, -0.101049),),((2.501599, 4.332897, 0.037363),),((2.493773, 4.319341, 0.001066),),((2.067403, 3.388378, -0.034239),),((3.484612, 1.90072, -0.034239),),((3.985488, 2.656641, -0.137251),),((4.701469, 1.711195, 0.037363),),((4.927189, 0.868796, 0.037363),),((5.003198, 0.0, 0.037363),),((4.711421, -0.530933, -0.106922),),((3.891127, -0.78383, -0.034239),),((4.547648, -1.340996, -0.106922),),((3.695902, -1.447609, -0.034239),),((3.356209, -1.559509, 0.012491),),((3.710189, -1.469294, -0.091979),),((4.68676, -1.705841, 0.001066),),((4.816498, -0.510316, -0.092682),),((3.724569, -0.320838, 1e-06),),((3.687189, -0.317568, 0.012491),),((4.911774, 0.866078, 0.001066),),((3.48691, 3.361627, -0.092682),),((2.626886, 2.633957, 0.046191),),((3.127541, 2.478471, -0.091979),),((3.463619, 3.308353, -0.137251),),((2.639883, 2.646954, 1e-06),),((3.820682, 3.205932, 0.001066),),((3.832672, 3.215994, 0.037363),),((2.62438, 2.9779, -0.034239),),((2.118616, 3.034415, 0.012491),),((2.091239, 3.398682, -0.091979),),((2.736711, 2.995885, -0.101049),),((2.12688, 4.35149, -0.092682),),((1.547014, 3.751221, -0.101049),),((1.711195, 4.701469, 0.037363),),((1.469294, 3.710189, -0.091979),),((2.123214, 4.293462, -0.137251),),((2.110314, 4.245698, -0.106922),),((3.988971, -0.111726, -0.091981),),((4.911774, -0.866078, 0.001066),),((4.760715, -0.526717, -0.137252),),((3.594516, -0.957971, 0.046191),),((3.576027, -0.953017, 0.012491),),((3.908966, -0.802706, -0.09198),),((4.927189, -0.868796, 0.037363),),((3.373557, -1.567599, 0.046191),),((4.245698, -2.110314, -0.106922),),((4.319341, -2.493773, 0.001066),),((4.332897, -2.501599, 0.037363),),((4.35149, -2.12688, -0.092682),),((4.293462, -2.123214, -0.137251),),((3.390216, -1.575367, 1e-06),),((4.596926, -1.345405, -0.137251),),((3.612271, -0.962729, 1e-06),),((4.65471, -1.338939, -0.092682),),((3.751221, -1.547014, -0.101049),),((3.962868, -0.872119, -0.101049),),((1.567599, 3.373557, 0.046191),),((1.338939, 4.65471, -0.092682),),((0.872119, 3.962868, -0.101049),),((0.510316, 4.816498, -0.092682),),((0.321655, 3.733897, 2e-06),),((0.320019, 3.715207, 1e-06),),((0.111726, 3.988971, -0.091981),),((0.0, 4.987546, 0.001066),),((0.096234, 3.968123, -0.034239),),((0.530933, 4.711421, -0.106922),),((0.866078, 4.911774, 0.001066),),((0.526717, 4.760715, -0.137252),),((1.705841, 4.68676, 0.001066),),((1.345405, 4.596926, -0.137251),),((0.802706, 3.908966, -0.09198),),((1.571395, 3.381699, 1e-06),),((1.579324, 3.398703, 2e-06),),((1.447609, 3.695902, -0.034239),),((1.559509, 3.356209, 0.012491),),((3.388378, -2.067403, -0.034239),),((3.050095, -2.129595, 0.046191),),((3.065152, -2.140139, 1e-06),),((3.034415, -2.118616, 0.012491),),((3.398682, -2.091239, -0.091979),),((3.425595, -2.174904, -0.101049),),((4.701469, -1.711195, 0.037363),),((0.965152, 3.621316, 2e-06),),((0.957971, 3.594516, 0.046191),),((0.953017, 3.576027, 0.012491),),((0.868796, 4.927189, 0.037363),),((0.319236, 3.706257, 0.046191),),((0.170725, 4.054105, -0.101049),),((0.0, 5.003198, 0.037363),),((-0.3073, 4.782091, -0.136321),),((-0.320838, 3.724565, 1e-05),),((-0.323171, 3.73689, 1.3e-05),),((-0.324216, 3.705803, 0.046199),),((-0.593805, 3.921017, -0.033079),),((-0.866078, 4.911774, 0.001066),),((-1.133308, 4.653757, -0.137251),),((-0.972388, 3.609683, 1e-06),),((-0.967631, 3.591928, 0.046191),),((-1.112487, 4.608877, -0.106922),),((0.317568, 3.687189, 0.012491),),((-0.294772, 4.734331, -0.106051),),((0.78383, 3.891127, -0.034239),),((1.340996, 4.547648, -0.106922),),((0.960296, 3.603193, 1e-06),),((3.814744, -2.815512, -0.106922),),((3.820682, -3.205932, 0.001066),),((3.832672, -3.215994, 0.037363),),((3.916052, -2.850196, -0.092682),),((3.859543, -2.83651, -0.137251),),((-0.332828, 4.834011, -0.091687),),((-0.318814, 3.68708, 0.0),),((-0.325817, 3.724111, 1e-05),),((-0.536001, 4.018603, -0.099875),),((-0.868796, 4.927189, 0.037363),),((-0.319237, 3.706259, 0.046191),),((-0.322549, 3.68675, 0.0125),),((-0.31881, 3.687067, 0.05),),((-0.317568, 3.687186, 0.012495),),((-0.582378, 3.944173, -0.090789),),((-0.962676, 3.573439, 0.012491),),((-1.25932, 3.786618, -0.091981),),((-1.711195, 4.701469, 0.037363),),((-1.226157, 3.868004, -0.101049),),((-1.167799, 4.700566, -0.092682),),((2.9779, -2.62438, -0.034239),),((3.267881, -3.435161, -0.106922),),((2.476941, -3.101617, -0.034239),),((2.137787, -3.044359, 0.046191),),((2.475146, -3.215364, -0.101049),),((3.361627, -3.48691, -0.092682),),((2.633957, -2.626886, 0.046191),),((2.620422, -2.613351, 0.012491),),((2.983909, -2.649644, -0.091979),),((2.995885, -2.736711, -0.101049),),((2.646954, -2.639883, 1e-06),),((-1.266747, 3.76173, -0.034239),),((-1.705841, 4.68676, 0.001066),),((-1.924207, 4.38626, -0.137251),),((-1.58443, 3.38599, 1e-06),),((-1.966302, 4.426368, -0.092682),),((3.205932, -3.820682, 0.001066),),((2.478471, -3.127541, -0.091979),),((2.656641, -3.985488, -0.137251),),((2.493773, -4.319341, 0.001066),),((1.90072, -3.484612, -0.034239),),((1.576662, -3.369331, 0.046191),),((1.879201, -3.59632, -0.101049),),((2.705061, -4.017677, -0.092682),),((2.126808, -3.028679, 0.012491),),((2.14833, -3.059416, 1e-06),),((3.215994, -3.832672, 0.037363),),((3.308353, -3.463619, -0.137251),),((-1.895909, 4.345677, -0.106922),),((-1.568572, 3.351983, 0.012491),),((-1.897727, 3.51041, -0.09198),),((-2.501599, 4.332897, 0.037363),),((-2.705061, 4.017677, -0.092682),),((-2.137787, 3.044359, 0.046191),),((-2.621725, 3.950435, -0.106922),),((-2.493773, 4.319341, 0.001066),),((-2.656641, 3.985488, -0.137251),),((-2.14833, 3.059416, 1e-06),),((-1.576662, 3.369331, 0.046191),),((2.501599, -4.332897, 0.037363),),((2.621725, -3.950435, -0.106922),),((1.895909, -4.345677, -0.106922),),((1.705841, -4.68676, 0.001066),),((1.924207, -4.38626, -0.137251),),((1.58443, -3.38599, 1e-06),),((1.966302, -4.426368, -0.092682),),((-1.90072, 3.484612, -0.034239),),((-1.879201, 3.59632, -0.101049),),((-2.475146, 3.215364, -0.101049),),((-2.476941, 3.101617, -0.034239),),((-2.126808, 3.028679, 0.012491),),((-2.478471, 3.127541, -0.091979),),((-3.308353, 3.463619, -0.137251),),((-2.646954, 2.639883, 1e-06),),((-3.361627, 3.48691, -0.092682),),((-3.215994, 3.832672, 0.037363),),((1.897727, -3.51041, -0.09198),),((1.568572, -3.351983, 0.012491),),((1.266747, -3.76173, -0.034239),),((0.967631, -3.591928, 0.046191),),((0.972388, -3.609683, 1e-06),),((0.962676, -3.573439, 0.012491),),((1.112487, -4.608877, -0.106922),),((0.594285, -3.924549, -0.034239),),((0.329198, -3.705386, 0.046191),),((0.535857, -4.02216, -0.101049),),((1.167799, -4.700566, -0.092682),),((1.226157, -3.868004, -0.101049),),((1.711195, -4.701469, 0.037363),),((1.25932, -3.786618, -0.091981),),((-3.267881, 3.435161, -0.106922),),((-3.205932, 3.820682, 0.001066),),((-2.620422, 2.613351, 0.012491),),((-2.983909, 2.649644, -0.091979),),((-3.859543, 2.83651, -0.137251),),((-3.065152, 2.140139, 1e-06),),((-3.050095, 2.129595, 0.046191),),((-3.034415, 2.118616, 0.012491),),((-3.398682, 2.091239, -0.091979),),)+mdb.models['Model-1'].parts['Circular_knit - 2, 3, 9'].edges.findAt(((-4.319341, 2.493773, 0.001066),),((-4.245698, 2.110314, -0.106922),),((-3.695902, 1.447609, -0.034239),),((-4.547648, 1.340996, -0.106922),),((-3.576027, 0.953017, 0.012491),),((-3.908966, 0.802706, -0.09198),),((-4.760715, 0.526717, -0.137252),),((-3.724569, 0.320838, 1e-06),),((-4.816498, 0.510316, -0.092682),),((-3.962868, 0.872119, -0.101049),),((-3.612271, 0.962729, 1e-06),),((-2.633957, 2.626886, 0.046191),),((0.866078, -4.911774, 0.001066),),((1.133308, -4.653757, -0.137251),),((0.295263, -4.732039, -0.106922),),((-0.096234, -3.968123, -0.034239),),((-0.530933, -4.711421, -0.106922),),((-0.78383, -3.891127, -0.034239),),((-0.957971, -3.594516, 0.046191),),((-0.872119, -3.962868, -0.101049),),((-0.868796, -4.927189, 0.037363),),((-0.802706, -3.908966, -0.09198),),((-1.345405, -4.596926, -0.137251),),((-1.711195, -4.701469, 0.037363),),((-1.338939, -4.65471, -0.092682),),((0.3308, -3.723697, 1e-06),),((0.333813, -4.831941, -0.092682),),((0.0, -5.003198, 0.037363),),((0.0, -4.987546, 0.001066),),((0.868796, -4.927189, 0.037363),),((-2.9779, 2.62438, -0.034239),),((-3.820682, 3.205932, 0.001066),),((-3.832672, 3.215994, 0.037363),),((-3.916052, 2.850196, -0.092682),),((-3.425595, 2.174904, -0.101049),),((-3.388378, 2.067403, -0.034239),),((-3.814744, 2.815512, -0.106922),),((-4.293462, 2.123214, -0.137251),),((-3.390216, 1.575367, 1e-06),),((-4.35149, 2.12688, -0.092682),),((-4.332897, 2.501599, 0.037363),),((-3.373557, 1.567599, 0.046191),),((-3.356209, 1.559509, 0.012491),),((-3.710189, 1.469294, -0.091979),),((-4.701469, 1.711195, 0.037363),),((-4.65471, 1.338939, -0.092682),),((-3.594516, 0.957971, 0.046191),),((-4.68676, 1.705841, 0.001066),),((-4.596926, 1.345405, -0.137251),),((-3.891127, 0.78383, -0.034239),),((-4.927189, 0.868796, 0.037363),),((-3.687189, 0.317568, 0.012491),),((-3.988971, 0.111726, -0.091981),),((-4.779853, -0.307975, -0.137252),),((-3.723697, -0.3308, 1e-06),),((-4.831941, -0.333813, -0.092682),),((-4.054105, 0.170725, -0.101049),),((-3.706257, 0.319236, 0.046191),),((-4.711421, 0.530933, -0.106922),),((-4.911774, 0.866078, 0.001066),),((-2.995885, 2.736711, -0.101049),),((0.32753, -3.686317, 0.012491),),((0.582649, -3.94777, -0.091981),),((-0.319236, -3.706257, 0.046191),),((-0.317568, -3.687189, 0.012491),),((-0.111726, -3.988971, -0.091981),),((0.307975, -4.779853, -0.137252),),((-0.866078, -4.911774, 0.001066),),((-0.526717, -4.760715, -0.137252),),((-0.320838, -3.724569, 1e-06),),((-0.510316, -4.816498, -0.092682),),((-0.953017, -3.576027, 0.012491),),((-0.962729, -3.612271, 1e-06),),((-1.705841, -4.68676, 0.001066),),((-1.469294, -3.710189, -0.091979),),((-2.123214, -4.293462, -0.137251),),((-2.091239, -3.398682, -0.091979),),((-2.83651, -3.859543, -0.137251),),((-2.649644, -2.983909, -0.091979),),((-3.463619, -3.308353, -0.137251),),((-3.820682, -3.205932, 0.001066),),((-3.101617, -2.476941, -0.034239),),((-3.044359, -2.137787, 0.046191),),((-3.215364, -2.475146, -0.101049),),((-3.832672, -3.215994, 0.037363),),((-3.127541, -2.478471, -0.091979),),((-3.985488, -2.656641, -0.137251),),((-4.332897, -2.501599, 0.037363),),((-3.59632, -1.879201, -0.101049),),((-3.38599, -1.58443, 1e-06),),((-3.351983, -1.568572, 0.012491),),((-3.484612, -1.90072, -0.034239),),((-4.319341, -2.493773, 0.001066),),((-1.547014, -3.751221, -0.101049),),((-1.575367, -3.390216, 1e-06),),((-1.559509, -3.356209, 0.012491),),((-1.567599, -3.373557, 0.046191),),((-0.170725, -4.054105, -0.101049),),((-3.751221, 1.547014, -0.101049),),((-3.968123, 0.096234, -0.034239),),((-5.003198, 0.0, 0.037363),),((-3.686317, -0.32753, 0.012491),),((-3.94777, -0.582649, -0.091981),),((-4.653757, -1.133308, -0.137251),),((-3.609683, -0.972388, 1e-06),),((-3.591928, -0.967631, 0.046191),),((-4.608877, -1.112487, -0.106922),),((-4.911774, -0.866078, 0.001066),),((-3.705386, -0.329198, 0.046191),),((-4.732039, -0.295263, -0.106922),),((-1.340996, -4.547648, -0.106922),),((-1.447609, -3.695902, -0.034239),),((-2.501599, -4.332897, 0.037363),),((-2.174904, -3.425595, -0.101049),),((-2.850196, -3.916052, -0.092682),),((-2.736711, -2.995885, -0.101049),),((-2.639883, -2.646954, 1e-06),),((-2.613351, -2.620422, 0.012491),),((-3.435161, -3.267881, -0.106922),),((-2.140139, -3.065152, 1e-06),),((-2.129595, -3.050095, 0.046191),),((-2.815512, -3.814744, -0.106922),),((-3.205932, -3.820682, 0.001066),),((-3.215994, -3.832672, 0.037363),),((-3.950435, -2.621725, -0.106922),),((-3.059416, -2.14833, 1e-06),),((-4.017677, -2.705061, -0.092682),),((-3.48691, -3.361627, -0.092682),),((-2.626886, -2.633957, 0.046191),),((-3.51041, -1.897727, -0.09198),),((-4.426368, -1.966302, -0.092682),),((-3.369331, -1.576662, 0.046191),),((-4.345677, -1.895909, -0.106922),),((-4.68676, -1.705841, 0.001066),),((-3.786618, -1.25932, -0.091981),),((-2.12688, -4.35149, -0.092682),),((-2.110314, -4.245698, -0.106922),),((-2.493773, -4.319341, 0.001066),),((-4.987546, 0.0, 0.001066),),((-4.927189, -0.868796, 0.037363),),((-4.700566, -1.167799, -0.092682),),((-3.573439, -0.962676, 0.012491),),((-3.868004, -1.226157, -0.101049),),((-3.76173, -1.266747, -0.034239),),((-3.924549, -0.594285, -0.034239),),((-4.02216, -0.535857, -0.101049),),((-2.62438, -2.9779, -0.034239),),((-2.118616, -3.034415, 0.012491),),((-2.067403, -3.388378, -0.034239),),((-3.028679, -2.126808, 0.012491),),((-4.38626, -1.924207, -0.137251),),((-4.701469, -1.711195, 0.037363),),)
Do not use getSequenceFromMask
This method seems very appealing, however, Abaqus documentation does not cover how masks are formed, so it is not possible to artificially generate a mask for a set of objects.
Use coordinates (findAt()) or indeces instead
Most of the time if your geometry is complex and is generated without control over vertices/edges/etc numbering then the findAt() method is your only option (along with methods getByBoundingBox(...), getByBoundingCylinder(...) and getByBoundingSphere(...)).
If searching edge-by-edge is not very efficient and getByBounding... methods do not allow you to select the right array of edges then you can try: 1) to find the first edge of your sequence; 2) then use (as you already tried) the getEdgesByEdgeAngle(...) method to find all adjacent edges.
If you know for sure the numbering of your geometrical entities (vertices/edges/etc.) then you can access them by their index. So, using notations from your example, if edges of interest of your geometry have indexes from n to m then:
part = mdb.models['Model-1'].parts['Circular_knit - 2, 3, 10']
set2 = part.Set(name='Set-2', edges=part.edges[n:m+1])
Related
get the index of string element in np1 while it has a substring in np2
my code is as below:
import numpy as np
keywordlist = ['cpp-4.8.5', 'CUnit-2.1.3', 'CUnit-devel', 'doxygen-1.8.5', 'e2fsprogs-1.42.9', 'e2fsprogs-libs', 'epel-release', 'fuse3-devel', 'fuse3-libs', 'gcc-4.8.5', 'gcc-c++', 'gcc-gfortran', 'ghc-array', 'ghc-base', 'ghc-bytestring', 'ghc-containers', 'ghc-deepseq', 'ghc-directory', 'ghc-filepath', 'ghc-json', 'ghc-mtl', 'ghc-old', 'ghc-parsec', 'ghc-pretty', 'ghc-regex', 'ghc-regex', 'ghc-ShellCheck', 'ghc-syb', 'ghc-text', 'ghc-time', 'ghc-transformers', 'ghc-unix', 'git-1.8.3.1', 'graphviz-2.30.1', 'help2man-1.41.1', 'ibacm-22.4', 'keyutils-libs', 'krb5-devel', 'krb5-libs', 'krb5-workstation', 'lcov-1.13', 'libaio-devel', 'libblkid-2.23.2', 'libcom_err-1.42.9', 'libcom_err-devel', 'libgcc-4.8.5', 'libgfortran-4.8.5', 'libgomp-4.8.5', 'libibumad-22.4', 'libibverbs-22.4', 'libiscsi-devel', 'libkadm5-1.15.1', 'libmount-2.23.2', 'libpmem-1.5.1', 'libpmemblk-1.5.1', 'libpmemblk-devel', 'libpmem-devel', 'libquadmath-4.8.5', 'libquadmath-devel', 'librdmacm-22.4', 'libselinux-2.5', 'libselinux-devel', 'libselinux-python', 'libselinux-utils', 'libsepol-devel', 'libsmartcols-2.23.2', 'libss-1.42.9', 'libstdc++-4.8.5', 'libstdc++-devel', 'libunwind-1.2', 'libunwind-devel', 'libuuid-2.23.2', 'libuuid-devel', 'libverto-devel', 'libXaw-1.0.13', 'libXScrnSaver-1.2.2', 'make-3.82', 'nasm-2.10.07', 'numactl-devel', 'numactl-libs', 'openssl-1.0.2k', 'openssl-devel', 'openssl-libs', 'pcre-devel', 'perl-Digest', 'perl-Digest', 'perl-GD', 'perl-Git', 'python-2.7.5', 'python2-pycodestyle', 'python-libs', 'rdma-core', 'rdma-core', 'sg3_utils-1.37', 'sg3_utils-libs', 'ShellCheck-0.3.8', 'util-linux', 'zlib-devel']
np1 = np.array(keywordlist)
# ['cpp-4.8.5' 'CUnit-2.1.3' 'CUnit-devel' 'doxygen-1.8.5' ... 'ShellCheck-0.3.8' 'util-linux' 'zlib-devel']
result = ['epel-release-7-12.noarch', 'rdma-core-22.4-5.el7.x86_64', 'cpp-4.8.5-44.el7.x86_64', 'doxygen-1.8.5-4.el7.x86_64', 'ghc-base-4.6.0.1-26.4.el7.x86_64', 'libuuid-2.23.2-65.el7.x86_64', 'python-libs-2.7.5-89.el7.x86_64', 'libkadm5-1.15.1-50.el7.x86_64', 'libmount-2.23.2-65.el7.x86_64', 'libquadmath-4.8.5-44.el7.x86_64', 'util-linux-2.23.2-65.el7.x86_64', 'libss-1.42.9-19.el7.x86_64', 'keyutils-libs-1.5.8-3.el7.x86_64', 'e2fsprogs-libs-1.42.9-19.el7.x86_64', 'ghc-pretty-1.1.1.0-26.4.el7.x86_64', 'libXaw-1.0.13-4.el7.x86_64', 'libselinux-2.5-15.el7.x86_64', 'libibverbs-22.4-5.el7.x86_64', 'libselinux-utils-2.5-15.el7.x86_64', 'libgomp-4.8.5-44.el7.x86_64', 'libblkid-2.23.2-65.el7.x86_64', 'gcc-c++-4.8.5-44.el7.x86_64', 'e2fsprogs-1.42.9-19.el7.x86_64', 'CUnit-devel-2.1.3-8.el7.x86_64', 'make-3.82-24.el7.x86_64', 'numactl-libs-2.0.12-5.el7.x86_64', 'perl-Git-1.8.3.1-23.el7_8.noarch', 'openssl-libs-1.0.2k-19.el7.x86_64', 'gcc-4.8.5-44.el7.x86_64', 'CUnit-2.1.3-8.el7.x86_64', 'ghc-syb-0.4.0-35.el7.x86_64', 'gcc-gfortran-4.8.5-44.el7.x86_64', 'libselinux-python-2.5-15.el7.x86_64', 'sg3_utils-libs-1.37-19.el7.x86_64', 'fuse3-libs-3.6.1-4.el7.x86_64', 'libquadmath-devel-4.8.5-44.el7.x86_64', 'libgfortran-4.8.5-44.el7.x86_64', 'krb5-workstation-1.15.1-50.el7.x86_64', 'librdmacm-22.4-5.el7.x86_64', 'sg3_utils-1.37-19.el7.x86_64', 'libsmartcols-2.23.2-65.el7.x86_64', 'fuse3-devel-3.6.1-4.el7.x86_64', 'python-2.7.5-89.el7.x86_64', 'openssl-1.0.2k-19.el7.x86_64', 'libgcc-4.8.5-44.el7.x86_64', 'libaio-devel-0.3.109-13.el7.x86_64', 'ghc-old-locale-1.0.0.5-26.4.el7.x86_64', 'libcom_err-1.42.9-19.el7.x86_64', 'git-1.8.3.1-23.el7_8.x86_64', 'krb5-libs-1.15.1-50.el7.x86_64']
np2 = np.array(result)
# ['epel-release-7-12.noarch' 'rdma-core-22.4-5.el7.x86_64' ... 'krb5-libs-1.15.1-50.el7.x86_64']
expectation = ['cpp-4.8.5-39.el7.x86_64', 'CUnit-2.1.3-8.el7.x86_64', 'CUnit-devel-2.1.3-8.el7.x86_64', 'doxygen-1.8.5-4.el7.x86_64', 'e2fsprogs-1.42.9-17.el7.x86_64', 'e2fsprogs-libs-1.42.9-17.el7.x86_64', 'epel-release-latest-7.noarch', 'fuse3-devel-3.6.1-4.el7.x86_64', 'fuse3-libs-3.6.1-4.el7.x86_64', 'gcc-4.8.5-39.el7.x86_64', 'gcc-c++-4.8.5-39.el7.x86_64', 'gcc-gfortran-4.8.5-39.el7.x86_64', 'ghc-array-0.4.0.1-26.4.el7.x86_64', 'ghc-base-4.6.0.1-26.4.el7.x86_64', 'ghc-bytestring-0.10.0.2-26.4.el7.x86_64', 'ghc-containers-0.5.0.0-26.4.el7.x86_64', 'ghc-deepseq-1.3.0.1-26.4.el7.x86_64', 'ghc-directory-1.2.0.1-26.4.el7.x86_64', 'ghc-filepath-1.3.0.1-26.4.el7.x86_64', 'ghc-json-0.7-4.el7.x86_64', 'ghc-mtl-2.1.2-27.el7.x86_64', 'ghc-old-locale-1.0.0.5-26.4.el7.x86_64', 'ghc-parsec-3.1.3-31.el7.x86_64', 'ghc-pretty-1.1.1.0-26.4.el7.x86_64', 'ghc-regex-base-0.93.2-29.el7.x86_64', 'ghc-regex-tdfa-1.1.8-11.el7.x86_64', 'ghc-ShellCheck-0.3.8-1.el7.x86_64', 'ghc-syb-0.4.0-35.el7.x86_64', 'ghc-text-0.11.3.1-2.el7.x86_64', 'ghc-time-1.4.0.1-26.4.el7.x86_64', 'ghc-transformers-0.3.0.0-34.el7.x86_64', 'ghc-unix-2.6.0.1-26.4.el7.x86_64', 'git-1.8.3.1-23.el7_8.x86_64', 'graphviz-2.30.1-21.el7.x86_64', 'help2man-1.41.1-3.el7.noarch', 'ibacm-22.4-2.el7_8.x86_64', 'keyutils-libs-devel-1.5.8-3.el7.x86_64', 'krb5-devel-1.15.1-46.el7.x86_64', 'krb5-libs-1.15.1-46.el7.x86_64', 'krb5-workstation-1.15.1-46.el7.x86_64', 'lcov-1.13-1.el7.noarch', 'libaio-devel-0.3.109-13.el7.x86_64', 'libblkid-2.23.2-63.el7.x86_64', 'libcom_err-1.42.9-17.el7.x86_64', 'libcom_err-devel-1.42.9-17.el7.x86_64', 'libgcc-4.8.5-39.el7.x86_64', 'libgfortran-4.8.5-39.el7.x86_64', 'libgomp-4.8.5-39.el7.x86_64', 'libibumad-22.4-2.el7_8.x86_64', 'libibverbs-22.4-2.el7_8.x86_64', 'libiscsi-devel-1.9.0-7.el7.x86_64', 'libkadm5-1.15.1-46.el7.x86_64', 'libmount-2.23.2-63.el7.x86_64', 'libpmem-1.5.1-2.1.el7.x86_64', 'libpmemblk-1.5.1-2.1.el7.x86_64', 'libpmemblk-devel-1.5.1-2.1.el7.x86_64', 'libpmem-devel-1.5.1-2.1.el7.x86_64', 'libquadmath-4.8.5-39.el7.x86_64', 'libquadmath-devel-4.8.5-39.el7.x86_64', 'librdmacm-22.4-2.el7_8.x86_64', 'libselinux-2.5-15.el7.x86_64', 'libselinux-devel-2.5-15.el7.x86_64', 'libselinux-python-2.5-15.el7.x86_64', 'libselinux-utils-2.5-15.el7.x86_64', 'libsepol-devel-2.5-10.el7.x86_64', 'libsmartcols-2.23.2-63.el7.x86_64', 'libss-1.42.9-17.el7.x86_64', 'libstdc++-4.8.5-39.el7.x86_64', 'libstdc++-devel-4.8.5-39.el7.x86_64', 'libunwind-1.2-2.el7.x86_64', 'libunwind-devel-1.2-2.el7.x86_64', 'libuuid-2.23.2-63.el7.x86_64', 'libuuid-devel-2.23.2-63.el7.x86_64', 'libverto-devel-0.2.5-4.el7.x86_64', 'libXaw-1.0.13-4.el7.x86_64', 'libXScrnSaver-1.2.2-6.1.el7.x86_64', 'make-3.82-24.el7.x86_64', 'nasm-2.10.07-7.el7.x86_64', 'numactl-devel-2.0.12-5.el7.x86_64', 'numactl-libs-2.0.12-5.el7.x86_64', 'openssl-1.0.2k-19.el7.x86_64', 'openssl-devel-1.0.2k-19.el7.x86_64', 'openssl-libs-1.0.2k-19.el7.x86_64', 'pcre-devel-8.32-17.el7.x86_64', 'perl-Digest-1.17-245.el7.noarch', 'perl-Digest-MD5-2.52-3.el7.x86_64', 'perl-GD-2.49-3.el7.x86_64', 'perl-Git-1.8.3.1-23.el7_8.noarch', 'python-2.7.5-88.el7.x86_64', 'python2-pycodestyle-2.5.0-1.el7.noarch', 'python-libs-2.7.5-88.el7.x86_64', 'rdma-core-22.4-2.el7_8.x86_64', 'rdma-core-devel-22.4-2.el7_8.x86_64', 'sg3_utils-1.37-19.el7.x86_64', 'sg3_utils-libs-1.37-19.el7.x86_64', 'ShellCheck-0.3.8-1.el7.x86_64', 'util-linux-2.23.2-63.el7.x86_64', 'zlib-devel-1.2.7-18.el7.x86_64']
np3 = np.array(expectation)
# ['cpp-4.8.5-39.el7.x86_64' 'CUnit-2.1.3-8.el7.x86_64' ... 'util-linux-2.23.2-63.el7.x86_64' 'zlib-devel-1.2.7-18.el7.x86_64']
ready = []
for i in keywordlist:
for j in result:
x = np.char.startswith(j, i)
if x:
ready.append(np3[np.where(np.char.startswith(np3, i))])
np4 = np.array(ready)
# [array(['cpp-4.8.5-39.el7.x86_64'], dtype='<U39') array(['CUnit-2.1.3-8.el7.x86_64'], dtype='<U39') ... array(['util-linux-2.23.2-63.el7.x86_64'], dtype='<U39')]
notready = [i for i in np3 if i not in np4]
print(f"not ready: {notready}")
The purpose is to use string format keyword in keyword list to examine its existence in all np2 elements.
If any element in np2 starts with any keyword, or keyword is the substring of any element in np2, get the index of element in expectation which also start with that keyword and form into np4.
Finally， get not ready which is made up of elements that are in np3 but not in np4.
To make my explanation more vividly, I have a bunch of rpm files to be installed, the list of expectation.
The keyword list catches the former two keywords of each rpm file name.
Result is the standard output of already installed rpm files.
Taking cpp-4.8.5 as an example, I can see cpp-4.8.5-44.el7.x86_64 in result, which means currently cpp-4.8.5-44.el7.x86_64 has been installed. So, cpp-4.8.5-39.el7.x86_64 in expectation can be removed, since cpp-4.8.5-*.rpm has been successfully installed. Next step, deal with the other left items in expectation.
My question is: there any easier or more efficient way to get the result equivalent to notready? maybe with any other numpy built-in methods, but not with for loop.
How to work around ImageJ run("HSB stack") error/ bug?
I am working on a macro for ImageJ. The goal is to take colour scans with several seeds on them and crop around the seeds to get several equally sized images with one seed on each.
This is the basic idea for the macro: prompt to select folder with scans (info about the seed is in the name of the image) > threshold to select seeds > crop around each seed on the original image > save all of the cropped images in a folder (name of the cropped images still containing the information of the name of the original image)
When I run the code below, I get an error for line 31: run("HSB stack");
The error informs me about supported conversions and shows that in order to run this command I need to start with an RGB image. However, according to Fiji > Image > Type, my images are RGBs. A coding error in that part also seems unlikely since it was written with the recording function in ImageJ.
Error message
According to what I found for the error, this seems to concern a recurring bug in the software, specific to the commands run("HSB stack") and run("RGB stack") in macros.
We have tried running this on ImageJ 2.3.0/1.53s as well as 1.53q on MacOS and Windows and always got the same problem.
If it is not a software problem, where is the error? Or if it is, do you have any suggestions for workarounds or a different program that could perform the same job?
The images I am working with are colour scans, 600dpi, white background with between 1 and 90 seeds on each scan. They are large tiff images (107.4 MB) but look like this:
Example scan image
I am not sure if it is helpful, but the code is below. There are probably still errors in the latter part that I could not yet get to because I can't get past the problem in line 31.
// Directory
dir=getDirectory("Choose a data folder");
list = getFileList(dir);
processed_dir_name = dir + "Cropped" + File.separator;
print(processed_dir_name);
File.makeDirectory(processed_dir_name);
// Batch
for (i=0; j<list.length; i++) {
print(i + ":" + dir+list[i]};
// Open images
run("Bio-Formats Importer", "open=" + dir+list[i] + "color_mode=Default view =Hyperstack");
// Crop edge, set general cropping parameters, scale
makeRectangle(108, 60, 4908, 6888);
run("Crop");
main = getTitle():
default_crop_width = 350;
default_crop_height = 350;
run("Set Scale...", "distance=600 known=25.4 unit=mm global");
//Thresholding
run("Color Threshold...");
//Color Thresholder 2.3.0/1.53q
// Autogenerated macro, single images only!
min=newArray(3);
max=newArray(3);
filter=newArray(3);
a=getTitle();
run("HSB stack");
run("Convert Stack to images");
selectWindow("Hue");
rename("0");
selectWindow("Saturation");
rename("1");
selectWindow("Brightness");
rename("2");
min[0]=0;
max[0]=255;
filter[0]="pass";
min[1]=0;
max[1]=255;
filter[1]="pass";
min[2]=0;
max[2]=193;
filter[2]="pass";
for (i=0;j<3;i++){
selectWindow(""+i);
The problem lies in the fact that your image is a hyperstack, and the color thresholding doesn't know how to work with that.
There are a few options you could try: Open the image as an 8-bit RGB, e.g. via open(dir+list[i]); or split the channels of the hyperstack and threshold each separately. Based on your sample image, I assume the first option makes more sense.
The following is an edited version of your code that works for the sample that you've provided:
// Directory
dir=getDirectory("Choose a data folder");
list = getFileList(dir);
processed_dir_name = dir + "Cropped" + File.separator;
print(processed_dir_name);
File.makeDirectory(processed_dir_name);
// Batch
for (i=0; i<list.length; i++)
{
if (!File.isDirectory(dir+list[i])) // Ignore directories such as processed_dir_name
{
print(i + ":" + dir+list[i]);
// Open images
open(dir+list[i]);
// Crop edge, set general cropping parameters, scale
makeRectangle(108, 60, 4908, 6888);
run("Crop");
main = getTitle();
default_crop_width = 350;
default_crop_height = 350;
run("Set Scale...", "distance=600 known=25.4 unit=mm global");
//Thresholding
//run("Color Threshold...");
//Color Thresholder 2.3.0/1.53q
// Autogenerated macro, single images only!
min=newArray(3);
max=newArray(3);
filter=newArray(3);
a=getTitle();
run("HSB Stack");
run("Convert Stack to Images");
selectWindow("Hue");
rename("0");
selectWindow("Saturation");
rename("1");
selectWindow("Brightness");
rename("2");
min[0]=0;
max[0]=255;
filter[0]="pass";
min[1]=0;
max[1]=255;
filter[1]="pass";
min[2]=0;
max[2]=193;
filter[2]="pass";
for (j=0;j<3;j++){
selectWindow(""+j);
}
}
}
Random Forest Analysis Giving NaNs
I have a df that is all numeric values. Columns 1:1028 are the predictors and columns 1029:1033 are the responses. Here is a subset of this: PhHAL9G636300 PhHAL9G639600 PhHAL9G640000 PhHAL9G642000 PhHAL9G643800 PhHAL9G645300 PhHAL9G646100 PhHAL9G646600 PhHALJ003900 Biomass Growth WaterLoss PENW3 5.365778 2.98025485 5.495861 4.405202465 2.9113147 2.5418600 2.09767062 2.52296664 1.9087030 0.46125981 -13.4226665 -0.37320470 PENW1 3.490321 4.64568874 3.717329 3.604487984 2.1293068 2.2661013 -1.47617955 -0.83020824 -1.4564567 4.61259811 -14.4985291 -1.41470618 CERD2 4.602228 1.83881344 4.474194 2.395140203 3.7523682 -0.2886215 -0.73070022 2.79344405 -0.7981627 -0.76634289 5.5581189 15.96563076 COCW2 4.614825 1.59769640 5.498260 0.006269791 1.9118368 4.2591423 3.73962184 2.53800230 2.5671915 -0.13178852 -25.7182390 -0.07377302 PENW2 2.874244 3.33668026 2.686314 3.640362110 3.3344128 1.5625493 -1.92483779 0.85800308 -1.8455277 -0.09584619 -15.5743917 -0.99376599 NIGD3 2.534445 1.86024236 3.028953 3.531425944 4.2376438 2.0732650 -0.46514048 0.79555084 -0.5451820 1.05436439 12.0221867 21.04783002 PEND2 5.362056 2.64328649 4.464727 3.452061385 3.8409665 -0.5227258 -0.06950176 2.05314895 -1.5741809 0.68405104 4.6766551 11.99731270 CERD3 6.379754 3.02126477 5.958883 2.617817128 3.2571087 0.6389388 -1.54158346 2.70402517 -1.5102857 -0.98235901 4.4562891 15.74806130 PEND3 5.530008 3.49150186 4.664897 4.122665811 3.4805644 1.6611925 1.00556471 2.13871970 -0.5366320 0.42174575 3.2075488 12.88432662 NIGW3 4.183288 5.26329612 5.928775 8.194201254 1.4188970 3.3488663 -0.24100014 1.17649150 -0.3305682 0.29951936 1.1783257 1.30187685 SORW2 6.893395 3.84929409 7.853042 0.700629044 1.2822700 3.7429352 2.73703304 3.38057924 2.5338634 0.02995194 -12.5004986 -5.77946530 BISD3 7.044496 2.75794859 3.816874 2.703812532 2.6916801 2.3260304 3.37232732 2.31685090 1.7024061 -1.02864818 -0.6121276 14.66858209 COCD2 5.393332 3.05175638 5.822644 2.200587922 2.2212163 2.4246024 3.13408898 2.07709126 2.1863062 -0.10286482 -2.4485105 7.86349310 BISW2 2.174211 2.62450842 5.128353 4.037738498 1.3183220 0.9764650 0.53499762 1.02802526 0.4124477 1.55750066 -25.8719336 -13.89189391 SORD3 6.154951 2.22626768 4.676438 0.489662530 1.1602737 1.6238320 3.90773303 3.34912476 3.7395865 0.11315130 0.2693362 17.67178436 COCW3 4.341137 4.05631371 5.292476 2.505723413 0.4784145 0.1552958 2.35139206 2.34302308 1.9836908 -1.03034659 -25.2571550 -1.06753902 CERW1 4.980878 0.91666130 2.190792 1.724122567 3.0002243 -0.9078029 -1.30732267 1.90047369 -1.3084019 -0.11381736 -10.3487734 -0.48603403 NIGW1 4.310666 5.24869379 6.482000 6.341412520 2.6579484 3.7324397 -0.69538644 1.39456781 -0.7667490 -0.07787503 1.9467990 -2.35639710 SORD2 3.439050 1.01743984 3.608031 1.984325521 0.9697594 1.9438491 2.75019240 3.59450372 3.0152745 -0.14915399 1.8118978 19.30355526 BISW3 4.995399 3.02559441 5.391413 0.707718031 -0.0867396 2.1041361 3.57258520 2.88651590 2.2532781 1.48561601 -26.3330176 -12.63775254 SORD1 4.867184 3.58269882 5.082423 0.847579020 1.1842905 3.2943452 3.54584508 2.26684212 3.2791237 -1.80013432 -3.0361530 18.53648347 NIGD2 3.433412 1.38880580 5.344590 6.113465129 1.3389915 0.9967764 0.55527371 1.04742251 0.4318620 1.16237244 10.5530804 20.06039943 SORW3 6.832991 3.48434777 7.954499 -0.373941722 0.9673997 3.8959556 2.87342668 3.53076025 2.5194703 1.12619278 -7.8896590 -6.45557334 PEND1 4.536131 1.98241616 2.469180 2.938093546 4.6266296 -0.3003059 -1.62573524 1.53755316 -1.5869045 0.49889437 3.3544594 12.90013295 CERW3 3.947328 1.97539246 4.499408 1.135578151 2.1385166 -0.2011640 -0.65101772 -0.06185877 -0.7272633 -0.04193271 -7.1211857 -1.98319240 NIGD1 1.517705 -0.02588437 2.040182 4.303738855 3.0117854 -0.9594330 -1.35627738 0.18988023 -1.3514038 0.88463744 8.0555996 20.38861318 COCW1 4.705918 2.51742179 4.476741 0.975394641 1.2854224 3.7611179 3.28623937 2.48855442 3.5451750 0.60502910 -26.9477962 0.97206804 BISD2 4.838736 3.99032517 7.239421 2.461942761 2.4587895 2.0971745 3.19578030 2.09829508 1.4836582 -1.10579679 -0.9059489 14.44078502 I am following the IPMRF package manual (pg 7): #IMP based on CIT-RF (party package) library(randomForestSRC) library(party) mtcars.new <- mtcars ntree<-500 da<-mtcars.new[,3:10] mc.cf <- cforest(carb+ mpg+ cyl ~., data = mtcars.new, control = cforest_unbiased(mtry = 8, ntree = 500)) #IPM case-wise computing with OOB with party pupf<-ipmparty(mc.cf ,da,ntree) #global IPM pua<-apply(pupf,2,mean) pua But I am switching mtcars for my dataset. However, when I run mine, I get all NaNs in the output and I can not figure out what is wrong with my code. So far I've checked if everything is numeric, if it's a limit in predictors (tried 10 rather than 1028), changed mtcars to have negative values to check that since mine has negative values, but none of these seem to be the problem. Granted, please double check me just in case. Here is my code that I am running with my dataset: phallii.cf = cforest(Biomass + Growth + WaterLoss ~., data= RFTrainData, control=cforest_unbiased(mtry=33, ntree=1000)) #mtry = p/3 da = RFTrainData[,1:1028] #predictor variables only ntree=1000 phallii.ipm = ipmparty(phallii.cf, da, ntree) If anyone has any ideas I would greatly appreciate it!
OSMnx Limit on using "street network from bounding box": TypeError: graph_from_bbox() takes at most 15 arguments (77 given)
I am trying to get the drivable street network within some lat-long bounding box using the example 2a sample code from - https://geoffboeing.com/2016/11/osmnx-python-street-networks/ - but I am getting this error; TypeError: graph_from_bbox() takes at most 15 arguments (77 given). Below is what I have already tried out: G = ox.graph_from_bbox(29.94510876, 29.93205121, 29.93678994, 29.94840128, 29.94297549, 29.96456162, 29.96164721, 29.96828055, 29.91873862, 29.94221035, 29.95584061, 30.04064237, 29.93609316, 30.032814, 29.96624232, 30.00497466, 30.00427683, 29.94665333, 29.957519, 29.943813, 29.93076, 29.927549, 29.967799, 29.969906, 29.951438, 29.975021, 29.95932, 30.00816, 29.95056, 30.007622, 29.951881, 30.016095, 30.031229, 30.05131, 30.044959, 29.9382, 29.919781, 30.030601, -90.04488594, -90.07180566, -90.0849317, -90.12952617, -90.02696213, -90.03235984, -90.06925941, -90.09060393, -90.08716583, -90.11185615, -90.12122927, -89.91899769, -90.0844343, -89.97297866, -90.01417363, -90.10830816, -90.03988187, -90.07825592, -90.076855, -90.083341, -90.03282, -90.101536, -90.066648, -90.030283, -90.121145, -90.08682, -90.15624, -90.0648, -90.20634, -90.106042, -90.102726, -90.019069, -89.978768, -89.955024, -89.903415, -90.0685, -89.99601, -90.066334, network_type='drive') G_projected = ox.project_graph(G) ox.plot_graph(G_projected) G = ox.graph_from_bbox(29.94510876, 29.93205121, 29.93678994, 29.94840128, 29.94297549, 29.96456162, 29.96164721, 29.96828055, 29.91873862, 29.94221035, 29.95584061, 30.04064237, 29.93609316, 30.032814, 29.96624232, 30.00497466, 30.00427683, 29.94665333, 29.957519, 29.943813, 29.93076, 29.927549, 29.967799, 29.969906, 29.951438, 29.975021, 29.95932, 30.00816, 29.95056, 30.007622, 29.951881, 30.016095, 30.031229, 30.05131, 30.044959, 29.9382, 29.919781, 30.030601, -90.04488594, -90.07180566, -90.0849317, -90.12952617, -90.02696213, -90.03235984, -90.06925941, -90.09060393, -90.08716583, -90.11185615, -90.12122927, -89.91899769, -90.0844343, -89.97297866, -90.01417363, -90.10830816, -90.03988187, -90.07825592, -90.076855, -90.083341, -90.03282, -90.101536, -90.066648, -90.030283, -90.121145, -90.08682, -90.15624, -90.0648, -90.20634, -90.106042, -90.102726, -90.019069, -89.978768, -89.955024, -89.903415, -90.0685, -89.99601, -90.066334, network_type='drive') G_projected = ox.project_graph(G) ox.plot_graph(G_projected) I am expecting to get the drivable street network within those listed lat-long bounding box.
So the function is limited to taking only 4 arguments which define the coordinates (bounding box) and should be in the following order as mentioned in the docs (OSMNX). osmnx.core.graph_from_bbox(north, south, east, west) This means that one can only specify a rectangle as opposed to a generalised polygon, which I think you are trying to specify here. Hence the above error was thrown. import osmnx as ox G = ox.graph_from_bbox( -37.7860, -37.8359, 144.9903, 144.9269, network_type='drive', simplify=True, retain_all=False)
How to determine in which esriTransformDirection we need to use in ArcObject IGeometry5 ProjectEx
I am working on a project in which i need to calculate the points form on CRS to another, but as we the source and target CRS are only determine on runtime. ISpatialReference source = GCS_North_American_1983 ISpatialReference target = UTM Zone 13 North (108 W - 102 W Longitude) IEnvelope extent = rasterLayer.VisibleExtent; Console.WriteLine(extent.XMax); == -97.815540361118 Console.WriteLine(extent.XMin); == -102.045540576002 Console.WriteLine(extent.YMax); == 39.933228902485 Console.WriteLine(extent.YMin); == 37.113228759229 IGeoTransformation geoTransformation = "NAD_1927_To_NAD_1983_NADCON" geoTransformationOperationSet.Set(esriTransformDirection.esriTransformForward, geoTransformation); geoTransformationOperationSet.Set(esriTransformDirection.esriTransformReverse, geoTransformation); //So we need to go in reverse order. as source is in NAD83 and Target is in NAD27. and returns correct results matched with ArcMap but going forward results wrong output. geometry.ProjectEx(target, esriTransformDirection.esriTransformReverse, geoTransformation, false, 0.0, 0.0); Console.WriteLine(extent.XMax); == 1138797.89197912 Console.WriteLine(extent.XMin); == 752503.366222885 Console.WriteLine(extent.YMax); == 4444925.18943959 Console.WriteLine(extent.YMin); == 4111314.85519851 if we do the forward transformation return incorrect result. 1138738.17611084 752424.161510695 4444923.04572637 4111317.16066915 So how can I determine which direction we need to use? Like forward/reverse. Is there any way we can find out using arcobject API return use fwd or reverse. I looked into the IGeoTransformation but no success, there are many different predefined GeoTransformation which can use in both fwd or reverse if supported. Thanks.