[8a20be5] | 1 | #!/usr/bin/env python |
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| 2 | # -*- coding: utf-8 -*- |
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[caeb06d] | 3 | """ |
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| 4 | Program to compare models using different compute engines. |
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| 5 | |
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| 6 | This program lets you compare results between OpenCL and DLL versions |
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| 7 | of the code and between precision (half, fast, single, double, quad), |
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| 8 | where fast precision is single precision using native functions for |
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| 9 | trig, etc., and may not be completely IEEE 754 compliant. This lets |
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| 10 | make sure that the model calculations are stable, or if you need to |
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[9cfcac8] | 11 | tag the model as double precision only. |
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[caeb06d] | 12 | |
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[9cfcac8] | 13 | Run using ./compare.sh (Linux, Mac) or compare.bat (Windows) in the |
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[caeb06d] | 14 | sasmodels root to see the command line options. |
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| 15 | |
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[9cfcac8] | 16 | Note that there is no way within sasmodels to select between an |
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| 17 | OpenCL CPU device and a GPU device, but you can do so by setting the |
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[caeb06d] | 18 | PYOPENCL_CTX environment variable ahead of time. Start a python |
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| 19 | interpreter and enter:: |
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| 20 | |
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| 21 | import pyopencl as cl |
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| 22 | cl.create_some_context() |
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| 23 | |
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| 24 | This will prompt you to select from the available OpenCL devices |
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| 25 | and tell you which string to use for the PYOPENCL_CTX variable. |
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| 26 | On Windows you will need to remove the quotes. |
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| 27 | """ |
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| 28 | |
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| 29 | from __future__ import print_function |
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| 30 | |
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[190fc2b] | 31 | import sys |
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| 32 | import math |
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| 33 | import datetime |
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| 34 | import traceback |
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[ff1fff5] | 35 | import re |
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[190fc2b] | 36 | |
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[7ae2b7f] | 37 | import numpy as np # type: ignore |
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[190fc2b] | 38 | |
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| 39 | from . import core |
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| 40 | from . import kerneldll |
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[6831fa0] | 41 | from . import exception |
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[190fc2b] | 42 | from .data import plot_theory, empty_data1D, empty_data2D |
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| 43 | from .direct_model import DirectModel |
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[f247314] | 44 | from .convert import revert_name, revert_pars, constrain_new_to_old |
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[ff1fff5] | 45 | from .generate import FLOAT_RE |
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[190fc2b] | 46 | |
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[dd7fc12] | 47 | try: |
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| 48 | from typing import Optional, Dict, Any, Callable, Tuple |
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[6831fa0] | 49 | except Exception: |
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[dd7fc12] | 50 | pass |
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| 51 | else: |
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| 52 | from .modelinfo import ModelInfo, Parameter, ParameterSet |
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| 53 | from .data import Data |
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[8d62008] | 54 | Calculator = Callable[[float], np.ndarray] |
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[dd7fc12] | 55 | |
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[caeb06d] | 56 | USAGE = """ |
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| 57 | usage: compare.py model N1 N2 [options...] [key=val] |
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| 58 | |
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| 59 | Compare the speed and value for a model between the SasView original and the |
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| 60 | sasmodels rewrite. |
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| 61 | |
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| 62 | model is the name of the model to compare (see below). |
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| 63 | N1 is the number of times to run sasmodels (default=1). |
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| 64 | N2 is the number times to run sasview (default=1). |
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| 65 | |
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| 66 | Options (* for default): |
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| 67 | |
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| 68 | -plot*/-noplot plots or suppress the plot of the model |
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| 69 | -lowq*/-midq/-highq/-exq use q values up to 0.05, 0.2, 1.0, 10.0 |
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| 70 | -nq=128 sets the number of Q points in the data set |
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[e78edc4] | 71 | -zero indicates that q=0 should be included |
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[caeb06d] | 72 | -1d*/-2d computes 1d or 2d data |
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| 73 | -preset*/-random[=seed] preset or random parameters |
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| 74 | -mono/-poly* force monodisperse/polydisperse |
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| 75 | -cutoff=1e-5* cutoff value for including a point in polydispersity |
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| 76 | -pars/-nopars* prints the parameter set or not |
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| 77 | -abs/-rel* plot relative or absolute error |
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| 78 | -linear/-log*/-q4 intensity scaling |
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| 79 | -hist/-nohist* plot histogram of relative error |
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| 80 | -res=0 sets the resolution width dQ/Q if calculating with resolution |
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| 81 | -accuracy=Low accuracy of the resolution calculation Low, Mid, High, Xhigh |
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| 82 | -edit starts the parameter explorer |
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[98d6cfc] | 83 | -default/-demo* use demo vs default parameters |
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[234c532] | 84 | -html shows the model docs instead of running the model |
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[9068f4c] | 85 | -title="note" adds note to the plot title, after the model name |
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[caeb06d] | 86 | |
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| 87 | Any two calculation engines can be selected for comparison: |
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| 88 | |
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| 89 | -single/-double/-half/-fast sets an OpenCL calculation engine |
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| 90 | -single!/-double!/-quad! sets an OpenMP calculation engine |
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| 91 | -sasview sets the sasview calculation engine |
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| 92 | |
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| 93 | The default is -single -sasview. Note that the interpretation of quad |
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| 94 | precision depends on architecture, and may vary from 64-bit to 128-bit, |
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| 95 | with 80-bit floats being common (1e-19 precision). |
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| 96 | |
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| 97 | Key=value pairs allow you to set specific values for the model parameters. |
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| 98 | """ |
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| 99 | |
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| 100 | # Update docs with command line usage string. This is separate from the usual |
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| 101 | # doc string so that we can display it at run time if there is an error. |
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| 102 | # lin |
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[d15a908] | 103 | __doc__ = (__doc__ # pylint: disable=redefined-builtin |
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| 104 | + """ |
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[caeb06d] | 105 | Program description |
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| 106 | ------------------- |
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| 107 | |
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[d15a908] | 108 | """ |
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| 109 | + USAGE) |
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[caeb06d] | 110 | |
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[750ffa5] | 111 | kerneldll.ALLOW_SINGLE_PRECISION_DLLS = True |
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[87985ca] | 112 | |
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[248561a] | 113 | # list of math functions for use in evaluating parameters |
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| 114 | MATH = dict((k,getattr(math, k)) for k in dir(math) if not k.startswith('_')) |
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| 115 | |
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[7cf2cfd] | 116 | # CRUFT python 2.6 |
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| 117 | if not hasattr(datetime.timedelta, 'total_seconds'): |
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| 118 | def delay(dt): |
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| 119 | """Return number date-time delta as number seconds""" |
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| 120 | return dt.days * 86400 + dt.seconds + 1e-6 * dt.microseconds |
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| 121 | else: |
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| 122 | def delay(dt): |
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| 123 | """Return number date-time delta as number seconds""" |
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| 124 | return dt.total_seconds() |
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| 125 | |
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| 126 | |
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[4f2478e] | 127 | class push_seed(object): |
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| 128 | """ |
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| 129 | Set the seed value for the random number generator. |
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| 130 | |
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| 131 | When used in a with statement, the random number generator state is |
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| 132 | restored after the with statement is complete. |
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| 133 | |
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| 134 | :Parameters: |
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| 135 | |
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| 136 | *seed* : int or array_like, optional |
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| 137 | Seed for RandomState |
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| 138 | |
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| 139 | :Example: |
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| 140 | |
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| 141 | Seed can be used directly to set the seed:: |
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| 142 | |
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| 143 | >>> from numpy.random import randint |
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| 144 | >>> push_seed(24) |
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| 145 | <...push_seed object at...> |
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| 146 | >>> print(randint(0,1000000,3)) |
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| 147 | [242082 899 211136] |
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| 148 | |
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| 149 | Seed can also be used in a with statement, which sets the random |
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| 150 | number generator state for the enclosed computations and restores |
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| 151 | it to the previous state on completion:: |
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| 152 | |
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| 153 | >>> with push_seed(24): |
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| 154 | ... print(randint(0,1000000,3)) |
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| 155 | [242082 899 211136] |
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| 156 | |
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| 157 | Using nested contexts, we can demonstrate that state is indeed |
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| 158 | restored after the block completes:: |
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| 159 | |
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| 160 | >>> with push_seed(24): |
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| 161 | ... print(randint(0,1000000)) |
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| 162 | ... with push_seed(24): |
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| 163 | ... print(randint(0,1000000,3)) |
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| 164 | ... print(randint(0,1000000)) |
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| 165 | 242082 |
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| 166 | [242082 899 211136] |
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| 167 | 899 |
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| 168 | |
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| 169 | The restore step is protected against exceptions in the block:: |
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| 170 | |
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| 171 | >>> with push_seed(24): |
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| 172 | ... print(randint(0,1000000)) |
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| 173 | ... try: |
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| 174 | ... with push_seed(24): |
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| 175 | ... print(randint(0,1000000,3)) |
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| 176 | ... raise Exception() |
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[dd7fc12] | 177 | ... except Exception: |
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[4f2478e] | 178 | ... print("Exception raised") |
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| 179 | ... print(randint(0,1000000)) |
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| 180 | 242082 |
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| 181 | [242082 899 211136] |
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| 182 | Exception raised |
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| 183 | 899 |
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| 184 | """ |
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| 185 | def __init__(self, seed=None): |
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[dd7fc12] | 186 | # type: (Optional[int]) -> None |
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[4f2478e] | 187 | self._state = np.random.get_state() |
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| 188 | np.random.seed(seed) |
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| 189 | |
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| 190 | def __enter__(self): |
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[dd7fc12] | 191 | # type: () -> None |
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| 192 | pass |
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[4f2478e] | 193 | |
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[b32dafd] | 194 | def __exit__(self, exc_type, exc_value, traceback): |
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[dd7fc12] | 195 | # type: (Any, BaseException, Any) -> None |
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| 196 | # TODO: better typing for __exit__ method |
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[4f2478e] | 197 | np.random.set_state(self._state) |
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| 198 | |
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[7cf2cfd] | 199 | def tic(): |
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[dd7fc12] | 200 | # type: () -> Callable[[], float] |
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[7cf2cfd] | 201 | """ |
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| 202 | Timer function. |
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| 203 | |
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| 204 | Use "toc=tic()" to start the clock and "toc()" to measure |
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| 205 | a time interval. |
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| 206 | """ |
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| 207 | then = datetime.datetime.now() |
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| 208 | return lambda: delay(datetime.datetime.now() - then) |
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| 209 | |
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| 210 | |
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| 211 | def set_beam_stop(data, radius, outer=None): |
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[dd7fc12] | 212 | # type: (Data, float, float) -> None |
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[7cf2cfd] | 213 | """ |
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| 214 | Add a beam stop of the given *radius*. If *outer*, make an annulus. |
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| 215 | |
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[dd7fc12] | 216 | Note: this function does not require sasview |
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[7cf2cfd] | 217 | """ |
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| 218 | if hasattr(data, 'qx_data'): |
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| 219 | q = np.sqrt(data.qx_data**2 + data.qy_data**2) |
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| 220 | data.mask = (q < radius) |
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| 221 | if outer is not None: |
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| 222 | data.mask |= (q >= outer) |
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| 223 | else: |
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| 224 | data.mask = (data.x < radius) |
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| 225 | if outer is not None: |
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| 226 | data.mask |= (data.x >= outer) |
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| 227 | |
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[8a20be5] | 228 | |
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[ec7e360] | 229 | def parameter_range(p, v): |
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[dd7fc12] | 230 | # type: (str, float) -> Tuple[float, float] |
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[87985ca] | 231 | """ |
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[ec7e360] | 232 | Choose a parameter range based on parameter name and initial value. |
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[87985ca] | 233 | """ |
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[8bd7b77] | 234 | # process the polydispersity options |
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[ec7e360] | 235 | if p.endswith('_pd_n'): |
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[dd7fc12] | 236 | return 0., 100. |
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[ec7e360] | 237 | elif p.endswith('_pd_nsigma'): |
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[dd7fc12] | 238 | return 0., 5. |
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[ec7e360] | 239 | elif p.endswith('_pd_type'): |
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[dd7fc12] | 240 | raise ValueError("Cannot return a range for a string value") |
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[caeb06d] | 241 | elif any(s in p for s in ('theta', 'phi', 'psi')): |
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[87985ca] | 242 | # orientation in [-180,180], orientation pd in [0,45] |
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| 243 | if p.endswith('_pd'): |
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[dd7fc12] | 244 | return 0., 45. |
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[87985ca] | 245 | else: |
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[dd7fc12] | 246 | return -180., 180. |
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[87985ca] | 247 | elif p.endswith('_pd'): |
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[dd7fc12] | 248 | return 0., 1. |
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[8bd7b77] | 249 | elif 'sld' in p: |
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[dd7fc12] | 250 | return -0.5, 10. |
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[eb46451] | 251 | elif p == 'background': |
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[dd7fc12] | 252 | return 0., 10. |
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[eb46451] | 253 | elif p == 'scale': |
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[dd7fc12] | 254 | return 0., 1.e3 |
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| 255 | elif v < 0.: |
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| 256 | return 2.*v, -2.*v |
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[87985ca] | 257 | else: |
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[dd7fc12] | 258 | return 0., (2.*v if v > 0. else 1.) |
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[87985ca] | 259 | |
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[4f2478e] | 260 | |
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[8bd7b77] | 261 | def _randomize_one(model_info, p, v): |
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[dd7fc12] | 262 | # type: (ModelInfo, str, float) -> float |
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| 263 | # type: (ModelInfo, str, str) -> str |
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[ec7e360] | 264 | """ |
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[caeb06d] | 265 | Randomize a single parameter. |
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[ec7e360] | 266 | """ |
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[f3bd37f] | 267 | if any(p.endswith(s) for s in ('_pd', '_pd_n', '_pd_nsigma', '_pd_type')): |
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[ec7e360] | 268 | return v |
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[8bd7b77] | 269 | |
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| 270 | # Find the parameter definition |
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[6d6508e] | 271 | for par in model_info.parameters.call_parameters: |
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[8bd7b77] | 272 | if par.name == p: |
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| 273 | break |
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[ec7e360] | 274 | else: |
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[8bd7b77] | 275 | raise ValueError("unknown parameter %r"%p) |
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| 276 | |
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| 277 | if len(par.limits) > 2: # choice list |
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| 278 | return np.random.randint(len(par.limits)) |
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| 279 | |
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| 280 | limits = par.limits |
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| 281 | if not np.isfinite(limits).all(): |
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| 282 | low, high = parameter_range(p, v) |
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| 283 | limits = (max(limits[0], low), min(limits[1], high)) |
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| 284 | |
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| 285 | return np.random.uniform(*limits) |
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[cd3dba0] | 286 | |
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[4f2478e] | 287 | |
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[8bd7b77] | 288 | def randomize_pars(model_info, pars, seed=None): |
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[dd7fc12] | 289 | # type: (ModelInfo, ParameterSet, int) -> ParameterSet |
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[caeb06d] | 290 | """ |
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| 291 | Generate random values for all of the parameters. |
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| 292 | |
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| 293 | Valid ranges for the random number generator are guessed from the name of |
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| 294 | the parameter; this will not account for constraints such as cap radius |
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| 295 | greater than cylinder radius in the capped_cylinder model, so |
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| 296 | :func:`constrain_pars` needs to be called afterward.. |
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| 297 | """ |
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[4f2478e] | 298 | with push_seed(seed): |
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| 299 | # Note: the sort guarantees order `of calls to random number generator |
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[dd7fc12] | 300 | random_pars = dict((p, _randomize_one(model_info, p, v)) |
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| 301 | for p, v in sorted(pars.items())) |
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| 302 | return random_pars |
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[cd3dba0] | 303 | |
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[17bbadd] | 304 | def constrain_pars(model_info, pars): |
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[dd7fc12] | 305 | # type: (ModelInfo, ParameterSet) -> None |
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[9a66e65] | 306 | """ |
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| 307 | Restrict parameters to valid values. |
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[caeb06d] | 308 | |
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| 309 | This includes model specific code for models such as capped_cylinder |
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| 310 | which need to support within model constraints (cap radius more than |
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| 311 | cylinder radius in this case). |
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[dd7fc12] | 312 | |
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| 313 | Warning: this updates the *pars* dictionary in place. |
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[9a66e65] | 314 | """ |
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[6d6508e] | 315 | name = model_info.id |
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[17bbadd] | 316 | # if it is a product model, then just look at the form factor since |
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| 317 | # none of the structure factors need any constraints. |
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| 318 | if '*' in name: |
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| 319 | name = name.split('*')[0] |
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| 320 | |
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[bb2d187] | 321 | if name == 'capped_cylinder' and pars['radius_cap'] < pars['radius']: |
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| 322 | pars['radius'], pars['radius_cap'] = pars['radius_cap'], pars['radius'] |
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| 323 | if name == 'barbell' and pars['radius_bell'] < pars['radius']: |
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| 324 | pars['radius'], pars['radius_bell'] = pars['radius_bell'], pars['radius'] |
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[b514adf] | 325 | |
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| 326 | # Limit guinier to an Rg such that Iq > 1e-30 (single precision cutoff) |
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| 327 | if name == 'guinier': |
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| 328 | #q_max = 0.2 # mid q maximum |
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| 329 | q_max = 1.0 # high q maximum |
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| 330 | rg_max = np.sqrt(90*np.log(10) + 3*np.log(pars['scale']))/q_max |
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[caeb06d] | 331 | pars['rg'] = min(pars['rg'], rg_max) |
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[cd3dba0] | 332 | |
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[82c299f] | 333 | if name == 'rpa': |
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| 334 | # Make sure phi sums to 1.0 |
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| 335 | if pars['case_num'] < 2: |
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[8bd7b77] | 336 | pars['Phi1'] = 0. |
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| 337 | pars['Phi2'] = 0. |
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[82c299f] | 338 | elif pars['case_num'] < 5: |
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[8bd7b77] | 339 | pars['Phi1'] = 0. |
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| 340 | total = sum(pars['Phi'+c] for c in '1234') |
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| 341 | for c in '1234': |
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[82c299f] | 342 | pars['Phi'+c] /= total |
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| 343 | |
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[d6850fa] | 344 | def parlist(model_info, pars, is2d): |
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[dd7fc12] | 345 | # type: (ModelInfo, ParameterSet, bool) -> str |
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[caeb06d] | 346 | """ |
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| 347 | Format the parameter list for printing. |
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| 348 | """ |
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[a4a7308] | 349 | lines = [] |
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[6d6508e] | 350 | parameters = model_info.parameters |
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[d19962c] | 351 | for p in parameters.user_parameters(pars, is2d): |
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| 352 | fields = dict( |
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| 353 | value=pars.get(p.id, p.default), |
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| 354 | pd=pars.get(p.id+"_pd", 0.), |
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| 355 | n=int(pars.get(p.id+"_pd_n", 0)), |
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| 356 | nsigma=pars.get(p.id+"_pd_nsgima", 3.), |
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[dd7fc12] | 357 | pdtype=pars.get(p.id+"_pd_type", 'gaussian'), |
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[bd49c79] | 358 | relative_pd=p.relative_pd, |
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[dd7fc12] | 359 | ) |
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[d19962c] | 360 | lines.append(_format_par(p.name, **fields)) |
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[a4a7308] | 361 | return "\n".join(lines) |
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| 362 | |
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| 363 | #return "\n".join("%s: %s"%(p, v) for p, v in sorted(pars.items())) |
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| 364 | |
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[bd49c79] | 365 | def _format_par(name, value=0., pd=0., n=0, nsigma=3., pdtype='gaussian', |
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| 366 | relative_pd=False): |
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[dd7fc12] | 367 | # type: (str, float, float, int, float, str) -> str |
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[a4a7308] | 368 | line = "%s: %g"%(name, value) |
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| 369 | if pd != 0. and n != 0: |
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[bd49c79] | 370 | if relative_pd: |
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| 371 | pd *= value |
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[a4a7308] | 372 | line += " +/- %g (%d points in [-%g,%g] sigma %s)"\ |
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[dd7fc12] | 373 | % (pd, n, nsigma, nsigma, pdtype) |
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[a4a7308] | 374 | return line |
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[87985ca] | 375 | |
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| 376 | def suppress_pd(pars): |
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[dd7fc12] | 377 | # type: (ParameterSet) -> ParameterSet |
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[87985ca] | 378 | """ |
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| 379 | Suppress theta_pd for now until the normalization is resolved. |
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| 380 | |
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| 381 | May also suppress complete polydispersity of the model to test |
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| 382 | models more quickly. |
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| 383 | """ |
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[f4f3919] | 384 | pars = pars.copy() |
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[87985ca] | 385 | for p in pars: |
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[8b25ee1] | 386 | if p.endswith("_pd_n"): pars[p] = 0 |
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[f4f3919] | 387 | return pars |
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[87985ca] | 388 | |
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[17bbadd] | 389 | def eval_sasview(model_info, data): |
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[dd7fc12] | 390 | # type: (Modelinfo, Data) -> Calculator |
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[caeb06d] | 391 | """ |
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[f247314] | 392 | Return a model calculator using the pre-4.0 SasView models. |
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[caeb06d] | 393 | """ |
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[dc056b9] | 394 | # importing sas here so that the error message will be that sas failed to |
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| 395 | # import rather than the more obscure smear_selection not imported error |
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[2bebe2b] | 396 | import sas |
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[dd7fc12] | 397 | import sas.models |
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[8d62008] | 398 | from sas.models.qsmearing import smear_selection |
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| 399 | from sas.models.MultiplicationModel import MultiplicationModel |
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[050c2c8] | 400 | from sas.models.dispersion_models import models as dispersers |
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[ec7e360] | 401 | |
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[256dfe1] | 402 | def get_model_class(name): |
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[dd7fc12] | 403 | # type: (str) -> "sas.models.BaseComponent" |
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[17bbadd] | 404 | #print("new",sorted(_pars.items())) |
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[dd7fc12] | 405 | __import__('sas.models.' + name) |
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[17bbadd] | 406 | ModelClass = getattr(getattr(sas.models, name, None), name, None) |
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| 407 | if ModelClass is None: |
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| 408 | raise ValueError("could not find model %r in sas.models"%name) |
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[256dfe1] | 409 | return ModelClass |
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| 410 | |
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| 411 | # WARNING: ugly hack when handling model! |
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| 412 | # Sasview models with multiplicity need to be created with the target |
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| 413 | # multiplicity, so we cannot create the target model ahead of time for |
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| 414 | # for multiplicity models. Instead we store the model in a list and |
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| 415 | # update the first element of that list with the new multiplicity model |
---|
| 416 | # every time we evaluate. |
---|
[17bbadd] | 417 | |
---|
| 418 | # grab the sasview model, or create it if it is a product model |
---|
[6d6508e] | 419 | if model_info.composition: |
---|
| 420 | composition_type, parts = model_info.composition |
---|
[17bbadd] | 421 | if composition_type == 'product': |
---|
[51ec7e8] | 422 | P, S = [get_model_class(revert_name(p))() for p in parts] |
---|
[256dfe1] | 423 | model = [MultiplicationModel(P, S)] |
---|
[17bbadd] | 424 | else: |
---|
[72a081d] | 425 | raise ValueError("sasview mixture models not supported by compare") |
---|
[17bbadd] | 426 | else: |
---|
[f3bd37f] | 427 | old_name = revert_name(model_info) |
---|
| 428 | if old_name is None: |
---|
| 429 | raise ValueError("model %r does not exist in old sasview" |
---|
| 430 | % model_info.id) |
---|
[256dfe1] | 431 | ModelClass = get_model_class(old_name) |
---|
| 432 | model = [ModelClass()] |
---|
[050c2c8] | 433 | model[0].disperser_handles = {} |
---|
[216a9e1] | 434 | |
---|
[17bbadd] | 435 | # build a smearer with which to call the model, if necessary |
---|
| 436 | smearer = smear_selection(data, model=model) |
---|
[ec7e360] | 437 | if hasattr(data, 'qx_data'): |
---|
| 438 | q = np.sqrt(data.qx_data**2 + data.qy_data**2) |
---|
| 439 | index = ((~data.mask) & (~np.isnan(data.data)) |
---|
| 440 | & (q >= data.qmin) & (q <= data.qmax)) |
---|
| 441 | if smearer is not None: |
---|
| 442 | smearer.model = model # because smear_selection has a bug |
---|
| 443 | smearer.accuracy = data.accuracy |
---|
| 444 | smearer.set_index(index) |
---|
[256dfe1] | 445 | def _call_smearer(): |
---|
| 446 | smearer.model = model[0] |
---|
| 447 | return smearer.get_value() |
---|
[b32dafd] | 448 | theory = _call_smearer |
---|
[ec7e360] | 449 | else: |
---|
[256dfe1] | 450 | theory = lambda: model[0].evalDistribution([data.qx_data[index], |
---|
| 451 | data.qy_data[index]]) |
---|
[ec7e360] | 452 | elif smearer is not None: |
---|
[256dfe1] | 453 | theory = lambda: smearer(model[0].evalDistribution(data.x)) |
---|
[ec7e360] | 454 | else: |
---|
[256dfe1] | 455 | theory = lambda: model[0].evalDistribution(data.x) |
---|
[ec7e360] | 456 | |
---|
| 457 | def calculator(**pars): |
---|
[dd7fc12] | 458 | # type: (float, ...) -> np.ndarray |
---|
[caeb06d] | 459 | """ |
---|
| 460 | Sasview calculator for model. |
---|
| 461 | """ |
---|
[256dfe1] | 462 | oldpars = revert_pars(model_info, pars) |
---|
[bd49c79] | 463 | # For multiplicity models, create a model with the correct multiplicity |
---|
| 464 | control = oldpars.pop("CONTROL", None) |
---|
| 465 | if control is not None: |
---|
| 466 | # sphericalSLD has one fewer multiplicity. This update should |
---|
| 467 | # happen in revert_pars, but it hasn't been called yet. |
---|
| 468 | model[0] = ModelClass(control) |
---|
| 469 | # paying for parameter conversion each time to keep life simple, if not fast |
---|
[050c2c8] | 470 | for k, v in oldpars.items(): |
---|
| 471 | if k.endswith('.type'): |
---|
| 472 | par = k[:-5] |
---|
[6831fa0] | 473 | if v == 'gaussian': continue |
---|
[050c2c8] | 474 | cls = dispersers[v if v != 'rectangle' else 'rectangula'] |
---|
| 475 | handle = cls() |
---|
| 476 | model[0].disperser_handles[par] = handle |
---|
[6831fa0] | 477 | try: |
---|
| 478 | model[0].set_dispersion(par, handle) |
---|
| 479 | except Exception: |
---|
| 480 | exception.annotate_exception("while setting %s to %r" |
---|
| 481 | %(par, v)) |
---|
| 482 | raise |
---|
| 483 | |
---|
[050c2c8] | 484 | |
---|
[f67f26c] | 485 | #print("sasview pars",oldpars) |
---|
[256dfe1] | 486 | for k, v in oldpars.items(): |
---|
[dd7fc12] | 487 | name_attr = k.split('.') # polydispersity components |
---|
| 488 | if len(name_attr) == 2: |
---|
[050c2c8] | 489 | par, disp_par = name_attr |
---|
| 490 | model[0].dispersion[par][disp_par] = v |
---|
[ec7e360] | 491 | else: |
---|
[256dfe1] | 492 | model[0].setParam(k, v) |
---|
[ec7e360] | 493 | return theory() |
---|
| 494 | |
---|
| 495 | calculator.engine = "sasview" |
---|
| 496 | return calculator |
---|
| 497 | |
---|
| 498 | DTYPE_MAP = { |
---|
| 499 | 'half': '16', |
---|
| 500 | 'fast': 'fast', |
---|
| 501 | 'single': '32', |
---|
| 502 | 'double': '64', |
---|
| 503 | 'quad': '128', |
---|
| 504 | 'f16': '16', |
---|
| 505 | 'f32': '32', |
---|
| 506 | 'f64': '64', |
---|
| 507 | 'longdouble': '128', |
---|
| 508 | } |
---|
[17bbadd] | 509 | def eval_opencl(model_info, data, dtype='single', cutoff=0.): |
---|
[dd7fc12] | 510 | # type: (ModelInfo, Data, str, float) -> Calculator |
---|
[caeb06d] | 511 | """ |
---|
| 512 | Return a model calculator using the OpenCL calculation engine. |
---|
| 513 | """ |
---|
[a738209] | 514 | if not core.HAVE_OPENCL: |
---|
| 515 | raise RuntimeError("OpenCL not available") |
---|
| 516 | model = core.build_model(model_info, dtype=dtype, platform="ocl") |
---|
[7cf2cfd] | 517 | calculator = DirectModel(data, model, cutoff=cutoff) |
---|
[ec7e360] | 518 | calculator.engine = "OCL%s"%DTYPE_MAP[dtype] |
---|
| 519 | return calculator |
---|
[216a9e1] | 520 | |
---|
[17bbadd] | 521 | def eval_ctypes(model_info, data, dtype='double', cutoff=0.): |
---|
[dd7fc12] | 522 | # type: (ModelInfo, Data, str, float) -> Calculator |
---|
[9cfcac8] | 523 | """ |
---|
| 524 | Return a model calculator using the DLL calculation engine. |
---|
| 525 | """ |
---|
[72a081d] | 526 | model = core.build_model(model_info, dtype=dtype, platform="dll") |
---|
[7cf2cfd] | 527 | calculator = DirectModel(data, model, cutoff=cutoff) |
---|
[ec7e360] | 528 | calculator.engine = "OMP%s"%DTYPE_MAP[dtype] |
---|
| 529 | return calculator |
---|
| 530 | |
---|
[b32dafd] | 531 | def time_calculation(calculator, pars, evals=1): |
---|
[dd7fc12] | 532 | # type: (Calculator, ParameterSet, int) -> Tuple[np.ndarray, float] |
---|
[caeb06d] | 533 | """ |
---|
| 534 | Compute the average calculation time over N evaluations. |
---|
| 535 | |
---|
| 536 | An additional call is generated without polydispersity in order to |
---|
| 537 | initialize the calculation engine, and make the average more stable. |
---|
| 538 | """ |
---|
[ec7e360] | 539 | # initialize the code so time is more accurate |
---|
[b32dafd] | 540 | if evals > 1: |
---|
[dd7fc12] | 541 | calculator(**suppress_pd(pars)) |
---|
[216a9e1] | 542 | toc = tic() |
---|
[dd7fc12] | 543 | # make sure there is at least one eval |
---|
| 544 | value = calculator(**pars) |
---|
[b32dafd] | 545 | for _ in range(evals-1): |
---|
[7cf2cfd] | 546 | value = calculator(**pars) |
---|
[b32dafd] | 547 | average_time = toc()*1000. / evals |
---|
[f2f67a6] | 548 | #print("I(q)",value) |
---|
[216a9e1] | 549 | return value, average_time |
---|
| 550 | |
---|
[ec7e360] | 551 | def make_data(opts): |
---|
[dd7fc12] | 552 | # type: (Dict[str, Any]) -> Tuple[Data, np.ndarray] |
---|
[caeb06d] | 553 | """ |
---|
| 554 | Generate an empty dataset, used with the model to set Q points |
---|
| 555 | and resolution. |
---|
| 556 | |
---|
| 557 | *opts* contains the options, with 'qmax', 'nq', 'res', |
---|
| 558 | 'accuracy', 'is2d' and 'view' parsed from the command line. |
---|
| 559 | """ |
---|
[ec7e360] | 560 | qmax, nq, res = opts['qmax'], opts['nq'], opts['res'] |
---|
| 561 | if opts['is2d']: |
---|
[dd7fc12] | 562 | q = np.linspace(-qmax, qmax, nq) # type: np.ndarray |
---|
| 563 | data = empty_data2D(q, resolution=res) |
---|
[ec7e360] | 564 | data.accuracy = opts['accuracy'] |
---|
[ea75043] | 565 | set_beam_stop(data, 0.0004) |
---|
[87985ca] | 566 | index = ~data.mask |
---|
[216a9e1] | 567 | else: |
---|
[e78edc4] | 568 | if opts['view'] == 'log' and not opts['zero']: |
---|
[b89f519] | 569 | qmax = math.log10(qmax) |
---|
[ec7e360] | 570 | q = np.logspace(qmax-3, qmax, nq) |
---|
[b89f519] | 571 | else: |
---|
[ec7e360] | 572 | q = np.linspace(0.001*qmax, qmax, nq) |
---|
[e78edc4] | 573 | if opts['zero']: |
---|
| 574 | q = np.hstack((0, q)) |
---|
[ec7e360] | 575 | data = empty_data1D(q, resolution=res) |
---|
[216a9e1] | 576 | index = slice(None, None) |
---|
| 577 | return data, index |
---|
| 578 | |
---|
[17bbadd] | 579 | def make_engine(model_info, data, dtype, cutoff): |
---|
[dd7fc12] | 580 | # type: (ModelInfo, Data, str, float) -> Calculator |
---|
[caeb06d] | 581 | """ |
---|
| 582 | Generate the appropriate calculation engine for the given datatype. |
---|
| 583 | |
---|
| 584 | Datatypes with '!' appended are evaluated using external C DLLs rather |
---|
| 585 | than OpenCL. |
---|
| 586 | """ |
---|
[ec7e360] | 587 | if dtype == 'sasview': |
---|
[17bbadd] | 588 | return eval_sasview(model_info, data) |
---|
[ec7e360] | 589 | elif dtype.endswith('!'): |
---|
[17bbadd] | 590 | return eval_ctypes(model_info, data, dtype=dtype[:-1], cutoff=cutoff) |
---|
[ec7e360] | 591 | else: |
---|
[17bbadd] | 592 | return eval_opencl(model_info, data, dtype=dtype, cutoff=cutoff) |
---|
[87985ca] | 593 | |
---|
[e78edc4] | 594 | def _show_invalid(data, theory): |
---|
[dd7fc12] | 595 | # type: (Data, np.ma.ndarray) -> None |
---|
| 596 | """ |
---|
| 597 | Display a list of the non-finite values in theory. |
---|
| 598 | """ |
---|
[e78edc4] | 599 | if not theory.mask.any(): |
---|
| 600 | return |
---|
| 601 | |
---|
| 602 | if hasattr(data, 'x'): |
---|
| 603 | bad = zip(data.x[theory.mask], theory[theory.mask]) |
---|
[dd7fc12] | 604 | print(" *** ", ", ".join("I(%g)=%g"%(x, y) for x, y in bad)) |
---|
[e78edc4] | 605 | |
---|
| 606 | |
---|
[013adb7] | 607 | def compare(opts, limits=None): |
---|
[dd7fc12] | 608 | # type: (Dict[str, Any], Optional[Tuple[float, float]]) -> Tuple[float, float] |
---|
[caeb06d] | 609 | """ |
---|
| 610 | Preform a comparison using options from the command line. |
---|
| 611 | |
---|
| 612 | *limits* are the limits on the values to use, either to set the y-axis |
---|
| 613 | for 1D or to set the colormap scale for 2D. If None, then they are |
---|
| 614 | inferred from the data and returned. When exploring using Bumps, |
---|
| 615 | the limits are set when the model is initially called, and maintained |
---|
| 616 | as the values are adjusted, making it easier to see the effects of the |
---|
| 617 | parameters. |
---|
| 618 | """ |
---|
[ff1fff5] | 619 | n_base, n_comp = opts['count'] |
---|
| 620 | pars, pars2 = opts['pars'] |
---|
[ec7e360] | 621 | data = opts['data'] |
---|
[87985ca] | 622 | |
---|
[dd7fc12] | 623 | # silence the linter |
---|
[b32dafd] | 624 | base = opts['engines'][0] if n_base else None |
---|
| 625 | comp = opts['engines'][1] if n_comp else None |
---|
[dd7fc12] | 626 | base_time = comp_time = None |
---|
| 627 | base_value = comp_value = resid = relerr = None |
---|
| 628 | |
---|
[4b41184] | 629 | # Base calculation |
---|
[b32dafd] | 630 | if n_base > 0: |
---|
[319ab14] | 631 | try: |
---|
[b32dafd] | 632 | base_raw, base_time = time_calculation(base, pars, n_base) |
---|
[dd7fc12] | 633 | base_value = np.ma.masked_invalid(base_raw) |
---|
[af92b73] | 634 | print("%s t=%.2f ms, intensity=%.0f" |
---|
[e78edc4] | 635 | % (base.engine, base_time, base_value.sum())) |
---|
| 636 | _show_invalid(data, base_value) |
---|
[319ab14] | 637 | except ImportError: |
---|
| 638 | traceback.print_exc() |
---|
[b32dafd] | 639 | n_base = 0 |
---|
[4b41184] | 640 | |
---|
| 641 | # Comparison calculation |
---|
[b32dafd] | 642 | if n_comp > 0: |
---|
[7cf2cfd] | 643 | try: |
---|
[ff1fff5] | 644 | comp_raw, comp_time = time_calculation(comp, pars2, n_comp) |
---|
[dd7fc12] | 645 | comp_value = np.ma.masked_invalid(comp_raw) |
---|
[af92b73] | 646 | print("%s t=%.2f ms, intensity=%.0f" |
---|
[e78edc4] | 647 | % (comp.engine, comp_time, comp_value.sum())) |
---|
| 648 | _show_invalid(data, comp_value) |
---|
[7cf2cfd] | 649 | except ImportError: |
---|
[5753e4e] | 650 | traceback.print_exc() |
---|
[b32dafd] | 651 | n_comp = 0 |
---|
[87985ca] | 652 | |
---|
| 653 | # Compare, but only if computing both forms |
---|
[b32dafd] | 654 | if n_base > 0 and n_comp > 0: |
---|
[ec7e360] | 655 | resid = (base_value - comp_value) |
---|
[b32dafd] | 656 | relerr = resid/np.where(comp_value != 0., abs(comp_value), 1.0) |
---|
[d15a908] | 657 | _print_stats("|%s-%s|" |
---|
| 658 | % (base.engine, comp.engine) + (" "*(3+len(comp.engine))), |
---|
[caeb06d] | 659 | resid) |
---|
[d15a908] | 660 | _print_stats("|(%s-%s)/%s|" |
---|
| 661 | % (base.engine, comp.engine, comp.engine), |
---|
[caeb06d] | 662 | relerr) |
---|
[87985ca] | 663 | |
---|
| 664 | # Plot if requested |
---|
[ec7e360] | 665 | if not opts['plot'] and not opts['explore']: return |
---|
| 666 | view = opts['view'] |
---|
[1726b21] | 667 | import matplotlib.pyplot as plt |
---|
[013adb7] | 668 | if limits is None: |
---|
| 669 | vmin, vmax = np.Inf, -np.Inf |
---|
[b32dafd] | 670 | if n_base > 0: |
---|
[e78edc4] | 671 | vmin = min(vmin, base_value.min()) |
---|
| 672 | vmax = max(vmax, base_value.max()) |
---|
[b32dafd] | 673 | if n_comp > 0: |
---|
[e78edc4] | 674 | vmin = min(vmin, comp_value.min()) |
---|
| 675 | vmax = max(vmax, comp_value.max()) |
---|
[013adb7] | 676 | limits = vmin, vmax |
---|
| 677 | |
---|
[b32dafd] | 678 | if n_base > 0: |
---|
| 679 | if n_comp > 0: plt.subplot(131) |
---|
[841753c] | 680 | plot_theory(data, base_value, view=view, use_data=False, limits=limits) |
---|
[af92b73] | 681 | plt.title("%s t=%.2f ms"%(base.engine, base_time)) |
---|
[ec7e360] | 682 | #cbar_title = "log I" |
---|
[b32dafd] | 683 | if n_comp > 0: |
---|
| 684 | if n_base > 0: plt.subplot(132) |
---|
[841753c] | 685 | plot_theory(data, comp_value, view=view, use_data=False, limits=limits) |
---|
[af92b73] | 686 | plt.title("%s t=%.2f ms"%(comp.engine, comp_time)) |
---|
[7cf2cfd] | 687 | #cbar_title = "log I" |
---|
[b32dafd] | 688 | if n_comp > 0 and n_base > 0: |
---|
[87985ca] | 689 | plt.subplot(133) |
---|
[d5e650d] | 690 | if not opts['rel_err']: |
---|
[caeb06d] | 691 | err, errstr, errview = resid, "abs err", "linear" |
---|
[29f5536] | 692 | else: |
---|
[caeb06d] | 693 | err, errstr, errview = abs(relerr), "rel err", "log" |
---|
[9068f4c] | 694 | #sorted = np.sort(err.flatten()) |
---|
| 695 | #cutoff = sorted[int(sorted.size*0.95)] |
---|
| 696 | #err[err>cutoff] = cutoff |
---|
[4b41184] | 697 | #err,errstr = base/comp,"ratio" |
---|
[841753c] | 698 | plot_theory(data, None, resid=err, view=errview, use_data=False) |
---|
[d5e650d] | 699 | if view == 'linear': |
---|
| 700 | plt.xscale('linear') |
---|
[e78edc4] | 701 | plt.title("max %s = %.3g"%(errstr, abs(err).max())) |
---|
[7cf2cfd] | 702 | #cbar_title = errstr if errview=="linear" else "log "+errstr |
---|
| 703 | #if is2D: |
---|
| 704 | # h = plt.colorbar() |
---|
| 705 | # h.ax.set_title(cbar_title) |
---|
[0c24a82] | 706 | fig = plt.gcf() |
---|
[a0d75ce] | 707 | extra_title = ' '+opts['title'] if opts['title'] else '' |
---|
[ff1fff5] | 708 | fig.suptitle(":".join(opts['name']) + extra_title) |
---|
[ba69383] | 709 | |
---|
[9068f4c] | 710 | if n_comp > 0 and n_base > 0 and opts['show_hist']: |
---|
[ba69383] | 711 | plt.figure() |
---|
[346bc88] | 712 | v = relerr |
---|
[caeb06d] | 713 | v[v == 0] = 0.5*np.min(np.abs(v[v != 0])) |
---|
| 714 | plt.hist(np.log10(np.abs(v)), normed=1, bins=50) |
---|
| 715 | plt.xlabel('log10(err), err = |(%s - %s) / %s|' |
---|
| 716 | % (base.engine, comp.engine, comp.engine)) |
---|
[ba69383] | 717 | plt.ylabel('P(err)') |
---|
[ec7e360] | 718 | plt.title('Distribution of relative error between calculation engines') |
---|
[ba69383] | 719 | |
---|
[ec7e360] | 720 | if not opts['explore']: |
---|
| 721 | plt.show() |
---|
[8a20be5] | 722 | |
---|
[013adb7] | 723 | return limits |
---|
| 724 | |
---|
[0763009] | 725 | def _print_stats(label, err): |
---|
[dd7fc12] | 726 | # type: (str, np.ma.ndarray) -> None |
---|
| 727 | # work with trimmed data, not the full set |
---|
[e78edc4] | 728 | sorted_err = np.sort(abs(err.compressed())) |
---|
[dd7fc12] | 729 | p50 = int((len(sorted_err)-1)*0.50) |
---|
| 730 | p98 = int((len(sorted_err)-1)*0.98) |
---|
[0763009] | 731 | data = [ |
---|
| 732 | "max:%.3e"%sorted_err[-1], |
---|
| 733 | "median:%.3e"%sorted_err[p50], |
---|
| 734 | "98%%:%.3e"%sorted_err[p98], |
---|
[dd7fc12] | 735 | "rms:%.3e"%np.sqrt(np.mean(sorted_err**2)), |
---|
| 736 | "zero-offset:%+.3e"%np.mean(sorted_err), |
---|
[0763009] | 737 | ] |
---|
[caeb06d] | 738 | print(label+" "+" ".join(data)) |
---|
[0763009] | 739 | |
---|
| 740 | |
---|
| 741 | |
---|
[87985ca] | 742 | # =========================================================================== |
---|
| 743 | # |
---|
[216a9e1] | 744 | NAME_OPTIONS = set([ |
---|
[5d316e9] | 745 | 'plot', 'noplot', |
---|
[ec7e360] | 746 | 'half', 'fast', 'single', 'double', |
---|
| 747 | 'single!', 'double!', 'quad!', 'sasview', |
---|
[e78edc4] | 748 | 'lowq', 'midq', 'highq', 'exq', 'zero', |
---|
[5d316e9] | 749 | '2d', '1d', |
---|
| 750 | 'preset', 'random', |
---|
| 751 | 'poly', 'mono', |
---|
| 752 | 'nopars', 'pars', |
---|
| 753 | 'rel', 'abs', |
---|
[b89f519] | 754 | 'linear', 'log', 'q4', |
---|
[5d316e9] | 755 | 'hist', 'nohist', |
---|
[234c532] | 756 | 'edit', 'html', |
---|
[98d6cfc] | 757 | 'demo', 'default', |
---|
[216a9e1] | 758 | ]) |
---|
| 759 | VALUE_OPTIONS = [ |
---|
| 760 | # Note: random is both a name option and a value option |
---|
[a0d75ce] | 761 | 'cutoff', 'random', 'nq', 'res', 'accuracy', 'title', |
---|
[87985ca] | 762 | ] |
---|
| 763 | |
---|
[b32dafd] | 764 | def columnize(items, indent="", width=79): |
---|
[dd7fc12] | 765 | # type: (List[str], str, int) -> str |
---|
[caeb06d] | 766 | """ |
---|
[1d4017a] | 767 | Format a list of strings into columns. |
---|
| 768 | |
---|
| 769 | Returns a string with carriage returns ready for printing. |
---|
[caeb06d] | 770 | """ |
---|
[b32dafd] | 771 | column_width = max(len(w) for w in items) + 1 |
---|
[7cf2cfd] | 772 | num_columns = (width - len(indent)) // column_width |
---|
[b32dafd] | 773 | num_rows = len(items) // num_columns |
---|
| 774 | items = items + [""] * (num_rows * num_columns - len(items)) |
---|
| 775 | columns = [items[k*num_rows:(k+1)*num_rows] for k in range(num_columns)] |
---|
[7cf2cfd] | 776 | lines = [" ".join("%-*s"%(column_width, entry) for entry in row) |
---|
| 777 | for row in zip(*columns)] |
---|
| 778 | output = indent + ("\n"+indent).join(lines) |
---|
| 779 | return output |
---|
| 780 | |
---|
| 781 | |
---|
[98d6cfc] | 782 | def get_pars(model_info, use_demo=False): |
---|
[dd7fc12] | 783 | # type: (ModelInfo, bool) -> ParameterSet |
---|
[caeb06d] | 784 | """ |
---|
| 785 | Extract demo parameters from the model definition. |
---|
| 786 | """ |
---|
[ec7e360] | 787 | # Get the default values for the parameters |
---|
[c499331] | 788 | pars = {} |
---|
[6d6508e] | 789 | for p in model_info.parameters.call_parameters: |
---|
[c499331] | 790 | parts = [('', p.default)] |
---|
| 791 | if p.polydisperse: |
---|
| 792 | parts.append(('_pd', 0.0)) |
---|
| 793 | parts.append(('_pd_n', 0)) |
---|
| 794 | parts.append(('_pd_nsigma', 3.0)) |
---|
| 795 | parts.append(('_pd_type', "gaussian")) |
---|
| 796 | for ext, val in parts: |
---|
| 797 | if p.length > 1: |
---|
[b32dafd] | 798 | dict(("%s%d%s" % (p.id, k, ext), val) |
---|
| 799 | for k in range(1, p.length+1)) |
---|
[c499331] | 800 | else: |
---|
[b32dafd] | 801 | pars[p.id + ext] = val |
---|
[ec7e360] | 802 | |
---|
| 803 | # Plug in values given in demo |
---|
[98d6cfc] | 804 | if use_demo: |
---|
[6d6508e] | 805 | pars.update(model_info.demo) |
---|
[373d1b6] | 806 | return pars |
---|
| 807 | |
---|
[ff1fff5] | 808 | INTEGER_RE = re.compile("^[+-]?[1-9][0-9]*$") |
---|
| 809 | def isnumber(str): |
---|
| 810 | match = FLOAT_RE.match(str) |
---|
| 811 | isfloat = (match and not str[match.end():]) |
---|
| 812 | return isfloat or INTEGER_RE.match(str) |
---|
[17bbadd] | 813 | |
---|
[424fe00] | 814 | def parse_opts(argv): |
---|
| 815 | # type: (List[str]) -> Dict[str, Any] |
---|
[caeb06d] | 816 | """ |
---|
| 817 | Parse command line options. |
---|
| 818 | """ |
---|
[fc0fcd0] | 819 | MODELS = core.list_models() |
---|
[424fe00] | 820 | flags = [arg for arg in argv |
---|
[caeb06d] | 821 | if arg.startswith('-')] |
---|
[424fe00] | 822 | values = [arg for arg in argv |
---|
[caeb06d] | 823 | if not arg.startswith('-') and '=' in arg] |
---|
[424fe00] | 824 | positional_args = [arg for arg in argv |
---|
[caeb06d] | 825 | if not arg.startswith('-') and '=' not in arg] |
---|
[d547f16] | 826 | models = "\n ".join("%-15s"%v for v in MODELS) |
---|
[424fe00] | 827 | if len(positional_args) == 0: |
---|
[7cf2cfd] | 828 | print(USAGE) |
---|
[caeb06d] | 829 | print("\nAvailable models:") |
---|
[7cf2cfd] | 830 | print(columnize(MODELS, indent=" ")) |
---|
[424fe00] | 831 | return None |
---|
| 832 | if len(positional_args) > 3: |
---|
[9cfcac8] | 833 | print("expected parameters: model N1 N2") |
---|
[87985ca] | 834 | |
---|
[ec7e360] | 835 | invalid = [o[1:] for o in flags |
---|
[216a9e1] | 836 | if o[1:] not in NAME_OPTIONS |
---|
[d15a908] | 837 | and not any(o.startswith('-%s='%t) for t in VALUE_OPTIONS)] |
---|
[87985ca] | 838 | if invalid: |
---|
[9404dd3] | 839 | print("Invalid options: %s"%(", ".join(invalid))) |
---|
[424fe00] | 840 | return None |
---|
[87985ca] | 841 | |
---|
[ff1fff5] | 842 | name = positional_args[0] |
---|
| 843 | n1 = int(positional_args[1]) if len(positional_args) > 1 else 1 |
---|
| 844 | n2 = int(positional_args[2]) if len(positional_args) > 2 else 1 |
---|
[ec7e360] | 845 | |
---|
[d15a908] | 846 | # pylint: disable=bad-whitespace |
---|
[ec7e360] | 847 | # Interpret the flags |
---|
| 848 | opts = { |
---|
| 849 | 'plot' : True, |
---|
| 850 | 'view' : 'log', |
---|
| 851 | 'is2d' : False, |
---|
| 852 | 'qmax' : 0.05, |
---|
| 853 | 'nq' : 128, |
---|
| 854 | 'res' : 0.0, |
---|
| 855 | 'accuracy' : 'Low', |
---|
[72a081d] | 856 | 'cutoff' : 0.0, |
---|
[ec7e360] | 857 | 'seed' : -1, # default to preset |
---|
| 858 | 'mono' : False, |
---|
| 859 | 'show_pars' : False, |
---|
| 860 | 'show_hist' : False, |
---|
| 861 | 'rel_err' : True, |
---|
| 862 | 'explore' : False, |
---|
[98d6cfc] | 863 | 'use_demo' : True, |
---|
[dd7fc12] | 864 | 'zero' : False, |
---|
[234c532] | 865 | 'html' : False, |
---|
[a0d75ce] | 866 | 'title' : None, |
---|
[ec7e360] | 867 | } |
---|
| 868 | engines = [] |
---|
| 869 | for arg in flags: |
---|
| 870 | if arg == '-noplot': opts['plot'] = False |
---|
| 871 | elif arg == '-plot': opts['plot'] = True |
---|
| 872 | elif arg == '-linear': opts['view'] = 'linear' |
---|
| 873 | elif arg == '-log': opts['view'] = 'log' |
---|
| 874 | elif arg == '-q4': opts['view'] = 'q4' |
---|
| 875 | elif arg == '-1d': opts['is2d'] = False |
---|
| 876 | elif arg == '-2d': opts['is2d'] = True |
---|
| 877 | elif arg == '-exq': opts['qmax'] = 10.0 |
---|
| 878 | elif arg == '-highq': opts['qmax'] = 1.0 |
---|
| 879 | elif arg == '-midq': opts['qmax'] = 0.2 |
---|
[ce0b154] | 880 | elif arg == '-lowq': opts['qmax'] = 0.05 |
---|
[e78edc4] | 881 | elif arg == '-zero': opts['zero'] = True |
---|
[ec7e360] | 882 | elif arg.startswith('-nq='): opts['nq'] = int(arg[4:]) |
---|
| 883 | elif arg.startswith('-res='): opts['res'] = float(arg[5:]) |
---|
| 884 | elif arg.startswith('-accuracy='): opts['accuracy'] = arg[10:] |
---|
| 885 | elif arg.startswith('-cutoff='): opts['cutoff'] = float(arg[8:]) |
---|
| 886 | elif arg.startswith('-random='): opts['seed'] = int(arg[8:]) |
---|
[a0d75ce] | 887 | elif arg.startswith('-title'): opts['title'] = arg[7:] |
---|
[dd7fc12] | 888 | elif arg == '-random': opts['seed'] = np.random.randint(1000000) |
---|
[ec7e360] | 889 | elif arg == '-preset': opts['seed'] = -1 |
---|
| 890 | elif arg == '-mono': opts['mono'] = True |
---|
| 891 | elif arg == '-poly': opts['mono'] = False |
---|
| 892 | elif arg == '-pars': opts['show_pars'] = True |
---|
| 893 | elif arg == '-nopars': opts['show_pars'] = False |
---|
| 894 | elif arg == '-hist': opts['show_hist'] = True |
---|
| 895 | elif arg == '-nohist': opts['show_hist'] = False |
---|
| 896 | elif arg == '-rel': opts['rel_err'] = True |
---|
| 897 | elif arg == '-abs': opts['rel_err'] = False |
---|
| 898 | elif arg == '-half': engines.append(arg[1:]) |
---|
| 899 | elif arg == '-fast': engines.append(arg[1:]) |
---|
| 900 | elif arg == '-single': engines.append(arg[1:]) |
---|
| 901 | elif arg == '-double': engines.append(arg[1:]) |
---|
| 902 | elif arg == '-single!': engines.append(arg[1:]) |
---|
| 903 | elif arg == '-double!': engines.append(arg[1:]) |
---|
| 904 | elif arg == '-quad!': engines.append(arg[1:]) |
---|
| 905 | elif arg == '-sasview': engines.append(arg[1:]) |
---|
| 906 | elif arg == '-edit': opts['explore'] = True |
---|
[98d6cfc] | 907 | elif arg == '-demo': opts['use_demo'] = True |
---|
| 908 | elif arg == '-default': opts['use_demo'] = False |
---|
[234c532] | 909 | elif arg == '-html': opts['html'] = True |
---|
[d15a908] | 910 | # pylint: enable=bad-whitespace |
---|
[ec7e360] | 911 | |
---|
[ff1fff5] | 912 | if ':' in name: |
---|
| 913 | name, name2 = name.split(':',2) |
---|
| 914 | else: |
---|
| 915 | name2 = name |
---|
| 916 | try: |
---|
| 917 | model_info = core.load_model_info(name) |
---|
| 918 | model_info2 = core.load_model_info(name2) if name2 != name else model_info |
---|
| 919 | except ImportError as exc: |
---|
| 920 | print(str(exc)) |
---|
| 921 | print("Could not find model; use one of:\n " + models) |
---|
| 922 | return None |
---|
[87985ca] | 923 | |
---|
[ec7e360] | 924 | # Get demo parameters from model definition, or use default parameters |
---|
| 925 | # if model does not define demo parameters |
---|
[98d6cfc] | 926 | pars = get_pars(model_info, opts['use_demo']) |
---|
[ff1fff5] | 927 | pars2 = get_pars(model_info2, opts['use_demo']) |
---|
[248561a] | 928 | pars2.update((k, v) for k, v in pars.items() if k in pars2) |
---|
[ff1fff5] | 929 | # randomize parameters |
---|
| 930 | #pars.update(set_pars) # set value before random to control range |
---|
| 931 | if opts['seed'] > -1: |
---|
| 932 | pars = randomize_pars(model_info, pars, seed=opts['seed']) |
---|
| 933 | if model_info != model_info2: |
---|
| 934 | pars2 = randomize_pars(model_info2, pars2, seed=opts['seed']) |
---|
| 935 | else: |
---|
| 936 | pars2 = pars.copy() |
---|
| 937 | print("Randomize using -random=%i"%opts['seed']) |
---|
| 938 | if opts['mono']: |
---|
| 939 | pars = suppress_pd(pars) |
---|
| 940 | pars2 = suppress_pd(pars2) |
---|
[87985ca] | 941 | |
---|
| 942 | # Fill in parameters given on the command line |
---|
[ec7e360] | 943 | presets = {} |
---|
[ff1fff5] | 944 | presets2 = {} |
---|
[ec7e360] | 945 | for arg in values: |
---|
[d15a908] | 946 | k, v = arg.split('=', 1) |
---|
[ff1fff5] | 947 | if k not in pars and k not in pars2: |
---|
[ec7e360] | 948 | # extract base name without polydispersity info |
---|
[87985ca] | 949 | s = set(p.split('_pd')[0] for p in pars) |
---|
[d15a908] | 950 | print("%r invalid; parameters are: %s"%(k, ", ".join(sorted(s)))) |
---|
[424fe00] | 951 | return None |
---|
[ff1fff5] | 952 | v1, v2 = v.split(':',2) if ':' in v else (v,v) |
---|
| 953 | if v1 and k in pars: |
---|
| 954 | presets[k] = float(v1) if isnumber(v1) else v1 |
---|
| 955 | if v2 and k in pars2: |
---|
| 956 | presets2[k] = float(v2) if isnumber(v2) else v2 |
---|
| 957 | |
---|
| 958 | # Evaluate preset parameter expressions |
---|
[248561a] | 959 | context = MATH.copy() |
---|
| 960 | context.update(pars) |
---|
[ff1fff5] | 961 | context.update((k,v) for k,v in presets.items() if isinstance(v, float)) |
---|
| 962 | for k, v in presets.items(): |
---|
| 963 | if not isinstance(v, float) and not k.endswith('_type'): |
---|
| 964 | presets[k] = eval(v, context) |
---|
| 965 | context.update(presets) |
---|
| 966 | context.update((k,v) for k,v in presets2.items() if isinstance(v, float)) |
---|
| 967 | for k, v in presets2.items(): |
---|
| 968 | if not isinstance(v, float) and not k.endswith('_type'): |
---|
| 969 | presets2[k] = eval(v, context) |
---|
| 970 | |
---|
| 971 | # update parameters with presets |
---|
[ec7e360] | 972 | pars.update(presets) # set value after random to control value |
---|
[ff1fff5] | 973 | pars2.update(presets2) # set value after random to control value |
---|
[fcd7bbd] | 974 | #import pprint; pprint.pprint(model_info) |
---|
[17bbadd] | 975 | constrain_pars(model_info, pars) |
---|
[ff1fff5] | 976 | constrain_pars(model_info2, pars2) |
---|
| 977 | |
---|
| 978 | same_model = name == name2 and pars == pars |
---|
| 979 | if len(engines) == 0: |
---|
| 980 | if same_model: |
---|
| 981 | engines.extend(['single', 'double']) |
---|
| 982 | else: |
---|
| 983 | engines.extend(['single', 'single']) |
---|
| 984 | elif len(engines) == 1: |
---|
| 985 | if not same_model: |
---|
| 986 | engines.append(engines[0]) |
---|
| 987 | elif engines[0] == 'double': |
---|
| 988 | engines.append('single') |
---|
| 989 | else: |
---|
| 990 | engines.append('double') |
---|
| 991 | elif len(engines) > 2: |
---|
| 992 | del engines[2:] |
---|
| 993 | |
---|
| 994 | use_sasview = any(engine == 'sasview' and count > 0 |
---|
| 995 | for engine, count in zip(engines, [n1, n2])) |
---|
[fa1582e] | 996 | if use_sasview: |
---|
| 997 | constrain_new_to_old(model_info, pars) |
---|
[ff1fff5] | 998 | constrain_new_to_old(model_info2, pars2) |
---|
| 999 | |
---|
[ec7e360] | 1000 | if opts['show_pars']: |
---|
[248561a] | 1001 | if not same_model: |
---|
| 1002 | print("==== %s ====="%model_info.name) |
---|
| 1003 | print(str(parlist(model_info, pars, opts['is2d']))) |
---|
| 1004 | print("==== %s ====="%model_info2.name) |
---|
| 1005 | print(str(parlist(model_info2, pars2, opts['is2d']))) |
---|
| 1006 | else: |
---|
| 1007 | print(str(parlist(model_info, pars, opts['is2d']))) |
---|
[ec7e360] | 1008 | |
---|
| 1009 | # Create the computational engines |
---|
[d15a908] | 1010 | data, _ = make_data(opts) |
---|
[9cfcac8] | 1011 | if n1: |
---|
[17bbadd] | 1012 | base = make_engine(model_info, data, engines[0], opts['cutoff']) |
---|
[ec7e360] | 1013 | else: |
---|
| 1014 | base = None |
---|
[9cfcac8] | 1015 | if n2: |
---|
[ff1fff5] | 1016 | comp = make_engine(model_info2, data, engines[1], opts['cutoff']) |
---|
[ec7e360] | 1017 | else: |
---|
| 1018 | comp = None |
---|
| 1019 | |
---|
[d15a908] | 1020 | # pylint: disable=bad-whitespace |
---|
[ec7e360] | 1021 | # Remember it all |
---|
| 1022 | opts.update({ |
---|
| 1023 | 'data' : data, |
---|
[ff1fff5] | 1024 | 'name' : [name, name2], |
---|
| 1025 | 'def' : [model_info, model_info2], |
---|
| 1026 | 'count' : [n1, n2], |
---|
| 1027 | 'presets' : [presets, presets2], |
---|
| 1028 | 'pars' : [pars, pars2], |
---|
[ec7e360] | 1029 | 'engines' : [base, comp], |
---|
| 1030 | }) |
---|
[d15a908] | 1031 | # pylint: enable=bad-whitespace |
---|
[ec7e360] | 1032 | |
---|
| 1033 | return opts |
---|
| 1034 | |
---|
[234c532] | 1035 | def show_docs(opts): |
---|
| 1036 | # type: (Dict[str, Any]) -> None |
---|
| 1037 | """ |
---|
| 1038 | show html docs for the model |
---|
| 1039 | """ |
---|
| 1040 | import wx # type: ignore |
---|
| 1041 | from .generate import view_html_from_info |
---|
| 1042 | app = wx.App() if wx.GetApp() is None else None |
---|
[ff1fff5] | 1043 | view_html_from_info(opts['def'][0]) |
---|
[234c532] | 1044 | if app: app.MainLoop() |
---|
| 1045 | |
---|
| 1046 | |
---|
[ec7e360] | 1047 | def explore(opts): |
---|
[dd7fc12] | 1048 | # type: (Dict[str, Any]) -> None |
---|
[d15a908] | 1049 | """ |
---|
[234c532] | 1050 | explore the model using the bumps gui. |
---|
[d15a908] | 1051 | """ |
---|
[7ae2b7f] | 1052 | import wx # type: ignore |
---|
| 1053 | from bumps.names import FitProblem # type: ignore |
---|
| 1054 | from bumps.gui.app_frame import AppFrame # type: ignore |
---|
[ec7e360] | 1055 | |
---|
[d15a908] | 1056 | is_mac = "cocoa" in wx.version() |
---|
[80013a6] | 1057 | # Create an app if not running embedded |
---|
| 1058 | app = wx.App() if wx.GetApp() is None else None |
---|
| 1059 | problem = FitProblem(Explore(opts)) |
---|
| 1060 | frame = AppFrame(parent=None, title="explore", size=(1000,700)) |
---|
[d15a908] | 1061 | if not is_mac: frame.Show() |
---|
[ec7e360] | 1062 | frame.panel.set_model(model=problem) |
---|
| 1063 | frame.panel.Layout() |
---|
| 1064 | frame.panel.aui.Split(0, wx.TOP) |
---|
[d15a908] | 1065 | if is_mac: frame.Show() |
---|
[80013a6] | 1066 | # If running withing an app, start the main loop |
---|
| 1067 | if app: app.MainLoop() |
---|
[ec7e360] | 1068 | |
---|
| 1069 | class Explore(object): |
---|
| 1070 | """ |
---|
[d15a908] | 1071 | Bumps wrapper for a SAS model comparison. |
---|
| 1072 | |
---|
| 1073 | The resulting object can be used as a Bumps fit problem so that |
---|
| 1074 | parameters can be adjusted in the GUI, with plots updated on the fly. |
---|
[ec7e360] | 1075 | """ |
---|
| 1076 | def __init__(self, opts): |
---|
[dd7fc12] | 1077 | # type: (Dict[str, Any]) -> None |
---|
[7ae2b7f] | 1078 | from bumps.cli import config_matplotlib # type: ignore |
---|
[608e31e] | 1079 | from . import bumps_model |
---|
[ec7e360] | 1080 | config_matplotlib() |
---|
| 1081 | self.opts = opts |
---|
[ff1fff5] | 1082 | model_info = opts['def'][0] |
---|
| 1083 | pars, pd_types = bumps_model.create_parameters(model_info, **opts['pars'][0]) |
---|
[21b116f] | 1084 | # Initialize parameter ranges, fixing the 2D parameters for 1D data. |
---|
[ec7e360] | 1085 | if not opts['is2d']: |
---|
[6d6508e] | 1086 | for p in model_info.parameters.user_parameters(is2d=False): |
---|
[303d8d6] | 1087 | for ext in ['', '_pd', '_pd_n', '_pd_nsigma']: |
---|
[69aa451] | 1088 | k = p.name+ext |
---|
[303d8d6] | 1089 | v = pars.get(k, None) |
---|
| 1090 | if v is not None: |
---|
| 1091 | v.range(*parameter_range(k, v.value)) |
---|
[ec7e360] | 1092 | else: |
---|
[013adb7] | 1093 | for k, v in pars.items(): |
---|
[ec7e360] | 1094 | v.range(*parameter_range(k, v.value)) |
---|
| 1095 | |
---|
| 1096 | self.pars = pars |
---|
| 1097 | self.pd_types = pd_types |
---|
[013adb7] | 1098 | self.limits = None |
---|
[ec7e360] | 1099 | |
---|
| 1100 | def numpoints(self): |
---|
[dd7fc12] | 1101 | # type: () -> int |
---|
[ec7e360] | 1102 | """ |
---|
[608e31e] | 1103 | Return the number of points. |
---|
[ec7e360] | 1104 | """ |
---|
| 1105 | return len(self.pars) + 1 # so dof is 1 |
---|
| 1106 | |
---|
| 1107 | def parameters(self): |
---|
[dd7fc12] | 1108 | # type: () -> Any # Dict/List hierarchy of parameters |
---|
[ec7e360] | 1109 | """ |
---|
[608e31e] | 1110 | Return a dictionary of parameters. |
---|
[ec7e360] | 1111 | """ |
---|
| 1112 | return self.pars |
---|
| 1113 | |
---|
| 1114 | def nllf(self): |
---|
[dd7fc12] | 1115 | # type: () -> float |
---|
[608e31e] | 1116 | """ |
---|
| 1117 | Return cost. |
---|
| 1118 | """ |
---|
[d15a908] | 1119 | # pylint: disable=no-self-use |
---|
[ec7e360] | 1120 | return 0. # No nllf |
---|
| 1121 | |
---|
| 1122 | def plot(self, view='log'): |
---|
[dd7fc12] | 1123 | # type: (str) -> None |
---|
[ec7e360] | 1124 | """ |
---|
| 1125 | Plot the data and residuals. |
---|
| 1126 | """ |
---|
[608e31e] | 1127 | pars = dict((k, v.value) for k, v in self.pars.items()) |
---|
[ec7e360] | 1128 | pars.update(self.pd_types) |
---|
[ff1fff5] | 1129 | self.opts['pars'][0] = pars |
---|
| 1130 | self.opts['pars'][1] = pars |
---|
[013adb7] | 1131 | limits = compare(self.opts, limits=self.limits) |
---|
| 1132 | if self.limits is None: |
---|
| 1133 | vmin, vmax = limits |
---|
[dd7fc12] | 1134 | self.limits = vmax*1e-7, 1.3*vmax |
---|
[87985ca] | 1135 | |
---|
| 1136 | |
---|
[424fe00] | 1137 | def main(*argv): |
---|
| 1138 | # type: (*str) -> None |
---|
[d15a908] | 1139 | """ |
---|
| 1140 | Main program. |
---|
| 1141 | """ |
---|
[424fe00] | 1142 | opts = parse_opts(argv) |
---|
| 1143 | if opts is not None: |
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[234c532] | 1144 | if opts['html']: |
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| 1145 | show_docs(opts) |
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| 1146 | elif opts['explore']: |
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[424fe00] | 1147 | explore(opts) |
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| 1148 | else: |
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| 1149 | compare(opts) |
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[d15a908] | 1150 | |
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[8a20be5] | 1151 | if __name__ == "__main__": |
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[424fe00] | 1152 | main(*sys.argv[1:]) |
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