Special Parsers¶

Some of the Tao python commands output special structures in a ; delimited fashion. Some PyTao methods parse these into more useful structures.

In [1]:

from pytao import Tao

from pytao import Tao

In [2]:

tao = Tao("-init $ACC_ROOT_DIR/regression_tests/pipe_test/cesr/tao.init -noplot")

tao = Tao("-init $ACC_ROOT_DIR/regression_tests/pipe_test/cesr/tao.init -noplot")

data_d_array¶

In [3]:

tao.data_d_array("orbit", "x")[7]

tao.data_d_array("orbit", "x")[7]

Out[3]:

{'ix_d1': 7,
 'data_type': 'orbit.x',
 'merit_type': 'target',
 'ele_ref_name': '',
 'ele_start_name': '',
 'ele_name': 'DET_07W',
 'meas_value': 0.0,
 'model_value': -0.00909995345022881,
 'design_value': -0.00909995345022881,
 'useit_opt': False,
 'useit_plot': False,
 'good_user': True,
 'weight': 1000000.0,
 'exists': True}

derivative¶

In [4]:

tao.cmd("veto var *;veto dat *;")
tao.cmd("use var quad_k1[3:5]")
tao.cmd("set dat orbit.x[1:5]|meas=0")
tao.cmd("use dat orbit.x[1:5]");

tao.cmd("veto var *;veto dat *;") tao.cmd("use var quad_k1[3:5]") tao.cmd("set dat orbit.x[1:5]|meas=0") tao.cmd("use dat orbit.x[1:5]");

In [5]:

result = tao.derivative()
result

result = tao.derivative() result

Out[5]:

{1: array([[-0.01758468, -0.03303895,  0.00216133],
        [-0.01711307, -0.03578881,  0.00283783],
        [ 0.00189157, -0.00956714,  0.002403  ],
        [-0.00893899,  0.00192383,  0.00267012]])}

n_datums x n_variables

In [6]:

result[1].shape

result[1].shape

Out[6]:

(4, 3)

ele_control_var¶

In [7]:

tao.ele_control_var("H01W")

tao.ele_control_var("H01W")

Out[7]:

{'HKICK': 0.0}

lat_ele_list¶

In [8]:

result = tao.lat_ele_list()

result[0:5]

result = tao.lat_ele_list() result[0:5]

Out[8]:

['BEGINNING', 'IP_L0', 'CLEO_SOL#3', 'DET_00W', 'CLEO_SOL#4']

matrix¶

In [9]:

tao.matrix("beginning", "end")

tao.matrix("beginning", "end")

Out[9]:

{'mat6': array([[-9.85453321e-01, -1.78459151e-01, -2.95064264e-02,
         -3.72328912e-05, -1.28463592e-03,  1.69890832e-03],
        [ 1.94136498e-01, -9.79571649e-01, -7.19934541e-03,
          8.91976963e-04, -5.89572298e-03, -3.81443689e-02],
        [-8.56326169e-04,  6.02559410e-05, -8.76189778e-01,
         -8.41353610e-03,  1.67854914e-05,  2.64910033e-03],
        [ 1.16108943e-02,  2.96794811e-02,  2.66272918e+01,
         -8.85649653e-01,  2.27202188e-05, -4.04349279e-02],
        [-8.86152164e-02, -6.13453961e-03,  3.48586759e-02,
         -2.68733720e-03,  9.47817657e-01, -8.79514378e+00],
        [ 5.30821801e-03, -2.93203403e-04,  1.07833932e-04,
         -1.59653540e-05,  1.15997844e-02,  9.47355161e-01]]),
 'vec0': array([ 3.92874185e-04,  4.73093997e-03,  1.86151033e-06, -9.57458176e-05,
        -7.06702237e-05,  5.03940903e-06])}

merit¶

In [10]:

tao.merit()

tao.merit()

Out[10]:

411.826621947948

plot_list¶

In [11]:

result = tao.plot_list("r")

result[0:2]

result = tao.plot_list("r") result[0:2]

Out[11]:

[{'region': 'top',
  'ix': 1,
  'plot_name': '',
  'visible': False,
  'x1': 0.0,
  'x2': 1.0,
  'y1': 0.48,
  'y2': 0.95},
 {'region': 'bottom',
  'ix': 2,
  'plot_name': '',
  'visible': False,
  'x1': 0.0,
  'x2': 1.0,
  'y1': 0.0,
  'y2': 0.48}]

In [12]:

# 't' gives a mapping of template plot to index
result = tao.plot_list("t")

result["cbar"]

# 't' gives a mapping of template plot to index result = tao.plot_list("t") result["cbar"]

Out[12]:

5

spin_invariant¶

In [13]:

tao.spin_invariant("l0")

tao.spin_invariant("l0")

Out[13]:

array([[ 0.        ,  0.99835696,  0.05730085],
       [ 0.        ,  0.99835696,  0.05730085],
       [-0.05286846,  0.99704205,  0.05578608],
       ...,
       [-0.24326431,  0.96860134,  0.05132168],
       [-0.29421324,  0.95443764,  0.0498734 ],
       [-0.29421324,  0.95443764,  0.0498734 ]], shape=(870, 3))

taylor_map¶

In [14]:

tt = tao.taylor_map("beginning", "end", order=2)
tt

tt = tao.taylor_map("beginning", "end", order=2) tt

Out[14]:

{1: {(0, 0, 0, 0, 0, 0): -1.66366331935176e-05,
  (1, 0, 0, 0, 0, 0): -0.985196712004978,
  (0, 1, 0, 0, 0, 0): -0.179943541553879,
  (0, 0, 1, 0, 0, 0): -0.0296993930689338,
  (2, 0, 0, 0, 0, 0): 0.446108376360043,
  (1, 1, 0, 0, 0, 0): -1.00840412690811,
  (0, 2, 0, 0, 0, 0): 1.02621408598452,
  (1, 0, 1, 0, 0, 0): -0.826526310689417,
  (0, 1, 1, 0, 0, 0): 0.66738975238496,
  (0, 0, 2, 0, 0, 0): 44.7241376522403,
  (0, 0, 0, 1, 0, 0): -3.8970786579565e-05,
  (1, 0, 0, 1, 0, 0): -0.00123736887685912,
  (0, 1, 0, 1, 0, 0): -0.037111736450792,
  (0, 0, 1, 1, 0, 0): -4.03450589559728,
  (0, 0, 0, 0, 1, 0): -0.00131163342342555,
  (1, 0, 0, 0, 1, 0): -0.149523435209748,
  (0, 1, 0, 0, 1, 0): 0.0299335213222391,
  (0, 0, 1, 0, 1, 0): 0.105807471287395,
  (0, 0, 0, 0, 0, 1): 0.00175860481206504,
  (1, 0, 0, 0, 0, 1): 2.90297313273057,
  (0, 1, 0, 0, 0, 1): 3.49580088045975,
  (0, 0, 1, 0, 0, 1): 7.97083495391285,
  (0, 0, 0, 2, 0, 0): -0.0184811091774087,
  (0, 0, 0, 1, 1, 0): -0.00392766901308479,
  (0, 0, 0, 0, 2, 0): 0.000742824197924029,
  (0, 0, 0, 1, 0, 1): 0.0279423395134347,
  (0, 0, 0, 0, 1, 1): -0.0134033172010638,
  (0, 0, 0, 0, 0, 2): -2.38971166203837},
 2: {(0, 0, 0, 0, 0, 0): 0.00239048642773681,
  (1, 0, 0, 0, 0, 0): 0.195138002493118,
  (0, 1, 0, 0, 0, 0): -0.979350347755823,
  (0, 0, 1, 0, 0, 0): -0.00732021296016823,
  (2, 0, 0, 0, 0, 0): 1.32511843855489,
  (1, 1, 0, 0, 0, 0): -0.169253235386875,
  (0, 2, 0, 0, 0, 0): 0.295823351810883,
  (1, 0, 1, 0, 0, 0): -0.962191303413663,
  (0, 1, 1, 0, 0, 0): 0.697983597586343,
  (0, 0, 2, 0, 0, 0): 100.484273524397,
  (0, 0, 0, 1, 0, 0): 0.000900228227261182,
  (1, 0, 0, 1, 0, 0): 0.0452520169954341,
  (0, 1, 0, 1, 0, 0): 0.0097237595133609,
  (0, 0, 1, 1, 0, 0): -2.89154417467537,
  (0, 0, 0, 0, 1, 0): -0.005895603143855,
  (1, 0, 0, 0, 1, 0): -0.0608697594082146,
  (0, 1, 0, 0, 1, 0): 0.131510316963394,
  (0, 0, 1, 0, 1, 0): 0.0812502671502623,
  (0, 0, 0, 0, 0, 1): -0.038187245824526,
  (1, 0, 0, 0, 0, 1): -9.55221126615965,
  (0, 1, 0, 0, 0, 1): -5.33578285297173,
  (0, 0, 1, 0, 0, 1): 4.52924011737334,
  (0, 0, 0, 2, 0, 0): 0.0629079369977707,
  (0, 0, 0, 1, 1, 0): -0.0014986359189501,
  (0, 0, 0, 0, 2, 0): 0.000587989290476936,
  (0, 0, 0, 1, 0, 1): -0.318535808858965,
  (0, 0, 0, 0, 1, 1): 0.0412944222742314,
  (0, 0, 0, 0, 0, 2): 0.766034293311184},
 3: {(0, 0, 0, 0, 0, 0): 1.0515763215525e-06,
  (1, 0, 0, 0, 0, 0): -0.000864193360888606,
  (0, 1, 0, 0, 0, 0): 6.23497462052501e-05,
  (0, 0, 1, 0, 0, 0): -0.873566454497795,
  (2, 0, 0, 0, 0, 0): -0.0217553558075661,
  (1, 1, 0, 0, 0, 0): 0.000631287940430662,
  (0, 2, 0, 0, 0, 0): -0.0181605962615151,
  (1, 0, 1, 0, 0, 0): 4.98227518044368,
  (0, 1, 1, 0, 0, 0): -3.43330387827155,
  (0, 0, 2, 0, 0, 0): -0.305561100969401,
  (0, 0, 0, 1, 0, 0): -0.00856834872271459,
  (1, 0, 0, 1, 0, 0): -0.132656653072126,
  (0, 1, 0, 1, 0, 0): -0.0220531115086416,
  (0, 0, 1, 1, 0, 0): 0.00641085060252567,
  (0, 0, 0, 0, 1, 0): 1.68093509091971e-05,
  (1, 0, 0, 0, 1, 0): 0.00244665980642929,
  (0, 1, 0, 0, 1, 0): -0.00396412903128415,
  (0, 0, 1, 0, 1, 0): -0.299055161154543,
  (0, 0, 0, 0, 0, 1): 0.00264467550362422,
  (1, 0, 0, 0, 0, 1): 0.319510925969635,
  (0, 1, 0, 0, 0, 1): 0.0141710069668825,
  (0, 0, 1, 0, 0, 1): -8.26626635917965,
  (0, 0, 0, 2, 0, 0): -0.000318155048313442,
  (0, 0, 0, 1, 1, 0): 0.000633772509646714,
  (0, 0, 0, 0, 2, 0): -2.10025933004997e-05,
  (0, 0, 0, 1, 0, 1): 0.0846818381893599,
  (0, 0, 0, 0, 1, 1): -0.00127341267516617,
  (0, 0, 0, 0, 0, 2): 0.0218741869008492},
 4: {(0, 0, 0, 0, 0, 0): 1.82087246910577e-06,
  (1, 0, 0, 0, 0, 0): 0.0117108773262394,
  (0, 1, 0, 0, 0, 0): 0.0298731605867765,
  (0, 0, 1, 0, 0, 0): 26.6637945907346,
  (2, 0, 0, 0, 0, 0): 0.0868154212323665,
  (1, 1, 0, 0, 0, 0): 0.861044547172263,
  (0, 2, 0, 0, 0, 0): 0.190821110096209,
  (1, 0, 1, 0, 0, 0): 92.6293368528103,
  (0, 1, 1, 0, 0, 0): 46.0396575980066,
  (0, 0, 2, 0, 0, 0): 0.449570842655751,
  (0, 0, 0, 1, 0, 0): -0.883232864349573,
  (1, 0, 0, 1, 0, 0): -0.0824329586467389,
  (0, 1, 0, 1, 0, 0): 4.59607348905793,
  (0, 0, 1, 1, 0, 0): 0.60897643502805,
  (0, 0, 0, 0, 1, 0): 2.46914546389749e-05,
  (1, 0, 0, 0, 1, 0): 0.0364418315318748,
  (0, 1, 0, 0, 1, 0): 0.00478840540608626,
  (0, 0, 1, 0, 1, 0): -0.706485573601523,
  (0, 0, 0, 0, 0, 1): -0.0404817456322482,
  (1, 0, 0, 0, 0, 1): -2.75082552578488,
  (0, 1, 0, 0, 0, 1): -8.49872065727191,
  (0, 0, 1, 0, 0, 1): -131.350469361068,
  (0, 0, 0, 2, 0, 0): 0.00467518361903948,
  (0, 0, 0, 1, 1, 0): 0.276221869133946,
  (0, 0, 0, 0, 2, 0): -1.88224706689664e-05,
  (0, 0, 0, 1, 0, 1): 4.50404232648761,
  (0, 0, 0, 0, 1, 1): 0.00433743886438137,
  (0, 0, 0, 0, 0, 2): 0.120061980604865},
 5: {(0, 0, 0, 0, 0, 0): -0.000398882588661428,
  (1, 0, 0, 0, 0, 0): -0.0886758653273395,
  (0, 1, 0, 0, 0, 0): -0.0060967948123514,
  (0, 0, 1, 0, 0, 0): 0.0349098945733697,
  (2, 0, 0, 0, 0, 0): -4.53639223085315,
  (1, 1, 0, 0, 0, 0): -3.2334051439405,
  (0, 2, 0, 0, 0, 0): -2.00770854973623,
  (1, 0, 1, 0, 0, 0): 6.72858859764847,
  (0, 1, 1, 0, 0, 0): -7.66972772273577,
  (0, 0, 2, 0, 0, 0): -193.642632680539,
  (0, 0, 0, 1, 0, 0): -0.00268389911768967,
  (1, 0, 0, 1, 0, 0): -0.311175087335103,
  (0, 1, 0, 1, 0, 0): -0.0386833165335798,
  (0, 0, 1, 1, 0, 0): 7.80657911683649,
  (0, 0, 0, 0, 1, 0): 0.947807431197128,
  (1, 0, 0, 0, 1, 0): 0.0363903902713366,
  (0, 1, 0, 0, 1, 0): 0.00980936090295559,
  (0, 0, 1, 0, 1, 0): -0.0420597362133058,
  (0, 0, 0, 0, 0, 1): -8.79504640834357,
  (1, 0, 0, 0, 0, 1): 1.2315638580293,
  (0, 1, 0, 0, 0, 1): 5.22581195573426,
  (0, 0, 1, 0, 0, 1): 1.12002951921809,
  (0, 0, 0, 2, 0, 0): -0.0114705886603623,
  (0, 0, 0, 1, 1, 0): 0.00185583353730949,
  (0, 0, 0, 0, 2, 0): -0.000315440257262236,
  (0, 0, 0, 1, 0, 1): -0.00772176644266498,
  (0, 0, 0, 0, 1, 1): 0.0125758928191825,
  (0, 0, 0, 0, 0, 2): 0.358289157829607},
 6: {(0, 0, 0, 0, 0, 0): -7.15739821666171e-06,
  (1, 0, 0, 0, 0, 0): 0.00531272335951633,
  (0, 1, 0, 0, 0, 0): -0.000311133855338647,
  (0, 0, 1, 0, 0, 0): 0.00010621473381561,
  (2, 0, 0, 0, 0, 0): -0.00967837592758609,
  (1, 1, 0, 0, 0, 0): -0.176395203912931,
  (0, 2, 0, 0, 0, 0): -0.0275604615086023,
  (1, 0, 1, 0, 0, 0): -0.0170187224784856,
  (0, 1, 1, 0, 0, 0): 0.00530105920106155,
  (0, 0, 2, 0, 0, 0): 2.02217526853222,
  (0, 0, 0, 1, 0, 0): -1.59179293270388e-05,
  (1, 0, 0, 1, 0, 0): -0.00164372025748337,
  (0, 1, 0, 1, 0, 0): -0.00408624712371079,
  (0, 0, 1, 1, 0, 0): -0.155773826126224,
  (0, 0, 0, 0, 1, 0): 0.0115997890382654,
  (1, 0, 0, 0, 1, 0): -0.000233337216477128,
  (0, 1, 0, 0, 1, 0): 0.00142789278074805,
  (0, 0, 1, 0, 1, 0): 0.000135626705220613,
  (0, 0, 0, 0, 0, 1): 0.947365021136244,
  (1, 0, 0, 0, 0, 1): -0.0563794701399377,
  (0, 1, 0, 0, 0, 1): 0.013279594421484,
  (0, 0, 1, 0, 0, 1): 0.00296525300489641,
  (0, 0, 0, 2, 0, 0): -0.000889800676997357,
  (0, 0, 0, 1, 1, 0): -1.09840049095265e-07,
  (0, 0, 0, 0, 2, 0): 4.33483140832018e-06,
  (0, 0, 0, 1, 0, 1): -0.00200396832898983,
  (0, 0, 0, 0, 1, 1): 0.000904983137930894,
  (0, 0, 0, 0, 0, 2): 0.0095857815977119}}

In [15]:

# Compare some terms with the matrix calc:
tao.matrix("beginning", "end")["mat6"][0, 0], tt[1][(1, 0, 0, 0, 0, 0)]

# Compare some terms with the matrix calc: tao.matrix("beginning", "end")["mat6"][0, 0], tt[1][(1, 0, 0, 0, 0, 0)]

Out[15]:

(np.float64(-0.985453321293568), -0.985196712004978)

In [16]:

tao.matrix("beginning", "end")["mat6"][1, 0], tt[2][(1, 0, 0, 0, 0, 0)]

tao.matrix("beginning", "end")["mat6"][1, 0], tt[2][(1, 0, 0, 0, 0, 0)]

Out[16]:

(np.float64(0.194136497704561), 0.195138002493118)

var_v_array¶

In [17]:

result = tao.var_v_array("quad_k1")
result[0:2]

result = tao.var_v_array("quad_k1") result[0:2]

Out[17]:

[{'ix_v1': 0,
  'var_attrib_name': 'Q00W[K1]',
  'meas_value': 0.0,
  'model_value': -0.841784836453016,
  'design_value': -0.841784836453016,
  'useit_opt': False,
  'good_user': False,
  'weight': 100000.0},
 {'ix_v1': 3,
  'var_attrib_name': 'Q03W[K1]',
  'meas_value': 0.0,
  'model_value': -0.128947,
  'design_value': -0.128947,
  'useit_opt': True,
  'good_user': True,
  'weight': 100000.0}]